PERHAPS A GIFT VOUCHER FOR MUM?: MOTHER'S DAY

Close Notification

Your cart does not contain any items

$265.95

Paperback

Not in-store but you can order this
How long will it take?

QTY:

English
Academic Press Inc
23 October 2020
Intelligent Environmental Data Monitoring for Pollution Management discusses evolving novel intelligent algorithms and their applications in the area of environmental data-centric systems guided by batch process-oriented data. Thus, the book ushers in a new era as far as environmental pollution management is concerned. It reviews the fundamental concepts of gathering, processing and analyzing data from batch processes, followed by a review of intelligent tools and techniques which can be used in this direction. In addition, it discusses novel intelligent algorithms for effective environmental pollution data management that are on par with standards laid down by the World Health Organization.

Edited by:   , , , , , , , , , , , , , , ,
Imprint:   Academic Press Inc
Country of Publication:   United States
Dimensions:   Height: 234mm,  Width: 191mm, 
Weight:   770g
ISBN:   9780128196717
ISBN 10:   0128196718
Series:   Intelligent Data-Centric Systems
Pages:   344
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active
1. Batch Adsorption Process in Water Treatment 2. Removal of heavy metals from industrial effluents by using Biochar 3. Nanoparticles: A new tool for control of mosquito larvae 4. Biosorption driven green technology for the treatment of heavy metal (loids) contaminated effluents 5. A Comprehensive Review of Glyphosate Adsorption with Factors Influencing Mechanism: Kinetics, Isotherms, Thermodynamics Study 6. Dyes and their removal technologies from wastewater 7. An Intelligent Estimation Model for Water Quality Parameters Assesment at Periyakulam Lake, South India 8. Recent Trends in Air Quality Prediction: An Artificial Intelligence Perspective 9. Optimisation of absorption process for exclusion of Carbaryl from aqueous environment using natural adsorbents 10. Artificial Neural Network: An Alternative Approach for Assessment of Biochemical Oxygen Demand of the Damodar River, West Bengal, India 11. Co-design to improve IAQ awareness in classrooms 12. Data Perspective on Environmental Mobile Crowd Sensing 13. A Survey of Adsorption Process Parameter Optimization related to Degradation of Environmental Pollutants

Siddhartha Bhattacharyya is a Senior Researcher in the Faculty of Electrical Engineering and Computer Science of VSB Technical University of Ostrava, Czech Republic. He is also serving as the Scientific Advisor of Algebra University College, Zagreb, Croatia. Prior to this, he served as the Principal of Rajnagar Mahavidyalaya, Rajnagar, Birbhum. He was a professor at CHRIST (Deemed to be University), Bangalore, India, and also served as the Principal of RCC Institute of Information Technology, Kolkata, India. He is the recipient of several coveted national and international awards. He received the Honorary Doctorate Award (D. Litt.) from the University of South America and the SEARCC International Digital Award ICT Educator of the Year in 2017. He was appointed as the ACM Distinguished Speaker for the tenure 2018-2020. He has been appointed as the IEEE Computer Society Distinguished Visitor for the tenure 2021-2023. He has co-authored six books, co-edited 75 books, and has more than 300 research publications in international journals and conference proceedings to his credit. Dr. Naba Kumar Mondal is a Professor in Environmental Science, Department of Environmental Science, The University of Burdwan, Burdwan, India. He completed his post graduate in Chemistry from Department of Chemistry and doctorate degree in Environmental Science from Department of Environmental Science, The University of Burdwan. He has published his research work in more than 200 reputed international and national journals. His primary research interest are Adsorption Chemistry by low cost adsorbents, Water quality degradation and management in Arsenic and Fluoride affected areas of West Bengal, Indoor Air Pollution and Human Health, Nanotechnology and Mosquito control, Mobile tower radiation and Human health, and Teacher Education. Dr. Mondal has delivered several invited talks and key note addresses in national and international conferences of high repute. Jan Platos received a Ph.D. in computer science in 2010. He became a Full professor in 2021 at the Department of Computer Science. Since 2021, he has been Dean of the Faculty of Electrical Engineering and Computer Science, VSB-TUO. He has co-authored more than 240 scientific articles published in proceedings and journals. His primary fields of interest are machine learning, artificial intelligence, industrial data processing, text processing, data compression, bioinspired algorithms, information retrieval, data mining, data structures, and data prediction. Vaclav Snasel's research and development experience includes over 25 years in the Industry and Academia. He works in a multi-disciplinary environment involving artificial intelligence, multidimensional data indexing, conceptual lattice, information retrieval, semantic web, knowledge management, data compression, machine intelligence, neural network, web intelligence, data mining and applications to various real-world problems. He has authored/co-authored several refereed journal/conference papers and book chapters. In 2003 he became a visiting scientist in the Institute of Computer Science, Academy of Sciences of the Czech Republic. Since 2003 he has been vice-dean for Research and Science at Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Czech Republic. He has been a full professor since 2006. Before turning into a full time academic, he was working with industrial companies where he was involved in different industrial research and development projects for nearly 8 years. He received Ph.D. degree in Algebra and Geometry from Masaryk University, Brno, Czech Republic and a Master of Science degree from Palacky University, Olomouc, Czech Republic. Pavel Krömer, Ph.D. graduated in Computer Science at the Faculty of Electrical Engineering and Computer Science (FEECS) of VŠB-Technical University of Ostrava. He worked as an analyst, developer, and trainer in a private company between 2005 and 2010. Since 2010, he has worked at the Department of Computer Science, FEECS of VŠB-Technical University of Ostrava. In 2014, he was a Postdoctoral Fellow at the University of Alberta. In 2015, he was awarded the title Assoc. Professor of Computer Science. He was Researcher at the IT4Innovations (National Supercomputing Center) between 2011 and 2016 and has been a member of its scientific council since February 2017. Since 2017, he has been the Vice Dean for External Affairs at FEECS. Since 2018, he is a Senior Member of the IEEE. In his research, he focuses on computational intelligence, information retrieval, data mining, machine learning, soft computing and real-world applications of intelligent methods. In this field, he has also contributed to a number of major conferences organized by the IEEE and ACM.

See Also