Author: Natalia SerdyukovaPublisher: Springer Nature
ISBN: 3031660404
Category :
Languages : en
Pages : 281
Book Description
Algebraic Quasi - Fractal Logic of Smart Systems
Author: Natalia SerdyukovaPublisher: Springer Nature
ISBN: 3031660404
Category :
Languages : en
Pages : 281
Book Description
Smart Education and e-Learning—Smart University
Author: Vladimir L. UskovPublisher: Springer Nature
ISBN: 9819929938
Category : Technology & Engineering
Languages : en
Pages : 300
Book Description
This book contains the contributions presented at the 10th international KES conference on Smart Education and e-Learning (SEEL-2023) with the Smart University as the main conference theme. The conference is being held on June 14-16, 2023 in Rome, Italy in both in-person and online modes. The book contains high quality peer-reviewed papers that are grouped into several interconnected parts: Part 1 – Smart Education, Part 2 – Smart e-Learning, Part 3 – Smart University, Part 4 – Smart Education: Case Studies and Research, and Part 5 – Smart Company: Case Studies and Research. Smart education, smart e-learning, smart universities and smart companies are emerging and rapidly growing areas with the potential to transform the existing teaching strategies, learning environments, and educational/training activities and technology in academic institutions and training centers. Smart education/training and smart e-learning are focused on enabling instructors/trainers to develop innovative ways of achieving excellence in teaching in highly technological smart classrooms/labs, and providing students/learners with new opportunities to maximize their success and select the best options for their education/training, location and learning style, as well as the mode of content delivery. This book serves as a useful source of research data and valuable information on current research projects, best practices and case studies for faculty, scholars, Ph.D. students, administrators, and practitioners – all those who are interested in smart education, smart e-learning, smart university and smart business/company paradigms, concepts, systems and technology.
Smart Education and e-Learning - Smart Pedagogy
Author: Vladimir L. UskovPublisher: Springer Nature
ISBN: 9811931127
Category : Technology & Engineering
Languages : en
Pages : 543
Book Description
This book serves as a reference for researchers and practitioners in academia and industry. Smart education, smart e-learning and smart pedagogy are emerging and rapidly growing areas that have a potential to transform existing teaching strategies, learning environments and educational activities and technology. They are focused at enabling instructors to develop innovative ways of achieving excellence in teaching in highly technological smart university and providing students with new opportunities to maximize their success using smart classrooms, smart systems and technology. This book contains the contributions presented at the 9th international KES conference on Smart Education and e-Learning (SEEL-2022) with the Smart Pedagogy as the main conference theme. It comprises of forty nine high-quality peer-reviewed papers that are grouped into several interconnected parts: Part 1—Smart Pedagogy, Part 2—Smart Education, Part 3—Smart e-Learning, Part 4—Smart University, Part 5—Smart Education: Systems and Technology, Part 6—Digital Humanities and Social Sciences for Smart University Development: the Innovative Methods, Models and Technologies, Part 7—Digital Transformation of Education and Economics in Smart University and Part 8—Smart Education for Children with Special Educational Needs. We believe this book will serve as a useful source of research data and valuable information for faculty, scholars, Ph.D. students, administrators and practitioners—those who are interested in smart education, smart e-learning and smart pedagogy.
Smart Education and e-Learning 2021
Author: Vladimir L. UskovPublisher: Springer Nature
ISBN: 9811628343
Category : Technology & Engineering
Languages : en
Pages : 506
Book Description
This book contains the contributions presented at the 8th International KES Conference on Smart Education and e-Learning (KES SEEL 2021), which being held as a virtual conference on June 14–16, 2021. It contains high-quality peer-reviewed papers that are grouped into several interconnected parts: smart education; smart e-learning; smart education: systems and technology; smart education: case studies and research; digital education and economics in smart university, smart university development: organizational, managerial and social Issues; smart universities and their Impact on students with disabilities. This book serves as a useful source of research data and valuable information on current research projects, best practices, and case studies for faculty, scholars, Ph.D. students, administrators, and practitioners— all those who are interested in smart education and smart e-learning.
Smart Education and e-Learning 2024
Author: Vladimir L. UskovPublisher: Springer Nature
ISBN: 9819749549
Category :
Languages : en
Pages : 210
Book Description
Algebraic Identification of Smart Systems
Author: Natalia A. SerdyukovaPublisher: Springer Nature
ISBN: 3030544702
Category : Technology & Engineering
Languages : en
Pages : 243
Book Description
This book is a continuation of our recently published book “Algebraic formalization of smart systems. Theory and practice.” It incorporates a new concept of quasi-fractal algebraic systems, based on A.I. Maltsev’s theory of algebraic systems and the theory of fractals developed by Benoit Mandelbrot, to investigate smart systems in more detail. The main tool used in the book, quasi-fractal algebraic systems, helps us to see smart systems in more detail by adding new factors, which e.g. make it possible to describe the previously indivisible elements of the initial model of factors. The techniques presented include fixed-point theorem, theorems of group theory, theory of Boolean algebras, and Erdös-Renyi algorithms. Given its focus, the book is intended for anyone interested in smart system theory.
Smart Education and e-Learning 2020
Author: Vladimir L. UskovPublisher: Springer Nature
ISBN: 9811555842
Category : Technology & Engineering
Languages : en
Pages : 610
Book Description
This book contains the contributions presented at the 7th international KES conference on Smart Education and e-Learning (KES SEEL-2020), which being held as a virtual conference on June 17-19, 2020. It contains fifty three high quality peer-reviewed papers that are grouped into several interconnected parts: Part 1 – Smart Education, Part 2 – Smart e-Learning, Part 3 – Smart Pedagogy, Part 4 - Smart Education: Systems and Technology, Part 5 – Smart Education: Case Studies and Research, Part 6 - Smart University Development: Organizational and Managerial Issues, Part 7 - Smart Education and Smart Universities and their Impact on Students with Disabilities, Part 8 - Mathematical Models in Smart Education and e-Learning, and Part 9 - Models of Professional Practice in Higher Education. Smart education and smart e-learning are emerging and rapidly growing areas with the potential to transform existing teaching strategies, learning environments, and educational activities and technology in the classroom. Smart education and smart e-learning focus on enabling instructors to develop new ways of achieving excellence in teaching in highly technological smart classrooms, and providing students with new opportunities to maximize their success and select the best options for their education, location and learning style, as well as the mode of content delivery. This book serves as a useful source of research data and valuable information on current research projects, best practices and case studies for faculty, scholars, Ph.D. students, administrators, and practitioners – all those who are interested in smart education and smart e-learning.
Algebraic Quasi—Fractal Logic of Smart Systems
Author: Natalia SerdyukovaPublisher: Springer
ISBN: 9783031660399
Category : Computers
Languages : en
Pages : 0
Book Description
This book is a continuation of the Algebraic Formalization of Smart Systems. Theory and Practice, 2018, and Algebraic Identification of Smart Systems. Theory and Practice, 2021. Algebraic logic refers to the connection between Boolean algebra and classical propositional calculus. This connection was discovered by George Boole and then developed by other mathematicians, such as C. S. Peirce and Ernst Schroeder. This trend culminated in the Lindenbaum-Tarski algebras. Here we try to connect algebraic logic and quasi-fractal technique, based on algebraic formalization of smart systems to get facts about smart systems functioning and connections of their qualitative and quantitative indicators. Basic techniques we used: algebraic quasi-fractal systems, Erdős–Rényi algorithm, a notion of –giant component of an algebraic system, fixed point theorem, purities, i.e., embeddings preserving -property of an algebraic system. The book is aimed for all interested in these issues.
An Introduction to Computational Learning Theory
Author: Michael J. KearnsPublisher: MIT Press
ISBN: 9780262111935
Category : Computers
Languages : en
Pages : 230
Book Description
Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.
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