This book provides a comprehensive overview of different biomedical data types, including both clinical and genomic data. Thorough explanations enable readers to explore key topics ranging from electrocardiograms to Big Data health mining and EEG analysis techniques. Each chapter offers a summary of the field and a sample analysis. Also covered are telehealth infrastructure, healthcare information association rules, methods for mass spectrometry imaging, environmental biodiversity, and the global nonlinear fitness function for protein structures. Diseases are addressed in chapters on functional annotation of lncRNAs in human disease, metabolomics characterization of human diseases, disease risk factors using SNP data and Bayesian methods, and imaging informatics for diagnostic imaging marker selection. With the exploding accumulation of Electronic Health Records (EHRs), there is an urgent need for computer-aided analysis of heterogeneous biomedical datasets. Biomedical data is notorious for its diversified scales, dimensions, and volumes, and requires interdisciplinary technologies for visual illustration and digital characterization. Various computer programs and servers have been developed for these purposes by both theoreticians and engineers. This book is an essential reference for investigating the tools available for analyzing heterogeneous biomedical data. It is designed for professionals, researchers, and practitioners in biomedical engineering, diagnostics, medical electronics, and related industries.

The development of polynomial-elimination techniques from classical theory to modern algorithms has undergone a tortuous and rugged path. This can be observed L. van der Waerden's elimination of the "elimination theory" chapter from from B. his classic Modern Algebra in later editions, A. Weil's hope to eliminate "from algebraic geometry the last traces of elimination theory," and S. Abhyankar's sug gestion to "eliminate the eliminators of elimination theory. " The renaissance and recognition of polynomial elimination owe much to the advent and advance of mod ern computing technology, based on which effective algorithms are implemented and applied to diverse problems in science and engineering. In the last decade, both theorists and practitioners have more and more realized the significance and power of elimination methods and their underlying theories. Active and extensive research has contributed a great deal of new developments on algorithms and soft ware tools to the subject, that have been widely acknowledged. Their applications have taken place from pure and applied mathematics to geometric modeling and robotics, and to artificial neural networks. This book provides a systematic and uniform treatment of elimination algo rithms that compute various zero decompositions for systems of multivariate poly nomials. The central concepts are triangular sets and systems of different kinds, in terms of which the decompositions are represented. The prerequisites for the concepts and algorithms are results from basic algebra and some knowledge of algorithmic mathematics."

There seems to be no doubt that geometry originates from such practical activ ities as weather observation and terrain survey. But there are different manners, methods, and ways to raise the various experiences to the level of theory so that they finally constitute a science. F. Engels said, "The objective of mathematics is the study of space forms and quantitative relations of the real world. " Dur ing the time of the ancient Greeks, there were two different methods dealing with geometry: one, represented by the Euclid's "Elements," purely pursued the logical relations among geometric entities, excluding completely the quantita tive relations, as to establish the axiom system of geometry. This method has become a model of deduction methods in mathematics. The other, represented by the relevant work of Archimedes, focused on the study of quantitative re lations of geometric objects as well as their measures such as the ratio of the circumference of a circle to its diameter and the area of a spherical surface and of a parabolic sector. Though these approaches vary in style, have their own features, and reflect different viewpoints in the development of geometry, both have made great contributions to the development of mathematics. The development of geometry in China was all along concerned with quanti tative relations."

With a pioneering methodology, the book covers the fundamental aspects of kinematic analysis and synthesis of linkage, and provides a theoretical foundation for engineers and researchers in mechanisms design. The first book to propose a complete curvature theory for planar, spherical and spatial motion Treatment of the synthesis of linkages with a novel approach Well-structured format with chapters introducing clearly distinguishable concepts following in a logical sequence dealing with planar, spherical and spatial motion Presents a pioneering methodology by a recognized expert in the field and brought up to date with the latest research and findings Fundamental theory and application examples are supplied fully illustrated throughout

How can we engineer systems capable of "cocktail party" listening?

Human listeners are able to perceptually segregate one sound source from an acoustic mixture, such as a single voice from a mixture of other voices and music at a busy cocktail party. How can we engineer "machine listening" systems that achieve this perceptual feat?

Albert Bregman's book Auditory Scene Analysis, published in 1990, drew an analogy between the perception of auditory scenes and visual scenes, and described a coherent framework for understanding the perceptual organization of sound. His account has stimulated much interest in computational studies of hearing. Such studies are motivated in part by the demand for practical sound separation systems, which have many applications including noise-robust automatic speech recognition, hearing prostheses, and automatic music transcription. This emerging field has become known as computational auditory scene analysis (CASA).

Computational Auditory Scene Analysis: Principles, Algorithms, and Applications provides a comprehensive and coherent account of the state of the art in CASA, in terms of the underlying principles, the algorithms and system architectures that are employed, and the potential applications of this exciting new technology. With a Foreword by Bregman, its chapters are written by leading researchers and cover a wide range of topics including: Estimation of multiple fundamental frequenciesFeature-based and model-based approaches to CASASound separation based on spatial locationProcessing for reverberant environmentsSegregation of speech and musical signalsAutomatic speech recognition in noisy environmentsNeural and perceptual modeling of auditory organization

The text is written at a level that will be accessible to graduate students and researchers from related science and engineering disciplines. The extensive bibliography accompanying each chapter will also make this book a valuable reference source. A web site accompanying the text, http: //www.casabook.org, features software tools and sound demonstrations.

IJCNN is the flagship conference of the INNS, as well as the IEEE Neural Networks Society. It
has arguably been the preeminent conference in the field, even as neural network conferences
have proliferated and specialized. As the number of conferences has grown, its strongest
competition has migrated away from an emphasis on neural networks. IJCNN has embraced the
proliferation of spin-off and related fields (see the topic list, below), while maintaining a core
emphasis befitting its name. It has also succeeded in enforcing an emphasis on quality.