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E-CARGO and role-based collaboration : Modeling and solving problems in the complex
A model for collaboratively solving complex problems Explains the nature of collaboration, explores an easy-to-follow process of collaboration, and defines a model to solve complex problems in collaboration and complex systems. Written by a noted expert on the topic, the book initiates the study of an effective collaborative system from a novel perspective. The role-based collaboration (RBC) methodology investigates the most important aspects of a variety of collaborative systems including societal-technical systems. The models and algorithms can also be applied across system engineering, production, and management. Contains a set of concepts, models, and algorithms for the analysis, design, implementation, maintenance, and assessment of a complex system Presents computational methods that use roles as a primary underlying mechanism to facilitate collaborative activities including role assignment Explores the RBC methodology that concentrates on the aspects that can be handled by individuals to establish a well-formed team Offers an authoritative book written by a noted expert on the topic
Discrete Mathematics Using a Computer
Discrete Mathematics Using a Computer offers a new, "hands-on" approach to teaching Discrete Mathematics. Using software that is freely available on Mac, PC and Unix platforms, the functional language Haskell allows students to experiment with mathematical notations and concepts -- a practical approach that provides students with instant feedback and allows lecturers to monitor progress easily.
Digital Document Processing : Major Directions and Recent Advances
With the advent of the Digital Library initiative, web document processing and biometric aspects of digital document processing, together with new techniques of printed and handwritten Optical Character Recognition (OCR), a good overview of this fast-developing field is invaluable. In this book, all the major and frontier topics in the field of document analysis are brought together into a single volume creating a unique reference source.
Differential Models : An Introduction with Mathcad
Differential equations are often used in mathematical models for technological processes or devices. However, the design of a differential mathematical model is crucial and difficult in engineering.
Developments in Language Theory ; 12th International Conference, DLT 2008, Kyoto, Japan, September 16-19, 2008. Proceedings
This book constitutes the refereed proceedings of the 12th International Conference on Developments in Language Theory, DLT 2008, held in Kyoto, Japan, September 2008.
Deontic Logic in Computer Science ; 9th International Conference, DEON 2008, Luxembourg, Luxembourg, July 15-18, 2008. Proceedings
This volume presents the refereed proceedings of the 9th International Conference on Deontic Logic in Computer Science, DEON 2008, held in Luxembourg in July 2008.
Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms
Presents a comprehensive comparison of the performance of stochastic optimization algorithms / Includes an introduction to benchmarking and statistical analysis / Provides a web-based tool for making statistical comparisons of optimization algorithms / Overviews of the current approaches used to analyze algorithm performance in a range of common scenarios, while also addressing issues that are often overlooked. In turn, it shows how these issues can be easily avoided by applying the principles that have produced Deep Statistical Comparison and its variants. The focus is on statistical analyses performed using single-objective and multi-objective optimization data. At the end of the book, examples from a recently developed web-service-based e-learning tool (DSCTool) are presented. The tool provides users with all the functionalities needed to make robust statistical comparison analyses in various statistical scenarios. The book is intended for newcomers to the field and experienced researchers alike. For newcomers, it covers the basics of optimization and statistical analysis, familiarizing them with the subject matter before introducing the Deep Statistical Comparison approach. Experienced researchers can quickly move on to the content on new statistical approaches.
Deep neural networks and data for automated driving : robustness, uncertainty quantification, and insights towards safety
Environment perception for highly automated driving heavily employs deep neural networks, facing many challenges. How much data do we need for training and testing? How to use synthetic data to save labeling costs for training? How do we increase robustness and decrease memory usage? For inevitably poor conditions: How do we know that the network is uncertain about its decisions? Can we understand a bit more about what actually happens inside neural networks? This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety? This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and, last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above.
Deep Learning-Based Face Analytics
Provides an overview of different deep learning-based methods for face recognition and related problems. Specifically, the authors present methods based on autoencoders, restricted Boltzmann machines, and deep convolutional neural networks for face detection, localization, tracking, recognition, etc. The authors also discuss merits and drawbacks of available approaches and identifies promising avenues of research in this rapidly evolving field.
Deep learning for computational problems in hardware security : Modeling attacks on strong physically unclonable function circuits
Discusses a broad overview of traditional machine learning methods and state-of-the-art deep learning practices for hardware security applications, in particular the techniques of launching potent "modeling attacks" on Physically Unclonable Function (PUF) circuits, which are promising hardware security primitives. The volume is self-contained and includes a comprehensive background on PUF circuits, and the necessary mathematical foundation of traditional and advanced machine learning techniques such as support vector machines, logistic regression, neural networks, and deep learning. This book can be used as a self-learning resource for researchers and practitioners of hardware security, and will also be suitable for graduate-level courses on hardware security and application of machine learning in hardware security.
Decrypted Secrets : Methods and Maxims of Cryptology
Cryptology, for millennia a "secret science", is rapidly gaining in practical importance for the protection of communication channels, databases, and software. Beside its role in computerized information systems (public key systems), more and more applications within computer systems and networks are appearing, which also extend to access rights and source file protection. The first part of this book treats secret codes and their uses - cryptography. The second part deals with the process of covertly decrypting a secret code - cryptanaly-sis - where in particular advice on assessing methods is given. The book presupposes only elementary mathematical knowledge.
Decision Procedures : An Algorithmic Point of View
Concentrates on decision procedures for first-order theories that are commonly used in automated verification and reasoning, theorem-proving, compiler optimization and operations research.
Database theory - ICDT 2005 ; 10th international conference, Edinburgh, UK, January 5-7, 2005, Proceedings
This volume collects the papers presented at the 10th International Conference on Database Theory, ICDT 2005, held during January 5–7, 2005, in Edinburgh, UK. ICDT (http://alpha.luc.ac.be/~lucp1080/icdt/) has now a long tra- tion of international conferences, providing a biennial scienti?c forum for the communication of high-quality and innovative research results on theoretical - pects of all forms of database systems and database technology. The conference usually takes place in Europe, and has been held in Rome (1986), Bruges (1988), Paris (1990), Berlin (1992), Prague (1995), Delphi (1997), Jerusalem (1999), London (2001), and Siena (2003) so far. ICDT has merged with the Sym- sium on Mathematical Fundamentals of Database Systems (MFDBS), initiated in Dresden in 1987, and continued in Visegrad in 1989 and Rostock in 1991. ICDT had a two-stage submission process. First, 103 abstracts were subm- ted, which were followed a week later by 84 paper submissions. From these 84 submissions, the ICDT Program Committee selected 24 papers for presentation at the conference. Most of these papers were “extended abstracts” and preli- nary reports on work in progress. It is anticipated that most of these papers will appear in a more polished form in scienti?c journals.
Data science in theory and practice : Techniques for big data analytics and complex data sets
Delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. Written in five parts, the book examines some of the most commonly used and fundamental mathematical and statistical concepts that form the basis of data science. The authors go on to analyze various data transformation techniques useful for extracting information from raw data, long memory behavior, and predictive modeling. Readers will also learn from topics like: Analyses of foundational theoretical subjects, including the history of data science, matrix algebra and random vectors, and multivariate analysis A comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity Introductions to both the R and Python programming languages, including basic data types and sample manipulations for both languages An exploration of algorithms, including how to write one and how to perform an asymptotic analysis A comprehensive discussion of several techniques for analyzing and predicting complex data sets
Curves and Surfaces for Computer Graphics
Computer graphics is important in many areas including engineering design, architecture, education, and computer art and animation. This book examines a wide array of current methods used in creating real-looking objects in the computer, one of the main aims of computer graphics.
Cryptography, information theory, and error-correction : A handbook for the 21st century ; 2nd ed.
A rich examination of the technologies supporting secure digital information transfers from respected leaders in the field. Is an indispensable resource for anyone interested in the secure exchange of financial information. Identity theft, cybercrime, and other security issues have taken center stage as information becomes easier to access. Three disciplines offer solutions to these digital challenges: cryptography, information theory, and error-correction, all of which are addressed in this book. The book also: Shares vital, new research in the field of information theory / Provides quantum cryptography updates / Includes over 350 worked examples and problems for greater understanding of ideas.
Control Theory Tutorial : Basic Concepts Illustrated by Software Examples
Introduces the basic principles of control theory in a concise self-study guide. It complements the classic texts by emphasizing the simple conceptual unity of the subject. A novice can quickly see how and why the different parts fit together. The concepts build slowly and naturally one after another, until the reader soon has a view of the whole. Each concept is illustrated by detailed examples and graphics. The full software code for each example is available, providing the basis for experimenting with various assumptions, learning how to write programs for control analysis, and setting the stage for future research projects. The topics focus on robustness, design trade-offs, and optimality. Most of the book develops classical linear theory. The last part of the book considers robustness with respect to nonlinearity and explicitly nonlinear extensions, as well as advanced topics such as adaptive control and model predictive control.
Continuous System Simulation
Continuous System Simulation describes systematically and methodically how mathematical models of dynamic systems, usually described by sets of either ordinary or partial differential equations possibly coupled with algebraic equations, can be simulated on a digital computer.
Constraint handling rules : Current research topics
The Constraint Handling Rules (CHR) language is a declarative concurrent committed-choice constraint logic programming language consisting of guarded rules that transform multisets of relations called constraints until no more change occurs. The aim of this volume was to attract high-quality research papers on these recent advances in Constraint Handling Rules.
Concurrency, Graphs and Models : Essays Dedicated to Ugo Montanari on the Occasion of His 65th Birthday
The volume consists of seven sections, six of which are dedicated to the main research areas to which Ugo Montanari has contributed: Graph Transformation; Constraint and Logic Programming; Software Engineering; Concurrency; Models of Computation; and Software Verification.
