This book is a collection of introductory, interdisciplinary articles and lectures covering the fundamentals of the maximum entropy approach, a powerful new technique that provides a much needed extension of the established principles of rational inference in the sciences. Maximum entropy allows the interpretation of incomplete and "noisy" data, providing a description of the underlying physical systems. It has found application in both practical and theoretical studies ranging from image enhancement to nuclear physics, and from statistical mechanics to economics. The work explores these applications with specific problems of data analysis taken from the physical sciences. It will interest all physical scientists who deal with data and its interpretation, including statisticians and statistical physicists.

Dictionary of Scientific Principles presents a unique and timeless collection of (almost) all known rules or laws commonly called principles, identified throughout the history of scientific development, their definition, and use. Exploring a broad range of disciplines, the book first lists more than 2,000 principles organized in a standard alphabetical order, then provides a list of subject headings for which related principles are identified. A staple addition to every library, the dictionary will also be of interest to scientists and general readers.

This pioneering graduate textbook provides readers with the concepts and practical tools required to understand the maximum entropy principle, and apply it to an understanding of ecological patterns. Rather than building and combining mechanistic models of ecosystems, the approach is grounded in information theory and the logic of inference. Paralleling the derivation of thermodynamics from the maximum entropy principle, the state variable theory of ecology developed in this book predicts realistic forms for all metrics of ecology that describe patterns in the distribution, abundance, and energetics of species over multiple spatial scales, a wide range of habitats, and diverse taxonomic groups. The first part of the book is foundational, discussing the nature of theory, the relationship of ecology to other sciences, and the concept of the logic of inference. Subsequent sections present the fundamentals of macroecology and of maximum information entropy, starting from first principles. The core of the book integrates these fundamental principles, leading to the derivation and testing of the predictions of the maximum entropy theory of ecology (METE). A final section broadens the book's perspective by showing how METE can help clarify several major issues in conservation biology, placing it in context with other theories and highlighting avenues for future research.

An account of the maximum entropy method and the related Bayesian probability theory, which are used to resolve the true structures underlying many types of data. The text aims to explain the role that entropy plays in the assignment of probabilities.

The two-volume proceedings of the ACIIDS 2016 conference, LNAI 9621 + 9622, constitutes the refereed proceedings of the 8th Asian Conference on Intelligent Information and Database Systems, held in Da Nang, Vietnam, in March 2016. The total of 153 full papers accepted for publication in these proceedings was carefully reviewed and selected from 392 submissions. They were organized in topical sections named: knowledge engineering and semantic Web; social networks and recommender systems; text processing and information retrieval; database systems and software engineering; intelligent information systems; decision support and control systems; machine learning and data mining; computer vision techniques; intelligent big data exploitation; cloud and network computing; multiple model approach to machine learning; advanced data mining techniques and applications; computational intelligence in data mining for complex problems; collective intelligence for service innovation, technology opportunity, e-learning, and fuzzy intelligent systems; analysis for image, video and motion data in life sciences; real world applications in engineering and technology; ontology-based software development; intelligent and context systems; modeling and optimization techniques in information systems, database systems and industrial systems; smart pattern processing for sports; and intelligent services for smart cities.

"Foundations of Intelligent Systems" presents selected papers from the 2013 International Conference on Intelligent Systems and Knowledge Engineering (ISKE2013). The aim of this conference is to bring together experts from different expertise areas to discuss the state-of-the-art in Intelligent Systems and Knowledge Engineering, and to present new research results and perspectives on future development. The topics in this volume include, but not limited to: Artificial Intelligence Theories, Pattern Recognition, Intelligent System Models, Speech Recognition, Computer Vision, Multi-Agent Systems, Machine Learning, Soft Computing and Fuzzy Systems, Biological Inspired Computation, Game Theory, Cognitive Systems and Information Processing, Computational Intelligence, etc. The proceedings are benefit for both researchers and practitioners who want to utilize intelligent methods in their specific research fields. Dr. Zhenkun Wen is a Professor at the College of Computer and Software Engineering, Shenzhen University, China. Dr. Tianrui Li is a Professor at the School of Information Science and Technology, Southwest Jiaotong University, Xi’an, China.