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Computational Fluid and Particle Dynamics in the Human Respiratory System (Biological and Medical Physics, Biomedical Engineering)
by Goodarz Ahmadi Jiyuan Tu Kiao InthavongTraditional research methodologies in the human respiratory system have always been challenging due to their invasive nature. Recent advances in medical imaging and computational fluid dynamics (CFD) have accelerated this research. This book compiles and details recent advances in the modelling of the respiratory system for researchers, engineers, scientists, and health practitioners. It breaks down the complexities of this field and provides both students and scientists with an introduction and starting point to the physiology of the respiratory system, fluid dynamics and advanced CFD modeling tools. In addition to a brief introduction to the physics of the respiratory system and an overview of computational methods, the book contains best-practice guidelines for establishing high-quality computational models and simulations. Inspiration for new simulations can be gained through innovative case studies as well as hands-on practice using pre-made computational code. Last but not least, students and researchers are presented the latest biomedical research activities, and the computational visualizations will enhance their understanding of physiological functions of the respiratory system.
Computational Gasdynamics
by Culbert B. LaneyNumerical methods are indispensable tools in the analysis of complex fluid flows. This book focuses on computational techniques for high-speed gas flows, especially gas flows containing shocks and other steep gradients. The book decomposes complicated numerical methods into simple modular parts, showing how each part fits and how each method relates to or differs from others. The text begins with a review of gasdynamics and computational techniques. Next come basic principles of computational gasdynamics. The last two parts cover basic techniques and advanced techniques. Senior and graduate level students, especially in aerospace engineering, as well as researchers and practising engineers, will find a wealth of invaluable information on high-speed gas flows in this text.
Computational Genomics with R (Chapman & Hall/CRC Computational Biology Series)
by Altuna AkalinComputational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.
Computational Geomechanics and Hydraulic Structures (Springer Tracts in Civil Engineering)
by Sheng-Hong ChenThis book presents recent research into developing and applying computational tools to estimate the performance and safety of hydraulic structures from the planning and construction stage to the service period. Based on the results of a close collaboration between the author and his colleagues, friends, students and field engineers, it shows how to achieve a good correlation between numerical computation and the actual in situ behavior of hydraulic structures. The book’s heuristic and visualized style disseminates the philosophy and road map as well as the findings of the research. The chapters reflect the various aspects of the three typical and practical methods (the finite element method, the block element method, the composite element method) that the author has been working on and made essential contributions to since the 1980s. This book is an advanced continuation of Hydraulic Structures by the same author, published by Springer in 2015.
Computational Geomechanics: Theory and Applications
by Manuel Pastor Andrew H. Chan Bernhard A. Schrefler Tadahiko Shiomi Olgierd C. ZienkiewiczCOMPUTATIONAL GEOMECHANICS The new edition of the first book to cover the computational dynamic aspects of geomechanics, now including more practical applications and up-to-date coverage of current research in the field Advances in computational geomechanics have dramatically improved understanding of the behavior of soils and the ability of engineers to design increasingly sophisticated constructions in the ground. When Professor Olek Zienkiewicz began the application of numerical approaches to solid dynamics at Swansea University, it became evident that realistic prediction of the behavior of soil masses could only be achieved if the total stress approaches were abandoned. Computational Geomechanics introduces the theory and application of Zienkiewicz’s computational approaches that remain the basis for work in the area of saturated and unsaturated soil to this day. Written by past students and colleagues of Professor Zienkiewicz, this extended Second Edition provides formulations for a broader range of problems, including failure load under static loading, saturated and unsaturated consolidation, hydraulic fracturing, and liquefaction of soil under earthquake loading. The internationally-recognized team of authors incorporates current computer technologies and new developments in the field, particularly in the area of partial saturation, as they guide readers on how to properly apply the formulation in their work. This one-of-a-kind volume: Explains the Biot-Zienkiewicz formulation for saturated and unsaturated soil Covers multiple applications to static and dynamic problems for saturated and unsaturated soil in areas such as earthquake engineering and fracturing of soils and rocks Features a completely new chapter on fast catastrophic landslides using depth integrated equations and smoothed particle hydrodynamics with applications Presents the theory of porous media in the saturated and unsaturated states to establish the foundation of the problem of soil mechanics Provides a quantitative description of soil behavior including simple plasticity models, generalized plasticity, and critical state soil mechanics Includes numerous questions, problems, hands-on experiments, applications to other situations, and example code for GeHoMadrid Computational Geomechanics: Theory and Applications, Second Edition is an ideal textbook for specialist and general geotechnical postgraduate courses, and a must-have reference for researchers in geomechanics and geotechnical engineering, for software developers and users of geotechnical finite element software, and for geotechnical analysts and engineers making use of the numerical results obtained from the Biot-Zienkiewicz formulation.
Computational Granular Mechanics and Its Engineering Applications (Springer Tracts in Mechanical Engineering)
by Lu Liu Shunying JiThis book systematically introduces readers to computational granular mechanics and its relative engineering applications. Part I describes the fundamentals, such as the generation of irregular particle shapes, contact models, macro-micro theory, DEM-FEM coupling, and solid-fluid coupling of granular materials. It also discusses the theory behind various numerical methods developed in recent years. Further, it provides the GPU-based parallel algorithm to guide the programming of DEM and examines commercial and open-source codes and software for the analysis of granular materials. Part II focuses on engineering applications, including the latest advances in sea-ice engineering, railway ballast dynamics, and lunar landers. It also presents a rational method of parameter calibration and thorough analyses of DEM simulations, which illustrate the capabilities of DEM. The computational mechanics method for granular materials can be applied widely in various engineering fields, such as rock and soil mechanics, ocean engineering and chemical process engineering.
Computational Heat Transfer (Series In Computational And Physical Processes In Mechanics And Thermal Sciences Ser.)
by Yogesh JaluriaThis new edition updated the material by expanding coverage of certain topics, adding new examples and problems, removing outdated material, and adding a computer disk, which will be included with each book. Professor Jaluria and Torrance have structured a text addressing both finite difference and finite element methods, comparing a number of applicable methods.
Computational Homogenization of Heterogeneous Materials with Finite Elements (Solid Mechanics and Its Applications #258)
by Julien YvonnetThis monograph provides a concise overview of the main theoretical and numerical tools to solve homogenization problems in solids with finite elements. Starting from simple cases (linear thermal case) the problems are progressively complexified to finish with nonlinear problems. The book is not an overview of current research in that field, but a course book, and summarizes established knowledge in this area such that students or researchers who would like to start working on this subject will acquire the basics without any preliminary knowledge about homogenization. More specifically, the book is written with the objective of practical implementation of the methodologies in simple programs such as Matlab. The presentation is kept at a level where no deep mathematics are required.
Computational Hydraulics and Hydrology: An Illustrated Dictionary
by Nicolas G. AdrienComputational hydraulics and hydrologic modeling are rapidly developing fields with a wide range of applications in areas ranging from wastewater disposal and stormwater management to civil and environmental engineering. These fields are full of promise, but the abundance of literature that now exists contains many new terms that are not always def
Computational Hydrodynamics of Capsules and Biological Cells (Chapman & Hall/CRC Computational Biology Series)
by C. PozrikidisSpanning biological, mathematical, computational, and engineering sciences, computational biofluiddynamics addresses a diverse family of problems involving fluid flow inside and around living organisms, organs, tissue, biological cells, and other biological materials. Computational Hydrodynamics of Capsules and Biological Cells provides a comprehen
Computational Immunology: Applications
by Shyamasree GhoshComputational Immunology: Applications focuses on different mathematical models, statistical tools, techniques, and computational modelling that helps in understanding complex phenomena of the immune system and its biological functions. The book also focuses on the latest developments in computational biology in designing of drugs, targets, biomarkers for early detection and prognosis of a disease. It highlights the applications of computational methods in deciphering the complex processes of the immune system and its role in health and disease. This book discusses the most essential topics, including Next generation sequencing (NGS) and computational immunology Computational modelling and biology of diseases Drug designing Computation and identification of biomarkers Application in organ transplantation Application in disease detection and therapy Computational methods and applications in understanding of the invertebrate immune system Shyamasree Ghosh (MSc, PhD, PGDHE, PGDBI) Scientific Officer (F), is currently working in the School of Biological Sciences, National Institute of Science Education and Research (NISER), Bhubaneswar, DAE, Govt of India, graduated from the prestigious Presidency College Kolkata in 1998. She was awarded the prestigious National Scholarship from the Government of India. She has worked and published extensively in glycobiology, sialic acids, immunology, stem cells and nanotechnology. She has authored several publications that include books and encyclopedia chapters in reputed journals and books.
Computational Immunology: Basics
by Shyamasree GhoshThe immune system is highly complex system with large number of macromolecules, signaling pathways, protein-protein interactions, and gene expressions. Studies from genomics, transcriptomics, metabolomics are generating huge high throughput data that needs to be analyzed for understanding the Immune system in Health and Disease. Computational approaches arehelping in understanding the study of complex biology of immunology and thereby enabling design of therapeutic strategies in diseases like infectious diseases, immunodeficiency, allergic, hypersensitive, autoimmune disorders and diseases like Cancer, HIV etc. Computational Immunology: Basics highlights the basics of the immune system and function in health and disease. This book offers comprehensive coverage of the most essential topics, including Overview of Immunology and computational Immunology Immune organs and cells, antigen, antibody, B, cell, T cell Antigen Processing and presentation Diseases due to abnormalities of the immune system Cancer Biology Shyamasree Ghosh (MSc, PhD, PGDHE, PGDBI), is currently working in the School of Biological Sciences, National Institute of Science Education and Research (NISER), Bhubaneswar, DAE, Govt of India, graduated from the prestigious Presidency College Kolkata in 1998. She was awarded the prestigious National Scholarship from the Government of India. She has worked and published extensively in glycobiology, sialic acids, immunology, stem cells and nanotechnology. She has authored several publications that include books and encyclopedia chapters in reputed journals and books.
Computational Inorganic and Bioinorganic Chemistry
by Robert A. Scott Edward I. Solomon R. Bruce KingOver the past several decades there have been major advances in our ability to computationally evaluate the electronic structure of inorganic molecules, particularly transition metal systems. This advancement is due to the Moore's Law increase in computing power as well as the impact of density functional theory (DFT) and its implementation in commercial and freeware programs for quantum chemical calculations. Improved pure and hybrid density functionals are allowing DFT calculations with accuracy comparable to high-level Hartree-Fock treatments, and the results of these calculations can now be evaluated by experiment.When calculations are correlated to, and supported by, experimental data they can provide fundamental insight into electronic structure and its contributions to physical properties and chemical reactivity. This interplay continues to expand and contributes to both improved value of experimental results and improved accuracy of computational predictions.The purpose of this EIC Book is to provide state-of-the-art presentations of quantum mechanical and related methods and their applications, written by many of the leaders in the field. Part 1 of this volume focuses on methods, their background and implementation, and their use in describing bonding properties, energies, transition states and spectroscopic features. Part 2 focuses on applications in bioinorganic chemistry and Part 3 discusses inorganic chemistry, where electronic structure calculations have already had a major impact. This addition to the EIC Book series is of significant value to both experimentalists and theoreticians, and we anticipate that it will stimulate both further development of the methodology and its applications in the many interdisciplinary fields that comprise modern inorganic and bioinorganic chemistry.This volume is also available as part of Encyclopedia of Inorganic Chemistry, 5 Volume Set.This set combines all volumes published as EIC Books from 2007 to 2010, representing areas of key developments in the field of inorganic chemistry published in the Encyclopedia of Inorganic Chemistry. Find out more.
Computational Intelligence Aided Systems for Healthcare Domain
by Akshansh GuptaThis book covers recent advances in artificial intelligence, smart computing, and their applications in augmenting medical and health care systems. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields including electrical, electronics and communication, computer, and biomedical. This book- Presents architecture, characteristics, and applications of artificial intelligence and smart computing in health care systems. Highlights privacy issues faced in health care and health informatics using artificial intelligence and smart computing technologies. Discusses nature-inspired computing algorithms for the brain-computer interface. Covers graph neural network application in the medical domain. Provides insights into the state-of-the-art artificial intelligence and smart computing enabling and emerging technologies. This book discusses recent advances and applications of artificial intelligence and smart technologies in the field of healthcare. It highlights privacy issues faced in health care and health informatics using artificial intelligence and smart computing technologies. It covers nature-inspired computing algorithms such as genetic algorithms, particle swarm optimization algorithms, and common scrambling algorithms to study brain-computer interfaces. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and biomedical engineering.
Computational Intelligence Assisted Design: In Industrial Revolution 4.0
by Yun Li Yi ChenComputational Intelligence Assisted Design framework mobilises computational resources, makes use of multiple Computational Intelligence (CI) algorithms and reduces computational costs. This book provides examples of real-world applications of technology. Case studies have been used to show the integration of services, cloud, big data technology and space missions. It focuses on computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. This book provides readers with wide-scale information on CI paradigms and algorithms, inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without difficulty through a few tested MATLAB source codes
Computational Intelligence Methods for Bioinformatics and Biostatistics: 12th International Meeting, CIBB 2015, Naples, Italy, September 10-12, 2015, Revised Selected Papers (Lecture Notes in Computer Science #9874)
by Stefano Rovetta Claudia Angelini Paola M. V. RancoitaThis book constitutes the thoroughly refereed post-conference proceedings of the 12th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2015, held in Naples, Italy, in September, 2015. The 21 revised full papers presented were carefully reviewed and selected from 24 submissions. They present problems concerning computational techniques in bioinformatics, systems biology and medical informatics discussing cutting edge methodologies and accelerate life science discoveries, as well as novel challenges with an high impact on molecular biology and translational medicine.
Computational Intelligence Methods for Bioinformatics and Biostatistics: 17th International Meeting, CIBB 2021, Virtual Event, November 15–17, 2021, Revised Selected Papers (Lecture Notes in Computer Science #13483)
by Paolo Cazzaniga Davide Chicco Angelo Facchiano Erica Tavazzi Enrico Longato Martina Vettoretti Anna Bernasconi Simone AvesaniThis book constitutes revised selected papers from the 17th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2021, which was held virtually during November 15–17, 2021. The 19 papers included in these proceedings were carefully reviewed and selected from 26 submissions, and they focus on bioinformatics, computational biology, health informatics, cheminformatics, biotechnology, biostatistics, and biomedical imaging.
Computational Intelligence Methods for Super-Resolution in Image Processing Applications
by Anand Deshpande Navid Razmjooy Vania V. EstrelaThis book explores the application of deep learning techniques within a particularly difficult computational type of computer vision (CV) problem ─ super-resolution (SR). The authors present and discuss ways to apply computational intelligence (CI) methods to SR. The volume also explores the possibility of using different kinds of CV techniques to develop and enhance the tools/processes related to SR. The application areas covered include biomedical engineering, healthcare applications, medicine, histology, and material science. The book will be a valuable reference for anyone concerned with multiple multimodal images, especially professionals working in remote sensing, nanotechnology and immunology at research institutes, healthcare facilities, biotechnology institutions, agribusiness services, veterinary facilities, and universities.
Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis (Studies in Computational Intelligence #923)
by Khalid RazaThe novel coronavirus disease 2019 (COVID-19) pandemic has posed a major threat to human life and health. This book is beneficial for interdisciplinary students, researchers, and professionals to understand COVID-19 and how computational intelligence can be used for the purpose of surveillance, control, prevention, prediction, diagnosis, and potential treatment of the disease. The book contains different aspects of COVID-19 that includes fundamental knowledge, epidemic forecast models, surveillance and tracking systems, IoT- and IoMT-based integrated systems for COVID-19, social network analysis systems for COVID-19, radiological images (CT, X-ray) based diagnosis system, and computational intelligence and in silico drug design and drug repurposing methods against COVID-19 patients. The contributing authors of this volume are experts in their fields and they are from various reputed universities and institutions across the world. This volume is a valuable and comprehensive resource for computer and data scientists, epidemiologists, radiologists, doctors, clinicians, pharmaceutical professionals, along with graduate and research students of interdisciplinary and multidisciplinary sciences.
Computational Intelligence Techniques for Combating COVID-19 (EAI/Springer Innovations in Communication and Computing)
by Sheng-Lung Peng Sandeep Kautish Ahmed J. ObaidThis book presents the latest cutting edge research, theoretical methods, and novel applications in the field of computational intelligence and computational biological approaches that are aiming to combat COVID-19. The book gives the technological key drivers behind using AI to find drugs that target the virus, shedding light on the structure of COVID-19, detecting the outbreak and spread of new diseases, spotting signs of a COVID-19 infection in medical images, monitoring how the virus and lockdown is affecting mental health, and forecasting how COVID-19 cases and deaths will spread across cities and why. Further, the book helps readers understand computational intelligence techniques combating COVID-19 in a simple and systematic way.
Computational Intelligence Techniques for Comparative Genomics: Dedicated to Prof. Allam Appa Rao on the Occasion of His 65th Birthday (SpringerBriefs in Applied Sciences and Technology)
by Vinit Kumar Gunjan Naresh Babu MuppalaneniThis Brief highlights Informatics and related techniques to Computer Science Professionals, Engineers, Medical Doctors, Bioinformatics researchers and other interdisciplinary researchers. Chapters include the Bioinformatics of Diabetes and several computational algorithms and statistical analysis approach to effectively study the disorders and possible causes along with medical applications.
Computational Intelligence Techniques for Green Smart Cities (Green Energy and Technology)
by Ala Al-Fuqaha Yassine Maleh Mohamed LahbyThis book contains high-quality and original research on computational intelligence for green smart cities research. In recent years, the use of smart city technology has rapidly increased through the successful development and deployment of Internet of Things (IoT) architectures. The citizens' quality of life has been improved in several sensitive areas of the city, such as transportation, buildings, health care, education, environment, and security, thanks to these technological advancesComputational intelligence techniques and algorithms enable a computational analysis of enormous data sets to reveal patterns that recur. This information is used to inform and improve decision-making at the municipal level to build smart computational intelligence techniques and sustainable cities for their citizens. Machine intelligence allows us to identify trends (patterns). The smart city could better integrate its transportation network, for example. By offering a better public transportation network adapted to the demand, we could reduce personal vehicles and energy consumption. A smart city could use models to predict the consequences of a change, such as pedestrianizing a street or adding a bike lane. A city can even create a 3D digital twin to test hypothetical projects. This book comprises many state-of-the-art contributions from scientists and practitioners working in machine intelligence and green smart cities. It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances in machine intelligence for green and sustainable smart city applications.
Computational Intelligence and Big Data Analytics: Applications in Bioinformatics (SpringerBriefs in Applied Sciences and Technology)
by Ch. Satyanarayana Kunjam Nageswara Rao Richard G. BushThis book highlights major issues related to big data analysis using computational intelligence techniques, mostly interdisciplinary in nature. It comprises chapters on computational intelligence technologies, such as neural networks and learning algorithms, evolutionary computation, fuzzy systems and other emerging techniques in data science and big data, ranging from methodologies, theory and algorithms for handling big data, to their applications in bioinformatics and related disciplines. The book describes the latest solutions, scientific results and methods in solving intriguing problems in the fields of big data analytics, intelligent agents and computational intelligence. It reflects the state of the art research in the field and novel applications of new processing techniques in computer science. This book is useful to both doctoral students and researchers from computer science and engineering fields and bioinformatics related domains.
Computational Intelligence and Biomedical Signal Processing: An Interdisciplinary, Easy and Practical Approach (SpringerBriefs in Electrical and Computer Engineering)
by Anil Kumar Mitul Kumar Ahirwal Girish Kumar SinghThis book presents an interdisciplinary paradigms of computational intelligence techniques and biomedical signal processing. The computational intelligence techniques outlined in the book will help to develop various ways to enhance and utilize signal processing algorithms in the field of biomedical signal processing. In this book, authors have discussed research, discoveries and innovations in computational intelligence, signal processing, and biomedical engineering that will be beneficial to engineers working in the field of health care systems. The book provides fundamental and initial level theory and implementation tools, so that readers can quickly start their research in these interdisciplinary domains.
Computational Intelligence and Data Sciences: Paradigms in Biomedical Engineering
by Ayodeji Olalekan Salau, Shruti Jain, Meenakshi SoodThis book presents futuristic trends in computational intelligence including algorithms as applicable to different application domains in health informatics covering bio-medical, bioinformatics, and biological sciences. Latest evolutionary approaches to solve optimization problems under biomedical engineering field are discussed. It provides conceptual framework with a focus on application of computational intelligence techniques in the domain of biomedical engineering and health informatics including real-time issues.