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Computational and Experimental Simulations in Engineering: Proceedings of ICCES 2024—Volume 2 (Mechanisms and Machine Science #173)
by Kun ZhouThis book gathers the latest advances, innovations, and applications in the field of computational engineering, as presented by leading international researchers and engineers at the 30th International Conference on Computational & Experimental Engineering and Sciences (ICCES), held in Singapore on August 3-6, 2024. ICCES covers all aspects of applied sciences and engineering: theoretical, analytical, computational, and experimental studies and solutions of problems in the physical, chemical, biological, mechanical, electrical, and mathematical sciences. As such, the book discusses highly diverse topics, including composites; bioengineering & biomechanics; geotechnical engineering; offshore & arctic engineering; multi-scale & multi-physics fluid engineering; structural integrity & longevity; materials design & simulation; and computer modeling methods in engineering. The contributions, which were selected by means of a rigorous international peer-review process, highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaborations.
Computational and Experimental Simulations in Engineering: Proceedings of ICCES 2024—Volume 3 (Mechanisms and Machine Science #175)
by Kun ZhouThis book gathers the latest advances, innovations, and applications in the field of computational engineering, as presented by leading international researchers and engineers at the 30th International Conference on Computational & Experimental Engineering and Sciences (ICCES), held in Singapore on August 3-6, 2024. ICCES covers all aspects of applied sciences and engineering: theoretical, analytical, computational, and experimental studies and solutions of problems in the physical, chemical, biological, mechanical, electrical, and mathematical sciences. As such, the book discusses highly diverse topics, including composites; bioengineering & biomechanics; geotechnical engineering; offshore & arctic engineering; multi-scale & multi-physics fluid engineering; structural integrity & longevity; materials design & simulation; and computer modeling methods in engineering. The contributions, which were selected by means of a rigorous international peer-review process, highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaborations.
Computational and Information Technologies in Science, Engineering and Education: 9th International Conference, CITech 2018, Ust-Kamenogorsk, Kazakhstan, September 25-28, 2018, Revised Selected Papers (Communications in Computer and Information Science #998)
by Yuri Shokin Zhassulan ShaimardanovThis book constitutes the refereed proceedings of the 9th International Conference on Computational and Information Technologies in Science, Engineering and Education, CITech 2018, held in Ust-Kamenogorsk, Kazakhstan, in September 2018.The 25 revised full papers presented were carefully reviewed and selected from 64 submissions. The papers address issues such as mathematical and computer modeling, fundamental problems of mathematics, technological aspects of the applications of parallel computer systems, high level parallel programming languages and systems.
Computational and Machine Learning Tools for Archaeological Site Modeling (Springer Theses)
by Maria Elena CastielloThis book describes a novel machine-learning based approach to answer some traditional archaeological problems, relating to archaeological site detection and site locational preferences. Institutional data collected from six Swiss regions (Zurich, Aargau, Grisons, Vaud, Geneva and Fribourg) have been analyzed with an original conceptual framework based on the Random Forest algorithm. It is shown how the algorithm can assist in the modelling process in connection with heterogeneous, incomplete archaeological datasets and related cultural heritage information. Moreover, an in-depth review of past and more recent works of quantitative methods for archaeological predictive modelling is provided. The book guides the readers to set up their own protocol for: i) dealing with uncertain data, ii) predicting archaeological site location, iii) establishing environmental features importance, iv) and suggest a model validation procedure. It addresses both academics and professionals in archaeology and cultural heritage management, and offers a source of inspiration for future research directions in the field of digital humanities and computational archaeology.
Computational and Manufacturing Strategies: Experimental Expressions Of Wood Capabilities (Springerbriefs In Architectural Design And Technology Ser.)
by Andrea Quartara Djordje StanojevicThis book highlights computationally enabled and digitally fabricated strategies used in the design of a series of full-size wooden structures. It introduces theoretical foundations and then focuses on the possibilities that have emerged as a result of the material-aware processes. The case studies expound wood as one of the most suitable materials to experience the seamless framework introduced with the digital design-to-construction chain. Two main aspects of the pavilions constructed, developed in various international academic groups, are considered. On one hand the case studies explore tolerances of raw and engineered material intertwined with machine processing; they also address material enhancement through strip applications in timber construction. In addition, the structures are examined in the light of an extensible designing path, which acts as an interoperable procedure, bridging the virtual and the real.
Computational and Methodological Statistics and Biostatistics: Contemporary Essays in Advancement (Emerging Topics in Statistics and Biostatistics)
by Din Ding-Geng Chen Andriëtte Bekker Johannes T. FerreiraIn the statistical domain, certain topics have received considerable attention during the last decade or so, necessitated by the growth and evolution of data and theoretical challenges. This growth has invariably been accompanied by computational advancement, which has presented end users as well as researchers with the necessary opportunities to handle data and implement modelling solutions for statistical purposes.Showcasing the interplay among a variety of disciplines, this book offers pioneering theoretical and applied solutions to practice-oriented problems. As a carefully curated collection of prominent international thought leaders, it fosters collaboration between statisticians and biostatisticians and provides an array of thought processes and tools to its readers. The book thereby creates an understanding and appreciation of recent developments as well as an implementation of these contributions within the broader framework of both academia and industry.Computational and Methodological Statistics and Biostatistics is composed of three main themes:• Recent developments in theory and applications of statistical distributions;• Recent developments in supervised and unsupervised modelling;• Recent developments in biostatistics;and also features programming code and accompanying algorithms to enable readers to replicate and implement methodologies. Therefore, this monograph provides a concise point of reference for a variety of current trends and topics within the statistical domain. With interdisciplinary appeal, it will be useful to researchers, graduate students, and practitioners in statistics, biostatistics, clinical methodology, geology, data science, and actuarial science, amongst others.
Computational and Statistical Epigenomics (Translational Bioinformatics #7)
by Andrew E. TeschendorffThis book introduces the reader to modern computational and statistical tools for translational epigenomics research. Over the last decade, epigenomics has emerged as a key area of molecular biology, epidemiology and genome medicine. Epigenomics not only offers us a deeper understanding of fundamental cellular biology, but also provides us with the basis for an improved understanding and management of complex diseases. From novel biomarkers for risk prediction, early detection, diagnosis and prognosis of common diseases, to novel therapeutic strategies, epigenomics is set to play a key role in the personalized medicine of the future. In this book we introduce the reader to some of the most important computational and statistical methods for analyzing epigenomic data, with a special focus on DNA methylation. Topics include normalization, correction for cellular heterogeneity, batch effects, clustering, supervised analysis and integrative methods for systems epigenomics. This book will be of interest to students and researchers in bioinformatics, biostatistics, biologists and clinicians alike. Dr. Andrew E. Teschendorff is Head of the Computational Systems Genomics Lab at the CAS-MPG Partner Institute for Computational Biology, Shanghai, China, as well as an Honorary Research Fellow at the UCL Cancer Institute, University College London, UK.
Computational and Strategic Business Modelling: IC-BIM 2021, Athens, Greece (Springer Proceedings in Business and Economics)
by Damianos P. Sakas Dimitrios K. Nasiopoulos Yulia TaratuhinaThis book presents advanced methods in business intelligence models that are applicable in research areas of business and enterprise research such as business informatics, e-business, customer behavior and agricultural business. Featuring selected contributions presented at the 2021 International Conference on Business Intelligence and Modelling (IC-BIM) held in Athens, Greece, this book analyses a series of issues and tools for business intelligence in everyday business operations. The International Conference on Business Intelligence and Modelling (IC-BIM) started in 2011 and is an international interdisciplinary conference focusing on the theoretical approach of the contemporary issues evolved in business intelligence and modelling and the integration of theory and practice.
Computational and Visualization Techniques for Structural Bioinformatics Using Chimera (Chapman & Hall/CRC Computational Biology Series)
by null Forbes J. BurkowskiA Step-by-Step Guide to Describing Biomolecular StructureComputational and Visualization Techniques for Structural Bioinformatics Using Chimera shows how to perform computations with Python scripts in the Chimera environment. It focuses on the three core areas needed to study structural bioinformatics: biochemistry, mathematics, and computation.Und
Computational Approaches in the Transfer of Aesthetic Values from Paintings to Photographs: Beyond Red, Green and Blue
by Xiaoyan Zhang Martin Constable Kap Luk Chan Jinze Yu Wang JunyanThis book examines paintings using a computational and quantitative approach. Specifically, it compares paintings to photographs, addressing the strengths and limitations of both. Particular aesthetic practices are examined such as the vista, foreground to background organisation and the depth planes. These are analysed using a range of computational approaches and clear observations are made. New generations of image-capture devices such as Google goggles and the light field camera, promise a future in which the formal attributes of a photograph are made available for editing to a degree that has hitherto been the exclusive territory of painting. In this sense paintings and photographs are converging, and it therefore seems an opportune time to study the comparisons between them. In this context, the book includes cutting-edge work examining how some of the aesthetic attributes of a painting can be transferred to a photograph using the latest computational approaches.
Computational Approaches to the Network Science of Teams
by Liangyue Li Hanghang TongBusiness operations in large organizations today involve massive, interactive, and layered networks of teams and personnel collaborating across hierarchies and countries on complex tasks. To optimize productivity, businesses need to know: what communication patterns do high-performing teams have in common? Is it possible to predict a team's performance before it starts work on a project? How can productive team behavior be fostered? This comprehensive review for researchers and practitioners in data mining and social networks surveys recent progress in the emerging field of network science of teams. Focusing on the underlying social network structure, the authors present models and algorithms characterizing, predicting, optimizing, and explaining team performance, along with key applications, open challenges, and future trends.
Computational Bayesian Statistics: An Introduction (Institute of Mathematical Statistics Textbooks #11)
by M. Antónia Amaral Turkman Carlos Daniel Paulino Peter MüllerMeaningful use of advanced Bayesian methods requires a good understanding of the fundamentals. This engaging book explains the ideas that underpin the construction and analysis of Bayesian models, with particular focus on computational methods and schemes. The unique features of the text are the extensive discussion of available software packages combined with a brief but complete and mathematically rigorous introduction to Bayesian inference. The text introduces Monte Carlo methods, Markov chain Monte Carlo methods, and Bayesian software, with additional material on model validation and comparison, transdimensional MCMC, and conditionally Gaussian models. The inclusion of problems makes the book suitable as a textbook for a first graduate-level course in Bayesian computation with a focus on Monte Carlo methods. The extensive discussion of Bayesian software - R/R-INLA, OpenBUGS, JAGS, STAN, and BayesX - makes it useful also for researchers and graduate students from beyond statistics.
Computational Biology: A Statistical Mechanics Perspective, Second Edition (Chapman & Hall/CRC Computational Biology Series)
by Ralf BlosseyComputational biology has developed rapidly during the last two decades following the genomic revolution which culminated in the sequencing of the human genome. More than ever it has developed into a field which embraces computational methods from different branches of the exact sciences: pure and applied mathematics, computer science, theoretical physics. This Second Edition provides a solid introduction to the techniques of statistical mechanics for graduate students and researchers in computational biology and biophysics. Material has been reorganized to clarify equilbrium and nonequilibrium aspects of biomolecular systems Content has been expanded, in particular in the treatment of the electrostatic interactions of biomolecules and the application of non-equilibrium statistical mechanics to biomolecules New network-based approaches for the study of proteins are presented. All treated topics are put firmly in the context of the current research literature, allowing the reader to easily follow an individual path into a specific research field. Exercises and Tasks accompany the presentations of the topics with the intention of enabling the readers to test their comprehension of the developed basic concepts.
Computational Biology: A Practical Introduction to BioData Processing and Analysis with Linux, MySQL, and R
by Röbbe WünschiersThis greatly expanded 2nd edition provides a practical introduction to - data processing with Linux tools and the programming languages AWK and Perl- data management with the relational database system MySQL, and- data analysis and visualization with the statistical computing environment R for students and practitioners in the life sciences. Although written for beginners, experienced researchers in areas involving bioinformatics and computational biology may benefit from numerous tips and tricks that help to process, filter and format large datasets. Learning by doing is the basic concept of this book. Worked examples illustrate how to employ data processing and analysis techniques, e.g. for - finding proteins potentially causing pathogenicity in bacteria, - supporting the significance of BLAST with homology modeling, or- detecting candidate proteins that may be redox-regulated, on the basis of their structure.All the software tools and datasets used are freely available. One section is devoted to explaining setup and maintenance of Linux as an operating system independent virtual machine. The author's experiences and knowledge gained from working and teaching in both academia and industry constitute the foundation for this practical approach.
Computational Biology of Non-Coding RNA: Methods and Protocols (Methods in Molecular Biology #1912)
by Xin Lai Shailendra K. Gupta Julio VeraThis volume details a collection of state-of-art methods including identification of novel ncRNAs and their targets, functional annotation and disease association in different biological contexts. Chapters guide readers through an overview of disease-specific ncRNAs, computational methods and workflows for ncRNA discovery, annotation based on high-throughput sequencing data, bioinformatics tools and databases for ncRNA analyses, network-based methods, and kinetic modelling of ncRNA-mediated gene regulation. 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 Biology of Non-Coding RNA: Methods and Protocols aims to provide a state-of-the-art collection of computational methods and approaches that will be of value to researchers interested in ncRNA field.
Computational Biomechanics for Medicine: Solid and Fluid Mechanics for the Benefit of Patients
by Karol Miller Adam Wittek Grand Joldes Martyn P. Nash Poul M. F. NielsenComputational Biomechanics for Medicine: Solid and fluid mechanics for the benefit of patients contributions and papers from the MICCAI Computational Biomechanics for Medicine Workshop help in conjunction with Medical Image Computing and Computer Assisted Intervention conference (MICCAI 2019) in Shenzhen, China. The content is dedicated to research in the field of methods and applications of computational biomechanics to medical image analysis, image-guided surgery, surgical simulation, surgical intervention planning, disease prognosis and diagnostics, analysis of injury mechanisms, implant and prostheses design, as well as artificial organ design and medical robotics. These proceedings appeal to researchers, students and professionals in the field.
Computational Biomechanics for Medicine: Personalisation, Validation and Therapy
by Karol Miller Adam Wittek Poul M. F. Nielsen Grand R. Joldes Martyn P. NashThis book contains contributions from computational biomechanics specialists who present and exchange opinions on the opportunities for applying their techniques to computer-integrated medicine, including computer-aided surgery and diagnostic systems. Computational Biomechanics for Medicine collects peer-reviewed chapters from the annual Computational Biomechanics for Medicine Workshop, in conjunction with the Medical Image Computing and Computer Assisted Intervention [MICCAI] Society conference. The works are dedicated to research in the field of methods and applications of computational biomechanics to medical image analysis, image-guided surgery, surgical simulation, surgical intervention planning, disease diagnosis and prognosis, analysis of injury mechanisms, implant and prosthesis design, artificial organ design, and medical robotics. These chapters will appeal to a wide range of researchers and students within the fields of engineering and medicine, as well as those working in computational science.
Computational Biomechanics for Medicine: Models, Algorithms And Implementation
by Poul M.F. Nielsen Karol MillerMathematical modelling and computer simulation have proved tremendously successful in engineering. One of the greatest challenges for mechanists is to extend the success of computational mechanics to fields outside traditional engineering, in particular to biology, biomedical sciences, and medicine. The proposed workshop will provide an opportunity for computational biomechanics specialists to present and exchange opinions on the opportunities of applying their techniques to computer-integrated medicine. For example, continuum mechanics models provide a rational basis for analysing biomedical images by constraining the solution to biologically reasonable motions and processes. Biomechanical modelling can also provide clinically important information about the physical status of the underlying biology, integrating information across molecular, tissue, organ, and organism scales. The main goal of this workshop is to showcase the clinical and scientific utility of computational biomechanics in computer-integrated medicine.
Computational Business Analytics (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series #34)
by Subrata DasThis book presents tools and techniques for descriptive, predictive, and prescriptive analytics applicable across multiple domains. The author first covers core descriptive and inferential statistics for analytics and then enhances numerical statistical techniques with symbolic artificial intelligence and machine learning techniques for richer predictive and prescriptive analytics. Through many examples and challenging case studies from a variety of fields, practitioners easily see the connections to their own problems and can then formulate their own solution strategies.
Computational Calculus: A Numerical Companion to Elementary Calculus (Synthesis Lectures on Mathematics & Statistics)
by William C. BauldryThis book offers readers the methods that are necessary to apply the power of calculus to analyze real problems. While most calculus textbooks focus on formula-based calculus, this book explains how to do the analysis of calculus, rates of change, and accumulation from data. The author’s introductory approach prepares students with the techniques to handle numerically-based problems in more advanced classes or in real-world applications. This self-contained book uses the computer algebra system Maple for computation, and the material is easily adaptable for calculators or other computer algebra systems. The author includes historical context and example exercises throughout the book in order to provide readers with a thorough understanding of the topic. This book:Prepares students with the techniques to handle numerically-based problems in in real-world applicationsProvides historical context and example exercises to give a thorough understanding of the topicUtilizes Maple for computation and is adaptable for calculators or other computer algebra systems
Computational Cancer Biology: An Interaction Network Approach (SpringerBriefs in Electrical and Computer Engineering)
by Mathukumalli VidyasagarThis brief introduces people with a basic background in probability theory to various problems in cancer biology that are amenable to analysis using methods of probability theory and statistics. The title mentions "cancer biology" and the specific illustrative applications reference cancer data but the methods themselves are more broadly applicable to all aspects of computational biology. Aside from providing a self-contained introduction to basic biology and to cancer, the brief describes four specific problems in cancer biology that are amenable to the application of probability-based methods. The application of these methods is illustrated by applying each of them to actual data from the biology literature. After reading the brief, engineers and mathematicians should be able to collaborate fruitfully with their biologist colleagues on a wide variety of problems.
Computational Collective Intelligence: 14th International Conference, ICCCI 2022, Hammamet, Tunisia, September 28–30, 2022, Proceedings (Lecture Notes in Computer Science #13501)
by Richard Chbeir Ngoc Thanh Nguyen Yannis Manolopoulos Bogdan Trawiński Adrianna KozierkiewiczThis book constitutes the refereed proceedings of the 14th International Conference on Computational Collective Intelligence, ICCCI 2022, held in Hammamet, Tunisia, in September 2022. The 56 full papers and 10 short papers were carefully reviewed and selected from 420 submissions. The papers are grouped in topical sections on collective intelligence and collective decision-making; deep learning techniques; natural language processing; data minning and machine learning; knowledge engineering and semantic web; computer vision techniques; social networks and intelligent systems; cybersecurity and internet of things; cooperative strategies for decision making and optimization; computational intelligence for digital content understanding; applications for industry 4.0.
Computational Collective Intelligence: 8th International Conference, ICCCI 2016, Halkidiki, Greece, September 28-30, 2016. Proceedings, Part I (Lecture Notes in Computer Science #9875)
by Yannis Manolopoulos Lazaros Iliadis Bogdan Trawiński Ngoc-Thanh NguyenCollective intelligence has become one of major research issues studied by today's and future computer science. Computational collective intelligence is understood as this form of group intellectual activity that emerges from collaboration and compe- tion of many artificial individuals. Robotics, artificial intelligence, artificial cognition and group working try to create efficient models for collective intelligence in which it emerges from sets of actions carried out by more or less intelligent individuals. The major methodological, theoretical and practical aspects underlying computational collective intelligence are group decision making, collective action coordination, collective competition and knowledge description, transfer and integration. Obviously, the application of multiple computational technologies such as fuzzy systems, evo- tionary computation, neural systems, consensus theory, knowledge representation etc. is necessary to create new forms of computational collective intelligence and support existing ones. Three subfields of application of computational technologies to support forms of collective intelligence are of special attention to us. The first one is semantic web treated as an advanced tool that increases the collective intelligence in networking environments. The second one covers social networks modeling and analysis, where social networks are this area of in which various forms of computational collective intelligence emerges in a natural way. The third subfield relates us to agent and mul- agent systems understood as this computational and modeling paradigm which is especially tailored to capture the nature of computational collective intelligence in populations of autonomous individuals.
Computational Collective Intelligence: 15th International Conference, ICCCI 2023, Budapest, Hungary, September 27–29, 2023, Proceedings (Lecture Notes in Computer Science #14162)
by Ngoc Thanh Nguyen János Botzheim László Gulyás Manuel Núñez Jan Treur Gottfried Vossen Adrianna KozierkiewiczThis book constitutes the refereed proceedings of the 15th International Conference on Computational Collective Intelligence, ICCCI 2023, held in Budapest, Hungary, during September 27–29, 2023.The 63 full papers included in this book were carefully reviewed and selected from 218 submissions. They are organized in topical sections as follows: collective intelligence and collective decision-making; deep learning techniques; natural language processing; data mining and machine learning; social networks and intelligent systems; cybersecurity, blockchain technology and Internet of Things; cooperative strategies for decision making and optimization; computational intelligence for digital content understanding; knowledge engineering and application for Industry 4.0; computational intelligence in medical applications; and ensemble models and data fusion.
Computational Collective Intelligence: 11th International Conference, ICCCI 2019, Hendaye, France, September 4–6, 2019, Proceedings, Part II (Lecture Notes in Computer Science #11684)
by Ngoc Thanh Nguyen Richard Chbeir Ernesto Exposito Philippe Aniorté Bogdan TrawińskiThis two-volume set (LNAI 11683 and LNAI 11684) constitutes the refereed proceedings of the 11th International Conference on Computational Collective Intelligence, ICCCI 2019, held in Hendaye France, in September 2019.The 117 full papers presented were carefully reviewed and selected from 200 submissions. The papers are grouped in topical sections on: computational collective intelligence and natural language processing; machine learning in real-world data; distributed collective intelligence for smart manufacturing; collective intelligence for science and technology; intelligent management information systems; intelligent sustainable smart cities; new trends and challenges in education: the university 4.0; intelligent processing of multimedia in web systems; and big data streaming, applications and security.