Algorithms and data structures Books

Book SynopsisThis book introduces the most recent research and innovative developments regarding the new strains of COVID-19. While medical and natural sciences have been working instantly on deriving solutions and trying to protect humankind against such virus types, there is also a great focus on technological developments for improving the mechanism – momentum of science for effective and efficient solutions. At this point, computational intelligence is the most powerful tools for researchers to fight against COVID-19. Thanks to instant data-analyze and predictive techniques by computational intelligence, it is possible to get positive results and introduce revolutionary solutions against related medical diseases. By running capabilities – resources for rising the computational intelligence, technological fields like Artificial Intelligence (with Machine / Deep Learning), Data Mining, Applied Mathematics are essential components for processing data, recognizing patterns, modelling new techniques and improving the advantages of the computational intelligence more. Nowadays, there is a great interest in the application potentials of computational intelligence to be an effective approach for taking humankind more step away, after COVID-19 and before pandemics similar to the COVID-19 many appear.

Read more less

Book SynopsisThis work is intended to serve as a guide for graduate students and researchers who wish to get acquainted with the main theoretical and practical tools for the numerical minimization of convex functions on Hilbert spaces. Therefore, it contains the main tools that are necessary to conduct independent research on the topic. It is also a concise, easy-to-follow and self-contained textbook, which may be useful for any researcher working on related fields, as well as teachers giving graduate-level courses on the topic. It will contain a thorough revision of the extant literature including both classical and state-of-the-art references.Trade Review“This short book is dedicated to convex optimization, beginning with theoretical aspects, ending with numerical methods, and complemented with numerous examples. … this is an interesting and well-written book that is adequate for a graduate-level course on convex optimization.” (Constantin Zălinescu, Mathematical Reviews, November, 2015)Table of ContentsBasic Functional Analysis.- Existence of Minimizers.- Convex Analysis and Subdifferential Calculus.- Examples.- Problem-solving Strategies.- Keynote Iterative Methods.

Read more less

Book SynopsisThis comprehensive textbook presents a clean and coherent account of most fundamental tools and techniques in Parameterized Algorithms and is a self-contained guide to the area. The book covers many of the recent developments of the field, including application of important separators, branching based on linear programming, Cut & Count to obtain faster algorithms on tree decompositions, algorithms based on representative families of matroids, and use of the Strong Exponential Time Hypothesis. A number of older results are revisited and explained in a modern and didactic way.The book provides a toolbox of algorithmic techniques. Part I is an overview of basic techniques, each chapter discussing a certain algorithmic paradigm. The material covered in this part can be used for an introductory course on fixed-parameter tractability. Part II discusses more advanced and specialized algorithmic ideas, bringing the reader to the cutting edge of current research. Part III presents complexity results and lower bounds, giving negative evidence by way of W[1]-hardness, the Exponential Time Hypothesis, and kernelization lower bounds.All the results and concepts are introduced at a level accessible to graduate students and advanced undergraduate students. Every chapter is accompanied by exercises, many with hints, while the bibliographic notes point to original publications and related work.Trade Review“I enjoyed reading this book, which is a good textbook for graduate and advanced undergraduate students of computer science. Each chapter contains sufficient exercises with hints whenever necessary and helpful bibliographic notes. I found the references quite comprehensive, and the index was quite useful. … this is the best book I have seen on the topic. I strongly recommend it.” (Soubhik Chakraborty, Computing Reviews, April, 2017)“The style of the book is clear, and the material is well positioned to be accessible by graduate students and advanced undergraduate students. The exercises and hints provide a good ground for self-study, while bibliographic notes point to original papers and related work. Overall, this is an excellent book that can be useful to graduate and advanced undergraduate students either as a self-study text or as part of a course.” (Alexander Tzanov, Computing Reviews, February, 2016)“This is the most recent and most up-to-date textbook on parameterized algorithms, one of the major thrusts in algorithmics in recent years. … this new textbook has more than twice as many pages shows the development of the field. … This book does a very good job at balancing the necessary mathematical rigour with a nice presentation of the results.” (Henning Fernau, Mathematical Reviews, February, 2016)“This book serves as an introduction to the field of parameterized algorithms and complexity accessible to graduate students and advanced undergraduate students. It contains a clean and coherent account of some of the most recent tools and techniques in the area.” (Paulo Mbunga, zbMATH 1334.90001, 2016)Table of ContentsIntroduction.- Kernelization.- Bounded Search Trees.- Iterative Compression.- Randomized Methods in Parameterized Algorithms.- Miscellaneous.- Treewidth.- Finding Cuts and Separators.- Advanced Kernelization Algorithms.- Algebraic Techniques: Sieves, Convolutions, and Polynomials.- Improving Dynamic Programming on Tree Decompositions.- Matroids.- Fixed-Parameter Intractability.- Lower Bounds Based on the Exponential-Time Hypothesis.- Lower Bounds for Kernelization.

Read more less

Book SynopsisIn this introductory textbook the author explains the key topics in cryptography. He takes a modern approach, where defining what is meant by "secure" is as important as creating something that achieves that goal, and security definitions are central to the discussion throughout.The author balances a largely non-rigorous style — many proofs are sketched only — with appropriate formality and depth. For example, he uses the terminology of groups and finite fields so that the reader can understand both the latest academic research and "real-world" documents such as application programming interface descriptions and cryptographic standards. The text employs colour to distinguish between public and private information, and all chapters include summaries and suggestions for further reading.This is a suitable textbook for advanced undergraduate and graduate students in computer science, mathematics and engineering, and for self-study by professionals in information security. While the appendix summarizes most of the basic algebra and notation required, it is assumed that the reader has a basic knowledge of discrete mathematics, probability, and elementary calculus.Trade Review“The goal of cryptography is to obfuscate data for unintended recipients. … The book is divided into four parts. … The book is very comprehensive, and very accessible for dedicated students.” (Klaus Galensa, Computing Reviews, computingreviews.com, October, 2016)“Cryptography made simple is a textbook that provides a broad coverage of topics that form an essential working knowledge for the contemporary cryptographer. It is particularly suited to introducing graduate and advanced undergraduate students in computer science to the concepts necessary for understanding academic cryptography and its impact on real-world practice, though it will also be useful for mathematicians or engineers wishing to gain a similar perspective on this material.” (Maura Beth Paterson, Mathematical Reviews, July, 2016)“This is a very thorough introduction to cryptography, aimed at lower-division undergraduates. It is an engineering textbook that uses modern mathematical terminology (such as groups and finite fields). … Bottom line: really for engineers, and a useful book if used carefully; the organization makes is easy to get overwhelmed by the background material before you get to the 'good stuff', and even the good stuff has an overwhelming amount of detail.” (Allen Stenger, MAA Reviews, maa.org, June, 2016)“This very thorough book by Smart (Univ. of Bristol, UK) is aimed at graduate students and advanced undergraduates in mathematics and computer science and intended to serve as a bridge to research papers in the field. … Summing Up: Recommended. Upper-division undergraduates through professionals/practitioners.” (C. Bauer, Choice, Vol. 53 (10), June, 2016)Table of ContentsModular Arithmetic, Groups, Finite Fields and Probability.- Elliptic Curves.- Historical Ciphers.- The Enigma Machine.- Information Theoretic Security.- Historical Stream Ciphers.- Modern Stream Ciphers.- Block Ciphers.- Symmetric Key Distribution.- Hash Functions and Message Authentication Codes.- Basic Public Key Encryption Algorithms.- Primality Testing and Factoring.- Discrete Logarithms.- Key Exchange and Signature Schemes.- Implementation Issues.- Obtaining Authentic Public Keys.- Attacks on Public Key Schemes.- Definitions of Security.- Complexity Theoretic Approaches.- Provable Security: With Random Oracles.- Hybrid Encryption.- Provable Security: Without Random Oracles.- Secret Sharing Schemes.- Commitments and Oblivious Transfer.- Zero-Knowledge Proofs.- Secure Multiparty Computation.

Read more less

Book SynopsisThis book treats graph colouring as an algorithmic problem, with a strong emphasis on practical applications. The author describes and analyses some of the best-known algorithms for colouring arbitrary graphs, focusing on whether these heuristics can provide optimal solutions in some cases; how they perform on graphs where the chromatic number is unknown; and whether they can produce better solutions than other algorithms for certain types of graphs, and why. The introductory chapters explain graph colouring, and bounds and constructive algorithms. The author then shows how advanced, modern techniques can be applied to classic real-world operational research problems such as seating plans, sports scheduling, and university timetabling. He includes many examples, suggestions for further reading, and historical notes, and the book is supplemented by a website with an online suite of downloadable code. The book will be of value to researchers, graduate students, and practitioners in the areas of operations research, theoretical computer science, optimization, and computational intelligence. The reader should have elementary knowledge of sets, matrices, and enumerative combinatorics.Trade Review“The book gives a comprehensive description and handling on arguably one of the most important notions of combinatorics—graph coloring. … The book is nicely written, and carries a big pile of information valuable for both users and researchers in the field.” (András Sándor Pluhár, Mathematical Reviews, February, 2017)“This well-written book will serve as a utilitarian guide to graph coloring and its practical applications. It includes many definitions, theorems, proofs, algorithms, and pointers for further reading. The book will be helpful for teaching courses on graph coloring to students of mathematics and computer science. I strongly recommend it for the intended audience.” (S. V. Nagaraj, Computing Reviews, computingreviews.com, June, 2016)“The book is a comprehensive guide to graph colouring algorithms. … The book is a nice textbook for both undergraduate and graduate students in the areas of operations research and theoretical computer science. … Finally, it is a good source of knowledge for practitioners.” (Marcin Anholcer, zbMATH 1330.05002, 2016)Table of ContentsIntroduction to Graph Colouring.- Bounds and Constructive Algorithms.- Advanced Techniques for Graph Colouring.- Algorithm Case Studies.- Applications and Extensions.- Designing Seating Plans.- Designing Sports Leagues.- Designing University Timetables.- App. A, Computing Resources.- References.- Index.

Read more less

Book SynopsisThis book explains the state-of-the-art algorithms used to simulate biological dynamics. Each technique is theoretically introduced and applied to a set of modeling cases. Starting from basic simulation algorithms, the book also introduces more advanced techniques that support delays, diffusion in space, or that are based on hybrid simulation strategies.This is a valuable self-contained resource for graduate students and practitioners in computer science, biology and bioinformatics. An appendix covers the mathematical background, and the authors include further reading sections in each chapter.Trade Review“I will not hesitate to recommend … this book, both as an introductory explanation as well as later on when they are deep in a modeling exercise and need to understand the many subtle yet important variations of stochastic simulation techniques applicable to biological systems.” (Sara Kalvala, Computing Reviews, March, 2018)​Table of ContentsIntroduction.- Deterministic Simulation Algorithms.- Stochastic Simulation Algorithms.- Hybrid Simulation Algorithms.- Reaction-Diffusion Systems.- Conclusions and Perspectives.

Read more less

Book SynopsisThis accessible and engaging textbook/guide provides a concise introduction to data structures and associated algorithms. Emphasis is placed on the fundamentals of data structures, enabling the reader to quickly learn the key concepts, and providing a strong foundation for later studies of more complex topics. The coverage includes discussions on stacks, queues, lists, (using both arrays and links), sorting, and elementary binary trees, heaps, and hashing. This content is also a natural continuation from the material provided in the separate Springer title Guide to Java by the same authors.Topics and features: reviews the preliminary concepts, and introduces stacks and queues using arrays, along with a discussion of array-based lists; examines linked lists, the implementation of stacks and queues using references, binary trees, a range of varied sorting techniques, heaps, and hashing; presents both primitive and generic data types in each chapter, and makes use of contour diagrams to illustrate object-oriented concepts; includes chapter summaries, and asks the reader questions to help them interact with the material; contains numerous examples and illustrations, and one or more complete program in every chapter; provides exercises at the end of each chapter, as well as solutions to selected exercises, and a glossary of important terms.This clearly-written work is an ideal classroom text for a second semester course in programming using the Java programming language, in preparation for a subsequent advanced course in data structures and algorithms. The book is also eminently suitable as a self-study guide in either academe or industry.Trade Review“This text is intended to provide undergraduates using Java with a concise, focused, and relatively simple coverage of some of the basic data structures in use. These include arrays, linked lists, trees, heaps (in arrays), and hash tables. … The book covers the algorithms and data structures well with clear language, abundant diagrams, and good exercises. It could be a good introduction for curricula using Java as a primary teaching language.” (Jeffrey Putnam, Computing Reviews, July, 2018)​Table of ContentsPreliminary Concepts Stacks Using Arrays Queues Using Arrays Lists Using Arrays Lists Using Objects and References Ordered Linked Lists Stacks and Queues Using References Binary Trees Sorting Heaps Hashing

Read more less

Book SynopsisDie Komplexitätstheorie untersucht den algorithmischen Aufwand zur Lösung von Problemen mit Hilfe einer Maschine. Dabei werden Rechnermodelle wie Turing-Maschinen oder Registermaschinen verwendet, um von speziellen Architektur- und Implementationsdetails unabhängige Ergebnisse zu gewinnen.Table of Contents1 Das TM-Modell.- 1.0 Vorbemerkungen.- 1.0.1 Mengen.- 1.0.2 Graphen.- 1.0.3 Strings, Sprachen.- 1.1 Turing-Maschinen.- 1.1.1 Das allgemeine Modell.- 1.1.2 Verschiedene Speichertypen.- 1.1.3 Beispiele für die Arbeitsweise von TM.- 1.1.4 Berechenbarkeit.- 1.1.5 Nichtdeterministische Berechnungen.- 1.2 Das Rechnen mit TM.- 1.2.1 Elementare Techniken.- 1.2.2 Simulation, Band- und Kopf-Reduktion.- 1.2.3 Universelle Maschinen.- 1.3 Mathematische Grundlagen.- 1.3.1 Notation.- 1.3.2 Asymptotisches Wachstum.- 1.3.3 Wachstumsordnungen.- 1.3.4 Rekursionsgleichungen.- 1.4 Die Komplexität von TM.- 1.4.1 Schranken, Maße und Konstruierbarkeit.- 1.4.2 Komplexitätsklassen.- 1.4.3 Diagonalisierung.- 1.4.4 Bandkompression.- 1.4.5 Lineare Beschleunigung.- 1.5 Übungsaufgaben.- 1.6 Bemerkungen und Literaturhinweise.- 2 Weitere Maschinenmodelle.- 2.1 Registermaschinen.- 2.1.1 Das RAM-Modell.- 2.1.2 Komplexitätsmaße für RAMs.- 2.1.3 Simulation von RAMs durch TM.- 2.1.4 Simulation von TM durch RAMs.- 2.2 Schaltkreis-Familien.- 2.2.1 Boolesche Funktionen und Schaltkreise.- 2.2.2 Schaltkreiskomplexität.- 2.2.3 Uniformität.- 2.2.4 Simulation von Schaltkreisfamilien durch TM.- 2.2.5 Simulation von TM durch Schaltkreisfamilien.- 2.2.6 Universelle Schaltkreise.- 2.3 Arithmetische Modelle, Entscheidungsgraphen.- 2.3.1 Arithmetische RAMs und Schaltkreise.- 2.3.2 Entscheidungsbaum-Modelle.- 2.4 Übungsaufgaben.- 2.5 Bemerkungen und Literaturhinweise.- 3 Hierarchie-Sätze.- 3.1 Untere Schranken und Komplexitätslücken.- 3.1.1 Logarithmische Platzschranke.- 3.1.2 Quadratische Zeitschranke für 1-Band Maschinen.- 3.1.3 Komplexitätslücke bei zeitbeschränkten 1-Band TM.- 3.1.4 Komplexitätslücke bei kleinen Platzschranken.- 3.2 Deterministische Hierarchien.- 3.2.1 Allgemeiner Hierarchiesatz.- 3.2.2 Zeithierarchien.- 3.2.3 Platzhierarchien.- 3.3 Translation.- 3.4 Nichtdeterministische Hierarchien.- 3.4.1 Komplementabschluß von nichtdeterministischem Platz.- 3.4.2 Nichtdeterministischer Platzhierarchiesatz.- 3.4.3 Nichtdeterministischer Zeithierarchiesatz.- 3.5 Das Komplexitätsmaß Reversal.- 3.5.1 Reversalbeschränkte TM.- 3.5.2 Vergleich von Time und Reversal.- 3.5.3 Vergleich von Space und Reversal.- 3.5.4 Bandreduktion und Reversal für NTM.- 3.6 Abstrakte Komplexitätstheorie.- 3.6.1 Allgemeines Gap-Theorem.- 3.6.2 Speedup-Theorem.- 3.6.3 Union-Theorem.- 3.6.4 Abstrakte Komplexitätsmaße.- 3.7 Übungsaufgaben.- 3.8 Bemerkungen und Literaturhinweise.- 4 Vergleich von Speicherstrukturen.- 4.1 Ein allgemeines Speichermodell.- 4.1.1 On-line versus off-line.- 4.1.2 Konstruierbare Speicher.- 4.1.3 Lineare Bandsimulation konstruierbarer Speicher.- 4.2 1-dimensionale Speicher.- 4.2.1 Bandreduktion für NTM.- 4.2.2 Simulation von Mehrkopf-Maschinen.- 4.2.3 TM mit separatem Einweg-Eingabeband.- 4.2.4 1 versus 2 Bänder bei Zweiweg-Eingabe.- 4.3 Untere Schranken für Speicherzugriffe.- 4.3.1 Kolmogorov-Komplexität von Strings.- 4.3.2 Der Einfluß des Radius.- 4.4 Obere Schranken für Speicherzugriffe.- 4.4.1 Einbettung von Graphen.- 4.4.2 Kompaktifizierung.- 4.4.3 Schnelle Simulationen.- 4.5 Übungsaufgaben.- 4.6 Bemerkungen und Literaturhinweise.- 5 Zeit- versus Platzkomplexität.- 5.1 Time-Space-Relationen für 1-Band TM.- 5.1.1 Simulation platzbeschränkter 1-Band DTM.- 5.1.2 Simulation platzbeschränkter 1-Band NTM.- 5.1.3 Mehrdimensionale 1-Band TM.- 5.2 Das Pebble-Game.- 5.2.1 Berechnungsgraphen.- 5.2.2 Superkonzentratoren.- 5.2.3 Schichtungen von Graphen.- 5.3 Platzeffiziente Simulation von TM und RAMs.- 5.3.1 Lineare Speicher.- 5.3.2 Nichtlineare Speicher.- 5.3.3 Auxiliary Pushdown TM.- 5.4 Simultane Ressource-Schranken.- 5.4.1 Schaltkreisweite.- 5.4.2 Vergleich der Ressourcen von TM und Schaltkreisen.- 5.5 Übungsaufgaben.- 5.6 Bemerkungen und Literaturhinweise.- 6 Sequentielle Komplexitätsklassen.- 6.1 Einführung.- 6.1.1 Notation.- 6.1.2 Zeit-Platz-Hierarchie.- 6.1.3 Reduzierbarkeit, Vollständigkeit.- 6.2 Die Klassen von L bis P.- 6.2.1 Labyrinth-Probleme zur Charakterisierung von L und NL.- 6.2.2 P -vollständige Probleme.- 6.3 NP-vollständige Probleme.- 6.3.1 Das Erfüllbarkeitsproblem.- 6.3.2 Selbstreduzierbarkeit.- 6.3.3 Erfüllbarkeit für 3-CNF.- 6.3.4 Graphenprobleme: Cliquen, Kreise und Überdeckungen.- 6.3.5 Das Färbungsproblem für Graphen.- 6.3.6 Diskrete Optimierung.- 6.3.7 NP -Vollständigkeit im strengen Sinne.- 6.3.8 Obere Schranken und Parameterkomplexität.- 6.4 Von NP bis PSP ACE.- 6.4.1 Die Struktur von NP.- 6.4.2 Die Relation zwischen NP und co-NP.- 6.4.3 UP, Einweg-Funktionen und Kryptologie.- 6.4.4 PSP ACE -Vollständigkeit.- 6.5 Linguistische Klassifikationen.- 6.5.1 Formale Grammatiken.- 6.5.2 Die Chomsky-Hierarchie.- 6.5.3 Kontextfreie Sprachen und Log CFL.- 6.5.4 Reguläre Ausdrücke.- 6.6 Übungsaufgaben.- 6.7 Bemerkungen und Literaturhinweise.- Stichwortverzeichnis.- Symbolverzeichnis.- Zeitschriftenverzeichnis.- Konferenzverzeichnis.- Verzeichnis von Fachorganisationen.

Read more less

Book SynopsisDieser Band behandelt numerische Algorithmen, die in der traditionellen Schulmathematik eine wichtige Rolle spielen. Ziel ist es dabei, nicht nur die einzelnen Algorithmen kennenzulernen, sondern zugleich auch die Methodik, die zur Elementarisierung mathematischer Probleme und zur Lösung in endlich vielen Schritten führt. Darüber hinaus werden nichtnumerische Such-, Sortier- und Simulationsalgorithmen dargestellt, die sich in der Schule in spielerischer und kreativer Weise behandeln lassen. Für die konkreten Lösungen einer mathematischen Aufgabe ist immer ein Algorithmus erforderlich. Vom Euklidischen Algorithmus zur Ermittlung des größten gemeinsamen Teilers zweier natürlicher Zahlen bis zur Lösung linearer Gleichungssysteme mit dem Gaußschen Algorithmus sind Algorithmen unverzichtbar. Die zweite, durchgesehene und erweiterte Auflage dieses Hochschullehrbuches enthält zusätzliche Beispiele, Lösungen und Aufgaben.Table of Contents1 Einführung.- 1.1 Was ist ein Algorithmus?.- 1.2 Zielsetzung.- 1.3 Beispiel 1 Potenzierung.- 1.4 Beispiel 2 Russisches Roulette.- 1.5 Folgerungen und Ausblick.- 2 Numerische Algorithmen.- 2.1 Teilbarkeitslehre in N.- 2.1.1 Teilbarkeit und Teilermengen.- 2.1.2 Größter gemeinsamer Teiler und kleinstes gemeinsames Vielfaches.- 2.1.3 Primzahleigenschaft.- 2.1.4 Primzahltabelle von 2 bis n.- 2.1.5 Zerlegung einer natürlichen Zahl in Primfaktoren.- 2.2 Stellenwertsysteme in Q.- 2.2.1 Darstellung natürlicher Zahlen in Stellenwertsystemen.- 2.2.2 Darstellung rationaler Zahlen in Stellenwertsystemen.- 2.2.3 Teilbarkeit und Teilbarkeitskriterien.- 2.3 Iterationen in Q.- 2.3.1 Quadratwurzeliteration (Halbierungsverfahren).- 2.3.2 Nullstellenbestimmung.- 2.3.3 Nullstelle einer kubischen Gleichung.- 2.3.4 Quadratwurzelnäherung nach Newton-Heron.- 3 Nichtnumerische Algorithmen.- 3.1 Suchvorgänge.- 3.1.1 Suchen eines Elementes in einer geordneten Liste.- 3.1.2 Einordnen eines Elementes in eine geordnete Liste.- 3.1.3 Zweidimensionales Suchen (Kobold).- 3.1.4 Damen-Problem.- 3.2 Sortiervorgänge.- 3.2.1 Minimales Element einer Liste.- 3.2.2 Sortieren einer Liste von n Wörtern mit der Austauschmethode.- 3.2.3 Sortieren einer Liste von n Wörtern mit der Sprudelmethode.- 3.2.4 Sortieren einer Liste von n Wörtern mit Quicksort.- 3.2.5 Sortieren durch Mischen.- 3.2.6 Türme von HANOI.- 4 Anhang: Arbeiten mit Visual-BASIC.- 4.1 EXCEL-Tabelle und Programm-Modul(e).- 4.2 EXCEL-Tabelle mit variabler Ein- und Ausgabe.- Literaturhinweise.- Stichwortverzeichnis.

Read more less

Book SynopsisNo pleasure lasts long unless there is variety in it. Publilius Syrus, Moral Sayings We've been very fortunate to receive fantastic feedback from our readers during the last four years, since the first edition of How to Solve It: Modern Heuristics was published in 1999. It's heartening to know that so many people appreciated the book and, even more importantly, were using the book to help them solve their problems. One professor, who published a review of the book, said that his students had given the best course reviews he'd seen in 15 years when using our text. There can be hardly any better praise, except to add that one of the book reviews published in a SIAM journal received the best review award as well. We greatly appreciate your kind words and personal comments that you sent, including the few cases where you found some typographical or other errors. Thank you all for this wonderful support.Table of ContentsI What Are the Ages of My Three Sons?.- 1 Why Are Some Problems Difficult to Solve?.- II How Important Is a Model?.- 2 Basic Concepts.- III What Are the Prices in 7–11?.- 3 Traditional Methods — Part 1.- IV What Are the Numbers?.- 4 Traditional Methods — Part 2.- V What’s the Color of the Bear?.- 5 Escaping Local Optima.- VI How Good Is Your Intuition?.- 6 An Evolutionary Approach.- VII One of These Things Is Not Like the Others.- 7 Designing Evolutionary Algorithms.- VIII What Is the Shortest Way?.- 8 The Traveling Salesman Problem.- IX Who Owns the Zebra?.- 9 Constraint-Handling Techniques.- X Can You Tune to the Problem?.- 10 Tuning the Algorithm to the Problem.- XI Can You Mate in Two Moves?.- 11 Time-Varying Environments and Noise.- XII Day of the Week of January 1st.- 12 Neural Networks.- XIII What Was the Length of the Rope?.- 13 Fuzzy Systems.- XIV Everything Depends on Something Else.- 14 Coevolutionary Systems.- XV Who’s Taller?.- 15 Multicriteria Decision-Making.- XVI Do You Like Simple Solutions?.- 16 Hybrid Systems.- 17 Summary.- Appendix A: Probability and Statistics.- A.1 Basic concepts of probability.- A.2 Random variables.- A.2.1 Discrete random variables.- A.2.2 Continuous random variables.- A.3 Descriptive statistics of random variables.- A.4 Limit theorems and inequalities.- A.5 Adding random variables.- A.6 Generating random numbers on a computer.- A.7 Estimation.- A.8 Statistical hypothesis testing.- A.9 Linear regression.- A.10 Summary.- Appendix B: Problems and Projects.- B.1 Trying some practical problems.- B.2 Reporting computational experiments with heuristic methods.- References.

Read more less

Book SynopsisThis book constitutes the refereed proceedings of the 7th International Symposium, Latin American Theoretical Informatics, LATIN 2006, held in March 2006. The 66 revised full papers presented together with seven invited papers were carefully reviewed and selected from 224 submissions. The papers presented are devoted to a broad range of topics in theoretical computer science with a focus on algorithmics and computations related to discrete mathematics as well as on cryptography, data compression and Web applications.Table of ContentsKeynotes.- Algorithmic Challenges in Web Search Engines.- RNA Molecules: Glimpses Through an Algorithmic Lens.- Squares.- Matching Based Augmentations for Approximating Connectivity Problems.- Modelling Errors and Recovery for Communication.- Lossless Data Compression Via Error Correction.- The Power and Weakness of Randomness in Computation.- Regular Contributions.- A New GCD Algorithm for Quadratic Number Rings with Unique Factorization.- On Clusters in Markov Chains.- An Architecture for Provably Secure Computation.- Scoring Matrices That Induce Metrics on Sequences.- Data Structures for Halfplane Proximity Queries and Incremental Voronoi Diagrams.- The Complexity of Diffuse Reflections in a Simple Polygon.- Counting Proportions of Sets: Expressive Power with Almost Order.- Efficient Approximate Dictionary Look-Up for Long Words over Small Alphabets.- Relations Among Notions of Security for Identity Based Encryption Schemes.- Optimally Adaptive Integration of Univariate Lipschitz Functions.- Classical Computability and Fuzzy Turing Machines.- An Optimal Algorithm for the Continuous/Discrete Weighted 2-Center Problem in Trees.- An Algorithm for a Generalized Maximum Subsequence Problem.- Random Bichromatic Matchings.- Eliminating Cycles in the Discrete Torus.- On Behalf of the Seller and Society: Bicriteria Mechanisms for Unit-Demand Auctions.- Pattern Matching Statistics on Correlated Sources.- Robust Model-Checking of Linear-Time Properties in Timed Automata.- The Computational Complexity of the Parallel Knock-Out Problem.- Reconfigurations in Graphs and Grids.- -Varieties, Actions and Wreath Product.- Local Construction of Planar Spanners in Unit Disk Graphs with Irregular Transmission Ranges.- An Efficient Approximation Algorithm for Point Pattern Matching Under Noise.- Oblivious Medians Via Online Bidding.- Efficient Computation of the Relative Entropy of Probabilistic Automata.- A Parallel Algorithm for Finding All Successive Minimal Maximum Subsequences.- De Dictionariis Dynamicis Pauco Spatio Utentibus.- Customized Newspaper Broadcast: Data Broadcast with Dependencies.- On Minimum k-Modal Partitions of Permutations.- Two Birds with One Stone: The Best of Branchwidth and Treewidth with One Algorithm.- Maximizing Throughput in Queueing Networks with Limited Flexibility.- Network Flow Spanners.- Finding All Minimal Infrequent Multi-dimensional Intervals.- Cut Problems in Graphs with a Budget Constraint.- Lower Bounds for Clear Transmissions in Radio Networks.- Asynchronous Behavior of Double-Quiescent Elementary Cellular Automata.- Lower Bounds for Geometric Diameter Problems.- Connected Treewidth and Connected Graph Searching.- A Faster Algorithm for Finding Maximum Independent Sets in Sparse Graphs.- The Committee Decision Problem.- Common Deadline Lazy Bureaucrat Scheduling Revisited.- Approximate Sorting.- Stochastic Covering and Adaptivity.- Algorithms for Modular Counting of Roots of Multivariate Polynomials.- Hardness Amplification Via Space-Efficient Direct Products.- The Online Freeze-Tag Problem.- I/O-Efficient Algorithms on Near-Planar Graphs.- Minimal Split Completions of Graphs.- Design and Analysis of Online Batching Systems.- Competitive Analysis of Scheduling Algorithms for Aggregated Links.- A 4-Approximation Algorithm for Guarding 1.5-Dimensional Terrains.- On Sampling in Higher-Dimensional Peer-to-Peer Systems.- Mobile Agent Rendezvous in a Synchronous Torus.- Randomly Colouring Graphs with Girth Five and Large Maximum Degree.- Packing Dicycle Covers in Planar Graphs with No K 5–e Minor.- Sharp Estimates for the Main Parameters of the Euclid Algorithm.- Position-Restricted Substring Searching.- Rectilinear Approximation of a Set of Points in the Plane.- The Branch-Width of Circular-Arc Graphs.- Minimal Eulerian Circuit in a Labeled Digraph.- Speeding up Approximation Algorithms for NP-Hard Spanning Forest Problems by Multi-objective Optimization.- RISOTTO: Fast Extraction of Motifs with Mismatches.- Minimum Cost Source Location Problems with Flow Requirements.- Exponential Lower Bounds on the Space Complexity of OBDD-Based Graph Algorithms.- Constructions of Approximately Mutually Unbiased Bases.- Improved Exponential-Time Algorithms for Treewidth and Minimum Fill-In.

Read more less

Book SynopsisData Science and Classification provides new methodological developments in data analysis and classification. The broad and comprehensive coverage includes the measurement of similarity and dissimilarity, methods for classification and clustering, network and graph analyses, analysis of symbolic data, and web mining. Beyond structural and theoretical results, the book offers application advice for a variety of problems, in medicine, microarray analysis, social network structures, and music.Trade ReviewFrom the reviews: "This book is a collection of papers presented at the Tenth Conference of the International Federation of Classification Societies. The contributors are primarily statisticians and computer scientists … . The typesetting and page layout are well done, and the graphics are very clear. … The main market for this book would be libraries, and researchers wanting a record of recent advances in statistical learning." (Jeffrey D. Picka, Technometrics, Vol. 49 (3), August, 2007)Table of ContentsSimilarity and Dissimilarity.- A Tree-Based Similarity for Evaluating Concept Proximities in an Ontology.- Improved Fréchet Distance for Time Series.- Comparison of Distance Indices Between Partitions.- Design of Dissimilarity Measures: A New Dissimilarity Between Species Distribution Areas.- Dissimilarities for Web Usage Mining.- Properties and Performance of Shape Similarity Measures.- Classification and Clustering.- Hierarchical Clustering for Boxplot Variables.- Evaluation of Allocation Rules Under Some Cost Constraints.- Crisp Partitions Induced by a Fuzzy Set.- Empirical Comparison of a Monothetic Divisive Clustering Method with the Ward and the k-means Clustering Methods.- Model Selection for the Binary Latent Class Model: A Monte Carlo Simulation.- Finding Meaningful and Stable Clusters Using Local Cluster Analysis.- Comparing Optimal Individual and Collective Assessment Procedures.- Network and Graph Analysis.- Some Open Problem Sets for Generalized Blockmodeling.- Spectral Clustering and Multidimensional Scaling: A Unified View.- Analyzing the Structure of U.S. Patents Network.- Identifying and Classifying Social Groups: A Machine Learning Approach.- Analysis of Symbolic Data.- Multidimensional Scaling of Histogram Dissimilarities.- Dependence and Interdependence Analysis for Interval-Valued Variables.- A New Wasserstein Based Distance for the Hierarchical Clustering of Histogram Symbolic Data.- Symbolic Clustering of Large Datasets.- A Dynamic Clustering Method for Mixed Feature-Type Symbolic Data.- General Data Analysis Methods.- Iterated Boosting for Outlier Detection.- Sub-species of Homopus Areolatus? Biplots and Small Class Inference with Analysis of Distance.- Revised Boxplot Based Discretization as the Kernel of Automatic Interpretation of Classes Using Numerical Variables.- Data and Web Mining.- Comparison of Two Methods for Detecting and Correcting Systematic Error in High-throughput Screening Data.- kNN Versus SVM in the Collaborative Filtering Framework.- Mining Association Rules in Folksonomies.- Empirical Analysis of Attribute-Aware Recommendation Algorithms with Variable Synthetic Data.- Patterns of Associations in Finite Sets of Items.- Analysis of Music Data.- Generalized N-gram Measures for Melodic Similarity.- Evaluating Different Approaches to Measuring the Similarity of Melodies.- Using MCMC as a Stochastic Optimization Procedure for Musical Time Series.- Local Models in Register Classification by Timbre.- Gene and Microarray Analysis.- Improving the Performance of Principal Components for Classification of Gene Expression Data Through Feature Selection.- A New Efficient Method for Assessing Missing Nucleotides in DNA Sequences in the Framework of a Generic Evolutionary Model.- New Efficient Algorithm for Modeling Partial and Complete Gene Transfer Scenarios.

Read more less

Book SynopsisAlgorithms provide the basic foundation for all computational processes. This volume presents algorithms at the foundational level and also at the various levels between this level and the user application. Some of these algorithms are classical and have become well established in the field. This material is therefore a rich source of information and is still relevant and up to date. The basic primitives of computer graphics have remained unchanged: lines, circles, conics, curves and characters. This volume contains reference material in all these areas. The higher levelsof contouring and surface drawing are also well covered. Developments in hardware architectures have continued since the first printing, but the basic principles of hardware/software trade-offs remain valid. This reprint is being published as a Study Edition to make the material more accessible to students and researchers in the field of computer graphics andits applications. The continuing popularity of the original book demonstrates the value and timeliness of its contents.Table of ContentsSection 1. Line and Area Algorithms.- Invited Papers.- “Theoretical and Linguistic Methods for Describing Straight Lines”.- “Run Length Slice Algorithm for Incremental Lines”.- “The Relationship between Euclid’s Algorithm and Run-Length Encoding”.- “Antialiasing in Practice”.- Submitted Papers.- “An Application of Euclid’s Algorithm to Drawing Straight Lines”.- “The Accuracy of the Digital Representation of a Straight Line”.- “Experience in Practical Implementation of Boundary-Defined Area Fill”.- “The Implementation of Fill Area for GKS”.- “A Simple Algorithm for Determining whether a Point Resides within an Arbitrarily Shaped Polygon”.- Section 2. Arcs, Circles and Conics.- Invited Papers.- “Algorithms for Circular Arc Generation”.- “Algorithms of Conic Generation”.- Submitted Papers.- “A High-Precision Digital Differential Analyzer for Circle Generation”.- “An Ellipse-Drawing Algorithm for Raster Displays”.- “An Algorithm for Determining the Draw Start Point of a Hyperbola given the System Direction of Draw and the Coordinates of the Video Window”.- Section 3. Curves and Curve Drawing.- Invited Papers.- “A Review of Curve Drawing Algorithms”.- “Methods for Drawing Curves”.- Submitted Paper.- “Generation of ?-Spline Curves using a Recurrence Relation”.- Section 4. Character Generation and Display.- Invited Papers.- “Character Generation and Display”.- “Font Information and Device-Independent Output”.- Section 5. Contouring and Surface Drawing.- Invited Papers.- “Contouring — the State of the Art”.- “A Review of Geostatistical Techniques for Contouring”.- “Algorithms for Three-Dimensional Interpolation between Planar Slices”.- Submitted Papers.- “GENSURF: A System for General Surface Definition and Manipulation”.- “An Interesting Modification to the Bresenham Algorithm for Hidden-Line Solution”.- “Efficient Hidden Line Removal for Surface Plots Utilising Raster Graphics”.- Section 6. Hardware Architectures and Algorithms.- Invited papers.- “Graphics Software Standards and their Evolution with Hardware Algorithms”.- “Hardware Enhancements for Raster Graphics”.- “Systolic Array Architectures for High Performance CAD/CAM Workstations”.- “Parallel Architectures for High Performance Graphics Systems”.- Section 7. Computational Geometry and CAD.- Invited Paper.- “Computational Geometry in Practice”.- Submitted Papers.- “An Algorithm for Direct Display of CSG Objects by Spatial Subdivision”.- “Computational Geometry and Prolog”.- “Subdivision Techniques for Processing Geometric Objects”.- Section 8. Theoretical Aspects and Models.- Invited Papers.- “Random Fractal Forgeries”.- “The Algebra of Algorithms”.- “Theoretical Considerations in Algorithm Design”.- “Technology for the Protection of Graphics Algorithms”.- “Spatial Concepts in 3D”.- Submitted Papers.- “Shortest Paths in 3-Space, Voronoi Diagrams with Barriers, and Related Complexity and Algebraic Issues”.- “Geometric Data Structures for Computer Graphics”.- “A Model for Raster Graphics Language Primitives”.- “Theoretical Framework for Shape Representation and Analysis”.- Section 9. Human-Computer Interface Issues.- Invited Papers.- “Aspects of Human Machine Interface”.- “Visual Perception and Computer Graphics”.- Section 10. Computer Animation.- Invited Paper.- “Object and Movement Description Techniques for Animation — An Informal Review”.- Scientific Organising Committee.- Lecturers.- Participants.

Read more less

Book SynopsisAlgorithms are at the heart of every nontrivial computer application, and algorithmics is a modern and active area of computer science. Every computer scientist and every professional programmer should know about the basic algorithmic toolbox: structures that allow efficient organization and retrieval of data, frequently used algorithms, and basic techniques for modeling, understanding and solving algorithmic problems. This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, priority queues, sorted sequences, graph representation, graph traversal, shortest paths, minimum spanning trees, and optimization. The algorithms are presented in a modern way, with explicitly formulated invariants, and comment on recent trends such as algorithm engineering, memory hierarchies, algorithm libraries and certifying algorithms. The authors use pictures, words and high-level pseudocode to explain the algorithms, and then they present more detail on efficient implementations using real programming languages like C++ and Java. The authors have extensive experience teaching these subjects to undergraduates and graduates, and they offer a clear presentation, with examples, pictures, informal explanations, exercises, and some linkage to the real world. Most chapters have the same basic structure: a motivation for the problem, comments on the most important applications, and then simple solutions presented as informally as possible and as formally as necessary. For the more advanced issues, this approach leads to a more mathematical treatment, including some theorems and proofs. Finally, each chapter concludes with a section on further findings, providing views on the state of research, generalizations and advanced solutions.Trade Review"This is another mainstream textbook on algorithms and data structures, mainly intended for undergraduate students and professionals … . The two-layer index table is also detailed and helpful. I do enjoy reading the informative sections of historical notes and further findings at the end of each chapter. … This book is very well written, with the help of … clear figures and tables, as well as many interesting and inspiring examples." Zhizhang Shen, Zentralblatt MATH, Vol. 1146, 2008"... the book develops the basic fundamental principles underlying their design and analysis without sacrificing depth or rigor. The authors' insight, knowledge and active research on algorithms and data structures provide a very solid approach to the book. I particularly liked their "as informally as possible and as formally as necessary" writing style, and I enjoyed a lot their decision to not only discuss classical results, but to broaden the view to alternative implementations, memory hierarchies and libraries, which transmits novelty and increases interest...I think that this book will be a superb addition particularly useful for teachers of undergraduate courses, to graduate students in Computer Science, and to researchers that work, or intend to work, with algorithms." Jordi Petit, Computer Science Review 3, 2009 "Mehlhorn and Sanders write well, and the well-organized presentation reflects their experience and interest in the various topics... it is an excellent reference, and could possibly be used in a transition course, serving students coming to graduate CS courses from other technical fields. [...]This text is intended for undergraduate computer science (CS) majors, and focuses on algorithm analysis. … it is an excellent reference, and could possibly be used in a transition course, serving students coming to graduate CS courses from other technical fields. Finally, the book contains interesting tidbits that are not readily available elsewhere." M. G. Murphy, ACM Computing Reviews, October 2008"A 'Toolbox' should be portable, practical, and useful. This book is all these, covering a nice swath of the classic CS algorithms but addressing them in a way that is accessible to the student and practitioner. Furthermore, it manages to incorporate interesting examples as well as subtle examples of wit compressed into its 300 pages. Although it is not tied to any one language or library, it provides practical references to efficient open-source implementations of many of the algorithms and data structures; these should be the first refuge of the commercial developer. I can easily recommend this book as an intermediate undergraduate text, a refresher for those of us who only dimly remember our intermediate undergraduate courses, and as a reference for the professional development craftsman." Hal C. Elrod, SIGACT News Book Review Column 42(4) 2011Table of ContentsAppetizer: Integer Arithmetics.- Representing Sequences by Arrays and Linked Lists.- Hash Tables and Associative Arrays.- Sorting and Selection.- Priority Queues.- Sorted Sequences.- Graph Representation.- Graph Traversal.- Shortest Paths.- Minimum Spanning Trees.- Generic Approaches to Optimization.

Read more less

Book SynopsisThe ?rst and foremost goal of this lecture series was to show the beauty, depth and usefulness of the key ideas in computer science. While working on the lecture notes, we came to understand that one can recognize the true spirit of a scienti?c discipline only by viewing its contributions in the framework of science as a whole. We present computer science here as a fundamental science that, interacting with other scienti?c disciplines, changed and changes our view on the world, that contributes to our understanding of the fundamental concepts of science and that sheds new light on and brings new meaning to several of these concepts. We show that computer science is a discipline that discovers spectacular, unexpected facts, that ?nds ways out in seemingly unsolvable s- uations, and that can do true wonders. The message of this book is that computer science is a fascinating research area with a big impact on the real world, full of spectacular ideas and great ch- lenges. It is an integral part of science and engineering with an above-average dynamic over the last 30 years and a high degree of interdisciplinarity. The goal of this book is not typical for popular science writing, whichoftenrestrictsitselftooutliningtheimportanceofaresearch area. Whenever possible we strive to bring full understanding of the concepts and results presented.Trade ReviewFrom the reviews: "A lucid exposition of fundamental ideas, concepts and methods of computer science, their essence and their limits, delightfully represented, and easily understandable for a broad readership. Scientific writing at its best." (Peter Widmayer, ETH Zürich)“This book originated from a series of lectures given by the author to describe what computer science is and what its principle Ideas are. Algorithms are the key concept of this book. … The inclusion of problems makes the book more than a personal reflection. The style is lively and avoids unnecessary jargon. With a good teacher, it could be suitable as a textbook on the foundations of computer science in an undergraduate classroom.” (Anthony J. Duben, ACM Computing Reviews, February, 2010)“This is a very readable book on theoretical computer science, written for nonspecialists. … Practical applications are illustrated by examples from DNA computing and quantum mechanics. … Summing Up: Recommended. Lower- and upper-division undergraduates and general readers.” (M. Bona, Choice, Vol. 47 (5), January, 2010)“The author is an acclaimed computer scientist and he proves why: apart from being an aggressive researcher, he is also an excellent teacher. Using his ability to teach complex computing topics in an interesting way, he introduces to the reader the ‘power and the magic’ of the underlying principles. … It will certainly draw interest from both undergraduate and post-graduate students of computing and allied fields. … I do recommend this beautiful book for a scientific library … .” (Soubhik Chakraborty, ACM Computing Reviews, August, 2010)Table of ContentsThe Development of Computer Science: Not Just a Driving Licence.- Algorithmics: What Programming and Baking Have in Common.- Infinity Is Not Infinity: Why Infinity Is Infinitely Important in Computer Science.- The Limits of Computability: Why There Exist Tasks That Cannot Be Automatically Solved Using Computers.- Complexity Theory: What to Do When the Energy of the Universe Isn't Enough to Perform a Computation.- Randomness in Nature: A Source of Efficiency in Algorithmics.- Cryptography: How to Transform Drawbacks into Advantages.- Computing Using DNA Molecules: A Biological Computer on the Horizon.- Quantum Computers: Computing in the Wonderland of Particles.- How to Make a Good Decision for an Unknown Future: How to Foil an Adversary

Read more less

Book SynopsisAt its core, information security deals with the secure and accurate transfer of information. While information security has long been important, it was, perhaps, brought more clearly into mainstream focus with the so-called “Y2K” issue. Te Y2K scare was the fear that c- puter networks and the systems that are controlled or operated by sofware would fail with the turn of the millennium, since their clocks could lose synchronization by not recognizing a number (instruction) with three zeros. A positive outcome of this scare was the creation of several Computer Emergency Response Teams (CERTs) around the world that now work - operatively to exchange expertise and information, and to coordinate in case major problems should arise in the modern IT environment. Te terrorist attacks of 11 September 2001 raised security concerns to a new level. Te - ternational community responded on at least two fronts; one front being the transfer of reliable information via secure networks and the other being the collection of information about - tential terrorists. As a sign of this new emphasis on security, since 2001, all major academic publishers have started technical journals focused on security, and every major communi- tions conference (for example, Globecom and ICC) has organized workshops and sessions on security issues. In addition, the IEEE has created a technical committee on Communication and Information Security. Te ?rst editor was intimately involved with security for the Athens Olympic Games of 2004.Trade ReviewAus den Rezensionen: “... Besonderes Augenmerk gilt dabei dem Wechselspiel zwischen Kommunikation und dem Bereich der Informationssicherheit. ... herausgegriffene Themen illustrieren die Relevanz des Buchs. … Verschiedene HIPs werden vorgestellt und verglichen Weitere Beitrage befassen sich mit Phishing Attacken bzw mit Authentifikationen mittels biometrischer Methoden. ... Die Beitrage sind theoretisch fundiert und oft praxisbezogen. … Das Buch eignet sich deshalb gut als Einstiegslektüre für Studierende oder für Informatiker, die sich nur am Rande für die Sicherheitsthematik interessieren. Für Experten ist das Buch eine wertvolle, vielseitige Inspirationsquelle.“ (in: Bulletin electrosuisse, 2/July/2010, Issue 7, S. 121)Table of ContentsPart A Fundamentals and Cryptography A Framework for System Security .- Public-Key Cryptography.- Elliptic Curve Cryptography.- Cryptographic Hash Functions.- Block Cipher Cryptanalysis.- Chaos-Based Information Security.- Bio-Cryptography.- Quantum Cryptography.- Part B Intrusion Detection and Access Control Intrusion Detection and Prevention Systems.- Intrusion Detection Systems.- Intranet Security via Firewalls.- Distributed Port Scan Detection.- Host-Based Anomaly Intrusion Detection.- Security in Relational Databases.- Anti-Bot Strategies Based on Human Interactive Proofs.- Access and Usage Control in GRID Systems.- Secure Human Identification.- Part C Networking Peer-to-Peer Botnets.- Security of Service Networks.- SCADA Security.- Mobile Ad-Hoc Network Routing.- Security Approach for Ad–Hoc Networks.- Phishing: Attacks and Countermeasures´.- Part D Optical Networking Chaos-Based Secure Optical Communications.- Chaos Applications in Optical Communications.- Part E Wireless Networking Security in Wireless Sensor Networks.- Secure routing in Wireless Sensor Networks.- Security Via Surveillance and Monitoring.- Security and QoS in Wireless Networks.- Part F Software Low-Level Software Security by Example.- Software Reverse Engineering.- Trusted Computing.- Security via Trusted Communications.- Viruses and Malware.- Designing a Secure Programming Language.- Part G Forensics and Legal Issues Fundamentals of Digital Forensic Evidence.- Multimedia Forensics for Detecting Forgeries.- Technological and Legal Aspects of CIS Subject Index

Read more less

Book SynopsisNo pleasure lasts long unless there is variety in it. Publilius Syrus, Moral Sayings We've been very fortunate to receive fantastic feedback from our readers during the last four years, since the first edition of How to Solve It: Modern Heuristics was published in 1999. It's heartening to know that so many people appreciated the book and, even more importantly, were using the book to help them solve their problems. One professor, who published a review of the book, said that his students had given the best course reviews he'd seen in 15 years when using our text. There can be hardly any better praise, except to add that one of the book reviews published in a SIAM journal received the best review award as well. We greatly appreciate your kind words and personal comments that you sent, including the few cases where you found some typographical or other errors. Thank you all for this wonderful support.Table of ContentsI What Are the Ages of My Three Sons?.- 1 Why Are Some Problems Difficult to Solve?.- II How Important Is a Model?.- 2 Basic Concepts.- III What Are the Prices in 7–11?.- 3 Traditional Methods — Part 1.- IV What Are the Numbers?.- 4 Traditional Methods — Part 2.- V What’s the Color of the Bear?.- 5 Escaping Local Optima.- VI How Good Is Your Intuition?.- 6 An Evolutionary Approach.- VII One of These Things Is Not Like the Others.- 7 Designing Evolutionary Algorithms.- VIII What Is the Shortest Way?.- 8 The Traveling Salesman Problem.- IX Who Owns the Zebra?.- 9 Constraint-Handling Techniques.- X Can You Tune to the Problem?.- 10 Tuning the Algorithm to the Problem.- XI Can You Mate in Two Moves?.- 11 Time-Varying Environments and Noise.- XII Day of the Week of January 1st.- 12 Neural Networks.- XIII What Was the Length of the Rope?.- 13 Fuzzy Systems.- XIV Everything Depends on Something Else.- 14 Coevolutionary Systems.- XV Who’s Taller?.- 15 Multicriteria Decision-Making.- XVI Do You Like Simple Solutions?.- 16 Hybrid Systems.- 17 Summary.- Appendix A: Probability and Statistics.- A.1 Basic concepts of probability.- A.2 Random variables.- A.2.1 Discrete random variables.- A.2.2 Continuous random variables.- A.3 Descriptive statistics of random variables.- A.4 Limit theorems and inequalities.- A.5 Adding random variables.- A.6 Generating random numbers on a computer.- A.7 Estimation.- A.8 Statistical hypothesis testing.- A.9 Linear regression.- A.10 Summary.- Appendix B: Problems and Projects.- B.1 Trying some practical problems.- B.2 Reporting computational experiments with heuristic methods.- References.

Read more less

Book SynopsisIn modern computing a program is usually distributed among several processes. The fundamental challenge when developing reliable and secure distributed programs is to support the cooperation of processes required to execute a common task, even when some of these processes fail. Failures may range from crashes to adversarial attacks by malicious processes.Cachin, Guerraoui, and Rodrigues present an introductory description of fundamental distributed programming abstractions together with algorithms to implement them in distributed systems, where processes are subject to crashes and malicious attacks. The authors follow an incremental approach by first introducing basic abstractions in simple distributed environments, before moving to more sophisticated abstractions and more challenging environments. Each core chapter is devoted to one topic, covering reliable broadcast, shared memory, consensus, and extensions of consensus. For every topic, many exercises and their solutions enhance the understanding This book represents the second edition of "Introduction to Reliable Distributed Programming". Its scope has been extended to include security against malicious actions by non-cooperating processes. This important domain has become widely known under the name "Byzantine fault-tolerance". Table of Contents1. Introduction. - 1.1 Motivation. -1.2 Distributed Programming Abstractions. 1.3 The End-to-End Argument. 1.4 Software Components. - 1.5 Classes of Algorithms. -1.6 Chapter Notes. 2. Basic Abstractions. - 2.1 Distributed Computation. - 2.2 Abstracting Processes. - 2.3 Cryptographic Abstractions. - 2.4 Abstracting Communication. - 2.5 Timing Assumptions. - 2.6 Abstracting Time. - 2.7 Distributed-System Models. - 2.8 Exercises. - 2.9 Solutions. - 2.10 Chapter Notes . - . - 3. Reliable Broadcast. - 3.1 Motivation. - 3.2 Best-Effort Broadcast. - 3.3 Regular Reliable Broadcast. - 3.4 Uniform Reliable Broadcast. - 3.5 Stubborn Broadcast. - 3.6 Logged Best-Effort Broadcast. - 3.7 Logged Uniform Reliable Broadcast. - 3.8 Probabilistic Broadcast. - 3.9 FIFO and Causal Broadcast. - 3.10 Byzantine Consistent Broadcast. - 3.11 Byzantine Reliable Broadcast. - 3.12 Byzantine Broadcast Channels. - 3.13 Exercises. - 3.14 Solutions. - 3.15 Chapter Notes . - . - 4. Shared Memory. - 4.1 Introduction. - 4.2 (1, N) Regular Register. - 4.3 (1, N) Atomic Register. - 4.4 (N, N) Atomic Register. - 4.5 (1, N) Logged Regular Register. - 4.6 (1,N) Byzantine Safe Register. - 4.7 (1, N) Byzantine Regular Register. - 4.8 (1,N) Byzantine Atomic Register. - 4.9 Exercises. - 4.10 Solutions. - 4.11 Chapter Notes . - . - 5. Consensus. - 5.1 Regular Consensus. - 5.2 Uniform Consensus. - 5.3 Uniform Consensus in the Fail-Noisy Model. - 5.4 Logged Consensus. - 5.5 Randomized Consensus. - 5.6 Byzantine Consensus. - 5.7 Byzantine Randomized Consensus. - 5.8 Exercises. - 5.9 Solutions. - 5.10 Chapter Notes . - . - 6. Consensus Variants. - 6.1 Total-Order Broadcast. - 6.2 Byzantine Total-Order Broadcast. - 6.3 Terminating Reliable Broadcast. - 6.4 Fast Consensus. - 6.5 Fast Byzantine Consensus. - 6.6 Non-blocking Atomic Commit. - 6.7 Group Membership. - 6.8 View-Synchronous Communication. - 6.9 Exercises. - 6.10 Solutions. - 6.11 Chapter Notes . - . - 7. Concluding Remarks. - 7.1 Implementation in Appia. - 7.2 Further Implementations. - 7.3 Further Reading

Read more less

Book SynopsisThis book constitutes the proceedings of the International Conference on Information Security and Assurance, held in Brno, Czech Republic in August 2011.

Read more less

Book SynopsisComputer science is the science of the future, and already underlies every facet of business and technology, and much of our everyday lives. In addition, it will play a crucial role in the science the 21st century, which will be dominated by biology and biochemistry, similar to the role of mathematics in the physical sciences of the 20th century. In this award-winning best-seller, the author and his co-author focus on the fundamentals of computer science, which revolve around the notion of the algorithm. They discuss the design of algorithms, and their efficiency and correctness, the inherent limitations of algorithms and computation, quantum algorithms, concurrency, large systems and artificial intelligence. Throughout, the authors, in their own words, stress the ‘fundamental and robust nature of the science in a form that is virtually independent of the details of specific computers, languages and formalisms'. This version of the book is published to celebrate 25 years since its first edition, and in honor of the Alan M. Turing Centennial year. Turing was a true pioneer of computer science, whose work forms the underlying basis of much of this book. Trade ReviewFrom the reviews of the third edition:“This book should be on any short list for a central course in computer science. It is designed to provide a uniform background on which all students might draw. It has a good-humored, easy style, which would make any reader unwilling to close the book after opening it anywhere. All computer scientists should have this book. … the bibliography is organized in a convenient chapter-by-chapter form, which makes the book useful for advanced work, and the exercises will help instructors identify capable students.” (Harvey Cohn, ACM Computing Reviews, August, 2012)“This is a reprint of the 3rd edition on the occasion of the 25th year of the existence of the book; it is also intended to honor Alan Turing’s 100th birthday. … it is highly readable, even if one is largely acquainted with the field. It is very well written, containing many illustrative examples, suited also for the non-specialist.” (Gunther Schmidt, Zentralblatt MATH, Vol. 1243, 2012)Table of ContentsPreliminaries.- and Historical Review.- Algorithms and Data.- Programming Languages and Paradigms.- Methods and Analysis.- Algorithmic Methods.- The Correctness of Algorithms.- The Efficiency of Algorithms.- Limitations and Robustness.- Inefficiency and Intractability.- Noncomputability and Undecidability.- Algorithmic Universality and Its Robustness.- Relaxing the Rules.- Parallelism, Concurrency, and Alternative Models.- Probabilistic Algorithms.- Cryptography and Reliable Interaction.- The Bigger Picture.- Software Engineering.- Reactive Systems.- Algorithmics and Intelligence.

Read more less

Book SynopsisThis book constitutes the refereed proceedings of the 13th Algorithms and Data Structures Symposium, WADS 2013, held in London, ON, Canada, August 2013. The Algorithms and Data Structures Symposium - WADS (formerly "Workshop on Algorithms and Data Structures") is intended as a forum for researchers in the area of design and analysis of algorithms and data structures. The 44 revised full papers presented in this volume were carefully reviewed and selected from 139 submissions. The papers present original research on algorithms and data structures in all areas, including bioinformatics, combinatorics, computational geometry, databases, graphics, and parallel and distributed computing.Table of ContentsAlgorithms and data structures in bioinformatics.- Algorithms and data structures in combinatorics.- Algorithms and data structures in computational geometry.- Algorithms and data structures in databases.- Algorithms and data structures in graphics.- Parallel and distributed computing.

Read more less

Book SynopsisTo learn to program is to be initiated into an entirely new way of thinking about engineering, mathematics, and the world in general. Computation is integral to all modern engineering disciplines, so the better you are at programming, the better you will be in your chosen field.The author departs radically from the typical presentation by teaching concepts and techniques in a rigorous manner rather than listing how to use libraries and functions. He presents pointers in the very first chapter as part of the development of a computational model that facilitates an ab initio presentation of subjects such as function calls, call-by-reference, arrays, the stack, and the heap. The model also allows students to practice the essential skill of memory manipulation throughout the entire course rather than just at the end. As a result, this textbook goes further than is typical for a one-semester course -- abstract data types and linked lists, for example, are covered in depth. The computational model will also serve students in their adventures with programming beyond the course: instead of falling back on rules, they can think through the model to decide how a new programming concept fits with what they already know.The book is appropriate for undergraduate students of engineering and computer science, and graduate students of other disciplines. It contains many exercises integrated into the main text, and the author has made the source code available online.Trade Review"This book builds a well-defined computation model that allows concepts that are important in technical and scientific applications -- like pointers, arrays and recursion -- to be gradually and rigorously introduced. The languages covered by the book, C and MATLAB, are highly relevant to engineering applications.Clarity of exposition, numerous well-chosen examples, pedagogical savvy, and logical sequencing of the topics all help the reader's progress through the chapters and make for an enjoyable learning experience. This book prepares one well to deal with advanced programming language constructs and the design of large, complex applications by promoting mastery of the fundamentals, by covering important practical aspects of a programmer's activity, and by instilling good design and implementation habits. It is therefore ideally suited for self-study or as a textbook in an introductory college-level programming course for engineers and similarly technically-minded students."Fabio Somenzi (University of Colorado at Boulder)Table of ContentsChap. 1, Memory: The Stack.- Chap. 2, Control.- Chap. 3, Arrays and Strings.- Chap. 4, Debugging.- Chap. 5, I/O.- Chap. 6, Memory: The Heap.- Chap. 7, Abstract Data Types.- Chap. 8, Linked Lists.- Chap. 9, Introduction to Matlab.- Chap. 10, Exploring ODEs with Matlab.- Chap. 11, Exploring Time and Frequency Domains with Matlab.- Chap. 12, Index.

Read more less

Book SynopsisComputer science is the science of the future, and already underlies every facet of business and technology, and much of our everyday lives. In addition, it will play a crucial role in the science the 21st century, which will be dominated by biology and biochemistry, similar to the role of mathematics in the physical sciences of the 20th century. In this award-winning best-seller, the author and his co-author focus on the fundamentals of computer science, which revolve around the notion of the algorithm. They discuss the design of algorithms, and their efficiency and correctness, the inherent limitations of algorithms and computation, quantum algorithms, concurrency, large systems and artificial intelligence. Throughout, the authors, in their own words, stress the ‘fundamental and robust nature of the science in a form that is virtually independent of the details of specific computers, languages and formalisms'. This version of the book is published to celebrate 25 years since its first edition, and in honor of the Alan M. Turing Centennial year. Turing was a true pioneer of computer science, whose work forms the underlying basis of much of this book. Trade ReviewFrom the reviews of the third edition:“This book should be on any short list for a central course in computer science. It is designed to provide a uniform background on which all students might draw. It has a good-humored, easy style, which would make any reader unwilling to close the book after opening it anywhere. All computer scientists should have this book. … the bibliography is organized in a convenient chapter-by-chapter form, which makes the book useful for advanced work, and the exercises will help instructors identify capable students.” (Harvey Cohn, ACM Computing Reviews, August, 2012)“This is a reprint of the 3rd edition on the occasion of the 25th year of the existence of the book; it is also intended to honor Alan Turing’s 100th birthday. … it is highly readable, even if one is largely acquainted with the field. It is very well written, containing many illustrative examples, suited also for the non-specialist.” (Gunther Schmidt, Zentralblatt MATH, Vol. 1243, 2012)Table of ContentsPreliminaries.- and Historical Review.- Algorithms and Data.- Programming Languages and Paradigms.- Methods and Analysis.- Algorithmic Methods.- The Correctness of Algorithms.- The Efficiency of Algorithms.- Limitations and Robustness.- Inefficiency and Intractability.- Noncomputability and Undecidability.- Algorithmic Universality and Its Robustness.- Relaxing the Rules.- Parallelism, Concurrency, and Alternative Models.- Probabilistic Algorithms.- Cryptography and Reliable Interaction.- The Bigger Picture.- Software Engineering.- Reactive Systems.- Algorithmics and Intelligence.

Read more less

Book SynopsisDas Buch Arithmetik ist eine Übersetzung des vierten Kapitels der legendären Werkreihe "The Art of Computer Programming" von Donald E. Knuth in der neuesten Fassung. Es handelt sich um eine umfangreiche Einführung in die Computeralgebra, die den neuesten Stand der Forschung berücksichtigt. Donald E. Knuth versteht es, die Algorithmen didaktisch sehr geschickt und ohne Kompromisse bei der Strenge aufzubereiten. Das Buch enthält außerdem Hunderte von Aufgaben verschiedener Schwierigkeitsgrade mit Lösungen. Der Übersetzer, Prof. Dr. R. Loos, lehrt an der Universität Tübingen.Table of Contents4 — Arithmetik.- 4.1. Stellenwertsysteme.- 4.2. Gleitkomma-Aritlunetik.- 4.2.1. Einfachgenaue Rechnungen.- 4.2.2. Genauigkeit der Gleitkonuna-Arithmetik.- *4.2.3. Doppeltgenaue Rechnungen.- 4.2.4. Verteilung von Gleitkomrnazahlen.- 4.3. Mehrfachgenaue Aritlunetik.- 4.3.1. Die klassischen Algorithmen.- *4.3.2. Modulare Aritlnnetik.- *4.3.3. Wie schnell könn en wir multiplizieren?.- 4.4. Basiswechsel.- 4.5. Rationale Arithmetik.- 4.5.1. Brüche.- 4.5.2. Der größte gemeinsame Teiler.- *4.5.3. Analyse des euklidschen Algorithmus.- 4.5.4. Zerlegung in Prirnfaktoren.- 4.6. Polynornarithmetik.- 4.6.1. Division von Polynomen.- *4.6.2. Faktorisierung von Polynomen.- 4.6.3. Auswertung von Potenzen.- 4.6.4. Auswertung von Polynomen.- *4.7. Operationen an Potenzreihen.- Lösungen zu den Übungsaufgaben.- Anhang A — Tafeln numerischer Größen.- 1. Fundamentale Konstanten (dezimal).- 2. Fundamentale Konstanten (oktal).- 3. Harrnonische Zahlen , Bernoulli-Zahlen, Fibonacci-Zahlen.- Anhang B — Index der Bezeichnungen.- Index und Glossar.

Read more less

Book SynopsisThe development of powerful computer algebra systems has considerably ex­ tended the scope of problems of scientific computing which can now be solved successfully with the aid of computers. However, as the field of applications of computer algebra in scientific computing becomes broader and more complex, there is a danger of separation between theory, systems, and applications. For this reason, we felt the need to bring together the researchers who now ap­ ply the tools of computer algebra for the solution of problems in scientific computing, in order to foster new and closer interactions. CASC'99 is the second conference devoted to applications of computer al­ gebra in scientific computing. The first conference in this sequence, CASC'98, was held 20-24 April 1998 in St. Petersburg, Russia. This volume contains revised versions of the papers submitted by the par­ ticipants and accepted by the program committee after a thorough reviewing process. The collection of papers included in the proceedings covers various topics of computer algebra methods, algorithms and software applied to scien­ tific computing: symbolic-numeric analysis and solving differential equations, efficient computations with polynomials, groups, matrices and other related objects, special purpose programming environments, application to physics, mechanics, optics and to other areas. In particular, a significant group of papers deals with applications of com­ puter algebra methods for the solution of current problems in group theory, which mostly arise in mathematical physics.Table of ContentsSolution of Ordinary Differential Equations with MathLie.- Analysis of Stability of Rational Approximations through Computer Algebra.- An Automatic Symbolic-Numeric Taylor Series ODE Solver.- About Normal Form Method.- Computer Algebra Investigation of Equivalence in 4-node Plane Stress/Strain Finite Elements.- Symmetry Theorems for the Newtonian 4- and 5-body Problems with Equal Masses.- Symbolic Derivation of Different Class of High-order Compact Schemes for Partial Differential Equations.- Implementation of Aerodynamic Computations with Mathematica.- Completion of Linear Differential Systems to Involution.- Constrained Hamiltonian Systems and Gröbner Bases.- Construction of Involutive Monomial Sets for Different Involutive Divisions.- Partial Inverse Heuristic for the Approximate Solution of Non-linear Equations.- Computing Cocycles on Simplicial Complexes.- Bifurcations of Maps in the Software Package CONTENT.- Extending a Java Based Framework for Scientific Software-Components.- Symbolic-numeric Investigations for Stability Analysis of Satellite Systems.- Quantization by Presentation: The Nambu-Goto String in 1+3 Dimensions.- One Algorithm of Finding Solutions for the Systems with First Integrals.- Cohomology of Lie Superalgebras of Hamiltonian Vector Fields: Computer Analysis.- Computer Algebra Tools in Construction of Renormgroup Symmetries 251.- Where Numerics Can Benefit from Computer Algebra in Finite Difference Modelling of Fluid Flows.- Effectively Computation of Some Radicals of Submodules of Free Modules.- Computations on Character Tables of Association Schemes.- Investigation of Subgroup Embeddings by the Computer Algebra Package GAP.- An Investigation into Stability of Conservative Mechanical Systems Using Analytic Calculations.- Superfast Computations with Singular Structured Matrices over Abstract Fields.- From Modeling to Simulation with Symbolic Computation: An Application to Design and Performance Analysis of Complex Optical Devices.- A Symbolic Numeric Environment for Analyzing Measurement Data in Multi-Model Settings (Extended Abstract).- Geometric Interpretation of Strong Inconsistency in Knowledge Based Systems.- Indices and Solvability for General Systems of Differential Equations.- Decomposing Systems of Polynomial Equations.- Polynomials with Coefficients of Limited Accuracy.- Localization of Roots of a Polynomial not Represented in Canonical Form.- On Normalization of a Class of Polynomial Hamiltonians: From Ordinary and Inverse Points of View.- On Multivariate Polynomial Decomposition.- Complexity of Monomial Evaluations and Duality.- On the Simplification of Nonlinear DAE Systems in Analog Circuit Design.- Symbolic Analysis of Computational Algorithms with SYDNA.

Read more less

Book SynopsisThe design and analysis of data structures and efficient algorithms has gained considerable importance in recent years. The concept of "algorithm" is central in computer science, and "efficiency" is central in the world of money. I have organized the material in three volumes and nine chapters. Vol. 1: Sorting and Searching (chapters I to III) Vol. 2: Graph Algorithms and NP-completeness (chapters IV to VI) Vol. 3: Multi-dimensional Searching and Computational G- metry (chapters VII and VIII) Volumes 2 and 3 have volume 1 as a common basis but are indepen­ dent from each other. Most of volumes 2 and 3 can be understood without knowing volume 1 in detail. A general kowledge of algorith­ mic principles as laid out in chapter 1 or in many other books on algorithms and data structures suffices for most parts of volumes 2 and 3. The specific prerequisites for volumes 2 and 3 are listed in the prefaces to these volumes. In all three volumes we present and analyse many important efficient algorithms for the fundamental computa­ tional problems in the area. Efficiency is measured by the running time on a realistic model of a computing machine which we present in chapter I. Most of the algorithms presented are very recent inven­ tions; after all computer science is a very young field. There are hardly any theorems in this book which are older than 20 years and at least fifty percent of the material is younger than 10 years.Table of ContentsI. Foundations.- 1. Machine Models: RAM and RASP.- 2. Randomized Computations.- 3. A High Level Programming Language.- 4. Structured Data Types.- 4.1 Queues and Stacks.- 4.2 Lists.- 4.3 Trees.- 5. Recursion.- 6. Order of Growth.- 7. Secondary Storage.- 8. Exercises.- 9. Bibliographic Notes.- II. Sorting.- 1. General Sorting Methods.- 1.1 Sorting by Selection, a First Attempt.- 1.2 Sorting by Selection: Heapsort.- 1.3 Sorting by Partitioning: Quicksort.- 1.4 Sorting by Merging.- 1.5 Comparing Different Algorithms.- 1.6 Lower Bounds.- 2. Sorting by Distribution.- 2.1 Sorting Words.- 2.2 Sorting Reals by Distribution.- 3. The Lower Bound on Sorting, Revisited.- 4. The Linear Median Algorithm.- 5. Exercises.- 6. Bibliographic Notes.- III. Sets.- 1. Digital Search Trees.- 1.1 Tries.- 1.2 Static Tries or Compressing Sparse Tables.- 2. Hashing.- 2.1 Hashing with Chaining.- 2.2 Hashing with Open Addressing.- 2.3 Perfect Hashing.- 2.4 Universal Hashing.- 2.5 Extendible Hashing.- 3. Searching Ordered Sets.- 3.1 Binary Search and Search Trees.- 3.2 Interpolation Search.- 4. Weighted Trees.- 4.1 Optimum Weighted Trees, Dynamic Programming, and Pattern Matching.- 4.2 Nearly Optimal Binary Search Trees.- 5. Balanced Trees.- 5.1 Weight-Balanced Trees.- 5.2 Height-Balanced Trees.- 5.3 AdvancedTopicson(a,b)-Trees.- 5.3.1 Mergable Priority Queues.- 5.3.2 Amortized Rebalancing Cost and Sorting Presorted Files.- 5.3.3 Finger Trees.- 5.3.4 Fringe Analysis.- 6. Dynamic Weighted Trees.- 6.1 Self-Organizing Data Structures and Their Amortized and Average Case Analysis.- 6.1.1 Self-Organizing Linear Lists.- 6.1.2 Splay Trees.- 6.2 D-trees.- 6.3 An Application to Multidimensional Searching.- 7. A Comparison of Search Structures.- 8. Subsets of a Small Universe.- 8.1 The Boolean Array (Bitvector).- 8.2 The O(log log N) Priority Queue.- 8.3 The Union-Find Problem.- 9. Exercises.- 10. Bibliographic Notes.- IX. Algorithmic Paradigms.

Read more less

Table of ContentsVII. Multidimensional Data Structures.- 1. A Black Box Approach to Data Structures.- 1.1 Dynamization.- 1.2 Weighting and Weighted Dynamization.- 1.3 Order Decomposable Problems.- 2. Multi-dimensional Searching Problems.- 2.1 D-dimensional Trees and Polygon Trees.- 2.2 Range Trees and Multidimensional Divide and Conquer.- 2.3 Lower Bounds.- 2.3.1 Partial MatchRetrieval in Minimum Space.- 2.3.2 The Spanning Bound.- 3. Exercises.- 4. Bibliographic Notes.- VIII. Computational Geometry.- 1. Convex Polygons.- 2. Convex Hulls.- 3. Voronoi Diagrams and Searching Planar Subdivisions.- 3.1 Voronoi Diagrams.- 3.2 Searching Planar Subdivisions.- 3.2.1 Removal of Large Independent Sets.- 3.2.2 Path Decompositions.- 3.2.3 Searching Dynamic Planar Subdivisions.- 3.3 Applications.- 4. The Sweep Paradigm.- 4.1 Intersection of Line Segments and Other Intersection Problems in the Plane.- 4.2 Triangulation and its Applications.- 4.3 Space Sweep.- 5. The Realm of Orthogonal Objects.- 5.1 Plane Sweep for Iso-Oriented Objects.- 5.1.1 The Interval Tree and its Applications.- 5.1.2 The Priority Search Tree and its Applications.- 5.1.3 Segment Trees.- 5.1.4 Path Decomposition and Plane Sweep for Non-Iso-Oriented Objects.- 5.2 Divide and Conquer on Iso-Oriented Objects.- 5.2.1 The Line Segment Intersection Problem.- 5.2.2 The Measure and Contour Problems.- 5.3 Intersection Problems in Higher-Dimensional Space.- 6. Geometric Transforms.- 6.1 Duality.- 6.2 Inversion.- 7. Exercises.- 8. Bibliographic Notes.- IX. Algorithmic Paradigms.

Read more less

Book Synopsis

Read more less

Book SynopsisDas an Studienanfänger der Mathematik gerichtete Lehrbuch bietet eine breit angelegte Einführung in verschiedene Facetten der computerorientierten Mathematik. Es ermöglicht eine frühzeitige und wertvolle Auseinandersetzung mit computerorientierten Methoden, Denkweisen und Arbeitstechniken innerhalb der Mathematik.Hierzu werden grundlegende mathematische Teilgebiete behandelt, die eine enge Beziehung zu computerorientierten Aspekten haben: Graphen, mathematische Algorithmen, Rekursionsgleichungen, computerorientierte lineare Algebra, Zahlen, Polynome und ihre Nullstellen. Anhand des mathematischen Kernstrangs werden Einblicke in die Modellierung, Analyse und algorithmische Aufbereitung fundamentaler mathematischer Sachverhalte gegeben. Eine Besonderheit des Buches ist die Verwendung des sich immer stärker in Forschung und Lehre verbreitenden, frei verfügbaren Software-Systems Sage.Das Buch eignet sich besonders gut zur Komplementierung der klassischen Grundvorlesungen in Analysis und linearer Algebra.Trade Review“... Jedes Kapitel wird durch theoretisch ausgestaltete Übungsaufgaben sowie weiterführende Anmerkungen mit Quellenangaben direkt am Kapitelende komplettiert. ... Insgesamt ist dies ein gelungenes Lehrbuch zur computerorientierten Mathematik, das sowohl für eine Vorlesung für Erstsemester als auch als Hintergrundliteratur für ein Computerpraktikum zu Studienbeginn sehr gut geeignet ist ...” (Anne Frühbis-Krüger, in: Computer Algebra, Heft 58, März 2016)Table of ContentsEinleitung und Überblick.- Grundlegende Begriffe und Techniken.- Das Software-System Sage.- Graphen.- Einstieg in die Mathematik mit Sage.- Algorithmen und Rekursion.- Grundlegende mathematische Algorithmen.- Rechnen mit komplexen Zahlen.- Computerorientierte lineare Algebra.- Polynome und ihre Nullstellen.- Computerorientierte Fallstudien natürlicher Zahlen.- Anhang: Analysis, Lineare Algebra, Notation, Liste der verwendeten Sage-Befehle.

Read more less

Book SynopsisDieses Buch bietet einen historisch orientierten Einstieg in die Algorithmik, also die Lehre von den Algorithmen, in Mathematik, Informatik und darüber hinaus. Besondere Merkmale und Zielsetzungen sind: Elementarität und Anschaulichkeit, die Berücksichtigung der historischen Entwicklung, Motivation der Begriffe und Verfahren anhand konkreter, aussagekräftiger Beispiele unter Einbezug moderner Werkzeuge (Computeralgebrasysteme, Internet). Als Zusatzmedien werden computer- und internetspezifische Interaktions- und Visualisierungsmöglichkeiten (kostenlos) zur Verfügung gestellt. Das Werk wendet sich an Studierende und Lehrende an Schulen und Hochschulen sowie an Nichtspezialisten, die an den Themen "Computer/Algorithmen/Programmierung" einschließlich ihrer historischen und geisteswissenschaftlichen Dimension interessiert sind.Table of ContentsEinleitung.- Begriffsbestimmungen.- Historische Bezüge.- Fundamentale heuristische Strategien des algorithmischen Problemlösens.- Effizienz von Algorithmen.- Korrektheit von Algorithmen, Korrektheit von Computerergebnissen.- Grenzen der Algorithmisierbarkeit, Grenzen des Computers.- Programmierung.- Informationstheorie, Codierung und Kryptographie.- Evolutionäre Algorithmen und neuronale Netze.

Read more less

Book SynopsisDas Buch bietet ein ausgewogenes Verhältnis zwischen Theorie und praktischen Anwendungen des berechnenden Ingenieurswesens. Es illustriert sowohl die mathematischen Modelle im Computational Engineering, wie auch die zugehörigen Simulationsmethoden für die verschiedenen Ingenieursanwendungen und benennt geeignete Softwarepakete. Die umfangreichen Beispiele aus der berechnenden Ingenieurswissenschaft, welche Wärme- und Massentransport, Plasmasimulation und hydrodynamische Transportprobleme einschließen, geben dem Leser einen Überblick zu den aktuellen Themen und deren praktische Umsetzung in spätere Simulationsprogramme. Übungsaufgaben und prüfungsrelevante Fragen schließen die einzelnen Kapitel ab.Table of ContentsEinführung in Computational Engineering - Theoretischer Überblick zu den numerischen Verfahren - Theoretischer Überblick zu den Modellen - Schwerpunkt: Numerische Verfahren im Bereich der Transportmodelle - Schwerpunkt: Multiskalenmodelle und deren Multiskalenlöser - Algorithmische Umsetzung der theoretischen Verfahren - Praktische Anwendung in ingenieurswissenschaftlichen Problemstellungen.

Read more less

Book SynopsisThis book is a comprehensive introduction to the methods and algorithms of modern data analytics. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. This book has been used for more than ten years in the Data Mining course at the Technical University of Munich. Much of the content is based on the results of industrial research and development projects at Siemens.Table of ContentsData Analytics - Data and Relations - Data Preprocessing - Data Visualization - Correlation - Regression - Forecasting - Classification - Clustering.

Read more less

Book SynopsisThis self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix.The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition.Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists in computational mathematics, physics, chemistry and engineering.Trade Review“Every line of the book reflects that the author is the leading expert for hierarchical matrices. … Hierarchical matrices: algorithms and analysis is without a doubt a beautiful, comprehensive introduction to hierarchical matrices that can serve as both a graduate level textbook and a valuable resource for future research.” (Thomas Mach, Mathematical Reviews, April, 2017)“The book ‘Hierarchical matrices: algorithms and analysis’ is a self-contained monograph which presents an efficient possibility to handle the numerical treatment of fully populated large scale matrices appearing in scientific computations, and therefore it is of interest to scientists in computational mathematics, physics, chemistry and engineering.” (Constantin Popa, zbMATH 1336.65041, 2016)Table of ContentsPreface.- Part I: Introductory and Preparatory Topics.- 1. Introduction.- 2. Rank-r Matrices.- 3. Introductory Example.- 4. Separable Expansions and Low-Rank Matrices.- 5. Matrix Partition.- Part II: H-Matrices and Their Arithmetic.- 6. Definition and Properties of Hierarchical Matrices.- 7. Formatted Matrix Operations for Hierarchical Matrices.- 8. H2-Matrices.- 9. Miscellaneous Supplements.- Part III: Applications.- 10. Applications to Discretised Integral Operators.- 11. Applications to Finite Element Matrices.- 12. Inversion with Partial Evaluation.- 13. Eigenvalue Problems.- 14. Matrix Functions.- 15. Matrix Equations.- 16. Tensor Spaces.- Part IV: Appendices.- A. Graphs and Trees.- B. Polynomials.- C. Linear Algebra and Functional Analysis.- D. Sinc Functions and Exponential Sums.- E. Asymptotically Smooth Functions.- References.- Index.

Read more less

Book SynopsisInformatik ist der Schlüssel, um unsere zunehmend digitalisierte Welt zu verstehen! In diesem Buch lesen Sie nicht nur, wie Navis den günstigsten Weg bestimmen, wie so viele Bilder auf eine kleine Speicherkarte passen oder welche Dinge ein Computer eben nicht ausrechnen kann. Mit Papier und Bleistift und den Bastelvorlagen können Sie die Antworten auf diese und viele weitere Fragen selbst buchstäblich begreifen. Ein Computer ist dafür gar nicht nötig! Genau genommen sind im Buch sogar mehrere Computer aus Pappe enthalten, anhand derer man besser versteht, wie die "echten" Geräte gestaltet sind und wie diese funktionieren. Als Neuerung gibt es ergänzende, aktive Webseiten, die Sie frei (und ohne Werbung) aus dem Internet abrufen können, um mit ihnen zu experimentieren. Das Buch ist für alle da, die schon immer mal hinter die Kulissen der Wissenschaft Informatik schauen wollten: Vom Schüler zum Lehrer, vom Studenten zum Professor, vom interessierten Laien zum IT-Experten, der zwar genau weiß, wie er bestimmte Dinge zu tun hat, aber vielleicht nicht, warum sie so funktionieren oder wie er den Kern seiner tägliche Arbeit seiner Familie verständlich machen kann. Die 5. Auflage enthält zusätzliche Kapitel mit neuem Material sowie die Erweiterung und Überarbeitung der vorhandenen Kapitel. Das bewährte Hands-on-Konzept mit Experimenten und Bastelbögen zum Ausschneiden ist der durchgängige rote Faden.Stimmen zu vorhergehenden Auflagen:„Wer mit einem Informatikstudium liebäugelt, erhält einen Vorgeschmack auf das, was ihn erwartet - alle anderen können das Buch einfach zum Vergnügen lesen.“ c't – Magazin für Computertechnik„Lassen Sie sich also ein auf das ‚Abenteuer Informatik’! Ich bin sicher, dass Sie Spaß daran haben“ LOG IN – Informatische Bildung und Computer in der Schule„Auch wenn es unglaublich klingt: Abenteuer Informatik ist ein Buch über wichtige Prinzipien der modernen informationsverarbeitenden Alltagswelt, das man beim Lesen nicht mehr aus der Hand legen will.“ BIOspektrum„Mit bester Empfehlung!" PM – Praxis der Mathematik„Bits zum Begreifen" Bild der WissenschaftProf. Dr. Jens Gallenbacher liegt am Herzen, die Fachwissenschaft Informatik lebendig und mit einem hohen Allgemeinbildungsgrad zu vermitteln. Er ist an der Johannes Gutenberg-Universität in Mainz für die Ausbildung neuer Informatiklehrerinnen und -lehrer verantwortlich. Um zu zeigen, dass Informatik mehr mit menschlicher Kreativität und konsequentem Denken zu tun hat als mit Computern, verzichtet er dabei weitgehend auf den Einsatz der Geräte. Seine Konzepte werden vom Kindergarten bis zur universitären Grundlagenausbildung eingesetzt.Trade Review“... Erklärungen werden wie in algorithmischen Schritten sehr genau analysiert und führen bis zu wesentlichen Grundlagen der Informatik. ... Weit verständlich, fesselnd, zum Nachdenken und Diskutieren. Mitunter notwendige Geduld wird reich belohnt. Als Vertiefung daneben gut "Algorithmen kapieren" ...” (Rolf Becker-Friedrich, in: ekz-Informationsdienst, Heft 49, 2021)Table of ContentsEinleitung.- 1 Sag' mir wohin ...- 2 Ordnung muss sein!- 3 Ich packe meinen Koffer und ...- 4 Der Trick mit dem Binären.- 5 100000000000 Jahre Informatik?- 6 Von Kamelen und dem Nadelöhr.- 7 Verluste gibt es doch immer!- 8 Erkennungsdienst.- 9 Paketpost.- 10 Alles im Fluss.- 11 Ordnung im Chaos.-12 Mit Sicherheit.- 13 Rechnen mit Strom.- 14 Besser rechnen mit Strom.- 15 Allmächtiger Computer!?.- 16 Spielchen gefällig?- 17 Schnelle Antworten.- 18 Computer auf der Schulbank.- Glossar.

Read more less

Book SynopsisThe LNCS journal Transactions on Large-Scale Data and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g., computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability.This, the 50th issue of Transactions on Large-Scale Data and Knowledge-Centered Systems, contains five fully revised selected regular papers. Topics covered include data anonymization, quasi-identifier discovery methods, symbolic time series representation, detection of anomalies in time series, data quality management in biobanks, and the use of multi-agent technology in the design of intelligent systems for maritime transport.Table of ContentsA Parallel Quasi-identifier Discovery Scheme for Dependable Data Anonymisation.- Towards Symbolic Time Series Representation Improved by Kernel Density Estimators.- Anomaly Detection in Time Series.- Designing Intelligent Marine Framework Based on Complex Adaptive System Principle.- Data Item Quality for Biobanks.

Read more less

Book SynopsisDavid Trachtenherz entwickelt einen Lösungsansatz zur eigenschaftsorientierten Beschreibung der logischen Architektur eingebetteter Systeme, der eine präzise deklarative Spezifikation funktionaler Eigenschaften mit wählbarem Grad der Abstraktion für unterschiedliche Entwicklungsphasen und -ebenen ermöglicht.Table of ContentsLogische Architektur; Formale Grundlagen; Grundlagen eigenschaftsorientierter Architekturbeschreibung; Anschauliche Darstellung eigenschaftsorientierter Architekturspezifikation; Fallstudie ; Ströme und temporale Logik in Isabelle/HOL

Read more less

Book SynopsisAlgorithms are not to be regarded as a technical structure but as a social phenomenon - they embed themselves, currently still very subtle, into our political and social system. Algorithms shape human behavior on various levels: they influence not only the aesthetic reception of the world but also the well-being and social interaction of their users. They act and intervene in a political and social context. As algorithms influence individual behavior in these social and political situations, their power should be the subject of critical discourse - or even lead to active disobedience and to the need for appropriate tools and methods which can be used to break the algorithmic power.Table of Contents(Dis)obeying Algorithms? Introductory Thoughts on the Power of Algorithms and the Possible Necessity of Resisting it; The Dialectics of Dis-Obedience. Notes from the Crystal Palace; Surveillance, Artificial Intelligence and Power; Embodied Algorithmic Optimization. How Our Bodies are Becoming a Product of Code; The Lock Down City and the Utopian Program of Open Interfaces; Hacking Google Maps; The Algorithmic Construction of Space; Torn Between Autonomy and Algorithmic Management. (Dis)Obedience of Solo Self-Employed Working via Digital Platforms; A Crack in the Algorithm's Facade. A Fundamental Rights Perspective on "Efficiency" and "Neutrality" Narratives of Algorithms; When Search Engines Discriminate. The Posthuman Mimesis of Gender Bias; Discrimination by Correlation. Towards Eliminating Algorithmic Biases and Achieving Gender Equality; The Power of Algorithms and the Structural Transformation of the Digital Public; Reclaim your Face and the Streets. Why Facial Recognition, and Other Biometric Surveillance Technology in Public Spaces, Should be Banned; Identity 5.0: How to Fight Algorithms Online (Fast). Heuristic Compressions of Personality Concepts (Dis)Obedient to Algorithmic Powerfrom Film, Television and a Cult Classic Novel; About the Authors.

Read more less

Book SynopsisThis book focuses on the standard algorithm design methods and the concepts are illustrated through representative examples to offer a ready text.

Read more less

Book SynopsisThis book is a compilation of the entire research work on the topic of Complex Binary Number System (CBNS) carried out by the author as the principal investigator and members of his research groups at various universities during the years 2000-2012. Pursuant to these efforts spanning several years, the realization of CBNS as a viable alternative to represent complex numbers in an “all-in-one” binary number format has become possible and efforts are underway to build computer hardware based on this unique number system. It is hoped that this work will be of interest to anyone involved in computer arithmetic and digital logic design and kindle renewed enthusiasm among the engineers working in the areas of digital signal and image processing for developing newer and efficient algorithms and techniques incorporating CBNS.Trade ReviewFrom the reviews:“This is a monograph presenting the results of a dozen or so years research of the author devoted to purely binary representation of complex numbers and design of circuits for arithmetic operations on them. … The topic of this book may be recommended as a facultative lecture for academic courses on digital arithmetic.” (Antoni Michalski, Zentralblatt MATH, Vol. 1262, 2013)Table of ContentsIntroduction.- Conversion Algorithms.- Arithmetic Algorithms.- Arithmetic Circuits Designs.- Complex Binary Associative Processor Design.- Conclusion and Further Research.

Read more less

Book SynopsisThe conical approach provides a geometrical understanding of optimization and is a powerful research tool and useful problem-solving technique (for example, in decision support and real time control applications). Conical optimality conditions are first stated in a very general optimization framework, and then applied to linear programming. A complete theory along with primal and dual algorithms is given, and solutions and algorithms are also provided for vector and robust linear optimization. The advantages of parameter dependence of conical methods are fully discussed. In addition to numerical results, the book provides source codes and detailed documentation of a Modula-2 implementation for the main algorithms.Table of ContentsPart I: General Theory Part II: Further Advanced Results Part III: Implementations and Numerical Results

Read more less

Book SynopsisThis book is the result of several decades of teaching experience in data structures and algorithms. It is self-contained but does assume some prior knowledge of data structures, and a grasp of basic programming and mathematics tools. Basic Concepts in Algorithms focuses on more advanced paradigms and methods combining basic programming constructs as building blocks and their usefulness in the derivation of algorithms. Its coverage includes the algorithms' design process and an analysis of their performance. It is primarily intended as a textbook for the teaching of Algorithms for second year undergraduate students in study fields related to computers and programming.Klein reproduces his oral teaching style in writing, with one topic leading to another, related one. Most of the classical and some more advanced subjects in the theory of algorithms are covered, though not in a comprehensive manner. The topics include Divide and Conquer, Dynamic Programming, Graph algorithms, probabilistic algorithms, data compression, numerical algorithms and intractability. Each chapter comes with its own set of exercises, and solutions to most of them are appended.Related Link(s)Table of ContentsDivide and Conquer; Dynamic Programming; Minimum Spanning Tree; Shortest Paths; Primality; Compression; Pattern Matching; Fat Fourier Transform; Cryptography; NP Completeness; Approximations; Solutions to Selected Exercises;

Read more less

Book SynopsisThis book is the first one that provides a solid bridge between algorithmic information theory and statistical mechanics. Algorithmic information theory (AIT) is a theory of program size and recently is also known as algorithmic randomness. AIT provides a framework for characterizing the notion of randomness for an individual object and for studying it closely and comprehensively. In this book, a statistical mechanical interpretation of AIT is introduced while explaining the basic notions and results of AIT to the reader who has an acquaintance with an elementary theory of computation.A simplification of the setting of AIT is the noiseless source coding in information theory. First, in the book, a statistical mechanical interpretation of the noiseless source coding scheme is introduced. It can be seen that the notions in statistical mechanics such as entropy, temperature, and thermal equilibrium are translated into the context of noiseless source coding in a natural manner. Then, the framework of AIT is introduced. On this basis, the introduction of a statistical mechanical interpretation of AIT is begun. Namely, the notion of thermodynamic quantities, such as free energy, energy, and entropy, is introduced into AIT. In the interpretation, the temperature is shown to be equal to the partial randomness of the values of all these thermodynamic quantities, where the notion of partial randomness is a stronger representation of the compression rate measured by means of program-size complexity. Additionally, it is demonstrated that this situation holds for the temperature itself as a thermodynamic quantity. That is, for each of all the thermodynamic quantities above, the computability of its value at temperature T gives a sufficient condition for T to be a fixed point on partial randomness.In this groundbreaking book, the current status of the interpretation from both mathematical and physical points of view is reported. For example, a total statistical mechanical interpretation of AIT that actualizes a perfect correspondence to normal statistical mechanics can be developed by identifying a microcanonical ensemble in the framework of AIT. As a result, the statistical mechanical meaning of the thermodynamic quantities of AIT is clarified. In the book, the close relationship of the interpretation to Landauer's principle is pointed out.Table of ContentsStatistical Mechanical Interpretation of Noiseless Source Coding.- Algorithmic Information Theory.- Partial Randomness.- Temperature Equals to Partial Randomness.- Fixed Point Theorems on Partial Randomness.- Statistical Mechanical Meaning of the Thermodynamic Quantities of AIT.- The Partial Randomness of Recursively Enumerable Reals.- Computation-Theoretic Clarification of the Phase Transition at Temperature T=1.- Other Related Results and Future Development.

Read more less

Book SynopsisThis book presents best selected research papers presented at the International Conference on Computer Networks, Big Data and IoT (ICCBI 2020), organized by Vaigai College Engineering, Madurai, Tamil Nadu, India, during 15–16 December 2020. The book covers original papers on computer networks, network protocols and wireless networks, data communication technologies and network security. The book is a valuable resource and reference for researchers, instructors, students, scientists, engineers, managers and industry practitioners in those important areas.Table of ContentsMaximizing Network Lifetime in WSN using Ant Colony Algorithm.- Deep Ensemble Approach for Question Answer System.- Information Sharing Over Social Media Analysis Using Centrality Measure.- Indoor Mobile Robot Navigation using Deep Convolutional Neural Network.- Etaheuristic Enabled Shortest Path Selection for IoT based Wireless Sensor Network.- Generation of Random Binary Sequence using Adaptive Row-Column Approach and Synthetic Colour Image.- A Study of Mobile Adhoc Network and its Performance Optimizaiton Algorithm.- Sentimental Analysis on Twitter Data of Political Domain.- Big Social Media Analytics: Applications and Challenges.- Intelligent Computing Application for Cloud Enhancing Health Care Services.- Corona Virus Detection and Classification using X-Rays and CT Scans with Machine Learning Techniques.- Security Issues and Solutions in E-Health and Telemedicine.- Accident Alert System with False Alarm Switch.- A Deep Learning Approach to Detect Lumpy Skin Disease in Cows.- Algorithmic Trading using Machine Learning and Neural Network.- Analysis on Intrusion Detection System using Machine Learning Techniques.- Content Related Feature Analysis for Fake Online Consumer Review Detection.- Approaches in Assistive Technology: A Survey on Existing Assistive Wearable Technology for The Visually-Impaired.- Filter Bank Multicarrier Systems using Gaussian Pulse based Filter Design for 5G Technologies.- Data Streaming Architecture for Visualizing Cryptocurrency Temporal Data.- Integration of IoT and SDN to Mitigate DDoS with RYU Controller.- A Framework for monitoring Patient’s Vital Signs with Internet-of-Things and Blockchain Technology.- Network Intrusion Detection using Cross Bagging based Stacking Model.- Performance Study of Free Space Optical System under Varied Atmospheric Conditions.- Review on Energy Efficient Routing Protocols in WSN.Comparative Analysis of Traffic and Congestion in Software Defined Networks.- Automatic Vehicle Service Monitoring and Tracking System using IoT and Machine Learning.

Read more less

Book SynopsisThis two-volume book provides an insight into the 10th International Conference on Soft Computing for Problem Solving (SocProS 2020). This international conference is a joint technical collaboration of Soft Computing Research Society and Indian Institute of Technology Indore. The book presents the latest achievements and innovations in the interdisciplinary areas of soft computing. It brings together the researchers, engineers and practitioners to discuss thought-provoking developments and challenges, in order to select potential future directions. It covers original research papers in the areas including but not limited to algorithms (artificial immune system, artificial neural network, genetic algorithm, genetic programming and particle swarm optimization) and applications (control systems, data mining and clustering, finance, weather forecasting, game theory, business and forecasting applications). The book will be beneficial for young as well as experienced researchers dealing across complex and intricate real-world problems for which finding a solution by traditional methods is a difficult task.Table of ContentsA deep semi-supervised approach for multi-label land-cover classification under scarcity of labelled images.- Role of individual samples in Modified Possibilistic c-Means classifier for handling heterogeneity within mustard crop.- Specially Structured Flow Shop Scheduling Models with processing times as Trapezoidal Fuzzy Numbers to optimize Waiting time of Jobs.- Potential Fishing Zone Characterization in the Indian Ocean by Machine Learning Approach.- A novel method to optimize interval length for intuitionistic fuzzy time series.- Low Altitude Unmanned Aerial Vehicle For Real Time Green House Plant Disease Monitoring Using Convolutional Neural Network.

Read more less

Book SynopsisThis book aims to address emerging challenges in the field of agriculture and natural resource management using the principles and applications of data science (DS). The book is organized in three sections, and it has fourteen chapters dealing with specialized areas. The chapters are written by experts sharing their experiences very lucidly through case studies, suitable illustrations and tables. The contents have been designed to fulfil the needs of geospatial, data science, agricultural, natural resources and environmental sciences of traditional universities, agricultural universities, technological universities, research institutes and academic colleges worldwide. It will help the planners, policymakers and extension scientists in planning and sustainable management of agriculture and natural resources. The authors believe that with its uniqueness the book is one of the important efforts in the contemporary cyber-physical systems.Table of ContentsData Science: Principles and Concepts in Data Analysis and Modelling.- Data Science: Tools, Techniques and Potential Applications in Earth Observation Studies.- Data Science in Agriculture and Natural Resource Management: An Overview.- Applications of Reinforcement Learning and Recurrent Neural Network Based Deep Learning Frameworks in Agriculture.- Precision Farming Using Emerging Technologies.- An Architecture for Quality Centric Crop Production.- Integrating UAV and Field Sensor Data for Better Decision Making in Broadacre Cropping Systems.- Object Based Crop Classification for Precision Farming.- Disruptive Innovations in Precision Agriculture - Towards BD Analytics for Better GeoFarmatics.- A Paradigm-shift in Global Cropland Maps and Products for Food and Water Security in the Twenty-first Century: Petabyte Scale Satellite Big-data Analytics, Machine Learning, and Cloud Computing.- Big Data Analytics for Climate Resilient Supply Chains: Opportunities and Way Forward.- Mapping Croplands Using Machine Learning Algorithms and Spectral Matching Techniques.- Applications of Computer Vision in Precision Agriculture.- Innovative Geoportal Platforms for Sustainable Management of Natural Resources.

Read more less

Book SynopsisDeep Learning models are at the core of artificial intelligence research today. It is well known that deep learning techniques are disruptive for Euclidean data, such as images or sequence data, and not immediately applicable to graph-structured data such as text. This gap has driven a wave of research for deep learning on graphs, including graph representation learning, graph generation, and graph classification. The new neural network architectures on graph-structured data (graph neural networks, GNNs in short) have performed remarkably on these tasks, demonstrated by applications in social networks, bioinformatics, and medical informatics. Despite these successes, GNNs still face many challenges ranging from the foundational methodologies to the theoretical understandings of the power of the graph representation learning.This book provides a comprehensive introduction of GNNs. It first discusses the goals of graph representation learning and then reviews the history, current developments, and future directions of GNNs. The second part presents and reviews fundamental methods and theories concerning GNNs while the third part describes various frontiers that are built on the GNNs. The book concludes with an overview of recent developments in a number of applications using GNNs. This book is suitable for a wide audience including undergraduate and graduate students, postdoctoral researchers, professors and lecturers, as well as industrial and government practitioners who are new to this area or who already have some basic background but want to learn more about advanced and promising techniques and applications.Table of ContentsChapter 1. Representation Learning.- Chapter 2. Graph Representation Learning.- Chapter 3. Graph Neural Networks.- Chapter 4. Graph Neural Networks for Node Classification.- Chapter 5. The Expressive Power of Graph Neural Networks.- Chapter 6. Graph Neural Networks: Scalability.- Chapter 7. Interpretability in Graph Neural Networks.- Chapter 8. "Graph Neural Networks: Adversarial Robustness".- Chapter 9. Graph Neural Networks: Graph Classification.- Chapter 10. Graph Neural Networks: Link Prediction.- Chapter 11. Graph Neural Networks: Graph Generation.- Chapter 12. Graph Neural Networks: Graph Transformation.- Chapter 13. Graph Neural Networks: Graph Matching.- Chapter 14. "Graph Neural Networks: Graph Structure Learning". Chapter 15. Dynamic Graph Neural Networks.- Chapter 16. Heterogeneous Graph Neural Networks.- Chapter 17. Graph Neural Network: AutoML.- Chapter 18. Graph Neural Networks: Self-supervised Learning.- Chapter 19. Graph Neural Network in Modern Recommender Systems.- Chapter 20. Graph Neural Network in Computer Vision.- Chapter 21. Graph Neural Networks in Natural Language Processing.- Chapter 22. Graph Neural Networks in Program Analysis.- Chapter 23. Graph Neural Networks in Software Mining.- Chapter 24. "GNN-based Biomedical Knowledge Graph Mining in Drug Development".- Chapter 25. "Graph Neural Networks in Predicting Protein Function and Interactions".- Chapter 26. Graph Neural Networks in Anomaly Detection.- Chapter 27. Graph Neural Networks in Urban Intelligence.

Read more less

Book SynopsisThis book focuses on research aspects of ensemble approaches of machine learning techniques that can be applied to address the big data problems. In this book, various advancements of machine learning algorithms to extract data-driven decisions from big data in diverse domains such as the banking sector, healthcare, social media, and video surveillance are presented in several chapters. Each of them has separate functionalities, which can be leveraged to solve a specific set of big data applications. This book is a potential resource for various advances in the field of machine learning and data science to solve big data problems with many objectives. It has been observed from the literature that several works have been focused on the advancement of machine learning in various fields like biomedical, stock prediction, sentiment analysis, etc. However, limited discussions have been carried out on application of advanced machine learning techniques in solving big data problems. Table of ContentsDeep Learning for Supervised Learning.- Deep Learning for Unsupervised Learning.- Support Vector Machine for Regression.- Support Vector Machine for Classification.- Decision Tree for Regression.- Higher Order Neural Networks.- Competitive Learning.- Semi-supervised Learning.- Multi-objective Optimization Techniques.- Techniques for Feature Selection/Extraction.- Techniques for Task Relevant Big Data Analysis.- Techniques for Post Processing Task in Big Data Analysis.- Customer Relationship Management.

Read more less