http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Intelligent Computing and Innovation on Data Science
1 online resource (XXXIII, 803 pages 426 illustrations, 258 illustrations in color.)
This book covers both basic and high-level concepts relating to the intelligent computing paradigm and data sciences in the context of distributed computing, big data, data sciences, high-performance computing and Internet of Things. It is becoming increasingly important to develop adaptive, intelligent computing-centric, energy-aware, secure and privacy-aware systems in high-performance computing and IoT applications. In this context, the book serves as a useful guide for industry practitioners, and also offers beginners a comprehensive introduction to basic and advanced areas of intelligent computing. Further, it provides a platform for researchers, engineers, academics and industrial professionals around the globe to showcase their recent research concerning recent trends. Presenting novel ideas and stimulating interesting discussions, the book appeals to researchers and practitioners working in the field of information technology and computer science.
Comprehensive Guide to Implementation of Data Warehouse in Education -- Computational Biology Tool Towards Studying the Interaction Between Azadirachtin Plant Compound with Cervical Cancer Proteins -- Intelligent Agent Based Organization For Studying the Big Five Personality Traits -- Automatic Pruning of Rules Through Multi-Objective Optimization - A Case Study With a Multi-Objective Cultural Algorithm -- Knowledge Genesis And Dissemination: Impact On Performance In Information Technology Services -- Artificial Intelligence Based Load Balancing In Cloud Computing Environment: A Study -- Implementation of Statistical Data Analytics in Data Science Life Cycle -- A Big Data Analytics-Based Design for Viable Evolution of Retail Sector -- Document Content Analysis Based on Random Forest Algorithm -- Sensing The Prostatectomy in Neuroendocrine Metastatic Active Surveillance in Data Mining Techniques -- Work Load Forecasting Based On Big Data Characteristics In Cloud Systems -- Phrase Extraction Using Pattern Based Bootstrapping Approach -- IOT Based Trash Collection Bin Using Arduino.
edited by Sheng-Lung Peng, Le Hoang Son, G. Suseendran, D. Balaganesh.
Lecture Notes in Networks and Systems, 118