Man Machine Interactions
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Advanced Man-Machine Interaction
Contemporary man-machine interfaces are increasingly characterized by multimodality, nonintrusiveness, context-sensitivity, adaptivity, and teleoperability. The implementation of such properties relies on novel techniques in felds such as, e.g., computer vision, speech technology, trainable classifiers, robotics, and virtual reality. This book puts special emphasis on technological aspects of advanced interface implementation. Furthermore it focuses on interface design and usability. For readers with a background in engineering and computer science, most chapters offer design guidelines and case studies, as well as a description of the functioning and limitations of the algorithms required for implementation. In addition, complementary code examples in C++ are given where appropriate. As a special feature the book is accompanied by two easy-to-handle software development environments, which offer access to extensive public domain software for computer vision, classification, and virtual reality. These environments also provide real-time access to peripheral components like, e.g., webcams or microphones, enabling hands-on experimentation and testing.
The Handbook of Human-Machine Interaction
The Handbook of Human-Machine Interaction features 20 original chapters and a conclusion focusing on human-machine interaction (HMI) from analysis, design and evaluation perspectives. It offers a comprehensive range of principles, methods, techniques and tools to provide the reader with a clear knowledge of the current academic and industry practice and debate that define the field. The text considers physical, cognitive, social and emotional aspects and is illustrated by key application domains such as aerospace, automotive, medicine and defence. Above all, this volume is designed as a research guide that will both inform readers on the basics of human-machine interaction from academic and industrial perspectives and also provide a view ahead at the means through which human-centered designers, including engineers and human factors specialists, will attempt to design and develop human-machine systems.
Data Mining and Machine Learning Applications
DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.