الصفحة 5
الصفحة 5
Multiagent System Technologies ; 6th German Conference, MATES 2008, Kaiserslautern, Germany, September 23-26, 2008. Proceedings
This book constitutes the refereed proceedings of the 6th German Conference on Multiagent Systems Technologies, MATES 2008, held in Kaiserslautern, Germany, in September 2008 - co-located with the 31st German Conference on Artificial Intelligence, KI 2008.The 16 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 35 submissions. The papers present and discuss the latest advances of research and development in the area of autonomous agents and multiagent systems ranging from theoretical and methodological issues to applications in various fields.
Multiaccess, Reservations & Queues
Reservation procedures constitute the core of many popular data transmission protocols. They consist of two steps: A request phase in which a station reserves the communication channel and a transmission phase in which the actual data transmission takes place. Such procedures are often applied in communication networks that are characterised by a shared communication channel with large round-trip times.In this book, we propose queuing models for situations that require a reservation procedure and validate their applicability in the context of cable networks.
Monitoring, Security, and Rescue Techniques in Multiagent Systems
This volume contains extended and improved versions of selected contributions presented at the International Workshop "Monitoring, Security and Rescue Techniques in Multiagent Systems".
Modular Algorithms in Symbolic Summation and Symbolic Integration
Brings together two streams in computer algebra: symbolic integration and summation on the one hand, and fast algorithmics on the other hand. In many algorithmically oriented areas of computer science, the analysis of al gorithms placed into the lime light by DonKnuth’stalkat the 1970ICM –provides a crystal-clear criterion for success. The researcher who designs an algorithm that is faster (asymptotically, in the worst case) than any previous method receives instant gratification : her result will be recognized as valuable. Al as, the downside is that such results come along quite infrequently, despite our best efforts. An alternative evaluation method is to run a new algorithm on examples; this has its obvious problems, but is sometimes the best we can do. George Collins, one of the fathers of computer algebra and a great experimenter,wrote in 1969: “I think this demonstrates again that a simple analysis is often more revealing than a ream of empirical data (although both are important). ” Within computer algebra, some areas have traditionally followed the former methodology, notably some parts of polynomial algebra and linear algebra. Other areas, such as polynomial system solving, have not yet been amenable to this - proach. The usual “input size” parameters of computer science seem inadequate, and although some natural “geometric” parameters have been identified (solution dimension, regularity), not all (potential) major progress can be expressed in this framework. Symbolic integration and summation have been in a similar state.
Modern parallel programming with C++ and assembly language : X86 SIMD development using AVX, AVX2, and AVX-512
Understand the essential details about x86 SIMD architectures and instruction sets including AVX, AVX2, and AVX-512. / Master x86 SIMD data types, arithmetic instructions, and data management operations using both integer and floating-point operands. / Code performance-enhancing functions and algorithms that fully exploit the SIMD capabilities of a modern x86 processor. Employ C++ intrinsic functions and x86-64 assembly language code to carry out arithmetic calculations using common programming constructs including arrays, matrices, and user-defined data structures. Harness the x86 SIMD instruction sets to significantly accelerate the performance of computationally intense algorithms in applications such as machine learning, image processing, computer graphics, statistics, and matrix arithmetic. / Apply leading-edge coding strategies and techniques to optimally exploit the x86 SIMD instruction sets for maximum possible performance.
Modern IoT onboarding platforms for advanced applications: a practitioner’s guide to KIS.ME
There is no doubt that digitalization solutions from Industry 4.0 and the Internet of Things (IoT) can be perceived as excellent candidate strategies capable of handling the above-stated issues concerning measurements and transparency. However, IoT tools themselves can provide appropriate data only, while their efficient integration and application are possible using a dedicated onboarding platform only. To settle this issue, the book undertakes the problem of modern IoT onboarding platforms for the advanced applications pertaining to manufacturing and logistics. In particular, instead of deliberating about a possible hypothetic platforms, an existing and efficient one is employed, which is called KIS.ME. KIS.ME (Keep It Simple. Manage Everything) is a complete IoT solution for a simple integration in manufacturing and logistics.
Modern deep learning for tabular data : Novel approaches to common modeling problems
Synthesizes and presents novel deep learning approaches to a seemingly unlikely domain - tabular data. Whether for finance, business, security, medicine, or countless other domain, deep learning can help mine and model complex patterns in tabular data - an incredibly ubiquitous form of structured data. Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs - Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks - through both their 'default' usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability.
Models, Methods and Tools for Product Service Design : The Manutelligence Project
This book summarizes research being pursued within the Manutelligence project, the goal of which is to help enterprises develop smart, social and flexible products with high value added services. Manutelligence has improved Product and Service Design by developing suitable models and methods, and connecting them through a modular, collaborative and secure ICT Platform. The use of real data collected in real time by Internet of Things (IoT) technologies underpins the design of product-service systems and makes it possible to monitor them throughout their life cycle. Available data allows costs and sustainability issues to be more accurately measured and simulated in the form of Life Cycle Cost (LCC) and Life Cycle Assessment (LCA). Analysing data from IoT systems and sharing LCC and LCA information via the ICT Platform can help to accelerate the design of product-service systems, reduce costs and better understand customer needs. Industrial partners involved in Manutelligence provide a clear overview of the project's outcomes, and demonstrate how its technological solutions can be used to improve the design of product-service systems and the management of product-service life cycles.
Modelling, Computation and Optimization in Information Systems and Management Sciences ; 2nd International Conference MCO 2008, Metz, France - Luxembourg, September 8-10, 2008. Proceedings
This book constitutes the refereed proceedings of the Second International Conference MCO 2008, Metz, France, September 2008.The 65 revised full papers presented were carefully reviewed and selected from 160 submissions. The papers are organized in topical sections on optimization and decision making; data mining theory, systems and applications; computer vision and image processing; computer communications and networks; optimization and search techniques for security, reliability, trust.
Modelling Distributed Systems
Process algebras are languages for the description of elementary parallel systems and are used to study the behavioural properties of distributed systems, but they often lack the ability to handle data. This textbook guides students through algebraic specification and verification of distributed systems, and some of the most prominent formal verification techniques.
Modelling and Simulation : Exploring Dynamic System Behaviour
Modelling and Simulation: Exploring Dynamic System Behaviour provides the reader with a balanced and integrated presentation of the modelling and simulation activity for both Discrete Event Dynamic Systems (DEDS) and Continuous Time Dynamic Systems (CTDS). This book presents the fundamentals necessary to understand the many important facets of the modeling and simulation methodology.
Modelling and Reasoning with Vague Concepts
This volume outlines a formal representation framework for modelling and reasoning with vague concepts in Artificial Intelligence. The new calculus has many applications, especially in automated reasoning, learning, data analysis and information fusion. This book gives a rigorous introduction to label semantics theory, illustrated with many examples, and suggests clear operational interpretations of the proposed measures. It also provides a detailed description of how the theory can be applied in data analysis and information fusion based on a range of benchmark problems.
Modelling and Development of Intelligent Systems ; 6th International Conference, MDIS 2019, Sibiu, Romania, October 3–5, 2019, Revised Selected Papers
This volume constitutes the refereed proceedings of the 6th International Conference on Modelling and Development of Intelligent Systems, MDIS 2019, held in Sibiu, Romania, in October 2019. The 13 revised full papers presented in the volume were carefully reviewed and selected from 31 submissions. The papers are organized in topical sections on adaptive systems; conceptual modelling; data mining; intelligent systems for decision support; machine learning.
Modeling Decisions for Artificial Intelligence ; Vol.3885 ; 3rd International Conference, MDAI 2006, Tarragona, Spain, April 3-5, 2006, Proceedings
This book constitutes the refereed proceedings of the Third International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2006, held in Tarragona, Spain, in April 2006.
Modeling Decisions for Artificial Intelligence ; 5th International Conference, MDAI 2008 Sabadell, Spain, October 30-31, 2008. Proceedings
This book constitutes the refereed proceedings of the 5th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2008, held in Sabadell, Spain, in October 2008.The 19 revised full papers presented together with 2 invited lectures were thoroughly reviewed and selected from 43 submissions; they are devoted to theory and tools for modeling decisions, as well as applications that encompass decision making processes and information fusion techniques. The papers are organized in topical sections on aggregation operators, decision making, clustering and similarity, computational intelligence and optimization, as well as data privacy.
Modeling Decisions for Artificial Intelligence ; 4th International Conference, MDAI 2007, Kitakyushu, Japan, August 16-18, 2007, Proceedings
Decision modeling is a key area in the developing field of AI, and this timely work connects researchers and professionals with the very latest research. It constitutes the refereed proceedings of the 4th International Conference on Modeling Decisions for Artificial Intelligence, held in Kitakyushu, Japan, in August 2007.
Modeling decisions : Information fusion and aggregation operators
This book covers the underlying science and application issues related to aggregation operators, focusing on tools used in practical applications that involve numerical information. Starting with detailed introductions to information fusion and integration, measurement and probability theory, fuzzy sets, and functional equations.
Modeling and simulation of complex communication networks
Covers important topics and approaches related to the modeling and simulation of complex communication networks from a complex adaptive systems perspective. The authors present different modeling paradigms and approaches as well as surveys and case studies. Modern network systems such as Internet of Things, Smart Grid, VoIP traffic, Peer-to-Peer protocol, and social networks, are inherently complex. They require powerful and realistic models and tools not only for analysis and simulation but also for prediction. With contributions from an international panel of experts, this book is essential reading for networking, computing, and communications professionals, researchers and engineers in the field of next generation networks and complex information and communication systems, and academics and advanced students working in these fields.
Modeling and Management of Fuzzy Semantic RDF Data
Presents the latest research findings in fuzzy RDF data modeling and management. Fuzziness widely exist in many data and knowledge intensive applications. With the increasing amount of metadata available, efficient and scalable management of massive semantic data with uncertainty is of crucial importance. This book goes to great depth concerning the fast-growing topic of technologies and approaches of modeling and managing fuzzy metadata with Resource Description Framework (RDF) format. Its major topics include representation of fuzzy RDF data, fuzzy RDF graph matching, query of fuzzy RDF data, and persistence of fuzzy RDF data in diverse databases. The objective of the book is to provide the state-of-the-art information to researchers, practitioners, and postgraduates students who work on the area of big data intelligence and at the same time serve as the uncertain data and knowledge engineering professional as a valuable real-world reference.
Model-Driven Development and Operation of Multi-Cloud Applications : The MODAClouds Approach
In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I "The Big Data Opportunity" explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission's BIG project.
