Data Science and Big Data Analytics ACM-WIR 2018

This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issues pertaining to big data analysis using computational intelligence techniques, and the conjectural elements are supported by simulation and modelling applications to help address real-world problems. An extensive bibliography is provided at the end of each chapter. Further, the main content is supplemented by a wealth of figures, graphs, and tables, offering a valuable guide for researchers in the field of big data analytics and computational intelligence.

A Study of the Correlation between Internet Addiction and Aggressive Behavior Among the Namibian University Students

An efficient model for outlier detection in time series dataset using clustering approach

Genetic Algorithm Approach for Optimization of Biomass Estimation at LiDAR

E-ALIVE: An Integrated Platform Based on Machine Learning Techniques to Aware and Educate Common People with the Current Statistics of Maternal and Child Health Care

An Effective TCP’s Congestion Control Approach for Cross Layer Design in MANET

A Study on Applying Agile Methodology to Manufacturing Industry Cloud Applications

Baron-Cohen Model based Personality Classification using Ensemble Learning

Analysis of Routing Protocols for Large Scale Multihop Multirate MANETs

Review on Internet Traffic Sharing using Markov Chain Model in Computer Network

Protein Sequence of Dengue Virus Classification and Secondary Structure Prediction using Random Forest Classifier

Anomaly detection using Dynamic Sliding Window in Wireless Body Area Networks

Scalable Privacy preservation in Big Data with Cloud Service Access

Effective Healthcare Services by IoT based Model of Voluntary Doctors

Multi Layer Architectures for SQLI Detection and Prevention in Web Application Development

Emotional State Recognition with EEG signals using Subject Independent Approach

Development of Early Prediction Model for Epileptic Seizures

Research Issue in data Anonymization in Electronic Health Service: A survey

Prediction of Cervical Cancer based on the life style, habits and diseases using Regression Analysis framework

Novel outlier detection by integration of clustering and classification 

A Study on Benefits of Big Data for Retail Industry

Protection of User Information by using Modified Data Copy Technique in Data Mining

Performance Analysis of Traffic at Intersection using Direction Based Clustering in VANET

Load Balancing using Amazon Cloud Services

A Review of Wireless Charging Nodes in Wireless Sensor Networks

Leeway of Lean concept to optimize Bigdata in manufacturing industry: An exploratory review

NeuroFeedback Guided Learning Style Adaptability Derived from EEG Sensors

Monitoring Public Participation in Multi-Lateral Initiatives using Social Media Intelligence

An efficient Context-aware Music Recommendation based on Emotion and Time Context

Locating and Detecting Nipple for Pornographic Image Identification

Implementation of Improved Energy Efficient FIR Filter using Reversible Logic

A Study on benefits of Big data for healthcare sector of India

Handling Uncertainty in Linguistics using Probability Theory

Review of Quality of Service based Techniques in Cloud Computing

Skyline Computation for Big Data

Available Energy Aware Multipath Routing For Reliable Service Discovery in MANET

Human Face Detection Enabled Smart Stick for Visually Impaired People

Web Based Service Recommendation System by Considering User Requirements

Optimal Energy Conservation for Route Selection to improve in MANET

Unsupervised Machine Learning for Clustering the Infected Leaves based on the Leaf-colours

Real Time Big Data Analysis Architecture and Application

Missing Value Imputation in Medical Records for Remote Healthcare

Reliable Data Discovery with Two Ray Ground Way on DSR Routing in MANET

Secure vehicular communication using Road side unit (RSU) trust management scheme

Recommendation Framework for Diet and Exercise based on Clinical Data: A Systematic Review

Predictive Models for Recommanding Restaurent System by users own Preference

Security Assessment of SAODV Protocols in Mobile Adhoc Networks

Attack Detection and its Analysis in DTN Mobile Ad-hoc network

Secure Sum Computation using Homomorphic Encryption

Traffic Analysis in Location Base Routing System in MANET

Automated Workload management using machine learning

A survey on Link Recovery in Wireless Mesh Network using resilience scheme

Multi User Detection in Wireless Networks Using Decision Feedback Signal Cancellation

ANN Based Predictive State Modelling of Finite State Machines

Deep dive exploration of mixed reality in the world of Big Data

Dr. Durgesh Kumar Mishra? is a Professor (CSE) and Director of the Microsoft Innovation Centre at Sri Aurobindo Institute of Technology, Indore, India and visiting faculty at IIT-Indore. He has 24 years of teaching and 12 years of research experience. He has published more than 90 papers in refereed international/national journals and conferences including IEEE, ACM conferences and organized many conferences as General Chair and Editor. He is a Senior Member of the IEEE, CSI, ACM, Chairman IEEE MP Subsection, IEEE Computer Society Bombay Chapter. At present he is Chairman of CSI Division IV Communication at the National Level and ACM Chapter Rajasthan and MP State. 

Prof. ?Xin-She Yang is an Associate Professor of Simulation  Modelling at Middlesex University, London. Prof. Yang’s main interests are applied mathematics, algorithm development,?computational intelligence, engineering optimisation, mathematical modelling, optimisation and swarm intelligence. His research projects have been supported by the National Measurement Office, BIS, Southwest Development Agency (UK), Euro Met, EPSRC, NPL, and the National Science Foundation of China. He is EEE CIS Task Force Chair of the BIKM, Technical Committee of Computational Finance and Economics of IEEE Computational Intelligence Society; Advisor to the International Journal of Bio-Inspired Computation; Editorial Board Member of Elsevier’s Journal of Computational Science; and Editor-in-Chief of the International Journal of Mathematical Modelling and Numerical Optimisation. 

 Dr. Aynur Unal is a Strategic Adviser & Visiting Full Professor at the IIT Guwahati, India. She has created a product-focused engineering program using the cloud-based infrastructure. Her main interests include Ecologically and socially responsible engineering, Zero waste Initiative and Sustainable Green Engineering. Her research focuses on both rural and urban sustainable development, renewable energy, solar towers and pumps. She has taught at Stanford University, and worked in Silicon Valley to develop products for data mining from big data (Triada’s Athena I & II), Collaborative Design and Manufacturing, secure and private communication, and collaboration software platforms (Amteus, listed in LSE AIM)