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WALCOM: Algorithms and Computation
This book constitutes the proceedings of the 10th International Workshop on Algorithms and Computation, WALCOM 2016, held in Kathmandu, Nepal, in March 2016.The 27 full papers presented together with 4 invited talks were carefully reviewed and selected from 68 submissions. The papers cover a wide range of topics such as approximation algorithms, computational complexity, computational geometry, data structures, graph algorithms, graph coloring, graph exploration, and online algorithms.
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Elementary Approach To Design And Analysis Of Algorithms, An
'The book under review is an interesting elaboration that fills the gaps in libraries for concisely written and student-friendly books about essentials in computer science … I recommend this book for anyone who would like to study algorithms, learn a lot about computer science or simply would like to deepen their knowledge … The book is written in very simple English and can be understood even by those with limited knowledge of the English language. It should be emphasized that, despite the fact that the book consists of many examples, mathematical formulas and theorems, it is very hard to find any mistakes, errors or typos.'zbMATHIn computer science, an algorithm is an unambiguous specification of how to solve a class of problems. Algorithms can perform calculation, data processing and automated reasoning tasks.As an effective method, an algorithm can be expressed within a finite amount of space and time and in a well-defined formal language for calculating a function. Starting from an initial state and initial input (perhaps empty), the instructions describe a computation that, when executed, proceeds through a finite number of well-defined successive states, eventually producing 'output' and terminating at a final ending state. The transition from one state to the next is not necessarily deterministic; some algorithms, known as randomized algorithms, incorporate random input.This book introduces a set of concepts in solving problems computationally such as Growth of Functions; Backtracking; Divide and Conquer; Greedy Algorithms; Dynamic Programming; Elementary Graph Algorithms; Minimal Spanning Tree; Single-Source Shortest Paths; All Pairs Shortest Paths; Flow Networks; Polynomial Multiplication, to ways of solving NP-Complete Problems, supported with comprehensive, and detailed problems and solutions, making it an ideal resource to those studying computer science, computer engineering and information technology.
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Grid Generation and Adaptive Algorithm
The papers in this volume are based on lectures given at the IMA Workshop on Grid Generation and Adaptive Algorithms held during April 28 - May 2, 1997. Grid generation is a common feature of many computational tasks which require the discretization and representation of space and surfaces. The papers in this volume discuss how the geometric complexity of the physical object or the non-uniform nature of the solution variable make it impossible to use a uniform grid. Since an efficient grid requires knowledge of the computed solution, many of the papers in this volume treat how to construct grids that are adaptively computed with the solution. This volume will be of interest to computational scientists and mathematicians working in a broad variety of applications including fluid mechanics, solid mechanics, materials science, chemistry, and physics.Papers treat residual-based error estimation and adaptivity, repartitioning and load balancing for adaptive meshes, data structures and local refinement methods for conservation laws, adaptivity for hp-finite element methods, the resolution of boundary layers in high Reynolds number flow, adaptive methods for elastostatic contact problems, the full domain partition approach to parallel adaptive refinement, the adaptive solution of phase change problems, and quality indicators for triangular meshes.
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How to Think about Algorithms
Understand algorithms and their design with this revised student-friendly textbook. Unlike other algorithms books, this one is approachable, the methods it explains are straightforward, and the insights it provides are numerous and valuable. Without grinding through lots of formal proof, students will benefit from step-by-step methods for developing algorithms, expert guidance on common pitfalls, and an appreciation of the bigger picture. Revised and updated, this second edition includes a new chapter on machine learning algorithms, and concise key concept summaries at the end of each part for quick reference. Also new to this edition are more than 150 new exercises: selected solutions are included to let students check their progress, while a full solutions manual is available online for instructors. No other text explains complex topics such as loop invariants as clearly, helping students to think abstractly and preparing them for creating their own innovative ways to solve problems.
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Graph Theory, Combinatorics and Algorithms
Graph Theory, Combinatorics and Algorithms: Interdisciplinary Applications focuses on discrete mathematics and combinatorial algorithms interacting with real world problems in computer science, operations research, applied mathematics and engineering. The book contains eleven chapters written by experts in their respective fields, and covers a wide spectrum of high-interest problems across these discipline domains. Among the contributing authors are Richard Karp of UC Berkeley and Robert Tarjan of Princeton; both are at the pinnacle of research scholarship in Graph Theory and Combinatorics. The chapters from the contributing authors focus on "real world" applications, all of which will be of considerable interest across the areas of Operations Research, Computer Science, Applied Mathematics, and Engineering. These problems include Internet congestion control, high-speed communication networks, multi-object auctions, resource allocation, software testing, data structures, etc. In sum, this is a book focused on major, contemporary problems, written by the top research scholars in the field, using cutting-edge mathematical and computational techniques.
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Algorithms on Strings, Trees, and Sequences
String algorithms are a traditional area of study in computer science. In recent years their importance has grown dramatically with the huge increase of electronically stored text and of molecular sequence data (DNA or protein sequences) produced by various genome projects. This book is a general text on computer algorithms for string processing. In addition to pure computer science, the book contains extensive discussions on biological problems that are cast as string problems, and on methods developed to solve them. It emphasises the fundamental ideas and techniques central to today's applications. New approaches to this complex material simplify methods that up to now have been for the specialist alone. With over 400 exercises to reinforce the material and develop additional topics, the book is suitable as a text for graduate or advanced undergraduate students in computer science, computational biology, or bio-informatics. Its discussion of current algorithms and techniques also makes it a reference for professionals.
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Analysis and Design of Algorithms
Analysis and Design of Algorithms provides a structured view of algorithm design techniques in a concise, easy-to-read manner. The book was written with an express purpose of being easy — to understand, read, and carry.It presents a pioneering approach in the teaching of algorithms, based on learning algorithm design techniques, and not merely solving a collection of problems. This allows students to master one design technique at a time and apply it to a rich variety of problems.Analysis and Design of Algorithms covers the algorithmic design techniques of divide and conquer, greedy, dynamic programming, branch and bound, and graph traversal. For each of these techniques, there are templates and guidelines on when to use and not to use each technique. Many sections contain innovative mnemonics to aid the readers in remembering the templates and key takeaways. Additionally, the book covers NP-completeness and the inherent hardness of problems. The third edition includes a new section on polynomial multiplication, as well as additional exercise problems, and an updated appendix.Written with input from students and professionals, Analysis and Design of Algorithms is well suited for introductory algorithm courses at the undergraduate and graduate levels. The structured organization of the text makes it especially appropriate for online and distance learning.
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Algorithms Unlocked
For anyone who has ever wondered how computers solve problems, an engagingly written guide for nonexperts to the basics of computer algorithms. Have you ever wondered how your GPS can find the fastest way to your destination, selecting one route from seemingly countless possibilities in mere seconds? How your credit card account number is protected when you make a purchase over the Internet? The answer is algorithms. And how do these mathematical formulations translate themselves into your GPS, your laptop, or your smart phone? This book offers an engagingly written guide to the basics of computer algorithms. In Algorithms Unlocked, Thomas Cormen-coauthor of the leading college textbook on the subject-provides a general explanation, with limited mathematics, of how algorithms enable computers to solve problems. Readers will learn what computer algorithms are, how to describe them, and how to evaluate them. They will discover simple ways to search for information in a computer; methods for rearranging information in a computer into a prescribed order ("sorting"); how to solve basic problems that can be modeled in a computer with a mathematical structure called a "graph" (useful for modeling road networks, dependencies among tasks, and financial relationships); how to solve problems that ask questions about strings of characters such as DNA structures; the basic principles behind cryptography; fundamentals of data compression; and even that there are some problems that no one has figured out how to solve on a computer in a reasonable amount of time.
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WALCOM: Algorithms and Computation
This book constitutes the thoroughly refereed conference proceedings of the 9th International Workshop on Algorithms and Computation, WALCOM 2015, held in Dhaka, Bangladesh, in February 2015. The 26 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 85 submissions. The papers are organized in topical sections on approximation algorithms, data structures and algorithms, computational geometry, combinatorial algorithms, distributed and online algorithms, graph drawing and algorithms, combinatorial problems and complexity, and graph enumeration and algorithms.
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Parallel Algorithms for Irregularly Structured Problems
This book presents the proceedings of the Second International Workshop on Parallel Algorithms for Irregularly Structured Problems, IRREGULAR '95, held in Lyon, France in September 1995. This workshop series addresses issues related to deriving efficient parallel solutions to irregularly structured problems and aims at fostering cooperation between practitioners and theoreticians in the field.Besides three invited papers, 20 full papers and eight short contributions are presented, all selected during a highly competitive refereeing process; the volume is organized in sections on programming methods and compiling techniques, mapping and scheduling, applications, and optimization.
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Applied Evolutionary Algorithms in Java
This book is intended for students, researchers, and professionals interested in evolutionary algorithms at graduate and postgraduate level. No mathematics beyond basic algebra and Cartesian graphs methods is required, as the aim is to encourage applying the JAVA toolkit to develop an appreciation of the power of these techniques.
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Algorithms for Graphics and Image Processing
The technological developments of the last ten years have made com puter graphics and image processing by computer popular. Pictorial pat tern recognition has also shown significant progress. Clearly, there exist overlapping interests among the three areas of research. Graphic displays are of concern to anyone involved in image processing or pic torial pattern recognition and many problems in graphics require methodologies from image processing for their solutions. The data structures used in all three areas are similar. It seems that there is a common body of knowledge underlying all three areas, pictorial informa tion processing by computer. The novelty of these fields makes it difficult to design a course or to a write a book covering their basic concepts. Some of the treatises on graphics focus on the hardware and methods of current interest while treatises on image processing often emphasize applications and classical signal processing. The fast evolution of technology causes such material to lose its relevance. For example, the development of optical fibers has reduced the importance of bandwidth compression.
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Advances in Computational Algorithms and Data Analysis
Advances in Computational Algorithms and Data Analysis offers state of the art tremendous advances in computational algorithms and data analysis. The selected articles are representative in these subjects sitting on the top-end-high technologies. The volume serves as an excellent reference work for researchers and graduate students working on computational algorithms and data analysis.
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Algorithms
This text explains the fundamentals of algorithms in a story line that makes the material enjoyable and easy to digest. Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include: The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated. Carefully chosen advanced topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence. An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. "Algorithms" is an outstanding undergraduate text, equally informed by the historical roots and contemporary applications of its subject.
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Algorithms and Methods in Structural Bioinformatics
The three-dimensional structure and function of molecules present many challenges and opportunities for developing an understanding of biological systems. With the increasing availability of molecular structures and the advancing accuracy of structure predictions and molecular simulations, the space for algorithmic advancement on many analytical and predictive problems is both broad and deep. To support this field, a rich set of methods and algorithms are available, addressing a variety of important problems such as protein-protein interactions, the effect of mutations on protein structure and function, and protein structure determination. Despite recent advancements in the field, in particular in protein folding with the development of AlphaFold, many problems still remain unsolved.In this book we focus on a number of topics in Structural Bioinformatics: Cryo-EM structural detection, protein conformational exploration, elucidation of molecular binding surface using geometry, the effect of mutations, insertions and deletions on protein structural stability, and protein-ligand binding.
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Functional Data Structures in R
Get an introduction to functional data structures using R and write more effective code and gain performance for your programs. This book teaches you workarounds because data in functional languages is not mutable: for example you’ll learn how to change variable-value bindings by modifying environments, which can be exploited to emulate pointers and implement traditional data structures. You’ll also see how, by abandoning traditional data structures, you can manipulate structures by building new versions rather than modifying them. You’ll discover how these so-called functional data structures are different from the traditional data structures you might know, but are worth understanding to do serious algorithmic programming in a functional language such as R.By the end of Functional Data Structures in R, you’ll understand the choices to make in order to most effectively work with data structures when you cannot modify the data itself. These techniques are especially applicable for algorithmic development important in big data, finance, and other data science applications.What You'll LearnCarry out algorithmic programming in R Use abstract data structures Work with both immutable and persistent data Emulate pointers and implement traditional data structures in RBuild new versions of traditional data structures that are knownWho This Book Is ForExperienced or advanced programmers with at least a comfort level with R. Some experience with data structures recommended.
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Programming GPS and OpenStreetMap Applications with Java
Written by an expert in the development of GPS systems with digital maps and navigation, Programming GPS and OpenStreetMap Applications with Java: The RealObject Application Framework provides a concrete paradigm for object-oriented modeling and programming. It presents a thorough introduction to the use of available global positioning data for the development of applications involving digital maps. The author first describes the different formats of GPS data and digital maps and shows how to use recorded GPS traces to replay and display this data on a digital map. Then, he works through in detail the processing steps of obtaining dedicated data from OpenStreetMaps and how to extract a network for a simple navigation application. For each topic covered—GPS data, OpenStreetMaps, and navigation—Java code is developed that can easily be adapted to the readers’ needs and locality.Finally, all components are put together in a sample computer-game application modeled on the well-known board game, Scotland Yard. The computer game is intended to be a basis from which readers can develop and customize their own application for their desired geographical area. The developed application can be "published" on the Internet and made available for interactive multiplayer competition.This book provides a fun and interesting way to learn distributed programming with Java and real-world data. Open-source software is available on a companion website at www.roaf.de
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Handbook of Applied Algorithms
Discover the benefits of applying algorithms to solve scientific, engineering, and practical problems Providing a combination of theory, algorithms, and simulations, Handbook of Applied Algorithms presents an all-encompassing treatment of applying algorithms and discrete mathematics to practical problems in "hot" application areas, such as computational biology, computational chemistry, wireless networks, and computer vision. In eighteen self-contained chapters, this timely book explores: * Localized algorithms that can be used in topology control for wireless ad-hoc or sensor networks * Bioinformatics algorithms for analyzing data * Clustering algorithms and identification of association rules in data mining * Applications of combinatorial algorithms and graph theory in chemistry and molecular biology * Optimizing the frequency planning of a GSM network using evolutionary algorithms * Algorithmic solutions and advances achieved through game theory Complete with exercises for readers to measure their comprehension of the material presented, Handbook of Applied Algorithms is a much-needed resource for researchers, practitioners, and students within computer science, life science, and engineering. Amiya Nayak, PhD, has over seventeen years of industrial experience and is Full Professor at the School of Information Technology and Engineering at the University of Ottawa, Canada. He is on the editorial board of several journals. Dr. Nayak's research interests are in the areas of fault tolerance, distributed systems/algorithms, and mobile ad-hoc networks. Ivan StojmenoviC?, PhD, is Professor at the University of Ottawa, Canada (www.site.uottawa.ca/~ivan), and Chair Professor of Applied Computing at the University of Birmingham, United Kingdom. Dr. Stojmenovic? received the Royal Society Wolfson Research Merit Award. His current research interests are mostly in the design and analysis of algorithms for wireless ad-hoc and sensor networks.
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Live Data Structures in Logic Programs
A common hazard for implementations of applicativeprogramming languages is the excessive creation of garbagecells during program execution. The available run-timegarbage collecting processes are expensive in time and oftenrequire a periodic disruption of the program execution. Thepresent book addresses the problem of memory re-use forlogic programs through program analysis rather than byrun-time garbage collection. The static analysis isconstructed as an application of abstractinterpretation forlogic programs. The starting point is a previously developedapplication of integrated type and mode analysis, whichbasically supplies a description of the logical terms towhich program variables can be bound at run time. Thecontribution of the book consists of a modular extension ofthe abstract domain and operations in order to deriverun-time properties concerning the sharing and liveness ofterm substructures dynamically created during programexecution. Alsoillustrated is how such information can beused by the compiler to improve the allocation of run-timestructures and to automatically introduce destructiveassignments in logic languages in a safe and transparentway, thereby shifting some part of the run-time storagereclamation overhead to compile time.
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Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery
This book constitutes the refereed proceedings of the 12th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2016, held in Ustroń, Poland, in May/June 2016.It consists of 57 carefully reviewed papers selected from 152 submissions. The papers are organized in topical sections, namely artificial intelligence, data mining and knowledge discovery; architectures, structures and algorithms for efficient data processing; data warehousing and OLAP; natural language processing, ontologies and semantic Web; bioinformatics and biomedical data analysis; data processing tools; novel applications of database systems.
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First Course in Algorithms Through Puzzles
This textbook introduces basic algorithms and explains their analytical methods. All algorithms and methods introduced in this book are well known and frequently used in real programs. Intended to be self-contained, the contents start with the basic models, and no prerequisite knowledge is required. This book is appropriate for undergraduate students in computer science, mathematics, and engineering as a textbook, and is also appropriate for self-study by beginners who are interested in the fascinating field of algorithms. More than 40 exercises are distributed throughout the text, and their difficulty levels are indicated. Solutions and comments for all the exercises are provided in the last chapter. These detailed solutions will enable readers to follow the author's steps to solve problems and to gain a better understanding of the contents.
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Algorithms and Theory of Computation Handbook, Volume 1
Algorithms and Theory of Computation Handbook, Second Edition: General Concepts and Techniques provides an up-to-date compendium of fundamental computer science topics and techniques. It also illustrates how the topics and techniques come together to deliver efficient solutions to important practical problems. Along with updating and revising many of the existing chapters, this second edition contains four new chapters that cover external memory and parameterized algorithms as well as computational number theory and algorithmic coding theory. This best-selling handbook continues to help computer professionals and engineers find significant information on various algorithmic topics. The expert contributors clearly define the terminology, present basic results and techniques, and offer a number of current references to the in-depth literature. They also provide a glimpse of the major research issues concerning the relevant topics.
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Nature-Inspired Optimization Algorithms with Java
Gain insight into the world of nature-inspired optimization techniques and algorithms. This book will prepare you to apply different nature-inspired optimization techniques to solve problems using Java.You'll start with an introduction to the hidden algorithms that nature uses and find the approximate solutions to optimization problems. You'll then see how living creatures such as fish and birds are able to perform computation to solve specific optimization tasks. This book also covers various nature-inspired algorithms by reviewing code examples for each one followed by crisp and clear explanations of the algorithm using Java code. You'll examine the use of each algorithm in specific industry scenarios such as fleet scheduling in supply chain management, and shop floor management in industrial and manufacturing applications. Nature-Inspired Optimization Algorithms with Java is your pathway to understanding a variety of optimization problems that exist in various industries and domains and it will develop an ability to apply nature-inspired algorithms to find approximate solutions to them.What You'll LearnStudy optimization and its problemsExamine nature-inspired algorithms such as Particle Swarm, Gray wolf, etc.See how nature-inspired algorithms are being used to solve optimization problemsUse Java for solving the different nature-inspired algorithms with real-world examplesWho This Book Is For Software developers/architects who are looking to hone their skills in area of problem solving related to optimization with Java.
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Fundamental Algorithms for Permutation Groups
This is the first-ever book on computational group theory.It provides extensive and up-to-date coverage of thefundamental algorithms for permutation groups with referenceto aspects of combinatorial group theory, soluble groups,and p-groups where appropriate.The book begins with a constructive introduction to grouptheory and algorithms for computing with small groups,followed by a gradual discussion of the basic ideas of Simsfor computing with very large permutation groups, andconcludes with algorithms that use group homomorphisms, asin the computation of Sylowsubgroups. No background ingroup theory is assumed.The emphasis is on the details of the data structures andimplementation which makes the algorithms effective whenapplied to realistic problems. The algorithms are developedhand-in-hand with the theoretical and practicaljustification.All algorithms are clearly described,examples are given, exercises reinforce understanding, anddetailed bibliographical remarks explain the history andcontext of the work.Much of the later material on homomorphisms, Sylowsubgroups, and soluble permutation groups is new.
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Efficient Algorithms for Listing Combinatorial Structures
First published in 1993, this thesis is concerned with the design of efficient algorithms for listing combinatorial structures. The research described here gives some answers to the following questions: which families of combinatorial structures have fast computer algorithms for listing their members? What general methods are useful for listing combinatorial structures? How can these be applied to those families which are of interest to theoretical computer scientists and combinatorialists? Amongst those families considered are unlabelled graphs, first order one properties, Hamiltonian graphs, graphs with cliques of specified order, and k-colourable graphs. Some related work is also included, which compares the listing problem with the difficulty of solving the existence problem, the construction problem, the random sampling problem, and the counting problem. In particular, the difficulty of evaluating Pólya's cycle polynomial is demonstrated.
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Fault-Tolerant Search Algorithms
Why a book on fault-tolerant search algorithms? Searching is one of the fundamental problems in computer science. Time and again algorithmic and combinatorial issues originally studied in the context of search find application in the most diverse areas of computer science and discrete mathematics. On the other hand, fault-tolerance is a necessary ingredient of computing. Due to their inherent complexity, information systems are naturally prone to errors, which may appear at any level – as imprecisions in the data, bugs in the software, or transient or permanent hardware failures. This book provides a concise, rigorous and up-to-date account of different approaches to fault-tolerance in the context of algorithmic search theory. Thanks to their basic structure, search problems offer insights into how fault-tolerant techniques may be applied in various scenarios. In the first part of the book, a paradigmatic model for fault-tolerant search is presented, the Ulam—Rényi problem. Following a didactic approach, the author takes the reader on a tour of Ulam—Rényi problem variants of increasing complexity. In the context of this basic model, fundamental combinatorial and algorithmic issues in the design of fault-tolerant search procedures are discussed. The algorithmic efficiency achievable is analyzed with respect to the statistical nature of the error sources, and the amount of information on which the search algorithm bases its decisions. In the second part of the book, more general models of faults and fault-tolerance are considered. Special attention is given to the application of fault-tolerant search procedures to specific problems in distributed computing, bioinformatics and computational learning. This book will be of special value to researchers from the areas of combinatorial search and fault-tolerant computation, but also to researchers in learning and coding theory, databases, and artificial intelligence. Only basic training in discrete mathematics is assumed. Parts of the book can be used as the basis for specialized graduate courses on combinatorial search, or as supporting material for a graduate or undergraduate course on error-correcting codes.
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Compact Data Structures
Compact data structures help represent data in reduced space while allowing it to be queried, navigated, and operated in compressed form. They are essential tools for efficiently handling massive amounts of data by exploiting the memory hierarchy. They also reduce the resources needed in distributed deployments and make better use of the limited memory in low-end devices. The field has developed rapidly, reaching a level of maturity that allows practitioners and researchers in application areas to benefit from the use of compact data structures. This first comprehensive book on the topic focuses on the structures that are most relevant for practical use. Readers will learn how the structures work, how to choose the right ones for their application scenario, and how to implement them. Researchers and students in the area will find in the book a definitive guide to the state of the art in compact data structures.
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Beyond Databases, Architectures and Structures. Paving the Road to Smart Data Processing and Analysis
This book constitutes the refereed proceedings of the 15th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2019, held in Ustroń, Poland, in May 2019.It consists of 26 carefully reviewed papers selected from 69 submissions. The papers are organized in topical sections, namely big data and cloud computing; architectures, structures and algorithms for efficient data processing and analysis; artificial intelligence, data mining and knowledge discovery; image analysis and multimedia mining; bioinformatics and biomedical data analysis; industrial applications; networks and security.
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Advances in Computational Algorithms and Data Analysis
Advances in Computational Algorithms and Data Analysis offers state of the art tremendous advances in computational algorithms and data analysis. The selected articles are representative in these subjects sitting on the top-end-high technologies. The volume serves as an excellent reference work for researchers and graduate students working on computational algorithms and data analysis.
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Algorithms and Computation
This book constitutes the refereed proceedings of the 18th International Symposium on Algorithms and Computation, ISAAC 2007, held in Sendai, Japan, in December 2007. The 77 revised full papers presented together with two invited talks were carefully reviewed and selected from 220 submissions. The papers included topical sections on graph algorithms, computational geometry, complexity, graph drawing, distributed algorithms, optimization, data structure, and game theory.
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Core Java, Volume II
The Classic Guide to the Java Programming Language--Fully Updated through Java 25 Core Java is the leading no-nonsense tutorial and reference for experienced programmers who want to write robust Java code for real-world applications. Now, Core Java, Volume II: Advanced Features, Fourteenth Edition, has been revised to cover the new features and enhancements in the Java 25 long-term support release. As always, all chapters have been completely updated, outdated material has been removed, and the new APIs are covered in detail. This volume focuses on the advanced topics that a programmer needs to know for professional software development and includes authoritative coverage of fi le processing, networking, databases, security, internationalization, compiling and scripting, and foreign functions, as well as complete chapters on the Streams, XML, and Date and Time APIs. In addition, the chapters on Swing and Graphics cover techniques that are applicable to both client-side user interfaces and server-side generation of graphics and images. Cay S. Horstmann clearly explains sophisticated new features with depth and completeness and demonstrates how to use them to build professional-quality applications. Horstmann's thoroughly tested sample code reflects modern Java style and best practices. The examples are carefully crafted for easy understanding and maximum practical value, so you can rely on them to jump-start your own programs. Effectively use Java streams, including new Java 25 features such as stream gatherersMaster advanced techniques, idioms, and best practices for writing reliable Java codeMake the most of enhanced Java I/O APIs, object serialization, and regular expressionsConnect to network services, harvest web data with the HTTP/2 client, and serve data with the built-in web server or implement your own serverProcess code via the Scripting and Compiler APIs, and generate code with the new Class File APILeverage the Java security model, user authentication, and the security library's cryptographic functionsLearn powerful new APIs for accessing foreign functions and memory "This is the definitive reference and instructional work for Java and the Java ecosystem."--Andrew Binstock, Java Magazine See Core Java, Volume I: Fundamentals, Fourteenth Edition, for expert coverage of Java programming fundamentals, including objects, generics, collections, lambda expressions, concurrency, modularity, and functional programming. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
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Algorithms for Data Science
This textbook on practical data analytics unites fundamental principles, algorithms, and data. Algorithms are the keystone of data analytics and the focal point of this textbook. Clear and intuitive explanations of the mathematical and statistical foundations make the algorithms transparent. But practical data analytics requires more than just the foundations. Problems and data are enormously variable and only the most elementary of algorithms can be used without modification. Programming fluency and experience with real and challenging data is indispensable and so the reader is immersed in Python and R and real data analysis. By the end of the book, the reader will have gained the ability to adapt algorithms to new problems and carry out innovative analyses.This book has three parts:(a) Data Reduction: Begins with the concepts of data reduction, data maps, and information extraction. The second chapter introduces associative statistics, the mathematical foundation of scalable algorithms and distributed computing. Practical aspects of distributed computing is the subject of the Hadoop and MapReduce chapter.(b) Extracting Information from Data: Linear regression and data visualization are the principal topics of Part II. The authors dedicate a chapter to the critical domain of Healthcare Analytics for an extended example of practical data analytics. The algorithms and analytics will be of much interest to practitioners interested in utilizing the large and unwieldly data sets of the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System.(c) Predictive Analytics Two foundational and widely used algorithms, k-nearest neighbors and naive Bayes, are developed in detail. A chapter is dedicated to forecasting. The last chapter focuses on streaming data and uses publicly accessible data streams originating from the Twitter API and the NASDAQ stock market in the tutorials.This book is intended for a one- or two-semester course in data analytics for upper-division undergraduate and graduate students in mathematics, statistics, and computer science. The prerequisites are kept low, and students with one or two courses in probability or statistics, an exposure to vectors and matrices, and a programming course will have no difficulty. The core material of every chapter is accessible to all with these prerequisites. The chapters often expand at the close with innovations of interest to practitioners of data science. Each chapter includes exercises of varying levels of difficulty. The text is eminently suitable for self-study and an exceptional resource for practitioners.
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