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This book focuses on the techniques of artificial intelligence that are mainly used in the power electronics field for the optimization of lost vehicle power. With the intention of optimizing the powerful energy of the vehicles and producing reliable energy, the most efficient methods, algorithms, and strategies of ethical artificial intelligence (AI) are being applied. By employing machine learning methods, the optimization of power energy in vehicles can be quickly recovered and managed efficiently. In today’s bustling world, power energy is indispensable for progress, yet in congested Vehicular Ad-hoc Networks (VANETs), vehicles often face power depletion and decreased efficiency. This ...
"This reference set provides a complete understanding of the development of applications and concepts in clinical, patient, and hospital information systems"--Provided by publisher.
This book constitutes the thoroughly refereed post-conference proceedings of the Third International Conference, eHealth 2010, held in Casablanca, Morocco, in December 2010. The 30 revised full papers presented along with 12 papers from 2 collocated workshops were carefully reviewed and selected from 70 submissions in total and cover a wide range of topics including web intelligence, privacy, trust and security, ontologies and knowledge management, eLearning and education, Web 2.0 and online communications of practice, and performance monitoring and evaluation frameworks for healthcare.
This two-volume set (LNAI 9875 and LNAI 9876) constitutes the refereed proceedings of the 8th International Conference on Collective Intelligence, ICCCI 2016, held in Halkidiki, Greece, in September 2016. The 108 full papers presented were carefully reviewed and selected from 277 submissions. The aim of this conference is to provide an internationally respected forum for scientific research in the computer-based methods of collective intelligence and their applications in (but not limited to) such fields as group decision making, consensus computing, knowledge integration, semantic web, social networks and multi-agent systems.
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Combining and integrating cross-institutional data remains a challenge for both researchers and those involved in patient care. Patient-generated data can contribute precious information to healthcare professionals by enabling monitoring under normal life conditions and also helping patients play a more active role in their own care. This book presents the proceedings of MEDINFO 2019, the 17th World Congress on Medical and Health Informatics, held in Lyon, France, from 25 to 30 August 2019. The theme of this year’s conference was ‘Health and Wellbeing: E-Networks for All’, stressing the increasing importance of networks in healthcare on the one hand, and the patient-centered perspectiv...
This book presents a collection of representative and novel work in the field of data mining, knowledge discovery, clustering and classification, based on expanded and reworked versions of a selection of the best papers originally presented in French at the EGC 2014 and EGC 2015 conferences held in Rennes (France) in January 2014 and Luxembourg in January 2015. The book is in three parts: The first four chapters discuss optimization considerations in data mining. The second part explores specific quality measures, dissimilarities and ultrametrics. The final chapters focus on semantics, ontologies and social networks. Written for PhD and MSc students, as well as researchers working in the field, it addresses both theoretical and practical aspects of knowledge discovery and management.
Data warehousing and online analysis technologies have shown their effectiveness in managing and analyzing a large amount of disparate data, attracting much attention from numerous research communities. Data Warehousing Design and Advanced Engineering Applications: Methods for Complex Construction covers the complete process of analyzing data to extract, transform, load, and manage the essential components of a data warehousing system. A defining collection of field discoveries, this advanced title provides significant industry solutions for those involved in this distinct research community.
The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment. Data Mining and Medical Knowledge Management: Cases and Applications presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies.