Editor-In-Chief Chair Dr. Shiv Kumar

Ph.D. (CSE), M.Tech. (IT, Honors), B.Tech. (IT)

Director, Blue Eyes Intelligence Engineering & Sciences Publication, Bhopal (M.P.), India

Professor, Department of Computer Science & Engineering, Lakshmi Narain College of Technology-Excellence (LNCTE), Bhopal

(M.P.), India

Associated Editor-In-Chief Chair Dr. Dinesh Varshney

Director of College Development Counseling, Devi Ahilya University, Indore (M.P.), Professor, School of Physics, Devi Ahilya

University, Indore (M.P.), and Regional Director, Madhya Pradesh Bhoj (Open) University, Indore (M.P.), India

Associated Editor-In-Chief Members Dr. Hai Shanker Hota

Ph.D. (CSE), MCA, MSc (Mathematics)

Professor & Head, Department of CS, Bilaspur University, Bilaspur (C.G.), India

Dr. Gamal Abd El-Nasser Ahmed Mohamed Said

Ph.D(CSE), MS(CSE), BSc(EE)

Department of Computer and Information Technology , Port Training Institute, Arab Academy for Science ,Technology and Maritime

Transport, Egypt

Dr. Mayank Singh

PDF (Purs), Ph.D(CSE), ME(Software Engineering), BE(CSE), SMACM, MIEEE, LMCSI, SMIACSIT

Department of Electrical, Electronic and Computer Engineering, School of Engineering, Howard College, University of KwaZulu-

Natal, Durban, South Africa.

Scientific Editors Prof. (Dr.) Hamid Saremi

Vice Chancellor of Islamic Azad University of Iran, Quchan Branch, Quchan-Iran

Dr. Moinuddin Sarker

Vice President of Research & Development, Head of Science Team, Natural State Research, Inc., 37 Brown House Road (2nd Floor)

Stamford, USA.

Dr. Shanmugha Priya. Pon

Principal, Department of Commerce and Management, St. Joseph College of Management and Finance, Makambako, Tanzania, East

Africa, Tanzania

Dr. Veronica Mc Gowan

Associate Professor, Department of Computer and Business Information Systems,Delaware Valley College, Doylestown, PA, Allman,

China.

Dr. Fadiya Samson Oluwaseun

Assistant Professor, Girne American University, as a Lecturer & International Admission Officer (African Region) Girne, Northern

Cyprus, Turkey.

Dr. Robert Brian Smith

International Development Assistance Consultant, Department of AEC Consultants Pty Ltd, AEC Consultants Pty Ltd, Macquarie

Centre, North Ryde, New South Wales, Australia

Dr. Durgesh Mishra

Professor & Dean (R&D), Acropolis Institute of Technology, Indore (M.P.), India

Executive Editor Chair Dr. Deepak Garg

Professor & Head, Department Of Computer Science And Engineering, Bennett University, Times Group, Greater Noida (UP), India

Executive Editor Members Dr. Vahid Nourani

Professor, Faculty of Civil Engineering, University of Tabriz, Iran.

Dr. Saber Mohamed Abd-Allah

Associate Professor, Department of Biochemistry, Shanghai Institute of Biochemistry and Cell Biology, Shanghai, China.

Dr. Xiaoguang Yue

Associate Professor, Department of Computer and Information, Southwest Forestry University, Kunming (Yunnan), China.

Dr. Labib Francis Gergis Rofaiel

Associate Professor, Department of Digital Communications and Electronics, Misr Academy for Engineering and Technology,

Mansoura, Egypt.

Dr. Hugo A.F.A. Santos

ICES, Institute for Computational Engineering and Sciences, The University of Texas, Austin, USA.

Dr. Sunandan Bhunia

Associate Professor & Head, Department of Electronics & Communication Engineering, Haldia Institute of Technology, Haldia

(Bengal), India.

Dr. Awatif Mohammed Ali Elsiddieg

Assistant Professor, Department of Mathematics, Faculty of Science and Humatarian Studies, Elnielain University, Khartoum Sudan,

Saudi Arabia.

Technical Program Committee Chair Dr. Mohd. Nazri Ismail

Associate Professor, Department of System and Networking, University of Kuala (UniKL), Kuala Lumpur, Malaysia.

Technical Program Committee Members Dr. Haw Su Cheng

Faculty of Information Technology, Multimedia University (MMU), Jalan Multimedia (Cyberjaya), Malaysia.

Dr. Hasan. A. M Al Dabbas

Chairperson, Vice Dean Faculty of Engineering, Department of Mechanical Engineering, Philadelphia University, Amman, Jordan.

Dr. Gabil Adilov

Professor, Department of Mathematics, Akdeniz University, Konyaaltı/Antalya, Turkey.

Convener Chair Mr. Jitendra Kumar Sen

International Journal of Soft Computing and Engineering (IJSCE)

Editorial Chair Dr. Sameh Ghanem Salem Zaghloul

Department of Radar, Military Technical College, Cairo Governorate, Egypt.

Editorial Members Dr. Uma Shanker

Professor, Department of Mathematics, Muzafferpur Institute of Technology, Muzafferpur(Bihar), India

Dr. Rama Shanker

Professor & Head, Department of Statistics, Eritrea Institute of Technology, Asmara, Eritrea

Dr. Vinita Kumar

Department of Physics, Dr. D. Ram D A V Public School, Danapur, Patna(Bihar), India

Dr. Brijesh Singh

Senior Yoga Expert and Head, Department of Yoga, Samutakarsha Academy of Yoga, Music & Holistic Living, Prahladnagar,

Ahmedabad (Gujarat), India.

Dr. J. Gladson Maria Britto

Professor, Department of Computer Science & Engineering, Malla Reddy College of Engineering, Secunderabad (Telangana), India.

Dr. Sunil Tekale

Professor, Dean Academics, Department of Computer Science & Engineering, Malla Reddy College of Engineering, Secunderabad

(Telangana), India.

Dr. K. Priya

Professor & Head, Department of Commerce, Vivekanandha College of Arts & Sciences for Women (Autonomous, Elayampalayam,

Namakkal (Tamil Nadu), India.

Dr. Pushpender Sarao

Professor, Department of Computer Science & Engineering, Hyderabad Institute of Technology and Management, Hyderabad

(Telangana), India.

S.

No

Volume-7 Issue-5C, February 2019, ISSN: 2277-3878 (Online)

Published By: Blue Eyes Intelligence Engineering & Sciences Publication

Page No.

1.

Authors: Anusha B, B.Annapurna, Arulananth T S, T.Nagarjuna

Paper Title: CSHM Multiplier and Radix-256 Algorithm Using Fir Filter Design

Abstract: Redundant Binary scheme (RB) vary systems are becoming well-liked for the reason that of its distinctive

carry broadcast free addition. A specific filter called as Finite Impulse Response filter which computes its yield

exploitation multiply& accumulation process. At intervals the reward work, a FIR filter supported to new higher radix-

256 and chemical element arithmetic is implemented. The employment of radix-256 booth secret writing cut down the

amount of partial product rows in any multiplication by eight fold. Inside the present work inputs and coefficients unit

of measurement thought-about of 16-bit. Hence, entirely two partial product rows unit of quantity obtained in

Redundant Binary (RB) kind for both input and constant multiplications. These two partial product rows unit of

measurement added exploitation carry free element addition. Finally the element output is converted back to Natural

Binary (NB) kind exploitation element to NB device. Thus the performance of planned number style for FIR filter is

compared with Computation Sharing Multiplier (CSHM) implementation.

Keywords: Redundant Binary, Computation Sharing Multiplier, Finite Impulse Response, FPGAs, ASICs

References: 1. Y. C. Lim, S. R. Parker, and A. G. Constantinides, "Finite word length FIR filter design using integer programming over a discrete coefficient

space," Aug. 1982.

2. Y. C. Lim and S. R. Parker, "FIR filter design over a discrete power-of two coefficient space," IEEE Trans. Acoustics, Speech Signal Processing,

June 1983. 3. H. Samueli, "An improved search algorithm for the design of multiplier less FIR filter with powers-of-two coefficients," July 1989.

4. Hai Huyen Dam, Cantoni A., Kok Lay Teo, Nordholm S.,"FIR Variable Digital Filter With Signed Power-of-Two Coefficients," June 2007.

5. Mustafa Aktan, Arda Yurdakul, and Günhan Dündar. "An Algorithm for the Design of Low-Power Hardware-Efficient FIR Filters," JULY 2008. 6. Vinod A.P., Singla A., Chang C.H., "Low-power differential coefficients-based FIR filters using hardware-optimised multipliers, " February

2007. 7. Dong Shi, Ya Jun Yu, "Design of Discrete-Valued Linear Phase FIR Filters in Cascade Form," July 2011.

8. Jongsun Park, Woopyo Jeong, Hamid Mahmoodi-Meimand, Yongtao Wang, Hunsoo Choo, Kaushik Roy., Computation sharing programmable

fir filter for low-power and high- performance applications. 9. Hiroshi Makino,Yasunobu Nakase, Hiroaki Suzuki, Hiroyuki Morinaka, Hirofumi Shinohara, and Koichiro Mashiko, "An 8.8-ns 54 x 54-Bit

multiplier with high speed redundant binary architecture," June 1996.

10. N. Takagi, H. Yasura and S.Yajima., "High-speed VLSI multiplication algorithm with a redundant binary addition tree" Sept.1985. 11. Yum Kim, Bang-Sup Song, John Grosspietsch, and Steven F. Gilling, " A carry-free 54b x 54b multiplier using equivalent bit conversion

algorithm, " Oct. 2001.

1-3

2.

Authors: Sivakumar Ellappan, Prabhu Kishore, P. Suresh

Paper Title: A Study of Dual Fuel Operation on LHR Diesel Engine

Abstract: Importance of this investigation is 100% biodiesel make use as fuel for low heat rejection (LHR) diesel

engine. Due to this reason bio-fuels namely, eucalyptus oil and paradise oil were selected and used as dual fuel.

Conventional engine hardware parts were coated with lanthana-doped yttria-stabilized zirconia (the doping of YSZ

coatings with small amount of La2O3) with a thickness of 300 µm, so as to analyze the operating parameters of

paradise oil–eucalyptus oil blends. Tests run were replicated on the conventional diesel engine and outcomes were

compared. Test outcomes confirmed that the major intention of this research was attained as engine operating

parameters like, brake thermal efficiency, exhaust gas temperature were increase with decrease of fuel consumption. In

addition, engine emissions of HC, CO and smoke were reduced with exception of NOx for LHR diesel engine than

conventional engine.

Keywords: Lanthana-doped yttria-stabilized zirconia, paradise oil, Eucalyptus oil, Duel fuel, Emission.

References: 1. R.O. Dunn, Low-temperature flow properties of vegetable oil/cosolvent blend diesel fuels, J.Am. Oil Chem. Soc. 79 (2002) 709-715.

2. L.C. Meher, D. VidyaSagar, S.N. Naik, Technical aspects of biodiesel production by Transesterification - a review, Renew. Sustainable Energy

Rev. 10 (2006) 248-268.

3. A. Murugesan, C. Umarani, R. Subramanian, N. Nedunchezhian, Bio-diesel as an alternative fuel for diesel engines - a review, Renew. Sustainable Energy Rev. 13 (2009) 653-662.

4. F.Ma,M.A.Hanna, Biodiesel production-a review, Bioresour. Technol. 70 (1999) 1-15.

5. R. Senthil, E. Sivakumar, R. Silambarasan, Performance and emission characteristics of a low heat rejection engine using Nerium biodiesel and its blends, International Journal of Ambient Energy ISSN: 0143-0750, (2015), 38:2, 186-192.

6. Bhattacharyya S, Reddy CS. vegetable oils as fuels for internal combustion engines: a review. Silsoc Res Inst (1994), 57:157-66.

7. B. K. Venkanna & C. Venkataraman Reddy, Performance, Emission, and Combustion Characteristics of a Diesel Engine Running on Blends of Honne Oil and Diesel Fuel, International Journal of Green Energy, 2015, 12:7, 728-736.

8. D. John PanneerSelvam&K.Vadivel, An Experimental Investigation on Performance, Emission, and Combustion Characteristics of a Diesel

Engine Fueled with Methyl Esters of Waste Pork Lard and Diesel Blends, International Journal of Green Energy, 2013, 10:9, 908-923. 9. G. Lakshmi NarayanaRao, B. DurgaPrasad, S. Sampath& K. Rajagopal Combustion Analysis of Diesel Engine Fueled with Jatropha Oil Methyl

Ester - Diesel Blends, International Journal of Green Energy, 2007, 4:6, 645-658.

10. HasanSerin&NeslihanYucelAkar The Performance and Emissions of a Diesel Engine Fueled with Tea Seed (Camellia sinensis) Oil Biodiesel-Diesel Fuel Blends, International Journal of Green Energy, 2014,11:3, 292-301

11. P.K. Devan, N.V.Mahalakshmi, Utilization of unattended methyl ester of paradise oil as fuel in diesel engine,Fuel, 2009, 88, 1828-1833

12. P. Tamilporai, N.Baluswamy, Simulation and analysis of heat transfer in low heat rejection direct injection diesel engines using a two zone model, in: 3rd Asian e Pacific International Symposium on Combustion and Energy Utilization.

13. S. Jaichandar, P. Tamilporai, Low heat rejection engines - an overview, 2003-01-0405.

14. P.K. Devan, N.V.Mahalakshmi, A study of the performance, emission and combustion characteristics of a compression ignition engine using methyl ester of paradise oil-eucalyptus oil blends,Applied Energy, 2009, 86,675-680.

15. M. Matsumoto, H. Takayama, D. Yokoe, et al., Scripta Mater.54, 2006, 2035.

16. M. Matsumoto, T. Kato, N. Yamaguchi, et al., Surf.Coat.Technol. 203, 2009, 2835.

4-9

17. Y. Liu, Y.F. Gao, S.Y. Tao, et al., J. Therm. Spray.Technol. 17, 2008, 603. 18. Y. Liu, Y.F. Gao, S.Y. Tao, et al., Surf. Coat.Technol. 203, 2009, 1014.

19. Venkata Rao, R.: Decision making in the manufacturing environment using graph theory and fuzzy multiple attribute decision making methods.

Vol. 2. Springer. Newyork (2012). 20. Dinesh Singh., Venkata Rao. R.: A hybrid multiple attribute decision making method for solving problems of industrial environment.

International journal of industrial engineering computations. 2, 631-644. (2011).

21. Saaty, T.L.The analytic hierarchy process. Mc Graw Hill. Newyork (1980).

22. Venkata Rao, R.: Decision making in the manufacturing environment using graph theory and fuzzy multiple attribute decision making methods.

Vol. 1, Springer, Newyork (2007).

3.

Authors: Arulananth T S, Pallavi Goud, Baskar M

Paper Title: Institutions - Industry – Society Collaborative Learning Bring Success in Engineering Education in India

Abstract: Education is one which is the continuous event which shifts the people or whole society from the dark to

light. From the past few decades’ education and educational methods made drastic changes in our real life. Teaching

and learning process has been made enormous growth in our society. Engineering education is literally different from

the general teaching learning scenario. In this world, whatever we are seeing, feeling and experiencing all except the

belongings from the nature are invented or innovated by engineering education. In the beginning of the era we are

unaware about engineering background also we are not finding answers for the basic questions which are raised in our

day to day life like why? how? what? when and where etc. But the engineering has proven that all uncertainties to the

world even though which are not close to the imagination. This growth happened in Indian engineering is not up to

comparable with worldwide growth. It is very clearly indicate that till we have to improve many things in our education

systems. Even though we are competent to produce multiple lakhs of engineers per year, they are not qualified for

availing the job directly. Many engineers are just fit in the job but that jobs are not relevant to their qualifications. Even

though we are following our own systems as well as western education system which will not satisfied our needs.

References: 1. Media Reports, Press Releases, Press Information Bureau, RNCOS Report, Department of Industrial Policy and Promotion (DIPP), Union Budget

2017-18

2. Crook, C. (2013). Varieties of "togetherness" in learning - and their mediation. In M. J. Baker, J. Andriessen & S. Järvelä (Eds.) Affective

Learning Together: social and emotional dimensions of collaborative learning, pp. 33-51. London: Routledge. 3. Détienne, F., Barcellini, F., Baker, M., Burkhardt, J-M., & Fréard, F. (2012). Online epistemic communities: theoretical and methodological

directions for understanding knowledge co-elaboration in new digital spaces. Work: A Journal of Prevention, Assessment and Rehabilitation,

41(1), 3511-3518. 4. Dillenbourg, P. (1999b). Introduction: what do you mean by "collaborative learning"? In P. Dillenbourg (Ed.) Collaborative learning: cognitive

and computational approaches, pp. 1-19. Oxford: Elsevier Science.

5. Baker, M. J. (2009). Intersubjective and intrasubjective rationalities in pedagogical debates: Realizing what one thinks. In B. Schwarz, T. Dreyfus & R. Hershkowitz (Eds.), Transformation of Knowledge through Classroom Interaction, pp. 145-158.

10-11

4.

Authors: Bhagya P, Mahesh P K

Paper Title: A Multimodal Bio-Cryptosystem as a Model against Spoofing Attacks

Abstract: With increased fraud happening, identity theft, and security attacks has becoming easier to spoof the

biometric. In addition to this cryptography as become one of the main concerns about the privacy of each human and

also have huge demand from public to promote a high standard secured system. Considering the main aspects of

privacy and spoofing, we presents a novel multimodal cryptosystem which is having high privacy and difficult to spoof.

The aim of this paper to provide a crypto-biometric system with anti-spoofing techniques with better data encryption

method, increasing the robustness and complexity.

Keywords: Bio-Cryptosystem, Multimodal biometric, Fusion level

References: 1. A. K. Jain, A. Ross, and S. Prabhakar, "An Introduction to Biometric Recognition", IEEE Transactions on Circuits and Systems for Video

Technology, vol. 14, pp. 4-19, 2004.

2. Christina-Angeliki Toli and Bart Preneel, "A Bimodal Veri?cation Cryptosystem as a Framework against Spoo?ng Attacks," International Journal of Intelligent Computing Research (IJICR), Infonomics Society, Volume 6-Issue 2, pp. 540 - 549, 2015.

3. Bhagya P, Dr. Mahesh P.K, "Crypto- Biometric using Substitution Encryption and Discrete Cosine Transformation for Secure Data

Communication", International conference on emerging research in Electronics and Communication Technology, ICERECT 2018, PES college

of Engineering, Mandya.

4. Bhagya P, Dr. Mahesh P.K, "An Efficient Approach to Fingerprint using Fuzzy Vault", in ICrtSIV 2015, Bangalore, Feb 2015, 10.3850/978-981-

09-6200-5_D-37. 5. U. Uludag and A. Jain, "Securing Fingerprint Template: Fuzzy Vault with Helper Data " in Proceedings of the 2006 Conference on Computer

Vision and Pattern Recognition Workshop IEEE Computer Society, 2006, pp. 163.

6. Y. Chung, D. Moon, S. Lee, S. Jung, T. Kim, and D. Ahn, "Automatic Alignment of Fingerprint Features for Fuzzy Fingerprint Vault" presented at Information Security and Cryptology, Beijing, China, 2005.

12-14

5.

Authors: B. Venkata Krishnaveni, K. Suresh Reddy, P. Ramana Reddy

Paper Title: Wireless Indoor Positioning Techniques Based on Ultra Wideband (UWB) Technology

Abstract: Indoor positioning is a challenging research area, and numerous varieties of indoor positioning systems

have been advanced based on specific technologies.Now a day, localization in indoor has appear as a tough

characteristic in lots of end person utilizations; which includes civilian, navy, catastrophe remedy. In evaluation to

outdoorarea, information of location in indoor needs a better accuracy and it is a tough assignment in element due to

numerous items return and scatterwave forms. Ultra Wideband (UWB) is acome upgeneration of indoor localization

and proven superior overall precisionin comparison to alternatives.

This paper affords an outline of indoor positioning solution primarily based on UWB technology. First, the theory,

standardization, and benefits of UWB had been added, followed by means of an in depth relativesurvey of UWB

localization techniques. For put down the degree for the effort, we offer an analysis of the modern technology in indoor

positioning, followed through an in depth comparative evaluation of UWB positioning technology. Dissimilar to prior

15-22

work, this paper provides new classifications, evaluating main recent advances, and disputes for more investigation

through the studies.

Keywords: Indoor positioning, Ultra-wideband, UWB, Measuring techniques

References: 1. Hightower, J.; Borriello, G. Location systems for ubiquitous computing. IEEE Comput. 2001, 34, 57-66. 2. Liu, H.; Darabi, H.; Banerjee, P.; Liu, J. Survey of wireless indoor positioning techniques and systems. IEEE Trans. Syst. Man Cybern. Part C

Appl. Rev. 2007, 37, 1067-1080.

3. Gu, Y.; Lo, A.; Niemegeers, I. A survey of indoor positioning systems for wireless personal networks. Tutor. IEEE Commun. Surv. 2009, 11, 13-32.

4. Al-Ammar, M.; Alhadhrami, S.; Al-Salman, A.; Alari?, A. Comparative Survey of Indoor Positioning Technologies, Techniques, and

Algorithms. In Proceedings of the 2014 International Conference on Cyber worlds (CW), Santander, Spain, 6-8 October 2014; pp. 1-8. 5. Al Nuaimi, K.; Kamel, H. A survey of indoor positioning systems and algorithms. In Proceedings of the 2011 International Conference on

Innovations in Information Technology (IIT), IEEE Society, Abu Dhabi, United Arab Emirates, 25-27 April 2011; pp. 185-190.

6. Chóliz, J.; Eguizabal, M.; Hernandez-Solana, A.; Valdovinos, A. Comparison of Algorithms for UWB Indoor Location and Tracking Systems. In Proceedings of the 2011 IEEE 73rd Conference on Vehicular Technology Conference (VTC Spring), Budapest, Hungary, 15-18 May 2011; pp. 1-

5.

7. Siwiak, K.; McKeown, D. Ultra-Wideband Radio Technology; John Wiley & Sons, Ltd: Newark, NJ, USA, 2005. 8. Arias-de Reyna, E.; Mengali, U. A maximum likelihood UWB localization algorithm exploiting knowledge of the service area layout. Wirel.

Pers. Commun. 2013, 69, 1413-1426.

9. Segura, M.; Mut, V.; Sisterna, C. Ultra wideband indoor navigation system. IET Radar Sonar Navig. 2012, 6, 402-411. 10. Krishnan, S.; Sharma, P.; Guoping, Z.; Woon, O. A UWB based localization system for indoor robot navigation. In Proceedings of the IEEE

International Conference on Ultra-Wideband, ICUWB 2007, Singapore, 24-26 September 2007; pp. 77-82.

11. Kuhn, M.; Mahfouz, M.; Turnmire, J.; Wang, Y.; Fathy, A. A multi-tag access scheme for indoor UWB localization systems used in medical environments. In Proceedings of the 2011 IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems (Bio

Wire leSS), Phoenix, AZ, USA, 16-19 January 2011; pp. 75-78.

12. Subramanian, A. UWB Linear Quadratic Frequency Domain Frequency Invariant Beam forming and Angle of Arrival Estimation. In Proceedings of the IEEE 65th Vehicular Technology Conference, VTC2007-Spring, Dublin, Ireland, 22-25 April 2007; pp. 614-618.

13. Gerok, W.; El-Hadidy, M.; El Din, S.; Kaiser, T. In?uence of the real UWB antennas on the AoA estimation based on the TDoA localization

technique. In Proceedings of the 2010 IEEE Middle East Conference on Antennas and Propagation (MECAP), Cairo, Egypt, 20-22 October 2010; pp. 1-6.

14. Dardari, D.; Conti, A.; Ferner, U.; Giorgetti, A.; Win, M.Z. Ranging with ultra wide band width signals in multi path environments. IEEE Proc.

2009, 97, 404-426. 15. Kok, M.; Hol, J.D.; Schon, T.B. Indoor positioning using ultra wide band and inertial measurements. IEEE Trans. Veh. Technol. 2015, 64, 1293-

1303.

16. Rowe, N.; Fathy, A.; Kuhn, M.; Mahfouz, M. A UWB transmit-only based scheme for multi-tag support in a millimeter accuracy localization system. In Proceedings of the 2013 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNet), Austin,TX, USA, 20-23

January 2013; pp.7-9.

17. Leitinger, E.; Meissner, P.; Rudisser, C.; Dumphart, G.; Witrisal, K. Evaluation of Position-Related Information in Multipath Components for Indoor Positioning. IEEE J. Sel. Areas Commun. 2015, 33, 2313-2328.

18. Porcino, D.; Hirt, W. Ultra-wideband radio technology: potential and challenges ahead. IEEE Commun. Mag. 2003, 41, 66-74.

19. Garcia, E.; Poudereux, P.; Hernandez, A.; Urena, J.; Gualda, D. A robust UWB indoor positioning system for highly complex environments. In

Proceedings of the 2015 IEEE International Conference on Industrial Technology (ICIT), Seville, Spain, 17-19 March 2015; pp. 3386-3391.

20. Pittet, S.; Renaudin, V.; Merminod, B.; Kasser, M. UWB and MEMS based indoor navigation. J. Navig. 2008, 61, 369-384.

21. Gigl, T.; Janssen, G.; Dizdarevic, V.; Witrisal, K.; Irahhauten, Z. Analysis of a UWB Indoor Positioning System Based on Received Signal Strength. In Proceedings of the 4th Workshop on Positioning, Navigation and Communication, WPNC '07, Hannover, Germany, 22 March 2007;

pp. 97-101.

22. Leitinger, E.; Fröhle, M.; Meissner, P.; Witrisal, K. Multipath-assisted maximum-likelihood indoor positioning using UWB signals. In Proceedings of the 2014 IEEE International Conference on Communications Workshops (ICC), Sydney, Australia, 10-14 June 2014; pp. 170-

175. 23. Wymeersch, H.; Lien, J.; Win, M.Z. Cooperative localization in wireless networks. IEEE Proc. 2009, 97, 427-450.

6.

Authors: C. Durga Sruthi, B. Dilip Kumar Reddy

Paper Title: Deep Stock Prediction using Visual Interpretation: DeepClue

Abstract: This proposed paper builds Deep Clue system that links text related models, final users using visual

interpretation. We try to implement following modules in this paper. 1.Designing an architecture for a 'deep neural

network' used for interpretation and we apply algorithms to give similar relevant factors. 2.By exploring different levels

of predictive(relevant) factors and visualizing them that can be interacted by the end users at different factor-levels.

Interpretation method differentiates the predicted and unpredicted values of stock price. 3.We examine visualization

integrated systems using some real-world scenarios like tweeter data, financial news data and obtained stock price

values by predictions. The effective working of Deep Clue helps for proper investment in stocks and to analyses tasks.

Keywords: Deep Clue, stck market, Text Based Visualization, Neural Network

References: 1. A. Dosovitskiy and T. Brox, "Inverting visual representations with convolutional networks," arXiv:1506.02753, 2015.

2. DeepClue: Visual Interpretation of Text-based Deep Stock Prediction

3. Lei Shi ; Zhiyang Teng ; Le Wang ; Yue Zhang ; Alexander Binder 4. .https://en.wikipedia.org/wiki/Deep_learning

5. C. Kearney and S. Liu, "Textual sentiment in finance: A survey of methods and models," International Review of Financial Analysis, vol. 33, pp.

171- 185, 2014. 6. https://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.html

23-24

7.

Authors: G. Sunil Santhosh Kumar, M. Neelakantappa, K.V. Rameswara Reddy

Paper Title: Advanced Mechanisims for Detection of Malware Family Attacks in Computer Networks

Abstract: Computer Networks are one of the fastest growing areas of research in this era.Security is an indispensable

need for all the type of networks i.e wired and wireless network communications. There are a wide variety of malware

and attacks that target the weakness of network. In this paper we have focused on malware which is most vulnerable

25-27

and is prone to attacks.we tried to address some malware detection methods.

Keywords: Ransomeware, spyware, adware, virusTrojan, Botnet, Zbot, GhostMirai, Redyms,

References: 1. Zhao Hengli, Xu Ming, Ning Zheng, Yao Jingjing, Q. Ho, "Malignant Executables Classification Based on Behavioral Factor Analysis",

introduced at the 2010 International Conference on e-Education e-Business e-Management and e-Learning, 2010. 2. Wikipedia. Tempest botnet, [online] Available: http://en.wikipedia.org/wiki/Storm_botnet.

3. 3.F.- S. Enterprise, F-Secure Reports Amount of Malware Grew by 100% amid, 2007, [online]Available: http://www.f-secure.comlf-

secure/pressroornlnews/fs_news_20071204_1_eng.html. 4. J. Stewart, "Behavioural malware analysis using Sandnets", Computer Fraud & Security, vol. 2006, pp. 4-6, December 2006.

5. H. D. Huang, T. Y. Chuang, Y. L. Tsai, C. S. Lee, "Ontology-based Intelligent System for Malware Behavioral Analysis", presented at the 2010

IEEE World Congress on Computational Intelligence (WCCI2010), 2010. 6. C. Willems, T. Holz, F. Freiling, "Toward automated dynamic malware analysis using CWSandbox", IEEE Security & Privacy, vol. 5, pp. 32-39,

2007.

7. A. Vasudevan, "MalTRAK: Tracking and Eliminating Unknown Malware", presented at the Computer Security Applications Conference 2008. ACSAC 2008, 2008..

8. "Practical malware analysis" by Michael sikorski

9. "Cuckoo Malware Analysis"by iqbalmuhardianto 10. "Tools and techniques for defending with malware" by Michael hale

11. "Malware detection and threats made easy" by solis tech.

12. "Malware data science" by Joshua saxe

8.

Authors: J. Swami Naik, N. Kasiviswanath,K. Ishthaq Ahamed,S. Raghunath Reddy

Paper Title: A Survey on Traffic Flow Prediction with Deep Learning Algorithms on Big Data

Abstract: Correct and very much planned activity stream data is vital for the fruitful arrangement of astute

transportation frameworks. In the course of the most recent couple of years, activity information have been report, and

we have truly entered the period of huge information for transportation. Existing movement stream expectation

strategies for the most part utilize shallow activity forecast models and square measure as yet frustrating for a few

genuine world applications.The objective of the smart transportation framework (ITS) is utilizing the correspondence

framework to entirely consolidate the vehicle arrangement of individuals, vehicles and street. Propelled movement

control framework and dynamic activity the executives framework are required to give real time activity stream data.

The conventional movement stream show is named the activity stream state variables(velocity, thickness and stream)

with the correction of your time and area.Traffic stream examination is essential research idea in the transportation

framework. Deep Learning is a type of machine learning used to anticipate movement flow.This circumstance moves us

to take the activity stream expectation issue dependent on profound design models with enormous activity information.

Keywords: Traffic flow prediction,Deep learning,Learning algorithms,Intelligent transportaion system,Artificial

neural network.

References: 1. SelvarajVasanthaKumar,Traffic Flow Prediction using Kalman Filtering Technique, Elsevier, 2017.

2. Yuhan Jia,1,2 Jianping Wu,1 and Ming Xu1,Traffic Flow Prediction with Rainfall Impact Using a Deep Learning Method, Journal of Advanced

Transportation, 2017. 3. HongsukYi, HeeJin Jung, SanghoonBae, Deep Neural Networks for Traffic Flow Prediction0,IEEE,2017

4. Dawei Chen, Research on Traffic Flow Prediction in the Big Data Environment Based on the Improved RBF Neural Network. IEEE Transactions

on Industrial Informatics, 2017 5. Nicholas G. Polson, Deep Learning for Short-Term Traffic Flow Prediction, arXiv,2017.

6. MinalDeshpande, Performance Improvement of Traffic Flow Prediction Model using Combination of Support Vector Machine and Rough Set,

International Journal of Computer Applications, 2017 7. Xianyao Ling, XinxinFeng, Zhonghui Chen, YiwenXu, HaifengZheng, Short-term Traffic Flow Prediction with Optimized Multi-kernel Support

Vector Machine. IEEE congress on Evolutionary Computation. 2017.

8. Hongxin Shao, Boon-Hee Soong, Traffic flow prediction with Long Short-Term Memory Networks (LSTMs),IEEE, 2016. 9. Yuhan Jia, Jianping Wu, and Ming Xu,Traffic Flow Prediction with Rainfall Impact Using a Deep Learning Method,Journal of Advanced

Transportation, 2017.

10. SivabalajiManoharan, Short Term Traffic Flow Prediction Using Deep Learning Approach, National College of Ireland, 2016. 11. Vedat TOPUZ, Hourly Traffic Flow Predictions by Different ANN Models,www.intechopen.com,2010.

12. Wenhao Huang,Haikun Hong,Man Li, Weisong Hu,Guojie Song,Kunqing Xie, Deep Architecture for TrafficFlow Prediction, springer 2013.

13. Wusheng Hu, Yuanlin Liu,The short-term traffic flow prediction based on neural network,IEEE, 2010. 14. Kranti Kumara *, M. Paridab, V.K. Katiyar, Short term traffic flow prediction for a non-urban highway using Artificial Neural Network,Elsevier,

2013.

15. Hua-pu Lu, Zhi-yuan Sun, and Wen-congQu, Big Data-Driven Based Real-Time Traffic Flow State Identification and Prediction, Hindawi,2015. 16. Kang kai, hanjinfeng,Short-term traffic flow prediction based on grid computing pool model, IEEE,2010.

17. Felix Kunde Alexander Hartenstein Stephan Pieper Petra Sauer, Traffic prediction using a Deep Learning paradigm, CEUR-WS.org, 2017.

18. Yuanfang Chen, Falin Chen, YizhiRen, Ting Wu, Ye Yao, DeepTFP: Mobile Time Series Data Analytics based Traffic Flow Prediction,arXiv:1710.01695,2017.

19. Xiaolei Ma, ZhuangDai, Zhengbing He, Jihui Ma, Yong Wang and Yunpeng Wang, Learning Traffic as Images: A Deep Convolutional Neural

Network for Large-Scale Transportation Network Speed Prediction, sensors, 2017. 20. ChengchengXu,&Wei Wang, Short-term traffic flow prediction using a methodology based on autoregressive integrated moving average and

genetic programming,Transport, 2016.

21. AriefKoesdwiady, RidhaSoua, and FakhriKarray, Improving Traffic Flow Prediction With Weather Information in Connected Cars: A Deep Learning Approach, IEEE Transactions on Vehicular Technology, 2015.

22. Qiang Shang, Ciyun Lin, ZhaoshengYang, Qichun Bing, Xiyang Zhou, A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine, 2016.PLOSONE,journal.pone.

23. Zhiyuan Ma andGuangchunLuo, Dijiang Huang, Short Term Traffic Flow Prediction Based on On-line Sequential Extreme Learning Machine,

International Conference on Advanced Computational Intelligence,2016.

24. Haiyang Yu, Zhihai Wu, Shuqin Wang, Yunpeng Wang and Xiaolei Ma, Spatiotemporal Recurrent Convolutional Networks for Traffic

Prediction in Transportation Networks, sensors, 2017.

25. YishengLv,YanjieDuan,Wenwen Kang,Zhengxi Li, Fei-Yue Wang,Traffic Flow Prediction With Big Data: A Deep Learning Approach,IEEE Transactions on intelligent Transportation Systems,2015.

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9.

Authors: M.Padma, N. KasiViswanath, T.Swathi

Paper Title: Blockchain for IoT Application: Challenges and Issues

Abstract: Since from the last decade, Blockchain technology has developed a new crypto-economy and has been

converting the financial industry. Reliability, persistence, scalability, the power of enduring is factors of an IoT

solution. On the other hand, Blockchain is an experimental and investigational type of technology, and not proven.

Blockchain burns up and then face the problems while IoT solutions, once deployed, are handled for years. The main

motivational ideas i.e. decentralized trust and distributed record are capable of distributed and the large-scale Internet of

Things (IoT) applications. Moreover, in this domain, the uses of Blockchain beyond crypto-currencies are very less and

far due to the lack of acceptance and integral framework challenges. In this paper, we illustrate the opportunities for

uses of Blockchain of IoT and study the concern challenges and issues in Blockchain based IoT applications.

Index Terms: Blockchain Technology, Internet of Things (IoT), crypto-economy.

References: 1. S. Nakamoto, "Bitcoin: A peer-to-peer electronic cash system," 2008.

2. N. Szabo, "Smart contracts," Unpublished manuscript, 1994.

3. C. Bormann, M. Ersue, and A. Keranen, "Terminology for constrained-node networks," Internet Requests for Comments, RFC Editor, RFC 7228, May 2014, http://www.rfc-editor.org/rfc/rfc7228. Txt. [Online]. Available: http://www.rfc-editor.org/rfc/rfc7228.txt

4. (2018) Running a full node. https://bitcoin.org/en/full-node# minimum-requirements.

5. T. Project. [Online]. Available: https://www.torproject.org/.

6. de Montjoye, Yves-Alexandre, et al., "openpds: Protecting the privacy of metadata through safeanswers," PloS one 9.7 (2014).

7. Jøsang, Audun, and Jochen Haller., "Dirichlet reputation systems," in Availability, Reliability and Security, 2007. ARES 2007. The Second

International Conference on., 2007. 8. https://datafloq.com/read/iot-and-blockchain-challenges-and-risks/3797

9. http://naveenbalani.com/index.php/2016/07/blockchain-and-enterprise-iot/.

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10.

Authors: Mallari Vijay Kumar, P.N.V.S. Pavan Kumar

Paper Title: A Study on Different Phases and Various Recommendation System Techniques

Abstract: Now-a-days, recommender systems(RS)are playing a crucial role in human tasks. The online websites like

movies, restaurants, education and much more, uses the recommender systems to suggest the customers for E-

commerce. Recommender systems make money by attracting users with recommendations. Each system may use

different datasets from various sources to analyze the user behavior and to find interesting patterns that predict the

user’s future purchase or taste. Most of the times lack of data results to the inappropriate recommendations (means bad

recommendations). This paper reviews different phases involved in implementing RS and various recommender

methods including the study of thosemethods that are used in several papers of various authors. We also included the

advantages and disadvantages of each method. Finally, this paper also gives analyses of various challenges and issues

(problems) faced in the implementation of RS algorithms.

Index Terms: phases, collaborative filtering, content-based filtering, hybrid filtering, problems.

References: 1. Schafer, J. Ben. "Application of Data Mining to Recommender Systems." Encyclopedia of Data Warehousing and Mining, 2015, pp. 345-353.,

doi:10.4018/9781591405573.ch009.

2. Francesco Rikki, et al. "Recommender Systems Handbook." Recommender Systems Handbook, 2011, pp. 1-845., doi:10.1007/978-0-387-85820-3.

3. Isinkaye, F.o., et al. "Recommendation Systems: Principles, Methods and Evaluation." Egyptian InformaticsJournal, vol. 16, no. 3, 2015, pp. 261-

273., doi:10.1016/j.eij.2015.06.005. 4. Patel, Bansari, et al. "Methods of Recommender System: A Review." 2017 International Conference on Innovations in Information, Embedded

and Communication Systems (ICIIECS), 2017, doi:10.1109/iciiecs.2017.8275856.

5. https://en.wikipedia.org/w/index.php?title=Recommender_system&oldid=86592141 6. Saha, Tanwistha, et al. "Journey to planet Datum and Beyond: Coursera-Introduction to recommender systems." Encyclopedia of Social Network

Analysis and Mining, 2017, pp. 1-12., doi:10.1007/978-1-4614-7163-9_110164-1.

7. Chu, Pang-Ming, and Shie-Jue Lee. "A Novel Recommender System for E-Commerce." 2017 10th International Congress on Image and Signal

Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2017, doi:10.1109/cisp-bmei.2017.8302310.

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11.

Authors: P. Nagabhushan Reddy, T. Bhaskara Reddy

Paper Title: Latest Power Management Technologies for Mobile Computing Devices

Abstract: Windows Modern Standby (MS) is the modern Power Management model that enables the Smart phone

like power management and responsiveness on laptops, personal computers. Modern standby provides enriched user

experience similar to the modern smart phones. The new power management model (Connected standby) allows system

to be connected while in standby there by saving the power. With Modern Standby, the system responds quickly, even

while in standby, whenever there is a valid wake events.

Index Terms: Connected Standby, Intel Platform, Personal Computers, Runtime Power Management

References: 1. Intel, Microsoft, and Toshiba. Advanced configuration and power interface specification. http://www.intel.com/ial/powermgm/specs.html, 1996.

2. T. Simunic, L. Benini and G. De Micheli, "Power Management of Laptop Hard Disk", Proceedings of DATE, p.736, 2000

3. T. Simunic, L. Benini, and G. D. Micheli. Event-driven power management. In International Symposium on System Synthesis, pages 18-23, 1999.

4. A. V. Ramesh, S. M. Reddy and D. K. Fitzsimmons, "Airplane system design for reliability and quality," 2018 IEEE International Reliability

Physics Symposium (IRPS), Burlingame, CA, USA, 2018. 5. https://docs.microsoft.com/en-us/windows-hardware/design/device-experiences/introduction-to-modern-standby-testing

42-44

6. Advanced Configuration and Power Interface Specification, Version 5.November 2013. 7. IEEE Standard for Test Access Port and Boundary-Scan Architecture - Redline," in IEEE Std 1149.1-2013 (Revision of IEEE Std 1149.1-2001) -

Redline, vol., no., pp.1-899, May 13 2013.

8. https://software.intel.com/en-us/articles/power-management-states-p-states-c-states-and-package-c-states

12.

Authors: Sriram Konduru, Sai Sushmitha Batchu,Geethika Parvataneni, Dr. Chejarla Venkata Narayana

Paper Title: Semi-Automation of Libraries

Abstract: In this paper we deal with the library management system. From the ancient times there are numerous

updating’s in the system but with the current trends in technology a semi-automated system is what we propose to

minimize the time usage and lessen the cost burden for the institutions or the government to maintain the libraries in a

most efficient manner. Like railways we will also make a self-issue counter for the library books. This will lessen the

time for searching and issuing of the book from the libraries.

Keywords: Technology, Library, Automation, Efficient.

References: 1. Bailey, N. R., Scerbo, M. W., Freeman, F. G., Mikulka, P. J., & Scott, L. A. (2003). Brain-based adaptive automation system and situation

awareness: The role of complacency potential. In Proceedings of the Human Factors and Ergonomics Society 47th Annual Meeting (pp. 1048-1052).

2. Billings, C. E. (1997). Aviation automation: The search for a human-centered approach. Mahwah, NJ: Lawrence Erlbaum. Bolstad, C. A., &

Endsley, M. R. (2000). 3. The effect of task load and shared displays on team situation awareness. In Proceedings of the Human Factors and Ergonomics Society 44th

Annual Meeting (pp. 189-192).

4. Chiou, E. K., & Lee, J. D. (2016). Cooperation in human agent systems to support resilience: A microworld experiment. Human Factors, 58, 846-863.

5. Endsley, M. R. (1996). Automation and situation awareness. In R. Parasuraman & M. Mouloua (Eds.), Automation and human performance: Theory and applications (pp. 163-181).

45-48

13.

Authors: S.Gunasekharan, D.Elangovan, M.Maheswari

Paper Title: Identification of Serious Success Factors to Implement Lean Manufacturing in Indian Middle Scale

Industries

Abstract: The MSMEs are acknowledged as the heart of economic development of a country. The MSMEs are

struggling a lot to withstand in the globalized market without adopting the pioneering move towards in their work. To

increase the efficiency of the organization and eliminate wastes, it is proposed to implement lean manufacturing. It acts

as one of the tool to make a company to sustain. To implement this tool, there are lots of problems faced by the

companies.

Thus the factors which turn as the barriers to implement lean in middle scale manufacturing is recognized through the

real time field study with well-defined form and views from the lean advisors. The top 11 serious success issues such as

durable management and headship, confrontation to change or institute philosophy, worker faith, services and

knowledge, financial abilities, active communication, recital measures, education and training, planning and strategy,

thinking growth and customer focus are identified as the barriers to contrivance lean in middle scale industries.

Keywords: MSMEs, Lean manufacturing, Serious success factors.

References: 1. Achanga, Pius Coxwell, et al. "Lean manufacturing for SMEs: enabling rapid response to demand changes." (2005).

2. S.Gunasekharan, D.Elangovan and P.Parthiban, "Serious Success Factors for Implementation of Lean and Green in Middle Scale Manufacturing Industries", Applied Mechanics and Materials Vols. 592-594 (2014) pp 2588-2595.

3. Bhasin, Sanjay, and Peter Burcher. "Lean viewed as a philosophy." Journal of manufacturing technology management 17.1 (2006): 56-72.

4. Browning, Tyson R., and Ralph D. Heath. "Reconceptualizing the effects of lean on production costs with evidence from the F-22 program." Journal of Operations Management 27.1 (2009): 23-44.

5. Cezar Lucato and Wagner, "Performance evaluation of lean manufacturing implementation in Brazil." International Journal of Productivity and

Performance Management 63.5 (2014): 529-549. 6. S.Gunasekharan, D.Elangovan and P.Parthiban, "A Comprehensive Study to Evaluate the Serious success Factors Affecting Lean concept in

Indian manufacturing Industries", Applied Mechanics and Materials Vols. 592-594 (2014) pp 2569-2576.

7. Diaz-Elsayed, Nancy, et al. "Investigation of lean and green strategies by simulation of manufacturing systems in discrete production environments." CIRP Annals-Manufacturing Technology 62.1 (2013): 475-478.

8. Fullerton, Rosemary R., Cheryl S. McWatters, and Chris Fawson. "An examination of the relationships between JIT and financial

performance."Journal of Operations Management 21.4 (2003): 383-404. 9. Narasimhan, Ram, Morgan Swink, and Soo Wook Kim. "Disentangling leanness and agility: an empirical investigation." Journal of operations

management 24.5 (2006): 440-457.

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14.

Authors: T.Srinivas Reddy

Paper Title: Analysis and CDNA Microarray Image Segmentation Based on Hough Circle Transform

Abstract: The investigation of cDNA microarray image involves of several steps; gridding, segmentation, and

quantification that can meaningfully reduce the quality of gene expression data, and henceforth decrease our self-

reliance in any derived research consequences. Circular Hough Transformation (CHT) is a powerful feature extraction

system used in image analysis, computer vision, and digital image processing. CHT algorithm is applied on the cDNA

microarray images to progress the exactness and the efficiency of the spots localization, addressing and segmentation

process. Thus, microarray data processing steps turn out to be serious for execution of optimal microarray data analysis

and developing assured biological data from microarray images. Segmentation is the method, by which each distinct

cell in the grid must be cautiously selected to define the spot indication and to estimate the background hybridization. In

this paper, a suggested segmentation method is explored, “Adaptive Form Segmentation”.

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Keywords: Hough circle transformation, cDNA microarray image analysis, cDNA microarray image segmentation,

spots localization

References: 1. Fenstermacher D. Introduction to Bioinformatics, Journal of the American Society for Information Science and Technology, 56 (5), 440-446,

(2005).

2. Abdul Ahad H. Biometrics-The Human Password, JITPS, 1 (1), 29-42, (2010).

3. Chee M., Yang R. and Hubbell E., Accessing genetic informationof DNA arrays, Science, 610-614, (1996).

4. Y. H. Yang, M. M. Buckley, S. Dudoit, and T. Speed, "Comparison of methods on cDNA microarray data," J. Compo Graph. Stat., pp.1 08-136, (2002).

5. Ye R., Wang T., Bedzyk L. , Croker K., Applications of DNA microarrays in microbial systems, Journal of Microbiological Methods, 47, 257-

272, (2001). 6. N. Giannakeas, F. Kalatzis, M. G. Tsipouras, and D. I. Fotiadis, Spot addresses for microarray images, Computers methods and programs in

biomedicine, 106 (1), 1-13, (2012).

7. J. D. and Thomas T.,Instinctive Gridding of DNA Microarray Images using Optimal Subimage, International Journal of Recent Trends in Engineering ,1 (4), (2009).

8. Rueda L. and Rezaeian I. A fully automatic gridding method for cDNA microarray images, BMC Bioinformatics, 12-113, (2011).

9. N. Giannakeas and D. I. Fotiadis, An automated method for clustering-based segmentation of cDNA microarray images, Computerized Medical Imaging 33, 40-49, (2009).

10. Karim R., Mahmud S., A review of image analysis techniques for gene spot identification in cDNA Microarray images, International Conference

of Next Generation Information Technology, (2011). 11. A. Ahmed, M. Vials, NG. Iyer, C. Caldas, JD. Brenton, Microarray segmentation methods, Nucleic Acids Res. 32, 50-58, (2004).

12. Y. Chen, E.R. Dougherty, and M.L. Bittner, "Ratio-Based Decisions and the Quantitative Analysis of cDNA Microarray Images, Journal Of

Biomedical Optics vol.2(4), pp.364-374, (1997). 13. M.J. Buckley, Spot User's Guide, CSIRO Mathematical and Information Sciences, Sydney, Australia, (2000).

14. K.I. Siddiqui, A. Hero, and M. Siddiqui, Mathematical Morphology applied to Spot Segmentation and Quantification of Gene Microarray

Images, Asilomar conference on Signals and Systems, (2002). 15. D. Bozinov, and J. Rahnenfuhrer, Unsupervised technique for robust target separation through adaptive pixel clustering, Bioinform,, vol. 18, pp.

747-756, (2002).

16. E. Ergüt, Y. Yardimci, E. Mumcuoglu, O. Konu, Analysis of microarray images using FCM and K-means clustering algorithm, in Proc IJCI, pp.116-121, 2003.

17. W. Shuanhu and H. Yan, Microarray Image Handling Based on Grouping, The First Asia-Pacific bioinformatics conference on Bioinformatics -

Australia, (19), 111-118, (2003).

15.

Authors: Yogesh Madaria, Vijay Kanjarla

Paper Title: Effectiveness of a Dimpled Non-Even Surface For Oscillations Control For Flow Over Fissure: Numerical

Analysis

Abstract: To decay the pressure oscillation in the flow above an open crater, a passive control method, namely

introduction of a dimpled non-even surface, is attempted. This paper presents the numerical analysis of the above

system, which was undertaken to govern the effectuality of the said control modem. This work focuses on an open

fissure with the length-to-depth ratio in proportions of 1: 2. To check the oscillation persuaded in the flow, a textured

non-even surface is fitted at the upstream of the crater. The even and dimpled non even cases are compared for the flow

instability and noise around fissure. Large eddy simulation coupled with acoustic model is utilized as a tool for this. The

results obtained for even cases were compared with available experimental and computation data. On the basis of flow

visualizations, it can be said that introduction of dimpled non-even surface upstream was significantly effective in

suppressing the oscillations in fissure flow. Based on the comparison of flow filed structure in the even and dimpled

non-even cases, the control mechanism of void oscillation technique is evaluated.

Keywords: fissure flow oscillation, passive control, numerical simulation, dimpled non-even surface.

References: 1. Chang, K., Constantinescu, G.., and Park, S.O., 2006, "Analysis of the flow featured mass transfer processes for the incompressible flow past an

open fissure with a laminar and a fully turbulent incoming boundary state", J. Fluid Mech., Vol. 561, pp 113-145. 2. Rowley C, Williams R. Dynamics of high-Reynolds-number flow . Annu Rev Fluid Mech 2006;38:251-76.

3. Williams DR, Cornelius D, Rowley CW. Supersonic fissure response on open loop forcing. Active Flow Control Notes Numer Fluid Mech

Multidiscip Des 2007;95:230-43. 4. Alam MM, Matsuo S, Teramoto K, Setoguchi T, Kim HD. A computational control of fissure-induced pressure oscillations using subfissure. J

Therm Sci 2006;15(3):213-9.

5. Wang YP, Lee SC, Li KM, Gu Z, Chen J. Combined experimental and numerical study of flow over fissure and its application . ACTA Acust United Acust 2012;98(4):600-11.

6. Chokani N, Kim I. Suppression of pressure oscillations in an open fissure by passive pneumatic control. AIAA 91-1729, 1991.

7. Sarno R, Franke M. Suppression of flow-induced pressure oscillations in craters. J Aircr 1994;31(1):90-6. 8. Stallings RL, Plentovich EB, Tracy MB, Hemsch MJ. Effect of passive venting on static pressure distributions in transonic speeds. NASA

Technical Memorandum 4549, 1994.

9. Zhang X, Chen X, Rona A, Edwards J. Attenuation of fissure flow oscillation through leading edge flow control. J Sound Vib 1999;221(1):23-47. 10. Ukeiley LS, Ponton MK, Seiner JM, Jansen B. Suppression of pressure loads in fissure flows. AIAA J 2004;42(1):70-9.

11. Li W, Taku N, Kozo F. Noise control of supersonic fissure flow with upstream mass blowing. Progress in hybrid RANS-LES modeling notes on

numerical fluidmechanics, vol. 117. p. 315-24. 12. [18] Alam MM, Matsuo S, Teramoto K, Setoguchi T, Kim HD. A new method of controlling fissure-induced pressure oscillatons using sub-

fissure. J Mech Sci Technol 2007;21:1398-407.

13. Alam F, Steiner T, Chowdhury H, Moria H, Khan I, Aldawi F, et al. A study of golf ball aerodynamic drag. Proc Eng 2011;13:226-31. 14. Lienhart H, Breuer M, Köksoy C. Drag reduction by dimples? A complementary experimental/numerical investigation. Int J Heat Fluid Flow

2008;29 (3):783-91.

15. Tian LM, Ren LQ, Liu QP, Han ZW, Jiang X. The mechanism of drag reduction around bodies of revolution using bionic non-even surfaces. J Bionic Eng 2007;4(2):109-16.

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16.

Authors: K.Yogitha Lakshmi, S.Dhanalakshmi, B.G.Obula Reddy

Paper Title: An Overview of Data Management in Cloud Computing

Abstract: As we all familiar with cloud computing, it’s not a latest technology, rather we can mention it as an 61-64

emerging technology where most of the industry is trying to store not only its crucial data for redundancy but also

looking for the service management. In that scenario first thing comes in mind is management of data in most efficient

way possible. So here we tried to showcase two technologies of cloud data management namely Cloud BigTable and

Cloud DataStore which they have their own way of working environments. It makes so much importance to choose the

right technology for the right nature of work.

Keywords: Cloud Storage, Data Management, Virtualization, Google File Systems, Data Store

References: 1. Hamlen, K. Kantarcioglu, M. Khan, L. Thuraisingham, B. (2010). Security Issues for Cloud Computing.International Journal of Information

Security and Privacy, 4(2), 36-48.

2. Bernardo Ferreira, Henrique Domingos (2012). Management and Search of Private Data on Storage Clouds.Center for Informatics and Information Technologies.SDMCMM'12, December 3-4, 2012, Montreal, Quebec, Canada.

3. RizwanMian, Patrick Martin (2012). Executing data-intensive workloads in a Cloud.ACM International Symposium on Cluster 2012 12th

IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing. 4. Xiao-Bai Li, SumitSarkar (2006). Privacy Protection in Data Mining: A Perturbation Approach for Categorical Data Information Systems

Research. (17) 3, 254-270

5. Iyengar, V. S. (2002). Transforming data to satisfy privacy constraints. Knowledge Discovery DataMining.ACM Press, New York, 279-288. 6. Daniel J. Abadi (nd) Data Management in the Cloud: Limitations and Opportunities. IEEE Computer Society Technical Committee on Data

Engineering

7. B. Siddhisena, Lakmal Wruasawithana, Mithila Mendis, ?Next generation muti tenant virtualization cloud computing platform?, In: Proceedings of 13th International conference on advanced communication technology(ICACT), vol. 12, no.3; 2011. p.405-10.

8. Z. Xiao and Y. Xiao, ?Security and Privacy in Cloud Computing?, IEEE Communications Surveys & Tutorials, vol. 15, no. 2, pp. 843-859, 2013.

9. Sunilkumar S.Manvi, Gopal Krishna Shyam, "Resource anagement for Infrastructure as a Service(IaaS) in cloud computing: A survey", Journal

of Network and Computer Applications 41, (2014) 424-440.

10. Chase JS, Darrell C Anderson, Prachi N Thakar, Amin M Vahdat, ?Managing energy and server resources in hosting centers?, In: Proceedings of 11th IEEE/ACM international conference on grid computing (GRID), vol.12, no.4; 2010. p.50-2.

11. B. Urgaonkar, P. Shenoy, A. Chandra, P. Goyal, T. Wood, ?Agile dynamic provisioning of multi-tier Internet applications?, ACM Trans Auton

Adaptive Syst 2010; 5 (5):139-48. 12. Vaquero LM, Luis Rodero-Merino, Rajkumar Buyya, ?Dynamically scaling applications in the cloud?, In: Proceedings of the ACM SIGCOMM

computer communication review, vol.41, no.1; 2011. p.45-52.

17.

Authors: R. P. Ram Kumar, R. Jayakumar, A. Sankaridevi

Paper Title: Apriori-based Frequent Symptomset Association Mining in Medical Databases

Abstract: Nowadays, healthcare organizations generate large volumes of data. An automatic way of retrieval is

necessary when the volume of data is increased. Data mining is becoming very popular and has extensively used in

various Healthcare organizations. With the use of various data mining algorithms, it is possible to extract many useful

patterns. Data mining applications can highly benefit various parties in Healthcare organization. This paper proposes to

enable healthcare organizations by predicting the number of patients affected by certain diseases with respect to their

symptoms in medical databases. The pharmacists can use this discovered knowledge and avoid the run out of required

drugs, so that the patients can be treated at the right time.

References: 1. Dhanya P Varghese and Tintu P B, "A survey on health data using data mining techniques", International Research Journal of Engineering and

Technology, Vol. 2, No. 7, pp. 713-720, 2015.

2. Ilayaraja & T. Meyyappan, "Mining medical data to identify frequent diseases using apriori algorithm", In Proceedings International Conference on Pattern Recognition, Informatics and Mobile Engineering, pp. 194-199, 21-22 February, 2013.

3. Sheenal Patel and Hardik Patel, "Survey of data mining techniques used in healthcare domain", International Journal of Information Sciences and Techniques (IJIST) Vol.6, No.1/2, pp. 53-60, 2016.

4. J. Yanqing, H. Ying, J. Tran, P. Dews, A. Mansour and R. Michael Massanari, "Mining infrequent causal associations in electronic health

databases", 11th IEEE International Conference on Data Mining Workshops, pp. 421-428, 2011. 5. R. Karthiyayini and J. Jayaprakash, "Association technique on prediction of chronic diseases using apriori algorithm", International Journal of

Innovative Research in Science, Engineering and Technology, Vol. 4, Special Issue. 6, pp. 255-259, 2015.

6. Yanwei Xing, Jie Wang, Zhihong Zhao and Yonghong Gao, "Combination data mining methods with new medical data to predicting outcome of coronary heart disease", International Conference on Convergence Information Technology, pp. 868-872, 2007.

7. Shweta and Dr. Kanwal Garg, "Mining Efficient Association Rules Through Apriori Algorithm Using Attributes and Comparative Analysis of

Various Association Rule Algorithm", IJARCSSE, Vol. 3, No. 6, pp. 306-312, 2013.

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18.

Authors: R. P. Ramkumar, Sanjeeva Polepaka

Paper Title: Certain Investigations on Sentimental Analysis Architecture and Tools

Abstract: The sentiment is defined as the feeling(s) about the review or comment. The Sentimental Analysis aims to

determine the attitude of content or product for a period at a given moment. Later, these observations are categorized as

negative, neutral, positive and sometimes no sentiment(s) at all. The review(s) or comment(s) on a concern product is

beneficial for the companies to prioritize the issues, narrow down the problems to be solved and to explore the scenarios

for success. This article deals with the study of sentimental analysis or opinion mining architecture and tools used for

Sentimental Analysis for the naive users.

Keywords: Opinion Mining, Tweets, Opinion Polarities, Crawling, Sentimental Analysis, Twitter Statistics.

References: 1. https://www.iprospect.com/en/ca/blog/10-sentiment-analysis-tools-track-social-marketing-success/ 2. http://www.predictiveanalyticstoday.com/top-software-for-text-analysis-text-mining-text-analytics/

3. Parashar and Sharma, "A Literature Review on Architecture, Classification Technique and Challenges of Sentiment Analysis", International

Journal of Engineering Research & Technology, Vol. 5, Issue 5, pp. 124-127, 2016. 4. Meenambigai, "An Efficient Surveillances of Products Based on Opinion Mining", International Journal of Innovative Research in Computer and

Communication Engineering, Vol. 2, Issue 8, pp. 5261-5265, August 2014.

5. Vivekanandan and Helen Josephine, "ROM - Review Opinion Mining a Novelized Framework", International Journal of Computer Sciences and

69-71

Engineering, Volume-2, Issue-11, pp. 86-89, November 2014. 6. Khandelwal, Mishra and V. K. Mishra, "A Survey on Subjective Sentiment Analysis from Twitter Corpus", IJSRSET, Volume 2, Issue 2, pp.

1198-1200, 2016.

7. DongSung Kim and Jong Woo Kim, "Public Opinion Mining on Social Media: A Case Study of Twitter Opinion on Nuclear Power", Advanced Science and Technology Letters, Vol. 51, pp. 224-228, 2014.

19.

Authors: K. Rama Krishna Reddy, B.G. Obula Reddy

Paper Title: Study and Analysis of Big data with MapReduce Framework

Abstract: Exponential growth in data has been observed in recent years. This huge amount of data has caused a new

kind of problem. Existing RDBMS systems cannot handle large data or they are not effective in managing them. Major

Big Data problems are storage and handling. Hadoop is displayed in storage and processing solutions in the form of

HDFS (Hadoop Distributed File System) and MapReduce. Traditional systems are not intended for Big Data

processing, and they can also process structured data. The financial sector is one of the challenges in Big Data. In this

work, unstructured data is processed by Hadoop MapReduce. An effective processing of unstructured data is analyzed

and explained.

Keywords: Big data, Hadoop, HDFS, MapReduce.

References: 1. L. Augusteijn. Sorting morphisms. In S. Swierstra, P. Henriques, and J. Oliveira, editors, 3rd International Summer School on Advanced

Functional Programming, volume 1608 of LNCS, pages 1-27. Springer-Verlag, Sept. 1998.

2. J.W. Backus. Can Programming Be Liberated From the von Neumann Style? A Functional Style and its Algebra of Programs. Communications of the ACM, 21(8):613-641, 1978.

3. R. Bird and O. de Moor. Algebra of programming. Prentice-Hall, Inc., 1996.

4. R. S. Bird. An introduction to the theory of lists. In Proceedings of the NATO Advanced Study Institute on Logic of programming and calculi of discrete design, pages 5-42. Springer-Verlag, 1987.

5. G. E. Blelloch. Programming parallel algorithms. Communications of the ACM, 39(3):85-97, 1996. 6. A. Borodin and J. E. Hopcroft. Routing, merging and sorting on parallel models of computation. In STOC'82: Proceedings of the fourteenth

annual ACM symposium on Theory of computing, pages 338-344. ACM Press, 1982.

7. L. Boug´e, P. Fraigniaud, A. Mignotte, and Y. Robert, editors. Proceedings of the 2nd International Euro-Par Conference on Parallel Processing, 2 volumes, EURO-PAR'96, volume 1123-1124 of LNCS. Springer-Verlag, 1996.

8. W.-N. Chin, J. Darlington, and Y. Guo. Parallelizing conditional recurrences. In Boug´e et al. [7], pages 579-586. Volume 1/2.

9. P. Zadrozny and R. Kodali, Big Data Analytics using Splunk, Berkeley, CA, USA: Apress, 2013. 10. F. Ohlhorst, Big Data Analytics: Turning Big Data into Big Money, Hoboken, N.J, USA: Wiley, 2013.

11. J. Dean and S. Ghemawat, "MapReduce: Simplified data processing on large clusters," Commun ACM, 51(1), pp. 107-113, 2008.

12. F. Li, B. C. Ooi, M. T. Özsu and S. Wu, "Distributed data management using MapReduce," ACM Computing Surveys, 46(3), pp. 1-42, 2014. 13. C. Doulkeridis and K. Nørvåg, "A survey of large-scale analytical query processing in MapReduce," The VLDB Journal, pp. 1-26, 2013.

14. S. Sakr, A. Liu and A. Fayoumi, "The family of mapreduce and large-scale data processing systems," ACM Computing Surveys, 46(1), pp. 1-44,

2013. 15. The emergence of "big data" technology and analytics Bernice Purcell -Holy Family University.

16. The Forrester Wave™: Big Data Predictive Analytics Solutions, Q1 2013 by Mike Gualtieri, January 3, 2013

72-74

20.

Authors: S. Dhanalakshmi, K. Ramakrishna Reddy, K. Vijaya Krupa Vatsal

Paper Title: Overview of Managing Data Storage, Resource Models and Security Issues in Cloud Computing

Environment

Abstract: The Main goal of cloud is more number of users stored data in cloud environments with incredible rate, this

cloud computing technologies performs some services/agreements done with provider and customer, once customer

reach the storage limits for accessing the drive, the cloud computing services specified with pay based on usage and

also mention the period for updating the service, many services generate large amount of data example. Organizations,

social networks, ecommerce applications and etc., these services are generate bulk data daily, it’s more useful to

cooperating the organizations. The storage systems storing capable of huge volumes of data, based on updation the

customer can interact with relational database systems through structured query language. The main concept of cloud

environment is secure, protect the data. To discuss the related issues of managing data in data storage technology,

resource management techniques and security mechanisms in the cloud based environments.

Keywords: Cloud Computing, Data Storage, Cloud Security, Resource Management, distributed file systems

References: 1. Ravishankar, M.N.; Pan, S.L.; and Leidner, D.E. (2011).Examining the strategic alignment and implementation success of a KMS: A subculture-

based multilevel analysis. Information Systems Research, 22(1), 39-59.

2. Tiwana, A (2012), Novelty-knowledge alignment: A theory of design convergence in systemsdevelopment, Journal of Management Information

Systems, 29(1) 15-52. 3. RizwanMian, Patrick Martin (2012). Executing data-intensive workloads in a Cloud. 12th IEEE/ACM International Symposium on Cluster,

Cloud and Grid Computing.

4. Yingjie Shi, XiaofengMeng, Jing Zhao, Xiangmei Hu, Bingbing Liu and HaipingWang (2010). Benchmarking Cloud-based Data Management Systems.CloudDB'10, Toronto, Ontario, Canada. ACM 978-1-4503-0380-4/10/10

5. Bernardo Ferreira, Henrique Domingos (2012). Management and Search of Private Data on Storage Clouds.Center for Informatics and

Information Technologies.SDMCMM'12, December 3-4, 2012, Montreal, Quebec, Canada. 6. XiaofengMeng, Adam Silberstein, Fusheng Wang (2012) Information and Knowledge Management. CIKM'12, October 29-November 2, 2012,

Maui, HI, USA.ACM 978-1-4503-1156-4/12/10.

7. Peter Géczy, Noriaki Izumi, KôitiHasida (2013). Hybrid cloud management: Foundations and strategies. Review of business and finance studies. (4) 1

8. Hussam Abu-Libdeh, Lonnie Princehouse, Hakim Weatherspoon (2010). RACS: A Case for Cloud Storage Diversity, ACM 978-1-4503-0036-

0/10/06

9. Anthes, G. (2010). Security in the Cloud: Cloud Computing Offers Many Advantages, but Also InvolvesSecurity Risks. Communications of

ACM, 53(11), 16-18.

10. Xiao-Bai Li, SumitSarkar (2006). Privacy Protection in Data Mining: A Perturbation Approach for Categorical Data Information Systems Research. (17) 3, 254-270

75-79

11. Iyengar, V. S. (2002). Transforming data to satisfy privacy constraints. Knowledge Discovery DataMining.ACM Press, New York, 279-288. 12. Daniel J. Abadi (nd) Data Management in the Cloud: Limitations and Opportunities. IEEE Computer Society Technical Committee on Data

Engineering

13. Data Management in the Cloud Computing. Ashish Adinath Vankudre, Department of Computer Science & Engineering, Adarsh Institute of Technology Vita, Maharashtra, India, IJSRD - International Journal for Scientific Research & Development| Vol. 5, Issue 12, 2018 | ISSN

(online): 2321-0613.

21.

Authors: H. Anwer Basha, S. Arivalagan, P. Sudhakar, R.P. Narmadha

Paper Title: A New Deterministic Code Allocation Technique for Data Compression in Wireless Sensor Networks

Abstract: Energy utilization is the huge conflict in modeling WSN because it has only inbuilt limited battery. To

diminish the sum of data requires to be communicated, an efficient technique data compression is used prior to

transmission. Since, there is lot of textual data that are available in WSN dataset, lossless compression method is

desirable where the data loss is not preferable. This paper introduces a new deterministic code allocation (DCA)

technique for effectively compresses the data. The DCA technique is a dictionary based, single character encoding

scheme which uses a static dictionary for codeword allocation. The unique feature of DCA technique is the use of fixed

4-bit codewords for every character in the input sequence. As the nodes are constrained on computational resources, the

proposed DCA technique is highly suitable because of its easier implementation. In addition, the DCA technique

compresses the data with no loss of quality and it does not requires any extra information to be transmitted along with

the compressed file. To verify the robustness and compression performance, an extensive experimental analysis is

carried out using real time WSN dataset interms of various performance measures. The experimental results ensured

that the DCA method obtains better compression performance with less computation complexity.

Keywords: WSN, Data compression, Encoding, Energy utilization.

References: 1. Sariga, P. Sujatha, A survey on unequal clustering protocols in wireless sensor networks, J. King Saud Univ. (2017).

2. K. Sohraby, D. Minoli, T. Znati, Wireless Sensor Networks: Technology, Protocols, and Applications, John Wiley & Sons, Hoboken, New Jersey, 2007.

3. Estrin, J. Heidemann, S. Kumar, M. Rey, Next century challenges: scalable coordination in sensor networks, in: Proceedings of the 5th annual

ACM, 1999, pp. 263-270. 4. G. Anastasi, M. Conti, M. Di Francesco, A. Passarella, Energy conservation in wireless sensor networks: a survey, Ad Hoc Networks 7 (2009)

(2009) 537-568.

5. I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, Wireless sensor networks: a survey, Comput. Networks 38 (4) (2002) 393-422. 6. C.S. Raghavendra, K.M. Sivalingam, T. Znati, Wireless Sensor Networks, 1st ed., Springer US, US, 2004.

7. Sadler, Martonosi, Data compression algorithms for energy-constrained devices in delay tolerant networks, in: In: Proceedings of the 4th

international conference on embedded networked sensor systems - SenSys '06, 2006, pp. 265-278. 8. T. Schoellhammer, B. Greenstein, E. Osterweil, M. Wimbrow, D. Estrin, Lightweight temporal compression of microclimate datasets, UCLA

Cent. Embed. Netw. Sens., 2004. 9. E.P. Capo-Chichi, H. Guyennet, J.M. Friedt, K-RLE: a new data compression algorithm for wireless sensor network, in: Proceedings of the 3rd

International Conference on Sensor Technologies and Applications, (SENSORCOMM'09), 2009, pp. 502-507.

10. M. Francesco, M. Vecchio, An efficient lossless compression algorithm for tiny nodes of monitoring wireless sensor networks, Comput. J. 52 (8) (2009) 969-987.

11. Y. Liang, Y. Li, An efficient and robust data compression algorithm in wireless sensor networks, IEEE Commun. Lett. 18 (3) (2014) 439-442.

12. J.G. Kolo, S.A. Shanmugam, D.W.G. Lim, L.-M. Ang, K.P. Seng, An adaptive lossless data compression scheme for wireless sensor networks, J. Sensors (2012).

13. Kiely, M. Xu, W.-Z. Song, R Huang, B. Shirazi, Adaptive networks, linear filtering compression on realtime sensor networks, Comput. J. 53 (10)

(2010) 1606-1620. 14. Y. Liang, W. Peng, Minimizing energy consumptions in wireless sensor networks via two-modal transmission, Comput. Commun. Rev. 40 (1)

(2010) 13-18.

15. J. Gana, S.A. Shanmugam, D. Wee, G. Lim, L. Ang, Fast and efficient lossless adaptive compression scheme for wireless sensor networks q, Comput. Electr. Eng. 41 (2015) 275-287.

16. A.L.L. Aquino, E.F. Nakamura, Data centric sensor stream reduction for real-time applications in wireless sensor networks, Sensors 9 (12) (2009)

9666-9688. 17. Alippi, G. Anastasi, An adaptive sampling algorithm for effective energy management in wireless sensor networks with energy-hungry sensors,

IEEE Trans. 59 (2) (2010) 335-344.

18. [18] T. Shu, M. Xia, J. Chen, C. de Silva, An energy efficient adaptive sampling algorithm in a sensor network for automated water quality monitoring, Sensors 17 (11) (2017) 2551.

19. A.L.L. Aquino, O.S. Junior, A.C. Frery, E.L. Albuquerque, R.A.F. Mini, MuSA: multivariate sampling algorithm for wireless sensor networks,

IEEE Trans. Comput. 63 (4) (2014) 968-978. 20. M. Taghout, A.K. Chorppath, T. Waurick, F.H.P. Fitzek, On the design of a joint compressed sensing and network coding framework, in:

European Wireless 2018; 24th European Wireless Conference, 2018, pp. 113-119.

21. P. Sun, L. Wu, Z. Wang, M. Xiao, Z. Wang, Sparsest random sampling for cluster-based compressive data gathering in wireless sensor networks, IEEE Access 6 (c) (2018) 36383-36394.

22. "Gzip Home Page," 2018. [Online]. Available: http://www.gzip.org/.

23. "Bzip2 Home Page," 2018. 24. D.A. Huffman, in: A method for the construction of minimum-redundancu codes, 1952, pp. 1098-1102.

25. I.H. Witten, R.M. Neal, J.G. Cleary, Arithmetic coding for data compression, Commun. ACM 30 (6) (1987) 520-540.

26. "Sensor Scope deployments homepage," 2011. [Online]. Available: https://lcav. epfl.ch/page-145180-en.html. 27. T. Schoellhammer, B. Greenstein, E. Osterweil, M. Wimbrow, D. Estrin, Lightweight temporal compression of microclimate datasets, UCLA

Cent. Embed. Netw. Sens., 2004

80-86

22.

Authors: R. Kamali, G. Jayalalitha

Paper Title: Renormalization in AC Circuits based on Fractal

Abstract: In this paper the Feynman infinite ladder AC circuits is analyzed by Renormalization method to form

Fractal AC circuits, since operative of Renormalization gives the potentialities and interrelations of an infinite ladder. In

particular, this analyzation is for the so-called Feynman Sierpinski ladder that exhibits the AC frequency response of

Sierpinski Gasket networks. This extends the self-similarity resistance networks. There forms a Regular Set which is

rectifiable and Line Graphs are also formed using adjacent edges of the AC circuits induces the connectedness and the

continuous self-similarity throughout the circuit.

87-90

Keywords: Fractals, AC circuits, Renormalization, Regular Set, Line Graphs, Rectifiable, Iteration.

References: 1. R. P. Feynman, R. B. Leighton and M. Sands, The Feynman Lectures on Physics, volume 2 Basic Books, California Institute of Technology,

(1965-2013).

2. E. Akkermans, Joe P. Chen, Gerald Dunne, Luke G. Rogers, and Alexander Teplyaev. Fractal AC circuits and propagating waves on fractals,

Xiv:1507.05682, Volume 2(2018).

3. Robert S Strichartz and Alexander Teplyaev, Spectral analysis on infinite sierpinskifractafolds, Journal d'AnalyseMathematique, 116(1),(2012),255-297.

4. A. Teplyaev, Spectral analysis on infinite Sierpinski gaskets, Journal of Functional Analysis, volume 159,no.2, (1998), 537-567.

5. R. Meyers, R. S. Strichartz and A.Teplyaev, Dirichlet forms on the Sierpinski gasket, Pacific Journal of Mathematics, volume 217, (2004), 149-174.

6. D. Fontaine, T. Smith and A. Teplyaev, Resistance of random Sierpinski gaskets, in Quantum graphs and their applications, volume 415 of

Contemp. Mathematics,( 2006), 121-136. 7. D. J. Kelleher, B. A. Steinhurst and C.M.M. Wong, From self-similar structures to self-similar groups, Internat Journal of Algebra computation

volume 22, no.7 1250056, (2012), 16.

8. Joe P. Chen, Luke G. Rogers, Loren Anderson, Ulysses Andrews, Antoni Brzoska, Aubrey Coffey, Hannah Davis, Lee Fisher, Madeline Hansalik, Stephew Loew, Alexander Teplyaev Power Dissipation in Fractal AC Circuits Journal of Physics A: Mathematical and Theoretical,

Volume 50(32),(2017)

9. Joe P. Chen, Gerald Dunne, Luke G. Rogers, and Alexander Teplyaev, Power Dissipation in Fractal Feynman-Sierpinski AC Circuits Patricia Alonso Ruizar Xiv:1701.08039VI, (2017)

10. B. Boyle, K. Cekala, D. Ferrone, N. Rifkin and A. Teplyaev, Electrical resistance of n-gasket fractal networks, Pacific Journal of Mathematics,

volume 233, (2007)15-40. 11. F. Englert, J. M. Freere, M. Rooman and P. Spindel, Metric space-time as fixed point of the renormalization group equations on fractal structures,

Nuclear Physics B, volume 280, (1987)147-180.

12. K. J. Falconer, The Geometry of Fractal Sets, Cambridge Tracts in Mathematics, 85.Cambridge University Press, Cambridge, (1986). 13. H. Whitney, Congruent graphs and the connectivity of graphs, Amer. J. Math. 54 (1932), 150-168.

14. Narsingh Deo, Graph Theory with Applications to Engineering and Computer Science, Prentice-Hall, Inc., Englewood Cliffs, N.J., U.S.A.,

(1974).

23.

Authors: D.M. Sheeba, R. Varalakshmi, N. Anbumani

Paper Title: Lightweight Algorithms for Low Powered IoT Devices Comparative Analysis

Abstract: Internet of Things is the Connections of embedded technologies that contained physical objects and is used

to communicate and intellect or interact with the inner states or the external surroundings. Rather than people-people

communication, IoT emphasis on machine-machine communication. This paper familiarizes the status of IoT growth.

The IoT embeds some intelligence in Internet connected objects to communicate, exchange information, take decisions,

invoke actions and provide amazing services. This paper addresses the existing development trends, the generic

architecture of IoT, its distinguishing features and possible future applications. This paper also forecast the key

challenges associated with the development of IoT. It emphasizes the use of lightweight algorithms to increase the

security of content with less iteration.

Keywords: Internet of Things, ubiquitous computing, Lightweight Algorithm, IoT architecture, IoT applications, IoT

security.

References: 1. D. Singh, G. Tripathi, and A.J. Jara. "A survey of Internet-of-things: Future vision, architecture, challenges and services." In Internet of Things

(WF-IoT), 2014 IEEE World Forum on, pp. 287-292. IEEE, 2014.

2. Johnson, L.; Adams, S.; Cummins, M. NMC Horizon Report: 2012 Higher Education Edition; Impacts of Current and Future Technologies on Higher Edudation; The New Media Consortium (NMC): Austin, TX, USA, 2012; ISBN 978-0-9846601-3-1. Available online:

http://www.nmc.org/pdf/2012-horizon-report-HE.pdf (accessed on 27 July 2018)

3. JYang Lu. Li Da XuIEEE IoT Journal Sep 2018. Biologically Inspired Resource Allocation for Network Slices in 5G-Enabled Internet of Things 4. Hochschule Aalen. Internet of Things. Available online: https://www.hs-aalen.de/en/courses/66/info (accessed on 27 July 2018).

5. S. Lanzisera et al., "Communicating power supplies: Bringing the internet to the ubiquitous energy gateways of electronic devices," IEEE

Internet Things J., vol. 1, no. 2, pp. 153-160, Apr. 2014. 6. Dezhgir, Hamid, And Haniyeh Hooshmand."Security On The Internet Of Things." (2017).

7. Holler, J.; Tsiatsis, V.; Mulligan, C.; Karnouskos, S.; Boyle, D. From Machine-to-Machine to the Internet of Things: Introduction to a New Age

of Intelligence, 1st ed.; Academic Press Ltd.: London, UK, 10 April 2014.

8. Evans, D. The Internet of Things: How the Next Evolution of the Internet Is Changing Everything; White Paper 2011; Cisco Internet Business

Solutions Group (IBSG), Cisco Systems, Inc.: San Jose, CA, USA,2011.Available online: http://www.cisco.com /web /about/ac79

/docs/innov/IoT_IBSG_0411 FINAL.pdf (accessed on 27 July 2018). 9. Borja Martinez ;MàriusMontón ; IgnasiVilajosana ; Joan Daniel PradesIEEE Sensors Journal ( Volume: 15, Issue: 10, Oct. 2015 )

10. Teich, P. Segmenting the Internet of Things (IoT); White Paper 2014; Moor Insights & Strategy: Austin, TX, USA, 2014. Available online: http://www.moorinsightsstrategy.com/wp-content/uploads/2014/05/Segmentingthe-Internet-of-Things-IoT-by-Moor-Insights-and-Strategy.pdf

(accessed on 27 July 2018).

11. Scully, P. The Top 10 IoT Segments in 2018-Based on 1,600 Real IoT Projects. IoT Analytics: Market Insights for the Internet of Things, February 2018. Available online: https://iot-analytics.com/top-10-iot-segments2018-real-iot-projects/# (accessed on 27 July 2018).

12. Weissberger, A. TiECon 2014 Summary-Part 1: Qualcomm Keynote & IoT Track Overview. IEEE ComSoc, May 2014. Available online:

https://community.comsoc.org/blogs/alanweissberger/tiecon-2014-summarypart-1-qualcomm-keynote-iot-track-overview (accessed on 27 July 2018).

13. Evans, D. The Internet of Everything: How More Relevant and Valuable Connections Will Change the World; White Paper 2012; Cisco Internet

Business Solutions Group (IBSG), Cisco Systems, Inc.: San Jose, CA, USA, 2012. Available online: https://www.cisco.com/web/about/ac79/docs/innov/IoE.pdf (accessed on 27 July 2018).

14. Darwish, D. (2015) "Improved Layered Architecture for Internet of Things." International Journal of Computing Academic Research (IJCAR),

4(4):214-223. 15. Evans, D. How the Internet of Everything Will Change the World. Cisco Blog, November 2012. Available online:

http://blogs.cisco.com/news/how-the-internet-of-everything-will-change-the-worldforthe-better-infographic/ (accessed on 27 July 2018).

16. Bradley, J.; Barbier, J.; Handler, D. Embracing the Internet of Everything to Capture Your Share of $14.4 Trillion: More Relevant, Valuable Connections Will Improve Innovation, Productivity, Efficiency & Customer Experience; White Paper 2013; Cisco Internet Business Solutions

Group (IBSG), Cisco Systems, Inc.: San Jose, CA, USA, 2013. Available online:

http://www.cisco.com/web/about/ac79/docs/innov/IoE_Economy.pdf (accessed on 27 July 2018). 17. Mahoney, J.; LeHong, H. Innovation Insight: The 'Internet of Everything' Innovation Will Transform Business; Research Report 2012; Gartner,

91-96

Inc.: Stamford, CT, USA, 2012. Available online: https://www.gartner.com/ doc/1886915/innovation-insight-internet-everything-innovation (accessed on 27 July 2018).

18. EOT Coin. IoT Needs EOT. Available online: https://eotcoin.org/ (accessed on 27 July 2018).

19. Bradley, J.; Reberger, C.; Dixit, A.; Gupta, V.; Macaulay, J. Internet of Everything (IoE): Top 10 Insights from Cisco's IoE Value at Stake Analysis for the Public Sector; Economic Analysis 2013; Cisco Internet Business Solutions Group (IBSG), Cisco Systems, Inc.: San Jose, CA,

USA, 2013. Available online: http://www.cisco. com/web/about/ac79/docs/IoE/IoE-VAS_Public-Sector_Top-10-Insights.pdf (accessed on 27

July 2018).

20. Miraz, M.H.; Khan, S.; Bhuiyan, M.; Excell, P. Mobile Academy: A Ubiquitous Mobile Learning (mLearning) Platform. In Proceedings of the

International Conference on eBusiness, eCommerce, eManagement, eLearning and eGovernance (IC5E 2014), London, UK, 30-31 July 2014; pp.

89-95. 21. G. Peretti, V. Lakkundi, M. Zorzi, "BlinkToSCoAP: An End-to-End Security Framework for the Internet of Things." (2015).

22. X. F. Wang, "Research on Security Issues of the Internet of Things." In Advanced Materials Research, vol. 989, pp. 4261-4264. 2014.

23. Z. Xu, Y. Yin, and J. Wang, "A density-based energy-efficient clustering algorithm for wireless sensor networks." International Journal of Future Generation Communication and Networking 6, no. 1 (2013): 75-86.

24. Khan, S.; Shayokh, M.A.; Miraz, M.H.; Bhuiyan, M. A Framework for Android Based Shopping Mall Applications. In Proceedings of the

International Conference on eBusiness, eCommerce, eManagement, eLearning and eGovernance, London, UK, 30-31 July 2014; pp. 27-32.. 25. Bradley, J.; Loucks, J.; Macaulay, J.; Noronha, A. Internet of Everything (IoE) Value Index: How Much Value Are Private-Sector Firms

Capturing from IoE in 2013? White Paper 2013; Cisco Internet Business Solutions Group (IBSG), Cisco Systems, Inc.: San Jose, CA, USA,

2013. Available online: https://www.cisco.com/c/dam/en_ us/about/business-insights/docs/ioe-value-index-whitepaper.pdf (accessed on 27 July 2018).

26. Soomro, S.; Miraz, M.H.; Prasanth, A.; Abdulla, M. Artificial Intelligence Enabled IoT: Traffic Congestion Reduction in Smart Cities. In

Proceedings of the IET 2018 Smart Cities Symposium (SCS '18), Zallaq, Bahrain, 22-23 April 2018; pp. 81-86. 27. Alansari, Z.; Anuar, N.B.; Kamsin, A.; Soomro, S.; Belgaum, M.R.; Miraz, M.H.; Alshaer, J. Challenges of Internet of Things and Big Data

Integration. In Proceedings of the International Conference on Emerging Technologies in Computing 2018 (iCETiC '18), London, UK, 23-24

August 2018. 28. Derbez P, Fouque PA. Exhausting demirci-seluk meet-in-the-middle attacks against reduced-round AES. International Workshop on Fast

Software Encryption; 2014. p. 541-60.

29. Mitchell, S.; Villa, N.; Stewart-Weeks, M.; Lange, A. The Internet of Everything for Cities: Connecting People, Process, Data, and Things To Improve the 'Livability' of Cities and Communities; White Paper 2013; Cisco Internet Business Solutions Group (IBSG), Cisco Systems, Inc.:

San Jose, CA, USA, 2013. Available online: http://www.cisco.com/ web/strategy/docs/gov/everything-for-cities.pdf (accessed on 27 July 2018)

30. Lee J, Lim D. Parallel architecture for high-speed block cipher, HIGHT. International Journal of Security and its Applications. 2014; 8(2):59-66. 31. Chaudhry, J.; Qidwai, U.; Miraz, M.H.; Ibrahim, A.; Valli, C. Data Security among ISO/IEEE 11073 Compliant Personal Healthcare Devices

through Statistical Fingerprinting. In Proceedings of the 9th IEEE-GCC Conference and Exhibition 2017, Manama, Bahrain, 9-11 May 2017; pp.

319-324. 32. Barbier, J.; Bhatia, P.K.; Kapoor, D. Internet of Everything in ASEAN: Driving Value and Opportunity in Oil and Gas, Utilities, and

Transportation; White Paper 2014; Cisco Internet Business Solutions Group (IBSG), Cisco Systems, Inc.: San Jose, CA, USA, 2014. Available

online: http://www.cisco.com/web/about/ac79/ docs/IoE/IoE-in-ASEAN.pdf (accessed on 27 July 2018). 33. Evans, D. Ask the Futurist: "How Will the Internet of Everything Impact Teachers' Roles in the Connected Classroom?", 12 September 2013.

Available online: http://blogs.cisco.com/ioe/connected-classroom/ (accessed on 27 July 2018)

34. Ali, N.A.; Abu-Elkheir, M. Internet of Nano-Things Healthcare Applications: Requirements, Opportunities, and Challenges. Proceedings of 11th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob' 2015), Abu Dhabi, UAE, 19-21

October 2015.

35. Nyberg K. Links between Truncated Differential and Multidimensional Linear Properties of Block Ciphers and Underlying Attack Complexities. 2015. p. 165-85.

36. Akyildiz, I.F.; Pierobon, M.; Balasubramaniam, S.; Koucheryavy, Y. The Internet of Bio-Nano Things. IEEE Commun. Mag. 2015, 53, 32-40.

[CrossRef] 37. Kalyani, V.L.; Sharma, D. IoT: Machine to Machine (M2M), Device to Device (D2D) Internet of Everything (IoE) and Human to Human (H2H):

Future of Communication. J. Manag. Eng. Inf. Technol. 2015, 2, 17-23.

38. Loughran, J. Graphene radios could unlock 'Internet of Nano-Things'. Engineering and Techbology (E&T), November 2016. Available online: https://eandt.theiet.org/content/articles /2016/11/graphene-radioscould-unlock-internet-of-nano-things/ (accessed on 27 July 2018).

39. Sheikh Ferdoush, Xinrong Li "Wireless Sensor Network System Design using Raspberry Pi and Arduino for Environmental Monitoring Applications", Elsevier The 9th International Conference on Future Networks and Communications (FNC-2014)

40. Gartner. Research Methodologies: Gartner Hype Cycle. Available online: http://www.gartner.com/ technology /research/ methodologies/hype-

cycle.jsp (accessed on 27 July 2018). 41. Gil Press. It's Official: The Internet of Things Takes over Big Data as The Most Hyped Technology. Forbes, August 2014. Available online:

http://www.forbes.com/sites/gilpress/2014/08/18/its-official-theinternet-of-things-takes-over-big-data-as-the-most-hyped-technology/ (accessed

on 27 July 2018) 42. 2. Gartner. Gartner's 2015 Hype Cycle for Emerging Technologies Identifies the Computing Innovations That Organizations Should Monitor.

Available online: http://www.gartner.com/newsroom/id/3114217 (accessed on 27 July 2018).

43. Lee, S.W.; Prenzel, O.; Bien, Z. Applying Human Learning Principles to User-Centered IoT Systems. Computer 2015, 46, 46-52 44. Hodges, S.; Taylor, S.; Villar, N.; Scott, J.; Bial, D.; Fischer, P.T. Prototyping Connected Devices for the Internet of Things. Computer 2013, 46,

26-34. [CrossRef]

45. Ferati, M.; Kurti, A.; Vogel, B.; Raufi, B. Augmenting Requirements Gathering for People with Special Needs Using IoT: A Position Paper. In

Proceedings of the 9th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE '16), Austin, TX, USA, 14-

16 May 2016; pp. 48-51.

46. Kim I, Back M, Yim H, Lee K. RFID adaptor for detecting and handling data events in Internet of Things. Indian Journal of Science and Technology. 2015; 8(5):140-8.

47. Bojanova I, Hurlburt G, Voas J. Imagineering an Internet of Anything. Computer (Long Beach Calif). 2014; 47(6):72-7.

48. Cooper, J.; James, A. Challenges for Database Management in the Internet of Things. IETE Tech. Rev. 2014, 26, 320-329. [CrossRef] 49. Dell EMC. The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things; EMC Digital Universe with

Research & Analysis by IDC April 2014; Dell EMC: Hopkinton, MA, USA, 2014. Available online: https://www.emc.com/leadership/digital-

universe/2014iview/executive-summary.htm (accessed on 27 July 2018). 50. Marvin, R. The 5 Worst Hacks and Breaches of 2016 and What They Mean for 2017. PC Magazine, January 2017. Available online:

https://www.pcmag.com/article/350793/the-5-worst-hacks-and-breachesof-2016-and-what-they-mean-fo (accessed on 27 July 2018).

51. Rahman, A.; Ali, M. Analysis and Evaluation of Wireless Networks by Implementation of Test Security Keys. In Proceedings of the International Conference on Emerging Technologies in Computing 2018 (iCETiC '18), London, UK, 23-24 August 2018

52. IEC. Internet of Things: Wireless Sensor Networks; White Paper 2014; International Electrotechnical Commission (IEC): Geneva, Switzerland,

2014. Available online: http://www.iec.ch/whitepaper/pdf/ iecWP-internetofthings-LR-en.pdf (accessed on 27 July 2018). 53. A. M. Ortiz et al., "The cluster between Internet of Things and social networks: Review and research challenges," IEEE Internet Things J., vol. 1,

no. 3, pp. 206-215, Jun. 2014.

54. Wollschlaeger, M.; Sauter, T.; Jasperneite, J. The Future of Industrial Communication: Automation Networks in the Era of the Internet of Things and Industry 4.0. IEEE Ind. Electr. Mag. 2017, 11, 17-27. [CrossRef]

55. Miraz, M.H.; Ali, M.; Excell, P.; Picking, R. A Review on Internet of Things (IoT), Internet of Everything (IoE) and Internet of Nano Things

(IoNT). In Proceedings of the Fifth International IEEE Conference on Internet Technologies and Applications (ITA 15), Wrexham, UK, 8-11 September 2015; pp. 219-224

56. Kortuem, G.; Bandara, A.; Smith, N.; Richards, M.; Petre, M. Educating the Internet-of-Things Generation. Computer 2013, 46, 53-61.

[CrossRef]

24.

Authors: R. Varalakshmi, R.S. Dhivya

Paper Title: A Survey on Big Data Applicability in Prediction Using Absence Information for Workforce Management

Abstract: Prediction is a method of finding new insights from large data sets, it’s a reliable way to use big data for

more accuracy. The overall goal of the process is to predict useful outcomes from dataset and transform into a

meaningful insight for decision. Absence data has thousands of leave type information; by analysing the data, new

insights can be predicted, since the data is growing exponentially, traditional method of prediction will not be effective.

In this paper we discuss about prediction techniques and a survey of works done in the field of absenteeism is

performed, This paper concentrates on machine learning algorithms and also presents the applicability of absence data

in big data for workforce planning.

Keywords: Big Data, Data Science, Predictive Analytics, Workforce planning, Random Forest.

References: 1. Goetzel, R.Z, Long, S.R., Ozminkowski, R.J., Hawkins, K.H., Wang, S. and Lynch, W. Journal of occupational and environmental medicine, on

Health, Absence, disability and presenteeism cost estimates of certain physical and mental health condition affecting US employee" 46pp.398-412.

2. Evans - Absenteeism- a complex problem A study on absenteeism in Trondheim's nursing homes Josiane, NTNU Master's thesis in Cultural,

Social and Community Psychology 3. Hafiz Bin Salih,Staff Absenteeism: The Case of Wa Municipal Education Office of the Ghana Education ServiceCoordinator, Ghana Education

Service, Wa, Ghana, Open Journal of Social Sciences, 2018, 6, 1-14

4. Valle, M.A., Vara, S., Ruz, G.A, (2012), Job performance prediction in a call centre using a Naïve Bayes classifier, Expert System with

Applications, 39(11), pp 9939-9945.

5. Jantan, H., Hamdan, A.R., & Othman, Z.A. (2010). Human talent prediction in HRM using C4.5 classification algorithm, International journal on

Computer Science and Engineering, (2008-2010), pp2526-2534. 6. Rishi Sai Reddy Sudireddy and Uttam Mande, GITAM University. Prediction of Road Accident using Correlation based on Map Reducing. 8th

International Conference on Computational Intelligence and Communication Networks 2016.

7. HamidahJantan, Norazmah Mat Yusoff and Mohamad Rozuan Noh, UniversitiTeknologi MARA (UiTM) Terengganu, Malaysia. Proceedings of the International Conference on Data Mining, Internet Computing and Big Data, Kuala Lumpur, Malaysia, 2014.Towards Applying Support

Vector Machine Algorithm in Employee Achievement Classification.

8. Aarya Vardhan Reddy Paakaala, Sai Saran Macha & Kumara SakethMudigonda in MSVR Engineering college India. Evaluation of clustering algorithms on absenteeism at work data set. International Journal of Scientific Research & Development Vol.6, 2321-0613.

9. Ricardo Pinto Ferreira., Andréa Martiniano., Domingos Napolitano., Edquel Bueno Prado Farias and Renato José Sassi.Artificial neural network

and their application in prediction of absenteeism at work., International journal of recent scientific research Jan'18, vol-9. 10. Gayathri, T. Data mining of Absentee data to increase productivity. International journal of engineering and techniques - vol-4, May' 18, Issue-3.

11. BetülKarakus&Galip Aydin, Computer Engineering Department Firat University Elazig, Turkey. Call Center Performance Evaluation Using Big

Data Analytics, 978-1-5090-0284-9/16/$31.00 ©2016 IEEE. 12. Aditya Sinha, Research School of Computer Science College of Engineering and Computer Science Australian National University ACT 0200

Australia., Predicting Absenteeism At Work using ANN, Effects of Pruning By Badness, and Deep NNs. 13. Yingchun Liu, Random forest algorithm in big data environment, Computer Modelling & New Technologies 2014 18(12a) 147-151.

14. Jiawei Hanl,2,YanhengLiul,Xin Sunl, A Scalable Random Forest Algorithm Based on MapReduce.

15. Breiman, L. Random forests. Machine Learning 45( 1), 5-32 (2001). 16. Weiwei Lin, Ziming Wu, Longxin Lin, Angzhan Wen, AndJin Li, For Fog and Mobile Edge Computing, An Ensemble Random Forest

Algorithm for Insurance Big Data Analysis, Special Section On Recent Advance In Computational Intelligence Paradigms for security and

privacy. 17. The Australian Faculty of Occupational Medicine: Workforce Attendance and Absenteeism.

97-100

25.

Authors: Shaik Akbar, P. Sri Silpa, Anand Thota, K. Nageswara Rao

Paper Title: An Intangible System to Augment the Prediction of Heart Diseases Using Machine Learning Techniques

Abstract: In Present day medical scenario, it is very difficult to find the Heart-attack, Blood Pressure of the patient.

So we are introducing an idea to monitor and analyze the disease of the patients they are suffering from and will alert

the particular or nearby hospitals about the patient if there is any danger. So that the patient’s medical condition can be

identified and can be cured.

Keywords: Prediction, data analytics, machine learning, data mining, heart diseases.

References: 1. Manikantan, V. and S. Latha. "Predicting the Analysis of Heart Disease Symptoms Using Medicinal Data Mining Methods." (2013).

2. Shadab Adam Pattekari and Alma Parveen," Prediction system for heart disease using naïve bayes", International Journal of Advanced Computer and Mathematical Sciences, vol.3,pp 290- 294,2012.

3. Soni, Jyoti & Ansari, Ujma & Sharma, Dipesh & Soni, Sunita. (2011). Predictive Data Mining for Medical Diagnosis: An Overview of

Heart Disease Prediction. International Journal of Computer Applications. 17. 43-48. 10.5120/2237-2860. 4. Agrawal, Rakesh & Imielinski, Tomasz & Swami, Arun. (1993). Mining Association Rules Between Sets of Items in Large Databases,

SIGMOD Conference. 10.1145/170036.170072.

5. Hnin Wint Khaing, "Data mining based fragmentation and prediction of medical data," 2011 3rd International Conference on Computer Research and Development, Shanghai, 2011, pp. 480-485. doi: 10.1109/ICCRD.2011.5764179

6. Masilamani, Anbarasi &, ANUPRIYA & Iyenger, N Ch Sriman Narayana. (2010). Enhanced Prediction of Heart Disease with Feature

Subset Selection using Genetic Algorithm. International Journal of Engineering Science and Technology. 2. 7. D. Burdick, M. Calimlim and J. Gehrke, "MAFIA: a maximal frequent itemset algorithm for transactional databases," Proceedings 17th

International Conference on Data Engineering, Heidelberg, Germany, 2001, pp. 443-452. doi: 10.1109/ICDE.2001.914857

8. Srinivas, Kavitha et al. "SURVEY ON PREDICTION OF HEART MORBIDITY USING DATA MINING TECHNIQUES." (2011). DOI:10.5121/ijdkp.2011.1302

9. S.Vijayarani, M. Divya, " An Efficient Algorithm for Generating Classification Rules", IJCST, vol. 2, Issue 4, 2011.

101-104

26.

Authors: S.B. Lenin, N. Tamilarasan, S. Malarkkan

Paper Title: Hybrid Adaptive Channel Estimation Technique in Time and Frequency Domain for MIMO-OFDM

Systems

Abstract: A multiple-input multiple (MIMO) communication model is integrated to orthogonal frequency division

multiplexing (OFDM) for reliable and data transmission at a higher rate in the broadband wireless channels. A

significant part in the wireless data transmission is use of adaptive channel estimation techniques in which the channel

105-110

is frequently varying. This paper introduces a hybrid adaptive channel estimation technique by integrating the beneficial

characteristics of the time domain as well as frequency domain. The column based time domain and the row based

frequency domain are combined together and they are used based on the channel quality and received bit error rate

(BER). Here, the channel estimation at pilot frequencies depends on minimum mean square error (MMSE). For the

evaluation of the proposed techniques, a set of experiments and detailed comparative analysis is made interms of

different measures under different condition. The experimental results depicted the proposed method outperforms the

other methods.

Keywords: Channel estimation, OFDM, CSI, MMSE.

References: 1. S. T. Chung and A. J. Goldsmith, "Degrees of freedom in adaptive modulation: a unified view," IEEE Trans. Commun., vol. 49, no. 9, pp.1561-

1571, 2001. 2. J. Goldsmith and S.-G. Chua, "Adaptive coded modulation for fading channels," IEEE Trans. Commun., vol. 46, no. 5, pp. 595-602, 1998.

3. T. Keller and L. Hanzo, "Adaptive multicarrier modulation: a convenient framework for time-frequency processing in wireless

communications,"Proc. IEEE, vol. 88, no. 5, pp. 611-640, 2000. 4. Svensson, "An introduction to adaptive QAM modulation schemes for known and predicted channels," Proc. IEEE, vol. 95, no. 12, pp. 2322-

2336, Dec. 2007.

5. M.-S. Alouini, X. Tang, and A. J. Goldsmith, "An adaptive modulation scheme for simultaneous voice and data transmission over fading channels," IEEE J. Sel. Areas Commun., vol. 17, no. 5, pp. 837-850,1999.

6. G. G. Raleigh and J. M. Cioffi, "Spatio-temporal coding for wireless communication," IEEE Trans. Commun., vol. 46, no. 3, pp. 357-366, 1998.

7. A. Goldsmith, Wireless Communications. Cambridge University Press, 2005. 8. S. T. Chung and A. Goldsmith, "Adaptive multicarrier modulation for wireless systems," in Proc. 2000 Asilomar Conf. Signals, Syst. Comput.,

vol. 2, pp. 1603-1607. 9. A. Olfat and M. Shikh-Bahaei, "Optimum power and rate adaptation for MQAM in Rayleigh flat fading with imperfect channel estimation,"

IEEE Trans. Veh. Technol., vol. 57, no. 4, pp. 2622-2627, 2008.

10. "Optimum power and rate adaptation with imperfect channel estimation for MQAM in Rayleigh flat fading channel," in Proc. 2005Veh. Technol. Conf. - Fall, vol. 4, pp. 2468-2471.

11. X. Cai and G. B. Giannakis, "Adaptive PSAM accounting for channel estimation and prediction errors," IEEE Trans. Wireless Commun., vol. 4,

no. 1, pp. 246-256, 2005. 12. S. Ye, R. S. Blum, and L. J. Cimini, "Adaptive OFDM systems with imperfect channel state information," IEEE Trans. Wireless Commun., vol.

5, no. 11, pp. 3255-3265, 2006.

13. S. Falahati, A. Svensson, T. Ekman, and M. Sternad, "Adaptive modulation systems for predicted wireless channels," IEEE Trans. Commun., vol. 52, no. 2, pp. 307-316, 2004.

14. M. Karami, A. Olfat, and N. C. Beaulieu, "Pilot symbol assisted adaptive modulation for OFDM systems with imperfect channel state

information," in Proc. 2010 IEEE Global Telecommun. Conf., pp. 1-6. 15. J. K. Cavers, "An analysis of pilot symbol assisted modulation for Rayleigh fading channels," IEEE Trans. Veh. Technol., vol. 40, no. 4, pp. 686-

693, 1991.

16. Y. Chen and N. C. Beaulieu, "Optimum pilot symbol assisted modulation," IEEE Trans. Commun., vol. 55, no. 8, pp. 1536-1546, 2007. 17. S. Sampei and T. Sunaga, "Rayleigh fading compensation for QAM inland mobile radio communications," IEEE Trans. Veh. Technol., vol.

42,no. 2, pp. 137-147, 1993.

18. J.H. Kotecha and A.M. Sayeed, "Transmit signal design for optimal estimation of correlated MIMO channels," IEEE Transactions on Signal

Processing, Vol. 52, pp. 546-557, Feb. 2004.

19. C. Chuah, D.N.C. Tse, J.M. Kahn, and R.A. Valenzuela, "Capacity scaling in MIMO wireless systems under correlated fading," IEEE Trans. on

Information Theory, Vol. 48., pp. 637-650, 2002.

27.

Authors: Manohar K. Kodmelwar, S.D. Joshi, V. Khanna

Paper Title: Using COCOMO Dataset Effort Estimation for Developing Software

Abstract: The development of software according to the required demand of customer. So it is important to find the

effort required to develop the software. The estimation is done using the particle swarm optimization technique by

applying the weights in the neural network. The usage of NN helps in estimating the efforts of the software with less

cost and failure rates. The NN is utilized together with optimization to attain an enhanced outcome. The dataset utilized

as input to the proposed system is the COCOMO dataset. The actual effort in the COCOMO dataset is measured by

person-month which represents the number of months that one person needs to develop a given project. The proposed

method gives the accurate estimation compared to the existing models

Keywords: COCOMO, NN, Hybrid swarm particle optimization, credit assignment path.

References: 1. Karnavel, K., and R. Dillibabu, "Development and application of new quality model for software projects", The Scientific World Journal, Vol.

2014, 2014.

2. Saleem Basha, and Dhavachelvan Ponnurangam, "Analysis of empirical software effort estimation models", 2010.

3. Ashish Sharma, and Dharmender Singh Kushwaha, "Estimation of software development effort from requirements based complexity", Procedia Technology, 2012, Vol. 4, PP. 716-722.

4. Magne Jørgensen, "Contrasting ideal and realistic conditions as a means to improve judgment-based software development effort estimation",

Information and Software Technology, 2011, Vol. 53, No. 12, PP. 1382-1390. 5. Philip Morrow, F. George Wilkie, and I. R. McChesney, "Function point analysis using NESMA: simplifying the sizing without simplifying the

size", Software Quality Journal, 2014, Vol. 22, No. 4, PP. 611-660.

6. Tony Rosqvist, Mika Koskela, and Hannu Harju, "Software quality evaluation based on expert judgement", Software Quality Journal, 2003, Vol. 11, No. 1, PP. 39-55.

7. Mandeep Kaur, and Sumeet Kaur Sehra, "Particle swarm optimization based effort estimation using Function Point analysis", In Issues and

Challenges in Intelligent Computing Techniques (ICICT), 2014 International Conference on, IEEE, 2014, PP. 140-145. 8. Frank Vijay, J., "Enrichment of accurate software effort estimation using fuzzy-based function point analysis in business data analytics", Neural

Computing and Applications, 2018, PP. 1-7.

9. Valentina Lenarduzzi, Ilaria Lunesu, Martina Matta, and Davide Taibi, "Functional size measures and effort estimation in agile development: a replicated study", In International Conference on Agile Software Development. Springer, Cham, 2015, PP. 105-116

10. Dengsheng Wu, Jianping Li, and Chunbing Bao, "Case-based reasoning with optimized weight derived by particle swarm optimization for

software effort estimation", Soft Computing, 2018, Vol. 22, No. 16, PP. 5299-5310.

111-113

28. Authors: S. Thendral, R. Subhashni, V. Madhan Karky

Paper Title: Seithiyalan – An iPhone Application for Cricket Summary Generation in Tamil

Abstract: Cricket plays vital role in Asian sports. Thus, there is a need for an application which summarize cricket in

Natural Language. The objective of Seithyalan application is to auto analyze the score card of the cricket match and

generate summary in Tamil. The data analyzed based on the parameter Interestingness to select relevant pattern. Based

on that pattern only the summary will generate.

Keywords: Cricket Summary, NLG, Machine Learning, Tamil Computing.

References: 1. Tholgappiar, "Tholgappiam," KazhagaVeliyeedu, Madras, 1973.

2. Alice Oh and Howard Shrobe, "Generating baseball summaries from multiple perspectives by reordering content,"in Proc. 5th International

Natural Language Generation Conference, 2008, pp. 173-176. 3. Bavananthymunivar, "Nannool," Pary Nilayam, Madras.

114-115

29.

Authors: B. Lakshma Reddy, A. Karthik, S. Prayla Shyry

Paper Title: A Blockchain Framework for Insurance Processes in Hospitals

Abstract: The Blockchain enabled system is to analyse, the best process of the treatment for a particular disease and

also the system determines if any fraudulent activity has been controlled by the doctor. The system also recommends

the most appropriate treatment process to perform for a particular disease in view of the movement of the previous

patient. Here the system is creating Block chain enabled framework for diseases and in this the system will create

disease as a unique key point and suggesting a better treatment to the hospitals. The basic objective of the project is to

suggest a best treatment to the hospitals.

Keywords: Blockchain, Hospital, Insurance, Treatment.

References: 1. Vukoli´c et.al (2017), "Rethinking permissioned blockchains," in Proceeding of the ACM Workshop on Blockchain, Cryptocurrencies and

agreements, ser. BCC '17. NewYork, NY, USA: ACM .

2. C. D. Clack et.al (2016) "Smart agreements templates: essential provisions and design options," arXiv preprint arXiv:1612.04496. 3. K. Christidis et.al (2016) "Blockchains and smart agreements for the IOT," IEEE Access, vol. 4, pp. 2292-2303.

4. I. Nath (2016) "Data exchange platform to conflict insurance fraud on blockchain," in 2016 IEEE 16th International Conference on Data Mining

Workshops (ICDMW), pp. 821-825. 5. W. Li et.al (2017) "Towards adaptable and personal industrial blockchain," in Proceedings of the ACM Workshop on Blockchains,

Cryptocurrencies and Contracts. ACM, pp. 9-14.

6. H. Watanabe et.al (2016) "Blockchain agreements: Securing a blockchain applied to smart agreements," in Consumer Electronics (ICCE), IEEE International Conferences on. IEEE, pp. 467-468.

7. F. Lamberti et.al (2017) "Blockchain or not blockchain, that is the question of the insurance and other sectors," IT Professional, vol. PP, no. 99,

pp. 1-1.

8. C. Christian (2017) "Blockchain, cryptography, and consensus".

9. Cachin and Christian (2016) "Architecture of the hyperledger blockchain fabric".

10. E. Androulaiki et.al (2017) "Cryptography and protocol in hyperledger fabric". 11. Dr. S. PraylaShyry", Efficient identification of bots by K-means clusterings", Proceeding of the international conferences on Soft Computing

System, Advances in Intelligent systems and Computing", pp 307-318, Springer India 2016.

12. Dr. S. PraylaShyry, Maria Sheeba," Literature review on the detection of bots in p2p network", International Journal of Applied Engineering Research, Volume 9, Number 24,pp. 23485-23489 2014.

116-119

30.

Authors: M.V.R. Vivek, D.V.V.S.S. Sri Harsha, P. Sardar Maran

Paper Title: A Survey on Crop Recommendation Using Machine Learning

Abstract: Agriculture arranging assumes an imperative job in any nation. Agriculture segment gives different yields,

for example, sustenance, crude material for industry, affordable lift and business. The Agriculture part contains huge

information regarding factors influencing its info and yield. With advances in innovation different information mining

systems are presented. These information mining methods can be utilized to dissect the multidimensional, time explicit

information of horticulture area to create powerful learning from it which can be utilized to support the economy.

Today, the term information mining [1][2] is an interdisciplinary procedure of breaking down, handling and assessing

this present reality datasets and forecast based on the discoveries. Our case-based investigation gives observational

proof that we can utilize diverse information mining arrangement calculations to group the dataset of horticultural

districts based on soil properties. Moreover, we have explored the most performing calculation having amazing

expectation exactness to suggest the best harvest for better yield. The proposed framework will coordinate the

information got from archive, climate office and by applying machine learning calculation: Multiple Linear Regression,

an expectation of most reasonable yields as indicated by current natural conditions is made. This furnishes an

agriculturist with assortment of alternatives of harvests that can be developed. This exploration goes for examination of

soil dataset utilizing information mining procedures. It centers around characterization of soil utilizing different

calculations accessible. Another essential design is to foresee untested traits utilizing relapse procedure, and usage of

computerized soil test grouping.

Keywords: Data mining, classification, regression, soil testing, agriculture, Machine Learning.

References: 1. 2016 IEEE Eighth International Conference on Advanced Computing (ICoAC), "Crop Recommendation System for Precision Agriculture",

S.Pudumalar*, E.Ramanujam*, R.HarineRajashree?, C.Kavya?, T.Kiruthika?, J.Nisha?.

2. 2017 International Conference on Electrical, Electronics, Communication, Computer and Optimization Techniques (ICEECCOT), "A Study on

Various Data Mining Techniques for Crop Yield Prediction", Yogesh Gandge, Sandhya. 3. 2017 IEEE Region 10 Humanitarian Technology Conference, "RSF: A Recommendation System for Farmers", Miftahul Jannat Mokarrama;

Mohammad Shamsul Arefin.

4. 2017 International Conference on I2C2, "Agriculture decision support system using data mining", Prof. Rakesh Shirsath; Neha Khadke; Divya

120-125

More. 5. 2018 the 3rd IEEE International Conference on Cloud Computing and Big Data Analysis, "Big Data Analysis Technology Application in

Agricultural Intelligence Decision System", Ji-chun Zhao; Jian-xin Guo. Proceedings of the Second International Conference on Inventive

Systems and Control (ICISC 2018), "Use of Data Mining in Crop Yield Prediction", Shruti Mishra, Priyanka Paygude, Snehal Chaudhary, SonaliIdate.

6. IEEE Sponsored 9th International Conference on Intelligent Systems and Control (ISCO) 2015, "XCYPF: A Flexible and Extensible Framework

for Agricultural Crop Yield Prediction", Aakunuri Manjula, Dr.G .Narsimha

7. 2015 International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials

(ICSTM), Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Chennai, T.N., India. 6 - 8 May 2015. pp.138-145,

"Crop Selection Method to Maximize Crop Yield Rate using Machine Learning Technique", Rakesh Kumar, M.P. Singh, Prabhat Kumar and J.P. Singh

8. Wang, Yuhong, Jiangrong Tang, and Wenbin Cao. "Grey prediction model-based food security early warning prediction." Grey Systems: Theory

and Application 2, no. 1 (2012): 13-23. 9. Liu Z., Meng L., Zhao W. and Yu F. Application of ANN in food safety early warning, The 2nd International Conference on Future Computer

and Communication, Wuhan, Vol. 3, 2010, pp. 677-80.

10. AnshalSavla, Parul Dhawan, HimtanayaBhadada, Nivedita Israni, Alisha Mandholia, Sanya Bhardwaj, "Survey of classification algorithms for formulating yield prediction accuracy in precision agriculture", Innovations in Information, Embedded and Communication systems (ICIIECS),

2015

11. Aakunuri Manjula, Dr.G .Narsimha, "XCYPF: A Flexible and Extensible Framework for Agricultural Crop Yield Prediction", Conference on Intelligent Systems and Control (ISCO), 2015

12. Yash Sanghvi, Harsh Gupta, Harmish Doshi, DivyaKoli, AmoghAnshDivyaKoli, Umang Gupta, "Comparison of Self Organizing Maps and

Sammon's Mapping on agricultural datasets for precision agriculture", International Conference on Innovations in Information, Embedded and Communication systems, 2015

13. Rakesh Kumar, M.P. Singh, Prabhat Kumar and J.P. Singh, "Crop Selection Method to Maximize Crop Yield Rate using Machine Learning

Technique", International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM).,2015

14. A.T.M Shakil Ahamed, NavidTanzeem Mahmood, Nazmul Hossain, Mohammad Tanzir Kabir, Kallal Das, Faridur Rahman, Rashedur M

Rahman, "Applying Data Mining Techniques to Predict Annual Yield of Major Crops and Recommend Planting Different Crops in Different Districts in Bangladesh", (SNPD) IEEE/ACIS International Conference., 2015

15. Yang, Liying. "Classifiers selection for ensemble learning based on accuracy and diversity." Procedia Engineering 15 (2011): 4266-4270.

16. Aymen E Khedr, Mona Kadry, Ghada Walid, "Proposed Framework for Implementing Data Mining Techniques to Enhance Decisions in Agriculture Sector Applied Case on Food Security Information Center Ministry of Agriculture, Egypt", International Conference on

Communications, management, and Information technology (ICCMIT'), 2015.

17. Monali Paul, Santosh K. Vishwakarma, Ashok Verma, "Analysis of Soil Behaviour and Prediction of Crop Yield using Data Mining Approach", International Conference on Computational Intelligence and Communication Networks, 2015.

18. Pudumalar, S., E. Ramanujam, R. HarineRajashree, C. Kavya, T. Kiruthika, and J. Nisha. "Crop recommendation system for precision

agriculture." In Advanced Computing (ICoAC), 2016 Eighth International Conference on, pp. 32-36. IEEE, 2017. 19. Daryl H. Hepting, Timothy Maciag, Harvey Hill, "Web-Based Support of Crop Selection for Climate Adaptation", 45th Hawaii International

Conference on System Sciences, 2012.

20. S. Dhamodaran, Allwyn raja, "Prediction of Weather Condition Using Probability Function", International Journal of Applied Engineering Research, ISSN 0973-4562 Volume 10, Number 4 (2015) pp.10665-10670.

31.

Authors: Su.Suganthi, P. Pavithra, C. Sri Lakshmi Priya, T. Thayamma

Paper Title: Microcontroller based Monitoring and Reprocessing System for Waste Water Management

Abstract: Monitoring systems are not able to monitor the water quality in all aspects of sectors like water emitted by

industries, drinking water, sea water etc., The aim of our project is to monitor the necessary quality parameters of the

water and reprocess it into Plasma Activated Water[PAW]. For knowing the purity content of water in day to day lives,

the system implemented, continuously checks and provides the data to the microcontroller. In order to ensure the safety

supply of the drinking water the quality needs to be monitored in real time. The system consists of serval sensors is used

to measure the physical and chemical properties of the water. The parameters such as temperature, pH, turbidity, flow

of the water can be measured. Furthermore, it is essentially converted to Plasma Activated Water[PAW] that acts as an

preservative for microbial infections. Non thermal plasma has been widely considered as an effective method for

bacterial inactivation in food safety. The bactericidal efficiency of Plasma Activated Water[PAW] was found to be

strongly dependent on PAW treatment intervals. Significant reduction in microbial populations were achieved in all

cases demonstrating the effectiveness of this new approach to treat contaminated media. Therefore Plasma Activated

Water [PAW] is a promising solution with potential application to the decontamination of equipment and surfaces.

Keywords: Temperature sensor, pH sensor, Turbidity sensor, Flow sensor, WI-FI module, Plasma Activated Water

[PAW], Microbial disinfection.

References: 1. Vaishnavi V. Daigavane and Dr.M.A.Gaikwad, "Water quality monitoring system based on IOT", ISSN 0973-6972 Volume 10, Number 5

(2017), pp. 1107-1116© Research India Publications, 2017. 2. Tha.Sugapriyaa, S.Rakshaya, "Smart water quality monitoring system for real time application", International journal of pure and applied

mathematics, Volume 118 No. 20 2018, 1363-1369 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version), 2018.

3. Jayti Bhatt,Jignesh Patoliya, "IOT based water quality monitoring system", International Journal of Industrial Electronics and Electrical Engineering, ISSN: 2347-6982, Volume-4, Issue-4, Apr.-2016.

4. J.M.Herry, G.Kangang-youbi, T.Meylheuc, "Microbial interaction using PAW obtained by gliding electric discharges", Letters in applied

microbiology, 2008.

126-129

32.

Authors: Vamsi, Manikanta, T. Anandhi

Paper Title: Survey on Enhancing Drainage Maintenance System Using IOT

Abstract: World has declared task making of many savvy urban communities. To develop a shrewd society one have

to look at numerous measurable factors, for example, brilliant water, savvy power, keen transportation and so on. There

is a scope of savvy system which incorporates lower-level water pipe connections, correspondence links, gas

connections, electric stream, and so forth. As the greater part of the urban areas in India have embraced lower level

drainage system, it was imperative that this mechanism should perform in a legitimate way to make the society spotless,

protected and sound. On the off chance that they neglect to keep up the scrap unadulterated water may transform to

polluted with drainage water. It also spread irresistible infections. So unique sort of idea has been done to identify, keep

130-135

up and deal with these lower-level systems. Additionally, breaks and blasts are unpreventable parts of water conveyance

system the executives. It can represent noteworthy water misfortune inside a dispersion arrange whenever left un

notified for significant lot. The drainage system is the activity of depleting waste water and sticky fluid segments

towards the waterways utilizing specific examples, drainage channels and streams. Drainage system essentially alludes

to all the funneling inside the private and open premises which passes on sewage, water and other fluid waste to a point

of transfer. The associated gadgets will make the waste system increasingly agreeable to work, screen, control with less

assets and to take important activities. Over stream of sewage on streets is been a noteworthy issue in many created and

immature urban communities also. Sewage is commonly considered as waste water. The reaction to the protests isn't

appropriately replied or considered. A prudent system is created where this issue of sewage flood can be diminished by

early detecting of increment in its dimension. The system rather essentially studies and checking the dimension, issue

articulation and solution about the drainagesystem.

Keywords: Drainage Maintenance System, IOT, Enhancing Smart City.

References: 1. Prof S. A. Shaikh1, Suvarna A. Sonawane2, "Monitoring Smart City Application Using Raspberry PI based on IoT" International Journal of

Innovative Science, Engineering & Technology, Vol 5 Issue VIL, July 2017.

2. Prof Muragesh SK1, Santhosha Rao2, "Automated Internet of Things For Underground Drainage and Manhole Monitoring Systems For Metropolitan Cities." International Journal of Innovative Science, Engineering & Technology, Vol. 2 Issue 4, June 2015.

3. Chandraleka.T, Shruti Rathore, Ram Vignesh C, "Neer: automated water drainage and anti flooding System" International Journal Of Electrical,

Electronics And Data Communication, ISSN: 2320-2084 Volume-5, Issue-5, May-2017 http://iraj.in Neer: Automated Water Drainage and Anti Flooding System.

4. Gaurangsonawane, Chetan Mahajan, ,AnujaNikale, Yogita Dalvi, "Smart Real-Time Drainage Monitoring System Using Internet of Things" © MAY 2018 | IRE Journals | Volume 1 Issue 11 | Issn: 2456-8880 Ire 1700668 Iconic Research And Engineering Journals.

5. Shruthi Shri A. S, "Smart Drainage Monitoring and Clog Identification Using IOT", Department of Electronics and Communication Engineering

Kongu Engineering College Perundurai, Tamil Nadu, India, © 2017 IJSRSET | Volume 3 | Issue 8 | Print ISSN: 2395-1990 | Online ISSN : 2394-4099 Themed Section : Engineering and Technology.

6. GAURANG SONAWANE 1, CHETAN MAHAJAN 2, ANUJA NIKALE 3, YOGITA DALVI 4, "Smart Real-Time Drainage Monitoring

System Using Internet of Things" © MAY 2018 | IRE Journals | Volume 1 Issue 11 | ISSN: 2456-8880 IRE 1700668 ICONIC RESEARCH AND ENGINEERING JOURNALS.

7. Shankara Narayanan.S1, Ramprakash. G2, Rajapandiyan. V3, Saravana Perumal. R4, Rathnapriya. K5, "Integrative Detection of Open Drainage,

Garbage & Drainage over Flow and Current Leakage using Zigbee Technology" Student1, 2, 3, 4, M. Tech, Assistant Professor O.G5 Valliammai Engineering College, India.

8. Brown, Eric (13 September 2016)."Who need the Internet of things".Linux.com. Retrieved 23 October 2016.

9. Wemer-Allen, G., Johnson, J., Ruize, M., Less, J., and Welsh, Matt "Monitoring Volcanic Eruptions with a Wireless sensor Network. (ISSN: 2321 - 5658) Volume 01- Issue 04, December 2013 Asian Online Journals

10. Basha, D. and Rus, D. "Design of Early Warning Flood Detection System for developing countries. Proceeding of the conference on ICTD,

Bonsalove, India. Pp 1-10, 2007. 11. Yuwat, C. and Kilaso, S. " A Wireless Sensor Network for Weather and Disaster Alarm System" , IPCSIT Vol. 6, Singapore. Pp 1 - 5, 2011

12. Morias, R., Valente, A., Serodo, C. "A Wireless Sensor Network for Smart Irrigation and Environmental Monitoring.© MAY 2018 | IRE Journals

| Volume 1 Issue 11 | ISSN: 2456-8880 IRE 1700668 ICONIC RESEARCH AND ENGINEERING JOURNALS 6EFTA/WCCA Joint Congress

on IT in Agriculture, Portugal, pp 845 - 850. 2005

13. Windarto, J." Flood Early Warning System develop at Garang River Semarang using Information Technology base on SMS and Web".

International Journal of Geomatics and Geosciences Vol. 1 No. 1, 2010 14. Wirawam, S., Pratoma, I., and Mita, Nagahisa. "Design of Low Cost Wireless Sensor Network-Based Environmental Monitoring System for

Developing Country". Proceedings of APCC 2008.

15. Retno Tri Wahyuni1* Yusmar Palapa Wijaya2 Dini Nurmalasari "Design of Wireless Sensor Network for Drainage Monitoring System" Vol.5, No.5, 2014

16. Pathak A.K, Ko lhe A.N, GagareJ.T ,Khemnar S.M " GSM BASED DISTRIBUTION TRANSFORMER MONITORINGAND CONTROLLING

SYST EM" 17. Y. Glouche and P. Couderc,"A smart waste management with self-describing objects", The Second InternationalConference on Smart Systems,

Devices and Technologies (SMART'13), June 2013

18. V. Kumar and R.K.Pandit,"Problems of solid waste management in Indian cities", International Journal of Scientific and Research Publicat ions, Volume 3, Issue 3, March 2013

19. A. Ramirez-Jaime, N. Quijano, Senior Member, IEEE, and C.Ocampo-Ma rtine z, Senior Member, IEEE. "A Differential Game Approach to

Urban Drainage Systems Control " 20. A.Medvedev, P.Fedchenkov, A.Zaslavsky, T.Anagnostopoulos and S. Khoruzhnikov," Waste management as an IoTenabled service in smart

cities", 8th International Conference on Internet of Things and Smart Spaces, ruSMART 2015

33.

Authors: P. Adlene Ebenezer, Asha Shajee, Dhruv Patel, Himangshu Shekhar Saikia, Rahul Mishra

Paper Title: Analysis of Wireless Intrusion Detection and Prevention System against Cyber Attacks

Abstract: This is a proposed topology for a wireless networked control system. It is implemented under several cyber

attack scenarios and a distributed intrusion detection system (IDS) is designed to identify the existence of attacks. More

specifically, it presents a modelling framework for the closed-loop control system with the IDS. It ensures a

computational procedure to design and compute the IDS. After successful detection, IPS will be implemented.IPS

analyzes packets for harmful protocols and stops these packets from reaching their destination based on the results of

IDS.

Keywords: IDS, IPS, Cyber Security, Cyber Attack, Intrusion Detection and Prevention, Analysis System.

References: 1. Ahmad W. Al-Dabbagh, Yuzhe Li and Togwen Chen, "An Intrusion Detection System for Cyber Attacks in Wireless Networked Control

System," IEEE, 2016. 2. Kun Zhi Liu, Rui Wang and Guo Ping Liu, "Tradeoffs between transmission intervals and delays for decentralized networked control systems

based on a gain assignment approach", IEEE, 2015.

3. G.P Liu, "Predictive Controller Design of Networked Systems With Communication Delays and Data Loss", IEEE, 2010. 4. Konstantinos Gatis and Alejandro Riberio, "Optimal Power Management in Wireless Control Systems", IEEE, 2013.

5. Andre Teixiera, Iman Shames, Henrik Sandbag and Karl Hendrik Johnnason, "A secure control framework for resources limited adversaries,"

IEEE, 2015. 6. Hamza Fauzi, Paulo Tabuada and Suhas Diggavi, "Secure Estimation and Control for Cyber-Physical Systems Under Adversarial Attacks,"

136-140

IEEE, 2013 7. M. Pajic, S. Sundaram, G. J. Pappas, and R. Mangharam, "The wireless control network: a new approach for control over networks," IEEE

Transactions on Automatic Control, vol. 56, no. 10, pp. 2305-2318, 2011.

8. R. Mangharam and M. Pajic, "Distributed control for cyber-physical systems," Journal of the Indian Institute of Science, vol. 93, no. 3, pp. 353-388, 2013.

9. I. Hwang, S. Kim, Y. Kim, and C. E. Seah, "A survey of fault detection, isolation, and recon?guration methods," IEEE Transactions on Control

Systems Technology, vol. 18, no. 3, pp. 636-653, 2010.

10. M. R. Davoodi, K. Khorasani, H. A. Talebi, and H. R. Momeni, "Distributed fault detection and isolation ?lter design for a network of

heterogeneous multiagent systems," IEEE Transactions on Control Systems Technology, vol. 22, no. 3, pp. 1061-1069, 2014.

R. E. Skelton, T. Iwasaki, and K. M. Grigoriadis, A Uni?ed Algebraic Approach to Linear Control Design. Taylor & Francis, 1998. 11. J. Han and R. E. Skelton, "An LMI optimization approach for structured linear controllers," in 42nd IEEE Conference on Decision and Control,

vol. 5, Maui, Hawaii, USA, 2003, pp. 5143-5148.

34.

Authors: B.J. Bipin Nair, T.R. Pruthvi

Paper Title: A Segmentation Approaches to Detect Autism and Dementia from Brain MRI

Abstract: Magnetic Resonance Imaging (MRI) and functional MRI (fMRI) studies involving allows to working

human brain to be imaged at high resolution within only in a particular time. In our studies fMRI helps in find out the

small changes in the brain image and using segmentation algorithm, using segmentation we locate the region in brain

MRI and apply any three-efficient segmentation technique checks, and finally predicting which algorithm is an efficient

way of doing segmentation the. Basically, so many researches are happened in the disorder like brain tumor, but the

present literature says that very less work happened in the disorder like mental and neurodevelopmental disorders. In

our proposed work, we are segmenting autism and dementia disorder using MRI image analysis.

Keywords: Fuzzy C-Means (FCM), K-Means, GT.

References: 1. Karani, N., Chaitanya, K., Baumgartner, C., &Konukoglu, E. (2018). A Lifelong Learning Approach to Brain MR Segmentation Across Scanners

and Protocols. arXiv preprint arXiv:1805.10170. 2. Iglesias, J. E., Augustinack, J. C., Nguyen, K., Player, C. M., Player, A., Wright, M., ...&Fischl, B. (2015). A ` segmentation of in vivo MRI.

Neuroimage, 115, 117-137.

3. Bhalerao, G. V., &Sampathila, N. (2014, November). K-means clustering approach for segmentation of corpus callosum from brain magnetic resonance images. In Circuits, Communication, Control, and Computing (I4C), 2014 International Conference on (pp. 434-437). IEEE.

4. El-Baz, A., Elnakib, A., Casanova, M. F., Gimel'farb, G., Switala, A. E., Jordan, D., & Rainey, S. (2011). Accurate automated detection of

autism-related corpus callosum abnormalities. Journal of medical systems, 35(5), 929-939. 5. Selvathi, D., &Anitha, J. (2009, March). Effective fuzzy clustering algorithm for abnormal MR brain image segmentation.In Advance Computing

Conference, 2009.IACC 2009. IEEE International (pp. 609-614). IEEE.

6. Forghani, N., Forouzanfar, M., &Forouzanfar, E. (2007, November). MRI fuzzy segmentation of brain tissue using IFCM algorithm with particle swarm optimization.

7. In Computer and information sciences, 2007.iscis 2007. 22nd international symposium on (pp. 1-4).IEEE.

8. Yushkevich, P. A., Piven, J., Hazlett, H. C., Smith, R. G., Ho, S., Gee, J. C., &Gerig, G. (2006). User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage, 31(3), 1116-1128.

9. Shen, S., Sandham, W., Granat, M., &Sterr, A. (2005). MRI fuzzy segmentation of brain tissue using neighborhood attraction with neural-

network optimization. IEEE transactions on information technology in biomedicine, 9(3), 459-467. 10. Ahmed, M. N., Yamany, S. M., Mohamed, N., Farag, A. A., & Moriarty, T. (2002). A modified fuzzy c-means algorithm for bias field estimation

and segmentation of MRI data. IEEE transactions on medical imaging, 21(3), 193-199.

11. Zhang, Y., Brady, M., & Smith, S. (2001). Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE transactions on medical imaging, 20(1), 45-57.

12. Bipinnairb.j., Arunjit k., &VijeshBhaskaran(2017). Melatonin and fluoxetine interaction with shank3 protein gene for autism spectrum disorder.

Pakistan journal of Biotechnology. 13. Rani, N. S., Verma, S. K., & Joseph, A. (2016). A Zone Based Approach for Classification and Recognition Of Telugu Handwritten Characters.

International Journal of Electrical and Computer Engineering (IJECE), 6(4), 1647-1653.

141-144

35.

Authors: G. Thamarai Selvi, M. Shanmuganathan, A. Sivabharath, S. Syed Irfan

Paper Title: Modern Methodology for the Detection and Removal of Herbicides

Abstract: It is known that the technical advancements are increasing at a faster pace. But the utilization of

technologies in various sectors are very low. We commonly know that nowadays, the fruits are highly infected with

herbicides. But we consume those fruits in our day-to-day lives. But because of their harmful effects, few people get

highly affected, babies in particular. So we propose a system to effective remove the herbicides present on the

fruit/Vegetable. Also we provide pest removal based on the amount of herbicide present on the fruit.

Keywords: Herbicide, Removal, Detection, Pic-Microcontroller, Neural Electrode.

References: 1. A. A. SHEHATA, W. SCHRODL, P. SEHLEDORN, AND M. KRUGER, "DISTRIBUTION OF GLYPHOSATE IN CHICKEN ORGANS

AND ITS REDUCTION BY HUMIC ACID SUPPLEMENTATION," JOURNAL OF POULTRY SCIENCE, VOL. 51, PP. 333-337, JUL 2014.

2. O. REBAI, M. BELKHIR, A. BOUJELBEN, S. FATTOUCH, AND M. AMRI, "MORUS ALBA LEAF EXTRACT MEDIATES NEUROPROTECTION AGAINST GLYPHOSATE-INDUCED TOXICITY AND BIOCHEMICAL ALTERATIONS IN THE BRAIN,"

ENVIRON SCI POLLUT RES INT, FEB 28 2017.

3. M. HVISTENDAHL, "IN RURAL ASIA, LOCKING UP POISONS TO PREVENT SUICIDES," SCIENCE, VOL. 341, PP. 738-9, AUG 16 2013.

4. K. C. WU, Y. Y. CHEN, AND P. S. YIP, "SUICIDE METHODS IN ASIA: IMPLICATIONS IN SUICIDE PREVENTION," INT J ENVIRON

RES PUBLIC HEALTH, VOL. 9, PP. 1135-58, APR 2012. 5. J. W. LEE, I. W. HWANG, J. W. KIM, H. J. MOON, K. H. KIM, S. PARK, ET AL., "COMMON PESTICIDES USED IN SUICIDE

ATTEMPTS FOLLOWING THE 2012 PARAQUAT BAN IN KOREA," JOURNAL OF KOREAN MEDICAL SCIENCE, VOL. 30, PP. 1517-

1521, OCT 2015. 6. J. P. MYERS, M. N. ANTONIOU, B. BLUMBERG, L. CARROLL, T. COLBORN, L. G. EVERETT, ET AL., "CONCERNS OVER USE OF

GLYPHOSATE-BASED HERBICIDES AND RISKS ASSOCIATED WITHEXPOSURES: A CONSENSUS STATEMENT," ENVIRONMENTAL HEALTH, VOL. 15, FEB 17 2016.

7. C. M. BENBROOK, "TRENDS IN GLYPHOSATE HERBICIDE USE IN THE UNITED STATES AND GLOBALLY," ENVIRON SCI EUR,

VOL. 28, P. 3, 2016.

145-147

8. C. GASNIER, C. DUMONT, N. BENACHOUR, E. CLAIR, M. C. CHAGNON, AND G. E. SERALINI, "GLYPHOSATE-BASED HERBICIDES ARE TOXIC AND ENDOCRINE DISRUPTORS IN HUMAN CELL LINES," TOXICOLOGY, VOL. 262, PP. 184-91, AUG 21

2009.

9. R. HOKANSON, R. FUDGE, R. CHOWDHARY, AND D. BUSBEE, "ALTERATION OF ESTROGEN-REGULATED GENE EXPRESSION IN HUMAN CELLS INDUCED BY THE AGRICULTURAL AND HORTICULTURAL HERBICIDE GLYPHOSATE," HUM EXP

TOXICOL, VOL. 26, PP. 747-52, SEP 2007.

10. C. JAYASUMANA, P. PARANAGAMA, S. AGAMPODI, C. WIJEWARDANE, S. GUNATILAKE, AND S. SIRIBADDANA, "DRINKING

WELL WATER AND OCCUPATIONAL EXPOSURE TO HERBICIDES IS ASSOCIATED WITH CHRONIC KIDNEY DISEASE, IN

PADAVI-SRIPURA, SRI LANKA," ENVIRON HEALTH, VOL. 14, P. 6, JAN 18 2015.

36.

Authors: B. Deva Naga Sylesh, B. Varun Kumar, M. Saravanan

Paper Title: Member Counting in Smart Buildings

Abstract: In this contemporary age almost every person carries a mobile device. The quantity of cell phones present

(number of people) is resolved utilizing techniques that catch arrange parcels sent by cell phones utilizing the 802.11

convention. The parcels are caught utilizing a Wi-Fi scanner, an equipment gadget that enables data to be assembled

from 802.11/a/b/g/n/air conditioning systems. The quantity of individuals in a working with a satisfactory check of Wi-

Fi scanners might be resolved with a positive likelihood which, beside its factual significance, may likewise be key in

crisis circumstances in which it is basic to decide what number of individuals are inside a specific building. We are

implementing Zigbee based network for different locations like colleges/ Shops / Floors. Exit doors are connected to the

micro controller board for any immediate exit process initiated in case of any emergency. Android application is

deployed to the customers after entering into the Mall. We would count the people based on the Zigbee count in every

floor.

Keywords: Zigbee, Mobile WIFI, Android Application.

References: 23. S.Depatla, A. Muralidharan, and Y. Mostofi, “Occupancy Estimation Using Only Wi-Fi Power Measurements,” IEEE Journal on Selected Areas

in Communications, vol. 33, July 2015.

24. A. B. M. Musa and J. Eriksson, “Tracking unmodified smartphones using Wi-Fi monitors,” in Proc. ACM Conf. Embedded Network Sensor

Systems, ser. SenSys ’12. New York, NY, USA: ACM, 2012, pp. 281– 294. 25. Simone Di Domenico, Giovanni Pecoraro, Ernestina Cianea, Mauro De Sanctis, "Trained-once device-free crowd counting and occupancy

estimation using Wi-Fi: A Doppler spectrum based approach", 2016 IEEE 12th International Conference on Wireless and Mobile Computing,

Networking and Communications (WiMob), vol. 00, pp. 1-8, 2016. 26. Saravanan, M., Jyothi, V.L.Implementation of getting similarity images using the concept of IWSL Indian Journal of Science and

Technology,2016

27. S.Dhamodaran, K. R. Sachin and Rahul Kumar, “Big Data Implementation of Natural Disaster Monitoring and Alerting System in Real Time Social Network using Hadoop Technology”, Indian Journal of Science and Technology, Vol 8(22), IPL0278, September 2015

148-150

37.

Authors: B.V. Surya Vardhan, Mohan Khedkar, Nitin Kumar Kulkarni

Paper Title: Impact on Fuse Settings and Size of Photovoltaic Distributed Generation Source Due to Fault Current

Abstract: Fault current contribution due to Grid connected Photovoltaic (PV) source has become a crucial factor in

deciding the settings of protection equipments like fuse, circuit breaker etc. especially where there is a high level of

penetration of PV, estimated in Megawatts. Setting of protection equipment, size of PV source to be interfaced with the

grid depends on the magnitude of fault current from PV source, A inverter based distributed generation (PV) is

considered here, it has limited fault current contribution but as grid penetration level increases fault current contribution

becomes significant. This paper aims at determining the change in relay settings due to addition of PV sources and also

determining the size (MVA rating) of PV source w.r.t. to its fault current contribution to avoid the existing setting

changes of protection equipments. For this analysis ,a Real time system of Katol PV transmission Solar Power plant

near Nagpur is taken. Using Single line to ground fault given at Grid side, the system is analysed &simulated in

MATLAB Simulink environment. The simulation results show that, relay settings and Size (MVA rating) change

considerably due to addition of PV, into grid.

Keywords: Photo- Voltaic (PV), Inverter, fault current contribution, protection settings, Distributed Generation (DG).

References: 1. “Ministry of New and Renewable Energy(MNRE)”,Government Of India Website : www.mnre.gov.in.

2. J. A. P. Lopes, N. Hatziargyriou, J. Mutale, P. Djapic, and N. Jenkins, "Integrating distributed generation into electric power systems: A review

of drivers, challenges and opportunities," Electric Power Systems Research, vol. 77, pp. 1189-1203, 2007. 3. Analysis of Photovoltaic Systems, International Energy AgencyPhotovoltaic Power Systems Program, Paris, France, 2000.

4. D. Tom Rizy, Fangxing Li, Huijuan Li, Sarina Adhikari, John D. Kueck, "Properly Understanding the Impacts of Distributed Resources on

Distribution Systems," IEEE PES General Meeting 2010, Minneapolis, MN, July 25-29,2010. 5. B. Kroposki, C. Pink, R. DeBlasio, H. Thomas, M. Simoes, and P. K. Sen, "Benefits of power electronic interfaces for distributed energy

systems," in Power Engineering Society General Meeting, 2006. IEEE, 2006, p. 8 pp.

6. S.Bhattacharys, T.Saha, M.J Hossain, “Fault current contribution from photovoltaic systems in residential power networks”, Proceedings of the Australasian Universities Power Engineering Conference, Hobart, 2013, Australia, pp.1-6.

7. IEEE 1547 and 2030 standards for Distributed Energy Resources and Interconnection and Interoperability with the Electricity Grid, IEEE

Standards 8. A. Girgis and S. Brahma, "Effect of distributed generation on protective coordination in distribution system" in Large Engineering Systems

Conference on Power Engineering , July 2001, pp. 1 5-119

9. P. H. Shah, B. R. Bhalja, “New Adaptive Digital Relaying Scheme to Tackle Recloser–Fuse Miscoordination During Distributed Generation Interconnections,” IET Generation, Transmission and. Distribution, Vol. 8, Iss. 4, 2014 pp. 682–688.

10. IEEE Standard Inverse-Time Characteristic Equations for Overcurrent Relays, IEEE Std C37.112-1996.

151-154

38.

Authors: K. Malathy, S. Meenakshi

Paper Title: Fuzzy Soft Bi-partite Graph and Its Application in Employee Selection for An Organisation

Abstract: Fuzzy sets and soft sets are two different tools for representing uncertainty and vagueness. A fuzzy soft set

is a mapping from parameter set to the fuzzy subsets of universe. Fuzzy soft set theory provides a parameterized point 155-159

of view for uncertainty modeling and soft computing model. In this paper we discuss the notions of fuzzy soft bi-partite

graph, Size and degree of fuzzy softbi-partite graph and investigating the application of Fuzzy soft Bi-partite graph in

Employee selection for an Organisation.

Keywords: Fuzzy soft graph, fuzzy soft bi-partite graph, and size and degree of fuzzy soft bi-partite graph.

References: 1. M.Akram, S. Nawaz, Fuzzy soft graphs with applications , Journal of Intelligent and Fuzzy Systems 30 (6) (2016) 3619 – 3632. 2. M.Akram, S. Nawaz , Operations onsoft graphs, Fuzzy Information and Engineering 7(4) (2015) 423 – 449.

3. Dr. K. Kalaiarasi and L. Mahalakshmi, An Introduction to Fuzzy strong graphs, Fuzzy soft graphs, compliment of fuzzy strong and soft

graphs,13,November 6(2017), 2235-2254. 4. J.N.Mordeson an C.S.Peneg, Operations on fuzzy graphs, Information sciences, 79, September 1994, 159 – 170.

5. S.Mohinta , T.K.Samanta, An Introduction to fuzzy soft graph , Mathematics Moravica19 – 2 ( 2015) 35 – 48.

6. T.K.MathewVarkey, A.M. Shyla . A Note on Bipartite and Balanced Fuzzy Graph Structures 6 ,7 (2017) : 12637 – 12640. 7. D.A.Molodtsov , Soft set theory -first results , Computers and Mathematics with Applications 37, 1999.

8. A.Rosenfeld, Fuzzy graph , in ; L.A.Zadeh, K.S.Fu, K.Tanaka, M.ShimuraedS , Fuzzy Sets and Their Applications to cognitive and decision

Process, Acaemic Press, New York, 1975, pp. 75 – 95. 9. N. Sarala, K. Manju, Application of Fuzzy soft Bi-partite graph in Matrimonial process, Volume 14, Issue 4 Ver. III (Jul - Aug 2018), PP 20-24.

39.

Authors: Himanshu Thakur, Ankit Rastogi, Ritik Raj Singh, Shubham Khanduri

Paper Title: Braking/Deceleration Mechanism in Hyperloop System Using Sensor Values and Feedback

Abstract: Hyperloop system is no longer a far-fetched idea and has got a lot of teams start to work on this seemingly

futuristic concept. Hyperloop system involves a high-speed pod travelling at a proposed speed of 700 mph. The

involvement of superlative speed at which the pod would be travelling brings down the entire focus on how to

decelerate and gradually stop the pod (i.e.) the braking system.

Keywords: Hyperloop, BLDC Motors, Arduino ATmega328P, Deceleration mechanism, RGB Sensor.

References: 1. Vivek Borse, Abhaysinha Satish Patil, and Rohit Srivastava, “Development and testing of portable flouroscence reader (PorFloRTM)” 2017 9th

international conference on communication systems and Networks(COMSNETS), January 2017.

2. Young Tae Shin ; Ying-Khai Teh, “Design analysis and considerations of power efficient electronic speed controller for small-scale quadcopter

unmanned aerial vehicle,” 2018 IEEE 8th Annual Computing and communications workshop and Conference(CCWC), 8-10 Jan 2018. 3. Neil Cameron,” Bluetooth Communication. In: Arduino Applied. Apress, Berkeley, CA”27 Dec 2018

4. Mark Seelye , Gourab Sen Gupta , Donald Bailey , John Seelye,” Low cost colour sensors for monitoring plant growth in a laboratory ” , 2011

IEEE International Instrumentation and Measurement Technology Conference ; 07 July 2011 5. Humayun Rashid , A.S.M Rabbi Al-Mamun , Mohammad Sijanur Rahaman Robin , Miraz Ahasan , S M Taslim Reza, ”Bilingual wearable

assistive technology for visually impaired persons ” , 2016 International Conference on Medical Engineering , Health Informatics and

Technology (MediTec) , 30 Jan 2017 6. Haifeng Lu , Lei Zhang , Wenlong Qu , ”Anew Torque Control Method for Torque Ripple Minimization of BLDC Motors with Un-Ideal Back

EMF”, IEEE Transactions on Power Electronics Volume: 23 , Issue: 2 , March 2008

7. Sukhen Das , Sanjoy Ganguly , Souvik Ghosh , Rishiraj Sarker , Debaparna Sengupta , ”A bluetooth based sophisticated home automation system using smarthone ” , 2016 International Conference on Intelligent Control Power and Instrumentation (ICICPI) , 23 Oct 2016

8. Aryuanto Soetedjo, M. Ibrahim Ashari, Claudio Ardiles, ” Development of Industrial control Training Module using Distance and Color Sensors

for Detecting Objects ” , Vol 1 No 1 (2017): International Journal of Engineering and Management , Aug 29 , 2017.

160-163

40.

Authors: S.P. Maniraj, R. Pranay Sharma, M. Venkata Siva Kumar, B.V. Sai Mohan Krishna, G. Sree Ram Pavan

Paper Title: Vulnerabilities and Security Issues in Cps and IOT for Wire Less Communication

Abstract: The concept of IoT stems from connected smart devices, which may or may not be connected physically

via wires. The Cyber-Physical Systems, on the other hand are complex distributed systems, consisting of a large number

of sensors and actuators, which are connected to a pool of computing nodes. With the fusion of sensors, computing

nodes, and actuators, which are connected through various means of communications, CPSs aim to perceive and

understand changes in the physical environment, analyse the impacts of such changes to their operation, and make

intelligent decisions to respond to the changes. Thus, in both CPS and IoT wireless communication plays a very

important role. With in increasing number of devices, the security against the manipulation of the sensor data is needed

as a change in the input can change the behaviour of the system altogether. In this paper, we take a deeper look into the

security issues and vulnerabilities of the wireless communication in both the Cyber Physical Systems (CPS) and the

Internet of Things (IoT).

Keywords: Distributed systems; nodes; manipulation; vulnerabilities.

References: 1. J. Shi, J. Wan, H. Yan, and H. Suo, “A survey of cyber-physical systems,” in Proc. Int. Conf. Wireless Commun. Signal Process., Nov. 2011, pp.

1–6, doi: 10.1109/WCSP.2011.6096958. 2. A. Humayed, J. Lin, F. Li, and B. Luo, “Cyber physical systems security—A survey,” CoRR,2017.

3. A. Chattopadhyay, A. Prakash, and M. Shafique, “Secure cyber-physical systems: Current trends, tools and open research problems,” in Proc.

DATE, 2017, pp. 1104–1109. 4. R. Want, “Near field communication,” IEEE Pervasive Comput., vol. 10, no. 3, pp. 4–7,Mar. 2011.

5. A. Chattopadhyay, A. Ukil, D. Jap, and S. Bhasin, “Towards threat of implementation attacks on substation security: Case study on fault

detection and isolation,” IEEE Trans. Ind. Informat.,2017, doi: 10.1109/TII.2017.2770096. 6. A. Wheeler, “Commercial applications of wireless sensor networks using ZigBee,” IEEE Commun. Mag., vol. 45, no. 4, pp. 70–77, Apr. 2007,

doi: 10.1109/MCOM.2007.343615.

7. Y. Mo and B. Sinopoli, “Integrity attacks on cyber-physical systems,” in Proc. of the 1st ACM International Conf. on High Confidence

Networked Systems, Beijing, China, Apr. 2012, pp. 47–54.

8. Y. Zou, J. Zhu, X. Wang, and L. Hanzo,“A survey on wireless security: technical challenges, recent advances, and future trends,” Proc. IEEE,

vol. 104, no. 9, pp. 1727–1765, Sep. 2016, doi: 10.1109/ JPROC.2016.2558521. 9. I. Butun, S. D. Morgera, and R. Sankar, “A survey of intrusion detection systems in wireless sensor networks,” IEEE Commun. Surveys Tuts.,

vol. 16, no. 1, pp. 266–282, 1st Quart., 2014, doi: 10.1109/ SURV.2013.050113.00191.

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10. J. Sametinger, J. Rozenblit, R. Lysecky, and P. Ott, “Security challenges for medical devices,” Commun. ACM, vol. 58, pp. 74–82, Mar. 2015, doi: 10.1145/2667218.

11. B. Zhu, A. Joseph, and S. Sastry, “A taxonomy of cyber attacks on SCADA systems,” in Proc. Int. Conf. Internet Things 4th Int. Conf. Cyber

Phys. Soc. Comput., Oct. 2011, pp. 380–388, doi: 10.1109/ iThings/CPSCom.2011.34. 12. C. Gomez and J. Paradells, “Wireless home automation networks: A survey of architectures and technologies,” IEEE Commun. Mag., vol. 48, no.

6, pp. 92–101, Jun. 2010, doi: 10.1109/ MCOM.2010.5473869.

13. S. S. R. Ahamed, “The role of ZigBee technology in future data communication system,” J. Theor. Appl. Inf. Technol., vol. 5, no. 2, p. 29, 2009.

14. M. Zhou and Z.-L. Nie, “Analysis and design of ZigBee MAC layers protocol,” in Proc. Int. Conf. Future Inf. Technol. Manage. Eng., vol. 2.

Oct. 2010, pp. 211– 15, doi: 10.1109/ FITME.2010.5654824.

15. Y. Mo and B. Sinopoli, “False data injection attacks in control systems,” In Proc. of the 1st Workshop on Secure Control Systems, Stockholm, Sweden, Apr. 2010, pp. 56–62.

41.

Authors: Deeba Kannan, Kuntal Bajpayee, Samriddho Roy

Paper Title: Solving Timetable Scheduling Problems Using Genetic Algorithm

Abstract: There are various methods to solve the timetable scheduling problem and preventing various slots from

clashing like the ant colony optimization problem which by result is a very time consuming process and other approach

includes heuristic approach where problem can be solved by using trial and error method or by using a multi

dimensional matrix which again may or may not give the optimal solution .The most important factor which should be

taken in consideration is that it’s a NP hard problem which means there is not any best solution to this problem so ,by

considering all the above factors it is found that Genetic Algorithm (GA) is the best approach to such problem where

the main algorithm goal is to minimize the number of conflicts in the timetable and reduction to encoding of search

space.

Keywords: Scheduling, Genetic Algorithm, NP hard.

References: 1. C. Liang and Y. Lin, "A coverage optimization strategy for mobile wireless sensor networks based on genetic algorithm," 2018 IEEE

International Conference on Applied System Invention (ICASI), Chiba, 2018, pp. 1272-1275.

2. M. Omari and S. Yaichi, "Image compression based on genetic algorithm optimization," 2015 2nd World Symposium on Web Applications and Networking (WSWAN), Sousse, 2015, pp. 1-5.

3. M. Collard and D. Francisci, "Evolutionary data mining: an overview of genetic-based algorithms," ETFA 2001. 8th International Conference on

Emerging Technologies and Factory Automation. Proceedings (Cat.No.01TH8597), Antibes-Juan les Pins, France, 2001, pp. 3-9 vol.1. 4. Ahmed H. Yousef, Cherif Salama, Mohammad Y. Jad, Tarek El-Gafy, Mona Matar, Suzanne S. Habashi, "A GPU based genetic algorithm

solution for the timetabling problem", Computer Engineering & Systems (ICCES) 2016 11th International Conference on, pp. 103-109, 2016.

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42.

Authors: J. Caroline El Fiorenza, Dinesh Udayakumar, Chandrasekar Rajah, M. Karthikeyan

Paper Title: Hardware based Anti-theft System for Smartphones

Abstract: In the world of technology, smartphones and laptops play a major role and is actively used by millions of

people around the world for the purpose of communication, entertainment and also as a tool for learning and updating

our knowledge. Users store important information on their smartphones ranging from personal details, photos, videos

and other confidential credentials such as banking information and even passwords. This possess a threat when the

smartphone is stolen where this information can be misused for certain criminal activities and all our important

information is at stake. The existing anti-theft systems are all software based where once stolen, these apps can be

uninstalled by anyone and hence cannot be accessed by owner and all the confidential information is gone with it too.

Therefore, the scope of this project is to propose a hardware based anti-theft system wherein a actual chip is embedded

in to the smartphone which can be accessed anytime by the user to track the smartphone even after the phone is reset

and also provide support for remotely erasing the data stored, hence data integrity is achieved and the data is not stolen.

The chip can communicate with the GPS sensor in the mobile and will provide GPS location of the smartphone in real-

time. The chip also has an dedicated storage where users can store important information and confidential data that can

be secured and can access it anytime.

Keywords: Anti-theft system, Cybersecurity, GPS, Information Security.

References: 1. Xixian LIU. A Method to Realize Guard Against Theft for Laptop[J]. Technology and Applications, 2011,(09):89-90.

2. BBC news: 314 mobile phones 'stolen in London every day', http://www.bbc.com/news/uk-england-london-21018569.

3. Norton Cybercrime Report 2011, http://us.norton.com/content/en/us/home_homeoffice/html/cybercrimereport/.

4. Symantec, “2014 Symantec canada smartphone honey stick project”,report, 2014. 5. “Tencent Mobile Phone Manager,” http://m.qq.com/anti_theft/login.jsp.

6. “Rising Phone Security Assistant,” http://mobile.rising.com.cn/android/.

7. X. Yu, Z, Wang, L. Sun, W. Zhu, N. Gao, and J. Jing, “Remotely wipingsensitive data on stolen smartphones,” in proceedings of the 9th ACMsymposium on Information, computer and communications security,2014, pp. 537-543.

8. L. Subramanian, G Q. M. Jr., and P. Stephanow, “An architecture toprovide cloud based security services for smartphones,” in proceedingsof

27th Meeting of the Wireless World Research Forum, 2011. 9. A. U. S. Khan, M. N. Qureshi, and M. A. Qadeer, “Anti-theft applicationfor android based devices,” in proceedings of IEEE

InternationalAdvance Computing Conference, 2014.

10. Simon, R. Anderson, “Security analysis of consumer-grade anti-theftsolutions provided by android mobile anti-virus apps,” in proceedings ofthe 4th Mobile Security Technologies Workshop, 2015.

11. “Software reduces identity theft risk in stolen cell phones,” http://mobiledevdesign.com/news/software-reduces-identity-theft-riskstolen-cell-

phones. 12. “Lookout Mobile Security,” https://www.lookout.com.

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43.

Authors: S.V. Abishek, G.M. Dhuruva Priyan, Sridatt More, A. Suganthan

Paper Title: IoT based Smart Band for Biometric Authentication Using Blockchain Technology

Abstract: Internet of Things has been ‘the next big thing’ for a while now and it is estimated that the number of

connected devices will exceed 50 billion by 2020. This extravagant growth in number of connected devices has alarmed

us to shift the approach in designing identity and access management systems. People tend to provide different

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passwords and identifications for each of the platforms they use. This could be troublesome as they might forget their

password and lose their identifications as well. One more problem is that the user doesn’t know if he is providing only

the necessary information or he is exposing himself to something he is not supposed to. This makes us think about a

solution where the user provides minimum amount of his personal information for verification. We propose an IoT

based solution using smart band with fingerprint biometric system to achieve the idea of ”one touch multiple login” (i.e.

single band to authenticate multiple platforms). We have addressed the Self-sovereign identity crisis using blockchain

technology and its derived protocols.

Index Terms: Biometric, Blockchain, Internet of Things(IOT), Self Sovereign Identity, Smart Band.

References: 1. P. Grassi, M. Garcia, and J. Fenton. SP 800-63-3 Digital Identity Guidelines. Technical report, National Institute of Standards & Technology,

Gaithersburg, MD, United States, 2017. 2. 2410-2017 IEEE biometric open protocol standard (BOPS).https://standards.ieee.org/findstds/standard/2410-2017.html.

3. A. Ross and A. Othman. Visual cryptography for biometric privacy. IEEE transactions on information forensics and security, 6(1):70–81,2011.

4. M. Mealling and R. Denenberg. Report from the joint w3c/ietf uri planning interest group: Uniform resource identifiers (uris), urls, and uniform resource names (urns): Clarifications and recommendations. Technical report, 2002.

5. D. Reed and M. Sporny. W3c decentralized identifiers (dids) 1.0. https://w3c-ccg.github.io/did-spec/, 2017.

6. https://en.bitcoin.it/wiki/Proof_of_work 7. https://www.hindawi.com/journals/scn/2018/9675050/

8. https://www.bayometric.com/increasing-importance-ofbiometric-security/

9. https://medium.com/blockchain-education-network/what 10. -is-blockchain-explained-for-beginners-5e747cea271

11. https://www.experian.com/blogs/ask-experian/how-can 12. -biometrics-protect-your-identity/

13. https://www.androidauthority.com/how-fingerprint-sca nners-work-670934/

14. www.rfidjournal.com/faq/show?68 15. A. Ashok, Poornachandran, P., and Dr. Krishnashree Achuthan, “Secure authentication in multimodal biometric systems using cryptographic

hash functions”, Communications in Computer and Information Science, vol. 335 CCIS, pp. 168177, 2012.

16. N. Lalithamani and R, S., “Countermeasures for indirect attack for iris based biometric authentication”, Indian Journal of Science and Technology, 2016.

44.

Authors: M. Ramesh, S. Sathiyaseelan, I. Ajit

Paper Title: The Portrayal of Great Mathematicians in Movies: A Review

Abstract: Mathematics, the queen of science, is inevitable in every field of study. And it forms the basis for almost all

the subjects related to the realms of science and technology. To attain mastery in mathematics is a real feat and the

world needs to celebrate those masters. This paper reviews four films celebrating four great mathematicians the world

has ever seen. Also, the reason behind their genius and their contributions are described in this paper in detail.

Keywords: Biography, Film, Mathematics, Review, Queen of Science.

References: 1. Bai, C. and Gosman, A., (1996) Mathematical Modelling of Wall Films Formed by Impinging Sprays," SAE Technical Paper 960626,

https://doi.org/10.4271/960626. 2. Bharathi S T and Ajit I (2018) "Hyper Reality as a Theme and Technique in the Film Truman Show" Global Media Journal 30(16).

3. DeMare N (2016) "Exaggerations and stereotypes of schizophrenia in contemporary films" Elon Journal of Undergraduate Research in

Communications 7(1). 4. Latterell, C M. and Wilson, J L. (2004) "Popular Cultural Portrayals of Those Who Do Mathematics," Humanistic Mathematics Network Journal

27(7).

5. Nithin K (2016) "Screen Shifts in Recent Tamil Cinemas: The "New" New Wave" Research Scholar An International Refereed e-Journal of Literary Explorations 4(2).

6. Qadri M & Mufti S (2016) "Flims and religion: An analysis of Aamir Khan's PK" Journal of Religion & Film 20(1).

7. Ranganathan. M &Velayutham. S (2012) "Imagining Eelam Tamils in Tamil cinema" Journal of Media & Cultural Studies 26(6). 8. Wilson, J. L., &Latterell, C. M. (2001). Nerds? Or Nuts? Pop culture portrayals of mathematicians. ETC: A Review of General Semantics, 58(2),

172-178.

9. Latterell, C M. and Wilson, J L. (2004) "Popular Cultural Portrayals of Those Who Do Mathematics," Humanistic Mathematics Network Journal. 27(7).

10. https://www.youtube.com/watch?v=bgfZ7db0e6I, Retrieved on 20th June 2018.

11. https://www.youtube.com/watch?v=PfBZWwQ_5Y4, Retrieved on 05th May 2018. 12. https://www.youtube.com/watch?v=Q96N7EJ-jnU, Retrieved on 17th May 2018.

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45.

Authors: Mary Thomas

Paper Title: Lyrics from Popular Songs and Rhyme to Enhance the ESL Learner's Proficiency in English Language

Abstract: The recent winning of the Nobel Prize for literature by Bob Dylan, a songwriter and lyricist inspired the

writing of this article. It has always been a dormant idea in my mind to use lyrics to get children interested in learning

the English Language. The acknowledgement of lyrics as a form of literature reinforced my conviction of the power of

the written and spoken Word and its effect on its listeners. Being an experienced teacher of English language I have

always adopted an eclectic approach to the teaching of Language; deciding on the most suitable technique and applying

the most appropriate methodology to achieve learner's specific objectives, learning style and context. English language

learning is a process that fits the method to the learner not the learner to the method. We should as teachers of language

opt for new trends that are more eclectic and humanistic in nature, which deals with emotions in the mind of the learner.

We can use technology and the audio linguicism to capture the attention of the learner. The teaching of English and the

imbibing of a language should be inherently and predominantly communicative. The most innate fact underlying the

mastery of a language is to make learning it an enjoyable experience.

Language cannot be taught but should be imbibed. We the teachers of English should be the facilitators helping children

imbibe the English Language. The doorway to a new enriching experience, the window to the world through which the

learner can explore and express his or her innate dreams and desires. The importance of the spoken word is something

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that I have always reiterated in all my classes of training and language learning. We must focus on the need to teach it

in a more creative manner through lyrics of popular rhymes and songs that not only touch the mind but also every

aspect of the life of prospective learners. It is an enjoyable and fun-filled method of imbibing the nuances of a

Language. Without a doubt, it transforms the uninterested student to an eager participant in the activity of learning and

imbibing and enriching himself and herself. I am a believer in the Power of the Word and its capacity to transform

something mundane to lofty heights. That has been my mission statement from the beginning of my English teaching

career that has spanned around twenty-five years of my life.

Keywords: Lyrics, Songs, Rhymes, Written and Spoken Words, Language Acquisition, Eclectic Approach, Audio

Linguicism, Humanistic Approaches, Communicative Language Teaching.

References: 1. Asher, J. James. (1993). Learning Another Language Through Actions. The Complete Teacher's Guidebook: Sky Oaks Productions 2. Dahl, Roald, Rhyme Stew

3. James, Clive. Norton. (2015) Poetry Notebook: Reflections on the Intensity of Language

4. Jolly, Y.S. (1975). The Use of Songs in Teaching Foreign Languages. The Modern Language Journal, 59(1/2), 11-14. http://dx.doi.org/10.2307/325440

5. Lawson, Jenny. (2015) Furiously Happy: Funny Book about Horrible Things

6. Murphey, T. (1992). Music and Song. Oxford, England: Oxford University Press 7. One Minute Till Bedtime: 60-Second Poems to Send you off to Sleep.

46.

Authors: A. Ajai, G. Bhuvaneswari

Paper Title: Multiple Colours of Gandhi in Post-Colonial Cinema

Abstract: Cinema is considered as the powerful medium for conveying ideas and documenting the history and

cultures of the world. Every filmmaker has their style of expressing their ideas through their portrayal. Sometimes, the

ideas may be conflicting and even controversial. Any individual once into public life is prone to criticism. Mahatma

Gandhi, father of our nation who put forth Ahimsa, non-violence, Love for all is criticized for his stand on the partition

of the nation, double side on Casteism, etc. This paper discusses the colors, herecolor refers to the stand or the faces of

Gandhi as portrayed in different movies.

Keywords: Mahatma Gandhi, Post-Colonial Cinema, Filmmaking, Mass Media.

References: 1. Birla, GhanshyamDass. In the Shadow of the Mahatma. 1953. 2. Dalton, Dennis. Mahatma Gandhi: Nonviolent power in action. Columbia University Press, 2012.

3. Gandhi, Mahatma. Autobiography: The story of my experiments with truth. Courier Corporation, 1948. 4. Gandhi, Mahatma. The Moral and Political Writings of Mahatma Gandhi: Civilization, Politics, and Religion. Vol. 1. Clarendon Press, 1986.

5. Gandhi. Non-Violent Resistance (Satyagraha).Dover Publications, 2001. Nagler, Michael N. The Nonviolence Handbook a Guide for Practical

Action.Berrett-Koehler, 2014. 6. Huttenback, Robert A. Racism, andEmpire: White settlers and colored immigrants in the British self-governing colonies, 1830-1910. Cornell

UnivPr, 1976.

7. Iyer, RaghavanNarasimhan. "The moral and political thought of Mahatma Gandhi." (2000). 8. Kehr, Dave. “FILM REVIEW; Gandhi Is Eclipsed by Another Revolutionary Hero of India's Freedom Fight.” The New York Times, The New

York Times, 10 June 2002, www.nytimes.com/2002/06/10/movies/film-review-gandhi-eclipsed-another-revolutionary-hero-india-s-freedom-

fight.html. 9. “Mahatma Gandhi Continues to Influence Indian Cinema: Author - Indian Express.” IndianExpress.com, 12 Nov. 1202,

archive.indianexpress.com/news/mahatma-gandhi-continues-to-influence-indian-cinema-author/1025175/.

10. Mahesh, Chitra. “‘The Legend of Bhagat Singh''.” Thehindu.com, 14 June 2002. 11. Tripathi, Akul. “Gandhi on and in Cinema.” Mkgandhi.org, Oct. 2015.

12. Stam, Robert. Film Theory: an introduction. Blackwell Publishers 2000

13. Said, E. (1978). Orientalism: Western representations of the Orient. New York: Pantheon. 14. https://www.youtube.com/watch?v=TNAdYLbGLKY

MOVIES CHOSEN:

15. Attenborough, Richard, director. Gandhi. Columbia Pictures, 1982.

16. Hassan, Kamal, director. Hey Ram. Kamal Hassan, 2000. 17. Patel, Jabbar, director. Dr. BabasahebAmbedkar. Tirlok Malik, 2000.

18. Santoshi, Rajkumar, director. The Legend of Bhagat Singh. Tips Industries Limited, 2002.

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47.

Authors: M.J. Bharathi, V.N. Rajavarman

Paper Title: A Survey on Big Data Management in Health Care Using IOT

Abstract: The Industrial science can decrease by and large expenses for the deterrent or administration of ongoing

diseases. That makes utilization of different sensor gadgets and innovations which consequently administrate

treatments, counsel wellbeing pointers that track continuous wellbeing information while a patient self-regulates a

treatment. This paper displays the Big information wellbeing application framework dependent on the Internet of

Things. The advantage of this action incorporates the accessibility, capacity to customize, and practical conveyance. All

things considered, many assignment should be tended to in trim to create precise, appropriate, sheltered, adaptable and

control productive frameworks fit for medicinal requirements. This paper produce the review of all primary approach in

Big Data analytics for healthcare- accouterment sensors, advanced pretentious healthcare systems in IOT Technologies

that are intended to providing telemedicine interferences to individuals for healthier condition.

Keywords: IOT, Big data, Healthcare, Security.

References: 1. https://www.ngdata.com/what-is-big-data-analytics

2. I.Olaronke, O.Oluwaseun, “Big data in healthcare: Prospects, challenges and resolutions” In Future Technologies Conference (FTC), IEEE, pp.

1152-1157, December,2016.

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3. R.Thomas-MacLean, D.Tarlier, S.Ackroyd-Stolarz, M.Fortin, M.Stewart, “No cookie-cutter response: conceptualizing primary health care”,2014. 4. https://iot.ieee.org/images/files/pdf/networks-of-things_jeff-voas_5-31-2016.pdf

5. https://iotdunia.com/what-is-an-iot-platform

6. https://hitconsultant.net/2017/11/03/internet-things-digital-future-value-based-care/ 7. C.Doukas, I.Maglogiannis, “Bringing IoT and cloud computing towards pervasive healthcare”, In Innovative Mobile and Internet Services in

Ubiquitous Computing (IMIS), 2012 Sixth International Conference on . IEEE,pp. 922-926, July, 2012.

8. S.R.Islam, D.Kwak, M.H.Kabir, M.Hossain, K.S.Kwak, “The internet of things for health care: a comprehensive survey”, IEEE Access, 3,

pp.678-708,2015..

9. K.Kavitha,, G.Suseendran, “A Review on Security Issues of IOT Based on Various Technologies”, Journal of Advanced Research in Dynamical

and Control Systems, Vol.10 (4), June, 2018. 10. H.K.Patil, R.Seshadri,"Big data security and privacy issues in healthcare." Big Data (BigData Congress), 2014 IEEE International Congress on.

IEEE,June,2014.

11. http://triotree.com/blog/medical-internet-of-things-challenges-benefits-applications/

48.

Authors: Krishna Prakash Kalyanathaya, D. Akila and P. Rajesh

Paper Title: Advances in Natural Language Processing – A Survey of Current Research Trends, Development Tools and

Industry Applications

Abstract: Natural Language Processing (NLP) is a subfield of Artificial Intelligence and getting lot of focus on

research and development due to emergence of its applications. The research areas in focus are conversation systems,

Language processing, Machine Translation, Deep learning. The researches in these areas lead to development of many

tools to build industrial applications. Combining Deep Learning techniques with Natural Language Processing is

finding lot of applications in domains such as Healthcare, Finance, Manufacturing, Education, Retail and customer

service. This paper provides bird’s view of advancement in research, development and application areas of Natural

Language Processing. This paper captures21research focus areas, 22 development tools and 6 domains where Natural

Language Processing are making rapid advancements.

Keywords: used in this text: NLP, Natural Language Processing, Deep Learning, Sentiment Analysis, Question

Answering, Dialogue Systems, Parsing, Named-Entity Recognition, POS Tagging, Chatbots, Human-Computer-

Interface.

References: 1. Daniel W. Otter, Julian R. Medina, and Jugal K. Kalita. 2018. A Survey of the Usages of Deep Learning inNatural Language Processing. 1, 1

(July 2018), 35 pages. 2. ROBERT DALE. "The commercial NLP Landscape in 2017", Article in Natural LanguageEngineering, July2017

3. ACL 2018: 56th Annual Meeting of Association for Computational Linguistics https://acl2018.org

4. Predictive Analytics Today: www.predictiveanalyticstoday.com[accessed in Dec 2018] 5. Ali Shatnawi, Ghadeer Al-Bdour, Raffi Al-Qurran and Mahmoud Al-Ayyoub 2018. A Comparative Study of Open Source Deep Learning

Frameworks. 2018 9th International Conference on Information and Communication Systems (ICICS)

6. Intelligent automation: Making cognitive real Knowledge Series I Chapter 2. 2018, EY report. 7. Jacques Bughin, Eric Hazan, SreeRamaswamy, Michael Chui , TeraAllas, Peter Dahlström, Nicolaus Henke, Monica Trench, 2017. MGI

ARTIFICIAL INTELLIGENCE THE NEXT DIGITAL FRONTIER? McKinsey & Company McKinsey & Company report July 2017

8. Svetlana Sicular, Kenneth Brant 2018, Hype Cycle for ArtificialIntelligence, 2018 Gartner report July 2018. 9. McCallum, Andrew Kachites. "MALLET: A Machine Learning for Language Toolkit." http://mallet.cs.umass.edu. 2002.

10. Quarteroni, Silvia. (2018). Natural Language Processing for Industry: ELCA’s experience. Informatik-Spektrum. 41. 10.1007/s00287-018-1094-

1. 11. Young, Tom &Hazarika, Devamanyu&Poria, Soujanya& Cambria, Erik. (2018). Recent Trends in Deep Learning Based Natural Language

Processing [Review Article]. IEEE Computational Intelligence Magazine. 13. 55-75. 10.1109/MCI.2018.2840738.

12. Amirhosseini, Mohammad Hossein, Kazemian, Hassan, Ouazzane, Karim and Chandler, Chris (2018) Natural language processing approach to NLP meta model automation. In: International Joint Conference on Neural Networks (IJCNN), 8-13 July 2018, Rio de Janeiro, Brazil.

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49.

Authors: P. Tamilarasi, D. Akila

Paper Title: Ground Water Data Analysis using Data Mining: A Literature Review

Abstract: Data mining is the process of discovering patterns from hidden datasets. Data mining tools are most widely

used in ground water quality prediction. Most of the agriculture field relies on ground water. The accurate prediction of

ground water quality may help in growth of agriculture sector. There are number of techniques for predicting Ground

water quality and Ground water levels such as regression analysis, clustering algorithms. There are many classification

algorithms used in data mining. The appropriate use of classification algorithm will enhance the prediction of water

quality easy and accurate. This paper conducts literature survey on recent researches in this field up to date. The study

reviews on the techniques of analysing ground water data to develop proper models for improving the quality and

prediction of ground water.

Keywords: Ground Water Quality, prediction, Data Mining, Classification Techniques, clustering algorithms.

References: 1. F. Aburub and W. Hadi, “Predicting Groundwater Areas Using Data Mining Techniques : Groundwater in Jordan as Case Study,” vol. 10, no. 9,

pp. 1621–1624, 2016. 2. J. Bansal and A. K. Dwivedi, “Assessment Of Ground Water Quality By Using Water Quality Index And Physico Chemical Parameters : Review

Paper,” vol. 7, no. 2, pp. 170–174, 2018.

3. A. P. Chatur, P. R. V Mante, and A. R. Dhakne, “Brief Survey of Different Techniques for Prediction of Groundwater Level and Groundwater Quality,” vol. 4, no. 11, pp. 168–172, 2017.

4. S. V. S. G. Devi, “Ground Water Quality Data Analysis Using Classification Techniques.”

5. S. M. Gorade and P. A. Deo, “A Study of Some Data Mining Classification Techniques,” pp. 3112–3115, 2017. 6. I. Journal et al., “Water Quality Prediction Using Data Mining techniques : A Survey,” vol. 3, no. 6, pp. 6299–6306, 2014.

7. K. Kolli, “Ground Water Quality Assessment using Data Mining Techniques,” vol. 76, no. 15, pp. 39–45, 2013.

8. S. Physics, “Evaluation of groundwater vulnerability using data mining technique in Hashtgerd plain,” vol. 42, no. 4, pp. 35–41, 2017.

9. U. P. Pradesh, “Analysis of groundwater quality using water quality index : A case study of greater Noida ( Region ), Uttar,” Cogent Eng., vol.

44, pp. 1–11, 2016.

10. R. Priya and R. Mallika, “Ground Water Quality Modelling for Irrigation Using Data Mining Technique and Spatio-Temporal Dates,” vol. 12, no. 16, pp. 6097–6101, 2017.

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11. C. Sarala and R. B. P, “Assessment of Groundwater Quality Parameters in and around Jawaharnagar , Hyderabad,” vol. 2, no. 10, pp. 1–6, 2012. 12. A. Shanmugasundharam, G. Kalpana, S. R. Mahapatra, E. R. Sudharson, and M. Jayaprakash, “Assessment of Groundwater quality in

Krishnagiri and Vellore Districts in Tamil Nadu , India,” Appl. Water Sci., vol. 7, no. 4, pp. 1869–1879, 2017.

50.

Authors: S. Arockiaraj, S. Sundara Mahalingam, B.V. Manikandan and V.P. Gowtham Kumar

Paper Title: A Reversible Data Hiding Technique Using Histogram Modification and SMVQ for Very Large Payloads

Abstract: Reversible data hiding (RDH) is the process of embedding secret information into a cover image. The

prime essence of the concept is that, the recovered secret information as well as the cover image should be recovered

without any damage or with imperceptible error in the pixel values. In this paper, we propose an RDH technique based

on simple histogram modification and SMVQ. The proposed histogram modification technique attains high PSNR

values with impressive payload capacities. The SMVQ technique further increases the payload capacity by four folds.

The damage in the extracted secret message is imperceptible and the recovered cover image is either exactly same or

has a very high PSNR value. The algorithm has been well tested and compared with various other techniques.

Keywords: RDH, PSNR, SMVQ, PAYLOADS.

References: 1. Chuan Qin, Chin-Chen Chang, Yi-Ping Chiu, “A Novel Joint Data-Hiding and Compression Scheme Based on SMVQ and Image Inpainting”,

IEEE Transactions Image Processing,Vol. 23, Issue 3, pp. 969 – 978, Jan 2014. 2. Z. Ni, Y. Q. Shi, N. Ansari, and W. Su, “Reversible data hiding,” IEEE Trans. Circuits Syst. Video Technol., vol. 16, no. 3, pp. 354 – 362, Mar.

2006.

3. Fridrich, J., Goljan, M. and Du, R. Lossless data embedding — new paradigm in digital watermarking. EURASIP J. Appl. Signal Process., 2002,

2002, 185–196.

4. Fridrich, J., Goljan, M. and Du, R. Lossless data embedding for all image formats. Proc. SPIE, 4675, 572–583.

5. Celik, M. U., Sharma, G., Tekalp, A. M. and Saber, E. Reversible data hiding, Proc. IEEE Int. Conf. on Image processing: ICIP 2002, Rochester, NY, USA, September 2002, IEEE, Vol. II, pp. 157–160.

6. Tian, J. Reversible data embedding using a difference expansion. IEEE Trans. Circuits Syst. Video Technol., 2003, 13, 890–896.

7. Alattar, A. M. Reversible watermark using the difference expansion of a generalized integer transform. IEEE Trans. Image Process., 2004, 13, 1147–1156.

8. Ni, Z., Shi, Y. Q., Ansari, N. and Su, W. Reversible data hiding. IEEE Trans. Circuits Syst. Video Technol., 2006, 16, 354–362.

9. Chang, C. C. and Lu, T. C. A difference expansion oriented data hiding scheme for restoring the original host images. J. Syst. Software, 2006, 79, 1754–1766.

10. Weng, S., Zhao, Y. and Pan, J. S. A novel reversible data hiding scheme. Int. J. Innov. Comput. Inf. Control, 2008, 4, 351–358.

11. Tseng, H. W. and Chang, C. C. An extended difference expansion algorithm for reversible watermarking. Image Vision Comput., 2008, 26, 1148–1153.

12. Thodi, D. M. and Rodriquez, J. J. Expansion embedding techniques for reversible watermarking. IEEE Trans. Image Process., 2007, 16, 721–730.

13. Tseng, H. W. and Hsieh, C. P. Prediction-based reversible data hiding. Inf. Sci, 2009, 179, 2460–2469. 14. Fallahpour, M. and Sedaaghi, M. H. High capacity lossless data hiding based on histogram modification. IEICE Electron. Express, 2007, 4, 205–

210.

15. Lin, C. C. and Hsueh, N. L. A lossless data hiding scheme based on three-pixel block differences. Patt. Recogn., 2008, 41, 1415–1425. 16. Lin, C. C., Tai, W. L. and Chang, C. C. Multilevel reversible data hiding based on histogram modification of difference images. Patt. Recogn.,

2008, 41, 3582– 3591.

17. Tsai, P., Hu, Y. C. and Yeh, H. L. Reversible image hiding scheme using predictive coding and histogram shifting. Signal Process., 2009, 89, 1129–1143.

18. Tai, W. L., Yeh, C. M. and Chang, C. C. Reversible data hiding based on histogram modification of pixel differences. IEEE Trans. Circuits Syst.

Video Technol., 2009, 19, 906–910.

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51.

Authors: P. Suresh and J. Revathy

Paper Title: Women’s Decision and Its Consequences Portrayed in Kavery Nambisan’s on Wings of Butterflies’

Abstract: Decision Making is a standout amongst the hugest fundamental abilities which can be gained just by having

great information about the idea and great determining aptitudes. This could be absorbed just by means of

understanding. It is an essential fundamental ability that one ought to have. Ladies get influenced by numerous

components while taking a choice, for the most part in the essential circumstances of their life. In this article, it will talk

about whether the life decisions of ladies depend on mental variables or not, If anyway, how they will be influenced by

those mental elements? Does the choices that are taken by ladies, do they influence both their own and expert lives?

Assuming this is the case, what can be the cure? The journey for the reactions of these inquiries is investigated from the

life of women of the novel On Wings of Butterflies (2002) by the famous author Kavery Nambisan. Her books express

the requirement for liberation, enlightenment and Decision Making of ladies; along these lines, her novel On Wings of

Butterflies (2002) has been set in the dialogue to show signs of improvement comprehension of the proposed point

"Women's choices and its results".

Keywords: Decision making, Psychoanalysis, Nightmares, Independent choices, mental traumas Wrong choices,

psychosomatic knowledge, and crucial circumstances.

References: 1. De, Shoba. Spouse: The Truth about Marriage. New Delhi: Penguin Books India Ltd, 2005. 2. Freud, Sigmund The Interpretation of Dreams the Illustrated Edition, Sterling Press 2010.

3. Irigaray, Lace. An Ethics of Sexual Difference. Trans. from the French by Carolyn Burke & Gillian C. Gill. London. NewYork: Continuum, 2004

4. Jung, Carl. Man and His Symbols. London: Pan Books, 1964. 5. Knoll G 1973. Management for Modern Family. New Jersey: Practice Hall Publications.

6. Myles, Anita. Feminism and Post Modern Indian Women Novelists in English. New Delhi: Sarup & Sons, 2006.

7. Nambisan, Kavery. On Wings of Butterflies. New Delhi. Penguin Books. 2002. 8. Nambisan, Kavery. The Scent of Pepper. New Delhi: Penguin Books India Ltd, 1996.

9. Rao PV 1982. Marriage, Family and Women in India. New Delhi, Heritage Publishers, 156 – 196

10. Wood, E Samuel, Green-Wood, R Ellen, the World of Psychology, United States of America: Allyn and Bacon, 1993.

213-218

52.

Authors: P. Suresh and R. Prigya

Paper Title: Humanistic Aspects Found in A.K.Ramanujan’s Poems

Abstract: Humanistic psychology is a psychological perspective that emphasizes the study of the whole person.

Humanistic psychologists believe that an individual's behaviour is related to his innermost feelings and self-perception.

Humanistic psychologists believe that human being is not merely the product of their surroundings. Though humanistic

psychologist study human values, considerations, and skills involved in growing, teaching, and learning. They highlight

features which are shared by all human beings such as love, sorrow, caring, and self-esteem. This paper focuses on the

Humanistic perspectives found in the poems of A. K. Ramanujan. His poems always have a union of his Physical

background in the West and his Origin to the Indian experiences to trace his individuality. Ramanujan has offered the

Indian culture, family, love and human relationships. His verse appears from heaviness amongst self and history. It

turns into the impressions of the exquisite person is a mystery. The necessity for relating oneself is to history through

resolutions opinions up close and personal with the contemporary ambience whose primary modes - the congruity of

custom fantasy, writing and family were a great extent sterile. He could merge the fundamental Indian sensibility with

the temper of advancement in his verse with a lot of ability. Though Ramanujan lived in the West, he did not forget his

own country and written many poems where he finds that relationships are delineated. The poems taken for highlighting

the humanistic perspectives are Ecology, Obituary, Self-portrait, Snakes, and Striders etc.

Keywords: Humanistic psychology, self-perception, human values, relationships, self –esteem.

References: 1. A.K.Ramanujan The Collected Poems (1995) Oxford University Press. New York. Print. 2. Bhatnagar, M.K. The Poetry of A.K.Ramanujan. New Delhi: Atlantic Publishers and Distributors, 2002. Print.

3. Bruce King, Twentieth Century Indian English Poetry Oxford University Press. New Delhi, 1987. Print.

4. Dwivedi, A.N. A.K.Ramanujan and His Poetry. New Delhi: Doaba House, 1983. Print. 5. Dwivedi, A.N. The Poetic Art of A.K.Ramanujan. New Delhi: B.R. Publishing Corporation, 1983. Print.

6. Indian English Literature, Edited by BasavarajNaikar. Atlantic Publishers, 2011. Print.

7. Iyengar, K. R. Srinivasa. Indian Writing in English.New Delhi: Sterling Publishers Pvt. Ltd., 1990. Print. 8. K. Raghavendra Rao, The Poetry of A.K.Ramanujan in aspects of Indian Writing in English (ed.) M.K.Naik (1979) Print.

9. M.K. Naik, Dimensions of Indian English Literature, New Delhi, 1984. Print.

10. Vasant A. Sahane& M. Shivramkrishna. (eds.) Indian Poetry in English: A Critical Assesment, MacMillan. New Delhi. 1981. 11. ZiniaMitra, Indian Poetry in English PHI Learning Private Limited, New Delhi. 2012. Print.

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53.

Authors: T.D. Srividya, V. Arulmozhi

Paper Title: A Review of Threshold based Segmentation for Skin Cancer with Image Processing

Abstract: Detecting skin cancer in premature stage is vital and decisive. Nowadays skin cancer is considered as the

most hazardous forms of cancer in humans. Skin cancer are of various types such as Melanoma, Basal and Squamous

cell carcinoma, amongst Melanoma is most erratic. The Malignant Melanoma is one of the dangerous in humans. Early

diagnosis can be curable. In Medical Image Diagnosis Computer vision plays an important role which is proved by

many existing systems.

This paper explains the method for detection of melanoma using image processing tools. The Efficient tools supporting

quantitative medical diagnosis are computer analysis and image processing. So the feature extraction phase is

enormously dependent on the detected region which has the disease. So suitable segmentation algorithm is required

which can effectively detect the skin melanoma pixels in the information image. In this work, we have discussed

various techniques which are used in the segmentation procedure.

This paper focuses on the method for the detecting Melanoma Skin Cancer by Segmentation. The input to the system is

the Dermoscopic Image and then by applying novel image processing techniques. The pre-processing approaches

employed in detecting various stages include collection of Dermoscopic Images, filtering the images by using Dull

Razor filtering for removing hairs and air bubbles in the image, converting to gray scale, noise filtering, segmenting the

images using threshold, hybrid threshold, iterative threshold, multilevel thresholding and Automatic Threshold.

Keywords: Skin cancer, Segmentation, Thresholding, Melanoma Detection, Digital Image, Carcinoma.

References: 1. EbthihalAlmansour and M.ArfanJaffar “Classification Of Dermoscopic Skin Cancer Images Using Color And Hybrid Texture Features” IJCSNS

International Journal of Computer Science and Network Security, VOL.16 No.4, April 2016

2. S.Gopinathan1, S. Nancy Arokia Rani2The Melanoma Skin Cancer Detection and Feature Extraction through Image Processing Techniques-

(IJETTCS)Volume 5, Issue 4, July - August 2016 ISSN 2278-6856

3. Sanjay Jaiswar, MehranKadri, VaishaliGatty “Skin Cancer Detection Using Digital Image Processing” IJSER ISSN (Online): 2347-3878 4. Saudamini S. Jivtode1, Amit Ukalkar2 “ Neural Network Based Detection of Melanoma Skin Cancer” International Journal of Science and

Research (IJSR) ISSN(Online): 2319-7064 5. A.S.Deshpande 1, GajbarAmruta M 2 “Automated Detection of Skin Cancer and Skin Allergy” IJARCSMS Issn:2321-7782

6. Ruchika Sharma*, Dr. Pankaj Mohindru, Dr. Pooja Review of Segmentation Techniques for Melanoma Detection Volume 6, Issue 7, July 2016

ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering 7. M.Chaithanya Krishna 1, S. Ranganayakulu 2, DR.P.Venkatesan3Skin Cancer Detection and Feature Extractionthrough Clustering

TechniqueISSN(Online): 2320-9801 ISSN (Print) : 2320-9798,International Journal of Innovative Research in Computer and Communication

Engineering,Vol. 4, Issue 3, March 2016 8. Swathi K and Raghavendra C.K “Techniques of skin cancer detection and classification”-IJTRD-vol 4(3), ISSN:2394-9333

9. Hina Sood#1, ManshiShukla*2, “Segmentation of Skin Lesions from Digital Images using an optimized Approach: Genetic A algorithm” IJCSIT

Vol 5 (5),2014, 6831-6837 ISSN:0975-9646 10. Sanjay Jaiswar, MehranKadri, VaishaliGatty “Skin Cancer Detection Using Digital Image Processing” IJSER ISSN (Online): 2347-3878

11. Roy Jackson Monteiro1, Dhanush J.K2 and Nausheeda B.S3“Comparison of various segmentation algorithms in image processing” International

Journal of Latest Trends in Engineering and Technology Special Issue SACAIM 2016, pp. 241-247e-ISSN:2278-621X

225-228

54.

Authors: P. Suresh, D. Angeline Jeba

Paper Title: The Struggle of Women, Social Realities and Psychological Approach in Ann Petry's The Street and the

Narrows

Abstract: This paper focuses on the investigation of Ann Petry's two fictions The Street and The Narrows. It

investigates the struggle of African American women, social realities, Harlem, the defeat of women, African American 229-234

culture and Triple Oppression. It asks into sexual orientation, segregation, personality and circumstance of ladies in the

public arena the situation of African American and self - acknowledgement or self-arousing through the procedure of

colonization, African American culture conveyed to America by the slaves. Actually, African Americans are abused

and smothered in various angles. This paper is an examination of the manners by which the protagonists of these novels

justify the struggles, concealment and suppression they suffered from horrible conditions under which African live.

This is an endeavour to investigate from various points of view the mission for the characters Lutie Johnson (The

Street) and Abbie Crunch (The Narrows). The protagonist's involvement in picking up the normal womanhood has

various dubious complexities. These fictions particularly explored the black female struggle from a feminist

perspective. This paper is an analysis of African American feminism, racial discrimination against blacks, gender

disparities, sexism and dominance expressed by both white people and people from their own community. It inquires

suppressed life of black women in society in the form of different aspects. The goal of this paper is to break down the

sufferings of Africans and their persecuted life. Also, this paper demonstrates how the difficulties looked by the

protagonists and how their life ends up outside in the general public and their partition from self-acknowledgement in

the general public.

Keywords: African American Feminism, Harlem, Triple Oppression, Gender and Social Disparities and

Psychological Approach.

References: 1. Alain Locke, ed., The New Negro, Atheneum. New York.1968 2. Baker, Houston, Modernism and the Harlem Renaissance: The University of Chicago Press, London. 1987

3. Bell, Bernard W. "Ann Petry's Demythologizing of American Culture and Afro-American Character." In Conjuring: Black Women, Fiction, and the Literary Tradition, edited by Marjorie Pryse and Hortense Spillers. Bloomington: Indiana University Press, 1985

4. Bontemps, Arna. "The Line." Saturday Review 36 (August 22, 1953): 11. Bontemps concedes that Petry's The Narrows

5. Ervin, Hazel A. Ann Petry: A Bio-Bibliography and A comprehensive compilation of reviews, analytical articles, and interviews with Petry. New York: G. K. Hall, 1993

6. Gates, Henry Louis, ed. Ann Petry: Critical Perspectives Past and Present. New York: Amistad Press, 1998

7. Gates, Henry Louis. The Signifying Monkey: A Theory of Afro- American Literary criticism. New York: Oxford UP, 1988 8. Nathan Huggies, Harlem Renaissance, Oxford University Press. New York.1971

9. Petry, Ann. "The Narrows" Northwestern University Press. Evanston. 1988

10. Petry, Ann. "The Street" Houghton Mifflin Harcourt Publishing company, New York.1974 11. Ralph Ellison, Shadow and Act, Vintage Book. New York. 1971.

55.

Authors: P. Suresh, Suchismita Bhattacharya

Paper Title: Traumatised Childhood in Mahesh Dattani’s Play Thirty Days in September

Abstract: Childhood is the most important phase in the life of any human being. The future of an individual depends

upon the type of childhood, he or she leads in. The character and the behaviour of a child depend upon the type of

people he or she comes across in the childhood. The childhood can either make or break the future of an individual.

Childhood days are usually the most pleasant days in the life of any human being, because, those days are usually free

from tension, pressure, stress or any such thing that takes away the peace and happiness from life. These days must be

enjoyed to the fullest as one can never get these days back in life. Childhood is a boon for any child, but it can turn as a

bane if one doesn't have a proper and healthy atmosphere to grow. The child is bound to get afraid or unsecured if his or

her life gets surrounded with freaky and wicked people. The childhood days of a child can even get destroyed if

monsters with friendly faces arrive in life. The play Thirty Days in September revolves around the life of a girl, Mala,

the protagonist of the play, who leads a traumatised childhood. The traumatised childhood affects her adulthood and her

life on a whole. Mahesh Dattani, the dramatist, has depicted the life of a child who is the victim of child sexual abuse,

in a very subtle manner. The play proves that sometimes the pain and the betrayal come from the closed ones in life and

not from the outsiders. The play focusses on many things but the present research paper focusses mainly on the

traumatised childhood of the protagonist.

Keywords: Childhood, Future, Life, Traumatised childhood, Pain, Betrayal, Child, Afraid, Monsters, Friendly faces,

Victim, Child Sexual Abuse, Subtle, Boon, Bane, Pleasant, Human Being.

References: 1. Dattani, Mahesh. Collected Plays. Penguin Books, New Delhi, India, 2000.

2. Dattani, Mahesh, Thirty Days in September. Surjeet Publications, Delhi, India. First Edition 2010 3. Multani, Angelie. Mahesh Dattani's Plays: Critical Perspectives. New Delhi. Pencraft International.

4. Agrawal, Dr Dipti. The Plays of Mahesh Dattani: A Study in Thematic Diversity and Dramatic Technique. New Delhi. Discovery Publishing

House Pvt. Ltd. 5. Agrawal, Beena. Mahesh Dattani's Plays: A New Horizon in Indian Theatre. Jaipur, Book Enclave, 2007.

6. Mukherjee, Tutun. The Plays of Mahesh Dattani: An Anthology of Recent Criticism. New Delhi: Pencraft International, 2012.

7. Parmar, Bipinkumar. Dramatic World of Mahesh Dattani: Voices and Visions. Jaipur: Aadi Publications, 2012. 8. Chaudhari, Asha Kuthari, Mahesh Dattani: An Introduction. New Delhi. Foundation Books. 2005.

9. https://www.simplypsychology.org/Sigmund-Freud.html

10. https://positivepsychologyprogram.com/psychoanalysis/ 11. https://www.livescience.com/54723-sigmund-freud-biography.html

235-238

56.

Authors: N. Sumathi, P. Suresh

Paper Title: Song of Innocence to Experience: A Freudian Critique of Dylan Thomas Select Poetry

Abstract: This research paper is an attempt to establish relationship between Psychology and Literature with the

explication of the text through Freudian terms. Literary criticism is enriched with the psycho-analytic criticism from

Sigmund Freud to Jacques Lacan. Psycho-analysis interpretation has enriched literature both in grave way and in

creative way. Creative approach to psychoanalysis to literature has enthralled the two disciplines. Some Psychologists

regarded dreams to be the result of random brain activity that occurs while sleeping. Psycho-analysts like Sigmund

239-243

Freud and Carl Jung propagates that “dreams can reveal a person’s deepest unconscious wishes and desires.” The

majority of the symbols that occur in dreams are sex symbols as considered by Freud. Dylan Thomas poetry has

enormous usage of images and symbols which are essentially to be analysed in Freudian concepts to explicit the layers

of meanings. He has concurred that he has read Freud’s theory which is subconsciously exposed in his poetry without

direct reference. This paper explicates those images and symbols in Freudian interpretation of dream psychology to be

applied in select poems of Dylan Thomas’ poetry with subjective understanding of his biography.

Keywords: Freudian Concepts - Psycho-Analytic–Conscious and Unconscious Mind - Innocence and Experience –

Dream Psychology – Meta Text.

References: 1. Abrams, R.E. (Fall 1975). The Function of Dreams and Dream Logic. Texas Studies in Literature and Language, 17, No.3, pp.599-614.

2. Ackerman, John. Dylan Thomas: His Life and Work. London: Oxford University Press, 1964. 3. AneirinTalfan Davies, Dylan: Druid of the Broken Body, Swansea: Christopher Davies, 1977.

4. Bayley, John. “Dylan Thomas.” Dylan Thomas. Ed. C.B. Cox Englewood Cliffs: Prentice-Hall, 1966.

5. Constantine FitzGibbon, The Life of Dylan Thomas, J.M.Dent& Sons Ltd., London,' 1965. 6. Cox, C.B. “Introduction.” Dylan Thomas: A Collection of Critical Essays. Ed. C.B. Cox.Englewood Cliffs: Prentice-Hall, 1966.

7. Davies, Aneirin Talfan. Dylan: Druid of the Broken Body. Swansea: Christopher Davies, 1977.

8. Davies, Walford. “The Wanton Starer.” Dylan Thomas: New Critical Essays. Ed. Walford Davies. London: J.M. Dent & Sons, 1972. 9. Davies, Walford, and Maud Ralph. “Notes.” Collected Poems 1934-1953. London: J.M. Dent,1993.

10. Davies, Walford, and Maud, Ralph. “General Preface to the Notes.” Collected Poems 1934-1953. London: J.M. Dent, 1993.

11. Dodsworth, Martin. “The Concept of Mind and the Poetry of Dylan Thomas.” Dylan Thomas: New Critical Essays. Ed. Walford Davies. London: J.M. Dent & Sons, 1972.

12. Fraser, G.S. Dylan Thomas. London: Longmans, Green, 1957. 13. Freud, Sigmund The Interpretation of Dreams (translated by James Strachey), Penguin Bools Ltd, Harmonds worth, Middlesex, England, 1976.

14. Fuller, John. “The Cancered Aunt on her Insanitary Farm.” Dylan Thomas: New Critical Essays. Ed. Walford Davies. London: J.M. Dent &

Sons, 1972. 15. Horan, Robert. “In Defence of Dylan Thomas.“Dylan Thomas: The Legend and the Poet. Ed.E.W. Tedlock. London: Mercury Books, 1960.

16. Jones, T.H. Dylan Thomas. London: Oliver and Boyd, 1963.

17. Kidder, Rushworth M. Dylan Thomas: The Country of the Spirit. Princeton: Princeton University Press, 1973. 18. Merwin, W.S. “The Religious Poet.” Dylan Thomas: The Legend and the Poet. Ed. E.W.Tedlock. London: Mercury Books, 1960.

19. Moore, Geoffrey. “Dylan Thomas.” Dylan Thomas: The Legend and the Poet. Ed. E.W.Tedlock. London: Mercury Books, 1960.

20. Olson, Elder. “The Universe of the Early Poems.” Dylan Thomas. Ed. C.B. Cox. Englewood Cliffs: Prentice-Hall, 1966. 21. Rawson, C.J. “Randy Dandy in the Cave of Spleen: Wit and Fantasy in Thomas (with Comments on Pope, Wallace Stevens, and others).” Dylan

Thomas: New Critical Essays. Ed. Walford Davies. London: J.M. Dent & Sons, 1972.

22. Reid, Alastair. “The Man.” Dylan Thomas: The Legend and the Poet. Ed. E.W. Tedlock. London: Mercury Books, 1960. 23. Savage, D.S. “The Poetry of Dylan Thomas.” Dylan Thomas: The Legend and the Poet. Ed.E.W. Tedlock. London: Mercury Books, 1960.

24. Scarfe, Francis. “Dylan Thomas: A Pioneer.” Dylan Thomas: The Legend and the Poet. Ed.E.W. Tedlock. London: Mercury Books, 1960.

25. Shapiro, Karl. “Dylan Thomas.” Dylan Thomas: The Legend and the Poet. Ed. E.W. Tedlock. London: Mercury Books, 1960. 26. Sinclair, Andrew. Dylan Thomas: Poet of His People. London: Michael Joseph, 1975.

27. Stephens, Raymond. “Self and World: The Earlier Poems.” Dylan Thomas: New Critical Essays. Ed. Walford Davies. London: J.M. Dent &

Sons, 1972.

28. Thomas, Dylan. Collected Poems 1934-1952. London: J.M. Dent & Sons, 1952.

29. Thomas, Dylan. Collected Poems 1934-1953. London: J.M. Dent, 1993.

30. Tindall, William York. A Reader’s Guide to Dylan Thomas. New York: The Noonday Press, 1962.

57.

Authors: P. Suresh, S. Suman Rajest

Paper Title: The Dialog on Postmodernism Intertextuality, Parody, the Talk of History and the Issue of Reference

Abstract: In light of assaults on innovator formalist closure, that postmodernist fiction opens itself up to history, to

what Edward Said (1983) calls the "world". It can never again do as such in any remotely blameless way. Thus those

un-honest confusing historiographic metafictions arrange themselves inside recorded talk while declining to surrender

their self-governance as fiction. Furthermore, it is a genuinely amusing satire that frequently empowers historiographic

metafictions' conflicting doubleness: the intertexts of history and fiction go up against parallel status in the parodic

improving the literary piece of both the "world" and writing and the printed consolidation of these intertextual pasts as a

basic constitutive component of postmodernist fiction works as a formal stamping of accuracy. It is both abstract and

"common" and the intertextual satire of historiographic metafiction orders, as it were. The perspectives of certain

contemporary historiographers: it offers a feeling of the nearness of the past and however a history that can be known

just from its messages, its follows be they scholarly or chronicled.

Keywords: Doubleness, History and Fiction, Contemporary Historiographers, Self-Contradictions, Worldly,

Postmodernist Fiction.

References: 1. Linda Hutcheon A Poetics of Postmodernism: History, Theory, Fiction Routledge: London 1988. p,82

2. Fredric Jameson Marxism and Form University of California Press: Berkeley, 1982, p245 3. Gilles Deleuze Foucault Continuum International Publishing Group: Columbia, 2006, p-45

4. Malcolm Bradbury The Social Context of Modern English Literature Schocken: New York, 1971, p-88

5. Ann Banfield Unspeakable Sentences: Narration and Representation in the Language of Fiction, Routledge: London, 1976, p-99 6. Linda Hutcheon A Poetics of Postmodernism: History, Theory, Fiction Routledge: London 1988. p,102

7. Williams Robert. Art and Thought. Oxford: Blackwell, 2004, p-204

8. Linda Hutcheon A Poetics of Postmodernism: History, Theory, Fiction Routledge: London 1988. p,36 9. Susan Daitch L.C Dalkey Archive Press: London, 2002, p-3

10. Fredric Jameson Marxism and Form University of California Press: Berkeley, 1982, p245

11. Gilles Deleuze Foucault Continuum International Publishing Group: Columbia, 2006, p-55 12. Linda Hutcheon A Poetics of Postmodernism: History, Theory, Fiction Routledge: London 1988. p105

13. Susan Daitch L.C Dalkey Archive Press: London, 2002, p-8

14. Linda Hutcheon A Poetics of Postmodernism: History, Theory, Fiction Routledge: London 1988. p160.

244-251

58. Authors: Geetika Patni, Keshav Nath, Ajay Sharma

Paper Title: Narrative Exuberance and Powerless Female Depicted in Alice Munro’s “Runaway”

Abstract: This paper mainly focuses onto explore the way in which Alice Munro employs certain key images to

dramatize the central theme of her fiction. Munro, who creates fantastic fiction, has fabricated collection of short stories

which are prominently concerned with the maturation process and the recognition of moral and social pressures which

can put an impact on an individual. My introduction praises Munro for her narrative exuberance and sense of accuracy

which discriminates men and women. Munro’s fictive marriages are world without end bargains and she studies not

only their Nostalgias, but there's surprising endurances to an extraordinary level. The raw material of Munro’s work

comes from her own life. She never abandons Southern Ontario as a setting, many considers it the inspiration for her

best work. Her admiration and fascination for her birth place contributes to the construction of her identity. Research

explored the ambivalent views of sexual freedom in terms of the progress of feminism and focused on the women’s

identity from the short stories written by Alice Munro.

Keywords: Dramatize, accuracy, nostalgias, ambivalent, feminism etc.

References: 1. Allentuck, M. (1977).Resolution and independence in the work of Alice Munro. Journal of Postcolonial Writing, 16(2), 340-343.

2. Atwood, M. (2012). Survival: A thematic guide to Canadian literature. House of Anansi.

3. Awano, L. D. (2006). Appreciations of Alice Munro. The Virginia Quarterly Review, 82(3), 91. 4. Martin, W. R. (1987). Alice Munro: paradox and parallel. University of Alberta.

5. Blodgett, E. D. (1988). Alice Munro (Vol. 800). Twayne Pub.

6. Bahador, R., &Zohdi, E. (2015). Inescapable doubleness of vision": a Kristevian reading of Alice Munro's" runaway. Theory and Practice in

Language Studies, 5(11), 2295.

7. Hooper, B. (2008). The fiction of Alice Munro: an appreciation. ABC-CLIO.

8. Barber, L. E. (2006). Alice Munro: The Stories of Runaway. ELOPE: English Language Overseas Perspectives and Enquiries, 3(1-2), 143-156. 9. Bausch, R. (Ed.). (2015). The Norton anthology of short fiction. WW Norton & Company.

10. Bigot, C. (2010). Alice Munro: A Bibliography. Journal of the Short Story in English. Les Cahiers de la nouvelle, (55).

11. Dahlie, H., & Relationships, U. (1972). Isolation and Rejection in Alice Munro's Stories,". World Literature Written in English, 11(1), 43-48. 12. Munro, S. (2001). Lives of mothers & daughters: Growing up with Alice Munro. Union Square Press.

13. Duffy, D. (1998). " A Dark Sort of Mirror":" The Love of a Good Women" as Pauline Poetic. Essays on Canadian Writing, (66), 169.

14. Franzen, J. (2004). Runaway: Alice’s Wonderland. New York Times Book Review, 14. 15. Mayberry, K. J. (1992). " Every Last Thing... Everlasting": Alice Munro and the Limits of Narrative. Studies in Short Fiction, 29(4), 531.

16. Gibson, G. (2014). Eleven Canadian Novelists Interviewed by Graeme Gibson. House of Anansi.

17. Howells, C. A. (2009). Intimate Dislocations: Alice Munro, Hateship, Friendship, Courtship, Loveship, Marriage. Bloom's Modern critical Views: Alice Munro, 167-192.

18. Woodcock, G. (1986). The plots of life: The realism of Alice Munro. Queen's Quarterly, 93(2), 235. 19. Waterston, E. (2003). Rapt in Plaid: Canadian Literature and Scottish Tradition. University of Toronto Press.

20. Cam, H. (1987, October). Learning From the Teacher: Alice Munro's Reworking of Eudora Welty's' June Recital.'. In Span(Vol. 25, pp. 16-30).

21. Irvine, L. (1987). Questioning Authority: Alice Munro's Fiction. CEA Critic, 50(1), 57-66. 22. Hoy, H. (1980). " Dull, Simple, Amazing and Unfathomable": Paradox and Double Vision In Alice Munro's Fiction. Studies in Canadian

Literature/Étudesenlittératurecanadienne, 5(1).

23. Laurence, M. The Controversy about The Diviners. 24. Osachoff, M. G. (1983). 'Treacheries of the Heart': Memoir, Confession, and Meditation in the Stories of Alice Munro. Probable Fictions: Alice

Munro's Narrative Acts, 61-82.

25. Macdonald, R. M. (1976). A Madman Loose in the World: The Vision of Alice Munro. Modern Fiction Studies, 22(3), 365-374. 26. Metcalf, J. (1972). A Conversation with Alice Munro. Journal of Canadian Fiction, 1(4), 54-62.

27. Moore, L. (2004). LEAVE THEM AND LOVE THEM In Alice Munro's fiction, memory and passion reorder life. Atlantic Monthly, 294(5),

125-128. 28. Moss, J. (Ed.). (1983). The Canadian novel: a critical anthology (Vol. 1). Dundurn.

29. Munro, A. (2013). Runaway.Random House.

30. Nischik, R. M. (Ed.). (2007). The Canadian short story: interpretations. Camden House. 31. Rae, I. (2010). Runaway Classicists: Anne Carson and Alice Munro’s “Juliet” Stories. Journal of the Short Story in English. Les Cahiers de la

nouvelle, (55).

32. Rasporich, B. J. (1990). Dance of the sexes: art and gender in the fiction of Alice Munro. University of Alberta. 33. Redekop, M. (2014). Mothers and Other Clowns (routledge Revivals): The Stories of Alice Munro. Routledge.

34. Struthers, J. T. (1975). Alice Munro and the American South. Canadian Review of American Studies, 6(2), 196-204.

35. Thacker, R. (2011). Alice Munro: Writing her lives: A biography. Emblem Editions. 36. Thacker, R. (2016). Reading Alice Munro, 1973-2013.University of Calgary Press.

37. Staines, D. (Ed.). (2016). The Cambridge Companion to Alice Munro. Cambridge University Press.

38. Mayberry, K. J. (1994). Narrative strategies of liberation in Alice Munro. Studies in Canadian Literature/Étudesen literature canadienne, 19(2).

39. Besner, N. K. (1990). Introducing Alice Munro's Lives of girls and women: a reader's guide (No. 8).ECW Press.

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59.

Authors: Esther Silvia, S. Rabiyathul Basariya

Paper Title: Role of Niche Marketing on Search Engine with Reference to Pay Per Click Advertisement

Abstract: A niche market is the subset of the market on which a specific product is focused. Niche market is highly

specialized effective and aiming to survive among the competition from numerous super companies using the niche

keywords. Niche marketing has influenced by the product features of specific market needs such as price range,

production quality etc. In the digital world, marketers using the Online niche marketing for the products to be advertised

using search engines. Search engines involve the promotion of websites by increasing the visibility of search engines

results pages through paid advertising. In this paper the researcher has focused on “ROLE OF NICHE MARKETING

ON SEARCH ENGINE WITH REFERENCE TO PAY PER CLICK ADVERTISEMENT”. Pay per click is an Internet

advertising model used to direct traffic to websites in which advertisers pay the publisher. When the ad is clicked with

search engines, advertisers used keyword phrases relevant to their target market. Pay per click advertisement also

known as banner ads shown on the websites. At present the niche markets has provided the attractive opportunities

available to marketers. Eye catching, effective and localized pay per click ads impact on buying markets. As the pay per

click advertisement provide purchase opportunity wherever people may be surfing.

References: 1. Niche online marketplaces- Here’s why there are so many e-shops out there http://indianonlineseller.com/2014/07/niche-online-marketplaces-

258-260

heres-many-e-shops/ 2. Emergence of niche e-commerce players

3. http://blog.refiral.com/emergence-of-niche-ecommerce-players/Being successful in the niche (Part 2): PPC is the key Marina Simmerl wrote this

on in Data & Market Insightshttps://crealytics.com/blog/2014/09/18/successful-niche-part-2-ppc-key/ 4. How to Research a Profitable Niche Market: Law of Attraction Case Study by Lorna Lihttp://lornali.com/how-to-research-profitable-niche-

market/

5. Ultimate guide to findout niche market Filed in Niche Research, Ultimate Guides &Resources by NicheHacks on December 9, 2013

http://nichehacks.com/ultimate-guide-finding-niche-market/

6. How PPC Fits into Your Internet Marketing Strategy https://www.portent.com/services/ppc/pay-per-click-explained

7. The Role of Your Niche in PPC http://www.standardmarketing.com/2015/02/role-niche-ppc/ 8. Pay-per-click Search Engine Marketing Handbook: Low Cost …) https://books.google.co.in/books

60.

Authors: S. Lavanyaa, D. Akila

Paper Title: Crime against Women (CAW) Analysis and Prediction in Tamilnadu Police Using Data Mining Techniques

Abstract: Crime examination and anticipation is a deliberate methodology for recognizing and breaking down

examples and patterns in wrongdoing against ladies in Tamilnadu state. Our framework can anticipate metropolitan

urban communities which have expansive volume of individuals living territories, workplaces, and corporate

organizations intended forcrime event and can representation crime point regions. Through the getting higher entry to

methodical, crimein sequence experts is capable offacilitate the rule implementation heads and extraordinary

examination police groups to attach the further enquiries of understanding violations. To apply the origination of in

sequence mining we can take out already unidentified, valuable data from unstructured information. In this paper, we

are in push toward software engineering and criminal equity to enhance an information mining system that can help

unravel Crimes against ladies quicker. As an alternate specializing in interference of crime prevalence like criminal

background of crook and conjointly we tend to area unit concentrating primarily on the crime factors of each day.

Keywords: Crime Patterns, Classification and Prediction, Crimes against Women (CAW), Rule enlistment, Crime

Analysis.

References: 1. Yamuna.S, N.Sudha Bhauvaneswari D, Data mining Techniques to Analyze and Predict Crimes, International Journal of Engineering And

Science(IJES) Vol-1,Issue-2,PP 243-247.

2. Sylvia Walby, Improving the statistics on violence against women, Statistical Journal of the united nation ECE 22(2005)193-216.

3. S.Bewley, J.Friend and G.Mezey, Eds, Violence against Women, London: Royal College of Obestricians and Gynaecologists, 1997. 4. Malathi.A and Dr.S.Santhosh Baboo. Article: an enhanced algorithm to predict a future crime using data mining. International Journal of

Computer Applications,21(1):1-6, May2011.Published by foundation of Computer Science.

5. A.Buczak and C.Gifford, ‘Fuzzy association rule mining for community crime pattern discovery’, in ACM SIGKDD workshop on intelligence and security Informatics, Washington, D.C., 2010, PP.1-10.

6. Crimereports.com,2015.[online].Available:http://www.crimereports.com.[Accessed:20-May-2015].

7. Anshu Sharma,Shilpa Sharma 2012 An Intelligent Analysis of Web Crime Data using Data Mining, International Journal of Engineering And Innovative Technology(Ijeit)2(3)

8. Devendra Kumar Tayal et al., Crime detection and criminal identification in India using data mining techniques,AI & Soc(2015) 30, pp.117-127.

9. Roslin V.Hausk and Hsinchun Chen., Coplink: A Case of Intelligent Analysis and Knowledge Management, Proceedings of International Conference on Information Systems, 1999, pp.15-28.

10. Rasoul kiani, Siamak mahdavi, Amin Keshavarzi, Analysis and Prediction of Crimes by clustering and Classification.(IJARAI) International

Journal of Advanced Research in Artificial Intelligence,Vol-4,No:8,2015 11. Amarnathan, L.C.(2003) Technological Advancement: Implications for the Crime, the Indian Police Journal, April-June.

12. Krishnamoorthy, S.(2003) Preparing the Indian Police for 21st Century, Puliani and Puliani, Bangalore, India.

13. Marshall, G.M. and Marshall, D.R.(2008) CRIME IN INDIA, Annual Series, 1954-2006,Published by the Government of India, Ministry of Home Affairs, National Crime Records Bureau, Electronic Dataset and Codebook, Published by center for Systemic Peace. http://

www.systemicpeace.org/inscr/inscr.htm

14. Shiju Sathyadevan, Devan M.S, Surya Gangadharan S.”Crime analysis and Prediction Using Data mining”, 2014 First International Conference on Networks & Soft Computing (ICNSC2014),2014

15. Krishnamoorthy P, Dr R.Gopinath.” Survey on Classifier algorithms for health care system in Diabetes”, International Journal of Engineering

&Technology,7(2.26)2018 pp19-24. 16. Syed Ahsan Shabbir and Kanna Dasan R 2013An Effective Fraud Detection System Using Mining Technique International Journal of Scientific

and Research Publications 3(5)

17. http://data.gov.in/catalog/persons-arrested-under-crime-against-Women 18. http://data.gov.in/catalog/age-group-wise-victims-murder

19. ShyamVaranNath., Crime Pattern Detection Using Data Mining, International Conference on Web Intelligence and Intelligent Agent Technology,

December 2006. 20. Dr.D.Akila, Dr.C. Jayakumar, "Acquiring Evolving Semantic Relationships for WordNet to Enhance Information Retrieval", International

Journal of Engineering and Technology, Volume 6, November 5, pp. 2115-2128, 2014.

21. Dr.D.Akila, Ms.Vidya and Mr.S.Rajesh , "Optimization Based Information Retrieval with the Enhancement of Annotator in WordNet Application", Journal of Advanced Research in Dynamical & Control systems Volume 10 , Issue 2, pp. 318-323,2018.

22. D.Akila,S.Sathya, G.Suseendran, “Survey on Query Expansion Techniques in Word Net Application”, Journal of Advanced Research in Dynamical and Control Systems, Vol.10(4), pp.119-124, 2018.

261-265

61.

Authors: G.G. Loganathan, S. Manoharan, T. Sudhamaheswari

Paper Title: Perception of Motivators-A Study of Public Sector Banks in Bangalore

Abstract: At the outset, the research embarks on the importance of the contribution of the service sector, especially

public sector banks, to the development of the Indian economy. An overview of banking scenario, banking challenges

and human resource challenges of banks in the Indian context is discussed. A large number of employees have started to

retire, and new recruits are joining the public sector banks. The new recruits have to be equipped well to face the

challenges and need to be motivated in order to be retained. Based on the above statement of the problem, the

researcher has stated the objectives of the study. The primary objective is to find out the perception of motivators. The

primary data were collected from 403 respondents from the population of officers with less than 10 years of experience

from select public sector banks in Bangalore. The sampling test was conducted to test the statistical validity.

Appropriate statistical tools were utilized to test the sample. From the data analysis, it was found that the motivators

namely achievement, responsibility and nature of work showed better satisfaction than other motivators namely

266-273

promotion opportunity, respect and recognition and advancement. The study was helpful in identifying the motivators

which have better effect on performance and modify the human resource policy to get better results.

Keywords: Motivation, Public Sector Banks, HR Challenges, promotion opportunity, Respect and Recognition,

Responsibility, Achievement, Advancement and Nature of Work

References: 1. Al-Mansour, A. H, Application of TQM to financial services, 2007, Retrieved from 2. Ankita Srivastav and Pooja Bhatia.2013.Issues and Challenges Involved in Motivational Factors in Nationalized Banks. The SIJ Transactions on

Industrial, Financial &Business Management (IFBM). 1:111-115

3. Benson Kunjukunju.2008 Commercial banks in India- Growth, challenges and strategies, New Century Publications, New Delhi, 1st Edition 4. Bergstrom, Andreas and Ternehall, Mattias.2005.Work motivation in Banks. International Handelshogskolan, Hogskolan Jonkoping

5. Chowdhury, M. S. 2007.Enhancing motivation and work performance of the salespople: The impact of supervisors’ behaviour, African Journal of

Business Management. 1:238-243 6. Dheeraj Kumar Pradhan.2019.Digital Banking –Journey of a nation. The Management Accountant.54:26-31

7. Gabriela Rusu and Silvia Avasilcai.2014. Linking human resources motivation to organizational climate. Social and Behavioura lSciences.24:51-

58 8. Ghafoor, M. D.2011.Organizational effectiveness: A case study of telecommunication and banking sector of Pakistan. Far East Journal of

Psychology and Business. 2: 37- 48

9. H.G.Rainey.H. G.1997. Understanding and managing public organizations. San Francisco, CA: Jossey-Bass 10. Herzberg,F., Mausner,B. and Snyderman,B.B.2004 The motivation to work, New Brunswick, Transaction Publishers

11. Houkes, Inge Janssen, Peter P MdeJonge, Jan Bakker, Arnold B.2003. Specific determinants of intrinsic work motivation , emotional exhaustion

and turn over intention : a multisample longitudinal study. Journal of Occupational and Organizational Psychology. 76: 427-450 ABI/INFROM Complete

12. Isiaka Sulu Babaita.2011. An Appraisal of Employee Motivation in the Nigerian Banking Industry. British Journal of Humanities and Social Sciences. 2: 92-103

13. Jeyapragash, A and Rani Chandrika, P.2013.A Study on Organizational Climate in Banks – With Special Reference to Dindigul. Paripex - Indian

Journal of Research. 2: 40-42 14. Judge, T., and Ilies, R.2002. Relationship of personality to performance motivation: A meta-analytic review. Journal of Applied Psychology.

87:797-807

15. Kaleem Ullah Khan, Syed Umar Farooq and Zilakat Khan.2010. A Comparative Analysis of the Factors Determining Motivational Level of Employees Working in Commercial Banks in Kohat, Khyber Pukhtunkhwa. International Journal of Business and Management. 5:180-184

16. Kanhaiya Singh and Vinay Kumar Dutta.2013. Commercial Bank Management. McGraw Hill Education (India) Private Limited, New Delhi, 1st

Edition 17. Kanungo, R.N., Misra,S., and Dayal,I.1975.Relationship of Job involvement to perceived importance and satisfaction of employee needs.

International Review of Applied Psychology. 24: 49-59

18. Kim, P. S.2003.Strengthening the Pay-Performance Link in Government: A Case Study of Korea. Public Personnel Management,.31:447-463 19. Kothari, C.R,.2009.Research Methodology Method and Techniques. New Age International Publishers

20. Kovach, K.A.1995.Employee motivation: Addressing a crucial factor in your organization’s performance. Employment Relations Today. 22: 93-

105. 21. Kreitner, R.1995. Management, Boston, Houghton Mifflin Company,6thEdition

22. McKinsey,2010. Report on Indian Banking: Towards Global Best practices. Retrieved from http://www.mckinsey.com/ locations

/India/McKinney on India /pdf / India Banking Overview.pdf. Accessed on 31.3.2015

23. Ministry of Finance.2019. http://mofapp.nic.in:8080/economicsurvey/pdf/152-166_ Chapter_09_ Economic_ Survey_2017-18.pdf. Accessed on

16.02.2019

24. Muchinsky,P.1993.Psychology applied and Work, Belmomt, CA: Wadsworth/Thomson Learning,4th Edition 25. Nadler, D.A., and Lawler, E.E.1983. Motivation – a diagnostic approach. In perspectives on behaviour in organizations, Ed. J.R.Hackman,

E.E.Lawler, III, and I.W. Porter, New York: McGraw –Hill.

26. Perry, J. L., and Porter, L. W.1982. Factors affecting the context for motivation in public organization. The Academy of Management Review. 7: 89-98

27. Pfeffer.1994. Competitive advantage through people, Boston, MA: Harvard Business School Press

28. Qayyum, A., Sukirno and Mahmood, A.2011. A Preliminary Investigation of Employee Motivation in Pakistan’s Banking Sector. Research and Practice in Human Resource Management. 19: 38-52

29. Quratul-Ain Manzoor.2011. Impact of Employees Motivation on Organizational Effectiveness. European Journal of Business and Management.

3: 36-44 30. Reserve Bank of India.2017. Bank GroupWise distribution of employees of scheduled commercial banks 2017, https://m.rbi.org.in-publications-

Annual-Handbook of statistics on Indian Economy, accessed on 23rd February 2019.

31. Reserve Bank of India.2018. Financial Stability Report, December 2018, https://rbi.org.in/scripts/BS-Press Release. Accessed on 12.02.2019 32. Reserve Bank of India.2019. Banks in India, https://www.rbi.org.in/commonman/ english/scripts /banksinindia.aspx. Accessed on 16.02.2019.

33. Sadia Rashid and Uzma Rashid.2012.Work Motivation Differences between Public and Private Sector. American International Journal of Social

Science,.1: 24-33 34. Sansone, C., and Harackiewicz, J. M.2000. Intrinsic and extrinsic motivation: The searchfor optimal motivation and performance. San Diego, CA:

Academic Press

35. Saradindu Bhaduri and Hemant Kumar.2011. Extrinsic and intrinsic motivations to innovate: tracing the motivation of grass root innovators in India. Mind Soc.10: 27–55

36. Shadare, O. A., and Hammed, T. A.2009. Influence of work motivation, leadership effectiveness and time management on employees’

performance in some selected industries in Ibadan, Oyo State, Nigeria. European Journal of Economics, Finance and Administrative Sciences. 16:7-17

37. Suryachandra Rao, D.2008.Banking reforms in India-An evaluative study of the performance of commercial banks, Deep Publications New

Delhi, 1st Edition 38. T.S.Bateman and S.A.Snell.2007. Management: Leading & Collaborating in a Competitive World, Boston, Mass: McGraw-Hill/Irwin, 7th

Edition

39. Van Yperen, N. W., and Hagedoorn, M.2003. Do high job demands increase intrinsic motivation or job strain or both? The role of job control and social support. Academy of Management Journal. 46: 339-348

62.

Authors: A.Vidhyalakshmi, C. Priya

Paper Title: A Study on Supervised Learning in Medical Image Gradingusing IoT

Abstract: Computerized medical imaging techniques is a process of creating visual interior representationof our body

part for examining clinical analysis and disrupting the visual functionsof some organs or tissues. The medical images

analyze the types of diseases present in the organs. The intensity often grades the severity and measures the risk score

of diseased image using the Medical Image grading techniques. The Machine learning algorithms constructs a

mathematical pattern of sample data known as training data, such that to make predictions or decisions without being

explicitly programmed to perform the task. TheSupervised learning inmachine learning is a task of investigating a

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function that maps input to an output which is based on input-output pairs. This paper presents the review about the

medical images and medical image grading techniques. The survey for the various result analyses of medical images

using the image processing techniques and the overview of the diseases present in the tongue, hand and lungs images

are discussed. In this paper we talk about the introduction of medical image analysis, medical image grading techniques

applied for the detection of lung cancer in twoways such as, metastasis and the Lingual acrometastatic disease in the

organ of tongue and hand. The proposed model includes the analysis of metastasis and the Lingual acrometastatic

analysis using the classification techniques. The implantation of the proposed paper will be completedthrough the

MATLAB software using the digital image processing techniques and the simulation results will be stored in the

Internet of Things (IoT) server for future verification process.The prediction of lungs cancer will be compared by the

results of the tongue and hand diseases will be stored present in the images.

Keywords: Classification, Supervised learning, detection, segmentation, medical image analysis.

References: 1. SandroQueirós, Pedro Morais, Daniel Barbosa, Jaime C. Fonseca, João L. Vilaça, and Jan D’hooge,” MITT: Medical Image Tracking Toolbox”,

IEEE Transactions on Medical Imaging, 2018.

2. Yong Reny, YiningWangy, Jun Zhuz, Member, IEEE,” Spectral Learning for Supervised Topic Models”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017.

3. YushanZheng, Zhiguo Jiang, Member, IEEE, Haopeng Zhang*, Member, IEEE, FengyingXie, Yibing Ma, Huaqiang Shi and Yu Zhao,”

Histopathological whole slide image analysis using context-based CBIR”, IEEE Transactions on Medical Imaging, 2018. 4. Shanshan Wang, Member, IEEE , Sha Tan, Yuan Gao, Qiegen Liu, Leslie Ying, Taohui Xiao, Yuanyuan Liu, Xin Liu, HairongZheng, and Dong

Liang, Senior Member, IEEE,” Learning Joint-Sparse Codes for Calibration-Free Parallel MR Imaging”, IEEE TRANSACTIONS ON

MEDICAL IMAGING, VOL. 37, NO. 1, JANUARY 2018 5. Qingsong Yang, Pingkun Yan , Senior Member, IEEE , Yanbo Zhang , Member, IEEE , Hengyong Yu , Senior Member, IEEE , Yongyi Shi,

XuanqinMou , Senior Member, IEEE , Mannudeep K. Kalra, Yi Zhang , Member, IEEE , Ling Sun, and Ge Wang , Fellow, IEEE,” Low-Dose

CT Image Denoising Using a Generative Adversarial Network With Wasserstein Distance and Perceptual Loss”, IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 37, NO. 6, JUNE 2018

6. Fuhai Chen, Student Member, IEEE, RongrongJi, Senior Member, IEEE, Jinsong Su, Member, IEEE, Donglin Cao, Member, IEEE, and YueGao,

Senior Member, IEEE,” Predicting Microblog Sentiments via Weakly Supervised Multi-Modal Deep Learning”, IEEE Transactions on Multimedia, 2017

7. AboozarTaherkhani , Member, IEEE, AmmarBelatreche, Member, IEEE, Yuhua Li, Senior Member, IEEE, and Liam P. Maguire, Member,

IEEE,” A Supervised Learning Algorithm for Learning Precise Timing of Multiple Spikes in Multilayer Spiking Neural Networks”, IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. 29, NO. 11, NOVEMBER 2018.

8. Huanfeng Qin and Mounim A. El Yacoubi,” Deep Representation based feature extraction and recovering for Finger-vein verification”,

JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 9. [9]. Kenta Matsumura*, TakehiroYamakoshi, Member, IEEE, Peter Rolfe, Member, IEEE, and Ken-ichiYamakoshi, Member, IEEE,” Advanced

Volume-Compensation Method for Indirect Finger Arterial Pressure Determination: Comparison with Brachial phygmomanometry”,2016

10. FrithjofKruggel,” A Simple Measure for Acuity in Medical Images”, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 20, 2018 11. C.Priya, “TaaS: Trust Management Model for Cloud-Based on QoS” in Journal of Advanced Research in Dynamical and Control Systems,

volume 9, issue 18, 1336-45, ISSN 1943-023X, SNIP 0.294, 2017

12. Hwayoung Choi, Kyung-Jin You, Nitish V. Thakor, Fellow, IEEE, Marc H. Schieber andHyun-Chool Shin, Member, IEEE,” Single-finger

Neural Basis Information-based Neural Decoder (nBINDER) for Multi-finger Movements”, JOURNAL OF LATEX CLASS FILES, VOL. 14,

NO. 8, AUGUST 2015.

13. Man-Sun Kim, Dongsan Kim and Jeong-Rae Kim,” Stage-Dependent Gene Expression Profiling in Colorectal Cancer”, IEEE TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, MANUSCRIPT ID, IEEE/ACM Transactions on Computational Biology and

Bioinformatics,2018.

14. C.Priya , D.Padmapriya,“Trusted Cloud Computing Platform in IaaS for Closed Box Execution Environment to VM” in Journal of Advanced Research in Dynamical and Control Systems, volume 10, issue 4, 193-98, ISSN 1943-023X, SNIP 0.294, 2018

15. Peter B´andi, Oscar Geessink, Quirine Manson, Marcory van Dijk, Maschenka Balkenhol, Meyke Hermsen, Babak Ehteshami Bejnordi, Byungjae Lee, KyunghyunPaeng, AoxiaoZhong, Quanzheng Li, FarhadGhazvinianZanjani, Svitlana Zinger, Keisuke Fukuta, Daisuke Komura,

VladoOvtcharov, Shenghua Cheng, ShaoqunZeng, JeppeThagaard, Anders B. Dahl, Huangjing Lin, Hao Chen, Ludwig Jacobsson, Martin

Hedlund, Melih C¸ etin, ErenHalıcı, Hunter Jackson, Richard Chen, Fabian Both, J¨orgFranke, Heidi K¨usters-Vandevelde, Willem Vreuls, Peter Bult, Bram van Ginneken, Jeroen van der Laak, and Geert Litjens,” From detection of individual metastases to classification of lymph node status

at the patient level: the CAMELYON17 challenge”, IEEE Transactions on Medical Imaging 2018.

16. Wei Yang, Yunbi Liu, Liyan Lin, Zhaoqiang Yun, Zhentai Lu, QianjinFeng*, Member, IEEE, and Wufan Chen, Senior Member, IEEE,” Lung Field Segmentation in Chest Radiographs from Boundary Maps by a Structured Edge Detector”, IEEE Journal of Biomedical and Health

Informatics, 2017.

17. Haibin Zhang, Member, IEEE, Jianpeng Li, Bo Wen, YijieXun, and Jiajia Liu, Senior Member, IEEE,” Connecting Intelligent Things in Smart Hospitals using NB-IoT”, , IEEE Internet of Things Journal, 2018.

18. R.Ranjani ,Dr.C.Priya, “A Survey on Face Recognition Techniques: A Review” in International Journal of Pure and Applied Mathematics,

volume 118, issue 5, 253-74, ISSN 1311-8080(Print), ISSN 1314-3395(Online) 2017 19. Philip joris, Wimdevelter, wim van de voorde, Paul suetens,Frederikmaes, Dirk vandermeulen, and Peter claes,” Preprocessing of Heteroscedastic

Medical Images”, Received February 23, 2018, accepted April 19, 2018, date of publication May 4, 2018, date of current version June 5, 2018.

20. Xiabi Liu, Ling Ma, Li Song, Yanfeng Zhao, Xinming Zhao* , Chunwu ZhouRecognizing Common CT Imaging Signs of Lung Diseases through a New Feature Selection Method based on Fisher Criterion and Genetic Optimization XiabiLiu, August 2015.

21. .R.Ranjani ,Dr.C.Priya, “A Fusion of Image Processing and Neural Networks for Lung Cancer Detection Using SVM In Matlab” in International

Journal of Pure and Applied Mathematics, Volume 119, issue 10, 100-111, ISSN 1311-8080(Print), ISSN 1314-3395(Online) 2018 22. Martin Storath, Christina Brandt, Martin Hofmann, Tobias Knopp, Johannes Salamon, Alexander Weber, and Andreas Weinmann,” Edge

preserving and noise reducing reconstruction for magnetic particle imaging”, IEEE Transactions on Medical Imaging, 2016.

23. C.Priya ,R.Latha, “TaaS: A Framework for Trust Management in Cloud Computing Environments” in International Journal of Science and Research, volume 5, issue 9, 1402-05, ISSN 2319-7064(Online), DOI: 10.21275/ART20161879, September 2016

24. Guotai Wang , Wenqi Li , Maria A. Zuluaga , Rosalind Pratt, Premal A. Patel, Michael Aertsen, Tom Doel, Anna L. David, Jan Deprest,

SébastienOurselin, and Tom Vercauteren,” Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning”, IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 37, NO. 7, JULY 2018.

25. K.Kavitha,, G.Suseendran, “A Review on Security Issues of IOT Based on Various Technologies”, Journal of Advanced Research in Dynamical

and Control Systems, Vol.10 (4), pp.385-390,2018. 26. G.Suseendran, S.Priya, “Segmentation of neoplasm tissues with convolutional neural networks Journal of Advanced Research in Dynamical and

Control Systems, Special Issue (12), , pp.-271-275, 2017

63.

Authors: V. Mathan Kumar, R. Velmurugan

Paper Title: Customer Preference for Online Shopping in Coimbatore District

Abstract: Online Shopping is a major growth in the field of e-commerce and will certainly be the upcoming buzz 280-282

word of shopping across the world. In the present era, all business houses are managing their business online and

initiate necessary steps to sell their products or services online. The development of internet has brought about a sea

change in the way shopping is done. The Internet and the World Wide Web (www) have radically changed the way

customers search for and use information. The Internet, which was previously conceptualized as an instrument for

gathering information has turned out to be an inseparable part of business now. For any business, the key towards their

continued existence and growth depends on how well it can incorporate this medium i.e., online shopping. In order to

put up for sale anything online, the manufacturers / sellers have to take into consideration who their customers are, what

their spending habits and what type of products and services they prefer. The present study has been carried out to

identify the factors associated with the level of preference for online shopping among customers.

References: 1. Kanupriya and Anupreet Kaur. 2016. A Study of Behaviour of Consumer towards Online Shopping”, Orbit-Biz-Dictum, 1:43-55.

2. Muhammad Umar Sultan and MD Nasiruddin .2016. Consumers’ Attitude towards Online Shopping Factors influencing Gotland consumers to shop online. Master Thesis in Business Administration.

3. Payal Upadhyay and Jasvinder Kaur .2016. Analysis of Online Shopping Behavior of Customer in Kota City. Shiv Shakti International Journal in

Multidisciplinary and Academic Research. 2:1-28. 4. Saranya and Anandh .2016. A Study On Customers Buying Behaviour Through Amazon. Inter Continental Journal of Marketing Research

Review.4:133-139.

5. Khushboo Makwana et al. .2017. What Drives Consumers to Shop Online. IOSR Journal of Computer Engineering. 42-47. 6. Priyanka Sharma .2017. Consumer Behavior Towards Online Shopping-An Empirical Study With Reference To Bhiwani City, Haryana.

International Conference on Recent Trends in Engineering Science and Management.

7. Rifaya Meera, R. Padmaja and Mohammed Abubakkar Siddique, R .2017. Preference of Customers towards Online Shopping Applications. Imperial Journal of Interdisciplinary Research. 3: 577-582.

64.

Authors: C. Sudha, D. Akila

Paper Title: Detection OFAES Algorithm for Data Security on Credit Card Transaction

Abstract: Nowadays, Credit card could be a little plastic card issued by a bank, savings and loan association, etc.,

permitting the owner to purchase items or services on credit. Debit card could be a card permitting holder to get

merchandise or services on credit. Open-end credit may well be a card permitting the owner to transfer money

automatically from their checking account once creating a buying deal. The utilization of credit cards and debit cards

are increasing day by day. Individuals are relying additional on each card these days than within the earlier days. As

credit cards and debit cards become the primary common mode of payment for each on-line additionally as consistent

purchase, cases of fake related to it are rising. In world, dishonorable transactions are scattered with real businesses and

easy pattern matching techniques are not typically spare to note those frauds accurately. We from this time forward

propose a window-sliding structure to mean the trades each social affair. Next, we void a party of specific individual

direct measures for each cardholder subject to the totaled trades and the cardholder chronicled trades. By then we train a

method of classifiers for every party on the base of all rules of direct. Finally, we use the classifier set to see mutilation

on the web and if another trade is coercion, an information instrument is taken in the prominent proof present with the

incredible old shaped focus to regard the issue of thought skim. The yielded consequences of our basics show up that

our structure is better than various individuals here we are using AES algorithm to maintain the data securely.

Keywords: Credit card, pattern matching techniques, Cryptography, Mutilation.

References: 1. LutaoZheng, Guanjun Liu , Member, IEEE, Chungang Yan, and Changjun Jiang,” Transaction Fraud Detection Based on Total Order Relation

and Behavior Diversity” IEEE transactions on computational social systems, 2329-924X © 2018 IEEE. 2. KuldeepRandhawa, Chu Kiong Loo, ManjeevanSeera, CheePengLim , And Asoke K. Nandi, Credit Card Fraud Detection Using AdaBoost and

Majority Voting, VOLUME 6, date of publication February 15, 2018, date of current version March 28, 2018

3. C. Sudha, T. Nirmalraj,” Analysis of Suspicious Pattern Discovery using AI-Neural Network in Credit Card Fraud Detection” submitted in International Journal of Current Research and Review, Vol.9.Issue10. May2017.

4. C. Sudha, T. Nirmal Raj, “Credit card fraud detection in internet using k-nearest neighbor algorithm” submitted in International Journal of

Current Research and Review, Volume 5, Issue 11, November 2017. 5. FahimehGhobadi, Mohsen Rohani, “Cost Sensitive Modeling of Credit Card Fraud Using Neural Network Strategy” ICSPIS 2016, 14-15 Dec.

2016, Amirkabir University of Technology, Tehran, Iran.

6. Andrea Dal Pozzolo, GiacomoBoracchi, Olivier Caelen, CesareAlippi and GianlucaBontempi, Credit Card Fraud Detection and Concept-Drift

Adaptation with Delayed Supervised Information, 978-1-4799-1959-8/15/2015 IEEE.

7. Aashlesha Bhingarde, Avnish Bangar, Krutika Gupta, Snigdha Karambe Review on Fraud Detection in Electronic Payment Gateway, Volume: 04

Issue: 01 ,Jan -2017, International Research Journal of Engineering and technology (irjet). 8. soltani halvaiee and akbari “a novel model for credit card fraud detection using artificial immune systems” volume 24 issue c, november 2014,

elsevier science publishers b. V. Amsterdam, the netherlands, the netherlands 9. Olszewski (2014) “fraud detection using self-organizing map visualizing the user profiles”, volume 70 issue c, november 2014

10. pages 324-334, elsevier science publishers b. v. amsterdam, the netherlands, the netherlands.

11. Siddhartha Bhattacharyya, “Data mining for credit card fraud: A comparative study”, Decision Support Systems 50 (2011) 602–613. 12. F. Fadaei noghani, m. moattar, ensemble classification and extended feature selection for credit card fraud detection

13. Alejandro Correa Bahnsen∗ , Djamila Aouada, Aleksandar Stojanovic, Björn Ottersten, “Feature ngineering strategies for credit card fraud

detection”, Expert Systems With Applications 51 (2016) 134–142.

14. G.Suseendran, E.Chandrasekaran “Interference Reduction Technique in Mobile Adhoc Networks Using Mathematical Prediction Filters,

International Journal of Computer Applications, Volume 60, Issue.6, December 2012.

283-287

65.

Authors: S. Gunasekharan, K.Tarun Raj

Paper Title: Structural Design and Modeling of Keystone Butterfly Valve

Abstract: A Keystone Butterfly valve is a kind of stream control gadget Keystone butterfly valve Air Actuators

(pneumatic), Keystone butterfly valve Electric Actuators, Positioners and other control embellishments for add up to

stream control arrangements cornerstone butterfly valve have a far-reaching scope of valves to suit numerous

mechanical applications. Cornerstone butterfly Valves can be joined with Keystone air actuators and Keystone Electric

Actuators, Positioners and extras, to make finish stream control bundles. Cornerstone Air Actuators (pneumatic)

incorporate both twofold acting and spring return actuators, with or without manual abrogates. The fundamental target

288-291

of this proposition work is to the configuration in view of Topology Optimization procedures. Topology improvement

is utilized at the idea level of the plan procedure to land at a calculated outline recommendation that is then tweaked for

execution and manufacturability. This replaces tedious and expensive outline cycles and consequently lessens plan

advancement time and by and large cost while enhancing plan execution. Investigations the created variation for

entryway and body instead of threw diminishment in the material of valve body and entryway by basic outline and FEM

examination and advancement in the material of valve part. The 3D representing to be achieves for cornerstone butterfly

valve by utilizing CATIA programming. Promote the pressure and dislodging FEM investigation of the cornerstone

butterfly valve to be done by utilizing ANSYS instrument to assess the improved outcome.

Index Terms: cornerstone butterfly valve, Topology Optimization strategies, CATIA, Ansys.

References: 1. Cohn, S.D., 1951, Performance Analysis of Butterfly Valves," J. Instruments and Control Systems, 24, pp. 880-884. 2. McPherson, M.B., Strausser, H.S., and Williams, J.C., 1957, “Butterfly Valve Flow Characteristics," J. Power through pressure Division, 83(1),

pp. 1-8.

3. Sarpkaya, T., 1961, “Torque and Cavitations Characteristics of Butterfly Valves," J. Connected Mechanics, 28(4), pp. 511{518. 4. Addy, A.L., Morris, M.J., and Dutton, J.C., 1985, “An Investigation of Compressible Flow Characteristics of Butterfly Valves," J. Liquids

Engineering, 107(4), pp. 512-517.

5. Edom, K., 1988, “Performance of Butterfly Valves as a Flow Controller," J. Liquids Engineering, 110(1), pp. 16-19. 6. Cohn, S.D., 1951, “Performance Analysis of Butterfly Valves," J. Instruments and Control Systems, 24, pp. 880-884.

7. McPherson, M.B., Strausser, H.S., and Williams, J.C., 1957, “Butterfly Valve Flow Characteristics," J. Power through pressure Division, 83(1),

pp. 1-8. 8. Sarpkaya, T., 1961, “Torque and Cavitations Characteristics of Butterfly Valves," J. Connected Mechanics, 28(4), pp. 511-518.

66.

Authors: M.V. Varalakshmi

Paper Title: Preparation and Tribological Properties of New Bisimidazolium Ionic Liquids

Abstract: In this paper two new bisimidazolium based ionic liquids (ILs), 3,3'- (3,6,9,12,15- pentaoxaheptadecane-

1,17-diyl) bis(1-vinyl-1H-imidazol-3-ium) methanesulfinate (1a), 3,3'- (3, 6,9,13-tetraoxapentadecane-1,15-diyl)bis(1-

vinyl-1H-imidazol-3-ium)methanesulfinate (1b) were prepared. Their structures were characterized with 1H and 13C

NMR, and Mass Spectroscopy. Tribological behavior of 1a and 1b ILs was studied.

Index Terms: Bisimidazolim ionic liquids, NMR, Mass, Four ball tester, Friction and Wear

References: 1. Chengfeng Y, Weimin L, Yunxia Chong and Laiguine Yugrane “Room-Temperature features of ionic liquids: a novel type lubricant character”,

Chem Commun, No 21, 2001, pp 2244-2245. 2. Feng Zhou tol, Yongmin Liang chan ,Weimin Liu “Ionic liquid lubricants:, Chem. Soc. Rev., Vol 38, 2009, pp 2590-2599.

3. Ichiro Minami “Ionic liquids in the field of tribology”, Molecules, Vol 14, No 6, 2009, pp 2286-2305. 4. Maria Anne Dolores Bermudez K.H, Ana Jimenez; Jose and Francisco Jose “Ionic liquids as lubricant fluids”, Molecules, Vol 14, No 8, 2009, pp

2888-2908.

5. Tsukasa itchi, Tetsuya Tsu, Ken Okazaki and Susumu Y Kuwabata “New frontiers in materials”, Adv. Materials, Vol 22, No 11, 2010, pp 1196-1221.

6. Anthony E. Somer,. Howlett Macfarlane “A review of ionic liquid lubricants”, Lubricants, Vol 1, No 1, 2013, 3-21.

7. Jun Qu, Dinesh G. Bansal,Jane Y. Howe, Huimin L,, Huaqing Li, Peter J. Blau, Bruce G., Gregory , and Donald Smolenski “Antiwear performance a lubricant additive”, Acs Applied Materials, Vol 4, No 2, 2012, pp 997-1002.

8. Lethesh Shah, Ayodele Mutalib and Y Uemura, “Nitrile functionalized thermophysical properties” J Mol Liq, Vol 221, 2016, pp 1140-1144.

9. Hernandez battez, R. Gonzalez; Viesca, D. Blanco and A. Osorio “Tribological behavior for steel”, Wear, Vol 266, No 11-12, 2009, pp 1224-1228.

10. Cai, M., Zhao, Z., Liang, Y. et al. “Alkyl imidazolium polyurea grease for steel/steel contacts”, Tribol Lett, Vol 40, No 2, 2010, pp 215-224.

11. Ana-Evajimenez, Bermudez “Imidazolium ionic liquids in aluminium-steel lubrication”, Wear, Vol 265, No 5-6, 2008, pp787-798. 12. A.-E. Jiménez and M.-D. Bermúdez, “Short imidazolium ionic liquid additives in lubrication of ester oil”, Tribology - Materials, Surfaces &

Interfaces, Vol 6, No 3, 2012, pp109-115.

13. Xiao, H., Guo, D., Liu, S. et al.,“Film thickness of ionic 14. alkyl chain length”, Tribol Lett, Vol 41, 2011, pp 471- 41: 471-477.

15. Palacio, M. & Bhushan, B.“A review of ionic liquids in nanotechnology”, Tribol Lett, Vol 40, 2010, pp 247-268.

16. Meirong Meihuan Yao,Feng Zhou, and Weimin Liu, “Imidazolium additives in poly(ethylene glycol)for steel”, Acs Applied Materials & Interfaces, Vol 2, No 3, 2010, pp 870-876.

17. Liu, X., Zhou, F., Liang, Y. et al.“Benzotriazole as the additive for liquid lubricant”, Tribol Lett, Vol 23, 2006, pp 191-196.

18. Meirong Cai, Yongmin Liang, Feng Zhou, and Weimin Liu “Tribological properties of bearing bezotriazole in ploy(ethylene glycol) and Ploy urea Grease for steel/steel contacts” Acs Applied Materials & Interfaces, Vol 3, No 12, 2011, pp 4580-4592.

19. G Hang, QYu, M Cai, F Zhou and W Liu, “Investigation of the lubricity and antiwear behavior of Guanidinium ” Tribol Int, Vol 114, 2017, pp

65-76. 20. Meihuan Yao, Yongmin Liang, Yanqiu Xia, and Feng Zhou “Bisimidazolium ionic liquids additives in poly(ethylene glycol) for steel- steel

contacts” , Vol 1, No 2, 2009, pp 467-471.

292-294

67.

Authors: Prasanthi Boyapati, N. Nagamalleswara Rao

Paper Title: Intuitionistic Neutro Soft Rough Sets and Classical Regression Model for Brain Image Segmentation

Abstract: Magnetic resonance image (MRI) is one of major component in medical brain image, imaging technique

and segmentation of brain medical image is a crucial & complex task in evaluation of MRI images. Conventionally,

different types of fuzzy, soft set related approaches like intuitionistic, fuzzy c-means, fuzzy c-means were developed to

segmentation of brain related image, but these approaches face accuracy loss in brain image segmentation. So we

consider new segmentation approach i.e. Intuitionistic neutro soft based rough sets and Classical Regression model

(INSRCRM) which is extension to Advanced machine learning approach i.e. Enhanced & Explored Intuitionistic FCM

clustering (EEISFCM) for smoothness and to increase image accuracy and intensity. Proposed approach is applied to

increase accuracy and intensity with respect to spatial data processing for medical brain image segmentation and

evaluate histon and histogram based image smoothness. Proposed approach evaluated with lower and upper

approximations for intensity based brain image segmentation. This approach mainly identifies real valleys to smooth

measure to present brain image segmentation to reduce noise reduction based on threshold of image pixels with

295-300

different image notations. Experimental results of proposed approach gives to find peaks and valleys to demonstrate

better image segmentation results with respect to traditional approaches.

Keywords: Medical image segmentation, regression model, Intuitionistic soft based rough sets, fuzzy c- means,

Classification accuracy and spatial weighted data

References: 1. Cong-Hua Xie & Yong-Jun Liu & Jin-Yi Chang,” Medical image segmentation using rough set and local polynomial regression”, Multimed

Tools Appl (2015) 74:1885–1914, DOI 10.1007/s11042-013-1723-2.

2. S. Ramathilagam, R. Pandiyarajan, A. Sathya, R. Devi, S.R. Kannan,” Modified fuzzy c-means algorithm for segmentation of T1–T2-weighted

brain MRI”, © 2010 Elsevier B.V. All rights reserved , Journal of Computational and Applied Mathematics 235 (2011) 1578–1586. 3. K.V. Leemput, F. Maes, D. Vandermeulen, P. Suetens, Automated model based bias field correction of MR images of the brain, IEEE Trans.

Med. Imaging 18 (1999) 885–896.

4. M.N. Ahmed, N.A. Mohamed, A.A. Farag, T. Moriarty, A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data, IEEE Trans. Med. Imaging 21 (2002) 193–199.

5. R.L. Cannon, J.V. Dave, J.C. Bezdek, Efficient implementation of the fuzzy c-means clustering algorithms, IEEE Trans. Pattern Anal. Mach.

Intell. PAMI-8 (2) (1986) 248–255. 6. Zujun Hou, A review on MR image intensity in homogeneity correction, Int. J. Biomed. Imaging (2006) 1–11. Article ID 49515.

7. B.R. Condon, J. Patterson, D. Wyper, Image nonuniformity in magnetic resonance imaging: its magnitude and methods for its correction, Br. J.

Radiol. 60 (1987) 83–87. 8. M. Tincher, C.R. Meyer, R. Gupta, D.M. Williams, Polynomial modelling and reduction of spatial body-coil spatial in homogeneity, IEEE Trans.

Med. Imaging 12 (1993) 361–365.

9. S. Lai, M. Fang, A new variational shape-from orientation approach to correcting intensity inhomogeneities in MR images, in: Proc. of Workshop on Biomedical Image Analysis CVPR98, 1998, pp. 56–63.

10. S.E. Moyher, D.B. Vigneron, S.J. Nelson, Surface coil MR imaging of the human brain with an analytic reception profile correction, J. Magn. Reson. Imaging 5 (1995) 139–144.

11. S. Krinidis, V. Chatzis, A robust fuzzy local information c-means clusteringalgorithm, IEEE Trans. Image Process. 19 (5) (2010) 1328–1337.

12. C. Li, J.C. Gore, C. Davatzikos, Multiplicative intrinsic component optimization(MICO) for MRI bias field estimation and tissue segmentation, Magn. Reson.Imaging 32 (7) (2014) 913–923.

13. Karoui I, Fablet R, Boucher J, Augustin J (2010) Variational region-based segmentation using multiple texture statistics. IEEE Trans Image

Process 19:3146–3156. 14. Khang ST, NorAshidi M (2011) Color image segmentation using histogram thresholding Fuzzy C-means hybrid approach. Pattern Recogn 44:1–

15.

15. Tan KS, Isa NAM (2011) Color image segmentation using histogram thresholding—Fuzzy C-means hybrid approach. Pattern Recogn 44:1–15. 16. Wu Z (2001) Research on remote sensing image classification using neural network based on rough sets. In: 2001 Proceedings of the Info-tech

and Info-net International Conferences, pp 279–284.

17. Zijdenbos AP, Dawant BM, Margolin RA et al (1994) Morphometric analysis of white matter lesions in MR images: method and validation. IEEE Trans Med Imaging 13:716–724.

18. Cai WL, Chen SC, Zhang DQ (2007) Fast and robust fuzzy c-means clustering algorithms incorporating local information for image

segmentation. Pattern Recogn 40:825–838. 19. Maji P, Kundu MK, Chanda B (2006) Segmentation of brain MR images using fuzzy sets and modified cooccurrence matrix. In: The Proceedings

of the IET International Conference on Visual Information Engineering, pp 327–332

20. Maji P, Pal SK (2007) Rough set based generalized fuzzy C-means algorithm and quantitative indices. IEEE Trans Syst Man Cybern B Cybern

37:1529–1540.

21. Milind MM, Ajoy KR (2008) Color image segmentation: rough-set theoretic approach. Pattern Recogn Lett 29:483–493.

22. Mohabey A, Ray AK (2000a) Rough set theory based segmentation of color images. In: 19th Internat. Conf. North Amer. Fuzzy Inform. Process. Soc. (NAFIPS), pp 338–342

23. Mohabey A, Ray AK (2000b) Fusion of rough set theoretic approximations and FCM for color image segmentation.In: 2000 I.E. Internat. Conf.

Systems Man Cybernet, pp 1529–1534. 24. Orlando J, Tobias RS (2002) Image segmentation by histogram thresholding using fuzzy sets. IEEE Trans Image Process 11:1457–1465

25. Pawlak Z (1982) Rough sets. Int J Comput Inform Sci 11:341–356.

26. Ridler TW, Calvard S (1978) Picture thresholding using an iterative selection method. IEEE Trans Syst Man Cybern 8:630–632. 27. Sen D, Pal SK (2006) Image segmentation using global and local fuzzy statistics. In: Proceedings of the 2006 Annual IEEE India Conference, pp

1–6

28. Sen D, Pal SK (2009) Histogram thresholding based on fuzzy and rough measures of association error. IEEE Trans Image Process 18:879–888. 29. Sen D, Pal SK (2009) Generalized rough sets, entropy, and image ambiguity measures. IEEE Trans System Man Cybern B Cybern 39:117–128.

30. Shan ZY, Yue GH, Liu JZ (2002) Automated histogram-based brain segmentation in T1-weighted three dimensional magnetic resonance head

images. NeuroImage 17:1587–1598. 31. Souplet JC, Lebrun C, Ayache N et al (2008) An automatic segmentation of T2-FLAIR multiple sclerosis lesions. In: Grand Challenge Work:

Mult. Scler. Lesion Segm. Challenge, pp 1–11.

68.

Authors: N. Manoj Kumar, Pallam Ravi

Paper Title: A Dynamic Access for Forecasting of User vitality Positions in Social Networking Services

Abstract: A infrequent clients continue accommodate with one by one regularly. One compelling and elementary

drawback inside the person to person communication authority is to position clients bolstered their essentialness in

exceptionally informal communication authority are present at a few on-line networks like twitter.com and weibo.com.

Relate in nursing right positioning rundown of client essentialness may profit a few collecting in interpersonal

organization authority like the promotions providers and site authority. In spite of the fact that it's frightfully

encouraging to get an imperativeness based positioning rundown of clients, there square measure a few specialized

challengers in light of the enormous scale and elements cooperation’s among clients on communal organizations. Tests

of communal organization grasp anyway don't appear to be confined to informal communities in smaller scale blog

destinations and scholastic coordinated effort systems.

Keywords: Distributed Systems, Checking Data, Social Networks, User Activity and Security.

References: 1. W Liu, G. Li, and J. Cheng, Fast PageRank estimation by adaptable assessing,? Learning. Inf. Syst., vol. 42, no. 1, pp. 127– 146, 2015.

2. Y Song, W. Ng, K. Wai-Ting Leung, and Q. Tooth, SFP-Rank: Significant progressive model examination for ground-breaking situating,?

Learning. Inf. Syst., vol. 43, no. 3, pp. 529– 553, 2015.

3. An Omidvar, M. Garakani, and H. R. Safarpour, Context based customer situating in social occasions for ace finding using WordNet dictionary and casual association examination,? Inf. Technol. Direct., vol. 15, no. 1, pp. 51– 63, 2014

301-305

4. D.M. Romero, W. Galuba, S. Asur, and B. A. Huberman, Influence and absence of contribution in online life,? in Machin Learning and Knowledge Discovery in Databases. Berlin, Germany: Springer, 2011, pp. 18– 33.

5. R. G. Dull hued, Smoothing, Forecasting and Prediction of Discrete Time Series. North Chelmsford, MA, USA: Courier Corporation, 2004.