Computational Intelligence for COVID-19 and Future Pandemics, Kose
Автор: Abhinav Juneja, Vikram Bali, Sapna Juneja, Vishal Название: Enabling Healthcare 4.0 for Pandemics ISBN: 1119768799 ISBN-13(EAN): 9781119768791 Издательство: Wiley Рейтинг: Цена: 25811.00 р. Наличие на складе: Поставка под заказ.
Описание: ENABLING HEALTHCARE 4.0 for PANDEMICS
The book explores the role and scope of AI, machine learning and other current technologies to handle pandemics.
In this timely book, the editors explore the current state of practice in Healthcare 4.0 and provide a roadmap for harnessing artificial intelligence, machine learning, and Internet of Things, as well as other modern cognitive technologies, to aid in dealing with the various aspects of an emergency pandemic outbreak. There is a need to improvise healthcare systems with the intervention of modern computing and data management platforms to increase the reliability of human processes and life expectancy. There is an urgent need to come up with smart IoT-based systems which can aid in the detection, prevention and cure of these pandemics with more precision. There are a lot of challenges to overcome but this book proposes a new approach to organize the technological warfare for tackling future pandemics.
In this book, the reader will find:
State-of-the-art technological advancements in pandemic management;
AI and ML-based identification and forecasting of pandemic spread;
Smart IoT-based ecosystem for pandemic scenario.
Audience The book will be used by researchers and practitioners in computer science, artificial intelligence, bioinformatics, data scientists, biomedical statisticians, as well as industry professionals in disaster and pandemic management.
Автор: M. Rubaiyat Hossain Mondal et al. Название: Emerging technologies for combatting pandemics : ISBN: 1032328282 ISBN-13(EAN): 9781032328287 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on both the design and implementation of AI-based approaches for systems that aid in monitoring and combating pandemics such as occurred with COVID-19. These systems are based on the Internet of Medical Things (IoMT), using sensor networks and other advanced technologies. The book examines different aspects of AI and IoMT.
Описание: This book emphasizes the increasingly important role that Computational Intelligence (CI) methods are playing in solving a myriad of entangled Wireless Sensor Networks (WSN) related problems.
Описание: 1. An Introduction to Computational Intelligence in COVID-19: Surveillance, Prevention, Prediction, and Diagnosis.- 2. Role of Computational Intelligence against COVID-19.- 3. Using Computational Intelligence for Tracking COVID-19 Outbreak in Online Social Networks.- 4. Social Network Analysis for the Identification of Key Spreaders during COVID-19.- 5. Mobile Technology Solution for COVID -19: Surveillance and Prevention.- 6. The Role of Internet of Things (IoT) in the Containment and Spread of the Novel COVID-19 Pandemic.- 7. A Review on Predictive Systems and Data Models for COVID-19.- 8. A Comparative Study of the SIR Prediction Models and Disease Control Strategies: A Case Study of the State of Kerala, India.- 9. Computational Intelligence Approach for Prediction of COVID-19 using Particle Swarm Optimization. 10. COVID-19 Insightful Data Visualization and Forecasting using Elasticsearch.
Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach provides a comprehensive guide for public health authorities, researchers and health professionals in psychological health. The book takes a unique approach by exploring how Artificial Intelligence (AI) and Machine Learning (ML) based solutions can assist with monitoring, detection and intervention for mental health at an early stage. Chapters include computational approaches, computational models, machine learning based anxiety and depression detection and artificial intelligence detection of mental health.
With the increase in number of natural disasters and the ongoing pandemic, people are experiencing uncertainty, leading to fear, anxiety and depression, hence this is a timely resource on the latest updates in the field.
Автор: Jahankhani Hamid, Kendzierskyj Stefan, Akhgar Babak Название: Information Security Technologies for Controlling Pandemics ISBN: 3030721191 ISBN-13(EAN): 9783030721190 Издательство: Springer Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It then turns to improved decision making in cyber security, also known as cyber situational awareness, by analysing security events and comparing data mining techniques, specifically classification techniques, when applied to cyber security data.
Автор: Kshatri Sapna Singh, Thakur Kavita, Khan Maleika Heenaye Mamode Название: Computational Intelligence and Applications for Pandemics and Healthcare ISBN: 1799898318 ISBN-13(EAN): 9781799898313 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 82994.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Provides both theoretical and practical evidence that demonstrates how through the integration, adaptation, construction and application of strategic models, methods and tools, organisational sustainability can be promoted for economies in a situation of uncertainty.
Автор: Jahankhani Название: Information Security Technologies for Controlling Pandemics ISBN: 3030721221 ISBN-13(EAN): 9783030721220 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It then turns to improved decision making in cyber security, also known as cyber situational awareness, by analysing security events and comparing data mining techniques, specifically classification techniques, when applied to cyber security data.
Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.
Автор: Ashutosh Kumar Singh, Rajiv Singh Название: Computational Methodologies for Electrical and Electronics Engineers ISBN: 1799833283 ISBN-13(EAN): 9781799833284 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 29779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Artificial intelligence has been applied to many areas of science and technology, including the power and energy sector. Renewable energy in particular has experienced the tremendous positive impact of these developments. With the recent evolution of smart energy technologies, engineers and scientists working in this sector need an exhaustive source of current knowledge to effectively cater to the energy needs of citizens of developing countries.
Computational Methodologies for Electrical and Electronics Engineers is a collection of innovative research that provides a complete insight and overview of the application of intelligent computational techniques in power and energy. Featuring research on a wide range of topics such as artificial neural networks, smart grids, and soft computing, this book is ideally designed for programmers, engineers, technicians, ecologists, entrepreneurs, researchers, academicians, and students.
Novel strategies for data-driven evolutionary optimization
Machine learning using distance-based methods
Counting cells and predicting immunoscore using gradient boosted convolutional neural networks
Kubelka-Munk model and stochastic model comparison in skin physical parameter retrieval using neural networks
A combined approach of neural networks and graphical models in skin cancer inference using spectral imaging
Using wave propagation simulations and convolutional neural networks to retrieve thin coating's thickness from hyperspectral images
Predicting future overweight and obesity from childhood growth data: A case study
Variable selection under a value acquisition budget
Stochastic approximation by successive piecewise linearization
Non-convex robust low-rank matrix recovery
Neural network learning via successive piecewise linearization
Learning for scientific computing purposes
Computational intelligence in design of new nanomaterials
Modeling flow, reactive transport and geomechanics in porous media
Physics constrained machine learning for industrial applications
Parameter and type identification in partial differential equations using deep neural networks
Stability maximization for layered moving web with total mass constraint
Similarity solutions for condensation on a non-isothermal vertical plate
Enhanced topology optimization approach using moving morphable components coupled with NURBS curves
Combined model order reduction and artificial neural network for data assimilation and damage detection in structures
Towards the optimization of fuzzy pattern trees by abs - linearization
Support vector machines in clusterwise linear regression
A Second-order method with enriched hessian information for composite sparse optimization problems
Missing value imputation via nonsmooth optimization and clusterwise linear regression
Parsimonious neural networks
Nobody can stop advancing artificial intelligence (AI) where developing
Computational sciences, physics field theories and geometry
Mini-symposium on ethics in AI
Essentializing software engineering practices for ethically designing and developing artificial intelligence systems 30 Ethics is important, but how can we implement it? Survey on software developers' views on AI ethics
Industrial IoT capabilities in reducing the LCOE of offshore wind energy: A review
High-Performance data analysis with the Helmholtz Analytics Toolkit (HeAT)
Dynamic data-driven application systems based on tensor factorization: learning the physics of model evolution
Predicting customer experience
Puhti-AI: Finland's new AI supercomputer
Using Artificial Intelligence to Classify Textual Applications for Reporting Purposes Application of machine learning methods to error control of approximate solutions
Iterative data selection strategy in offline data-driven evolutionary multiobjective optimization
On surrogate management in interactive multiobjective building energy system design
A modified deep neural network for the rapid inversion of geo-physical resistivity measurements
Using agents for automatic meta-modelling algorithm selection in data-driven multiobjective optimization problems
Future cooperation between Computational Science and AI in Industrial and Societal Applications - challenges, impact and expectations?
Описание: The book covers a wide topic collection starting from essentials of Computational Intelligence to advance, and possible application types against COVID-19 as well as its effects on the field of medical, social, and different data-oriented research scopes. Among these topics, the book also covers very recently, vital topics in terms of fighting against COVID-19 and solutions for future pandemics. The book includes the use of computational intelligence for especially medical diagnosis and treatment, and also data-oriented tracking-predictive solutions, which are key components currently for fighting against COVID-19. In this way, the book will be a key reference work for understanding how computational intelligence and the most recent technologies (i.e. Internet of Healthcare Thing, big data, and data science techniques) can be employed in solution phases and how they change the way of future solutions. The book also covers research works with negative results so that possible disadvantages of using computational intelligence solutions and/or experienced side-effects can be known widely for better future of medical solutions and use of intelligent systems against COVID-19 and pandemics. The book is considering both theoretical and applied views to enable readers to be informed about not only research works but also theoretical views about essentials/components of intelligent systems against COVID-19/pandemics, possible modeling scenarios with current and future perspective as well as solution strategies thought by researchers all over the world.
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