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A novel view of fitness as it relates to healthcare, which the authors don't really view as separate. Nor do they view the "mind" as separate from the body, rather arises out of it, and is a powerful tool for health and longevity.
DISCOVER A NEW OUTLOOK ON THE PROCESS OF LIFE-AND IMPROVE YOUR HEALTH AS A RESULT In Intended Evolution, authors Dongxun and Bob Zhang introduce a different perspective on the theory of evolution: Life is not only selected by nature but intentionally interacts with it, learning how to better its future. They explain that applying this idea to generally accepted principles of biology can have startling results in your ability to affect your own health-and even your evolution. According to the theory of intended evolution, organisms gather information through sensory experience and use that knowledge to effect change in themselves and their environments. The authors propose that organisms use this saved information to make choices projected to enhance their survival. It is through experience, choices, and action, within a given environment, that life changes itself from moment to moment and determines what changes are needed for future generations. Because of humans' unique ability to understand how our own evolution functions, we can effect changes within ourselves to influence and enhance our health and fitness, even to lengthen our lifespan.
In the big data era, increasing information can be extracted from the same source object or scene. For instance, a person can be verified based on their fingerprint, palm print, or iris information, and a given image can be represented by various types of features, including its texture, color, shape, etc. These multiple types of data extracted from a single object are called multi-view, multi-modal or multi-feature data. Many works have demonstrated that the utilization of all available information at multiple abstraction levels (measurements, features, decisions) helps to obtain more complex, reliable and accurate information and to maximize performance in a range of applications.This book provides an overview of information fusion technologies, state-of-the-art techniques and their applications. It covers a variety of essential information fusion methods based on different techniques, including sparse/collaborative representation, kernel strategy, Bayesian models, metric learning, weight/classifier methods, and deep learning. The typical applications of these proposed fusion approaches are also presented, including image classification, domain adaptation, disease detection, image restoration, etc. This book will benefit all researchers, professionals and graduate students in the fields of computer vision, pattern recognition, biometrics applications, etc. Furthermore, it offers a valuable resource for interdisciplinary research.
This is the first book offering a systematic description of tongue image analysis and processing technologies and their typical applications in computerized tongue diagnostic (CTD) systems.
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