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Computational Intelligence Aided Systems for Healthcare Domain
This book covers recent advances in artificial intelligence, smart computing, and their applications in augmenting medical and health care systems. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields including electrical, electronics and communication, computer, and biomedical. This book: Presents architecture, characteristics, and applications of artificial intelligence and smart computing in health care systems Highlights privacy issues faced in health care and health informatics using artificial intelligence and smart computing technologies Discusses nature-inspired computing algorithms for the brain-computer interface Cove...
Proceedings of Third Emerging Trends and Technologies on Intelligent Systems
This book presents best selected papers presented at the International Conference on Emerging Trends and Technologies on Intelligent Systems (ETTIS 2023) held from 23 – 24 February 2023 in hybrid mode at C-DAC, Noida, India. The book includes current research works in the areas of artificial intelligence, big data, cyber-physical systems, and security in industrial/real-world settings. The book illustrates on-going research results, projects, surveying works, and industrial experiences that describe significant advances in all of the related areas.
Information and Decision Sciences
This book presents the proceedings of the 6th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA-2017), held in Bhubaneswar, Odisha. The event brought together researchers, scientists, engineers, and practitioners to exchange their new ideas and experiences in the domain of intelligent computing theories with prospective applications to various engineering disciplines. The book is divided into two volumes: Information and Decision Sciences, and Intelligent Engineering Informatics. This volume covers broad areas of Information and Decision Sciences, with papers exploring both the theoretical and practical aspects of data-intensive computing, data mining, evolutionary computation, knowledge management & networks, sensor networks, signal processing, wireless networks, protocols & architectures etc. The book also offers a valuable resource for students at the post-graduate level in various engineering disciplines.
HUMAN RIGHTS LAW AND PRACTICE, SECOND EDITION
The book, written with a rich teaching and research experience of the author, emphasises the critical evaluation of contemporary human rights law and practice with special reference to India. It evaluates the ongoing discourse on various issues relating to life, liberty, equality, and human dignity and their reflections in international human rights law referring to the state practices through constitutional guarantees, judicial decisions as well as through enacting appropriate legislations. This lucid and comprehensive book is logically organised into nine chapters. Beginning with the theoretical foundations of human rights law referring to origin, development, and theories of human rights ...
Neural Information Processing
The two-volume set CCIS 1332 and 1333 constitutes thoroughly refereed contributions presented at the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020.* For ICONIP 2020 a total of 378 papers was carefully reviewed and selected for publication out of 618 submissions. The 191 papers included in this volume set were organized in topical sections as follows: data mining; healthcare analytics-improving healthcare outcomes using big data analytics; human activity recognition; image processing and computer vision; natural language processing; recommender systems; the 13th international workshop on artificial intelligence and cybersecurity; computational intelligence; machine learning; neural network models; robotics and control; and time series analysis. * The conference was held virtually due to the COVID-19 pandemic.
Advances in Knowledge Discovery and Data Mining, Part I
The two-volume set LNAI 7301 and 7302 constitutes the refereed proceedings of the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2012, held in Kuala Lumpur, Malaysia, in May 2012. The total of 20 revised full papers and 66 revised short papers were carefully reviewed and selected from 241 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas. The papers are organized in topical sections on supervised learning: active, ensemble, rare-class and online; unsupervised learning: clustering, probabilistic modeling in the first volume and on pattern mining: networks, graphs, time-series and outlier detection, and data manipulation: pre-processing and dimension reduction in the second volume.
Databases and Information Systems IX
Databases and information systems are now indispensable for the day-to-day functioning of businesses and society. This book presents 25 selected papers from those delivered at the 12th International Baltic Conference on Databases and Information Systems 2016 (DB&IS 2016), held in Riga, Latvia, in July 2016. Since it began in 1994, this biennial conference has become an international forum for researchers and developers in the field of databases, information systems and related areas, and the papers collected here cover a wide spectrum of topics related to the development of information systems and data processing. These include: the development of ontology applications; tools, technologies and languages for model-driven development; decision support systems and data mining; natural language processing and building linguistic components of information systems; advanced systems and technologies related to information systems, databases and information technologies in teaching and learning. The book will be of interest to all those whose work involves the design, application and use of databases and information systems.
Applications of Machine Learning and Deep Learning on Biological Data
The automated learning of machines characterizes machine learning (ML). It focuses on making data-driven predictions using programmed algorithms. ML has several applications, including bioinformatics, which is a discipline of study and practice that deals with applying computational derivations to obtain biological data. It involves the collection, retrieval, storage, manipulation, and modeling of data for analysis or prediction made using customized software. Previously, comprehensive programming of bioinformatical algorithms was an extremely laborious task for such applications as predicting protein structures. Now, algorithms using ML and deep learning (DL) have increased the speed and ef...
