Data Science and Big Data Analytics (häftad)
Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
406
Utgivningsdatum
2018-08-02
Upplaga
1st ed. 2019
Förlag
Springer Verlag, Singapore
Medarbetare
Yang, Xin-She / Unal, Aynur
Illustrationer
100 Tables, color; 95 Illustrations, color; 57 Illustrations, black and white; XXIV, 406 p. 152 illu
Dimensioner
234 x 156 x 22 mm
Vikt
604 g
Antal komponenter
1
Komponenter
1 Paperback / softback
ISBN
9789811076404
Data Science and Big Data Analytics (häftad)

Data Science and Big Data Analytics

ACM-WIR 2018

Häftad Engelska, 2018-08-02
1769
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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.
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Övrig information

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)

Innehållsförteckning

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 machi