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Artificial Intelligence for Societal Development and Global Well-Being, Abhay Saxena, Ashutosh Kumar Bhatt, Rajeev Kumar


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Автор: Abhay Saxena, Ashutosh Kumar Bhatt, Rajeev Kumar
Название:  Artificial Intelligence for Societal Development and Global Well-Being
ISBN: 9781668424438
Издательство: Mare Nostrum (Eurospan)
Классификация:

ISBN-10: 1668424436
Обложка/Формат: Hardback
Страницы: 315
Вес: 0.78 кг.
Дата издания: 30.06.2022
Серия: Computing & IT
Язык: English
Размер: 187 x 263 x 26
Читательская аудитория: Professional and scholarly
Ключевые слова: Artificial intelligence, BUSINESS & ECONOMICS / Development / General,COMPUTERS / Intelligence (AI) & Semantics,COMPUTERS / Social Aspects / Human-Computer Interaction
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Поставляется из: Англии
Описание: Who will AI primarily serve? Will AI be confined to the elite or within research labs? This book`s main emphasis is to provide valuable insights on best practices and success factors.

Artificial Intelligence for Societal Development and Global Well-Being

Автор: Abhay Saxena, Ashutosh Kumar Bhatt, Rajeev Kumar
Название: Artificial Intelligence for Societal Development and Global Well-Being
ISBN: 1668424444 ISBN-13(EAN): 9781668424445
Издательство: Mare Nostrum (Eurospan)
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Цена: 212520.00 T
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Описание: Considers the various uses, best practices, and success factors of artificial intelligence across fields and industries and discusses critical ways in which the technology must be developed further for the good of society. The book covers a range of topics, including smart devices, artificial neural networks, and natural intelligence.

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: 186330.00 T
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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
Artificial Intelligence and Machine Learning in Public Healthcare: Opportunities and Societal Impact

Автор: Santosh Kc, Gaur Loveleen
Название: Artificial Intelligence and Machine Learning in Public Healthcare: Opportunities and Societal Impact
ISBN: 9811667675 ISBN-13(EAN): 9789811667671
Издательство: Springer
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Цена: 60550.00 T
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Описание: It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues.

Societal Responsibility of Artificial Intelligence: Towards an Ethical and Eco-Responsible AI

Автор: Beranger Jerome
Название: Societal Responsibility of Artificial Intelligence: Towards an Ethical and Eco-Responsible AI
ISBN: 1786306948 ISBN-13(EAN): 9781786306944
Издательство: Wiley
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Цена: 145670.00 T
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Описание: This standard describes the various types and classes of cold-water singlejet meters in sizes 5/8 in. (15 mm) through 6 in. (150 mm) for water utilities` customer service and the materials and workmanship employed in their fabrication. These meters register by recording the revolutions of a rotor powered by the force of flowing water striking its blades.

Machine Learning for Societal Improvement, Modernization, and Progress

Автор: Vishnu S. Pendyala
Название: Machine Learning for Societal Improvement, Modernization, and Progress
ISBN: 1668440466 ISBN-13(EAN): 9781668440469
Издательство: Mare Nostrum (Eurospan)
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Цена: 212520.00 T
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Описание: Showcases the groundbreaking applications of machine learning that are leading to the next generation of computing and living standards. The focus of the book is machine learning and its application to specific domains, which is resulting in substantial civilizational progress.

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: 38010.00 T
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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.

Evolutionary and Deterministic Methods for Design Optimization and Control With Applications to Industrial and Societal Problems

Автор: Esther Andr?s-P?rez; Leo M. Gonz?lez; Jacques Peri
Название: Evolutionary and Deterministic Methods for Design Optimization and Control With Applications to Industrial and Societal Problems
ISBN: 3030078876 ISBN-13(EAN): 9783030078874
Издательство: Springer
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Цена: 158380.00 T
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Описание: This book contains thirty-five selected papers presented at the International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems (EUROGEN 2017). This was one of the Thematic Conferences of the European Community on Computational Methods in Applied Sciences (ECCOMAS).Topics treated in the various chapters reflect the state of the art in theoretical and numerical methods and tools for optimization, and engineering design and societal applications. The volume focuses particularly on intelligent systems for multidisciplinary design optimization (mdo) problems based on multi-hybridized software, adjoint-based and one-shot methods, uncertainty quantification and optimization, multidisciplinary design optimization, applications of game theory to industrial optimization problems, applications in structural and civil engineering optimum design and surrogate models based optimization methods in aerodynamic design.

Techno-Societal 2018

Автор: Prashant M. Pawar; Babruvahan P. Ronge; R. Balasub
Название: Techno-Societal 2018
ISBN: 3030168476 ISBN-13(EAN): 9783030168476
Издательство: Springer
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Цена: 307450.00 T
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Описание: This book, divided in two volumes, originates from Techno-Societal 2018: the 2nd International Conference on Advanced Technologies for Societal Applications, Maharashtra, India, that brings together faculty members of various engineering colleges to solve Indian regional relevant problems under the guidance of eminent researchers from various reputed organizations.The focus is on technologies that help develop and improve society, in particular on issues such as the betterment of differently abled people, environment impact, livelihood, rural employment, agriculture, healthcare, energy, transport, sanitation, water, education. This conference aims to help innovators to share their best practices or products developed to solve specific local problems which in turn may help the other researchers to take inspiration to solve problems in their region. On the other hand, technologies proposed by expert researchers may find applications in different regions. This offers a multidisciplinary platform for researchers from a broad range of disciplines of Science, Engineering and Technology for reporting innovations at different levels.

Decision Support Systems XII: Decision Support Addressing Modern Industry, Business, and Societal Needs: 8th International Conference on Decision Su

Автор: Cabral Seixas Costa Ana Paula, Papathanasiou Jason, Jayawickrama Uchitha
Название: Decision Support Systems XII: Decision Support Addressing Modern Industry, Business, and Societal Needs: 8th International Conference on Decision Su
ISBN: 3031065298 ISBN-13(EAN): 9783031065293
Издательство: Springer
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Цена: 60550.00 T
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Описание: This book constitutes the proceedings of the 8th International Conference on Decision Support Systems Technologies, ICDSST 2022, held during May 23-25, 2022. The EWG-DSS series of International Conference on Decision Support System Technology (ICDSST) is planned to consolidate the tradition of annual events organized by the EWG-DSS in offering a platform for European and international DSS communities, comprising the academic and industrial sectors, to present state-of-the-art DSS research and developments, to discuss current challenges that surround decision-making processes, to exchange ideas about realistic and innovative solutions, and to co-develop potential business opportunities. The main aim of this year’s conference is to investigate the role DSS and related technologies can play in mitigating the impact of pandemics and post-crisis recovery. The 15 papers presented in this volume were carefully reviewed and selected from 46 submissions. They were organized in topical sections as follows: decision support addressing modern industry; decision support addressing business and societal needs, and multiple criteria approaches.

Evolutionary and Deterministic Methods for Design Optimization and Control With Applications to Industrial and Societal Problems

Автор: Andr?s-P?rez
Название: Evolutionary and Deterministic Methods for Design Optimization and Control With Applications to Industrial and Societal Problems
ISBN: 3319898892 ISBN-13(EAN): 9783319898896
Издательство: Springer
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Цена: 139750.00 T
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Описание: Preface.- PART I: Adjoint Methods for Optimisation, Mesh Adaptation and Uncertainty Quantification.- Gradient projection, constraints and surface regularization methods in adjoint shape optimization, by Pavlos P. Alexias and Eugene De Villiers.- Adjoint Shape Optimisation using model Boundary Representation, by E. Andres-Perez et al..- CAD and Adjoint based Multipoint Optimization of an Axial Turbine Profile, by Ismael Sanchez Torreguitart, Tom Verstraete, and Lasse Mueller.- A Comparative Study of Two Different CAD-Based Mesh Deformation Methods for Structural Shape Optimization, by Marc Schwalbach, Tom Verstraete, Jens-Dominik Miller, and Nicolas R. Gauger.- Node-based Adjoint Surface Optimization of U-bend duct for pressure loss reduction, by Giacomo Alessi, Lilla Koloszar, Tom Verstraete, and J. van Beeck.- On the Properties of Solutions of the 2D Adjoint Euler Equations, by Carlos Lozano.- Finite Transformation Rigid Motion Mesh Morpher, by Athanasios G. Liatsikouras, Guillaume Pierrot, Gabriel Fougeron, and George S. Eleftheriou.- The Unsteady Continuous Adjoint Method Assisted by the Proper Generalized Decomposition Method, by V. S. Papageorgiou, K. D. Samouchos and K. C. Giannakoglou.- A Two-Step Mesh Adaptation Tool Based on RBF with application to turbomachinery Optimization Loops, by Flavio Gagliardi, Konstantinos T. Tsiakas and Kyriakos C. Giannakoglou.- Adjoint-based Aerodynamic Optimisation of Wing Shape Using Non-Uniform Rational B-splines, by Xingchen Zhang, Rejish Jesudasan and Jens-Dominik Mьller.- PART II: Surrogate-assisted Optimization of Real World problems.- A comparative evaluation of surrogate models for transonic wing shape optimization, by Emiliano Iuliano.- Study of the influence of the initial a-priori training dataset size in the efficiency and convergence of surrogate-based evolutionary optimization, by Daniel Gonzalez Juarez and Esther Andres Perez.- Garteur AD/AG52: Surrogate-based global optimization methods in preliminary aerodynamic design, by E. Andres-Perez et al..- A Response Surface Based Strategy for Accelerated Compressor Map Computation, by Dmitrij Ivanov, Dieter Bestle, and Christian Janke.- Surrogate-Based Shape Optimization of the ERCOFTAC Centrifugal Pump Impeller, by Remo De Donno and Stefano Rebay and Antonio Ghidoni.- CFD based Design Optimization of a Cabinet Nitrogen Generator, by Bбrbara Arizmendi Gutiйrrez and Edmondo Minisci.- Delaunay-based global optimization in nonconvex domains defined by hidden constraints, by Shahrouz Ryan Alimo, Pooriya Beyhaghi, and Thomas R. Bewley.- PART III: Applications of optimization in engineering design automation.- Optimized Vehicle Dynamics Virtual Sensing using Metaheuristic Optimization and Unscented Kalman Filter, by Manuel Acosta and Stratis Kanarachos.- On Combinatorial Problem Representation based Ascent Assembly Design Optimization, by Michael Hellwig, Doris Entner, Thorsten Prante, Alexandru-Ciprian Zavoianu, Martin Schwarz, and Klara Fink.- On the Optimization of 2D Path Network Layouts in Engineering Designs via Evolutionary Computation Techniques, by Alexandru-Ciprian Ziivoianu, Susanne Saminger-Platz, Doris Entner, Thorsten Prante, Michael Hellwig, Martin Schwarz, and Klara Fink.- Taking Advantage of 3D Printing so as to Simultaneously Reduce Weight and Mechanical Bonding Stress, by Markus Schatz, Robert Schweikle, Christian Lausch, Michael Jentsch and Werner Konrad.- Interactive Optimization of Path Planning for a Robot Enabled by Virtual Commissioning, by Ruth Fleisch, Doris Entner, Thorsten Prante, Reinhard Pfefferkorn.- Box-Type Boom Design using Surrogate Modeling: Introducing an Industrial Optimization Benchmark, by Philipp Fleck, Doris Entner, Clemens Munzer, Michael Kommenda, Thorsten Prante, Martin Schwarz, Martin Hachl, and Michael Affenzeller.- Knowledge Objects Enable Mass-Individualization, by Joel Johansson and Fredrik Elgh.- Free-form Optimization of a Shell Structure with Curvature Constraint,

Machine Learning for Societal Improvement, Modernization, and Progress

Автор: Vishnu S. Pendyala
Название: Machine Learning for Societal Improvement, Modernization, and Progress
ISBN: 1668440458 ISBN-13(EAN): 9781668440452
Издательство: Mare Nostrum (Eurospan)
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Цена: 280890.00 T
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Описание: Showcases applications of machine learning that are leading us to the next generation of computing and living standards. The book explores the application of machine learning to cutting-edge technologies that are playing a prominent role in improving the quality of life and the progress of civilization.

Machine Learning and Internet of Things for Societal Issues

Автор: Satyanarayana Ch, Gao Xiao-Zhi, Ting Choo-Yee
Название: Machine Learning and Internet of Things for Societal Issues
ISBN: 9811650896 ISBN-13(EAN): 9789811650895
Издательство: Springer
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Цена: 55890.00 T
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Описание: This book highlights recent advance in the area of Machine Learning and IoT, and their applications to solve societal issues/problems or useful for various users in the society. It is known that many smart devices are interconnected and the data generated is being analyzed and processed with machine learning models for prediction, classification, etc., to solve human needs in various sectors like health, road safety, agriculture, and education. This contributed book puts together chapters concerning the use of intelligent techniques in various aspects related to the IoT domain from protocols to applications, to give the reader an up-to-date picture of the state-of-the-art on the connection between computational intelligence, machine learning, and IoT.


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