Principles And Applications Of Socio Cognitive And Affective Computing
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Principles and Applications of Socio-Cognitive and Affective Computing by Geetha, S.,Renuka, Karthika,Phamila, Asnath Victy,N., Karthikeyan Pdf
Recent advances in socio-cognitive and affective computing require further study as countless benefits and opportunities have emerged from these innovative technologies that may be useful in a number of contexts throughout daily life. In order to ensure these technologies are appropriately utilized across sectors, the challenges and strategies for adoption as well as potential uses must be thoroughly considered. Principles and Applications of Socio-Cognitive and Affective Computing discusses several aspects of affective interactions and concepts in affective computing, the fundamentals of emotions, and emerging research and exciting techniques for bridging the emotional disparity between humans and machines, all within the context of interactions. The book also considers problem and solution guidelines emerging in cognitive computing, thus summarizing the roadmap of current machine computational intelligence techniques for affective computing. Covering a range of topics such as social interaction, robotics, and virtual reality, this reference work is crucial for scientists, engineers, industry professionals, academicians, researchers, scholars, practitioners, instructors, and students.
Antonio Fernández-Caballero,Pascual Gonzalez (editor of Socio-cognitive and affective computing),María Teresa Lopez (editor of Socio-cognitive and affective computing),Elena Navarro (editor of Socio-cognitive and affective computing)
Author : Antonio Fernández-Caballero,Pascual Gonzalez (editor of Socio-cognitive and affective computing),María Teresa Lopez (editor of Socio-cognitive and affective computing),Elena Navarro (editor of Socio-cognitive and affective computing) Publisher : Unknown Page : 244 pages File Size : 43,7 Mb Release : 2018 Category : Electronic books ISBN : 3038971995
Socio-cognitive and Affective Computing by Antonio Fernández-Caballero,Pascual Gonzalez (editor of Socio-cognitive and affective computing),María Teresa Lopez (editor of Socio-cognitive and affective computing),Elena Navarro (editor of Socio-cognitive and affective computing) Pdf
"Social cognition focuses on how people process, store, and apply information about other people and social situations. It focuses on the role that cognitive processes play in our social interactions. On the other hand, the term cognitive computing is generally used to refer to new hardware and/or software that mimics the functioning of the human brain and helps to improve human decision-making. In this sense, it is a type of computing with the goal of discovering more accurate models of how the human brain/mind senses, reasons, and responds to stimuli. Thus, Socio-Cognitive Computing should be understood as a set of theoretical interdisciplinary frameworks, methodologies, methods and hardware/software tools to model how the human brain mediates social interactions. In addition, Affective Computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects, a fundamental aspect of socio-cognitive neuroscience. It is an interdisciplinary field spanning computer science, electrical engineering, psychology, and cognitive science. Moreover, Physiological Computing is a category of technology in which electrophysiological data recorded directly from human activity are used to interface with a computing device. This technology becomes even more relevant when computing can be integrated pervasively in everyday life environments. Thus, Socio-Cognitive and Affective Computing systems should be able to adapt their behavior according to the Physiological Computing paradigm. This Special Issue on Socio-Cognitive and Affective Computing aimed at integrating these various albeit complementary fields. Proposals from researchers who use signals from the brain and/or body to infer people's intentions and psychological state in smart computing systems were welcome. Designing this kind of system requires combining knowledge and methods of ubiquitous and pervasive computing, as well as physiological data measurement and processing, with those of socio-cognitive and affective computing. Papers with a special focus on multidisciplinary approaches and multimodality were especially welcome"--Page 1.
Affective Information Processing by Jianhua Tao,Tieniu Tan Pdf
Affective information processing assigns computers the human-like capabilities of observation, interpretation and generation of affect features. It is an important topic for harmonious human-computer interaction, by increasing the quality of human-computer communication and improving the intelligence of the computer. Discussing state of art of the research in affective information processing, this book summarises key technologies researched, such as facial expression recognition, face animation, emotional speech synthesis, intelligent agent, and virtual reality. The detailed discussion covers a wide range of topics including hot topics which look to challenge and improve current research work. Written to provide an opportunity for scientists, engineers and graduate students to learn problems, solutions and technologies in the topic area, this book will provide insight and prove a valuable reference tool.
The Oxford Handbook of Affective Computing by Rafael A. Calvo,Sidney D'Mello,Jonathan Gratch,Arvid Kappas Pdf
Affective Computing is a growing multidisciplinary field encompassing computer science, engineering, psychology, education, neuroscience, and many other disciplines. It explores how affective factors influence interactions between humans and technology, how affect sensing and affect generation techniques can inform our understanding of human affect, and on the design, implementation, and evaluation of systems that intricately involve affect at their core. The Oxford Handbook of Affective Computing will help both new and experienced researchers identify trends, concepts, methodologies, and applications in this burgeouning field. The volume features 41 chapters divided into five main sections: history and theory, detection, generation, methodologies, and applications. Section One begins with a look at the makings of AC and a historical review of the science of emotion. Chapters discuss the theoretical underpinnings of AC from an interdisciplinary perspective involving the affective, cognitive, social, media, and brain sciences. Section Two focuses on affect detection or affect recognition, which is one of the most commonly investigated areas in AC. Section Three examines aspects of affect generation including the synthesis of emotion and its expression via facial features, speech, postures and gestures. Cultural issues in affect generation are also discussed. Section Four features chapters on methodological issues in AC research, including data collection techniques, multimodal affect databases, emotion representation formats, crowdsourcing techniques, machine learning approaches, affect elicitation techniques, useful AC tools, and ethical issues in AC. Finally, Section Five highlights existing and future applications of AC in domains such as formal and informal learning, games, robotics, virtual reality, autism research, healthcare, cyberpsychology, music, deception, reflective writing, and cyberpsychology. With chapters authored by world leaders in each area, The Oxford Handbook of Affective Computing is suitable for use as a textbook in undergraduate or graduate courses in AC, and will serve as a valuable resource for students, researchers, and practitioners across the globe.
Applied Affective Computing by Leimin Tian,Sharon Oviatt,Michal Muszynski,Brent Chamberlain,Jennifer Healey,Akane Sano Pdf
Affective computing is a nascent field situated at the intersection of artificial intelligence with social and behavioral science. It studies how human emotions are perceived and expressed, which then informs the design of intelligent agents and systems that can either mimic this behavior to improve their intelligence or incorporate such knowledge to effectively understand and communicate with their human collaborators. Affective computing research has recently seen significant advances and is making a critical transformation from exploratory studies to real-world applications in the emerging research area known as applied affective computing. This book offers readers an overview of the state-of-the-art and emerging themes in affective computing, including a comprehensive review of the existing approaches to affective computing systems and social signal processing. It provides in-depth case studies of applied affective computing in various domains, such as social robotics and mental well-being. It also addresses ethical concerns related to affective computing and how to prevent misuse of the technology in research and applications. Further, this book identifies future directions for the field and summarizes a set of guidelines for developing next-generation affective computing systems that are effective, safe, and human-centered. For researchers and practitioners new to affective computing, this book will serve as an introduction to the field to help them in identifying new research topics or developing novel applications. For more experienced researchers and practitioners, the discussions in this book provide guidance for adopting a human-centered design and development approach to advance affective computing.
Affect and Emotion in Human-Computer Interaction by Christian Peter,Russell Beale Pdf
Affect and emotion play an important role in our everyday lives: They are present whatever we do, wherever we are, and wherever we go, without us being aware of them for much of the time. When it comes to interaction, be it with humans, technology, or humans via technology, we suddenly become more aware of emotion, either by seeing the other’s emotional expression, or by not getting an emotional response while anticipating one. Given this, it seems only sensible to explore affect and emotion in human-computer interaction, to investigate the underlying principles, to study the role they play, to develop methods to quantify them, and to finally build applications that make use of them. This is the research field for which, over ten years ago, Rosalind Picard coined the phrase "affective computing". The present book provides an account of the latest work on a variety of aspects related to affect and emotion in human-technology interaction. It covers theoretical issues, user experience and design aspects as well as sensing issues, and reports on a number of affective applications that have been developed in recent years.
Affective Computing and Interaction: Psychological, Cognitive and Neuroscientific Perspectives by Gkay, Didem,Yildirim, Glsen Pdf
Since interactions may occur between animals, humans, or computational agents, an interdisciplinary approach which investigates foundations of affective communication in a variety of platforms is indispensable. In the field of affective computing, a collection of research, merging decades of research on emotions in psychology, cognition and neuroscience will inspire creative future research projects and contribute to the prosperity of this emerging field. Affective Computing and Interaction: Psychological, Cognitive and Neuroscientific Perspectives examines the current state and the future prospects of affect in computing within the context of interactions. Uniting several aspects of affective interactions and topics in affective computing, this reference reviews basic foundations of emotions, furthers an understanding of the contribution of affect to our lives and concludes by revealing current trends and promising technologies for reducing the emotional gap between humans and machines, all within the context of interactions.
Advances in Virtual Agents and Affective Computing for the Understanding and Remediation of Social Cognitive Disorders by Eric Brunet-Gouet,Ali Oker,Jean-Claude Martin,Ouriel Grynszpan,Philip L. Jackson Pdf
Advances in modern sciences occur thanks to within-fields discoveries as well as confrontation of concepts and methods from separated, sometimes distant, domains of knowledge. For instance, the fields of psychology and psychopathology benefited from accumulated contributions from cognitive neurosciences, which, in turn, received insights from molecular chemistry, cellular biology, physics (neuroimaging), statistics and computer sciences (data processing), etc. From the results of these researches, one can argue that among the numerous cognitive phenomena supposedly involved in the emergence the human intelligence and organized behavior, some of them are specific to the social nature of our phylogenetic order. Scientific reductionism allowed to divide the social cognitive system into several components, i.e. emotion processing and regulation, mental state inference (theory of mind), agency, etc. New paradigms were progressively designed to investigate these processes within highly-controlled laboratory settings. Moreover, the related constructs were successful at better understanding psychopathological conditions such as autism and schizophrenia, with partial relationships with illness outcomes. Here, we would like to outline the parallel development of concepts in social neurosciences and in other domains such as computer science, affective computing, virtual reality development, and even hardware technologies. While several researchers in neurosciences pointed out the necessity to consider naturalistic social cognition (Zaki and Ochsner, Ann N Y Acad Sci 1167, 16-30, 2009), the second person perspective (Schilbach et al., Behav Brain Sci 36(4), 393-414, 2013) and reciprocity (de Bruin et al., Front Hum Neurosci 6, 151, 2012), both computer and software developments allowed more and more realistic real-time models of our environment and of virtual humans capable of some interaction with users. As noted at the very beginning of this editorial, a new convergence between scientific disciplines might occur from which it is tricky to predict the outcomes in terms of new concepts, methods and uses. Although this convergence is motivated by the intuition that it fits well ongoing societal changes (increasing social demands on computer technologies, augmenting funding), it comes with several difficulties for which the current Frontiers in’ topic strives to bring some positive answers, and to provide both theoretical arguments and experimental examples. The first issue is about concepts and vocabulary as the contributions described in the following are authored by neuroscientists, computer scientists, psychopathologists, etc. A special attention was given during the reviewing process to stay as close as possible to the publication standards in psychological and health sciences, and to avoid purely technical descriptions. The second problem concerns methods: more complex computerized interaction models results in unpredictable and poorly controlled experiments. In other words, the assets of naturalistic paradigms may be alleviated by the difficulty to match results between subjects, populations, conditions. Of course, this practical question is extremely important for investigating pathologies that are associated with profoundly divergent behavioral patterns. Some of the contributions of this topic provide description of strategies that allowed to solve these difficulties, at least partially. The last issue is about heterogeneity of the objectives of the researches presented here. While selection criteria focused on the use of innovative technologies to assess or improve social cognition, the fields of application of this approach were quite unexpected. In an attempt to organize the contributions, three directions of research can be identified: 1) how innovation in methods might improve understanding and assessment of social cognition disorders or pathology? 2) within the framework of cognitive behavioral psychotherapies (CBT), how should we consider the use of virtual reality or augmented reality? 3) which are the benefits of these techniques for investigating severe mental disorders (schizophrenia or autism) and performing cognitive training? The first challenging question is insightfully raised in the contribution of Timmermans and Schilbach (2014) giving orientations for investigating alterations of social interaction in psychiatric disorders by the use of dual interactive eye tracking with virtual anthropomorphic avatars. Joyal, Jacob and collaborators (2014) bring concurrent and construct validities of a newly developed set of virtual faces expressing six fundamental emotions. The relevance of virtual reality was exemplified with two contributions focusing on anxiety related phenomena. Jackson et al. (2015) describe a new environment allowing to investigate empathy for dynamic FACS-coded facial expressions including pain. Based on a systematic investigation of the impact of social stimuli modalities (visual, auditory), Ruch and collaborators are able to characterize the specificity of the interpretation of laughter in people with gelotophobia (2014). On the issue of social anxiety, Aymerich-Franch et al. (2014) presented two studies in which public speaking anxiety has been correlated with avatars’ similarity of participants’ self-representations. The second issue focuses on how advances in virtual reality may benefit to cognitive and behavioral therapies in psychiatry. These interventions share a common framework that articulates thoughts, feelings or emotions and behaviors and proposes gradual modification of each of these levels thanks to thought and schema analysis, stress reduction procedures, etc. They were observed to be somehow useful for the treatment of depression, stress disorders, phobias, and are gaining some authority in personality disorders and addictions. The main asset of new technologies is the possibility to control the characteristics of symptom-eliciting stimuli/situations, and more precisely the degree to which immersion is enforced. For example, Baus and Bouchard (2014) provide a review on the extension of virtual reality exposure-based therapy toward recently described augmented reality exposure-based therapy in individuals with phobias. Concerning substance dependence disorders, Hone-Blanchet et collaborators (2014) present another review on how virtual reality can be an asset for both therapy and craving assessment stressing out the possibilities to simulate social interactions associated with drug seeking behaviors and even peers’ pressure to consume. The last issue this Frontiers’ topic deals with encompasses the questions raised by social cognitive training or remediation in severe and chronic mental disorders (autistic disorders, schizophrenia). Here, therapies are based on drill and practice or strategy shaping procedures, and, most of the time, share an errorless learning of repeated cognitive challenges. Computerized methods were early proposed for that they do, effortlessly and with limited costs, repetitive stimulations. While, repetition was incompatible with realism in the social cognitive domain, recent advances provide both immersion and full control over stimuli. Georgescu and al. (2014) exhaustively reviews the use of virtual characters to assess and train non-verbal communication in high-functioning autism (HFA). Grynszpan and Nadel (2015) present an original eye-tracking method to reveal the link between gaze patterns and pragmatic abilities again in HFA. About schizophrenia, Oker and collaborators (2015) discuss and report some insights on how an affective and reactive virtual agents might be useful to assess and remediate several defects of social cognitive disorders. About assessment within virtual avatars on schizophrenia, Park et al., (2014) focused on effect of perceived intimacy on social decision making with schizophrenia patients. Regarding schizophrenia remediation, Peyroux and Franck (2014) presented a new method named RC2S which is a cognitive remediation program to improve social cognition in schizophrenia and related disorders. To conclude briefly, while it is largely acknowledged that social interaction can be studied as a topic of its own, all the contributions demonstrate the added value of expressive virtual agents and affective computing techniques for the experimentation. It also appears that the use of virtual reality is at the very beginning of a new scientific endeavor in cognitive sciences and medicine.
A Blueprint for Affective Computing by Klaus R. Scherer,Tanja Bänziger,Etienne Roesch Pdf
'Affective computing' is a branch of computing concerned with the theory and construction of machines which can detect, respond to, and simulate human emotional states. This book presents an interdisciplinary exploration of this rapidly expanding field, aimed at those in psychology, computational neuroscience, computer science, and AI.
Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence by Chowdhary, Chiranji Lal Pdf
Emotional intelligence has emerged as an important area of research in the artificial intelligence field as it covers a wide range of real-life domains. Though machines may never need all the emotional skills that people need, there is evidence to suggest that machines require at least some of these skills to appear intelligent when interacting with people. To understand how deep learning-based emotional intelligence can be applied and utilized across industries, further study on its opportunities and future directions is required. Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence explores artificial intelligence applications, such as machine and deep learning, in emotional intelligence and examines their use towards attaining emotional intelligence acceleration and augmentation. It provides research on tools used to simplify and streamline the formation of deep learning for system architects and designers. Covering topics such as data analytics, deep learning, knowledge management, and virtual emotional intelligence, this reference work is ideal for computer scientists, engineers, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.
Artificial Intelligence Applications in Agriculture and Food Quality Improvement by Khan, Mohammad Ayoub,Khan, Rijwan,Praveen, Pushkar Pdf
Food is a necessary aspect of human life, and agriculture is crucial to any country’s global economy. Because the food business is essential to both a country’s economy and global economy, artificial intelligence (AI)-based smart solutions are needed to assure product quality and food safety. The agricultural sector is constantly under pressure to boost crop output as a result of population growth. This necessitates the use of AI applications. Artificial Intelligence Applications in Agriculture and Food Quality Improvement discusses the application of AI, machine learning, and data analytics for the acceleration of the agricultural and food sectors. It presents a comprehensive view of how these technologies and tools are used for agricultural process improvement, food safety, and food quality improvement. Covering topics such as diet assessment research, crop yield prediction, and precision farming, this premier reference source is an essential resource for food safety professionals, quality assurance professionals, agriculture specialists, crop managers, agricultural engineers, food scientists, computer scientists, AI specialists, students, libraries, government officials, researchers, and academicians.
Intelligent Solutions for Cognitive Disorders by Jadhav, Dipti,Chavan, Pallavi Vijay,Chaudhari, Sangita,Williams, Idongesit Pdf
Cognitive disorders are a growing concern, affecting individuals across the age spectrum and society. These disorders can profoundly disrupt daily life, and their timely diagnosis is crucial for effective intervention and care. As the prevalence of cognitive disorders continues to rise, the need for precise and early diagnosis has never been more pressing. Intelligent Solutions for Cognitive Disorders is a research-based book which delves into the intersection of medical science and technology, exploring the latest advancements in cognitive disorder diagnosis and treatment. This book assembles a multidisciplinary team of experts, including researchers, clinicians, and technologists, to address this challenge head-on. This book commences with an in-depth introduction to cognitive disorders, providing a solid foundation for readers of all backgrounds. It then navigates the role of intelligent systems in cognitive healthcare, unveiling the potential of artificial intelligence, machine learning, and deep learning techniques. The book highlights how these intelligent systems can enable the early and accurate detection of cognitive disorders, a pivotal factor in improving patients' quality of life. This book is an invaluable resource for technologists, researchers, linguists, data scientists, healthcare practitioners, medical professionals, and students seeking a comprehensive understanding of cognitive disorders and the role of intelligent technologies in their diagnosis and care.
Deep Learning Research Applications for Natural Language Processing by Ashok Kumar, L.,Karthika Renuka, Dhanaraj,Geetha, S. Pdf
Humans have the most advanced method of communication, which is known as natural language. While humans can use computers to send voice and text messages to each other, computers do not innately know how to process natural language. In recent years, deep learning has primarily transformed the perspectives of a variety of fields in artificial intelligence (AI), including speech, vision, and natural language processing (NLP). The extensive success of deep learning in a wide variety of applications has served as a benchmark for the many downstream tasks in AI. The field of computer vision has taken great leaps in recent years and surpassed humans in tasks related to detecting and labeling objects thanks to advances in deep learning and neural networks. Deep Learning Research Applications for Natural Language Processing explains the concepts and state-of-the-art research in the fields of NLP, speech, and computer vision. It provides insights into using the tools and libraries in Python for real-world applications. Covering topics such as deep learning algorithms, neural networks, and advanced prediction, this premier reference source is an excellent resource for computational linguists, software engineers, IT managers, computer scientists, students and faculty of higher education, libraries, researchers, and academicians.
Convergence of Deep Learning and Internet of Things: Computing and Technology by Kavitha, T.,Senbagavalli, G.,Koundal, Deepika,Guo, Yanhui,Jain, Deepak Pdf
Digital technology has enabled a number of internet-enabled devices that generate huge volumes of data from different systems. This large amount of heterogeneous data requires efficient data collection, processing, and analytical methods. Deep Learning is one of the latest efficient and feasible solutions that enable smart devices to function independently with a decision-making support system. Convergence of Deep Learning and Internet of Things: Computing and Technology contributes to technology and methodology perspectives in the incorporation of deep learning approaches in solving a wide range of issues in the IoT domain to identify, optimize, predict, forecast, and control emerging IoT systems. Covering topics such as data quality, edge computing, and attach detection and prediction, this premier reference source is a comprehensive resource for electricians, communications specialists, mechanical engineers, civil engineers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.
