This volume presents the Proceedings of the Joint U.S. / Israel Workshop on Operator Theory and Its Applications, held February 24-28, 1992, at the Ben Gurion University of the Negev, Beersheva. This event was sponsored by the United States / Israel Binational Science Foundation and the Ben Gurion University of the Negev, and many outstanding experts in operator theory took part. The workshop honored Professor Emeritus Moshe Livsic on the occasion of his retirement. The volume contains a selection of papers covering a wide range of topics in modern operator theory and its applications, from abstract operator theory to system theory and computers in operator models. The papers treat linear and nonlinear problems, and study operators from different abstract and concrete classes. Many of the topics concern the area in which contributions of Moshe Livsic were extremely important. This book will appeal to a wide audience of pure and applied mathematicians and engineers.

This edited book is about preparing pre-service and in-service teachers to teach secondary-level mathematics to English Language Learners (ELLs) in twenty-first century classrooms. Chapter topics are grounded in both research and practice, addressing a range of timely topics including the current state of ELL education in the secondary mathematics classroom, approaches to leveraging the talents and strengths of bilingual students in heterogeneous classrooms, best practices in teaching mathematics to multilingual students, and ways to infuse the secondary mathematics teacher preparation curriculum with ELL pedagogy. This book will appeal to all teachers of ELLs, teacher educators and researchers of language acquisition more broadly. This volume is part of a set of four edited books focused on teaching the key content areas to English language learners. The other books in the set focus on teaching History and Social Studies, English Language Arts, and Science to ELLs.

The book focuses on the next fields of computer science: combinatorial optimization, scheduling theory, decision theory, and computer-aided production management systems. It also offers a quick introduction into the theory of PSC-algorithms, which are a new class of efficient methods for intractable problems of combinatorial optimization. A PSC-algorithm is an algorithm which includes: sufficient conditions of a feasible solution optimality for which their checking can be implemented only at the stage of a feasible solution construction, and this construction is carried out by a polynomial algorithm (the first polynomial component of the PSC-algorithm); an approximation algorithm with polynomial complexity (the second polynomial component of the PSC-algorithm); also, for NP-hard combinatorial optimization problems, an exact subalgorithm if sufficient conditions were found, fulfilment of which during the algorithm execution turns it into a polynomial complexity algorithm. Practitioners and software developers will find the book useful for implementing advanced methods of production organization in the fields of planning (including operative planning) and decision making. Scientists, graduate and master students, or system engineers who are interested in problems of combinatorial optimization, decision making with poorly formalized overall goals, or a multiple regression construction will benefit from this book.

Eugene B. Dynkin published his first paper, on Markov chain theory, whilst still an undergraduate student at Moscow State University. He went on to make fundamental contributions to the theory of Markov processes and to Lie groups, generating entire schools in these areas. This volume features original mathematical papers, written to honour E.B. Dynkin's 70th birthday. It contains papers dealing with problems in stochastic analysis, probability theory and mathematical physics.

This contributed volume presents an overview of concepts, methods, and applications used in several quantitative areas of drug research, development, and marketing. Chapters bring together the theories and applications of various disciplines, allowing readers to learn more about quantitative fields, and to better recognize the differences between them. Because it provides a thorough overview, this will serve as a self-contained resource for readers interested in the pharmaceutical industry, and the quantitative methods that serve as its foundation. Specific disciplines covered include: Biostatistics Pharmacometrics Genomics Bioinformatics Pharmacoepidemiology Commercial analytics Operational analytics Quantitative Methods in Pharmaceutical Research and Development is ideal for undergraduate students interested in learning about real-world applications of quantitative methods, and the potential career options open to them. It will also be of interest to experts working in these areas.

This book explores internet applications in which a crucial role is played by classification, such as spam filtering, recommender systems, malware detection, intrusion detection and sentiment analysis. It explains how such classification problems can be solved using various statistical and machine learning methods, including K nearest neighbours, Bayesian classifiers, the logit method, discriminant analysis, several kinds of artificial neural networks, support vector machines, classification trees and other kinds of rule-based methods, as well as random forests and other kinds of classifier ensembles. The book covers a wide range of available classification methods and their variants, not only those that have already been used in the considered kinds of applications, but also those that have the potential to be used in them in the future. The book is a valuable resource for post-graduate students and professionals alike.

This proceedings book presents selected contributions from the XVIII Congress of APDIO (the Portuguese Association of Operational Research) held in Valenca on June 28-30, 2017. Prepared by leading Portuguese and international researchers in the field of operations research, it covers a wide range of complex real-world applications of operations research methods using recent theoretical techniques, in order to narrow the gap between academic research and practical applications. Of particular interest are the applications of, nonlinear and mixed-integer programming, data envelopment analysis, clustering techniques, hybrid heuristics, supply chain management, and lot sizing and job scheduling problems. In most chapters, the problems, methods and methodologies described are complemented by supporting figures, tables and algorithms. The XVIII Congress of APDIO marked the 18th installment of the regular biannual meetings of APDIO - the Portuguese Association of Operational Research. The meetings bring together researchers, scholars and practitioners, as well as MSc and PhD students, working in the field of operations research to present and discuss their latest works. The main theme of the latest meeting was Operational Research Pro Bono. Given the breadth of topics covered, the book offers a valuable resource for all researchers, students and practitioners interested in the latest trends in this field.

Modern life is increasingly relying on digital technology, which in turn runs on mathematics. However, this underlying math is hidden from us. That is mostly a good thing since we do not want to be solving equations and calculating fractions just to get things done in our everyday business. But the mathematical details do matter for anyone who wants to understand how stuff works, or wishes to create something new in the jungle of apps and algorithms. This book takes a look at the mathematical models behind weather forecasting, climate change prediction, artificial intelligence, medical imaging and computer graphics. The reader is expected to have only a curious mind; technical math skills are not needed for enjoying this text.

This book discusses topics related to the topological structure and biological function of gene networks regulated by microRNAs. It focuses on analyzing the relation between topological structure and biological function, applying these theoretical results to gene networks involving microRNA, illustrating their biological mechanisms, and identifying the roles of microRNA in controlling various phenomena emerging from the networks. In addition, the book explains how to control the complex biological phenomena using mathematical tools and offers a new perspective on studying microRNA. It is a useful resource for graduate students and researchers who are working on or interested in microRNAs and gene network.

An essential contribution to the study of the history of computers, this work identifies the computer's impact on the physical, biological, cognitive, and medical sciences. References fundamental to the understudied area of the history of scientific computing also document the significant role of the sciences in helping to shape the development of computer technology. More broadly, the many resources on scientific computing help demonstrate how the computer was the most significant scientific instrument of the 20th century.

The only guide of its kind covering the use and impact of computers on the the physical, biological, medical, and cognitive sciences, it contains more than 1,000 annotated citations to carefully selected secondary and primary resources. Historians of technology and science will find this a very useful resource. Computer scientists, physicians, biologists, chemists, and geologists will also benefit from this extensive bibliography on the history of computer applications and the sciences.

This volume of selected and peer-reviewed contributions on the latest developments in time series analysis and forecasting updates the reader on topics such as analysis of irregularly sampled time series, multi-scale analysis of univariate and multivariate time series, linear and non-linear time series models, advanced time series forecasting methods, applications in time series analysis and forecasting, advanced methods and online learning in time series and high-dimensional and complex/big data time series. The contributions were originally presented at the International Work-Conference on Time Series, ITISE 2016, held in Granada, Spain, June 27-29, 2016. The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing the disciplines of computer science, mathematics, statistics and econometrics.

This volume gathers contributions from participants of the Introductory School and the IHP thematic quarter on Numerical Methods for PDE, held in 2016 in Cargese (Corsica) and Paris, providing an opportunity to disseminate the latest results and envisage fresh challenges in traditional and new application fields. Numerical analysis applied to the approximate solution of PDEs is a key discipline in applied mathematics, and over the last few years, several new paradigms have appeared, leading to entire new families of discretization methods and solution algorithms. This book is intended for researchers in the field.

This book includes original research findings in the field of memetic algorithms for image processing applications. It gathers contributions on theory, case studies, and design methods pertaining to memetic algorithms for image processing applications ranging from defence, medical image processing, and surveillance, to computer vision, robotics, etc. The content presented here provides new directions for future research from both theoretical and practical viewpoints, and will spur further advances in the field.

Classical vs Quantum Groups as Symmetries of Quantized Systems; M. Arik, G. UEnel. Algebraic Model of an Oblate Top; R.Bijker, A. Leviatan. The Mass-Squared Operator and the Einstein-Hilbert Action for Rescaled Lorentz Metrics; E. Binz, P. Oellers. Multichannel Dynamic Symmetry; J. Cseh. Kazhdan-Lusztig Polynomials, Subsingular Vectors and Conditionally Invariant; q-Deformed Equations; V.K. Dobrev. On a Path to Nonlinear Quantum Mechanics; H.-D. Doebner, J.-D. Hennig. Quantum Mechanical Problems with q-Deformations and over the p-Adic Number Fields; I.H. Duru. A Symmetry Adapted Algebraic Approach to Molecular Spectroscopy; A. Frank, et al. Dyson Boson-Fermion Realization of Lie (Super)Algebras; D.V. Fursa, et al. Formal Languages for Quasicrystals; J.G. Escudero. On Quadratic and Nonquadratic Forms: Applications to R2m R2m-n Nonbijective Transformations; M. Kibler. Quantization of Systems with Constraints; J.R. Klauder. Automorphisms and Discrete Fiber Bundles; P. Kramer, et al. Algebraic Approach to Baryon Structure; A. Leviatan, R. Bijker. Discrete Reflection Groups and Induced Representations of Poincare Group on the Lattice; M. Lorente. 10 Additional Articles. Index.

Statistical Techniques for Transportation Engineering is written with a systematic approach in mind and covers a full range of data analysis topics, from the introductory level (basic probability, measures of dispersion, random variable, discrete and continuous distributions) through more generally used techniques (common statistical distributions, hypothesis testing), to advanced analysis and statistical modeling techniques (regression, AnoVa, and time series). The book also provides worked out examples and solved problems for a wide variety of transportation engineering challenges.

Growth curve models in longitudinal studies are widely used to model population size, body height, biomass, fungal growth, and other variables in the biological sciences, but these statistical methods for modeling growth curves and analyzing longitudinal data also extend to general statistics, economics, public health, demographics, epidemiology, SQC, sociology, nano-biotechnology, fluid mechanics, and other applied areas. There is no one-size-fits-all approach to growth measurement. The selected papers in this volume build on presentations from the GCM workshop held at the Indian Statistical Institute, Giridih, on March 28-29, 2016. They represent recent trends in GCM research on different subject areas, both theoretical and applied. This book includes tools and possibilities for further work through new techniques and modification of existing ones. The volume includes original studies, theoretical findings and case studies from a wide range of applied work, and these contributions have been externally refereed to the high quality standards of leading journals in the field.

Taking the Qinghai-Tibet Railway as an example, this book introduces intelligent processing for Global Positioning Data (GPS) data. Combining theory with practical applications, it provides essential insights into the Chinese Qinghai-Tibet Railway and novel methods of data processing for GPS satellite positioning, making it a valuable resource for all those working with train control systems, train positioning systems, satellite positioning, and intelligent data processing. As satellite positioning guarantees the safe and efficient operation of train control systems, it focuses on how to best process the GPS data collected, including methods for error detection, reduction and information fusion.

This book offers an ideal introduction to singular perturbation problems, and a valuable guide for researchers in the field of differential equations. It also includes chapters on new contributions to both fields: differential equations and singular perturbation problems. Written by experts who are active researchers in the related fields, the book serves as a comprehensive source of information on the underlying ideas in the construction of numerical methods to address different classes of problems with solutions of different behaviors, which will ultimately help researchers to design and assess numerical methods for solving new problems. All the chapters presented in the volume are complemented by illustrations in the form of tables and graphs.

This book is a substantially revised and expanded edition reflecting major developments in stochastic numerics since the first edition was published in 2004. The new topics, in particular, include mean-square and weak approximations in the case of nonglobally Lipschitz coefficients of Stochastic Differential Equations (SDEs) including the concept of rejecting trajectories; conditional probabilistic representations and their application to practical variance reduction using regression methods; multi-level Monte Carlo method; computing ergodic limits and additional classes of geometric integrators used in molecular dynamics; numerical methods for FBSDEs; approximation of parabolic SPDEs and nonlinear filtering problem based on the method of characteristics. SDEs have many applications in the natural sciences and in finance. Besides, the employment of probabilistic representations together with the Monte Carlo technique allows us to reduce the solution of multi-dimensional problems for partial differential equations to the integration of stochastic equations. This approach leads to powerful computational mathematics that is presented in the treatise. Many special schemes for SDEs are presented. In the second part of the book numerical methods for solving complicated problems for partial differential equations occurring in practical applications, both linear and nonlinear, are constructed. All the methods are presented with proofs and hence founded on rigorous reasoning, thus giving the book textbook potential. An overwhelming majority of the methods are accompanied by the corresponding numerical algorithms which are ready for implementation in practice. The book addresses researchers and graduate students in numerical analysis, applied probability, physics, chemistry, and engineering as well as mathematical biology and financial mathematics.

This textbook provides concise coverage of the basics of linear and integer programming which, with megatrends toward optimization, machine learning, big data, etc., are becoming fundamental toolkits for data and information science and technology. The authors' approach is accessible to students from almost all fields of engineering, including operations research, statistics, machine learning, control system design, scheduling, formal verification and computer vision. The presentations enables the basis for numerous approaches to solving hard combinatorial optimization problems through randomization and approximation. Readers will learn to cast various problems that may arise in their research as optimization problems, understand the cases where the optimization problem will be linear, choose appropriate solution methods and interpret results appropriately.

The special volume offers a global guide to new concepts and approaches concerning the following topics: reduced basis methods, proper orthogonal decomposition, proper generalized decomposition, approximation theory related to model reduction, learning theory and compressed sensing, stochastic and high-dimensional problems, system-theoretic methods, nonlinear model reduction, reduction of coupled problems/multiphysics, optimization and optimal control, state estimation and control, reduced order models and domain decomposition methods, Krylov-subspace and interpolatory methods, and applications to real industrial and complex problems. The book represents the state of the art in the development of reduced order methods. It contains contributions from internationally respected experts, guaranteeing a wide range of expertise and topics. Further, it reflects an important effor t, carried out over the last 12 years, to build a growing research community in this field. Though not a textbook, some of the chapters can be used as reference materials or lecture notes for classes and tutorials (doctoral schools, master classes).

This book is a collection of selected papers presented at the 10th International Conference on Scientific Computing in Electrical Engineering (SCEE), held in Wuppertal, Germany in 2014. The book is divided into five parts, reflecting the main directions of SCEE 2014: 1. Device Modeling, Electric Circuits and Simulation, 2. Computational Electromagnetics, 3. Coupled Problems, 4. Model Order Reduction, and 5. Uncertainty Quantification. Each part starts with a general introduction followed by the actual papers. The aim of the SCEE 2014 conference was to bring together scientists from academia and industry, mathematicians, electrical engineers, computer scientists, and physicists, with the goal of fostering intensive discussions on industrially relevant mathematical problems, with an emphasis on the modeling and numerical simulation of electronic circuits and devices, electromagnetic fields, and coupled problems. The methodological focus was on model order reduction and uncertainty quantification.

Written by the pioneer and foremost authority on the subject, this new book is both a comprehensive university textbook and professional/research reference on the finite-difference time-domain (FD-TD) computational solution method for Maxwell's equations. It presents in-depth discussions of: The revolutionary Berenger PML absorbing boundary condition; FD-TD modelling of nonlinear, dispersive, and gain optical materials used in lasers and optical microchips; unstructured FD-TD meshes for modelling of complex systems; 2.5-dimensional body-of-revolution FD-TD algorithms; Linear and nonlinear electronic circuit models, including a seamless tie-in to SPICE; Digital signal postprocessing of FD-TD data; FD-TD modelling of microlaser cavities; and FD-TD software development for the latest Intel and Cray massively parallel computers.

Preface. From Integrable Models to Conformal Field Theory via Quantum Groups; L.D. Faddeev. A Brief History of Hidden Quantum Symmetries in Conformal Field Theories; C. Gomez, G. Sierra. q-Deformation of Semisimple and Non-Semisimple Lie Algebras; H. Ruegg. Quantum Algebras and Quantum Groups in q-Special Function Theory; R. Floreanini, L. Vinet. Lectures in Topological Quantum Field Theory; D.S. Freed. Canonical Quantum Gravity and the Problem of Time; C.J. Isham. Higher Symmetries in Lower-Dimensional Models; R. Jackiw. Three Lectures on Supersymmetry and Extended Objects; P.K. Townsend. The Geometric Phase in Quantum Physics; A. Bohm. Quantum Mechanics on Phase Space; M. Gadella. Lie Groups and Solutions of Nonlinear Partial Differential Equations; P. Winternitz. Index.

1 Reference Material.- 1.1 Introduction.- 1.2 Singular Integral Equations.- 1.3 Improper Integrals.- 1.3.1 The Gamma function.- 1.3.2 The Beta function.- 1.3.3 Another important improper integral.- 1.3.4 A few integral identities.- 1.4 The Lebesgue Integral.- 1.5 Cauchy Principal Value for Integrals.- 1.6 The Hadamard Finite Part.- 1.7 Spaces of Functions and Distributions.- 1.8 Integral Transform Methods.- 1.8.1 Fourier transform.- 1.8.2 Laplace transform.- 1.9 Bibliographical Notes.- 2 Abel's and Related Integral Equations.- 2.1 Introduction.- 2.2 Abel's Equation.- 2.3 Related Integral Equations.- 2.4 The equation $$\int_{0}^{s} {{{{(s - t)}}^{\beta }}g(t)dt = f(s), \Re e \beta > - 1}$$.- 2.5 Path of Integration in the Complex Plane.- 2.6 The Equation $$\int_{{{ {C}_{{a\xi }}}}} {\frac{{g(z)dz}}{{ {{{(z - \xi )}}^{\nu }}}}} + k\int_{ {{{C}_{{\xi b}}}}} {\frac{ {g(z)dz}}{{{{{(\xi - z)}}^{\nu }}}}} = f(\xi )$$.- 2.7 Equations on a Closed Curve.- 2.8 Examples.- 2.9 Bibliographical Notes.- 2.10 Problems.- 3 Cauchy Type Integral Equations.- 3.1 Introduction.- 3.2 Cauchy Type Equation of the First Kind.- 3.3 An Alternative Approach.- 3.4 Cauchy Type Equations of the Second Kind.- 3.5 Cauchy Type Equations on a Closed Contour.- 3.6 Analytic Representation of Functions.- 3.7 Sectionally Analytic Functions (z?a)n?v(z?b)m+v.- 3.8 Cauchy's Integral Equation on an Open Contour.- 3.9 Disjoint Contours.- 3.10 Contours That Extend to Infinity.- 3.11 The Hilbert Kernel.- 3.12 The Hilbert Equation.- 3.13 Bibliographical Notes.- 3.14 Problems.- 4 Carleman Type Integral Equations.- 4.1 Introduction.- 4.2 Carleman Type Equation over a Real Interval.- 4.3 The Riemann-Hilbert Problem.- 4.4 Carleman Type Equations on a Closed Contour.- 4.5 Non-Normal Problems.- 4.6 A Factorization Procedure.- 4.7 An Operational Approach.- 4.8 Solution of a Related Integral Equation.- 4.9 Bibliographical Notes.- 4.10 Problems.- 5 Distributional Solutions of Singular Integral Equations.- 5.1 Introduction.- 5.2 Spaces of Generalized Functions.- 5.3 Generalized Solution of the Abel Equation.- 5.4 Integral Equations Related to Abel's Equation.- 5.5 The Fractional Integration Operators .- 5.6 The Cauchy Integral Equation over a Finite Interval.- 5.7 Analytic Representation of Distributions of ?'[a, b].- 5.8 Boundary Problems in A[a, b].- 5.9 Disjoint Intervals.- 5.9.1 The problem [RjF]j =hj.- 5.9.2 The equation A1?1(0F) + A2?2(F) = G.- 5.10 Equations Involving Periodic Distributions.- 5.11 Bibliographical Notes.- 5.12 Problems.- 6 Distributional Equations on the Whole Line.- 6.1 Introduction.- 6.2 Preliminaries.- 6.3 The Hilbert Transform of Distributions.- 6.4 Analytic Representation.- 6.5 Asymptotic Estimates.- 6.6 Distributional Solutions of Integral Equations.- 6.7 Non-Normal Equations.- 6.8 Bibliographical Notes.- 6.9 Problems.- 7 Integral Equations with Logarithmic Kernels.- 7.1 Introduction.- 7.2 Expansion of the Kernel In x-y.- 7.3 The Equation $$\int_{a}^{b} {\ln } \left {x - y} \rightg(y)dy = f(x)$$.- 7.4 Two Related Operators.- 7.5 Generalized Solutions of Equations with Logarithmic Kernels.- 7.6 The Operator $$\int_{a}^{b} {(P(x - y)\ln \left {x - y} \right + Q(x, y))g(y)dy}$$.- 7.7 Disjoint Intervals of Integration.- 7.8 An Equation Over a Semi-Infinite Interval.- 7.9 The Equation of the Second Kind Over a Semi-Infinite Interval.- 7.10 Asymptotic Behavior of Eigenvalues.- 7.11 Bibliographical Notes.- 7.12 Problems.- 8 Wiener-Hopf Integral Equations.- 8.1 Introduction.- 8.2 The Holomorphic Fourier Transform.- 8.3 The Mathematical Technique.- 8.4 The Distributional Wiener-Hopf Operators.- 8.5 Illustrations.- 8.6 Bibliographical Notes.- 8.7 Problems.- 9 Dual and Triple Integral Equations.- 9.1 Introduction.- 9.2 The Hankel Transform.- 9.3 Dual Equations with Trigonometric Kernels.- 9.4 Beltrami's Dual Integral Equations.- 9.5 Some Triple Integral Equations.- 9.6 Erdelyi-Koeber Operators.- 9.7 Dual Integral Equations of the Titchmarsh Type.- 9.8 D