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الصفحة 8
الصفحة 8
An Introduction to Optical Wireless Mobile Communications
Discusses existing conventional radio frequency (RF)-based wireless access technology and presents the challenges that can impact the requirements of the future wave of new wireless services in the context of artificial intelligence (AI) driven autonomous systems and machine-type communications. The relationship between visible light communications (VLC) and light fidelity (LiFi), is explored, and the major advantages of VLC and LiFi such as security and data density, and discuss existing research challenges are also introduced. Channel modeling techniques are provided for mobile multiuser scenarios, and will introduce key building blocks to achieve LiFi cellular networks achieving orders of magnitude improvements of area spectral efficiency compared to state-of-the-art. Challenges that arise from moving from a static point-to-point visible light link to a LiFi network that is capable of serving hundreds of mobile and fixed nodes are discussed. An overview of recent standardization activities and the commercialization challenges of this disruptive technology is also provided.
An introduction to ontology engineering
Provides the reader with a comprehensive introductory overview of ontology engineering. A secondary aim is to provide hands-on experience in ontology development that illustrate the theory. The book is divided into three blocks: Block I: logic foundations for ontologies both regarding the languages (mainly First Order predicate Logic, Description Logics, and OWL) and automated reasoning. Block II: developing good ontologies with methods and methodologies, the top-down approach with foundational ontologies, and the bottom-up approach to extract as much useful content as possible from legacy material. Block III: advanced topics with a selection of areas of specialisation, including Ontology-Based Data Access, the interaction between ontologies and natural languages (multilingual ontologies, controlled natural language), and advanced modelling with additional language features (fuzzy and temporal ontologies)
An introduction to description logics
Designed so that domain knowledge can be described and so that computers can reason about this knowledge. DLs have recently gained increased importance since they form the logical basis of widely used ontology languages, in particular the web ontology language OWL. Written by four renowned experts, this is the first textbook on description logics. It is suitable for self-study by graduates and as the basis for a university course. Starting from a basic DL, the book introduces the reader to their syntax, semantics, reasoning problems and model theory and discusses the computational complexity of these reasoning problems and algorithms to solve them.
Ambient Intelligence ; European Conference, AmI 2008, Nuremberg, Germany, November 19-22, 2008. Proceedings
This book constitutes the refereed proceedings of the Second European Conference on Ambient Intelligence, AmI 2008, held in Nuremberg, Germany, in November 2008.
Ambient intelligence : A novel paradigm
Ambient Intelligence (AmI) is an integrating technology for supporting a pervasive and transparent infrastructure for implementing smart environments. Such technology is used to enable environments for detecting events and behaviors of people and for responding in a contextually relevant fashion. AmI proposes a multi-disciplinary approach for enhancing human machine interaction. The authors start with a description of the iDorm as an example of a smart environment conforming to the AmI paradigm, and introduces computer vision as an important component of the system. Other computer vision examples describe visual monitoring for the elderly, classic and novel surveillance techniques using clusters of cameras installed in indoor and outdoor application domains, and the monitoring of public spaces. Face and speech recognition systems are also covered as well as enhanced LEGO blocks for novel educational purposes. The book closes with a provocative chapter on how a cybernetic system can be designed as the backbone of a human machine interaction.
Algorithms on Trees and Graphs : With Python Code
Introduces graph algorithms on an intuitive basis followed by a detailed exposition using structured pseudocode, with correctness proofs as well as worst-case analyses. Centered around the fundamental issue of graph isomorphism, the content goes beyond classical graph problems of shortest paths, spanning trees, flows in networks, and matchings in bipartite graphs. Advanced algorithmic results and techniques of practical relevance are presented in a coherent and consolidated way. Numerous illustrations, examples, problems, exercises, and a comprehensive bibliography support students and professionals in using the book as a text and source of reference. Furthermore, Python code for all algorithms presented is given in an appendix. Topics and features: Algorithms are first presented on an intuitive basis, followed by a detailed exposition using structured pseudocode / Correctness proofs are given, together with a worst-case analysis of the algorithms / Full implementation of all the algorithms in Python / An extensive chapter is devoted to the algorithmic techniques used in the book / Solutions to all the problems
Algorithms in Invariant Theory
The book of Sturmfels is both an easy-to-read textbook for invariant theory and a challenging research monograph that introduces a new approach to the algorithmic side of invariant theory. The Groebner bases method is the main tool by which the central problems in invariant theory become amenable to algorithmic solutions.
Algorithms for Decision Making
A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them.
Algorithms and data structures for massive datasets
Learn: Probabilistic sketching data structures for practical problems Choosing the right database engine for your application Evaluating and designing efficient on-disk data structures and algorithms Understanding the algorithmic trade-offs involved in massive-scale systems Deriving basic statistics from streaming data Correctly sampling streaming data Computing percentiles with limited space resources Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You'll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects--and there's no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you'll find the sweet spot of saving space without sacrificing your data's accuracy. About the Technology Standard algorithms and data structures may become slow--or fail altogether--when applied to large distributed datasets. Choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost.
Agile software engineering
This textbook presents the crucial issues in software engineering using the agile approach to software development - one of the mainstream paradigms for the management of software projects and one that is being applied more and more extensively.
Advances in Applied Self-organizing Systems
This book presents the state-of-the-practice in successfully engineered self-organizing systems, and examines ways to balance design and self organization in the context of applications.
Advancement of Deep Learning and its Applications in Object Detection and Recognition
In just the past five years, deep learning has taken the world by surprise, driving rapid progress in fields as diverse as computer vision, natural language processing, automatic speech recognition, etc. This book presents an introduction to deep learning and various applications of deep learning such as recommendation systems, text recognition, diabetic retinopathy prediction of breast cancer, prediction of epilepsy, sentiment, fake news detection, software defect prediction and protein function prediction.
Advanced Wired and Wireless Networks
ADVANCED WIRED AND WIRELESS NETWORKS brings the reader a sample of recent research efforts representative of advances in the areas of recognized importance for the future Internet, In Part I, we bring ad-hoc networking closer to the reality of practical use. The focus is on more advanced scalable routing suitable for large networks, directed flooding useful in information dissemination networks, as well as self-configuration and security issues important in practical deployments. Part II illustrates the efforts towards development of advanced mobility support techniques (beyond traditional "mobile phone net") and Mobile IP technologies. The issues range from prediction based mobility support, through context transfer during Mobile IP handoff, to service provisioning platforms for heterogeneous networks. The focus of the final section concerns the performance of networks and protocols. Furthermore this section illustrates researchers’ interest in protocol enhancement requests for improved performance with advanced networks, reliable and efficient multicast methods in unreliable networks, and composite scheduling in programmable/active networks where computing resources equal network performance as transmission bandwidth.
Advanced Topics in Exception Handling Techniques
Modern software systems are becoming more complex in many ways and are having to cope with a growing number of abnormal situations which, in turn, are increasingly complex to handle.This book is composed of five parts; the first four deal with topics related to exception handling in the context of programming languages, concurrency and operating systems, pervasive computing systems, and requirements and specifications. The last part focuses on case studies, experimentation and qualitative comparisons. The 16 coherently written chapters by leading researchers competently address a wide range of issues in exception handling.
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.
Adobe® Acrobat® and PDF for Architecture, Engineering, and Construction
Adobe® Acrobat® and PDF for Architecture, Engineering, and Construction is designed to appeal to the engineering mind. The book is a practical guide focusing on the applications of PDF in the solution of "engineering" problems which may arise in a number of disciplines from architecture to construction. Using real-world examples, the authors follow a project from design through build and long-term maintenance. As the sample project evolves, suitable Acrobat® tools and techniques are identified and brought into play at each stage, showing readers how to personalize the context and processes to meet their own project development and management needs.
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.
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
