Intelligent Technologies: Concepts, Applications, and Future Directions
Published on 21. May 2022
XIII, 335 pages
978-981-19-1021-0 (ISBN)
Description
This book discusses automated computing systems which are mostly powered by intelligent technologies like artificial intelligence, machine learning, image recognition, speech processing, cloud computing, etc., to perform complex automated tasks which are not possible by traditional computing systems. The chapters are extended version of research works presented at first Ph.D. Research Symposium in various advanced technologies used in the field of computer science. This book provides an opportunity for the researchers to get ideas regarding the ongoing works that help them in formulating problems of their interest. The academicians can also be benefited to know about the current research trends that smooth the way to guide their students to carry out research work in the proper direction. The industry people will be also facilitated to know about the current advances in research work and materialize the research work into industrial applications.
More details
Series
Language
English
Place of publication
Singapore
Singapore
Publishing group
Springer Singapore
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
XIII, 335 p. 156 illus., 112 illus. in color.
File size
9,94 MB
ISBN-13
978-981-19-1021-0 (9789811910210)
DOI
10.1007/978-981-19-1021-0
Schweitzer Classification
Other editions
Additional editions
Satya Ranjan Dash | Manas Ranjan Lenka | Kuan-Ching Li
Intelligent Technologies: Concepts, Applications, and Future Directions
Book
05/2022
Springer
€192.59
Shipment within 3-4 weeks
Persons
Satya Ranjan Dash
is currently working as an associate professor at KIIT University, India. His current research includes epileptic seizure detection based on EEG signal through spiking neural network (SNN), classification of schizophrenia patients from EEG and fMRI using SNN and SSN, fetal heart rate signals classification through extreme learning machine (ELM), mammogram analysis with local binary pattern (LBP), and generative adversarial network (GAN) model.
Manas Ranjan Lenka is working as an assistant professor in KIIT University and has around 17 years of experience, out of which 9 years of industry experience in telecom software developments and 8 years of teaching experience. His current research topic is wireless sensor networks.
Kuan-Ching Li is currently a professor in the Department of Computer Science and Information Engineering at the Providence University, Taiwan. Dr. Li is the editor-in-chief of technical publications in International Journal of Computational Science and Engineering (IJCSE), International Journal of Embedded Systems (IJES), and International Journal of High Performance Computing and Networking (IJHPCN), all published by Interscience, also serving a number of journal's editorial boards and guest editorship. His topics of interest include networked computing, GPU computing, parallel software design, and performance evaluation and benchmarking. Dr. Li is a fellow of the IET and a senior member of the IEEE.
Esaú Villatoro Tello is currently a full-time professor-researcher at the Universidad Autónoma Metropolitana Unidad Cuajimalpa (UAM-C) in Mexico City. From September 2019 to date, he is a visiting professor at Idiap Research Institute, in Martigny, Switzerland. His main research interests are associated with natural language processing (NLP) and computational linguistics topics, specifically he has done research on the topics of authorship analysis and authorship attribution, thematic and non-thematic text classification, plagiarism detection, information retrieval, and NLP applied in psycholinguistics for mental health support.
Manas Ranjan Lenka is working as an assistant professor in KIIT University and has around 17 years of experience, out of which 9 years of industry experience in telecom software developments and 8 years of teaching experience. His current research topic is wireless sensor networks.
Kuan-Ching Li is currently a professor in the Department of Computer Science and Information Engineering at the Providence University, Taiwan. Dr. Li is the editor-in-chief of technical publications in International Journal of Computational Science and Engineering (IJCSE), International Journal of Embedded Systems (IJES), and International Journal of High Performance Computing and Networking (IJHPCN), all published by Interscience, also serving a number of journal's editorial boards and guest editorship. His topics of interest include networked computing, GPU computing, parallel software design, and performance evaluation and benchmarking. Dr. Li is a fellow of the IET and a senior member of the IEEE.
Esaú Villatoro Tello is currently a full-time professor-researcher at the Universidad Autónoma Metropolitana Unidad Cuajimalpa (UAM-C) in Mexico City. From September 2019 to date, he is a visiting professor at Idiap Research Institute, in Martigny, Switzerland. His main research interests are associated with natural language processing (NLP) and computational linguistics topics, specifically he has done research on the topics of authorship analysis and authorship attribution, thematic and non-thematic text classification, plagiarism detection, information retrieval, and NLP applied in psycholinguistics for mental health support.
Content
Design of Efficient Algorithms for Mobile Charging in Wireless Sensor Networks.- Registration of Point Clouds for Human Face Recognition.- Classifying the Social Media Author Profile through a Multimodal Representation.- An Investigation into Effective Fault Localization.- Dependability Analysis for Transaction Processing in On-Demand Computing System.- Investigating and Devising Privacy Preserving Approaches for Location based Services.- Design of Intelligent Scheduling Algorithms for Cloud Computing.- Studies in Algorithms and Architectures for Sample Preparation with Digital Microfluidics.- Application of Soft Computing Techniques in Database Intrusion Detection.- Design and Applications of Improved Meta Heuristic Algorithms for Neural Network Training.
