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Challenges and trends in multimodal fall detection for healthcare
(Springer Books, 2020)
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HIRAM EREDIN PONCE ESPINOSA;376768
This book focuses on novel implementations of sensor technologies, artificial intelligence, machine learning, computer vision and statistics for automated, human fall recognition systems and related topics using data fusion. It includes theory and coding implementations to help readers quickly grasp the concepts and to highlight the applicability of this technology. For convenience, it is divided into two parts. The first part reviews the state of the art in human fall and activity recognition systems, while the second part describes a public dataset especially curated for multimodal fall detection. It also gathers contributions demonstrating the use of this dataset and showing examples. This book is useful for anyone who is interested in fall detection systems, as well as for those interested in solving challenging, signal recognition, vision and machine learning problems. Potential applications include health care, robotics, sports, human–machine interaction, among others.
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Nature-inspired computing for control systems
(Springer, 2016)
The book presents recent advances in nature-inspired computing, giving a special emphasis to control systems applications. It reviews different techniques used for simulating physical, chemical, biological or social phenomena at the purpose of designing robust, predictive and adaptive control strategies. The book is a collection of several contributions, covering either more general approaches in control systems, or methodologies for control tuning and adaptive controllers, as well as exciting applications of nature-inspired techniques in robotics. On one side, the book is expected to motivate readers with a background in conventional control systems to try out these powerful techniques inspired by nature. On the other side, the book provides advanced readers with a deeper understanding of the field and a broad spectrum of different methods and techniques. All in all, the book is an outstanding, practice-oriented reference guide to nature-inspired computing addressing graduate students, researchers and practitioners in the field of control engineering. ©2016 © 2022 Springer Nature Switzerland AG. Part of Springer Nature.
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Ultrafine-grain Steels: Mechanical Behavior
(2016)
Quintana Hernández, María José
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MARÍA JOSÉ QUINTANA HERNÁNDEZ;576914
In recent years, both the steelmaking industry and laboratories in different parts of the world, have shown an increasing interest in reaching an industrial-level production of ultrafine grained steels (also known as ultrafine ferrite), which have a grain size d lower than 5 μm, and enhanced mechanical resistance and fracture toughness. At room temperature, the capacity of the material to be deformed during bending or drawing operations (typical of requirements for automotive parts applications) depends on the interaction of a hard and a soft phase in the microstructure. On the other hand, at high temperatures, these steels may show superplastic behavior if deformed at a precise combination of temperature and strain rate.
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