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Multi-Fractal Traffic and Anomaly Detection in Computer Communications
by Ming LiThis book provides a comprehensive theory of mono- and multi-fractal traffic, including the basics of long-range dependent time series and 1/f noise, ergodicity and predictability of traffic, traffic modeling and simulation, stationarity tests of traffic, traffic measurement and the anomaly detection of traffic in communications networks. Proving that mono-fractal LRD time series is ergodic, the book exhibits that LRD traffic is stationary. The author shows that the stationarity of multi-fractal traffic relies on observation time scales, and proposes multi-fractional generalized Cauchy processes and modified multi-fractional Gaussian noise. The book also establishes a set of guidelines for determining the record length of traffic in measurement. Moreover, it presents an approach of traffic simulation, as well as the anomaly detection of traffic under distributed-denial-of service attacks. Scholars and graduates studying network traffic in computer science will find the book beneficial.
Multi-Label Dimensionality Reduction (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
by Liang Sun Shuiwang Ji Jieping YeSimilar to other data mining and machine learning tasks, multi-label learning suffers from dimensionality. An effective way to mitigate this problem is through dimensionality reduction, which extracts a small number of features by removing irrelevant, redundant, and noisy information. The data mining and machine learning literature currently lacks
Multi-Layer Potentials and Boundary Problems
by Marius Mitrea Irina MitreaMany phenomena in engineering and mathematical physics can be modeled by means of boundary value problems for a certain elliptic differential operator in a given domain. When the differential operator under discussion is of second order a variety of tools are available for dealing with such problems, including boundary integral methods, variational methods, harmonic measure techniques, and methods based on classical harmonic analysis. When the differential operator is of higher-order (as is the case, e.g., with anisotropic plate bending when one deals with a fourth order operator) only a few options could be successfully implemented. In the 1970s Alberto Calderón, one of the founders of the modern theory of Singular Integral Operators, advocated the use of layer potentials for the treatment of higher-order elliptic boundary value problems. The present monograph represents the first systematic treatment based on this approach. This research monograph lays, for the first time, the mathematical foundation aimed at solving boundary value problems for higher-order elliptic operators in non-smooth domains using the layer potential method and addresses a comprehensive range of topics, dealing with elliptic boundary value problems in non-smooth domains including layer potentials, jump relations, non-tangential maximal function estimates, multi-traces and extensions, boundary value problems with data in Whitney-Lebesque spaces, Whitney-Besov spaces, Whitney-Sobolev- based Lebesgue spaces, Whitney-Triebel-Lizorkin spaces,Whitney-Sobolev-based Hardy spaces, Whitney-BMO and Whitney-VMO spaces.
Multi-Level Bayesian Models for Environment Perception
by Csaba BenedekThis book deals with selected problems of machine perception, using various 2D and 3D imaging sensors. It proposes several new original methods, and also provides a detailed state-of-the-art overview of existing techniques for automated, multi-level interpretation of the observed static or dynamic environment. To ensure a sound theoretical basis of the new models, the surveys and algorithmic developments are performed in well-established Bayesian frameworks. Low level scene understanding functions are formulated as various image segmentation problems, where the advantages of probabilistic inference techniques such as Markov Random Fields (MRF) or Mixed Markov Models are considered. For the object level scene analysis, the book mainly relies on the literature of Marked Point Process (MPP) approaches, which consider strong geometric and prior interaction constraints in object population modeling. In particular, key developments are introduced in the spatial hierarchical decomposition of the observed scenarios, and in the temporal extension of complex MRF and MPP models. Apart from utilizing conventional optical sensors, case studies are provided on passive radar (ISAR) and Lidar-based Bayesian environment perception tasks. It is shown, via several experiments, that the proposed contributions embedded into a strict mathematical toolkit can significantly improve the results in real world 2D/3D test images and videos, for applications in video surveillance, smart city monitoring, autonomous driving, remote sensing, and optical industrial inspection.
Multi-Objective Optimization Problems
by Fran Sérgio Lobato Valder SteffenThis book is aimed at undergraduate and graduate students in applied mathematics or computer science, as a tool for solving real-world design problems. The present work covers fundamentals in multi-objective optimization and applications in mathematical and engineering system design using a new optimization strategy, namely the Self-Adaptive Multi-objective Optimization Differential Evolution (SA-MODE) algorithm. This strategy is proposed in order to reduce the number of evaluations of the objective function through dynamic update of canonical Differential Evolution parameters (population size, crossover probability and perturbation rate). The methodology is applied to solve mathematical functions considering test cases from the literature and various engineering systems design, such as cantilevered beam design, biochemical reactor, crystallization process, machine tool spindle design, rotary dryer design, among others.
Multi-Objective Optimization: Evolutionary to Hybrid Framework
by Paramartha Dutta Somnath Mukhopadhyay Jyotsna K. MandalThis book brings together the latest findings on efficient solutions of multi/many-objective optimization problems from the leading researchers in the field. The focus is on solving real-world optimization problems using strategies ranging from evolutionary to hybrid frameworks, and involving various computation platforms. The topics covered include solution frameworks using evolutionary to hybrid models in application areas like Analytics, Cancer Research, Traffic Management, Networks and Communications, E-Governance, Quantum Technology, Image Processing, etc. As such, the book offers a valuable resource for all postgraduate students and researchers interested in exploring solution frameworks for multi/many-objective optimization problems.
Multi-Omics Analysis of the Human Microbiome: From Technology to Clinical Applications
by Vijai Singh Indra ManiThis book introduces the rapidly evolving field of multi-omics in understanding the human microbiome. The book focuses on the technology used to generate multi-omics data, including advances in next-generation sequencing and other high-throughput methods. It also covers the application of artificial intelligence and machine learning algorithms to the analysis of multi-omics data, providing readers with an overview of the powerful computational tools that are driving innovation in this field. The chapter also explores the various bioinformatics databases and tools available for the analysis of multi-omics data. The book also delves into the application of multi-omics technology to the study of microbial diversity, including metagenomics, metatranscriptomics, and metaproteomics. The book also explores the use of these techniques to identify and characterize microbial communities in different environments, from the gut and oral microbiome to the skin microbiome and beyond. Towards theend, it focuses on the use of multi-omics in the study of microbial consortia, including mycology and the viral microbiome. The book also explores the potential of multi-omics to identify genes of biotechnological importance, providing readers with an understanding of the role that this technology could play in advancing biotech research. Finally, the book concludes with a discussion of the clinical applications of multi-omics technology, including its potential to identify disease biomarkers and develop personalized medicine approaches. Overall, this book provides readers with a comprehensive overview of this exciting field, highlighting the potential for multi-omics to transform our understanding of the microbial world.
Multi-Regional Input–Output Analysis of the Japanese Economy
by Mitsuo YamadaThis book presents multi-regional input-output tables from the prefectural level as well as non-survey methods for creating the tables that divide a prefecture into sub-regions—into municipalities, for instance. In this book, the reader will find a survey of Japan's multilayered input–output tables and the research employing them, with an explanation of how to compile and apply a multi-regional input–output table for the country’s economy. Also included is research on currently important topics in municipal economies, carried out by municipality-based input–output analysis. Many input–output tables already have been compiled for each of the 47 prefectures of Japan as well as for major municipalities such as ordinance-designated cities, i.e., with populations greater than 500,000. The input–output table, or “benchmark table”, for the entire country, which is jointly compiled by 10 ministries and agencies including the Ministry of Internal Affairs and Communications, provides the essential information for the compilation of regional input-output tables. In recent years, there has been a great deal of interest in the estimation of municipality-based input–output tables to help provide perspective for regional economic revitalization and evidence-based policymaking. This book, with its information on how to create and apply multiregional input–output tables, is useful for graduate students, researchers, and local government officials who are concerned with this field.
Multi-Resolution Methods for Modeling and Control of Dynamical Systems (Chapman & Hall/CRC Applied Mathematics & Nonlinear Science)
by Puneet Singla John L. JunkinsUnifying the most important methodology in this field, Multi-Resolution Methods for Modeling and Control of Dynamical Systems explores existing approximation methods as well as develops new ones for the approximate solution of large-scale dynamical system problems. It brings together a wide set of material from classical orthogonal function
Multi-State Survival Models for Interval-Censored Data (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
by Ardo van den HoutMulti-State Survival Models for Interval-Censored Data introduces methods to describe stochastic processes that consist of transitions between states over time. It is targeted at researchers in medical statistics, epidemiology, demography, and social statistics. One of the applications in the book is a three-state process for dementia and survival in the older population. This process is described by an illness-death model with a dementia-free state, a dementia state, and a dead state. Statistical modelling of a multi-state process can investigate potential associations between the risk of moving to the next state and variables such as age, gender, or education. A model can also be used to predict the multi-state process. The methods are for longitudinal data subject to interval censoring. Depending on the definition of a state, it is possible that the time of the transition into a state is not observed exactly. However, when longitudinal data are available the transition time may be known to lie in the time interval defined by two successive observations. Such an interval-censored observation scheme can be taken into account in the statistical inference. Multi-state modelling is an elegant combination of statistical inference and the theory of stochastic processes. Multi-State Survival Models for Interval-Censored Data shows that the statistical modelling is versatile and allows for a wide range of applications.
Multi-Strategy Learning Environment: Proceedings of ICMSLE 2024 (Algorithms for Intelligent Systems)
by Vincenzo Piuri Isidoros Perikos Vrince Vimal Amrit MukherjeeThe book presents selected papers from International Conference on Multi-Strategy Learning Environment (ICMSLE 2024), held at Graphic Era Hill University, Dehradun, India, during 12–13 January 2024. This book presents current research in machine learning techniques, deep learning theories and practices, interpretability and explainability of AI algorithms, game theory and learning, multi-strategy learning (MSL) in distributed and streaming environments, and adaptive data analysis and selective inference.
Multi-Valued Variational Inequalities and Inclusions (Springer Monographs in Mathematics)
by Siegfried Carl Vy Khoi LeThis book focuses on a large class of multi-valued variational differential inequalities and inclusions of stationary and evolutionary types with constraints reflected by subdifferentials of convex functionals. Its main goal is to provide a systematic, unified, and relatively self-contained exposition of existence, comparison and enclosure principles, together with other qualitative properties of multi-valued variational inequalities and inclusions. The problems under consideration are studied in different function spaces such as Sobolev spaces, Orlicz-Sobolev spaces, Sobolev spaces with variable exponents, and Beppo-Levi spaces. A general and comprehensive sub-supersolution method (lattice method) is developed for both stationary and evolutionary multi-valued variational inequalities, which preserves the characteristic features of the commonly known sub-supersolution method for single-valued, quasilinear elliptic and parabolic problems. This method provides a powerful tool for studying existence and enclosure properties of solutions when the coercivity of the problems under consideration fails. It can also be used to investigate qualitative properties such as the multiplicity and location of solutions or the existence of extremal solutions. This is the first in-depth treatise on the sub-supersolution (lattice) method for multi-valued variational inequalities without any variational structures, together with related topics. The choice of the included materials and their organization in the book also makes it useful and accessible to a large audience consisting of graduate students and researchers in various areas of Mathematical Analysis and Theoretical Physics.
Multi-armed Bandit Allocation Indices
by John Gittins Richard Weber Kevin GlazebrookIn 1989 the first edition of this book set out Gittins' pioneering index solution to the multi-armed bandit problem and his subsequent investigation of a wide of sequential resource allocation and stochastic scheduling problems. Since then there has been a remarkable flowering of new insights, generalizations and applications, to which Glazebrook and Weber have made major contributions.This second edition brings the story up to date. There are new chapters on the achievable region approach to stochastic optimization problems, the construction of performance bounds for suboptimal policies, Whittle's restless bandits, and the use of Lagrangian relaxation in the construction and evaluation of index policies. Some of the many varied proofs of the index theorem are discussed along with the insights that they provide. Many contemporary applications are surveyed, and over 150 new references are included.Over the past 40 years the Gittins index has helped theoreticians and practitioners to address a huge variety of problems within chemometrics, economics, engineering, numerical analysis, operational research, probability, statistics and website design. This new edition will be an important resource for others wishing to use this approach.
Multi-criteria Decision Analysis
by Philippe Nemery Alessio IshizakaThis book presents an introduction to MCDA followed by more detailed chapters about each of the leading methods used in this field. Comparison of methods and software is also featured to enable readers to choose the most appropriate method needed in their research.Worked examples as well as the software featured in the book are available on an accompanying website.
Multi-fidelity Surrogates: Modeling, Optimization and Applications (Engineering Applications of Computational Methods #12)
by Qi Zhou Min Zhao Jiexiang Hu Mengying MaThis book investigates two types of static multi-fidelity surrogates modeling approaches, sequential multi-fidelity surrogates modeling approaches, the multi-fidelity surrogates-assisted efficient global optimization, reliability analysis, robust design optimization, and evolutionary optimization. Multi-fidelity surrogates have attracted a significant amount of attention in simulation-based design and optimization in recent years. Some real-life engineering design problems, such as prediction of angular distortion in the laser welding, optimization design of micro-aerial vehicle fuselage, and optimization design of metamaterial vibration isolator, are also provided to illustrate the ability and merits of multi-fidelity surrogates in support of engineering design. Specifically, lots of illustrative examples are adopted throughout the book to help explain the approaches in a more “hands-on” manner. This book is a useful reference for postgraduates and researchers of mechanical engineering, as well as engineers of enterprises in related fields.
Multi-finger Haptic Interaction
by Manuel Ferre Ignacio GalianaMulti-finger Haptic Interaction presents a panorama of technologies and methods for multi-finger haptic interaction, together with an analysis of the benefits and implications of adding multiple-fingers to haptic applications. Research topics covered include: design and control of advanced haptic devices;multi-contact point simulation algorithms;interaction techniques and implications in human perception when interacting with multiple fingers.These multi-disciplinary results are integrated into applications such as medical simulators for training manual skills, simulators for virtual prototyping and precise manipulations in remote environments. Multi-finger Haptic Interaction presents the current and potential applications that can be developed with these systems, and details the systems' complexity. The research is focused on enhancing haptic interaction by providing multiple contact points to the user. This state-of-the-art volume is oriented towards researchers who are involved in haptic device design, rendering methods and perception studies, as well as readers from different disciplines who are interested in applying multi-finger haptic technologies and methods to their field of interest.
Multi-indicator Systems and Modelling in Partial Order
by Rainer Brüggemann Lars Carlsen Jochen Wittmann"Multi-indicator Systems and Modelling in Partial Order" contains the newest theoretical concepts as well as new applications or even applications, where standard multivariate statistics fail. Some of the presentations have their counterpart in the book; however, there are many contributions, which are completely new in the field of applied partial order.
Multi-objective Swarm Intelligence
by Satchidananda Dehuri Alok Kumar Jagadev Mrutyunjaya PandaThe aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO.
Multi-objective, Multi-class and Multi-label Data Classification with Class Imbalance: Theory and Practices (Springer Tracts in Nature-Inspired Computing)
by Sanjay Chakraborty Lopamudra DeyThis book explores intricate world of data classification with 'Multi-Objective, Multi-Class, and Multi-Label Data Classification.' This book studies sophisticated methods and strategies for working with complicated data sets, tackling the difficulties of various classes, many objectives, and complicated labelling tasks. This resource fosters a deeper grasp of multi-dimensional data analysis in today's data-driven world by providing readers with the skills and insights needed to navigate the subtleties of modern classification jobs, from algorithmic techniques to practical applications.
Multi-parameter Singular Integrals. (Annals of Mathematics Studies #189)
by Brian StreetThis book develops a new theory of multi-parameter singular integrals associated with Carnot-Carathéodory balls. Brian Street first details the classical theory of Calderón-Zygmund singular integrals and applications to linear partial differential equations. He then outlines the theory of multi-parameter Carnot-Carathéodory geometry, where the main tool is a quantitative version of the classical theorem of Frobenius. Street then gives several examples of multi-parameter singular integrals arising naturally in various problems. The final chapter of the book develops a general theory of singular integrals that generalizes and unifies these examples. This is one of the first general theories of multi-parameter singular integrals that goes beyond the product theory of singular integrals and their analogs. Multi-parameter Singular Integrals will interest graduate students and researchers working in singular integrals and related fields.
Multi-parametric Optimization and Control (Wiley Series in Operations Research and Management Science)
by Efstratios N. Pistikopoulos Nikolaos A. Diangelakis Richard OberdieckRecent developments in multi-parametric optimization and control Multi-Parametric Optimization and Control provides comprehensive coverage of recent methodological developments for optimal model-based control through parametric optimization. It also shares real-world research applications to support deeper understanding of the material. Researchers and practitioners can use the book as reference. It is also suitable as a primary or a supplementary textbook. Each chapter looks at the theories related to a topic along with a relevant case study. Topic complexity increases gradually as readers progress through the chapters. The first part of the book presents an overview of the state-of-the-art multi-parametric optimization theory and algorithms in multi-parametric programming. The second examines the connection between multi-parametric programming and model-predictive control—from the linear quadratic regulator over hybrid systems to periodic systems and robust control. The third part of the book addresses multi-parametric optimization in process systems engineering. A step-by-step procedure is introduced for embedding the programming within the system engineering, which leads the reader into the topic of the PAROC framework and software platform. PAROC is an integrated framework and platform for the optimization and advanced model-based control of process systems. Uses case studies to illustrate real-world applications for a better understanding of the concepts presented Covers the fundamentals of optimization and model predictive control Provides information on key topics, such as the basic sensitivity theorem, linear programming, quadratic programming, mixed-integer linear programming, optimal control of continuous systems, and multi-parametric optimal control An appendix summarizes the history of multi-parametric optimization algorithms. It also covers the use of the parametric optimization toolbox (POP), which is comprehensive software for efficiently solving multi-parametric programming problems.
Multi-scale Analysis for Random Quantum Systems with Interaction
by Yuri Suhov Victor ChulaevskyThe study of quantum disorder has generated considerable research activity in mathematics and physics over past 40 years. While single-particle models have been extensively studied at a rigorous mathematical level, little was known about systems of several interacting particles, let alone systems with positive spatial particle density. Creating a consistent theory of disorder in multi-particle quantum systems is an important and challenging problem that largely remains open. Multi-scale Analysis for Random Quantum Systems with Interaction presents the progress that had been recently achieved in this area. The main focus of the book is on a rigorous derivation of the multi-particle localization in a strong random external potential field. To make the presentation accessible to a wider audience, the authors restrict attention to a relatively simple tight-binding Anderson model on a cubic lattice Zd. This book includes the following cutting-edge features: an introduction to the state-of-the-art single-particle localization theory an extensive discussion of relevant technical aspects of the localization theory a thorough comparison of the multi-particle model with its single-particle counterpart a self-contained rigorous derivation of both spectral and dynamical localization in the multi-particle tight-binding Anderson model. Required mathematical background for the book includes a knowledge of functional calculus, spectral theory (essentially reduced to the case of finite matrices) and basic probability theory. This is an excellent text for a year-long graduate course or seminar in mathematical physics. It also can serve as a standard reference for specialists.
Multi-scale Simulation of Composite Materials: Results from the Project MuSiKo (Mathematical Engineering)
by Stefan Diebels Sergej RjasanowDue to their high stiffness and strength and their good processing properties short fibre reinforced thermoplastics are well-established construction materials.Up to now, simulation of engineering parts consisting of short fibre reinforced thermoplastics has often been based on macroscopic phenomenological models, but deformations, damage and failure of composite materials strongly depend on their microstructure. The typical modes of failure of short fibre thermoplastics enriched with glass fibres are matrix failure, rupture of fibres and delamination, and pure macroscopic consideration is not sufficient to predict those effects. The typical predictive phenomenological models are complex and only available for very special failures. A quantitative prediction on how failure will change depending on the content and orientation of the fibres is generally not possible, and the direct involvement of the above effects in a numerical simulation requires multi-scale modelling.One the one hand, this makes it possible to take into account the properties of the matrix material and the fibre material, the microstructure of the composite in terms of fibre content, fibre orientation and shape as well as the properties of the interface between fibres and matrix. On the other hand, the multi-scale approach links these local properties to the global behaviour and forms the basis for the dimensioning and design of engineering components. Furthermore, multi-scale numerical simulations are required to allow efficient solution of the models when investigating three-dimensional problems of dimensioning engineering parts.Bringing together mathematical modelling, materials mechanics, numerical methods and experimental engineering, this book provides a unique overview of multi-scale modelling approaches, multi-scale simulations and experimental investigations of short fibre reinforced thermoplastics. The first chapters focus on two principal subjects: the mathematical and mechanical models governing composite properties and damage description. The subsequent chapters present numerical algorithms based on the Finite Element Method and the Boundary Element Method, both of which make explicit use of the composite’s microstructure. Further, the results of the numerical simulations are shown and compared to experimental results.Lastly, the book investigates deformation and failure of composite materials experimentally, explaining the applied methods and presenting the results for different volume fractions of fibres.This book is a valuable resource for applied mathematics, theoretical and experimental mechanical engineers as well as engineers in industry dealing with modelling and simulation of short fibre reinforced composites.
Multi-valued Logic for Decision-Making Under Uncertainty (Computer Science Foundations and Applied Logic)
by Ronald Yager Evgeny Kagan Alexander RybalovMulti-valued and fuzzy logics provide mathematical and computational tools for handling imperfect information and decision-making with rational collective reasoning and irrational individual judgements. The suggested implementation of multi-valued logics is based on the uninorm and absorbing norm with generating functions defined by probability distributions. Natural extensions of these logics result in non-commutative and non-distributive logics. In addition to Boolean truth values, these logics handle subjective truth and false values and model irrational decisions. Dynamics of decision-making are specified by the subjective Markov process and learning – by neural network with extended Tsetlin neurons. Application of the suggested methods is illustrated by modelling of irrational economic decisions and biased reasoning in the wisdom-of-the-crowd method, and by control of mobile robots and navigation of their groups. Topics and features: Bridges the gap between fuzzy and probability methods Includes examples in the field of machine-learning and robots’ control Defines formal models of subjective judgements and decision-making Presents practical techniques for solving non-probabilistic decision-making problems Initiates further research in non-commutative and non-distributive logics The book forms a basis for theoretical studies and practice of decision-making under uncertainty and will be useful for computer scientists and mathematicians interested in multi-valued and fuzzy logic, as well as for engineers working in the field of data mining and data analysis.
Multi-variant User Interfaces in E-commerce: A Practical Approach to UI Personalization (Progress in IS)
by Adam WasilewskiThis book focuses on the personalisation of the user interface in e-commerce based on collected data on customer behaviour. While product recommendation systems are widely used for this purpose today, they do not allow for a comprehensive adaptation of the layout to different user groups. The proposed approach is based on the conclusion that since e-commerce customers are different, the user interface should also be different. To make this possible, several components need to be combined, which together allow the design of the online shop to be automatically or expertly adapted to the customer's choices and behaviour. It presents and discusses a framework that allows data to be collected, processed and used to optimise UI variants for generated customer segments. The proposed approach has been verified in practice and further developed on this basis, so that the reader is presented with a solution that is not riddled with 'baby age' problems, and the limitations and challenges identified are described and commented on in detail. Typical e-commerce systems currently have a single UI for all customers. The implementation of multi-variant UIs therefore represents an opportunity for companies to create a marketing advantage by addressing the personalisation trends in e-commerce.The book is intended for those responsible for developing e-commerce platform and user interfaces for web-based systems, as well as individuals interested in practical applications of machine learning in business.