Explores problems of information and learning theory, using tools from analytic combinatorics to analyze precise behavior of source codes.

Demonstrates how the information theory approach to experimental data can be of benefit not only to analytical chemists but to all those using these techniques in the decision making process. Deals with information-theoretic fundamentals as well as with practical aspects. Discusses the system nature of analysis which is of particular importance in multicomponent analysis.

What Every Engineer Should Know About Data-Driven Analytics provides a comprehensive introduction to the theoretical concepts and approaches of machine learning that are used in predictive data analytics. By introducing the theory and by providing practical applications, this text can be understood by every engineering discipline. It offers a detailed and focused treatment of the important machine learning approaches and concepts that can be exploited to build models to enable decision making in different domains. Utilizes practical examples from different disciplines and sectors within engineering and other related technical areas to demonstrate how to go from data, to insight, and to decision making Introduces various approaches to build models that exploits different algorithms Discusses predictive models that can be built through machine learning and used to mine patterns from large datasets Explores the augmentation of technical and mathematical materials with explanatory worked examples Includes a glossary, self-assessments, and worked-out practice exercises Written to be accessible to non-experts in the subject, this comprehensive introductory text is suitable for students, professionals, and researchers in engineering and data science.

Quantifying the Qualitative by Katya Drozdova and Kurt Taylor Gaubatz presents a systematic approach to comparative case analysis based on insights from information theory. This new method, which requires minimal quantitative skills, helps students, policymakers, professionals, and scholars learn more from comparative cases. The approach avoids the limitations of traditional statistics in the small-n context and allows analysts to systematically assess and compare the impact of a set of factors on case outcomes with easy-to-use analytics. Rigorous tools reduce bias, improve the knowledge gained from case studies, and provide straightforward metrics for effectively communicating results to a range of readers and leaders.

This book deals with various aspects of scientific numerical computing. No at tempt was made to be complete or encyclopedic. The successful solution of a numerical problem has many facets and consequently involves different fields of computer science. Computer numerics- as opposed to computer algebra- is thus based on applied mathematics, numerical analysis and numerical computation as well as on certain areas of computer science such as computer architecture and operating systems. Applied Mathemalies I I I Numerical Analysis Analysis, Algebra I I Numerical Computation Symbolic Computation I Operating Systems Computer Hardware Each chapter begins with sample situations taken from specific fields of appli cation. Abstract and general formulations of mathematical problems are then presented. Following this abstract level, a general discussion about principles and methods for the numerical solution of mathematical problems is presented. Relevant algorithms are developed and their efficiency and the accuracy of their results is assessed. It is then explained as to how they can be obtained in the form of numerical software. The reader is presented with various ways of applying the general methods and principles to particular classes of problems and approaches to extracting practically useful solutions with appropriately chosen numerical software are developed. Potential difficulties and obstacles are examined, and ways of avoiding them are discussed. The volume and diversity of all the available numerical software is tremendous.

This book constitutes the refereed proceedings of the 5th International Symposium, Latin American Theoretical Informatics, LATIN 2002, held in Cancun, Mexico, in April 2002. The 44 revised full papers presented together with a tutorial and 7 abstracts of invited contributions were carefully reviewed and selected from a total of 104 submissions. The papers presented are devoted to a broad range of topics from theoretical computer science and mathematical foundations, with a certain focus on algorithmics and computations related to discrete structures.

This book constitutes the refereed proceedings of the18th International Conference on Information Systems Security, ICISS 2022, held in Tirupati, India, during December 16–20, 2022 The 8 full papers and 5 short papers included in this book were carefully reviewed and selected from 55 submissions. They were organized in topical sections as follows: ​ostinato: cross-host attack correlation through attack activity similaritydetection; DKS-PKI: a distributed key server architecture for public keyinfrastructure;generating-set evaluation of bloom filter hardening techniques in privaterecord linkage; etc

This timely publication covers prompt measurements as well as delayed activation measurements used in chemical analysis of the elements. It describes the various possibilities of activation: neutrons, charged ions, and photons. Also discussed are the advantages and disadvantages of each activation method. These volumes are important for those in geology, archaeology, biology, analytical chemistry, radioanalytical and nuclear chemistry, the semiconductor industry, and others.