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Parallel Algorithms
This book is an introduction to the field of parallel algorithms and the underpinning techniques to realize the parallelization. The emphasis is on designing algorithms within the timeless and abstracted context of a high-level programming language. The focus of the presentation is on practical applications of the algorithm design using different models of parallel computation. Each model is illustrated by providing an adequate number of algorithms to solve some problems that quite often arise in many applications in science and engineering.The book is largely self-contained, presuming no special knowledge of parallel computers or particular mathematics. In addition, the solutions to all exercises are included at the end of each chapter.The book is intended as a text in the field of the design and analysis of parallel algorithms. It includes adequate material for a course in parallel algorithms at both undergraduate and graduate levels.
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Structures in Concurrency Theory
This book is the proceedings of the Structures in Concurrency Theory workshop (STRICT) that was held from 11 th to l3th May 1995 in Berlin, Germany. It includes three invited contributions - by J. de Bakker, E. Best et aI, and E. R. Olderog and M. Schenke - and all papers which were submitted and accepted for presentation. Concurrency Theory deals with formal aspects of concurrent systems. It uses partly competing and partly complementary formalisms and structures. The aim of this workshop was to present and compare different formalisms and results in Concurrency Theory. STRICT was organized by the Humboldt-University Berlin and the ESPRIT Basic Research Working Group CALIBAN. Original papers had been sought from all scientists in the field of Concurrency Theory. The Programme Committee selected twenty contributions with various different topics, including Petri Nets, Process Algebras, Distributed Algorithms, Formal Semantics, and others. I am grateful to the Programme Committee and to the other referees for the careful evaluation of the submitted papers.
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Algorithms and Discrete Applied Mathematics
This book constitutes the proceedings of the 5th International Conference on Algorithms and Discrete Applied Mathematics, CALDAM 2019, held in Kharagpur, India, in February 2019.The 22 papers presented together with 3 invited papers in this volume were carefully reviewed and selected from 86 submissions.The conference had papers in the areas of algorithms, graph theory, combinatorics, computational geometry, discrete geometry, and computational complexity.
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Approximation and Online Algorithms
This book constitutes the thoroughly refereed post-workshop proceedings of the 12th International Workshop on Approximation and Online Algorithms, WAOA 2014, held in Wrocław, Poland, in September 2014 as part of ALGO 2014. The 22 revised full papers presented were carefully reviewed and selected from 49 submissions. They cover a wide range of topics such as coloring and partitioning, competitive analysis, network design, packing and covering, paradigms for design and analysis of approximation and online algorithms, randomization techniques, real-world applications, and scheduling problems.
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Evolutionary Algorithms
Evolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are expected to provide non-optimal but good quality solutions to problems whose resolution is impracticable by exact methods. In six chapters, this book presents the essential knowledge required to efficiently implement evolutionary algorithms. Chapter 1 describes a generic evolutionary algorithm as well as the basic operators that compose it. Chapter 2 is devoted to the solving of continuous optimization problems, without constraint. Three leading approaches are described and compared on a set of test functions. Chapter 3 considers continuous optimization problems with constraints. Various approaches suitable for evolutionary methods are presented. Chapter 4 is related to combinatorial optimization. It provides a catalog of variation operators to deal with order-based problems. Chapter 5 introduces the basic notions required to understand the issue of multi-objective optimization and a variety of approaches for its application. Finally, Chapter 6 describes different approaches of genetic programming able to evolve computer programs in the context of machine learning.
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Foundations of Software Science and Computation Structures
This open access book constitutes the proceedings of the 23rd International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020.The 31 regular papers presented in this volume were carefully reviewed and selected from 98 submissions.The papers cover topics such as categorical models and logics; language theory, automata, and games; modal, spatial, and temporal logics; type theory and proof theory; concurrency theory and process calculi; rewriting theory; semantics of programming languages; program analysis, correctness, transformation, and verification; logics of programming; software specification and refinement; models of concurrent, reactive, stochastic, distributed, hybrid, and mobile systems; emerging models of computation; logical aspects of computational complexity; models of software security; and logical foundations of data bases.
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Numerical Algorithms for Modern Parallel Computer Architectures
Parallel computers have started to completely revolutionize scientific computation. Articles in this volume represent applied mathematics, computer science, and application aspects of parallel scientific computing. Major advances are discussed dealing with multiprocessor architectures, parallel algorithm development and analysis, parallel systems and programming languages. The optimization of the application of massively parallel architectures to real world problems will provide the impetus for the development of entirely new approaches to these technical situations.
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Advances in Knowledge Discovery and Data Mining
The two-volume set LNAI 12084 and 12085 constitutes the thoroughly refereed proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, which was due to be held in Singapore, in May 2020. The conference was held virtually due to the COVID-19 pandemic.The 135 full papers presented were carefully reviewed and selected from 628 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems, and the emerging applications. They are organized in the following topical sections: recommender systems; classification; clustering; mining social networks; representation learning and embedding; mining behavioral data; deep learning; feature extraction and selection; human, domain, organizational and social factors in data mining; mining sequential data; mining imbalanced data; association; privacy and security; supervised learning; novel algorithms; mining multi-media/multi-dimensional data; application; mining graph and network data; anomaly detection and analytics; mining spatial, temporal, unstructured and semi-structured data; sentiment analysis; statistical/graphical model; multi-source/distributed/parallel/cloud computing.
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Tools and Algorithms for the Construction and Analysis of Systems
This book is Open Access under a CC BY licence.The LNCS 11427 and 11428 proceedings set constitutes the proceedings of the 25th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2019, which took place in Prague, Czech Republic, in April 2019, held as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2019.The total of 42 full and 8 short tool demo papers presented in these volumes was carefully reviewed and selected from 164 submissions. The papers are organized in topical sections as follows:Part I: SAT and SMT, SAT solving and theorem proving; verification and analysis; model checking; tool demo; and machine learning.Part II: concurrent and distributed systems; monitoring and runtime verification; hybrid and stochastic systems; synthesis; symbolic verification; and safety and fault-tolerant systems.
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Network Flow Algorithms
Network flow theory has been used across a number of disciplines, including theoretical computer science, operations research, and discrete math, to model not only problems in the transportation of goods and information, but also a wide range of applications from image segmentation problems in computer vision to deciding when a baseball team has been eliminated from contention. This graduate text and reference presents a succinct, unified view of a wide variety of efficient combinatorial algorithms for network flow problems, including many results not found in other books. It covers maximum flows, minimum-cost flows, generalized flows, multicommodity flows, and global minimum cuts and also presents recent work on computing electrical flows along with recent applications of these flows to classical problems in network flow theory.
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Introduction to Genetic Algorithms
Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics-particularly in machine learning, scientific modeling, and artificial life-and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.
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Power of Algorithms
To examine, analyze, and manipulate a problem to the point of designing an algorithm for solving it is an exercise of fundamental value in many fields. With so many everyday activities governed by algorithmic principles, the power, precision, reliability and speed of execution demanded by users have transformed the design and construction of algorithms from a creative, artisanal activity into a full-fledged science in its own right. This book is aimed at all those who exploit the results of this new science, as designers and as consumers. The first chapter is an overview of the related history, demonstrating the long development of ideas such as recursion and more recent formalizations such as computability. The second chapter shows how the design of algorithms requires appropriate techniques and sophisticated organization of data. In the subsequent chapters the contributing authors present examples from diverse areas – such as routing and networking problems, Web search, information security, auctions and games, complexity and randomness, and the life sciences – that show how algorithmic thinking offers practical solutions and also deepens domain knowledge. The contributing authors are top-class researchers with considerable academic and industrial experience; they are also excellent educators and communicators and they draw on this experience with enthusiasm and humor. This book is an excellent introduction to an intriguing domain and it will be enjoyed by undergraduate and postgraduate students in computer science, engineering, and mathematics, and more broadly by all those engaged with algorithmic thinking.
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Algorithms: Design Techniques And Analysis (Revised Edition)
Problem solving is an essential part of every scientific discipline. It has two components: (1) problem identification and formulation, and (2) the solution to the formulated problem. One can solve a problem on its own using ad hoc techniques or by following techniques that have produced efficient solutions to similar problems. This requires the understanding of various algorithm design techniques, how and when to use them to formulate solutions, and the context appropriate for each of them.Algorithms: Design Techniques and Analysis advocates the study of algorithm design by presenting the most useful techniques and illustrating them with numerous examples — emphasizing on design techniques in problem solving rather than algorithms topics like searching and sorting. Algorithmic analysis in connection with example algorithms are explored in detail. Each technique or strategy is covered in its own chapter through numerous examples of problems and their algorithms.Readers will be equipped with problem solving tools needed in advanced courses or research in science and engineering.
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Introduction to Machine Learning Algorithms
Mathematics is the foundation of machine learning algorithms. To understand the shortcomings of existing algorithms and develop more effective methods, it is essential to understand the mathematical concepts underlying these algorithms and their operational principles. This book serves as an introductory resource, outlining the preliminary concepts and offering insights into the mathematical foundations and operational mechanisms of machine learning algorithms. It describes the basic equations and interrelates the questions arising during practical applications of machine learning with the basic mathematical picture of the algorithms used.• Introduces machine learning, highlights the central role of algorithms in machine learning, and explains the core mathematical prerequisites to understanding machine learning algorithms• Systematically examines the sequential steps of classical machine learning algorithms used for classification of data sets into distinct groups; regression, clustering analysis,• Provides an overview of value, policy, and model-based reinforcement learning algorithms. This book is for academicians, scholars, students, and professionals engaged in the study of machine learning and artificial intelligence.
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Grammatical Inference: Algorithms and Applications
The Fifth International Colloquium on Grammatical Inference (ICGI-2000) was heldinLisbononSeptember11-13th,2000.ICGI-2000wasthe?fthinaseriesof successfulbiennialinternationalconferencesintheareaofgrammaticalinference. Previous conferences were held in Essex, U.K.; Alicante, Spain; Montpellier, France; and Ames, Iowa, USA. This series of meetings seeks to provide a forum for the presentation and discussion of original research on all aspects of grammatical inference. Gram- tical inference, the process of inferring grammar from given data, is a ?eld that is not only challenging from a purely scienti?c standpoint but also ?nds many applications in real world problems. Despitethefactthatgrammaticalinferenceaddressesproblemsinarelatively narrow area, it uses techniques from many domains, and intersects a number of di?erent disciplines. Researchers in grammatical inference come from ?elds as diverse as machine learning, theoretical computer science, computational ling- stics, pattern recognition and arti?cial neural networks.From a practical standpoint, applications in areas such as natural language acquisition, computational biology, structural pattern recognition, information retrieval, text processing and adaptive intelligent agents have either been - monstrated or proposed in the literature. ICGI-2000 was held jointly with CoNLL-2000, the Computational Natural Language Learning Workshop and LLL-2000, the Second Learning Language in LogicWorkshop.Thetechnicalprogramincludedthepresentationof24accepted papers (out of 35 submitted) as well as joint sessions with CoNLL and LLL. A tutorial program organized by Gabriel Pereira Lopes took place after the meetings and included tutorials by Raymond Mooney, Gregory Grefenstette, Walter Daelemans, Ant' onio Ribeiro, Joaquim Ferreira da Silva, Gael Dias, Nuno Marques,VitorRossio,Jo" aoBalsaandAlexandreAgostini.Thejointrealization of these events represents a unique opportunity for researchers in these related ?elds to interact and exchange ideas.
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Algorithmic Aspects in Information and Management
This volume constitutes the proceedings of the 13th International Conference on Algorithmic Aspects in Information and Management, AAIM 2019, held in Bejing, China in August 2019.The 31 full papers presented were carefully reviewed and selected. The papers deal with most aspects of theoretical computer science and their applications. Special considerations are given to algorithmic research that is motivated by real-world applications.
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Tools and Algorithms for the Construction and Analysis of Systems
This open access two-volume set constitutes the proceedings of the 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2021, which was held during March 27 – April 1, 2021, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021. The conference was planned to take place in Luxembourg and changed to an online format due to the COVID-19 pandemic. The total of 41 full papers presented in the proceedings was carefully reviewed and selected from 141 submissions. The volume also contains 7 tool papers; 6 Tool Demo papers, 9 SV-Comp Competition Papers.The papers are organized in topical sections as follows:Part I: Game Theory; SMT Verification; Probabilities; Timed Systems; Neural Networks; Analysis of Network Communication.Part II: Verification Techniques (not SMT); Case Studies; Proof Generation/Validation; Tool Papers; Tool Demo Papers; SV-Comp Tool Competition Papers.
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Mathematical Structures for Computer Graphics
A comprehensive exploration of the mathematics behind the modeling and rendering of computer graphics scenes Mathematical Structures for Computer Graphics presents an accessible and intuitive approach to the mathematical ideas and techniques necessary for two- and three-dimensional computer graphics. Focusing on the significant mathematical results, the book establishes key algorithms used to build complex graphics scenes. Written for readers with various levels of mathematical background, the book develops a solid foundation for graphics techniques and fills in relevant graphics details often overlooked in the literature. Rather than use a rigid theorem/proof approach, the book provides a flexible discussion that moves from vector geometry through transformations, curve modeling, visibility, and lighting models. Mathematical Structures for Computer Graphics also includes: Numerous examples of two- and three-dimensional techniques along with numerical calculationsPlenty of mathematical and programming exercises in each chapter, which are designed particularly for graphics tasksAdditional details at the end of each chapter covering historical notes, further calculations, and connected concepts for readers who wish to delve deeperUnique coverage of topics such as calculations with homogeneous coordinates, computational geometry for polygons, use of barycentric coordinates, various descriptions for curves, and L-system techniques for recursive images Mathematical Structures for Computer Graphics is an excellent textbook for undergraduate courses in computer science, mathematics, and engineering, as well as an ideal reference for practicing engineers, researchers, and professionals in computer graphics fields. The book is also useful for those readers who wish to understand algorithms for producing their own interesting computer images.
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Nature-Inspired Algorithms and Applied Optimization
This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.
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Fast Parallel Algorithms for Graph Matching Problems
The matching problem is one of the central problems in graph theory as well as in the theory of algorithms and their applications. This book will provide the reader with a comprehensive and straightforward introduction to the basic methods of designing efficient parallel algorithms for graph matching problems. The text is written for students at the beginning graduate level. The exposition is mostly self-contained and example-driven. Prerequisites have been kept to aminimum by including relevant background material. The book contains full details of several new techniques and should also be of interest to research workers in computer science, operations research, discrete mathematics, and electrical engineering. The main theoretical tools are combined intothree independent chapters, devoted to combinatorial tools, probabilistic tools, and algebraic tools. One of the main goals of the book is to bring together these three approaches and highlight how their combination works in the development of efficient parallel algorithms. The reader will be provided with a simple and transparent presentation of a variety of interesting algorithms, including many examples and illustrations. The combination of different approaches makes the matching problem andits applications an attractive and fascinating subject. It is hoped that the book represents a meeting point of interesting algorithmic techniques and opens up new algebraic and geometric areas. Marek Karpinski is Chair Professor of Computer Science at the University of Bonn. Wojciech Rytter isProfessor of Computer Science at the University of Warsaw and at the University of Liverpool.
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Genetic Algorithms and Genetic Programming
Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications discusses algorithmic developments in the context of genetic algorithms (GAs) and genetic programming (GP). It applies the algorithms to significant combinatorial optimization problems and describes structure identification using HeuristicLab as a platform for algorithm development.The book focuses on both theoretical and empirical aspects. The theoretical sections explore the important and characteristic properties of the basic GA as well as main characteristics of the selected algorithmic extensions developed by the authors. In the empirical parts of the text, the authors apply GAs to two combinatorial optimization problems: the traveling salesman and capacitated vehicle routing problems. To highlight the properties of the algorithmic measures in the field of GP, they analyze GP-based nonlinear structure identification applied to time series and classification problems. Written by core members of the HeuristicLab team, this book provides a better understanding of the basic workflow of GAs and GP, encouraging readers to establish new bionic, problem-independent theoretical concepts. By comparing the results of standard GA and GP implementation with several algorithmic extensions, it also shows how to substantially increase achievable solution quality.
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Conceptual Structures: Current Practices
This book is the proceedings of the Second International Conference on Conceptual Structures, ICCS '94, held at College Park, Maryland, USA in August 1994.This proceedings presents, on an international scale, up-to- the-minute research results on theoretical and applicational aspects of conceptual graphs, particularly on the use of contexts in knowledge representation. The concept of contexts is highly important for all kinds of knowledge-intensive systems. The book is organized into sections on natural language understanding, rational problem solving, conceptual graph theory, contexts and canons, and data modeling.
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Compression and Coding Algorithms
Compression and Coding Algorithms describes in detail the coding mechanisms that are available for use in data compression systems. The well known Huffman coding technique is one mechanism, but there have been many others developed over the past few decades, and this book describes, explains and assesses them. People undertaking research of software development in the areas of compression and coding algorithms will find this book an indispensable reference. In particular, the careful and detailed description of algorithms and their implementation, plus accompanying pseudo-code that can be readily implemented on computer, make this book a definitive reference in an area currently without one.
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Optimal Analysis of Structures by Concepts of Symmetry and Regularity
Optimal analysis is defined as an analysis that creates and uses sparse, well-structured and well-conditioned matrices. The focus is on efficient methods for eigensolution of matrices involved in static, dynamic and stability analyses of symmetric and regular structures, or those general structures containing such components. Powerful tools are also developed for configuration processing, which is an important issue in the analysis and design of space structures and finite element models. Different mathematical concepts are combined to make the optimal analysis of structures feasible. Canonical forms from matrix algebra, product graphs from graph theory and symmetry groups from group theory are some of the concepts involved in the variety of efficient methods and algorithms presented. The algorithms elucidated in this book enable analysts to handle large-scale structural systems by lowering their computational cost, thus fulfilling the requirement for faster analysis and design of future complex systems. The value of the presented methods becomes all the more evident in cases where the analysis needs to be repeated hundreds or even thousands of times, as for the optimal design of structures by different metaheuristic algorithms. The book is of interest to anyone engaged in computer-aided analysis and design and software developers in this field. Though the methods are demonstrated mainly through skeletal structures, continuum models have also been added to show the generality of the methods. The concepts presented are not only applicable to different types of structures but can also be used for the analysis of other systems such as hydraulic and electrical networks.
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Elements of Distributed Algorithms
Distributed Computing is rapidly becoming the principal computing paradigm in diverse areas of computing, communication, and control. Processor clusters, local and wide area networks, and the information highway evolved a new kind of problems which can be solved with distributed algorithms.In this textbook a variety of distributed algorithms are presented independently of particular programming languages or hardware, using the graphically suggestive technique of Petri nets which is both easy to comprehend intuitively and formally rigorous. By means of temporal logic the author provides surprisingly simple yet powerful correctness proofs for the algorithms.The scope of the book ranges from distributed control and synchronization of two sites up to algorithms on any kind of networks. Numerous examples show that description and analysis of distributed algorithms in this framework are intuitive and technically transparent.
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Randomization, Approximation, and Combinatorial Optimization. Algorithms and Techniques
This volume contains the papers presented at the3rd International Wo- shoponRandomizationandApproximationTechniquesinComputer Science (RANDOM'99) and the 2nd International Workshop on - proximation Algorithms for Combinatorial Optimization Problems (APPROX'99), which took place concurrently at the University of California, Berkeley, from August 8-11, 1999. RANDOM'99 is concerned with appli- tions of randomness to computational and combinatorial problems, and is the third workshop in the series following Bologna (1997) and Barcelona (1998). APPROX'99 focuses on algorithmic and complexity issues surrounding the - velopment of e?cient approximate solutions to computationally hard problems, and is the second in the series after Aalborg (1998). The volume contains 24 contributed papers, selected by the two program committees from 44 submissions received in response to the call for papers, together with abstracts of invited lectures by Uri Feige (Weizmann Institute), Christos Papadimitriou (UC Berkeley), Madhu Sudan (MIT), and Avi Wigd- son (Hebrew University and IAS Princeton).We would like to thank all of the authors who submitted papers, our invited speakers, the external referees we consulted and the members of the program committees, who were: RANDOM'99 APPROX'99 Alistair Sinclair, UC Berkeley Dorit Hochbaum, UC Berkeley Noga Alon, Tel Aviv U. Sanjeev Arora, Princeton U. Jennifer Chayes, Microsoft Leslie Hall, Johns Hopkins U. Monika Henzinger, Compaq-SRC Samir Khuller, U. of Maryland Mark Jerrum, U. of Edinburgh Phil Klein, Brown U.
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Discrete Structures
The aim of this text is to introduce discrete mathematics to beginning students of mathematics or computer science. It does this by bringing some coherency into the seemingly incongruent subjects that compose discrete math, such as logic, set theory, algebra, and combinatorics. It emphasizes their theoretical foundations and illustrates proofs along the way. The book prepares readers for the analysis of algorithms by discussing asymptotic analysis and a discrete calculus for sums. The book also deduces combinatorial methods from the foundations that are laid out. Unlike other texts on this subject, there is a greater emphasis on foundational material that leads to a better understanding. To further assist the reader in grasping and practicing concepts, roughly 690 exercises are provided at various levels of difficulty. Readers are encouraged to study the examples in the text and solve as many of the exercises as possible.The text is intended for freshman or sophomore undergraduate students in mathematics, computer science, or similar majors. The assumed background is precalculus. The chapter dependency chart included is designed to help students, independent readers, and instructors follow a systematic path for learning and teaching the material, with the option to explore material in later chapters.
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Heuristic Approach to Possibilistic Clustering: Algorithms and Applications
The present book outlines a new approach to possibilistic clustering in which the sought clustering structure of the set of objects is based directly on the formal definition of fuzzy cluster and the possibilistic memberships are determined directly from the values of the pairwise similarity of objects. The proposed approach can be used for solving different classification problems. Here, some techniques that might be useful at this purpose are outlined, including a methodology for constructing a set of labeled objects for a semi-supervised clustering algorithm, a methodology for reducing analyzed attribute space dimensionality and a methods for asymmetric data processing. Moreover, a technique for constructing a subset of the most appropriate alternatives for a set of weak fuzzy preference relations, which are defined on a universe of alternatives, is described in detail, and a method for rapidly prototyping the Mamdani’s fuzzy inference systems is introduced. This book addresses engineers, scientists, professors, students and post-graduate students, who are interested in and work with fuzzy clustering and its applications
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Theory and Practice of Algorithms in (Computer) Systems
This book constitutes the refereed proceedings of the First International ICST Conference on Theory and Practice of Algorithms in (Computer) Systems, TAPAS 2011, held in Rome, Italy, in April 2011. The 25 papers presented, including three short papers by invited speakers, were carefully reviewed and selected from 45 submissions. The papers all feature original research in the design, implementation and evaluation of algorithms with special focus on algorithms for combinatorial optimization problems, and to real-world applications, engineering and experimental analysis of algorithms - thus fostering the cooperation among researchers in computer science, networking, discrete mathematics, mathematical programming and operations research.
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Tools and Algorithms for the Construction and Analysis of Systems
This book presents 12 revised refereed papers selected as the best from 32 submissions for the First International Workshop on Tools and Algorithms for the Construction and Analysis of Systems, TACAS '95, held in Aarhus, Denmark, in May 1995.The workshop brought together 46 researchers interested in the development and application of tools and algorithms for specification, verification, analysis, and construction of distributed systems. The papers included in the book are devoted to refinement-based and compositional verification, construction techniques, analysis and verification via theorem proving, process algebras, temporal and modal logics, techniques for real-time, hybrid and probabilistic systems, and value-passing systems.
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Link Reversal Algorithms
Link reversal is a versatile algorithm design technique that has been used in numerous distributed algorithms for a variety of problems. The common thread in these algorithms is that the distributed system is viewed as a graph, with vertices representing the computing nodes and edges representing some other feature of the system (for instance, point-to-point communication channels or a conflict relationship). Each algorithm assigns a virtual direction to the edges of the graph, producing a directed version of the original graph. As the algorithm proceeds, the virtual directions of some of the links in the graph change in order to accomplish some algorithm-specific goal. The criterion for changing link directions is based on information that is local to a node (such as the node having no outgoing links) and thus this approach scales well, a feature that is desirable for distributed algorithms.This monograph presents, in a tutorial way, a representative sampling of the work on link-reversal-based distributed algorithms. The algorithms considered solve routing, leader election, mutual exclusion, distributed queueing, scheduling, and resource allocation. The algorithms can be roughly divided into two types, those that assume a more abstract graph model of the networks, and those that take into account more realistic details of the system. In particular, these more realistic details include the communication between nodes, which may be through asynchronous message passing, and possible changes in the graph, for instance, due to movement of the nodes.We have not attempted to provide a comprehensive survey of all the literature on these topics. Instead, we have focused in depth on a smaller number of fundamental papers, whose common thread is that link reversal provides a way for nodes in the system to observe their local neighborhoods, take only local actions, and yet cause global problems to be solved. We conjecture that future interesting uses of link reversal are yet to be discovered.Table of Contents: Introduction / Routing in a Graph: Correctness / Routing in a Graph: Complexity / Routing and Leader Election in a Distributed System / Mutual Exclusion in a Distributed System / Distributed Queueing / Scheduling in a Graph / Resource Allocation in a Distributed System / Conclusion
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Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms
Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks.Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.
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Algorithm-Architecture Matching for Signal and Image Processing
Advances in signal and image processing together with increasing computing power are bringing mobile technology closer to applications in a variety of domains like automotive, health, telecommunication, multimedia, entertainment and many others. The development of these leading applications, involving a large diversity of algorithms (e.g. signal, image, video, 3D, communication, cryptography) is classically divided into three consecutive steps: a theoretical study of the algorithms, a study of the target architecture, and finally the implementation. Such a linear design flow is reaching its limits due to intense pressure on design cycle and strict performance constraints. The approach, called Algorithm-Architecture Matching, aims to leverage design flows with a simultaneous study of both algorithmic and architectural issues, taking into account multiple design constraints, as well as algorithm and architecture optimizations, that couldn’t be achieved otherwise if considered separately. Introducing new design methodologies is mandatory when facing the new emerging applications as for example advanced mobile communication or graphics using sub-micron manufacturing technologies or 3D-Integrated Circuits. This diversity forms a driving force for the future evolutions of embedded system designs methodologies.The main expectations from system designers’ point of view are related to methods, tools and architectures supporting application complexity and design cycle reduction. Advanced optimizations are essential to meet design constraints and to enable a wide acceptance of these new technologies.Algorithm-Architecture Matching for Signal and Image Processing presents a collection of selected contributions from both industry and academia, addressing different aspects of Algorithm-Architecture Matching approach ranging from sensors to architectures design. The scope of this book reflects the diversity of potential algorithms, including signal, communication, image, video, 3D-Graphics implemented onto various architectures from FPGA to multiprocessor systems. Several synthesis and resource management techniques leveraging design optimizations are also described and applied to numerous algorithms.Algorithm-Architecture Matching for Signal and Image Processing should be on each designer’s and EDA tool developer’s shelf, as well as on those with an interest in digital system design optimizations dealing with advanced algorithms.
R 4,655.02
Algorithm-Architecture Matching for Signal and Image Processing
Advances in signal and image processing together with increasing computing power are bringing mobile technology closer to applications in a variety of domains like automotive, health, telecommunication, multimedia, entertainment and many others. The development of these leading applications, involving a large diversity of algorithms (e.g. signal, image, video, 3D, communication, cryptography) is classically divided into three consecutive steps: a theoretical study of the algorithms, a study of the target architecture, and finally the implementation. Such a linear design flow is reaching its limits due to intense pressure on design cycle and strict performance constraints. The approach, called Algorithm-Architecture Matching, aims to leverage design flows with a simultaneous study of both algorithmic and architectural issues, taking into account multiple design constraints, as well as algorithm and architecture optimizations, that couldn’t be achieved otherwise if considered separately. Introducing new design methodologies is mandatory when facing the new emerging applications as for example advanced mobile communication or graphics using sub-micron manufacturing technologies or 3D-Integrated Circuits. This diversity forms a driving force for the future evolutions of embedded system designs methodologies.The main expectations from system designers’ point of view are related to methods, tools and architectures supporting application complexity and design cycle reduction. Advanced optimizations are essential to meet design constraints and to enable a wide acceptance of these new technologies.Algorithm-Architecture Matching for Signal and Image Processing presents a collection of selected contributions from both industry and academia, addressing different aspects of Algorithm-Architecture Matching approach ranging from sensors to architectures design. The scope of this book reflects the diversity of potential algorithms, including signal, communication, image, video, 3D-Graphics implemented onto various architectures from FPGA to multiprocessor systems. Several synthesis and resource management techniques leveraging design optimizations are also described and applied to numerous algorithms.Algorithm-Architecture Matching for Signal and Image Processing should be on each designer’s and EDA tool developer’s shelf, as well as on those with an interest in digital system design optimizations dealing with advanced algorithms.
R 4,655.92
R 5,266.47
Java 11 and 12 – New Features
Enhance your development skills with Java’s state-of-the-art features and projects to make your applications leaner and fasterKey FeaturesOvercome the challenges involved in migrating to new versions of JavaDiscover how Oracle has bridged the gap between Java and native codeMake the best use of new Java features and libraries in your applicationsBook DescriptionWith its new six-monthly release cadence, Java is moving forward faster. In addition to planned version releases, a lot of work is currently being undertaken on various Java projects at Oracle. In order to make best use of the new features in their applications and libraries, you must be well-versed with the most recent advancements.Java 11 and 12 – New Features will take you through the latest developments in Java, right from variable type inference and simplified multithreading through to performance improvements, which are covered in depth to help you make your applications more efficient. This book explains the relevance and applicability of Java's new features, and answers your questions on whether to invest in migrating to new Java versions and when to migrate. You'll also get to grips with platform features, such as AppCDS and new garbage collectors, to tune and optimize your application—from reduced launch time and latency to improved performance and throughput.By the end of this book, you will be equipped with a thorough understanding of the new features of Java 11, 12, and Project Amber, and possess the skills to apply them with a view to improving your application's performance.What you will learnStudy type interference and how to work with the var typeUnderstand Class-Data Sharing, its benefits, and limitationsDiscover platform options to reduce your application’s launch timeImprove application performance by switching garbage collectorsGet up to date with the new Java release cadenceDefine and assess decision criteria for migrating to a new version of JavaWho this book is forIf you’re an executive or solutions architect responsible for technology selection or Java migration decisions, this Java book is for you. You’ll also benefit from this book if you’re a computer science enthusiast curious to learn about the latest and upcoming Java features. This book will help you migrate your solutions from Java 8 or older to the latest Java release.
R 1,140.00
R 1,010.00
Representations for Genetic and Evolutionary Algorithms
In the field of genetic and evolutionary algorithms (GEAs), a large amount of theory and empirical study has been focused on operators and test problems, while problem representation has often been taken as given. This book breaks with this tradition and provides a comprehensive overview on the influence of problem representations on GEA performance. The book summarizes existing knowledge regarding problem representations and describes how basic properties of representations, such as redundancy, scaling, or locality, influence the performance of GEAs and other heuristic optimization methods. Using the developed theory, representations can be analyzed and designed in a theory-guided matter. The theoretical concepts are used for solving integer optimization problems and network design problems more efficiently. The book is written in an easy-readable style and is intended for researchers, practitioners, and students who want to learn about representations. This second edition extends the analysis of the basic properties of representations and introduces a new chapter on the analysis of direct representations.
R 4,660.61
Intersection and Decomposition Algorithms for Planar Arrangements
Several geometric problems can be formulated in terms of the arrangement of a collection of curves in a plane, which has made this one of the most widely studied topics in computational geometry. This book, first published in 1991, presents a study of various problems related to arrangements of lines, segments, or curves in the plane. The first problem is a proof of almost tight bounds on the length of (n,s)-Davenport–Schinzel sequences, a technique for obtaining optimal bounds for numerous algorithmic problems. Then the intersection problem is treated. The final problem is improving the efficiency of partitioning algorithms, particularly those used to construct spanning trees with low stabbing numbers, a very versatile tool in solving geometric problems. A number of applications are also discussed. Researchers in computational and combinatorial geometry should find much to interest them in this book.
R 1,834.32
Robustness and Complex Data Structures
This Festschrift in honour of Ursula Gather’s 60th birthday deals with modern topics in the field of robust statistical methods, especially for time series and regression analysis, and with statistical methods for complex data structures. The individual contributions of leading experts provide a textbook-style overview of the topic, supplemented by current research results and questions. The statistical theory and methods in this volume aim at the analysis of data which deviate from classical stringent model assumptions, which contain outlying values and/or have a complex structure. Written for researchers as well as master and PhD students with a good knowledge of statistics.
R 4,030.00
Tools and Algorithms for the Construction and Analysis of Systems
This book presents the refereed proceedings of the Second International Workshop on Tools and Algorithms for the Construction and Analysis of Systems, TACAS '96, held in Passau, Germany in March 1996.The book presents 19 revised full papers selected from a total of 47 submissions together with 11 tool presentations and 3 invited papers. The collection of papers addresses all current aspects of the design and analysis of distributed systems; the volume is organized in topical sections on tools, model checking and testing, security, models and methods, case studies, and logic and programs.
R 1,581.34
Multilevel Optimization: Algorithms and Applications
Researchers working with nonlinear programming often claim "the word is non linear" indicating that real applications require nonlinear modeling. The same is true for other areas such as multi-objective programming (there are always several goals in a real application), stochastic programming (all data is uncer tain and therefore stochastic models should be used), and so forth. In this spirit we claim: The word is multilevel. In many decision processes there is a hierarchy of decision makers, and decisions are made at different levels in this hierarchy. One way to handle such hierar chies is to focus on one level and include other levels' behaviors as assumptions. Multilevel programming is the research area that focuses on the whole hierar chy structure. In terms of modeling, the constraint domain associated with a multilevel programming problem is implicitly determined by a series of opti mization problems which must be solved in a predetermined sequence. If only two levels are considered, we have one leader (associated with the upper level) and one follower (associated with the lower level).
R 6,018.31
Sensors: Theory, Algorithms, and Applications
The objective of this book is to advance the current knowledge of sensor research particularly highlighting recent advances, current work, and future needs. The goal is to share current technologies and steer future efforts in directions that will benefit the majority of researchers and practitioners working in this broad field of study.
R 3,857.31
