Computer science

The first book of its kind to review the current status and future direction of the exciting new branch of machine learning/data mining called imbalanced learning Imbalanced learning focuses on how an intelligent system can learn when it is provided with imbalanced data.

The first book of its kind to review the current status and future direction of the exciting new branch of machine learning/data mining called imbalanced learning Imbalanced learning focuses on how an intelligent system can learn when it is provided with imbalanced data.

A highly accessible reference offering a broad range of topics and insights on large scale network-centric distributed systems Evolving from the fields of high-performance computing and networking, large scale network-centric distributed systems continues to grow as one of the most important topics in computing and communication and many interdisciplinary areas.

Sustainable IT Architecture: The Progressive Way of Overhauling Information Systems with SOA This book focuses on Service Oriented Architecture (SOA), the basis of sustainable and more agile IT systems that are able to adapt themselves to new trends and manage processes involving a third party.

During the last decade, image and signal compression for storage and transmission purpose has seen a great expansion.

Many scientific, medical or engineering problems raise the issue of recovering some physical quantities from indirect measurements; for instance, detecting or quantifying flaws or cracks within a material from acoustic or electromagnetic measurements at its surface is an essential problem of non-destructive evaluation.

This book describes the optimization methods most commonly encountered in signal and image processing: artificial evolution and Parisian approach; wavelets and fractals; information criteria; training and quadratic programming; Bayesian formalism; probabilistic modeling; Markovian approach; hidden Markov models; and metaheuristics (genetic algorithms, ant colony algorithms, cross-entropy, particle swarm optimization, estimation of distribution algorithms, and artificial immune systems).

This title sets out to show that 2-D signal analysis has its own role to play alongside signal processing and image processing.

Markov Decision Processes (MDPs) are a mathematical framework for modeling sequential decision problems under uncertainty as well as reinforcement learning problems.

Markov Decision Processes (MDPs) are a mathematical framework for modeling sequential decision problems under uncertainty as well as reinforcement learning problems.

Linear systems have all the necessary elements (modeling, identification, analysis and control), from an educational point of view, to help us understand the discipline of automation and apply it efficiently.

Linear systems have all the necessary elements (modeling, identification, analysis and control), from an educational point of view, to help us understand the discipline of automation and apply it efficiently.

Information systems have an enormous potential for improving business performance.

Model-based development methods, and supporting technologies, can provide the techniques and tools needed to address the dilemma between reducing system development costs and time, and developing increasingly complex systems.

Model Driven Engineering for Distributed Real-Time Embedded Systems 2009: Advances, Standards, Applications and Perspectives Model-based development methods, and supporting technologies, can provide the techniques and tools needed to address the dilemma between reducing system development costs and time, and developing increasingly complex systems.

It is almost universally agreed that consciousness and possession of a conscience are essential characteristics of human intelligence.

Learn to identify the social engineer by non-verbal behavior Unmasking the Social Engineer: The Human Element of Security focuses on combining the science of understanding non-verbal communications with the knowledge of how social engineers, scam artists and con men use these skills to build feelings of trust and rapport in their targets.

Emphasizes a hands-on approach to learning statistical analysis and model building through the use of comprehensive examples, problems sets, and software applications With a unique blend of theory and applications, Simulation Modeling and Arena , Second Edition integrates coverage of statistical analysis and model building to emphasize the importance of both topics in simulation.

Multimodal transport network customers need to be directed during their travels.

This book deals with these parametric methods, first discussing those based on time series models, Capon s method and its variants, and then estimators based on the notions of sub-spaces.

Multimodal transport network customers need to be directed during their travels.

This book places IT in perspective by tracing its development through time, covering its origins in business, the massive expansion of the role of IT at the end of the 20th century, the growth of the internet, and the successes and failures of companies involved in this development.

Logic and its components (propositional, first-order, non-classical) play a key role in Computer Science and Artificial Intelligence.

Logic and its components (propositional, first-order, non-classical) play a key role in Computer Science and Artificial Intelligence.

Integrating empirical, conceptual, and theoretical approaches, this book presents the thinking of researchers and experts in the fields of cybersecurity, cyberdefense, and information warfare.

Integrating empirical, conceptual, and theoretical approaches, this book presents the thinking of researchers and experts in the fields of cybersecurity, cyberdefense, and information warfare.

Nowadays, distributed systems are increasingly present, for public software applications as well as critical systems.

Nowadays, distributed systems are increasingly present, for public software applications as well as critical systems.

Starting with an updated description of Allen's calculus, the book proceeds with a description of the main qualitative calculi which have been developed over the last two decades.

The new digital media offers us an unprecedented memory capacity, an ubiquitous communication channel and a growing computing power.

In today's digital environment, distributed systems are increasingly present in a wide variety of environments, ranging from public software applications to critical systems.

The new digital media offers us an unprecedented memory capacity, an ubiquitous communication channel and a growing computing power.

In today's digital environment, distributed systems are increasingly present in a wide variety of environments, ranging from public software applications to critical systems.

Starting with an updated description of Allen's calculus, the book proceeds with a description of the main qualitative calculi which have been developed over the last two decades.

Graph partitioning is a theoretical subject with applications in many areas, principally: numerical analysis, programs mapping onto parallel architectures, image segmentation, VLSI design.

Graph partitioning is a theoretical subject with applications in many areas, principally: numerical analysis, programs mapping onto parallel architectures, image segmentation, VLSI design.

It is currently quite easy for students or designers/engineers to find very general books on the various aspects of safety, reliability and dependability of computer system architectures, and partial treatments of the elements that comprise an effective system architecture.

It is currently quite easy for students or designers/engineers to find very general books on the various aspects of safety, reliability and dependability of computer system architectures, and partial treatments of the elements that comprise an effective system architecture.

Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals.

Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals.

3D Face Modeling, Analysis and Recognition presents methodologies for analyzing shapes of facial surfaces, develops computational tools for analyzing 3D face data, and illustrates them using state-of-the-art applications.

3D Face Modeling, Analysis and Recognition presents methodologies for analyzing shapes of facial surfaces, develops computational tools for analyzing 3D face data, and illustrates them using state-of-the-art applications.

This book introduces policy, government, and security professionals to the concept of information warfare, covering its evolution over the last decade and its developments among such economic and political giants as China, Russia, Japan, India, and Singapore.

Concise Encyclopaedia of Bioinformatics and Computational Biology, 2nd Edition is a fully revised and updated version of this acclaimed resource.

Concise Encyclopaedia of Bioinformatics and Computational Biology, 2nd Edition is a fully revised and updated version of this acclaimed resource.

A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successfully apply wavelet networks as well as extensive comparisons of alternate methods.

A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successfully apply wavelet networks as well as extensive comparisons of alternate methods.

A modern approach to statistical learning and its applications through visualization methods With a unique and innovative presentation, Multivariate Nonparametric Regression and Visualization provides readers with the core statistical concepts to obtain complete and accurate predictions when given a set of data.

Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applications Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics.

Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applications Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics.