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Multi-Net Optimization of VLSI Interconnect
by Konstantin Moiseev Avinoam Kolodny Shmuel WimerThis book covers layout design and layout migration methodologies for optimizing multi-net wire structures in advanced VLSI interconnects. Scaling-dependent models for interconnect power, interconnect delay and crosstalk noise are covered in depth, and several design optimization problems are addressed, such as minimization of interconnect power under delay constraints, or design for minimal delay in wire bundles within a given routing area. A handy reference or a guide for design methodologies and layout automation techniques, this book provides a foundation for physical design challenges of interconnect in advanced integrated circuits.
Multi-objective Evolutionary Optimisation for Product Design and Manufacturing
by Lihui Wang Kalyanmoy Deb Amos H. NgWith the increasing complexity and dynamism in today's product design and manufacturing, more optimal, robust and practical approaches and systems are needed to support product design and manufacturing activities. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing presents a focused collection of quality chapters on state-of-the-art research efforts in multi-objective evolutionary optimisation, as well as their practical applications to integrated product design and manufacturing. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing consists of two major sections. The first presents a broad-based review of the key areas of research in multi-objective evolutionary optimisation. The second gives in-depth treatments of selected methodologies and systems in intelligent design and integrated manufacturing. Recent developments and innovations in multi-objective evolutionary optimisation make Multi-objective Evolutionary Optimisation for Product Design and Manufacturing a useful text for a broad readership, from academic researchers to practicing engineers.
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-Objective Optimization: Evolutionary to Hybrid Framework
by Jyotsna K. Mandal Somnath Mukhopadhyay Paramartha DuttaThis 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-Objective Optimization in Computer Networks Using Metaheuristics
by Yezid Donoso Ramon FabregatMetaheuristics are widely used to solve important practical combinatorial optimization problems. Many new multicast applications emerging from the Internet-such as TV over the Internet, radio over the Internet, and multipoint video streaming-require reduced bandwidth consumption, end-to-end delay, and packet loss ratio. It is necessary to design an
Multi-Objective Optimization using Artificial Intelligence Techniques (SpringerBriefs in Applied Sciences and Technology)
by Seyedali Mirjalili Jin Song DongThis book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.
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-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-photon Quantum Secure Communication (Signals and Communication Technology)
by Pramode K. Verma Mayssaa El Rifai Kam Wai ChanThis book explores alternative ways of accomplishing secure information transfer with incoherent multi-photon pulses in contrast to conventional Quantum Key Distribution techniques. Most of the techniques presented in this book do not need conventional encryption. Furthermore, the book presents a technique whereby any symmetric key can be securely transferred using the polarization channel of an optical fiber for conventional data encryption. The work presented in this book has largely been practically realized, albeit in a laboratory environment, to offer proof of concept rather than building a rugged instrument that can withstand the rigors of a commercial environment.
Multi-Platform Graphics Programming with Kivy: Basic Analytical Programming for 2D, 3D, and Stereoscopic Design
by Moisés Cywiak David CywiakModern science requires computer graphics models to provide realistic visual renderings. Learning the appropriate programming tools for 2D and 3D modeling doesn’t have to be so difficult. This book reviews the best programming tools to achieve this and explains how to apply them to mobile platforms like Android. Multi-Platform Graphics Programming with Kivy provides a straightforward introductory approach for designing 2D, 3D, and stereoscopic applications, using analytical equations from vector algebra. Throughout the book you’ll look closely at this approach and develop scenes in Kivy, taking advantage of powerful mathematical functions for arrays by NumPy for Python. Unbuntu is used to develop the programs, which allows you to easily convert to Android platform. Each chapter contains step-by-step descriptions on each subject and provides complete program listings.What You’ll LearnWork with Kivy, a modern, powerful multi-platform graphics systemConvert and run programs on Android devicesProgram, fill faces, and rotate 2D and 3D polygonsApply the concepts of 2D and 3D applicationsDevelop stereoscopic scenesReview a straightforward introduction to 2D, 3D, and stereoscopic graphics applicationsUse simple analytical equations from vector algebraWho This Book Is ForThe primary audience is students and researchers in graphics programming with experience in analytical equations.
Multi-Processor System-on-Chip 1: Architectures
by Liliana Andrade Frederic RousseauA Multi-Processor System-on-Chip (MPSoC) is the key component for complex applications. These applications put huge pressure on memory, communication devices and computing units. This book, presented in two volumes – Architectures and Applications – therefore celebrates the 20th anniversary of MPSoC, an interdisciplinary forum that focuses on multi-core and multi-processor hardware and software systems. It is this interdisciplinarity which has led to MPSoC bringing together experts in these fields from around the world, over the last two decades. Multi-Processor System-on-Chip 1 covers the key components of MPSoC: processors, memory, interconnect and interfaces. It describes advance features of these components and technologies to build efficient MPSoC architectures. All the main components are detailed: use of memory and their technology, communication support and consistency, and specific processor architectures for general purposes or for dedicated applications.
Multi-Processor System-on-Chip 2: Applications
by Liliana Andrade Frederic RousseauA Multi-Processor System-on-Chip (MPSoC) is the key component for complex applications. These applications put huge pressure on memory, communication devices and computing units. This book, presented in two volumes – Architectures and Applications – therefore celebrates the 20th anniversary of MPSoC, an interdisciplinary forum that focuses on multi-core and multi-processor hardware and software systems. It is this interdisciplinarity which has led to MPSoC bringing together experts in these fields from around the world, over the last two decades. Multi-Processor System-on-Chip 2 covers application-specific MPSoC design, including compilers and architecture exploration. This second volume describes optimization methods, tools to optimize and port specific applications on MPSoC architectures. Details on compilation, power consumption and wireless communication are also presented, as well as examples of modeling frameworks and CAD tools. Explanations of specific platforms for automotive and real-time computing are also included.
Multi-Robot Systems: Coordinated Fencing Control and Applications (Cognitive Intelligence and Robotics)
by Bin-Bin Hu Hai-Tao ZhangMulti-robot coordinated fencing, where a team of robots forms a protective formation around a target, has garnered significant attention and proven useful in practical applications such as area convoying. However, real-world scenarios often involve complex target characteristics, including varying dynamics and multiple targets, which can pose challenges in maintaining the formation. Additionally, due to sensor costs and environmental constraints, robots may only have access to directional constraint information, presenting further challenges. This book highlights cooperative fencing approaches for multi-robot systems and their practical applications to different unmanned surface (ground) vehicles, providing an overview of research trends and future directions in coordinated fencing. Firstly, a basic fencing controller using neighboring angle repulsion for a constant-velocity target is designed, laying the groundwork for complex fencing missions. Then, for more complex fencing with an evenly rotating formation, a distributed controller is developed using input-to-state stability, achieving coordinated fencing under intermittently varying topologies. For more complex varying-velocity targets, a distributed fencing controller based on output regulation theory is proposed. For general target fencing missions in both 2D and 3D, a formal long-term task execution framework is developed using control barrier functions. Moreover, unlike previous methods that rely on the relative position between the robot and the target, a distributed bearing-only fencing control algorithm based on the persistent-excitation condition is developed, requiring only comparatively inexpensive sensors. Finally, this exploration into the theory and application of coordinated fencing control provides guidelines for robust, efficient, and complex practical implementations of multi-robot missions.
Multi-run Memory Tests for Pattern Sensitive Faults
by Ireneusz MrozekThis book describes efficient techniques for production testing as well as for periodic maintenance testing (specifically in terms of multi-cell faults) in modern semiconductor memory. The author discusses background selection and address reordering algorithms in multi-run transparent march testing processes. Formal methods for multi-run test generation and many solutions to increase their efficiency are described in detail. All methods presented ideas are verified by both analytical investigations and numerical simulations.Provides the first book related exclusively to the problem of multi-cell fault detection by multi-run tests in memory testing process;Presents practical algorithms for design and implementation of efficient multi-run tests;Demonstrates methods verified by analytical and experimental investigations.
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-Sensor and Multi-Temporal Remote Sensing: Specific Single Class Mapping
by Anil Kumar Priyadarshi Upadhyay Uttara SinghThis book elaborates fuzzy machine and deep learning models for single class mapping from multi-sensor, multi-temporal remote sensing images while handling mixed pixels and noise. It also covers the ways of pre-processing and spectral dimensionality reduction of temporal data. Further, it discusses the ‘individual sample as mean’ training approach to handle heterogeneity within a class. The appendix section of the book includes case studies such as mapping crop type, forest species, and stubble burnt paddy fields. Key features: Focuses on use of multi-sensor, multi-temporal data while handling spectral overlap between classes Discusses range of fuzzy/deep learning models capable to extract specific single class and separates noise Describes pre-processing while using spectral, textural, CBSI indices, and back scatter coefficient/Radar Vegetation Index (RVI) Discusses the role of training data to handle the heterogeneity within a class Supports multi-sensor and multi-temporal data processing through in-house SMIC software Includes case studies and practical applications for single class mapping This book is intended for graduate/postgraduate students, research scholars, and professionals working in environmental, geography, computer sciences, remote sensing, geoinformatics, forestry, agriculture, post-disaster, urban transition studies, and other related areas.
Multi-sensor Fusion for Autonomous Driving
by Xinyu Zhang Jun Li Zhiwei Li Huaping Liu Mo Zhou Li Wang Zhenhong ZouAlthough sensor fusion is an essential prerequisite for autonomous driving, it entails a number of challenges and potential risks. For example, the commonly used deep fusion networks are lacking in interpretability and robustness. To address these fundamental issues, this book introduces the mechanism of deep fusion models from the perspective of uncertainty and models the initial risks in order to create a robust fusion architecture. This book reviews the multi-sensor data fusion methods applied in autonomous driving, and the main body is divided into three parts: Basic, Method, and Advance. Starting from the mechanism of data fusion, it comprehensively reviews the development of automatic perception technology and data fusion technology, and gives a comprehensive overview of various perception tasks based on multimodal data fusion. The book then proposes a series of innovative algorithms for various autonomous driving perception tasks, to effectively improve the accuracy and robustness of autonomous driving-related tasks, and provide ideas for solving the challenges in multi-sensor fusion methods. Furthermore, to transition from technical research to intelligent connected collaboration applications, it proposes a series of exploratory contents such as practical fusion datasets, vehicle-road collaboration, and fusion mechanisms. In contrast to the existing literature on data fusion and autonomous driving, this book focuses more on the deep fusion method for perception-related tasks, emphasizes the theoretical explanation of the fusion method, and fully considers the relevant scenarios in engineering practice. Helping readers acquire an in-depth understanding of fusion methods and theories in autonomous driving, it can be used as a textbook for graduate students and scholars in related fields or as a reference guide for engineers who wish to apply deep fusion methods.
Multi-Site Network and Security Services with NSX-T: Implement Network Security, Stateful Services, and Operations
by Iwan HoogendoornKnow the basics of network security services and other stateful services such as NAT, gateway and distributed firewalls (L2-L7), virtual private networks (VPN), load balancing (LB), and IP address management. This book covers these network and security services and how NSX-T also offers integration and interoperability with various other products that are not only created by VMware, but are also referred by VMware as third-party integrated vendors.With the integration of VMware vRealize Automation, you can automate full application platforms consisting of multiple virtual machines with network and security services orchestrated and fully automated.From the operational perspective, this book provides best practices on how to configure logging, notification, and monitoring features and teaches you how to get the required visibility of not only your NSX-T platform but also your NSX-T-enabled network infrastructure.Another key part of this book is the explanation of multi-site capabilities and how network and security services can be offered across multiple on-premises locations with a single management pane. Interface with public cloud services also is included. The current position of NSX-T operation in on-premises private clouds and the position and integration with off-premises public clouds are covered as well.This book provides a good understanding of integrations with other software to bring the best out of NSX-T and offer even more features and capabilities.What You Will LearnUnderstand the NSX-T security firewall and advanced securityBecome familiar with NAT, DNS, DHCP, and load balancing featuresMonitor your NSX-T environmentBe aware of NSX-T authentication and authorization possibilitiesUnderstand integration with cloud automation platformsKnow what multi-cloud integrations are possible and how to integrate NSX-T with the public cloud Who This Book Is ForVirtualization administrators, system integrators
Multi-source, Multilingual Information Extraction and Summarization
by Horacio Saggion Jakub Piskorski Roman Yangarber Thierry PoibeauInformation extraction (IE) and text summarization (TS) are powerful technologies for finding relevant pieces of information in text and presenting them to the user in condensed form. The ongoing information explosion makes IE and TS critical for successful functioning within the information society. These technologies face particular challenges due to the inherent multi-source nature of the information explosion. The technologies must now handle not isolated texts or individual narratives, but rather large-scale repositories and streams---in general, in multiple languages---containing a multiplicity of perspectives, opinions, or commentaries on particular topics, entities or events. There is thus a need to adapt existing techniques and develop new ones to deal with these challenges. This volume contains a selection of papers that present a variety of methodologies for content identification and extraction, as well as for content fusion and regeneration. The chapters cover various aspects of the challenges, depending on the nature of the information sought---names vs. events,--- and the nature of the sources---news streams vs. image captions vs. scientific research papers, etc. This volume aims to offer a broad and representative sample of studies from this very active research field.
Multi-spectral and Intelligent Sensing (SpringerBriefs in Computer Science)
by Liting Wang Xiaoming Tao Lu Sun Wentao ShenThis book provides a concise overview of intelligent technologies for vision and sensing, with a particular focus on their applications in various multispectral configurations, including safety monitoring in rural areas. Within the realm of intelligent perception and contemporary healthcare, the book emphasizes the real-time monitoring, analysis, and prediction of vital signals using biomedical optical sensors. This approach aims to offer more adaptable and personalized services within the medical health management domain. Furthermore, the book delves into the comprehensive comprehension of physiological signals and additional data sources, such as environmental and motion data. The goal is to enhance the breadth and depth of data analysis, providing more integrated support for the life and health sector. Additionally, the book explores the implementation of edge intelligence algorithms at the sensor level to enable real-time analysis, enhancing the efficiency of sensor data processing and utilization. Detailed explanations of the configuration and deployment of an active vision camera system featuring an integrated edge algorithm are provided to elucidate the coordination and communication mechanisms of edge intelligence technology across multiple edge devices. A specific application case is then presented—the universal camera jamming system—which underscores the benefits of intelligent sensing fusion for tasks such as attitude and position recognition, as well as self-feedback excitation jamming. The book underscores the pervasive and seamless integration of smart sensing in both current and future lifestyles, spanning from active vision cameras to diverse applications across multiple spectrums. Its insights are poised to stimulate innovation and application within the realms of smart vision and sensing, including a comprehensive analysis of future healthcare paradigms.
Multi-Step Multi-Input One-Way Quantum Information Processing with Spatial and Temporal Modes of Light
by Ryuji UkaiIn this thesis, the author develops for the first time an implementation methodology for arbitrary Gaussian operations using temporal-mode cluster states. The author also presents three experiments involving continuous-variable one-way quantum computations, where their non-classical nature is shown by observing entanglement at the outputs. The experimental basic structure of one-way quantum computation over two-mode input state is demonstrated by the controlled-Z gate and the optimum nonlocal gate experiments. Furthermore, the author proves that the operation can be controlled by the gain-tunable entangling gate experiment.
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 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-UAV Planning and Task Allocation (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)
by Yasmina Bestaoui SebbaneMulti-robot systems are a major research topic in robotics. Designing, testing, and deploying aerial robots in the real world is a possibility due to recent technological advances. This book explores different aspects of cooperation in multiagent systems. It covers the team approach as well as deterministic decision-making. It also presents distributed receding horizon control, as well as conflict resolution, artificial potentials, and symbolic planning. The book also covers association with limited communications, as well as genetic algorithms and game theory reasoning. Multiagent decision-making and algorithms for optimal planning are also covered along with case studies. Key features: Provides a comprehensive introduction to multi-robot systems planning and task allocation Explores multi-robot aerial planning; flight planning; orienteering and coverage; and deployment, patrolling, and foraging Includes real-world case studies Treats different aspects of cooperation in multiagent systems Both scientists and practitioners in the field of robotics will find this text valuable.
Multi-valued Logic for Decision-Making Under Uncertainty (Computer Science Foundations and Applied Logic)
by Evgeny Kagan Alexander Rybalov Ronald YagerMulti-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.