An Introduction to Distributed Algorithms takes up some of the main concepts and algorithms, ranging from basic to advanced techniques and applications, that underlie the programming of distributed-memory systems such as computer networks, networks of work-stations, and multiprocessors. Written from the broad perspective of distributed-memory systems in general it includes topics such as algorithms for maximum flow, programme debugging, and simulation that do not appear in more orthodox texts on distributed algorithms.

Foundations of Algorithms, Fifth Edition offers a well-balanced presentation of algorithm design, complexity analysis of algorithms, and computational complexity. Ideal for any computer science students with a background in college algebra and discrete structures, the text presents mathematical concepts using standard English and simple notation to maximize accessibility and user-friendliness. Concrete examples, appendices reviewing essential mathematical concepts, and a student-focused approach reinforce theoretical explanations and promote learning and retention. C++ and Java pseudocode help students better understand complex algorithms. A chapter on numerical algorithms includes a review of basic number theory, Euclid's Algorithm for finding the greatest common divisor, a review of modular arithmetic, an algorithm for solving modular linear equations, an algorithm for computing modular powers, and the new polynomial-time algorithm for determining whether a number is prime.The revised and updated Fifth Edition features an all-new chapter on genetic algorithms and genetic programming, including approximate solutions to the traveling salesperson problem, an algorithm for an artificial ant that navigates along a trail of food, and an application to financial trading. With fully updated exercises and examples throughout and improved instructor resources including complete solutions, an Instructor’s Manual and PowerPoint lecture outlines, Foundations of Algorithms is an essential text for undergraduate and graduate courses in the design and analysis of algorithms. Key features include:• The only text of its kind with a chapter on genetic algorithms• Use of C++ and Java pseudocode to help students better understand complex algorithms• No calculus background required• Numerous clear and student-friendly examples throughout the text• Fully updated exercises and examples throughout• Improved instructor resources, including complete solutions, an Instructor’s Manual, and PowerPoint lecture outlines

Shimon Even's Graph Algorithms, published in 1979, was a seminal introductory book on algorithms read by everyone engaged in the field. This thoroughly revised second edition, with a foreword by Richard M. Karp and notes by Andrew V. Goldberg, continues the exceptional presentation from the first edition and explains algorithms in a formal but simple language with a direct and intuitive presentation. The book begins by covering basic material, including graphs and shortest paths, trees, depth-first-search and breadth-first search. The main part of the book is devoted to network flows and applications of network flows, and it ends with chapters on planar graphs and testing graph planarity.

It is only during the last decade that the functions of sinusoidal endothelial cells, Kupffer cells, hepatic stellate cells, pit cells and other intrahepatic lymphocytes have been better understood. The development of methods for isolation and co-culturing various types of liver cells has established that they communicate and cooperate via secretion of various intercellular mediators. This monograph summarizes multiple data that suggest the important role of cellular cross-talk for the functions of both normal and diseased liver. Special features of the book include concise presentation of the majority of detailed data in 19 tables. Original schemes allow for the clear illustration of complicated intercellular relationships. This is the first ever presentation of the newly emerging field of liver biology, which is important for hepatic function in health and disease and opens new avenues for therapeutic interventions.

This book constitutes the refereed proceedings of the 14th International Workshop on Algorithms in Bioinformatics, WABI 2014, held in Wroclaw, Poland, in September 2014. WABI 2014 was one of seven conferences that were organized as part of ALGO 2014. WABI is an annual conference series on all aspects of algorithms and data structure in molecular biology, genomics and phylogeny data analysis. The 26 full papers presented together with a short abstract were carefully reviewed and selected from 61 submissions. The selected papers cover a wide range of topics from sequence and genome analysis through phylogeny reconstruction and networks to mass spectrometry data analysis.

Data warehousing and knowledge discovery has been widely accepted as a key te- nology for enterprises and organizations to improve their abilities in data analysis, decision support, and the automatic extraction of knowledge from data. With the exponentially growing amount of information to be included in the decision-making process, the data to be considered become more and more complex in both structure and semantics. New developments such as cloud computing add to the challenges with massive scaling, a new computing infrastructure, and new types of data. Consequently, the process of retrieval and knowledge discovery from this huge amount of heterogeneous complex data forms the litmus test for research in the area. In the last decade, the International Conference on Data Warehousing and Kno- edge Discovery (DaWaK) has become one of the most important international sci- tific events bringing together researchers, developers, and practitioners to discuss the latest research issues and experiences in developing and deploying data warehousing and knowledge discovery systems, applications, and solutions. th This year’s conference, the 12 International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2010), continued the tradition by discussing and disseminating innovative principles, methods, algorithms, and solutions to challe- ing problems faced in the development of data warehousing, knowledge discovery, the emerging area of "cloud intelligence," and applications within these areas. In order to better reflect novel trends and the diversity of topics, the conference was organized in four tracks: Cloud Intelligence, Data Warehousing, Knowledge Discovery, and Industry and Applications.

Annotation This volume constitutes the refereed proceedings of the 11th Pacific Rim Conference on Artificial Intelligence, PRICAI 2010, held in Daegu, Korea, in August/September 2010. The 48 revised full papers presented together with 21 short papers in this volume were carefully reviewed and selected from 191 submissions. The volume concentrates on AI theories, technologies and their applications in the areas of social and economic importance for countries in the Pacific Rim.

This text covers the proceedings of the Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, which was held in Atlanta, Georgia, in January 1996.