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AJCC Atlante per la stadiazione dei tumori maligni = Atlas for the Staging of Malignant Tumors
he atlas contains over 400 specially created black and white illustrations describing the anatomical extent of the malignant tumor in the primary site (T), regional lymph nodes (N) and distant metastases (M) for various sites, including the head and neck area, the digestive system, the thorax, the musculoskeletal system, the soft tissues, the breast, the urinary system and the genital system. Each illustration provides precise and detailed descriptions designed to clarify the crucial anatomical structures and to provide the reader with an immediate view of the progressive extension of the disease. The most important anatomical structures are identified by specific definitions.
C++ /CLI : The Visual C++ Language for .NET
C++/CLI: The Visual C++ Language for .NET introduces Microsoft's extensions to the C++ syntax that allow you to target the common language runtime the key to the heart of the .NET 3.0 platform. In 12 no-fluff chapters, Microsoft insider Gordon Hogenson takes you into the core of the C++/CLI language and explains both how the language elements work and how Microsoft intends them to be used.
Bayesian Networks and Decision Graphs
Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. As modeling languages they allow a natural specification of problem domains with inherent uncertainty, and from a computational perspective they support efficient algorithms for automatic construction and query answering. This includes belief updating, finding the most probable explanation for the observed evidence, detecting conflicts in the evidence entered into the network, determining optimal strategies, analyzing for relevance, and performing sensitivity analysis. The book introduces probabilistic graphical models and decision graphs, including Bayesian networks and influence diagrams.It contians two parts. The first part focuses on probabilistic graphical models. Compared with the previous book, the new edition also includes a thorough description of recent extensions to the Bayesian network modeling language, advances in exact and approximate belief updating algorithms, and methods for learning both the structure and the parameters of a Bayesian network. The second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision processes and partially ordered decision problems.
Agile Development with the ICONIX Process : People, Process, and Pragmatism
Describes how to apply ICONIX Process (a minimal, use case-driven modeling process) in an agile software project. It's full of practical advice for avoiding common agile pitfalls. Further, the book defines a core agile subset so those of you who want to get agile need not spend years learning to do it. Instead, you can simply read this book and apply the core subset of techniques. The book follows a real-life .NET/C# project from inception and UML modeling, to working code through several iterations. You can then go on-line to compare the finished product with the initial set of use cases. The book also introduces several extensions to the core ICONIX Process, including combining test-driven development (TDD) with up-front design to maximize both approaches (with examples using Java and JUnit). And the book incorporates persona analysis to drive the projects goals and reduce requirements churn.
Agent Intelligence Through Data Mining
AGENT INTELLIGENCE THROUGH DATA MINING offers a self-contained overview of a relatively young but important area of research: the intersection of agent technology and data mining. This intersection leads to considerable advancements in the area of information technologies, drawing the increasing attention of both research and industrial communities. It can take two forms: a) the more mundane use of intelligent agents for improved data mining and; b) the use of data mining for smarter, more efficient agents. The second approach is the main focus of this volume. this book presents a methodology for developing multi-agent systems, describes available open-source tools to support this process, and demonstrates the application of the methodology on three different cases. AGENT INTELLIGENCE THROUGH DATA MINING is designed for a professional audience composed of researchers and practitioners in industry.
Adaptive Motion of Animals and Machines
Apparently, the ability of animals and robots to adapt in a real world cannot be explained or realized by one single function in a control system and mechanism. That is, adaptation in motion is induced at every level from the central nervous system to the musculoskeletal system.Thus,weorganized the International Symposium on Adaptive Motion in Animals and Machines (AMAM) forscientist sandengineersconcerned with adaptation on various level stobebrought together todiscussprinciplesateachleveland to investigate principles governing total systems.
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.
Jubilee Line Extension : From concept to completion
Details the story of London Underground's award winning Jubilee Line Extension (JLE), how it came to being, how it was planned, how it was designed, built and commissioned, and how the millennium deadline imposed by the Dome was met. Always in the public eye and the political spotlight, the JLE has played a significant role in the success of the Canary Wharf development, improved public transport immeasurably in the areas of southeast and east London, and set new standards for London Underground and public transport.
Machine learning for risk calculations : A practitioner's view
Fundamental Approximation Methods. Machine Learning -- Deep Neural Nets -- Chebyshev Tensors -- The toolkit - plugging in approximation methods. Introduction: why is a toolkit needed -- Composition techniques -- Tensors in TT format and Tensor Extension Algorithms -- Sliding Technique -- The Jacobian projection technique -- Hybrid solutions - approximation methods and the toolkit.
Logistics Systems Analysis
It has two new sections, a new appendix, and more than half a dozen new figures. A few references have also been added, Much of the new material is based on work , The financial support of the National Science Foundation and the Volvo Foundations Center of Excellence for the Future of Urban Transportation at U. C. Berkeley is also acknowledged. The new appendix presents the logic behind the traveling salesman and vehicle routing results used in Sec. 4. 2 to describe the transportation ope- tion; Chapter 4 is more self-contained as a result. New section 5. 6 int- duces and evaluates a general method that automatically translates the c- tinuum approximation recipes of Chapters 4 and 5 into discrete system designs. This closes a gap in previous editions. Other additions include an explanation of how to develop system designs that can efficiently acc- modate real-time control strategies to manage uncertainty (new section 4. 6. 3), and extensions of the many-to-many design ideas of Chap. 6
Leveraging Mobile Media : Cross-Media Strategy and Innovation Policy for Mobile Media Communication
Mobile communications and next generation wireless networks emerge as new distribution channels for the media. This development offers exciting new opportunities for media companies: the mobile communication system creates new usage contexts for media content and services; the social use of mobile communications suggests that identity representation in social networks, impulsive access to trusted media brands, and micro-coordination emerge as new sources of value creation in the media industries. In the light of this background, this book takes two different viewpoints on the development of mobile media: from a competitive strategy point of view it analyzes the extension of cross-media strategies and the emergence of cross-network strategies; from a public policy point of view it develops demands and requirements for an innovation policy that fosters innovation in mobile media markets.
Cellular Genetic Algorithms
CELLULAR GENETIC ALGORITHMS defines a new class of optimization algorithms based on the concepts of structured populations and Genetic Algorithms (GAs). The authors explain and demonstrate the validity of these cellular genetic algorithms throughout the book. This class of genetic algorithms is shown to produce impressive results on a whole range of domains, including complex problems that are epistatic, multi-modal, deceptive, discrete, continuous, multi-objective, and random in nature. The focus of this book is twofold. On the one hand, the authors present new algorithmic models and extensions to the basic class of Cellular GAs in order to tackle complex problems more efficiently. On the other hand, practical real world tasks are successfully faced by applying Cellular GA methodologies to produce workable solutions of real-world applications.
Applied Econometrics with R
This is the first book on applied econometrics using the R system for statistical computing and graphics. It presents hands-on examples for a wide range of econometric models, from classical linear regression models for cross-section, time series or panel data and the common non-linear models of microeconometrics such as logit, probit and tobit models, to recent semiparametric extensions. In addition, it provides a chapter on programming, including simulations, optimization, and an introduction to R tools enabling reproducible econometric research.
An Introduction to Efficiency and Productivity Analysis
It is designed to be a "first port of call" for people wishing to study efficiency and productivity analysis. The book provides an accessible introduction to the four principal methods involved: econometric estimation of average response models; index numbers; data envelopment analysis (DEA); and stochastic firontier analysis (SFA). For each method, we provide a detailed introduction to the basic concepts, give some simple numerical examples, discuss some of the more important extensions to the basic methods, and provide references for further reading. In addition, we provide a number of detailed empirical applications using real-world data.
LMI Approach to Analysis and Control of Takagi-Sugeno Fuzzy Systems with Time Delay
A fuzzy system is, in a very broad sense, any fuzzy logic-based system where fuzzy logic can be used either asthebasisfor the representation of different forms of system knowledge or the model for the interactions and relationships among the system variables. Fuzzy systems have proven to be an important tool for modeling complex systems for which, due to complexity or imprecision, classical tools are unsuccessful. There have been diverse fields of applications of fuzzy technology from medicine to management, from engineering to behavioral science, from vehicle control to computational linguistics, and so on. Fuzzy modeling is a conjunction to understand the s- tem’s behavior and build useful mathematical models. Different types of fuzzy models have been proposed in the literature, among which the Takagi-Sugeno (T-S) fuzzy model is a rule-based one suitable for the accurate approximation and identi?cation of a wide class of nonlinear systems.
Linear Programming : Foundations and Extensions
Linear Programming: Foundations and Extensions is an introduction to the field of optimization. The book emphasizes constrained optimization, beginning with a substantial treatment of linear programming, and proceeding to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. The book is carefully written. Specific examples and concrete algorithms precede more abstract topics. Topics are clearly developed with a large number of numerical examples worked out in detail.
Light scattering by systems of particles : Null-field method with discrete sources : Theory and programs
Light Scattering by Systems of Particles comprehensively develops the theory of the null-field method, while covering almost all aspects and current applications. The "Null-field Method with Discrete Sources" is an extension of the Null-field Method (also called T-Matrix Method) to compute light scattering by arbitrarily shaped dielectric particles. This book incorporates FORTRAN programs and exemplary simulation results that demonstrate all aspects of the latest developments of the method. Worked examples of the application of the FORTRAN programs show readers how to adapt or modify the programs for their specific application.
Classification and Clustering for Knowledge Discovery
This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. In its first part the book provides a collection of recent research on distributed clustering, self organizing maps and their recent extensions. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees. Therefore this book presents a collection of important methods of supervised data analysis. "Classification and Clustering for Knowledge Discovery" also includes variety of applications of knowledge discovery in health, safety, commerce, mechatronics, sensor networks, and telecommunications.
Bandwidth Extension of Speech Signals
Bandwidth Extension of Speech Signals provides discussion on different approaches for efficient and robust bandwidth extension of speech signals while acknowledging the influence of noise corrupted real-world signals. The book describes the theory and methods for quality enhancement of clean speech signals and distorted speech signals.
Arguing on the Toulmin model : New essays in argument analysis and evaluation
In The Uses of Argument Stephen Toulmin proposed a new model for the layout of arguments, with six components: claim, data, warrant, qualifier, rebuttal, backing. Toulmin’s model has been appropriated, adapted and extended by researchers in the fields of speech communications, philosophy and artificial intelligence. The volume aims to bring together the best contemporary reflection in these fields on the Toulmin model and its current appropriation.
