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Computational Sciences - Modelling, Computing and Soft Computing: First International Conference, CSMCS 2020, Kozhikode, Kerala, India, September 10-12, 2020, Revised Selected Papers (Communications in Computer and Information Science #1345)
by Ashish Awasthi Sunil Jacob John Satyananda PandaThis book constitutes revised and selected papers of the First International Conference on Computational Sciences - Modelling, Computing and Soft Computing, held in Kozhikode, Kerala, India, in September 2020. The 15 full papers and 6 short papers presented were thoroughly revised and selected from the 150 submissions. They are organized in the topical secions on computing; soft computing; general computing; modelling.
Computational Ship Design (Springer Series On Naval Architecture, Marine Engineering, Shipbuilding And Shipping Ser. #4)
by Myung-Il Roh Kyu-Yeul LeeThis book offers an introduction to the fundamental principles and systematic methodologies employed in computational approaches to ship design. It takes a detailed approach to the description of the problem definition, related theories, mathematical formulation, algorithm selection, and other core design information. Over eight chapters and appendices the book covers the complete process of ship design, from a detailed description of design theories through to cutting-edge applications. Following an introduction to relevant terminology, the first chapters consider ship design equations and models, freeboard calculations, resistance prediction and power estimation. Subsequent chapters cover topics including propeller deign, engine selection, hull form design, structural design and outfitting. The book concludes with two chapters considering operating design and economic factors including construction costs and fuel consumption. The book reflects first-hand experiences in ship design and R&D activities, and incorporates improvements based on feedback received from many industry experts. Examples provided are based on genuine case studies in the field. The comprehensive description of each design stage presented in this book offers guidelines for academics, researchers, students, and industrial manufactures from diverse fields, including ocean engineering and mechanical engineering. From a commercial point of view the book will be of great value to those involved in designing a new vessel or improving an existing ship.
Computational Signal Processing and Analysis: Select Proceedings Of Icnets2, Volume I (Lecture Notes In Electrical Engineering #490)
by John Sahaya Rani Alex R. Menaka N. Sujatha Asoke K. NandiThis book comprises a collection of papers by international experts, presented at the International Conference on NextGen Electronic Technologies (ICNETS2-2017). ICNETS2 encompassed six symposia covering all aspects of electronics and communications engineering domains, including relevant nano/micro materials and devices. Featuring the latest research on computational signal processing and analysis, the book is useful to researchers, professionals, and students working in the core areas of electronics and their applications, especially signal processing, embedded systems, and networking.
Computational Social Network Analysis: Trends, Tools and Research Advances (Computer Communications and Networks)
by Ajith Abraham Aboul-Ella Hassanien Vaclav SnášelSocial networks provide a powerful abstraction of the structure and dynamics of diverse kinds of people or people-to-technology interaction. Web 2.0 has enabled a new generation of web-based communities, social networks, and folksonomies to facilitate collaboration among different communities. This unique text/reference compares and contrasts the ethological approach to social behavior in animals with web-based evidence of social interaction, perceptual learning, information granulation, the behavior of humans and affinities between web-based social networks. An international team of leading experts present the latest advances of various topics in intelligent-social-networks and illustrates how organizations can gain competitive advantages by applying the different emergent techniques in real-world scenarios. The work incorporates experience reports, survey articles, and intelligence techniques and theories with specific network technology problems. Topics and Features: Provides an overview social network tools, and explores methods for discovering key players in social networks, designing self-organizing search systems, and clustering blog sites, surveys techniques for exploratory analysis and text mining of social networks, approaches to tracking online community interaction, and examines how the topological features of a system affects the flow of information, reviews the models of network evolution, covering scientific co-citation networks, nature-inspired frameworks, latent social networks in e-Learning systems, and compound communities, examines the relationship between the intent of web pages, their architecture and the communities who take part in their usage and creation, discusses team selection based on members' social context, presents social network applications, including music recommendation and face recognition in photographs, explores the use of social networks in web services that focus on the discovery stage in the life cycle of these web services. This useful and comprehensive volume will be indispensible to senior undergraduate and postgraduate students taking courses in Social Intelligence, as well as to researchers, developers, and postgraduates interested in intelligent-social-networks research and related areas.
Computational Social Networks: Security and Privacy
by Ajith AbrahamThis book is the second of three volumes that illustrate the concept of social networks from a computational point of view. The book contains contributions from a international selection of world-class experts, concentrating on topics relating to security and privacy (the other two volumes review Tools, Perspectives, and Applications, and Mining and Visualization in CSNs). Topics and features: presents the latest advances in security and privacy issues in CSNs, and illustrates how both organizations and individuals can be protected from real-world threats; discusses the design and use of a wide range of computational tools and software for social network analysis; describes simulations of social networks, and the representation and analysis of social networks, with a focus on issues of security, privacy, and anonymization; provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology.
Computational Social Networks: Mining and Visualization
by Ajith AbrahamThis book is the third of three volumes that illustrate the concept of social networks from a computational point of view. The book contains contributions from a international selection of world-class experts, with a specific focus on knowledge discovery and visualization of complex networks (the other two volumes review Tools, Perspectives, and Applications, and Security and Privacy in CSNs). Topics and features: presents the latest advances in CSNs, and illustrates how organizations can gain a competitive advantage from a better understanding of complex social networks; discusses the design and use of a wide range of computational tools and software for social network analysis; describes simulations of social networks, and the representation and analysis of social networks, highlighting methods for the data mining of CSNs; provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology.
Computational Social Networks: Tools, Perspectives and Applications
by Ajith Abraham Aboul-Ella HassanienThis book is the first of three volumes that illustrate the concept of social networks from a computational point of view. The book contains contributions from a international selection of world-class experts, with a specific focus on practical tools, applications, and open avenues for further research (the other two volumes review issues of Security and Privacy, and Mining and Visualization in CSNs). Topics and features: presents the latest advances in CSNs, and illustrates how organizations can gain a competitive advantage by applying these ideas in real-world scenarios; discusses the design and use of a wide range of computational tools and software for social network analysis; describes simulations of social networks, the representation and analysis of social networks, and the use of semantic networks in knowledge discovery and visualization; provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology.
Computational Social Networks: 5th International Conference, CSoNet 2016, Ho Chi Minh City, Vietnam, August 2-4, 2016, Proceedings (Lecture Notes in Computer Science #9795)
by Hien T. Nguyen Vaclav SnaselSocial networks provide a powerful abstraction of the structure and dynamics of diverse kinds of people or people-to-technology interaction. Web 2. 0 has enabled a new generation of web-based communities, social networks, and folksonomies to facilitate collaboration among different communities. This unique text/reference compares and contrasts the ethological approach to social behavior in animals with web-based evidence of social interaction, perceptual learning, information granulation, the behavior of humans and affinities between web-based social networks. An international team of leading experts present the latest advances of various topics in intelligent-social-networks and illustrates how organizations can gain competitive advantages by applying the different emergent techniques in real-world scenarios. The work incorporates experience reports, survey articles, and intelligence techniques and theories with specific network technology problems. Topics and Features: Provides an overview social network tools, and explores methods for discovering key players in social networks, designing self-organizing search systems, and clustering blog sites, surveys techniques for exploratory analysis and text mining of social networks, approaches to tracking online community interaction, and examines how the topological features of a system affects the flow of information, reviews the models of network evolution, covering scientific co-citation networks, nature-inspired frameworks, latent social networks in e-Learning systems, and compound communities, examines the relationship between the intent of web pages, their architecture and the communities who take part in their usage and creation, discusses team selection based on members social context, presents social network applications, including music recommendation and face recognition in photographs, explores the use of social networks in web services that focus on the discovery stage in the life cycle of these web services. This useful and comprehensive volume will be indispensible to senior undergraduate and postgraduate students taking courses in Social Intelligence, as well as to researchers, developers, and postgraduates interested in intelligent-social-networks research and related areas. "
Computational Social Psychology (Frontiers of Social Psychology)
by Robin R. Vallacher; Stephen J. Read; Andrzej NowakComputational Social Psychology showcases a new approach to social psychology that enables theorists and researchers to specify social psychological processes in terms of formal rules that can be implemented and tested using the power of high speed computing technology and sophisticated software. This approach allows for previously infeasible investigations of the multi-dimensional nature of human experience as it unfolds in accordance with different temporal patterns on different timescales. In effect, the computational approach represents a rediscovery of the themes and ambitions that launched the field over a century ago. The book brings together social psychologists with varying topical interests who are taking the lead in this redirection of the field. Many present formal models that are implemented in computer simulations to test basic assumptions and investigate the emergence of higher-order properties; others develop models to fit the real-time evolution of people’s inner states, overt behavior, and social interactions. Collectively, the contributions illustrate how the methods and tools of the computational approach can investigate, and transform, the diverse landscape of social psychology.
Computational Statics and Dynamics: An Introduction Based on the Finite Element Method
by Andreas ÖchsnerThis book is the 2nd edition of an introduction to modern computational mechanics based on the finite element method. It includes more details on the theory, more exercises, and more consistent notation; in addition, all pictures have been revised. Featuring more than 100 pages of new material, the new edition will help students succeed in mechanics courses by showing them how to apply the fundamental knowledge they gained in the first years of their engineering education to more advanced topics. In order to deepen readers’ understanding of the equations and theories discussed, each chapter also includes supplementary problems. These problems start with fundamental knowledge questions on the theory presented in the respective chapter, followed by calculation problems. In total, over 80 such calculation problems are provided, along with brief solutions for each. This book is especially designed to meet the needs of Australian students, reviewing the mathematics covered in their first two years at university. The 13-week course comprises three hours of lectures and two hours of tutorials per week.
Computational Statistical Methodologies and Modeling for Artificial Intelligence (ISSN)
by Priyanka Harjule Azizur Rahman Basant Agarwal Vinita TiwariThis book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering.The key features of this book are: Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial Intelligence Examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications Examines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionals Provides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fields Integrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence
Computational Statistics and Data Intelligence: APCAMS 2023, Chongqing, China, June 24–26 (Springer Proceedings in Mathematics & Statistics #463)
by Hari M. Srivastava Wenfeng Wang Wanyang DaiThis book gathers selected papers presented at the Asia-Pacific Conference on Applied Mathematics and Statistics held on June 24–26, 2023, in Chongqing, China. It presents the most recent research and advances in various areas of applied mathematics and statistics, span from mathematical theory, calculation, modeling, simulation, to applications such as big data and image processing.
Computational Statistics and Mathematical Modeling Methods in Intelligent Systems: Proceedings of 3rd Computational Methods in Systems and Software 2019, Vol. 2 (Advances in Intelligent Systems and Computing #1047)
by Radek Silhavy Petr Silhavy Zdenka ProkopovaThis book presents real-world problems and exploratory research in computational statistics, mathematical modeling, artificial intelligence and software engineering in the context of the intelligent systems. This book constitutes the refereed proceedings of the 3rd Computational Methods in Systems and Software 2019 (CoMeSySo 2019), a groundbreaking online conference that provides an international forum for discussing the latest high-quality research results.
Computational Statistics Handbook with MATLAB (Chapman & Hall/CRC Computer Science & Data Analysis)
by Wendy L. Martinez Angel R. MartinezA Strong Practical Focus on Applications and AlgorithmsComputational Statistics Handbook with MATLAB, Third Edition covers today's most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of the bestselling previous editions. The text keeps theoretical concepts to a minimum, emphasizing the i
Computational Statistics in the Earth Sciences: With Applications in MATLAB
by Chave Alan D.Based on a course taught by the author, this book combines the theoretical underpinnings of statistics with the practical analysis of Earth sciences data using MATLAB. The book is organized to introduce the underlying concepts, and then extends these to the data, covering methods that are most applicable to Earth sciences. Topics include classical parametric estimation and hypothesis testing, and more advanced least squares-based, nonparametric, and resampling estimators. Multivariate data analysis, not often encountered in introductory texts, is presented later in the book, and compositional data is treated at the end. Datasets and bespoke MATLAB scripts used in the book are available online, as well as additional datasets and suggested questions for use by instructors. Aimed at entering graduate students and practicing researchers in the Earth and ocean sciences, this book is ideal for those who want to learn how to analyse data using MATLAB in a statistically-rigorous manner.
Computational Stem Cell Biology: Methods and Protocols (Methods in Molecular Biology #1975)
by Patrick CahanThis volume details methods and protocols to further the study of stem cells within the computational stem cell biology (CSCB) field. Chapters are divided into four sections covering the theory and practice of modeling of stem cell behavior, analyzing single cell genome-scale measurements, reconstructing gene regulatory networks, and metabolomics. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.Authoritative and cutting-edge, Computational Stem Cell Biology: Methods and Protocols will be an invaluable guide to researchers as they explore stem cells from the perspective of computational biology.
Computational Stochastic Programming: Models, Algorithms, and Implementation (Springer Optimization and Its Applications #774)
by Lewis NtaimoThis book provides a foundation in stochastic, linear, and mixed-integer programming algorithms with a focus on practical computer algorithm implementation. The purpose of this book is to provide a foundational and thorough treatment of the subject with a focus on models and algorithms and their computer implementation. The book’s most important features include a focus on both risk-neutral and risk-averse models, a variety of real-life example applications of stochastic programming, decomposition algorithms, detailed illustrative numerical examples of the models and algorithms, and an emphasis on computational experimentation. With a focus on both theory and implementation of the models and algorithms for solving practical optimization problems, this monograph is suitable for readers with fundamental knowledge of linear programming, elementary analysis, probability and statistics, and some computer programming background. Several examples of stochastic programming applications areincluded, providing numerical examples to illustrate the models and algorithms for both stochastic linear and mixed-integer programming, and showing the reader how to implement the models and algorithms using computer software.
Computational Studies on Cultural Variation and Heredity (Kaist Research Ser.)
by Ji-Hyun LeeThis book explores the emerging concept of cultural DNA, considering its application across different fields and examining commonalities in approach. It approaches the subject from four different perspectives, in which the topics include theories, analysis and synthesis of cultural DNA artefacts. After an opening section which reviews theoretical work on cultural DNA research, the second section discusses analysis & synthesis of cultural DNA at the urban scale. Section three covers analysis & synthesis of cultural DNA artefacts, and the final section offers approaches to grammar-based cultural DNA research.The book places emphasis on two specific axes: one is the scale of the object under discussion, which ranges from the small (handheld artefacts) to the very large (cities); and the other is the methodology used from analysis to synthesis. This diverse approach with detailed information about grammar-based methodologies toward cultural DNA makes the book unique.This book will serve as a source of inspiration for designers and researchers trying to find the essence, archetype, and the building blocks of our environment for the incorporation of social and cultural factors into their designs.
Computational Sustainability (Studies in Computational Intelligence #645)
by Kristian Kersting Jörg Lässig Katharina MorikThe book athand gives an overview of the state of the art research in ComputationalSustainability as well as case studies of different application scenarios. Thiscovers topics such as renewable energy supply, energy storage and e-mobility, efficiencyin data centers and networks, sustainable food and water supply, sustainablehealth, industrial production and quality, etc. The book describescomputational methods and possible application scenarios.
Computational Systems Biology: Methods And Protocols (Methods In Molecular Biology #1754)
by Tao HuangThis volume introduces the reader to the latest experimental and bioinformatics methods for DNA sequencing, RNA sequencing, cell-free tumour DNA sequencing, single cell sequencing, single-cell proteomics and metabolomics. Chapters detail advanced analysis methods, such as Genome-Wide Association Studies (GWAS), machine learning, reconstruction and analysis of gene regulatory networks and differential coexpression network analysis, and gave a practical guide for how to choose and use the right algorithm or software to handle specific high throughput data or multi-omics data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.Authoritative and cutting-edge, Computational Systems Biology: Methods and Protocols aims to ensure successful results in the further study of this vital field.
Computational Systems Biology Approaches in Cancer Research (Chapman & Hall/CRC Computational Biology Series)
by Inna Kuperstein Emmanuel BarillotPraise for Computational Systems BiologyApproaches in Cancer Research: "Complex concepts are written clearly and with informative illustrations and useful links. The book is enjoyable to read yet provides sufficient depth to serve as a valuable resource for both students and faculty." — Trey Ideker, Professor of Medicine, UC Xan Diego, School of Medicine "This volume is attractive because it addresses important and timely topics for research and teaching on computational methods in cancer research. It covers a broad variety of approaches, exposes recent innovations in computational methods, and provides acces to source code and to dedicated interactive web sites." — Yves Moreau, Department of Electrical Engineering, SysBioSys Centre for Computational Systems Biology, University of Leuven With the availability of massive amounts of data in biology, the need for advanced computational tools and techniques is becoming increasingly important and key in understanding biology in disease and healthy states. This book focuses on computational systems biology approaches, with a particular lens on tackling one of the most challenging diseases - cancer. The book provides an important reference and teaching material in the field of computational biology in general and cancer systems biology in particular. The book presents a list of modern approaches in systems biology with application to cancer research and beyond. It is structured in a didactic form such that the idea of each approach can easily be grasped from the short text and self-explanatory figures. The coverage of topics is diverse: from pathway resources, through methods for data analysis and single data analysis to drug response predictors, classifiers and image analysis using machine learning and artificial intelligence approaches. Features Up to date using a wide range of approaches Applicationexample in each chapter Online resources with useful applications’
Computational Systems Biology of Cancer (Chapman & Hall/CRC Computational Biology Series)
by null Emmanuel Barillot null Laurence Calzone null Philippe Hupe null Jean-Philippe Vert null Andrei ZinovyevThe future of cancer research and the development of new therapeutic strategies rely on our ability to convert biological and clinical questions into mathematical models-integrating our knowledge of tumour progression mechanisms with the tsunami of information brought by high-throughput technologies such as microarrays and next-generation sequencin
Computational Techniques for Human Smile Analysis (SpringerBriefs in Computer Science)
by Hassan Ugail Ahmad Ali AldahoudIn this book, the authors discuss the recent developments in computational techniques for automated non-invasive facial emotion detection and analysis with particular focus on the smile. By way of applications, they discuss how genuine and non-genuine smiles can be inferred, how gender is encoded in a smile and how it is possible to use the dynamics of a smile itself as a biometric feature. It is often said that the face is a window to the soul. Bearing a metaphor of this nature in mind, one might find it intriguing to understand, if any, how the physical, behavioural as well as emotional characteristics of a person could be decoded from the face itself. With the increasing deductive power of machine learning techniques, it is becoming plausible to address such questions through the development of appropriate computational frameworks. Though there are as many as over twenty five categories of emotions one could express, regardless of the ethnicity, gender or social class, across humanity, there exist six common emotions – namely happiness, sadness, surprise, fear, anger and disgust - all of which can be inferred from facial expressions. Of these facial expressions, the smile is the most prominent in social interactions. The smile bears important ramifications with beliefs such as it makes one more attractive, less stressful in upsetting situations and employers tending to promote people who smile often. Even pockets of scientific research appear to be forthcoming to validate such beliefs and claims, e.g. the smile intensity observed in photographs positively correlates with longevity, the ability to win a fight and whether a couple would stay married. Thus, it appears that many important personality traits are encoded in the smile itself. Therefore, the deployment of computer based algorithms for studying the human smiles in greater detail is a plausible avenue for which the authors have dedicated the discussions in this book.
Computational Techniques for Intelligence Analysis: A Cognitive Approach
by Vincenzo Loia Francesco Orciuoli Angelo GaetaThis book focuses on the definition and implementation of data-driven computational tools supporting decision-making along heterogeneous intelligence scenarios. Intelligence analysis includes methodologies, activities, and tools aimed at obtaining complex information from a set of isolated data gathered from different sensors. The tools aim at increasing the level of situation awareness of decision-makers through the construction of abstract structures supporting human operators in reasoning and making decisions. This book appeals to students, professionals, and academic researchers in computational intelligence and approximate reasoning applications. It is a comprehensive textbook on the subject, supported with case studies and practical examples in Python. The readers will learn how to define decision support systems for the intelligence analysis through the application of situation awareness and granular computing for information processing.
Computational Techniques for Structural Health Monitoring (Springer Series in Reliability Engineering)
by Srinivasan Gopalakrishnan Sathyanaraya Hanagud Massimo RuzzeneThe increased level of activity on structural health monitoring (SHM) in various universities and research labs has resulted in the development of new methodologies for both identifying the existing damage in structures and predicting the onset of damage that may occur during service. Designers often have to consult a variety of textbooks, journal papers and reports, because many of these methodologies require advanced knowledge of mechanics, dynamics, wave propagation, and material science. Computational Techniques for Structural Health Monitoring gives a one-volume, in-depth introduction to the different computational methodologies available for rapid detection of flaws in structures. Techniques, algorithms and results are presented in a way that allows their direct application. A number of case studies are included to highlight further the practical aspects of the selected topics. Computational Techniques for Structural Health Monitoring also provides the reader with numerical simulation tools that are essential to the development of novel algorithms for the interpretation of experimental measurements, and for the identification of damage and its characterization. Upon reading Computational Techniques for Structural Health Monitoring, graduate students will be able to begin research-level work in the area of structural health monitoring. The level of detail in the description of formulation and implementation also allows engineers to apply the concepts directly in their research.