Anomaly Detection In Random Heterogeneous Media

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Anomaly Detection In Random Heterogeneous Media

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Author : Martin Simon
language : en
Publisher: Springer
Release Date : 2015-07-23

Anomaly Detection In Random Heterogeneous Media written by Martin Simon and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-23 with Mathematics categories.

This monograph is concerned with the analysis and numerical solution of a stochastic inverse anomaly detection problem in electrical impedance tomography (EIT). Martin Simon studies the problem of detecting a parameterized anomaly in an isotropic, stationary and ergodic conductivity random field whose realizations are rapidly oscillating. For this purpose, he derives Feynman-Kac formulae to rigorously justify stochastic homogenization in the case of the underlying stochastic boundary value problem. The author combines techniques from the theory of partial differential equations and functional analysis with probabilistic ideas, paving the way to new mathematical theorems which may be fruitfully used in the treatment of the problem at hand. Moreover, the author proposes an efficient numerical method in the framework of Bayesian inversion for the practical solution of the stochastic inverse anomaly detection problem.

Electromagnetic Scattering From Random Media

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Author : Timothy R. Field
language : en
Publisher: OUP Oxford
Release Date : 2008-12-18

Electromagnetic Scattering From Random Media written by Timothy R. Field and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-18 with Science categories.

The book develops the dynamical theory of scattering from random media from first principles. Its key findings are to characterize the time evolution of the scattered field in terms of stochastic differential equations, and to illustrate this framework in simulation and experimental data analysis. The physical models contain all correlation information and higher order statistics, which enables radar and laser scattering experiments to be interpreted. An emphasis is placed on the statistical character of the instantaneous fluctuations, as opposed to ensemble average properties. This leads to various means for detection, which have important consequences in radar signal processing and statistical optics. The book is also significant also because it illustrates how ideas in mathematical finance can be applied to physics problems in which non-Gaussian noise processes play an essential role. This pioneering book represents a significant advance in this field, and should prove valuable to leading edge researchers and practitioners at the postgraduate level and above.

Anomaly Detection In Random Heterogeneous Media

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Author : Martin Simon
language : en
Publisher:
Release Date : 2015

Anomaly Detection In Random Heterogeneous Media written by Martin Simon and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.

This monograph is concerned with the analysis and numerical solution of a stochastic inverse anomaly detection problem in electrical impedance tomography (EIT). Martin Simon studies the problem of detecting a parameterized anomaly in an isotropic, stationary and ergodic conductivity random field whose realizations are rapidly oscillating. For this purpose, he derives Feynman-Kac formulae to rigorously justify stochastic homogenization in the case of the underlying stochastic boundary value problem. The author combines techniques from the theory of partial differential equations and functional analysis with probabilistic ideas, paving the way to new mathematical theorems which may be fruitfully used in the treatment of the problem at hand. Moreover, the author proposes an efficient numerical method in the framework of Bayesian inversion for the practical solution of the stochastic inverse anomaly detection problem. Contents Feynman-Kac formulae Stochastic homogenization Statistical inverse problems Target Groups Students and researchers in the fields of inverse problems, partial differential equations, probability theory and stochastic processes Practitioners in the fields of tomographic imaging and noninvasive testing via EIT About the Author Martin Simon has worked as a researcher at the Institute of Mathematics at the University of Mainz from 2008 to 2014. During this period he had several research stays at the University of Helsinki. He has recently joined an asset management company as a financial mathematician.

Outlier Analysis

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Author : Charu C. Aggarwal
language : en
Publisher: Springer
Release Date : 2016-12-10

Outlier Analysis written by Charu C. Aggarwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-10 with Computers categories.

This book provides comprehensive coverage of the field of outlier analysis from a computer science point of view. It integrates methods from data mining, machine learning, and statistics within the computational framework and therefore appeals to multiple communities. The chapters of this book can be organized into three categories: Basic algorithms: Chapters 1 through 7 discuss the fundamental algorithms for outlier analysis, including probabilistic and statistical methods, linear methods, proximity-based methods, high-dimensional (subspace) methods, ensemble methods, and supervised methods. Domain-specific methods: Chapters 8 through 12 discuss outlier detection algorithms for various domains of data, such as text, categorical data, time-series data, discrete sequence data, spatial data, and network data. Applications: Chapter 13 is devoted to various applications of outlier analysis. Some guidance is also provided for the practitioner. The second edition of this book is more detailed and is written to appeal to both researchers and practitioners. Significant new material has been added on topics such as kernel methods, one-class support-vector machines, matrix factorization, neural networks, outlier ensembles, time-series methods, and subspace methods. It is written as a textbook and can be used for classroom teaching.

Outlier Ensembles

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Author : Charu C. Aggarwal
language : en
Publisher: Springer
Release Date : 2017-04-06

Outlier Ensembles written by Charu C. Aggarwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-06 with Computers categories.

This book discusses a variety of methods for outlier ensembles and organizes them by the specific principles with which accuracy improvements are achieved. In addition, it covers the techniques with which such methods can be made more effective. A formal classification of these methods is provided, and the circumstances in which they work well are examined. The authors cover how outlier ensembles relate (both theoretically and practically) to the ensemble techniques used commonly for other data mining problems like classification. The similarities and (subtle) differences in the ensemble techniques for the classification and outlier detection problems are explored. These subtle differences do impact the design of ensemble algorithms for the latter problem. This book can be used for courses in data mining and related curricula. Many illustrative examples and exercises are provided in order to facilitate classroom teaching. A familiarity is assumed to the outlier detection problem and also to generic problem of ensemble analysis in classification. This is because many of the ensemble methods discussed in this book are adaptations from their counterparts in the classification domain. Some techniques explained in this book, such as wagging, randomized feature weighting, and geometric subsampling, provide new insights that are not available elsewhere. Also included is an analysis of the performance of various types of base detectors and their relative effectiveness. The book is valuable for researchers and practitioners for leveraging ensemble methods into optimal algorithmic design.

Deep Learning For Social Media Data Analytics

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Author : Tzung-Pei Hong
language : en
Publisher: Springer Nature
Release Date : 2022-09-18

Deep Learning For Social Media Data Analytics written by Tzung-Pei Hong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-18 with Computers categories.

This edited book covers ongoing research in both theory and practical applications of using deep learning for social media data. Social networking platforms are overwhelmed by different contents, and their huge amounts of data have enormous potential to influence business, politics, security, planning and other social aspects. Recently, deep learning techniques have had many successful applications in the AI field. The research presented in this book emerges from the conviction that there is still much progress to be made toward exploiting deep learning in the context of social media data analytics. It includes fifteen chapters, organized into four sections that report on original research in network structure analysis, social media text analysis, user behaviour analysis and social media security analysis. This work could serve as a good reference for researchers, as well as a compilation of innovative ideas and solutions for practitioners interested in applying deep learning techniques to social media data analytics.

Secure Cloud Computing

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Author : Sushil Jajodia
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-01-23

Secure Cloud Computing written by Sushil Jajodia and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-23 with Computers categories.

This book presents a range of cloud computing security challenges and promising solution paths. The first two chapters focus on practical considerations of cloud computing. In Chapter 1, Chandramouli, Iorga, and Chokani describe the evolution of cloud computing and the current state of practice, followed by the challenges of cryptographic key management in the cloud. In Chapter 2, Chen and Sion present a dollar cost model of cloud computing and explore the economic viability of cloud computing with and without security mechanisms involving cryptographic mechanisms. The next two chapters address security issues of the cloud infrastructure. In Chapter 3, Szefer and Lee describe a hardware-enhanced security architecture that protects the confidentiality and integrity of a virtual machine’s memory from an untrusted or malicious hypervisor. In Chapter 4, Tsugawa et al. discuss the security issues introduced when Software-Defined Networking (SDN) is deployed within and across clouds. Chapters 5-9 focus on the protection of data stored in the cloud. In Chapter 5, Wang et al. present two storage isolation schemes that enable cloud users with high security requirements to verify that their disk storage is isolated from some or all other users, without any cooperation from cloud service providers. In Chapter 6, De Capitani di Vimercati, Foresti, and Samarati describe emerging approaches for protecting data stored externally and for enforcing fine-grained and selective accesses on them, and illustrate how the combination of these approaches can introduce new privacy risks. In Chapter 7, Le, Kant, and Jajodia explore data access challenges in collaborative enterprise computing environments where multiple parties formulate their own authorization rules, and discuss the problems of rule consistency, enforcement, and dynamic updates. In Chapter 8, Smith et al. address key challenges to the practical realization of a system that supports query execution over remote encrypted data without exposing decryption keys or plaintext at the server. In Chapter 9, Sun et al. provide an overview of secure search techniques over encrypted data, and then elaborate on a scheme that can achieve privacy-preserving multi-keyword text search. The next three chapters focus on the secure deployment of computations to the cloud. In Chapter 10, Oktay el al. present a risk-based approach for workload partitioning in hybrid clouds that selectively outsources data and computation based on their level of sensitivity. The chapter also describes a vulnerability assessment framework for cloud computing environments. In Chapter 11, Albanese et al. present a solution for deploying a mission in the cloud while minimizing the mission’s exposure to known vulnerabilities, and a cost-effective approach to harden the computational resources selected to support the mission. In Chapter 12, Kontaxis et al. describe a system that generates computational decoys to introduce uncertainty and deceive adversaries as to which data and computation is legitimate. The last section of the book addresses issues related to security monitoring and system resilience. In Chapter 13, Zhou presents a secure, provenance-based capability that captures dependencies between system states, tracks state changes over time, and that answers attribution questions about the existence, or change, of a system’s state at a given time. In Chapter 14, Wu et al. present a monitoring capability for multicore architectures that runs monitoring threads concurrently with user or kernel code to constantly check for security violations. Finally, in Chapter 15, Hasan Cam describes how to manage the risk and resilience of cyber-physical systems by employing controllability and observability techniques for linear and non-linear systems.

Social Inequality And Equity In Community Actions For Health

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Author : Mobolanle Balogun
language : en
Publisher: Frontiers Media SA
Release Date : 2023-03-16

Social Inequality And Equity In Community Actions For Health written by Mobolanle Balogun and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-16 with Medical categories.

Principles Systems And Applications Of Ip Telecommunications Services And Security For Next Generation Networks

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Author : Henning Schulzrinne
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-10-22

Principles Systems And Applications Of Ip Telecommunications Services And Security For Next Generation Networks written by Henning Schulzrinne and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-22 with Computers categories.

This book constitutes the thoroughly refereed proceedings of the 10th International Workshop on Principles, Systems and Applications of IP Telecommunications, held in Heidelberg, Germany, in July 2008. The 16 full papers presented were carefully reviewed and selected from a total of 56 submissions. Topics covered include recent advances in the domains of convergent networks, VoIP security, and multimedia service environments for next generation networks.

Affective Computing For Social Good

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Author : Muskan Garg
language : en
Publisher: Springer Nature
Release Date : 2024-10-07

Affective Computing For Social Good written by Muskan Garg and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-07 with Computers categories.

Affective Computing for Social Good: Enhancing Well-being, Empathy, and Equity offers an insightful journey into the intricate realm of affective computing. It covers a spectrum of topics ranging from foundational theories and technologies to ethical considerations and future possibilities. Beginning with "Deciphering the Emotional Spectrum: Advances in Emotion Science and Analysis," it sets the stage by tracing the evolution of understanding human emotions. Subsequent chapters explore practical applications, such as integrating clinical psychology with affective computing for therapeutic progress and leveraging affective computing in diagnosing and managing mood disorders more efficiently. As the narrative unfolds, the book emphasizes the crucial role of affective computing in fostering social justice and equity. It underscores the need for developing inclusive algorithms and databases while addressing ethical challenges like privacy, consent, and the risk of emotional manipulation. These discussions emphasize the significance of ethical deployment and regulation. The book also covers the technical aspects and applications of affective computing, including natural language processing for emotion recognition and analysis, voice emotion detection, and visual emotion recognition. It extends to applications, such as the use of affective computing in health management via recommender systems and personalized well-being interventions in mental health care. Addressing data challenges, "Enhancing Affective Computing with Data Augmentation: Strategies for Overcoming Limited Data Availability" presents solutions for imbalances affecting model performance. "Advancements in Multimodal Emotion Recognition" highlights the integration of facial expressions with physiological signals to improve emotion recognition accuracy and reliability. Concluding with "Ethical Considerations in Affective Computing" and "Cognitive Currents: A Path from Neuroscience to Consciousness," the book connects technical advancements in affective computing with broader ethical and philosophical inquiries surrounding consciousness and the human experience. Features: Helps readers understand the potential benefits of emotionally intelligent AI systems, such as improving mental health care, enhancing education, or promoting more ethical decision-making. Addresses ethical considerations related to the development and deployment of emotionally intelligent AI systems, helping readers to become more aware of the potential risks and trade-offs involved. Presents new approaches or frameworks for developing emotionally intelligent AI systems, providing readers with innovative ideas and perspectives. Provides examples of successful case studies where emotionally intelligent AI systems were used for social good, which may inspire readers to think about how they can contribute to society through AI development. Overall, this book will help readers gain a deeper understanding of the intersection between AI and human emotions, and how this technology can be used to create a more empathetic, compassionate, and socially responsible world.