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Green Computing and Predictive Analytics for Healthcare excavates
the rudimentary concepts of Green Computing, Big Data and the
Internet of Things along with the latest research development in
the domain of healthcare. It also covers various applications and
case studies in the field of computer science with state-of-the-art
tools and technologies. The rapid growth of the population is a
challenging issue in maintaining and monitoring various experiences
of quality of service in healthcare. The coherent usage of these
limited resources in connection with optimum energy consumption has
been becoming more important. The major healthcare nodes are
gradually becoming Internet of Things-enabled, and sensors, work
data and the involvement of networking are creating smart campuses
and smart houses. The book includes chapters on the Internet of
Things and Big Data technologies. Features: Biomedical data
monitoring under the Internet of Things Environment data sensing
and analyzing Big data analytics and clustering Machine learning
techniques for sudden cardiac death prediction Robust brain tissue
segmentation Energy-efficient and green Internet of Things for
healthcare applications Blockchain technology for the healthcare
Internet of Things Advanced healthcare for domestic medical tourism
system Edge computing for data analytics This book on Green
Computing and Predictive Analytics for Healthcare aims to promote
and facilitate the exchange of research knowledge and findings
across different disciplines on the design and investigation of
healthcare data analytics. It can also be used as a textbook for a
master's course in biomedical engineering. This book will also
present new methods for medical data evaluation and the diagnosis
of different diseases to improve quality-of-life in general and for
better integration of Internet of Things into society. Dr. Sourav
Banerjee is an Assistant Professor at the Department of Computer
Science and Engineering of Kalyani Government Engineering College,
Kalyani, West Bengal, India. His research interests include Big
Data, Cloud Computing, Distributed Computing and Mobile
Communications. Dr. Chinmay Chakraborty is an Assistant Professor
at the Department of Electronics and Communication Engineering,
Birla Institute of Technology, Mesra, India. His main research
interests include the Internet of Medical Things, WBAN, Wireless
Networks, Telemedicine, m-Health/e-Health and Medical Imaging. Dr.
Kousik Dasgupta is an Assistant Professor at the Department of
Computer Science and Engineering, Kalyani Government Engineering
College, India. His research interests include Computer Vision,
AI/ML, Cloud Computing, Big Data and Security.
This book presents studies involving algorithms in the machine
learning paradigms. It discusses a variety of learning problems
with diverse applications, including prediction, concept learning,
explanation-based learning, case-based (exemplar-based) learning,
statistical rule-based learning, feature extraction-based learning,
optimization-based learning, quantum-inspired learning,
multi-criteria-based learning and hybrid intelligence-based
learning.
This book presents studies involving algorithms in the machine
learning paradigms. It discusses a variety of learning problems
with diverse applications, including prediction, concept learning,
explanation-based learning, case-based (exemplar-based) learning,
statistical rule-based learning, feature extraction-based learning,
optimization-based learning, quantum-inspired learning,
multi-criteria-based learning and hybrid intelligence-based
learning.
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Computational Intelligence, Communications, and Business Analytics - Second International Conference, CICBA 2018, Kalyani, India, July 27-28, 2018, Revised Selected Papers, Part II (Paperback, 1st ed. 2019)
Jyotsna Kumar Mandal, Somnath Mukhopadhyay, Paramartha Dutta, Kousik Dasgupta
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R1,653
Discovery Miles 16 530
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Ships in 10 - 15 working days
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The two volume set CCIS 1030 and 1031 constitutes the refereed
proceedings of the Second International Conference on Computational
Intelligence, Communications, and Business Analytics, CICBA 2018,
held in Kalyani, India, in July 2018. The 76 revised full papers
presented in the two volumes were carefully reviewed and selected
from 240 submissions. The papers are organized in topical sections
on computational intelligence; signal processing and
communications; microelectronics, sensors, and intelligent
networks; data science & advanced data analytics; intelligent
data mining & data warehousing; and computational forensics
(privacy and security).
This book brings together the diversified areas of contemporary
computing frameworks in the field of Computer Science, Engineering
and Electronic Science. It focuses on various techniques and
applications pertaining to cloud overhead, cloud infrastructure,
high speed VLSI circuits, virtual machines, wireless and sensor
networks, clustering and extraction of information from images and
analysis of e-mail texts. The state-of-the-art methodologies and
techniques are addressed in chapters presenting various proposals
for enhanced outcomes and performances. The techniques discussed
are useful for young researchers, budding engineers and industry
professionals for applications in their respective fields.
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Computational Intelligence, Communications, and Business Analytics - Second International Conference, CICBA 2018, Kalyani, India, July 27-28, 2018, Revised Selected Papers, Part I (Paperback, 1st ed. 2019)
Jyotsna Kumar Mandal, Somnath Mukhopadhyay, Paramartha Dutta, Kousik Dasgupta
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R2,557
Discovery Miles 25 570
|
Ships in 10 - 15 working days
|
The two volume set CCIS 1030 and 1031 constitutes the refereed
proceedings of the Second International Conference on Computational
Intelligence, Communications, and Business Analytics, CICBA 2018,
held in Kalyani, India, in July 2018. The 76 revised full papers
presented in the two volumes were carefully reviewed and selected
from 240 submissions. The papers are organized in topical sections
on computational intelligence; signal processing and
communications; microelectronics, sensors, and intelligent
networks; data science & advanced data analytics; intelligent
data mining & data warehousing; and computational forensics
(privacy and security).
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