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Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction

by Friedhelm Schwenker Stefan Scherer Louis-Philippe Morency

This book constitutes the thoroughly refereed post-workshop proceedings of the Third IAPR TC3 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2014, held in Stockholm, Sweden, in August 2014, as a satellite event of the International Conference on Pattern Recognition, ICPR 2014. The 14 revised papers presented focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition, user identification, and recognition of human activities.

Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction

by Friedhelm Schwenker Stefan Scherer

This book constitutes the thoroughly refereed post-workshop proceedings of the Third IAPR TC3 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2014, held in Stockholm, Sweden, in August 2014, as a satellite event of the International Conference on Pattern Recognition, ICPR 2014. The 14 revised papers presented focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition, user identification, and recognition of human activities.

Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction: 5th IAPR TC 9 Workshop, MPRSS 2018, Beijing, China, August 20, 2018, Revised Selected Papers (Lecture Notes in Computer Science #11377)

by Friedhelm Schwenker Stefan Scherer

This book constitutes the refereed post-workshop proceedings of the 5th IAPR TC9 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2018, held in Beijing, China, in August 2018. The 10 revised papers presented in this book focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition and pain intensity estimation, especially the question how to distinguish between human emotions from pain or stress induced by pain is discussed.

Multimodal Retrieval in the Medical Domain

by Henning Müller Oscar Alfonso Jimenez del Toro Allan Hanbury Georg Langs Antonio Foncubierta Rodriguez

This book constitutes the proceedings of the First International Workshop on Multimodal Retrieval in the Medical Domain, MRMD 2015, held in Vienna, Austria, on March 29, 2015. The workshop was held in connection with ECIR 2015. The 14 full papers presented, including one invited paper, a workshop overview and five papers on the VISCERAL Retrieval Benchmark, were carefully reviewed and selected from 18 submissions. The papers focus on the following topics: importance of data other than text for information retrieval; semantic data analysis; scalability approaches towards big data sets.

Multimodal Sentiment Analysis (Socio-Affective Computing #8)

by Amir Hussain Erik Cambria Soujanya Poria

This latest volume in the series, Socio-Affective Computing, presents a set of novel approaches to analyze opinionated videos and to extract sentiments and emotions. Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer. This volume covers the three main topics of: textual preprocessing and sentiment analysis methods; frameworks to process audio and visual data; and methods of textual, audio and visual features fusion. The inclusion of key visualization and case studies will enable readers to understand better these approaches. Aimed at the Natural Language Processing, Affective Computing and Artificial Intelligence audiences, this comprehensive volume will appeal to a wide readership and will help readers to understand key details on multimodal sentiment analysis.

Multimodal Usability

by Laila Dybkjær Niels Ole Bernsen

This book is about how to develop and evaluate multimodal systems which are usable by, or fit, people. The main objective is to answer the practical question of what system developers need to know and be able to do in order to develop usable new multimodal applications. The need to know is addressed in the first part of the book, in which the role of development and evaluation for multimodal usability in the software engineering life-cycle is described, and 9 key multimodal usability parameters are presented as well as theory of modalities and multimodality. The need to be able to do is addressed in the second part of the book. The distinction between interleaved and iteratively performed (i) development for multimodal usability and (ii) evaluation for usability is discussed.

Multimodal and Tensor Data Analytics for Industrial Systems Improvement (Springer Optimization and Its Applications #211)

by Panos M. Pardalos Nathan Gaw Mostafa Reisi Gahrooei

This volume covers the latest methodologies for using multimodal data fusion and analytics across several applications. The curated content presents recent developments and challenges in multimodal data analytics and shines a light on a pathway toward new research developments. Chapters are composed by eminent researchers and practitioners who present their research results and ideas based on their expertise. As data collection instruments have improved in quality and quantity for many applications, there has been an unprecedented increase in the availability of data from multiple sources, known as modalities. Modalities express a large degree of heterogeneity in their form, scale, resolution, and accuracy. Determining how to optimally combine the data for prediction and characterization is becoming increasingly important. Several research studies have investigated integrating multimodality data and discussed the challenges and limitations of multimodal data fusion. This volume provides a topical overview of various methods in multimodal data fusion for industrial engineering and operations research applications, such as manufacturing and healthcare.Advancements in sensing technologies and the shift toward the Internet of Things (IoT) has transformed and will continue to transform data analytics by producing new requirements and more complex forms of data. The abundance of data creates an unprecedented opportunity to design more efficient systems and make near-optimal operational decisions. On the other hand, the structural complexity and heterogeneity of the generated data pose a significant challenge to extracting useful features and patterns for making use of the data and facilitating decision-making. Therefore, continual research is needed to develop new statistical and analytical methodologies that overcome these data challenges and turn them into opportunities.

Multimodality in Architecture: Collaboration, Technology and Education

by Michael J. Ostwald Ju Hyun Lee Mi Jeong Kim

This book examines multimodality in architecture and its impacts on collaborative, technical and educational processes or systems. Multimodality is becoming increasingly critical in contemporary architectural practice and education. Creative design teams face new challenges when they embrace new modes of communication, technology, and knowledge development processes. From diverse online modes of communication to shared digital environments, generative AI and advanced hardware solutions, new modes of information creation, sharing, and application are changing the ways architects and designers work.The book presents new research which empowers international researchers and designers to work more effectively in a diverse range of digital environments.Whether the readers are architects, teachers, students, or scholars, this book provides critical insights and practical tools for understanding and optimising processes in architecture and design.

Multiobjective Linear Programming

by Dinh The Luc

This book introduces the reader to the field of multiobjective optimization through problems with simple structures, namely those in which the objective function and constraints are linear. Fundamental notions as well as state-of-the-art advances are presented in a comprehensive way and illustrated with the help of numerous examples. Three of the most popular methods for solving multiobjective linear problems are explained, and exercises are provided at the end of each chapter, helping students to grasp and apply key concepts and methods to more complex problems. The book was motivated by the fact that the majority of the practical problems we encounter in management science, engineering or operations research involve conflicting criteria and therefore it is more convenient to formulate them as multicriteria optimization models, the solution concepts and methods of which cannot be treated using traditional mathematical programming approaches.

Multiobjective Optimization Algorithms for Bioinformatics

by Ujjwal Maulik Sanghamitra Bandyopadhyay Anirban Mukhopadhyay Sumanta Ray

This book provides an updated and in-depth introduction to the application of multiobjective optimization techniques in bioinformatics. In particular, it presents multiobjective solutions to a range of complex real-world bioinformatics problems. The authors first provide a comprehensive yet concise and self-contained introduction to relevant preliminary methodical constructions such as genetic algorithms, multiobjective optimization, data mining and several challenges in the bioinformatics domain. This is followed by several systematic applications of these techniques to real-world bioinformatics problems in the areas of gene expression and network biology. The book also features detailed theoretical and mathematical notes to facilitate reader comprehension. The book offers a valuable asset for a broad range of readers – from undergraduate to postgraduate, and as a textbook or reference work. Researchers and professionals can use the book not only to enrich their knowledge of multiobjective optimization and bioinformatics, but also as a comprehensive reference guide to applying and devising novel methods in bioinformatics and related domains.

Multiobjective Programming and Planning

by Jared L. Cohon

This text takes a broad view of multiobjective programming, emphasizing the methods most useful for continuous problems. It reviews multiobjective programming methods in the context of public decision-making problems, developing each problem within a context that addresses practical aspects of planning issues. Topics include a review of linear programming, the formulation of the general multiobjective programming problem, classification of multiobjective programming methods, techniques for generating noninferior solutions, multiple-decision-making methods, multiobjective analysis of water resource problems, and multiobjective analysis of facility location problems. 1978 edition.

Multiphase Flow and Heat Transfer in Pebble Bed Reactor Core

by Jiyuan Tu Shengyao Jiang Xingtuan Yang Nan Gui

This book introduces readers to gas flows and heat transfer in pebble bed reactor cores. It addresses fundamental issues regarding experimental and modeling methods for complex multiphase systems, as well as relevant applications and recent research advances. The numerical methods and experimental measurements/techniques used to solve pebble flows, as well as the content on radiation modeling for high-temperature pebble beds, will be of particular interest. This book is intended for a broad readership, including researchers and practitioners, and is sure to become a key reference resource for students and professionals alike.

Multiphysics Simulation

by Ercan M. Dede Jaewook Lee Tsuyoshi Nomura

This book highlights a unique combination of numerical tools and strategies for handling the challenges of multiphysics simulation, with a specific focus on electromechanical systems as the target application. Features: introduces the concept of design via simulation, along with the role of multiphysics simulation in today's engineering environment; discusses the importance of structural optimization techniques in the design and development of electromechanical systems; provides an overview of the physics commonly involved with electromechanical systems for applications such as electronics, magnetic components, RF components, actuators, and motors; reviews the governing equations for the simulation of related multiphysics problems; outlines relevant (topology and parametric size) optimization methods for electromechanical systems; describes in detail several multiphysics simulation and optimization example studies in both two and three dimensions, with sample numerical code.

Multiphysics in Porous Materials

by Zhen Leo Liu

This book summarizes, defines, and contextualizes multiphysics with an emphasis on porous materials. It covers various essential aspects of multiphysics, from history, definition, and scope to mathematical theories, physical mechanisms, and numerical implementations. The emphasis on porous materials maximizes readers’ understanding as these substances are abundant in nature and a common breeding ground of multiphysical phenomena, especially complicated multiphysics. Dr. Liu’s lucid and easy-to-follow presentation serve as a blueprint on the use of multiphysics as a leading edge technique for computer modeling. The contents are organized to facilitate the transition from familiar, monolithic physics such as heat transfer and pore water movement to state-of-the-art applications involving multiphysics, including poroelasticity, thermohydro-mechanical processes, electrokinetics, electromagnetics, fluid dynamics, fluid structure interaction, and electromagnetomechanics. This volume serves as both a general reference and specific treatise for various scientific and engineering disciplines involving multiphysics simulation and porous materials.

Multiplayer Game Development with HTML5

by Rodrigo Silveira

If you are a HTML5 game developer who can make basic single-player games and you are now ready to incorporate multiplayer functionality in your games as quickly as possible, then this book is ideal for you.

Multiplayer Online Games: Origins, Players, and Social Dynamics

by Guo Freeman

Multiplayer Online Games (MOGs) have become a new genre of "play culture," integrating communication and entertainment in a playful, computer-mediated environment that evolves through user interaction. This book comprehensively reviews the origins, players, and social dynamics of MOGs, as well as six major empirical research methods used in previous works to study MOGs (i.e., observation/ethnography, survey/interviews, content and discourse analysis, experiments, network analysis, and case studies). It concludes that MOGs represent a highly sophisticated, networked, multimedia and multimodal Internet technology, which can construct entertaining, simultaneous, persistent social virtual worlds for gamers. Overall, the book shows that what we can learn from MOGs is how games and gaming, as ubiquitous activities, fit into ordinary life in today’s information society, in the moments where the increased use of media as entertainment, the widespread application of networked information technologies, and participation in new social experiences intersect. <P><P>Key Features: <li>Contains pertinent knowledge about online gaming: its history, technical features, player characteristics, social dynamics, and research methods <li>Sheds light on the potential future of online gaming, and how this would impact every aspect of our everyday lives – socially, culturally, technologically, and economically <li>Asks promising questions based on cutting-edge research in the field of online game design and development

Multiple Access Techniques for 5G Wireless Networks and Beyond

by H. Vincent Poor Mojtaba Vaezi Zhiguo Ding

This book presents comprehensive coverage of current and emerging multiple access, random access, and waveform design techniques for 5G wireless networks and beyond. A definitive reference for researchers in these fields, the book describes recent research from academia, industry, and standardization bodies. The book is an all-encompassing treatment of these areas addressing orthogonal multiple access and waveform design, non-orthogonal multiple access (NOMA) via power, code, and other domains, and orthogonal, non-orthogonal, and grant-free random access. The book builds its foundations on state of the art research papers, measurements, and experimental results from a variety of sources.

Multiple Biological Sequence Alignment: Scoring Functions, Algorithms and Evaluation

by Yi Pan Ken Nguyen Xuan Guo

Covers the fundamentals and techniques of multiple biological sequence alignment and analysis, and shows readers how to choose the appropriate sequence analysis tools for their tasks This book describes the traditional and modern approaches in biological sequence alignment and homology search. This book contains 11 chapters, with Chapter 1 providing basic information on biological sequences. Next, Chapter 2 contains fundamentals in pair-wise sequence alignment, while Chapters 3 and 4 examine popular existing quantitative models and practical clustering techniques that have been used in multiple sequence alignment. Chapter 5 describes, characterizes and relates many multiple sequence alignment models. Chapter 6 describes how traditionally phylogenetic trees have been constructed, and available sequence knowledge bases can be used to improve the accuracy of reconstructing phylogeny trees. Chapter 7 covers the latest methods developed to improve the run-time efficiency of multiple sequence alignment. Next, Chapter 8 covers several popular existing multiple sequence alignment server and services, and Chapter 9 examines several multiple sequence alignment techniques that have been developed to handle short sequences (reads) produced by the Next Generation Sequencing technique (NSG). Chapter 10 describes a Bioinformatics application using multiple sequence alignment of short reads or whole genomes as input. Lastly, Chapter 11 provides a review of RNA and protein secondary structure prediction using the evolution information inferred from multiple sequence alignments. * Covers the full spectrum of the field, from alignment algorithms to scoring methods, practical techniques, and alignment tools and their evaluations * Describes theories and developments of scoring functions and scoring matrices *Examines phylogeny estimation and large-scale homology search Multiple Biological Sequence Alignment: Scoring Functions, Algorithms and Applications is a reference for researchers, engineers, graduate and post-graduate students in bioinformatics, and system biology and molecular biologists. Ken Nguyen, PhD, is an associate professor at Clayton State University, GA, USA. He received his PhD, MSc and BSc degrees in computer science all from Georgia State University. His research interests are in databases, parallel and distribute computing and bioinformatics. He was a Molecular Basis of Disease fellow at Georgia State and is the recipient of the highest graduate honor at Georgia State, the William M. Suttles Graduate Fellowship. Xuan Guo, PhD, is a postdoctoral associate at Oak Ridge National Lab, USA. He received his PhD degree in computer science from Georgia State University in 2015. His research interests are in bioinformatics, machine leaning, and cloud computing. He is an editorial assistant of International Journal of Bioinformatics Research and Applications. Yi Pan, PhD, is a Regents' Professor of Computer Science and an Interim Associate Dean and Chair of Biology at Georgia State University. He received his BE and ME in computer engineering from Tsinghua University in China and his PhD in computer science from the University of Pittsburgh. Dr. Pan's research interests include parallel and distributed computing, optical networks, wireless networks and bioinformatics. He has published more than 180 journal papers with about 60 papers published in various IEEE/ACM journals. He is co-editor along with Albert Y. Zomaya of the Wiley Series in Bioinformatics.

Multiple Classifier Systems

by Friedhelm Schwenker Fabio Roli Josef Kittler

This book constitutes the refereed proceedings of the 12th International Workshop on Multiple Classifier Systems, MCS 2015, held in Günzburg, Germany, in June/July 2015. The 19 revised papers presented were carefully reviewed and selected from 25 submissions. The papers address issues in multiple classifier systems and ensemble methods, including pattern recognition, machine learning, neural network, data mining and statistics. They are organized in topical sections on theory and algorithms and application and evaluation.

Multiple Criteria Decision Aid: Methods, Examples and Python Implementations (Springer Optimization and Its Applications #136)

by Jason Papathanasiou Nikolaos Ploskas

Multiple criteria decision aid (MCDA) methods are illustrated in this book through theoretical and computational techniques utilizing Python. Existing methods are presented in detail with a step by step learning approach. Theoretical background is given for TOPSIS, VIKOR, PROMETHEE, SIR, AHP, goal programming, and their variations. Comprehensive numerical examples are also discussed for each method in conjunction with easy to follow Python code. Extensions to multiple criteria decision making algorithms such as fuzzy number theory and group decision making are introduced and implemented through Python as well. Readers will learn how to implement and use each method based on the problem, the available data, the stakeholders involved, and the various requirements needed. Focusing on the practical aspects of the multiple criteria decision making methodologies, this book is designed for researchers, practitioners and advanced graduate students in the applied mathematics, information systems, operations research and business administration disciplines, as well as other engineers and scientists oriented in interdisciplinary research. Readers will greatly benefit from this book by learning and applying various MCDM/A methods. (Adiel Teixeira de Almeida, CDSID-Center for Decision System and Information Development, Universidade Federal de Pernambuco, Recife, Brazil) Promoting the development and application of multicriteria decision aid is essential to ensure more ethical and sustainable decisions. This book is a great contribution to this objective. It is a perfect blend of theory and practice, providing potential users and researchers with the theoretical bases of some of the best-known methods as well as with the computing tools needed to practice, to compare and to put these methods to use. (Jean-Pierre Brans, Vrije Universiteit Brussel, Brussels, Belgium) This book is intended for researchers, practitioners and students alike in decision support who wish to familiarize themselves quickly and efficiently with multicriteria decision aiding algorithms. The proposed approach is original, as it presents a selection of methods from the theory to the practical implementation in Python, including a detailed example. This will certainly facilitate the learning of these techniques, and contribute to their effective dissemination in applications. (Patrick Meyer, IMT Atlantique, Lab-STICC, Univ. Bretagne Loire, Brest, France)

Multiple Criteria Decision Making and Aiding: Cases on Models and Methods with Computer Implementations (International Series in Operations Research & Management Science #274)

by Adiel Teixeira de Almeida Martin Josef Geiger Sandra Huber

This book introduces students on Multiple Criteria Decision Aiding and Making courses to practical, real-world cases. Each case study introduces a problem or situation together with a method, and a description and explanation of a computer application. In this sense each chapter is based on four pillars: the problem, the model building, the methods and their implementation. The book presents and elaborates a rich and comprehensive set of practical problems comprising multiple criteria, including numerous approaches for their solution, for decision support or decision aid. It complements traditional textbooks and lecture material by employing case studies to promote a deeper understanding of the investigated concepts and help students apply these methods to other areas.

Multiple Criteria Decision Making with Fuzzy Sets: MS Excel® and Other Software Solutions (Multiple Criteria Decision Making)

by Gerhard-Wilhelm Weber Babek Erdebilli

Using numerical examples to illustrate their concepts and results, this book examines recently developed fuzzy multi-criteria methods, such as Intuitionistic Fuzzy TOPSIS, Intuitionistic Fuzzy TOPSIS & DEA-AHP, Intuitionistic VIKOR, Pythagorean WASPAS, Pythagorean ENTROPI, Hesitant CBD, Hesitant MABAC, Triangular EDAS, Triangular PROMETHEE, q-Rung Orthopair COPRAS, and Fuzzy Type – 2 ELECTRE. Each chapter covers practical applications in addition to fresh developments and results. Given its structure and scope, the book can be used as a textbook in graduate courses on operations research and industrial engineering. It also offers a valuable resource for scientists working in a range of disciplines that require multi-criteria decision making.

Multiple Instance Learning

by Sebastián Ventura Francisco Herrera Rafael Bello Chris Cornelis Amelia Zafra Dánel Sánchez-Tarragó Sarah Vluymans

This book provides a general overview of multiple instance learning (MIL), defining the framework and covering the central paradigms. The authors discuss the most important algorithms for MIL such as classification, regression and clustering. With a focus on classification, a taxonomy is set and the most relevant proposals are specified. Efficient algorithms are developed to discover relevant information when working with uncertainty. Key representative applications are included. This book carries out a study of the key related fields of distance metrics and alternative hypothesis. Chapters examine new and developing aspects of MIL such as data reduction for multi-instance problems and imbalanced MIL data. Class imbalance for multi-instance problems is defined at the bag level, a type of representation that utilizes ambiguity due to the fact that bag labels are available, but the labels of the individual instances are not defined. Additionally, multiple instance multiple label learning is explored. This learning framework introduces flexibility and ambiguity in the object representation providing a natural formulation for representing complicated objects. Thus, an object is represented by a bag of instances and is allowed to have associated multiple class labels simultaneously. This book is suitable for developers and engineers working to apply MIL techniques to solve a variety of real-world problems. It is also useful for researchers or students seeking a thorough overview of MIL literature, methods, and tools.

Multiple Perspectives on Artificial Intelligence in Healthcare: Opportunities and Challenges (Lecture Notes in Bioengineering)

by Mowafa Househ Elizabeth Borycki Andre Kushniruk

This book offers a comprehensive yet concise overview of the challenges and opportunities presented by the use of artificial intelligence in healthcare. It does so by approaching the topic from multiple perspectives, e.g. the nursing, consumer, medical practitioner, healthcare manager, and data analyst perspective. It covers human factors research, discusses patient safety issues, and addresses ethical challenges, as well as important policy issues. By reporting on cutting-edge research and hands-on experience, the book offers an insightful reference guide for health information technology professionals, healthcare managers, healthcare practitioners, and patients alike, aiding them in their decision-making processes. It will also benefit students and researchers whose work involves artificial intelligence-related research issues in healthcare.

Multiple Perspectives on Problem Solving and Learning in the Digital Age

by Dirk Ifenthaler J. Michael Spector Kinshuk Pedro Isaias Demetrios G. Sampson

This edited volume with selected expanded papers from CELDA (Cognition and Exploratory Learning in the Digital Age) 2009 (http://www.celda-conf.org/) addresses the main issues concerned with problem solving, evolving learning processes, innovative pedagogies, and technology-based educational applications in the digital age. There have been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a fast pace and affecting academia and professional practice in many ways. Paradigms such as just-in-time learning, constructivism, student-centered learning and collaborative approaches have emerged and are being supported by technological advancements such as simulations, virtual reality and multi-agents systems. These developments have created both opportunities and areas of serious concerns. This volume aims to cover both technological as well as pedagogical issues related to these developments.

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