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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 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 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 Nikolos Gurney Gita SukthankarThis 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 Thinking: A Beginner's Guide to Problem-Solving and Programming
by Karl BeecherComputational thinking is a timeless, transferable skill that enables you to think more clearly and logically, as well as a way to solve specific problems. <p><p> Beginning with the core ideas of computational thinking, with this book you'll build up an understanding of the practical problem-solving approach and explore how computational thinking aids good practice in programming, complete with a full guided example.
Computational Thinking: Des Welt des algorithmischen Denkens – in Spielen, Zaubertricks und Rätseln
by Paul Curzon Peter W. McOwan Bernhard GerlIn diesem Buch lernen Sie die Grundzüge und Vorteile des Computational Thinking kennen, also des analytischen, von Algorithmen geprägten Denkens. Die Autoren behandeln dabei unterhaltsam und anwendungsbezogen die Grundelemente dieser Denkweise - darunter Denken in Algorithmen, Zerlegung, Abstraktion und Mustererkennung. Diese Prinzipien werden anschaulich an Hand von Zaubertricks, Spielen und Rätseln, aber auch an echten, anspruchsvollen Problemen erklärt. Sie erkunden dabei auch die Verbindungen zwischen Computational Thinking und wissenschaftlichem, aber auch kreativem Denken - und wie daraus Innovationen entstehen können.Computational Thinking hat die Art und Weise, wie wir alle leben, arbeiten und spielen, verändert. Es hat Auswirkungen darauf, wie Wissenschaft betrieben wird, Kriege gewonnen, ganz neue Industrien geschaffen und Leben gerettet werden. Es ist das Herzstück der Programmierung und ein leistungsfähiger Ansatz zur Problemlösung, mit oder ohne Computer. In einigen Ländern werden bereits Kindern in der Grundschule diese Fertigkeiten beigebracht.Ob Sie also einfach wissen wollen, um was es beim Computational Thinking geht oder ob Sie neue Möglichkeiten finden wollen, auch im Alltag effektiver zu werden, ob Sie (Informatik-)Lehrer oder Schüler sind oder einfach Spaß an Spielen und Rätseln haben – in diesem Buch finden Sie die nötigen Grundlagen.
Computational Thinking (The MIT Press Essential Knowledge Series)
by Peter J. Denning Matti TedreAn 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 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 Strategies and activities for teaching computational thinking and coding inside and outside of school, at any grade level, across disciplines Instruction-ready lessons for every grade A discussion guide and companion website with videos, activities, and other resources
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 Strategies and activities for teaching computational thinking and coding inside and outside of school, at any grade level, across disciplines Instruction-ready lessons for every grade A discussion guide and companion website with videos, activities, and other resources
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 in Education: A Pedagogical Perspective
by Aman YadavComputational Thinking in Education explores the relevance of computational thinking in primary and secondary education. As today’s school-aged students prepare to live and work in a thoroughly digitized world, computer science is providing a wealth of new learning concepts and opportunities across domains. This book offers a comprehensive overview of computational thinking, its history, implications for equity and inclusion, analyses of competencies in practice, and integration into learning, instruction, and assessment through scaffolded teacher education. Computer science education faculty and pre- and in-service educators will find a fresh pedagogical approach to computational thinking in primary and secondary classrooms.
Computational Thinking in the STEM Disciplines: Foundations And Research Highlights
by Myint Swe KhineThis book covers studies of computational thinking related to linking, infusing, and embedding computational thinking elements to school curricula, teacher education and STEM related subjects. Presenting the distinguished and exemplary works by educators and researchers in the field highlighting the contemporary trends and issues, creative and unique approaches, innovative methods, frameworks, pedagogies and theoretical and practical aspects in computational thinking. A decade ago the notion of computational thinking was introduced by Jeannette Wing and envisioned that computational thinking will be a fundamental skill that complements to reading, writing and arithmetic for everyone and represents a universally applicable attitude. The computational thinking is considered a thought processes involved in a way of solving problems, designing systems, and understanding human behaviour. Assimilating computational thinking at young age will assist them to enhance problem solving skills, improve logical reasoning, and advance analytical ability - key attributes to succeed in the 21st century. Educators around the world are investing their relentless effort in equipping the young generation with real-world skills ready for the demand and challenges of the future. It is commonly believed that computational thinking will play a pivotal and dominant role in this endeavour. Wide-ranging research on and application of computational thinking in education have been emerged in the last ten years. This book will document attempts to conduct systematic, prodigious and multidisciplinary research in computational thinking and present their findings and accomplishments.
Computational Thinking: A Perspective on Computer Science
by Zhiwei Xu Jialin ZhangThis textbook is intended as a textbook for one-semester, introductory computer science courses aimed at undergraduate students from all disciplines. Self-contained and with no prerequisites, it focuses on elementary knowledge and thinking models. The content has been tested in university classrooms for over six years, and has been used in summer schools to train university and high-school teachers on teaching introductory computer science courses using computational thinking. This book introduces computer science from a computational thinking perspective. In computer science the way of thinking is characterized by three external and eight internal features, including automatic execution, bit-accuracy and abstraction. The book is divided into chapters on logic thinking, algorithmic thinking, systems thinking, and network thinking. It also covers societal impact and responsible computing material – from ICT industry to digital economy, from the wonder of exponentiation to wonder of cyberspace, and from code of conduct to best practices for independent work. The book’s structure encourages active, hands-on learning using the pedagogic tool Bloom's taxonomy to create computational solutions to over 200 problems of varying difficulty. Students solve problems using a combination of thought experiment, programming, and written methods. Only 300 lines of code in total are required to solve most programming problems in this book.
Computational Topology in Image Context: 6th International Workshop, CTIC 2016, Marseille, France, June 15-17, 2016, Proceedings (Lecture Notes in Computer Science #9667)
by Alexandra Bac Jean-Luc MariThis book constitutes the proceedings of the 6th International Workshop on Computational Topology in Image Context, CTIC 2016, held in Marseille, France, in June 2016. The 24 papers presented in this volume were carefully reviewed and selected from 35 submissions. Additionally, this volume contains 2 invited papers. CTIC covers a wide range of topics such as: topological invariants and their computation, homology, cohomology, linking number, fundamental groups; algorithm optimization in discrete geometry, transfer of mathematical tools, parallel computation in multi-dimensional volume context, hierarchical approaches; experimental evaluation of algorithms and heuristics; combinatorial or multi-resolution models; discrete or computational topology; geometric modeling guided by topological constraints; computational topological dynamics; and use of topological information in discrete geometry applications.
Computational Topology in Image Context: 7th International Workshop, CTIC 2019, Málaga, Spain, January 24-25, 2019, Proceedings (Lecture Notes in Computer Science #11382)
by Rebeca Marfil Mariletty Calderón Fernando Díaz del Río Pedro Real Antonio BanderaThis book constitutes the proceedings of the 7th International Workshop on Computational Topology in Image Context, CTIC 2019, held in Málaga, Spain, in January 2019. The 14 papers presented in this volume were carefully reviewed and selected from 21 submissions. Papers deal with theoretical issues but most of them put the attention on the applicability of concepts and algorithms. These were designed to deal with objects and images, but also with the speech signal. The final application must be for instance in the medical domain or in the robotics one.
A Computational View of Autism: Using Virtual Reality Technologies in Autism Intervention
by Uttama LahiriThis book first explains autism, its prevalence, and some conventional intervention techniques, and it then describes how virtual reality technology can support autism intervention and skills training. The approaches and technologies covered include immersive virtual reality, augmented reality and mixed reality. The tasks covered include emotion recognition, affective computing, teaching communication skills, imparting literacy skills, training for imitation skills, and joint attention skills. Most of the chapters assume no prerequisite knowledge of autism or virtual reality, and they are supported throughout with detailed references for further investigation.While the author is an engineer by profession, with specialist knowledge in robotics and computer-based platforms, in this book she adopts a user perspective and cites many real-life examples from her own experience. The book is suitable for students of cognitive science, and researchers and practitioners engaged with designing and offering technological assistance for special needs training.