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The Big Data-Driven Digital Economy: Artificial and Computational Intelligence, Musleh Al-Sartawi


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Автор: Musleh Al-Sartawi
Название:  The Big Data-Driven Digital Economy: Artificial and Computational Intelligence
ISBN: 9783030730598
Издательство: Springer
Классификация:

ISBN-10: 303073059X
Обложка/Формат: Soft cover
Страницы: 472
Вес: 0.74 кг.
Дата издания: 13.06.2022
Серия: Studies in Computational Intelligence
Язык: English
Издание: 1st ed. 2021
Иллюстрации: 27 illustrations, color; 15 illustrations, black and white; xvi, 472 p. 42 illus., 27 illus. in color.; 27 illustrations, color; 15 illustrations, bla
Размер: 235 x 155
Читательская аудитория: Professional & vocational
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book shows digital economy has become one of the most sought out solutions to sustainable development and economic growth of nations. This book discusses the implications of both artificial intelligence and computational intelligence in the digital economy providing a holistic view on AI education, economics, finance, sustainability, ethics, governance, cybersecurity, blockchain, and knowledge management. Unlike other books, this book brings together two important areas, intelligence systems and big data in the digital economy, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations. The chapters hereby focus on how societies can take advantage and manage data, as well as the limitations they face due to the complexity of resources in the form of digital data and the intelligence which will support economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, students, economic development strategies, and the efforts made by the UN towards achieving their sustainability goals.
Дополнительное описание: Leveraging Big Data to Accelerate Supply Chain Management in Covid-19.- Mobile Computing Technologies for Enhanced Living Environments: A Literature Review.- Sentiment Analysis for Modern Standard Dialect Using Genetic Folding Algorithm.- The Usage of E-



Computational Intelligence for Machine Learning and Healthcare Informatics

Автор: Rajshree Srivastava, Pradeep Kumar Mallick, Siddha
Название: Computational Intelligence for Machine Learning and Healthcare Informatics
ISBN: 3110647826 ISBN-13(EAN): 9783110647822
Издательство: Walter de Gruyter
Цена: 20446.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

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.

Edge Computing and Computational Intelligence Paradigms for the IoT

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)
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Цена: 35739.00 р.
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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.

Artificial Intelligence for Games,Third Edition

Автор: Millington
Название: Artificial Intelligence for Games,Third Edition
ISBN: 1138483974 ISBN-13(EAN): 9781138483972
Издательство: Taylor&Francis
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Цена: 17609.00 р.
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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 Intelligence in Digital Pedagogy

Автор: Deyasi, A., Mukherjee, S., Mukherjee, A., Bhattach
Название: Computational Intelligence in Digital Pedagogy
ISBN: 9811587434 ISBN-13(EAN): 9789811587436
Издательство: Springer
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Цена: 23757.00 р.
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Описание: This book is a useful guide for the teaching fraternity, administrators and education technology professionals to make good use of AI across outcome-based technical education (OBTE) ecosystem and infuse innovations and affordable digital technologies to traditional pedagogic processes to make teaching-learning more independent of human factor (teacher/student quality), time and place and at the same time more impactful and enjoyable for the learners. Providing access to the digital media and learning tools (even to the extent of mobile apps) to the students would allow them to keep pace with innovations in learning technologies, learn according to their own pace and improve their understanding level and have instantaneous feedback and evaluation. The book explores these new challenges and scope of using computational intelligence in educational technology.

The book also addresses how based on the data collected from the outcome of conventional educational system, intelligent diagnostic and feedback system is developed which will change the teaching strategies and corresponding teaching-learning process. The book covers a wider framework of digital pedagogy and its intelligent applications on various sectors of education system.

The Big Data-Driven Digital Economy: Artificial and Computational Intelligence

Автор: Musleh Al-Sartawi Abdalmuttaleb M. a.
Название: The Big Data-Driven Digital Economy: Artificial and Computational Intelligence
ISBN: 3030730565 ISBN-13(EAN): 9783030730567
Издательство: Springer
Цена: 27950.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Leveraging Big Data to Accelerate Supply Chain Management in Covid-19.- Mobile Computing Technologies for Enhanced Living Environments: A Literature Review.- Sentiment Analysis for Modern Standard Dialect Using Genetic Folding Algorithm.- The Usage of E- Learning among Mass Communication Students.- The Influence of Relational Capital on the Relationship between Intellectual Capital and Earnings Per Share in the Digital Economy in the Jordanian Industrial Sector.- Machine Learning and Earnings Management Detection.- Artificial Intelligence and IT Governance: A Literature Review.- Blending of Physicians' Leadership and Decision-making Style Within Virtual Platforms for Improving Service Quality.- Social Capital Improves Virtually Shared Learner for Enhancing Their Readiness to Learn.- Game-based Learning: Recommendations Driven from Literature.- Utilizing Blockchain Technology to Manage Functional Areas in Healthcare Systems.- Fintech and Entrepreneurship Boosting in Developing Countries: A Comparative Study of India and Egypt.

We, the Robots?: Regulating Artificial Intelligence and the Limits of the Law

Автор: Chesterman Simon
Название: We, the Robots?: Regulating Artificial Intelligence and the Limits of the Law
ISBN: 1316517683 ISBN-13(EAN): 9781316517680
Издательство: Cambridge Academ
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Цена: 5702.00 р.
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Описание: Should we regulate artificial intelligence? Can we? From self-driving cars and high-speed trading to algorithmic decision-making, the way we live, work, and play is increasingly dependent on AI systems. This book examines how our laws are dealing with AI, as well as what additional rules and institutions are needed.

Computational Methodologies for Electrical and Electronics Engineers

Автор: Ashutosh Kumar Singh, Rajiv Singh
Название: Computational Methodologies for Electrical and Electronics Engineers
ISBN: 1799833283 ISBN-13(EAN): 9781799833284
Издательство: Mare Nostrum (Eurospan)
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Цена: 29779.00 р.
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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.

Computational Intelligence in the Internet of Things

Автор: Purnomo Hindriyanto Dwi
Название: Computational Intelligence in the Internet of Things
ISBN: 1522579559 ISBN-13(EAN): 9781522579557
Издательство: Mare Nostrum (Eurospan)
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Цена: 28215.00 р.
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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.

Artificial intelligence for computational modeling of the heart

Автор: Mansi, Tommaso Passerini, Tiziano
Название: Artificial intelligence for computational modeling of the heart
ISBN: 012817594X ISBN-13(EAN): 9780128175941
Издательство: Elsevier Science
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Цена: 19875.00 р.
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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
Computational Models for Cognitive Vision

Автор: Hiranmay Ghosh
Название: Computational Models for Cognitive Vision
ISBN: 1119527864 ISBN-13(EAN): 9781119527862
Издательство: Wiley
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Цена: 7754.00 р.
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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.

Computational Sciences and Artificial Intelligence in Industry: New Digital Technologies for Solving Future Societal and Economical Challenges

Автор: Tuovinen Tero, Periaux Jacques, Neittaanmдki Pekka
Название: Computational Sciences and Artificial Intelligence in Industry: New Digital Technologies for Solving Future Societal and Economical Challenges
ISBN: 3030707865 ISBN-13(EAN): 9783030707866
Издательство: Springer
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Цена: 27950.00 р.
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Описание:

  • 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
Transforming Healthcare with Big Data and AI

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)
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Цена: 7069.00 р.
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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.


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