Human Computer Interaction And Augmented Intelligence
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Human-Computer Interaction and Augmented Intelligence
This book explores the transformative roles of human-computer interaction (HCI) and augmented intelligence (AI) in shaping intelligent systems. HCI focuses on designing interactive systems that enhance human-technology relationships, while AI empowers users with adaptive, data-driven tools that complement decision-making. Together, these fields drive innovation, creating systems that are efficient, intuitive, and inclusive, addressing diverse user needs across various domains. Central to this work is the paradigm of interactive machine learning (IML), which builds on HCI and AI principles to create adaptive systems capable of evolving in real-time. The book highlights the application of IML in educational software, demonstrating how dynamic, personalized, and responsive learning environments can enhance student engagement and success. It provides detailed case studies and practical examples that showcase how IML aligns educational content, feedback, and interactions with learner behaviors and preferences. Additionally, it includes numerous Python code implementations and actionable design strategies, making these concepts accessible to practitioners and researchers alike. Key topics include leveraging cognitive and communication styles to shape adaptive systems, integrating learning models to enhance personalization, and addressing ethical considerations such as data privacy and algorithmic fairness. Readers will also discover discussions on creating personalized tutoring systems, collaborative platforms, and immersive environments that redefine educational technology. This book is a valuable resource for researchers, software developers, educators, instructional designers, and technologists at the intersection of human-computer interaction, augmented intelligence, and educational innovation. With its comprehensive framework and practical insights, it offers the tools to design adaptive, inclusive, and impactful learning systems for the future.
Advanced Soft Computing Techniques in Data Science, IoT and Cloud Computing
This book plays a significant role in improvising human life to a great extent. The new applications of soft computing can be regarded as an emerging field in computer science, automatic control engineering, medicine, biology application, natural environmental engineering, and pattern recognition. Now, the exemplar model for soft computing is human brain. The use of various techniques of soft computing is nowadays successfully implemented in many domestic, commercial, and industrial applications due to the low-cost and very high-performance digital processors and also the decline price of the memory chips. This is the main reason behind the wider expansion of soft computing techniques and its application areas. These computing methods also play a significant role in the design and optimization in diverse engineering disciplines. With the influence and the development of the Internet of things (IoT) concept, the need for using soft computing techniques has become more significant than ever. In general, soft computing methods are closely similar to biological processes than traditional techniques, which are mostly based on formal logical systems, such as sentential logic and predicate logic, or rely heavily on computer-aided numerical analysis. Soft computing techniques are anticipated to complement each other. The aim of these techniques is to accept imprecision, uncertainties, and approximations to get a rapid solution. However, recent advancements in representation soft computing algorithms (fuzzy logic,evolutionary computation, machine learning, and probabilistic reasoning) generate a more intelligent and robust system providing a human interpretable, low-cost, approximate solution. Soft computing-based algorithms have demonstrated great performance to a variety of areas including multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, big data analytics, time series, biomedical and health informatics, etc. Soft computing approaches such as genetic programming (GP), support vector machine–firefly algorithm (SVM-FFA), artificial neural network (ANN), and support vector machine–wavelet (SVM–Wavelet) have emerged as powerful computational models. These have also shown significant success in dealing with massive data analysis for large number of applications. All the researchers and practitioners will be highly benefited those who are working in field of computer engineering, medicine, biology application, signal processing, and mechanical engineering. This book is a good collection of state-of-the-art approaches for soft computing-based applications to various engineering fields. It is very beneficial for the new researchers and practitioners working in the field to quickly know the best performing methods. They would be able to compare different approaches and can carry forward their research in the most important area of research which has direct impact on betterment of the human life and health. This book is very useful because there is no book in the market which provides a good collection of state-of-the-art methods of soft computing-based models for multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, big data analytics, time series, and biomedical and health informatics.
Human-Computer Interaction. Interaction Technologies
The 3 volume-set LNCS 10901, 10902 + 10903 constitutes the refereed proceedings of the 20th International Conference on Human-Computer Interaction, HCI 2018, which took place in Las Vegas, Nevada, in July 2018. The total of 1171 papers and 160 posters included in the 30 HCII 2018 proceedings volumes was carefully reviewed and selected from 4346 submissions. HCI 2018 includes a total of 145 papers; they were organized in topical sections named: Part I: HCI theories, methods and tools; perception and psychological issues in HCI; emotion and attention recognition; security, privacy and ethics in HCI. Part II: HCI in medicine; HCI for health and wellbeing; HCI in cultural heritage; HCI in complex environments; mobile and wearable HCI. Part III: input techniques and devices; speech-based interfaces and chatbots; gesture, motion and eye-tracking based interaction; games and gamification.