The Big Data-Driven Digital Economy: Artificial and Computational Intelligence, Musleh Al-Sartawi Abdalmuttaleb M. a.
Автор: Millington Название: Artificial Intelligence for Games,Third Edition ISBN: 1138483974 ISBN-13(EAN): 9781138483972 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Artificial Intelligence is an integral part of every video game. This book helps propfessionals keep up with the constantly evolving technological advances in the fast growing game industry and equips students with up-to-date infortmation they need to jumpstart their careers.
Computational and Data-Driven Chemistry Using Artificial Intelligence: Volume 1: Fundamentals, Methods and Applications highlights fundamental knowledge and current developments in the field, giving readers insight into how these tools can be harnessed to enhance their own work. Offering the ability to process large or complex data-sets, compare molecular characteristics and behaviors, and help researchers design or identify new structures, Artificial Intelligence (AI) holds huge potential to revolutionize the future of chemistry. Volume 1 explores the fundamental knowledge and current methods being used to apply AI across a whole host of chemistry applications.
Drawing on the knowledge of its expert team of global contributors, the book offers fascinating insight into this rapidly developing field and serves as a great resource for all those interested in exploring the opportunities afforded by the intersection of chemistry and AI in their own work. Part 1 provides foundational information on AI in chemistry, with an introduction to the field and guidance on database usage and statistical analysis to help support newcomers to the field. Part 2 then goes on to discuss approaches currently used to address problems in broad areas such as computational and theoretical chemistry; materials, synthetic and medicinal chemistry; crystallography, analytical chemistry, and spectroscopy. Finally, potential future trends in the field are discussed.
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?
Artificial Intelligence, Deep Lea
Автор: Mansi, Tommaso Passerini, Tiziano Название: Artificial intelligence for computational modeling of the heart ISBN: 012817594X ISBN-13(EAN): 9780128175941 Издательство: Elsevier Science Рейтинг: Цена: 19875.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Artificial Intelligence for Computational Modeling of the Heart presents recent research developments towards streamlined and automatic estimation of the digital twin of a patient's heart by combining computational modeling of heart physiology and artificial intelligence. The book first introduces the major aspects of multi-scale modeling of the heart, along with the compromises needed to achieve subject-specific simulations. Reader will then learn how AI technologies can unlock robust estimations of cardiac anatomy, obtain meta-models for real-time biophysical computations, and estimate model parameters from routine clinical data. Concepts are all illustrated through concrete clinical applications.
Presents recent advances in computational modeling of heart function and artificial intelligence technologies for subject-specific applications
Discusses AI-based technologies for robust anatomical modeling from medical images, data-driven reduction of multi-scale cardiac models, and estimations of physiological parameters from clinical data
Illustrates the technology through concrete clinical applications and discusses potential impacts and next steps needed for clinical translation
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: Hiranmay Ghosh Название: Computational Models for Cognitive Vision ISBN: 1119527864 ISBN-13(EAN): 9781119527862 Издательство: Wiley Рейтинг: Цена: 7754.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Learn how to apply cognitive principles to the problems of computer vision
Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision, and applies those models to computer vision tasks. Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few. The author's ultimate goal is to provide a framework for creation of a machine vision system with the capability and versatility of the human vision.
Written by Dr. Hiranmay Ghosh, the book takes readers through the basic principles and the computational models for cognitive vision, Bayesian reasoning for perception and cognition, and other related topics, before establishing the relationship of cognitive vision with the multi-disciplinary field broadly referred to as "artificial intelligence". The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heritage and social robots. The author concludes with suggestions for future research and salient observations about the state of the field of cognitive vision.
Other topics covered in the book include:
- knowledge representation techniques
- evolution of cognitive architectures
- deep learning approaches for visual cognition
Undergraduate students, graduate students, engineers, and researchers interested in cognitive vision will consider this an indispensable and practical resource in the development and study of computer vision.
Автор: Nagarajan G., Minu R. I. Название: Edge Computing and Computational Intelligence Paradigms for the IoT ISBN: 1522585559 ISBN-13(EAN): 9781522585558 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 35739.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Edge computing is focused on devices and technologies that are attached to the internet of things (IoT). Identifying IoT use across a range of industries and measuring strategic values helps identify what technologies to pursue and can avoid wasted resources on deployments with limited values. The Handbook of Research on Edge Computing and Computational Intelligence Paradigms for the IoT is a critical research book that provides a complete insight on the recent advancements and integration of intelligence in IoT. This book highlights various topics such as disaster prediction, governance, and healthcare. It is an excellent resource for researchers, working professionals, academicians, policymakers, and defense companies.
Автор: Purnomo Hindriyanto Dwi Название: Computational Intelligence in the Internet of Things ISBN: 1522579559 ISBN-13(EAN): 9781522579557 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 28215.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In recent years, the need for smart equipment has increased exponentially with the upsurge in technological advances. To work to their fullest capacity, these devices need to be able to communicate with other devices in their network to exchange information and receive instructions. Computational Intelligence in the Internet of Things is an essential reference source that provides relevant theoretical frameworks and the latest empirical research findings in the area of computational intelligence and the Internet of Things. Featuring research on topics such as data analytics, machine learning, and neural networks, this book is ideally designed for IT specialists, managers, professionals, researchers, and academicians.
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.
Автор: Alex Lui, Anna Farzinder, Mingboo Gong Название: Transforming Healthcare with Big Data and AI ISBN: 1641138971 ISBN-13(EAN): 9781641138970 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 7069.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Healthcare and technology are at a convergence point where significant changes are poised to take place. The vast and complex requirements of medical record keeping, coupled with stringent patient privacy laws, create an incredibly unwieldy maze of health data needs. While the past decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be accumulated, processed, and shared around the globe. Transforming Healthcare with Big Data and AI examines the crossroads of these two fields and looks to the future of leveraging advanced technologies and developing data ecosystems to the healthcare field.
This book is the product of the Transforming Healthcare with Data conference, held at the University of Southern California. Many speakers and digital healthcare industry leaders contributed multidisciplinary expertise to chapters in this work. Authors’ backgrounds range from data scientists, healthcare experts, university professors, and digital healthcare entrepreneurs. If you have an understanding of data technologies and are interested in the future of Big Data and A.I. in healthcare, this book will provide a wealth of insights into the new landscape of healthcare.
Описание: This book explores the complex ways in which algorithms and big data are reshaping everyday culture, while at the same time perpetuating inequality and intersectional discrimination. It situates issues of humanity, identity, and culture in relation to free will, surveillance, capitalism, neoliberalism, consumerism, solipsism, and creativity.
Digital transformation continues to create new growth opportunities for businesses and improve the lives of citizens. To help businesses seize these opportunities, the Infocomm Media Development Authority (IMDA) launched the Digital Economy Framework for Action in 2018. This living document aims to enhance Singapore's digital competitiveness and become a global node in Asia.
As part of Singapore's push for a Digital Economy, IMDA and the Singapore University of Social Sciences have collaborated to jointly publish the Artificial Intelligence, Data and Blockchain in a Digital Economy, First Edition. This book explains how frontier technologies such as blockchain and artificial intelligence can empower Singapore's digital transformation. It also highlights and provides insights on transformative services and how frontier technology can impact the nation's digitalisation journey.
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