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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 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 Structural Bioinformatics: International Workshop, CSBW 2024, Boston, MA, USA, November 16, 2024, Proceedings (Communications in Computer and Information Science #2396)
by Nurit Haspel Kevin MolloyThis book constitutes the proceedings of the Computational Structural Bioinformatics Workshop, CMSB 2024, which took place in Boston, MA, USA, on November 16, 2024. The 7 papers presented in this book were carefully reviewed and selected for inclusion in the proceedings. They deal with relevant problems in classification, modeling and analyzing protein structures and complexes.
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 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 Emmanuel Barillot Laurence Calzone Philippe Hupe Jean-Philippe Vert 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 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 Techniques for Biological Sequence Analysis
by Ranjeet Kumar Rout Saiyed Umer Monika Khandelwal Smitarani PatiThis book provides an overview of basic and advanced computational techniques for analyzing and understanding protein, RNA, and DNA sequences. It covers effective computing techniques for DNA and protein classifications, evolutionary and sequence information analysis, evolutionary algorithms, and ensemble algorithms. Furthermore, the book reviews the role of machine learning techniques, artificial intelligence, ensemble learning, and sequence-based features in predicting post-translational modifications in proteins, DNA methylation, and mRNA methylation, along with their functional implications. The book also discusses the prediction of protein–protein and protein–DNA interactions, protein structure, and function using computational methods. It also presents techniques for quantitative analysis of protein–DNA interactions and protein methylation and their involvement in gene regulation. Additionally, the use of nature-inspired algorithms to gain insights into gene regulatory mechanisms and metabolic pathways in human diseases is explored. This book acts as a useful reference for bioinformaticians and computational biologists working in the fields of molecular biology, genomics, and bioinformatics.Key Features: Reviews machine learning techniques for DNA sequence classification and protein structure prediction Discusses genetic algorithms for analyzing multiple sequence alignments and predicting protein–protein interaction sites Explores computational methods for quantitative analysis of protein–DNA interactions Examine the role of nature-inspired algorithms in understanding the gene regulation and metabolic pathways Covers evolutionary algorithms and sequence-based features in predicting post-translational modifications
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.
Computational Techniques for Text Summarization based on Cognitive Intelligence
by V. Priya K. UmamaheswariThe book is concerned with contemporary methodologies used for automatic text summarization. It proposes interesting approaches to solve well-known problems on text summarization using computational intelligence (CI) techniques including cognitive approaches. A better understanding of the cognitive basis of the summarization task is still an open research issue; an extent of its use in text summarization is highlighted for further exploration. With the ever-growing text, people in research have little time to spare for extensive reading, where summarized information helps for a better understanding of the context at a shorter time. This book helps students and researchers to automatically summarize the text documents in an efficient and effective way. The computational approaches and the research techniques presented guides to achieve text summarization at ease. The summarized text generated supports readers to learn the context or the domain at a quicker pace. The book is presented with reasonable amount of illustrations and examples convenient for the readers to understand and implement for their use. It is not to make readers understand what text summarization is, but for people to perform text summarization using various approaches. This also describes measures that can help to evaluate, determine, and explore the best possibilities for text summarization to analyse and use for any specific purpose. The illustration is based on social media and healthcare domain, which shows the possibilities to work with any domain for summarization. The new approach for text summarization based on cognitive intelligence is presented for further exploration in the field.
Computational Technologies and Electronics: First International Conference, ICCTE 2023, Siliguri, India, November 23–25, 2023, Proceedings, Part I (Communications in Computer and Information Science #2376)
by Samarjit Chakraborty Mukta Majumder J. K. M. Sadique Uz Zaman Mili GhoshThis two-volume set, CCIS 2376 and CCIS 2377, constitutes proceedings from the First International Conference on Computational Technologies and Electronics, ICCTE 2023, held in Siliguri, India, during November 23–25, 2023. The 46 full papers presented here were carefully selected and reviewed from 157 submissions. These papers have been organized in the following topical sections: Pat I- Pattern recognition & AI Part II- Data communication & security; Applied electronics.
Computational Technologies and Electronics: First International Conference, ICCTE 2023, Siliguri, India, November 23–25, 2023, Proceedings, Part II (Communications in Computer and Information Science #2377)
by Samarjit Chakraborty Mukta Majumder J. K. M. Sadique Uz Zaman Mili GhoshThis two-volume set, CCIS 2376 and CCIS 2377, constitutes proceedings from the First International Conference on Computational Technologies and Electronics, ICCTE 2023, held in Siliguri, India, during November 23–25, 2023. The 46 full papers presented here were carefully selected and reviewed from 157 submissions. These papers have been organized in the following topical sections: Pat I- Pattern recognition & AI Part II- Data communication & security; Applied electronics.
Computational Technology For Effective Health Care: Immediate Steps And Strategic Directions
by National Research Council of the National AcademiesDespite a strong commitment to delivering quality health care, persistent problems involving medical errors and ineffective treatment continue to plague the industry. Many of these problems are the consequence of poor information and technology (IT) capabilities, and most importantly, the lack cognitive IT support. Clinicians spend a great deal of time sifting through large amounts of raw data, when, ideally, IT systems would place raw data into context with current medical knowledge to provide clinicians with computer models that depict the health status of the patient. Computational Technology for Effective Health Care advocates re-balancing the portfolio of investments in health care IT to place a greater emphasis on providing cognitive support for health care providers, patients, and family caregivers; observing proven principles for success in designing and implementing IT; and accelerating research related to health care in the computer and social sciences and in health/biomedical informatics. Health care professionals, patient safety advocates, as well as IT specialists and engineers, will find this book a useful tool in preparation for crossing the health care IT chasm.
Computational Theory of Mind for Human-Machine Teams: First International Symposium, ToM for Teams 2021, Virtual Event, November 4–6, 2021, Revised Selected Papers (Lecture Notes in Computer Science #13775)
by Gita Sukthankar Nikolos GurneyThis book constitutes the proceedings of the First International Symposium, ToM for Teams 2021, held in Washington, DC, USA, during November 4–6, 2021, Each chapter in this section tackles a different aspect of AI representing the thoughts and beliefs of human agents. The work presented herein represents our collective efforts to better understand ToM, develop AI with ToM capabilities (ASI), and study how to integrate such systems into human teams.
Computational Thermo-kinetics of Rigid Polyurethane Foams: Theory and Applications (SpringerBriefs in Applied Sciences and Technology)
by Arnold A. Lubguban Roberto M. Malaluan Gerard G. Dumancas Arnold C. AlgunoThis book presents a detailed exploration of advanced computational modeling techniques in the design, testing, and applications of rigid polyurethane foams (RPUFs). By leveraging modern approaches such as database-driven predictions, iterative simulations, and emerging innovations in computational material engineering, it offers a more accurate and efficient way to model the thermo-kinetic behavior of RPUFs. The necessity for computational tools in materials science is intertwined with the growth of the polyurethane market, with many academic and industrial researchers seeking to adopt these methods. The book comprehensively discusses the advancement in bridging the gap between traditional empirical methods and cutting-edge computational techniques specifically applied to RPUFs. Furthermore, it is a comprehensive guide to the computational modeling of the thermo-kinetics of RPUFs, making it an essential resource for researchers, engineers, and academicians seeking to innovate in material science and engineering. This book addresses a niche yet critical area within this broader scope.
Computational Thinking (The MIT Press Essential Knowledge Series)
by Matti Tedre Peter J. DenningAn introduction to computational thinking that traces a genealogy beginning centuries before the digital computer. A few decades into the digital era, scientists discovered that thinking in terms of computation made possible an entirely new way of organizing scientific investigation; eventually, every field had a computational branch: computational physics, computational biology, computational sociology. More recently, “computational thinking” has become part of the K–12 curriculum. But what is computational thinking? This volume in the MIT Press Essential Knowledge series offers an accessible overview, tracing a genealogy that begins centuries before digital computers and portraying computational thinking as pioneers of computing have described it. The authors explain that computational thinking (CT) is not a set of concepts for programming; it is a way of thinking that is honed through practice: the mental skills for designing computations to do jobs for us, and for explaining and interpreting the world as a complex of information processes. Mathematically trained experts (known as “computers”) who performed complex calculations as teams engaged in CT long before electronic computers. The authors identify six dimensions of today's highly developed CT—methods, machines, computing education, software engineering, computational science, and design—and cover each in a chapter. Along the way, they debunk inflated claims for CT and computation while making clear the power of CT in all its complexity and multiplicity.
Computational Thinking Education
by Siu-Cheung Kong Harold AbelsonThis This book is open access under a CC BY 4.0 license.This book offers a comprehensive guide, covering every important aspect of computational thinking education. It provides an in-depth discussion of computational thinking, including the notion of perceiving computational thinking practices as ways of mapping models from the abstraction of data and process structures to natural phenomena. Further, it explores how computational thinking education is implemented in different regions, and how computational thinking is being integrated into subject learning in K-12 education. In closing, it discusses computational thinking from the perspective of STEM education, the use of video games to teach computational thinking, and how computational thinking is helping to transform the quality of the workforce in the textile and apparel industry.
Computational Thinking Education in K-12: Artificial Intelligence Literacy and Physical Computing
by Siu-Cheung Kong and Harold AbelsonA guide to computational thinking education, with a focus on artificial intelligence literacy and the integration of computing and physical objects. Computing has become an essential part of today&’s primary and secondary school curricula. In recent years, K–12 computer education has shifted from computer science itself to the broader perspective of computational thinking (CT), which is less about technology than a way of thinking and solving problems—&“a fundamental skill for everyone, not just computer scientists,&” in the words of Jeanette Wing, author of a foundational article on CT. This volume introduces a variety of approaches to CT in K–12 education, offering a wide range of international perspectives that focus on artificial intelligence (AI) literacy and the integration of computing and physical objects. The book first offers an overview of CT and its importance in K–12 education, covering such topics as the rationale for teaching CT; programming as a general problem-solving skill; and the &“phenomenon-based learning&” approach. It then addresses the educational implications of the explosion in AI research, discussing, among other things, the importance of teaching children to be conscientious designers and consumers of AI. Finally, the book examines the increasing influence of physical devices in CT education, considering the learning opportunities offered by robotics. ContributorsHarold Abelson, Cynthia Breazeal, Karen Brennan, Michael E. Caspersen, Christian Dindler, Daniella DiPaola, Nardie Fanchamps, Christina Gardner-McCune, Mark Guzdial, Kai Hakkarainen, Fredrik Heintz, Paul Hennissen, H. Ulrich Hoppe, Ole Sejer Iversen, Siu-Cheung Kong, Wai-Ying Kwok, Sven Manske, Jesús Moreno-León, Blakeley H. Payne, Sini Riikonen, Gregorio Robles, Marcos Román-González, Pirita Seitamaa-Hakkarainen, Ju-Ling Shih, Pasi Silander, Lou Slangen, Rachel Charlotte Smith, Marcus Specht, Florence R. Sullivan, David S. Touretzky
Computational Thinking and Coding for Every Student: The Teacher’s Getting-Started Guide
by Jane Krauss Kiki ProttsmanEmpower tomorrow’s tech innovators Our students are avid users and consumers of technology. Isn’t it time that they see themselves as the next technological innovators, too? Computational Thinking and Coding for Every Student is the beginner’s guide for K-12 educators who want to learn to integrate the basics of computer science into their curriculum. Readers will find Practical strategies for teaching computational thinking and the beginning steps to introduce coding at any grade level, across disciplines, and during out-of-school time Instruction-ready lessons and activities for every grade Specific guidance for designing a learning pathway for elementary, middle, or high school students Justification for making coding and computer science accessible to all A glossary with definitions of key computer science terms, a discussion guide with tips for making the most of the book, and companion website with videos, activities, and other resources Momentum for computer science education is growing as educators and parents realize how fundamental computing has become for the jobs of the future. This book is for educators who see all of their students as creative thinkers and active contributors to tomorrow’s innovations. "Kiki Prottsman and Jane Krauss have been at the forefront of the rising popularity of computer science and are experts in the issues that the field faces, such as equity and diversity. In this book, they’ve condensed years of research and practitioner experience into an easy to read narrative about what computer science is, why it is important, and how to teach it to a variety of audiences. Their ideas aren’t just good, they are research-based and have been in practice in thousands of classrooms…So to the hundreds and thousands of teachers who are considering, learning, or actively teaching computer science—this book is well worth your time." Pat Yongpradit Chief Academic Officer, Code.org
Computational Thinking and Coding for Every Student: The Teacher’s Getting-Started Guide
by Jane Krauss Kiki ProttsmanEmpower tomorrow’s tech innovators Our students are avid users and consumers of technology. Isn’t it time that they see themselves as the next technological innovators, too? Computational Thinking and Coding for Every Student is the beginner’s guide for K-12 educators who want to learn to integrate the basics of computer science into their curriculum. Readers will find Practical strategies for teaching computational thinking and the beginning steps to introduce coding at any grade level, across disciplines, and during out-of-school time Instruction-ready lessons and activities for every grade Specific guidance for designing a learning pathway for elementary, middle, or high school students Justification for making coding and computer science accessible to all A glossary with definitions of key computer science terms, a discussion guide with tips for making the most of the book, and companion website with videos, activities, and other resources Momentum for computer science education is growing as educators and parents realize how fundamental computing has become for the jobs of the future. This book is for educators who see all of their students as creative thinkers and active contributors to tomorrow’s innovations. "Kiki Prottsman and Jane Krauss have been at the forefront of the rising popularity of computer science and are experts in the issues that the field faces, such as equity and diversity. In this book, they’ve condensed years of research and practitioner experience into an easy to read narrative about what computer science is, why it is important, and how to teach it to a variety of audiences. Their ideas aren’t just good, they are research-based and have been in practice in thousands of classrooms…So to the hundreds and thousands of teachers who are considering, learning, or actively teaching computer science—this book is well worth your time." Pat Yongpradit Chief Academic Officer, Code.org