uČni naČrt predmeta / course syllabus · apply a suitable data structure and algorithm to a given...

UČNI NAČRT PREDMETA / COURSE SYLLABUS

Predmet: Algoritmi in podatkovne strukture

Course title: Algorithms and Data structures

Študijski program in stopnja Study programme and level

Študijska smer Study field

Letnik Academic

year

Semester Semester

Računalništvo in informacijske tehnologije 1. stopnja UN

Computer Science and Information

Technologies 1st cycle

Academic undergraduate

1. poletni Spring

Vrsta predmeta / Course type

Univerzitetna koda predmeta / University course code:

Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework

Druge oblike študija

Samost. delo Individ. work

ECTS

30 45 105 6

Nosilec predmeta / Lecturer: Damjan Strnad

Jeziki / Languages:

Predavanja / Lectures:

slovenski / Slovene

Vaje / Tutorial: slovenski / Slovene

Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:

Prerequisites:

Ni pogojev, None.

Vsebina:

Content (Syllabus outline):

Uvod: pojem problema in algoritma, časovna in prostorska zahtevnost.

Osnovne podatkovne strukture: polje, sklad, vrsta, povezani seznami.

Drevo: osnovni pojmi, dvojiško drevo, dvojiško iskalno drevo, poizvedbe v dvojiškem iskalnem drevesu, vstavljanje in odstranjevanje.

Kopica: predstavitev s poljem, vzdrževanje lastnosti kopice, tvorba kopice, urejanja kopice, vrste s prednostjo.

Introduction: problem and algorithm, time and space complexity.

Elementary data structures: array, stack, queue, linked lists.

Tree: elementary items, binary tree, binary search tree, querying a binary search tree, insertion and deletion.

Heap: heap viewed as an array, maintaining the heap property, building a heap, heapsort algorithm, priority queues.

Sekljalna preglednica: sekljalne funkcije, odprava sovpadanja z veriženjem, odprto naslavljanje.

Deli-in-vladaj: splošna strategija, hitro urejanje, urejanje z zlivanjem, množenje matrik, Strassenovo množenje matrik.

Graf: predstavitve grafov. Zmanjšaj-in-vladaj: urejanje z vrivanjem, iskanje z

razvijanjem v širino, iskanje z razvijanjem v globino. Požrešna tehnika: splošna metoda, preprosti problem

nahrbtnika, Kruskalov algoritem, Primov algoritem, Dijkstrin algoritem, Bellman-Fordov algoritem.

Dinamično programiranje: 0/1 nahrbtnik, problem trgovskega potnika.

Vračanje: splošna metoda, N kraljic na šahovsko desko, barvanje grafov.

Razveji-in-omeji: iskanje najkrajše poti med mestoma.

Hash table: hash functions, collision resolution by chaining, open addressing.

Divide-and-conquer: general strategy, quicksort, mergesort, matrix multiplication, Strassen’s algorithm for matrix multiplication.

Graph: representations of graphs. Decrease-and-conquer: insertion sort, breadth-first search,

depth-first search. Greedy technique: general method, simple knapsack

problem, Kruskal's algorithm, Prim's algorithm, Dijkstra's algorithm, Bellman-Ford algorithm.

Dynamic programming: 0/1-knapsack problem, traveling salesman problem.

Backtracking: general method, N-queens problem, graph colouring.

Branch-and-bound: finding the shortest path between towns.

Temeljni literatura in viri / Readings: J. Kozak: Podatkovne strukture in algoritmi, Društvo matematikov, fizikov in astronomov, Ljubljana, 1997. A. Levitin: Introduction to the Design & Analysis of Algorithms, Pearson Education, Boston, 2007. T. H. Cormen, S. Clifford, C. E. Leiserson, R. L. Rivest: Introduction to Algorithms, Third Edition, MIT Press, Cambridge,

Massachusetts, 2009. D. Baldwin, G. W. Scragg: Algorithms and Data structures. The Science of Computing, Charles River Media Inc., Hingham,

2004. E. Horowitz, S. Sahni, S. Rajasekaran, Computer Algorithms, Computer Science Press, New York, 1998. Cilji in kompetence:

Objectives and competences:

Cilj predmeta je seznaniti študente z najpomembnejšimi računalniškimi podatkovnimi strukturami in algoritmi, strategijami za načrtovanje algoritmov in metodami za ovrednotenje njihove učinkovitosti.

The objectives of this course is to acquaint the students with the most important computer data structures and algorithms, strategies for algorithm design, and methods for evaluating the algorithm efficiency.

Predvideni študijski rezultati:

Intended learning outcomes:

Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben opisati temeljne podatkovne strukture, algoritme urejanja,

algoritme na drevesih in grafih, prepoznati različne strategije algoritmov, kot so deli in

vladaj, požrešna metoda, dinamično programiranje, uporabiti primerno podatkovno strukturo in algoritem za

podani problem, ovrednotiti algoritem, tako da določi najboljšo, povprečno

in najslabšo časovno in prostorsko zahtevnost.

Knowledge and understanding: On completion of this course the student will be able to describe basic data structures, sorting algorithms, tree and

graph algorithms, recognize algorithms with various strategies, such as divide

and conquer, greedy method, dynamic programming, apply a suitable data structure and algorithm to a given

problem, evaluate an algorithm by determining the best, the mean

and the worst time and space complexity.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: ustni zagovor laboratorijskih vaj,

pisno izražanje pri pisnem izpitu. Uporaba informacijske tehnologije: pisanje računalniških

programov. Spretnosti računanja: reševanje računskih problemov pri

domačih nalogah. Reševanje problemov: ocenjevanje časovne in prostorske

zahtevnosti algoritmov.

Transferable/Key skills and other attributes: Communication skills: oral lab work defence, manner of

expression at written examination. Use of information technology: writing computer programs. Calculation skills: solving calculation problems in homework

assignments. Problem solving: estimating time and space complexity of

algorithms.

Metode poučevanja in učenja:

Learning and teaching methods:

predavanja, seminarske vaje, laboratorijske vaje.

lectures, tutorials, lab work.

Načini ocenjevanja:

Delež (v %) / Weight (in %)

Assessment:

laboratorijske vaje, 1. vmesni pisni izpit, 2. vmesni pisni izpit.

50 25 25

lab work, 1st midterm written exam, 2nd midterm written exam.

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 50 %. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50 %. Reference nosilca / Lecturer's references: STRNAD, Damjan, GUID, Nikola. A fuzzy-genetic decision support system for project team formation. Applied soft computing,

ISSN 1568-4946, Sep. 2010, vol. 10, iss. 4, str. 1178-1187. STRNAD, Damjan. Parallel terrain visibility calculation on the graphics processing unit. Concurrency and computation, ISSN

1532-0634, 2011, vol. 23, iss. 8, str. 2452-2462. KOHEK, Štefan, STRNAD, Damjan. Interactive synthesis of self-organizing tree models on the GPU. Computing, ISSN 0010-

485X, Feb. 2015, vol. 97, iss. 2, str. 145-169. STRNAD, Damjan, GUID, Nikola. Parallel alpha-beta algorithm on the GPU. V: 33rd International Conference on Information

Technology Interfaces [also] ITI 2011, June 27-30, 2011, Cavtat / Dubrovnik, Croatia. LUŽAR - STIFFLER, Vesna (ur.), JAREC, Iva (ur.), BEKIĆ, Zoran (ur.). Proceedings of the ITI 2010, (ITI ... (Tisak), ISSN 1330-1012). Zagreb: University of Zagreb: University Computing Centre, cop. 2010, str. 571-576.

FISTER, Iztok, STRNAD, Damjan, YANG, Xin-She, FISTER, Iztok. Adaptation and hybridization in nature-inspired algorithms. V: FISTER, Iztok (ur.), FISTER, Iztok (ur.). Adaptation and Hybridization in Computational Intelligence, (Adaptation, learning, and optimization, ISSN 1867-4534, Vol. 18). Cham ... [et al.]: Springer, 2015, str. 3-50.


Predmet: Aplikacije računalniških algoritmov

Course title: Algorithms in the Real World



Letnik Academic

year

Semester Semester



technologies 1st cycle


1. poletni Spring



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6

Nosilec predmeta / Lecturer: Borut Žalik

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Uvod. Urejanje v linearnem času: števno urejanje, Romanov

algoritem, urejanje radix. Iskanje ujemanja nizov: naivni pristop, Rabin-Karpov

algoritem, Knut-Morris-Prattov algoritem, Boyer-Mooreov algoritem, Horspoolov algoritem, Sundayev algoritem.

Razdalja urejanja tekstovnih nizov, dinamičen algoritem, Bellmanova enačba, Wagner-Fischerjev algoritem.

Enostavni algoritmi kriptologije: pomikalni šifrirnik

Introduction. Sorting in linear time: count sort, Roman's sort, Radix sort. String matching: naive approach, Rabin-Karp algorithm,

Knut-Morris-Pratt algorithm, Boyer-Moore algorithm, Horspool algorithm, Sunday algorithm.

Editing distance, dynamic algorithm, Bellman equation, Wagner-Fischer algorithm.

Vigenerjev šifrirnik, šifrirnik Playfair, šifrirnik ADFGX.

Stiskanje podatkov: entropija informacije, kodiranje zaporedja enakih znakov (RLE), Shannon - Fanojev algoritem, Huffmanov algoritem, Huffmanov algoritem s prilagajanjem, aritmetično kodiranje, aritmetično kodiranje s pomikanjem, aritmetično kodiranje s transformacijo E1, E2, E3, stiskanje s slovarjem (LZ77, LZ78, LZSS LZW), izgradnja in upravljanje s slovarjem, Golombovo kodiranje, kodiranje zaporedja celih števil z algoritmom BASC, interpolativno kodiranje, FELICS.

Metode transformacije niza:, premik naprej (MTF), inverzne frekvence (IF), inverzne frekvence permutacij (IFP) drevo valčkov (WT), Burrows-Wheelerjeva transformacija (BWT).

Priponsko polje. Priponsko polje in BWT, Manber-Mayersov algoritem, algoritem DC3.

Priponsko drevo. Številsko drevo – TRIE. Naivna metoda konstrukcije priponskega drevesa. Ukkonenov algoritem. Uporaba priponskih dreves.

Simple cryptology algorithms: shift cipher, Vigener cipher, Playfair cipher, ADFGX cipher.

Compression: information entropy, Run-Length Encoding

(RLE), Shannon-Fano algorithm, Huffman algorithm, adaptive Huffman algorithm, arithmetic coding, arithmetic coding with shifting, arithmetic coding with transformation E1, E2, E3, dictionary based methods (LZ77, LZ78, LZSS, LZFG, LZW), building and maintaining of the dictionary, Golomb coding, Binary adaptive sequential coding (BASC), interpolative coding, FELICS, coding.

String transformation methods: Move-To-Front transform

(MTF), inverse frequencies (IF), inverse frequencies of permutations (IFP), wavelet tree (WT), Burrows-Wheeler transform (BWT).

Suffix array. Suffix array and BWT, Manber-Mayers algorithm, DC3 algorithm.

Suffix tree. RADIX tres - TRIE. Top-down algorithm for suffix tree construction. Ukkonen's algorithm. Applications of suffix trees.

Temeljni literatura in viri / Readings: T. H. Cormen, S. Clifford, C. E. Leiserson, R. L. Rivest: Introduction to Algorithms, Third Edition, MIT Press, Cambridge,

Massachusetts, 2009. D. Adjeroh, T. Bell, A. Mukherjee: The Burrows-Wheeler transform: Data Compression, Suffix Arrays, and Pattern Matching,

Springer Science+Bussiness Media, New York, 2008. D. Salomon, G. Motta: Handbook of Data Compression, Springer, Fifth Edition, New York, 2010. Cilji in kompetence:


Cilj predmeta je, da bodo študentje razumeli obravnavane algoritme, jih znali implementirati in uporabiti v praktičnih aplikacijah.

The objective of this course is for students to be able do demonstrate the understanding of considered algorithms, to implement them and to use them in different applications.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben uporabiti znanje računalniških algoritmov v različnih

praktičnih aplikacijah, razložiti principe učinkovitega reševanje algoritmičnih

problemov, načrtovati lastne učinkovite rešitve praktičnih algoritmičnih

problemov.

Knowledge and understanding: On completion of this course the student will be able to demonstrate understanding of algorithms in different

practical applications, explain principles of solving algorithmic problems in an

efficient way, Design of own solutions for practical algorithmic problems.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: pisno izražanje pri pisnem

izpitu, pisanje strokovnega poročila o opravljenih vajah, ustni zagovor laboratorijskih vaj.

Uporaba informacijske tehnologije: pisanje računalniških programov, iskanje dodatnih informacij na svetovnem spletu.

Transferable/Key skills and other attributes: Communication skills: written exam, writing report about lab

work, oral examination of lab work. Use of information technology: software development,

searching additional information of the WEB.

Reševanje problemov: izbira najprimernejšega algoritma za posamezno nalogo, ocenjevanje uspešnosti implementiranih algoritmov glede na časovno in prostorsko zahtevnost.

Problem solving: selecting the most suitable algorithm for desired task, estimation of efficiency of implemented algorithms regarding time and space complexity.



predavanja, seminarske vaje, laboratorijske vaje, reševanje domačih nalog.

lectures, tutorials, lab work, homework assignments.



Assessment:

opravljene domače naloge, laboratorijske vaje, 1. vmesni pisni izpit, 2. vmesni pisni izpit,

10 40 25 25

completed homework, lab work, 1st midterm written exam, 2nd midterm written exam,

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 50 %. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references: ŽALIK, Borut, MONGUS, Domen, LUKAČ, Niko, RIZMAN ŽALIK, Krista. Efficient chain code compression with interpolative

coding. Information sciences, 2018, vol. 439/440, str. 39-49. KOHEK, Štefan, STRNAD, Damjan, ŽALIK, Borut, KOLMANIČ, Simon. Interactive synthesis and visualization of self-

organizing trees for large-scale forest succession simulation. Multimedia systems, 2018, str. 1-15. LIPUŠ, Bogdan, ŽALIK, Borut. Robust watermarking of airborne LiDAR data. Multimedia tools and applications, 2018, vol. 77,

iss. 21, str. 29077-29097. ŽALIK, Borut, MONGUS, Domen, RIZMAN ŽALIK, Krista, LUKAČ, Niko. Boolean operations on rasterized shapes represented

by chain codes using space filling curves. Journal of visual communication and image representation, 2017, vol. 49, str. 420-432.


Predmet: Diskretne strukture

Course title: Discrete structures



Letnik Academic

year

Semester Semester





1. zimski Autum



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

45 45 90 6

Nosilec predmeta / Lecturer: Iztok Peterin

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Izjavni in predikatni račun: izjave, pravilnostne tabele, kvantifikatorji, pravila sklepanja, formalni dokaz.

Matematična indikcija, induktivna posplošitev, teorije. Osnove teorije števil: naravna števila, izrek o faktorizaciji,

kongruence, kitajski izrek o ostankih. Kombinatorika: pravilo vsote in pravilo produkta, princip

golobnjakov, variacije, kombinacije in permutacije, princip vključitve-izključitve.

Binarne relacije: operacije nad relacijami, tranzitivno

Fundamentals of mathematical logic: statements, truth tables, quantifiers, rules of inference, formal proof.

Mathematical induction, inductive generalization, theories. Fundamentals of Number theory: natural numbers,

factorisation theorem, congruences, Chinese remainder theorem.

Combinatorics: principle of sum and product, pigeon-hole principle, variations, combinations and permutations, inclusion-exclusion principle.

Binary relations: operations on relations, transitive closure

zaprtje in Warshallov algoritem, ekvivalenčne relacije, urejenosti.

Mreže in Boolove algebre: polurejenost in delna urejenost, ekstremni elementi, mreže, lastnosti mrež, Boolove algebre, Boolove funkcije

Diferenčne enačbe: homogene in nehomogene linearne diferenčne enačbe.

Osnove teorije grafov: osnovne definicije in lastnosti, dvodelni grafi, drevesa, Eulerjevi grafi, Hamiltonovi grafi, algoritmični vidiki, sorodni problemi na omrežjih, ravninski grafi.

and Warshall algorithm, equivalence relations, order relations.

Lattices and Boolean algebra, semi-order and partial order, extremal elements, lattices, properties of lattices, Boolean algebras. Recurrence relations: homogeneous and non-homogeneous linear recurrence relation.

Fundamentals of graph theory: basic definitions and properties, bipartite graphs, trees, Eulerian graphs, Hamiltonian graphs, algorithmic aspects, similar problems on networks, planar graphs.

Temeljni literatura in viri / Readings: K. H. Rosen: Discrete Mathematics and its Applications, McGraw-Hill, New York, 1995. V. Batagelj, S. Klavžar: DS1, DMFA, Ljubljana, 1997. V. Batagelj, S. Klavžar: DS2, DMFA, Ljubljana, 2000. R. P. Grimaldi: Discrete and Combinatorial Mathematics, Addison-Wesley, Reading, 1994. D. B. West: Introduction to Graph Theory, Prentice Hall, New Jersey, 2001. Cilji in kompetence:


Cilj predmeta je, da bodo študentje razumeli osnove diskretne matematike in da bodo sposobni reševati probleme, ki izhajajo iz nje.

The objective of this course is that students will understand the basics of discrete mathematics and that they will be able to solve the problems that arose from it.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben izkazati znanje in razumevanje osnovnih principov

diskretne matematike, identificirati in reševati probleme z uporabo

kombinatoričnih orodij, razložiti postopek reševanja diferenčnih enačb in rešiti

glavne tipe diferenčnih enačb, načrtovati in sestaviti osnovne algoritme na relacijah in

grafih ter analizirati njihovo časovno zahtevnost.

Knowledge and understanding: On completion of this course the student will be able to demonstrate knowledge and understanding of basic

principles of discrete mathematics, identify and solve problems by using combinatorial tools, explain the procedure of solving reccurence relations and

solve main types of reccurence relations, design and construct basic algorithms on relations and

graphs, and analyse their time complexity. Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: ustno izražanje na ustnem

izpitu, pisno izražanje pri pisnem izpitu. Uporaba informacijske tehnologije: uporaba programskih

orodij v diskretni matematiki. Spretnosti računanja: izvajanje računskih operacij za

reševanje diferenčnih enačb in pri reševanju kombinatoričnih problemov.

Reševanje problemov: sposobnost reševanja problemov z uporabo diskretnih struktur in kombinatoričnih principov.

Transferable/Key skills and other attributes: Communication skills: oral exam, manner of expression at

written exam. Use of information technology: use of software tools in

discrete mathematics. Calculation skills: performing computing operations for

solving reccurence relations and for solving combinatorial problems.

Problem solving: ability to solve problems by using discrete structures and combinatorial principles.




lectures, tutorial, lab work.



Assessment:

testi iz uporabnih znanj izpit iz teoretičnih znanj

50 % 50 %

practical knowledge tests theoretical knowledge exam

Opomba: Testi se lahko nadomestijo s pisnim izpitom. Note: The tests may be replaced with a written exam. Reference nosilca / Lecturer's references: HENNING, Michael A., PETERIN, Iztok. A characterization of graphs with disjoint total dominating sets.

Ars mathematica contemporanea, ISSN 1855‐3974. [Spletna izd.], 2019, vol. 16, no. 2, str. 359‐375. https://amc‐journal.eu/index.php/amc/article/download/1525/1302, doi: 10.26493/1855‐3974.1525.7f3. [COBISS.SI‐ID 18544217]

PETERIN, Iztok, YERO, Ismael G. Efficient closed domination in digraph products. Journal of combinatorial optimization, ISSN 1382‐6905, July 2019, vol. 38, iss. 1, str. 130‐149. https://doi.org/10.1007/s10878‐018‐0370‐y, doi: 10.1007/s10878‐018‐0370‐y. [COBISS.SI‐ID 18650713]

IMRICH, Wilfried, PETERIN, Iztok. Cartesian products of directed graphs with loops. Discrete Mathematics, ISSN 0012‐365X. [Print ed.], May 2018, vol. 341, iss. 5, str. 1336‐1343. https://doi.org/10.1016/j.disc.2018.01.021, doi: 10.1016/j.disc.2018.01.021. [COBISS.SI‐ID 18271065] PETERIN, Iztok, SCHREYER, Jens, FECKOVÁ ŠKRABUL'ÁKOVÁ, Erika, TARANENKO, Andrej. A note on the Thue chromatic number of lexicographic produts of graphs. Discussiones mathematicae, Graph theory, ISSN 1234‐3099, 2018, vol. 38, iss. 3, str. 635‐643. http://www.discuss.wmie.uz.zgora.pl/php/discuss3.php?ip=&url=pdf&nIdA=25507&nIdSesji=‐1, doi: 10.7151/dmgt.2032. [COBISS.SI‐ID 18373465]

GOLOGRANC, Tanja, JAKOVAC, Marko, PETERIN, Iztok. The security number of lexicographic products. Quaestiones mathematicae, ISSN 1607‐3606, 2018, vol. 41, iss. 5, str. 601‐613. https://doi.org/10.2989/16073606.2017.1393705, doi: 10.2989/16073606.2017.1393705. [COBISS.SI‐ID 18407257]


Predmet: Matematična analiza

Course title: Mathematical analysis



Letnik Academic

year

Semester Semester





1. Letni Spring



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

45 45 90 6


Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Zaporedja: monotonost, omejenost, konvergenca, limita, Cauchyjeva zaporedja, podzaporedja, stekališča, število e.

Funkcije ene spremenljivke: elementarne funkcije, limita, zveznost, zveznost elementarnih funkcij, lastnosti zveznih funkcij, enakomerna zveznost.

Diferencialni račun: odvod, osnovna pravila, odvod elementarnih funkcij, diferenciabilnost, višji odvodi, diferenciali, lastnosti diferenciabilnih funkcij, L'Hospitalovo pravilo, Taylorjev polinom, ekstremi, konveksnost, konkavnost, prevoj.

Vrste: številske vrste, lastnosti konvergentnih vrst,

Sequences: monotone and bounded sequences, convergence, limit, Cauchy sequences, subsequences, condensation points, the number e.

Functions of one variable: elementary functions, limit, continuity, continuity of elementary functions, properties of continuous functions, uniform continuity.

Differential calculus: derivative, basic rules, derivatives of elementary functions, differentiability, derivatives of higher orders, differentials, properties of differentiable functions, L’Hospital’s rule, Taylor’s polynomial, extreme values, convexity, concavity, points of inflection.

Series: series of numbers, properties of convergent series,

konvergenčni kriteriji, absolutna konvergenca, alternirajoče vrste in Leibnitzov pogoj, funkcijske vrste, točkovna in enakomerna konvergenca, potenčne vrste, Taylorjeva vrsta.

Integral: nedoločeni integral, osnovna pravila, integracijske metode, določeni integral, lastnosti določenega integrala, Newton - Leibnizova formula, posplošeni integrali, uporaba določenega integrala.

criterions of convergence, absolute convergence, alternating series and Leibnitz’s criterion, function series, point and uniform convergence, power series, Taylor’s series.

Integration: indefinite integral, basic rules, methods of integration, definite integral, properties of definite integral, Newton-Leibniz formula, improper integrals, applications of definite integrals.

Temeljni literatura in viri / Readings: F. Brešar, B. Brešar: Analiza I, Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko, Maribor, 2004. F. Brešar, B. Brešar: Analiza II, Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko, Maribor, 2005. I. Vidav: Višja matematika I, DMFA, Ljubljana, 1987. P. Mizori-Oblak: Matematika I, Univerza v Ljubljani, Fakulteta za strojništvo, Ljubljana, 1997. R. C. Buck, E. F. Buck: Advanced Calculus, McGraw-Hill, New York, 1965. Cilji in kompetence:


Cilj predmeta je razumevanje študentov osnov matematične analize in reševanje problemov, ki izhajajo iz nje.

The objective of this course is students to understand the basics of mathematical analysis and to solve the problems that arose from it.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben izkazati znanje in razumevanje osnovnih pojmov

matematične analize, identificirati in rešiti probleme povezane z matematično

analizo in jih uporabiti na drugih področjih, pokazati sposobnost matematičnega sklepanja in

razumevanje principov dokazovanja.

Knowledge and understanding: On completion of this course the student will be able to demonstrate knowledge and understanding of basic

concepts in mathematical analysis, identify and solve problems related to mathematical

analysis and use them in other areas, show ability of mathematical reasoning and understanding

of principles of proofs.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: izražanje pri ustnem izpitu,

pisno izražanje pri pisnem izpitu. Uporaba informacijske tehnologije: uporaba programskih

orodij v matematiki. Spretnosti računanja: izvajanje računskih operacij pri

odvajanju, integriranju in računanju limit. Reševanje problemov: sposobnost reševanja

matematičnih problemov v različnih kontekstih.

Transferable/Key skills and other attributes: Communication skills: oral exam, manner of expression at

written examination. Use of information technology: use of software tools in

mathematics. Calculation skills: performing computing operations for

derivation, integration and calculation of limits. Problem solving: ability to solve mathematical problems in

various contexts Metode poučevanja in učenja:






Assessment:

testi iz uporabnih znanj izpit iz teoretičnih znanj

50 % 50 %


Opomba: Testi se lahko nadomestijo s pisnim izpitom. Note: The tests may be replaced with a written exam. Reference nosilca / Lecturer's references:

HENNING, Michael A., PETERIN, Iztok. A characterization of graphs with disjoint total dominating sets. Ars mathematica contemporanea, ISSN 1855‐3974. [Spletna izd.], 2019, vol. 16, no. 2, str. 359‐375. https://amc‐journal.eu/index.php/amc/article/download/1525/1302, doi: 10.26493/1855‐3974.1525.7f3. [COBISS.SI‐ID 18544217]





Predmet: Osnove računalniških sistemov

Course title: Computer Şystems Basics



Letnik Academic

year

Semester Semester

Računalništvo in informacijske tehnologije Computer science and information technologies

1. zimski

Autumn



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 30 90 5

Nosilec predmeta / Lecturer: Milan Zorman

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Uvod v računalništvo: zgodovinski pregled, mehanski elektromehanski in elektronski računalniki.

Informacijska tehnologija, računalniška pismenost. Reševanje problemov z računalniki: postopkovno

razmišljanje, snovanje rešitev, programiranje. Računalniška arhitektura: von Neumannov model

računalnika. Sestava računalnika; pregled razvoja ter stanja tehnike

sestavnih elementov: centralna procesna enota, vhodno izhodne enote, notranji in zunanji pomnilnik, periferne naprave.

Številski sistemi, pretvorbe in aritmetika. Logični izrazi in operacije. Turingov stroj. Računalniški sistemi in programska oprema. Računalništvo in intelektualna lastnina.

Introduction to Computer Science: historical timeline; mechanical and electronic computers.

Information technology, computer literacy. Solving problems with computers: procedural thinking,

generating solutions, programming. Computer architecture: von Neumann’s model. Components of computer architecture; development and

state of the art of components: CPU, input – output units, internal and external memory, peripheral devices.

Number systems, conversions and arithmetic. Logic expressions and operations. Turing machine. Computer systems and software. Computer Science and intellectual property.

Temeljni literatura in viri / Readings: R. E. Bryant, D. R. O'Hallaron: Computer Systems: A Programmer's Perspective, Pearson, 2016. J. S. Warford: Computer Systems, Jones & Bartlett Learning, 2009. M. E. Vermaat, S. L. Sebok, S. M. Freund, J. T. Campbell, M. Frydenberg,: Discovering Computers 2018: Digital Technology,

Data, and Devices, Course Technology, 2017. B. Christian, T. Griffiths: Algorithms to Live By: The Computer Science of Human Decisions, HarperCollins Publishers, 2017. Cilji in kompetence:


Naučiti študenta osnov delovanja računalnika. Študent dojame vlogo informacijsko komunikacijske tehnologije v sodobnem svetu. Študent se nauči osnovnih aplikacij računalnika v sodobnem svetu.

The student will learn the basic working of a computer system. The student understands the role of the information and communication technology in real world. The students know the real world applications of computers.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben poznavati delovanja računalnika, razumeti možnosti uporabe računalniških sistemov in

informacijske tehnologije, uporabiti računalniške sisteme in informacijske tehnologije

za reševanje problemov.

Knowledge and understanding: On completion of this course the student will be able to present the knowledge in the basics of computers systems, understand possible applications of computer systems and

information technology, use computer systems and information technologies to

solve problems.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: poznavanje osnovnih terminov s

področja računalniških sistemov in informacijske tehnologije.

Transferable/Key skills and other attributes: Communication skills: knowing of basic computers system

and information system terminology



predavanja, vaje.

Lectures, lab vork.



Assessment:

vaje, 1. vmesni izpit, 2. vmesni izpit.

20

40

40

lab work, 1st midterm examination, 2nd midterm examination.

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 80 %. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 80 %

Reference nosilca / Lecturer's references: ZORMAN, Milan, SÁNCHEZ DE LA ROSA, José Luis, DINEVSKI, Dejan. Classification of follicular lymphoma images : a holistic

approach with symbol-based machine learning methods. Wien. Klin. Wochenschr., 2011, jg. 123, heft 23/24, str. 700-709, graf. prikazi. [COBISS.SI-ID 15706134]

POHOREC, Sandi, VERLIČ, Mateja, ZORMAN, Milan. Information extraction from concise passages of natural language sources. Lect. notes comput. sci., 2010, vol. 6295, str. 463-474. [COBISS.SI-ID 14442774]

ZORMAN, Milan, POHOREC, Sandi, BRUMEN, Boštjan. Opening the knowledge tombs - web based text mining as approach for re-evaluation of machine learning rules. Lect. notes comput. sci., 2010, vol. 6295, str. 533-542. [COBISS.SI-ID 14444310]

ZORMAN, Milan, VERLIČ, Mateja. Explanatory approach for evaluation of machine learning-induced knowledge. J. int. med. res., 2009, letn. 37, št. 5, str. 1543-1551. [COBISS.SI-ID 13645334]

PODGORELEC, Vili, ZORMAN, Milan. Decision trees. V: MEYERS, Robert A. (ur.). Encyclopedia of complexity and systems science. New York: Springer, cop. 2009, vol. 2, str. 1826-1845. [COBISS.SI-ID 13603350]


Predmet: Osnove svetovnega spleta

Course title: Web Fundamentals



Letnik Academic

year

Semester Semester





1. zimski

Automn



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6

Nosilec predmeta / Lecturer: Niko Lukač

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Uvod: zgodovina interneta, osnovne storitve, iskanje informacij po spletu, pasti interneta.

HTML: osnovne značke, tabele, okvirji, seznami, pomenske značke, obrazci, slikovne mape, večpredstavne vsebine, XHTML, HTML5, optimizacija za spletne iskalnike.

Osnove spletnega oblikovanja, barve, CSS in CSS3, odzivno spletno oblikovanje..

Javascript: krmilne strukture in operatorji, funkcije, osnovni objekti (Array, Boolean, Date, Math, String, HTML

Introduction: history of the internet, internet services, searching on the Web, internet traps.

HTML: basic tags, tables, frames, lists, forms, clickable maps, backgrounds,,multimedia content, XHTML, HTML5, search engine optimisation.

Web design basics, colours, CSS and CSS3, responsive Web design.

JavaScript: control structures and operators, functions, basic objects (Array, Boolean, Date, Math, String, HTML DOM objects), AJAX, JQuery.

objekti DOM), AJAX, JQuery. Osnove skriptnega jezika PHP: podatkovni tipi, osnovni

konstrukti, polja, funkcije. Mikroformati, HTML5 microdata, XML, RDFa, SVG. Uvod v spletne tehnologije.

PHP: control structures and operators, data types, arrays, functions.

Microformats. HTML5 microdata, XML, RDFa, SVG. Intoroduction to Web technologies.

Temeljni literatura in viri / Readings: Ojsteršek M: Učno gradivo in primeri dosegljivi na E-študij UM: https://estudij.um.si/ – potrebna je prijava v portal. Spletni vir W3Schools: dosegljiv na http://www.w3schools.com/, obiskano 31. 5. 2018 Frain, B.: Responsive Web design with HTML5 and CSS3. Packt Publishing Ltd, 2015. Ruvalcaba, Z., Delamater, M., Boehm, A.,Murach, M.: Murach's JavaScript and jQuery, 3rd Edition. Mike Murach & Associates.

2017. Murach J., Harris R, Boehm A.: Murach's PHP and MySQL, 3rd Edition, Mike Murach & Ąsociates, Fresno, 2017.. Cilji in kompetence:


Cilj predmeta je študenta naučiti kako uporabiti osnovne storitve na internetu, izdelati in testirati preproste spletne aplikacije, pisane v HTML, CSS, Javascriptu in PHP-ju.

The objective of this course is to teach students how to use basic services on the internet and how to implement and test simple Web pages, written in HTML, CSS, Javascript and PHP.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben: poiskati in uporabiti ustrezne informacije na internetu, uporabljati osnovne storitve, ki jih ponuja internet, pisati preproste spletne strani z uporabo jezika HTML,

Javascript in PHP.

Knowledge and understanding: On completion of this course the student will be able to find and use appropriate information on the internet, use basic internet services, write simple Web pages with usage of HTML, CSS,

Javascript and PHP.


ustno izražanje na ustnem izpitu, pisno izražanje pri pisnem izpitu.

Uporaba informacijske tehnologije: uporaba programskih orodij za načrtovanje, implementacijo, razhroščevanje in testiranje enostavnih spletnih programov.

Reševanje problemov: načrtovanje in implementacija enostavnih spletnih programov.


expression at written examination and oral examination. Use of information technology: use of different tools for

program design, implementation, debugging and testing of simple Web applications.

Problem solving: design and implementation of simple Web application.



predavanja, laboratorijske vaje.

lectures, lab work.



Assessment:

laboratorijske vaje , 1. vmesni pisni izpit, 2. vmesni pisni izpit.

50 25 25

computer lab work*, 1st midterm written exam, 2nd midterm written exam.

*Obvezno / Mandatory Opomba: Če študent ni uspešno opravil vseh treh vmesnih izpitov, jih nadomesti s pisnim izpitom v deležu 50%. Note: If a student has not completed all three midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references:

• LUKAČ, Niko, ŽALIK, Borut. GPU-based roofs' solar potential estimation using LiDAR data. Computers & Geosciences, ISSN 0098-3004. [Print ed.], Mar. 2013, vol. 52, str. 23-41, doi: 10.1016/j.cageo.2012.10.010. • LUKAČ, Niko, ŠPELIČ, Denis, ŽALIK, Borut. Hybrid visualization of sparse point-based data using GPGPU. V: CANDAR 2014 : proceedings, Second International Symposium on Computing and networking, 10-12 December 2014, Shizuoka, Japan. Los Alamitos (California) • LUKAČ, Niko, JESENKO, David, BIZJAK, Marko, ŽALIK, Borut. GPU-based DBSCAN clustering on locality sensitive hashing. V: Conference proceeding, 7th international conference of engineering and applied sciences (ICEAS 2017) at Toronto, ON, Canada, June 27-28, 2017. • LUKAČ, Niko, ŽALIK, Borut. GPU-based rectification of high-resolution remote sensing stereo images. V: HUANG, Bormin (ur.), LÓPEZ, Sebastián (ur.), WU, Zhensen (ur.). High-Performance Computing in Remote Sensing IV, September 22, 2014, Amsterdam, Netherlands, (Proceedings of SPIE, the International Society for Optical Engineering, ISSN 0277-786X, vol. 9247). [Bellingham: SPIE. 2014], str. 1-8. • LUKAČ, Niko, ŽALIK, Borut, RIZMAN ŽALIK, Krista. Sweep-hyperplane clustering algorithm using dynamic model. Informatica, ISSN 0868-4952, 2014, vol. 25, no 4, str. 564-580, doi: 10.15388/Informatica.2014.30.


Predmet: Podatkovne baze I

Course title: Databases I



Letnik Academic

year

Semester Semester





1. poletni Spring



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

45 30 105 6

Nosilec predmeta / Lecturer: Tatjana Welzer Družovec

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Uvod v oblikovanje podatkovne baze: seznanitev z osnovnimi pojmi in s posameznimi fazami oblikovanja s poudarkom na zbiranju in analizi zahtev.

Konceptualno modeliranje: vloga konceptualnega modela, uvedba entitetno - relacijskega (E-R) modela (entiteta, relacija, atribut, ključ, kardinalnost).

Normalizacija: vloga in pomen normalizacije pri oblikovanju podatkovne baze, funkcionalne odvisnosti, normalne oblike (1NO, 2NO, 3NO, BCNO, 4NO, 5NO).

Logično modeliranje: predstavitev logičnega modeliranja

Introduction to database modelling: basic definitions and acquaintance of each modelling phases with focus on requirements collection and analysis.

Conceptual modelling: role of conceptual model, entity-relationship model (entity, relationship, attribute, key, cardinality).

Normalization: role and meaning of normalization for database modelling, functional dependencies, normal forms (1NF, 2NF, 3NF, BCNF, 4NF, 5NF).

Logical modelling: logical data models (hierarcical, ,

in logičnih podatkovnih modelov (hierarhičnega, mrežnega in relacijskega).

Relacijski podatkovni model: vzroki za nastanek relacijskega podatkovnega modela in njegova uveljavitev, pravila za prehod iz E-R modela v relacijski model, relacijska algebra, relacijski račun.

Povpraševalni jeziki: teoretične osnove, QBE, SQL - osnovni stavki, sestavljeni stavki in primeri uporabe.

Administriranje podatkovne baze: osebe in funkcije, podatkovni slovar.

relational). Relational data model: reasons for appearance of relational

data model, rules for making transformation from E-R model to relational model, relational algebra, relational calculus.

Query languages: theoretical basis, QBE, SQL – basic sentences, composed sentences and use cases.

Administrating databases: persons and functions, data dictionary.

Temeljni literatura in viri / Readings: D. Mohorič: Uvod v podatkovne baze, Bi-TIM, Ljubljana, 1995. R. Elmasri, S. Navathe: Fundamentals of Database Systems, 7th.Edition, Pearson, 2016. T. Connolly, C. Begg: Database Systems:A Practical Approach to Design, Implementation and Management, 6th. Edition,

Pearson, 2014. P.O'Neil, E. O'Neil: Database, 2nd. Edition, Morgan Kaufmann Publishers, 2001. C. J. Date: An introduction to Database Systems, Pearson, 2012. Cilji in kompetence:


Cilj predmeta je usposobiti študente, da bodo poznali ANSI-SPARC arhitekturo in da bodo razumeli razliko med posameznimi nivoji modeliranja relacijske podatkovne baze. Ključni cilj je študente pripraviti, da bodo znali primerno načrtovati in s tem konceptualno modelirati relacijsko podatkovno bazo in učinkovito uporabiti povpraševalni jezik SQL za upravljanje tabel relacijske podatkovne baze ter vnos, posodabljanje in branje podatkov iz relacijske podatkovne baze.

The objective of the course is to present students with the ANSI-SPARC architecture and to prepare them to understand the difference between the individual levels of the relational database modeling. The key goal is to prepare students to be able to properly design a relational database, thereby conceptually model it, and effectively use the SQL query language to manage the relational database tables and to input, update and retrieve data from a relational database.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben: opisati ANSI-SPARC arhitekturo, razumeti konceptualno, logično in fizično modeliranje

relacijske podatkovne baze RPB, pojasniti povezavo med različnimi nivoji modeliranja, raziskati zahteve za RPB, načrtovati RPB, izvesti konceptualno modeliranje RPB s pomočjo ER

diagramske tehnike, prenesti konceptualni model v logični model, uporabiti povpraševalni jezik SQL za upravljanje RPB,

vnos, posodabljanje, brisanje in iskanje podatkov iz RPB.

Knowledge and understanding: On completion of this course the student will be able to: describe the ANSI-SPARC architecture, understand the conceptual, logical, and physical modeling

of the relational database RDB, clarify the connection between different levels of modeling

RDB, investigate the requirements for RDB, design RDB, perform conceptual modeling of RDB using the ER

diagram, transform the conceptual model into a logical model, use SQL query language to manage RDB, input, update,

delete, and retrieve data from RDB.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja ustni zagovor laboratorijskih vaj,

izražanje pri pisnem izpitu. Uporaba informacijske tehnologije: uporaba programskih

orodij za načrtovanje podatkovnih baz in izvedbo

Transferable/Key skills and other attributes: Communication skills: oral laboratory work defense, manner

of expression at written examination. Use of information technology: use of software tools for

modelling databases and query sentences execution. Problem solving designing and implementing simple

povpraševanja. Reševanje problemov: načrtovanje in implementacija

preprostih podatkovnih baz.

databases.



Predavanja, laboratorijske vaje, priprava na laboratorijske vaje.

Lectures, laboratory work, preparation on laboratory work.



Assessment:

laboratorijske vaje, pisni izpit.

40 60

laboratory work, written exam

Reference nosilca / Lecturer's references: WELZER-DRUŽOVEC, Tatjana, DRUŽOVEC, Marjan, HÖLBL, Marko, ZORIČ-VENUTI, Metka. Experiences in international

cooperation in teaching. Elektron. elektrotech.. [Print ed.], 2010, nr. 6, str. 19-22. [COBISS.SI-ID 14245398], [JCR, WoS do 9. 9. 2010: št. citatov (TC): 0, čistih citatov (CI): 0, normirano št. čistih citatov (NC): 0, Scopus do 13. 6. 2012: št. citatov (TC): 1, čistih citatov (CI): 1, normirano št. čistih citatov (NC): 1]

WELZER-DRUŽOVEC, Tatjana, ZORIČ-VENUTI, Metka, WARD, Antony, HÖLBL, Marko, DRUŽOVEC, Marjan. Virtual education centre for the development of expert skills and competencies. International journal of advanced corporate learning. [Online izd.], 2011, vol. 4, no. 4, str. 51-54, doi: ijac.v4i4.1747. [COBISS.SI-ID 15528726]

KAMIŠALIĆ, Aida, HERIČKO, Marjan, WELZER-DRUŽOVEC, Tatjana, TURKANOVIĆ, Muhamed. Experimental study on the effectiveness of a teaching approach using Barker or Bachman notation for conceptual database design. Computer science and information systems, ISSN 1820-0214. [Print ed.], 2018, vol. 15, no. 2, str. 421-448, doi: 10.2298/CSIS180322008K. [COBISS.SI-ID 21524246]

WELZER-DRUŽOVEC, Tatjana. Cultural and security issues in knowledge management (Invited lecture). V: Znalosti 2009 : zborník príspevkov : proceedings, (Edícia zborníkov Informatiky a informačných technológií). Bratislava: Vydavatel'stvo Slovenskej technickej univerzity, 2009, str. 25-29. [COBISS.SI-ID 13043478]

WELZER-DRUŽOVEC, Tatjana, JAAKKOLA, Hannu, DRUŽOVEC, Marjan, HÖLBL, Marko. Cultural awareness for the global modeling. V: KIYOKI, Yasushi (ur.). EJC2012 : proceedings of the 21th European-Japanese Conference on Information Modelling and Knowledge Bases, Prague, Czech Republic, June 4-9, 2012. [S. l.]: EJC Program Committee: EJC Program Coordination Team, 2012, str. 306-311. [COBISS.SI-ID 16065814]


Predmet: Programiranje II

Course title: Programming II



Letnik Academic

year

Semester Semester





1. poletni Spring



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6

Nosilec predmeta / Lecturer: Marjan Mernik

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Ni pogojev. None.

Vsebina:


Uvod v objektno usmerjeno programiranje: slabosti strukturiranega programiranja, prednosti objektno usmerjenega programiranja.

Razredi in objekti: razred in komponente razreda, ustvarjanje objektov, konstruktorji in destruktorji, konstantni objekti, statični elementi razreda, skrivanje informacij.

Kazalci: kazalci na objekte, kazalec this, dinamične podatkovne strukture.

Prekrivanje: prekrivanje metod, prekrivanje operatorjev, operatorji kot prijateljske funkcije.

Introduction to object-oriented programming: shortcomings of structured programming, advantages of object-oriented programming.

Classes and objects: class and class members, object creation, constructors and destructors, constant objects, static class members, information hiding.

Pointers: pointer to objects, this pointer, dynamic data

structures. Overloading: method overloading, operator overloading,

operators as friend functions.

Dedovanje: nadrazredi in izpeljani razredi, zaščiteni elementi, virtualne funkcije, abstraktni razredi, dinamično povezovanje, večkratno dedovanje.

Uvod v objektno usmerjeno analizo in načrtovanje: analiza, načrtovanje, osnove UML.

Šablone: šablone funkcij, šablone razredov, knjižnica STL. Izjeme: zbujanje izjem, lovljenje izjem. Podatkovni tokovi: vhodni tokovi, izhodni tokovi, datoteke,

vhod/izhod za uporabniško definirane tipe. Novi konstrukti v jeziku C++11 in C++14

Inheritance: super classes, derived classes, protected members, virtual functions, abstract classes, dynamic binding, multiple inheritance.

Introduction to object-oriented analysis and design: analysis, design, UML fundamentals.

Templates: function templates, class templates, Standard Template Library (STL).

Exceptions: throwing exceptions, exception handling. Data streams: input streams, output streams, files, I/O

streams for user defined types. New language features of C++11 and C++14

Temeljni literatura in viri / Readings: B. Stroustrup: Programming: Principles and Practice Using C++, Addison-Wesley, Reading, 2014. B. Stroustrup: The C++ Programming Language, Second Edition, Addison-Wesley, Reading, 1991. H. M. Deitel, P. J. Deitel: C++ How to Program, Fourth Edition, Prentice Hall, London, 2002. F. M. Carrano: Data Abstraction and Problem Solving with C++: Walls and Mirrors, Fourth Edition, Addison Wesley, Reading,

2004. F. L. Friedman, E. B. Koffman: Problem Solving, Abstraction, and Design Using C++, Addison-Wesley, Reading, 1994. Cilji in kompetence:


Cilj tega predmeta je razumeti osnove objektno usmerjenega programiranja in jih naučiti načrtovanja, kodiranja, razhroščevanja, testiranja in dokumentiranja programov.

The objective of this course is to understand the fundamentals of object-oriented programming and to teach them how to design, implement, debug, test, and document programs.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben razumeti tehnike objektno usmerjenega programiranja, razumeti razlike med strukturiranim in objektno

usmerjenim programiranjem, definirati razrede in podrazrede, ustvarjati objekte,

definirati polimorfne metode, razumeti, kako so objekti implementirani v jeziku C++, uporabljati podatkovne tokove, definirati šablone in obravnavati izjeme, uporabljati knjižnico STL, načrtovanja, implementiranja, razhroščevanja in

dokumentiranja preprostejših programov.

Knowledge and understanding: On completion of this course the student will be able to understand object-oriented programming techniques, understand differences between structured and object-

oriented programming, define classes and subclasses, create objects and define

polymorphic methods, understand how objects are implemented in C++ language, use data streams, define templates and exceptions, use Standard Template Library, design, implement, debug, and document simple programs.


pisno izražanje pri pisnem izpitu. Uporaba informacijske tehnologije: uporaba programskih

orodij za načrtovanje, implementacijo, razhroščevanje in testiranje programov.

Reševanje problemov: načrtovanje in implementacija programov.


expression at written examination. Use of information technology: use of different tools for

program design, implementation, debugging and testing. Problem solving: design and implementation of programs.



Predavanja, laboratorijske vaje.

Lectures, lab work.

Delež (v %) /

Načini ocenjevanja: Weight (in %) Assessment: Sprotni način laboratorijske vaje, 1. vmesni izpit, 2. vmesni izpit

Delež 50

25

25

Constant assessment methods lab work, 1st midterm examination, 2nd midterm examination,

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 50 %. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50 %.. Reference nosilca / Lecturer's references:

KOSAR, Tomaž, MERNIK, Marjan, GRAY, Jeffrey G., KOS, Tomaž. Debugging measurement systems using a domain-specific modeling language. Computers in industry, ISSN 0166-3615. [Print ed.], 2014, vol. 65, iss. 4, str. 622-635.

MERNIK, Marjan. An object-oriented approach to language compositions for software language engineering. The Journal of Systems and Software, ISSN 0164-1212. [Print ed.], 2013, vol. 86, iss. 9, str. 2451-2464.

KOS, Tomaž, KOSAR, Tomaž, MERNIK, Marjan. Development of data acquisition systems by using a domain-specific modeling language. Computers in industry, ISSN 0166-3615. [Print ed.], Apr. 2012, vol. 63, no. 3, str. 181-192.

KOSAR, Tomaž, MERNIK, Marjan, CARVER, Jeffrey C. Program comprehension of domain-specific and general-purpose languages : comparison using a family of experiments. Empirical software engineering, ISSN 1382-3256, 2012, vol. 17, no. 3, str. 276-304.

ARORA, Ritu, BANGALORE, Purushotham, MERNIK, Marjan. Raising the level of abstraction for developing message passing applications. The journal of supercomputing, ISSN 0920-8542, 2012, vol. 59, no. 2, str. 1079-1100.


Predmet: Programiranje I

Course title: Programming I



Letnik Academic

year

Semester Semester





1. zimski

Automn



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 135 7

Nosilec predmeta / Lecturer: Janez Brest

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

NI pogojev. None.

Vsebina:


Uvod: osnovna sintaksa in semantika visoko nivojskega programskega jezika, algoritem, von Neumannov računalnik, spremenljivka, prirejanje, enostavni primeri programov.

Tipi in izrazi: osnovni podatkovni tipi, izrazi in operatorji. Krmilne strukture: pogojne in iterativne krmilne strukture,

strukturna dekompozicija. Funkcije: podprogram, prenos parametrov po vrednosti,

prenos parametrov po referenci, prekrivanje funkcij. Algoritmi in reševanje nalog: strategije reševanja nalog,

vloga algoritmov pri reševanju nalog, koncepti in lastnosti

Introduction: basics of syntax and semantic of high-level programming language, algorithm, von Neumann computer, variable, assignment, simple program examples.

Types and expressions: primitive data types, expressions and operators.

Control structures: choices, repetitions, structured decomposition.

Functions: subroutines, parameter passing by value, parameter passing by reference, function overloading.

Algorithms and problem-solving: problem solving strategies, role of algorithms in the problem solving process, concepts

algoritmov. Načrtovanje programov: psevdokod, strategije

implementacij algoritma, funkcije, testiranje, razhroščevanje.

Polja: algoritmi iskanja, urejanje polj, prenos polj v funkcijo.

Strukture in kazalci, uporabniško definirane podatkovne strukture, predstavitev podatkov v pomnilniku, nizi in delo z nizi.

Kazalci in reference: kazalec na strukturo, referenca, upravljanje s pomnilnikom v času izvajanja programa.

Dinamična podatkovna struktura, seznam. Rekurzija: rekurzivne matematične funkcije,

implementacija rekurzije, algoritmi, dinamične podatkovne strukture, drevo.

and properties of algorithms. Algorithm design: pseudocode, implementation strategies

for algorithms, functions, testing, debugging. Arrays: search algorithms, array sorting, array passing into

function. representation in memory, strings and string processing.

Structure and pointers, user-defined data structures, data Pointers and references: pointer to a structure, reference,

runtime storage management. Dynamic data structures, linked list. Recursion: recursive mathematical functions,

implementation of recursion, algorithms, dynamic data structures, tree.

Temeljni literatura in viri / Readings:

V. Žumer, J. Brest: Strukturirano programiranje v C++, 2. izdaja, Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko, Inštitut za računalništvo, Maribor, 2002.

S. Prata: C++ Primer Plus, Sixth Edition, Addison Wesley Professional, Indianapolis, 2011. S. Sahni: Data Strutures, Algorithms, and Applications in C++, Second Edition, Silicon Press,

Summit, NJ, 2005. P. J. Deitel, H. Deitel: C++ How to Program, Tenth Edition, Person Education Limited,Harlow, Essex, England, 2017.

Cilji in kompetence:


Cilj predmeta je naučiti študente algoritmičnega razmišljanja in strukturiranega programiranja.

The objective of this course is to learn students with algorithmic thinking and structure programming.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben izkazati znanje in razumevanje strukturiranega

programiranja, izkazati znanje in razumevanje sintakse programskega

jezika C++, izkazati in uporabiti osnovne pristope pri analizi,

načrtovanju, kodiranju in testiranju računalniških programov,

načrtovati algoritme za reševanje preprostih nalog, izkazati znanje in implementirati osnovne algoritme in

podatkovne strukture.

Knowledge and understanding: On completion of this course the student will be able to demonstrate knowledge and understanding of the structure

programming, understand and demonstrate knowledge of C++

programming language syntax, demonstrate and use fundamental principles of problem

analysis, design, coding, and testing of computer programs, create algorithms for solving simple problems, demonstrate knowledge and use of basic algorithms and

data structures.


pisno izražanje pri pisnem izpitu, ustno izražanje pri ustnem izpitu.

Uporaba informacijske tehnologije: uporaba programskih orodij za programiranje.

Reševanje nalog: načrtovanje, kodiranje, testiranje programov.


expression at written and oral examination. Use of information technology: use of software tools and

scripts to automate routine tasks in system administration. Problem solving: designing, coding, testing programs.




lectures, lab work.



Assessment:


50 % 25 % 25 %


Opomba: Če študent ni uspešno opravildveh vmesnih izpitov, jih nadomesti s pisnim izpitom v deležu 50%. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references: BOŠKOVIĆ, Borko, BREST, Janez. Protein folding optimization using differential evolution extended with local search and

component reinitialization. Information sciences, ISSN 0020-0255. [Print ed.], July 2018, vol. 454/455, str. 178-199, doi: 10.1016/j.ins.2018.04.072. [COBISS.SI-ID 21401878], [JCR, SNIP, WoS do 11. 11. 2018: št. citatov (TC): 1, čistih citatov (CI): 1, čistih citatov na avtorja (CIAu): 0.50, Scopus do 29. 10. 2018: št. citatov (TC): 1, čistih citatov (CI): 1, čistih citatov na avtorja (CIAu): 0.50]

SEPESY MAUČEC, Mirjam, BREST, Janez, BOŠKOVIĆ, Borko, KAČIČ, Zdravko. Improved differential evolution for large-scale black-box optimization. IEEE access, ISSN 2169-3536, Dec. 2018, iss. 1, vol. 6, str. 29516-29531, doi: 10.1109/ACCESS.2018.2842114. [COBISS.SI-ID 21465622], [JCR, SNIP, WoS do 14. 4. 2019: št. citatov (TC): 2, čistih citatov (CI): 2, čistih citatov na avtorja (CIAu): 0.50, Scopus do 30. 11. 2018: št. citatov (TC): 2, čistih citatov (CI): 1, čistih citatov na avtorja (CIAu): 0.25]

FISTER, Iztok, FISTER, Dušan, DEB, Suash, MLAKAR, Uroš, BREST, Janez, FISTER, Iztok. Post hoc analysis of sport performance with differential evolution. Neural computing & applications, ISSN 0941-0643, First Online: 02 March 2018, str. 1-10, doi: 10.1007/s00521-018-3395-3. [COBISS.SI-ID 21214998], [JCR, SNIP, Scopus do 29. 4. 2019: št. citatov (TC): 1, čistih citatov (CI): 1, čistih citatov na avtorja (CIAu): 0.17]

BREST, Janez, BOŠKOVIĆ, Borko. A heuristic algorithm for a low autocorrelation binary sequence problem with odd length and high merit factor. IEEE access, ISSN 2169-3536, 2018, vol. 6, str. 4127-4134, doi: 10.1109/ACCESS.2018.2789916. [COBISS.SI-ID 21347606], [JCR, SNIP, WoS do 14. 4. 2018: št. citatov (TC): 0, čistih citatov (CI): 0, čistih citatov na avtorja (CIAu): 0, Scopus do 14. 4. 2018: št. citatov (TC): 0, čistih citatov (CI): 0, čistih citatov na avtorja (CIAu): 0]

BREST, Janez, GREINER, Sašo, BOŠKOVIĆ, Borko, MERNIK, Marjan, ŽUMER, Viljem. Self-adapting control parameters in differential evolution: a comparative study on numerical benchmark problems. IEEE transactions on evolutionary computation, ISSN 1089-778X. [Print ed.], dec. 2006, vol. 10, no. 6, str. 646-657. [COBISS.SI-ID 10376982], [JCR, SNIP, WoS do 11. 9. 2016: št. citatov (TC): 806, čistih citatov (CI): 790, čistih citatov na avtorja (CIAu): 158.00, normirano št. čistih citatov (NC): 789, Scopus do 20. 9. 2016: št. citatov (TC): 1290, čistih citatov (CI): 1240, čistih citatov na avtorja (CIAu): 248.00, normirano št. čistih citatov (NC): 1239]


Predmet: Uporabniška programska oprema

Course title: User Software



Letnik Academic

year

Semester Semester





1. zimski

Autumn



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 30 120 6

Nosilec predmeta / Lecturer: Danilo Korže

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Uvod: delitev programske opreme, uporabniška programska oprema kot intelektualna lastnina, zaščita uporabniške programske opreme z vidika varovanja intelektualne lastnine, kriteriji za ocenjevanje kvalitete uporabniške programske opreme.

Komunikacija človek in računalniški sistem: načini interakcije, grafični uporabniški vmesnik uporabniške programske opreme, kontrolniki, lastnosti kvalitetnih uporabniških vmesnikov, kriteriji za ocenjevanje uporabniških vmesnikov uporabniške programske opreme.

Operacijski sistemi in uporabniška programska oprema:

Introduction: partition of software, user software as an intellectual property, protection of user software from safeguarding intellectual property point of view, criteria for assessing quality of user software.

Communication human and computer system: manners of

interactions, graphical user interfaces of user software, controls, properties of quality user interfaces, criteria for assessing user interfaces of user software.

Operating systems and user software: basic concepts, file

system and user software.

osnovni koncepti, datotečni sistem in uporabniška programska oprema.

Urejanje in obdelava besedil: koncepti, vizualno in logično urejanje, osnove tipografije, programski jezik postscript in pdf, oblikovanje besedil, zgradba strokovnih besedil in napotki za pisanje tehničnih besedil, latex.

Elektronske preglednice: osnovni pojmi, naslavljanje celic, enostavni izrazi, napredno delo.

Elektronske predstavitve: koncepti, govorne predstavitve, vrste gradiv, oblikovanje in izdelava elektronskih predstavitev.

Urejanje digitalnih slik: koncepti, lastnosti vektorske in rastrske grafike, delo z rastrsko grafiko, delo z vektorsko grafiko.

Matematična orodja: koncepti, lastnosti, programski orodji Matlab in Octave.

Uporabniška programska oprema za povečanje storilnosti: osebni organizatorji, programska oprema za tvorjenje zapiskov in zabeležk, programska oprema za publiciranje vsebine, programska oprema za oblikovanje obrazcev.

Uporabniška programska oprema za vzdrževanja računalniških sistemov: računalniški virusi in uporabniška programska oprema, stiskanje podatkov in uporabniška programska oprema, arhiviranje podatkov in uporabniška programska oprema.

Izmenjava in integracija podatkov med uporabniško programsko opremo: izmenjava podatkov, integracija podatkov.

Editing and word processing: concepts, visual and logic

editing, basis of typography, programming language Postscript and pdf, text formatting, structure of professional texts and directions for technical texts writing, Latex.

Spreadsheets: basic concepts, cell addressing, simple expressions, advanced work.

Electronic presentations: concepts, speaking presentations, types of materials, formatting and composition of electronic presentations.

Digital images editing: concepts, properties of vector and raster graphics, work with raster graphics, work with vector graphics.

Mathematical tools: concepts, properties, software tools Matlab and Octave.

User software for increasing productivity: personal organizers, software for notes creation, software for contents publishing, software for forms forming.

User software for computer systems maintenance:

computer viruses and user software, data compression and user software, data backuping and user software.

Data exchange and integration amongst user software:

data exchange, data integration.

Temeljni literatura in viri / Readings: M. Artač, B. Batagelj, M. Jogan, Ž. Kranjec, B. Kverh, K. Mele, P. Peer, M. Peternel, F. Solina: Uporabniška programska

oprema, Druga izdaja, Univerza v Ljubljani, Fakulteta za računalništvo in informatiko, Ljubljana, 2004. W. J. Palm III: Introduction to Matlab for Engineers, Third Edition, McGraw-Hill, New York, 2010. B. Long: Complete Digital Photography, Seventh Edition, CENGAGE Learning, Boston, 2013. H. Kopka, P. W. Daly: A Guide To LaTeX, Tools and techniques for computer typesetting, Fourth Edition, Addison Wesley

Professional, Reading, 2003. D. Cougias, E. L. Heiberger, K. Koop: The Backup Book: Disaster Recovery from Desktop to Data Center, Third Edition,

Schaser-Vartan Books, Lecanto, 2003. Cilji in kompetence:


Cilj predmeta je seznaniti študente z osnovnimi znanji in koncepti s področja uporabniške programske opreme.

The objective of this course is to acquaint students with basic knowledge and concepts from a user software field.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben izkazati znanje in razumevanje konceptov uporabniške

programske opreme, navesti lastnosti in na tej osnovi izbrati primerno

uporabniško programsko opremo za izbrano nalogo, učinkovito uporabljati uporabniško programsko opremo s

področja informacijskih tehnologij. Izpostaviti in izbrati primerno programsko opremo za

različne konkretne namene.

Knowledge and understanding: On completion of this course the student will be able to demonstrate knowledge and understanding of user

software concepts, list properties and on this basis select appropriate user

software tools for selected task, efficiently use user software from a field of information

technologies, expose and select the most appropriate software for

different concrete purposes

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: pisni zagovor laboratorijskih vaj,

Transferable/Key skills and other attributes: Communication skills: written lab work defence, manner of

pisno izražanje pri pisnem izpitu. Uporaba informacijske tehnologije: uporaba sodobne

uporabniške programske opreme, pisanje računalniških programov – makrov.

expression at written examination. Use of information technology: use of contemporary user

software, writing of computer programs – macros.







Assessment:

opravljene domače naloge, laboratorijske vaje, 1. vmesni pisni izpit, 2. vmesni pisni izpit.

15 % 35 % 25 % 25 %

completed homework, lab work, 1st midterm written exam, 2nd midterm written exam.

Opomba: V kolikor študent ni uspešno opravil obeh vmesnih izpitov, jih nadomesti s pisnim izpitom v deležu 50%. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references:

KORŽE, Danilo, VESEL, Aleksander. (d,n)-packing colorings of infinite lattices. Discrete applied mathematics, ISSN 0166-218X. [Print ed.], March 2018, vol. 237, str. 97-108, doi: 10.1016/j.dam.2017.11.036. [COBISS.SI-ID 21067542]

KORŽE, Danilo, VESEL, Aleksander. On the packing chromatic number of square and hexagonal lattice. V: Bled'11 - 7th Slovenian International Conference on Graph Theory, 19-25 June 2011, Bled, Slovenia. Ars mathematica contemporanea : special issue Bled'11, (Ars mathematica contemporanea, ISSN 1855-3966, Vol. 7, no. 1, 2014). Ljubljana: DMFA Slovenije, 2014, str. 13-22. http://amc-journal.eu/index.php/amc/article/view/255/224. [COBISS.SI-ID 16791897]

KORŽE, Danilo, VESEL, Aleksander. A note on the independence number of strong products of odd cycles. Ars combinatoria, ISSN 0381-7032, 2012, vol. 106, str. 473-481. [COBISS.SI-ID 16138006]

KORŽE, Danilo. Zbirka izpitnih nalog iz optimizacijskih problemov : e-učno gradivo. [Maribor]: Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko, 2012. 24 str. http://storm.uni-mb.si/eZbirke/KORZEZbirka_izpitnih_nalog_iz_operacijskih_problemov.pdf. [COBISS.SI-ID 16261142]

KORŽE, Danilo, SELINŠEK, Liljana. Digitalna forenzika in njena vloga pri sodnih postopkih = Digital forensis and its role in judicial processes : zaključno poročilo o rezultatih opravljenega raziskovalnega dela na projektu v okviru ciljnega raziskovalnega programa (CRP) "Konkurenčnost Slovenije 2006-2013". Maribor: Fakulteta za elektrotehniko, računalništvo in informatiko, 2008. 10 str. [COBISS.SI-ID 16260886]


Predmet: Elektronika

Course title: Electronics



Letnik Academic

year

Semester Semester





2. poletni Spring



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6

Nosilec predmeta / Lecturer: Iztok Kramberger

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Vezja in signali: osnovne vrste in oblike signalov, prenos signalov, viri signalov, osnovni elementi električnih vezij; upori, kondenzatorji, tuljave, dvovhodna predstavitev električnih vezij.

Polprevodniški elementi: polprevodniški materiali, svetlobna občutljivost polprevodnikov, dioda, bipolarni transistor, MOSFET-transistor, CCD-elementi, operacijski ojačevalniki, modeliranje.

Analogna elektronska vezja: vrste ojačevalnih vezij, frekvenčna odvisnost ojačenja, osnovne ojačevalne stopnje s tranzistorji in z operacijskimi ojačevalniki,

Circuits and signals: elementary types of electrical signals, signal sources and signal transmision, the elements of electrical circuits, two port presentation of electrical circuits.

Semiconductor devices: semiconductor materials, light

dependence, diodes, bipolar junction transistors, MOSFET transistors, CCD elements, operational amplifiers, modeling.

Analog electronic circuits: classification of amplification circuits, amplifiers and frequency response, basic amplification stages with transistors and operational

povratne vezave v ojačevalnih vezjih, generiranje in oblikovanje signalov.

Digitalna elektronska vezja: stikalne lastnosti transistorjev, elektronika logičnih vezij, sekvenčna vezja in sistemi, pomnilniška vezja.

Vezja za pretvorbo signalov: primerjalniki, vezja za vzorčenje in zadrževanje, digitalno analogni pretvorniki, analogno digitalni pretvorniki.

Integrirana vezja: načrtovanje in izdelava, standardna integrirana vezja, integrirana vezja po naročilu.

amplifiers, feedback in amplifier circuits, waveform generators and waveshaping.

Digital electronic circuits: switching properties of BJT and MOSFET transistors, logic circuits electronics, sequential circuits and systems, memory circuits.

Signal conversion circuits: comparators, sample and hold circuits, digital to analog converters, analog to digital converters.

Integrated circuits: design and realization, general integrated circuits, application specific integrated circuits.

Temeljni literatura in viri / Readings: B. Jarc, R. Babič: Elektronika: laboratorijske vaje za program računalništva in informatike, Univerza v Mariboru, Fakulteta za

elektrotehniko, računalništvo in informatiko, Maribor, 2000. R. Babič: Operacijski ojačevalnik. Vrste, lastnosti in osnovna vezja, Univerza v Mariboru, Fakulteta za elektrotehniko,

računalništvo in informatiko, Maribor, 2001. J. Furlan, Osnove polprevodniških elementov, Tehniška založba Slovenije, Ljubljana, 2002. R. C. Jaeger: Microelectronic Circuit Design, McGraw-Hill, New York, 2004. Cilji in kompetence:


Cilj predmeta je seznaniti študente z osnovnimi elektronskimi komponentami ter njihovimi lastnostmi. Vpelje jih v svet načrtovanja diskretnih in integriranih elektronskih vezij za ojačenje, generiranje, pretvorbo in obdelavo signalov.

The objective of this course is to acquaint students with the elementary electronic elements and their properties and enable them introducing into the world of designing discrete and integrated electronic circuits for amplification, generation, conversion, and processing of signals.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben izkazati znanje o osnovnih elektronskih komponentah,

razumeti njihovo delovanje in poznati uporabo, sestaviti in napraviti preprost ojačevalnik ali vmesnik pri

pretvorbi analognih in digitalnih signalov, sodelovati z elektroniki pri načrtovanju in izdelavi

elektronskih vezij in sistemov.

Knowledge and understanding: On completion of this course the student will be able to demonstrate knowledge of basic electronic components

and understand their functions and application, construct and make simple amplifier or interface for

conversion between analog and digital signals, cooperate with electronic engineers for electronic circuits

and systems design and realization. Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: ustno zagovarjanje

laboratorijskih vaj. Uporaba informacijske tehnologije: iskanje podatkov po

spletnih straneh. Reševanje problemov: izračun lastnosti pri preprostih

elektronskih vezij. Praktične veščine: izvajanje laboratorijskih vaj,

sestavljanje merilnih vezij, uporaba merilnih instrumentov.

Transferable/Key skills and other attributes: Communication skills: oral lab work defence. Use of information technology: finding technical data on

web. Problem solving: the analysis of the simple electronic

circuits. Practical skills: lab work performing, composing the

measurement circuits, using measurement instruments. Metode poučevanja in učenja:






Assessment:

opravljene domače naloge, laboratorijske vaje,

15 % 35 %

completed homework, lab work,

test 1, test 2.

25 % 25 %

test 1, test 2.

Opomba: Testa se lahko nadomestita s pisnim izpitom v deležu 50%. Note: The tests may be replaced with a written examination in the weight of 50%. Reference nosilca / Lecturer's references: KRAMBERGER, Iztok, GRAŠIČ, Matej, ROTOVNIK, Tomaž.Door phone embedded system for voice based user identification

and verification platform. IEEE trans. consum. electron.. [Print ed.], Aug. 2011, vol. 57, no. 3, str. 1212-1217, doi: 10.1109/TCE.2011.6018876. [COBISS.SI-ID 15462166]

KIRBIŠ, Matej, KRAMBERGER, Iztok.Mobile device for electronic eye gesture recognition. IEEE trans. consum. electron.. [Print ed.], 2009, vol. 55, no. 4, str. 2127-2133. [COBISS.SI-ID 13818646]

RULIĆ, Peter, KRAMBERGER, Iztok, KAČIČ, Zdravko.Progressive method for color selective edge detection. Opt. eng. (Bellingham. Print). [Tiskana izd.], Mar. 2007, vol. 46, iss. 3, str. 037004-1 - 037004-10. http://spiedl.aip.org/jhtml/doi.jsp. [COBISS.SI-ID 11574806]

RULIĆ, Peter, KRAMBERGER, Iztok, KAČIČ, Zdravko.Razčlenjevanje barvne slike, zajete s splošnonamenskimi barvnimi kamerami = Segmentation of color image captured with general-purpose color cameras. Elektrotehniški vestnik. [Slovenska tiskana izd.], 2006, vol. 73, no. 2-3, str. 117-124. [COBISS.SI-ID 10672406]

KRAMBERGER, Iztok.Real-time skin feature identification in a time-sequential video stream. Opt. eng. (Bellingham. Print). [Tiskana izd.], April 2005, vol. 44, no 4, str. 047201-1-047201-10. [COBISS.SI-ID 9671446]


Predmet: Interakcija človek-računalnik

Course title: Human-Computer Interaction



Letnik Academic

year

Semester Semester





3. poletni

Summer



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6


Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Ni pogojev. None.

Vsebina:


Uvod: zgodovinski pregled, definicija. Vrste interakcij pri grafičnem vmesniku: ukazna vrstica,

izbira menujev, izpolnjevanje formularjev, neposredna manipulacija.

Modeliranje človeškega doseganja in izbire elementov na zaslonu

Pomembne človeške lastnosti: zaznavanje, spomin, vizualna ostrina, hitrost branja, tipkanja, razumevanja audio posnetkov.

Obdelava informacij, mentalni modeli, vodenje gibov, učenje, kognitivna obremenitev, kinematična obremenitev.

Introduction: historical overview, definition. Graphic interface interaction styles: command line, menu

selection, form fill-in, direct manipulation. Predictive modelling of human pointing and selections of

items on the screen Important human characteristics: perception, memory,

visual acuity, reading. Important human characteristics: perception, memory,

visual acuity, speed of reading, typing, perception of audio recordings.

Information processing, mental models, movement control,

Osnovni elementi vizualne komunikacije. Značilnosti vizualnih spremenljivk in njihovo zaznavanje.

Tipografija: osnovni pojmi, vrste pisav, tekst, mreža. Izbira ustreznih barv: zaznavanje barv, barvni modeli,

konotacije barv, izbira barv za tekstualne grafične zaslone.

Principi snovanja uporabniških vmesnikov. Hevristično ocenjevanje uporabniškega vmesnika.

Testiranje uporabnosti. 3D in govorni uporabniški vmesniki: uporaba, tehnike

interakcije, načrtovanje in izvedba, prihodnost 3D in govornih uporabniških vmesnikov.

Haptična komunikacija, telerobotika, haptične naprave in haptične vmesnike.

Koncepti obogatene resničnosti, uporabljena strojna oprema in aplikacija.

Koncepti navidezne resničnosti, uporabljena strojna oprema in aplikacije. Jezik za modeliranje navidezne resničnosti.

Principi kolaborativne poglobljene analitike.

learning, cognitive load, kinematic load. Basic elements of visual communication. Characteristics of

visual variables and their perception. Typgraphy: basic elements, type families, text, grid.

Choice of proper colors: perception of colors, color models, color connotations, choosing colors for textual graphic screens.

Principles of designing user interfaces. Heuristic evaluation of user interface design. Usability

testing. 3D and voice user interfaces: what is a 3D and voice user

interface, applications, interaction techniques, design and implementation, future of 3D and voice user interfaces

Haptic communications, telerobotics, tactile devices and tactile interfaces.

Augmented reality concepts, hardware and applications. Virtual reality concepts, hardware and applications. Principles of collaborative immersive analytics (CIA).

Temeljni literatura in viri / Readings: J. Johnson: Designing with the Mind in Mind, Morgan Kaufmann Publishers, 2014. C. Ware: Visual Thinking for Design, Morgan Kaufmann Publishers, 2008. J. Rubin, D. Chisnell: Handbook of Usability Testing: How to Plan, Design, and Conduct Effective Tests, Wiley Publishing Inc.,

2008 D. Schmalstieg, T. Hollerer: Augmented Reality: Principles and Practice (Usability), Addison-Wesley Professional, 2016. J. Jerald: The VR Book: Human-Centered Design for Virtual Reality (Acm Books), Morgan & Claypool Publishers, 2015. J. Preece, H. Sharp, Y. Rogers: Interaction Design: Beyond Human-Computer Interaction, John Wiley, 2015. Cilji in kompetence:


Cilj predmeta je, da bodo študenti razumeli in znali uporabljat osnovne tehnologije iz področja interakcije človek-računalnik, ter bodo zmožni načrtovati in razviti napredne uporabniške vmesnike

The objective of this course is to for students to understand and be able to analyse of human-computer interaction technologies, as well to be able to design and implement advanced user interfaces



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben izkazati razumevanje karakteristik človekovih zaznav in

njihov pomen pri interakciji človek stroj, izkazati sposobnost ciljno-usmerjenega načrtovanja

uporabniškega vmesnika, prepoznati skupine uporabnikov in njihove karakteristike, analizirati rezultate testa uporabnosti, implementirat napredne uporabniške vmesnike, razumet in uporabit različne tehnologije obogatene in

navidezne resničnosti.

Knowledge and understanding: On completion of this course the student will be able to demonstrate knowledge of human senses and their role at

human-computer interaction, demonstrate the ability of goal-oriented design of user

interface, recognise groups of users and their characteristic, analyse results of usability test, to be able to implement advanced user interfaces, to understand and to be able to use various augmented and

virtual reality technologies.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: ustno izražanje pri ustnem


Transferable/Key skills and other attributes: Communication skills: oral examination, writing report about

lab work, oral examination of lab work. Use of information technology: the use of software tools for

Uporaba informacijske tehnologije: uporaba programskih orodij za hitro izdelavo uporabniških vmesnikov in testiranje uporabnosti interakcije človek-računalnik.

Reševanje problemov: ocenjevanje uporabnosti različnih uporabniških vmesnikov.

Delo v skupini: občasno delo v skupini pri laboratorijskih vajah.

rapid prototyping of user interfaces and for testing usability of the human-computer interaction.

Problem solving: evaluation of usability of different user interfaces,

Working in a group: periodic group work in the lab.







Assessment:

laboratorijske vaje, 1. vmesni pisni izpit, 2. vmesni pisni izpit,

50 % 25 % 25 %

lab work, 1st midterm written exam, 2nd midterm written exam,

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, jih nadomesti s pisnim izpitom v deležu 50%. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references: LUKAČ, Niko, ŽALIK, Borut. GPU-based roofs' solar potential estimation using LiDAR data. Computers & Geosciences, ISSN

0098-3004. [Print ed.], Mar. 2013, vol. 52, str. 23-41, doi: 10.1016/j.cageo.2012.10.010. LUKAČ, Niko, ŠPELIČ, Denis, ŽALIK, Borut. Hybrid visualization of sparse point-based data using GPGPU. V: CANDAR 2014

: proceedings, Second International Symposium on Computing and networking, 10-12 December 2014, Shizuoka, Japan. Los Alamitos (California)

LUKAČ, Niko, JESENKO, David, BIZJAK, Marko, ŽALIK, Borut. GPU-based DBSCAN clustering on locality sensitive hashing. V: Conference proceeding, 7th international conference of engineering and applied sciences (ICEAS 2017) at Toronto, ON, Canada, June 27-28, 2017.

LUKAČ, Niko, ŽALIK, Borut. GPU-based rectification of high-resolution remote sensing stereo images. V: HUANG, Bormin (ur.), LÓPEZ, Sebastián (ur.), WU, Zhensen (ur.). High-Performance Computing in Remote Sensing IV, September 22, 2014, Amsterdam, Netherlands, (Proceedings of SPIE, the International Society for Optical Engineering, ISSN 0277-786X, vol. 9247). [Bellingham: SPIE. 2014], str. 1-8.

LUKAČ, Niko, ŽALIK, Borut, RIZMAN ŽALIK, Krista. Sweep-hyperplane clustering algorithm using dynamic model. Informatica, ISSN 0868-4952, 2014, vol. 25, no 4, str. 564-580, doi: 10.15388/Informatica.2014.30.


Predmet: Linearna algebra

Course title: Linear algebra



Letnik Academic

year

Semester Semester





3. zimski Autum



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

45 45 90 6

Nosilec predmeta / Lecturer: Tatjana Petek

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Matrični račun: osnovne operacije, transponiranje, adjungiranje, algebra kvadratnih matrik, posebne matrike.

Sistemi linearnih enačb, Gaussova eliminacija, Gaussova metoda s skaliranjem in z delnim oziroma kompletnim pivotiranjem, iteracijske metode.

Determinanta, Cramerjevo pravilo. Vektorski prostor, linearna neodvisnost in baza,

geometrijski vektorji, skalarni in vektorski produkt, ravnine in premice v prostoru.

Linearne preslikave, predstavitev z matriko, ničelnost in rang, sprememba baze, ekvivalentnost in podobnost matrik.

Matrix calculus: basic operations, transposition, adjoint, algebra of square matrices, special matrices.

Systems of linear equations, Gaussian elimination, Gaussian method with scaling and partial or complete pivoting, iteration methods.

Determinant, Cramer's rule. Vector space, linear independence and basis, spacial

vectors, dot and cross product, planes and lines in the space.

Linear mappings, representation with a matrix, nullity and rank, change of basis, equivalence and similarity of matrices.

Lastne vrednosti in lastni vektorji matrik, diagonalizacija, triangularizacija, Jordanova kanonična forma.

Evklidski in unitarni prostor, skalarni produkt, ortormirana baza, Gram-Schmidtov postopek.

Spektralne lastnosti posebnih matrik, pozitivna (semi-) definitnost, kvadratne forme, unitarna diagonalizacija, razcep s singularnimi vrednostmi.

Eigenvalues and eigenvectors of matrices, diagonalization, triangularization, Jordan canonical form. Application in systems of linear differential equations.

Euclidean and unitary spaces, inner product, orthonormal basis, Gram-Schmidt algorithm.

Spectral properties of special matrices, positive (semi-) definitness, quadratic forms, unitary diagonalization, singular value decomposition.

Temeljna literatura in viri / Readings: T. Petek: Izbrana poglavja iz tehniške matematike, Univerza v Mariboru, FERI, Maribor, 2014. B. Orel, Linearna algebra [Elektronski vir] - 1. izd., Založba FE in FRI Ljubljana, 2012. M. Kolar, B. Zgrablić: Več kot nobena, a manj kot tisoč in ena rešena naloga iz linearne algebre, Univerza v Ljubljani,

Pedagoška fakulteta, Ljubljana, 1996. G. Strang: Linear algebra and its applications, Brooks/Cole, Belmont, 2006. S. Lipschutz: Schaum's outline of theory and problems of linear algebra, McGraw-Hill, New York [etc.], 1968. Cilji in kompetence:


Cilj predmeta je seznaniti študente z osnovnimi linearnimi strukturami in standardnimi linearnimi metodami.

The objective of this course is to acquaint students with basic linear algebra structures and standard linear methods.



UZnanje in razumevanje: Po zaključku tega predmeta bo študent sposoben prepoznavati linearne strukture v različnih okoljih, razložiti temeljne pojme linearne algebre, uporabljati standardne metode linearne algebre.

UKnowledge and understanding: On completion of this course the student will be able to recognize linear structures in different settings, apply standard methods of linear algebra.

UPrenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: nedvoumno in natančno

izražanje. Uporaba informacijsko komunikacijske tehnologije:

uporaba programov za simbolično in numerično računanje.

Spretnosti računanja: učenje raznovrstnih računskih postopkov.

Reševanje problemov: prepoznavanje in reševanje matematičnih problemov.

UTransferable/Key skills and other attributes: Communication skills: unambiguous and accurate

expression. Use of information communication technology: using

programs for symbolic and numerical computing. Calculation skills: learning diverse calculation procedures. Problem solving: identifying and solving mathematical

problems.



predavanja, seminarske vaje.

lectures, tutorial.



Assessment:

testi iz praktičnih znanj izpit iz teoretičnih znanj

50 % 50 %


Opomba: Testi se lahko nadomestijo s pisnim izpitom. Note: The tests may be replaced with a written exam. Reference nosilca / Lecturer's references: HAN, Maoan, PETEK, Tatjana, ROMANOVSKI, Valery. Reversibility in polynomial systems of ODE's. Applied mathematics

and computation, ISSN 0096-3003. [Print ed.], 2018, vol. 338, str. 55-71. [COBISS.SI-ID 21654550]

KUZMA, Bojan, PETEK, Tatjana. Maps preserving unitarily invariant norms of Jordan product of matrices. Journal of mathematical analysis and applications, ISSN 0022-247X. [Print ed.], 2017, vol. 455, iss. 2, str. 1579-1596. http://dx.doi.org/10.1016/j.jmaa.2017.06.043, doi: 10.1016/j.jmaa.2017.06.043. [COBISS.SI-ID 18085721]

KARDER, Mahdi, PETEK, Tatjana. Maps on states preserving generalized entropy of convex combinations. Linear Algebra and its Applications, ISSN 0024-3795. [Print ed.], 1 Nov. 2017, vol. 523, str. 86-98, doi: 10.1016/j.laa.2017.06.003. [COBISS.SI-ID 20705046]

PETEK, Tatjana, RADIĆ, Gordana. Linear preservers of equivalence relations on infinite-dimensional spaces. Studia Mathematica, ISSN 0039-3223, 2017, vol. 238, no. 2, str. 101-119, doi: 10.4064/sm8356-12-2016. [COBISS.SI-ID 20705302]

KARDER, Mahdi, PETEK, Tatjana, TAGHAVI, Ali. Unitary similarity preserving linear maps on B(H). Integral equations and operator theory, ISSN 0378-620X, 2015, vol. 82, iss. 1, str. 51-60. http://dx.doi.org/10.1007/s00020-014-2189-y. [COBISS.SI-ID 17319001]


Predmet: Mrežno usmerjeno računanje

Course title: Network centric computing



Letnik Academic

year

Semester Semester





2. zimski

Autumn



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6

Nosilec predmeta / Lecturer: Borko Bošković

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Uvod: zgodovina, osnovni koncepti prenosa podatkov, lastnosti porazdeljenih računalniških sistemov, ISO/OSI in TCP/IP model.

Zgradba komunikacijskih omrežij: lokalno komunikacijsko omrežje (LAN), javno komunikacijsko omrežje (WAN), brezžične tehnologije za prenos informacij.

Fizični nivo. Podatkovni nivo: odpravljanje in popravljanje napak,

osnovni protokoli, protokoli, ki omogočajo sodostop( multiple access protokoli) ethernet, brezžična omrežja

Introduction: basic concepts of data transmission, characteristics of distributed systems, ISO/OSI and TCP/IP model.

Structure of computer networks: local-area networks, wide-area networks, wireless technologies.

The physical layer. The data link layer: error detection and correction,

elementary data link protocols, multiple access protocols, Ethernet, wireless LANs (IEEE 802.11), broadband

(IEEE 802.11), brezžična lokalna omrežja, brezžična globalna omrežja, bluetooth omrežja, preklaplanje na podatkovnem nivoju.

Mrežni nivo: algoritmi preusmerjanja, algoritmi nadzora nad zasičenjem, zagotavljanje kvalitete storitve, prenos podatkov po medmrežju.

Transportni nivo: osnovne funkcije transportne storitve, UDP, TCP.

Brezžična in mobilna omrežja: CDMA, WiFi 802.11, mobilni IP.

Omrežna varnost: šifriranje, avtentikacija, digitalni podpis, digitalno potrdilo, SSL protokol, detektorji vdora, požarni zidovi.

Aplikacijski nivo: sinhroni in asinhroni način komunikacije, model gospodar-suženj, model odjemalec- strežnik, model vsak z vsakim, modeli ki podpirajo skupinsko komunikacijo, multimedijski tokovni model, objektni model, sporočilno usmerjena komunikacija, tokovno usmerjena komunikacija, RPC, imenske storitve, izmenjevalne storitve, zaganjalne storitve, porazdeljene datotečne storitve, časovna sinhronizacija, koordinacija porazdeljenih aktivnosti, HTTP protocol, potrditveni sistemi, P2P sistemi, tehnologije grid, VOIP, RTP, SIP elektronska in glasovna pošta, internetni radio, video na zahtevo, MPI, procesiranje v oblaku, »map-reduce« računski model.

wireless networks, Bluetooth, data link layer switching. The network layer: routing algorithms, congestion control

algorithms, quality of service, internetworking. The transport layer: elements of transport protocol, UDP,

TCP. Wireless and mobile networks: CDMA, WiFi 802.11, mobile

IP. Network security: cryptography, authentication protocols,

digital signatures, certificates, SSL protocol, intrusion detection, firewall.

The application layer: synchronous and asynchronous communication, master slave, client-server, peer to peer, group communication, multimedia stream model, object model, message-oriented communication, stream-oriented communication, RPC, name services, distributed file services, clock synchronization, mutual exclusion, consistency and replication, trading services, factory services, HTTP protocol, notification services, P2P systems, grid technology, electronic and voice mail, VOIP, RTP, SIP, internet radio, video on demand, MPI, cloud computing, map-reduce computational model.

Temeljni literatura in viri / Readings: M. Ojsteršek: Učno gradivo in primeri dosegljivi na E-študij UM: https://estudij.um.si/– potrebna je prijava v portal. J. F. Kurose, K. W. Ross: Computer Networking: A Top-Down Approach (7th Edition), Pearson education; New Yersey, 2016. A. S. Tanenbaum: Computer Networks, Fifth Edition; Prentice Hall PTR; New Jersey, 2010. G. Coulouris, J. Dollimore, T. Kindberg: Distributed Systems : Concepts and Design, 5th Edition, Addison Wesley; Harlow,

2010 Cilji in kompetence:


Cilj tega predmeta je naučiti študente razumevanja delovanja in zgradbe računalniških omrežij (arhitektura, protokoli, nivoji računalniškega omrežja, načrtovanje in upravljanje računalniških omrežij). Študentje se naučijo pisati preproste komunikacijske programe za različne nivoje računalniškega omrežja.

The objective of this course is to teach students understanding of functions and structure of computer networks (architecture, protocols, computer network layers, design and management of computer networks). Students will be able to write simple communication programs on all layers of computer networks.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben: izkazati razumevanje delovanja računalniških omrežij

(arhitektura, protokoli, nivoji računalniškega omrežja), poiskati na internetu in v strokovni literaturi podrobnejše

informacije o delovanju posameznih komponent in protokolov računalniških omrežij,

izbrati in uporabiti ustrezne komponente za postavitev lokalnih in javnih komunikacijskih omrežij,

načrtovati in upravljati računalniška omrežja, pisati preprostejše komunikacijske programe za različne

nivoje računalniškega omrežja.

Knowledge and understanding: On completion of this course the student will be able to demonstrate understanding of function and structure of

computer networks (architecture, protocols, layers), find appropriate information about operation of computer

network components on the internet and on professional literature,

select and use of appropriate components for LANs or WANs,

design and management of computer networks, write a simple communication programs for all layers of

computer networks.



Uporaba informacijske tehnologije: uporaba programskih orodij za načrtovanje, analiziranje in upravljanje računalniških omrežij.

Reševanje problemov: načrtovanje in implementacija enostavnih komunikacijskih programov.



network design, analysis and management of computer networks implementation, debugging and testing of simple Web applications.

Problem solving: design and implementation of a simple communication programs.




lectures, lab work.



Assessment:


50 % 25 % 25 %

computer lab work*, 1st midterm written exam, 2nd midterm written exam.

*Obvezno / Mandatory Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, jih nadomesti s pisnim izpitom v deležu 50%. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references: BOŠKOVIĆ, Borko, BREST, Janez. Protein folding optimization using differential evolution extended with local search and

component reinitialization. Information sciences, ISSN 0020-0255. [Print ed.], July 2018, vol. 454/455, str. 178-199, doi: 10.1016/j.ins.2018.04.072. [COBISS.SI-ID 21401878]

BOŠKOVIĆ, Borko, BRGLEZ, Franc, BREST, Janez. Low-autocorrelation binary sequences : on improved merit factors and runtime predictions to achieve them. Applied soft computing, ISSN 1568-4946. [Print ed.], July 2017, vol. 55, str. 262-285, doi: 10.1016/j.asoc.2017.02.024. [COBISS.SI-ID 20553750]

BOŠKOVIĆ, Borko, BREST, Janez. Genetic algorithm with advanced mechanisms applied to the protein structure prediction in a hydrophobic-polar model and cubic lattice. Applied soft computing, ISSN 1568-4946. [Print ed.], 2016, vol. 45, str. 61-70, doi: 10.1016/j.asoc.2016.04.001.

BREST, Janez, BOŠKOVIĆ, Borko. A heuristic algorithm for a low autocorrelation binary sequence problem with odd length and high merit factor. IEEE access, ISSN 2169-3536, 2018, vol. 6, str. 4127-4134, doi: 10.1109/ACCESS.2018.2789916. [COBISS.SI-ID 21347606]

SEPESY MAUČEC, Mirjam, BREST, Janez, BOŠKOVIĆ, Borko, KAČIČ, Zdravko. Improved differential evolution for large-scale black-box optimization. IEEE access, ISSN 2169-3536, Dec. 2018, iss. 1, vol. 6, str. 29516-29531, doi: 10.1109/ACCESS.2018.2842114. [COBISS.SI-ID 2146562


Predmet: Operacijski sistemi

Course title: Operating systems



Letnik Academic

year

Semester Semester





2. zimski

Autumn



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6

Nosilec predmeta / Lecturer: Božidar Potočnik

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Uvod: vloga operacijskega sistema (OS) ter njegove temeljne funkcije, zgradba računalniških sistemov in OS, delo s prekinitvami in z vhodni-izhodnimi napravami.

Upravljanje s posli in procesi: posel in njegovo izvrševanje, zgradba in stanja procesa, procesov nadzorni blok, niti, komunikacija med procesi.

Razvrščanje procesov: kriteriji za razvrščanje, razvrščevalni algoritmi (kdor prej pride, prej melje, najkrajši posli najprej, prioriteta, krožna prioriteta, več aktivnih vrst).

Upravljanje s posli: dvonivojsko in trinivojsko razvrščanje

Introduction: role of operating systems (OS) and their basic functionality, computer systems and OS architectures, interrupt handling and access to input/output devices.

Job and process management: jobs and their scheduling, process structure and states, process control block, threads, process communication.

Process scheduling: scheduling criteria, scheduling algorithms (first-come first-served, shortest-job-first, priority, round-robin, several active queues.

Job management: two- and three-level scheduling, process

poslov, izločanje procesov. Sinhronizacija med procesi: kritični odsek, Petersonova

rešitev za sinhronizacijo med dvema procesoma, pekarniški algoritem, strojni pripomočki za sinhronizacijo, semafor, monitor, problem popolnega zastoja in pomanjkanja.

Klasični problemi sinhronizacije: proizvajalec in potrošnik, pisci in bralci, filozofi pri kosilu, speči brivec.

Upravljanje s pomnilnikom: particije, ostranjevanje, izvedbe tabel strani, asociativni pomnilnik, segmentiranje, segmentiranje z ostranjevanjem.

Virtualni pomnilnik: postopki nalaganja in zamenjave strani, napaka strani, algoritmi za zamenjavo strani (kdor prej pride, prej melje, optimalni, najdlje neuporabljeni, števni.

Upravljanje z zbirčnim sistemom: kazala in njihova izvedba (večnivojska, drevesna, aciklični grafi), funkcije OS pri delu z zbirkami in kazali, sloji zbirčnega sistema.

Izvedbe zbirčnega sistema: fizični zapisi zbirk v obliki sklenjenega zapisa, kazalčnega seznama in indeksne namestitve, NTFS.

Razvrščanje zahtev za disk: algoritmi (kdor prej pride, prej melje, prebirni, ciklični prebirni, multimedijski), upravljanje s prostim diskovnim prostorom in z odlagalnim prostorom.

suspension. Process synchronisation: critical section, Peterson’s

solution for synchronisation of two processes, bakery algorithm, hardware for synchronisation, semaphore, monitor, the problem of deadlock and starvation.

Classical problems of synchronisation: producer-consumer, readers and writers, dining philosophers, sleeping barber.

Memory management: partitions, paging, page table design, associative registers, segmentation, segmentation with paging.

Virtual memory: loading and replacement algorithms, page fault, page replacement algorithms (first-come first-served, optimal, least-recently-used, counting.

File system management: directories and their implementation (multilevel, tree, acyclic graphs), functions of OS to handle files and directories, levels of file system.

Implementation of file systems: physical allocation of files as contiguous, list of pointers and indexing, NTFS.

Disk scheduling: algorithms (first-come first-served, scan, cyclic scan, multimedia), disk free-space and swap-space management.

Temeljni literatura in viri / Readings: D. Zazula: Operacijski sistemi, Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko, Maribor, 2008. A. Silberschatz, P. B. Galvin, G. Gagne: Operating System Concepts, Tenth Edition, Wiley, Hoboken, 2018. W. Stallings: Operating systems, Ninth Edition, Pearson Education Limited, Essex, 2018. A. S. Tanenbaum, H. Bos: Modern Operating Systems, Prentice Hall, Boston, 2014.



Cilj tega predmeta je, da bodo študentje razumeli temeljna znanja o zasnovi in delovanju operacijskih sistemov in operacijske sisteme uporabiti v praksi.

The objective of this course is for students to be able to understand the basic knowledge of operating systems design and operation and to use operating systems in practice.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben razumeti glavne principe načrtovanja in delovanja

operacijskih sistemov, analizirati in pouporabiti algoritme za razvrščanje in

sinhronizacijo procesov ter za upravljanje s pomnilnikom in z zbirčnimi sistemi,

optimalno namestiti operacijski sistem in uporabljati njegove funkcije.

Knowledge and understanding: On completion of this course the student will be able to understand the basic principles of the operating systems

design and operation, analyse and re-implement the algorithms for process

scheduling and synchronisation, and for memory and file-system management,

install and set-up the operating system and use its functions.


pisni izpit. Uporaba informacijske tehnologije: delo z različnimi

operacijskimi sistemi, pisanje krajših sistemskih programov.

Delo v skupini: skupinsko delo pri določenih laboratorijskih vajah.

Reševanje problemov: sodelovanje z industrijskimi

Transferable/Key skills and other attributes: Communication skills: oral lab work defence, written

examination. Use of information technology: use of different operating

systems, implementation of plain system programs.

Team work: team execution of some lab work.

Problem solving: co-operation with industrial partners.

partnerji. Metode poučevanja in učenja:

Teaching and learning methods:





Assessment:


50 25 25


Opomba: Če študent ni uspešno opravil obeh vmesnih pisnih izpitov, ju nadomesti s pisnim izpitom v deležu 50 %. Note: If a student has not completed both midterm written exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references: POTOČNIK, Božidar. Automated landmark points detection by using a mixture of approaches: the vole-teeth case. Signal,

image and video processing, Published online 21 December 2012, str. 1-14. http://link.springer.com/article/10.1007/s11760-012-0414-1# . [COBISS.SI-ID 16578070].

POTOČNIK, Božidar, CIGALE, Boris, ZAZULA, Damjan. Computerized detection and recognition of follicles in ovarian ultrasound images: a review. Medical & biological engineering & computing, 2012, vol. 50, iss. 12, str. 1201-1212. [COBISS.SI-ID 16344854].

MLAKAR, Uroš, POTOČNIK, Božidar, BREST, Janez. A hybrid differential evolution for optimal multilevel image thresholding. Expert systems with applications, ISSN 0957-4174. [Print ed.], Dec. 2016, vol. 65, str. 221-232, doi: 10.1016/j.eswa.2016.08.046. [COBISS.SI-ID 19733526].

POTOČNIK, Božidar, HOLOBAR, Aleš. A new optical flow model for motor unit conduction velocity estimation in multichannel surface EMG. Computers in Biology and Medicine, ISSN 0010-4825. [Print ed.], April 2017, vol. 83, str. 59-68, ilustr., doi: 10.1016/j.compbiomed.2017.02.006. [COBISS.SI-ID 20327446].

MLAKAR, Uroš, FISTER, Iztok, BREST, Janez, POTOČNIK, Božidar. Multi-objective differential evolution for feature selection in facial expression recognition systems. Expert systems with applications, ISSN 0957-4174. [Print ed.], 15 Dec. 2017, vol. 89, str. 129-137, doi: 10.1016/j.eswa.2017.07.037. [COBISS.SI-ID 20731926].


Predmet: Prevajanje programski jezikov

Course title: Compiling Programming Languages



Letnik Academic

year

Semester Semester





2. poletni Spring



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6

Nosilec predmeta / Lecturer: Marjan Mernik

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Ni pogojev. None.

Vsebina:


Uvod v prevajalnike: prevajanje in interpretiranje programov, osnovna zgradba prevajalnikov.

Leksikalna analiza: regularni izrazi, deterministični končni avtomat, nedeterministični končni avtomat, lastnosti regularnih jezikov, implementacija leksikalnega analizatorja.

Sintaktična analiza: razredi gramatik, drevo izpeljave, normalna oblika po Chomskem, normalna oblika po Greibachovi, BNF in sintaktični diagrami, razpoznavanje od zgoraj navzdol, razpoznavanje od spodaj navzgor,

Introduction to compilers: program compiling and interpreting, basic compiler structure.

Lexical analysis: regular expressions, deterministic finite state automata, non-deterministic finite state automata, properties of regular languages, implementation of lexical analysers.

Syntax analysis: grammar classes, derivation tree, Chomsky normal form, Greibach normal form, BNF and syntactic diagrams, top-down parsing, bottom-up parsing, pushdown automata and context-free languages, properties

skladovni avtomati in kontekstno neodvisni jeziki, lastnosti kontekstno neodvisnih jezikov, razpoznavalnik z vračanjem, razpoznavalnik LL(k), razpoznavalnik LR(k).

Semantična analiza: sintaktično usmerjeno prevajanje, atributne gramatike vrste S in L, absolutno neciklične atributne gramatike.

Generiranje in optimizacija kode. Denotacijska in operacijska semantika.

Generatorji prevajalnikov. Praktična uporaba v programskem inženirstvu:

razpoznavanje XML, uporaba regularnih izrazov, sistemi, temelječi na gramatikah.

of context-free languages, backtracking parser, LL(k) parser, LL(R) parser.

Semantic analysis: syntax-directed translation, S-attribute grammars, L-attribute grammars, absolute non-cyclic attribute grammars.

Generation and code optimization. Denotational and operational semantics.

Compiler generators. Practical usage in software engineering: XML parsing,

usage of regular expressions, grammar-based systems.

Temeljni literatura in viri / Readings: A. V. Aho, M. S. Lam, R. Sethi, J. D. Ullman: Compilers – Principles, Techniques, and Tools, Second Edition, Addison-Wesley,

Reading, 2006. A. V. Aho, R. Motwani, J. D. Ullman: Introduction to Automata Theory, Languages, and Computation, Third Edition, Addison-

Wesley, Reading, 2006. A. W. Appel: Modern Compiler Implementation in Java, Cambridge University Press, Cambridge, 1997. B. Vilfan: Prevajanje programskih jezikov, I. del, Univerza v Ljubljani, Fakulteta za elektrotehniko in računalništvo, Ljubljana,

1991. Cilji in kompetence:


Cilj tega predmeta je razumeti osnovne pojme iz teorije avtomatov in jezikov in njihovo praktično uporabo pri prevajanju programskih jezikov.

The objective of this course is to understand basics of automata and language theory and their usage in compiling of programming languages.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben razumeti osnovne pojme iz teorije avtomatov in jezikov, razumeti tehnike, ki se uporabljajo pri prevajanju/

interpretaciji programov, načrtovati in implementirati prevajalnik/intepreter, uporabljati generatorje prevajalnikov, uporabiti pridobljeno znanje na praktičnih primerih s

področja programskega inženirstva.

Knowledge and understanding: On completion of this course the student will be able to understand basics of automata and language theory, understand techniques using in compiling/interpreting

programs, design and implement compiler/interpreter, use compiler generators, apply acquired knowledge in practical examples in the field

of software engineering. Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: ustni zagovor laboratorijskih vaj,

pisno izražanje pri pisnem izpitu. Uporaba informacijske tehnologije: uporaba generatorjev

prevajalnikov. Reševanje problemov: implementacija prevajalnika/

interpreterja.


expression at written examination. Use of information technology: use of different compiler

generators. Problem solving: implementation of compiler/interpreter.



Predavanja, laboratorijske vaje.

Lectures, lab work.



Assessment:

Sprotni način laboratorijske vaje,

Delež 50

Constant assessment methods lab work,

1. vmesni izpit,

2. vmesni izpit. 25

25

1st midterm examination,

2nd midterm examination.

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 50 %. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50 %. Reference nosilca / Lecturer's references:

KOSAR, Tomaž, MERNIK, Marjan, GRAY, Jeffrey G., KOS, Tomaž. Debugging measurement systems using a domain-specific modeling language. Computers in industry, ISSN 0166-3615. [Print ed.], 2014, vol. 65, iss. 4, str. 622-635.

MERNIK, Marjan. An object-oriented approach to language compositions for software language engineering. The Journal of Systems and Software, ISSN 0164-1212. [Print ed.], 2013, vol. 86, iss. 9, str. 2451-2464.

KOS, Tomaž, KOSAR, Tomaž, MERNIK, Marjan. Development of data acquisition systems by using a domain-specific modeling language. Computers in industry, ISSN 0166-3615. [Print ed.], Apr. 2012, vol. 63, no. 3, str. 181-192.

KOSAR, Tomaž, MERNIK, Marjan, CARVER, Jeffrey C. Program comprehension of domain-specific and general-purpose languages : comparison using a family of experiments. Empirical software engineering, ISSN 1382-3256, 2012, vol. 17, no. 3, str. 276-304.

ARORA, Ritu, BANGALORE, Purushotham, MERNIK, Marjan. Raising the level of abstraction for developing message passing applications. The journal of supercomputing, ISSN 0920-8542, 2012, vol. 59, no. 2, str. 1079-1100.

UČNI NAČRT PREDMETA / SUBJECT SPECIFICATION Predmet: Principi programskih jezikov Subject Title: Principles of Programming Languages

Študijski program Study programme

Študijska smer Study option

Letnik Year

Semester Semester





2. poletni Spring

Univerzitetna koda predmeta / University subject code:

Predavanja Lectures

Seminar Seminar

Seminarske vaje Tutorial

Laborat. vaje Lab work

Terenske vaje Field work

Samostojno delo Individual work ECTS

30 3 42 105 6 Nosilec predmeta / Lecturer: Marjan Mernik Jeziki / Languages:

Predavanja / Lecture: slovenski / Slovene Vaje / Tutorial: slovenski / Slovene


Prerequisites:

Ni pogojev. None. Vsebina:


Uvod v programske jezike: neformalna definicija programskih jezikov, delitve programskih jezikov, kratka zgodovina programskih jezikov.

Vrednosti in tipi: delitev tipov, statično in dinamično preverjanje tipov, ekvivalenca tipov, vrste izrazov.

Pomnilnik: spremenljivka, shranljive vrednosti, življenjska doba spremenljivk, vrste ukazov, izrazi s stranskimi učinki.

Povezovanje: povezljive vrednosti, statični in dinamični doseg, vrste deklaracij, bločni ukazi in bločni izrazi, kvalifikacijski princip.

Abstrakcije: princip abstrakcije, vrste abstrakcij, mehanizmi prenosa parametrov, korespondenčni princip, dosledni in normalni izračun.

Ograjevanje: paketi, abstraktni tipi, objekti in razredi, generični moduli.

Sistemi tipov: monomorfni in polimorfni sistem tipov, vrste polimorfizma. Generiki v programskem jeziku java.

Objektno usmerjeno programiranje: objekt, razred, meta-razred. Razredni objektno usmerjeni jeziki in prototipni objektno usmerjeni jeziki. Vrste dedovanja: enkratno/večkratno, razredno/objektno, striktno/nestriktno, urejeno/neurejeno, dinamično/selektivno, običajno/mixin. Vgnezdeni razredi v programskem jeziku java.

Funkcijsko programiranje: značilnosti funkcijskih jezikov, uvod v programski jezik lisp/haskell.

Introduction to programming languages: informal definition of programming languages, classification of programming languages, brief history of programming languages.

Values and types: type classification, static and dynamic type checking, type equivalence, kind of expressions.

Storage: variable, storable values, variable lifetime, kind of commands, expressions with side effects.

Binding: bindable values, static and dynamic scope, kind of declarations, block commands and block expressions, the qualification principle.

Abstractions: abstraction principle, kind of abstractions, parameter passing mechanisms, the correspondence principle, eager and normal evaluation.

Encapsulation: packages, abstract types, objects and classes, generic modules.

Type systems: monomorphic and polymorphic type systems, kind of polymorphisms. Java generics.

Object-Oriented programming: object, class, meta-class. Class-based object-oriented languages and prototype-based object-oriented languages. Kinds of inheritance: single/multiple, class-based/object-based, strict/non-strict, ordered/un-ordered, dynamic/selective, ordinary/mixin. Nested Java classes.

Functional programming: characteristics of functional languages, introduction to Lisp/Haskell programming language.

Temeljni študijski viri / Textbooks: K.C. Louden: Programming Languages: Principles & Practices, Third Edition, Cenage Learning, 2013. P. Sestoft: Programming Language Concepts, Springer, Berlin, 2012. D. A. Watt: Programming Language Design Concepts, John Wiley, Chichester, 2004.

Cilji:

Objectives:

Cilj tega predmeta je razumevanje osnovnih konceptov programskih jezikov in razumeti bistvene razlike med funkcijskim, proceduralnim in objektno usmerjenim programiranjem.

The objective of this course is to understand the basic concepts of programming languages and to understand essential differences between functional, procedural and object-oriented programming.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben identificirati slabosti in prednosti posameznega

programskega vzorca, izbrati primeren programski jezik za rešitev dane naloge, razumeti koncepte programskih jezikov, s pomočjo katerih

se bo hitreje naučil novega programskega jezika, razumeti razlike med statičnim in dinamičnim tipiziranjem, razumeti različne oblike dodeljevanja pomnilnika, razumeti različne tehnike prenosa parametrov, razumeti različne oblike polimorfizma.

Knowledge and understanding: On completion of this course the student will be able to identify shortcomings and advantages of particular

programming language, select suitable programming language to solve particular

problem, understand concepts of programming languages with the

aim to quicker learn new programming language, understand differences between static and dynamic typing, understand different ways of memory allocation, understand different parameter passing techniques, understand different forms of polymorphisms.


pisno izražanje pri pisnem izpitu. Uporaba informacijske tehnologije: uporaba različnih

prevajalnikov in interpreterjev. Reševanje problemov: načrtovanje in implementacija

programov z uporabo različnih programskih vzorcev.


expression at written examination. Use of information technology: use of different compilers

and interpreters. Problem solving: program design and implementation using

different programming paradigms. Metode poučevanja in učenja:



lectures, lab work.



Assessment methods:

Sprotni način laboratorijske vaje, 1. vmesni izpit, 2. vmesni izpit.

Delež 50

25

25

Constant assessment methods lab work, 1st midterm examination, 2nd midterm examination.

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 50 %. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50 %. Reference nosilca / Lecturer's references: 1. KOSAR, Tomaž, MERNIK, Marjan, GRAY, Jeffrey G., KOS, Tomaž. Debugging measurement systems using a domain-specific

modeling language. Computers in industry, ISSN 0166-3615. [Print ed.], 2014, vol. 65, iss. 4, str. 622-635. 2. MERNIK, Marjan. An object-oriented approach to language compositions for software language engineering. The Journal of

Systems and Software, ISSN 0164-1212. [Print ed.], 2013, vol. 86, iss. 9, str. 2451-2464. 3. KOS, Tomaž, KOSAR, Tomaž, MERNIK, Marjan. Development of data acquisition systems by using a domain-specific

modeling language. Computers in industry, ISSN 0166-3615. [Print ed.], Apr. 2012, vol. 63, no. 3, str. 181-192.

4. KOSAR, Tomaž, MERNIK, Marjan, CARVER, Jeffrey C. Program comprehension of domain-specific and general-purpose languages : comparison using a family of experiments. Empirical software engineering, ISSN 1382-3256, 2012, vol. 17, no. 3, str. 276-304.

5. ARORA, Ritu, BANGALORE, Purushotham, MERNIK, Marjan. Raising the level of abstraction for developing message passing applications. The journal of supercomputing, ISSN 0920-8542, 2012, vol. 59, no. 2, str. 1079-1100.

W: feri.um.si | E: [email protected] | T: 02 220 7000 | F: 02 220 7272 | TRR: 01100 6090106039 | ID: SI71674705

UČNI NAČRT PREDMETA / SUBJECT SPECIFICATION Predmet: Projektni praktikum Subject Title: Practicum Project



Letnik Year

Semester Semester

Računalništvo in informacijske tehnologije

1. stopnja UN




2 poletni Spring


Predavanja Lectures

Seminar Seminar

Seminarske vaje

Tutorial


Terenske vaje

Field work

Samostojno delo

Individual work ECTS

5 175 6 Nosilec predmeta / Lecturer: Jeziki / Languages:



Prerequisites:

Študent se prijavi na razpisane projekte ob vpisu v 2. letnik ob upoštevanju pravil za vpis in izvedbo projektov.

A student enrolls in the selected projects at the time of enrollment in the 2nd year, taking into account the rules for enrollment and implementation of projects.

Vsebina:


Projekt vsebinsko povezuje pridobljena temeljna, strokovna in praktična znanja študijskega programa. Študentu omogoča integracijo znanj s ciljem pridobivanja praktičnih izkušenj.

The project connects the acquired basic, professional and practical knowledge of the study program. It enables the student to integrate knowledge with the goal of gaining practical experience.

Temeljni študijski viri / Textbooks: Literatura vezana na projekt, ki si določi vsako leto posebej. / Literature related to the project, which is determined each year separately.

Cilji:

Objectives:

Cilj tega predmeta je usposobiti študenta za industrijsko okolje pri reševanju večjega problema, ki ga projektna skupina rešuje tudi v okviru projektnih predmetov tega semestra.

The aim of this course is to train a student for the industrial environment in solving a major problem, which the project team also solves in the framework of the project subjects of this semester.

2 / 2

Predvideni študijski rezultati: Intended learning outcomes: Znanje in razumevanje: Po zaključku tega predmeta bo študent obvladal naslednja znanja: Pridobil zahtevane kompetence, ki mu bodo

omogočale reševanje inženirskih problemov. Obvladal znanje širšega strokovnega področja v

katerega sodi projekt in ožje znanje vezano na projekt. Analiziral problem, načrtoval, izdelal in testiral

aplikacijo.

Knowledge and understanding: On completion of this course the student will gain knowledge on the following topics: Gain the required competencies to solve engineering

problems. Student mastered the knowledge of a wider field of

expertise in which the project belongs and narrow knowledge related to the project.

Student analyzed the problem, designed, constructed, and tested the application.

Prenosljive/ključne spretnosti in drugi atributi: Študenti se naučijo dela v skupini.

Transferable/Key skills and other attributes: Students learn to work in a group.



seminar skupinsko delo samostojno delo

seminar team work individual work



Assessment methods:

izvedba projekta

100

project implementation

Reference nosilca / Lecturer's references:


Predmet: Računalniške arhitekture

Course title: Computer Architecture



Letnik Academic

year

Semester Semester





2. zimski

Autumn



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6


Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Ni pogojev. None.

Vsebina:


Uvod: zgodovinski pregled računalniških arhitektur, strojne komponente, zmogljivost, predstavitev podatkov.

Instrukcijska množica: karakteristike, načini naslavljanj, instrukcijski formati, semantični prepad, zbirni jezik.

Arhitektura 80x86: zgodovinski pregled, zgradba, načini delovanja, instrukcijska množica CISC.

Komponente računalnika: centralno procesna enota, instrukcijski cikel, pomnilnik, naprave, prekinitve.

Pomnilnik: hierarhija, zgodovinski pregled, zunanji pomnilnik, analitični modeli zmogljivosti.

Predpomnilnik: vloga, struktura, funkcije preslikave,

Introduction: historic overview of computer architectures, hardware components, performance, data representation.

Instruction set: characteristics, addressing modes, instruction formats, semantic gap, assembly language.

Architecture 80x86: historic overview, structure, modes of operation, CISC instruction set.

Computer components: central processing unit, instruction cycle, memory, devices, interrupts.

Memory: hierarchy, historic overview, external memory, analytical performance models.

Cache: role, structure, mapping functions, writing policy.

politika pisanja. Operacijski sistem: arhitekturni vidik, večopravilnost,

upravljanje s pomnilnikom, razvrščanje procesov. Navidezni pomnilnik: razdeljevanje in odstranjevanje,

izmenjevanje, tabela strani, TLB, segmentacija. Centralno procesna enota: struktura, registri, notranja

vodila, mikroprogram, izvršitev instrukcije. Cevenje: pohitritve, podroben instrukcijski cikel, stopnje

cevenja, hazardi, predvidevanje vejitev. Paralelne arhitekture: superskalarnost, procesorji SMP,

NUMA, grozdne arhitekture.

Operating system: architectural view, multitasking, memory

management, scheduling. Virtual memory: partitioning, paging, swapping, page table,

TLB, segmentation. Central processing unit: structure, registers, datapath,

microprogram, instruction execution. Pipelining: speedup, detailed instruction cycle, pipelining

levels, hazards, branch prediction. Parallel architectures: superscalar, SMP, NUMA, cluster

architectures. Temeljni literatura in viri / Readings: W. Stallings: Computer Organizations and Architecture, Designing for Performance, Tenth Ed., Prentice Hall, 2015. D. A. Patterson, J. L. Hennessy: Computer Architecture: A Quantitative Approach, Morgan Kaufmann Publishers. Inc., 2011. D. A. Patterson, J. L. Hennessy: Computer Organization and Design: The Hardware/Software Interface, Fourth Ed., Morgan

Kaufmann, 2011. D. Kodek: Arhitektura računalniških sistemov. 2. popravljena in razširjena izdaja, Bi-Tim, Ljubljana, 2008. S. G. Shiva: Advanced Computer Architectures, Taylor & Francis Group, Boca Raton, 2006. Cilji in kompetence:


Cilj predmeta je vpeljati študente, da bodo sposobni razumeti organizacijo in arhitekturo računalnika od von Neumannovega modela do novejših arhitektur.

The objective of this course is to acquaint students that they will be able to understand organization and architecture of a computer dating from von Neumann model to modern architectures.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben razumeti in podrobno razložiti delovanje posameznih

računalniških komponent, njihovo vlogo in parametre zmogljivosti,

z uporabo zbirnega jezika programirati posamezne komponente računalnika.

Knowledge and understanding: On completion of this course the student will be able to understand and explain in detail the operation of specific

computer components, their role and performance parameters,

program specific computer components with assembly language.


pisno izražanje pri pisnem izpitu. Uporaba informacijske tehnologije: uporaba zbirnega

jezika za programiranje in orodij za simulacijo procesorja. Reševanje nalog: načrtovanje arhitektur, programiranje

strojnih komponent, izračun parametrov zmogljivosti.


expression at written examination. Use of information technology: use of assembly for

programming and tools for processor simulation. Problem solving: designing architecture, programming of

hardware components, performance evaluation. Metode poučevanja in učenja:



lectures, lab work.



Assessment:


50 % 25 % 25 %


Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, jih nadomesti s pisnim izpitom v deležu 50%. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references: BOŠKOVIĆ, Borko, BREST, Janez. Protein folding optimization using differential evolution extended with local search and






UČNI NAČRT PREDMETA / SUBJECT SPECIFICATION Predmet: Razvoj programske opreme Subject Title: Software development



Letnik Year

Semester Semester


Computer Science and Information Technologies

1st cycle Academic undergraduate

2. zimski Winter


Predavanja Lectures

Seminar Seminar





30 3 42 105 6 Nosilec predmeta / Lecturer: Peter Kokol Jeziki / Languages:



Prerequisites:

Pogojev ni. None. Vsebina:


Uvod: zgodovina, kriza programske opreme, programsko inženirstvo v prihodnosti

Inženirske osnove oblikovanja programske opreme: empirične metode, merjenje, reševanje problemov, modeliranje, simulacije, prototipiranje

Modeli življenjskega cikla programske opreme Inženiring zahtev: definicija, procesi pridobivanja

zahtev, funkcionalne in nefunkcionalne specifikacije, specifikacije uporabniškega vmesnika, standardi, dokumenti, analiza zahtev, vzdrževanje dokumentov zahtev, validacija zahtev

Oblikovanje programske opreme: osnovni koncepti, procesi, principi, strategije, strukture in arhitekture programske opreme, vzorci, oblikovanje uporabniških vmesnikov, notacije, verzioniranje

Oblikovanje za optimalnost: Minimizacija kompleksnosti, fleksibilnost, prilagodljivost, po uporaba, trajnost. orodja

Osnove projektnega vodenja: planiranje in kontrola, kadrovanje, motiviranje, upravljanje z viri, metode komuniciranja, timsko delo.

Testiranje programske opreme: validacija, verifikacija, testiranje. metrike, procesi testiranja

Vzdrževanje programske opreme; definicije, tehnični in upravljavski vidik, stroškovni vidik, procesi, migracija, prenova

Introduction: history, software crisis, the future of

software engineering Engineering principles of of software design: empirical

methods, measurement, problem solving, modelling, simulation, prototyping

Software life cycle models Requirements engineering: definition, process of

requirements eliciting, functional and non-functional requirements, user interface requirements, standards, documents, requirement analysis. Document maintenance, validation of requirements

Software development: basic concepts, processes, principles, strategies, software structures and architectures, patterns, user interface design, notations, versioning

Software optimisation: complexity reduction, flexibility, adaptability, reuse, sustainability, tools

Project management basics: planning and control, human resource management, motivation, resource management, communication, team work

Software testing: validation, verification, testing methods, metrics, processes,

Software maintenance: definitions, technical and management aspects, economics, processes, migration, re-engineering

Temeljni študijski viri / Textbooks: Sommerville: Software Engineering, Addison-Wesley, Pearson Education Ltd, New York, 2015. R. S. Pressman: Software Engineering: A Practitioner's Approach, McGraw-Hill Book Company, New York, 2014. K. Wiegers and J. Beatty, Software Requirements (3rd Edition), Microsoft Press, Redmond, Washington, 2013 Cilji:

Objectives:

Naučiti študenta razumevanja in uporabe: pojma življenjskega cikla od inženiringa zahtev, metod oblikovanja, implementacije, testiranja , do vzdrževanja s stališča kakovosti programske opreme, človeških faktorjev in projektnega vodenja v okviru inženirskih principov

The student will understand: life cycle concept, from requirement engineering, software development, implementation, testing trough maintenace, - from the aspects, human factors, project managemt in the scope of engineering principles,



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben uporabiti pridobljeno znanje v vseh faz življenjskega cikla oblikovanja kakovostne programske opreme,.

Knowledge and understanding: On completion of this course the student will be able to present and use the knowledge about software lifecycle approaches, for quality software development

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: komunicirati z uporabniki glede zahtev programske opreme,kakor znotraj tima. Uporaba informacijske tehnologije: sposobnost uporabe orodij za oblikovanje programske opreme. Organizacijske spretnosti: organizirati timsko delo pri razvoju programske opreme. Reševanje problemov: načrtovanje in oblikovanje programske opreme po željah uporabnikov. Delo v skupini: sposobnost delati v skupini za razvoj programske opreme.

Transferable/Key skills and other attributes: Communication skills: to communicate with users regarding software requirements and inside the team. ·Use of information technology: to use software development tools ·Organisation skills: to organise team work during software development. · Problem solving: the design and development of software according to user needs. ·Working in a group: to be able to work in the software development team



predavanja, seminar, laboratorijske vaje.

lectures, seminar, lab work.



Assessment methods:

Laboratorijske vaje 1. vmesni pisni izpit 2. vmesni pisni izpit

50 % 25 % 25 %

Lab work 1st midterm written exam 2nd midterm written exam

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 50 %. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50 Reference nosilca / Lecturer's references: KOKOL, Peter, POHOREC, Sandi, ŠTIGLIC, Gregor, PODGORELEC, Vili. Evolutionary design of decision trees for medical

application. Wiley interdisciplinary reviews, Data mining and knowledge discovery. [Print ed.], May 2012, vol. 2, iss. 3, str. 237-254, doi: 10.1002/widm.1056. [COBISS.SI-ID 15997462], [JCR, SNIP]

BLAŽUN, Helena, BOBEK, Samo, KOKOL, Peter, JAVORNIK KREČIČ, Marija. Attitudes of active older Internet users towards online social networking. Computers in human behavior, ISSN 1873-7692. [Online ed.], feb. 2016, vol. 55, part A, str. 230-241, graf. prikazi. http://www.sciencedirect.com/science/article/pii/S074756321530145X, doi: 10.1016/j.chb.2015.09.014. [COBISS.SI-ID 84085249], [JCR, SNIP]

KOKOL, Peter, BLAŽUN, Helena, ŽELEZNIK, Danica. Visualising nursing data using correspondence analysis. Nurse researcher, ISSN 2047-8992, sep. 2016, no. 1, vol. 24, str. 38-40, graf. prikazi, doi: 10.7748/nr.2016.e1441. [COBISS.SI-ID 88885505], [SNIP]

KOKOL, Peter, BLAŽUN, Helena, ŽELEZNIK, Danica, VOŠNER, Janez, SARANTO, Kaija. Bibliometric patterns of research literature production on nursing informatics competence. The Journal of nursing education, ISSN 0148-4834, 2015, vol. 54, no. 10, str. 565-571, graf. prikazi, doi: 10.3928/01484834-20150916-04. [COBISS.SI-ID 84086273], [JCR, SNIP]

KOKOL, Peter, ZAVRŠNIK, Jernej, ŽELEZNIK, Danica, BLAŽUN, Helena. Creating a self-plagiarism research topic typology through bibliometric visualisation. Journal of academic ethics, ISSN 1572-8544, 22. mar. 2016, [10] str., doi: 10.1007/s10805-016-9258-6. [COBISS.SI-ID 86374145], [SNIP]


Predmet: Signali in slike Course title: Signals and Images



Letnik Academic year

Semester Semester





2. poletni Spring

Vrsta predmeta / Course type Univerzitetna koda predmeta / University course code:

Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vaje work



ECTS

30 45 105 6 Nosilec predmeta / Lecturer: Aleš Holobar Jeziki / Languages:

Predavanja / Lectures: slovenski / Slovene Vaje / Tutorial: slovenski / Slovene


Prerequisits:

Ni pogojev. None.

Vsebina:


Uvod: zvezni sistemi in princip zvezne Fourierove transformacije, Laplaceova transformacija, konvolucija.

Vzorčenje: Nyquistov kriterij, prehod k diskretnim

sistemom in transformacijam, z-transformacija, diskretna Fourierova transformacija.

Hitra Fourierova transformacija: razvoj algoritmov, kratkočasovna Fourierova transformacija.

Načrtovanje digitalnih filtrov: pregled metod, razvoj s pomočjo glavničnega filtra, okenske funkcije.

Predobdelava slik: histogram sivin, lokalni operatorji, glajenje, izenačevanje, binarizacija.

Segmentacija slik: pragovni postopki, odkrivanje robov (gradientni operatorji, Cannyjev postopek sledenja), rast regij.

Razpoznavalni sistem: odkrivanje slikovnih značilk, preprosti prijemi za rotacijsko neodvisno razpoznavanje objektov na slikah.

Introduction: continuous systems and the principle of continuous Fourier transform, Laplace transform, convolution.

Sampling: Nyquist theorem, introduction of discrete systems and transforms, z-transform, discrete Fourier transform.

Fast Fourier transform: development of the algorithms, short-time Fourier.

Digital filter design: survey of methods, development using the transversal filter, window functions.

Image preprocessing: grey-level histogram, local operators, smoothing, equalisation, binarization.

Image segmentation: thresholding, edge detection (gradient operators, Canny tracking procedure), region growing.

Recognition system: image feature extraction, simple

approach to rotation-independent recognition of image objects.

Temeljni literatura in viri / Readings: S. W. Smith: The Scientist and Engineer's Guide to Digital Signal Processing, California Technical Publishing, 2011. L. Tan, J. Jiang: Digital Signal Processing, Second Edition: Fundamentals and Applications, Academic Press, 2013. D. Zazula: Računalniška obdelava signalov in slik, pisno gradivo, Univerza v Mariboru, Fakulteta za elektrotehniko,

računalništvo in informatiko, Maribor, 2006. A. V. Oppenheim, R. W. Schaffer, J. R. Buck: Discrete-Time Signal Processing, Prentice Hall, London, 1999. Cilji in kompetence:


Cilj predmeta je utrditi razumevanje in uporabo osnovnih transformacij in postopkov za računalniško obdelavo signalov in slik.

The objective of this course is to instil the comprehension and utilization of basics transforms and algorithms for computer signal and image processing.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben izkazati znanje in razumevanje Fourierove, kratkočasovne

Fourierove in z-transformacije, uporabiti te transformacije pri analizi diskretnih sistemov

oziroma za obdelavo signalov in slik v časovnem in frekvenčnem prostoru,

načrtovati in implementirati računalniške postopke za digitalne filtre, segmentacijo slik in preproste postopke za razpoznavanje objektov,

uporabljati računalniška razvojna okolja in namensko računalniško opremo s področja signalov in slik.

Knowledge and understanding: On completion of this course the student will be able to demonstrate knowledge and understanding of Fourier,

short-time Fourier, and z-transform, apply these transforms to analyse discrete systems and

process signals and images in time and frequency domain, implelent computer algorithms for digital filtering, image

segmentation, and simple object recognition, use computer development environments in specialised

hardware for signal and image processing tasks.


priprava in javna predstavitev poročila o študentskem projektu, ustni izpit.

Uporaba informacijske tehnologije: uporaba programskih orodij in naprav za načtrovanje in razvoj postopkov za obdelavo signalov in slik.

Delo v skupini: skupinsko delo v študentskem projektu. Reševanje problemov: načrtovanje in izvedba

študentskega projekta, sodelovanje z industrijskimi partnerji.

Transferable/Key skills and other attributes: Communication skills: oral lab work defence, preparation

and presentation of the student project report, oral examination.

Use of information technology: use of special software tools and devices for the design and development of signal and image processing algorithms.

Team work: team execution of student projects. Problem solving: designing and implementing of student

projects, co-operation with industrial partners.



predavanja, seminarske vaje, projektno delo, laboratorijske vaje, reševanje domačih nalog.

lectures, tutorials, project work, lab work, homework assignments.



Assessment:

Sprotni način laboratorijske vaje, 1. vmesni izpit,

2. vmesni izpit.

Delež 50

25

25

Constant assessment methods lab work, 1st midterm examination,


Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti z ustnim izpitom v deležu 50 %. Note:

If a student has not completed both midterm exams, he replaces them with an oral exam in the weight of 50 %. Reference nosilca / Lecturer's references: FARINA, Dario, HOLOBAR, Aleš. Characterization of human motor units from surface EMG decomposition. Proceedings of the IEEE, ISSN 0018-9219. [Print ed.], Feb. 2016, vol. 104, no. 2, str. 353-373, doi: 10.1109/JPROC.2015.2498665. [COBISS.SI-ID 19441174] FARINA, Dario, HOLOBAR, Aleš. Human-machine interfacing by decoding surface electromyogram. IEEE signal processing magazine, ISSN 1053-5888. [Print ed.], Jan. 2015, vol. 32, no. 1, str. 115-120, doi: 10.1109/MSP.2014.2359242. [COBISS.SI-ID 18364950] HOLOBAR, Aleš, MINETTO, Marco A., FARINA, Dario. Accurate identification of motor unit discharge patterns from high-density surface EMG and validation with a novel signal-based performance metric. Journal of neural engineering, ISSN 1741-2560, Feb. 2014, vol. 11, no. 1, str. 1-11, doi: 10.1088/1741-2560/11/1/016008. [COBISS.SI-ID 17445654] GLASER, Vojko, HOLOBAR, Aleš, ZAZULA, Damjan. Real-time motor unit identification from high-density surface EMG. IEEE transactions on neural systems and rehabilitation engineering, ISSN 1534-4320. [Print ed.], Nov. 2013, vol. 21, no. 6, str. 949-958, doi: 10.1109/TNSRE.2013.2247631. [COBISS.SI-ID 17016854] HOLOBAR, Aleš, GLASER, Vojko, GALLEGO, J.A., DIDERIKSEN, J.L., FARINA, Dario. Non-invasive characterization of motor unit behaviour in pathological tremor. Journal of neural engineering, ISSN 1741-2560, 2012, vol. 9, no. 5, str. 1-6, doi: 10.1088/1741-2560/9/5/056011. [COBISS.SI-ID 16676630]


Predmet: Sistemska programska oprema

Course title: System Software



Letnik Academic

year

Semester Semester





2. poletni Spring



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6

Nosilec predmeta / Lecturer: Aleš Holobar

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Ni pogojev. None.

Vsebina:


Uvod: lastnosti in principi sistemske programske opreme, statično in dinamično programsko izvajalno okolje.

Računalniško shranjevanje in prenašanje informacij: standardizirani znakovni kodi in nabori, jeziki za oblikovanje in izmenjavo podatkov.

Strojni in simbolični jeziki: princip zbiranja, osnove delovanja zbirnika, sistemsko odvisne in neodvisne funkcije.

Poenoteni vmesni nivoji: statični objektni moduli in princip

Introduction: properties and principles of system software, static and dynamic programme environment.

Information storage and transmission: standardised character codes and fonts, graphical page description languages, data exchange, mark-up languages.

Machine and symbolic languages: principle of assembly programming language, basic operation of assembler, machine-dependent and independent functions.

Unified intermediate level: static object modules and the

dinamičnih razrednih zbirk pri javi in .NET, pomen internih struktur (globalne tabele, prenaslovitvene tabele, nabor konstant) in primeri (ELF pri OS linux, PE pri OS windows, ART pri OS Android).

Statično povezovanje: razreševanje globalnih sklicevanj, prenaslavljanje, knjižnice objektnih modulov, tvorba izvedljivih programov.

Dinamično povezovanje: uporaba nabora konstant v razrednih zbirkah, dinamično povezljive knjižnice.

Nalaganje: začetno nalaganje operacijskega sistema, začetni nalagalnik, diskovna struktura s particijami in nalagalnimi zapisi, nalaganje s prenaslavljanjem, BIOS in UEFI.

Nadziranje delovanja programov: očiščevalnik, uporaba programske prekinitve pri koračnem izvajanju in prekinitvenih točkah, simbolični očiščevalnik, krpanje in simbolični krpalnik.

Komunikacija z V/I napravami in gonilniki: Sistemski klici in signali, jedro in njegovi moduli v OS Linux, zasnova jedra pri OS Windows, gonilniki v OS Linux in OS Windows, podatkovna vodila in prekinitve.

Komunikacija človek-stroj: naravni vmesniki, vmesniki mišice-stroj, vmesniki možgani-stroj, kinetični uporabniški vmesniki.

principle of dynamic Java class and .NET files, importance of internal structures (global tables, relocation tables, constant pool), and examples (Linux ELF, Windows PE, Android ART).

Static linking: global symbol resolution, relocation, object libraries, output executable programs.

Dynamic linking: implementation of constant pools in class

files, dynamic linked libraries. Loading: boot loading of operating system, initial loader,

disk partitioning and boot records, loading with relocation, BIOS and UEFI.

Checking the executed programs: debugger, step-by-step

execution and breakpoints based on software interrupts, symbolic debugger, patching and symbolic patch.

Communication with I/O devices: system calls and signals,

kernel and it's modules in OS Linux, kernel in OS Windows, Linux drivers, Windows drivers, data buses and programme interrupts

Human-computer communication: natural user interfaces, muscle-computer interfaces, brain-computer interfaces, kinetic user interfaces.

Temeljni literatura in viri / Readings: D. Abbott: Linux for embedded and real-time applications, Elsevier ; Oxford : Newnes, cop. 2013. M. E. Russinovich, D. A. Solomon, A. Ionescu: Windows internals, Microsoft Press, 2012. D. Zazula, M. Lenič: Principi sistemske programske opreme, Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in

informatiko, Maribor, 2006. I. Englander: The Architecture of Computer Hardware, Systems Software, and Networking, John Wiley & Sons, 2010. M. Kerrisk The Linux programming interface : a Linux and UNIX System Programming Handbook , San Francisco : No Starch

Press, 2010. W. J. Savitch, K. Mock: Absolute Java, Pearson Education, 2010. Cilji in kompetence:


Cilj predmeta je poučiti študente o osnovah sistemske programske opreme in doseči, da jo bodo razumeli in znali uporabiti sistemska programska orodja sodobnih operacijskih sistemov.

The objective of this course is for the students to be able to understand and use system software tools, including system programming and special-purpose software in modern operating systems.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben razumeti pomen in delovanja sistemske programske

opreme ter osnovnih postopkov za vrednotenje računalniških sistemov in aplikacij,

uporabljati sistemske klice za delo z zbirkami, računalniškimi omrežji in namenskimi napravami,

uporabljati sistemska orodja za vrednotenje in izboljševanje delovanja računalniških instalacij in aplikacij.

razumeti pomen ter oceniti prednosti in slabosti sodobnih uporabniških komunikacijskih vmesnikov med človekom in računalnikom

Knowledge and understanding: On completion of this course the student will be able to understand the importance and operation of system

software, and basic principles of computer system and application evaluation,

implement system calls to access files, communication links, and special-purpose devices,

use system tools to evaluate and improve the computer system and application performance.

understand the importance and identify the advantages and disadvantages of modern human-computer communication interfaces.

Prenosljive/ključne spretnosti in drugi atributi:

Transferable/Key skills and other attributes:

Spretnosti komuniciranja: ustni zagovor laboratorijskih vaj in projekta, priprava in javna predstavitev poročila o študentskem projektu.

Uporaba informacijske tehnologije: uporaba programskih orodij in naprav za delo v sistemskem računalniškem okolju.

Organizacijske spretnosti: izdelava in vodenje preprostega projekta.

Reševanje problemov: načrtovanje in izvedba študentskega projekta.

Delo v skupini: skupinsko delo v študentskem projektu.

Communication skills: oral lab work defence, preparation and presentation of the student project report.

Use of information technology: use of special software tools and devices for the development at system level.

Organization skills: design and coordination of simple

project. Problem solving: designing and implementation of student

projects. Team work: team work in a student project.

Metode poučevanja in učenja: Learning and teaching methods:

predavanja, seminarske vaje, projektno delo, laboratorijske vaje, reševanje domačih nalog.




Assessment:


Delež 50

25

25

Constant assessment methods lab work, 1st midterm examination,


Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti z ustnim izpitom v deležu 50 %. Note: If a student has not completed both midterm exams, he replaces them with an oral exam in the weight of 50 %. Reference nosilca / Lecturer's references: FARINA, Dario, HOLOBAR, Aleš. Human-machine interfacing by decoding surface electromyogram. IEEE signal processing

magazine, ISSN 1053-5888. [Print ed.], Jan. 2015, vol. 32, no. 1, str. 115-120, doi: 10.1109/MSP.2014.2359242. [COBISS.SI-ID 18364950]

ŠAVC, Martin, GLASER, Vojko, KRANJEC, Jernej, CIKAJLO, Imre, MATJAČIĆ, Zlatko, HOLOBAR, Aleš. Comparison of convolutive kernel compensation and non-negative matrix factorization of surface electromyograms. IEEE transactions on neural systems and rehabilitation engineering, ISSN 1534-4320. [Print ed.], 2018, vol. 26, no. 10, str. 1935-1944, ilustr., doi: 10.1109/TNSRE.2018.2869426. [COBISS.SI-ID 21717270]

HOLOBAR, Aleš, DIVJAK, Matjaž, KOROŠEC, Dean, ZAZULA, Damjan. Training scenario prototyping for VR-based simulation of neonatal decision-making. Comput. appl. eng. educ., 2007, vol. 15, iss. 4, str. 317-327, doi: 10.1002/cae.20121. [COBISS.SI-ID 12006934]

HOLOBAR, Aleš, DIVJAK, Matjaž, PRELOG, Iztok, KOROŠEC, Dean, ZAZULA, Damjan. A distributed virtual reality-based system for neonatal decision-making training. Comput. appl. eng. educ., 2007, vol. 15, iss. 4, str. 329-339, doi: 10.1002/cae.20120. [COBISS.SI-ID 12007190]

HOLOBAR, Aleš, OJSTERŠEK, Milan, ZAZULA, Damjan. Distributed Jacobi joint diagonalization on clusters of personal computers. Int. j. parallel program.. [Print ed.], 2006, vol. 34, no. 6, str. 509-530. http://dx.doi.org/10.1007/s10766-006-0025-y. [COBISS.SI-ID 10982678]


Predmet: Sistemska administracija

Course title: System Administration



Letnik Academic

year

Semester Semester





2. poletni Spring



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vaje work


Samost. delo

Individ. work

ECTS

30 45 105 6


Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Ni pogojev. None.

Vsebina:


Uvod: operacijski sistemi, aplikacije, administrativna opravila.

Nameščanje, konfiguriranje in upravljanje operacijskih sistemov.

Skriptno programiranje: primeri bash, … Storitve, ki jih ponuja internet: upravljanje storitev,

konfiguriranje storitev. Upravljanje in konfiguriranje: upravljanje in

Introduction: operating systems, applications, administrative activities.

Installation, configuration and management of operating systems.

Script programming: examples: bash, … Internet services: service management, service

configuration. Management and configuration: networks management

konfiguriranje omrežij, upravljanje in konfiguriranje stikal in usmerjevalnikov, upravljanje in konfiguriranje mobilnih omrežij.

Upravljanje računalniških sistemov in podatkovnih baz. Računalniška varnost, pogoste napake pri

programiranju. Programska oprema: programska oprema za analizo

omrežnega prometa, programska oprema za ugotavljanje vdorov.

Kriptografija. Uporabniki: tehnična podpora uporabnikom. Odpornost na napake: metode, študij primerov.

and configuration, management and configuration of switches and routers, management and configuration of mobile networks.

Management of computer systems and databases. Computer security, common programming mistakes. Software: software tools for network traffic analysis,

intrusion detection systems. Cryptography. Users: technical support. Fault tolerance: methods, case study.

Temeljni literatura in viri / Readings: M. Burgess: Principles of Network and System Administration, Second Edition, John Wiley & Sons, Ltd, West Sussex,

2004. E. Nemeth, G. Snyder, T. R. Hein, B. Whaley, D. Mackin: UNIX and Linux System Administration Handbook,

Addison-Wesley Professional, 5 edition, 2017. C. Benvenuti: Understanding Linux Network Internals, O’Reilly, Sebastopol, 2006. M. Bishop: Computer Security: Art and Science. Addison Wesley (2nd edition), 2017. Cilji in kompetence:


Cilj predmeta je seznaniti študente z osnovnimi principi sistemske administracije in varnosti.

The objective of this course is to acquaint students with the basic principles of computer system administration and security.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben prikazati sposobnost namestitve vsaj enega izmed

operacijskih sistemov, izkazati sposobnost vzdrževanja različnih operacijskih

sistemov, ločevati med storitvami na serverju in odjemalcu, uporabiti različne operacijske sisteme in analizirati ter

priporočati določen operacijski sistem za določene potrebe,

identificirati, opisati in analizirati situacije, kjer so potrebne administrativne aktivnosti.

Knowledge and understanding: On completion of this course the student will be able to illustrate the ability to install at least one operating

system, demonstrate the ability to support various operating

systems, distinguish between server and client services, demonstrate knowledge and understanding of various

operating systems,analyse and recommend a particular operating system to satisfy given needs,

identify, describe and analyse situations, which interfere with administrative activities.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: ustni zagovor laboratorijskih

vaj, pisno izražanje pri pisnem izpitu. Uporaba informacijske tehnologije: uporaba

programskih orodij in skript za avtomatizacijo opravil v sistemski administraciji.

Reševanje problemov: načrtovanje, namestitev in vzdrževanje računalniških sistemov.


expression at written examination. Use of information technology: use of software tools

and scripts to automate routine tasks in system administration.

Problem solving: designing, installing and managing of

computer systems. Metode poučevanja in učenja:


predavanja, laboratorijske vaje

lectures, lab work.



Assessment:


50 % 25 % 25 %


Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, jih nadomesti s pisnim izpitom v deležu 50%. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references:

BOŠKOVIĆ, Borko, BREST, Janez. Protein folding optimization using differential evolution extended with local search and component reinitialization. Information sciences, ISSN 0020-0255. [Print ed.], July 2018, vol. 454/455, str. 178-199, doi: 10.1016/j.ins.2018.04.072. [COBISS.SI-ID 21401878], [JCR, SNIP, WoS do 11. 11. 2018: št. citatov (TC): 1, čistih citatov (CI): 1, čistih citatov na avtorja (CIAu): 0.50, Scopus do 29. 10. 2018: št. citatov (TC): 1, čistih citatov (CI): 1, čistih citatov na avtorja (CIAu): 0.50]






Predmet: Spletno programiranje

Course title: Web Programming



Letnik Academic

year

Semester Semester





2. poletni Spring



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6

Nosilec predmeta / Lecturer: Tomaž Kosar

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Uvod: življenjski cikel gradnje spletnih aplikacij, spletni strežniki, brskalniki.

Lastnosti spletnih aplikacij: piškotki, seje, zmogljivost, predpomnenje, zanesljivost, varnost.

Programiranje na odjemalcu. Programiranje na strežniku. Evolucija spletnih aplikacij. Označevalni jeziki: XML, DTD, sheme XML, XML DOM,

XSLT, XPath, XLink, XPointer, XQuery.

Introduction: Web application life cycle, Web servers, Web browsers.

Web application properties: cookies, sessions, performance, caching, reliability, security.

Client side Web programming. Server side Web programming. Evolution of Web applications. Markup languages: XML, DTD, XML shema, XML DOM,

XSLT, XPath, XLink, XPointer, XQuery.

Socialna omrežja in tehnologije Spleta 2.0. Spletne storitve in storitveno usmerjena arhitektura:

SOAP, WSDL, UDDI, WS standardi, storitveno vodilo, BPEL, storitveni vzorci.

Portali, sistemi za upravljanje z vsebino, dokumentni sistemi, integracija vsebin in storitev.

Priporočilni sistemi, iskalniki in upravljanje z identitetami.

Pomenski splet: RDF, OWL, ontologije, predstavitev znanja.

Social networks and Web 2.0 technologies. Web Services and service oriented architecture: SOAP,

WSDL, UDDI, WS standards, service oriented bus, BPEL, Web services patterns.

Portals, content management systems, document systems, integration of content and services.

Recommendation systems, search engines and identity management.

Semantic Web: RDF, OWL, ontology, knowledge representation.

Temeljni literatura in viri / Readings: M. Ojsteršek: Učno gradivo in primeri dosegljivi na E-študij UM: https://estudij.um.si/ – potrebna je prijava v portal. L. Shklar, R. Rosen: Web Application Architecture: Principles, Protocols and Practices, John Wiley & Sons, Chichester, West

Sussex, 2009. N. S. Williams: Professional Java for Web Applications, John Wiley & Suns , Indianapolis, 2014 D. Esposito: Go to "Programming Microsoft ASP.NET MVC (3rd Edition) (Developer Reference)", O'Relly Media Inc., 2014. S. Bergmann, S. Priebsch: Real-World Solutions for Developing High-Quality PHP Frameworks and Applications, John Wiley &

Suns , Indianapolis, 2011. D. K. Barry: Web Services, Service-Oriented Architectures, and Cloud Computing, Second Edition: The Savvy Manager's

Guide (The Savvy Manager's Guides), Elsevier, Waltham, 2013. Cilji in kompetence:


Cilj predmeta je naučiti študenta implementirati spletne aplikacije s trenutno aktualnimi spletnimi tehnologijami, programskimi orodji, skriptnimi in programskimi jeziki za razvoj spletnih aplikacij.

The objective of this course is to teach students to implement Web applications with the latest technologies, programming tools, scripting and programming languages suitable for Web applications development.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben: poiskati na internetu ustrezne informacije o tehnologijah,

skriptnih in programskih jezikih, programskih orodjih, ki jih uporablja pri razvoju svojih spletnih aplikacij,

izbrati ustrezno tehnologijo, skriptni jezik, programski jezik, programsko orodje in podatkovno bazo za razvoj spletne aplikacije,

uporabljati skriptne jezike pri razvoju predstavitvenega dela splene aplikacije,

uporabljati trenutno aktualne programske jezike pri razvoju poslovne logike in podatkovnega sloja spletnih aplikacij,

analizirati, načrtovati, izdelati, testirati in promovirati spletno aplikacijo,

izdelati spletno storitev.

Knowledge and understanding: On completion of this course the student will be able to find appropriate information on the internet about

programming tools, scripting and programming languages suitable for development of Web applications,

select appropriate technology, data base, programming tool, scripting and programming language for Web application development,

use of scripting languages for development of presentation layer of Web application,

implement of business and data layer of Web application,

analyse, design, implement, test and promote Web application,

implement a Web service.



Uporaba informacijske tehnologije: uporaba programskih orodij za načrtovanje, implementacijo, razhroščevanje in testiranje spletnih aplikacij.

Reševanje problemov: načrtovanje in implementacija spletnih aplikacij.

Delo v skupini: študenti v skupini analizirajo, načrtujejo,



program design, implementation, debugging and testing of simple Web applications.

Problem solving: design and implementation of simple Web application.

Working in a group: team of students analyse, design,

izdelajo in testirajo spletno aplikacijo. implement and test their Web application. Metode poučevanja in učenja:


predavanja, laboratorijske vaje, delo v skupini.

lectures, lab work, working in group.



Assessment:

računalniške vaje, 1. vmesni pisni izpit, 2. vmesni pisni izpit.

50 % 25 % 25%

computer lab work, 1st midterm written exam, 2nd midterm written exam.

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, jih nadomesti s pisnim izpitom v deležu 50%. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references:

• KOSAR, Tomaž, GABERC, Sašo, CARVER, Jeffrey C., MERNIK, Marjan. Program comprehension of domain-specific and general-purpose languages: replication of a family of experiments using integrated development environments. Empirical software engineering, ISSN 1382-3256, 2018, vol. 23, iss. 5, str. 2734-2763, doi: 10.1007/s10664-017-9593-2. [COBISS.SI-ID 21123606]. • KOSAR, Tomaž, BOHRA, Sudev, MERNIK, Marjan. Domain-specific languages : a systematic mapping study. Information and software technology, ISSN 0950-5849. [Print ed.], March 2016, vol. 71, str. 77-91. • KOS, Tomaž, KOSAR, Tomaž, MERNIK, Marjan. Development of data acquisition systems by using a domain-specific modeling language. Computers in industry, ISSN 0166-3615. [Print ed.], Apr. 2012, vol. 63, no. 3, str. 181-192, doi: 10.1016/j.compind.2011.09.004. [COBISS.SI-ID 15485974] • KOSAR, Tomaž, MERNIK, Marjan, CARVER, Jeffrey C. Program comprehension of domain-specific and general-purpose languages : comparison using a family of experiments. Empirical software engineering, ISSN 1382-3256, 2012, vol. 17, no. 3, str. 276-304, doi: 10.1007/s10664-011-9172-x. [COBISS.SI-ID 15213590] • KOSAR, Tomaž, MARTÍNEZ LÓPEZ, Pablo E., BARRIENTOS, Pablo A., MERNIK, Marjan. A preliminary study on various implementation approaches of domain-specific language. Information and software technology, ISSN 0950-5849. [Print ed.], apr. 2008, vol. 50, iss. 5, str. 390-405. http://dx.doi.org/10.1016/j.infsof.2007.04.002. [COBISS.SI-ID 11399958]


Predmet: Umetna inteligenca

Course title: Artificial Intelligence



Letnik Academic

year

Semester Semester





2. poletni Spring



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6


Jeziki / Languages:


slovenski / Slovene



Prerequisites:

Ni pogojev. None.

Vsebina:


Uvod: kaj je umetna inteligenca, zgodovina umetne inteligence, pregled področij umetne inteligence, reference v umetni inteligenci.

Inteligentni agenti: agenti in okolja, koncept racionalnosti, narava okolij, struktura agentov.

Reševanje problemov z iskanjem: agenti reševanja problemov, primeri problemov, iskanje rešitev, neinformirane iskalne strategije, izogibanje ponovljenim stanjem, iskanje z delno informacijo.

Introduction: what is artificial intelligence (AI), history of AI, survey of AI fields, references in AI.

Intelligent agents: agents and environments, concept of

rationality, nature of environments, structure of agents. Solving problem by searching: problem-solving agents,

example problems, searching for solutions, uninformed search strategies, avoiding repeated states, searching with partial information.

Igranje iger: procedura minimaks, algoritem alfa-beta, izboljšave algoritma alfa-beta, vzorčno znanje in mehanizem nasvetov.

Logika prvega reda: sintaksa in semantika, uporaba, inženirstvo znanja.

Sklepanje v logiki prvega reda: unifikacija, veriženje naprej, veriženje nazaj, resolucija.

Planiranje: sistem STRIPS, planiranje s preiskovanjem prostora stanj, grafi planiranja, hierarhično mrežno planiranje, multiagentno planiranje.

Verjetnostno sklepanje: predstavitev znanja v negotovi domeni, semantika Bayesovih mrež, sklepanje v Bayesovih mrežah, drugi pristopi verjetnostnega sklepanja (Dempster-Shaferjeva teorija, mehka logika).

Nevronske mreže: definicija, lastnosti, uporaba, model nevrona, mrežne arhitekture, proces učenja.

Pragovna logična enota (perceptron): učno pravilo perceptrona.

Učno pravilo delta: padajoči gradient, perceptron s sigmoidno aktivacijsko funkcijo.

Game playing: the minimax procedure, the alpha-beta procedure, improvements of the alpha-beta procedure, pattern knowledge and the mechanism of advice.

First-order logic: syntax and semantics, use, knowledge engineering.

Inference in first-order logic: unification, forward chaining, backward chaining, resolution.

Planning: system STRIPS, planning with state-space search, planning graphs, hierarchical task network planning, multiagent planning.

Probabilistic reasoning: representing knowledge in an uncertain domain, semantics of Bayesian networks, inference in Bayesian networks, other approaches to uncertain reasoning (Dempster-Shafer theory, fuzzy logic).

Neural networks: definition, properties, use, neuron model, network architectures, learning process.

Threshold logic unit (perceptron): perceptron learning rule. Delta learning rule: gradient descent, perceptron with

sigmoidal activation function. Večplastne nevronske mreže: algoritem vzvratnega

razširjanja. Asociativni pomnilnik in Hopfieldova mreža. Kohonenove nevronske mreže.

Multilayer neural networks: backpropagation algorithm. Associative memory and Hopfield network. Kohonen neural networks.

Temeljni literatura in viri / Readings: N. Guid, D. Strnad: Umetna inteligenca, učbenik, Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in

informatiko, Maribor, 2007. S. Russell, P. Norvig: Artificial Intelligence. A Modern Approach, 2. izdaja, Prentice Hall, Upper Saddle River, 2003. G. F. Luger: Artificial Intelligence, Addison-Wesley, Harlow, England, 2005. I. Bratko: Prolog in umetna inteligenca, Društvo matematikov, fizikov in astronomov, Ljubljana, 1997. S. Haykin: Neural Networks. A Comprehensive Foundation, Macmillan College Publ. Company, New York, 1994. Cilji in kompetence:


Cilj predmeta je seznaniti študente z različnimi področji umetne inteligence, ki računalniku omogočajo reševanje kompleksnih problemov. Študenti se bodo seznanili z uporabo iskalnih algoritmov za reševanjem problemov, načini predstavitve znanja, osnovnimi algoritmi za sklepanje in izpeljavo novega znanja, ter pristopi za sklepanje z negotovim znanjem. Spoznali bodo tudi ozadje delovanja različnih oblik nevronskih mrež in njihovo uporabo v klasifikacijskih in regresijskih problemih.

The objective of this course is to acquaint the students with diverse fields of artificial intelligence that allow the computer to solve complex problems. The students will familiarize themselves with the use of search algorithms for problem solving, techniques for knowledge representation, basic inference algorithms for derivation of new knowledge, and approaches for uncertain inference. They will also learn about the operation of various neural network architectures and their use in classification and regression problems.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben opisati neinformirane, informirane in lokalne iskalne

strategije za reševanje problemov v prostoru stanj, razumeti temeljne koncepte predstavitve znanja z logiko, izvesti sklepanje in izpeljavo novega znanja s predikatno

logiko, uporabiti preproste sisteme verjetnostnega sklepanja, opisati delovanje nevronskih mrež in z njihovo pomočjo

Knowledge and understanding: On completion of this course the student will be able to describe the uninformed, informed, and local search

strategies for solving problems in state spaces, understand the basic concepts of using logic for knowledge

representation, perform the inference and derive new knowledge using

predicate logic, use simple systems for probabilistic reasoning,

izvesti klasifikacijo.

describe the operation of neural networks and use them to perform classification.


pisno izražanje pri pisnem izpitu. Uporaba informacijske tehnologije: pisanje računalniških

programov. Spretnosti računanja: reševanje računskih problemov pri

domačih nalogah. Reševanje problemov: načrtovanje in izvedba preprostih

inteligentnih agentov.


expression at written examination. Use of information technology: writing computer programs. Calculation skills: solving calculation problems in homework

assignments. Problem solving: design and construction of simple

intelligent agents. Metode poučevanja in učenja:


predavanja, seminarske vaje, laboratorijske vaje, projekt

lectures, tutorials, lab work, project



Assessment:


50 25 25









Predmet: Uvod v računalniško geometrijo

Course title: Introduction to Computational Geometry



Letnik Academic

year

Semester Semester





2. poletni

Summer



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6


Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni none

Vsebina:


Uvod: pomen in aplikacije algoritmov računalniške geometrije.

Pasti algoritmov z aritmetiko s plavajočo vejico. Pogoji od dobrooblikovanih površjih. Predstavitvene metode (dvoumne in nedvoumne) Eulerjevi operatorji Osnovne podatkovne strukture za iskanje v ravnini:

enakomerna delitev ravnine, štiriško drevo, drevo BSP.

Introduction: significance and applications of computational geometry algorithms

Traps of the algorithms with floating-point arithmetic. Conditions of well-formed shapes. Representation methods (ambiguous, unambiguous). Euler operators. Basic data structure for geometric search in the plane:

uniform space division, quadtree, BSP tree.

Izbočena (konveksna) lupina: definicija in uporaba, naivna metoda, Grahamovo preiskovanje, Jarvishev obhod, inkrementalna metoda, metoda s preiskovalno premico, hitra konveksna lupine, aproksimativna rešitev.

Iskanje najbližje točke: delitev problemov najbližje točke in aplikacije, reševanje inkrementalnega problema najbližje točke z enakomerno delitvijo ravnine.

Triangulacija: definicija in lastnosti, triangulacija MWT, Hammiltonova triangulacija, Delaunayeva triangulacija.

Algoritmi za konstrukcijo Delaunayeve triangulacije: inkrementalne metode, konstrukcijska metoda, pristop deli in vladaj, metoda s prebirno premico, metoda s preslikavo na paraboloid, Delaunayeva lomljenka.

Algoritmi konstrukcije Voronoievih diagramov: definicija in lastnosti, aplikacije, posplošeni Voronoievi diagrami, naivna metoda, metoda deli in vladaj, inkremetalna metoda, metoda s prebirno premico.

Definicija in klasifikacija mnogokotnikov. Vsebnostni testi: brez priprave podatkov (s poltrakom, z

vsoto kotov, s kodiranim koordinatnim sistemom, test enakega predznaka) in s pripravo podatkov (delitev v trakove, algoritem s klini, algoritem CBCA).

Triangulacija mnogokotnika: brez kriterija, Delaunayeva

triangulacija, triangulacija s Steinerjevimi točkami. Omejena Delaunayeva triangulacija. Trapezna delitev mnogokotnika: Seidlov algoritem,

algoritem z dvema preiskovalnima premicama, algoritem z odprtimi trapezi.

Boolove operacije nad mnogokotniki.

Convex hull: definition and the usage, naive approach, Graham search, Jarvish marsh, incremental method, sweep-line method, quick hull, approximate algorithm.

The nearest point problem: classification of nearest point

problems and their applications, solving of incremental nearest point problem by uniform space subdivision.

Triangulation: definition and properties, MWT, Hammilton triangulation, Delaunay triangulation.

Delaunay triangulation algorithms: incremental method, constructive method, divide & conquer approach, sweep-line approach, high-dimensional mapping, Delaunay polyline.

Algorithms for Voronoi diagram construction: definition and properties, applications, generalized Voronoi diagrams, naive approach, divide & conquer approach, incremental algorithm, Fortune’s sweep-line approach.

Definition and classification of polygons. Containment tests: tests without preprocessing (ray-

intersection method, sum of angles, approach with coded coordinate system, the same sigh test), tests with preprocessing (strip-based approach, wedge-based approach, algorithm CBCA).

Polygon triangulation: without criterion, Delaunay criterion, triangulation using Steiner points.

Constrained triangulation. Polygon trapezoidation: Seidel’s algorithm, algorithm with

two sweep-lines, algorithm with the open trapezoids. Boolean operations on polygons.

Temeljni literatura in viri / Readings: M. de Berg, M. van Kreveld, M. Overmars, O. Schwarzkopf, Computational Geometry - Algorithms and Applications, Fourth

Edition, Springer, Berlin, 2010. F. P. Preparata, M. I. Shamos, Computational Geometry: An Introduction, Second Edition, Springer, New York, 1990. J. O'Rourke, Computational Geometry in C, Second Edition, Cambridge University Press, Cambridge, 1998. B. Žalik, Algoritmi računalniške geometrije, Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko,

Maribor, 2006. Cilji in kompetence:


Cilj predmeta je, da bodo i študentje razumeli pomen učinkovite in zanesljive obdelave geometrijskih podatkov, da bodo znali implementirati geometrijske algoritme in jih uporabiti v praksi.

The objective of this course is for students to be able to demonstrate understanding of efficient and safe geometric data processing, to implement the geometric algorithms and to use them in practice.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben razumeti pomena računalniške geometrije v različnih

aplikacijah, rešiti probleme računalniške geometrije, izdelati učinkovite algoritme za reševanje geometrijskih

nalog z računalnikom, odločiti se za ustrezne podatkovne strukture za učinkovito

geometrijsko iskanje.

Knowledge and understanding: On completion of this course the student will be able to understand importance of computational geometry in

various applications, solve problems of computational geometry, implement efficient algorithms for solving geometric tasks

with the computer, select adequate data structures for efficient geometric

search.



Uporaba informacijske tehnologije: pisanje računalniških programov, iskanje dodatnih virov na spletu.

Reševanje problemov: načrtovanje lastnih algoritmov računalniške geometrije.

Reševanje problemov: izbira najprimernejšega algoritma za posamezno nalogo, ocenjevanje uspešnosti implementiranih algoritmov glede na časovno in prostorsko zahtevnost.

Transferable/Key skills and other attributes: Communication skills: written exam, writing report about lab

work, oral examination of lab work. Use of information technology: software development,

obtaining additional information on the WEB. Problem solving: design of own algorithms of computational

geometry. Working in a group: selecting the most suitable algorithm

for desired task, estimation of efficiency of implemented algorithms regarding time and space complexity.







Assessment:

opravljene domače naloge, laboratorijske vaje, 1. vmesni pisni izpit, 2. vmesni pisni izpit,

10 40 25 25

completed homeworks, lab work, 1st midterm written exam, 2nd midterm written exam,

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 50 %. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references: LUKAČ, Niko, ŠTUMBERGER, Gorazd, ŽALIK, Borut. Wind resource assessment using airborne LiDAR data and smoothed

particle hydrodynamics. Environmental Modelling & Software, 2017, vol. 95, str. 1-12. HORVAT, Denis, ŽALIK, Borut. Inclusion test for polyhedra using depth value comparison on the GPU. International journal of

computer theory and engineering, 2017, vol. 9, no. 2, str. 137-141. HORVAT, Denis, ŽALIK, Borut, MONGUS, Domen. Context-dependent detection of non-linearly distributed points for

vegetation classification in airborne LiDAR. ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing, 2016, vol. 116, str. 1-14.

RUPNIK, Bojan, MONGUS, Domen, ŽALIK, Borut. Point density evaluation of airborne LiDAR datasets. Journal for universal computer science, 2015, vol. 21, no. 4, str. 587-603.

LUKAČ, Niko, ŽALIK, Borut. Fast approximate k-nearest neighbours search using GPGPU. V: CAI, Yiyu (ur.), SEE, Simon (ur.). GPU computing and applications. Berlin; Heidelberg: Springer. 2015, str. 221-234.


UČNI NAČRT PREDMETA / SUBJECT SPECIFICATION Predmet: Algoritmi in tehnike za učinkovito reševanje problemovSubject Title: Algorithms and techniques for efficient problem solving



Letnik Year

Semester Semester





3 zimski winter


Predavanja Lectures

Seminar Seminar




Samostojno delo Individual work

ECTS

15 30 135 6 Nosilec predmeta / Lecturer: Damjan Strnad Jeziki / Languages:



Prerequisites:



Analiza problema: določanje tipa problema, izbira podatkovne strukture za predstavitev problema, primerjava možnih pristopov in izbira najboljšega algoritma za učinkovito rešitev problema.

Kombinatorični problemi Problemi iskanja Optimizacijski problemi Numerični računski problemi Verjetnostni problemi Problemi z rekurzijo Geometrijski problemi Problemi na nizih Napredne podatkovne strukture: predponsko drevo,

uravnoteženo drevo, Fibonaccijeva kopica, podatkovne strukture za množice, sekljalno drevo

Problem analysis: problem type identification, data structure selection for problem representation, comparison of viable approaches and selection of the best algorithm for efficient problem solution.

Combinatorial problems Search problems Optimization problems Numerical computation problems Probabilistic problems Problems with recursion Geometrical problems Problems on strings Advanced data structures: prefix tree, balanced tree,

Fibonacci heap, data structures for sets, hash tree

Temeljni študijski viri / Textbooks: P. Brass, Advanced Data Structures, Cambridge University Press, 2008 A. Levitin, M. Levitin, Algorithmic Puzzles, Oxford University Press, 2011 N. Karumanchi, Data Structures and Algorithms Made Easy: Data Structures and Algorithmic Puzzles, 5. izdaja, CareerMonk

Publications, 2016

2 / 2

Cilji:

Objectives:

Cilj predmeta je, da študentje pridobijo izkušnje z reševanjem različnih tipov tekmovalnih problemov ter znajo uporabiti primerno kombinacijo podatkovne strukture in algoritma za učinkovito rešitev danega problema.

The aim of the course is for the students to acquire the necessary experience with solving different types of competition problems, as well as using the suitable combination of data structure and algorithm to efficiently solve the problem.

Predvideni študijski rezultati: Intended learning outcomes: Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben identificirati tip problema in ga povezati s podobnimi

problemi z znanimi učinkovitimi rešitvami, določiti nabor možnih podatkovnih struktur za predstavitev

danega problema in med njimi izbrati najprimernejšo v smislu prostorske in/ali časovne učinkovitosti,

predvideti primernost različnih pristopov za reševanje problema in izbrati najbolj učinkovitega.

Knowledge and understanding: On completion of this course the student will be able to identify the problem type and relate it to similar problems

with known effective solutions, determine the set of applicable data structures for given

problem presentation and select among them the most suitable one with respect to space and/or time efficiency,

predict the suitability of different approaches for problem solving and choose the most efficient one.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: zagovor vaj ter pisno izražanje

pri izpitu. Reševanje problemov: identifikacija vrste problema in

določitev ustrezne strategije za njegovo reševanje.

Transferable/Key skills and other attributes: Communication skills: oral defence of practical exercises

and manner of expression at written examination. Problem solving: identification of problem type and selection

of appropriate strategy for its solution.



predavanja, seminarske vaje, samostojno delo.

lectures, seminar work, individual work.



Assessment methods:

praktične naloge

100 practical assignments

Reference nosilca / Lecturer's references: STRNAD, Damjan, NERAT, Andrej. Parallel construction of classification trees on a GPU. Concurrency and

computation, ISSN 1532-0626. [Print ed.], Apr. 2016, vol. 28, iss. 5, str. 1417-1436, doi: 10.1002/cpe.3660. [COBISS.SI-ID 19144726]

FISTER, Iztok, SUGANTHAN, Ponnuthurai Nagaratnam, FISTER, Iztok, KAMAL, Salahuddin M., AL-MARZOUKI, Fahad M., PERC, Matjaž, STRNAD, Damjan. Artificial neural network regression as a local search heuristic for ensemble strategies in differential evolution. Nonlinear dynamics, ISSN 0924-090X, 2016, vol. 84, iss. 2, str. 895-914, doi: 10.1007/s11071-015-2537-8. [COBISS.SI-ID 19305750]

KOHEK, Štefan, STRNAD, Damjan. Interactive synthesis of self-organizing tree models on the GPU. Computing, ISSN 0010-485X, Feb. 2015, vol. 97, iss. 2, str. 145-169, doi: 10.1007/s00607-014-0424-7. [COBISS.SI-ID 18066454]

STRNAD, Damjan, NERAT, Andrej, KOHEK, Štefan. Neural network models for group behavior prediction : a case of soccer match attendance. Neural computing & applications, ISSN 0941-0643, First online: 08 September 2015, str. 1-14, doi: 10.1007/s00521-015-2056-z. [COBISS.SI-ID 18933014]

STRNAD, Damjan, KOHEK, Štefan. Novel discrete differential evolution methods for virtual tree pruning optimization. Soft computing, ISSN 1432-7643. [Print ed.], Published online 19 August 2015, str. 1-13, doi: 10.1007/s00500-015-1827-x. [COBISS.SI-ID 18883606]


UČNI NAČRT PREDMETA / SUBJECT SPECIFICATION Predmet: Razvoj računalniških iger Subject Title: Computer game development



Letnik Year

Semester Semester





3 zimski winter


Predavanja Lectures

Seminar Seminar





ECTS

30 3 42 105 6 Nosilec predmeta / Lecturer: Matej Črepinšek Jeziki / Languages:



Prerequisites:



Uvod: predstavitev predmeta, motivacija. Igre: zgodovina, vrste iger, računalniške igre.

Načrtovanje iger: mehanika iger, logika iger, osnove

grafičnega oblikovanja iger. Objektno usmerjeno načrtovanje računalniških iger. Programski vzorci pri razvoju iger: vzorci zaporedja,

vedenjski vzorci, vzorci za optimizacijo. Načini upravljanja iger: tipkovnica, miška, zasloni na dotik,

pospeškometer, kompas, igralna palica, glas. Zaledne storitve iger: ogrodja, orodja, najboljše prakse. Igralski pogoni. Razvoj 2D iger. Razvoj 3D iger. Teorija iger: uvod in uporaba konceptov (strategije

ravnovesja, pareto optimalnost). Igrifikacija: definicija, primeri, tehnike. Dejavniki zabave: pregled, analiza in implementacija. Uspešnost iger: analiza in merjenje. Večigralske igre: orodja, načrtovanje, implementacija.

Introduction: overview of the subject, motivation. Games: history, types of games, computer games. Game design: game mechanic, game logic, basic game

graphics design. Object-orientated design for computer games.

Game programming patterns: sequencing patterns,

behavioral patterns, optimization patterns. Game Input Handling: keyboard, mouse, touchscreen,

accelerometer, compass, joystick, voice. Backend services for games: frameworks, tools, best

practices. Game engines. Development of 2D games. Development of 3D games. Game Theory: introduction and use of concepts

(equilibrium strategies, pareto optimality). Gamification: definitions, examples, techniques. Fun factors: overview, analyse and implementation. The success of games: analysis and measurement. Multiplayer games: tools, design, implementation.

2 / 3

Temeljni študijski viri / Textbooks: Robert Nystrom; Game Programming Patterns; 2014. Jason Gregory; Game Engine Architecture; 2014. Kevin Werbach Dan Hunter; The Gamification Toolkit: Dynamics, Mechanics, and Components for the Win; 2015. Ian Bogost; Persuasive Games: The Expressive Power of Videogames (MIT Press); 2010. Jane McGonigal; Reality Is Broken: Why Games Make Us Better and How They Can Change the World; 2014.

Cilji:

Objectives:

Cilj predmeta je, da študentje osvojijo specifična znanja potrebna pri razumevanju, načrtovanju in implementaciji računalniških iger. Poglobiti znanja in izboljšati spretnosti iz programiranja. Izdelati ali dodelati aplikacijo, da vsebuje tipične elemente igrifikacije. Spodbuditi študente h kreativnemu in kritičnemu razmišljanju.

The aim of the course is to give the students the specific knowledge needed for understanding, designing and implementation of computer games. To improve knowledge and improve skills of programming. To develop or upgrade an application that includes the elements of gamification. Encourage students to creative and critical thinking.

Predvideni študijski rezultati: Intended learning outcomes: Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben: Načrtovati in implementirati preprosto računalniško igro. Uporaba podpornih orodij in tehnologij v procesu razvoja

igre. Razložiti zgradbo računalniških iger in elemente iger. Prepoznati in vpeljati osnovne elemente igrifikacije.

Knowledge and understanding: On completion of this course the student will be able to: Design and implement simple computer game. Using the support tools and the technologies in the process

of a game development. Explain computer game design and game elements. Identify and implement basic elements of gamification.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: podajanje opisa težav pri

razvoju programske opreme, zagovor vaj ter pisno izražanje pri izpitu.

Uporaba informacijske tehnologije: uporaba sodobnih naprav in razvojnih orodij, uporaba programskih jezikov in analiza podatkov.

Reševanje problemov: definiranje ciljev, metod, programiranje, razhroščevanje, iskanje novih načinov komunikacije človek-računalnik.

Transferable/Key skills and other attributes: Communication skills: to describe problems and errors

during software development, oral defence of practical exercises and manner of expression at written examination.

Use of information technology: the use of modern digital devices and developing tools, programming and data analyse.

Problem solving: defining goals, methods, programming, debugging, search for new ways for computer human communication.



predavanja, seminarske vaje laboratorijske vaje, samostojno delo.

lectures, seminar work lab work, individual work.



Assessment methods:


Delež 50 25

25

Constant assessment methods lab work, 1st midterm examination, 2nd midterm examination.

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 50 %. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50 %.. Reference nosilca / Lecturer's references:

3 / 3

1. VEČEK, Niki, MERNIK, Marjan, ČREPINŠEK, Matej. A chess rating system for evolutionary algorithms : a new method for the comparison and ranking of evolutionary algorithms. Information sciences, ISSN 0020-0255. [Print ed.], Sep. 2014, vol. 277, str. 656-679.

2. ČREPINŠEK, Matej, LIU, Shih-Hsi, MERNIK, Luka, MERNIK, Marjan. Is a comparison of results meaningful from the inexact replications of computational experiments?. Soft computing, ISSN 1432-7643. [Print ed.], Jan. 2016, vol. 20, no. 1, str. 223-235.

3. ČREPINŠEK, Matej, LIU, Shih-Hsi, MERNIK, Marjan. Replication and comparison of computational experiments in applied evolutionary computing : common pitfalls and guidelines to avoid them. Applied soft computing, ISSN 1568-4946. [Print ed.], June 2014, vol. 19, str. 161-170.


Predmet: Angleščina – jezik stroke

Course title: English for Specific Purposes



Letnik Academic

year

Semester Semester





3. poletni

Summer

Vrsta predmeta / Course type Izbirni/Elective


Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework


Samost. deloIndivid. work

ECTS

30 15 45 3

Nosilec predmeta / Lecturer: Nataša Potočnik

Jeziki / Languages:


angleški / English

Vaje / Tutorial: angleški /English


Prerequisits:

Osnovno znanje angleškega jezika na nivoju najmanj B1. Basic knowledge of English on the level B1. Vsebina:


Izpopolnitev jezikovnih veščin (uporaba časov). Univerza v Mariboru Inženirstvo (osnovne veje) Študijski programi Študent inženirstva Uporaba računalnikov Vhodno/izhodne naprave Internet Službe na področju računalništva Računalniki v prihodnosti

Improving the Language Skills (Summary of Tenses). University of Maribor Engineering – What's it All About? Choosing a Course An Engineering Student Computers Today Input/Output. Devices Faces of the Internet Jobs in ICT Computers Tomorrow

Temeljni literatura in viri / Readings: S. R. Esteras: Infotech, English for Computer Users, Cambridge University Press, Cambridge, 2014. E. G. Glendinning & N. Glendinning: Oxford English for Electrical and Mechanical Engineering, Oxford University Press, Oxford,

1996. University Maribor: Welcome to Maribor (Survival Guide), University Maribor, 2016. V. Evans: Round –up 4, English Grammar Book, Virginia Pagoulatou – Vlachou, 1993. A. S. Hornby: Oxford Advanced Learner's Dictionary of Current English, Oxford University Press, Oxford, 2010. Various sources offering material related to the area of computers in English and Slovene language Cilji in kompetence:


Cilj predmeta je seznaniti študente z osnovami jezika na področju slovnice in računalniške stroke (ESP), predstaviti izbrane računalniške teme ter razvijati vse štiri osnovne jezikovne spretnosti: branje, pisanje, poslušanje, govorjenje.

The aim of this course is to improve the students' level of English language (grammar), to introduce students to the ESP for computing, to introduce the selected computer topics and to develop the four basic skills: reading, writing, listening and speaking.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben izkazati znanje (ustno in pisno) in razumevanje

pridobljenega splošnega in strokovnega besedišča angleškega jezika iz zgoraj navedenih vsebin predmeta.

Knowledge and understanding: On completion of this course the student will be able to demonstrate and express (in written and oral forms) the

acquired knowledge of general and technical English related to the contents above.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: javno nastopanje in pisna

predstavitev lastnega seminarskega dela. Uporaba informacijske tehnologije: pri samostojnem učenju

in javnem nastopanju. Organizacijske spretnosti: delo v dvojicah, skupinah in

samostojna predstavitvi strokovnega vprašanja. Reševanje problemov: reševanje nalog. Delo v skupini: reševanje nalog pri predavanjih in

seminarju.

Transferable/Key skills and other attributes: Communication skills: oral and written communication, in-

class presentation of the seminary work. Use of information technology: at individual study and

presenting. Organisation skills: pair-work, group-work and presentation

of technical issues. Problem solving: solving tasks. Working in a group: exercises and tasks at lectures and

seminar. Metode poučevanja in učenja:


diskusija, debata, metoda mešanih skupin.

discussion, debate, group work method.



Assessment:

dva testa, študent lahko dodatne odstotke pridobi z neobveznim seminarjem.

50%, 50% do/to 16%

two tests, a student can get the extra points with an optional seminar.

Opomba: Testa se lahko nadomestita s pisnim izpitom. Note: The tests may be replaced with a written exam. Reference nosilca / Lecturer's references: POTOČNIK, Nataša, 12. 5. 1970 - Wendy Jones Nakanishi: briding different cultures through literature. International Journal of

English Literature and Culture, ISSN 2360-7831, 2016, letn. 4, št. 8, str. 155-164. COBISS.SI-ID 19854614 POTOČNIK, Nataša, 12. 5. 1970 - Robert Dean Frisbie, a writer of the South Seas and his contribution to South Pacific literature:

lecture, presented at the University of Hawai’I at Manoa campus, Center for bibliographical research, Honolulu, Hawaii, USA September 5, 2013. 2013 COBISS.SI-ID 17195286

POTOČNIK, Nataša, 12.5.1970- Bridging East and West : Wendy Jones Nakanishi's writings as English language and literature about Japan / Nataša Potočnik. - Bibliografija: str. 30-32. V: L & C. - ISSN 1348-3226. - Vol. 10, [no.] 3 (2012), str. 1-32. COBISS.SI-ID 15952662

POTOČNIK, Nataša, 12.5.1970- Robert Dean Frisbie : writer of the south seas ; his contribution to pacific literature / Nataša Potočnik. - Bibliografija: str. 140-141. V: Osaka daigaku sekai gengo kenkyuu senta ronshuu. - ISSN 1883-5139. - No. 5 (2011), str. 119-141. COBISS.SI-ID 15729174

POTOČNIK, Nataša, 12.5.1970- The south seas idyll in The book of Puka-Puka and My Tahiti by Robert Dean Frisbie / Nataša Potočnik. - Bibliografija: str. 34-35. V: L & C. - ISSN 1348-3226. - Vol. 9, [no.] 3 (Mar. 2011), str. 17-35. COBISS.SI-ID 15728406


Predmet: Geografski informacijski sistemi

Course title: Geographic Information Systems



Letnik Academic

year

Semester Semester





3. poletni Spring



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 3 42 105 6

Nosilec predmeta / Lecturer: Domen Mongus

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Uvod: kaj je geografski informacijski sistem (GIS), cilji GIS, komponente GIS, aplikacije GIS, zgodovina GIS.

Osnove kartografije: kartografske projekcije, koordinatni

sistemi, merila. Podatki v GIS: kartografski podatki (merilo, projekcije,

topografske in tematske karte, simboli), prostorski podatki (topološki, geometrijski, tekstualni).

Pridobivanje in predobdelava podatkov: lokalno

Introduction: what is a geographic information system (GIS), GIS objectives, GIS components, GIS applications, history of GIS.

Basics of cartography: map projections, coordinate systems, scales.

GIS data: cartographic data (scale, projections, topographic and thematic maps, symbols), spatial data (topologic, geometric, textual).

Data acquisition and pre-processing: local observation,

opazovanje, daljinsko zaznavanje, večspektralni posnetki, rasterizacija in vektorizacija, konstrukcija plastnic.

Funkcije v GIS: algebra karte, Boolove operacije nad sloji, izračun oddaljenosti, osončenost, izračun profilov in prečnih prerezov, karta vidnosti, naklon terena, določanje topoloških značilnosti terena, sledenje gibanja, geometrijska očrtja.

Podatkovne baze GIS: Oracle Spatial, ESRI SDE, Map Tools.

WEB GIS: konzorcij OpenGIS.

remote sensing, multispectral images, rasterisation and vectorisation, contour line construction.

Functions of GIS: map algebra, Boolean operations on layers, distance calculation, sun exposition, profile and cross section calculation, visibility map, terrain inclination, determination of topologic terrain features, movement tracking, geometric buffers.

GIS databases: Oracle Spatial, ESRI SDE, Map Tools. WEB GIS: OpenGIS Consortium.

Temeljni literatura in viri / Readings: K. Kvamme, K. Oštir-Sedej, Z. Stančič, R. Šumrada: Geografski informacijski sistemi, Znanstvenoraziskovalni center

Slovenske akademije znanosti in umetnosti, Ljubljana, 1997. K. Chang: Introduction to Geographic Information Systems, Third Edition, McGraw-Hill Science/Engineering/Math, Dubuque,

Iowa, 2005. P. A. Burrough, R. A. McDonnell: Principles of Geographical Information Systems (Spatial Information Systems), Second

Edition, Oxford University Press, Oxford, 1998. M. de Berg, M. van Kreveld, M. Overmars, O. Schwarzkopf: Computational Geometry, Algorithms and Applications, Second

Edition, Springer-Verlag, Berlin, 2000. Cilji in kompetence:


Cilj tega predmeta je seznaniti študente z osnovami in s posebnostmi geografskih informacijskih sistemov ter z zahtevami Konzorcija OpenGIS, jim nuditi ustrezen besedni zaklad in jim omogočiti razumevanje specifičnih podatkov ter tipičnih funkcij GIS.

The objective of this course is to acquaint students with basics and particularities of geographic information systems and with requirements of the OpenGIS Consortium, to offer to them a corresponding vocabulary and to enable them understanding of specific GIS data and typical GIS functions.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben izkazati razumevanje pomena in široke uporabnosti GIS, izkazati razumevanje osnov kartografije, navesti, razložiti in klasificirati podatke v GIS, navesti in povzeti načine pridobivanja podatkov GIS, razložiti delovanje nekaterih osnovnih algoritmov

predprocesiranja podatkov GIS, kot so rasterizacija, vektorizacija in tvorba izohips,

navesti in razložiti glavne funkcije GIS ter nekatere izmed njih tudi uporabiti,

navesti, oceniti in uporabiti najpopularnejša sodobna komercialna razvojna orodja GIS,

navesti in primerjati najpomembnejše podatkovne baze GIS,

razložiti poslanstvo Konzorcija OpenGIS in navesti njegove aktivnosti (specifikacije zahtev).

Knowledge and understanding: On completion of this course the student will be able to demonstrate knowledge of significance and wide usability

of GIS, demonstrate understanding of cartography basics, list, explain, and classify data types presented in GIS, list and summarise methods of GIS data acquisition, explain performance of some basic algorithms for GIS data

pre-processing, such as rasterization, vectorisation, and contour line creation,

list and explain main GIS functions, and also to use some of them,

list, assess, and use the most popular up-to-date commercial GIS development tools,

list and compare the most significant GIS databases, explain mission of OpenGIS Consortium, and list its

activities (requirements specifications).

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: ustno izražanje pri ustnem izpitu

in zagovoru laboratorijskih vaj, pisanje seminarske naloge. Uporaba informacijske tehnologije: uporaba aktualnih

razvojnih orodij GIS in spoznavanje komercialnih sistemov podatkovnih baz GIS.

Reševanje problemov: samostojno reševanje vaj in

Transferable/Key skills and other attributes: Communication skills: oral manner of expression at oral

exemination and lab work defense, writing seminar work. Use of information technology: use of present software

development tools for GIS, and cognition of up-to-date commercial GIS databases.

Problem solving: individual lab work solving and seminar

priprava seminarske naloge. work preparation. Metode poučevanja in učenja:


predavanja, seminarske vaje, laboratorijske vaje. .




Assessment:


50 % 25 % 25 %


Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 50%. Note: If a student has not completed all two midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references: MONGUS, Domen, LUKAČ, Niko, ŽALIK, Borut. Ground and building extraction from LiDAR data based on differential

morphological profiles and locally fitted surfaces. ISPRS journal of photogrammetry and remote sensing, ISSN 0924-2716. [Print ed.], July 2014, vol. 93, str. 145-156, doi: 10.1016/j.isprsjprs.2013.12.002. [COBISS.SI-ID 17466134]

Nagrada: Odlični v znanosti 2013, Tehnika: Računalništvo in informatika (ARRS 2014) MONGUS, Domen, ŽALIK, Borut. Computationally efficient method for the generation of a digital terrain model from airborne

LiDAR data using connected operators. IEEE journal of selected topics in applied earth observations and remote sensing, ISSN 1939-1404, Jan. 2014, vol. 7, no. 1, str. 340-351, doi: 10.1109/JSTARS.2013.2262996. [COBISS.SI-ID 16937494]

MONGUS, Domen, REPNIK, Blaž, MERNIK, Marjan, ŽALIK, Borut. A hybrid evolutionary algorithm for tuning a cloth-simulation model. Applied soft computing, ISSN 1568-4946, Jan. 2012, vol. 12, iss. 1, str. 266-273, doi: 10.1016/j.asoc.2011.08.047. [COBISS.SI-ID 15310102]

MONGUS, Domen, ŽALIK, Borut. Parameter-free ground filtering of LiDAR data for automatic DTM generation. ISPRS journal of photogrammetry and remote sensing, ISSN 0924-2716. [Print ed.], Jan. 2012, vol. 67, str. 1-12, ilustr., doi: 10.1016/j.isprsjprs.2011.10.002.

MONGUS, Domen, ŽALIK, Borut. Efficient method for lossless LIDAR data compression. International journal of remote sensing, ISSN 0143-1161. [Print ed.], 2011, vol. 32, no. 9, str. 2507-2518, doi: 10.1080/01431161003698385. [COBISS.SI-ID 14953494]


Predmet: Konvergenca in integracija sistemov

Course title: System Convergence and Integration



Letnik Academic

year

Semester Semester





3. Zimski Autumn



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

45 30 105 6

Nosilec predmeta / Lecturer: Boštjan Šumak

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Znanja o razvoju aplikacij. Knowledge on application development.

Vsebina:


Uvod v integracijo in konvergenco sistemov: pomen, integracija aplikacij in informacijskih sistemov, tehnološka in vsebinska konvergenca, priložnosti in pasti konvergence.

Integracija sistemov: vloga, opredelitev in pomen, tipi integracije, primerjava med EAI, IAI, EII, B2B, SOA.

Integracija kot proces: večfazni postopek integracije, konsistentnost podatkov, nivo aplikacijskih vmesnikov, nivo poslovne logike, predstavitveni nivo.

Integracija na nivoju podatkov: dostop do podatkov, transformacije podatkov.

Introduction to integration and system convergence: role, application integration, information systems integration, technology and content integration, opportunities and pitfalls of convergence.

System integration: roles, definition and significance, types of integration, comparison between EAI, IAI, EII, B2B, SOA.

Integration process: multiphase approach to integration, data consistency, application interface level, business logic level, presentation level.

Data level integration: data access, data transformations. Application interface level integration:

Integracija na nivoju aplikacijskih vmesnikov: sinhronost/asinhronost, razpoložljivost.

Integracija na nivoju poslovne logike: komponente, storitve, granulacija vmesnikov.

Integracija na nivoju predstavitve: portali, enotna vstopna točka, enkratna prijava.

Tehnologije za integracijo: sporočilni sistemi, oddaljeno proženje operacij, integracijski posredniki, vloga tehnologij XML in povezanih tehnologij za integracijo na različnih nivojih.

Kompozicija storitev in podpora procesom ter delovnim tokovom.

Tehnologije za avtomatizacijo in integracijo poslovnih procesov ter storitev (BPEL).

Vidiki integracije: varnostni vidiki, transakcijski vidiki, arhitekturni vidiki.

Povezovalni strežniki in njihova vloga pri integraciji Vzorci za integracijo: integracijski posrednik, integracijska

ovojnica, navidezna komponenta, preslikava podatkov, avtomator procesov.

Organizacija integracijskih projektov: vloge, odgovornosti, mejniki, aktivnosti.

synchronicity/asynchronicity, availability. Business logic level integration: components, services,

interface granulation. Presentation level integration: portals, single entry point,

single sign-on. Integration technologies: message oriented middleware,

remote operation invocation middleware, integration brokers, mark-up languages.

Service composition and support for processes and workflows.

Technologies for businesses process automation and integration of services (BPEL).

Integration aspects: security aspects, transactional aspects, architectural aspects.

Integration server and their role in system integration Integration patterns: integration broker, integration wrapper,

virtual component, data mapper, process automator. Integration project management: roles, responsibilities,

milestones, activities.

Temeljni literatura in viri / Readings: M. B. Juric with S. J. Basha, R. Leander, R. Nagappan: Professional J2EE EAI, Wrox Press, Birmingham, 2001. G. Hohpe, B. Woolf: Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions, Addison-Wesley

Professional, New York, 2005. M. B. Juric with B. Mathew and P. Sarang: Business Process Execution Language for Web Services, 2nd Edition, Packt

Publishing, Birmingham, 2006. R. Corchuelo, A. Ruiz-Cortes, R. Wrembel: Technology Supporting Business Solutions, Nova Science, New York, 2004. Cilji in kompetence:


Cilj predmeta je spoznati pomen integracije in konvergence sistemov, spoznati se z metodami integracije, tehnologijami, orodji in semantiko. Študentje se spoznajo z metodami integracije znotraj podjetja in med podjetji ter s podatkovni, aplikacijskim, poslovnim in predstavitveni nivojem integracije. Nadalje študentje spoznajo integracijske vzorce in načine planiranja projektov organizacije. Po zaključku predmeta so sposobni reševati integracijske probleme.

The objective of the subject is to understand the importance of integration and convergence of systems, get familiar with the integration methods, technologies, tools, and semantics. Students get familiar with the intra-enterprise and inter-enterprise integration methods, and with data-level, application-level, business-level, and presentation-level integration layers. Students also get familiar with integration patterns and integration project management. After successful subject competition students are capable of solving integration problems.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben načrtovati in implementirati integracijo sistemov na nivoju

podatkov, aplikacijskih vmesnikov, procesov in uporabniškega vmesnika,

razumel konvergenco sistemov in njene implikacije, načrtoval in implementiral integracijske procese, obvladoval organizacijo integracijskih projektov.

Knowledge and understanding: On completion of this course the student will be able to Design and implement integration of systems on data-level,

application-level, process-level, and presentation-level, Understand system convergence and their implications, Design and implement integration processes, Accomplish integration project management.



pisno izražanje pri pisnem izpitu. Uporaba informacijske tehnologije: uporaba metod in

tehnologij za integracijo. Organizacijske spretnosti: organizacija integracijskih

projektov. Reševanje problemov: razvoj enostavnih in srednje

kompleknih rešitev za integracijo. Delo v skupini: izvajanje skupinskih integracijskih

projektov.

expression at written examination. Use of information technology: understanding and usage of

integration methods and technologies. Organisation skills: integration project organisation and

management. Problem solving: development of simple and semi-complex

integration solutions. Working in a group: execution of group integration projects.



predavanja, projekt, laboratorijske vaje.

lectures, project, lab work.



Assessment:

laboratorijske vaje, opravljen projekt, vmesni pisni izpiti.

15 % 35 % 50 %

lab work, completed project, midterm written exams.

Opomba: Vmesni pisni izpiti se lahko nadomestijo s pisnim izpitom. Note: Midterm written exams may be replaced by a written exam. Reference nosilca / Lecturer's references: PUŠNIK, Maja, JURIČ, Matjaž B., HERIČKO, Marjan, ŠUMAK, Boštjan. Pomen spletnih storitev in izvajalnega jezika poslovnih

procesov BPEL pri orkestraciji elektronskega poslovanja. Uporab. inform. (Ljubl.), jul/avg/sep 2004, letn. 12, št. 3, str. 121-131. [COBISS.SI-ID 9127190] kategorija: 1C (Z2); uvrstitev: MBP; tipologijo je verificiral OSICT točke: 7.5, št. avtorjev: 4

ŠUMAK, Boštjan, HERIČKO, Marjan, POLANČIČ, Gregor, PUŠNIK, Maja. Investigation of e-learning system acceptance using UTAUT. Int. j. eng. educ., 2010, vol. 26, no. 6, str. 1327-1342. [COBISS.SI-ID 14690838], [WoS, št. citatov do 6. 4. 2011: 0, brez avtocitatov: 0, normirano št. citatov: 0] kategorija: 1A4 (Z1); uvrstitev: SCI, ERIHB, MBP; tipologijo je verificiral OSICT točke: 10, št. avtorjev: 4

POLANČIČ, Gregor, ŠUMAK, Boštjan. Pregled in iskanje programskih ogrodij in sorodnih tehnologij. Uporab. inform. (Ljubl.), 2010, letn. 18, št. 3, str. 144-154. [COBISS.SI-ID 14622742] kategorija: 1C (Z2); uvrstitev: MBP; tipologijo je verificiral OSICT točke: 15, št. avtorjev: 2

ŠUMAK, Boštjan, HERIČKO, Marjan, PUŠNIK, Maja, POLANČIČ, Gregor. Factors affecting acceptance and use of Moodle : an empirical study based on TAM. Informatica (Ljublj.), 2011, vol. 35, no. 1, str. 91-100. [COBISS.SI-ID 14881814] kategorija: 1C (Z2); uvrstitev: MBP; tipologijo je verificiral OSICT točke: 7.5, št. avtorjev: 4

ŠUMAK, Boštjan, HERIČKO, Marjan, PUŠNIK, Maja. A meta-analysis of e-learning technology acceptance : the role of user types and e-learning technology types : review. Comput. hum. behav.. [Print ed.], Nov. 2011, vol. 27, iss. 6, str. 2067-2077, doi: 10.1016/j.chb.2011.08.005. [COBISS.SI-ID 15270166], [JCR, WoS, št. citatov do 6. 11. 2011: 0, brez avtocitatov: 0, normirano št. citatov: 0] kategorija: 1A1 (Z1, A'', A'); uvrstitev: SSCI, ERIHB, MBP; tipologijo je verificiral OSICT točke: 35.46, št. avtorjev: 3


Predmet: Multimedia

Course title: Multimedia



Letnik Academic

year

Semester Semester





3. zimski Autumn



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6


Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Ni pogojev. None.

Vsebina:


Uvod: kaj je multimedia, razvoj multimedijev, hipertekst, hipermedia in multimedia, klasifikacija multimedijskih tipov, multimedijske aplikacije.

Tekst: uporaba teksta, osnove tipografije, računalniške

predstavitve teksta, operacije nad tekstom. Rastrske slike: predstavitev rastrskih slik, pridobivanje

rastrskih slik, geometrijske transformacije nad slikami, obdelava slik, barvna kvantizacija, algoritmi stresanja, stiskanje slik brez izgub (štiriška drevesa), stiskanje

Introduction: what is multimedia, development of multimedia, hypertext, hypermedia and multimedia, classification of multimedia data types, multimedia applications.

Text: using text in multimedia, typography basics, computer representations of text, operations on text.

Raster images: raster image representations, raster image acquisition, geometric transformations in raster images, image processing, colour quantization, dithering algorithms, loseless raster image compression (quadtrees), raster

rastrskih objektov z verižnimi kodami, stiskanje slik z izgubami (diskretna kosinusna transformacija in valčna transformacija), standardni datotečni formati rastrskih slik GIF, PNG in JPEG.

Zvok in glasba: psihoakustične lastnosti človeškega sluha, analogna in digitalna predstavitev zvoka, priprava digitalnih zvočnih datotek, datotečni formati digitalnega zvoka, izbira med MIDI in Digital Audio, stiskanje zvoka brez izgub, stiskanje zvoka z izgubami, MP3 in AAC.

Video: analogni video, digitalni video, snemanje, urejanje in shranjevanje digitalnega videa, stiskanje digitalnega videa, stiskanje posameznih slik in stiskanje zaporedja slik, algoritmi napovedovanja gibanja, družina MPEG.

Sinhronizacija in integracija podatkov različnih multimedijskih tipov: izbira cilju primernega orodja za sinhronizacijo in integracijo multimedijskih podatkov, možnost urejanja, programirne možnosti, organizacijske možnosti, interaktivnost, izvajanje in predvajanje, nastavitve parametrov izvajanja, distribucija produkta, prenosljivost med različnimi platformami, internetna raba.

objects compression by means of chain codes, loosy image compression (discrete cosine transformation, wavelet transformation), progressive image decompression and visualisation, standard raster image formats GIF, PNG, JPEG.

Sound and music: psychoacoustic characteristics of human hearing, analog and digital sound representation, preparation of digital audio files, digital audio file formats, MIDI versus Digital Audio, loseless audio compression, loosy audio compression, MP3 and AAC.

Video: analog video, digital video, shooting, editing and storing digital video, digital video compression, intra-frame and inter-frame compression, motion prediction algorithms, MPEG family.

Synchronisation and integration of versatile multimedia types: goal-oriented selection of a multimedia authoring tool, editing features, programming features, organisation features, interactivity features, performance and playback features, performance tuning features, delivery features, cross-platform features, internet playability.

Temeljni literatura in viri / Readings: C. Wooton: A Practical Guide To Video And Audio Compression, Focal Press, Burlington, USA, 2005. I. E. Richardson: The H.264 Advanced Video Compression Standard, 2nd Edition, John Wiley & Sons, Chichester, 2010. N. Chapman, J. Chapman: Digital multimedia, Second Edition, John Wiley & Sons, Chichester, 2004. D. Salomon: Data Compression - The Complete Reference, 4th Edition, Springer-Verlag, New York , 2007.



Cilj tega predmeta je, da bodo študenti razumeli osnovna znanja računalniške multimedije, pri čemer bodo znali razvit multimedijske aplikacije s poudarkom na stiskanju podatkov

The objective of this course is for students to obtain and understand basic principles of computer multimedia, where they will also be able to demostrate and implement different multimedia applications, with focus on data compression.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben razumet osnovne multimedijske tipe, njihove karakteristike

in operacije nad njimi, uporabit znanje brezizgubnega in izgubnega stiskanja

multimedijskih podatkov, razumeti in razložiti bistvene lastnosti formatov: GIF, PNG,

JPEG , MIDI, MP3, AAC, MPEG-1, MPEG-2, MPEG-4 in AVC,

razložiti lastnosti analognega in digitalnega zvoka kot tudi videa.

Knowledge and understanding: On completion of this course the student will be able to to understand different multimedia types, their

characteristics and operations on them, demonstrate practical usage of knowledge about basics of

loseless and loosy multimedia data compression, to understand and explain the main properties of file

formats GIF, PNG, JPEG, MIDI, MP3, AAC, MPEG-1, MPEG-2, MPEG-4 and AVC,

explain features of analog and digital audio, as well as video.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: ustno izražanje pri ustnem

izpitu, zagovoru laboratorijskih vaj in predstavitvi rezultatov projekta, pisno dokumentiranje projekta.

Uporaba informacijske tehnologije: uporaba programskih orodij za implementacijo algoritmov stiskanja podatkov posameznih multimedijskih tipov, uporaba orodij za obdelavo, urejanje in komponiranje podatkov različnih multimedijskih tipov ter orodij za sinhronizacijo in

Transferable/Key skills and other attributes: Communication skills: oral manner of expression at oral

examination, lab work defence and presenting the project results, written project documentation.

Use of information technology: use of software tools for programming algorithms for compression of various multimedia data types, use of software tools for processing, editing, and compositing multimedia data of various types, and tools for synchronisation and integration of these data

integracijo teh podatkov v integrirano multimedijsko okolje. Reševanje problemov: samostojno delo na projektu, izbira

ustrezne ciljno usmerjene predstavitve multimedijskih podatkov, tehnike in orodja za načrtovanje privlačne ter učinkovite multimedijske aplikacije.

into an integrated multimedia environment. Problem solving: individual project work, selection of

corresponding goal-oriented presentation of multimedia data, technique and tool for designing attractive and efficient multimedia application.



predavanja, seminarske vaje, laboratorijske vaje, projekt.

lectures, tutorials, lab work, project.



Assessment:


50 % 25 % 25 %


Opomba: V kolikor študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 50 %. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references: KOHEK, Štefan, STRNAD, Damjan, ŽALIK, Borut, KOLMANIČ, Simon. Interactive synthesis and visualization of self-organizing trees for large-scale forest

succession simulation. Multimedia systems, 2018, str. 1-15. LIPUŠ, Bogdan, ŽALIK, Borut. Robust watermarking of airborne LiDAR data. Multimedia tools and applications, 2018, vol. 77,

iss. 21, str. 29077-29097. ŽALIK, Borut, MONGUS, Domen, RIZMAN ŽALIK, Krista, LUKAČ, Niko. Boolean operations on rasterized shapes represented

by chain codes using space filling curves. Journal of visual communication and image representation, 2017, vol. 49, str. 420-432.

ŽALIK, Borut, MONGUS, Domen, LIU, Yong Kui, LUKAČ, Niko. Unsigned Manhattan Chain Code. Journal of visual communication and image representation, 2016, vol. 38, str. 186-194.


Predmet: Paralelno in porazdeljeno računanje

Course title: Parallel and Distributed Computing



Letnik Academic

year

Semester Semester





3. zimski

Autumn



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6


Jeziki / Languages:


slovenski / Slovene



Prerequisits:



Uvod: paralelni računalniški sistemi, porazdeljeni računalniški sistemi, heterogeno procesiranje.

Pohitritev (Amdahlov zakon), zmogljivost, skalabilnost paralelnih algoritmov in porazdeljenih sistemov.

Zasnova paralelnih računalniških sistemov: pomnilnik, omrežja, operacijski sistemi, večjederni procesorji, vhod in izhod. Paralelni arhitekturi SIMD in MIMD.

Principi paralelnega računanja: programski jeziki, prevajalniki, podatkovni in krmilnini paralelizem, dekompozicija podatkov, pošiljanje sporočil in deljeni pomnilnik.

Programiranje s pošiljanjem sporočil. Uvod v standard MPI in aplikacijski programski vmesnik OpenMP ter paralelnost

Introduction: parallel computer systems, distributed computer systems, heterogeneous computing.

Speedup (Amdahl’s law), performance, scalability of parallel algorithms and distributed systems.

Components of parallel computers: memory, interconnection networks, operating systems, multi-core processors, input and output. SIMD and MIMD parallel architectures.

Principles of parallel programming: programming languages, compilers, data and control parallelisms, data decomposition, message passing and shared memory.

Programming with message passing. Introduction to the

v standardih C++. Arhitektura grafičnih procesnih enot (GPE), paralelno

računanje s pomočjo GPE. Splošno namensko računanje z GPE, spoznavanje tehnologij CUDA in OpenCL.

Omejitve in cena pri paralelnem programiranju. Porazdeljeni sistemi: modeli porazdeljenega procesiranja,

komunikacija in sinhronizacija v porazdeljenih sistemih, porazdeljeni podatkovni sistemi (GoogleFS, HDFS, HFS). Visokozmogljivo in visokoprepustno računanje s porazdeljenimi gručami in t.i. superračunalniki. Spoznavanje programskega modela MapReduce.

Podatkovno vodeno paralelno računanje. Transakcije: lastnosti transakcij, metode zaklepanja,

porazdeljene transakcije, smrtni objem.

MPI standard and application programming interface OpenMP and parallelism in C++ standards.

Graphics processing units (GPUs) architecture, parallel computing using GPU. General purpose computing using GPU, CUDA and OpenCL technologies.

Limits and costs of parallel programming. Distributed systems: distributed models, communication and

synchronisation in distributed systems, distributed file systems (GoogleFS, HDFS, HFS). High-performance and high-throughput computing using distributed clusters and supercomputers. Introduction of the MapReduce model.

Data-driven parallel computing. Transactions: properties of transactions, lock methods,

distributed transactions, dead lock.

Temeljni literatura in viri / Readings: G. Coulouris, J. Dollimore, T. Kindberg: Distributed Systems: Concepts and Design, Fifth Edition, Addison Wesley Publishing

Company, USA, England, 2011. A. Grama, A. Gupta, G. Karypis, V. Kumar: Introduction to Parallel Computing: Design and Analysis of Algorithms, Second

Edition, Addison Wesley, New York, 2003. Anthony Williams: C++ Concurrency in Action, Practical Multithreading, Manning Publications, 2012. A. S. Tanenbaum, M. van Steen: Distributed Systems: Principles and Paradigms, Second Edition, Pearson Prentice Hall,

Upper Saddle River, NJ, USA, 2006. Michael J. Quinn: Parallel programming in C with MPI and OpenMP, McGraw-Hill Education Group, 2003.



Cilj predmeta je, da bodo študenti sposobni razumeti osnovne principe porazdeljenega in paralelnega računanja.

The objective of this course that students wiil be able to understand the basic principles of distributed and parallel computing.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben: izkazati znanje in uporabiti porazdeljene računalniške

sisteme in paralelne računalniške sisteme, izkazati razumevanje paralelnih programov in načrtovati

paralelni program, identificirati, opisati in analizirati situacije, kjer so potrebne

aktivnosti paralelnega in/ali porazdeljenega računanja.

Knowledge and understanding: On completion of this course the student will be able to: demonstrate knowledge and use of distributed computer

architectures and parallel computer architectures, demonstrate understanding and design of a parallel

program, identify, describe and analyse situations, which interfere

with activities of parallel and/or distributed computing. Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: ustni zagovor laboratorijskih vaj,

pisno izražanje pri pisnem izpitu. Uporaba informacijske tehnologije: iskanje informacij na

svetovnem spletu in uporaba programskih orodij za potrebe heterogenega procesiranja.

Reševanje problemov: načrtovanje in implementacija paralelnih programov.


expression at written examination. Use of information technology: web based information

search and use of software tools for heterogeneous computing.

Problem solving: design and implementation parallel programs.




lectures, lab work.



Assessment:


50 % 25 % 25 %


Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, jih nadomesti s pisnim izpitom v deležu 50%. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references: BOŠKOVIĆ, Borko, BREST, Janez. Protein folding optimization using differential evolution extended with local search and







UČNI NAČRT PREDMETA / SUBJECT SPECIFICATION Predmet: Platformno odvisen razvoj aplikacij Subject Title: Platform-Based Application Development



Letnik Year

Semester Semester





3 zimski winter


Predavanja Lectures

Seminar Seminar





30 3 42 105 6 Nosilec predmeta / Lecturer: Matej Črepinšek Jeziki / Languages:



Prerequisites:



Uvod: predstavitev predmeta, zgodovina razvoja platformno odvisnih aplikacij.

Pregled platform: splet, mobilne, industrijske in za igre. Primer arhitekture platforme: nivo aplikacij, nivo

aplikacijskega ogrodja, nivo knjižnic, nivo izvajalnega okolja, nivo jedra.

Življenjski cikel razvoja platformno odvisne aplikacije: osnove načrtovanja, uporaba razvojnih orodij, testiranje, vzdrževanje.

Načrtovanje izgleda: uporaba različnih kumunikacijskih gradnikov, povezovanje gradnikov.

Upravljanje in shranjevanje podatkov: shranjevanje ključ-vrednost, shranjevanje datotek, uporaba baze SQL.

Izbrani koncepti: namen, fragment, aktivnost, ponudniki vsebin, sprejemniki vsebin.

Izzivi pri mobilni in brezžični komunikaciji. Delo s senzorji: dotik, kompas, pospeškometer, GPS,

mikrofon, senzor svetlobe. Napredni pristopi k razvoju: načrtovalski vzorec MVC,

arhitekturni vzorec MVP. Razvoj heterogenih mobilnih aplikacij: pregled orodij in

njihove omejitve. Ostalo: varnost, testiranje, distribucija.

Introduction: overview of the subject, history of platform-based application development.

Overview of platforms: Web, Mobile, Industrial and Games. Example of platform architecture: application level,

application framework level, libraries level, runtime level and kernel level.

Platform-Based software development of the application life cycle: basic application design, developing tools, testing, maintenance.

Designing layout: usage of different communication components, binding components.

Data management and persistence: using key-value data, saving files, using SQL database.

Selected concepts: Intent, Fragment, Activity, Content providers, Broadcast receivers.

Challenges with mobility and wireless communication. Using sensors: touch, compass, accelerometer, GPS,

microphone, light sensor. Advanced topics: design pattern MVC, architectural pattern

MVP. Cross platform development: overview of tools and their

limitations. Other: security, testing, distribution.

2 / 3

Temeljni študijski viri / Textbooks: David S. Evans, Andrei Hagiu, Richard Schmalensee: Invisible Engines; The MIT Press, England; 2006. Trish Cornez, Richard Cornez: Android Programming Concepts Paperback, ZDA, 2015. Chris Stewart, Brian Hardy, Kristin Marsicano: Android Programming: The Big Nerd Ranch Guide (2nd Edition, Indianapolis

ZDA, 2015. Matt Neuburg: iOS 8 Programming Fundamentals with Swift: Swift, Xcode, and Cocoa Basics 1st Edition, ZDA, 2015.

Cilji:

Objectives:

Cilj predmeta je, da študentje osvojijo specifična znanja potrebna pri razvoju platformno odvisnih aplikacij. Združiti različna znanja drugih predmetov in jih uporabiti na drugačni razvijalski platformi. Analiza in uporaba ključnih funkcionalnosti aplikacijskih vmesnikov potrebnih za razvoj mobilne aplikacije. Poglobiti znanja in izboljšati spretnosti iz programiranja. Izdelati aplikacijo, ki zajema vse elemente tipične mobilne aplikacije. Delo z različnimi senzorji mobilnih naprav. Spodbuditi študente k kreativnemu razmišljanju.

The aim of the course is to give the students the specific knowledge needed for development of platform-based applications. Combine different skills from other courses and use them in a different developer platform. Use and analysis of the key functionality of application interfaces necessary for mobile applications. To improve knowledge and improve skills of programming. To develop an application that includes all the elements of typical mobile applications. Working with a variety of sensors, mobile devices. Encourage students to creative thinking.

Predvideni študijski rezultati: Intended learning outcomes: Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben: Ovrednotiti in uporabiti razvojno platformo. Načrtovanje in razvoj mobilnih aplikacij. Razširjeno znanje in izkušnje iz programiranja v

programskem jeziku Java. Uporabo senzorjev za obogatitev uporabniške izkušnje

mobilne aplikacije. Načrtovanje in izdelava mobilne aplikacije.

Knowledge and understanding: On completion of this course the student will be able to: Evaluate and use of the development platform. Designing and developing mobile applications. Advanced knowledge and experience of programming in

Java programming language. Using sensors to enrich the user experience of mobile

applications. Designing and development of mobile applications.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: podajanje opisa težav pri

razvoju programske opreme, zagovor vaj ter pisno izražanje pri izpitu.

Uporaba informacijske tehnologije: uporaba sodobnih naprav in razvojnih orodij, uporaba programskih jezikov in analiza podatkov.

Reševanje problemov: definiranje algoritmov, razhroščevanje, iskanje novih načinov uporabe mobilnih naprav.

Transferable/Key skills and other attributes: Communication skills: to describe problems and errors

during software development, oral defence of practical exercises and manner of expression at written examination.

Use of information technology: the use of modern digital devices and developing tools, programming and data analyse.

Problem solving: defining algorithms, debugging, search for new ways to use mobile devices.



predavanja, seminarske vaje laboratorijske vaje, samostojno delo.

lectures, seminar work lab work, individual work.



Assessment methods:

laboratorijske vaje, 1. vmesni izpit, 2. vmesni izpit.

50 25

25

lab work, 1st midterm examination, 2nd midterm examination.

3 / 3

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 50 %. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50 %.. Reference nosilca / Lecturer's references: 1. VEČEK, Niki, MERNIK, Marjan, ČREPINŠEK, Matej. A chess rating system for evolutionary algorithms : a new method for the

comparison and ranking of evolutionary algorithms. Information sciences, ISSN 0020-0255. [Print ed.], Sep. 2014, vol. 277, str. 656-679.

2. ČREPINŠEK, Matej, LIU, Shih-Hsi, MERNIK, Luka, MERNIK, Marjan. Is a comparison of results meaningful from the inexact replications of computational experiments?. Soft computing, ISSN 1432-7643. [Print ed.], Jan. 2016, vol. 20, no. 1, str. 223-235.

3. ČREPINŠEK, Matej, LIU, Shih-Hsi, MERNIK, Marjan. Replication and comparison of computational experiments in applied evolutionary computing : common pitfalls and guidelines to avoid them. Applied soft computing, ISSN 1568-4946. [Print ed.], June 2014, vol. 19, str. 161-170.


Predmet: Podjetništvo

Course title: Entrepreneurship



Letnik Academic

year

Semester Semester





3. poletni Spring

Vrsta predmeta / Course type Izbirni/Elective


Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 15 45 3

Nosilec predmeta / Lecturer: Dijana Močnik

Jeziki / Languages:


slovenski / Slovene



Prerequisits:



Sodobni svet podjetništva. Značilnosti podjetnika: značilnosti uspešnega podjetnika,

dejavniki uspeha. Ustanovitev podjetja ali nakup obstoječega podjetja. Razvijanje poslovnega načrta. Temeljni ekonomski koncepti. Viri začetnega kapitala: osnovne vrste kapitala, viri

financiranja. Izbira pravno organizacijske oblike podjetja: individualno

lastništvo, partnerstvo, delniška družba. Proces upravljanja: kaj je upravljanje, temeljne funkcije

The contemporary world of entrepreneurship. Characteristics of an entrepreneur: characteristics for a

successful entrepreneur, success factors. Starting a new firm or buying an existing business. Developing a business plan. Basic economic concepts. Sources of start-up capital: basic types of capital, sources

of capital. Selecting the legal form for an organization: the

proprietorship, the partnership, the corporation. Managerial process: what is management, basic

upravljanja, upravljanje rastočega podjetja, upravljanje celovite kakovosti.

Notranje podjetništvo. Mednarodno podjetništvo. Nasledstvo in nadaljevanje poslovanja – vidik družinskega

podjetja: problemi nasledstva, ključni dejavniki pri nasledstvu, oblikovanje nasledstvene strategije, strategija žetve.

Prenehanje podjetja.

managerial functions, managing the growing small business, total quality management.

Intrapreneurship. International entrepreneurship. Management succession and continuity – a family business

perspective: the succession issues, key factors in succession, developing a succession strategy, the harvest strategy.

Ending the venture. Temeljni literatura in viri / Readings: D. Močnik: Uvod v podjetništvo za inženirje, Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko,

Maribor, učbenik v pripravi. M. Ruzzier, B. Antončič, T. Bratkovič, R.D. Hisrich, Podjetništvo, Društvo za akademske in aplikativne raziskave, Koper, 2008. R. D. Hisrich, M. P. Peters, D. A. Shepherd, Entrepreneurship, 7th edition, McGraw-Hill Education Singapore, Singapore, 2008.



Cilj predmeta je študenta vpeljati v podjetniško ekonomijo, ki se ukvarja z ustvarjanjem, ocenjevanjem, rastjo in delovanjem novih in nastajajočih podjemov.

The objective of this course is to introduce the students to an entrepreneurial economy that deals with the creation, assessment, growth development, and operation of new and emerging ventures.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben razumeti sodobni svet podjetništva, razložiti dejavnike uspeha in poraza novih podjetij, razpravljati o različnih načinih, kako lahko posamezniki

postanejo podjetniki – z nakupom obstoječega podjetja, z ustanovitvijo novega podjetja ali z nakupom franšize,

razpravljati o specifičnih problemih novih podjetij: financiranje, lokacija, ureditev in pravna oblika organizacije,

razpravljati o upravljanju podjetja: planiranje, organiziranje, vodenje in kontrola,

razumeti dele poslovnega načrta, usmeriti se na etični vidik podjetništva za razvoj bolj

socialno zavedajočega se podjetja.

Knowledge and understanding: On completion of this course the student will be able to understand the contemporary world of entrepreneurship, explain the factors that bring success and failure to new

enterprises, discuss the various ways individuals can get into small

business – by buying an ongoing concern, by starting a business from scratch or by purchasing a franchise,

discuss the special problems faced by new businesses: financing, location, layout, and legal forms of organization,

discuss how to manage an enterprise: planning, organizing, directing, and controlling,

understand the parts of a business plan, focus on the ethical perspective that entrepreneurs need to

take in developing a more socially conscious approach to business.


izpitu, ustno izražanje pri predstavitvi poročila intervjuja s podjetnikom, ustno izražanje pri predstavitvi poročila o intervjuju s podjetnikom, ustno izražanje v razgovoru s podjetnikom kot tudi pri aktivnem sodelovanju na seminarskih vajah.

Uporaba informacijske tehnologije: iskanje informacij in podatkov na svetovnem spletu in v drugih medijih, uporaba specifičnih programskih orodij.

Reševanje problemov: reševanje problemov realnih podjetij s področja podjetništva, ki se proučujejo kot študije primerov na vajah.

Organizacijske sposobnosti: sposobnosti organiziranja srečanja s podjetnikom za uspešno izvedbo intervjuja.

Transferable/Key skills and other attributes: Communication skills: manner of expression at written

exam, oral expression at public defence of the report as well as in discussion with an entrepreneur and active cooperation in solving different problems at tutorials.

Use of information technology: searching of information and data on the Web and in other media, using of specific software tools.

Problem solving: solving entrepreneurial problems of real firms that are studied as case studies at tutorials.

Organizational skills: capability of organizing the meeting with an entrepreneur to successfully complete an interview.



predavanja, seminarske vaje, intervju ali seminarska naloga.

lectures, tutorial, interview or seminar work.



Assessment:

opravljeno seminarsko delo, pisni izpit.

20% 80%

completed seminar work, written exam.

Reference nosilca / Lecturer's references: MOČNIK, Dijana, ŠIREC, Karin. Determinants of a fast-growing firm's profits : empirical evidence for Slovenia. Analele

ştiinţifice ale Universitæaţii "Al.I. Cuza" din Iaşi, Ştiinţe economice, ISSN 0379-7864. [Print ed.], 2015, vol. 62, no. 1, str. 37-54. http://saaic.feaa.uaic.ro/index.php/saaic/article/view/147/pdf_62, doi: 10.1515/aicue-2015-0003. [COBISS.SI-ID 18590998], [Scopus do 28. 12. 2018: št. citatov (TC): 1, čistih citatov (CI): 1]

ŠIREC, Karin, MOČNIK, Dijana. A gender perspective of Slovenian high-growth firmʼs profitability. International journal of entrepreneurship & small business, ISSN 1476-1297, 2016, vol. 27, no. 2/3, str. 247-261. [COBISS.SI-ID 12170780], [SNIP, Scopus do 1. 3. 2019: št. citatov (TC): 2, čistih citatov (CI): 2]

MOČNIK, Dijana, ŠIREC, Karin. Growth aspirations of early-stage entrepreneurs : empirical investigation of South-Eastern and Western European countries. Journal of East European management studies, ISSN 0949-6181, 2016, vol. 21, no. 3, str. 298-317. http://www.hampp-verlag.de/hampp_e-journals_JEMS.htm, doi: 10.1688/JEEMS-2016-Mocnik. [COBISS.SI-ID 12213788], [JCR, SNIP, WoS do 30. 11. 2017: št. citatov (TC): 2, čistih citatov (CI): 0, Scopus do 27. 2. 2016: št. citatov (TC): 0, čistih citatov (CI): 0]

ŠIREC, Karin, MOČNIK, Dijana. Indicators of Start-ups´ adoption of blue ocean strategy : empirical evidence for the Danube region. International Review of Entrepreneurship, 2016, vol. 14, iss. 3, str. [1-24]. http://www.senatehall.com/entrepreneurship?article=550. [COBISS.SI-ID 12510748], [WoS do 4. 7. 2017: št. citatov (TC): 0, čistih citatov (CI): 0]

PIŽMOHT, Franja, GYÖRKÖS, József, MOČNIK, Dijana. Financial evaluation of the convergent technologies development in a digital economy. Kybernetes : the international journal of systems & cybernetics, ISSN 0368-492X, 2017, vol. 46, iss. 8, str. 1425-1451, doi: 10.1108/K-03-2017-0090. [COBISS.SI-ID 20683542], [JCR, SNIP, WoS do 14. 4. 2019: št. citatov (TC): 2, čistih citatov (CI): 2, Scopus do 1. 3. 2019: št. citatov (TC): 2, čistih citatov (CI): 2]

UČNI NAČRT PREDMETA / COURSE SYLLABUS Predmet: Preizkušanje računalniške opreme Course title: Computer Equipment Testing




Semester Semester





3. zimski Autumn


Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vaje work



ECTS

30 45 105 6 Nosilec predmeta / Lecturer: Danilo Korže Jeziki / Languages:



Prerequisits:



Uvod: pomen preizkušanja računalniške opreme, tipični faktorji kvalitete računalniških programov, nivoji preizkušanja, analiza tveganja, vrste preizkušanj.

Programske napake: definicija, vrste napak, kategorizacija napak.

Pristopi k preizkušanju: primer testne metodologije (STEP), načrtovanje glavnega testnega plana.

Preizkusne metode in tehnike: življenjski cikel programske opreme in preizkušanja, delitev preizkusnih metod, preizkušanje s pregledovanjem, preizkušanje zahtev, preizkušanje zasnove obdelav, metrike pri preizkušanju.

Strukturno in funkcionalno preizkušanje: strukturno preizkušanje in primeri, preizkušanje skladnosti z dogovori in standardi, funkcionalno preizkušanje in primeri, avtomatski regresijski testi in testi sprejemljivosti.

Primer testnega načrta: upravljanje projekta preizkušanja, načini upravljanja z napakami, analiza trendov, najpogostejše napake pri testiranju.

Primeri preizkušanja programske opreme: preizkušanje aplikacij na spletu, preizkušanje podatkovnih baz, preizkušanje uporabniških vmesnikov.

Introduction: meaning of computer equipment testing, typical factors of computer programme quality, levels of testing, risk analysis, types of testing.

Programming errors: definition, error types, categorization of errors.

Approaches by testing: example of testing methodology (STEP), design of master test plan.

Testing methods and techniques: life cycle of software and testing, categorization of testing methods, testing reviews, testing requirements, design testing, metrics by testing.

Structural and functional testing: structural testing and

examples, testing of accordance with agreements and standards, functional testing and examples, automated regression tests and acceptance testing.

Example of testing plan: management of testing project, manners of errors management, trend analysis, most frequent errors by testing.

Examples of software testing: testing applications on Web, database testing, user interface testing.

Preizkušanje strojne opreme: diagnostika, življenjski cikel strojne opreme in diagnostika, pravila pri snovanju preizkusov, vrste strojnih diagnostik.

Načrtovanje diagnostike: zasnova za preizkušanje, modeli napak, tabela okvar, preizkusni vektorji.

Diagnostične metode in orodja: vgrajeni testi, signaturna analiza, preizkusni vzorci, vgrajeni samopreizkusi.

Preizkusna orodja in aktualne diagnostike: delitev, analogni merilniki, merilniki za delo z digitalnimi vezji.

Primeri preizkušanja strojne opreme: preizkušanje matične plošče, preizkušanje delovnega pomnilnika, preizkušanje sekundarnih pomnilnikov, preizkušanje video grafičnih naprav.

Hardware testing: diagnostics, hardware life cycle and diagnostics, rules by test design, types of hardware diagnostics.

Diagnostics design: design for test, model of errors, fault table, testing vectors.

Diagnostics methods and tools: built-in tests, signature analysis, scan patterns, built-in self-tests.

Testing tools and current diagnostics: categorization, analogue meters, meters for work with digital circuits.

Examples of hardware testing: motherboard testing, main memory testing, secondary memory testing, video graphical devices testing.

Temeljni literatura in viri / Readings: D. Zazula: Preizkušanje računalniške opreme, Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko,

Maribor, 2006. R. E. Howland: Computer hardware diagnostics for engineers, McGraw-Hill, New York, 1995. R. D. Craig, S. P. Jaskiel: Systematic Software Testing, Artech House, Boston, 2002. R. Patton: Software testing, Second Edition, Sams Publishing, Indianapolis, 2006. H. Q. Nguyen, B. Johnson, M. Hackett: Testing applications on the Web: Test planning for mobile and internet-based systems,

Second Edition, John Wiley & Sons, New York, 2003. Cilji in kompetence:


Cilj predmeta je dati študentom poglobljeno znanje o preizkušanju računalniške opreme.

The objective of this course is to give students a profound knowledge about computer equipment testing.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben izkazati znanje in razumevanje postopkov preizkušanja

računalniške opreme, razčleniti problem preizkušanja in načrtovati, sestaviti in

uporabiti ustrezen preizkusni postopek bodisi za programsko, kakor tudi za strojno opremo,

oceniti rezultate preizkušanja ter napovedati primernost preizkušane računalniške opreme za produkcijsko delovanje.

Knowledge and understanding: On completion of this course the student will be able to demonstrate knowledge and understanding of computer

equipment testing procedures, break down a problem of testing and design, construct and

apply a suitable testing procedure either for software as for hardware,

assess testing results and predict a suitability of tested computer equipment for production operating .

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: pisni zagovor laboratorijskih vaj,

pisanje strokovnega poročila pri projektu, pisno izražanje pri pisnem izpitu.

Uporaba informacijske tehnologije: uporaba programskih orodij za preizkušanje računalniške opreme.

Organizacijske spretnosti: izdelava in vodenje preprostega projekta preizkušanja.

Reševanje problemov: načrtovanje primerne testne metode za računalniško opremo.

Delo v skupini: delo v skupini pri projektu.

Transferable/Key skills and other attributes: Communication skills: written lab work defence, writing of

professional report at project, manner of expression at written examination.

Use of information technology: use of software tools for equipment testing.

Organization skills: design and coordination of simple testing project.

Problem solving: design of suitable testing method for computer equipment.

Group work: group work at project. Metode poučevanja in učenja:


predavanja, seminarske vaje, projekt, laboratorijske vaje, reševanje domačih nalog.

lectures, tutorials, project, lab work, homework assignments.



Assessment:


50 % 25 % 25 %.


Opomba: V kolikor študent ni uspešno opravil obeh vmesnih izpitov, jih nadomesti s pisnim izpitom v deležu 50%. Note: If a student has not completed both midterm exam, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references: KORŽE, Danilo, VESEL, Aleksander. Packing coloring of generalized Sierpiński graphs. Discrete mathematics

and theoretical computer science, ISSN 1365-8050, 2019, vol. 21, no. 3, str. 1-18. https://dmtcs.episciences.org/5178/pdf. [COBISS.SI-ID 22126870]

KORŽE, Danilo, VESEL, Aleksander. (d,n)-packing colorings of infinite lattices. Discrete applied mathematics, ISSN 0166-218X. [Print ed.], March 2018, vol. 237, str. 97-108, doi: 10.1016/j.dam.2017.11.036. [COBISS.SI-ID 21067542]

KORŽE, Danilo, VESEL, Aleksander. On the packing chromatic number of square and hexagonal lattice. V: Bled'11 - 7th Slovenian International Conference on Graph Theory, 19-25 June 2011, Bled, Slovenia. Ars mathematica contemporanea : special issue Bled'11, (Ars mathematica contemporanea, ISSN 1855-3966, Vol. 7, no. 1, 2014). Ljubljana: DMFA Slovenije, 2014, str. 13-22. http://amc-journal.eu/index.php/amc/article/view/255/224. [COBISS.SI-ID 16791897]

KORŽE, Danilo, VESEL, Aleksander. A note on the independence number of strong products of odd cycles. Ars combinatoria, ISSN 0381-7032, 2012, vol. 106, str. 473-481. [COBISS.SI-ID 16138006]

KORŽE, Danilo. Zbirka izpitnih nalog iz optimizacijskih problemov : e-učno gradivo. [Maribor]: Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko, 2012. 24 str. http://storm.uni-mb.si/eZbirke/KORZEZbirka_izpitnih_nalog_iz_operacijskih_problemov.pdf. [COBISS.SI-ID 16261142]


Predmet: Računalniška grafika

Course title: Computer Graphics



Letnik Academic

year

Semester Semester





3. zimski Autumn



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6


Jeziki / Languages:


slovenski / Slovene



Prerequisites:

Ni pogojev. None.

Vsebina:


Uvod: definicija računalniške grafike, definicija obdelave in analize slik, zgodovinski oris, uporaba računalniške grafike, viri v računalniški grafiki.

Osnove OpenGL: grafični cevovod, senčilniki. Geometrijske transformacije: 2D geometrijske

transformacije, homogene koordinate, kompozicija 2D transformacij, 3D geometrijske transformacije, kompozicija 3D transformacij, inverzne transformacije.

Projekcije: perspektivne projekcije, vzporedne projekcije.

Odstranjevanje zakritih ploskev.

Introduction: computer graphics definition, definition of image processing and analysis, history, computer graphics application, references in computer graphics.

OpenGL basics: graphics pipeline, shaders. Geometrical transformations: 2D geometrical transfor-

mations, homogeneous coordinates, composition of 2D transformations, 3D geometrical transformations, composition of 3D transformations, inverse transformations.

Projections: perspective projections, parallel projections. Hidden surface removal. Rasterization: scanline conversion of lines and circles,

Rasterizacija: prebirna pretvorba daljic in krožnic, antialias.

Lokalni osvetlitveni modeli: Gouraudovo senčenje, Phongovo senčenje.

Teksture: preslikava tekstur, preslikava izboklin, preslikava odmikov, preslikava okolja, sence.

Globalni osvetlitveni modeli: algoritem sledenja žarku, tehnike in strukture delitve prostora.

Krivulje: želene lastnosti krivulj, krivulje B-zlepkov, Bézierove krivulje, krivulje NURBS.

Ploskve: ploskve B-zlepkov, Bézierove ploskve, ploskve NURBS.

Barve: človeški vid, določevanje barv in barvni modeli, uporaba barv.

Grafična strojna oprema: arhitektura grafičnega procesorja, splošnonamensko računanje na grafičnih procesorjih, CUDA, OpenCL.

antialiasing. Local shading models: Gouraud shading, Phong shading. Textures: texture mapping, bump mapping, displacement

mapping, environment mapping, shadows. Global illumination models: ray-tracing algorithm, space

subdivision techniques and structures. Curves: desired curve properties, B-spline curves, Bézier

curves, NURBS curves. Surfaces: B-spline surfaces, Bézier surfaces, NURBS

surfaces. Colours: human vision, colour determination and colour

models, use of colours. Graphical hardware: graphics processor architecture,

general purpose computation on graphics processors, CUDA, OpenCL.

Temeljni literatura in viri / Readings: N. Guid: Računalniška grafika, učbenik, Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko, Maribor,

2001. D. Hearn, M. P. Baker, W. Carithers: Computer graphics with Open GL, Prentice Hall, Upper Saddle River, 2010. R. S. Wright, B Lipchak: OpenGL Superbible, 3. izdaja, Sams Publishing, Indianapolis, 2005.



Cilj predmeta je seznaniti študente s strukturo sodobnega grafičnega cevovoda. Študenti bodo podrobneje spoznali delovanje posameznih stopenj cevododa in se naučili uporabe OpenGL za implementacijo preprostih grafičnih aplikacij,

The objective of this course is to acquaint the students with the structure of a modern graphics pipeline. The students will learn about the detailed operation of individual pipeline stages and the use of OpenGL for implementing simple graphical applications.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben opisati strukturo sodobnega grafičnega cevovoda, razumeti temeljne koncepte prebirne pretvorbe grafičnih

gradnikov, 2D in 3D geometrijskih transformacij, projekcij, odstranjevanja zakritih ploskev, lokalnih in globalnih osvetlitvenih modelov in barvnih modelov,

našteti in primerjati tehnike za tvorbo 3D krivulj in ploskev, uporabiti standard OpenGL za implementacijo preproste

grafične aplikacije, zgraditi preprost osvetlitveni model.

Knowledge and understanding: On completion of this course the student will be able to describe the structure of a modern graphics pipeline, understand the basic concepts of scan conversion of

graphical primitives, 2D and 3D geometrical transformations, projections, hidden-surface removal, local and global illumination models, and colour models,

describe and compare the techniques for 3D curve and surface creation,

use the OpenGL standard for implementing a simple graphical application,

construct a simple illumination model.


pisno izražanje pri projektu. Uporaba informacijske tehnologije: pisanje računalniških

programov, uporaba programskih orodij za grafične aplikacije.

Spretnosti računanja: reševanje računskih problemov pri domačih nalogah.

Reševanje problemov: izvedba preprostih grafičnih aplikacij.


expression at project. Use of information technology: writing computer programs,

use of software tools for graphical applications. Calculation skills: solving calculating problems in homework

assignments. Problem solving: construction of simple graphical

applications.

Metode poučevanja in učenja: Learning and teaching methods: predavanja, seminarske vaje, laboratorijske vaje, projekt

lectures, tutorials, lab work, project



Assessment:

laboratorijske vaje 1. vmesni pisni izpit, 2. vmesni pisni izpit.

50 25 25








UČNI NAČRT PREDMETA / COURSE SYLLABUS Predmet: Snovanje računalniških in digitalnih sistemov Course title: Computer and Digital Systems Engineering




Semester Semester





3. zimski

Autumn


Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vaje work



ECTS

30 45 105 6 Nosilec predmeta / Lecturer: Aleš Holobar Jeziki / Languages:



Prerequisits:

Ni pogojev. None.

Vsebina:


Uvod: razvoj digitalnih vezij, razvojna orodja, programirljiva vezja in jeziki (VHDL).

Snovanje sistemov – povezovanje komponent: sistemska vodila in njihove lastnosti, razvoj tehnologije in vodil, usklajeno delovanje sistemov (princip gospodarja in sužnjev), naslavljanje in naslovna logika.

Gradnja naslovne logike: razdelitev naslovnega prostora in naslovno dekodiranje, izvedba z diskretnimi logičnimi elementi, gradnja s programiranimi logičnimi elementi

Sklop procesor-pomnilnik: sinhroni in asinhroni principi usklajenega delovanja mikroračunalniških komponent (branje, pisanje).

Povezovanje procesorja z vhodno-izhodnimi krmilniki: prekinitveno delovanje, medračunalniške komunikacije (zaporedni in vzporedni prenos), lastnosti komunikacijskih linij in hitrosti prenosov (simetrični, asimetrični), standardizirani komunikacijski protokoli, fizični in podatkovni nivo (RS-232, RS-485, I2C, SPI, UART,

Introduction: digital circuits development, development tools, programmable chips and languages (VHDL).

Computer system engineering–component interconnection: system bus and its properties, development of bus technologies, system operation control (the principle of master and slaves), addressing and address logic.

Address logic design: address space mapping and address decoding, design with discrete logic elements, address logic based on programmed logic arrays.

Design of processor-memory interconnections: synchronous and asynchronous principles of microelectronic component operation (read, write).

Processor and input-output controllers: interrupt-driven operation, intersystem communications (serial and parallel circuits), communication lines properties and the speed of data transfer (symmetric, asymmetric), standardized communication protocols, physical and data level (RS-232, RS-485, I2C, SPI, UART, Ethernet, USB).

ethernet, USB). Računalniški sistemi z analognimi moduli: A/D in D/A

pretvorniki, dodatna analogna vezja (aktivni filtri, ojačevalniki), električna kompatibilnost digitalnih in analognih modulov, posebnosti usklajene gradnje.

Serijska proizvodnja digitalnih in računalniških sistemov: razvoj testnih postopkov in naprav.

Computer systems comprising analogue circuits: A/D and D/A converters, auxiliary analogue circuits (active filters, amplifiers), electrical compatibility of digital and analogue modules, rules for such design.

Mass production of digital and computer systems: development of testing procedures and devices.

Temeljni literatura in viri / Readings: R. Tocci, N. Widmer, G. Moss: Digital Systems, Pearson, 2014. B. C. Readler: Vhdl By Example. Lulu Enterprises Inc. 2014. K. L. Short : VHDL for Engineers, Pearson Education, Inc., Prentice Hall, 2009. D. M. Harris, S. L. Harris: Digital design and computer architecture, Elsevier : Morgan Kaufmann Publishers, 2007. D. Zazula: Preizkušanje računalniške opreme, Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko,

Maribor, 2006. R. H. Katz, G. Borriello: Contemporary Logic Design, Prentice Hall, Upper Saddle River, 2004.



Cilj predmeta je uvesti študente v postopke načrtovanja in gradnje in preizkušanja računalniških sistemov in doseči, da jih bodo razumeli in znali uporabiti in povezati različne računalniške sklope.

The objective of this course is for the students to understand computer systems design, construction and testing, and to use and integrate different computer modules.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben izkazati znanje in razumevanje osnovnih načinov za

snovanje računalniških sklopov, obvladovati življenjski ciklus računalniške opreme od

postavljanja zahtev, prek razvoja in proizvodnje do servisiranja,

načrtovati in izdelovati preprostejše testne naprave in postopke ter programirati logična vezja.

Knowledge and understanding: On completion of this course the student will be able to demonstrate knowledge and understanding of the basics of

computer engineering techniques, cope with the life cycle of computer equipment starting from

requirements analysis, to the development and production, to final field-servicing,

design and build simpler test beds and algorithms, as well as program logic circuits.


priprava in javna predstavitev poročila o študentskem projektu, ustni izpit.

Uporaba informacijske tehnologije: uporaba programskih orodij in naprav za razvoj in preizkušanje računalniških in digitalnih vezij.

Delo v skupini: skupinsko delo v študentskem projektu. Reševanje problemov: načrtovanje in izvedba

študentskega projekta, sodelovanje z industrijskimi partnerji.

Transferable/Key skills and other attributes: Communication skills: oral lab work defence, preparation

and presentation of the student project report, oral examination.

Use of information technology: use of special software tools and devices for the development and tests of computer and digital circuits.

Team work: team execution of student projects. Problem solving: designing and implementing of student

projects, co-operation with industrial partners.



predavanja, seminarske vaje, projektno delo, laboratorijske vaje, domače naloge.




Assessment:

Sprotni način laboratorijske vaje, 1. vmesni izpit, 2. vmesni izpit

Delež 50

25

25

Constant assessment methods lab work, 1st midterm examination, 2nd midterm examination,

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti z ustnim izpitom v deležu 50 %. Note: If a student has not completed both midterm exams, he replaces them with an oral exam in the weight of 50 %. Reference nosilca / Lecturer's references: FARINA, Dario, JIANG, Ning, REHBAUM, Hubertus, HOLOBAR, Aleš, GRAIMANN, Bernhard, DIETL, Hans, ASZMANN,

Oskar. The extraction of neural information from the surface EMG for the control of upper-limb prostheses : emerging avenues and challenges. IEEE transactions on neural systems and rehabilitation engineering, 2014, vol. 22, no. 4, str. 797-809, doi: 10.1109/TNSRE.2014.2305111. [COBISS.SI-ID 18018070]

FARINA, Dario, HOLOBAR, Aleš. Human-machine interfacing by decoding surface electromyogram. IEEE signal processing magazine, ISSN 1053-5888. [Print ed.], Jan. 2015, vol. 32, no. 1, str. 115-120, doi: 10.1109/MSP.2014.2359242. [COBISS.SI-ID 18364950]

GLASER, Vojko, HOLOBAR, Aleš. Motor unit identification from high-density surface electromyograms in repeated dynamic muscle contractions. IEEE transactions on neural systems and rehabilitation engineering, ISSN 1534-4320. [Print ed.], 17 Dec. 2018, doi: 10.1109/TNSRE.2018.2885283. [COBISS.SI-ID 21986838]

HOLOBAR, Aleš, MINETTO, Marco A., FARINA, Dario. Accurate identification of motor unit discharge patterns from high-density surface EMG and validation with a novel signal-based performance metric. Journal of neural engineering, ISSN 1741-2560, Feb. 2014, vol. 11, no. 1, str. 1-11, doi: 10.1088/1741-2560/11/1/016008. [COBISS.SI-ID 17445654]

GLASER, Vojko, HOLOBAR, Aleš, ZAZULA, Damjan. Real-time motor unit identification from high-density surface EMG. IEEE transactions on neural systems and rehabilitation engineering, ISSN 1534-4320. [Print ed.], Nov. 2013, vol. 21, no. 6, str. 949-958, doi: 10.1109/TNSRE.2013.2247631. [COBISS.SI-ID 17016854]

UČNI NAČRT PREDMETA / SUBJECT SPECIFICATION Predmet: Sociološki in poklicni vidiki Subject Title: Social and professional issues



Letnik Year

Semester Semester





3. Poletni

Summer


Predavanja Lectures

Seminar Seminar





30 1 14 135 6 Nosilec predmeta / Lecturer: Peter Kokol Jeziki / Languages:



Prerequisites:



Uvod: vpliv IKT na družbo, družbene skupine, posameznike in obratno,

Informacijska družba Filozofska pojmovanja računalništva in tehnologije Sociološki vidiki računalništva, Računalništvo in digitalna razmejitev družbe (glede

na spol, premoženje, starost, ipd) Sociologija kibernetskega prostora Strokovna in etična odgovornost, poklicni etični

kodeksi, informacijska etika Reševanje problemov in ustvarjalno razmišljanje Vodenje inovacijskega procesa Intelektualna lastnina Zasebnost in državljanske svoboščine: etični in pravni

vidik zasebnosti računalniških informacij, zasebnost in svoboda informacij, cenzura.

Računalniški kriminalno pravo Računalništvo in odprta družba.

Introduction: the influence of ICT on the society and vice versa

Information society The philosophy of information and communication

technologies, Digital divide (gender issues,rich and poor, old and

young) The sociology of cyberspace Professional and ethic responsibility, professional

codexes, information ethics Problem solving and creative thinking Management of innovation process Intellectual property Privacy and freedom: law, ethics, freedom of

information, census Computer crime, working law Openness and information and communication

technologies Temeljni študijski viri / Textbooks: R. S. Rosenberg: Social Impact of Computers, Academic Press, 2nd edition, 1997. B. Pretnar: Intelektualna lastnina v sodobni konkurenci in poslovanju, GV Založba, Ljubljana, 2002. B. Likar: Uspeti z idejo, Korona Plus, Ljubljana, 2002. M. J, Quinn, Ethics for the information age, 7th Edition,, Pearson, 2016. D. Morley, Understanding Computers in a Changing Society, 6th Edition Cengage Learning, 2014.

Cilji:

Objectives:

Razumeti Friedmanov teorem »računalnik+človek > človek«. Razumeti vlogo računalništva in računalničarjev v družbi. Razumeti inovacijski proces, njegove rezultate, ter njihovo uporabo. Analiziratia družbene, poklicne, kulturne, filozofske, etične, moralne, pravne, politične in ekonomske vidike računalništva. Pomembnost vseživljenskega učenja.

To understand the Friedman theorem: computer+man › man. To understand the role of ICT and the role of a computer scientist in society. To understand innovation process, it’s results and their usage. To be able to present and analyse the social, professional, cultural, philosophical, ethics, economic and other aspects of ICT and computer science and applay them in practice. The importance of lifelong learning.



Znanje in razumevanje: Razumeti Friedmanov teorem »računalnik+človek>človek« v smislu pozitivnih in negativni posledic hitrega razvoja IKT na človeštvo v okvirih etični in poklinih norm.

Knowledge and understanding: To understand the Friedman theorem: »computer+man>man«.in the sense of positive and negative effects of ICT on humanity in the scope of ethical standards.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: predstaviti vlogo računalničarja in IKT v sodobni družbi. .Razumevanje etičnih in poklicnih naćel ter jih uporabiti v praksi. Študenti bodo razvili sposobnost postavljanja resnih vprašanj o socialnem vplivu računalništva in ocenjevanju predlaganih odgovorov na ta vprašanja. Študenti bodo lahko predvideli vpliv uvedbe določenega izdelka v določeno okolje. Ali bo ta izdelek izboljšal ali poslabšal kakovost življenja?

Transferable/Key skills and other attributes: Communication skills: to present the role of ICT and the computer scientist in modern society. Understanding of ethical and professional principles and how to apply them in practice. Students will develop the ability to ask serious questions about the social impact of computing and to evaluate proposed answers to those questions. Students will be able to anticipate the impact of introducing a given product into a given environment. Will that product enhance or degrade the quality of life?.







Assessment methods:

opravljen projekt, 1. vmesni pisni izpit 2. vmesni pisni izpit

50 % 25 % 25 %

completed project, 1st midterm written exam 2nd midterm written exam

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 50 %. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50 Reference nosilca / Lecturer's references: KOKOL, Peter, POHOREC, Sandi, ŠTIGLIC, Gregor, PODGORELEC, Vili. Evolutionary design of decision trees for medical

application. Wiley interdisciplinary reviews, Data mining and knowledge discovery. [Print ed.], May 2012, vol. 2, iss. 3, str. 237-254, doi: 10.1002/widm.1056. [COBISS.SI-ID 15997462], [JCR, SNIP]

BLAŽUN, Helena, BOBEK, Samo, KOKOL, Peter, JAVORNIK KREČIČ, Marija. Attitudes of active older Internet users towards online social networking. Computers in human behavior, ISSN 1873-7692. [Online ed.], feb. 2016, vol. 55, part A, str. 230-241, graf. prikazi. http://www.sciencedirect.com/science/article/pii/S074756321530145X, doi: 10.1016/j.chb.2015.09.014. [COBISS.SI-ID 84085249], [JCR, SNIP]

KOKOL, Peter, BLAŽUN, Helena, ŽELEZNIK, Danica. Visualising nursing data using correspondence analysis. Nurse researcher, ISSN 2047-8992, sep. 2016, no. 1, vol. 24, str. 38-40, graf. prikazi, doi: 10.7748/nr.2016.e1441. [COBISS.SI-ID 88885505], [SNIP]

KOKOL, Peter, BLAŽUN, Helena, ŽELEZNIK, Danica, VOŠNER, Janez, SARANTO, Kaija. Bibliometric patterns of research literature production on nursing informatics competence. The Journal of nursing education, ISSN 0148-4834, 2015, vol. 54, no. 10, str. 565-571, graf. prikazi, doi: 10.3928/01484834-20150916-04. [COBISS.SI-ID 84086273], [JCR, SNIP]

KOKOL, Peter, ZAVRŠNIK, Jernej, ŽELEZNIK, Danica, BLAŽUN, Helena. Creating a self-plagiarism research topic typology through bibliometric visualisation. Journal of academic ethics, ISSN 1572-8544, 22. mar. 2016, [10] str., doi: 10.1007/s10805-016-9258-6. [COBISS.SI-ID 86374145], [SNIP]


Predmet: Uvod v računalniški vid in razpoznavanje vzorcev

Course title: Introduction to the Computer Vision and Pattern Recognition



Letnik Academic

year

Semester Semester





3. poletni Spring



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

30 45 105 6

Nosilec predmeta / Lecturer: Božidar Potočnik

Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Kamera: kamera na luknjico, model CCD kamere, tehnologije za zajem slik, parametri in kalibracija kamere.

Filtriranje in izboljšava slik: odstranjevanje šuma. Postopki za sledenje gibanja: model zaporedja slik in

gibanja, slika razlik in sledenje gibanja, optični pretok in sledenje gibanja, primeri.

Ujemanje šablon v 2D prostoru: statistično ujemanje, strategije ujemanja.

Geometrija več pogledov: dva in trije pogledi, stereo

Camera: pinhole camera, model of CCD camera, image acquisition technologies, parameters and calibration of camera.

Filtering and image enhancement: noise suppression. Procedures for motion tracking: model of image sequence

and motion, difference image and motion tracking, optical flow and motion tracking, examples.

Template matching in 2D space: statistical matching, matching strategies.

Geometry of multiple views: two and three views,

pogled, fuzija pogledov, uporaba več kamer. Uvod v razpoznavanje vzorcev: osnovni pojmi, model

razpoznavalnika vzorcev, zapis preprostih vzorcev z množico značilk, določanje značilk, spoznavanje področja uporabe (rojenje), razvrščanje vzorcev, preizkušanje razpoznavalnika vzorcev.

Uvod v nevronske mreže kot orodje za razvrščanje vzorcev: organski nevron, umetni nevron in umetne nevronske mreže.

Zvezni večplastni perceptron: shema, učenje z gradientnim sestopom, razvrščanje vzorcev z enonevronskim in dvoplastnim zveznim perceptronom.

Samoorganizirajoče nevronske mreže: ekvivalenten algoritem samoorganizirajočih nevronskih mrež, učenje.

stereopsis, fusion of views, using more cameras. Introduction to pattern recognition: basic terms, model of

pattern classifier, description of simple patterns by feature set, feature extraction, clustering, pattern classification, testing of pattern classifier.

Introduction to neural networks as tool for pattern classification: organic neuron, artificial neuron and artificial neural networks.

Continuous multi-layer perceptron: scheme, learning by gradient descent, pattern classification by single-neuron and two-layer continuous perceptron.

Self-organizing neural networks: equivalent algorithm of self-organizing neural networks, learning.

Temeljni literatura in viri / Readings:

D. A. Forsyth, J. Ponce: Computer Vision: A Modern Approach, Second Edition, Pearson Education International, Upper Saddle River, 2011.

M. Sonka, V. Hlavac, R. Boyle: Image processing, analysis and machine vision, Fourth Edition, CENGAGE Learning, London, 2015.

S. E. Umbaugh: Computer Imaging: Digital Image Analysis and Processing, CRC Press, Boca Raton, 2005. N. Pavešić: Razpoznavanje vzorcev: uvod v analizo in razumevanje vidnih in slušnih signalov, Univerza v Ljubljani, Fakulteta

za elektrotehniko, Ljubljana, 2000. C. M. Bishop: Pattern Recognition and Machine Learning, Springer Science+Bussiness Media, New York, 2006. L. P. J. Veelenturf: Analysis and applications of artificial neural networks, Prentice Hall, London, 1995. Cilji in kompetence:


Cilj tega predmeta je, da bodo študentje razumeli osnovne postopke s področij računalniškega vida, razvrščanja vzorcev in uporabe nevronskih mrež, ter jih uporabiti v praksi.

The objective of this course is for students to be able to demonstrate understanding of basic procedures from fields of computer vision, pattern classification and neural networks usage, and to use them in practice.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben razumeti osnovne postopke računalniškega vida,

razvrščanja vzorcev in uporabe nevronskih mrež, načrtati in sestaviti preproste razpoznavalne sisteme, ki

temeljijo na slikovnem materialu, oceniti in ovrednotiti ter uglasiti razpoznavalne sisteme

oziroma njegove posamezne dele.

Knowledge and understanding: On completion of this course the student will be able to demonstrate understanding of basic procedures of

computer vision, pattern classification, and application of neural networks,

design and construct simple recognition systems based on imaging data,

assess and evaluate and fine-tune recognition systems or its individual parts, respectively.


pisanje strokovnega poročila pri projektu, pisno izražanje pri pisnem izpitu.

Uporaba informacijske tehnologije: uporaba programskih orodij za računalniški vid in razvrščanje vzorcev, pisanje računalniških programov.

Organizacijske spretnosti: izdelava in vodenje preprostega projekta za izgradnjo razpoznavalnega sistema.

Reševanje problemov: načrtovanje primerne razpoznavalne metode.

Delo v skupini: delo v skupini pri projektu.

Transferable/Key skills and other attributes: Communication skills: oral lab work defence, writing of

professional report at project, manner of expression at written examination.

Use of information technology: use of software tools for a computer vision and pattern classification, writing of computer programs.

Organization skills: design and coordination of simple project for recognition system construction.

Problem solving: design of suitable recognition method. Group work: group work at project.

Metode poučevanja in učenja: Learning and teaching methods: predavanja, seminarske vaje, projekt, laboratorijske vaje.

lectures, tutorials, project, lab work.



Assessment:


50 % 25 % 25 %


Opomba: V kolikor študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 50 %. Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references: POTOČNIK, Božidar. Automated landmark points detection by using a mixture of approaches: the vole-teeth case. Signal,

image and video processing, Published online 21 December 2012, str. 1-14. http://link.springer.com/article/10.1007/s11760-012-0414-1# . [COBISS.SI-ID 16578070].

POTOČNIK, Božidar, CIGALE, Boris, ZAZULA, Damjan. Computerized detection and recognition of follicles in ovarian ultrasound images: a review. Medical & biological engineering & computing, 2012, vol. 50, iss. 12, str. 1201-1212. [COBISS.SI-ID 16344854].

MLAKAR, Uroš, POTOČNIK, Božidar, BREST, Janez. A hybrid differential evolution for optimal multilevel image thresholding. Expert systems with applications, ISSN 0957-4174. [Print ed.], Dec. 2016, vol. 65, str. 221-232, doi: 10.1016/j.eswa.2016.08.046. [COBISS.SI-ID 19733526].

POTOČNIK, Božidar, HOLOBAR, Aleš. A new optical flow model for motor unit conduction velocity estimation in multichannel surface EMG. Computers in Biology and Medicine, ISSN 0010-4825. [Print ed.], April 2017, vol. 83, str. 59-68, ilustr., doi: 10.1016/j.compbiomed.2017.02.006. [COBISS.SI-ID 20327446].

MLAKAR, Uroš, FISTER, Iztok, BREST, Janez, POTOČNIK, Božidar. Multi-objective differential evolution for feature selection in facial expression recognition systems. Expert systems with applications, ISSN 0957-4174. [Print ed.], 15 Dec. 2017, vol. 89, str. 129-137, doi: 10.1016/j.eswa.2017.07.037. [COBISS.SI-ID 20731926].


Predmet: Verjetnost

Course title: Probability



Letnik Academic

year

Semester Semester





3. zimski Autum



Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vajework



ECTS

45 45 90 6


Jeziki / Languages:


slovenski / Slovene



Prerequisits:

Pogojev ni. None.

Vsebina:


Pomen naključnosti v znanosti in tehniki. Algebra dogodkov, vpeljava verjetnosti. Pogojna verjetnost, neodvisnost, Bayesov izrek. Uporaba

v umetni inteligenci. Naključne spremenljivke: porazdelitveni zakoni, tipi

porazdelitev. Diskretne porazdelitve. Matematično upanje, standardni

odklon, momenti. Binomska porazdelitev, Poissonova porazdelitev.

Zvezne porazdelitve. Normalna porazdelitev.

The importance of randomness in science and technology. Algebra of events, introduction to probability. Conditional probability, independence, Bayes' theorem,

applications in Artificial Intelligence. Random variables: probability laws, types of distributions. Discrete distributions. Expected value, standard deviation,

moments. Binomial distribution, Poisson's distribution. Continuous distributions. Normal distribution. Homogenous Markov chains. Law of large numbers and limit theorems. Important

Homogene markovske verige. Zakoni velikih števil in limitni izreki. Pomembne

aproksimacije. Porazdelitve parov naključnih spremenljivk. Neodvisnost,

kovarianca, korelacija. Pogojne porazdelitve, regresija. Normalna porazdelitev

naključnih vektorjev. Opisna statistika. Analitična statistika: ocenjevanje parametrov, testiranje

statističnih domnev.

approximations. Distributions of pairs of random variables. Independence,

covariance, correlation. Conditional distributions, regression. Normal distribution of

random vectors. Descriptive statistics. Inferential statistics: estimation of parameters, testing

statistical hypotheses.

Temeljni literatura in viri / Readings: R. Jamnik: Verjetnostni račun in statistika, DMFA SRS, Ljubljana, 1986. J. L. Devore: Probability and Statistics for Engineering and the Sciences, Barnes & Noble, New York, 2003. K. S. Trivedi, Probability and Statistics with Reliability, Queuing, and Computer Science Applications, John Wiley and Sons,

2001. M. Baron, Probability and Statistics for Computer Scientists, Chapman and Hall/CRC, 2013. J. L. Johnson, Probability and Statistics for Computer Science. Wiley-Interscience, 2003. Cilji in kompetence:


Cilj predmeta je, da študent zna uporabljati verjetnostni račun in je sposoben analizirati večje množice podatkov.

The objective of this course is for student to use the probability and to analyse bigger sets of data.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben uporabljati metode verjetnostnega računa in statistike pri

svojem delu, analizirati množice naključnih podatkov, opravljati statistične teste, uporabljati, prikazati in razložiti statistične izsledke, upoštevati naključnost pri gradnji modelov in jih statistično

preverjati.

Knowledge and understanding: On completion of this course the student will be able to use techniques of probability theory and statistics in his

work, analyze sets of random data, perform statistical tests, use, present and evaluate statistical results, take into account the randomness when constructing

models, and checking models statistically.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: opisovanje in tolmačenje

rezultatov statističnih raziskav. Uporaba informacijsko komunikacijske tehnologije:

uporaba računalniških paketov za statistiko. Spretnosti računanja: preproste naloge verjetnostnega

računa, analiza značilnosti porazdelitev. Reševanje problemov: prepoznavanje in reševanje

matematičnih problemov. Delo v skupini: skupinski pristop.

Transferable/Key skills and other attributes: Communication skills: description and evaluation of results

obtained through statistical testing. Use of information communication technology: using

statistical software. Calculation skills: simple problem solving in probability

calculation, analyzing distribution properties. Problem solving: identifying and solving mathematical

problems. Team work: team approach.





Delež (v %) /

Načini ocenjevanja: Weight (in %) Assessment: testi iz uporabnih znanj, testi iz laboratorijskih vaj, izpit iz teorije.

40 % 20 % 40 %

practical knowledge tests, lab work examination, theoretical knowledge exam.

Opomba: Testi se lahko nadomestijo s pisnim izpitom. Note: The tests may be replaced with a written exam. Reference nosilca / Lecturer's references: HENNING, Michael A., PETERIN, Iztok. A characterization of graphs with disjoint total dominating sets.

Ars mathematica contemporanea, ISSN 1855‐3974. [Spletna izd.], 2019, vol. 16, no. 2, str. 359‐375. https://amc‐journal.eu/index.php/amc/article/download/1525/1302, doi: 10.26493/1855‐3974.1525.7f3. [COBISS.SI‐ID 18544217]





UČNI NAČRT PREDMETA / SUBJECT SPECIFICATION Predmet: Veščine komuniciranja v inženirskem poklicu Subject Title: Communication skills for engineers



Letnik Year

Semester Semester





3 poletni spring


Predavanja Lectures

Seminar Seminar





ECTS

30 15 135 6 Nosilec predmeta / Lecturer: Darinka Verdonik Jeziki / Languages:



Prerequisites:



Uvod: predstavitev predmeta, motivacija. Razumevanje sporočil: orodja za komunikacijo na

delovnem mestu, osrednji namen sporočila, posredno sporočeno, aktivno poslušanje.

Tvorjenje sporočil in uspešna komunikacija: kako izraziti to, kar hočemo sporočiti, kako razumejo drugi naša sporočila, neverbalna komunikacija, težave v komunikaciji, praktične veščine komuniciranja.

Medosebni odnosi: hierarhija medsebojnih razmerij, ohranjanje pozitivne podobe, olika, čustva v komunikaciji, konflikti.

Samopredstavljanje: ohranjanje pozitivne lastne podobe, obvladovanje neverbalnih elementov naše podobe, vloga interneta pri kreiranju lastne podobe.

Veščine prepričevanja in nastopanja: samozavest, praktične veščine prepričevanja, neverbalni elementi prepričevanja, pripravljanje predstavitve.

Izdelava strokovnega/znanstvenega besedila.

Introduction: overview of the subject, motivation. Understanding messages: tools for communication on

workplace, intent of the message, implicit meaning, active listening.

Production of a message and successful communication: how to express what we want to communicate, non-verbal communication, problems in communication, practical skills of communication.

Personal relationships: power relationships, positive face construction, manners, emotions in communication, conflicts.

Self-introduction: positive face construction, managing non-verbal elements of our face, the role of Internet in creating our positive face.

Skills of persuasion and public performance: self-esteem, practical skills of persuasion, non-verbal elements of persuasion, preparing a public performance.

Creating a professional/scientific text. Temeljni študijski viri / Textbooks:

2 / 3

M. McKay, M. Davis, P. Fanning: Messages: The Communication Skillls Book. 2009. E. F. Becker, J. Wortmann: Mastering Communication at Work: How to Lead, Manage and Influence. 2009. Lakhani, D.: Persuation: The Art of Getting What You Want. Hoboken: John Wiley & Sons. 2005. J. C. Wetherbe, B. Wetherbe: Veščine sporazumevanja. Ljubljana: Orbis, 2005. M. Paladin: Neverbalna komunikacija. Nova Gorica: Educa, Melior, 2011.

Cilji:

Objectives:

Motivirati študente, da bodo v svojem poklicnem življenju namenjali pozornost temu, kako se dobro razumeti z ljudmi, s katerimi sodelujejo, kako prepričati druge v svojo kvaliteto in sodelovanje ter kakšen vtis puščajo pri drugih s svojo pojavo in svojimi izjavami/sporočili. Dati študentom nekatera temeljna in praktična znanja s področja komunikacije ter jih spodbuditi, da začnejo razvijati svoje komunikacijske veščine, z namenom, da jih pri doseganju uspeha v njihovem poklicnem življenju ne bi ovirala nevešča komunikacija. Izdelava projektne dokumentacije.

The aim is to motivate students for more careful, successful communication, and to make them aware that in order to achieve goals in our professional lives it is important to manage communication, to develop good relationships with people we co-operate with, to be persuasive and to keep positive impressions. The aim is also to give students some basic and practical knowledge from the field of communication, and to encourage them to further develope communication skills in their everyday lives. Creation of project documentation.

Predvideni študijski rezultati: Intended learning outcomes: Znanje in razumevanje: Po zaključku tega predmeta bo študent: poznal lastnosti različnih komunikacijskih kanalov in

uporabljal to znanje v lastni komunikaciji, poznal tehnike uspešnega tvorjenja in interpretacije

sporočil ter jih uporabljal v različnih sporazumevalnih okoliščinah,

poznal in razumel pomen neverbalne komunikacije, prepoznaval nesporazume in pomanjkljivo

sporazumevanje, razumel in analiziral razloge zanj ter poiskal ustrezne sporazumevalne rešitve,

poznal, razumel in uporabljal načela vljudnosti, olike in medosebnih odnosov v komunikaciji,

prepoznaval tehnike prepričevanja, poznal, razumel in znal uporabljal strategije gradnje

pozitivne lastne podobe in uspešnega javnega nastopanja. znal napisati strokovno/znanstveno besedilo.

Knowledge and understanding: On completion of this course the student will: recognize characteristics of different communication

channels and use this knowledge in own communication; know technics for successful creation and interpretation of

messages, use this knowledge in different communication circumstances;

know and understand the meaning of non-verbal communication;

recognize misunderstandings and miscommunication, analyse reasons for it and search for communicative solutions;

know, understand and use politeness principles, communication manners and interpersonal relationships;

recognize persuasion technics. know, understand and use strategies of self-representation

and successful public performances. able to write a professional/scientific texts.

Prenosljive/ključne spretnosti in drugi atributi:

sposobnost celostno in ustrezno razumeti različna sporočila ter primerno reagirati nanje

predstavljanje strokovnih vsebin na razumljiv in dostopen način, komunikacija s strankami, komunikacija s poslovnimi partnerji

vzpostavljanje in razvijanje dobrih medosebnih odnosov, ravnanje v neprijetnih komunikacijskih situacijah, razumevanje neverbalne komunikacije

vzpostavljanje pozitivne podobe sebe, svojega dela in podjetja

prepričevanje in nastopanje pred publiko

Transferable/Key skills and other attributes: ability to understand messages properly and to react to

messages ability to present professional contents in an

understandably and user-friendly way, communication with clients and with business partners

building good relationships with others, how to react in miscommunication, understanding the ways of non-verbal communication

building a positive representation of self, of the work that was done and of the company

persuasion and public representations Metode poučevanja in učenja:


predavanja seminarske vaje projekti skupinsko delo samostojno delo

lectures seminar work projects team work individual work

3 / 3



Assessment methods:

seminarske naloge pisni izpit

50

50

seminar papers paper examination

Reference nosilca / Lecturer's references: VERDONIK, Darinka, SEPESY MAUČEC, Mirjam. A speech corpus as a source of lexical information. International journal of

lexicography, ISSN 0950-3846, First published online: March 1, 2016, vol. , no. , str. 1-4, doi: 10.1093/ijl/ecw004. [COBISS.SI-ID 19374870], [JCR, SNIP]

VERDONIK, Darinka. Internal variety in the use of Slovene general extenders in different spoken discourse settings. International journal of corpus linguistics, ISSN 1384-6655, 2015, vol. 20, no. 4, str. 445-468, doi: 10.1075/ijcl.20.4.02ver. [COBISS.SI-ID 19266838], [JCR, SNIP, WoS do 15. 2. 2016: št. citatov (TC): 0, čistih citatov (CI): 0, Scopus do 25. 1. 2016: št. citatov (TC): 0, čistih citatov (CI): 0]

VERDONIK, Darinka, KOSEM, Iztok, ZWITTER VITEZ, Ana, KREK, Simon, STABEJ, Marko. Compilation, transcription and usage of a reference speech corpus : the case of the Slovene corpus GOS. Language resources and evaluation, ISSN 1574-020X, Dec. 2013, vol. 47, iss. 4, str. 1031-1048, doi: 10.1007/s10579-013-9216-5. [COBISS.SI-ID 16771606], [JCR, SNIP, WoS do 4. 3. 2016: št. citatov (TC): 3, čistih citatov (CI): 2, Scopus do 4. 2. 2016: št. citatov (TC): 2, čistih citatov (CI): 1]

VERDONIK, Darinka. Koncept konteksta v jezikoslovnih in diskurznih teorijah. Slavistična revija, ISSN 0350-6894. [Tiskana izd.], okt.-dec. 2013, letn. 61, št. 4, str. 631-649. http://www.srl.si/sql_pdf/SRL_2013_4_08.pdf. [COBISS.SI-ID 17578006], [Scopus do 11. 11. 2014: št. citatov (TC): 0, čistih citatov (CI): 0]

VERDONIK, Darinka, KAČIČ, Zdravko. Označevalci odprte propozicije v govorjenem diskurzu. Slavistična revija, ISSN 0350-6894. [Tiskana izd.], jan.-mar. 2012, letn. 60, št. 1, str. 79-94, ilustr. http://www.srl.si/sql_pdf/SRL_2012_1_06.pdf. [COBISS.SI-ID 48889442], [SNIP, WoS do 5. 3. 2016: št. citatov (TC): 1, čistih citatov (CI): 0, Scopus do 5. 2. 2016: št. citatov (TC): 1, čistih citatov (CI): 0]

UČNI NAČRT PREDMETA / SUBJECT SPECIFICATION Predmet: Vgrajeni sistemi Subject Title: Embedded Systems



Letnik Year

Semester Semester


Computer Science and Information Technologies

1st cycle Academic undergraduate

3. zimski

Automn

Univerzitetna koda predmeta / University subject code: 61U031

Predavanja Lectures

Seminar Seminar

Vaje Tutorial

Klinične vaje work


Samost. delo Individ. work ECTS

30 45 105 6 Nosilec predmeta / Lecturer: Matjaž Colnarič Jeziki / Languages:



Prerequisites:



Osnovni koncepti vgrajenih sistemov: čas v vgrajenih računalniških sistemih, specifične lastnosti: pravočasnost, napovedljivost, zanesljivost, omejena sredstva, vrste sistemov v realnem času.

Arhitektura procesorjev ARM Cortex. Večopravilnost: diagram prehajanja stanj. Sinhronizacija med opravili v realnem času, osnovni koncepti,

mehanizmi, omejevanje časa čakanja Razvrščanje opravil v realnem času, strategije, analiza

razvrstljivosti. Specifične značilnosti vgrajene strojne opreme in komunikacij.

Smernice za izbiro, primeri. Specifične značilnosti vgrajene programske opreme, analiza

časovnih zahtev (analiza WCET). Operacijski sistemi za vgrajene sisteme. Zanesljivost in varnost vgrajenih sistemov.

Basic concepts of embedded systems: time in embedded computer systems, specific properties: timeliness, predictability, dependability, limited resources, types of real-time systems.

Architecture of ARM Cortex processors Multitasking: state transition diagram. Synchronisation between real-time tasks, basic concepts,

mechanisms, waiting time bounding. Scheduling of real-time tasks, strategies, schedulability

analysis. Specific characteristics of hardware and communications

for embedded systems. Selection guidelines, examples. Specific properties of embedded software, analysis of

temporal requirements (WCET analysis). Operating systems for embedded applications. Safety and dependability of embedded systems.

Temeljni študijski viri / Textbooks: M. Colnarič: Študijski material iz vgrajenih sistemov, Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko,

2019. Vir je dostopen v elektronski obliki na estudij.um.si. M. Colnarič, D. Verber, W. A. Halang: Distributed Embedded Control Systems: Improving Dependability with Coherent Design,

Springer Verlag, London, 2008. P. Marwedel: Embedded System Design, 2nd Edition, Springer, 2011 A. Burns, A. Wellings: Real-Time Systems and Programming Languages, Addison Wesley, Boston MA, 2009. Edward Lee, Sanjit A. Seshia, Introduction to Embedded Systems - A Cyber-Physical Systems Approach. University of Berkeley,

http://LeeSeshia.org, 2011. Joseph Yiu, The Definitve Guide to ARM CORTEX-M3 and Cortex-M4 Processors, Third Edition, Elsevier, 2014

Cilji:

Objectives:

Študentom posredovati občutek za čas v računalniških sistemih in soodvisnost dogajanja v njih. Pokazati, da na časovno obnašanje medsebojno vpliva večina komponent sistema ter kako jih je potrebno zasnovati za dosego časovne predvidljivosti. Naučiti jih razvijati preproste vgrajene aplikacije na nivoju večopravilnosti.

To convey to students the sense of time in computer systems and inter-dependablity of their internal behaviour. To show that most components have impact on systems' temporal behaviour and how they should be designed for temporal predictability. Teach them how to develop simple embedded applications on the multitasking level.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben razumeti način delovanja sistemov v realnem času

(principi, opravila, večopravilnost, sinhronizacija, razvrščanja),

izvesti analizo razvrstljivosti za nabor opravil, izbrati ustrezne aparaturne platforme in programska ter

razvojna orodja, zgraditi preprostejši vgrajeni sistem.

Knowledge and understanding: On completion of this course the student will be able to understand operation of computer systems in real-time (principles,

tasks, multitasking, synchronisation, scheduling policies), do schedulability analysis for a task set, select proper hardware platforms, and programming and

development tools, design a simple embedded system.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: predstavitev seminarja. Uporaba informacijske tehnologije: razvoj projekta. Organizacijske spretnosti: priprava projekta. Reševanje problemov: izvedba projekta. Delo v skupini: sodelovanje v skupinskih projektih.

Transferable/Key skills and other attributes: Communication skills: seminar presentation. Use of information technology: project work. Organisation skills: preparations for the project. Problem solving: implementation of the project. Working in a group: collaboration in joint projects.




lectures, lab work.



Assessment methods:

opravljene praktične laboratorijske vaje, vmesni pisni izpiti.

50 % 50 %

completed practical laboratory work, mid-term exams.

Opomba: Vmesni pisni izpiti se lahko nadomestijo s pisnim izpitom v deležu 50%. Note: Midterm written exams may be replaced by a written exam in the weight of 50%. Reference nosilca / Lecturer's references: COLNARIČ, Matjaž, VERBER, Domen, HALANG, Wolfgang A.. Distributed embedded control systems : improving

dependability with coherent design, (Advances in industrial control). Hagen: Springer, cop. 2010. XVII, 250 str., ilustr. ISBN 978-1-84996-715-0. ISBN 978-1-84800-052-0. [COBISS.SI-ID 68989441]

COLNARIČ, Matjaž An example of fault detection and reconfiguration-based tolerance within distributed embedded control systems / Matjaž Colnarič, Domen Verber and Matej Šprogar. - Dostopno tudi na: http://www.springer.com/gp/book/9783319288581. - Bibliografija: str. 487V: Complex systems. - [S. l.] : Springer, 2016. - (Studies in systems, decision and control, ISSN 2198-4182 ; vol. 55). - ISBN 978-3-319-28858-1. - ISBN 978-3-319-28860-4. - Str. 473-487

RUANO, António E., COLNARIČ, Matjaž, et al. Computational intelligence in control. Annual Reviews in Control, ISSN 1367-5788. [Print ed.], Available online 7 October 2014, vol. , iss. , str. 1-10, doi: 10.1016/j.arcontrol.2014.09.006. [COBISS.SI-ID 18142742], [JCR, SNIP]

COLNARIČ, Matjaž, TROST, Andrej. Vgrajeni sistemi - priložnosti in partnerstva. V: ZAJC, Baldomir (ur.), TROST, Andrej (ur.). Zbornik Osemnajste mednarodne elektrotehniške in računalniške konference - ERK 2009, 21-23. september 2009, Portorož, Slovenija. Ljubljana: IEEE Region 8, Slovenska sekcija IEEE, 2009, zv. A, str. 11-12. [COBISS.SI-ID 13482518]

VERBER, Domen, ŠPROGAR, Matej, COLNARIČ, Matjaž. Implementation of non-intrusive fault detection in embedded control systems. Inf. MIDEM, mar. 2007, letn. 37, št. 1(121), str. 23-30. [COBISS.SI-ID 11552534]

VERBER, Domen, COLNARIČ, Matjaž. Operating system Kernel coprocessor for embedded applications. V: JOO ER, Meng (ur.). New trends in technologies: devices, computer, communication and industrial systems. Rijeka: Sciyo, cop. 2010, str. [135]-144, ilustr. [COBISS.SI-ID 14661398]

uČni naČrt predmeta / course syllabus · apply a suitable data structure and algorithm to a given...

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