The topic of this book is finite group actions and their use in order to approach finite unlabeled structures by defining them as orbits of finite groups of sets. Well-known examples are graph, linear codes, chemical isomers, spin configurations, isomorphism classes of combinatorial designs etc.The second edition is an extended version and puts more emphasis on applications to the constructive theory of finite structures. Recent progress in this field, in particular in design and coding theory, is described.This book will be of great use to researchers and graduate students.

This book offers a comprehensive introduction to Subdivision Surface Modeling Technology focusing not only on fundamental theories but also on practical applications. It furthers readers' understanding of the contacts between spline surfaces and subdivision surfaces, enabling them to master the Subdivision Surface Modeling Technology for analyzing subdivision surfaces. Subdivision surface modeling is a popular technology in the field of computer aided design (CAD) and computer graphics (CG) thanks to its ability to model meshes of any topology. The book also discusses some typical Subdivision Surface Modeling Technologies, such as interpolation, fitting, fairing, intersection, as well as trimming and interactive editing. It is a valuable tool, enabling readers to grasp the main technologies of subdivision surface modeling and use them in software development, which in turn leads to a better understanding of CAD/CG software operations.

This volume contains 17 surveys that cover many recent developments in Discrete Geometry and related fields. Besides presenting the state-of-the-art of classical research subjects like packing and covering, it also offers an introduction to new topological, algebraic and computational methods in this very active research field. The readers will find a variety of modern topics and many fascinating open problems that may serve as starting points for research.

Visualization technology is becoming increasingly important for medical and biomedical data processing and analysis. The interaction between visualization and medicine is one of the fastest expanding fields, both scientifically and commercially. This book discusses some of the latest visualization techniques and systems for effective analysis of such diverse, large, complex, and multi-source data.

This unique book gives a comprehensive account of new mathematical tools used to solve polygon problems.

In the 20th and 21st centuries, many problems in mathematics, theoretical physics and theoretical chemistry - and more recently in molecular biology and bio-informatics - can be expressed as counting problems, in which specified graphs, or shapes, are counted.

One very special class of shapes is that of polygons. These are closed, connected paths in space. We usually sketch them in two-dimensions, but they can exist in any dimension. The typical questions asked include "how many are there of a given perimeter?," "how big is the average polygon of given perimeter?," and corresponding questions about the area or volume enclosed. That is to say "how many enclosing a given area?" and "how large is an average polygon of given area?" Simple though these questions are to pose, they are extraordinarily difficult to answer. They are important questions because of the application of polygon, and the related problems of polyomino and polycube counting, to phenomena occurring in the natural world, and also because the study of these problems has been responsible for the development of powerful new techniques in mathematics and mathematical physics, as well as in computer science. These new techniques then find application more broadly.

The book brings together chapters from many of the major contributors in the field. An introductory chapter giving the history of the problem is followed by fourteen further chapters describing particular aspects of the problem, and applications to biology, to surface phenomena and to computer enumeration methods.

Dynamical models on graphs or random graphs are increasingly used in applied sciences as mathematical tools to study complex systems whose exact structure is too complicated to be known in detail. Besides its importance in applied sciences, the field is increasingly attracting the interest of mathematicians and theoretical physicists also because of the fundamental phenomena (synchronization, phase transitions etc.) that can be studied in the relatively simple framework of dynamical models of random graphs. This volume was developed from the Mathematical Technology of Networks conference held in Bielefeld, Germany in December 2013. The conference was designed to bring together functional analysts, mathematical physicists, and experts in dynamical systems. The contributors to this volume explore the interplay between theoretical and applied aspects of discrete and continuous graphs. Their work helps to close the gap between different avenues of research on graphs, including metric graphs and ramified structures.

This nice text (twenty years in the writing, published posthumously) would serve well to introduce graduate students (those who can afford it ) to a rich and important class of graph-theoretic problems and concepts. Fifteen short chapters (under three broad topical heads), to each of which are attac

Combinatorics is one of the fastest growing fields of mathematics. One reason for this is because many practical problems can be modeled and then efficiently solved using combinator combinatorial theory. This real world motivation for studying algorithmic combinatorics has led not only to the development of many software packages but also to some beautiful mathematics which has no direct application to applied problems. This book highlights a few of the exciting recent developments in algorithmic combinatorics, including the search for patterns in DNA and protein sequences, the theory of semi-definite programming and its role in combinatorial optimization, and the algorithmic aspects of tree decompositions and it's applications to the theory of databases, code optimization, and bioinformatics. Claudia Linhares-Sales is Assistant Professor of Computer Science at the Federal University of Cearß, Brazil. Bruce Reed is Canada Research Chair in Graph Theory at the School of of Computer Science of McGill University.

The theory of tree languages, founded in the late Sixties and still active in the Seventies, was much less active during the Eighties. Now there is a simultaneous revival in several countries, with a number of significant results proved in the past five years. A large proportion of them appear in the present volume.

The editors of this volume suggested that the authors should write comprehensive half-survey papers. This collection is therefore useful for everyone interested in the theory of tree languages as it covers most of the recent questions which are not treated in the very few rather old standard books on the subject. Trees appear naturally in many chapters of computer science and each new property is likely to result in improvement of some computational solution of a real problem in handling logical formulae, data structures, programming languages on systems, algorithms etc. The point of view adopted here is to put emphasis on the properties themselves and their rigorous mathematical exposition rather than on the many possible applications.

This volume is a useful source of concepts and methods which may be applied successfully in many situations: its philosophy is very close to the whole philosophy of the ESPRIT Basic Research Actions and to that of the European Association for Theoretical Computer Science.

In July 2004, a conference on graph theory was held in Paris in memory of Claude Berge, one of the pioneers of the field. The event brought together many prominent specialists on topics such as perfect graphs and matching theory, upon which Claude Berge's work has had a major impact. This volume includes contributions to these and other topics from many of the participants.

This ambitious exposition by Malik and Mordeson on the fuzzification of discrete structures not only supplies a solid basic text on this key topic, but also serves as a viable tool for learning basic fuzzy set concepts "from the ground up" due to its unusual lucidity of exposition. While the entire presentation of this book is in a completely traditional setting, with all propositions and theorems provided totally rigorous proofs, the readability of the presentation is not compromised in any way; in fact, the many ex cellently chosen examples illustrate the often tricky concepts the authors address. The book's specific topics - including fuzzy versions of decision trees, networks, graphs, automata, etc. - are so well presented, that it is clear that even those researchers not primarily interested in these topics will, after a cursory reading, choose to return to a more in-depth viewing of its pages. Naturally, when I come across such a well-written book, I not only think of how much better I could have written my co-authored monographs, but naturally, how this work, as distant as it seems to be from my own area of interest, could nevertheless connect with such. Before presenting the briefest of some ideas in this direction, let me state that my interest in fuzzy set theory (FST) has been, since about 1975, in connecting aspects of FST directly with corresponding probability concepts. One chief vehicle in carrying this out involves the concept of random sets."

Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: * A survey of computational approaches to reconstruct and partition biological networks * An introduction to complex networks measures, statistical properties, and models * Modeling for evolving biological networks * The structure of an evolving random bipartite graph * Density-based enumeration in structured data * Hyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.

This is a supplementary volume to the major three-volume Handbook of Combinatorial Optimization set. It can also be regarded as a stand-alone volume presenting chapters dealing with various aspects of the subject in a self-contained way.

Pierri clearly links modern psychoanalytic practice with Freud's interests in the occult using primary sources, some of which have never before been published in English. Assesses the origins of key psychoanalytic ideas.

The notes that eventually became this book were written between 1977 and 1985 for the course called Constructive Combinatorics at the University of Minnesota. This is a one-quarter (10 week) course for upper level undergraduate students. The class usually consists of mathematics and computer science majors, with an occasional engineering student. Several graduate students in computer science also attend. At Minnesota, Constructive Combinatorics is the third quarter of a three quarter sequence. The fIrst quarter, Enumerative Combinatorics, is at the level of the texts by Bogart [Bo], Brualdi [Br], Liu [Li] or Tucker [Tu] and is a prerequisite for this course. The second quarter, Graph Theory and Optimization, is not a prerequisite. We assume that the students are familiar with the techniques of enumeration: basic counting principles, generating functions and inclusion/exclusion. This course evolved from a course on combinatorial algorithms. That course contained a mixture of graph algorithms, optimization and listing algorithms. The computer assignments generally consisted of testing algorithms on examples. While we felt that such material was useful and not without mathematical content, we did not think that the course had a coherent mathematical focus. Furthermore, much of it was being taught, or could have been taught, elsewhere. Graph algorithms and optimization, for instance, were inserted into the graph theory course where they naturally belonged. The computer science department already taught some of the material: the simpler algorithms in a discrete mathematics course; effIciency of algorithms in a more advanced course.

This book is about graph energy. The authors have included many of the important results on graph energy, such as the complete solution to the conjecture on maximal energy of unicyclic graphs, the Wagner-Heuberger's result on the energy of trees, the energy of random graphsor the approach to energy using singular values. It contains an extensive coverage of recent results and a gradual development of topics and the inclusion of complete proofs from most of the important recent results in the area. The latter fact makes it a valuable reference for researchers looking to get into the field of graph energy, further stimulating it with occasional inclusion of open problems. The book provides a comprehensive survey of all results and common proof methods obtained in this field with an extensive reference section. The book is aimed mainly towards mathematicians, both researchers and doctoral students, with interest in the field of mathematical chemistry. "

This book offers a comprehensive treatment of linear programming as well as of the optimization of linear functions over polyhedra in finite dimensional Euclidean vector spaces. An introduction surveying fifty years of linear optimization is given. The book can serve both as a graduate textbook for linear programming and as a text for advanced topics classes or seminars. Exercises as well as several case studies are included. The book is based on the author's long term experience in teaching and research. For his research work he has received, among other honors, the 1983 Lanchester Prize of the Operations Research Society of America, the 1985 Dantzig Prize of the Mathematical Programming Society and the Society for Industrial Applied Mathematics and a 1989 Alexander-von-Humboldt Senior U.S. Scientist Research Award.

This second edition of "A Beginner's Guide to Finite Mathematics" takes a distinctly applied approach to finite mathematics at the freshman and sophomore level. Topics are presented sequentially: the book opens with a brief review of sets and numbers, followed by an introduction to data sets, histograms, means and medians. Counting techniques and the Binomial Theorem are covered, which provides the foundation for elementary probability theory; this, in turn, leads to basic statistics. This new edition includes chapters on game theory and financial mathematics. Requiring little mathematical background beyond high school algebra, the text will be especially useful for business and liberal arts majors.

This book contains translations of papers from the second volume of the new Russian-language journal published at the Sobolev Institute of Mathematics (Sibe- rian Branch of the Russian Academy of Sciences, Novosibirsk) since 1994. In 1994 the journal was titled Sibirskil Zhurnal Issledovaniya Oper- atsil. Since 1995 this journal has the title Diskretny'l Analiz i Issledovanie Operatsi'l (Discrete Analysis and Operations Research). The aim of this journal is to bring together research papers in different areas of discrete mathematics and computer science. The journal DiskretnYl Analiz i Issledovanie Operatsil covers the following fields: * discrete optimization * synthesis and complexity * discrete structures and * of control systems extremal problems * automata * combinatorics * graphs * control and reliability * game theory and its of discrete devices applications * mathematical models and * coding theory methods of decision making * scheduling theory * design and analysis * functional systems theory of algorithms Contributions presented to the journal can be original research papers and occasional survey articles of moderate length. The journal is published in one volume of four issues per year that appear in March, June, September, and December. Each volume contains approximately 400 pages. I express my sincere gratitude to Professor S. S. Kutateladze for his help in editing the English translation.

The inverse scattering problem is central to many areas of science and technology such as radar and sonar, medical imaging, geophysical exploration and nondestructive testing. This book is devoted to the mathematical and numerical analysis of the inverse scattering problem for acoustic and electromagnetic waves. In this third edition, new sections have been added on the linear sampling and factorization methods for solving the inverse scattering problem as well as expanded treatments of iteration methods and uniqueness theorems for the inverse obstacle problem. These additions have in turn required an expanded presentation of both transmission eigenvalues and boundary integral equations in Sobolev spaces. As in the previous editions, emphasis has been given to simplicity over generality thus providing the reader with an accessible introduction to the field of inverse scattering theory.

Review of earlier editions:

"Colton and Kress have written a scholarly, state of the art account of their view of direct and inverse scattering. The book is a pleasure to read as a graduate text or to dip into at leisure. It suggests a number of open problems and will be a source of inspiration for many years to come."

SIAM Review, September 1994

"This book should be on the desk of any researcher, any student, any teacher interested in scattering theory."

Mathematical Intelligencer, June 1994"

This book explores fundamental aspects of geometric network optimisation with applications to a variety of real world problems. It presents, for the first time in the literature, a cohesive mathematical framework within which the properties of such optimal interconnection networks can be understood across a wide range of metrics and cost functions. The book makes use of this mathematical theory to develop efficient algorithms for constructing such networks, with an emphasis on exact solutions. Marcus Brazil and Martin Zachariasen focus principally on the geometric structure of optimal interconnection networks, also known as Steiner trees, in the plane. They show readers how an understanding of this structure can lead to practical exact algorithms for constructing such trees. The book also details numerous breakthroughs in this area over the past 20 years, features clearly written proofs, and is supported by 135 colour and 15 black and white figures. It will help graduate students, working mathematicians, engineers and computer scientists to understand the principles required for designing interconnection networks in the plane that are as cost efficient as possible.

This book presents 13 peer-reviewed papers as written results from the 2005 workshop "Topology-Based Methods in Visualization" that was initiated to enable additional stimulation in this field. It contains a survey of the state-of-the-art, as well original work by leading experts that has not been published before, spanning both theory and applications. It captures key concepts and novel ideas and serves as an overview of current trends in its subject.

To function in modern society complex data must be absorbed and understood at a breakneck pace. The most efficient way to do this is through data-based graphics. This book is an exploration and celebration of graphical methods of data presentation.
"Visual Revelations'" principal purpose is to enlighten, inform, and amuse the reader regarding the shortcomings of common graphical practices; particularly how they can misinform while simultaneously providing models of wonderful graphics. There are many examples of the best graphic practice, graphs that go beyond conveying, facts, and structure to be able to carry emotion as well.
Aimed at an educated, lay audience, this volume benefits anyone who must either convey or receive quantitative information, including designers, statisticians, and people in the media.

In delivering lectures and writing books, we were most often forced to pay absolutely no attention to a great body of interesting results and useful algorithms appearing in numerous sources and occasionally encountered. It was absolutely that most of these re sults would finally be forgotten because it is impossible to run through the entire variety of sources where these materials could be published. Therefore, we decided to do what we can to correct this situation. We discussed this problem with Ershov and came to an idea to write an encyclopedia of algorithms on graphs focusing our main attention on the algorithms already used in programming and their generalizations or modifications. We thought that it is reasonable to group all graphs into certain classes and place the algo rithms developed for each class into a separate book. The existence of trees, i. e., a class of graphs especially important for programming, also supported this decision. This monograph is the first but, as we hope, not the last book written as part of our project. It was preceded by two books "Algorithms on Trees" (1984) and "Algorithms of Processing of Trees" (1990) small editions of which were published at the Computer Center of the Siberian Division of the Russian Academy of Sciences. The books were distributed immediately and this made out our decision to prepare a combined mono graph on the basis of these books even stronger."

This is a book about graph homomorphisms. Graph theory is now an established discipline but the study of graph homomorphisms has only recently begun to gain wide acceptance and interest. The subject gives a useful perspective in areas such as graph reconstruction, products, fractional and circular colorings, and has applications in complexity theory, artificial intelligence, telecommunication, and, most recently, statistical physics.
Based on the authors' lecture notes for graduate courses, this book can be used as a textbook for a second course in graph theory at 4th year or master's level and has been used for courses at Simon Fraser University (Vancouver), Charles University (Prague), ETH (Zurich), and UFRJ (Rio de Janeiro).
The exercises vary in difficulty. The first few are usually intended to give the reader an opportunity to practice the concepts introduced in the chapter; the later ones explore related concepts, or even introduce new ones. For the harder exercises hints and references are provided.
The authors are well known for their research in this area and the book will be invaluable to graduate students and researchers alike.