الصفحة 7
الصفحة 7
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.
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
Data science and analytics ; 5th International conference on recent developments in science, engineering and technology, REDSET 2019, Gurugram, India, November 15–16, 2019, Revised Selected Papers, Part I
This two-volume set (CCIS 1229 and CCIS 1230) constitutes the refereed proceedings of the 5th International Conference on Recent Developments in Science, Engineering and Technology, REDSET 2019, held in Gurugram, India, in November 2019. The 74 revised full papers presented were carefully reviewed and selected from total 353 submissions. The papers are organized in topical sections on data centric programming; next generation computing; social and web analytics; security in data science analytics; big data analytics.
Data mining with computational intelligence
Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions.
CyberParks – The Interface Between People, Places and Technology: New Approaches and Perspectives
This book is about public open spaces, about people, and about the relationship between them and the role of technology in this relationship. It is about different approaches, methods, empirical studies, and concerns about a phenomenon that is increasingly being in the centre of sciences and strategies – the penetration of digital technologies in the urban space. As the main outcome of the CyberParks Project, this book aims at fostering the understanding about the current and future interactions of the nexus people, public spaces and technology. It addresses a wide range of challenges and multidisciplinary perspectives on emerging phenomena related to the penetration of technology in people’s lifestyles - affecting therefore the whole society, and with this, the production and use of public spaces. Cyberparks coined the term cyberpark to describe the mediated public space, that emerging type of urban spaces where nature and cybertechnologies blend together to generate hybrid experiences and enhance quality of life.
Crimean-Congo Hemorrhagic Fever : A Global Perspective
Crimean-Congo hemorrhagic fever (CCHF) is a tick-borne disease associated with severe hemorrhagic manifestations. CCHF has been referred to as the "Asian Ebola." However, in fact, the disease is one of the most widely distributed tick-borne diseases in the world, occurring in Africa, Asia, Europe, and the Middle East. This volume covers major aspects of this important disease and the virus which causes it. Chapters are written by leading experts in their fields and detail historical, public health, epidemiological, and clinical aspects of CCHF and the genetics and molecular biology of the virus. Additional chapters focus on disease control, tick vectors and infection among animals, both natural and experimental.
Cours doptique : Simulations et exercices résolus avec Maple, Matlab, Mathematica, Mathcad = Optics course: Simulations and exercises solved with Maple, Matlab, Mathematica, Mathcad
Intended for students at the L and M levels of the university as well as for engineers wishing to study certain subjects in greater depth. It covers all the themes of a traditional optics course, from geometric optics to holography, interference, diffraction, coherence and the use of the Fourier transform for spectroscopy. The presentation is developed from mathematical models deriving from typical situations and fundamental examples which are presented in the form of computer programs ready to be implemented. These programs are also available on the CD accompanying the book, for each of the following scientific programming environments: Matlab, Maple, Mathematica and Mathcad. Thus, the reader will be able to modify the parameters of the examples proposed to adapt them to new situations.
Convective and Advective Heat Transfer in Geological Systems
This monograph aims to provide state-of-the-art theoretical results in a systematic treatment of convective and advective heat transfer during fluid flow in geological systems at the crustal scale. Although some numerical results are provided to complement theoretical ones, the main focus of this monograph is on theoretical aspects of the topic. The theoretical treatment contained in this monograph is also applicable to a wide range of problems of other length-scales such as engineering length-scales.
Convection in Porous Media
This book provides a user-friendly introduction to convection in porous media, such as fibrous insulation, geological strata, and catalytic reactors. The presentation is self-contained, requiring only routine classical mathematics and the basic elements of fluid mechanics and heat transfer. It will thus be of use not only to researchers and practicing engineers as a review and reference, but also to graduate students and others just entering the field. Convection in Porous Media includes nearly 1000 new references and covers: convection in deforming porous media, "designed" porous media, the theory of deformable media, modeling viscous dissipation in hyperporous media, and more.
Control of Turbulent and Magnetohydrodynamic Channel Flows : Boundary Stabilization and State Estimation
This monograph presents new constructive design methods for boundary stabilization and boundary estimation for several classes of benchmark problems in flow control, with potential applications to turbulence control, weather forecasting, and plasma control. The basis of the approach used in the work is the recently developed continuous backstepping method for parabolic partial differential equations, expanding the applicability of boundary controllers for flow systems from low Reynolds numbers to high Reynolds number conditions. Efforts in flow control over the last few years have led to a wide range of developments in many different directions, but most implementable developments thus far have been obtained using discretized versions of the plant models and finite-dimensional control techniques. In contrast, the design methods examined in this book are based on the “continuum” version of the backstepping approach, applied to the PDE model of the flow.
Content based image retrieval systems
With an advent of technology, huge collection of digital images is formed as repositories on crime prevention, medical diagnosis, military, face finding, satellites and remote sensing. The task of searching for similar images in the repository is difficult. The data is growing enormously which makes it difficult to store and manage. The traditional image retrieval technique is inefficient in retrieving these images. Content-based image retrieval is an approach from data mining community, which provides the solution of managing this huge quantity of data. In this research, a Content-Based Image Retrieval (CBIR) system has been developed using color and texture as retrieval features from the image repository. The system allows the user to search for an image based on any of the two features alone or in combination by assigning weights to the features. The histogram and color moments approach is used to extract the color feature, texture feature is extracted using statistical moments and co-occurrence matrix method and the shape feature is extracted using the morphological operations. The images and the extracted feature vectors are stored in the Pickle file. The system is robust as it provides search based on the multiple features. The performance of the system was evaluated by analyzing the retrieval results using precision and recall.
Constrained optimization and image space analysis ; Vol.1 : Separation of sets and optimality conditions
Constrained Optimization and Image Space Analysis unites his results and presents optimization theory and variational inequalities in their light.It presents a new approach to the theory of constrained extremum problems, including Mathematical Programming, Calculus of Variations and Optimal Control Problems. Such an approach unifies the several branches: Optimality Conditions, Duality, Penalizations, Vector Problems, Variational Inequalities and Complementarity Problems. The applications benefit from a unified theory.
Computer vision - ECCV 2008 ; 10th European conference on computer vision, Marseille, France, October 12-18, 2008, Proceedings, Part IV
The four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed proceedings of the 10th European Conference on Computer Vision, ECCV 2008, held in Marseille, France, in October 2008.
Computational Turbulent Incompressible Flow: Applied Mathematics : Body and Soul 4
This is Volume 4 of the book series of the Body & Soul mathematics education reform program, and presents a unified new approach to computational simulation of turbulent.
Computational Noncommutative Algebra and Applications
The fusion of algebra, analysis and geometry, and their application to real world problems, have been dominant themes underlying mathematics for over the years. This book features topics such as: signal and image processing in remote sensing, computer vision, medical image processing, biological signal processing, geometric algebras, and more.
Computational Intelligence in Reliability Engineering : New Metaheuristics, Neural and Fuzzy Techniques in Reliability
This volume contains chapters presenting applications of different metaheuristics (ant colony optimization, great deluge algorithm, cross-entropy method and particle swarm optimization) in reliability engineering. It also includes chapters devoted to cellular automata and support vector machines and different applications of artificial neural networks, a powerful adaptive technique that can be used for learning, prediction and optimization. Several chapters describe different aspects of imprecise reliability and applications of fuzzy and vague set theory.
Computational intelligence in economics and finance ; Vol. II
Computational intelligence (CI), as an alternative to statistical and econometric approaches, has been applied to a wide range of economics and finance problems in recent years, for example to price forecasting and market efficiency. This book contains research ranging from applications in financial markets and business administration to various economics problems. Not only are empirical studies utilizing various CI algorithms presented, but so also are theoretical models based on computational methods. In addition to direct applications of computational intelligence, readers can also observe how these methods are combined with conventional analytical methods such as statistical and econometric models to yield preferred results.
Computational intelligence for engineering and manufacturing
Unlike traditional computing, Computational Intelligence is tolerant of imprecise information, partial truth and uncertainty. This book presents a collection of contributions on a focused treatment of important elements of CI, centred on its key element: learning.
Computational intelligence and security ; Vol. 3801 ; International Conference, CIS 2005, Xi'an, China, December 15-19, 2005, Proceedings, Part I
The two volume set LNAI 3801 and LNAI 3802 constitute the refereed proceedings of the annual International Conference on Computational Intelligence and Security, CIS 2005, held in Xi'an, China, in December 2005. The 338 revised papers presented - 254 regular and 84 extended papers - were carefully reviewed and selected from over 1800 submissions. The first volume is organized in topical sections on learning and fuzzy systems, evolutionary computation, intelligent agents and systems, intelligent information retrieval, support vector machines, swarm intelligence, data mining, pattern recognition, and applications.
Computational intelligence and bioinspired systems ; 8th International Work-conference on artificial neural networks, IWANN 2005, Vilanova i la Geltrú, Barcelona, Spain, June 8-10, 2005, Proceedings
We present in this volume the collection of finally accepted papers of the eighth edition of the “IWANN” conference (“International Work-Conference on Artificial Neural Networks”). This biennial meeting focuses on the foundations, theory, models and applications of systems inspired by nature (neural networks, fuzzy logic and evolutionary systems). For scientists, engineers and professionals working in the area, this is a very good way to get solid and competitive applications. We are facing a real revolution with the emergence of embedded intelligence in many artificial systems (systems covering diverse fields: industry, domotics, leisure, healthcare, … ). So we are convinced that an enormous amount of work must be, and should be, still done. Many pieces of the puzzle must be built and placed into their proper positions, offering us new and solid theories and models (necessary tools) for the application and praxis of these current paradigms. The above-mentioned concepts were the main reason for the subtitle of the IWANN 2005 edition: “Computational Intelligence and Bioinspired Systems.” papers was addressing the following topics: 1. Mathematical and theoretical methods in computational intelligence.
