This volume considers resistance networks: large graphs which are connected, undirected, and weighted. Such networks provide a discrete model for physical processes in inhomogeneous media, including heat flow through perforated or porous media. These graphs also arise in data science, e.g., considering geometrizations of datasets, statistical inference, or the propagation of memes through social networks. Indeed, network analysis plays a crucial role in many other areas of data science and engineering. In these models, the weights on the edges may be understood as conductances, or as a measure of similarity. Resistance networks also arise in probability, as they correspond to a broad class of Markov chains.The present volume takes the nonstandard approach of analyzing resistance networks from the point of view of Hilbert space theory, where the inner product is defined in terms of Dirichlet energy. The resulting viewpoint emphasizes orthogonality over convexity and provides new insights into the connections between harmonic functions, operators, and boundary theory. Novel applications to mathematical physics are given, especially in regard to the question of self-adjointness of unbounded operators.New topics are covered in a host of areas accessible to multiple audiences, at both beginning and more advanced levels. This is accomplished by directly linking diverse applied questions to such key areas of mathematics as functional analysis, operator theory, harmonic analysis, optimization, approximation theory, and probability theory.

Data Science: Theory and Applications, Volume 44 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of interesting topics, including Modeling extreme climatic events using the generalized extreme value distribution, Bayesian Methods in Data Science, Mathematical Modeling in Health Economic Evaluations, Data Science in Cancer Genomics, Blockchain Technology: Theory and Practice, Statistical outline of animal home ranges, an application of set estimation, Application of Data Handling Techniques to Predict Pavement Performance, Analysis of individual treatment effects for enhanced inferences in medicine, and more. Additional sections cover Nonparametric Data Science: Testing Hypotheses in Large Complex Data, From Urban Mobility Problems to Data Science Solutions, and Data Structures and Artificial Intelligence Methods.

A recent development is the discovery that simple systems of equations can have chaotic solutions in which small changes in initial conditions have a large effect on the outcome, rendering the corresponding experiments effectively irreproducible and unpredictable. An earlier book in this sequence, Elegant Chaos: Algebraically Simple Chaotic Flows provided several hundred examples of such systems, nearly all of which are purely mathematical without any obvious connection with actual physical processes and with very limited discussion and analysis.In this book, we focus on a much smaller subset of such models, chosen because they simulate some common or important physical phenomenon, usually involving the motion of a limited number of point-like particles, and we discuss these models in much greater detail. As with the earlier book, the chosen models are the mathematically simplest formulations that exhibit the phenomena of interest, and thus they are what we consider 'elegant.'Elegant models, stripped of unnecessary detail while maximizing clarity, beauty, and simplicity, occupy common ground bordering both real-world modeling and aesthetic mathematical analyses. A computational search led one of us (JCS) to the same set of differential equations previously used by the other (WGH) to connect the classical dynamics of Newton and Hamilton to macroscopic thermodynamics. This joint book displays and explores dozens of such relatively simple models meeting the criteria of elegance, taste, and beauty in structure, style, and consequence.This book should be of interest to students and researchers who enjoy simulating and studying complex particle motions with unusual dynamical behaviors. The book assumes only an elementary knowledge of calculus. The systems are initial-value iterated maps and ordinary differential equations but they must be solved numerically. Thus for readers a formal differential equations course is not at all necessary, of little value and limited use.

Classical Deformation Theory is used for determining the completions of the local rings of an eventual moduli space. When a moduli variety exists, a main result in the book is that the local ring in a closed point can be explicitly computed as an algebraization of the pro-representing hull (therefore, called the local formal moduli) of the deformation functor for the corresponding closed point.The book gives explicit computational methods and includes the most necessary prerequisites. It focuses on the meaning and the place of deformation theory, resulting in a complete theory applicable to moduli theory. It answers the question 'why moduli theory' and it give examples in mathematical physics by looking at the universe as a moduli of molecules. Thereby giving a meaning to most noncommutative theories.The book contains the first explicit definition of a noncommutative scheme, covered by not necessarily commutative rings. This definition does not contradict any of the previous abstract definitions of noncommutative algebraic geometry, but rather gives interesting relations to other theories which is left for further investigation.

The Blockchain Technology for Secure and Smart Applications across Industry Verticals, Volume 121, presents the latest information on a type of distributed ledger used for maintaining a permanent and tamper-proof record of transactional data. The book presents a novel compendium of existing and budding Blockchain technologies for various smart applications. Chapters in this new release include the Basics of Blockchain, The Blockchain History, Architecture of Blockchain, Core components of Blockchain, Blockchain 2.0: Smart Contracts, Empowering Digital Twins with Blockchain, Industrial Use Cases at the Cusp of the IoT and Blockchain Paradigms, Blockchain Components and Concepts, Digital Signatures, Accumulators, Financial Systems, and more. This book is a unique effort to illuminate various techniques to represent, improve and authorize multi-institutional and multidisciplinary research in a different type of smart applications, like the financial system, smart grid, transportation system, etc. Readers in identity-privacy, traceability, immutability, transparency, auditability, and security will find it to be a valuable resource.

Besides their intrinsic mathematical interest, geometric partial differential equations (PDEs) are ubiquitous in many scientific, engineering and industrial applications. They represent an intellectual challenge and have received a great deal of attention recently. The purpose of this volume is to provide a missing reference consisting of self-contained and comprehensive presentations. It includes basic ideas, analysis and applications of state-of-the-art fundamental algorithms for the approximation of geometric PDEs together with their impacts in a variety of fields within mathematics, science, and engineering.

The Handbook of Reliability, Maintenance, and System Safety through Mathematical Modeling discusses the many factors affect reliability and performance, including engineering design, materials, manufacturing, operations, maintenance, and many more. Reliability is one of the fundamental criteria in engineering systems design, with maintenance serving as a way to support reliability throughout a system's life. Addressing these issues requires information, modeling, analysis and testing. Different techniques are proposed and implemented to help readers analyze various behavior measures (in terms of the functioning and performance) of systems.

The modelling of systems by differential equations usually requires that the parameters involved be completely known. Such models often originate from problems in physics or economics where we have insufficient information on parameter values. One important class of stochastic mathematical models is stochastic partial differential equations (SPDEs), which can be seen as deterministic partial differential equations (PDEs) with finite or infinite dimensional stochastic processes - either with colour noise or white noise. Though white noise is a purely mathematical construction, it can be a good model for rapid random fluctuations.This research monograph concerns analysis of discrete-time approximations for stochastic differential equations (SDEs) driven by Wiener processes. The first chapter of the book provides a theoretical basis for working with SDEs and stochastic processes.This book has been written in a simple and clear mathematical logical language. The basic definitions and theorems on stochastic calculus have been provided initially. Each chapter contains illustrated examples via figures and tables. Problems are included which will help readers understand the theories better. Also, the reader can construct new wavelets by using the procedure presented in the book. It will certainly fill up the blank space that the lack of a comprehensive book has caused.

AI and Cloud Computing, Volume 120 in the Advances in Computers series, highlights new advances in the field, with this updated volume presenting interesting chapters on topics including A Deep-forest based Approach for Detecting Fraudulent Online Transaction, Design of Cyber-Physical-Social Systems with Forensic-awareness Based on Deep Learning, Review on Privacy-preserving Data Comparison Protocols in Cloud Computing, Fingerprint Liveness Detection Using an Improved CNN with the Spatial Pyramid Pooling Structure, Protecting Personal Sensitive Data Security in the Cloud with Blockchain, and more.

This is a book for the second course in linear algebra whereby students are assumed to be familiar with calculations using real matrices. To facilitate a smooth transition into rigorous proofs, it combines abstract theory with matrix calculations.This book presents numerous examples and proofs of particular cases of important results before the general versions are formulated and proved. The knowledge gained from a particular case, that encapsulates the main idea of a general theorem, can be easily extended to prove another particular case or a general case. For some theorems, there are two or even three proofs provided. In this way, students stand to gain and study important results from different angles and, at the same time, see connections between different results presented in the book.