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Computational Life Sciences: Data Engineering and Data Mining for Life Sciences (Studies in Big Data #112)
by Jens Dörpinghaus Vera Weil Sebastian Schaaf Alexander ApkeThis book broadly covers the given spectrum of disciplines in Computational Life Sciences, transforming it into a strong helping hand for teachers, students, practitioners and researchers. In Life Sciences, problem-solving and data analysis often depend on biological expertise combined with technical skills in order to generate, manage and efficiently analyse big data. These technical skills can easily be enhanced by good theoretical foundations, developed from well-chosen practical examples and inspiring new strategies. This is the innovative approach of Computational Life Sciences-Data Engineering and Data Mining for Life Sciences: We present basic concepts, advanced topics and emerging technologies, introduce algorithm design and programming principles, address data mining and knowledge discovery as well as applications arising from real projects. Chapters are largely independent and often flanked by illustrative examples and practical advise.
Computational Liquid Crystal Photonics: Fundamentals, Modelling and Applications
by Salah Obayya Nihal F. Areed Mohamed Farhat HameedOptical computers and photonic integrated circuits in high capacity optical networks are hot topics, attracting the attention of expert researchers and commercial technology companies. Optical packet switching and routing technologies promise to provide a more efficient source of power, and footprint scaling with increased router capacity; integrating more optical processing elements into the same chip to increase on-chip processing capability and system intelligence has become a priority. This book is an in-depth look at modelling techniques and the simulation of a wide range of liquid crystal based modern photonic devices with enhanced high levels of flexible integration and enhanced power processing. It covers the physics of liquid crystal materials; techniques required for modelling liquid crystal based devices; the state-of-the art liquid crystal photonic based applications for telecommunications such as couplers, polarization rotators, polarization splitters and multiplexer-demultiplexers; liquid core photonic crystal fiber (LC-PCF) sensors including biomedical and temperature sensors; and liquid crystal photonic crystal based encryption systems for security applications. Key features Offers a unique source of in-depth learning on the fundamental principles of computational liquid crystal photonics. Explains complex concepts such as photonic crystals, liquid crystals, waveguides and modes, and frequency- and time-domain techniques used in the design of liquid crystal photonic crystal photonic devices in terms that are easy to understand. Demonstrates the useful properties of liquid crystals in a diverse and ever-growing list of technological applications. Requires only a foundational knowledge of mathematics and physics.
Computational Lithography
by Alastair D. McaulayRecent advances in ultra-high-power lasers, including the free-electron laser, and impressive airborne demonstrations of laser weapons systems, such as the airborne laser, have shown the enormous potential of laser technology to revolutionize 21st century warfare. Military Laser Technology for Defense, includes only unclassified or declassified information. The book focuses on military applications that involve propagation of light through the atmosphere and provides basic relevant background technology. It describes high-power lasers and masers, including the free-electron laser. Further, Military Laser Technology for Defense addresses how laser technology can effectively mitigate six of the most pressing military threats of the 21st century: attack by missiles, terrorists, chemical and biological weapons, as well as difficulty in imaging in bad weather and threats from directed beam weapons and future nuclear weapons. The author believes that laser technology will revolutionize warfare in the 21st century.
Computational Lithography
by Gonzalo R. Arce Xu MaA Unified Summary of the Models and Optimization Methods Used in Computational LithographyOptical lithography is one of the most challenging areas of current integrated circuit manufacturing technology. The semiconductor industry is relying more on resolution enhancement techniques (RETs), since their implementation does not require significant changes in fabrication infrastructure. Computational Lithography is the first book to address the computational optimization of RETs in optical lithography, providing an in-depth discussion of optimal optical proximity correction (OPC), phase shifting mask (PSM), and off-axis illumination (OAI) RET tools that use model-based mathematical optimization approaches.The book starts with an introduction to optical lithography systems, electric magnetic field principles, and the fundamentals of optimization from a mathematical point of view. It goes on to describe in detail different types of optimization algorithms to implement RETs. Most of the algorithms developed are based on the application of the OPC, PSM, and OAI approaches and their combinations. Algorithms for coherent illumination as well as partially coherent illumination systems are described, and numerous simulations are offered to illustrate the effectiveness of the algorithms. In addition, mathematical derivations of all optimization frameworks are presented.The accompanying MATLAB® software files for all the RET methods described in the book make it easy for readers to run and investigate the codes in order to understand and apply the optimization algorithms, as well as to design a set of optimal lithography masks. The codes may also be used by readers for their research and development activities in their academic or industrial organizations. An accompanying MATLAB® software guide is also included. An accompanying MATLAB® software guide is included, and readers can download the software to use with the guide at ftp://ftp.wiley.com/public/sci_tech_med/computational_lithography.Tailored for both entry-level and experienced readers, Computational Lithography is meant for faculty, graduate students, and researchers, as well as scientists and engineers in industrial organizations whose research or career field is semiconductor IC fabrication, optical lithography, and RETs. Computational lithography draws from the rich theory of inverse problems, optics, optimization, and computational imaging; as such, the book is also directed to researchers and practitioners in these fields.
Computational Management: Applications of Computational Intelligence in Business Management (Modeling and Optimization in Science and Technologies #18)
by Vipul Jain Srikanta Patnaik Kayhan TajeddiniThis book offers a timely review of cutting-edge applications of computational intelligence to business management and financial analysis. It covers a wide range of intelligent and optimization techniques, reporting in detail on their application to real-world problems relating to portfolio management and demand forecasting, decision making, knowledge acquisition, and supply chain scheduling and management.
Computational Materials System Design
by Dongwon Shin James SaalThis book provides state-of-the-art computational approaches for accelerating materials discovery, synthesis, and processing using thermodynamics and kinetics. The authors deliver an overview of current practical computational tools for materials design in the field. They describe ways to integrate thermodynamics and kinetics and how the two can supplement each other.
Computational Materials, Chemistry, and Biochemistry: In Honor of William A. Goddard’s Contributions to Science and Engineering (Springer Series in Materials Science #284)
by Richard Muller Thom Dunning Sadasivan Shankar Guan Hua ChenThis book provides a broad and nuanced overview of the achievements and legacy of Professor William (“Bill”) Goddard in the field of computational materials and molecular science. Leading researchers from around the globe discuss Goddard’s work and its lasting impacts, which can be seen in today’s cutting-edge chemistry, materials science, and biology techniques. Each section of the book closes with an outline of the prospects for future developments.In the course of a career spanning more than 50 years, Goddard’s seminal work has led to dramatic advances in a diverse range of science and engineering fields. Presenting scientific essays and reflections by students, postdoctoral associates, collaborators and colleagues, the book describes the contributions of one of the world’s greatest materials and molecular scientists in the context of theory, experimentation, and applications, and examines his legacy in each area, from conceptualization (the first mile) to developments and extensions aimed at applications, and lastly to de novo design (the last mile). Goddard’s passion for science, his insights, and his ability to actively engage with his collaborators in bold initiatives is a model for us all. As he enters his second half-century of scientific research and education, this book inspires future generations of students and researchers to employ and extend these powerful techniques and insights to tackle today’s critical problems in biology, chemistry, and materials. Examples highlighted in the book include new materials for photocatalysts to convert water and CO2 into fuels, novel catalysts for the highly selective and active catalysis of alkanes to valuable organics, simulating the chemistry in film growth to develop two-dimensional functional films, and predicting ligand–protein binding and activation to enable the design of targeted drugs with minimal side effects.
Computational Mechanics and Applied Mathematics: GIMC SIMAI Young 2024 (Lecture Notes in Mechanical Engineering)
by Francesco Marmo Salvatore Cuomo Arsenio CutoloThis book collects the latest advances and innovations in the field of applied mathematics and computational mechanics, as presented at the 2nd Workshop GIMC SIMAI YOUNG, held in Naples, Italy, on July 10–12, 2024. The workshop was the joint effort of Computational Mechanics Group of the Italian Association of Theoretical and Applied Mechanics -AIMETA (GIMC) and Italian Society of Applied and Industrial Mathematics (SIMAI) and was meant to highlight the works of young researchers in the field. Topics include mathematical models for socio-epidemiological dynamics, efficient numerical methods for evolutionary PDEs, multi-scale approaches and machine learning techniques in material modelling, nonlinear material behaviour, computational methods for shells and spatial structures, assessment, monitoring, and design of masonry structures, particles in numerical simulations, non-Newtonian complex fluids, mathematical modelling in mechanobiology and oncology, mechanics of biological systems and bioinspired materials, computational approaches for complex dynamical systems, optimization methods for classical and data-driven approaches. The contributions, which were selected by means of a rigorous peer-review process, present a wealth of exciting ideas that will open novel research directions and foster multidisciplinary collaboration.
Computational Mechanics in Structural Engineering: Recent developments and future trends
by Franklin Y. Cheng Fu ZizhiProceedings of Sino-US Joint Symposium/Workshop on Recent Developments and Future Trends of Computational Mechanics in Structural Engineering, Beijing, China, September 24-28 1991
Computational Mechanics of Arbitrarily Shaped Granular Materials (Springer Tracts in Mechanical Engineering)
by Shunying Ji Siqiang WangThis book focuses on discrete element methods for arbitrarily shaped granular materials, including super-quadric models, spherical harmonic functions and level set methods, and numerical analysis of the flow characteristics of non-spherical granular materials. This book is used as a reference book for scientific researchers engaged in dynamic analysis of granular materials and optimal design of equipment structures in the fields of engineering mechanics, applied physics, mechanical engineering, and chemical engineering, as well as for graduate students or senior undergraduates of related majors in institutions of higher education.
Computational Mechanics of Discontinua
by Earl E. Knight Antonio A. Munjiza Esteban RougierMechanics of Discontinua is the first book to comprehensively tackle both the theory ofthis rapidly developing topic and the applications that span a broad field of scientific and engineering disciplines, from traditional engineering to physics of particulates, nano-technology and micro-flows. Authored by a leading researcher who has been at the cutting edge of discontinua simulation developments over the last 15 years, the book is organized into four parts: introductory knowledge, solvers, methods and applications. In the first chapter a short revision of Continuum Mechanics together with tensorial calculus is introduced. Also, a short introduction to the finite element method is given. The second part of the book introduces key aspects of the subject. These include a diverse field of applications, together with fundamental theoretical and algorithmic aspects common to all methods of Mechanics of Discontinua. The third part of the book proceeds with the most important computational and simulation methods including Discrete Element Methods, the Combined Finite-Discrete Element Method, Molecular Dynamics Methods, Fracture and Fragmentation solvers and Fluid Coupling. After these the reader is introduced to applications stretching from traditional engineering and industry (such as mining, oil industry, powders) to nanotechnology, medical and science.
Computational Mechanics of Fluid-Structure Interaction: Computational Methods for Coupled Fluid-Structure Analysis
by Rajeev Kumar Jaiman Vaibhav JoshiThis book is intended to provide a compilation of the state-of-the-art numerical methods for nonlinear fluid-structure interaction using the moving boundary Lagrangian-Eulerian formulation. Single and two-phase viscous incompressible fluid flows are considered with the increasing complexity of structures ranging from rigid-body, linear elastic and nonlinear large deformation to fully-coupled flexible multibody system. This book is unique with regard to computational modeling of such complex fluid-structure interaction problems at high Reynolds numbers, whereby various coupling techniques are introduced and systematically discussed. The techniques are demonstrated for large-scale practical problems in aerospace and marine/offshore engineering. This book also provides a comprehensive understanding of underlying unsteady physics and coupled mechanical aspects of the fluid-structure interaction from a computational point of view. Using the body-fitted and moving mesh formulations, the physical insights associated with structure-to-fluid mass ratios (i.e., added mass effects), Reynolds number, large structural deformation, free surface, and other interacting physical fields are covered. The book includes the basic tools necessary to build the concepts required for modeling such coupled fluid-structure interaction problems, thus exposing the reader to advanced topics of multiphysics and multiscale phenomena.
Computational Mechanics with Deep Learning: An Introduction (Lecture Notes on Numerical Methods in Engineering and Sciences)
by Genki Yagawa Atsuya OishiThis book is intended for students, engineers, and researchers interested in both computational mechanics and deep learning. It presents the mathematical and computational foundations of Deep Learning with detailed mathematical formulas in an easy-to-understand manner. It also discusses various applications of Deep Learning in Computational Mechanics, with detailed explanations of the Computational Mechanics fundamentals selected there. Sample programs are included for the reader to try out in practice. This book is therefore useful for a wide range of readers interested in computational mechanics and deep learning.
Computational Mechanics with Neural Networks (Lecture Notes on Numerical Methods in Engineering and Sciences)
by Genki Yagawa Atsuya OishiThis book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other machine learning method in computational mechanics. Part II highlights the applications of neural networks to a variety of problems of computational mechanics. The final chapter gives perspectives to the applications of the deep learning to computational mechanics.
Computational Methods Based on Peridynamics and Nonlocal Operators: Theory and Applications (Computational Methods in Engineering & the Sciences)
by Timon Rabczuk Xiaoying Zhuang Huilong RenThis book provides an overview of computational methods based on peridynamics and nonlocal operators and their application to challenging numerical problems which are difficult to deal with traditional methods such as the finite element method, material failure being “only” one of them. The authors have also developed a higher-order nonlocal operator approaches capable of solving higher-order partial differential equations on arbitrary domains in higher-dimensional space with ease. This book is of interest to those in academia and industry.
Computational Methods and Clinical Applications for Spine Imaging: 6th International Workshop and Challenge, CSI 2019, Shenzhen, China, October 17, 2019, Proceedings (Lecture Notes in Computer Science #11963)
by Guoyan Zheng Shuo Li Yunliang Cai Liansheng Wang Michel AudetteThis book constitutes the proceedings of the 7th International Workshop and Challenge on Computational Methods and Clinical Applications for Spine Imaging, CSI 2019, which was held in conjunction with MICCAI on October 17, 2019, in Shenzhen, China. All submissions were accepted for publication; the book contains 5 peer-reviewed regular papers, covering topics of vertrebra detection, spine segmentation and image-based diagnosis, and 9 challenge papers, investigating (semi-)automatic spinal curvature estimation algorithms and providing a standard evaluation framework with a set of x-ray images.
Computational Methods and Data Engineering: Proceedings of ICCMDE 2021 (Lecture Notes on Data Engineering and Communications Technologies #139)
by Vijendra Singh Vijayan K. Asari R. B. Patel Rajkumar RajasekaranThe book features original papers from International Conference on Computational Methods and Data Engineering (ICCMDE 2021), organized by School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India, during November 25–26, 2021. The book covers innovative and cutting-edge work of researchers, developers, and practitioners from academia and industry working in the area of advanced computing.
Computational Methods and Data Engineering: Proceedings of ICMDE 2020, Volume 1 (Advances in Intelligent Systems and Computing #1227)
by Sanjay Kumar Vijendra Singh Vijayan K. Asari R. B. PatelThis book gathers selected high-quality research papers from the International Conference on Computational Methods and Data Engineering (ICMDE 2020), held at SRM University, Sonipat, Delhi-NCR, India. Focusing on cutting-edge technologies and the most dynamic areas of computational intelligence and data engineering, the respective contributions address topics including collective intelligence, intelligent transportation systems, fuzzy systems, data privacy and security, data mining, data warehousing, big data analytics, cloud computing, natural language processing, swarm intelligence, and speech processing.
Computational Methods and Data Engineering: Proceedings of ICMDE 2020, Volume 2 (Advances in Intelligent Systems and Computing #1257)
by Sanjay Kumar Vijendra Singh Vijayan K. Asari R. B. PatelThis book gathers selected high-quality research papers from the International Conference on Computational Methods and Data Engineering (ICMDE 2020), held at SRM University, Sonipat, Delhi-NCR, India. Focusing on cutting-edge technologies and the most dynamic areas of computational intelligence and data engineering, the respective contributions address topics including collective intelligence, intelligent transportation systems, fuzzy systems, data privacy and security, data mining, data warehousing, big data analytics, cloud computing, natural language processing, swarm intelligence, and speech processing.
Computational Methods and GIS Applications in Social Science
by Fahui Wang Lingbo LiuThis textbook integrates GIS, spatial analysis, and computational methods for solving real-world problems in various policy-relevant social science applications. Thoroughly updated, the third edition showcases the best practices of computational spatial social science and includes numerous case studies with step-by-step instructions in ArcGIS Pro and open-source platform KNIME. Readers sharpen their GIS skills by applying GIS techniques in detecting crime hotspots, measuring accessibility of primary care physicians, forecasting the impact of hospital closures on local community, or siting the best locations for business. FEATURES Fully updated using the latest version of ArcGIS Pro and open-source platform KNIME Features two brand-new chapters on agent-based modeling and big data analytics Provides newly automated tools for regionalization, functional region delineation, accessibility measures, planning for maximum equality in accessibility, and agent-based crime simulation Includes many compelling examples and real-world case studies related to social science, urban planning, and public policy Provides a website for downloading data and programs for implementing all case studies included in the book and the KNIME lab manual Intended for students taking upper-level undergraduate and graduate-level courses in quantitative geography, spatial analysis, and GIS applications, as well as researchers and professionals in fields such as geography, city and regional planning, crime analysis, public health, and public administration.
Computational Methods and GIS Applications in Social Science - Lab Manual
by Fahui Wang Lingbo LiuThis lab manual is a companion to the third edition of the textbook Computational Methods and GIS Applications in Social Science. It uses the open-source platform KNIME to illustrate a step-by-step implementation of each case study in the book. KNIME is a workflow-based platform supporting visual programming and multiple scripting language such as R, Python, and Java. The intuitive, structural workflow not only helps students better understand the methodology of each case study in the book, but also enables them to easily replicate, transplant and expand the workflow for further exploration with new data or models. This lab manual could also be used as a GIS automation reference for advanced users in spatial analysis. FEATURES The first hands-on, open-source KNIME lab manual written in tutorial style and focused on GIS applications in social science Includes 22 case studies from the United States and China that parallel the methods developed in the textbook Provides clear step-by-step explanations on how to use the open-source platform KNIME to understand basic and advanced analytical methods through real-life case studies Enables readers to easily replicate and expand their work with new data and models A valuable guide for students and practitioners worldwide engaged in efforts to develop GIS automation in spatial analysis This lab manual is intended for upper-level undergraduate and graduate students taking courses in quantitative geography, spatial analysis, GIS applications in socioeconomic studies, GIS applications in business, and location theory, as well as researchers in the similar fields of geography, city and regional planning, sociology, and public administration.
Computational Methods for Application in Industry 4.0 (SpringerBriefs in Applied Sciences and Technology)
by J. Paulo Davim Angelos P. Markopoulos Nikolaos E. KarkalosThis book presents computational and statistical methods used by intelligent systems within the concept of Industry 4.0. The methods include among others evolution-based and swarm intelligence-based methods. Each method is explained in its fundamental aspects, while some notable bibliography is provided for further reading. This book describes each methods' principles and compares them. It is intended for researchers who are new in computational and statistical methods but also to experienced users.
Computational Methods for Approximation of Large-Scale Dynamical Systems
by Mohammad Monir UddinThese days, computer-based simulation is considered the quintessential approach to exploring new ideas in the different disciplines of science, engineering and technology (SET). To perform simulations, a physical system needs to be modeled using mathematics; these models are often represented by linear time-invariant (LTI) continuous-time (CT) systems. Oftentimes these systems are subject to additional algebraic constraints, leading to first- or second-order differential-algebraic equations (DAEs), otherwise known as descriptor systems. Such large-scale systems generally lead to massive memory requirements and enormous computational complexity, thus restricting frequent simulations, which are required by many applications. To resolve these complexities, the higher-dimensional system may be approximated by a substantially lower-dimensional one through model order reduction (MOR) techniques. Computational Methods for Approximation of Large-Scale Dynamical Systems discusses computational techniques for the MOR of large-scale sparse LTI CT systems. Although the book puts emphasis on the MOR of descriptor systems, it begins by showing and comparing the various MOR techniques for standard systems. The book also discusses the low-rank alternating direction implicit (LR-ADI) iteration and the issues related to solving the Lyapunov equation of large-scale sparse LTI systems to compute the low-rank Gramian factors, which are important components for implementing the Gramian-based MOR. Although this book is primarly aimed at post-graduate students and researchers of the various SET disciplines, the basic contents of this book can be supplemental to the advanced bachelor's-level students as well. It can also serve as an invaluable reference to researchers working in academics and industries alike. Features: Provides an up-to-date, step-by-step guide for its readers. Each chapter develops theories and provides necessary algorithms, worked examples, numerical experiments and related exercises. With the combination of this book and its supplementary materials, the reader gains a sound understanding of the topic. The MATLAB® codes for some selected algorithms are provided in the book. The solutions to the exercise problems, experiment data sets and a digital copy of the software are provided on the book's website; The numerical experiments use real-world data sets obtained from industries and research institutes.
Computational Methods for Biological Models (Studies in Computational Intelligence #1109)
by Hemen Dutta Harendra SinghThis book discusses computational methods related to biological models using mathematical tools and techniques. The book chapters concentrate on numerical and analytical techniques that provide a global solution for biological models while keeping long-term benefits in mind. The solutions are useful in closely understanding biological models, and the results will be very useful for mathematicians, engineers, doctors, scientists and researchers working on real-life biological models. This book provides significant and current knowledge of biological models related to real-life applications. The book covers both methods and applications.
Computational Methods for Complex Liquid-Fluid Interfaces (Progress in Colloid and Interface Science)
by Reinhard Miller Mohsen Karbaschi Mohammad Taeibi RahniComputational Methods for Complex Liquid-Fluid Interfaces highlights key computational challenges involved in the two-way coupling of complex liquid-fluid interfaces. The book covers a variety of cutting-edge experimental and computational techniques ranging from macro- to meso- and microscale approaches (including pivotal applications). As example