BOOK : Big Data in Engineering Applications,by SPRINGER

BOOK : Big Data in Engineering Applications,by SPRINGER


************************************************************************ BOOK : Big Data in Engineering Applications, SPRINGER. Editors: Roy, S.S., Samui, P., Deo, R., Ntalampiras, S. (Eds.). *************************************************************************
Dear All,
The most anticipated book titled***Big Data in Engineering Applications*** has been published by Springer, recently.#
This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. The book is a useful reference for graduate students, researchers, and scientists interested in exploring the potential of Big Data in the application of engineering areas.
Order your book from #Springer or #Amazon https://www.springer.com/in/book/9789811084751
https://www.amazon.com/Big-Data-Engineering-Applications-Studies/dp/9811084750

Chapters 

Applying Big Data Concepts to Improve Flat Steel Production Processes

        Brandenburger, Jens (et al.)
Pages 1-20

Parallel Generation of Very High Resolution Digital Elevation Models: High-Performance Computing for Big Spatial Data Analysis

        Zheng, Minrui (et al.)
Pages 21-39

Big-Data Analysis of Process Performance: A Case Study of Smart Cities

       Vera-Baquero, Alejandro (et al.)
Pages 41-63

Implementing Scalable Machine Learning Algorithms for Mining Big Data: A State-of-the-Art Survey

       Skënduli, Marjana Prifti (et al.)
Pages 65-81

Concepts of HBase Archetypes in Big Data Engineering

      Saxena, Ankur (et al.)
Pages 83-111

Scalable Framework for Cyber Threat Situational Awareness Based on Domain Name Systems Data Analysis

     Vinayakumar, R. (et al.)
Pages 113-142

Big Data in HealthCare

       Ramírez, Margarita Ramírez (et al.)
Pages 143-159

Facing Up to Nomophobia: A Systematic Review of Mobile Phone Apps that Reduce Smartphone Usage

      Bychkov, David (et al.)
Pages 161-171

A Fast DBSCAN Algorithm with Spark Implementation

      Han, Dianwei (et al.)
Pages 173-192

Understanding How Big Data Leads to Social Networking Vulnerability

     Mansour, Romany F.
Pages 193-201

Big Data Applications in Health Care and Education

      Tripathy, B. K.
Pages 203-219

BWT: An Index Structure to Speed-Up Both Exact and Inexact String Matching

     Chen, Yangjun (et al.)
Pages 221-264

Traffic Condition Monitoring Using Social Media Analytics

        Adetiloye, Taiwo (et al.)
Pages 265-278

Modelling of Pile Drivability Using Soft Computing Methods

        Zhang, Wengang (et al.)
Pages 279-301

Three Different Adaptive Neuro Fuzzy Computing Techniques for Forecasting Long-Period Daily Streamflows

      Kisi, Ozgur (et al.)
Pages 303-321

Prediction of Compressive Strength of Geopolymers Using Multi-objective Feature Selection

         Garanayak, Lasyamayee (et al.)
Pages 323-346

Application of Big Data Analysis to Operation of Smart Power Systems

        Madadi, Sajad (et al.)
Pages 347-362

A Structural Graph-Coupled Advanced Machine Learning Ensemble Model for Disease Risk Prediction in a Telehealthcare Environment

        Lafta, Raid (et al.)
Pages 363-384



Link: BOOK : Big Data in Engineering Applications,by SPRINGER