Proceeding of International Conference on Computational Science and Applications

Prof. Subhash Bhalla joined the faculty of the School of Computer and Systems Sciences at Jawaharlal Nehru University (JNU), New Delhi, in 1986. He was a Visiting Scientist at Sloan School of Management, Massachusetts Institute of Technology (MIT), USA (1987–1988). He is a member of the Computer Society of IEEE and SIGMOD of ACM. He currently works at the Department of Computer Software at the University of Aizu. He has lectured at numerous companies on conducting feasibility studies and adopting modern techniques. He has received several research grants, and his research interests include creating user interfaces for web users and transaction management systems for mobile computing, transaction management and algorithmic designs for distributed real-time systems. He is also pursuing performance evaluation and modelling of distributed algorithms. Dr. Peter Kwan is Honorary Principal and Chief Advisor at Hong Kong College of Engineering. Previously, he also worked at Queen Mary Hospital and Wheelock Properties Ltd. He completed his B.Sc.Eng. at University of Glasgow in 1984; M.B.A. at the University of Strathclyde in 1990; and Ph.D. at the University of Newcastle in 2008. He has received numerous awards and honors for his academic achievements. Dr. Mangesh V. Bedekar received his Ph.D. in Computer Science and Engineering from BITS Pilani, India. Prior to the Ph.D. program, he graduated from SSGMCE, Shegaon and completed his master’s at BITS Pilani, India. He currently heads the School of Computer Engineering and Technology at MIT-WPU. His primary research interests include web data mining, web personalization, user interface design, user interface improvements, browser customization, affective computing and information visualization. He has authored numerous national and international publications. Dr. Rashmi Phalnikar is an Associate Professor at School of Computer Engineering and Technology at MIT-WPU, Pune. She completed her Ph.D. in Computer Engineering at SV NIT Surat. Her research interests include data science and analysis and software engineering. She has published more than 40 research papers in international journals and conferences and has completed a research consultancy project. Ms. Sumedha Sirsikar teaches at School of Computer Engineering and Technology at MIT-WPU, Pune. She has published 38 research papers in various renowned journals and 26 papers at international conferences. Her research interests include of computer networks and security and wireless sensor networks.

• Empathic Diary based on Emotion Recognition using Convolutional Neural Network.- Detection of Ransomware attack: A Review.- Room Service Robot.- Comparative Analysis For An Optimized Data Driven System.- Fake Email & Spam Detection: User Feedback with Naives Bayesian Approach.- C-ASFT: Convolutional Neural Networks based Anti-Spam Filtering Technique.- Cognitive Control of Robotic-Rehabilitation Device using Emotiv EEG Headset.- Non-Stationary Data Stream Analysis: State-of-Art Challenges and Solutions.- Parallel Job Execution To Minimise Overall Execution Time And Individual Schedule Time Using Modified Credit Based Firefly Algorithm.- Novel Non-Invasive Approach for Diagnosis of Medical Disorders based on De Broglie’s Matter Waves & Water Memory.- Tamper Detection in Cassandra and Redis Database- A Comparative Study.- Tamper Detection In MongoDB And CouchDB Database.- Recommender System in eLearning: A Survey.- A Realistic Mathematical Approach for Academic Feedback Analysis System.- Fake News classification on Twitter using Flume, N-gram analysis and Decision Tree machine learning technique.- Swarm Intelligence Based Systems: A Review.- Internet of Things: A Survey on Distributed Attack Detection using Deep Learning Approach.- Precise Orbit and Clock Estimation of Navigational Satellite using Extended Kalman Filter Applicable to IRNSS NavIC Receiver Data.- Effects of Color on Visual Aesthetics Sense.- Performance Evaluation of Video Segmentation Metrics.- Suspicious Activity Detection Using Live Video Analysis.- A Review on Using Dental Images as A Screening Tool for Osteoporosis.- An expert diagnosis system for Parkinson's disease using Bagging based Ensemble of Polynomial Kernel SVMs with Improved GA-SVM Features Selection.- Case Study: Use of AWS Lambda for Building a Serverless Chat Application.- Detection and Classification of Diabetic Retinopathy Using Alex Net architecture of Convolutional Neural Networks.- Contextual Recommendation and Summary of Enterprise Communication.- Cybersecurity and Communication Performance Improvement of Industrial-IoT Network Towards Success of Machine Visioned IR 4.0 Technology.- Dynamic Load Balancing in Software Defined Networks using Machine Learning.- Analysis and Comparison of Timbral Audio Descriptors with Traditional Audio Descriptors Used in Automatic Tabla Bol Identification of North Indian Classical Music.- Sentiment Analysis on Aadhaar for Twitter Data – A Hybrid Classification Approach.- Song Recommendation System Using Hybrid approach.- Arrhythmia Detection using ECG Signal: A Survey.- Towards Designing the Best Model for Classification of Fish Species using Deep Neural Networks.- A Study on Attribute Based Predictive Modelling for Personal Systems & Components A Machine Learning & Deep Learning Based Predictive Framework.- Text Categorization Using Sentiment Analysis.- Automated Real Time E-mail Classification System based on Machine Learning.- Smart Detection Of Parking Rates And Determining The Occupancy.- Deep Learning-based Approach to classify Praise’s or Complaint’s from Customer Reviews.- Psychological Behavioral Analysis of Defaulter Students.- TNM Cancer Stage Detection from Unstructured Pathology Reports of Breast Cancer Patients.- Restructuring of Object Oriented Software System using Clustering Techniques.- Analysis of System Logs for Pattern Detection and Anomaly Prediction.- Phishing Detection: Malicious and Benign Websites Classification using Machine Learning Techniques.- Automation of Paper Setting and Identification of Difficulty Level of Questions and Question Papers.