The Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces- user input involving new media (speech, multi-touch, gestures, writing) embedded in multimodal-multisensor interfaces. These interfaces support smart phones, wearables, in-vehicle and robotic applications, and many other areas that are now highly competitive commercially. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This first volume of the handbook presents relevant theory and neuroscience foundations for guiding the development of high-performance systems. Additional chapters discuss approaches to user modeling and interface designs that support user choice, that synergistically combine modalities with sensors, and that blend multimodal input and output. This volume also highlights an in-depth look at the most common multimodal-multisensor combinations-for example, touch and pen input, haptic and non-speech audio output, and speech-centric systems that co-process either gestures, pen input, gaze, or visible lip movements. A common theme throughout these chapters is supporting mobility and individual differences among users. These handbook chapters provide walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this emerging field. In the final section of this volume, experts exchange views on a timely and controversial challenge topic, and how they believe multimodal-multisensor interfaces should be designed in the future to most effectively advance human performance.

This is an applied handbook for the application of data mining techniques in the CRM framework. It combines a technical and a business perspective to cover the needs of business users who are looking for a practical guide on data mining. It focuses on Customer Segmentation and presents guidelines for the development of actionable segmentation schemes. By using non-technical language it guides readers through all the phases of the data mining process.

The first NFT book that tells of the beginning of Crypto Art with 50 of the best artists in the movement. In the last year, crypto art has overwhelmed the world of digital art and beyond, involving collectors, museums, and auction houses, creating a fully-fledged digital revolution. It is guided by visionary artists who have promoted this unprecedented movement, with new rules, overwhelming dynamics, and innovative ways of using art. Crypto Art Begins, published by Rizzoli Italia and New York, is based on an idea and project by The NFT Magazine, the first monthly magazine to be read and collected on the blockchain Ethereum. The volume tells of this exciting movement through the history and works of 50 crypto artists including Hackatao, Refik Anadol, Kevin Abosch, Osinachi, Federico Clapis, Giant Swan, and DADA.Art who contributed to its creation and form a part of it with their NFTs (non-fungible tokens) representing the present and future of this new world.

The body of research in all aspects of Semantic Web development, design, and application continues to grow alongside new trends in the information systems community. Semantic-Enabled Advancements on the Web: Applications Across Industries reviews current and future trends in Semantic Web research with the aim of making existing and potential applications more accessible to a broader community of academics, practitioners, and industry professionals. Covering topics including recommendation systems, semantic search, and ontologies, this reference is a valuable contribution to the existing literature in this discipline.

Focused on the latest mobile technologies, this book addresses specific features (such as IoT) and their adoptions that aim to enable excellence in business in Industry 4.0. Furthermore, this book explores how the adoption of these technologies is related to rising concerns about privacy and trusted communication issues that concern management and leaders of business organizations. Managing IoT and Mobile Technologies with Innovation, Trust, and Sustainable Computing not only targets IT experts and drills down on the technical issues but also provides readers from various groups with a well-linked concept about how the latest trends of mobile technologies are closely related to daily living and the workplace at managerial and even individual levels.

Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. ""Multi-Objective Optimization in Computational Intelligence: Theory and Practice"" explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.

As enterprise access networks evolve with a larger number of mobile users, a wide range of devices and new cloud-based applications, managing user performance on an end-to-end basis has become rather challenging. Recent advances in big data network analytics combined with AI and cloud computing are being leveraged to tackle this growing problem. AI is becoming further integrated with software that manage networks, storage, and can compute. This edited book focuses on how new network analytics, IoTs and Cloud Computing platforms are being used to ingest, analyse and correlate a myriad of big data across the entire network stack in order to increase quality of service and quality of experience (QoS/QoE) and to improve network performance. From big data and AI analytical techniques for handling the huge amount of data generated by IoT devices, the authors cover cloud storage optimization, the design of next generation access protocols and internet architecture, fault tolerance and reliability in intelligent networks, and discuss a range of emerging applications. This book will be useful to researchers, scientists, engineers, professionals, advanced students and faculty members in ICTs, data science, networking, AI, machine learning and sensing. It will also be of interest to professionals in data science, AI, cloud and IoT start-up companies, as well as developers and designers.

Nature provides inspiration and guidance in the creation of techniques, applications and new technologies in the fields of Artificial Intelligence and Soft Computing. Soft Computing Methods for Practical Environment Solutions: Techniques and Studies presents various practical applications of Soft Computing techniques in real-world situations and problems, aiming to show the enormous potential of such techniques in solving all kinds of problems, and thus, providing the latest advances in these techniques in an extensive state-of-the-art and a vast theoretical study. Ideal for students studying AI and researchers familiarizing themselves with such techniques, so to offer recent and novel applications, helping expand and explore new areas of research.

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.

These proceedings presents the state-of-the-art in spoken dialog systems with applications in robotics, knowledge access and communication. It addresses specifically: 1. Dialog for interacting with smartphones; 2. Dialog for Open Domain knowledge access; 3. Dialog for robot interaction; 4. Mediated dialog (including crosslingual dialog involving Speech Translation); and,5. Dialog quality evaluation. These articles were presented at the IWSDS 2012 workshop.

The amount of new information is constantly increasing, faster than our ability to fully interpret and utilize it to improve human experiences. Addressing this asymmetry requires novel and revolutionary scientific methods and effective human and artificial intelligence interfaces. By lifting the concept of time from a positive real number to a 2D complex time (kime), this book uncovers a connection between artificial intelligence (AI), data science, and quantum mechanics. It proposes a new mathematical foundation for data science based on raising the 4D spacetime to a higher dimension where longitudinal data (e.g., time-series) are represented as manifolds (e.g., kime-surfaces). This new framework enables the development of innovative data science analytical methods for model-based and model-free scientific inference, derived computed phenotyping, and statistical forecasting. The book provides a transdisciplinary bridge and a pragmatic mechanism to translate quantum mechanical principles, such as particles and wavefunctions, into data science concepts, such as datum and inference-functions. It includes many open mathematical problems that still need to be solved, technological challenges that need to be tackled, and computational statistics algorithms that have to be fully developed and validated. Spacekime analytics provide mechanisms to effectively handle, process, and interpret large, heterogeneous, and continuously-tracked digital information from multiple sources. The authors propose computational methods, probability model-based techniques, and analytical strategies to estimate, approximate, or simulate the complex time phases (kime directions). This allows transforming time-varying data, such as time-series observations, into higher-dimensional manifolds representing complex-valued and kime-indexed surfaces (kime-surfaces). The book includes many illustrations of model-based and model-free spacekime analytic techniques applied to economic forecasting, identification of functional brain activation, and high-dimensional cohort phenotyping. Specific case-study examples include unsupervised clustering using the Michigan Consumer Sentiment Index (MCSI), model-based inference using functional magnetic resonance imaging (fMRI) data, and model-free inference using the UK Biobank data archive. The material includes mathematical, inferential, computational, and philosophical topics such as Heisenberg uncertainty principle and alternative approaches to large sample theory, where a few spacetime observations can be amplified by a series of derived, estimated, or simulated kime-phases. The authors extend Newton-Leibniz calculus of integration and differentiation to the spacekime manifold and discuss possible solutions to some of the "problems of time". The coverage also includes 5D spacekime formulations of classical 4D spacetime mathematical equations describing natural laws of physics, as well as, statistical articulation of spacekime analytics in a Bayesian inference framework. The steady increase of the volume and complexity of observed and recorded digital information drives the urgent need to develop novel data analytical strategies. Spacekime analytics represents one new data-analytic approach, which provides a mechanism to understand compound phenomena that are observed as multiplex longitudinal processes and computationally tracked by proxy measures. This book may be of interest to academic scholars, graduate students, postdoctoral fellows, artificial intelligence and machine learning engineers, biostatisticians, econometricians, and data analysts. Some of the material may also resonate with philosophers, futurists, astrophysicists, space industry technicians, biomedical researchers, health practitioners, and the general public.

The long-standing debate on public vs. private healthcare systems has forced an examination of these organisations, in particular whether these approaches play corresponding or conflicting roles in service to global citizens. Healthcare Management and Economics: Perspectives on Public and Private Administration discusses public and private healthcare organisations by gathering perspectives on the differences in service, management, delivery, and efficiency. Highlighting the impact of citizens and information technology in these healthcare processes, this book is a vital collection of research for practitioners, academics, and scholars in the healthcare management field.

Technologies for Supporting Reasoning Communities and Collaborative Decision Making: Cooperative Approaches includes chapters from diverse fields of enquiry including decision science, political science, argumentation, knowledge management, cognitive psychology and business intelligence. Each chapter illustrates a perspective on group reasoning that ultimately aims to lead to a greater understanding of reasoning communities and inform technological developments.

The Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry examines the drug discovery process, assessing how new technologies have improved effectiveness. Artificial intelligence and machine learning are considered the future for a wide range of disciplines and industries, including the pharmaceutical industry. In an environment where producing a single approved drug costs millions and takes many years of rigorous testing prior to its approval, reducing costs and time is of high interest. This book follows the journey that a drug company takes when producing a therapeutic, from the very beginning to ultimately benefitting a patient's life. This comprehensive resource will be useful to those working in the pharmaceutical industry, but will also be of interest to anyone doing research in chemical biology, computational chemistry, medicinal chemistry and bioinformatics.

Education and research in the field of database technology can prove problematic without the proper resources and tools on the most relevant issues, trends, and advancements. Selected Readings on Database Technologies and Applications supplements course instruction and student research with quality chapters focused on key issues concerning the development, design, and analysis of databases. Containing over 30 chapters from authors across the globe, these selected readings in areas such as data warehousing, information retrieval, and knowledge discovery depict the most relevant and important areas of classroom discussion within the categories of Fundamental Concepts and Theories; Development and Design Methodologies; Tools and Technologies; Application and Utilization; Critical Issues; and Emerging Trends.

Computer science especially pattern recognition, signal processing and mathematical algorithms can offer important information about archaeological finds, information that is otherwise undetectable by the human senses and traditional archaeological approaches. Pattern Recognition and Signal Processing in Archaeometry: Mathematical and Computational Solutions for Archaeology offers state of the art research in computational pattern recognition and digital archaeometry. Computer science researchers in pattern recognition and machine intelligence will find innovative research methodologies combined to create novel and efficient computational systems, offering robust, exact, and reliable performance and results. Archaeologists, conservators, and historians will discover reliable automated methods for quickly reconstructing archaeological materials and benefit from the application of non-destructive, automated processing of archaeological finds.

A compilation of key chapters from the top MK computer animation books available today - in the areas of motion capture, facial features, solid spaces, fluids, gases, biology, point-based graphics, and Maya. The chapters provide CG Animators with an excellent sampling of essential techniques that every 3D artist needs to create stunning and versatile images. Animators will be able to master myriad modeling, rendering, and texturing procedures with advice from MK's best and brightest authors.

Divided into five parts (Introduction to Computer Animation and Technical Background, Motion Capture Techniques, Animating Substances, Alternate Methods, and Animating with MEL for MAYA), each one focusing on specific substances, tools, topics, and languages, this is a MUST-HAVE book for artists interested in proficiency with the top technology available today Whether you're a programmer developing new animation functionality or an animator trying to get the most out of your current animation software, Computer Animation Complete: will help you work more efficiently and achieve better results. For programmers, this book provides a solid theoretical orientation and extensive practical instruction information you can put to work in any development or customization project. For animators, it provides crystal-clear guidance on determining which of your concepts can be realized using commercially available products, which demand custom programming, and what development strategies are likely to bring you the greatest success.
Expert instruction from a variety of pace-setting computer graphics researchers.Provides in-depth coverage of established and emerging animation algorithms.For readers who lack a strong scientific background, introduces the necessary concepts from mathematics, biology, and physics.A variety of individual languages and substances are addressed, but addressed separately - enhancing your grasp of the field as a whole while providing you with the ability to identify and implement solutions by category.

The science of simulation and modeling (SM) is multifaceted and complex due to the numerous applications involved, particularly since SM applications range from nuclear reaction to supermarket queuing. Simulation and Modeling: Current Technologies and Applications offers insight into the computer science aspect of simulation and modeling while integrating the business practices of SM.Simulation and Modeling: Current Technologies and Applications includes current issues related to simulation, such as: Web-based simulation, virtual reality, augmented reality, and artificial intelligence. This book depicts different methods, views, theories, and applications of simulations in one volume.

Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.