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Advanced Autonomic Networking and Communication
This book presents a comprehensive reference of state-of-the-art efforts and early results in the area of autonomic networking and communication.
Advanced artificial intelligence models and its applications
The field of artificial intelligence (AI) has undergone enormous expansion since its inception in the mid-20th century, as demonstrated by its application across an array of engineering and scientific challenges. Particularly in the last decade, AI has witnessed a significant breakthrough with the advent of deep learning, which has facilitated the employment of various AI models across a multitude of domains. This reprint features ten papers accepted for publication in the Special Issue titled "Advanced Artificial Intelligence Models and Their Applications," published in the MDPI Mathematics journal. These papers explore numerous facets of advanced artificial intelligence models and their applications, covering areas such as cybersecurity, image classification, logistics optimization, automatic music generation, human capital investment, writer recognition, remote sensing image indexing, target tracking, and more.
Advanced .NET Remoting
Surpassing any white papers, specialist documents and other documentationthis book features in-depth coverage of the .NET Remoting Framework. The text is organized into three main parts, and this revised, second edition features 150 pages of entirely new material! Part one includes a guide to the 1.1 framework and its capabilities in real-world applications. Part two presents .NET remoting internals, and provides real-world code and development strategies. Finally, part three looks at futuristic remoting tools and their present implementation in Visual Studio .NET 2005. You will come to see how remoting procedures will change within the new IDE and revised framework.
Advance Concepts of Image Processing and Pattern Recognition : Effective Solution for Global Challenges
Explains the important concepts and principles of image processing to implement the algorithms and techniques to discover new problems and applications. It contains numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. It presents essential background theory, shape methods, texture about new methods, and techniques for image processing and pattern recognition. It maintains a good balance between a mathematical background and practical implementation. This book also contains the comparison table and images that are used to show the results of enhanced techniques. This book consists of novel concepts and hybrid methods for providing effective solutions for society. It also includes a detailed explanation of algorithms in various programming languages like MATLAB, Python, etc.
Adaptive-robust control with limited knowledge on systems dynamics : An artificial input delay approach and beyond
investigates the role of artificial input delay in approximating unknown system dynamics, referred to as time-delayed control (TDC), and provides novel solutions to current design issues in TDC. Its central focus is on designing adaptive-switching gain-based robust control (ARC) for a class of Euler–Lagrange (EL) systems with minimal or no knowledge of the system dynamics parameters. The newly proposed TDC-based ARC tackles the commonly observed over- and under-estimation issues in switching gain. The consideration of EL systems lends a practical perspective on the proposed methods, and each chapter is supplemented by relevant experimental data
Adaptive Learning of Polynomial Networks : Genetic Programming, Backpropagation and Bayesian Methods
This book provides theoretical and practical knowledge for develop ment of algorithms that infer linear and nonlinear models. It offers a methodology for inductive learning of polynomial neural network mod els from data. The design of such tools contributes to better statistical data modelling when addressing tasks from various areas like system identification, chaotic time-series prediction, financial forecasting and data mining. The main claim is that the model identification process involves several equally important steps: finding the model structure, estimating the model weight parameters, and tuning these weights with respect to the adopted assumptions about the underlying data distrib ution. When the learning process is organized according to these steps, performed together one after the other or separately, one may expect to discover models that generalize well.
Adaptive Business Intelligence
In the modern information era, managers must recognize the competitive opportunities represented by decision-support tools. Adaptive business intelligence systems combine prediction and optimization techniques to assist decision makers in complex, rapidly changing environments. These systems address the fundamental questions: What is likely to happen in the future? And what is the best decision right now? Adaptive Business Intelligence includes elements of data mining, predictive modeling, forecasting, optimization, and adaptability.
Adaptive Autonomous Secure Cyber Systems
Establishes scientific foundations for adaptive autonomous cyber systems and ultimately brings about a more secure and reliable Internet. The recent advances in adaptive cyber defense (ACD) have developed a range of new ACD techniques and methodologies for reasoning in an adaptive environment.
Adaptive agents and multi-agent systems II : Adaptation and multi-agent learning
Adaptive agents and multi-agent systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, software engineering, and developmental biology, as well as cognitive and social science. This book presents 17 revised and carefully reviewed papers taken from two workshops on the topic as well as 2 invited papers by leading researchers in the area. The papers deal with various aspects of machine learning, adaptation, and evolution in the context of agent systems and autonomous agents.
Adapting Proofs-as-Programs : The Curry--Howard Protocol
This book nuds new things to do with an old idea. The proofs-as-programs paradigm constitutes a set of approaches to developing programs from proofs in constructive logic. there is increasingly active research in applying constructive techniques to industrial-scale, complex software engineering problems. Thismonographdetailsseveralimportantadvancesinthisdirectionofpr- tical proofs-as-programs. One of the central themes of the book is a general, abstract framework for developing new systems of program synthesis by adapting proofs-as-programs to new contexts. Framework-oriented approaches that facilitate analogous - proaches to building systems for solving particular problems have been popular and successful. Thesemethodsarehelpful asthey providea formal toolbox that enablesa“roll-your-own”approachtodevelopingsolutions.Itishopedthatour framework will have a similar impact. The framework is demonstrated by example. We will give two novel - plications of proofs-as-programs to large-scale, coarse-grain software engine- ing problems: contractual imperative program synthesis and structured p- gram synthesis.
Active Lighting and Its Application for Computer Vision : 40 Years of History of Active Lighting Techniques
Computer vision entails both passive and active illumination techniques. Whereas passive techniques observe the scene statically and analyse it as is, by contrast active techniques give the scene some actions and try to facilitate the analysis. In particular, active illumination techniques project specific light, for which the characteristics are known beforehand, to a target scene to enable stable and accurate analysis of the scene.
Active Conceptual Modeling of Learning : Next Generation Learning-Base System Development
This volume contains a collection of the papers presented during the 1st International ACM-L Workshop, which was held on November 8, 2006 during the 25th International Conference on Conceptual Modeling, ER 2006, held November 6–9,2006, in Tucson, Arizona, plus several invited papers.These papers plus the invited papers represent the current thinking in conceptual modeling research, The active model can only be realized through technology integration (e.g., AI, software engineering, information technology,cognitive science, art and sciences, philosophy, etc.)
Accessible access 2003
In that book we tried very hard not to simply list everything that we knew about the product. Instead we tried to act as intelligent filters, presenting only the essential information that you need to get started. Every screen shot has been retaken and every section has been re-checked to ensure, not only that it still works, but also that it is actually still relevant. We have re-written parts where the product has changed and also added some. For example, there is a new section on Object Dependencies and a whole new chapter about Data Access Pages - helping you to put your Access database onto an intranet.
Abstraction, refinement and proof for probabilistic systems
Probabilistic techniques are increasingly being employed in computer programs and systems because they can increase efficiency in sequential algorithms, enable otherwise nonfunctional distribution applications, and allow quantification of risk and safety in general. This makes operational models of how they work, and logics for reasoning about them, extremely important. Abstraction, Refinement and Proof for Probabilistic Systems presents a rigorous approach to modeling and reasoning about computer systems that incorporate probability. Its foundations lie in traditional Boolean sequential-program logic—but its extension to numeric rather than merely true-or-false judgments takes it much further, into areas such as randomized algorithms, fault tolerance, and, in distributed systems, almost-certain symmetry breaking. The presentation begins with the familiar "assertional" style of program development and continues with increasing specialization: Part I treats probabilistic program logic, including many examples and case studies; Part II sets out the detailed semantics; and Part III applies the approach to advanced material on temporal calculi and two-player games.
Abstract Computing Machines : A Lambda Calculus Perspective
The book addresses ways and means of organizing computations, highlighting the relationship between algorithms and the basic mechanisms and runtime structures necessary to execute them using machines. It completely abstracts from concrete programming languages and machine architectures, taking instead the lambda calculus as the basic programming and program execution model to design various abstract machines for its correct implementation. The emphasis is on fully normalizing machines based on full-fledged beta-reductions as essential prerequisites for symbolic computations that treat functions and variables truly as first-class objects. Their weakly normalizing counterparts are shown to be functional abstract machines that sacrifice the flavors of full beta-reductions for decidedly simpler runtime structures and improved runtime efficiency. Further downgrading of the lambda calculus leads to classical imperative machines that permit side-effecting operations on the runtime environment.
A Programmers Introduction to C#2.0
A Programmer's Introduction to C# 2.0, Third Edition is a critical update to the highly successful second edition. It is written by a member of the original C# language-design team and a C# program manager, so you can be certain this book contains the expertise you're looking for. This third edition covers the elements of C# 2005 that you'll soon embrace. This comprehensive tutorial explains features like generics, iterators, anonymous types, and partial classes. It is sure to be a key resource for all you C# programmers!
A Modern Approach to Intelligent Animation : Theory and Practice
Part of the new series, Advanced Topics in Science and Technology in China, this book discusses concepts, theory, and core technologies of intelligent theory and human animation, including video based human animation, and intelligent technology of motion data management and reusing. It introduces systems developed to demonstrate the technologies of video based animation. Each chapter is independent. Lively pictures and demos will be presented to make the theory and technologies more understandable.
A Matrix Algebra Approach to Artificial Intelligence
The book consists of two parts: the first discusses the fundamentals of matrix algebra in detail, while the second focuses on the applications of matrix algebra approaches in AI. Highlighting matrix algebra in graph-based learning and embedding, network embedding, convolutional neural networks and Pareto optimization theory, and discussing recent topics and advances, the book offers a valuable resource for scientists, engineers, and graduate students in various disciplines
A General introduction to data analytics
A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming. A guide to the reasoning behind data mining techniques. A unique illustrative example that extends throughout all the chapters. Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts
A Computational Model of Natural Language Communication : Interpretation, Inference, and Production in Database Semantics
Part I of this book presents a high-level description of an artificial agent which humans can freely communicate with in their accustomed language. Part II analyzes the major constructions of natural language, i.e., intra- and extrapropositional functor - argument structure, coordination, and coreference, in the speaker and the hearer mode. Part III defines declarative specifications for fragments of English, which are used for an implementation in Java.
