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Mugging as a Social Problem (Routledge Revivals)
by Michael PrattFirst published in 1980, Mugging as a Social Problem sets out to remedy the deficiency of serious research on mugging. The work is based on a random sample of over 1000 muggings which occurred within the Metropolitan Police District in the mid-1970s, and the author analyses the results not only in absolute and comparative terms but also against a background of social determinants such as ecology, deprivation and race. Dr. Pratt’s long-term solution is not novel: an all-round improvement in housing, employment and social conditions will eventually remove the circumstances which create muggers; but there are steps, he suggests, which can be taken in the short term to stop mugging by reducing opportunity. However, before any effective measures can be introduced, more facts are needed about the background, motives and methods of the typical mugger: it is just such facts that this study sets out to provide. This book will be of interest to students of sociology, law, urban studies and criminology.
Mulholland's The Nurse, The Math, The Meds: Drug Calculations Using Dimensional Analysis
by Susan TurnerMulholland’s The Nurse, The Math, The Meds, 4th Edition helps you overcome any math anxiety you may have by clearly explaining how to use dimensional analysis to minimize drug calculation errors. It shows how to analyze and set up problems, estimate a reasonable answer, and then evaluate the answer for accuracy. But first, a review of basic math ensures that you remember essential math skills. Updated by nursing educator Susan Turner, this edition includes plenty of practice exercises to help you understand and master each aspect of dimensional analysis.
Multi Tenancy for Cloud-Based In-Memory Column Databases: Workload Management and Data Placement
by Jan SchaffnerWith the proliferation of Software-as-a-Service (SaaS) offerings, it is becoming increasingly important for individual SaaS providers to operate their services at a low cost. This book investigates SaaS from the perspective of the provider and shows how operational costs can be reduced by using "multi tenancy," a technique for consolidating a large number of customers onto a small number of servers. Specifically, the book addresses multi tenancy on the database level, focusing on in-memory column databases, which are the backbone of many important new enterprise applications. For efficiently implementing multi tenancy in a farm of databases, two fundamental challenges must be addressed, (i) workload modeling and (ii) data placement. The first involves estimating the (shared) resource consumption for multi tenancy on a single in-memory database server. The second consists in assigning tenants to servers in a way that minimizes the number of required servers (and thus costs) based on the assumed workload model. This step also entails replicating tenants for performance and high availability. This book presents novel solutions to both problems.
Multi-Agent Systems and Agreement Technologies
by Nardine Osman Natalia Criado Pacheco Carlos Carrascosa Vicente Julián IngladaThis book constitutes the revised selected papers from the 14th European Conference on Multi-Agent Systems, EUMAS 2016, and the Fourth International Conference on Agreement Technologies, AT 2016, held in Valencia, Spain, in December 2016. The 43 papers and 2 invited papers presented in this volume were carefully reviewed and selected from 68 submissions. The papers cover thematic areas as agent and multi-agent system models, algorithms, applications, simulations, theoretical studies, and for AT the thematic areas are: algorithms
Multi-Agent Systems: 16th European Conference, EUMAS 2018, Bergen, Norway, December 6–7, 2018, Revised Selected Papers (Lecture Notes in Computer Science #11450)
by Marija SlavkovikThis book constitutes the revised post-conference proceedings of the 16th European Conference on Multi-Agent Systems, EUMAS 2018, held at Bergen, Norway, in December 2018.The 18 full papers presented in this volume were carefully reviewed and selected from a total of 34 submissions. The papers report on both early and mature research and cover a wide range of topics in the field of multi-agent systems.
Multi-Band Effective Mass Approximations
by Matthias Ehrhardt Thomas KopruckiThis book addresses several mathematical models from the most relevant class of kp-Schrödinger systems. Both mathematical models and state-of-the-art numerical methods for adequately solving the arising systems of differential equations are presented. The operational principle of modern semiconductor nano structures, such as quantum wells, quantum wires or quantum dots, relies on quantum mechanical effects. The goal of numerical simulations using quantum mechanical models in the development of semiconductor nano structures is threefold: First they are needed for a deeper understanding of experimental data and of the operational principle. Secondly, they allow us to predict and optimize in advance the qualitative and quantitative properties of new devices in order to minimize the number of prototypes needed. Semiconductor nano structures are embedded as an active region in semiconductor devices. Thirdly and finally, the results of quantum mechanical simulations of semiconductor nano structures can be used with upscaling methods to deliver parameters needed in semi-classical models for semiconductor devices, such as quantum well lasers. This book covers in detail all these three aspects using a variety of illustrative examples. Readers will gain detailed insights into the status of the multiband effective mass method for semiconductor nano structures. Both users of the kp method as well as advanced researchers who want to advance the kp method further will find helpful information on how to best work with this method and use it as a tool for characterizing the physical properties of semiconductor nano structures. The book is primarily intended for graduate and Ph. D. students in applied mathematics, mathematical physics and theoretical physics, as well as all those working in quantum mechanical research or the semiconductor / opto-electronic industry who are interested in new mathematical aspects.
Multi-Component Acoustic Characterization of Porous Media
by Karel N. van DalenThe feasibility to extract porous medium parameters from acoustic recordings is investigated. The thesis gives an excellent discussion of our basic understanding of different wave modes, using a full-waveform and multi-component approach. Focus lies on the dependency on porosity and permeability where especially the latter is difficult to estimate. In this thesis, this sensitivity is shown for interface-wave and reflected-wave modes. For each of the pseudo-Rayleigh and pseudo-Stoneley interface waves unique estimates for permeability and porosity can be obtained when impedance and attenuation are combined. The pseudo-Stoneley wave is most sensitive to permeability: both the impedance and the attenuation are controlled by the fluid flow. Also from reflected-wave modes unique estimates for permeability and porosity can be obtained when the reflection coefficients of different reflected modes are combined. In this case the sensitivity to permeability is caused by subsurface heterogeneities generating mesoscopic fluid flow at seismic frequencies. The results of this thesis suggest that estimation of in-situ permeability is feasible, provided detection is carried out with multi-component measurements. The results of this thesis argely affect geotechnical and reservoir engineering practices.
Multi-Criteria Decision Analysis: Case Studies in Disaster Management
by Muhammet Gul Melih Yucesan Melike ErdoganMulti-Criteria Decision-Making (MCDM) includes methods and tools for modeling and solving complex problems. MCDM has become popular in the production and service sectors to improve the quality of service, reduce costs, and make people more prosperous. This book illustrates applications through case studies focused on disaster management. With a presentation of both Multi-Attribute Decision-Making (MADM) and Multi-Objective Decision-Making (MODM) models, this is the first book to merge these methods and tools with disaster management. This book raises awareness for society and decision-makers on how to measure readiness and what necessary preventive measures need to be taken. It offers models and case studies that can be easily adapted to solve complex problems and find solutions in other fields. Multi-Criteria Decision Analysis: Case Studies in Disaster Management will offer new insights to researchers working in the areas of industrial engineering, systems engineering, healthcare systems, operations research, mathematics, business, computer science, and disaster management, and, hopefully, the book will also stimulate further work in MCDM.
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.