Modern Mathematical Methods And High Performance Computing In Science And Technology
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| Author | : Vinai K. Singh |
| Publisher | : Springer |
| Total Pages | : 319 |
| Release | : 2016-08-06 |
| Genre | : Mathematics |
| ISBN | : 981101454X |
The book discusses important results in modern mathematical models and high performance computing, such as applied operations research, simulation of operations, statistical modeling and applications, invisibility regions and regular meta-materials, unmanned vehicles, modern radar techniques/SAR imaging, satellite remote sensing, coding, and robotic systems. Furthermore, it is valuable as a reference work and as a basis for further study and research. All contributing authors are respected academicians, scientists and researchers from around the globe. All the papers were presented at the international conference on Modern Mathematical Methods and High Performance Computing in Science & Technology (M3HPCST 2015), held at Raj Kumar Goel Institute of Technology, Ghaziabad, India, from 27–29 December 2015, and peer-reviewed by international experts. The conference provided an exceptional platform for leading researchers, academicians, developers, engineers and technocrats from a broad range of disciplines to meet and discuss state-of-the-art mathematical methods and high performance computing in science & technology solutions. This has brought new prospects for collaboration across disciplines and ideas that facilitate novel breakthroughs.
| Author | : Vinai K. Singh |
| Publisher | : Springer Nature |
| Total Pages | : 441 |
| Release | : 2021-08-23 |
| Genre | : Mathematics |
| ISBN | : 3030682811 |
This volume explores the connections between mathematical modeling, computational methods, and high performance computing, and how recent developments in these areas can help to solve complex problems in the natural sciences and engineering. The content of the book is based on talks and papers presented at the conference Modern Mathematical Methods and High Performance Computing in Science & Technology (M3HPCST), held at Inderprastha Engineering College in Ghaziabad, India in January 2020. A wide range of both theoretical and applied topics are covered in detail, including the conceptualization of infinity, efficient domain decomposition, high capacity wireless communication, infectious disease modeling, and more. These chapters are organized around the following areas: Partial and ordinary differential equations Optimization and optimal control High performance and scientific computing Stochastic models and statistics Recent Trends in Mathematical Modeling and High Performance Computing will be of interest to researchers in both mathematics and engineering, as well as to practitioners who face complex models and extensive computations.
| Author | : Vinai K. Singh |
| Publisher | : Springer |
| Total Pages | : 498 |
| Release | : 2019-02-14 |
| Genre | : Computers |
| ISBN | : 3030024873 |
This special volume of the conference will be of immense use to the researchers and academicians. In this conference, academicians, technocrats and researchers will get an opportunity to interact with eminent persons in the field of Applied Mathematics and Scientific Computing. The topics to be covered in this International Conference are comprehensive and will be adequate for developing and understanding about new developments and emerging trends in this area. High-Performance Computing (HPC) systems have gone through many changes during the past two decades in their architectural design to satisfy the increasingly large-scale scientific computing demand. Accurate, fast, and scalable performance models and simulation tools are essential for evaluating alternative architecture design decisions for the massive-scale computing systems. This conference recounts some of the influential work in modeling and simulation for HPC systems and applications, identifies some of the major challenges, and outlines future research directions which we believe are critical to the HPC modeling and simulation community.
| Author | : Georg Hager |
| Publisher | : CRC Press |
| Total Pages | : 350 |
| Release | : 2010-07-02 |
| Genre | : Computers |
| ISBN | : 1439811938 |
Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. From working in a scientific computing center, the author
| Author | : Megha Rathi |
| Publisher | : CRC Press |
| Total Pages | : 339 |
| Release | : 2022-07-25 |
| Genre | : Computers |
| ISBN | : 1000454312 |
Advanced Computational Techniques for Sustainable Computing is considered multi-disciplinary field encompassing advanced computational techniques across several domain, including, Computer Science, Statistical Computation and Electronics Engineering. The core idea of sustainable computing is to deploy algorithms, models, policies and protocols to improve energy efficiency and management of resources, enhancing ecological balance, biological sustenance and other services on societal contexts. The book offers a comprehensive coverage of some of the most essential topics: It provides an insight on building smart sustainable solutions. Includes details of applying mining, learning, IOT and sensor-based techniques for sustainable computing. Entails data extraction from various sources followed with pre-processing of data, and how to make effective use of extracted data for application-based research. Involves practical usage of data analytic language, including R, Python, etc. for improving sustainable services offered by multi-disciplinary domains. Encompasses comparison and analysis of recent technologies and trends. Includes development of smart models for information gain and effective decision making with visualization. The readers would get acquainted with the utilization of massive data sets for intelligent mining and processing. It includes the integration of data mining techniques for effective decision-making in the social, economic, and global environmental domains to achieve sustainability. The implementation of computational frameworks can be accomplished using open-source software for the building of resource-efficient models. The content of the book demonstrates the usage of data science and the internet of things for the advent of smart and realistic solutions for attaining sustainability.
| Author | : Athanassios Fokas |
| Publisher | : World Scientific |
| Total Pages | : 568 |
| Release | : 2022-12-12 |
| Genre | : Mathematics |
| ISBN | : 180061182X |
Modern Mathematical Methods for Scientists and Engineers is a modern introduction to basic topics in mathematics at the undergraduate level, with emphasis on explanations and applications to real-life problems. There is also an 'Application' section at the end of each chapter, with topics drawn from a variety of areas, including neural networks, fluid dynamics, and the behavior of 'put' and 'call' options in financial markets. The book presents several modern important and computationally efficient topics, including feedforward neural networks, wavelets, generalized functions, stochastic optimization methods, and numerical methods.A unique and novel feature of the book is the introduction of a recently developed method for solving partial differential equations (PDEs), called the unified transform. PDEs are the mathematical cornerstone for describing an astonishingly wide range of phenomena, from quantum mechanics to ocean waves, to the diffusion of heat in matter and the behavior of financial markets. Despite the efforts of many famous mathematicians, physicists and engineers, the solution of partial differential equations remains a challenge.The unified transform greatly facilitates this task. For example, two and a half centuries after Jean d'Alembert formulated the wave equation and presented a solution for solving a simple problem for this equation, the unified transform derives in a simple manner a generalization of the d'Alembert solution, valid for general boundary value problems. Moreover, two centuries after Joseph Fourier introduced the classical tool of the Fourier series for solving the heat equation, the unified transform constructs a new solution to this ubiquitous PDE, with important analytical and numerical advantages in comparison to the classical solutions. The authors present the unified transform pedagogically, building all the necessary background, including functions of real and of complex variables and the Fourier transform, illustrating the method with numerous examples.Broad in scope, but pedagogical in style and content, the book is an introduction to powerful mathematical concepts and modern tools for students in science and engineering.
| Author | : Vinai K. Singh |
| Publisher | : Springer |
| Total Pages | : 503 |
| Release | : 2019-03-14 |
| Genre | : Computers |
| ISBN | : 9783030024864 |
This special volume of the conference will be of immense use to the researchers and academicians. In this conference, academicians, technocrats and researchers will get an opportunity to interact with eminent persons in the field of Applied Mathematics and Scientific Computing. The topics to be covered in this International Conference are comprehensive and will be adequate for developing and understanding about new developments and emerging trends in this area. High-Performance Computing (HPC) systems have gone through many changes during the past two decades in their architectural design to satisfy the increasingly large-scale scientific computing demand. Accurate, fast, and scalable performance models and simulation tools are essential for evaluating alternative architecture design decisions for the massive-scale computing systems. This conference recounts some of the influential work in modeling and simulation for HPC systems and applications, identifies some of the major challenges, and outlines future research directions which we believe are critical to the HPC modeling and simulation community.
| Author | : Mamtesh Singh |
| Publisher | : CRC Press |
| Total Pages | : 798 |
| Release | : 2022-11-16 |
| Genre | : Technology & Engineering |
| ISBN | : 1000626679 |
Microbial Products: Applications and Translational Trends offers complete coverage of the production of microbial products, including biopolymers, biofuels, bioactive compounds, and their applications in fields such as bioremediation, agriculture, medicine, and other industrial settings. This book focuses on multiple processes including upstream procedures and downstream processing, and the tools required for their production. Lab-scale development processes may not be as efficient when aiming for large-scale industrial production, so it is necessary to utilize in silico modeling tools for bioprocess design to ensure success at translational levels. Therefore, this book presents in silico and mathematical simulations and approaches used for such applications. Further, it examines microbial products produced from bacteria, fungi, and algae. These major microbial categories have the capacity to produce various, diverse secondary metabolites, bioactive compounds, enzymes, biopolymers, biofuels, probiotics, and more. The bioproducts examined in the book are of great social, medical, and agricultural benefit, and include examples of biodegradable polymers, biofuels, biofertilizers, and drug delivery agents. Presents approaches and tools that aid in the design of eco-friendly, efficient, and economic bioprocesses. Utilizes in silico and mathematical simulations for optimal bioprocess design. Examines approaches to be used for bioproducts from the lab scale to widely applied microbial biotechnologies. Presents the latest trends and technologies in the production approaches for microbial bio-products manufacture and application. This book is ideal for both researchers and academics, as it provides up-to-date knowledge of applied microbial biotechnology approaches for bio-products.
| Author | : Vijay Gupta |
| Publisher | : Springer |
| Total Pages | : 295 |
| Release | : 2018-07-06 |
| Genre | : Mathematics |
| ISBN | : 3319921657 |
This book presents an in-depth study on advances in constructive approximation theory with recent problems on linear positive operators. State-of-the-art research in constructive approximation is treated with extensions to approximation results on linear positive operators in a post quantum and bivariate setting. Methods, techniques, and problems in approximation theory are demonstrated with applications to optimization, physics, and biology. Graduate students, research scientists and engineers working in mathematics, physics, and industry will broaden their understanding of operators essential to pure and applied mathematics. Topics discussed include: discrete operators, quantitative estimates, post-quantum calculus, integral operators, univariate Gruss-type inequalities for positive linear operators, bivariate operators of discrete and integral type, convergence of GBS operators.
| Author | : Raphael Urs Keusch |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 275 |
| Release | : 2022-08-19 |
| Genre | : Computers |
| ISBN | : 3866287682 |
Normal with unknown variance (NUV) priors are a central idea of sparse Bayesian learning and allow variational representations of non-Gaussian priors. More specifically, such variational representations can be seen as parameterized Gaussians, wherein the parameters are generally unknown. The advantage is apparent: for fixed parameters, NUV priors are Gaussian, and hence computationally compatible with Gaussian models. Moreover, working with (linear-)Gaussian models is particularly attractive since the Gaussian distribution is closed under affine transformations, marginalization, and conditioning. Interestingly, the variational representation proves to be rather universal than restrictive: many common sparsity-promoting priors (among them, in particular, the Laplace prior) can be represented in this manner. In estimation problems, parameters or variables of the underlying model are often subject to constraints (e.g., discrete-level constraints). Such constraints cannot adequately be represented by linear-Gaussian models and generally require special treatment. To handle such constraints within a linear-Gaussian setting, we extend the idea of NUV priors beyond its original use for sparsity. In particular, we study compositions of existing NUV priors, referred to as composite NUV priors, and show that many commonly used model constraints can be represented in this way.
