This proceeding features papers discussing big data innovation for sustainable cognitive computing. The papers feature detail on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on cognitive computing technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform. The EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2018), took place on 13 15 December 2018 in Coimbatore, India.
Chapter
1. Data Security In The Cloud Via Artificial Intelligence
With Vector Quantization For Image Compression.
Chapter
2. Hybrid Ant-Fuzzy
Approach For Data Clustering (Afc) In Distributed.
Chapter
3. S-Transform
Based Efficient Copy-Move Forgery Detection Technique In Digital Images.-
Chapter
4. Neuro Fuzzy Ant Bee Colony Based Feature Selection For Cancer
Classification.
Chapter
5. Entity Resolution For Maintaining Electronic
Medical Record Using Oyster.
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6. Lifetime Improvement Of Wireless
Sensor Networks Using Tree Based Routing Protocol.
Chapter
7. An
Energy-Efficient Distributed Unequal Clustering Approach For Lifetime
Maximization In Wireless Sensor Network.
Chapter
8. An Effective Big-Data
And Blockchain [ Bd-Bc] Based Decision Support Model For Sustainable
Agriculture System.
Chapter
9. An Sdn Based Strategy For Reliable Data
Transmission In Mobile Wireless Sensor Networks.
Chapter
10. Different
Aspects Of 5G Wireless Network - An Overview.
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11. Intelligent
Systems For Volumetric Feature Recognition From Cad Mesh Models.
Chapter
12.
Factors Affecting A Mobile Learning System: A Case Study.
Chapter
13.
Document Similarity Approach Using Grammatical Linkages With Graph
Databases.
Chapter
14. Missing Data Handling By Mean Imputation
And Statistical Analysis.
Chapter
15. Task Identification System For Elderly
Paralysed Patients Using Electrooculography And Neural Networks.
Chapter
16.
Software Defined Networking (Sdn) Architecture For Smart Trashcan Using Iot.-
Chapter
17. Modified K- Nearest Neighbour Fuzzy Classifier Using Group
Prototypes And Its Application To Skin Segmentation.
Chapter
18. Enhancing
Cooperative Spectrum Sensing In Flying Cell Towers For Disaster Management
Using Convolutional Neural Networks.
Chapter
19. Emoticons And Their Effects
On Sentiment Analysis Of Twitter Data.
Chapter
20. Prediction Of Customer
Churn Using Machine Learning.
Chapter
21. Prediction Of Crop Yield Using
Fuzzy-Neural System.
Chapter
22. Speed Estimation And Detection Of Moving
Vehicles Based On Probabilistic Principal Component Analysis And New Digital
Image Processing Approach.
Chapter
23. A Posture Recognition System For
Assisted Self-Learning Of Yoga By Cognitive Impaired Older People For The
Prevention Of Falls.
Chapter
24. Improved Ufhlsnn (Iufhlsnn) For
Generalized Representation Of Knowledge And Its Cpu Parallel Implementation
Using Openmp.
Chapter
25. Performance Evaluation Of Multihop Multibranch Df
Relaying Cooperative Wireless Network.
Chapter
26. Predicting Property
Prices A Universal Model.
Chapter
27. Facial Based Human Age Estimation
Using Deep Belief Network..
Chapter
28. Randomized Agent Based Model For
Mobile Customer Retention Behaviour Prediction.
Chapter
29. Keyword-Based
Approach For Detecting Civil Unrest Events From Online Social Media.
Chapter
30. Socioeconomic Status Classification Of Geographic Regions In Sri Lanka
Through Anonymised Call Detail Records.
Chapter
31. Hand Gesture Based
Human-Computer Interaction Using Arduino.
Chapter
32. An Automatic Diabetes
Risk Assessment System Using Iot Cloud Platform.
Chapter
33. Message And
Image Encryption Embedding Data To Gf(2M) Elliptic Curve Point For Nodes In
Wireless Sensor Networks.
Chapter
34. Crack Detection In Welded Images
A Comprehensive Survey.
Chapter
35. An Effective Hybridized Classifier
Integrated With Homomorphic Encryption To Enhance Big Data Security.
Chapter
36. Ai Powered Analytics App For Visualizing Accident-Prone Areas.
Chapter
37. Iot Based Autonomous Inventory Management For Warehouses.
Chapter
38.
Internal Repeats Of Human Organs On Cloud.
Chapter
39. Bitcoin Prediction
And Timeseries Analysis.
Chapter
40. Smart Active Helmet.
Dr. Anandakumar Haldorai, Professor (Associate) and Research Head in Department of Computer Science and Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamilnadu, India. He has received his Masters in Software Engineering from PSG College of Technology, Coimbatore and PhD in Information and Communication Engineering from PSG College of Technology under, Anna University, Chennai. His research areas include Big Data, Cognitive Radio Networks, Mobile Communications and Networking Protocols. He has authored more than 82 research papers in reputed International Journals and IEEE conferences. He has authored 7 books and many book chapters with reputed publishers such as Springer and IGI. He is editor of Inderscience IJISC and served as a reviewer for IEEE, IET, Springer, Inderscience and Elsevier journals. He is also the guest editor of many journals with Elsevier, Springer, Inderscience, etc. He has been the General Chair, Session Chair, and Panelist in several conferences. He is senior member of IEEE, IET, ACM and EAI research group.
Dr. Arulmurugan Ramu is a Professor, Department of Computer Science and Engineering, Presidency University, Bangalore, India. His research focuses on the automatic interpretation of images and related problems in machine learning and optimization. Arulmurugans main research interest is in vision, particularly high-level visual recognition. In computer vision, Arulmurugans interests include image and video classification, understanding and retrieval. Some of the most recent work in his lab relates to fundamental technological problems related to large-scale data, machine learning and artificial intelligence. He is author of more than 25 papers in major computer vision and machine learning conferences and journals. From 2011 to 2015 he was researcher fellow at the Anna University. He is the recipient of the PhD degrees in Information and Communication Engineering from the Anna University at Chennai in 2015, M.Tech in Information Technology Anna University of Technology in 2009 respectively and of the B.Tech degree in Information Technology by the Aruani Engineering College in 2007.
Dr. Sudha Mohanram, has graduated from Government College of Engineering, Salem and has obtained her Masters in Engineering from Coimbatore Institute of Technology. She has completed her PhD in Electrical Engineering in Anna University Chennai in the year 2010. She started her teaching profession as a Lecturer in Government College of Technology, Coimbatore. She possesses 20 years of teaching experience. When she was about 13 years into teaching profession, her family founded Sri Eshwar College of Engineering in 2008. She has been playing the role of Secretary till 2011 and became the Principal of the institution in 2011. She has steered the institution to be one of the most sought after institutions in Coimbatore, within a short span of time through its laudable achievement in Academicexcellence and Placement. She has published many papers in leading journals. She is a member of IEEE and EAI research group.
Dr. Chee-Onn Chow received his Bachelor of Engineering (Hons) and Master of Engineering Science degrees from University of Malaya, Malaysia in 1999 and 2001, respectively. He received his Doctorate of Engineering from the Tokai University, Japan in 2008. He joined the Department of Electrical Engineering as tutor in 1999, and subsequently been offered a lecturer position in 2001. He is currently an Associate Professor in the same department since 2015. His research interests include various issues related to wireless communications. He is a Chartered Engineer (IET, UK), a Professor Engineer (BEM, Malaysia) and a Senior Members of IEEE.
