This book offers an introduction to applications prompted by tensor analysis, especially by the spectral tensor theory developed in recent years. It covers applications of tensor eigenvalues in multilinear systems, exponential data fitting, tensor complementarity problems, and tensor eigenvalue complementarity problems. It also addresses higher-order diffusion tensor imaging, third-order symmetric and traceless tensors in liquid crystals, piezoelectric tensors, strong ellipticity for elasticity tensors, and higher-order tensors in quantum physics. This book is a valuable reference resource for researchers and graduate students who are interested in applications of tensor eigenvalues.

The book presents a coherent understanding of computational intelligence from the perspective of what is known as "intelligent computing" with high-dimensional parameters. It critically discusses the central issue of high-dimensional neurocomputing, such as quantitative representation of signals, extending the dimensionality of neuron, supervised and unsupervised learning and design of higher order neurons. The strong point of the book is its clarity and ability of the underlying theory to unify our understanding of high-dimensional computing where conventional methods fail. The plenty of application oriented problems are presented for evaluating, monitoring and maintaining the stability of adaptive learning machine. Author has taken care to cover the breadth and depth of the subject, both in the qualitative as well as quantitative way. The book is intended to enlighten the scientific community, ranging from advanced undergraduates to engineers, scientists and seasoned researchers in computational intelligence.

Hydroelectric power stations are a major source of electricity around the world; understanding their dynamics is crucial to achieving good performance. The electrical power generated is normally controlled by individual feedback loops on each unit. The reference input to the power loop is the grid frequency deviation from its set point, thus structuring an external frequency control loop. The book discusses practical and well-documented cases of modelling and controlling hydropower stations, focused on a pumped storage scheme based in Dinorwig, North Wales. These accounts are valuable to specialist control engineers who are working in this industry. In addition, the theoretical treatment of modern and classic controllers will be useful for graduate and final year undergraduate engineering students. This book reviews SISO and MIMO models, which cover the linear and nonlinear characteristics of pumped storage hydroelectric power stations. The most important dynamic features are discussed. The verification of these models by hardware in the loop simulation is described. To show how the performance of a pumped storage hydroelectric power station can be improved, classical and modern controllers are applied to simulated models of Dinorwig power plant, that include PID, Fuzzy approximation, Feed-Forward and Model Based Predictive Control with linear and hybrid prediction models.

This book focuses on the stability analysis of Markovian jump systems (MJSs) with various settings and discusses its applications in several different areas. It also presents general definitions of the necessary concepts and an overview of the recent developments in MJSs. Further, it addresses the general robust problem of Markovian jump linear systems (MJLSs), the asynchronous stability of a class of nonlinear systems, the robust adaptive control scheme for a class of nonlinear uncertain MJSs, the practical stability of MJSs and its applications as a modelling tool for networked control systems, Markovian-based control for wheeled mobile manipulators and the jump-linear-quadratic (JLQ) problem of a class of continuous-time MJLSs. It is a valuable resource for researchers and graduate students in the field of control theory and engineering.

This book presents the construction and resolution of 50 practical optimization problems and covers an exceptionally wide range, including games-associated problems (Unblock Me, Sudokus), logistical problems, and problems concerning plant distribution, production, operations scheduling, management and resource allocation. The problems are divided into 5 difficulty levels. Problems in the first few levels are focused on learning the model construction methodology, while those in the last level include complex optimization environments. For each problem solution, the specific steps are illustrated, promoting reader comprehension. In addition, all the models are implemented in an optimization library, LINGO, their solutions have been analyzed and their correct construction has been verified. The book also includes a simple guide to implementing models in LINGO in a straightforward manner and in any input data format (text files, spreadsheets or databases). As an ideal companion to the author's previously published work Modelling in Mathematical Programming, the book is intended as a basic tool for students of operations research, and for researchers in any advanced area involving mathematical programming.

This book adopts numerical method to model soil constitutive relationship while it abandons the traditional idea of looking for plastic potential as the only way to model. Firstly, the triaxial compression tests of expansive soil, sand and clay under different stress paths are introduced; then the elastoplastic constitutive equations of expansive soil, sand and clay under various stress paths are established by numerical modeling method; finally, the constitutive equations are embedded in the finite element program and verified by comparing the finite element calculation results of the triaxial test soil samples with the corresponding test results. The modeling obtains high accuracy.

Since its inception in 2013, Mathematics of Planet Earth (MPE) focuses on mathematical issues arising in the study of our planet. Interested in the impact of human activities on the Earth's system, this multidisciplinary field considers the planet not only as a physical system, but also as a system supporting life, a system organized by humans, and a system at risk. The articles collected in this volume demonstrate the breadth of techniques and tools from mathematics, statistics, and operations research used in MPE. Topics include climate modeling, the spread of infectious diseases, stability of ecosystems, ecosystem services, biodiversity, infrastructure restoration after an extreme event, urban environments, food security, and food safety. Demonstrating the mathematical sciences in action, this book presents real-world challenges for the mathematical sciences, highlighting applications to issues of current concern to society. Arranged into three topical sections (Geo- and Physical Sciences; Life Sciences, Ecology and Evolution; Socio-economics and Infrastructure), thirteen chapters address questions such as how to measure biodiversity, what mathematics can say about the sixth mass extinction, how to optimize the long-term human use of natural capital, and the impact of data on infrastructure management. The book also treats the subject of infectious diseases with new examples and presents an introduction to the mathematics of food systems and food security. Each chapter functions as an introduction that can be studied independently, offering source material for graduate student seminars and self-study. The range of featured research topics provides mathematical scientists with starting points for the study of our planet and the impact of human activities. At the same time, it offers application scientists a plethora of modern mathematical tools and techniques to address the various topics in practice. Including hundreds of references to the vast literature associated with each topic, this book serves as an inspiration for further research.

Produced by an award-winning translator of Henri Poincare, this book contains translations of several seminal articles by Poincare and discusses the experimental and theoretical investigations of electrons that form their context. In the 1950s, a dispute ignited about the origin of the theory of special relativity and thrust considerable notoriety on a paper written by Henri Poincare in 1905. Accordingly, Part I presents the relevant translations of Poincare's work showing that radiation carries momentum and the covariance of the equations of electrodynamics, the continuity equation for charge, and the spacetime interval. Part II then discusses investigations by Thomson, Becquerel, and Kaufmann of electrons in diverse contexts; contributions of Abraham, Lorentz and Poincare to a theory of electrons that includes Lorentz transformations and explains the dependence of mass on velocity; and finally, Poincare's exploration of the relativity principle, electron stability, and gravitation while rejecting absolute motion (ether) and an electromagnetic origin of mass. Part III contains the 1904 article by H. A. Lorentz presenting his transformations.This book will be a fascinating read to graduate-level students, physicists, and science historians who are interested in the development of electrodynamics and the classical, relativistic theory of electrons at the beginning of the 20th century.

This book presents practical optimization techniques used in image processing and computer vision problems. Ill-posed problems are introduced and used as examples to show how each type of problem is related to typical image processing and computer vision problems. Unconstrained optimization gives the best solution based on numerical minimization of a single, scalar-valued objective function or cost function. Unconstrained optimization problems have been intensively studied, and many algorithms and tools have been developed to solve them. Most practical optimization problems, however, arise with a set of constraints. Typical examples of constraints include: (i) pre-specified pixel intensity range, (ii) smoothness or correlation with neighboring information, (iii) existence on a certain contour of lines or curves, and (iv) given statistical or spectral characteristics of the solution. Regularized optimization is a special method used to solve a class of constrained optimization problems. The term regularization refers to the transformation of an objective function with constraints into a different objective function, automatically reflecting constraints in the unconstrained minimization process. Because of its simplicity and efficiency, regularized optimization has many application areas, such as image restoration, image reconstruction, optical flow estimation, etc. Optimization plays a major role in a wide variety of theories for image processing and computer vision. Various optimization techniques are used at different levels for these problems, and this volume summarizes and explains these techniques as applied to image processing and computer vision.

This textbook is unique because of its in-depth treatment of the applications of wavelets and wavelet transforms to many areas, across many disciplines. The book is written to serve the needs of a one or two semester course at either the undergraduate or graduate level. The author uses a very simplified, accessible approach that de-emphasizes mathematical rigor. The presentation includes many diagrams to illustrate points being discussed and uses MATLAB for all of application code. The author reinforces concepts introduced in the book with easy to grasp review questions and problems, tailored to each specific chapter for better mastery of the subject matter. This book enables students to understand the fundamental concepts of wavelets and wavelet transforms, as well as how to use them for problem solutions in digital signal and image processing, mixed-signal testing, space applications, aerospace applications, biomedical, cyber security, homeland security and many other application areas.

The book conveys modern techniques and the latest state-of-the-art with regard to the most fundamental aspects of computational contact mechanics. However, since contact can readily be interpreted as a special type of interface problem, it seems advisable not to isolate contact mechanics, but rather to address it in the context of a broader class of problems denoted as computational interface mechanics. The book gives a clear understanding of the underlying physics of interfaces, and a comprehensive insight into the current state-of-the-art and selected cutting-edge research directions in the computational treatment of interface effects. It focuses on the modeling of friction, wear, lubrication, cohesive interfaces, grain boundaries, phase boundaries, fracture, thermo-mechanics and particulate contact (e.g. granular media). Also the most important computational aspects are addressed, including discretization techniques for finite deformations, solution algorithms for single- and multi-processor computing environments, multi-scale approaches, discrete element models and multi-physics problems including contact and interface constraints. Among the computational techniques covered in this book are finite element (FEM) and boundary element (BEM) methods, atomistic models, molecular dynamics (MD), discrete element methods (DEM), coupling approaches for multi-scale simulations, and tools for an efficient automated FEM code generation.

"The book of nature is written in the language of mathematics "-- "Galileo Galilei"

How is it possible to predict weather patterns for tomorrow, with access solely to today s weather data? And how is it possible to predict the aerodynamic behavior of an aircraft that has yet to be built?

The answer is computer simulations based on mathematical models sets of equations that describe the underlying physical properties. However, these equations are usually much too complicated to solve, either by the smartest mathematician or the largest supercomputer. This problem is overcome by constructing an approximation: a numerical model with a simpler structure can be translated into a program that tells the computer how to carry out the simulation.

This book conveys the fundamentals of mathematical models, numerical methods and algorithms. Opening with a tutorial on mathematical models and analysis, it proceeds to introduce the most important classes of numerical methods, with finite element, finite difference and spectral methods as central tools. The concluding section describes applications in physics and engineering, including wave propagation, heat conduction and fluid dynamics. Also covered are the principles of computers and programming, including MATLAB(r).

This is the first textbook to address quantified risk assessment (QRA) as specifically applied to offshore installations and operations. As the first part of the two-volume updated and expanded fourth edition, it adds a new focus on the EU Offshore Safety Directive, and discusses the new perspective on risk from the Norwegian Petroleum Safety Authority, followed by new and updated international standards. New safety statistics for the Norwegian sectors are presented, as well as new case studies on international offshore accidents, such as the explosion on FPSO Sao Mateus in 2015, which involved 9 fatalities. Separate chapters analyse the main hazards for offshore structures: fire, explosion, collision, and falling objects, as well as structural and marine hazards. Risk mitigation and control are discussed, as well as how the results of quantitative risk assessment studies should be presented. The fourth edition presents updated hydrocarbon release statistics, together with new methods for modelling the risk from ignited hydrocarbon releases. There have been recent advances in the modelling of collision risk from passing and attending vessels, based on extensive research; these advances are described in detail, in addition to new developments in the safety of Dynamic Positioning vessels. In closing, the book provides updated statistics and lessons learned from accidents involving offshore helicopter transportation of personnel. The book offers a comprehensive reference guide for academics and students of marine/offshore risk assessment and management. It will also be of interest to professionals in the industry, as well as contractors, suppliers, consultants and regulatory authorities.

This volume reports on a large variety of mathematical simulations, covering all production steps of special glass manufacturing: melting, fining, mixing, homogenizing, hot and cold forming, thermal treatment, post-processing. Modern, commercially available software packages have been used and - whenever necessary - modified to satisfy the special requirements and situations in liquid or solid glasses, or the boundary conditions of forming processes. The mathematical approach often helps in understanding the overall and sometimes hidden features of processes and thus is a highly efficient tool for optimization efforts. Complementing and partly replacing experimental investigations, mathematical simulation makes possible considerable savings in time and money. Several of the results reported here are unique and published for the first time. The CD-ROM shows 27 simulations of different aspects such as surprising details of the pressing and casting process.

Mathematical modeling is a powerful craft that requires practice. The more practice the better one will become in executing the art. The authors wrote this book to develop the craft of mathematical modeling and to foster a desire for lifelong learning, habits of mind and develop competent and confident problem solvers and decision makers for the 21st century. This book offers a problem-solving approach. The authors introduce a problem to help motivate the learning of a particular mathematical modeling topic. The problem provides the issue or what is needed to solve using an appropriate modeling technique. Then principles are applied to the problem and present the steps in obtaining an appropriate model to solve the problem. Modeling Change and Uncertainty: Covers both linear and nonlinear models of discrete dynamical systems. Introduces statistics and probability modeling. Introduces critical statistical concepts to handle univariate and multivariate data. Establishes a foundation in probability modeling. Uses ordinary differential equations (ODEs) to develop a more robust solution to problems. Uses linear programming and machine learning to support decision making. Introduces the reality of uncertainty and randomness that is all around us. Discusses the use of linear programing to solve common problems in modern industry. Discusses he power and limitations of simulations. Introduces the methods and formulas used in businesses and financial organizations. Introduces valuable techniques using Excel, MAPLE, and R. Mathematical modeling offers a framework for decision makers in all fields. This framework consists of four key components: the formulation process, the solution process, interpretation of the solution in the context of the actual problem, and sensitivity analysis. Modeling Change and Uncertainty will be of interest to mathematics departments offering advanced mathematical modeling courses focused on decision making or discrete mathematical modeling and by undergraduate, graduate students and practitioners looking for an opportunity to develop, practice, and apply the craft of mathematical modeling. Table of Contents 1. Perfect Partners: Combining Models of Change and Uncertainty with Technology 2. Modeling Change: Discrete Dynamical Systems (DDS) and Modeling Systems of DDS 3. Statistical and Probabilistic Models 4. Modeling with Probability 5. Differential Equations 6. Forecasting with Linear Programming and Machine Learning 7. Stochastic Models and Markov Chains 8. Linear Programming 9. Simulation of Queueing Models 10. Modeling of Financial Analysis 11. Reliability Models 12. Machine Learning and Unconstrained Optimal Process Dr. William P. Fox is currently a visiting professor of Computational Operations Research at the College of William and Mary. He is an emeritus professor in the Department of Defense Analysis at the Naval Postgraduate School and teaches a three-course sequence in mathematical modeling for decision making. He received his Ph.D. in Industrial Engineering from Clemson University. He has taught at the United States Military Academy for twelve years until retiring and at Francis Marion University where he was the chair of mathematics for eight years. He has many publications and scholarly activities including twenty plus books and one hundred and fifty journal articles. Colonel (R) Robert E. Burks, Jr., Ph.D. is an Associate Professor in the Defense Analysis Department of the Naval Postgraduate School (NPS) and the Director of the NPS' Wargaming Center. He holds a Ph.D. in Operations Research from the Air Force Institute of Technology. He is a retired logistics Army Colonel with more than thirty years of military experience in leadership, advanced analytics, decision modeling, and logistics operations who served as an Army Operations Research analyst at the Naval Postgraduate School, TRADOC Analysis Center, United States Military Academy, and the United States Army Recruiting Command. Other book by William P. Fox and Robert E. Burks: Advanced Mathematical Modeling with Technology, 2021, CRC Press. Other books by William P. Fox from CRC Press: Mathematical Modeling in the Age of the Pandemic, 2021, CRC Press. Advanced Problem Solving Using Maple: Applied Mathematics, Operations Research, Business Analytics, and Decision Analysis (w/William Bauldry), 2020, CRC Press. Mathematical Modeling with Excel (w/Brian Albright), 2020, CRC Press. Nonlinear Optimization: Models and Applications, 2020, CRC Press. Advanced Problem Solving with Maple: A First Course (w/William Bauldry), 2019. CRC Press. Mathematical Modeling for Business Analytics, 2018, CRC Press.

Includes a balanced coverage of modeling as well as applications of layout, materials handling, and warehousing Presents automated materials handling and warehousing along with queuing, queuing network, and basic simulation modeling Introduces new material on supply chain designing and management, aggregate planning and stochastic inventory control, transportation, and logistics/distribution Provides Layout-iQ software and data files from the authors own website Offers a solutions manual and PowerPoint slides for qualified textbook adoption

COVID Transmission Modeling: An Insight into Infectious Diseases Mechanism provides an interdisciplinary overview of the COVID-19 pandemic crisis and covers various aspects of newer modeling techniques and practical solutions for health emergencies. This book aims to formulate various innovative and pragmatic mathematical, statistical, and epidemiological models using COVID-19 real data sets. It emphasizes interdisciplinary theoretical postulates derived from practical insights and knowledge of public health. Each of the book's 12 chapters provides invaluable and exploratory tools to enable explicit assumptions, highlights key health indicators, and determines the geometric progression and control measures of the disease. The present developed models will allow readers to extrapolate the exact reason for the outbreak and pave the way for scientific information on vaccine trials and socioeconomic, psychological, and disease burden worldwide. These advanced techniques of modeling and their applications are in greater need than ever for effective connection between mathematicians, statisticians, epidemiologists, researchers, clinicians, and policymakers for making appropriate decisions at the right time. With the advent of emerging health science, all models are demonstrated with real-life data sets and provided with illustrations and eye-catching graphs and diagrams so that the readers can easily understand the concept of COVID-19 pandemic interventions and their control measures, and their impact. Features Addresses all aspects of mitigation/control measures, estimation of transmission rate, economic impact assessment, genetic complexity of COVID-19, herd immunity, and various methods, including newer mathematical, statistical, and epidemiological models in the analysis of COVID-19 pandemic outbreak Covers the application of innovative, advanced statistical and epidemiological models and demonstrates possible solutions toward supportive treatment aspects of COVID-19 and its control measures Includes models that can easily be followed in formulating the mathematical derivations and key points Supplemented with ample illustrations, images, diagrams, and figures This book is aimed at postgraduate students studying medicine and healthcare, mathematics, and statistical information. Researchers will also find this book very helpful.

This book addresses the functioning of financial markets, in particular the financial market model, and modelling. More specifically, the book provides a model of adaptive preference in the financial market, rather than the model of the adaptive financial market, which is mostly based on Popper's objective propensity for the singular, i.e., unrepeatable, event. As a result, the concept of preference, following Simon's theory of satisficing, is developed in a logical way with the goal of supplying a foundation for a robust theory of adaptive preference in financial market behavior. The book offers new insights into financial market logic, and psychology: 1) advocating for the priority of behavior over information - in opposition to traditional financial market theories; 2) constructing the processes of (co)evolution adaptive preference-financial market using the concept of fetal reaction norms - between financial market and adaptive preference; 3) presenting a new typology of information in the financial market, aimed at proving point (1) above, as well as edifying an explicative mechanism of the evolutionary nature and behavior of the (real) financial market; 4) presenting sufficient, and necessary, principles or assumptions for developing a theory of adaptive preference in the financial market; and 5) proposing a new interpretation of the pair genotype-phenotype in the financial market model. The book's distinguishing feature is its research method, which is mainly logically rather than historically or empirically based. As a result, the book is targeted at generating debate about the best and most scientifically beneficial method of approaching, analyzing, and modelling financial markets.

Dynamics is what characterizes virtually all phenomenae we face in the real world, and processes that proceed in practically all kinds of inanimate and animate systems, notably social systems. For our purposes dynamics is viewed as time evolution of some characteristic features of the phenomenae or processes under consideration. It is obvious that in virtually all non-trivial problems dynamics can not be neglected, and should be taken into account in the analyses to, first, get insight into the problem consider, and second, to be able to obtain meaningful results.

A convenient tool to deal with dynamics and its related evolution over time is to use the concept of a dynamic system which, for the purposes of this volume can be characterized by the input (control), state and output spaces, and a state transition equation. Then, starting from an initial state, we can find a sequence of consecutive states (outputs) under consecutive inputs (controls). That is, we obtain a trajectory. The state transition equation may be given in various forms, exemplified by differential and difference equations, linear or nonlinear, deterministic or stochastic, or even fuzzy (imprecisely specified), fully or partially known, etc. These features can give rise to various problems the analysts may encounter like numerical difficulties, instability, strange forms of behavior (e.g. chaotic), etc.

This volume is concerned with some modern tools and techniques which can be useful for the modeling of dynamics. We focus our attention on two important areas which play a key role nowadays, namely automation and robotics, and biological systems. We also add some new applications which can greatly benefit from the availability of effective and efficient tools for modeling dynamics, exemplified by some applications in security systems.

From Markov Jump Processes to Spatial Queues aims to develop a unified theory of spatial queues that yields concrete results for the performance analysis of mobile communication networks. A particular objective is to develop the most natural generalization of existing concepts (e.g. the BMAP) toward the needs of mobile communication networks. To these belong the spatial distribution of batch arrivals and users in the system as well as time-inhomogeneous (e.g. periodic) arrival intensities and user movements.

One of the major recent challenges for the stochastic modelling of communication systems is the emergence of wireless networks, which are used by more and more subscribers today. The main new feature of those, which is not covered by classical queuing theory, clearly is the importance of the user location within the area that is served by the base stations of the network.

In the framework of queuing theory, this opens up the natural extension of classical queuing models towards queues with a structured space in which users are served. The present book is intended to introduce this extension under the name of spatial queues. The main point of view and the general approach will be that of Markov jump processes. We start with a closer look into the theory. Then we present new results for the theory of stochastic processes as well as for classical queuing theory. Finally we introduce the new concepts of spatial Markovian arrival processes and spatial queues.

The main text is divided into three parts. The first part provides a new presentation of the theory of Markov jump processes. We derive a number of new results, especially for time-inhomogeneous processes, which have been neglected too much in the current textbooks on stochastic processes. For the first time, the class of Markov-additive jump processes is analysed in detail. This extends and unifies all Markovian arrival processes that have been proposed up to now (including arrivals for fluid queues) and provides a foundation for the subsequent introduction of spatial Markovian arrival processes.

The second part contains new results for classical queues with BMAP input. These include the first explicit formulae for the distribution of periodic queues. The class of fluid Markovian arrival processes is introduced, and we give statistical estimates for the parameters of a BMAP.

In the third part, the concepts of spatial Markovian arrival processes (abbreviated: SMAPs) and spatial queues are introduced. After that, periodic spatial Markovian queues are analysed as a model for the cells of a wireless communication network.
From Markov Jump Processes to Spatial Queues is intended to reach queuing theorists, researchers in the field of communication systems, as well as engineers with some background in probability theory. Furthermore, it is suitable as a textbook for advanced queuing theory on the graduate or post-graduate level.

This book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications. The first half of the book looks at theoretical investigations on artificial neural networks and addresses the key architectures that are capable of implementation in various application scenarios. The second half is designed specifically for the production of solutions using artificial neural networks to solve practical problems arising from different areas of knowledge. It also describes the various implementation details that were taken into account to achieve the reported results. These aspects contribute to the maturation and improvement of experimental techniques to specify the neural network architecture that is most appropriate for a particular application scope. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals.

Modelling with Ordinary Differential Equations: A Comprehensive Approach aims to provide a broad and self-contained introduction to the mathematical tools necessary to investigate and apply ODE models. The book starts by establishing the existence of solutions in various settings and analysing their stability properties. The next step is to illustrate modelling issues arising in the calculus of variation and optimal control theory that are of interest in many applications. This discussion is continued with an introduction to inverse problems governed by ODE models and to differential games. The book is completed with an illustration of stochastic differential equations and the development of neural networks to solve ODE systems. Many numerical methods are presented to solve the classes of problems discussed in this book. Features: Provides insight into rigorous mathematical issues concerning various topics, while discussing many different models of interest in different disciplines (biology, chemistry, economics, medicine, physics, social sciences, etc.) Suitable for undergraduate and graduate students and as an introduction for researchers in engineering and the sciences Accompanied by codes which allow the reader to apply the numerical methods discussed in this book in those cases where analytical solutions are not available

* Suitable for researchers in mathematical neuroscience and potentially as supplementary reading for postgraduate students * Thoroughly researched and replete with references.

Double Sequence Spaces and Four-Dimensional Matrices provides readers with a clear introduction to the spaces of double sequences and series, as well as their properties. The book then goes beyond this to investigate paranormed double sequence spaces and their algebraic and topological properties, triangle matrices and their domains in certain spaces of double sequences, dual spaces of double sequence spaces, and matrix transformations between double sequence spaces and related topics. Each chapter contains a conclusion section highlighting the importance of results and pointing out possible new ideas that can be studied further. Features Suitable for students at graduate or post-graduate level and researchers Investigates different types of summable spaces and computes their duals Characterizes several four-dimensional matrix classes transforming one summable space into other Discusses several algebraic and topological properties of new sequence spaces generated by the domain of triangles.

This work is devoted to the late Ukrainian computer scientist V. M. Glushkov on the 90th anniversary of his birthday. Dr. Glushkov is known for his contribution to the world computer science and technology and this volume analyzes the ideas and paths of development of informatics formulated by him and demonstrate their important role in constructing computer technologies of basic research in the fields of applied mathematics, theories of computer programming and computing systems. A significant portion of the monograph is devoted to the elucidation of new results obtained in the field of mathematical modeling of complicated processes, creation of new methods for solving and investigating optimization problems in different statements and development of computer technologies for investigations in the field of economy, biology, medicine and information security in systems. The monograph will be of particular interest to informatics specialists and experts using methods of informatics and computer technologies to investigate complicated processes of different natures and developing new information technologies. It may also be useful for both graduate students and postgraduates specializing in Computer Science.