Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics

Presents the state of the technology and points to future directions for semantic computing Semantic computing, a rapidly evolving interdisciplinary field, seeks to structure, design, and manipulate computer content to better satisfy the needs and intentions of users and create a more meaningful user experience. This remarkable contributed work examines the art, engineering, technology, and applications of the field. Moreover, it brings together researchers from such disciplines as natural language processing, software engineering, multimedia semantics, semantic Web, signal processing, and pattern recognition in order to provide a single source that presents the state of the technology and points to new breakthroughs on the horizon. Semantic Computing begins with an introduction that explores the concepts, technology, applications, and future of semantic computing. Next, the book is divided into four parts: Part One: Semantic Analysis Part Two: Semantic Languages and Integration Part Three: Semantic Applications Part Four: Semantic Programming and Interface As readers progress through the book, they'll learn not only the underlying science, but also the fundamental technological building blocks of semantic computing. Moreover, they'll discover a variety of cross-disciplinary solutions to current computing and communication problems. Throughout the book, references to the primary literature enable further investigation of each individual topic. Semantic Computing is ideal for industrial managers, researchers, and engineers seeking to design the next generation of computing systems in order to better meet user needs. It is also recommended as a textbook for senior undergraduate and graduate-level semantic computing courses.

Presenting a holistic and thoroughly practical investigation of the true nature of computer games that arms readers with a small yet powerful set of theories for developing unique approaches to understanding games. Game Invaders fully integrates genre theory, new media aesthetics, perceptual opportunities, and semiotics into a practical DIY toolkit for games analysis—offering detailed guidance for how to conduct in-depth critiques of game content and gameplay. Featuring an informal and witty writing style, the book devotes a number of chapters to specific games from all eras, clearly demonstrating the practical application of the theories to modern, large-scale computer games. Readers will find: • Suggestions on how to apply the DIY package to major issues central to understanding computer games and their design • Coverage of the semiotics of video games, laying the foundation for such topics as the role of agency and virtual storytelling • Tasks and solutions for readers wishing to practice techniques introduced in the book • A companion website featuring access to an app that enables the reader to conduct their own activity profiling of games An important resource for those wishing to dig deeper into the games they design, Game Invaders gives game designers the skills they need to stand out from the crowd. It is also a valuable guide for anyone wishing to learn more about computer games, virtual reality, and new media.

A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies The book presents an overview of Blind Source Separation, a relatively new signal processing method. Due to the multidisciplinary nature of the subject, the book has been written so as to appeal to an audience from very different backgrounds. Basic mathematical skills (e.g. on matrix algebra and foundations of probability theory) are essential in order to understand the algorithms, although the book is written in an introductory, accessible style. This book offers a general overview of the basics of Blind Source Separation, important solutions and algorithms, and in-depth coverage of applications in image feature extraction, remote sensing image fusion, mixed-pixel decomposition of SAR images, image object recognition fMRI medical image processing, geochemical and geophysical data mining, mineral resources prediction and geoanomalies information recognition. Firstly, the background and theory basics of blind source separation are introduced, which provides the foundation for the following work. Matrix operation, foundations of probability theory and information theory basics are included here. There follows the fundamental mathematical model and fairly new but relatively established blind source separation algorithms, such as Independent Component Analysis (ICA) and its improved algorithms (Fast ICA, Maximum Likelihood ICA, Overcomplete ICA, Kernel ICA, Flexible ICA, Non-negative ICA, Constrained ICA, Optimised ICA). The last part of the book considers the very recent algorithms in BSS e.g. Sparse Component Analysis (SCA) and Non-negative Matrix Factorization (NMF). Meanwhile, in-depth cases are presented for each algorithm in order to help the reader understand the algorithm and its application field. A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies Presents new improved algorithms aimed at different applications, such as image feature extraction, remote sensing image fusion, mixed-pixel decomposition of SAR images, image object recognition, and MRI medical image processing With applications in geochemical and geophysical data mining, mineral resources prediction and geoanomalies information recognition Written by an expert team with accredited innovations in blind source separation and its applications in natural science Accompanying website includes a software system providing codes for most of the algorithms mentioned in the book, enhancing the learning experience Essential reading for postgraduate students and researchers engaged in the area of signal processing, data mining, image processing and recognition, information, geosciences, life sciences.

3D Face Modeling, Analysis and Recognition presents methodologies for analyzing shapes of facial surfaces, develops computational tools for analyzing 3D face data, and illustrates them using state-of-the-art applications. The methodologies chosen are based on efficient representations, metrics, comparisons, and classifications of features that are especially relevant in the context of 3D measurements of human faces. These frameworks have a long-term utility in face analysis, taking into account the anticipated improvements in data collection, data storage, processing speeds, and application scenarios expected as the discipline develops further. The book covers face acquisition through 3D scanners and 3D face pre-processing, before examining the three main approaches for 3D facial surface analysis and recognition: facial curves; facial surface features; and 3D morphable models. Whilst the focus of these chapters is fundamentals and methodologies, the algorithms provided are tested on facial biometric data, thereby continually showing how the methods can be applied. Key features: • Explores the underlying mathematics and will apply these mathematical techniques to 3D face analysis and recognition • Provides coverage of a wide range of applications including biometrics, forensic applications, facial expression analysis, and model fitting to 2D images • Contains numerous exercises and algorithms throughout the book

Image processing and image analysis are typically important fields in information science and technology. By “image processing”, we generally understand all kinds of operation performed on images (or sequences of images) in order to increase their quality, restore their original content, emphasize some particular aspect of the information or optimize their transmission, or to perform radiometric and/or spatial analysis. By “image analysis” we understand, however, all kinds of operation performed on images (or sequences of images) in order to extract qualitative or quantitative data, perform measurements and apply statistical analysis. Whereas there are nowadays many books dealing with image processing, only a small number deal with image analysis. The methods and techniques involved in these fields of course have a wide range of applications in our daily world: industrial vision, material imaging, medical imaging, biological imaging, multimedia applications, satellite imaging, quality control, traffic control, and so on