csic 2014 ( november )

CSI Communications | November 2014 | 1ww

w.c

si-i

nd

ia.o

rg

ISS

N 0

97

0-6

47

X |

Vo

lum

e N

o. 3

8 |

Iss

ue

No

. 8 |

No

vem

be

r 2

014

` 5

0/

-

Cover StoryVisualization-Techniques, Methods and Tools 7

ArticleInformation Technology to Curb Piracy in Bollywood 23

Technical TrendsBig Data Visualization using Cassandra and R 15

Security CornerA Case Study of Netrapur Police 39

IT Industry PerspectiveFuture of Medical Transcription Jobs in India - Need to Extend it beyond Record Generating Process 29

Research FrontA Walkthrough & Pathfi nder for Research Novitiates: Google Scholar Vs Microsoft Academic Search 18

CSI Job Specifi c Certifi cationsComputer Society of India enters into Knowledge Partnership with

InfoComm International, USA In its drive towards empowering IT students beyond regular diplomas and degrees, CSI has launched professional certifi cation programme

to certify them for direct employment in niche domains. As the members are aware, CSI has already entered into collaboration with the Open

Group for TOGAF Foundations Certifi cate to students in the graduate engineering stream. InfoComm certifi cation is the second in line.

InfoComm International of USA is a nonprofi t association serving the professional audio video communication industry worldwide.

InfoComm University education supported by CSI would off er those Indian students from the IT stream, pursuing diplomas as well as

degree, the opportunity to qualify as “AV Essential Technology Specialist”.

Initially, a pilot programme that would open around 200 vacancies for successful certifi ed students will be made available by InfoComm.

The course would consist of:

• Quick start to the AV Industry, • The essentials of audio visual technology, • Certifi cation preparation, and,• Recognized Audio Visual Technologist Certifi cate.

The delivery of the pilot programme will be via the InfoComm University online learning platform supported by CSI and their partner

Institutions.

Each year, InfoComm International will consolidate the vacancies arising among its member organizations in India and will recruit competent

certifi ed students through the CSI Educational Directorate.

All CSI member educational institutions are invited to be part of the partnership programme, which off ers placement opportunities

to the young professionals. Interested institutions may please contact the Director (Education), Computer Society of India, Education

Directorate, CIT Campus, 4th Cross Road, Taramani, Chennai - 600 113.

Phone : +91-44-2254 1102/1103/2874

Email : [email protected]

Institutions in the Mumbai Region may also contact Computer Society of India, Headquarters, Samruddhi Venture Park, Unit No.3, 4th Floor,

MIDC, Andheri (E). Mumbai-400093 Maharashtra,

India. Phone: 91-22-29261700, Fax: 91-22-28302133

Email: [email protected]

www.csi-india.org

CSI Communications | November 2014 | 3

ContentsVolume No. 38 • Issue No. 8 • November 2014

CSI Communications

Please note:

CSI Communications is published by Computer

Society of India, a non-profi t organization.

Views and opinions expressed in the CSI

Communications are those of individual authors,

contributors and advertisers and they may

diff er from policies and offi cial statements of

CSI. These should not be construed as legal or

professional advice. The CSI, the publisher, the

editors and the contributors are not responsible

for any decisions taken by readers on the basis of

these views and opinions.

Although every care is being taken to ensure

genuineness of the writings in this publication,

CSI Communications does not attest to the

originality of the respective authors’ content.

© 2012 CSI. All rights reserved.

Instructors are permitted to photocopy isolated

articles for non-commercial classroom use

without fee. For any other copying, reprint or

republication, permission must be obtained

in writing from the Society. Copying for other

than personal use or internal reference, or of

articles or columns not owned by the Society

without explicit permission of the Society or the

copyright owner is strictly prohibited.

Published by Suchit Gogwekar for Computer Society of India at Unit No. 3, 4th Floor, Samruddhi Venture Park, MIDC, Andheri (E), Mumbai-400 093.

Tel. : 022-2926 1700 • Fax : 022-2830 2133 • Email : [email protected] Printed at GP Off set Pvt. Ltd., Mumbai 400 059.

Editorial Board

Chief EditorDr. R M Sonar

EditorsDr. Debasish Jana

Dr. Achuthsankar Nair

Resident EditorMrs. Jayshree Dhere

Published byExecutive Secretary

Mr. Suchit Gogwekar

For Computer Society of India

Design, Print and Dispatch byCyberMedia Services Limited

PLUSBrain TeaserDr. Debasish Jana

42

Ask an ExpertDr. Debasish Jana

43

Happenings@ICTH R Mohan

44

On the Shelf!Peeyush Chomal

45

CSI Report 46

CSI News 48

Cover Story

7 Visualization-Techniques, Methods and

Tools

Dr. KVSN Rama Rao, Mr. Surya Putchala and Midhun Thaduru

10 Visualization for STEM Subjects

A.B. Karthick Anand Babu, D. Maghesh Kumar and G. RajaRaja Cholan

Technical Trends

1 1 Visualization Tool for Data Mining

Dr. B. Eswara Reddy and Mr. K. Rajendra Prasad

12 Information Visualization in Gene

Expression Data

Sreeja Ashok, Dr. M. V. Judy and N. Thushara Vijayakumar

15 Big Data Visualization using Cassandra

and R

Ris hav Singh and Dr. Sanjay Kumar Singh

Research Front

16 Visualization Methods for Vector Fields:

An Insight

Dilip Kumar Dalei, B. V. Hari Krishna Nanda and N. Venkataramanan

18 A Walkthrough & Pathfi nder for Research

Novitiates: Google Scholar Vs Microsoft

Academic Search

Anchal Garg, Madhurima, Madhulika and Saru Dhir

Articles

22 Active Queue Management

Amol Dhumane and Dr. Rajesh Prasad

23 Information Technology to Curb

Piracy in Bollywood

Sumith Kumar Puri and Dr. H K Anasuya Devi

25 Protection of Software as Intellectual

Property

Dr. M Hanumanthappa, Mrs. S Regina Lourdhu Suganthi and Mrs. Rashmi S

Practitioner Workbench

27 Programming.Tips() »

Fun with ‘C’ Programs – Reversing a

String using a Bitwise Operator

Wallace Jacob

Programming.Learn(“R”) »

28 RStudio- Studio of R

Umesh P and Silpa Bhaskaran

IT Industry Perspective

29 Future of Medical Transcription Jobs

in India - Need to Extend it beyond

Record Generating Process

Prof (Dr.) D G Jha

Innovations in India

36 Software User Experience Maturity

Model

Rajiv Thanawala and Prachi Sakhardande

Security Corner

37 Information Security »

A Quick Look at Virtual Private

Database Security

Jignesh Doshi and Bhushan Trivedi

39 Case Studies in IT Governance, IT Risk and Information Security » A Case Study of Netrapur Police

Dr. Vishnu Kanhere

CSI Communications | November 2014 | 4 www.csi-india.org

Know Your CSI

Executive Committee (2013-14/15) »President Vice-President Hon. Secretary Hon. TreasurerMr. H R Mohan Prof. Bipin V Mehta Mr. Sanjay Mohapatra Mr. Ranga [email protected] [email protected] [email protected] [email protected]

Immd. Past PresidentProf. S V [email protected]

Nomination Committee (2014-2015)

Prof. P. Kalyanaraman Mr. Sanjeev Kumar Mr. Subimal Kundu

Regional Vice-PresidentsRegion - I Region - II Region - III Region - IVMr. R K Vyas Mr. Devaprasanna Sinha Prof. R P Soni Mr. Hari Shankar Mishra Delhi, Punjab, Haryana, Himachal Assam, Bihar, West Bengal, Gujarat, Madhya Pradesh, Jharkhand, Chattisgarh,

Pradesh, Jammu & Kashmir, North Eastern States Rajasthan and other areas Orissa and other areas in

Uttar Pradesh, Uttaranchal and and other areas in in Western India Central & South

other areas in Northern India. East & North East India [email protected] Eastern India

[email protected] [email protected] [email protected]

Region - V Region - VI Region - VII Mr. Raju L kanchibhotla Dr. Shirish S Sane Mr. S P Soman Karnataka and Andhra Pradesh Maharashtra and Goa Tamil Nadu, Pondicherry,

[email protected] [email protected] Andaman and Nicobar,

Kerala, Lakshadweep

[email protected]

Division ChairpersonsDivision-I : Hardware (2013-15) Division-II : Software (2014-16) Division-III : Applications (2013-15) Prof. M N Hoda Dr. R Nadarajan Dr. A K Nayak [email protected] [email protected] [email protected]

Division-IV : Communications Division-V : Education and Research (2014-16) (2013-15)

Dr. Durgesh Kumar Mishra Dr. Anirban Basu [email protected] [email protected]

Important links on CSI website »

Publication Committee (2014-15)

Dr. S S Agrawal Chairman

Prof. R K Shyamasundar Member

Prof. R M Sonar Member

Dr. Debasish Jana Member

Dr. Achuthsankar Nair Member

Dr. Anirban Basu Member

Prof. A K Saini Member

Prof. M N Hoda Member

Dr. R Nadarajan Member

Dr. A K Nayak Member

Dr. Durgesh Kumar Mishra Member

Mrs. Jayshree Dhere Member

Important Contact Details »For queries, correspondence regarding Membership, contact [email protected]

About CSI http://www.csi-india.org/about-csiStructure and Orgnisation http://www.csi-india.org/web/guest/structureandorganisationExecutive Committee http://www.csi-india.org/executive-committeeNomination Committee http://www.csi-india.org/web/guest/nominations-committeeStatutory Committees http://www.csi-india.org/web/guest/statutory-committeesWho's Who http://www.csi-india.org/web/guest/who-s-whoCSI Fellows http://www.csi-india.org/web/guest/csi-fellowsNational, Regional & State http://www.csi-india.org/web/guest/104Student Coordinators Collaborations http://www.csi-india.org/web/guest/collaborationsDistinguished Speakers http://www.csi-india.org/distinguished-speakersDivisions http://www.csi-india.org/web/guest/divisionsRegions http://www.csi-india.org/web/guest/regions1Chapters http://www.csi-india.org/web/guest/chaptersPolicy Guidelines http://www.csi-india.org/web/guest/policy-guidelinesStudent Branches http://www.csi-india.org/web/guest/student-branchesMembership Services http://www.csi-india.org/web/guest/membership-serviceUpcoming Events http://www.csi-india.org/web/guest/upcoming-eventsPublications http://www.csi-india.org/web/guest/publicationsStudent's Corner http://www.csi-india.org/web/education-directorate/student-s-cornerCSI Awards http://www.csi-india.org/web/guest/csi-awardsCSI Certifi cation http://www.csi-india.org/web/guest/csi-certifi cationUpcoming Webinars http://www.csi-india.org/web/guest/upcoming-webinarsAbout Membership http://www.csi-india.org/web/guest/about-membershipWhy Join CSI http://www.csi-india.org/why-join-csiMembership Benefi ts http://www.csi-india.org/membership-benefi tsBABA Scheme http://www.csi-india.org/membership-schemes-baba-schemeSpecial Interest Groups http://www.csi-india.org/special-interest-groups

Membership Subscription Fees http://www.csi-india.org/fee-structureMembership and Grades http://www.csi-india.org/web/guest/174Institutional Membership http://www.csi-india.org /web/guest/institiutional-

membershipBecome a member http://www.csi-india.org/web/guest/become-a-memberUpgrading and Renewing Membership http://www.csi-india.org/web/guest/183Download Forms http://www.csi-india.org/web/guest/downloadformsMembership Eligibility http://www.csi-india.org/web/guest/membership-eligibilityCode of Ethics http://www.csi-india.org/web/guest/code-of-ethicsFrom the President Desk http://www.csi-india.org/web/guest/president-s-deskCSI Communications (PDF Version) http://www.csi-india.org/web/guest/csi-communicationsCSI Communications (HTML Version) http://www.csi-india.org/web/guest/csi-communications-

html-versionCSI Journal of Computing http://www.csi-india.org/web/guest/journalCSI eNewsletter http://www.csi-india.org/web/guest/enewsletterCSIC Chapters SBs News http://www.csi-india.org/csic-chapters-sbs-newsEducation Directorate http://www.csi-india.org/web/education-directorate/homeNational Students Coordinator http://www.csi- india .org /web/national-students-

coordinators/homeAwards and Honors http://www.csi-india.org/web/guest/251eGovernance Awards http://www.csi-india.org/web/guest/e-governanceawardsIT Excellence Awards http://www.csi-india.org/web/guest/csiitexcellenceawardsYITP Awards http://www.csi-india.org/web/guest/csiyitp-awardsCSI Service Awards http://www.csi-india.org/web/guest/csi-service-awardsAcademic Excellence Awards http://www.csi-india.org/web/guest/academic-excellence-

awardsContact us http://www.csi-india.org/web/guest/contact-us


On behalf of the CSI Execom 2014-15, I am pleased to invite you to CSI-2014, the 49th Annual Convention on the theme “Emerging ICT for Bridging Future”. It will be held as a part of CSI@50 during 12-14, Dec 2014 at Jawaharlal Nehru Technological University (JNTU), Hyderabad. CSI-2014 is hosted by CSI Hyderabad chapter in association with JNTU and Defense Research Development Organization (DRDO). The Convention is spearheaded by Mr. JA Chowdary (OC), Dr. A Govardhan (PC) and Mr. Gautam Mahapatra (FC) and a dedicated team of CSI members, academic and industry professionals from Hyderabad. The arrangements for CSI-2014 are in full swing. The team is putting up an excellent programme which is under its fi nal stage and will soon be available at the convention website www.csi-2014.org. I am sure that the sessions by a wide range of eminent speakers on a variety of topics will be a feast to all participants. Prior to the CSI-2014, the Annual Students Convention will be held on 10-11, Dec 2014 at GNIT campus. Under the theme “Campus to Corporate and Beyond”, the programme will focus on career opportunities and enhancements. It is hosted by Guru Nanak Institutions under the chairmanship of Dr. HS Saini. I look forward to active participation by the members in CSI-2014 and student members in the student convention. As a heritage city, Hyderabad has a lot to off er fi rst-time visitors. Please plan your trip well in advance and have a great time at CSI-2014. We will be delighted to see you at Hyderabad. I was happy to be among the CSI veterans at Pune who had organized a meet as part of CSI@50 events along with the International Conference on Advances in Cloud Computing (ACC-2014) on 10th Oct 2014. Launched in 1972, CSI Pune has gained prominence by organizing a number of national and international events including two annual conventions. Incidentally, CSI-77 at Pune was my fi rst convention as a regular member after I graduated in 1976. In the CSI@50 meet, after a briefi ng on chapter activities by Mr. Anand Joglekar, I shared my views on CSI and the way to move forward in the current context of capacity building and creating intellectual property. In a special talk, Dr. Mathai Joseph, a seasoned computer scientist, academic, researcher and one of the most respected members of the Pune’s software industry took us down the memory lane on computing in India from 1960s till now. He highlighted the growth as well the opportunities we had missed. Mr. Shekhar Sahasrabudhe, a former RVP-VI and past chairman of CSI Pune, made a lively presentation on past chairpersons of CSI Pune and their contributions to the growth of the chapter. A few other former chair persons and Dr. Deepak Shikarpur, former chairman of CSI Pune, and fellow of CSI, shared their experiences. The conf. ACC-2014, held under the Div V on “Education & Research” headed by Dr. Anirban Basu, was well attended with over 100 enthusiastic participants who had interacted actively with the speakers. The panel on “IoT – the present and the future” was the highpoint of ACC-2014. Dr. Rajesh Ingle and his team brought out an excellent proceeding with 13 papers, which will be available in the CSI Digital Library soon. The CSI Pune deserves a hearty congratulation for showcasing their organizing capacity once again. Formal Methods (FM), a discipline in theoretical computing, plays an important role by applying mathematical techniques in the specifi cation, development and verifi cation of software and hardware systems. NCFM - the National workshop-cum-Conference on Formal Methods - recently held during 15-17, Oct 2014 in Bangalore was the fi rst of its kind that brought together scientists and engineers who are active in the area of FM and are interested in exchanging their experiences in the industrial usage of these methods. The NCFM was organized by the new CSI SIG on Formal Methods whose convener is Ms. Bhanumathi Shekhar, along with CSI Bangalore and hosted by IISc. Dr. Ramaswamy Srinivasan, Global R&D Project Manager of ABB Global Industries, Bangalore in his inaugural address highlighted the growing needs in FM. In view of the fact that 400 out of 600 talent-starved R&D centers of international companies are now located in India and the role of CSI SIG-FM in creating awareness and motivating students to work in FM, the need to educate our students and working professionals in FM were the highlights of the special address by the President. The CSI BC Chairman Chander Mannar and his team have spared no eff orts in making this conf. a technically rich one with a lot of interactions and learning by the participants. While speaking to Prof. N. Balakrishnan, of the Supercomputer Education and Research Centre at IISc, it was given to understand that funding is available for research in the Formal

Methods in Cyber Security and related areas, and that SIG-FM can work with them in popularizing Formal Methods among researchers. While we at CSI are taking advantage of our association with IEEE & IEEE Computer Society in organizing a number of Distinguished Visitor Programme talks and tutorials at various CSI Student Branches, our own home grown Distinguished Speaker Programme (DSP) requires attention for its eff ective implementation. The growth in the number of engineering institutions has created a shortage of qualifi ed teachers; DSP was initiated to rope in both experienced academic and industry professionals to supply an alternative stream of teachers who will help our students become industry ready. While it is quite easy to organize programmes with speakers from abroad, my personal experience in getting our senior members of academia and industry for talks is quite a mixed one. Some have been overwhelmingly responsive to our request but a few do not even acknowledge the request, left alone coming forward to speak at conferences organized by CSI. I am happy to share some of the activities of our Education Directorate in their continued eff ort in service to our members which include: Signing of MoU with Telecom Sector Skill Council (TSSC) for skill development initiatives in the Telecommunications domain; Conducting the SEARCC International School Software Competition ISSC-2014 at Rajalakshmi Engineering College, Chennai in which ROC Taiwan came fi rst, followed by India (Team-B) and Sri Lanka (Team-A) in the second and third places respectively. The prizes were presented by Mr. HR Mohan, President, CSI, Dr. Thangam Meganathan, Chairperson, Rajalakshmi Group of Institutions, Prof. P Thrimurthy, Past President, CSI, Mr. S Ramanathan, Past Hony. Secretary and Mr. Bhaskaran, Vice Chairman, CSI Chennai; and Continuing its campaign on Open Source Technology, by organizing a free workshop for faculty members on BOSS MOOL at JNTU, Anantapur, Andhra, jointly with CDAC, IIT Madras. The workshop, attended by over 100 was inaugurated by Prof. Lal Kishore, Vice Chancellor, JNTU-A and facilitated by Prof. Ananda Rao. I am happy to note that CSI Chennai in association with IEEE Computer Society and IEEE Professional Communication Society is organizing an Essay Contest for the school and college students on the topics “ICT for Digital India”, “ICT for Make in India” and “ICT for Clean India” which are the important initiatives of the Government of India. I wish all the best for their eff orts and request them to share the views of the young minds to the PMO and DeitY. Due to space constraints, I will discuss some of the recent developments in the country such as eCommerce, ICT in manufacturing and other initiatives in the next month. While I conclude my message, let me once again remind you to enroll new members in CSI by letting them know about the 15% discount on Life Membership being off ered for a limited period. This will end by Dec 2014. Once again I extend my personal invitation to all for your participation in CSI-2014, the fl agship event of CSI at Hyderabad. I eagerly look forward to seeing you at Hyderabad in Dec 2014.

With best regards

H R MohanPresidentComputer Society of India

President’s Message H R Mohan

From : President’s Desk:: [email protected] : President's MessageDate : 1st November, 2014

Dear Members


EditorialRajendra M Sonar, Achuthsankar S Nair, Debasish Jana and Jayshree DhereEditors

Dear Fellow CSI Members,

We have come a long way since the time when data was displayed only in text form. With increasing computing power over the years, and deluge of data from a variety of fi elds from e-business to gene sequencing, the visual representation of data has assumed greater and greater importance. Techniques and technologies for visualisation have emerged over the years making it possible and feasible to make sense out of the overwhelming amount of data. Information today can be represented in various formats which makes computing more and more interesting with a variety of applications in diff erent fi elds. The advent of Google glass which displays information in a smartphone-like hands-free format, is a pointer to the future. The theme of CSI Communications this month is related to the vast fi eld of Visualization Technologies. The articles of course are not covering the breadth of the fi eld, but as with other such fi elds, the theme would be taken up again in future to do justice to the coverage.

We start our cover story section with an article titled “Visualization – Techniques, Methods and Tools” by Dr. KVSN Rama Rao, Mr. Surya Putchala and Midhun Thaduru. The article talks about how visualization adds value to the data that needs to be analyzed. After explaining the process of visualization the article provides information about various open source tools available for visualization. The second article is by A.B. Karthick Anand Babu, D. Maghesh Kumar and G. RajaRaja Cholan and is titled “Visualization for STEM Subjects”. The article discusses how visualization enhances learning experience for students of subjects such as Science, Technology, Engineering and Mathematics. It also gives information about visualization tools that can be used and concludes saying that domain knowledge is required for customizing and designing eff ective visualization using readily available open source tools.

Our Technical Trends section is enriched with three articles. The fi rst article is written by Dr. B. Eswara Reddy and Mr. K. Rajendra Prasad on “Visualization Tool for Data Mining”. This article provides information about a tool called Visual Access Tendency (VAT) which is useful for detecting information of number of data clusters (or classes) in visual form. The second article is by Sreeja Ashok, Dr. M. V. Judy and N. Thushara Vijayakumar n on “Information Visualization in Gene Expression Data”. The article talks about signifi cance of visualization in the context of gene expression data and then goes about explaining the process of visualization. The third article is by Rishav Singh and Dr. Sanjay Kumar Singh and is titled “Big Data Visualization Using Cassandra and R” which discusses the use of distributed database system Cassandra and compares it with SQL database.

Research Front section has two articles. First one is by Dilip Kumar Dalei, B. V. Hari Krishna Nanda and N. Venkataramanan titled “Visualization Methods for Vector Fields: An Insight”. The article provides introduction to scientifi c data visualization and provides overview of fundamental fl ow visualization technique. The second article is by Anchal Garg, Madhurima, Madhulika and Saru Dhir titled “A Walkthrough & Pathfi nder for Research Novitiates: Google Scholar Vs Microsoft Academic Search”. The article explains how searching can be done while researching.

In regular article section, we have three articles on diff erent topics. The fi rst article titled “Active Queue Management” is written by Amol Dhumane and Dr. Rajesh Prasad who write about new queue management technique used for handling congestion in networks. The second article is on an interesting topic of “Information Technology

to Curb Piracy in Bollywood” written by Sumith Kumar Puri and Dr. H K Anasuya Devi. This article makes us aware about CineCat, a software application idea. The third article titled “Protection of Software as Intellectual Property” is sent by Dr. M Hanumanthappa, Mrs. S Regina Lourdhu Suganthi and Mrs. Rashmi S. The article explains the meaning of intellectual property and discusses the protection provided by law for such intangible property in the form of patents and copyrights. It compares the two and concludes saying that for software adequate protection in the form of patent right is highly desirable and dual IP protection in the form of Patents and Copyrights can also be explored to cover both functional and non-functional aspects of software.

In Practitioner workbench section we have two articles from our regular contributors. The fi rst one: “Fun with ‘C’ Programs: Reversing a String using a Bitwise Operator” under Programming.Tips() section is written by Prof. Wallace Jacob of Tolani Maritime Institute and second one: “RStudio – Studio of R” under Programming.Learn(“R”) section is written by Umesh P and Silpa Bhaskaran, Department of Computational Biology and Bioinformatics.

Under IT industry perspective we have an article titled “Future of Medical Transcription Jobs in India – Need to Extend it Beyond Record Generating Process?” by Prof (Dr.) DG Jha. This article discusses various points such as importance of medical transcriptions (MT), why the MT work is outsourced, quality standards applicable to MT, stages in the process of MT, technological innovations which are creating a doubt whether it is dead end for smaller Indian companies doing MT jobs, factors obstructing outsourcing MT work to India and fi nally talks about revival strategy that can make India a preferred destination once again for MT work.

Under Innovations in India column, which we recently started from July 2014 issue, we have a brief article titled “Software User Experience Maturity Model” by Rajiv Thanawala and Prachi Sakhardande of TCS. In this article they explain how metrics can be used for measuring quality of software products in terms of user experience.

Under information security section of Security Corner column, this time we have an article on “A Quick Look at Virtual Private Database Security” by Jignesh Doshi and Bhushan Trivedi, where they explain how Oracle’s virtual private database technology can be used for prevention of theft of sensitive data. In the second section of Security Corner column, we have a case study in IT Governance, IT Risk and Information Security by Dr. Vishnu Kanhere, who writes about case of Netrapur Police who plan to implement new surveillance system called San-nirikshan and the kind of disruption it is expected to create.

In our regular section called Brain Teaser we have a cross-word by Dr. Debasish Jana, Editor on Visualization Technologies. He also answers readers’ questions under the column Ask an Expert: Your question, Our answer. Briefs of various ICT news of October 2014 are compiled and brought to us by H R Mohan, ICT Consultant, President, CSI and former AVP (Systems), The Hindu, Chennai under Happenings@ICT.

We have other regular features like CSI Announcements, CSI Reports, Chapter and Student Branch news etc. Please remember we welcome your suggestions and feedback at [email protected]. Please do write and help us serve you better. Wish you happy reading and learning.

With warm regards,

Rajendra M Sonar, Achuthsankar S Nair,Debasish Jana and Jayshree DhereEditors

... for software adequate protection in the form of patent right is highly desirable and dual IP protection in the form of Patents and Copyrights can also be explored to cover both functional and non-functional aspects of software.

With increasing computing power over the years, and deluge of data from a variety of fi elds from e-business to gene sequencing, the visual representation of data has assumed greater and greater importance. Techniques and technologies for visualisation have emerged over the years making it possible and feasible to make sense out of the overwhelming amount of data.


Why Visualization?It is a well known fact that “A picture

is worth a thousand words.“ To extract

and analyze the massive amount of

generated data, visualization plays an

incredible role. Further it amplifi es the

cognition by helping in pattern detection

and enhancing visual insight of a large

quantity of data. It helps us to see data in

context, analyze and discover knowledge.

For companies across diff erent industries

– retail, logistics, banking and Finance,

Insurance, energy etc., data visualization

off er terrifi c opportunities to identify

new products or uncover customer

propensities that can provide insights

of tremendous value to Businesses. For

example, in a retail industry, increased use

of geo-spatial visualization and analysis,

the location of store, the diff erence in

market size according to region, price and

compensation studies in regard to specifi c

regions, etc. refl ect more clearly their

potential advantage.

Data Visualization techniques often

comes handy while representing large

quantities of data and help making sense

of big data and thus provide an exploratory

platform for gaining deeper and clear

insights. Some of the key functions of

visualization are highlighted below.

• To present large volumes of data

(structured or unstructured)

eff ectively and elegantly.

• Provide a platform for exploring

various facets of information

aesthetically and interactively.

• Promote a deeper level of

understanding of the data under

investigation and assists us in

drawing conclusions.

• Share information eff ectively to

persuade, collaborate and emphasize

important aspects of data.

A Simple Process for Visualization As the data and the number of sources of

information keeps growing, extraction of

suitable information and presenting in a

human consumable form becomes a great

challenge. However, a data analyst can

systemically increase the value of data

through two major processes – one, Data

Cleansing/Pre Processing and the second,

Visualization process. Visualization is a six

step process.

• Mapping : is encoding of data into

visual form. It is used for achieving

accurate relationship between data

points and visual objects that are to

be described.

• Selection : of attributes from the

data which aims for right pictorial

representation.

• Presentation : is eff ective management

and organization of information in

the available screen space.

• Interactivity : is providing facilities to

organize explore and rearrange the

visualization.

• Human factors : are easy readability

and accessibility of information for

end user.

• Evaluation: is fi nding out eff ectiveness

in the created visual, if we have

succeeded in reaching our goal in

creating lucid and easy to understand

graphics.

A Brief Survey of Graphical TechniquesCharting or Graphing is small subset of

visualization where the data in question is

explained with the help of bar charts, line

charts or pie charts.

Information graphics or infographics

are graphic visual representations of

information, data or knowledge intended

to present complex information quickly

and clearly. They can improve cognition

by utilizing graphics to enhance the

human visual system’s ability to see

patterns and trends. Infographics are

used to communicate a message, to

simplify presentation of large amount of

data, often diff erent facets arranged in a

thematic way.

A Scorecard is a tabular visualization

of measures and their respective targets

with visual indicators to see how each

measure is performing against their

targets at a glance. Scorecards may

contain columns that show trends in spark

lines. It measures performance against

goals. It displays the graphic indicators

that visually convey the overall success or

failure of an organization in its eff orts to

achieve a particular goal.

A report is the presentation of

data transformed into formatted and

organized according to specific business

requirement. Reports contain detailed

data in a tabular format and typically

display numbers and text only, but

they can use visualization to highlight

key data.

Dashboarding takes visualization

a step further by aggregating several

diff erent pieces of visual information in

a single location. As quoted by Stephen

Few, “dashboarding is a visual display of

the most information needed to achieve

one or more objectives which fi ts entirely

on a single computer screen so that it

can be monitored at a glance.” A typical

dashboard might contain a scorecard,

an analytical report and an analytical

chart. Digital dashboards are laid out to

track the fl ow inherent in the business

process that they monitor. Dashboard is

a user interface that is used to organize

and present information in a way that is

easy to read. A good dashboard presents

information about important data, with

fewer graphs and time overview.

To generate visualization, data plays

a major role. In order to visualize, data

need to be in one of the format.

Following are various data formats

that are available.

• Spreadsheets are electronic

document in which the attributes are

stored in columns and the objects are

stored in rows.

• JSON (Java Script Object Notation) is

a simple human readable fi le format

with data objects consisting of key

value pairs.

• XML (extensible Markup language)

is a fl exible way to create common

information formats and share both

the format and the data on the world

wide web

• Delimited Separated Values is format

of data that is used to store various

two dimensional arrays of data by

separating the values in each row

with specifi c delimiter characters.

Various types of delimiters are

comma, space, tab, and semi-colon.

• RDF (Resource Description

Framework) is a general framework

for describing website metadata, or

information about information.

• HTML (Hyper Text Mark-up Language)

is a language used for describing web-

pages using ordinary text.

In many cases, there will be a need

to use more than one data format (variety

Visualization-Techniques, Methods and Tools

Cover Story

Dr. KVSN Rama Rao*, Mr. Surya Putchala** and Midhun Thaduru****Prof., Dept. of CSE, MLR Institute of Technology,Hyderabad**CEO and Chairman, Zettamine Technologies***Associate Consultant, Zettamine Technologies


of data). In such situations, we need to

integrate diff erent varieties of data. To

create visualizations for such complex

data, there are several popular approaches

and methods which are discussed below.

Popular Approaches/Methods for Data VisualizationsThere have been some conventional

ways to visualize data in the form of

tables, histograms, pie charts and bar

graphs. However to convey a message

effectively there are some exciting

visual techniques that are available.

In addition to the above methods, there

are certain popular open source tools.

Technique Description

Choropleth

Thematic map where each spatial unit is fi lled with pattern or color which are scaled and normalized.

Choropleth used to show spatial variation of one or two variables at time by using color, shades

and/or patterns. E.g. population density of each state in a country.

Contour Heat Map

used to display density from the vector point of data. Contour heat maps are used to plot when there are

large number of clustered and continuous data points which can also take categorical variables. These

maps do not actually plot the data but designs a surface fi t to the data. E.g. density of population.

Chord Diagramused to display inter-relationship between group of entities. The data is arranged around the circle

and the relationships are displayed by arcs.

Collapsible Tree

Used for hierarchical data of long nested lists on the web pages can be diffi cult to understand.

The tree view, a user interface widget that displays hierarchical data as nested lists, solves this

problem by making lists collapsible and expandable; a list can be opened by or closed by clicking

on its parent list item. where the parent node and children nodes are are joined by arcs or line. E.g.

government divisions and sub-divisions.

Tree Map

Used for hierarchical data that shows attributes of leaf nodes using size and color coding. Tree

maps enable users to compare nodes and sub-trees even at varying depth in the tree and help them

spot the pattern. E.g. visualization of continents, countries, population and area

Calendar Heat MapChart time series onto vector of dates. E.g. Twitter activity of a celebrity on each day.

Method Description

Word cloud

is a method of visualizing unstructured text data. Word cloud expresses the occurrence of words in

the text form with size of word or phrase directly related to the frequency of occurrence with which

the word has occurred in the text document. Word cloud helps quickly analyze the main focus or

topics of discussion and can also help us in sentiment analysis.

Association Trees

are used for understanding word association in large quantities of text. Association is most

commonly used in social media text, News analysis or customer feedback. Latent Semantic

Analysis (LSA) is a statistical computation used to identify relationships between a set of

documents and the terms contain by producing a set of concepts related to the documents and

terms. The main idea behind LSA is that all the word combinations in which a given word and

word does not appear can determine the similarity of word meanings. Association trees are a

way defining such similarities.

Cubism Horizon graphsis used to analyze time series, or streaming content. Cubism Horizon graphs is an intuitive way of

project real-time time series plot. Horizon charts reduce vertical space without losing resolution.

Self-Organizing maps or Topological

Analysis

is used for relationships and gaining insights from multidimensional data from multiple sources. A

topological network represents the data by grouping similar data points into nodes and connecting

those nodes by an edge if the corresponding collections have data points in common. The

visualization techniques comes under the heading of scatter plot methods, where the data points

are projected on to 2D or 3D dimensional space, then plotting projections on the coordinates in

usual way.

Network Graphs

is used to study meaning and relationships between large contextual data. These graphs are used

to quantify relationships between diff erent vertices of data. These graphs can be directional or

non-directional based on requirement. A network is a collection of points; called vertices with lines

connection these points are called arcs.


Abo

ut th

e A

utho

rs

Dr. KVSN Rama Rao is a Professor,Dept of CSE at MLR Institute of Technology,Hyderabad.He is a Doctrate in Computer Science with over two decades of academic experience. He has published several papers in reputed International and National journals and conferences. His research interests are Cyber Security and Big data.

Surya Putchala is CEO and Chairman for ZettaMine Technologies, a fi rm focuses on providing high end educational and Management consulting services to Business around the world. It also aims to become the fi rst think tank in “Big Data” space in India. Over the last 2 decades, he provided thought leading consulting solutions in the areas of Business Intelligence, Data Warehousing, Data Management and Analytics to Fortune 500 Clients. He has architected commercial Analytical Applications such as Product MDM and Procurement Optimization. He has held senior leadership roles with fi rms such as GE capital, Cognizant, Accenture and HCL.

Midhun Thaduru is an Associate Consultant at ZettaMine Technologies. He is with the Data Science team and focusses on Statistical Analysis, Exploratory Data Analysis, machine learning and Visualization. He extensively uses R, python, D3.js for his day to day programming. His area of focus is in Life Sciences (Pharma) and Insurance, particularly, Payer and Provider analytics. His interests are in developing high performance algorithms for Predictive modelling. Midhun graduated from BITS, Pilani.

Open Source Visualization ToolsR is a programming language used for

Statistical Analysis, Data Visualization and

Predictive Modelling. R is an implementation

of S language combined with lexical scoping

semantics. R is a scripting and an interpreted

language i.e. a programming language for

which most of the implementations execute

instructions directly without compiling the

program into machine language. R is an open

source software with great contribution

from R-community towards R-programming

in the form of packages which are available

on Comprehensive R Archive Network

(CRAN).

The base graphs in R are used most

commonly and are a very powerful system

for creating 2-D graphics. The main

function for base graphic is plot(). The

base graphs are loaded by default into R.

Grid is an alternative graphics system

added to R that allows for the creation of

multiple regions on a single graphics page.

The grid package needs to be loaded before

it can be used by using library function.

lattice graphics is a powerful

Implementation and elegant high-

level data visualization system with an

emphasis on multivariate data. The lattice

package is an implementation of Trellis

graphics for R originally developed for the

S-Language. The lattice consists of high-

level generic functions each designed

to create a particular type of display by

default. Lattice gives advantage of high

user controllable settings.

ggplot2 is a plotting system which

takes the best from the base and lattice

graphics. The plot can be split into

scales and layers which gives the added

advantage over base plot.

rShiny is an interactive web application

framework for r which helps us do our

analysis in dynamic fashion. Shiny combines

the computational power of R with

interactivity of modern web. rShiny has

its own capabilities which doesn’t require

HTML, CSS or JavaScript Knowledge.

D3.js is a Java Script Library which helps

build data visualization framework. D3

stands for Data Driven Documentations.

D3.js is a powerful tool for creating dynamic

and interactive data visualizations. D3.js

uses Scalable Vector Graphics, JavaScript,

HTML5, and Cascading Style Sheets

(CSS3) standards.

google charts is a simple and powerful

open source which can be used to visualize

simple line charts to complex hierarchical

tree maps. Google charts are a specialist

for geocharts. Google charts can easily

connect charts and controls into interactive

dashboards. It can also be used to connect

to data in real time using variety of data

connection tools and protocols.

Gephi is an interactive visualization

and exploration platform for all kinds of

network and complex systems, dynamic

and hierarchical graphs. Gephi is used for

exploratory data analysis, link analysis,

social network analysis, and biological

network analysis and poster creation.

Lumify is a open source big data analysis

and visualization platform. Its intuitive

web-based interface helps users discover

connections and explore relationships in

their data via a suite of analytic options,

including 2D and 3D graph visualizations,

full-text faceted search, dynamic

histograms, interactive geographic maps,

and collaborative workspaces shared in

real-time.

ConclusionVisualization provides great value addition

for the data that is to be analyzed. There

are several techniques, methods and open

source tools for visualization. Once the data

is ready in a particular format, visualization

can be generated by using these techniques.

References[1] M Khan and S S Khan, (2011). “Data

and Information Visualization

Methods, and Interactive

Mechanisms: A Survey”,

International Journal of Computer

Application (0975-8887), vol. 34 –

No.1, November 2011

[2] https://www.dashingd3js.com/why-

build-with-d3js

[3] S Card, J MacKinlay, and

B Shneiderman, (1998). “Readings

in Information Visualization:

Using Vision to Think”. Morgan

Kaufmann.

[4] Alfredo R Teyseyre and Marcelo

R Campo, (2009). “An Overview

of 3D Software Visualization”, IEEE

Transactions on Visualization and

Computer Graphics, vol.15, No.1.

[5] L Chittaro, (2006). “Visualizing

Information on Mobile Devices”,

ACM Computer, v.39 n.3, p.40-45.

[6] Edward R Tufte, (2007). “The Visual

Display of Quantitative Inforamtion”,

Second Edition, Graphics Press.

[7] http ://what is .techtarget .com/

defi nition/infographics

[8] h t t p : // t h e n e x t w e b . c o m /

dd/2013/10/16/10-ways-use-

infographics/

[9] h t t p : // b l o g s . w s j . c o m /

cmo/2014/06/24/outside-voices-

t h e - v i s u a l - w e b - i s - c h a n g i n g -

e v e r y t h i n g - i n - m e d i a - a n d -

advertising/

[10] h t t p : //s p o t f i r e . t i b c o . c o m /

blog/?cat=34

[11] http://www.computer.org/portal/

w e b /c o m p u t i n g n o w/a r c h i v e /

january2014

[12] http://smartdatacollective.com/

jgptec/140486/3-big-trends-data-

visualization

[13] http://code.stephenmorley.org /

javascript/collapsible-lists/

n


The process of learning in Science,

Technology, Engineering, and Mathematics

(STEM) fi elds using visualization will be

more interesting and can surely improve

the eff ectiveness in the learning and

teaching process. Besides making it easier

for students to understand the STEM

subjects, facilitates teachers in teaching

STEM lessons material in the classroom.

VisualizationVisual means of processed information

is referred as Visualization. The foremost

objectives of any visualization

techniques are data exploration

and communicating information

effectively to the intended audience.

Data Exploration is the practice of

using visualization techniques to find

unforeseen relationships between

data points or sets of points from huge

databases. Once a relationship has been

found, a similar visualisation will be used

to communicate that will be a reference

to others. Visualization techniques can

also be applied to information that is

already known and it has the potential

to organize large amounts of data in

meaningful ways. Visualizations are

often static, dynamic and interactive,

allowing users to manipulate the data

that they observe. Static visualizations

are the one that do not change with

time. Dynamic visualizations are

those in which the graphical elements

being displayed can change with time.

Interactive visualisation involves

humans’ interaction with computers

to create graphic illustrations of

information.

Visualization in EducationThe application areas of Visualization

are many, one such area is Education.

Thomas Carpenter and James Hiebert

in[1] address the role of visualization in

education and also represent a framework

for knowledge representation in the

domain of education way back in early

1990s. The purpose of any visualization

to be used in an educational context

is to facilitate the learning of some

knowledge in the form of algorithm,

concept, idea, relationship, fact, decision

making and application. In order to

accomplish this visualization must make

connections between knowledge of the

learner has and the knowledge being

taught. Knowledge of a learner might

be of Fragmented and knowledge being

taught might be Coherent. Fragmented

knowledge results in domains in

which the learner has had little or no

experience. Coherent knowledge refers

to a wealth of information to draw upon

from a domain.

STEM EducationEducation in any domain can be viewed

as the externally facilitated development

and representation of knowledge.

Education particularly in the field of

Science, Technology, Engineering, and

Mathematics (STEM) subjects is quite

difficult for the students to understand.

This is because the STEM subjects are

not simple and it requires high levels

of thinking and reasoning from the

students, especially in the areas of

Concepts and Logics. In addition, the

subject material is also quite difficult to

teach. Teachers, as educators, need a

specific way to teach in order to make the

material easily understood by students.

To make teaching more attractive and

effective, it needs a learning model or

a medium which can provide a concrete

conceptual, illustration, and definitive,

in order to improve the effectiveness of

the learning process and to achieve the

learning objectives.

Visualization tools in STEM EducationTeachers and students have long been

using charts and graphs to analyze and

make sense of data. The eff ective use

of any technology in teaching requires

thoughtful consideration and planning.

Technology has brought these tools to

a new level. In order to design eff ective

visualizations in STEM subjects it is

necessary to know the level of audience.

Table 1, list some of the open source

visualization tools used by educators to

provide STEM lessons’ material in the

classroom. This visualization tools acts

either as a primary medium or as an

alternative tool in the teaching learning

environment.

A.B. Karthick Anand Babu*, D. Maghesh Kumar** and G. RajaRaja Cholan****Managing Director, KK Infotech, Thanjavur**Assistant Professor, Department of Software Engineering, Periyar Maniammai University, Vallam, Thanjavur***PRIST Univerity, Thanjavur

Visualization for STEM Subjects

Cover Story

S.No Tools Features

Science Tools

1. ChemSketch • Tool for learning Chemistry

• Includes comprehensive chemical drawing package,

• Off ers drawing of polymers, organic elements and structures

• h t t p : //w w w. a c d l a b s . c o m /re s o u rc e s /f re e w a re /

chemsketch/

2. Step • Tool for learning physics

• Simulator supports classical mechanics, particles, springs,

gravitational and coulomb forces, collisions, molecular

dynamics, and much more.

• https://edu.kde.org/applications/all/step

Technology Tools

3. gEDA • Refers to GPL'd Electronic Design Automation tools,

• Supports the teaching of electronics to the students of

technical institutions.

• off ers various analog, digital simulation and printed circuit

board (PCB) layout capabilities.

• http://git.geda-project.org/

4. Player Project • Supports teaching of robotics in technical institutions

• Provides a simulated network interface for sensors and to

control robots

• Simulates the 2D and 3D robotic interaction in environment.

• http://playerstage.sourceforge.net/index.php?src=index

Continued on Page 41


ConclusionVisualization technology will provide

a detailed representation and creates

interesting defi nitions of Concepts,

Theories, Formulas, and the Principles

that are contained in the STEM materials.

Visualization tools can also be useful for

bridging the gap between domains of

knowledge and applications. Knowledge

base of the audience is much needed

for customizing and designing eff ective

visualizations. There are visualization tools

that are available as open source products,

which allow students and educators to

customize the tool and to learn the domain

of education.

References[1] Hiebert, James & Carpenter, Thomas

P. "Learning and Teaching with

Understanding" Handbook on

Mathematics Teaching and Learning1992.

[2] h t t p : //e n . w i k i p e d i a . o r g /w i k i /

Interactive_visualization

[3] http ://www.dpi .state .nc .us/cte/

program-areas/technology/ n

Engineering Tools

5. OpenModelica • Tool for modelling and simulating industrial applications

such as control system design, embedded system modelling

and numerical algorithms

• https://www.openmodelica.org/download/download-linux

6. OpenSCAD • Provides a software for creating solid 3D Computer Aided

Design models

• off ers two modeling techniques such as constructive solid

geometry and extrusion of 2D outlines

• http://www.openscad.org/about.html

Mathematical Tools

7. Maxima • Tool for Algebra and calculus teaching

• Manipulates and provides good numerical results

• http://www.gnu.org/software/maxima/

8. GeoGebra • The award-winning math app combines tools for, arithmetic

algebra, calculus and geometry.

• Supports instructors to create worksheets and suitable

teaching aids for teaching maths to the students of schools,

colleges and university.

• http://www.geogebra.org/cms/

Abo

ut th

e A

utho

rs

A.B. Karthick Anand Babu is member of CSI and Managing Director, KK Infotech, Thanjavur, Tamilnadu. He has rich experience in teaching and software development. He can be contacted through [email protected].

D. Maghesh Kumar is devoted Assistant Professor of Faculty of Software Engineering, Periyar Maniammai University,Tamilnadu. He has more than 20 years of teaching experience. His research area includes “Big Data” , “Cloud Computing” and “Internet of Things”. Reach him through [email protected]

G. Raja Raja Cholan, Assistant Professor,Department of Computer Science and Engineering, PRIST University. He has also served as a Coordinator for Centre for Knowledge Management. His primary research area includes Network Security, Internet of Things and Data Science. He can be reached at [email protected]


IntroductionCharacterizing and classifying the data

is an emerging need for data mining

functionality. The aim of data mining is

to extract and classify the data based on

the data characteristics. We may have

pre-requisite to prior knowledge about

the number of distinct data classes for

any data mining functionality. For this

valuable determination, we introduce the

visualization tool called as Visual Access

Tendency (VAT), which is used to detect the

information of number of data clusters (or

classes) in visual form. The VAT has been

introduced by author Bezdek. The visual

pattern apparent will presents with the more

clarity of visual results for data classes (or

clusters). A very beginner of data clustering

can makes use of this tool for accessing of

data clusters from the organized data.

MotivationMany algorithms of data clustering such

as k-means, hierarchical, density based

clustering algorithm etc have to produce

the clustering results without knowing

any prior knowledge about number of

clusters. Suppose the user has trying the

clustering results with incorrect k value in

the k-means, then the k-means procedure

may also produce the inaccurate clustering

results. This is the key motivation for

choosing of visualization tool (VAT) and

it has capable for detecting the number of

clusters (k value) as correctly. Thus, this

visualization tool helps for achieving the

best clustering results.

HistoryInitially, the author Bezdek has developed

the algorithm of VAT tool for classifying

of clusters. Later he has modifi ed with the

spectral approach called as SpecVAT which

works better than VAT where in the cases of

tough data such as it may be huge, higher

dimensionality etc. He has also developed

another version iVAT (Improved VAT) for

the cases of path based data. Therefore,

we can use any one of the visualization tool

among the three based on our degree of the

complexity of the data.

Visual Access Tendency (VAT)The following key diagram introduces

the processing steps of VAT tool.

Data Objects The organization of data consists of a set

of data objects which is further clustered

based on the similarity features for

every two-element subset data objects.

Initially, the data is organized as data

matrix (n x m) form which can be shown

as follows with n number of objects and

m number of properties

O\P P1 P2 ............... Pm

O1 X11 X12 .................. X1m

O2 .

. .

On Xn1 Xn2 .................. Xnm

These n data objects are compared

using the distance measures such as

Euclidean, Mhanttan, and Minkowski etc

for obtaining the dissimilarity matrix R.

The following matrix is represents the

dissimilarity matrix R (with size n x n)

O\P O1 O2 ............... On

O1 0 D12 .................. D1n

O2 . 0

. .

On Dn1 Dn2 .................. 0

Dissimilarity Matrix and its VAT ImageThe dissimilarity matrix R is the input of VAT,

and the VAT tool outputs the VAT Image

with fi nite number of visual squared shaped

dark blocks. Thus, we detect the number of

clusters by counting of square shaped dark

blocks along the diagonal of VAT Image. The

accessing of number of data clusters by VAT

tool is depicted by the following results

Advantages of VAT Tool

1. It presents the information in visual

so that even normal user also can

able the number of clusters

2. The VAT tool is uses only the Prim’s

logic, so there is no complexity about

understanding of how it works

3. We use this visualization to any kind

of data such as text, image, audio,

and video etc for defi ning of clusters

or classes

4. It is possible to extract the correct

k value; so that it is useful for the

k-means

Limitations

1. It takes much time for solving of k

value where in the cases of big data

2. We have less clarity of visual results

if the data clusters are overlapped

3. The visualization results will depends

on distance measures

Designing of VAT Tool

The VAT uses the logic of Prim’s

algorithm for the major purpose of

changing the current indices of the data

objects. In this way, the indices of data

objects are reordered by the VAT tool.

Reordering the indices of data objects

would shown the number of clusters by

squared shaped dark blocks along the

diagonal in the VAT Image, this is clearly

shown in Fig. 2a. The main aspect of VAT

tool is to display the hidden clustering

structure for a set of data objects. The

logical steps of VAT tool are described

as follows

1. Choose the longest edge weight

e(vi,vj) from the dissimilarity matrix R

Index=1;P(index)=vj; Set I = { };

J = {1,2,…,n};

I = I ∪ {j} and J = J – {j}

2. Use Prim’s Logic

For the interactions t = 2,…, n

Select (i,j)∈ arg minp∈I,q∈J {Rpq} ;

P(t) = j;

I = I ∪ {j} , and J = J – {j}

3. Reordered dissimilarity matrix

[RRi,j] =[RP(i),P(j)]

Visualization Tool for Data Mining

Technical Trends

Dr. B. Eswara Reddy* and Mr. K. Rajendra Prasad***Professor, Dept. of CSE, JNTUA, Ananthapur**Associate Professor, Dept. of IT, RGM College of Engg. & Tech.,Nandyal

Fig. 1: Processing steps of VAT

Fig. 2a: Dissimilarity matrix ‘R’ and its dissimi-larity image ‘I’ (before applying the VAT tool)

Fig. 2b: Aft er applying VAT tool


4. Display the VAT Image of RR

Let R=[0.00 0.73 0.19 0.71 0.16;

0.73 0.00 0.59 0.12 0.78;

0.19 0.59 0.00 0.55 0.19;

0.71 0.12 0.55 0.00 0.74;

0.16 0.78 0.19 0.74 0.00];

Tracing steps for VAT Tool Algorithm for

the Input R(Dissimilarity Matrix)

Finally, we display the VAT image

in MATLAB by executing the command

of imshow(RR), then it displays image of

Fig. 2b. Hence, we can extract the number

of clusters information from this visualized

image.

ConclusionWe make use of visualization tool as VAT

especially in the data mining. The VAT

tool visualizes and reveals the similarity

structure of data objects. Hence we have

a prior knowledge about the number of

data classes (or clusters) which helps

the further processing of data mining

functionality. Specifi cally this visualization

tool has been used for the purpose of

unsupervised learning. In the k-means,

we can attempt the good clustering

results by this prior k value. Other

clustering algorithms are also required the

knowledge about number of clusters.

References[1] Liang Wang, James Bezdek, Enhanced

Visual Analysis for cluster tendency

assessment and data partitioning,

EEE Trans. on Knowledge and Data

Engineering, 22(10), 1401-1413(2010).

[2] http://www.ece.mtu.edu/~thavens/

pubs.html


code/VAT.m


code/iVAT.m

[5] Timothy C Havens ,and James

C Bezdek, An Effi cient Formulation

of the Improved Visual Assessment

of Cluster Tendency (iVAT) Algorthm,

IEEE Trans. on Knowledge and Data

Engineering. 22( 10), 1401-1413(2010).

[6] Liang Wang, James Bezdek,

Automatically Determining the

Number of Clusters in Unlabeled

Datasets, IEEE Trans. on Knowledge

and Data Engineering, 21(3), 335-

349.(2009).

[7] B Eswara Reddy, K Rajendra Prasad,

Reducing runtime values in minimum

spanning tree based clustering by

visual access tendency, International

Journal of Data Mining & Knowledge

Management Process, 2(3), 11-22

(2012).

[8] James Bezdek, VAT: A Tool for Visual

Assessment of Cluster Tendency, Proc.

Int’l Joint Conf. Neural Networks. 2225-

2230 (2002).

n

Step No. Iter. No. Choose the Max edge

from R (In Step1) or

Choosing of Min Edge

from the vertices I to J

(In Step 2)

P I J

1 - (2,5)-Max Edge P(1)=5 {5} {1,2,3,4}

2 t=2 (5,1)-Min Edge P(2)=1 {1,5} {2,3,4}

3 t=3 (1,3)-Min Edge P(3)=3 {1,3,5} {2,4}

4 t=4 (3,4)-Min Edge P(4)=4 {1,3,4,5} {2}

5 t=5 (4,2)-Min Edge P(5)=2 {1,2,3,4,5} { }

Abo

ut th

e A

utho

rs

Dr. B. Eswara Reddy Graduated in B.Tech.(CSE) from Sri Krishna Devaraya University in 1995. He received Masters Degree in M.Tech.(Software Engineering), from JNT University, Hyderabad, in 1999. He received Ph.D in Computer Science & Engineering from JNT University, Hyderabad, in 2008. Currently he is working as professor in the Dept. of CSE, JNTUACE, Anantapur. His research interests include Pattern Recognition & Image Analysis, Data Warehousing & Mining and Software Engineering. He is a life member of CSI, ISTE, IE, ISCA and member IEEE.

Mr. K. Rajendra Prasad has a research scholar at JNTUA, Anantapur. He has completed B.Tech(CSE) at RGM Engg College, Nandyal and M.Tech(CSE) at KBN College of Engg, Gulbarga. Currently, he is pursuing PhD (CSE) at JNTUACE, Ananthapur. He is life member of CSI and a member of IEEE.


Signifi cance of Visualization in Gene Expression DataBioinformatics is an exploration area

that manages huge amount of data.

Gene expression analysis is a signifi cant

instance of Bioinformatics which tries to

identify expression levels of genes through

microarray experiments. Gene expression

data generated through this process

typically represents thousands of gene

expressions across multiple experiments.

Mostly, gene expression data are noisy

and of high dimensionality which makes

the analysis process diffi cult. They

have to be transformed into a reduced

set of genes for subsequent analysis.

Transforming large-scale gene expression

data into a meaningful set of data can be

done through preprocessing techniques

and through feature reduction methods.

The primary objective of analysis could

be to fi nd functional groupings of genes

by discovering similarity or dissimilarity

among gene expression profi les, or

predicting the pathways of previously

uncharacterized genes. This can be

done through diff erent supervised and

unsupervised methods. The challenge

is to interpret and to make sense out of

this processed information. Representing

the analysis output through a suitable

visualization framework simplifi es the

reasoning process and allows users to

easily explore the relationships among

genes and conditions.

Visualization ProcessData mining and Visualization techniques

work hand in hand to enable complete

elucidation and user interpretation of

large datasets. The sandwich technology

that combines both techniques is

useful in molecular biology where large

volumes of sequences and gene arrays

can be effi ciently mined and represented

in graphs, trees and chains to extract

meaningful information. Visualization

process of gene expression data focuses

on data preprocessing, data reduction,

clustering/classifi cation, visualization

technique and Analysis & Knowledge

discovery. The visualization process fl ow

is shown in below Fig. 1.

Genes that contribute noise will

lead to wrong analysis and results.

Preprocessing techniques helps in

converting raw data to meaningful

biological data by removing noise, low

intensity, bad quality and empty spots from

gene expression data using Normalization,

Filtration, Sampling, Extraction, Labeling,

Scanning etc. Feature reduction procedure

is an eff ective approach to downsize the

data. For example, when the dataset has

thousands of genes and few samples and

the objective is to classify novel samples

into known disease type, dimensionality

reduction methods helps in fi nding

a subset of informative genes which

can be processed for further analysis.

Classifi cation helps in understanding the

complex relationship/interaction among

the various conditions and features of a

biological object. For example, a training

dataset has diseased and normal cells and

when a new cell is obtained, classifi cation

process has to automatically determine

whether it is normal or a diseased

cell. Cluster analysis helps in grouping

genes with similar function or grouping

samples with similar expression profi les.

Visualization techniques help in visually

inspecting and interacting with two/

three dimensional view of processed data

set. Following table shows the available

visualization techniques.

Sreeja Ashok*, Dr. M. V. Judy** and N. Thushara Vijayakumar****JRF, DST Funded Research Project, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham University, Kochi**Associate Professor, HOD, CS and IT, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham University, Kochi***JRF, DST Funded Research Project, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham University, Kochi

Information Visualization in Gene Expression Data

Technical Trends

Fig. 1: Visualizati on process fl ow

Visualization techniques

Objective Methods

Geometric techniques

Visualization of geometric transformations and projections of the data

Scatterplots Matrices , Hyperslice, Parallel Coordinates, Projection Pursuit Techniques, Prosection Views, Landscapes

Icon- based techniques

Visualization of the data values as features of icons Chernoff -Faces , Stick Figures ,Shape Coding, Color icons, Tile Bars

Pixel-oriented techniques

The basic idea of pixel-oriented techniques is to map each data value to a colored pixel. Each attribute value is represented by a pixel with a color tone proportional to a relevance factor in a separate window

Query-Independent Techniques -Simple Techniques -Recursive Pattern Technique -Space-Filling CurvesQuery-Dependent Techniques -Spiral Technique -Circle Techniques -Axes Technique

Hierarchical techniques

Visualization of the data using a hierarchical partitioning into two- or three-dimensional subspaces

Treemap , Cone trees , Dimensional Stacking , InfoCube ,Worlds-within-Worlds , Box plots

Available Visualization Techniques


Brief summary of some of the prominently

used visualization techniques for gene

expression data are given below

• Heat map: Provides an overview of

the data. A colored matrix display

will represent the matrix of values

as a grid, number of rows equal to

the number of genes being analyzed,

and the number of columns equal

to expression levels (Fig. 2a). A big

challenge for interpreting patterns in

a colored matrix is that the rows and

columns need to be re-ordered in a

meaningful way.

• Scatter plots : Scatter plots are

useful for pair wise comparisons,

fi nding which genes are excessively

expressed, they provide an overview

of the multivariate distribution of

expression values (Fig. 2b)

• Parallel coordinates: Parallel

coordinates are a common information

visualization technique for high-

dimensional data sets. Expression

data for each gene corresponds to a

dimension in the data set, with data for

each gene being represented by one of

a series of parallel vertical axes. Color-

coding of expression profi les are very

effi cient (Fig. 2c)

• Dendrogram: The dendrogram

method plots the hierarchical

tree information obtained as a

graph from the cluster pane. The

numbers along the horizontal axis

represent genes and the height of

the diagram indicates the distance

between the genes. Diff erent color

codes can be assigned to represent

null values or zero values. Shades

represent intensity or magnitude of

expression(Fig. 2d)

ConclusionEvery day new discoveries are made in the

fi eld of molecular biology & genetics and

sheer volume of data comes out from studies.

These vast quantities of heterogeneous,

dynamic and largely unprocessed

information have to be transformed into

a coherent and user friendly format easily

accessible to all. Analytical methods

together with visualization techniques play

a major role in exploring, analyzing and

presenting meaningful inferences.

References[1] Ashraf S Hussein “Analysis and

Visualization of Gene Expressions

and Protein Structures”, Journal of

Software , Vol. 3, No. 7, October

2008.

[2] Tangirala Venkateswara Prasad and

Syed Ismail Ahson , “Visualization

of microarray gene expression

data”, Bioinformation by Biomedical

Informatics Publishing Group, May

03, 2006.

[3] Wegman, E “ Hyperdimensional data

analysis using parallel coordinates.”

Journal of American Statistics

Association 85, 664-675.

[4] Pavlopoulos, G A, Wegener, A L,

& Schneider, R “A survey of

visualization tools for biological

network analysis. Biodata mining”,

1(1), 1-11.

[5] Chun Tang, Li Zhang and Aidong

Fig. 2: Visualizati on techniques for gene expression data

Graph-based visualization

Graphs (edges + nodes) with labels and attributes are used where emphasis is on data relationship (databases, telecom)Useful for discovering patterns

2D and 3D graphBasic Graphs (e.g., Straight-Line, Polyline, Curved-Line, Orthogonal Graphs)Enrichment Map

Distortion techniques

Global context/view of the information content. Hyperbolic tree , Graphical Fisheye view, Perspective wall , Polyfocal Display , 2D Bifocal Display

Dynamic/ Interaction techniques

Providing interaction mechanism that make it possible to manipulate visualization eff ectively and eff ortlessly

Brushing , Linking , Zooming & Panning,Detail on Demand , Filtering (Selection, Querying), Data-to-Visualization Mapping, Projections

Matrix Techniques

To simultaneously explore the associations of up to thousands of subjects, variables, and their interactions, without fi rst reducing dimension

Heat map

Hybrid Techniques

Integrated use of multiple techniques in one or multiple windows to enhance the expressiveness of the visualizations

Scatter plot of icons with dynamic zooming and mappingDynamically link and brush scatterplot matrices, star icons, parallel coordinates. Graph Matrix Visualization.


Abo

ut th

e A

utho

rs

Sreeja Ashok is currently working as JRF for a DST Funded Research project at Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham University, Kochi. She has completed MCA, has 14 years of experience in IT industry (Avenir & Wipro Technologies) with expertise in Software Engineering, Project Management, Quality Management & Data Analysis, 2 years of teaching experience.

Dr. M. V. Judy is Associate Professor, Head of the Department of CS and IT at Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham University, Kochi and also principle Investigator for DST Funded Research Project under Cognitive Science Research Initiative. She has completed MCA, Mphil and Ph.D in Computer Science from reputed universities/institutes and has 12 years of teaching experience.

N.Thushara Vijayakumar is a former lecturer at NIT Calicut, completed M-Tech in Genetic Engineering from SRM University, Chennai and B-tech from Anna university, Chennai. Currently working as JRF for a DST Funded Research project at Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham University, Kochi.

Zhang , “Interactive Visualization and

Analysis for Gene Expression Data” ,

HICSS-35: 35th Hawaii International

Conference on System Sciences.

[6] Poornima. S, Dr. J Jeba Emilyn,”

A Comparative Analysis on

Visualization of Microarray Gene

Expression Data”, ISSN: 1694-2108 |

Vol. 12, No. 1. APRIL 2014.

[7] Purvi Saraiya, Chris North, Karen

Duca, “An Evaluation of Microarray

Visualization Tools for Biological

Insight”, IEEE Symposium on

Information Visualization 2004,

October 10-12, Austin, Texas, USA.

[8] Janne Nikkila, Petri Toronenb,

Samuel Kaskia, Jarkko Vennaa, Eero

Castrenb, Garry Wongb,” Analysis and

visualization of gene expression data

using Self-Organizing Maps”, Neural

Networks 15 (2002) 953–966. n


In the current world each organization

is moving towards big data. Big data

basically consist of data storage and data

analysis. Earlier people used to store

only important data, since there was

no cost effective way of storing all the

data. But most of the organisations and

researchers felt the need of huge volume

of data for building up mathematical

models, so that complex problems can

be solved. However, in the last few years

many frameworks and databases have

been designed to store huge volume

of data using commodity hardware.

Whenever we talk about big data there

are 3 V’s that come to our mind Velocity

(the rate at which the data is growing),

Variety (structured, semi-structured and

unstructured) and Volume (Size of the

data in terms of petabytes or xetabytes).

There are many solutions which have

been proposed for the same, but most of

the time people are not aware of which

framework or database to choose. While

creating a database for any particular

application, the architect should

consider three features: consistency,

availability and partition tolerance.

Consistency means even if concurrent

updates are happening, users will get

the updated result irrespective of the

place from where they are accessing the

data. Availability means data should be

available to the users 24*7 irrespective

of the load on the server. Partition

tolerance means even in the case of

the partial failure the system should

be functional. Brewer suggested a CAP

theorem, which is applicable for all the

databases. According to him a database

cannot have all the three features, i.e

consistency, availability and partition

tolerance. They can have only two

features out of the three, for Example:

Consistent & Available: postgres

My SQL, SQL server.

Available & Partition Tolerance:

Cassandra, RIAK, Voldemort, CouchDB.

Consistent & partition tolerance: Neo4J,

MongoDB, HBase, Hypertable, Redis.

CassandraThere are many distributed database

systems available but they have only

two features out of the three desired

features. Cassandra is a distributed and

decentralized database, which has high

availability and partition tolerance, but at

the same time it is eventually consistent

which means that its consistency level

can be increased by sacrifi cing the

availability. It is capable of storing all the

forms of digital data i.e structured, semi –

structured and unstructured data.

Cassandra[1] was designed with

a motive to have a database that

should be able to write at a very high

speed irrespective of the load on the

server or even if most of the nodes in

the cluster are dead or unavailable. In

Cassandra[2] the write operation is very

fast as compared to the read operation.

During the write operation, data is fi rst

written to the commit log along with the

instructions for the durability purpose

and the fl ag bit is set to one,

then the data is moved to the

memtable which resides in RAM,

when the memtable exceeds a

given threshold value the data

is fl ushed into the SStable which

is present in the secondary

memory. Once the data is written

in the SStable, fl ag bit is again set

to zero or if anything goes wrong

the data will again be sent to the

memtable from the commit log.

But the user gets the confi rmation that

the data is written successfully, when the

data is fi rst written inside the commit log

fi le, and he does not have to wait for all

this process to complete.

Cassandra is a distributed system

and all of us know that the distributed

system works on network, which is one

of the highly unreliable resource in this

world, we don’t know when the traffi c on

the network is going to increase/decrease

or it will get disconnected. Keeping this

thing in mind Cassandra was provided

with a mechanism known as Hinted-

Handoff , which means that if a user wants

to write any data on a particular node(A)

which is unavailable, then a hint will be

written on its neighbor node(B), stating

that whenever node(A) comes back

node(B) will pass this hint.

RMany organizations are moving towards

big data analysis and visualization. R

is an open source tool which is being

used by most of the analysts for building

up a mathematical model such as

recommendation system and predictive

system. To build up such models many

optimized algorithms packages[3] are

present in R such as SVM, kNN, Decision

Trees, outliers, Naïve Bayes, adaboost ,

JRip and many more.

R has a Cassandra package

(RCassandra[4]) to access the functionality

of apache cassandra cluster such as login,

updates, queries and read/write operation

without using java.

Following plot shows the iris data in 4

dimensions which has been fi rst inserted

into Cassandra database using R and then

read the same data for analysis. Plot()

function is used for the representation of

data.

Cassandra Vs SQL:The SQL was designed with a motive to

have database that can store only the

normalized form of data because at that

time the hardware cost was very high, but

due to normalization the query needs to

refer multiple tables for fetching a particular

record, due to this the latency time of the

query is very high and which aff ects the

overall performance of the application.

SQL was designed to handle data

in terms of Gigabytes and up to some

extent Terabytes. But the Cassandra can

handle the data in terms of petabytes and

xetabytes.

In SQL the table schemas are defi ned

upfront and the users are forced to insert

data for each column or else they have to

use the NULL value.

Scaling up and scaling down depending

upon the load is very expensive in SQL, but

in Cassandra you just have to plug in a new

node or remove the node. No confi guration

needs to be done on the cluster side.

Ris hav Singh* and Dr. Sanjay Kumar Singh***Working in Infosys**Associate professor, IIT-BHU, Department of Computer Science and Engineering

Big Data Visualization using Cassandra and R

Technical Trends


In SQL fi rst the database is designed,

then the queries are identifi ed to solve the

problem. But in Cassandra fi rst the queries

are identifi ed and then the data is organized

around the queries. There are no unions and

joins. Each query will refer to a single table.

Since SQL is a 100% consistent

database they need to use locks on

each transaction and if in a distributed

system the locks are not used properly

it will either lead it to starvation or

deadlock. Most of the time people say

that my data is important and it needs

to be consistent, but there are many

organizations such as Google, Facebook,

Amazon which have an inconsistent

database although there data is very

important.

References:[1] http://cassandra.apache.org/

[2] http://www.datastax.com/

[3] http://en.wikibooks.org/wiki/Data_

Mining_Algorithms_In_R

[4] http://cran.r-project.org/ n

Abo

ut th

e A

utho

rs

Ris hav Singh is currently working in Infosys and also pursuing his Ph.D (part time) from Indian School of Mines, Dhanbad.

Dr. Sanjay Kumar Singh is an Associate professor in IIT-BHU in the department of Computer Science and Engineering.

His main area of interest are Biometrics, Computer Vision, Image Processing, Video Processing, Pattern Recognition and

Artifi cial Intelligence.


IntroductionScientifi c Data Visualization is the branch

of science which deals with transformation

of scientifi c data into meaningful visuals

to comprehend and gain insight into the

underlying scientifi c phenomena. The

output data from scientifi c experiments

and simulations are normally sampled

in 2D or 3D grids. The grids provide

an effi cient data structure for data

storage and retrieval. A variety of grids

with diff erent topology and geometry

are constantly used for numerous

applications. The choice of a right kind

of grid depends solely on the application

domain. These grid-based data are then

processed by diff erent visualization

methods to generate visuals suitable for

human interpretation.

Over the years, researchers have

devised various methods, which form the

core part of any scientific visualization

system. There are various schemes of

classification for visualization methods.

Based on type of input data, these

can be broadly put into three major

categories, viz. Scalar, Vector and Tensor

visualization methods.

Scalar methods operate on the

data that represents scalar quantity viz.

temperature, pressure, density etc. In

vector fi eld visualization, we deal with

vector quantity based data (like velocities).

The Tensor data type is more complex

than other ones. They generally arise

from applications such as engineering

analysis (Stress-Strain tensors), molecular

diff usion measurements etc.

What are Vector FieldsVector fi elds are defi ned as the collection

of vectors over a region of space in

the domain. Mathematically, they are

represented as a vector-valued function

that assigns a vector at each point of the

fi eld. The examples of vector fi elds are

gravitational fi eld, electrical fi eld that

surrounds charges, magnetic fi elds and

velocity fi elds (Fig. 1).

Fig. 1: Vector fi eld with equati on Vx = x, Vy = -y in Matlab

In a vector field the vector

quantities can vary over space and time.

A static vector field represents vector-

values that change over space, while a

time-dependent one changes over both

space and time. One of the important

applications of vector field visualization

is study of flow (velocity). In case of

flow, the field is termed as velocity

field, which is frequently encountered

in vector visualization arena. We have

assumed a flow vector field for the study

of visualization methods. The concepts

are still applicable to other vector fields.

The flow field is further divided into two

categories: steady (time-independent)

and unsteady (time-dependent).

Visualization MethodsThe vector field needs to be visualized

effectively by considering both

magnitude and direction simultaneously.

The problem gets challenging if the data

size is large and time-variant. In recent

times, vector visualization techniques

have received widespread attention.

This is due to extensive research in

areas such as Metrological simulation,

Medical blood flow, Computational

simulation of air fl ow around aircrafts,

ships and diff erential equation systems.

The vector fi elds representing fl uids

are transparent in nature, thus making

the fl ow pattern invisible to us. The

visualization discerns the fl ow patterns

to convey its qualitative and quantitative

information. To get an insight of vector

fi eld it is necessary to explore the fl ow

both locally and globally. Based on the

density of representation[1], the vector

based methods can be classifi ed as local

and global techniques. A local technique

visualizes only a portion of domain, while

the complete fl ow is considered in global

techniques.

The local techniques create a

representation based on flow lines –

streamlines, streaklines and pathlines

etc. The flow lines are trajectory of

mass-less particles through the vector

field. They describe flow path with start

(come from) and end (will go). On the

other hand, global techniques visualize

the entire flow in single picture with

minimal user intervention. Examples

are line plots (hedgehogs), arrow plots,

glyphs, texture based methods (LIC

& Texture Splats). They give a sense

of vector magnitude and direction at

a point. E.g. at any point what is the

strength of flow and direction.

Lines, Arrows & Glyphs

These are the elementary visualization

techniques to make an overall picture of

the vector fi eld. They put icons such as

lines, arrows or 3D objects to highlight

local features (magnitude, direction,

time dependency) of the fi eld. The icons

are drawn directly at each data point.

Their scaling is controlled according to

magnitude and orientation of vectors.

Fig. 2: Arrowplot for Air fl ow over a city model

These methods are quite suitable

for 2D vector fields. In 3D, they

pose the problem of cluttering and

overlapping. As the number increases,

it is difficult to understand the

position and orientation of the field.

Visualization Methods for Vector Fields: An Insight

ResearchFront

Dilip Kumar Dalei*, B. V. Hari Krishna Nanda** and N. Venkataramanan****Scientist (ANURAG), Defence R & D Organization (DRDO), Hyderabad** Scientist (ANURAG), Defence R & D Organization (DRDO), Hyderabad*** Scientist (ANURAG), Defence R & D Organization (DRDO), Hyderabad


There is also no satisfactory scaling

mechanism exists. With large scaling,

they occlude each other. If the scaling

is fixed to study directions only, then

the magnitude information is lost.

Spot Noise & Line Integral Convolution

Spot noise and Line Integral

Convolutions (LIC) are texture synthesis

methods to visualize fl ow. Both employ

same mathematical principle of

convolution to create the visual eff ect.

Spot Noise distributes a large number of

small intensity functions – called spots

– over the vector fi eld. The shape of the

intensity functions is deformed by the

vector fi eld. In LIC, a random noise is

convoluted with a piece of streamline. The

fi nal result is a smeared image, which can

give the idea of fl uid motion.

Fig. 3: 2D Line Integral convoluti on texture applied to space shutt le[4]

Textured Splats

It is an extension of a popular volume

rendering technique, called splatting to

visualize vector data. It also uses texture

as a medium of visualization. Spaltting

is the projection of data volumes on a

2D viewing plane. The splats are fi nally

composited on top of each other to

produce the fi nal image. Texture splatting

combines multiple textures and blend

them accordingly.

Fig. 4: Test tornado data rendered using the textured splat[5]

Flowlines: Streamline, Streakline,

Pathline

The fl ow lines visualize the fl ow starting

from a particular location. They are

calculated as integral lines that simply

assume the path traversed by a particle if

dropped in the vector fi eld. The examples

of fl ow lines are Streamlines, Streaklines

and Pathlines. The lines are identical in

a steady fl ow, where the velocity fi eld

remains constant over time. But, in

unsteady fl ow they are diff erent. They

are displayed using standard graphical

primitives (points, lines, arrows).

Mathematically, the fl owlines are the

solution of simple ordinary diff erential

equations (ODE) as given below for a 2D

vector fi eld.

dx = vx(x(t), yt) dy = vy(x(t), y(t),t)dt dt

Intial Conditon: At t=0 x(0), y(0)

The clear advantage with flow line

methods is the ease of implementation

and rendering. But the technique heavily

relies on seed point (start point of flow)

placement, which becomes a major

drawback. The efficient seed generation

is still an active area of research. A

significant amount of user’s involvement

and prior knowledge of vector field is

required to generate effective flow lines.

The other issue is related to number of

flowlines to be generated. With large

number, the computation becomes

expensive.

Streamlines represents a family

of curves that are tangential to fl uid

fl ow everywhere. At any instant of time

streamlines provide a snapshot of a region

of the fi eld. A streamline start from a given

initial position (seed point) and move

along the lines tangential to the vectors.

In an unsteady fl ow, streamlines keep

changing as the vector at each point varies

with time.

Fig. 5: Streamlines of air fl ow over city model

The streamlines mostly don’t

intersect each other, as there cannot

be two velocities at the same point.

The streamlines are easier to compute

compared to others, because they have

no temporal Interpolation. The technique

is better suited for static visualization.

The streamlines are further extended to

encode more spatial information in 3D

through the use of geometrical objects.

Some of the extensions are streamtubes,

streamribbons, streamsurfaces, stream-

balls and streamarrows.

The path lines are the curves

describing the traversals of all the

particles. They are identical to streamlines

in a steady vector fi eld. The path lines are

drawn only in forward direction. But an

unsteady fi eld has diff erent pathlines and

streamlines. At every moment the vector

fi eld changes, so the streamlines. This

makes the paths traversed by particles

diff erent. The paths are determined by the

streamline at that time stamp.

The streak line is the locus of all the

particles passed through a certain position.

It is also similar to streamlines when the

fl ow is steady. In unsteady fl ow, when

particles are released from a fi xed point

they travel along diff erent paths because

of continuous change of vector fi eld with

time. The collection of such points at later

instant of time gives a streakline.

ConclusionVector fi eld visualization is an active topic

for research and analysis. An overview of

fundamental fl ow visualization techniques

are discussed in the current paper. The

aforementioned techniques are applicable

to both 2D and 3D vector fi elds. In 3D

Vector fi elds they generally pose issues

such as occlusion, Visual data density,

depth perception. People have come

up with suitable modifi cations - sparse

representations, color diff erences, semi-

transparency and many more to overcome

these issues.

AcknowledgementWe would like to thank members of

visualization wing and Director, ANURAG

for constant support and encouragement.

References[1] Charles D Hansen, Chris R Johnson

“The Visualization Handbook”,

Elsevier Academic Press, pp. 261-277,

2005.

[2] J van Wijk, Spot Noise,


TextureSynthesis for Data

Visualization, ACM SIGGRAPH ‘91.

[3] B Cabral, C Leedom, Imaging Vector

Fields Using Line Integral Convolution

ACM SIGGRAPH ‘93.

[4] Roger A Crawfi s, Han-Wei Shen, Nelson

Max, Flow visualization techniques

for CFD using Volume rendering, 9th

International symposium on fl ow

visualization, 2000.

[5] Roger A Crawfi s, Nelson Max, Texture

Splats for 3D Vector and Scalar

Field Visualization, Proceedings

Visualization ‘93 IEEE CS Press.

n

Abo

ut th

e A

utho

rs

Shri Dilip Kumar Dalei is Scientist at ANURAG, Defence Research & Development Organization (DRDO), Hyderabad. He received his Bachelor degree in 2004 from NIT, Rourkela, India. He obtained his master degree in the fi eld of Computer Science and Engineering in 2010 from IIT, Kharagpur, India. His areas of interest are Scientifi c Data Visualization, Computer Graphics, 3D Displays and GPU programming. He has publications in International and National Conferences.

Shri B. V. Hari Krishna Nanda received his M.Sc degree in Computer Science from Andhra University in 1992 and M.Tech in Computer Science & Engineering from Acharya Nagarjuna University in 2010. He is presently working as scientist at ANURAG, Defence Research & Development Organization (DRDO), Hyderabad. He has more than 20 years of experience in the area of Scientifi c Data Visualization, Computer Graphics and Database Management.

Shri N. Venkataramanan received his M. Sc. in Computer Science from University of Mysore. He is presently working as Scientist at ANURAG, Defence Research & Development Organization (DRDO), Hyderabad. He has more than 20 years of experience in the area of Scientifi c Data Visualization and Computer Graphics. He has published research papers in various International and National Conferences.


A Walkthrough & Pathfi nder for Research Novitiates: Google Scholar Vs Microsoft Academic Search

Anchal Garg*, Madhurima**, Madhulika*** and Saru Dhir **** *Assistant Professor, Department of CSE, Amity University Uttar Pradesh, Noida, India**Assistant Professor, Department of Information Technology, Amity University Uttar Pradesh, Noida, India***Assistant Professor, Department of CSE, Amity University Uttar Pradesh, Noida, India****Assistant Professor, Department of Information Technology, Amity University Uttar Pradesh, Noida, India

Research Front

What Exactly Research is?In our day to day life we are surrounded

by data, information, knowledge, opinions,

ideas etc. Initially we study, learn and use

them for our own advantage and later,

this information is disseminated for the

benefi t of the society and the mankind.

Research is search for new knowledge.

When we extend the knowledge by

digging the unveiled information, we are

doing research. We often come across

this term through peers and while working

on it. Beginners in formal research often

encounter problems searching for relevant

scholarly papers[1]. They generally tend to

waste their enormous time in searching

and very often get baffl ed and frustrated.

Tutorial InsightThis short tutorial explains very precisely

and clearly how to begin and understand

the searching mechanism while

researching in very simple steps. We

have explained the steps using Google

Scholar and Microsoft Academic Search.

Searching results are explained below

with the help of snapshots. The steps below are showing the

searching tricks in Google Scholar.

Step 1- Go to Google Scholar by typing www.scholar.google.com on the Web BrowserThe Google Scholar is an excellent aid

for searching when we have to search for

diff erent articles, thesis, books, abstracts

and research papers across diff erent

disciplines[2]. The Fig. 1 below shows a

snapshot when you type www.scholar.google.com in the Web Browser’s address

bar.

Step 2- Enter the topic to be searched (For example artifi cial intelligence)Then in the search fi eld provided,

enter the topic for which you want to

fetch information. For example, in the

Fig. 2 below we have typed “artifi cial

intelligence” to get all the scholarly

articles related to it.

Step 3- Click on the Search button. You will get the list of scholarly articles.Further click on the

search button. This

will give access to a

list of scholarly articles

related to “artifi cial

intelligence” as shown

in the Fig. 3 below.

The scholarly articles

may include research

papers, thesis, books,

abstracts, etc.

The boxes represented in the fi gure are explained below:1. Clicking on “Since 2010”, you can

view papers published from the year

2010.

2. You can view the

paper by clicking on

this link.

3. Citations for a

particular paper can

be seen through

the “Cited by” link.

Here “Cited by

1903”indicates that

this paper has been

referred by 1903

paper [3].

4. People generally have

problems writing

references. Click on

“Cite” in order to cite/

refer this paper in

your research paper.

You can fi nd MLA,

APA and Chicago

referencing styles

here. You can change

the referencing style

as required. Each

journal has its own

referencing style.

5. It shows the Academic Publisher.

Here the Publisher is Elsevier.

6. It shows the name of the Journal.

Here the name of the Journal is

“Artifi cial Intelligence”.

7. It shows the year of publication. Here

Fig. 1: Showing the scholar.google.com page in the Google Chrome Web Browser

Fig. 2: Showing the topic “arti fi cial intelligence” for searching

Fig. 3: Showing the results or list of scholarly arti cles generated aft er clicking on the search butt on.


year in which the research paper was

published is “1987”.

Step 4- Click on “Cited by” to view papers that have referred this paper in their research papers.For instance, if you click on “Cited by

1903” of the article titled “On agent based

software engineering”, then you will be

navigated to the webpage containing all

the scholarly articles that have referred

the above article. This new webpage will

help you fi nd further work on the research

paper titled “On agent based software

engineering”.

Step 5-Click on “Cite” to refer this article in your paper.It has several

formats; you can use

any one of them to

add it as a reference

in your paper. Fig.

5 below shows the

snapshot when we

click on “Cite”.

Searching through Microsoft Academic SearchSimilarly, we can search the scholarly

articles on Microsoft Academic Search. The

Microsoft Academic

Search searches

research papers

from various sources

based on the selected

conferences and

journals.

The steps below are showing the searching tricks in Microsoft Academic Search.

Step 1: To search a research paper

on Microsoft Academic search, type “academic.research.microsoft.com” on the address bar.

Step 2: Next enter the topic to be searched. As in previous case, type “artifi cial intelligence”.

Step 3: Next, select the “Field of Study”. For instance, select “Computer Science” and click on search button as

shown in Fig. 8.

On clicking the search button, you

will be navigated to a new webpage

containing the following information as

shown in Fig. 9.

1. List of renowned authors in your

research area as shown in Fig. 9.

2. List of best rated conferences in your

research area as shown in Fig. 9.

3. List of Publications as shown in Fig. 9.

Fig. 4: Showing the results aft er clicking on “Cited by”

Fig. 5: Snapshot of the web page when the user clicks on “cite”.

Fig. 6: Showing the academic.research.microsoft .com page in the Google Chrome Web Browser

Fig. 7: Showing the topic “arti fi cial intelligence” for searching

Fig. 8: Showing various opti ons for selecti on aft er clicking the search butt on

Fig. 9: Search Result showing list of publicati ons


4. List of best journals in your fi eld of

study (Shown in Fig. 10.)

Scrolling down, we can see the list of

journals relevant to our research fi eld.

Step 4: Clicking on the “AI” shown

in Fig. 10 (extreme left), we will be

navigated to new webpage. The Fig.

11 shows the information related to

“Journal on Artificial Intelligence”. The

most cited authors, the keywords and

list of research papers.

Similarly, clicking on “IJCAI” shown

in Fig. 9 (extreme left), we will be

navigated to the new webpage displaying

information on “International Joint

Conference on Artifi cial Intelligence”.

The famous authors, keywords and the

list of research papers published in IJCAI

(shown in Fig. 12).

Closing remarksThis article gives an overview for

eff ectively searching scholarly articles

using Google Scholar and Microsoft

Academic Search. This tutorial has

provided a step by step procedure for

effi ciently searching the relevant articles

related to your research. Google scholar

off ers a more user friendly interface as

compared to its counterpart Microsoft

Academic Search. Also, it is more

popular and up to date. Google scholar

has rich repository of academic materials

and citations than Microsoft Academic

Search. The main advantage of Microsoft

Academic Search over Google Scholar

is that more parochial proportionate

service. Also, the data processing in

Google Scholar is more time expensive.

Furthermore, Microsoft Academic Search

is more suitable search for retrieving

results from multidisciplinary fi elds[4] [5].

We sincerely hope the above

information will prove to be a useful aid to

your research navigation. We expect that

the information shared above facilitates

enough explanation to your unanswered

questions. We also hope that this concise

article will make your search for research

much trivial.

AcknowledgementsAuthors are very thankful to Dept. of

Information Technology and Computer

Science & Engineering, Amity School

of Engineering and Technology, Amity

University Uttar Pradesh, Noida, India for

their support to carry out this study.

End Notes[1] http://scholar.google.co. in

[2] www.researchgate.net/

[3] http://en.wikipedia.org/wiki/Citation

[4] Orduna-Malea, E, Ayllon, J M,

Martin-Martin, A, & López-Cózar,

E D (2014). Empirical Evidences

in Citation-Based Search Engines:

Is Microsoft Academic Search

dead?. arXiv preprint arXiv:1404.7045.

[5] Ortega, JL, & Aguillo, I F (in

press). Microsoft academic search

and Google scholar citations:

Comparative analysis of author

profi les. Journal of the Association for

Information Science and Technology.

n

Fig. 10: Search Result showing list of publicati ons

Fig. 11: Showing the informati on related to “Journal on Arti fi cial Intelligence”. The most cited authors, the keywords and list of research papers.

Fig. 12: Showing informati on on “Internati onal Joint Conference on Arti fi cial Intelligence”


Abo

ut th

e A

utho

rs

Anchal Garg has more than twelve years of teaching experience. She is working as Assistant Professor in Department of Computer Science and Engineering at Amity University, Noida. Her major research areas are information systems, business process management, data mining, process mining and higher education and research. She is a member of ACM and IET (UK). She has number of international and national publications to her credit.

Madhurima did her Master’s Degree in Information Technology from Guru Gobind Singh Indraprastha University, New Delhi. She is at presently doing her Ph.D in Information Technology from Sri Venkateshwara University. She has 7.6 years of working experience in academic field. She has number of international and national publications to her credit. She has published one book with the title “Computer Networks” with Laxmi Publications. Her M.Tech work has been published as a book titled “Video Object Tracking” by LAP LAMBERT Academic Publishing GmbH & Co. KG, Germany. She is a member of CSI and ACM. Her primary research area includes image segmentation, object tracking and object oriented testing, ajax and databases.

Madhulika is working as Assistant Professor in Department of Computer Science and Engineering at Amity University, Noida. She holds diploma in Computer Science Engineering, B.E in Computer Science Engineering, MBA in Information Technology, M.Tech in Computer Science & Pursuing Ph.D from Amity University, Noida. She has total 8 years of teaching experience. She published almost 15 Research Papers in National, International conferences and journals. Her primary research area includes video object tracking and soft computing techniques.

Saru Dhir did her Master's Degree in Computer Science and Technology from Amity University Uttar Pradesh, Noida. She is at presently doing her Ph.D in Engineering. She has 5 years of working experience in academic field. She has number of international and national publications to her credit. She is a member of IEEE. Her primary research area includes Software Engineering, Software Testing, Agile Methodology and databases.


Congestion is a complex process. It

is really a hard task to defi ne congestion

but it can be easily sensed through the

tainted performance of the network.

Sometimes, user experiences long delays

in the delivery of messages, perhaps

signifi cant losses due to buff er overfl ows.

One of the reasons of high packet loss rate

is the disappointment from the network

to provide early congestion notifi cation

to the sources of traffi c. It is essential

to avoid high packet loss rates in the

internet. Packet loss means the wastage

of the resources that have been used by

the packet. Normally network congestion

occurs when a link or node is carries

huge amount of data which deteriorates

networks quality of service.

In the traditional Droptail queuing

algorithm a mechanism of simple queue is

used but the problem with the algorithm

was, it was not able to handle the bursty

traffi c.

To sort out the issue of bursty traffi c

large buff ers at the routers were used, but

it introduced the problem of high queuing

delays in the network especially during

the congestion. Small buff ers reduced the

problem of large queuing delays but added

a problem of high packet loss, which will

further result into underuse of the link in

Droptail queues.

So we want a fair and sensible

tradeoff between high link utilization and

low queuing delays.

These limitations of endpoint

congestion are highlighted by peer to peer,

multimedia and short lived web traffi c.

These applications mainly required less

delay and jitter, high bandwidth and less

packet drop. This created a need of new

queue management technique against

traditional Droptail queues, which becomes

the point of origin for the development of

new queue management technique known

as “Active Queue Management”.

Since the introduction to IP networks

in 1993 there has been a steady stream

of research output with respect to Active

Queue Management (AQM).

Congestion occurs when the total

requirement of a resource, (e.g. link

bandwidth) go beyond the capacity of the

available resource. Congestion results

into: high latencies in data transfers;

wasted resources due to packet losses;

and network failure in extreme case for

which there is essentially no data transfer

through the network: the throughput

drops to zero and the response time

goes to infi nity. The aim would then to

be control congestion or more preferably

avoid congestion. Initial work is done in

the area of congestion control primarily

focused around the responsive fl ow

(TCP) traffi c.

Endpoint congestion control

mechanism was employed at end points of

the network by keeping the core network

simple. In contrast AQM mechanism had

taken the advantage of powerful hardware

technology and tried to implement it

in the core network components (such

as routers).

Unlike Droptail, AQM is a proactive

congestion control scheme by which the

network informs the sources when the

incipient congestion is detected. The

network can inform the sources by means

of packet drops or with the help of Explicit

Congestion Notifi cation (ECN) marks

inside the packet headers.

AQM marks the packets according

to the severity of the congestion. When

congestion increases the probability of

packet dropping (or marking) will also

increase.

Increase in the packet marking

reduces the transmission rate of the

sources which results into decreasing

the queue length and reducing the packet

losses by preventing the queue overfl ow.

As AQM algorithm used to drop

the packets randomly before buff er

overfl ow, it avoids the problem of

“global synchronization” that was

present in the Droptail algorithms

AQM Components are shown in the

diagram below:

Congestion indicator gives signal

of the occurrence of congestion, control

function proposes the strategies to

deal with the congestion and feedback

mechanism makes the sources aware

of it and asks them to adjust their pace

of transmission to bring the congestion

under control.

At earlier stages AQM algorithms

were entirely based on the queue length

as a congestion indicator, but as the

research progressed it has been found

that there are harms in using only queue

length as a congestion indicator. So for

detecting link congestion, AQM may

utilize any combination of the following

parameters: queue length (average

or instantaneous), input rate (packet

arrival rate or queue drain rate), queuing

delay and events of buff er overfl ow and

emptiness.

Congestion control function

calculates the probability of packet

marking (or dropping) based on the

level of congestion shown by the various

congestion indicating parameters and

decides which packets to drop (or mark).

Congestion control function can use

diff erent parameters or blend of diff erent

parameters. For getting better results, it

is essential to tune the congestion control

parameters according to the current traffi c

condition in the network.

One important point here to note that,

in current AQM mechanisms, diff erent

control function types are suited for

diff erent traffi c environments.

There is not a unique control function

that is suitable in all network conditions.

There are two major approaches to

in designing the control function: heuristic

approach and control theoretic approach.

Heuristic approach is completely

based on intuition of the algorithm

developer. There is always simplicity in

design and implementation to certain

extent. Mathematical modeling is generally

not present in this approach and the control

parameters are tuned manually depending

on the network traffi c conditions.

Sometimes this approach may lead the

system into unstable state. As heuristic

approach is not always trustworthy, control

theoretic approach came into. It is based

on mathematical modeling where there

is always a explanation exists for the

Amol Dhumane* and Dr. Rajesh Prasad***Assistant Professor, Department of Computer Engineering, NBN Sinhgad School of Engineering, Ambegaon (Bk), Pune**Professor & Head, Department of Computer Engineering, NBN Sinhgad School of Engineering, Ambegaon (Bk), Pune

Active Queue Management

Article


selection of the parameter values. Most

of the control theoretic approaches are

responsive fl ows centric.

Finally Feedback Mechanism informs

the sources about the incipient or transient

congestion in the network with the help of

ECN notifi cation or packet drops (using

TCP’s triple duplicate acknowledgement

policy or retransmission policy).

Issues upsetting AQM performance:

a) Buff er size and link capacity

b) Traffi c load and RTT

c) The manner in which fl ows enter

into the queue i.e. in-synch or out-of-

phase way.

d) Routing matrix gain (it is used

to represent the topologies

mathematically). Network

robustness is inversely proportional

to this routing matrix gain.

e) The presence of short lived fl ows and

unresponsive fl ows.

f) Reverse path asymmetry.

Some of the existing AQM algorithms

are listed below:

Heuristic

Approach

Control-Theoretic

Approach

Random Early

Detection

Proportional Integral

(PI) controller

Adaptive

Random Early

Detection

Proportional

Derivative (PD)

controller

BLUE Proportional

Integral-Derivative

controller

BLACK Gain adaptive smith

predictor

Hyperbola RED PI-PD

Load/Delay

Controller

Various fuzzy logic

controllers.

LUBA

And many more And many more

AcknowledgementsWe are thankful to our Principal Dr. S

D Markande, Prof. S P Patil, Head, IT

department and entire NBN Sinhgad

School of Engineering for their support in

our work.

References[1] Richelle Adams, “Active Queue

Management: A Survey”, IEEE

Communications Surveys & Tutorials,

Vol. 15, No. 3, Third Quarter 2013, pp

1425-1476.

[2] S Floyd and V Jacobson, “Random

Early Detection Gate-ways for

Congestion Avoidance”, IEEE/

ACM Transactions on Networking,

1(4):397-413, Aug. 1993.

[3] W Feng, D Kandlur, D Saha and

K Shin, “A Self Confi guring RED

Gateway,” in Proc.IEEEINFOCOM’99,

March (1999), pp.1320-1328.

n

Abo

ut th

e A

utho

rs

Amol Dhumane has received his masters (M.E. Computer Engg.) from Bharati Vidyapeeth University, Pune. He is having 10 years of teaching experience. His area of interest includes congestion control and IoT. He has published more than 10 papers in national and international conferences. He is a life member of ISTE.

Dr. Rajesh Prasad has received masters (M.E. Computer Engg.) from College of Engineering, Pune and his doctorate from Swami Ramanand Tirth Marathwada University, Nanded. He is having 18 years of experience. His area of interest is Soft computing, Text Analytic and Information management. He has published more than 40 papers in national and international journals. He is a life member of IAENG, CSI and ISTE.


Information Technology to Curb Piracy in Bollywood

Sumith Kumar Puri* and Dr. H K Anasuya Devi***Bachelor of Engineering [Information Science and Engineering], Sri Revana Siddeshwara Institute of Technology, Bengaluru**Researcher & Professor, Artificial Intelligence, CCE, Indian Institute of Science, Bengaluru

This was it! The huge 1.5 GB download

was done. He observed that he was the

fastest seed, as he had close to a 60Mbps

connection. Albert now opened his

facebook friends' list and shot across a

message, announcing the link to all. By the

way, this was the latest in the series of sci-

fi superhero movies that he and majority

of his peer group were awaiting. This

being the third day of the offi cial release.

All set to watch the movie now, Albert

opened up his favorite video player on the

computer. But his joy was shortlived... The

movie quality did not live up to what was

mentioned on the site. It had promised

'HD 1080p video and DVD 384kbps

audio' as part of its title and description.

In spite of wanting to tear his hair apart at

the jumping of scenes, he plans to watch

the entire movie. The audio being hardly

audible, the video jittery and sometimes

tilted, the only pleasure he seemed to

have was his favorite cheese popcorn

and a glass of cola. Interestingly, the last

time Albert had ever paid for a movie or

music clip online was about three years

ago. That too, was actually an accidentally

downloaded clip, through auto-pay, as he

had his credit card registered on one of the

sites.

This is a normal daily or weekly

scenario of almost all of the netizens

who are within the teenage, graduate or

starting professional levels. Given the

same situation a few years earlier, we

would have seen the likes of Albert along

with his friends queuing up at a movie

theatre or waiting eagerly for the video

tape or compact disc release of the movie.

As per one of the reports the total

loss to Bollywood alone, in the year 2010,

was close to a billion dollars. This loss

was also attributed to camcorders' being

used in theatres to create pirated compact

discs and digital video discs. So, Hasn't

any one taken any steps to get back what

should be rightfully theirs? Though there

are many options including enhancing

the already available digital watermarking

techniques, policing and governance. But

in the reality of things, How much of this is

actually enforced and How much does the

fi lm creator actually bother about? As per

a study by the Harvard Business School in

2011, the implementation of some of the

steps could actually outdo the fi nancial

benefi ts associated with it. Hence,

sometimes even the creators overlook

these measures.

So, How about implementing a pure

information technology solution or system

that is not only helpful for the creators, but

also a fun and legal way for the users. My

proposal is not only to create a software

mechanism that promotes a legal way, but

one that also that is cost eff ective, cheaper

to implement, generates user interest,

direct business to customer, promotes

legality and is enjoyable. What's more,

it promises to even re-employ pirates as

legal vendors of the same media, albeit at

a lesser profi t to them.

CineCat is what I call this software

idea, which will allow people of all ages

to easily and legally access any media,

primarily related to Bollywood. CineCat

acts not only as a directory or database

of movie information but as an online

distributor of, primarily, movies and music.

Unlike the YouTube's of our era, it works in

a mode that is even more closely tied to

Commerce, Anti-Piracy and Bollywood.

The simple driving process is that when

the movie is ready to release and it hits off

a calculated cooling period, the software

allows the creator to provide an online

release.

With proprietary security

mechanisms that are tied to the hardware,

it aims to distribute the release at equal or

lesser the cost to download or purchase

a pirated movie disc. The delivery can be

either digital or on an actual disc, through

post. Since the security mechanisms

are tied to hardware or the registered

player and to a specifi c user, they

cannot be duplicated or cracked easily.

The calculation of a cooling period is

done based on history, at times being a

calculated risk. It also aims to generate

further interest in the users who await

that ultimate digital experience and

would outright deny any pirated media. It

will create further avenues for revenues,

a legal approach which is attractive to

educated users and curb piracy eff ectively.

All of these can be combined with many

other digital and traditional marketing

techniques, to maintain users' interest.

The diff erence in the solution that we

are proposing is that an online release

would not only use CineCat as a form

of distribution but also as a player and

security control mechanism. It is not only

in India, but in even bigger countries such

as the United States, tying movies with

ordinary post or digital delivery is a tried

mechanism that has got good response.

So, the loose ends that remain in

such a proposal is what is that appropriate

time when the online release would outdo

or curb piracy to abysmal levels. Also, it

should allow the creator to gain revenues

that is rightfully theirs. Then there is the

issue of periodic or perpetual rights on

the creation itself. These are only minor

issues or calculated risks, that would

never take away the normal theatre,

multiplex or big screen watchers. Since

CineCat would allow a digital database,

which is equivalent of a movie wikipedia

and a lifelong availability of the original

or high quality creation itself – the issue

of rights is a decision to make that would

only eventually give benefi ts, now starting

from an earlier period.

But why would one chose a tedious

process as an user? What would appeal to

him, like our own Albert?

Albert is one of the normal graduate

or undergraduate that you would come

across, who has a group of geeky friends.

Albert is not the only one who prefers the

highest quality of video, audio or even

a trailer – his entire peer group does. At

the same time, they all vie to create the

best repository or collection of music or

movies. They are also the ones who don't

bother to spend a very small amount

of money, not only because it provides

quality – but also because it is now cool to

pay for this form of viewing. Also, being an

avid fan of sci-fi superhero movies, he is

even more enthusiastic of using CineCat.

He expects an autographed compact

disc to be delivered to him, and doesn't

Article


lose hope that he may win the contest on

CineCat to meet the superhero (actor)

himself. Even other buyers off the road

of a pirated compact disc, have now an

option – even if they do not use a personal

computer. This will mostly be tied to

the serial number of the playing device.

Since most household's may own a single

device (or at the most two) – a suitable

serial number can be provided to encode

it for playing with CineCat loaded onto the

movie disc itself.

What about the other side, that of

the creator? Does he see anything that

is diff erent or lucrative from what he was

doing till now?

This could lead to a cheaper form of

distribution, that may infact itself pay for

itself in many ways, because of including

advertising to one extent – with CineCat

taking care of almost all processes which

include online security, distribution,

advertising, marketing, delivery and even

policing. Some of these ideas can be diffi cult

in implementing because of curtailed

internet speeds, but then there always is the

option of delivery of discs by post.

Also, since CineCat relies on

proprietary mechanisms, it would keep a

constant check (and update) on crackers

and any form of threats to its reliability.

We, in this article, are not covering

or studying any other application or

software system that is already in place

that is close to what CineCat does or is

intended to do.

But then there is a common sense

that may prevail in many minds. Why

curtail some piracy, When it is actually

good? There maybe positive vibes due to

the piracy. Well, there are steps to actually

take that too into account, as is done to one

extent even today. CineCat can be used as

an extended trailer, an extended promo to

ascertain not only the content, interest of

the user but also the quality, security and

reliability processes. Most of the times for

an user a very short wait is mostly worth

the watch (beyond the trailers).

All of the mentioned policies and

ideas are also applicable to music,

events, short fi lms and any other form

of distribution that may need exclusive

rights, or are subject to piracy.

We are evolving into a society

where the cyber laws are too loose when

compared to the prevalent usage, and

of that do exist a small percentage are

enforced. One aspect of CineCat is also a

stronger enforcement of cyber laws related

to media and information technology. It

could lead to a combination of banning of

certain sites, internet service providers,

torrent sites, peer-to-peer sharing, fi le

sharing sites and even sale of pirated cd's.

CineCat can curb or provide alerts for

many of the online piracy methods and

also provide a way to tackle the offl ine

menace (out of this discussion).

Albert is back to watching the movie,

which is almost at the end. No, He isn't

the one who has lost hope... All this while,

with the movie quality not capturing his

interest - he spent some time reading

this article about CineCat. He is the one

eagerly awaiting the fi rst time he gets to

see an online movie release on CineCat!

Glossary of TermsCineCat was a Software Application

Idea based on the concepts mentioned

in this article. This was to be built by the

now closed startup, named TechArmy,

of one of the authors.

Interesting Read (Google Search Terms)Hollywood and Bollywood Join Arms...

Protecting against the Pirates of Bollywood

Bollywood & Rights, Piracy Is Mostly Via

Torrents

Bollywood No Longer Worrying About

Piracy...

ETC Fights against Movie Piracy...

Film Piracy Funding Terror in India...

Piracy cost Bollywood $959m: Report

YRF digitizes Dhoom 3 to combat piracy

n

Abo

ut th

e A

utho

rs

Sumith Kumar Puri holds a Bachelor of Engineering [Information Science and Engineering] from Sri Revana Siddeshwara Institute

of Technology, Bengaluru. He has also completed his Profi cience [Cryptography & Network Security] and Profi cience [Intelligent

Agents] from the Indian Institute of Science, Bengaluru. Sumith has recently completed a Part-Time Acting Course from Actor

Prepares, Mumbai. He has more than 9 years of experience in various facets of Software Development. You can reach him at sumith.

[email protected]

Dr. H K Anasuya Devi received her Ph D degree from the Indian Institute of Science, Bangalore in 1985. Her research interests include

– Computational Linguistics and Language Techonology, Artifi cial Intelligence and Expert Systems, Remote Sensing Applications

and Geographic Information Systems, Archaeology and Epigraphy, Sports. She possesses extensive research experience with over

25 years in inter-disciplinary areas, including 15 years of teaching experience at graduate and post-graduate levels. Over the last

decade and half, she has guided over 150 students in their research projects, published over 298 papers in all forms. You can reach

her at [email protected]


ArticleDr. M Hanumanthappa*, Mrs. S Regina Lourdhu Suganthi** and Mrs. Rashmi S****Associate Professor, Department of Computer Science and Applications, Bangalore University, Bangalore**Research Scholar, Department of Computer Science and Applications, Bangalore University, Bangalore***Research Scholar, Department of Computer Science and Applications, Bangalore University, Bangalore

Protection of Software as Intellectual PropertyEach system of Law has its own

definition of what can be bought and

sold, i.e., what is tangible property?

Therefore, by virtue of implication

of law, the ownership of property

such as tangible goods is defined and

apportioned. Whereas, the ownership

in Intellectual Property (IP), represents

a proprietary right in intangible products

of human minds, which are generally

referred to as “knowledge goods” and

the ownership of IP, is also defined by

law. However, as against the existence

of laws that define and protect the

ownership of tangible goods, a separate

form of legal protection is recognized

for the protection of knowledge goods,

since knowledge goods are intangible,

non-excludable and inexhaustible.

Accordingly, the laws that govern IP

define ownership rights in IP. Therefore,

the term “Intellectual Property Rights

(IPRs)”, is bundle of legal rights,

granted for knowledge goods, such

as inventions (Patent Right), brand

names (Trademark), artistic and literary

creations (Copyright), aesthetic designs

(Designs) and industrial secrets (Trade

secret).

Traditionally, computer software is

recognized as a literary work and hence

its legal protection is provided under

the law of Copyright (albeit statutory

registration is not mandatory). Prior to the

unbundling of computer software from

hardware and where there was no distinct

value for software, copyright protection

was deemed suffi cient. It is important to

understand that Copyright Law provides

protection only to expression of ideas

(non-functional ideas) and not to ideas

(functional ideas) per se.

However, with the unbundling of

computer software from hardware in 1970s

and software assuming an independent

work of creation, the protection of

software, only under the law of Copyright

was found grossly inadequate.

In Lotus Development Corporation v.

Borland International, U.S. Supreme Court,

while deciding a copyright infringement

case, in a dispute between Borland and

Quattro Pro (Lotus 1-2-3), exposed the

limitation of legal protection of copyright

for software. In this case none of the source

code or machine code that generated the

menus was copied, but the names of the

commands and the organization of those

commands into a hierarchy were virtually

identical. The Court, while denying the

Copyright protection for the software,

where the functional aspects of software

are claimed, pronounced that copyright

was limited only to the protection of

non-functional aspects of software, as a

literary work.

Copyright law provides protection

for literary works, which are original

and non-functional in nature. With the

separation of software from hardware

and the greater value of realization for

software as an intellectual asset, a need

was felt to provide a comprehensive IP

protection for the functional aspects

of software and an effort was made to

seek protection of software as invention

(functional idea).

Accordingly, protection of software

in the form of Patents gained momentum,

in countries like US and Europe, by

considering them as inventions rather

than literary works.

Legal protection in the form of Patents

is granted by a State (Registration is

mandatory for exercising the legal rights),

for inventions, that are New, Inventive

and having Industrial Application. In

addition to the satisfaction of these legal

conditions, it is also imperative to ensure

that such inventions do not fall under the

category of ‘non-statutory inventions”. In

other words, patent statutes of countries,

do have negative list, with which they bar,

explicitly, certain categories of inventions,

irrespective of such inventions being

Novel and Inventive.

One such category of inventions,

which are often being considered as

“non-statutory” is software. For instance,

under US Patent Law (35 U.S.C. §101), the

subject matter of inventions relating to

laws of nature, natural phenomena, and

abstract ideas, are specifi cally excluded

from patentability. The rejection of

software as a patentable subject matter

is based on the premise that they are

abstract ideas and hence not patentable.

US Supreme Court in Gottschalk v.

Benson(409 U.S. 63 (1972)) ruled that a

process claim directed to a numerical

algorithm, as such, was not patentable

because the patent would wholly pre-

empt the mathematical formula and in

practical effect would be a patent on

the algorithm itself and hence it would

amount to allowing a patent on an

abstract idea.

However, the US Supreme Court, in

the case Diamond v. Diehr, 450 U.S. 175

(1981), held that controlling the execution of

a physical process, by running a computer

program did not preclude patentability of

the invention as a whole. In other words,

the mere presence of a software element

did not make an otherwise patent-

eligible machine or process un-patentable.

This decision of US Supreme Court opened

up vistas for the protection of software as

patents in the USA.

Similarly, in Europe, in terms of

European Patent Convention (EPC), (Art

52 of EPC), "programs for computers" are

not regarded as inventions for the purpose

of granting European patents, but this

exclusion from patentability only applies

to the extent to which a European patent

application relates to a computer program

“as such”. In other words, inventions

relating to claiming of “mere algorithms”

fall foul of this provision of law. In

Europe, patents for software inventions

are granted, as long as they have new

“technical eff ect” and they do not relate to

the implementation of normal functioning

of computer hardware.

The term “technical eff ect” is

generally interpreted to include, solution

to a technical problem, higher speed,

reduced hard-disk access time, more

economical use of memory, more effi cient

data base search strategy, more eff ective

data compression techniques, improved

user interface, better control of robotic

arm, improved reception/transmission of

a radio signal etc.

In India, the subject matter of the

inventions relating to “mathematical or

business methods or a computer program per

se or algorithms”, fall outside the purview of

patent protection. Nevertheless, software

can be protected as literary work under

Indian Copyright Law. In view, Indian

Patent Law governing software inventions

are similar to European Patent Law, Indian

Patent Law, also reckons “new technical


eff ect” in considering the patentability of

inventions claiming computer software.

To conclude, Software as an IP, needs

to be framed as an invention and adequate

protection in the form of patent right is highly

desirable, since patents off er comprehensive

protection for functional ideas. If necessary,

dual IP protection for software in the form of

Patents and Copyrights can also be explored

to cover both functional and non-functional

aspects of software.

References[1] Manish Arora, “Guide to Patents Law”,

Universal Law Publishing Co. Pvt. Ltd, 2002.

[2] P Narayanan, “Law of Copyright and

Industrial Designs”, Eastern Law House,

2002.

[3] Frederick W. Mostert& Lawrence E

Aploson, “ From Edison to iPod”, Dorling

Kindersley Limited, 2007.

Web References[1] http://en.wikipedia.org/wiki/Lotus_Dev._

Corp._v._Borland_Int'l,_Inc.

[2] http://supreme.justia.com/cases/federal/

us/409/63/case.html

[3] http://www.invispress.com/law/patents/

diehr.html


Gottschalk_v._Benson


Diamond_v._Diehr

[6] http://en.wikipedia.org/wiki/Software_

patents_under_the_European_Patent_

Convention

n

Abo

ut th

e A

utho

rs

Dr. M Hanumanthappa is currently working as Associate Professor in the Department of Computer Science and Applications, Bangalore University, Bangalore, India. He has over 15 years of teaching (Post Graduate) as well as Industry experience. He is member of Board of Studies/Board of Examiners for various Universities in Karnataka, India. He is actively involved in the funded research project and guiding research scholars in the fi eld of Data Mining and Network Security.

Mrs. S Regina Lourdhu Suganthi is a Research Scholar in the Department of Computer Science and Applications, Bangalore University, Bangalore. She has two decades of rich teaching experience in the fi eld of Computer Science. Areas of interest include Data Mining, Image Processing, Algorithms and Problem solving. She also assists in computer related patent drafting work.

Mrs. Rashmi S is a Research Scholar in the Department of Computer Science and Applications, Bangalore University, Bangalore, India. She also has over 3 years of teaching as well as Industry experience. Her specialization in research is Data Mining. She has published several papers in various National and International conference and Journals.


Programming.Tips() »

Fun with ‘C’ Programs – Reversing a String using a Bitwise OperatorThe program and its output below exemplify a novel method of

reversing a string using one of the bitwise operators:

Program listing one

#include<stdio.h>#include<string.h>main(){ char str[80]; int i, len; printf(“Enter a string (less than 80 characters): “); scanf(“%[^\n]s”, str); printf(“\nBefore reversal, str= %s”, str); len=strlen(str)-1; for(i=0;i<len;i++,len--) { str[i] ^= str[len]; str[len] ^= str[i]; str[i] ^= str[len]; } printf(“\nAfter reversal, str= %s”, str); return 0;}

Sample output:Enter a string (less than 80 characters):

Before reversal, str= Abc

After reversal, str= cbA

The underlying logic is explored below:

The string (Abc) would be stored as follows:

A b c \0

str[0] str[1] str[2] str[3] . . . str[79]

If we convert each character of str, into its corresponding ASCII

code, then the storage can be visualised as follows:

65 98 99 0

str[0] str[1] str[2] str[3] . . . str[79]

The binary representation of the ASCII codes would be as follows:

01000001 01100010 01100011 00000000

str[0] str[1] str[2] str[3] . . .

str[79]

Now let us dissect the statements:

str[i] ^= str[len]; str[len] ^= str[i]; str[i] ^= str[len];

In the fi rst run of the for loop, it would imply:

str[0] ^= str[2]; /* str[0] = 01000001 ^ 01100011; i.e. str[0] = 00100010 */

str[2] ^= str[0]; /* str[2] = 01100011 ^ 00100010; i.e. str[2] = 01000001 */

str[0] ^= str[2]; /* str[0] = 00100010 ^ 01000001; i.e. str[0] = 01100011 */

i.e. the contents of str[0] and str[2] have been interchanged.

The rest is simple iteration using the for loop.

[Why should we use bitwise operators? For the simple reason that bitwise operations are faster and use less power because of reduced resource usage.] n

Abo

ut th

e A

utho

r Wallace Jacob is a Senior Assistant Professor at Tolani Maritime Institute, Induri, Talegaon-Chakan Road,

Talegaon Dabhade, Pune, Maharashtra. He has contributed articles to CSI Communications especially in the

Programming.Tips section under Practitioner Workbench.

E-mail: [email protected]

Offi ce Contact No: 02114 242121


Wallace JacobSenior Assistant Professor, Tolani Maritime Institute


Programming.Learn("R") »RStudio- Studio of RRStudio is one of the most popular open source Integrated Development Environment (IDE) for R. Both Desktop version for Windows, Linux and Mac and Server version of RStudio are available. RStudio has both Open Source Edition and Commercial License. The open source edition is supported by the Community forums only, whereas commercial users will get email support for eight hour response during business hours. RStudio is written in the C++ programming language and the Qt framework was used to develop its graphical user interface. RStudio makes the life of data scientist easy by off ering an open source and enterprise-ready professional software.

Let us have a look at the RStudio IDE.

RStudio has mainly four windows –

1. Source Window (Data objects in Spreadsheet form).

2. Console Window, where you can type commands and see

output (as in the R environment )

3. Environment and History Window- Environment Tab shows

all the active objects and history tab shows a list of commands

used so far. By using the environment tab, you can

import/ load data into R.

4. File, Plot, Package, Help and Viewer area. You can also make changes of the look and feel of

the environment by editing the Global Options (go to tools> Global Options) of RStudio.

R studio provides syntax highlighting facility and line numbering which help you in writing code in R. Importing data from various resources including web goes interactively in RStudio. You can add packages by a single click on the IDE and load the package into the environment by checking the box. Also you can view plots and export fi gure into the format you wish to.

A new R script can be created by using RStudio by either clicking the icon or from the file menu. You can also create a new text file from the Rstudio interface itself. RStudio also supports C++ programming.

One of the signifi cant features of RStudio is that you can make presentations and html documentation

using it. A particular block of code in R can be inserted in the html code and you can run the block. In the documentation, you can show the code and gives its plot/result.

In a similar way, you can also use RStudio as an editor to produce documentation of your R experiment or tutorial and save it in PDF.

RStudio has a number of packages like Packrat, Shiny, ggvis, dplyr, knitr, R Markdown, which are actually assets of statisticians. Packrat is one of such package which helps you to handle the package dependencies. This makes the package installed in your machine portable and thus you can move your project easily and reproduce result in some other machine. Shiny helps to create interactive web applications on R. We will discuss more on Shiny in the next tutorial. n


Umesh P and Silpa BhaskaranDepartment of Computational Biology and Bioinformatics, University of Kerala


Future of Medical Transcription Jobs in India - Need to Extend it beyond Record Generating Process

Prof (Dr.) D G JhaProfessor & Area Chairperson – IT; Programme Coordinator-MCA

IT Industry Perspective

The real India still lives in villages

and farming continues to be the main

occupation of the people of this nation-

a country among the largest agriculture

producers in the world, a nation that

survives necessarily because of the agro

sector; INDIA is and will continue to

be viewed globally as a giant granary.

However, this perception that India is

still only an agro-based nation is fast

changing and going by the recent policy

statements of Government of India, it

defi nitely refl ects the determination that

it is ready to recognise that the services

sectors are slowly but surely occupying

the drivers’ seat in the economy. Indian

government offi cial plan for 2020 says,

“Our vision of India in 2020 is of a nation

busting with energy, entrepreneurship and

innovation” (Yojana Aayog;-Planning

Commission.2000, p21). This is an opportunity.

Given the kind of support the

government provided to service

sector specially the ITES (Information

Technology Enabled Services) sector,

it certainly has managed to accelerate

India’s transformation from an agrarian

economy to a service economy to a

certain extent. For the sector to thrive

further, it should be understood that ITES

holds enormous promise for India but at

the same time it has to be handled with

utmost care. Having, a powerful revenue

generating model and support policy of the

government alone will not be the primary

success determining factor; the ability to

manage human resources and maintain

quality will be paramount. ITES is a global

industry – sourced locally – and India can

succeed only if it is globally competitive

(Dhar-Patel & Vishwanath eds. 2002, p1).

IT Enabled Services (ITES) is defi ned

as all those services which can be

delivered to the end user from a remote

location with the aid of information

technology (Dhar-Patel & Vishwanath

eds. 2002, p7). In simple terms, the set

of processes that can be outsourced

and (can be) enabled with the help of

Information Technology can be defi ned as

Information Technology Enabled Services

or more simply as ITES. The sectors

(indicative) that can be classifi ed as the

part of ITES are: Call Centers; Back Offi ce

Processing; Medical Transcription (MT); Geographic Information System (GIS);

Knowledge Process Outsourcing (KPO).

The Economic survey of 2012-13 indicates

four major sub components of IT/ITeS

industry as: IT services, business process

outsourcing (BPO), engineering services

and R & D and software products. (http://

indiabudget.nic.in. Economic Survey 2012-

13, p223)

Importance of Medical Transcription“Health is one of the most information-

intensive businesses you will fi nd, and

that information can have a direct impact

on the quality of patient care” notes Prof

Michael Smith – editor of Healthcare

Informatics Journal (cited in Brady et al.

2001, p118).

Since, the entire healthcare industry

in the US revolves around insurance; the

detailed, comprehensive, accurate and

complete patient records are needed

for processing insurance claims making

medical transcription one of the most

challenging and fastest growing aspects

within healthcare.

Medical Transcription assumes

greater importance as it is concerned with

preserving each and every patient-related

document, including the doctor’s note.

• A patient visiting a clinic may require

investigation by physicians with

diff erent medical specialties, nurses,

therapists, and technicians, all of

whom will record observation or test

data in separate fi les

• During examination the patients may

be asked about his/her condition or

lifestyle by all of the above involved

in diagnosis

• A patient upon investigation may

be prescribed several drugs and

treatments by diff erent physicians

Each of these responses can get recorded

in diff erent ways and in diff erent fi les.

(Nair (Dr) cited in www.chillibreeze.com).

Reasons for Outsourcing of Medical Transcription ProcessThe processing of insurance claim

requires comprehensive documentation of

the patient’s medical consultation history

and records of the every interaction with

physicians. Most of such documents that

recorded the interaction of the patients

and the physicians were handwritten in

the past and that made at times diffi cult

for insurance auditors and lawyers to

decipher and interpret. They started

insisting on the typed medical records.

This gave birth to the concept of Medical

Transcription. An effi cient record-keeping

system thus becomes important and

indispensable (especially in the US) since

insurance claims form an integral part of

the medical industry.

Transcribe (across + write in Latin)

means writing something out in full

from notes or shorthand. It also means

transferring of information from one way

of storing it on a computer to another,

or from computer to an external storage

device.

Medical records noted or dictated

by the doctor (or his assistants or nurses

or a clinician), physical therapists, health

professionals such as dietician or social

psychologist are loaded into the tape or

onto the digital voice processing system

precisely and aptly transcribed i.e.,

converted into the word document by MT

or MLS (Medical Language Specialist). All

the clinic notes, offi ce notes, operative or

consultation notes, patient’s history and

physical reports, psychiatric evaluations,

laboratory reports, x-ray reports and

discharge summaries after transcription

are proofread up to 98% accuracy before

being uploaded back to the doctor’s offi ce

or clinic (Dhar-Patel & Vishwanath eds.,

2002, p.100) .


Since the US is the only country in

the world that has such stringent policies

on maintaining medical records, medical

transcription is largely the US based

industry. The need to reduce the cost of

administering these records pushed many

hospitals towards adopting electronic

formats for documentation. India, for its

excellence in interpretation and large

English-speaking population base, became

the preferred destination (till recently) for

the US medical practitioners.

The documents are expected to be

returned within the stipulated time frame

of 24 hours and time zone diff erence that

India has with US makes it quite easy.

Apart from need to cut cost, the other

apparent reason is increased reliance on

core competence that prompted hospital

administration to outsource this job. The

benefi ts of ordering out for the medical

practitioners are:

• Concentration on core activity

• Production based compensation

• Minimized expenses on perks and

other employee benefi ts

• Elimination of recruitment and

training expenses

• Flexibility in choosing quality

manpower at reduced cost

• Greater accountability and

transparency in production

standards.

(Dhar-Patel & Vishwanath eds.,

2002, p.101)

Quality Standards for Medical Transcription

The healthcare industry in US needs

to adhere to stringent quality standards.

One such standard adopted by software

companies focused on healthcare domain

is HL7 (Health Level Seven) standards.

The HL7 standards (Shet 2005,

p.326-328) addresses the following

key processes as outlined in capability

Maturity Model or more simply CMM:

• Requirements management

• Software quality assurance

• Organisation process focus

• Training programmes

• Software quality management

• Technology change management

• Defect prevention

It is one of the several ANSI

(American National Standard Institute)

-accredited Standards Developing

Organisation (SDO) operating in the

Healthcare domain. Members of the HL7

are collectively known as working group,

which is mainly organized into technical

committees (TC) and Special Interest

Groups (SIG).

The role of the Technical Committee

(TC) is to:

• Identify the scope and range of data

elements

• Work with other SIG, TCs, or any

other related organisation to identify

appropriate controlled vocabulary for

encoding those data elements

• Identify or defi ne messages (or

objects) required to support the

specifi c information exchange needs

of applications, both as input to the

application as well as output from the

application.

The Special Interest Groups (SIGs)

provides/certifi es the standard for

electronic data interchange pertaining

to healthcare. It keeps on enhancing

the current standards and works in

conjunctions with technical committees

to advance the quality standards and

improve HL7 standards.

The goals of the HL7 standards are to

create fl exible, cost eff ective approaches,

standards, guidelines, methodologies

and related services that help in the

interoperability of healthcare information

system with other dependent system

within the domain.

Another important and specifi c

standard that all healthcare organisations

Fig. 1: The enti re medical transcripti on process [source: htt p://www. outsource2india.com]

Fig. 2: The enti re medical transcripti on process [source: htt p:// www.slideshare.net/rohitpate l203/medical-transcripti on-industry]


are required to adhere to is the HIPAA

compliance. Health Insurance Portability

and Accountability Act of 1996 -or more

simple referred to as HIPAA compliance-

is the federal law amended to the

Internal Revenue Code of 1996. The

healthcare insurance industry to improve

portability and continuity for the groups

as well individuals rely heavily on the

HIPAA compliance standards. The main

objectives of HIPAA are:

• To increase the effi ciency and

eff ectiveness of health information

systems through improvements in

electronic health care transactions

recording and maintenance process

• To maintain security and privacy

of individual identifi able health

information.

The processes and information

impacted by HIPAA are (but not limited

to):

• Health claims and equivalent

encounter information

• Enrolment in and disenrollment from

a health plan

• Eligibility for health plan

• Healthcare payment and remittance

advice

• Health plan premium payments

• Referral certifi cation and

authorization

• Coordination of benefi ts

• Prescriptions

(www.call-centers-india.com/ites.

html)

Stages in Medical Transcription ProcessThe parameters that defi ne a successful

medical transcription unit are effi cient

receiving of voice fi les, allotting,

transcribing and sending of transcribed

fi les in cost-effi cient manner and without

any error. Accuracy and quick delivery

is paramount in the fi eld of medical

transcription. Figure 1 and 2 describes

the Standardized Medical Transcription

Process as stipulated by HIPAA.

Traditionally, Indian MT sector

followed:

• DictationThe fi rst step in MT begins with

physician dictating the observation

and diagnosis during examination

of the patient. The dictation is done

onto a device such as tape recorder,

Dictaphone, digital Dictaphone, a PC

or a normal telephone after dialling a

toll free telephone number provided by

the outsourced MT service provider.

First of such dictating machine was

engineered in the late 1880s and since

then it has progressed to several phases

of development from grooves cut on

a cylinder, to fl exible belts of plastic,

magnetic media, digital dictation and

speech recognition.

Dictating through toll-free number

is currently the most used technique by

the physician. Since it is possible that a

physician may meet the same patient

at more than one hospital, the doctors

are allotted phone numbers where the

last digit indicates the hospital at which

the patient has been/is being examined.

The innovation like this helps the MT

service provider to locate the hospital

and accordingly decide upon the format

for recording, as diff erent hospitals may

follow diff erent formats.

To make the task of dictation easier

and effi cient, voice recognition devices

that can record the message directly into

the PC are now being employed by the MT

service providers. Also, Personal Digital

Assistants or more popularly known

as PDA’s are now made available with

embedded voice recognition capacity or

dictation capture system.

• Storage and retrieval of audio fi lesThe audio fi les are directed towards the

MT service provider’s voice capturing

server using the intelligent network.

The MT Company’s server host

application capable of digitizing the

voice on real time basis pushes these

voice data (fi les) to the production unit

through Internet.

• Encryption and transmissionThe digitized data is then compressed

and properly encrypted for onward

transmission through satellite link

to MT service provider’s destination

(such as India) where the transcription

gets carried out. The fi les are then

allotted by the local unit of MT

Company or consultant to various

medical transcriptionist or franchisee.

• Allotment and actual transmissionDepending upon the familiarity with the

physician or based on specifi c stream

of medicine, the fi les are classifi ed and

allotted to various transcriptionists

matching the required skill set and

needed turn-around time. The fi les

are then transcribed in the formats

as prescribed by the physicians or

hospitals. The completed fi les are

uploaded into the quality controllers

work area where these are checked for

quality before uploading it back. The

various types of error that may occur

while transcribing are:

• Medical terminology misunder-

stood (wrong disease attributed to

the patient)

• Omitted dictation (omission of

the laboratory fi nding as the value

dictated could not be heard or was

misunderstood)

• Medical terminology wrongly spelt

• English word misinterpreted and

hence wrongly spelt (entered

‘elicit’ instead of ‘illicit’ or ‘dissent’

instead of ‘descent’

• Grammatical errors

• Punctuation errors

• Inappropriate blanks

• Typographical errors (typos)

• Formatting errors

• Returning Completed TranscriptionThe quality checked transcripts

are generally uploaded to the MT’s

company server and are then sent

back to the individual doctors or the

hospitals where they are fi lled for

storage. Ideally, the medical records

are returned to the hospital servers

in real-time, ready to be accessed.

The encrypted transcribed fi les are

commonly known as EMR (Electronic

Medical Records).Transcribing/editing

all the hospital reports dictated by

hospital medical staff (physicians,

nurses and physician assistants)

is the responsibility of the Medical

Information Transcriptionist/editor

also at times referred to as Medical

Language Specialists. The other tasks

include but not restricted to:

• Utilisation of sourcing hospital

information system in order to

place the transcribed report into

the patients account

• Based on sense of the report

and the patient types, selection

of apt report format and print

destinations

• Complete the required number

of transcription tasks within the

stipulated time frame without any

error as per the guidelines set by

the sourcing hospital

(Dhar-Patel & Vishwanath eds., 2002,

p.105-107)


ITeS/MT Industry in India: Over the Years“India controls 44 percent of the global

off shore outsourcing market for software

and back-offi ce services, with revenues

of US $17.2 billion (euro14.07 billion) in

the year ended March 2005…” (Source:

Associated Press, June 2005. http://

www.medicaltranscription-olutions.com/

medical_transcription_statistics.html).

Over the years, the slowdown across

the globe has impacted the revenues of

this sector and this gets refl ected in a

study by NASSCOM indicating that the

growth reduced from 15 percent in 2011-

12 to an estimated 8.4 percent in 2012-13.

The estimated growth for 2013-14 are 13-

15 percent for total IT-BPM revenue (of

which MT is still a component perhaps to

reckon with), 12-14 percent for exports and

13-15 percent for domestic circuit. IT and

Business Process Management (however)

sector revenues have grown from

1.2 percent in 1997-98 to an estimated

8 percent in 2012-13. (http://indiabudget.

nic.in. Economic Survey 2012-13, p224)

When it comes to MT, starting from

1990, MT ranks amongst the fi rst set of

ITeS-BPO activities to be sourced from

India. Currently MT segment in India

is estimated to earn annual revenue

aggregate of US$ 220-240 million.

(http://www.aiita.org /news/blogs/3322-

medical-transcription-the-way-to-get-

your-bright-career.html)

In India, there are about 120-150 mid

to large size vendors off ering medical

transcription services and 70% of the

revenues in the industry are generated

by the large players (mostly US medical

transcription service organizations -

MTSOs) with off shore centers in India.

Cbay is one the major vendors (www.

cbayscribe.com /cbay systems/ index.

htm) with aggressive growth plan having

headcount of over 3,500. Apart from

large-size and mid-size players there

are few small-size vendors off ering MT

services with average employee strength

of about 50 competing for remaining 30%

market. (http://www .sourcingnotes.com/

content/ view/333/58/).

Technological Innovations in MT – Does it mean Dead End for smaller Indian MT Outsourcing Agencies…To imagine that the industry will have

reliable speech recognition output without

human intervention was never envisaged,

and hence the elimination of medical

transcriptionist was completely ruled out

until the new disruptive voice recognition

(VR) technology got introduced. The

automated VR technology allows the data

to be fed directly by the doctors into the

system.

Nuance and Royal Philips Electronics

are the two key players in providing

technology that caters to speech-to-text

market for health care professionals.

The use of speech-to-text technology

by US military’s health system grew by

100% over the last year with about 6000

professional adopting Nuance’s software

across all branches of the military. (http://

www.sourc ingnotes .com/content /

view/333/58/)

Role of Information as a Business

Resource (IaBR) in healthcare industry

and its impact on patients care, reputation

of the hospital, seamless archiving of

patients data, health tourism and ease

of retrieval has been well-established.

Some of the important terms (http://

w w w.c h i ro c a re .co m /w p - co n t e n t /

uploads/2013/03/HITTerms.pdf) related

to health information systems are:

• EMR (Electronic Medical Record):Capturing patient data and

facilitating access of these details

to authorized clinical staff from any

specifi ed location characterises a

computer-based medical recording

system popularly referred to as EMR.

Some of important deliverables

associated with EMR are: accurate

and complete claim processing as

required by insurance companies,

providing automated alerts for

drugs’ allergic reactions (and

interactions), generating clinical

notes, prescriptions and schedules,

allowing labs to communicate with

clinical staff etc. The advanced EMR

systems now include units which

keep track of all relevant (from

internal as well as external sources)

medical information and are now

often referred to PMS (practice

management system)

• EHR (Electronic Health Record):EHR comprises of processes such

as recording, storing, classifying,

retrieving, querying, generating

reports with respect to patients

physical and mental health.

Past, progressive and predictive

information is then used for providing

primary-health care and health-

related services. EHR also comprises

of decision-based tools that helps

clinical staff to access and take

decisions on the basis of evidences.

Apart, from clinical purpose EHR

also has modules that help collect

and manipulate data with regards

to billing, quality management,

outcome reporting and public-health

disease surveillance and reporting

modules. The primary contents of

a typical Electronic Health Record

would include: patient demographics,

progress notes, SOAP (Subjective,

Objective, Assessment and Plan)

notes, persisting problems, vital

signs, diagnosis details, medical

history, immunizations time-lines,

laboratory data and radiological data.

Also, using Discrete Reportable

Transcription (DRT) facility, clinical

documentation on EHRs can be further

improved. It not only directly populates

transcribed information into the EHR’s

fi elds and templates, but also facilitates

structured documentation (right format)

of information in EHR.

Fig. 3: Electronic Medical Record [Source: Nuesoft XpressTM Electronic Medical Record accessed at htt p://mtherald.com/how-emr-ehr-is-going-to-aff ect-medical-transcripti on-industry]


• PHR (Personal Health Record):Electronically maintaining and

managing individuals’ health

information requires a very secured

and confi dential environment.

PHR provides an application that

provides access of the details only

to the authorized person. It controls

an keeps track of accesses made

(accountability), authorization (provide

access to right people in right format at

the right time), authentication (verify

the credentials before allowing the

access) and privacy.

Factors that Obstruct Outsourcing MT Jobs to IndiaThe healthcare industry in US brought in a

major change in the 1990’s by recognising

and adopting standards that would clearly

defi ne medical terminologies which

was later referred to as standardized

transcription style. In order to lay

emphasis on standardized documentation

and accuracy the American Association of

Medical Transcription (AAMT) published

Book of Style for Medical Transcription in

1995. The increased use of standards

made hospitals and clinics outsource

their work to medical transcription service

organizations (MTSOs) or home-based

US medical transcriptionists having their

own centers or at the most leased out

the task and services (sub-contract) to

smaller medical transcription companies

within the US. These MTSOs account

for 40% of the transcription job that are

outsourced in the US while only 5% of

these task are currently off shored to low

cost destinations such India, Philippines

and other Asian countries. (http://

www.sourc ingnotes .com/content /

view/333/58/). This very clearly indicates

that several hospitals and physician

groups out in the US doesn’t favour the

off -shoring of medical records.

There have been widespread protests

by unions and employees of a hospital in

the east Midlands town of Leicester against

outsourcing of medical transcription work

to India as a part of plans to cut costs. For

the management, outsourcing of task such

as typing of letters by doctors would cut to

48 hours and save about 500,000 pounds

annually. The proposed changes when

implemented would cause loss of jobs for

the medical secretary’s - fears unions and

employees of the medical hospitals in UK.

(http://articles.economictimes.

i n d i a t i m e s . c o m / 2 0 1 2 - 0 5 - 1 3 /

news/31689733_1_outsourcing-move-

medical-transcription-typing).

Use of technology has added another

dimension. The speech recognition

software is said to get upto 98%

accuracy in results. For the large player

in India adapting itself to the changes in

technology is seamless and in tandem

with the requirements of the industry. Also

these big players not only can aff ord to get

in new technology but also complement it

with apt training schedule which in turn can

tackle employee attrition/retention issues.

For the small India-based MT companies

bringing in the new technology is always

not aff ordable and hence it means lesser

fl ows of works to them which they could

bag either directly or via sub-contracting

earlier. Since smaller off shore vendors

are dependent on medical transcription

service organizations (MTSOs) for

subcontracted work, the non-compatible

obsolete technology makes it diffi cult to

change the task-giver perception that the

Fig. 4: Sample EHR [Source: htt p://www.assistmed.com/ blog/ bid/79204/Save-Physicians-90-Minutes-Per-Day-with-DRT-Transcripti on]

Fig. 5: Sample PHR [Source: htt p://mtherald.com/how-emr-ehr-is-going-to-aff ect-medical-transcripti on-industry/]


capabilities of small off shore vendors are

found wanting on technology front. This

apparently means loss of opportunity

in MT off shoring job to smaller MT

companies.

For the small India based MT

industry facing stiff internal competition

and lack of stable and trained manpower;

advancements in speech recognition

and Electronic Health Records (EHR)

technology is adding new challenges

to their very existence. The technology

due to features such as easy to use is

gaining popularity and is expected to

be increasingly adopted by clinics in the

US. (http://www.sourcingnotes.com/

content/ view/333/58/). This would

simply mean that a clinic on successful

implementation of EMR can stop

outsourcing transcription work and can

become self compliant to fulfi l statutory

requirements of state/s altogether.

Availability of low cost technology

with low operational cost has defi nitely

boosted the confi dence of physician to

acquire these applications in-house.

However, not all the EMR applications

follow the same methodology for creating

patient records. While some are strictly

non-customizable but standardized

template-driven point and click technique

others are DRT enabled, which allows

physicians to use traditional dictation

technique for feeding the data into the

system. Needless to say if the former

becomes more prevalent, need for

transcription will further decrease. (http://

mtherald.com/how-emr-ehr-is-going-to-

aff ect-medical-transcription-industry/)

Currently one of the major concerns

for the medical practitioners is medical

accuracy of the patients’ data and this

view is getting stronger that Indian MT

organisations are not fully equipped to

handle this. But still India continues to

get the job outsourced to its shore. But,

what if the law makes it compulsory for

the physicians do it on their own to avoid

medical errors?

Revival Strategy that can Make India Once Again the Preferred DestinationThough technology is a threat for Indian

MT industry but then it is and will not be

possible for all the doctors’ to switchover

instantly, physicians with less volume

of practice may not be able to aff ord to

automate and implement EMR solution

into their clinics. And these are the

targets for Indian MT industry. However,

once it becomes aff ordable - the word of

caution is, EMR in not too tough a task to

perform on a PC or a tablet, the easy to

use interface and training (as part of their

academics) is enough for the doctors to

fi ll in the prescription with few clicks. It’s

time clicking fast for Indian MT industry

to change and think fast to take advantage

of brand that India has created in the

outsourcing business over the years.

According to the Bureau of Labor

Statistics (US):

"Employment of medical

transcriptionists is projected to grow

faster than the average; job opportunities

should be good, especially for those who

are certifi ed. Employment of medical

transcriptionists is projected to grow 14

percent from 2006 to 2016, faster than

the average for all occupations." (Source:

http://www.bls.gov/oco/ocos271.htm and

http:// mteducationonline.com)

About 80 medical transcriptionist

(MT) fi rms in Philippines have formed

the Medical Transcription Industry

Association of the Philippines Inc.

(MTIAPI), in order to provide standardized

training in various functions. It aims

at providing standardised training and

increasing the workforce three times as

that of present. The vision states “The

Organization envisions the Philippines to be

the off shore destination of choice for Medical

Transcription services.”(http:// www.ncc.

gov.ph/default.php).

In India too, eff orts are being

made towards launching the training

programmes in medical transcription

especially for the rural youth. The 4-6

months program covering the subjects

like Science, US accent training, English

typing and grammar aims at improving

the quality of MT jobs and deliverables in

India. This would then help India spruce

up MT industry and make it ready to

tackle the threat from the countries such

as Philippines which are churning out

adequate numbers of trained manpower.

(http://www.sourcingnotes.com/content/

view/333/58/)

In August 2004, Medical

Transcription fi rms in the country formed

the Indian Medical Transcription Industry

Association with the aim of boosting the

growth to US$ 100 million (www.imtia.

net). Accessing the website, however,

gives the feeling that the association is

defunct with web links of some of the

founder members leading to load page

error. In the news and event section it

still shows the latest news pertaining

to August 6, 2004. One of the revival

strategies could be to have IMTIA as more

visible association representing India in

the fi eld of MT globally. Consortiums

always help. Another key factor is the

wage. Currently, the wages for the medical

transcriptionist in India is:

National Salary Data

Salary Rs 72,650 - Rs 348,068

per year ($1207.51 -

$5785.22 per year)

Bonus Rs 0.00 – Rs 39,732 per

year

Certifi ed

Professional

Coder

Employees

Rs 180,000 – Rs 3,60,000

per year ($2991.71

-$5983.55 per year)

(Country: India | Currency: INR | Updated:

9 Jun 2014 | Individuals Reporting: 336;

http://www.payscale.com/research/IN/

Job=Medical_Transcriptionist/Salary)

The above fi gures don’t inspire the

current generation youth to join the MT

industry as they perceive this to be the

dead end to their careers. Not only have

wages remained stagnant since the new

millennium, but the introduction of voice

recognition has actually reduced wages

by nearly one-half. Moreover even after

acquiring the certifi ed profession coder

credential the salary ranges to about Rs

15,000 – Rs 30,000 per month which does

not meet the GenNext aspiration. With

perception that MT industry in India is not

doing enough to stand the competition,

the sector is moving towards the dead

end opines several of the MT professional

interacting on social network? Wage

correction and defi ning the standards can

help regain the past glory of MT industry

in India. Compare this to the wages in US:

US Data

2012 Median Pay $34,020 per year

$16.36 per hour

Entry-Level

Education

Postsecondary

non-degree award

Work experience in

a related occupation

None

On-the-Job-Training None

Number of Jobs

2012

84,100

Job Outlook, 2012-22 8% (As fast as

average)

Employment

Change 2012-22

6,400

Quick Facts: Medical Transcription in

US (Source: http://www.bls.gov/ooh/

healthcare/ medical- transcriptionists.

htm)


Inaccuracies in medical records

can put patients’ lives to risk. Once the

records are generated by transcriptionist,

the outsourced agency should make their

process of checking more rigorous and

ensure that records are accurate. This

would help rebuild the confi dence of the

hospitals and doctors outsourcing their

task to India as they don’t have to recheck

the records before replacing the patient

information into the shelf.

Hacking, breach of security and

leakage of sensitive patient data are cited

as other reasons by hospitals and clinics

for not sourcing the MT tasks to India. It is

important for MT industry in India to build

the robust and protective security system

that will prevent the hacking as technology

advances, merely stating that hacking

happens day in and day out and even

military or banking data are not immune

to these kind of attempt will not suffi ce

and further alienate the MT outsourcing

task from India. (http://mtherald.com/

how-emr-ehr-is-going-to-aff ect-medical-

transcription-industry/)

ConclusionFor whom the bell tolls? The answer may

seem obvious to many given the rate of

change of technology. The same technology

which brought the MT work from the

faraway shores of U.S.A many years back

today seems to be a hindrance to the health

of the Medical Transcription job in general.

Technologies like speech to text and

handwriting recognition are terms which

we are becoming aware more and more in

everyday life. With the proliferation of hand

held devices, be it smart phones or tablets

or palm tops, connected to internet at ever

increasing speed, the internet of things

(IOT) is increasingly becoming a reality. The

practising doctor in U.S. is not an exception

to the bevy of users getting smarter in use

of these devices and technologies. In such a

condition the absence of even a functional

industry association may seem like the last

nail on the coffi n- specially when a country

like Philippines is trying to catch up to give

a tough competition to established player

like India.

Will the Indian MT industry sit up and

notice? Will it use the same technology

disruption to its advantage? Quality is the

mantra. Can we take it to six sigma level

which can instil confi dence in the hearts of

the users? Can we make it secure enough to

pass laws like HIPPA and standards like HL7.

Can we make it more productive so that we

can attract better talent who are in search of

better salaries? That is the need of the hour.

It remains to be seen how the Indian MT

industry copes with this challenge brought

about by new wave of technology.

References[1] Associated Press, June 2005. http://

www.medicaltranscription-solutions.com/medical_ transcription_statistics.html

[2] Brady, JA Monk, EF & Wagner, BJ, 2001. Concepts in Enterprise Resource Planning. Bangalore: Thomson Course Technology.

[3] Dhar-Patel, M & Vishwanath, CV eds., 2002. The Economic Times: IT enabled services – An ETIG report. Mumbai: The ET knowledge series.

[4] en.wikipedia.org[5] http:// mteducationonline.com[6] http:// www.ncc.gov.ph/default.php[7] http://articles.economictimes.indiatimes.

com/2012-05-13/news/31689733_1_outsourcing-move-medical-transcription-typing

[8] http://indiabudget.nic.in. Economic Survey 2012-13

[9] http://mtherald.com/how-emr-ehr-is-going-to-affect-medical-transcription-industry/

[10] http://www .sourcingnotes.com/content/ view/333/58/

[11] http://www. outsource2india.com[12] http://www.aiita.org /news/blogs/3322-

medical-transcription-the-way-to-get-your-bright-career.html

[13] http://www.assistmed.com/ blog/ b i d / 7 92 0 4 / S a ve - P h y s i c i a n s - 9 0 -Minutes-Per-Day-with-DRT-Transcription

[14] http://www.bls.gov/oco/ocos271.htm [15] http://www.bls.gov/ooh/healthcare/

medical- transcriptionists.htm)[16] http://www.chirocare.com/wp-content/

uploads/2013/03/HITTerms.pdf [17] http://www.payscale.com/research/IN/

Job=Medical_Transcriptionist/Salary)[18] http://www.slideshare.net/rohitpate

l203/medical-transcription-industry[19] http://www.sourcingnotes.com/content/

view/333/58[20] Nair, K (Dr.)., 2008. Medical Transcription

and India: The current scenario and the future. Available at http://chillibreeze.com/articles/MedicaltranscriptionandIndia.asp [accessed 16 December 2008].

[21] Nuesoft Xpress TM Electronic Medical Record accessed at http://mtherald.com/how-emr-ehr-is going-to-eff ect-medical-transcription-industry/

[22] www.call-centers-india.com/ites.html[23] www.cbayscribe.com/cbaysystems/

index.htm[24] www.imtia.net[25] Yojana Aayog;-Planning Commission.

2000. India Vision 2020 [pl_vsn2020.pdf], Government of India. Available at http://www.planningcommission.gov.in/plnre/pl_vsn2020.pdf; pg21 of 108.

[accessed on 5 April 2008] n

Some of the facts are taken from blogs and other social networks, where the Medical transcriptionist and others associated with industry have expressed their opinions. These are

represented here for the academic purpose only. Also, websites are liberally referred - to get the overview of the industry and the prevailing conditions, the inferences are based purely

on the availability of these secondary data. The trademarks used here belong to the respective organisations and have been used here for the academic purpose as well.


Kind Attention: Prospective Contributors of CSI CommunicationsPlease note that Cover Themes for forthcoming issues are planned as follows:

• December 2014 – Algorithmic Computing • January 2015 – IT Infrastructure• February 2015 – Quantum Computing • March 2015 – Machine Translation

Articles may be submitted in the categories such as: Cover Story, Research Front, Technical Trends and Article. Please send your contributions

before 20th of a month prior to the issue month for which you are contributing. The articles may be long (2500-3000 words maximum)

or short (1000-1500 words) and authored in as original text. Plagiarism is strictly prohibited.

Please note that CSI Communications is a magazine for membership at large and not a research journal for publishing full-fl edged

research papers. Therefore, we expect articles written at the level of general audience of varied member categories. Equations and

mathematical expressions within articles are not recommended and, if absolutely necessary, should be minimum. Include a brief

biography of four to six lines for each author with high resolution author picture.

Please send your articles in MS-Word and/or PDF format to the CSI Communications Editorial Board via email id [email protected].

(Issued on behalf of Editorial Board of CSI Communications)


Innovations in India

Rajiv Thanawala* and Prachi Sakhardande**Product Experience CoE, Component Engg. Group, TCS

Software User Experience Maturity ModelTo improve software code quality, we use

quality metrics that are measurable. Defects

per Line of Code, Cyclometric Complexity,

and so on, are examples of measurable

metrics that enable this. User Experience

(UX) is a critical quality aspect for software.

How can we then measure UX quality?We assessed the existing UX

assessment methods. They revealed that though the current UX assessments helped identify usability fl aws, they lacked quantifi able metrics for an objective review of UX quality, and also lacked increasing levels of UX maturity using which one can strive for continuous improvement of UX quality.

To objectively and quantitatively assess UX quality, we then formulated User Experience Maturity Model (UXMM) – a system and framework built based on established UX assessment techniques. UXMM is applicable to

software products and applications,

irrespective of its domain or device.

Figure 1 shows diagrammatic represen-

tation of User Experience Maturity Model.

Main features of UXMM are as follows:

• 4 hierarchical levels of UX maturity—

Usable, Useful, Desirable and

Delightful—indicating progression in

user experience

• 14 Key UX Parameters (KUXP)] –

Ease of Use, Speed of Use and others

as shown in the fi gure

• Each KUXP comprising of attributes.

E.g. “Ease of Use” KUXP has

attributes like Ease of access, Ease

of Data Input, Visibility of System

Status etc. (not shown in the fi gure)

• Levels 1 and 2 based on fi rst 10

KUXPs—from ‘Ease of Use’ to ‘Help’

• Levels 3 and 4 based on additional

4 KUXPs—from ‘Brand Recall’ to

‘Greater Good’

• ‘Expert Review’ used as assessment

method for certifying software at Level 1

• ‘Usability Tests’, ‘Competitor Analysis’

and ‘Emotional Heuristics’ used for

certifying software at Levels 2, 3 and 4

• Quantitative scores as result of

assessments

The approach for UXMM assessment is as

follows:1. Capture context of use of a software

application or product through a pre-assessment questionnaire. Based on the context, UXMM system generates weightages for each KUXP.

2. Steps to Certify for each Level:2.1 UXMM system generates a level

specifi c benchmark score.2.2 A usability expert rates the

application across KUXPs with a scorecard based on a specifi c assessment technique (‘E.g. Expert Review’ for Level 1).

2.3 If this score is lesser than benchmark score, the expert identifi es improvement areas. Else, the software is considered certifi ed for that specifi c Level.

2.4 Once a level is achieved, repeat steps 2.1 to 2.3 for the next level, all the way up to Level 4: Delightful

Over the last two and half years, more than 100 UXMM assessments have been used to certify UX quality of our software products and applications. Use of a standardised assessment mechanism has helped improve our products’ UX quality and institutionalised UX as a practice.

Reference [1] TCS Published Patent Application – US

20130254735 A1 – ‘User Experience Maturity Level Assessment’ – Prachi Sakhardande, Rajiv Thanawala

n(© 2014, Tata Consultancy Services Limited, Printed

with permission)

Abo

ut th

e A

utho

rs Rajiv has 25 yrs of experience in IT consulting and product development. He leads Product Experience Center of Excellence which provides User Experience, Information Visualization, User Assistance and Customer Experience services to a products group at TCS.

Prachi Sakhardande has consulted with Fortune companies and leads User Experience and Customer Experience within Product Experience Center of Excellence for a products group at TCS. Her team is responsible for UX design and benchmarking.

Fig. 1: User Experience Maturity Model

Innovators interested in publishing about their work can send a brief write up in 150 words to Dr Anirban Basu, Chairman, CSI Div V, at [email protected].


A Quick Look at Virtual Private Database Security

Security Corner Jignesh Doshi* and Bhushan Trivedi** *Associate Professor, L J Institute of Management studies**Ph.D.

IntroductionInternet users and usage have increased

drastically in past few years. Internet

is widely used for business. Millions of

transactions are taking place via web

applications. Cyber attacks are becoming

more sophisticated day by day with

evolution of technologies and increasing in

numbers. Security is a big challenge for IT.

As per Open World Application Security

Projects (2013), 5 out of 10 top attacks are

related to databases.

A new attack, “Sensitive Data

Exposure” is added into top 10 list.

After getting access, attacker can dump

sensitive data like credit card number,

social security number, fi nancial data

etc. As a result it may impact data loss,

negative publicity and a loss of customer

confi dence.

Oracle Virtual Private Database

(VPD) is one of the key technologies

powering sensitive data theft prevention.

In this article, some of the ways in which

sensitive data exposure can be prevented

using Oracle Virtual private Database is

discussed.

Limitations of Traditional Security PoliciesThere are two types of database

security available in oracle databases

are Discretionary access control using

grant and revoke (DAC) and Mandatory

Access Control (MAC).

Two level of access privileges can

be granted using DAC security policy, at

account level ( like create table, drop table

etc.) and table level (like insert, update,

select or delete). DAC is very fl exible

policy and DBA must provide selective

access using Grant or Revoke statements.

In many applications, additional security policy is needed for classifying data and

users based on security classes. This

approach is known as Mandatory Access Control.

Most commercial DBMS provide

mechanisms only for Discretionary

Access Control.

Security Flaws in DAC and MAC is

summarized as below:

Security Policy DrawbacksDAC 1) In this security

policy. users either

have or do not have

a certain privilege.

2) No method to Limit

propagation e.g. one can not restrict

GRANT OPTION

privilege to at most

‘n’ other accounts.

3) Not suitable for high

security data.

MAC 1) Not fl exible as a

result it can not

work with all types

of applications.

With DAC security policy, we can not

restrict data selection at horizontally

(row) or vertically (column) level. i.e. if

we want to restrict that AR user can see

only his department data or he can not see

salary of employees.

What is VPD?Oracle Virtual Private Database (VPD)

enables you to create security policies to

control database access at the row and

column level. VPD can be enforced directly

on database tables, views, or synonyms.

We can apply VPD policies on SELECT,

INSERT, UPDATE, INDEX, and DELETE

statements. Oracle database engine

automatically applies security functions

whenever a user access data and there is no

way to bypass security i.e. adds a dynamic

WHERE clause to a SQL statement.

How Oracle Virtual Private Database Works?VPD execution fl ow is narrated in Fig. 1.

Whenever any statement is executed,

DBMS engine checks whether security

policy is confi gured on the objects found

in query or not. If security policy is

confi gured on the objects of query, it will

modify query and execute the query.

How to Confi gure?Pre-requisites: Fine grained access

control must be enabled in database.

Check using query “select * from v$option

where parameter = 'Fine-grained access

control”, it should be TRUE.

ROW LEVEL VPD Security Policy

One can create multiple security policies

on diff erent objects using same function.

We can apply row level security directly

on database tables, views, or synonyms.

Row Level VPD confi guration is a two

step process.

i) In fi rst step, we will create the stored

function.

ii) Second step comprise of creation

of security policy using DBMS_RLS

Fig. 1: Oracle VPD processing fl ow

CREATE OR REPLACE FUNCTION

SEC_AUTH_ORDERS

(SCHEMA_VAR IN VARCHAR2,

TABLE_VAR IN VARCHAR2 )

RETURN VARCHAR2 IS RETURN_

VAL VARCHAR2 (400);

BEGIN

RETURN_VAL := 'SALESMAN_ID

= 101';

RETURN RETURN_VAL;

END AUTH_ORDERS;

Table 1: Security Functi on

Information Security »


package for stored function created

in step 1.

Example: If you have confi gured policy

such that JOHN can view only his sales

orders and employee id of John is 101.

Step 1: Create Security Function

Create the stored function (refer to

Table 1), which will append the WHERE

SALESMAN_ID = 101 clause to any SELECT

statement on the OE.ORDERS table.

Step 2: Create the Oracle Virtual Private

Database Policy

Next, create the policy (refer to Table 2)

using the ADD_POLICY procedure in the

DBMS_RLS package.

How security policy will work?

Query Executed

by JOHN

SELECT* FROM

OE.ORDERS;

Converted Query

by VPD

SELECT* FROM

OE.ORDERS

WHERE SALESMAN

_ID = 101;

COLUMN LEVEL VPD Security Policy

Column Level VPD confi guration is a two

step process. In fi rst step, we will create

the stored function. Using it we will defi ne

row level access control Second step

comprise of creation of security policy

using DBMS_RLS package.

Two ways to implement column level

security policies are as below:

• Displaying Only the Column Rows

Relevant to the Query

• Using Column Masking to Display

Sensitive Columns as NULL Values

We can apply column-level security

policies to tables and views, but not

to synonyms. Let us understand using

example.

Example: Security policy in which

Chicago sales users cannot see the salaries

and commission details of people outside

the Chicago. (Location id is 15 for Chicago).

Above security policy will display salary

and commission details of Chicago sales

representatives only. However, super user

can view all details.

ConclusionKey Benefi ts of Oracle Virtual Private

Database security policies are as below:

• High Level of Security:

˚ As plemented at database level, it

provides consistent access control

on tables, views or synonyms, no

matter from where user access

data ( Front end, back end or third

party tools)

˚ we can mitigate Sensitive data

exposure risk using VPD security

policies.

• Simplicity;

˚ Adding security policy is very easy

and simple.

• Flexibility.

˚ One can create diff erent policies

for diff erent operations (select,

insert, update or delete) on same

table.

Security policy functions run as it had

been declared with defi ner’s rights so

do not declare it with invoker’s rights.

We can extend user Role based access

control (RBAC) to fi ne grained row or

column level.

References[1] OWASP: https://www.owasp.org/

index.php/Top_10_2013-A1-Injection:

accessed 31st May 2014

[2] Internet hosting statistics : http://www.

netcraft.com/internet-data-mining:

accessed 31st May 2014

[3] Common Weakness Enumeration:

h t t p : //c w e . m i t r e . o r g /d a t a /

defi nitions/89.html : accessed 3rd June

2013

[4] Internet users : http://www.

internetlivestats.com/internet-users:

accessed 14th June 2014

[5] Oracle documentation ; docs.oracle.

com

[6] DBMS_RLS :docs.oracle.com: visited on

25th july 2014.

n

a) Security Function

CREATE OR REPLACE FUNCTION

SEC_HIDE_SALES_DATA

(SCHEMA_VAR IN VARCHAR2,

TABLE_VAR IN VARCHAR2 )

RETURN VARCHAR2 IS RETURN_

VAL VARCHAR2 (400);

BEGIN

RETURN_VAL := 'LOCID=15';

RETURN RETURN_VAL;

END AUTH_ORDERS;

b) Confi gure security Policy

BEGIN

DBMS_RLS.ADD_POLICY (

OBJECT_SCHEMA => 'OE',

OBJECT_NAME => 'EMPLOYEE',

POLICY_NAME => 'SEC_POLICY_

HIDE_SAL',

POLICY_FUNCTION => 'SEC_

HIDE_SALES_DATA',

SEC_RELEVANT_COLS =>

'SAL,COMM');

END;

BEGIN

DBMS_RLS.ADD_POLICY (

OBJECT_SCHEMA => ‘OE’,

OBJECT_NAME => ‘ORDERS’,

POLICY_NAME => ‘SEC_POLICY_

ORDERS’,

FUNCTION_SCHEMA => ‘SYS’,

POLICY_FUNCTION => ‘SEC_

AUTH_ORDERS’,

STATEMENT_TYPES => ‘SELECT,

INSERT, UPDATE, DELETE’ );

END;

Table 2: Security Functi on

Abo

ut th

e A

utho

rs

Jignesh Doshi received the B.Sc (Maths) and M.C.A. degrees in 1989 and 1992, respectively. He is an Oracle Certifi ed Professional ( OCP 10g). He has nearly 22 years of experience. During 1992-2008, he worked in various IT fi rms like Patni Computer Systems, Vodafone (Fascel), Gujarat Lease Financing Ltd., Erhardt + Leimer (I) Ltd.. Since 2008, he is working as associate professor at L J Institute of Management studies. His areas of interest are Database, Database security and Data warehousing and data mining.

Bhushan Trivedi received Ph.D. in 2008. He has nearly 25 years of teaching experience. His areas of interest are Intrusion Detection with mobile agents, Sensor Networks, Using artifi cial intelligence techniques to solve real world Problems. He had conducted workshops on Eff ective Teaching (20), "how to debug a network with TCPDUMP and WireShark" (15) and “how to write an eff ective research paper” across India. He has written books are on ANSI C++ and Computer Networks under Oxford publications. He is guiding 8 students in their doctorate degree.


Visualization – to make visible: Visualization covers a wide range from mental and creative visualization to geo visualization, fl ow

visualization, computer graphics, data visualization and even network visualization. Visualization has been used by mankind since

its early days and is not a new concept. The early prehistoric cave paintings and the later Egyptian hieroglyphs are examples of the

use of visual symbols and pictures by humans to communicate, convey and interact meaningfully. Visualization has found growing

acceptance and extensive use in science, education, engineering, communication, multimedia and medicine to name a few. In the

fi eld of computing the growth and emphasis on use of visualization was limited due to the lack of graphics power. However, since late

1990’s the fi eld has seen an accelerated growth which has been further boosted with the use of computer animation. Moving forward

from the more familiar digital animations used for weather pictures and satellite photos and the complex scientifi c 2D & 3D imaging,

- visualization is now being used for educational animations, and dynamic representation of timelines.

Computer Visualization has two main aspects. The fi rst is a major benefi t in terms of providing a powerful tool for better and

smarter governance. Governance whether of nations, corporate, organizations, entities or individuals requires a robust measurement

and reporting system and effi cient MIS for better control, monitoring, corrective action and delivery. Computer visualization has enabled

improved meaningful MIS which has provided a strong boost at a micro as well as macro level, for both IT and corporate governance.

In today’s information age an increasing amount of data is being created by the internet and social media and the various sensors

in and around us – be it the CCTV’s in offi ces, public places, housing societies or at traffi c signals, which in turn does at times get

related or is relatable to data bases holding personally identifi able information like PAN data base, Aadhaar data base etc. This data is

often referred to as Big Data. Computer visualization includes Data visualization which enables and improves the processing, analyzing

and communicating of this Big Data. This is the second aspect. In this context visualization of Big Data presents a variety of ethical

and analytical challenges for visualization.

The potential threats to the data and from the use of such data are many – these primarily arise from the SMAC threats which

are ever present in mobile, social media, cloud environment and in analytics – since visualization does require and makes extensive

use of analytics.

Mobile devices are not always secured, are often mishandled, lost or stolen and used for almost all activities, both personal and

professional exposing data.

Social media has its own vulnerabilities with users, their friends and relations indiscriminately and accidentally posting and

exchanging sensitive information.

Analytics aggregates and analyzes such information making it even more critical, hence enlarging the threat.

Finally, the Cloud has removed the barriers between the entity dealing with the information and the outside world. Even if you are

not on the cloud your service providers, associates, users, are bound to be there and that is enough to increase the risk further.

In such situation the need has arisen for a specialized fi eld in Governance – the fi eld of data governance to improve data security

and to ensure accountability and ethics in use of data within a robust framework that promotes public confi dence.

Given this background the current Case in Information Systems is being presented. The facts of the case are based on information

available in media reports, online information and some real life incidents. Although every case may cover multiple aspects it will have

a predominant focus on some aspect which it aims to highlight.

A case study cannot and does not have one right answer. In fact answer given with enough understanding and application of mind

can seldom be wrong. The case gives a situation, often a problem and seeks responses from the reader. The approach is to study the

case, develop the situation, fi ll in the facts and suggest a solution. Depending on the approach and perspective the solutions will diff er

but they all lead to a likely feasible solution. Ideally a case study solution is left to the imagination of the reader, as the possibilities

are immense. Readers’ inputs and solutions on the case are invited and may be shared. A possible solution from the author’s personal

viewpoint is also presented.

Case Studies in IT Governance, IT Risk and Information Security »

Security Corner Dr. Vishnu KanhereConvener SIG – Humane Computing of CSI (Former Chairman of CSI Mumbai Chapter)

Satyarthi the SP of Netrapur was newly

posted to this state. He is tech savvy and

wishes to go in for major initiatives to make

his policing better and more eff ective.

He has unveiled his policing plans and

initiatives. He has planned to introduce

state of the art surveillance system “San-

nirikshan” initially in the urban and the

remote far fl ung areas followed up by

coverage of the semi urban and rural

parts of Netrapur. He is convinced that

adopting state of the art monitoring

technology with face recognition software

for CCTVs and cross referencing with

universal data base of Aadhaar and PAN

will enable quick identifi cation of persons

from footage and help prevent, detect

and resolve crimes eff ectively. It will also

improve policing with rapid pinpointed

and eff ective action. Coupled with this

he also plans to introduce cyber-policing

of the internet, social media and mobile

messaging using network traffi c analysis.

Combining these two in “san-nirikshan”

will enable compilation of Big Data and

computer visualization of all the activities

of the population helping in curbing of

criminal, anti social as well as socially and

morally reprehensible practices.

He calls a meeting of his top offi cials

and shares his viewpoint. He emphasizes

that adopting “san-nirikshan” and using

visualization will enable Netrapur police to -

• Go beyond geo-political, cultural,

social and physical barriers

• Deploy cost eff ective policing

A Case Study of Netrapur Police


solutions enabling comprehensive 24

by 7 coverage

• Enhance operations and logistics

enabling rapid and eff ective response

• Enable better data gathering and

analysis with visualization for crime

prevention and promoting moral and

ethical society

• Promote inter-state and inter-agency

collaboration and exchange of data

• Use real time data analytics and

advanced visualization techniques

thereby improving the policing

process enabling deterrence,

prediction and prevention of crimes

that are about to happen

• Enable rapid scaling up and right

sizing of the Police force and support

internal and external security

His CP Varun Pal and Joint CP

Crime Vishal are apprehensive of the far

reaching changes and possible impact

especially given the fact that such a major

initiative is being adopted without taking

the people into confi dence and virtually

being thrust on the public. Samar the DSP

is extremely bullish and is certain that this

would provide a defi nite edge to the police

force over criminals, terrorist networks,

anti-social elements and trouble makers

and keep the pseudo intellectuals who

generally foment trouble over human

rights as well as the media in check.

Anticipating some resistance to the

project – “san-nirikshan” from intellectuals

and vested interests Satyarthi emphasizes

that there are both privacy / human rights

concerns as well as deployment issues.

He selects a crack team consisting of

Samar, Varun and Vishal to overcome the

social resistance and nip it in the bud to

enable smooth deployment. They are

also tasked to put in place systems to

address the various issues and concerns

about deploying “san-nirikshan”. The

political set up is fully supportive of the

project and has already given a go ahead

using administrative powers. The project

involves sensitive internal security issues

and hence is outside the purview of

RTI, and is to be kept confi dential with

complete media blackout.

The crack team develops a plan and

submits it. Varun is very uneasy with the

manner in which the whole project is

steamrolled. He seeks an appointment

with Satyarthi and voices his reservations

about privacy and human rights and

freedom of the press. He suggests that

the project be introduced in remote

areas fi rst as a pilot and then extended

to metro cities in a transparent manner. If

implemented initially on a small scale and

then deployed in phases taking the people

into confi dence it will be both acceptable

and successful.

Satyarthi rejects Varun’s approach,

points out the increasing criminal activities

and terrorist attacks and stresses the

need for a full deployment with utmost

secrecy. He advises Varun to go ahead and

implement the plan as it is.

After much persuasion Varun relents

and the project is implemented. The

project achieves quick and remarkable

success. A number of criminal gangs are

neutralized, terrorist activities are visibly

reduced. The backbone of the Naxalite

resistance in remote areas is broken and as

a result the law and order situation in the

state of Netrapur improves considerably.

The police are lauded for their good work

and Satyarthi is promoted. Varun is still

ill at ease and opts for a posting in the

police housing project where he remains

till retirement.

What are your views on project -

“san-nirikshan”?

SolutionThe situation:

Visualization techniques using computer

graphics and imagery, analytics and

presentation using visualization techniques

relating to Big Data especially from Social,

Mobile, Analytics and Cloud technologies

have added a new dimension to surveillance.

The eyes and ears of the police – the Big

Brother are now omnipresent. Surveillance

and use of covert means and secret agents

including agencies like FBI, MI6 and KGB

are common in countries subscribing

to all shades of political, economic and

social viewpoints. The recent use of similar

techniques by the US, to tackle terror and

ensure ‘Homeland Security’, has been

accepted without question. It has had a

signifi cant impact across the world and an

even more profound impact on privacy and

human rights.

There exists a case both for and

against the use of technology for such

means and the case both for and against

use of visualization techniques for internal

and external security is equally strong.

Information technology when combined

with technological advances like street

level view satellites and micro drones

carrying eavesdropping equipment and

remote CCTVs make the visualization and

analytical technology even more powerful.

The way forward therefore cannot

be either to pull the plug on use of Data

visualization for internal policing and / or

external defense or to wait and watch till

the technology is deployed, stabilizes and

is eventually safe and acceptable enough

to adopt.

The challenge:

Disruptive technology as has often been

said needs proper governance. In the same

fashion use of Data visualization has to be

understood, the risks appreciated and the

technology proactively adopted.

There are primarily four challenges

which need to be understood and

considered.

1. Preventing the potential abuse of the

technology and the power it provides

either for selective victimization,

oppression, political misuse, or moral

policing

2. Preventing the leakage, compromise

and misuse of the data resulting

in harm to the community or to

individuals

3. Preventing the loss of privacy and

fundamental human rights

4. Preventing the loss of freedom

of expression and preserving the

opportunity for reasonable dissent

and diff erence of opinion either

collective or individual.

The consequences:

Continuing in the existing fashion with

the project, given the lack of proper

governance and transparency may despite

initial encouraging results, ultimately lead

to a totalitarian situation where a handful

few control the multitude. It will pose a

clear threat to the democratic polity and

cultural ethos. Ethical values may not be

maintained and freedom of expression

and privacy may be lost.

The strategy:

The right strategy for the state of Netrapur

at this stage would be:

1. The four arms – the parliament, the

executive, the judiciary and the press

and public need to understand the

technology and the pressing need to

deploy it.

2. Understand and agree on the need

of using Big Data Visualization and


analytics for internal and external

security and protection.

3. Understand potential threats of

abuse, leakage, and threats to privacy,

fundamental rights and freedom.

4. Develop a GRC (Governance, Risk,

and Compliance) framework with

proper safeguards and security built

in to protect integrity and ethical

values and prevent misuse.

5. Deploy framework and manage

Vulnerabilities and threats.

6. Ensure appropriate controls to

protect the system from future abuse

or compromise.

It is evident from the reported

and unreported incidents till date that

aberrations are possible and misuse

cannot be entirely prevented. However

given the pressing need for adopting

emerging technologies the way forward is

to proactively adopt Data visualization and

analytics. The police in Netrapur cannot

aff ord to lag behind their counterparts in

other countries and states, nor fall short

of the criminal and terrorist networks.

The police have to be where the action

is and even where the action is going to

be in a proactive manner. Likewise the

governance and security framework and

its scope have to deal both with the threats

and the key issues identifi ed above.

An eff ective solution is generally

expected to proceed on these lines.

n

Abo

ut th

e A

utho

r

Dr. Vishnu Kanhere Dr. Vishnu Kanhere is an expert in taxation, fraud examination, information systems security and system audit and has done his PhD in Software Valuation. He is a practicing Chartered Accountant, a qualifi ed Cost Accountant and a Certifi ed Fraud Examiner. He has over 30 years of experience in consulting, assurance and taxation for listed companies, leading players from industry and authorities, multinational and private organizations. A renowned faculty at several management institutes, government academies and corporate training programs, he has been a key speaker at national and international conferences and seminars on a wide range of topics and has several books and publications to his credit. He has also contributed to the National Standards Development on Software Systems as a member of the Sectional Committee LITD17 on Information Security and Biometrics of the Bureau of Indian Standards, GOI. He is former Chairman of CSI, Mumbai Chapter and has been a member of Balanced Score Card focus group and CGEIT- QAT of ISACA, USA. He is currently Convener of SIG on Humane Computing of CSI and Topic Leader – Cyber Crime of ISACA(USA). He can be contacted at email id [email protected]


Solution to October 2014 crossword

Brain Teaser Dr. Debasish JanaEditor, CSI Communications

Crossword »Test your Knowledge on Visualization TechnologiesSolution to the crossword with name of fi rst all correct solution provider(s) will appear in the next issue. Send your answers to CSI

Communications at email address [email protected] with subject: Crossword Solution - CSIC November 2014

CLUESACROSS1. Displays tree data structure in a way that expands outwards (9)5. A property or characteristic of data (9)6. A common data visualization method used in computational fl uid

dynamics (10)7. A data structure optimized to quickly answer multi-dimensional

analytical queries (4)8. A schematic representation of a sequence of operations in a computer

program (9)9. Used in project management to illustrate schedule of a project (5, 5)10. Type of diagram used for data visualization (11)11. Type of diagram showing the fl ow of data through an information system (4, 4)15. A graphical representation of data (5) 16. Field lines resulting from this vector fi eld description of the fl ow (11)17. Type of fi shbone shaped diagram that shows the causes of a specifi c event (8)19. open source JavaScript charting library (8)21. Type of dictionary that illustrates the meaning of words primarily

through pictures (6)22. A sequence of related images viewed in rapid succession to show

apparent movement of objects (9)23. Online analytical processing (4)24. comma separated values (3)27. Online transactional processing (4)28. Displays a list of events in chronological order (8)29. Microsoft Windows-based visual mapping software (10)

DOWN2. Organic-looking n-dimensional objects used in computer graphics for

visualization (8)3. An open-source Java based framework that allows the creation of a wide

variety of charts (10)4. An assignment of a vector to each point in a subset of space used in vector

calculus (11)9. Visualization technique supporting geospatial data analysis (16)12. Describes the property that allows light to partially pass through and

partially refl ect (12)13. What you see is what you get (7)14. A measure of spatial extent, especially width, height, or length (9)18. an open-source network analysis and visualization software package

written in Java (5)20. An eff ect that causes diff erent signals to become indistinguishable when

sampled (8)25. Type of diagram that shows all possible logical relations between a fi nite

collection of sets (4)26. Symbol or icon used to represent data values (5)

Did you know view of Hal Varian on how the Web challenges managers?

Hal Varian, Google’s chief economist commented in The McKinsey Quarterly, Jan 2009:The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill in the next decades, … because now we really do have essentially free and ubiquitous

data. So the complimentary scarce factor is the ability to understand that data and extract value from it.

(More details can be found in http://www.mckinsey.com/insights/innovation/hal_varian_on_how_the_web_challenges_managers)

We are overwhelmed by the responses and solutions received from our enthusiastic readers

Congratulations!ALL correct answers to October 2014 month’s crossword received from the

following readers:

Prof. Suresh Kumar (Dept. of Computer Science and Engineering, Manav

Rachna International University, Faridabad)


Ask an Expert Dr. Debasish JanaEditor, CSI Communications

Your Question, Our Answer“There is a magic in graphs. The profile of a curve reveals in a flash a whole situation — the life history of an epidemic, a panic, or an era of prosperity. The curve informs the mind, awakens the imagination, convinces.”

~ Henry D. Hubbard, 1939

On Object Oriented ProgrammingFrom: Himanshu Raghav, B.Sc. Final Year, Dev Sanskriti Vishwavidyalaya, Haridwar, Uttrakhand

I want to know the concepts of object oriented programming with example that I can easily understand them and not forget them in my whole life time.

AObject Oriented Programming (OOP) involves

� a new paradigm of concepts to programmers

of traditional procedural languages such as Pascal,

C, FORTRAN, COBOL etc. These new ideas, such as,

data hiding, encapsulation and polymorphism lie at the

heart of OOP. In OO system, the system is based

on objects rather than on actions. Here, procedures

operate on abstract values called objects rather than

on stored representations. Objects interact with each

other through well-defi ned interfaces. Objects can be

created and destroyed dynamically. Commonality of

objects can be made explicit by using inheritance.

OO paradigm has two important philosophies:

data hiding and data abstraction. Data hiding philosophy

says to partition the program so that data is hidden

in modules such that users of the service shouldn't

know the underlying implementation. Internal

representation can be accessed from internal

implementation and not by the users of the modules.

Data abstraction philosophy says to decide which

types are needed, to provide full set of operations

for each type so that a new type of data if defi ned

can be used similar to built in type of data with all

sort of operations permissible. Data abstraction is

the decision to concentrate on properties, which are

shared by many objects or situations in the real world,

and to ignore the diff erences between them.

In contrast to procedural programming paradigm

to have a large single store where all procedures work,

in Object-Oriented paradigm, procedures operate

on abstract values called objects rather than on

stored representations. OO programming paradigm

is based on the idea of communicating between

objects to simulate the temporal evolution of a set

of real world phenomena. Data as well as operations

are encapsulated in objects. Information hiding is

used to protect internal properties of an object.

Objects interact by means of message passing or

function invocations. Objects are active entities that

communicate with each other. State of an object may

change in response to some interaction requested

from some other object. In object-oriented paradigm,

objects are grouped in classes. Objects in classes are

similar enough to allow programming of the classes,

as opposed to programming of the individual objects.

Let’s take an example of approach in

implementing say, a stack using procedural paradigm

through C and same implementation using object

oriented paradigm using C++, and let’s compare the

philosophy by discussing pro’s and con’s.

‘C’ implementaion of Stack

#include <stdio.h>#define MAX_SZ 10typedef struct { int data[MAX_SZ]; int sp;} STACK;

void Init(STACK *which) { which->sp = -1; //initialize the stack}bool Push(int d, STACK *which) { if (which->sp == MAX_SZ-1) // overflow return false; which->data[++which->sp]=d; return true;}bool Pop(int *d, STACK *which) { if (which->sp == 1) // underflow return false; *d = which->data[which->sp--]; return true;}int main() { STACK s1, s2; Init(&s1); Init(&s2); Push(3, &s1); Push(4, &s2); Push(5, &s2); int d; Pop(&d, &s1); // d becomes 3 Pop(&d, &s2); // d becomes 5 Pop(&d, &s2); // d becomes 4 return 0;}

In the above approach, we fi nd little strength and few

weaknesses, which are kind of risky.

Strength, fi rst

1. The program is structured, written in a

methodical way

2. Multiple stacks can be used, since stack pointer

is not kept as a global data. Keeping one global

data as stack pointer restricts the usage of

multiple stacks

Weaknesses

1. #defi ne has its own hazards, if we by mistake

put a semicolon after #defi ne MAX_SZ 10; or a

line comment i.e. //, we fall into trap of macros.

2. #defi ne does not ensure datatypes, which are

essence of any data

3. The implementation is well exposed, yet not

protected from wrong usage by the user. For

example, the person who writes main, may

start accessing s1.data[2] directly, absolutely no

control on that.

4. What happens if the user (who writes main)

forgets to initialize the stack by calling Init?

5. Push, Pop take d as a pointer, and the pointer is

passed by value (not reference) in C. Passing

pointer is kind of risky, as, we don’t know

whether the pointer is pointing to a valid content

or not, a pointer may be null or spurious having

uninitialized data, which is very risky.

Now, let’s see if we take a C++ route through object-orientedness.

#include <stdio.h>const int MAX_SZ = 10;//put ; at your willclass STACK {

int data[MAX_SZ];//by default, private

int sp; // by default, private

public:

STACK() { this->sp = -1; }

bool Push(int d) {

if (this->sp == MAX_SZ-1) // overflow

return false;

this->data[++this->sp]=d;

return true;

}

bool Pop(int &d) {

if (this->sp == 1) // underflow

return false;

d = this->data[this->sp--];

return true;

}

};

int main() {

STACK s1, s2; //constructor call

s1.Push(3);

s2.Push(4);

s2.Push(5);

int d;

s1.Pop(d); //d passed as reference, //d becomes 3

s2.Pop(d); // d becomes 5

s2.Pop(d); // d becomes 4

return 0;

}

The eff ect?

1. #defi ne has its own hazards, we don’t fall into

trap of macros. Instead, we defi ne an integer

constant.

2. const int ensures datatypes, which is the

essence of any data

3. The implementation is well exposed, yet

protected from wrong usage by the user.

For example, the person who writes main, is

prevented from accessing s1.data[2] directly, as

the data is private within a stack.

4. No chance of forgetting by the user (who writes

main) to initialize the stack. constructors are

called automatically when variables (objects)

are declared.

5. Push, Pop take d as a integer reference, saves

memory, also, no pointer is passed explicitly,

putting less risk and also looks elegant. No risk

of un-initialized data exists.

A class is a construct for implementing a user-defi ned type. Once defi ned, such types may be conveniently used as the languages primitive types. The instances of a class are called objects. A class specifi es the representation of objects and a set of operations that are applicable to such objects. We have already discussed two important philosophies of object oriented programming as data hiding and data abstraction. Ideally, a class is an implementation of an abstract data type. This implies that the implementation details of the class are private to the class. The public interface of a class is exposed

externally. n

Do you have something to ask? Send your questions to CSI Communications with subject line ‘Ask an Expert’ at email address [email protected]


Happenings@ICT H R MohanICT Consultant, Former AVP (Systems), The Hindu & President, CSIEmail: hrmohan.csi@gmail .com

ICT News Briefs in October 2014The following are the ICT news and headlines of interest in October 2014. They have been compiled from various news & Internet sources including the dailies - The Hindu, Business Line, and Economic Times.

Voices & Views• Smartphones, data plans cheapest in

India, the Internet access remains beyond the grasp of about 95 crore people. It is predicted about 30 crore Internet users will be added by 2018, taking the total number to 50 crore users. Even the cheapest data plans are simply too expensive, equal to 13% of the total spending of people in the segment – McKinsey.

• The demand for regular satellite capacity in India has been growing at over 6% between 2008 and 2013 and now reached 214 transponder equivalents – Euroconsult.

• Better urban planning through telecom networks – LIRNEasia.

• The global semiconductor revenue is on pace to reach $338 billion in 2014, a 7.2% increase from 2013. In 2014, unit production of smartphones and ultramobiles to increase 27% and 18.9% respectively – Gartner.

• Smartphones, a tool for driving productivity. Globally, one-third of business smartphone users said their devices save them more than 5 hours during an average working week – survey.

• The domestic demand of electronic goods is projected to grow to $400 billion by 2020, of which domestic production can cater to only $100 billion.

• India is a test-bed to create tools, ideas for the world. Internet growth in India will have a big global impact – Zuckerberg.

• India is destination of choice for engineering R&D - BVR Mohan Reddy, Vice-Chairman, Nasscom.

• India today is a home to over 600 ER&D companies, and over 400 global ER&D organisations with 2,00,000 engineers are employed by service providers and engineering fi rms.

• As e-commerce grows, protecting consumers is a challenge – Paswan.

• Cyclone Hudhud hits, 1000 crore revenue generating IT industry at Vizag.

• Online retailing - both direct and through marketplaces - will become a Rs. 50,000 crore industry by 2016, growing at a whopping 50-55% annually over the next three years - Crisil Research.

• Mobile messaging apps eating into telcos’ SMS revenue. Operators worldwide will lose $14 billion to OTT services this year - Juniper Research.

• E-commerce sector, which is a little less than one per cent (at $3.2 billion) of the $700-billion retail industry, has attracted several global investors in a short span of time – Industry experts.

• India is the third largest base for start-ups in the world with 3,100 of them after the US (41,500) and the UK (4,000) - Nasscom.

Govt, Policy, Telecom, Compliance• Vizag smart city to get US-funding.• DoT ropes in ISRO scientists to explore

use of satellite for broadband.• Four years after receiving 4G spectrum,

telecom operators - Airtel, Reliance Jio and Aircel have approached the DoTseeking another fi ve years to complete their rollout obligation.

• Two electronic manufacturing clusters (EMC) coming up in Madhya Pradesh at Purva near Jabalpur and Badwai near Bhopal. They will be the fi rst greenfi eld EMCs in the country.

• Audit by CAG fi nds under-utilisation (compared to a total collection of Rs. 58,579 crore, only Rs. 17,947 crore has been disbursed), misuse of Universal Services Obligation funds. In three circles (Kerala, Tamil Nadu and Karnataka), subsidy amount of Rs. 20.34 crore was allowed for 32,759 multiple connections in the name of one person/address and for more than one member of a family at the same address.

• Centre to use Aadhaar-based system to track staff attendance.

• Zuckerberg meets PM and IT Minister to discuss how Facebook can help with the Digital India mission.

• Govt to start reimbursing electronic fi rms under special incentive scheme soon.

• 2G auction: TRAI for 10% hike in 1800 MHz base price at Rs. 2,138 crore per MHz.

• Karnataka drafts policy on rural BPOs; Cabinet nod soon.

• India may dilute stand on Net control. Proposes backing for the popular view on a multi-stakeholder approach to Internet Governance.

• US-based Iridium wants a piece of the Indian satellite services play.

• Green signal for entire SmartCity Kochi project.

• IT fi rms get domestic boost due to Govt. IT spending.

• Japan’s SoftBank to invest $10 billion in India. Picks up stake in Snapdeal ($627m), Ola ($210m)

IT Manpower, Staffi ng & Top Moves• EMC at Jabalpur will generate around

3,000 direct employment opportunities and around 9,000 indirect employment opportunities.

• Kris Gopalakrishnan’s innings at Infosys set to end on 10th Oct 2014. He recently donated $35 million to IISc for brain research and $1.8 million to CMU to fund its research partnership with IISc.

• Yahoo! India R&D Centre lays off 600 in engineering & product development.

• S. Ramadorai steps down from Tata companies.

• Out of Yahoo! into waiting arms of start-ups, e-commerce fi rms.

• Pegasystems to tap varsities, Java, .NET professionals.

• TCS plans to hire 35,000 from campus this year.

• Software majors on hiring spree in Sept quarter.

Company News: Tie-ups, Joint Ventures, New Initiatives• The country’s, claimed to be the fi rst

dedicated medical search engine - www.braham.in to emerge as a one-stop-shop information source for all medical and healthcare-related information has been lauched.

• Online car rental companies - Meri Cabs, Ola Cabs have launched digital wallets. Others like Savaari, Taxiforsure, TabCab, Uber and Mytaxiindia are also said to be in talks with fi rms such as Citrus, PayU and Paytm for creating a mobile or digital wallet.

• Microsoft to continue with the Nokia brand continues in the entry and feature phones for the next 10 years. In the smartphones space, they will be branded as Lumia.

• Flipkart fumbles on the “Big Billion Day” on 6th Oct 2014, as server fails. Flipkart says sorry for mega snag. But claims to a have received a billion hits with about 1.5 million people shopped and achieved a 24-hour sales target of $100 million in gross merchandise value in just 10 hours.

• Hewlett-Packard spinoff likely to hit Mphasis outsourcing biz.

• Flipkart campaign leads retailers to Amazon as www.bigbillionday.com were redirected to rival online marketplace www.amazon.in

• Pre booking starts by Apple for its launch of iPhone 6 and iPhone 6 Plus in India on October 17.

• Microsoft Devices will now import phones from the Hanoi (Vietnam) factory instead of the facility owned by Nokia in Chennai.

• DigitSecure has launched online and mobile social wallet platform – HotRemit for money transfer and payments service.

• Citi downgrades IT sector; shares of Infy, TechM, Mindtree tank.

• Facebook’s Zuckerberg in India to focus on driving Internet access.

• Infi beam.com’s model, ‘live online stores’ - buildabazaar.com, has gathered over 30,000 live stores, enabling merchants or brand owners to set up their own e-retailing portals and off er discounts as they deem fi t for their business.

• Microsoft Ventures is accepting applications for the next batch of its Accelerator programme aimed at technology start-ups.

• With Drones and 3D visuals, real-estate players innovate to attract buyers.

• Flipkart to unveil world’s fi rst dual-screen phone today .

• Philips unveils handset, with large font size keypad, a torch-cum-SOS button and long lasting battery life targeting senior citizens.

• Google’s Inbox promises to act as your personal secretary.

• Zensar Tech sets up the fi rst National Digital Literacy Mission (NDLM) Centre in Pune.

• Dell off ers cloud-based solution targeting mid-size hospital chains.

n


On the Shelf!

Book Review »

Peeyush ChomalSr. Technical Offi cer, C-DAC, Mumbai

First I must congratulate Dr. Debasish Jana for successfully

bringing out 3rd edition of his book C++ and Object-Oriented

P r o g r a m m i n g

Paradigm, which

refl ects upon

acceptance of his

textbook as a fi ne

academic material

amongst students,

professionals and

casual readers’

community. I have

grown up reading

books in C++

dominated largely

by foreign authors

such as Stroustoup,

Lippman with

few contributions

in that area by

Indian Authors.

It is defi nitely

pleasant to see a quality material coming from one more author

with Indian origin who has painstakingly addressed almost each

aspect of C++ and OO paradigm together in roughly 500 pages.

In other words, the book is not voluminous which otherwise tends

to discourage students/casual readers in carrying a bulky load of

material to read through but at the same time is addressing all the

critical mass within the paradigm and C++ as a tool for attaining it.

What has further impressed me is that Dr. Jana has tried to

introduce all the relevant concepts surrounding a particular topic

while discussing it in his book. For example, most books limit their

talk to static

binding and

dynamic binding

whereas Dr Jana

has introduced

his readers to

even concept

of static typing

and dynamic typing and presented the matrix showcasing which

language/tool provides for all four in his very fi rst chapter. But he

has done this without digressing too much into the nitty-gritties

which otherwise would tend to distract reader from main idea into

unnecessary detailing. He has basically given pointers to readers who

can at their will then decide to pursue the in-depth understanding

from alternative material subject to his/her interest in the area.

The book consists of 15 chapters with last two chapters

discussing on Object Oriented Design and Modelling, and

Unifi ed Modelling Language. Each chapter is concluded with

questions challenging reader to assess his/her conceptual

understanding of the topic. The book also comprises of problems

(for laboratory workouts), glossary, bibliography and Index which

take up around 50 pages towards the end. I also appreciate him

for covering pre-processor directives, operator overloading and

advanced concepts in dedicated chapters of their own. He also

has placed emphasis on importance of program design through

chapters on Data abstraction through classes and user defi ned

data types, and Data Structures and Applications in C++. I have

found the textual material well-balanced and well-supported

with diagrams and numerous examples. I therefore recommend

this book to fi nd place on your shelf, your collections and your

Institution’s library, if it has one.

n

Abo

ut th

e A

utho

r Peeyush Chomal serves as Sr Technical Offi cer at C-DAC, Mumbai (Erstwhile NCST) in Research & Development

areas of Software Architectures, Middleware Computing and Sensor Technologies. Equipped with Postgraduation from

University of Madras, Graduation from University of Mumbai and MBA from JBIMS, he has 15 years of experience

spread across Turnkey Project deliveries for DeitY, IAEA, BARC, DGoV and NPCIL. In his free time, he enjoys fi ddling

with open source tools, trying out new gadgets and messing with ROMs on Android/Window platform.

Book Title : C++ and Object-Oriented Programming Paradigm, 3rd edition

Author : Dr. Debasish Jana

ISBN : 978-81-203-5033-5

No. of Pages : 551

Price : Rs. 495/-

Publisher : Prentice Hall India


CSI Report

From CSI SIG and Divisions »Please check detailed news at:

http://www.csi-india.org/web/guest/csic-reports

SPEAKER(S) TOPIC AND GISTInformation Retrieval Society of India, IEEE Uttar Pradesh Section, IEEE Computer Society GLA University SB and CSI Region-1, Division-1 & Mathura Chapter, Department of Computer Engineering & Applications, GLA University, Mathura, India

Prof. DS Chauhan, Prof. Naresh Chauhan, Dr. Sujoy Das, Prof. MM Sufyan Beg, Prof. Krishna Kant, Prof. Anand Singh Jalal, Prof. Charul Bhatnagar, Dr. Dilip Kumar Sharma

L-R: Dr. Dilip Kr Sharma, Prof. Krishna Kant, Prof. DS Chauhan, Dr. Sujoy Das, Prof. Naresh Chauhan & Prof. AS Jalal

27 September 2014: One day National Workshop on “Emerging Trends in Information Retrieval (ETIR – 2014)”

Dr. Dilip introduced workshop theme & focused on need of Information Retrieval

in day to day life. He discussed about how other Computer Science domains

are contributing to Information Retrieval (IR) research area. Emerging trends of

Information Retrieval include cross linguistic IR systems, recommender systems,

social network analysis & temporal Information Retrieval. He explained how

music IR system can play song(s) based on our mood. Dr. Sujoy discussed basic

concepts of IR, IR models & evolution and explained how to search faster. He

gave emphasis on how to index data, phases of indexing & its applications while

assigning tokens. Prof Beg unveiled concept of Precisiating natural language for

question answer system. He explained how natural language processes English

language as well as functioning of computer system to understand English

language through Stenford POS tagger. Dr. Sujoy Das along with Ms. Aarti

Kumar, Ms. Anubha Jain, Avinash Samuel & Mohd. Amir Khan gave hands on

experience on Terrier IR tool to participants.


A.V. Ramachandra Rao Memorial Award for Best Papers in Hardware AreaWe are pleased to announce a new award - A.V. Ramachandra Rao Memorial Award for Best Papers in Hardware Area, named after the late husband of one of our Fellows, Dr Swarnalatha Rao.

Two cash awards of Rs. 10,000/= and Rs. 5,000/= each will be presented to the Best Papers presented in the area of Hardware in the conferences organized by the CSI Units – Chapters, Divisions, Regions during the year and ranked First & Second.

These awards will be presented for the fi rst time in the Annual Convention CSI-2015 to be held at New Delhi in 2015.

The Programme Committee chairs of conferences being held from Apr 2014 till Mar 2015 are requested to nominate and forward three shortlisted papers in the area of Hardware to [email protected] for review and fi nal selection. For more details on the award, pl. visit www.csi-india.org

Brief profi le of

Late Shri. A. V. Ramachandra Rao(1-2-1934 to 2-5-2014)

Late Shri. A. V. Ramachandra Rao was an eminent technologist and entrepreneur in electronic devices and equipment. Over a period of two decades, in the 1960’s and 1970’s, in the formative years of Bharat Electronics Ltd (BEL), he lead teams in the development and manufacturing of X-Ray tubes and systems, electronic tubes of various kinds for civilian and military communication and radar applications, black and white CRTs for use in medical diagnostic systems and in televisions etc. He had aslo contributed to the development of germanium semiconductor devices.

On leaving BEL, Shri Ramachandra Rao became an entrepreneur, and concentrated in developing and manufacturing components and subsystems for import substitution in important electronic equipment, such as defl ection components in TVs, pulse transformers especially for high end power electronic equipment etc.

Shri Ramachandra Rao on invitation by the West Bengal Electronics Corporation, involved in the setting up their TV Picture Tube manufacturing plant – Webel Video Devices in late 1970’s and served as its Managing Director.

He had also set up successful companies in Chennai and Bangalore, concentrating on import substitutions in areas which were important at that time, thus enabling the country to save precious foreign exchange.

Shri. Ramachandra Rao was a keen follower of technological developments taking place across the world. He admired the culture and achievements of western societies. He was deeply interested in education and training of the younger generation in India to do innovative contributions at the level of the advanced industrialized countries.


DETAILS OF CSI GRANTS AVAILABLE FOR CHAPTERS/STUDENT BRANCHES/MEMBERS

(Presented by Mr. Ranga Rajagopal. Hon. Treasurer – CSI)

CSI has made available several new categories of grants for the benefi t of members during the last few years. Following are the

categories of grants available to CSI chapters, student branches and members (as applicable). Members/chapters are requested

to avail the grants provided for the fi scal year before 31st March 2015. Members may share any feedback/suggestions in this

regard with [email protected].

- Tech Bridge - Grant of 5k per event of the chapter (upto 2 events per year) to be availed before 31st March 2015.

Refer http://www.csi-india.org/grant-to-csi-chapters for details

Total Grant budget for 2014-15 Rs. 5.0 Lacs

- Golden Jubilee Chapter Grant (50k for Cat A, 25K for Cat B and 15K for Cat C) - a one

time grant to chapters for a Golden Jubilee event to be conducted before March 31st 2015 to enable all chapter members/Past OBs/

Patrons/Fellows to participate. Refer http://www.csi-india.org/grant-to-csi-chapters for details

Total Grant budget for 2014-15 Rs. 10. Lacs

- Divisional Grant - 25 K available for any chapter level technical event conducted in association with any Division. Event should be

planned and announced well in advance. Refer http://www.csi-india.org/divisions for details


- Tech Bridge (for Student chapters) - 5k for 1 event during the year for the 100

proposals received during the year 2014-15.

Refer http://www.csi-india.org/web/education-directorate/grant-to-student-branch


- Travel grant for Research scholars/students for participation in International Conferences upto Rs. 25K. (Available for fi rst 12

proposals received during the year).

Refer http://www.csi-india.org/c/document_library/get_fi le?uuid=944dd521-20c9-4541-aaf5-a2a6de694be0&groupId=10157

Total Grant budget available for 2014-15 Rs. 3.0 Lacs

- Student Convention grant for Student Branches (25k for State Student convention, 35k for Regional Student Convention and 70k

for National Student Convention). Claim format available with Education Directorate. Convention proposal to be submitted to ED/

NSC for approval as per guidelines in advance


-Support grant to chapters for conducting Chapter level/Regional level/National level rounds of Discover Thinking School Quiz,

Discover Thinking Project Contest. Alan Turing Programming Contest, Discover Thinking Online Quiz for Student members. Refer

notifi cation in CSIC or contact [email protected]



Application for Travel Grants for ResearchersResearch Committee of Computer Society of India has decided to partly fund CSI Life Members to the extent of Rs. 25000/ for

travelling abroad to present research papers at conferences.

CSI Life Members who have been invited to present papers abroad and have received partial or no funding are eligible to apply for the

same. They have to apply within December 31, 2014 to [email protected] and furnish:

1. Name of the Applicant, Organization Details and Bio Data of Applicant

2. CSI Life Membership Number

3. Name of the International Conference with details of the organizers

4. Conference Venue and Date

5. Copy of the Research Paper

6. Copy of the Invitation Letter received from the organizers

7. Details of funding received from/applied to for funding to any other agency

8. Justifi cation for requesting support (in 100 words).

9. Two References (including one from head of the organization)

Dr Anirban Basu

Chairman,

CSI Division V (Education and Research)


CSI News

From CSI Chapters »Please check detailed news at:

http://www.csi-india.org/web/guest/csic-chapters-sbs-news

SPEAKER(S) TOPIC AND GIST

DELHI (REGION I)

Dr. Roop N Bharadwaj, VK Gupta, Dr. AK Bansal

and SD Sharma

13 September 2014: Technical talk on “Innovation Means of IT & Telecommunication of Education”

Mr. Sharma explained how new ideas and innovations in IT are impacting our

day to day life. Dr. Bhardwaj covered the topic on e-learning - education with

innovative means, how it was 30 years before with limited technical support

and how it is as on date with latest technologies. He spoke about how IT is

playing useful role in imparting education to masses living in remote areas.

Speaker and parti cipants during technical talk

HARIDWAR (REGION I)

Dr. Satish K. Peddoju, Lt.Col. (Rtd.) PK Jain,

Prof. VK Sharma, Dr. Mayank Aggrawal and

Dr. Mahendra Singh Aswal

11 October 2014: Expert Session on “Cloud Computing”

Dr. Satish delivered lecture on very current and popular issue of “Cloud

Computing”. He covered all aspects of cloud computing including

Introduction, tools knowledge, practical view of cloud, simulators required

for research and how it works. The session was full of information for all

students, researchers, teachers etc.

Faculty members and parti cipants

CHENNAI (REGION VII)

HR Mohan, Judges-Prof. P Thrimurthy, S Ramanathan

and Bhaskaran assisted by Prof. P Kumar and

Bhuvaneswaran

9 & 12 October 2014: SEARCC – International Schools’ Software Competition

(ISSC) 2014

Participating team had 3 students each. 2 teams from India, 2 from

Sri Lanka, 1 from ROC Taiwan and 1 from Papua New Guinea participated.

Trial competition was held on 11th Oct 2014 and all teams participated in

it for getting experience. Software displaying minute to minute position

was very handy. Result: First- ROC Taiwan, Second-India (Team-B) and

Third- Sri Lanka (Team-A). Mr. Mohan gave away prizes and addressed

the gathering. SEARCC Rolling Trophy was given away to the Taiwan team.

Prize winners with CSI President HR Mohan, Dr. Thangam Meganathan and other dignitaries of CSI

TRIVANDRUM (REGION VII)

Mr. Vinod Purushothaman 6 August 2014: Technical talk on “Connecting with Agile Principles and Practices”

CSI Trivandrum Chapter organized a technical talk on ‘Connecting with

Agile Principles and Practices’ by Mr. Vinod Purushothaman, Technical

Architect, Envestnet Inc. (NYSE: ENV) at Institution of Engineers Hall,

Thiruvananthapuram.

Mr. Vinod Purushothman delivering the lecture


TRIVANDRUM (REGION VII)

Mr. Ramnath Jayakumar 24 September 2014: Technical talk on the topic “Time Management Using A Tomato”

CSI Trivandrum Chapter organized a Technical talk on the

topic ‘Time Management Using A Tomato’ by Mr. Ramnath

Jayakumar, Lead Engineer, Envestnet Inc. (NYSE: ENV),

Thiruvananthapuram at The Institution of Engineers Hall,

Thiruvananthapuram.

Mr. Ramnath Jayakumar delivering the lecture

From Student Branches »(REGION-V) (REGION-V)

CMR TECHNICAL CAMPUS, HYDERABAD ANURAG GROUP OF INSTITUTIONS, HYDERABAD

16th Oct 14: Mr. Somagiri delivered a lecture on “Big Data Analytics" 9th Oct, 2014 : Conducted an one day “TECHNICAL QUIZ CONTEST”

to bring out the talent of the students in Computer programming skills

and winners with certifi cates awarded by the Principal

(REGION-V) (REGION-V)SREE VIDYANIKETHAN INSTITUTE OF MANAGEMENT, TIRUPATI LAKIREDDY BALI REDDY COLLEGE OF ENGINEERING, MYLAVARAM

14th Oct, 2014: New student branch was inaugurated by Consultant

Mr. S. Ramasamy and Mr. Y. Kathiresan, Dr. Mohan, Dean, Mr. Prabhakar,

Guest speaker are during the inauguration

20th and 21st of Sep, 2014: Two day workshop on “ASP.NET MVC4.0”

was conducted by Mr. V. Phani Sekhar, Senior Software Engineering from

HPS, Bangalore

(REGION-V) (REGION-V)KLE DR M S SHESHGIRI COLLEGE OF ENGINEERING AND TECHNOLOGY, BELGAUM

SWARNANDHRA INSTITUTE OF ENGINEERING AND TECHNOLOGY (SIET), NARASAPUR

27th Aug, 2014: Mr. Prasad Inchal, Senior Consultant, HP, Bangalore

inaugurated the CSI activities for the year 2014-15

15th Sep, 2014: Activities for 2014-15 inaugurated Prof, J V R Murthy,

JNTUK – Kakinada. Prof. Rajesh C Jampala, Chairman - CSI Vijayawada

chapter and Principal, Dr. T Madhu with the Student branch Plaque


(REGION-VI) (REGION-VII)P.E.S COLLEGE OF ENGINEERING, AURANGABAD DE PAUL INSTITUTE OF SCIENCE AND TECHNOLOGY, ANGAMALY

12th Oct, 2014: Orphan children and Students of the college along with

Prof. V.A.Losarwar, HOD & Prof. A.U.Jadhav

7th Oct, 2014: Workshop on Ethical Hacking and Web Application

Security by Mr. Manu Zacharia, Information Security Evangelist

(REGION-VII) (REGION-VII)SRINIVASA RAMANUJAN CENTRE, SASTRA UNIVERSITY, KUMBAKONAM SENGAMALA THAYAR EDUCATIONAL TRUST STUDENT BRANCH

9th Oct 14: Event INNOVATE-AD based on advertisement for enriching

student’s creativity and innovative ideas organized wherein 26 teams

from various streams of Engineering, Arts and Science participated.

26th Sep, 2014: National Seminar on Cloud computing was conducted.

Correspondent , Principal, Tamilnadu State student Coordinator

Dr. Srinath and Mr. S. Ramasamy, Consultant are on the dais

(REGION-VII) (REGION-VII)JYOTHI ENGINEERING COLLEGE, THRISSUR MCA DEPARTMENT OF COMPUTING SCIENCE, VELS UNIVERSITY, CHENNAI

22nd Sep, 2014: Computer Awareness Programme for plus students was

conducted by CSI Student Volunteers Mr. Gijo Vargese, Mr. Joe Mathew

and Mr. Sanjo Simon under the guidance of Mr. Viju Shankar, SBC

1st Oct, 2014: Mr. Rajan T.Joseph Director-Education, CSI was the Chief

Guest and delivered the Inaugural address in the National level Technical

symposium CIPHERMIX 2014

(REGION-VII) (REGION-VII)JEPPIAAR ENGINEERING COLLEGE , CHENNAI ST. PETER’S UNIVERSITY, CHENNAI

25th & 26th Sep, 14: Workshop On NS2 Simulations by Mr. Pradeep Kumar

along with Principal Dr. Sushil Lal Das , Director Mrs. M. Regeena Jeppiaar,

CSE HOD Dr. V. L. Jyothi, IT HOD Dr. R. Sabeetha

Inauguration of New student branch by Mr. Rajan Joseph, Director

Education with Vice Chancellor

Please send your student branch news to Education Director at [email protected]. News sent to any other email id will not be considered.

Low-resolution photos and news without gist will not be published. Please send only 1 photo per event, not more.


CSI Calendar 2014

Prof. Bipin V MehtaVice President, CSI & Chairman, Conf. CommitteeEmail: [email protected]

Date Event Details & Organizers Contact Information

November 2014 events

14–16 Nov 2014 International Conference on Emerging Computing Technologies-2014 (ICECT-2014) Organized by Dept. of Computer Science and Applications, M.

D. University, Rohtak in association with CSI Region – I and CS Division – I.

Prof. R S Chhillar

[email protected]

14–16 Nov 2014 International Conference on Information and Communication Technology for Competitive strategies (ICTCS-2014) Organized by: Computer Society of

India, Udaipur Chapter, Division IV, I, SIG-WNs, Hosted by: Sunrise Group of

Institutions, Udaipur. http://www.csi-udaipur.org/ictcs-2014

Prof. Amit Joshi

Organizing Secretary

[email protected]

28-30 Nov 2014 International Conference on Advance in Computing Communication and Informatics at COER School of Management, Roorkee , Uttrakhand

http://coer.ac.in/ICACCI2014/index.html

Dr. Vishal Singhal, Convener

[email protected]

December 2014 events

10-11 Dec 2014 49th Annual Student Convention, Organized by Computer Society of India, Hyderabad Chapter In association with GNIT, Hyderabad. Theme: “ Campus to

Corporate” Venue: GNIT, Ibrahimpatnam, Rangareddy District Telangana.

http://www.csihyderabad.org/csi-2014

Dr. DD Sarma,

Shri Raju Kanchibhotla

Shri Chandra Sekhar Dasaka.

http://www.csihyderabad.

org/csi-2014

12-14 Dec 2014 49th Annual Convention ,Organized by Computer Society of India, Hyderabad Chapter In association with JNTU-Hyderabad & DRDO. Theme:

Emerging ICT for Bridging Future Venue: JNTUH, Kukatpally, Hyderabad

http://www.csihyderabad.org/csi-2014

Sri. J A Chowdary

Sri. GautamMahapatra

[email protected]

12-14 Dec 2014 Special session on “Cyber Security and Digital Forensics” during Computer Society of India Annual Convention - 2014 by CSI Special Interest Group on Cyber Forensics,

JNTU Hyderabad

Dr. Vipin Tyagi

[email protected]

16-20 Dec 2014 ICISS-2014: International Conference on Information Systems Security. At

Institute for Development & Research in Banking Technology (IDRBT), Hyderabad,

India. Co-sponsored by CSI Division IV and CSI SIG-IS.

http://www.idrbt.ac.in/ICISS_2014/

[email protected]

19-21 Dec 2014 EAIT-2014: Fourth International Conference on Emerging Applications of Information Technology at Kolkata. Organized by CSI Kolkata at Indian Statistical

Institute, Kolkata https://sites.google.com/site/csieait/ For paper ssubmission :

https://cmt.research.microsoft.com/EAIT2014

Prof. Aditya Bagchi

Dr. Debasish Jana

Prof. Pinakpani Pal

Prof. R T Goswami

[email protected]

22-24 Dec 2014 ICHPCA-2014: International Conference on High Performance Computing and Applications Organized by: CV Raman College of Engg. in association with CSI

Div-V and IEEE Kolkata Section http://www.ichpca-2014.in/

Prof. (Dr.) Rachita Misra

[email protected]

March 2015

11–13 Mar 2015 9th INDIACom; 2015 2nd International Conference on “Computing for Sustainable Global Development” Organized by Bharati Vidyapeeth’s Institute of Computer

Applications and Management (BVICAM), New Delhi

Prof. MN Hoda

[email protected],

[email protected]

Registered with Registrar of News Papers for India - RNI 31668/78 If undelivered return to : Regd. No. MH/MR/N/222/MBI/12-14 Samruddhi Venture Park, Unit No.3, Posting Date: 10 & 11 every month. Posted at Patrika Channel Mumbai-I 4th fl oor, MIDC, Andheri (E). Mumbai-400 093 Date of Publication: 10 & 11 every month

CSI-2014Annual Convention and

International Conference on Emerging ICT for Bridging FutureHosted by: CSI Hyderabad Chapter

In Association with JNTU Hyderabad & DRDODates: 12th- 14th December 2014, Venue: JNTU Hyderabad

www.csihyderabad.org/csi-2014, www.csi-2014.orgCall for Sponsors/ Participation

Introduction: CSI-2014, the 49th Annual Convention of Computer Society of India (CSI) is being organized as a part of CSI@50, the Golden Jubilee celebrations of CSI by CSI Hyderabad Chapter, in association with Jawaharlal Nehru Technological University, Hyderabad and DRDO.The Golden Jubilee Celebration along with International Conference will be held at JNTU Hyderabad on 12th ,13th and 14th December 2014. The theme of the convention is “Emerging ICT for Bridging Future”. The objective of this convention is to bring together researchers, engineers, developers, practitioners, IT professionals from academia, industry, government establishments, SME, Public Sectors and multi-national companies and share their experience, exchange ideas and update their knowledge on the latest developments in emerging areas. As part of this convention Knowledge sharing sessions on e-governance have been organized where the implementers, policy makers, users and developers from various agencies will be deliberating regarding successful implementation of E-Governance for achieving the vision of Digital India. In this convention many IT luminaries, famous personalities from industries, Govt and Public sectors are participating and deliberating from various aspects of ICT’s for IT enabling of India. Number of Keynote sessions, CIO’s panel discussions is also part of this convention. Large scale exhibition from various IT fi rms is one of the main attractions. We have already received more than 160 high quality research papers on all aspects of the ICT’s and same will be presented in this convention in various parallel tracks.

National Student convention is also being organized at Gurunanak Group of Institutions, Ibrahimpatnam, Hyderabad to make the student community glide through “Campus to Corporate and Beyond” on 10th and 11th December 2014.

Invitation: Govt, Public sectors, Educational Institutes, Software fi rms, industries and business houses are invited to participate in the convention and present and exhibit their products and services. Online registrations facilities are provided in the website: www.csi-2014.org.We also invites proposals for workshops, pre-conference tutorials and doctoral consortium.Registration fee and Sponsorship plan is given below:

*12.36% service tax extra. Payments to be made by DD/Cheque drawn in favour of:

“CSI Annual Convention” Payable at MUMBAI or by RTGS/NEFT at A/c no: 34242332507IFSC Code: SBIN0007074, Service Tax Registration No: AAATC1710FSD001

Sri. J A Chowdary Dr. A Govardhan, JNTU Hyderabad Sri. Gautam Mahapatra, RCI, DRDO Organizing Committee Programme Committee Finance Committee

Souvenir

Page Amount (Rs)

Full Page 50000

Half Page 25000

Qtr. Page 15000

Exhibition Stall 9x6ft:Rs 30000

Delegates will be provided accommodation on fi rst come fi rst serve basis.Transport to venue will be provided by the convention team.

Address for Communication:CSI-Hyderabad Chapter,

#302,Archana Aracde,10-3-190,

Opp: Railway Reservation Complex,

Secunderabad,Telangana-500025

Email:[email protected]

[email protected]

Registrations

Delegate Type CSI Ins(Rs) Others(Rs) Overseas($)

Regular 3000 4000 150

Paper Presenter

Springer

5000 6000 250

Student For Stu.

Convention

400 500 25

Sponsorship Plans

Plan Amount (Rs)

Facilities Given

Registrations Exhibition Stall Ad Pages

Crown 700000 10 2 2

Platinum 500000 5 2 1

Diamond 300000 3 1 1

Gold 200000 2 1 1

Silver 100000 1 Shared Half Page

Bronze 50000 1 None Half Page

csic 2014 ( november )

Documents