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Studies in Big Data

Big Data in Engineering Applications

Editors: Roy, S.S., Samui, P., Deo, R., Ntalampiras, S. (Eds.)

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  • Reviews exhaustively the key recent applications of Big Data in engineering areas
  • Includes chapters related to the application of advanced machine learning techniques in Big Data environment
  • Treats both theoretical and practical aspects of Big Data applications in various engineering sectors
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eBook 118,99 €
price for India (gross)
  • ISBN 978-981-10-8476-8
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
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  • Immediate eBook download after purchase
Hardcover 149,99 €
price for India (gross)
  • ISBN 978-981-10-8475-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover 149,99 €
price for India (gross)
  • ISBN 978-981-13-4162-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book


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. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. 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.

About the authors


Sanjiban Sekhar Roy is working as an associate professor in School of Computer Science and Engineering, VIT University. He joined this institute in  the year 2009 as an assistant professor. He holds a B.E degree in Information Technology from the University of North Bengal and an M.Tech degree in Computer Science and Engineering from VIT University. He qualified GATE examination, which is a national level engineering entrance test conducted by IITs and IISC. Sanjiban carried out his nine months M.Tech project as an intern student in Indian Institute of Technology (IIT), Kharagpur, India. In the year 2016 he completed his Ph.D. degree in Computer science and Engineering from VIT University. His research interests include machine learning, data mining, and pattern recognitions. He has to his credit around 33 articles published in international journals and international conferences and one edited book with Elsevier publisher. He is an editorial board member of “International Journal of Advanced Intelligent Paradigms”, Inderscience and reviewer for many international journals.

Pijush Samui is working as an associate professor in civil engineering department at NIT Patna, India. He graduated in 2000, with a B.Tech. in Civil Engineering from Indian Institute of Engineering Science and Technology, Shibpur, India. He received his M.Sc. in Geotechnical Earthquake Engineering from Indian Institute of Science, Bangalore, India (2004). He holds a Ph.D. in Geotechnical Earthquake Engineering
(2008) from Indian Institute of Science, Bangalore, India. He was a postdoctoral fellow at University of Pittsburgh (USA) (2008-2009) and Tampere University of Technology (Finland) (2009- 2010). At University of Pittsburgh, he worked on design of efficient tool for rock cutting and application of Support Vector Machine (SVM) in designing of geostructure. At Tampere University of Technology, he worked on design of railway embankment, slope reliability and site characterization. In 2010, Dr. Pijush joined in the Center for Disaster Mitigation and Management at VIT University as an Associate Professor. He was promoted to a Professor in 2012. Dr. Pijush’s research focuses on the application of Artificial Intelligence for designing civil engineering structure, design of foundation, stability of railway embankment, reliability analysis, site characterization, earthquake engineering and BIG data. Dr. Pijush is the recipient of the prestigious CIMO fellowship (2009) from Finland, for his integrated research on the design of railway embankment. He was awarded Shamsher Prakash Research Award (2011) by IIT Roorkee for his innovative research on the application of Artificial Intelligence in designing civil engineering structure. He was selected as the recipient of IGS Sardar Resham Singh Memorial Award – 2013 for his innovative research on infrastructure project. He was elected Fellow of International Congress of Disaster Management in 2010. He served as a guest in disaster advance journal.He also serves as an editorial board member in several international journals. Dr. Pijush is active in a variety of professional organizations including the Indian Geotechnical Society, Indian Science Congress, Institution of Engineers, World federation of Soft Computing, and Geotechnical Engineering for Disaster Mitigation and Rehabilitation. He has organized numerous workshops and conferences on the applications of artificial intelligence in civil engineering design. As per google scholar, his citation is 787 and H index=17. As per Scopus his citation is 522 and H index=14.

Dr Ravinesh Deo, an Environmental Modelling Expert, has a PhD from The University of Adelaide (Australia), Master of Science (University of Canterbury, New Zealand), Bachelor of Science (University of the South Pacific, Fiji) and Graduate Certificate in Tertiary Teaching and Learning (University of Southern Queensland, Australia). Currently Dr Deo works as Senior Lecturer at University of Southern Queensland and Associate Professor at Chinese Academy of Sciences (Cold and Arid Regions Environmental and Engineering Research Institute, Lanzhou). Dr Deo has also worked Senior Research Fellow (McGill University, Canada), Research Academic in Wind Engineering (The University of Sydney, Australia), Visiting Research Fellow (University of Adelaide, Australia) and Postdoctoral Research Fellow (The University of Queensland), Principal Research Scientist at Queensland Climate Change Centre of Excellence and as Associate Lecturer (University of the South Pacific). Dr Deo won high competitive fellowships and grants including internationally-competitive Chinese Academy of Science Presidential Fellowship and nationally-competitive Endeavour Executive Fellowship that funded Visiting Professor positions in China and Europe. He was awarded the University’s Publication Excellence Award, Head of Department Research Award and University Gold Medal for Academic Excellence. Dr Deo has served as Editorial Board Member of journals, chaired on "IEEE ICMLA Special Session on Machine Learning Algorithms for Environmental Applications, serves as Committee Member of IEEE and other international conference. Dr Deo works with international researchers from Australia, Algeria, Bangladesh, Canada, India, Turkey, Spain, Iran, Malaysia, China, Africa, Korea and United States. Dr Deo’s Google scholar profile has more than 870 citations with H Index of 14, and he has published more than 50 high-impact journal and conference papers. Dr Deo supervises a significant load of PhD and Masters Projects in machine learning applications, health, climate, agriculture, environment, engineering and renewable energy sectors.

Stavros Ntalampiras received the engineering and Ph.D. degrees from the Department of Electrical and Computer Engineering, University of Patras, Greece, in 2006 and 2010, respectively. Subsequently, he joined the System Architectures Group of the Department of Electronics and Information at Politecnico di Milano as a post-doc researcher. From May 2013 to March 2015, he was conducting research with the Joint Research Center of the European Commission. Since April 2015 he is a Politecnico di Milano senior research fellow carrying out didactic and research activities. He has authored over 50 publications in peer-reviewed journals and conferences with more than 450 citations. He is a member of the IEEE Computational Intelligent Society Task Force on Computational  Audio Processing, while his current research interests include content-based signal processing, fault diagnosis, audio pattern recognition, cyber physical systems, and critical infrastructure protection.


Table of contents (18 chapters)

Table of contents (18 chapters)
  • Applying Big Data Concepts to Improve Flat Steel Production Processes

    Pages 1-20

    Brandenburger, Jens (et al.)

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

    Pages 21-39

    Zheng, Minrui (et al.)

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

    Pages 41-63

    Vera-Baquero, Alejandro (et al.)

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

    Pages 65-81

    Skënduli, Marjana Prifti (et al.)

  • Concepts of HBase Archetypes in Big Data Engineering

    Pages 83-111

    Saxena, Ankur (et al.)

Buy this book

eBook 118,99 €
price for India (gross)
  • ISBN 978-981-10-8476-8
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 149,99 €
price for India (gross)
  • ISBN 978-981-10-8475-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover 149,99 €
price for India (gross)
  • ISBN 978-981-13-4162-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Big Data in Engineering Applications
Editors
  • Sanjiban Sekhar Roy
  • Pijush Samui
  • Ravinesh Deo
  • Stavros Ntalampiras
Series Title
Studies in Big Data
Series Volume
44
Copyright
2018
Publisher
Springer Singapore
Copyright Holder
Springer Nature Singapore Pte Ltd.
eBook ISBN
978-981-10-8476-8
DOI
10.1007/978-981-10-8476-8
Hardcover ISBN
978-981-10-8475-1
Softcover ISBN
978-981-13-4162-5
Series ISSN
2197-6503
Edition Number
1
Number of Pages
VI, 384
Number of Illustrations
47 b/w illustrations, 88 illustrations in colour
Topics