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Machine Learning in Social Networks: Embedding Nodes, Edges, Communities, and Graphs (SpringerBriefs in Applied Sciences and Technology)
by Manasvi Aggarwal M.N. MurtyThis book deals with network representation learning. It deals with embedding nodes, edges, subgraphs and graphs. There is a growing interest in understanding complex systems in different domains including health, education, agriculture and transportation. Such complex systems are analyzed by modeling, using networks that are aptly called complex networks. Networks are becoming ubiquitous as they can represent many real-world relational data, for instance, information networks, molecular structures, telecommunication networks and protein–protein interaction networks. Analysis of these networks provides advantages in many fields such as recommendation (recommending friends in a social network), biological field (deducing connections between proteins for treating new diseases) and community detection (grouping users of a social network according to their interests) by leveraging the latent information of networks. An active and important area of current interest is to come out with algorithms that learn features by embedding nodes or (sub)graphs into a vector space. These tasks come under the broad umbrella of representation learning. A representation learning model learns a mapping function that transforms the graphs' structure information to a low-/high-dimension vector space maintaining all the relevant properties.
Evolutionary Data Clustering: Algorithms and Applications (Algorithms for Intelligent Systems)
by Ibrahim Aljarah Hossam Faris Seyedali MirjaliliThis book provides an in-depth analysis of the current evolutionary clustering techniques. It discusses the most highly regarded methods for data clustering. The book provides literature reviews about single objective and multi-objective evolutionary clustering algorithms. In addition, the book provides a comprehensive review of the fitness functions and evaluation measures that are used in most of evolutionary clustering algorithms. Furthermore, it provides a conceptual analysis including definition, validation and quality measures, applications, and implementations for data clustering using classical and modern nature-inspired techniques. It features a range of proven and recent nature-inspired algorithms used to data clustering, including particle swarm optimization, ant colony optimization, grey wolf optimizer, salp swarm algorithm, multi-verse optimizer, Harris hawks optimization, beta-hill climbing optimization. The book also covers applications of evolutionary data clustering in diverse fields such as image segmentation, medical applications, and pavement infrastructure asset management.
Quantum f-Divergences in von Neumann Algebras: Reversibility of Quantum Operations (Mathematical Physics Studies)
by Fumio HiaiRelative entropy has played a significant role in various fields of mathematics and physics as the quantum version of the Kullback–Leibler divergence in classical theory. Many variations of relative entropy have been introduced so far with applications to quantum information and related subjects. Typical examples are three different classes, called the standard, the maximal, and the measured f-divergences, all of which are defined in terms of (operator) convex functions f on (0,∞) and have respective mathematical and information theoretical backgrounds. The α-Rényi relative entropy and its new version called the sandwiched α-Rényi relative entropy have also been useful in recent developments of quantum information.In the first half of this monograph, the different types of quantum f-divergences and the Rényi-type divergences mentioned above in the general von Neumann algebra setting are presented for study. While quantum information has been developing mostly in the finite-dimensional setting, it is widely believed that von Neumann algebras provide the most suitable framework in studying quantum information and related subjects. Thus, the advance of quantum divergences in von Neumann algebras will be beneficial for further development of quantum information. Quantum divergences are functions of two states (or more generally, two positive linear functionals) on a quantum system and measure the difference between the two states. They are often utilized to address such problems as state discrimination, error correction, and reversibility of quantum operations. In the second half of the monograph, the reversibility/sufficiency theory for quantum operations (quantum channels) between von Neumann algebras via quantum f-divergences is explained, thus extending and strengthening Petz' previous work.For the convenience of the reader, an appendix including concise accounts of von Neumann algebras is provided.
Modern Classification Theory of Superconducting Gap Nodes (Springer Theses)
by Shuntaro SumitaThis book puts forward a modern classification theory for superconducting gap nodes, whose structures can be observed by experiments and are essential for understanding unconventional superconductivity. In the first part of the book, the classification method, based on group theory and K theory, is introduced in a step-by-step, pedagogical way. In turn, the latter part presents comprehensive classification tables, which include various nontrivial gap (node) structures, which are not predicted by the Sigrist-Ueda method, but are by the new method. The results obtained here show that crystal symmetry and/or angular momentum impose critical constraints on the superconducting gap structures. Lastly, the book lists a range of candidate superconductors for the nontrivial gap nodes. The classification methods and tables presented here offer an essential basis for further investigations into unconventional superconductivity. They indicate that previous experimental studies should be reinterpreted, while future experiments should reflect the new excitation spectrum.
Passivity of Complex Dynamical Networks: Analysis, Control and Applications
by Jin-Liang Wang Huai-Ning Wu Shun-Yan RenThis book intends to introduce some recent results on passivity of complex dynamical networks with single weight and multiple weights. The book collects novel research ideas and some definitions in complex dynamical networks, such as passivity, output strict passivity, input strict passivity, finite-time passivity, and multiple weights. Furthermore, the research results previously published in many flagship journals are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers and graduate students in Engineering and Mathematics who wish to study the passivity of complex dynamical networks.
Essential Tools for Water Resources Analysis, Planning, and Management (Springer Water)
by Omid Bozorg-HaddadThis book describes concepts and tools needed for water resources management, including methods for modeling, simulation, optimization, big data analysis, data mining, remote sensing, geographical information system, game theory, conflict resolution, System dynamics, agent-based models, multiobjective, multicriteria, and multiattribute decision making and risk and uncertainty analysis, for better and sustainable management of water resources and consumption, thus mitigating the present and future global water shortage crisis. It presents the applications of these tools through case studies which demonstrate its benefits of proper management of water resources systems. This book acts as a reference for students, professors, industrial practitioners, and stakeholders in the field of water resources and hydrology.
Design of Experiments for Pharmaceutical Product Development: Volume II : Applications and Practical Case studies
by Sarwar BegThis book volume provides complete and updated information on the applications of Design of Experiments (DoE) and related multivariate techniques at various stages of pharmaceutical product development. It discusses the applications of experimental designs that shall include oral, topical, transdermal, injectables preparations, and beyond for nanopharmaceutical product development, leading to dedicated case studies on various pharmaceutical experiments through illustrations, art-works, tables and figures. This book is a valuable guide for all academic and industrial researchers, pharmaceutical and biomedical scientists, undergraduate and postgraduate research scholars, pharmacists, biostatisticians, biotechnologists, formulations and process engineers, regulatory affairs and quality assurance personnel.
Proceedings of First International Conference on Mathematical Modeling and Computational Science: ICMMCS 2020 (Advances in Intelligent Systems and Computing #1292)
by Sheng-Lung Peng Rong-Xia Hao Souvik PalThis book presents the most recent scientific and technological advances in the fields of engineering mathematics and computational science, to strengthen the links in the scientific community. It is a collection of high-quality, peer-reviewed research papers presented at the First International Conference on Mathematical Modeling and Computational Science (ICMMCS 2020), held in Pattaya, Thailand, during 14–15 August 2020. The topics covered in the book are mathematical logic and foundations, numerical analysis, neural networks, fuzzy set theory, coding theory, higher algebra, number theory, graph theory and combinatory, computation in complex networks, calculus, differential educations and integration, application of soft computing, knowledge engineering, machine learning, artificial intelligence, big data and data analytics, high-performance computing, network and device security, and Internet of things (IoT).
Motions of Ice Hydrometeors in the Atmosphere: Numerical Studies and Implications (Atmosphere, Earth, Ocean & Space)
by Pao K. WangThis book summarizes unique research findings on the hydrodynamic behavior of ice particles (ice crystals, snow, graupel and hailstones) in the atmosphere. The fall behavior of ice hydrometeors determines how and how fast a mixed-phase cloud can grow or dissipate. The book discusses how the authors used computational fluid dynamics (CFD) methods and numerical simulations to determine these behaviors, and presents these computations along with numerous detailed tables and illustrations of turbulent flow fields. It also examines the implications of the results for the general atmospheric sciences as well as for climate science (since the cloud problem is the source of the greatest uncertainty in model-based climate predictions). As such it allows readers to gain a clear and comprehensive understanding of how particles fall in clouds and offers insights into cloud physics and dynamics and their impact on the climate..
Advanced Fixture Design Method and Its Application
by Guohua QinThis book uses kinematics, mechanics, mathematics, and so on, to systematically propose the fixturing performance evaluation and fixturing layout planning method. The proposed method is a novel method, including the analysis method of locating determination, the analysis method of workpiece stability, the analysis method of clamping reasonability, the analysis method of workpiece attachment/detachment, the analysis method of locating accuracy, and the planning algorithm of locating point layout, the planning algorithm of clamping force, and so forth. It can enrich and develop the basic theory of computer aided fixture design, change the empirical method of fixture design. The combination of theoretical analysis and mathematical modeling technology can resolve the key problems in the process of fixture design, which will play a certain role in promoting the progress of manufacturing technology, improving the precision and level of product manufacturing, and meeting the higher and higher requirements of mechanical manufacturing industry.
Distributed Optimization, Game and Learning Algorithms: Theory and Applications in Smart Grid Systems
by Huiwei Wang Huaqing Li Bo ZhouThis book provides the fundamental theory of distributed optimization, game and learning. It includes those working directly in optimization,-and also many other issues like time-varying topology, communication delay, equality or inequality constraints,-and random projections. This book is meant for the researcher and engineer who uses distributed optimization, game and learning theory in fields like dynamic economic dispatch, demand response management and PHEV routing of smart grids.
Mathematical Analysis and Computing: ICMAC 2019, Kalavakkam, India, December 23–24 (Springer Proceedings in Mathematics & Statistics #344)
by R. N. Mohapatra S. Yugesh G. Kalpana C. KalaivaniThis book is a collection of selected papers presented at the International Conference on Mathematical Analysis and Computing (ICMAC 2019) held at Sri Sivasubramaniya Nadar College of Engineering, Chennai, India, from 23–24 December 2019. Having found its applications in game theory, economics, and operations research, mathematical analysis plays an important role in analyzing models of physical systems and provides a sound logical base for problems stated in a qualitative manner. This book aims at disseminating recent advances in areas of mathematical analysis, soft computing, approximation and optimization through original research articles and expository survey papers. This book will be of value to research scholars, professors, and industrialists working in these areas.
Air Traffic Management and Systems IV: Selected Papers of the 6th ENRI International Workshop on ATM/CNS (EIWAC2019) (Lecture Notes in Electrical Engineering #731)
by Electronic Navigation Research InstituteThis book provides novel concepts and techniques for air traffic management (ATM) and communications, navigation, and surveillance (CNS) systems. The book consists of selected papers from the 6th ENRI International Workshop on ATM/CNS (EIWAC2019) held in Tokyo in October 2019, the theme of which was “Exploring Ideas for World Aviation Challenges”. Included are key topics to realize safer and more efficient skies in the future, linked to the integrated conference theme consisting of long-term visions based on presentations from various fields. The book is dedicated not only to researchers, academicians, and university students, but also to engineers in the industry, air navigation service providers (ANSPs), and regulators of aviation.
Theory of Generation and Conversion of Phonon Angular Momentum (Springer Theses)
by Masato HamadaThis book presents a theoretical study of the generation and conversion of phonon angular momentum in crystals.Recently, rotational motions of lattice vibrations, i.e., phonons, in crystals attract considerable attentions. As such, the book theoretically demonstrate generations of phonons with rotational motions, based on model calculations and first-principle calculations. In systems without inversion symmetry, the phonon angular momentum is shown to be caused by the temperature gradient, which is demonstrated in crystals such as wurtzite gallium nitride, tellurium, and selenium using the first-principle calculations. In systems with neither time-reversal nor inversion symmetries, the phonon angular momentum is shown to be generated by an electric field. Secondly, the book presents the microscopic mechanisms developed by the author and his collaborator on how these microscopic rotations of nuclei are coupled with electron spins. These predictions serve as building blocks for spintronics with phonons or mechanical motions.
Design of Experiments for Pharmaceutical Product Development: Volume I : Basics and Fundamental Principles
by Sarwar BegThis book volume provides complete and updated information on the applications of Design of Experiments (DoE) and related multivariate techniques at various stages of pharmaceutical product development. It discusses the applications of experimental designs that shall include oral, topical, transdermal, injectables preparations, and beyond for nanopharmaceutical product development, leading to dedicated case studies on various pharmaceutical experiments through illustrations, art-works, tables and figures. This book is a valuable guide for all academic and industrial researchers, pharmaceutical and biomedical scientists, undergraduate and postgraduate research scholars, pharmacists, biostatisticians, biotechnologists, formulations and process engineers, regulatory affairs and quality assurance personnel.
Proceedings of International Conference on Big Data, Machine Learning and Applications: BigDML 2019 (Lecture Notes in Networks and Systems #180)
by Ripon Patgiri Sivaji Bandyopadhyay Valentina Emilia BalasThis book covers selected high-quality research papers presented at the International Conference on Big Data, Machine Learning, and Applications (BigDML 2019). It focuses on both theory and applications in the broad areas of big data and machine learning. It brings together the academia, researchers, developers and practitioners from scientific organizations and industry to share and disseminate recent research findings.
Nonlinear Partial Differential Equations for Future Applications: Sendai, Japan, July 10–28 and October 2–6, 2017 (Springer Proceedings in Mathematics & Statistics #346)
by Shigeaki Koike Hideo Kozono Takayoshi Ogawa Shigeru SakaguchiThis volume features selected, original, and peer-reviewed papers on topics from a series of workshops on Nonlinear Partial Differential Equations for Future Applications that were held in 2017 at Tohoku University in Japan. The contributions address an abstract maximal regularity with applications to parabolic equations, stability, and bifurcation for viscous compressible Navier–Stokes equations, new estimates for a compressible Gross–Pitaevskii–Navier–Stokes system, singular limits for the Keller–Segel system in critical spaces, the dynamic programming principle for stochastic optimal control, two kinds of regularity machineries for elliptic obstacle problems, and new insight on topology of nodal sets of high-energy eigenfunctions of the Laplacian. This book aims to exhibit various theories and methods that appear in the study of nonlinear partial differential equations.
Semigroups, Categories, and Partial Algebras: ICSAA 2019, Kochi, India, December 9–12 (Springer Proceedings in Mathematics & Statistics #345)
by P. G. Romeo Mikhail V. Volkov A. R. RajanThis book is a collection of selected papers presented at the International Conference on Semigroups and Applications, held at the Cochin University of Science and Technology, India, from December 9–12, 2019. This book discusses the recent developments in semigroups theory, category theory and the applications of these in various areas of research, including structure theory of semigroups, lattices, rings and partial algebras. This book presents chapters on ordering orders and quotient rings, block groups and Hall’s relations, quotients of the Booleanization of inverse semigroup, Markov chains through semigroup graph expansions, polycyclic inverse monoids and Thompson group, balanced category and bundle category. This book will be of much value to researchers working in areas of semigroup and operator theory.
Signal Polarization Selection for Aircraft Radar Control: Models and Methods (Springer Aerospace Technology)
by Nikolay Kondratyevich Yurkov Alexey Yevgenyevich Bukharov Dmitry Alexandrovich ZatuchnyThis book highlights the synthesis of polarization selection system in the background of passive noise formed by reflections from space-distributed targets. This synthesis is fulfilled as close as possible to its ideal configuration in terms of maximal signal-to-noise ratio for the matched load of radar station antenna system. It presents a new approach to radar system resolution enhancement based on the development of mathematical model for radiometric receivers with mono-pulse antenna systems, as well as creation of a new algorithm that allows increasing angular resolution during the object’s search and tracking due to special signal processing.
Risk Management Methods in the Aviation Enterprise (Springer Aerospace Technology)
by Valery Dmitryevich Sharov Vadim Vadimovich Vorobyov Dmitry Alexandrovich ZatuchnyThis book provides a comprehensive content for professionals engaged in the development of flight safety regulatory framework, as well as in the design and operation of ground-based or on-board flight support radio electronic systems. It presents mathematical tools and methods of probabilistic theory, mathematical statistics and graph theory, along with some provisions of decision-making theory and multi-criteria analysis. This book helps as a good guide for those involved in aviation risk assessment and air traffic management.
Theory and Application of Acoustic Sources Using Complex Analysis: Complex Acoustic Sources, Green’s Functions and Half-Space Problems, Acoustic Radiation and Scattering Using Equivalent Source and Boundary Element Methods
by Martin Ochmann Rafael PiscoyaThis book highlights the mathematical and physical properties of acoustical sources with singularities located in the complex plane and presents the application of such special elements to solve acoustical radiation and scattering problems. Sources whose origin lies in the complex plane are also solutions of the wave equation but possess different radiating properties as their counterparts with real positions. Such mathematical constructions are known in the fields of optics and electrodynamics, but they are not common in acoustical research. The objective of the book is to introduce this concept to acousticians and motivate them to engage themselves in further research and application of complex sources. Such sources are particularly useful to formulate Green’s functions and related equivalent source and boundary element methods in half-spaces.
Applications of Flower Pollination Algorithm and its Variants (Springer Tracts in Nature-Inspired Computing)
by Nilanjan DeyThis book presents essential concepts of traditional Flower Pollination Algorithm (FPA) and its recent variants and also its application to find optimal solution for a variety of real-world engineering and medical problems. Swarm intelligence-based meta-heuristic algorithms are extensively implemented to solve a variety of real-world optimization problems due to its adaptability and robustness. FPA is one of the most successful swarm intelligence procedures developed in 2012 and extensively used in various optimization tasks for more than a decade. The mathematical model of FPA is quite straightforward and easy to understand and enhance, compared to other swarm approaches. Hence, FPA has attracted attention of researchers, who are working to find the optimal solutions in variety of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization, and linear/nonlinear optimization problems. Along with the traditional bat algorithm, the enhanced versions of FPA are also considered to solve a variety of optimization problems in science, engineering, and medical applications.
Deep Learning and Physics (Mathematical Physics Studies)
by Akinori Tanaka Akio Tomiya Koji HashimotoWhat is deep learning for those who study physics? Is it completely different from physics? Or is it similar? In recent years, machine learning, including deep learning, has begun to be used in various physics studies. Why is that? Is knowing physics useful in machine learning? Conversely, is knowing machine learning useful in physics? This book is devoted to answers of these questions. Starting with basic ideas of physics, neural networks are derived naturally. And you can learn the concepts of deep learning through the words of physics.In fact, the foundation of machine learning can be attributed to physical concepts. Hamiltonians that determine physical systems characterize various machine learning structures. Statistical physics given by Hamiltonians defines machine learning by neural networks. Furthermore, solving inverse problems in physics through machine learning and generalization essentially provides progress and even revolutions in physics. For these reasons, in recent years interdisciplinary research in machine learning and physics has been expanding dramatically. This book is written for anyone who wants to learn, understand, and apply the relationship between deep learning/machine learning and physics. All that is needed to read this book are the basic concepts in physics: energy and Hamiltonians. The concepts of statistical mechanics and the bracket notation of quantum mechanics, which are explained in columns, are used to explain deep learning frameworks.We encourage you to explore this new active field of machine learning and physics, with this book as a map of the continent to be explored.
Fintech with Artificial Intelligence, Big Data, and Blockchain (Blockchain Technologies)
by Paul Moon Sub Choi Seth H. HuangThis book introduces readers to recent advancements in financial technologies. The contents cover some of the state-of-the-art fields in financial technology, practice, and research associated with artificial intelligence, big data, and blockchain—all of which are transforming the nature of how products and services are designed and delivered, making less adaptable institutions fast become obsolete. The book provides the fundamental framework, research insights, and empirical evidence in the efficacy of these new technologies, employing practical and academic approaches to help professionals and academics reach innovative solutions and grow competitive strengths.
Nature-Inspired Computing for Smart Application Design (Springer Tracts in Nature-Inspired Computing)
by Santosh Kumar Das Thanh-Phong Dao Thinagaran PerumalThis book focuses primarily on the nature-inspired approach for designing smart applications. It includes several implementation paradigms such as design and path planning of wireless network, security mechanism and implementation for dynamic as well as static nodes, learning method of cloud computing, data exploration and management, data analysis and optimization, decision taking in conflicting environment, etc. The book fundamentally highlights the recent research advancements in the field of engineering and science.