الصفحة 7
الصفحة 7
Modular Algorithms in Symbolic Summation and Symbolic Integration
Brings together two streams in computer algebra: symbolic integration and summation on the one hand, and fast algorithmics on the other hand. In many algorithmically oriented areas of computer science, the analysis of al gorithms placed into the lime light by DonKnuth’stalkat the 1970ICM –provides a crystal-clear criterion for success. The researcher who designs an algorithm that is faster (asymptotically, in the worst case) than any previous method receives instant gratification : her result will be recognized as valuable. Al as, the downside is that such results come along quite infrequently, despite our best efforts. An alternative evaluation method is to run a new algorithm on examples; this has its obvious problems, but is sometimes the best we can do. George Collins, one of the fathers of computer algebra and a great experimenter,wrote in 1969: “I think this demonstrates again that a simple analysis is often more revealing than a ream of empirical data (although both are important). ” Within computer algebra, some areas have traditionally followed the former methodology, notably some parts of polynomial algebra and linear algebra. Other areas, such as polynomial system solving, have not yet been amenable to this - proach. The usual “input size” parameters of computer science seem inadequate, and although some natural “geometric” parameters have been identified (solution dimension, regularity), not all (potential) major progress can be expressed in this framework. Symbolic integration and summation have been in a similar state.
Modern Trends in Geomechanics
This book is loaded with rich and stimulating articles by a roster of brilliant scholars, reflecting some recent trends in the frontier research of geomechanics. This collection of 32 contributions stems from an international workshop on "Modern Trends of Geomechanics" held in Vienna. The contributions span a wide range of topics and an enormous range of physical scales, from micromechanics at grain scale to engineering problems at large scale; from laboratory and field testing over constitutive modelling to numerical analysis.
Modern treatments for chronic blood diseases
Blood is a body fluid in humans and other animals that delivers necessary substances such as nutrients and oxygen to the cells and transports metabolic waste products away from those same cells. In vertebrates, it is composed of blood cells suspended in blood plasma. Plasma, which constitutes 55% of blood fluid, is mostly water (92% by volume), and contains proteins, glucose, mineral ions, hormones, carbon dioxide (plasma being the main medium for excretory product transportation), and blood cells themselves. Albumin is the main protein in plasma, and it functions to regulate the colloida osmotic pressure of blood. The blood cells are mainly red blood cells (also called RBCs or erythrocytes), white blood cells (also called WBCs or leukocytes) and platelets (also called thrombocytes). Thalassemias are inherited blood disorders characterized by decreased hemoglobin production Symptoms depend on the type and can vary from none to severe. Often there is mild to severe anemia (low red blood cells or hemoglobin). Anemia can result in feeling tired and pale skin. There may also be bone problems, an enlarged spleen, yellowish skin, and dark urine. Slow growth may occur in children.
Modern Formal Methods and Applications
Formal methods are a robust approach for problem solving. It is based on logic and algebraic methods where problems can be formulated in a way that can help to find an appropriate solution. This book shows the basic concepts of formal methods and highlights modern modifications and enhancements to provide a more robust and efficient problem solving tool.Applications are presented from different disciplines such as engineering where the operation of chemical plants is synthesized using formal methods. Computational biology becomes easier and systematic using formal methods. Also, hardware compilation and systems can be managed using formal methods.
Modern Econometric Analysis : Surveys on Recent Developments
The importance of empirical economics and econometric methods has greatly in creased during the last 20 years due to the availability of better data and the improved performance of computers. In an information-driven society such as ours we need quickly to obtain complete and convincing statistical results. This is only possible if the appropriate econometric methods are applied. Traditional econometric analysis concentrates on classical methods which are far from suitable for handling actual economic problems.
Modern deep learning for tabular data : Novel approaches to common modeling problems
Synthesizes and presents novel deep learning approaches to a seemingly unlikely domain - tabular data. Whether for finance, business, security, medicine, or countless other domain, deep learning can help mine and model complex patterns in tabular data - an incredibly ubiquitous form of structured data. Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs - Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks - through both their 'default' usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability.
Modern Deep Learning Design and Application Development : Versatile Tools to Solve Deep Learning Problems
Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and deep-learning case studies, this book reveals how to acquire the tools you need to design and implement like a deep-learning architect. It covers tools deep learning engineers can use in a wide range of fields, from biology to computer vision to business. With nine in-depth case studies, this book will ground you in creative, real-world deep learning thinking. You will: Improve the performance of deep learning models by using pre-trained models, extracting rich features, and automating optimization. Compress deep learning models while maintaining performance. Reframe a wide variety of difficult problems and design effective deep learning solutions to solve them. Use the Keras framework, with some help from libraries like HyperOpt, TensorFlow, and PyTorch, to implement a wide variety of deep learning approaches.
Modern Control Theory
This book presents a unified, systematic description of basic and advanced problems, methods and algorithms of the modern control theory treated as a foundation for the design of computer control and management systems.
Modern Control Systems ; 14th ed.
Written to be equally useful for all engineering disciplines, this text is organized around the concepts of control systems theory in the context of frequency and time domains. It provides coverage of both classical and modern methods of control engineering to give students a strong foundation in basic principles that they can utilize to explore advanced topics in later chapters. Emphasis is placed on real-world complex control systems and practical design applications as well as evolving design strategies like green engineering and human-centered design. Problem solving is strongly emphasized, with an abundance of problems of increasing complexity that help students learn to apply theory to computer-aided design and analysis concepts using MATLAB® and LabVIEW MathScript.
Modern Control Systems ; 13th ed.
Presents the structure of feedback control theory and to provide a sequence of exciting discoveries. The book demonstrates various real-world, global engineering problems while touching on evolving design strategies like green technology. Some of the themes at-hand include climate change, clean water, sustainability, waste management, emissions reduction, and minimizing energy. Throughout the text, students apply theory to the design and analysis of control systems.
Models and Algorithms for Global Optimization : Essays Dedicated to Antanas Žilinskas on the Occasion of His 60th Birthday
The research of Antanas Žilinskas has focused on developing models for global optimization, implementing and investigating the corresponding algorithms, and applying those algorithms to practical problems. This volume, dedicated to Professor Žilinskas on the occasion of his 60th birthday, contains new survey papers in which leading researchers from the field present various models and algorithms for solving global optimization problems.
Modellistica numerica per problemi differenziali = Numerical modeling for differential problems
This text introduces the basic concepts for the numerical modeling of partial differential problems. We consider the classic elliptic, parabolic and hyperbolic linear equations, but also other equations, such as those of diffusion and transport, of Navier-Stokes, and the conservation laws, and we provide numerous physical examples underlying these equations. Then we analyze numerical resolution methods based on finite elements, finite differences, finite volumes, spectral methods and domain decomposition methods. In particular, the algorithmic and computer implementation aspects are discussed and various easy-to-use programs are provided.
Modellistica Numerica per Problemi Differenziali = Numerical Modeling for Differential Problems
This text introduces the fundamental concepts for the numerical modeling of partial differential problems. We consider the classic linear elliptic, parabolic and hyperbolic equations, but also other equations, such as those of diffusion and transport, of Navier-Stokes, and the conservation laws. Numerous physical examples underlying these equations are provided, their main mathematical properties are studied, then numerical resolution methods based on finite elements, finite differences, finite volumes and spectral methods are proposed and analyzed. In particular, the algorithmic and computer implementation aspects are discussed and some easy-to-use programs in C ++ language are provided. The text does not presuppose an advanced mathematical knowledge of partial differential equations: the strictly indispensable concepts in this regard are reported in the Appendix. The volume is therefore suitable for students of scientific degree courses (Engineering, Mathematics, Physics, Chemistry, Information Sciences) and recommended for researchers from the academic and extra-academic world who want to approach this interesting branch of applied mathematics.
Modelling, State Observation and Diagnosis of Quantised Systems
The book concerns quantised systems which emerge from continuous-variable systems by quantising the values of all signals. It is shown how this leads to an abstract system description by means of a stochastic automaton. Based on stochastic automata, new methods for the solution to state observation and fault diagnostic problems are derived. The methods are extended to networks of stochastic automata, allowing component-oriented modelling and, thus, to deal with complex systems. The practical applicability and usefulness of the approach is shown at several examples.
Modelling, Analysis and Optimization of Biosystems
Mathematical models in biology and medicine cannot be based on natural laws as it is the case with physics and chemistry. This is due to the fact that biological and medical processes are concerned with living organisms. Mathematical models, however, can be used as a language by which certain aspects of biological or medical processes can be expressed. In general, several mathematical models can be designed in order to describe a biological or medical process and there is no unique criterion which model gives the best description. This book presents several of these models and shows applications of them to different biological and medical problems. The book shows that operations research expertise is necessary in respect to modeling, analysis and optimization of biosystems.
Modelling in Mathematical Programming : Methodology and Techniques
This book provides basic tools for learning how to model in mathematical programming, from models without much complexity to complex system models. It presents a unique methodology for the building of an integral mathematical model, as well as new techniques that help build under own criteria. It allows readers to structure models from the elements and variables to the constraints, a basic modelling guide for any system with a new scheme of variables, a classification of constraints and also a set of rules to model specifications stated as logical propositions, helping to better understand models already existing in the literature. It also presents the modelling of all possible objectives that may arise in optimization problems regarding the variables values. The book is structured to guide the reader in an orderly manner, learning of the components that the methodology establishes in an optimization problem. The system includes the elements, which are all the actors that participate in the system, decision activities that occur in the system, calculations based on the decision activities, specifications such as regulations, impositions or actions of defined value and objective criterion, which guides the resolution of the system.
Modelling and simulation of discrete-event systems
Allows engineers to study and analyze complex systems. Discrete-event system (DES)-M&S is used in modern management, industrial engineering, computer science, and the military. As computer speeds and memory capacity increase, so DES-M&S tools become more powerful and more widely used in solving real-life problems.
Modelling and Reasoning with Vague Concepts
This volume outlines a formal representation framework for modelling and reasoning with vague concepts in Artificial Intelligence. The new calculus has many applications, especially in automated reasoning, learning, data analysis and information fusion. This book gives a rigorous introduction to label semantics theory, illustrated with many examples, and suggests clear operational interpretations of the proposed measures. It also provides a detailed description of how the theory can be applied in data analysis and information fusion based on a range of benchmark problems.
Modeling, Simulation and Optimization of Complex Processes ; Proceedings of the Third International Conference on High Performance Scientific Computing, March 6–10, 2006, Hanoi, Vietnam
This proceedings volume contains a selection of papers presented at the Third International Conference on High Performance Scientific Computing held at the Hanoi Institute of Mathematics, Vietnamese Academy of Science and Technology (VAST), March 6-10, 2006. The conference has been organized by the Hanoi Institute of Mathematics, Interdisciplinary Center for Scientific Computing (IWR), Heidelberg, and its International PhD Program ``Complex Processes: Modeling, Simulation and Optimization'', and Ho Chi Minh City University of Technology. The contributions cover the broad interdisciplinary spectrum of scientific computing and present recent advances in theory, development of methods, and applications in practice. Subjects covered are mathematical modelling, numerical simulation, methods for optimization and control, parallel computing, software development, applications of scientific computing in physics, chemistry, biology and mechanics, environmental and hydrology problems, transport, logistics and site location, communication networks, production scheduling, industrial and commercial problems.
Modeling, Simulation and Optimization of Complex Processes ; Proceedings of the International Conference on High Performance Scientific Computing, March 10-14, 2003, Hanoi, Vietnam
This proceedings volume contains a selection of papers presented at the symposium "International Conference on High Performance Scientific Computing'' held at the Hanoi Institute of Mathematics of the Vietnam National Center for Natural Science and Technology (NCST). The contributions cover the broad interdisciplinary spectrum of scientific computing and present recent advances in theory, development of methods, and applications in practice. Subjects covered are mathematical modelling, numerical simulation, methods for optimization and optimal control, parallel computing, symbolic computing, software development, applications of scientific computing in physics, chemistry, biology and mechanics, environmental and hydrology problems, transport, logistics and site location, communication networks, production scheduling, industrial and commercial problems.
