Sensor Fusion - Foundation and Applications comprehensively covers the foundation and applications of sensor fusion. This book provides some novel ideas, theories, and solutions related to the research areas in the field of sensor fusion. The book explores some of the latest practices and research works in the area of sensor fusion. The book contains chapters with different methods of sensor fusion for different engineering as well as non-engineering applications. Advanced applications of sensor fusion in the areas of mobile robots, automatic vehicles, airborne threats, agriculture, medical field and intrusion detection are covered in this book. Sufficient evidences and analyses have been provided in the chapter to show the effectiveness of sensor fusion in various applications. This book would serve as an invaluable reference for professionals involved in various applications of sensor fusion.
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This book addresses the unprecedented convergence between the digital and the corporeal in the life sciences and turns to Foucault’s biopolitics in order to understand how life is being turned into a technological object. It examines a wide range of bioscientific knowledge practices that allow life to be known through codes that can be shared (copied), owned (claimed, and managed) and optimised (remade through codes based on standard language and biotech engineering visions).
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Genome-wide association studies (GWAS) for complex disorders with large case-control populations have been performed on hundreds of traits in more than 1200 published studies (http://www.genome.gov/gwastudies/) but the variants detected by GWAS account for little of the heritability of these traits, leading to an increasing interest in using family based designs. While GWAS studies are designed to find common variants with low to moderate attributable risks, family based studies are expected to find rare variants with high attributable risk. Because family-based designs can better control both genetic and environmental background, this study design is robust to heterogeneity and population stratification. Moreover, in family-based analysis, the background genetic variation can be modeled to control the residual variance which could increase the power to identify disease associated rare variants. Analysis of families can also help us gain knowledge about disease transmission and inheritance patterns. Although a family-based design has the advantage of being robust to false positives, novel and powerful methods to analyze families in genetic epidemiology continue to be needed, especially for the interaction between genetic and environmental factors associated with disease. Moreover, with the rapid development of sequencing technology, advances in approaches to the design and analysis of sequencing data in families are also greatly needed. The 11 articles in this book all introduce new methodology and, using family data, substantial new findings are presented in the areas of infectious diseases, diabetes, eye traits, autism spectrum disorder and prostate cancer.