الصفحة 22
الصفحة 22
Logistics Systems : Design and Optimization
In a context of global competition, the optimization of logistics systems is inescapable. LOGISTICS SYSTEMS: Design and Optimization falls within this perspective and presents twelve chapters that well illustrate the variety and the complexity of logistics activities. Each chapter is written by recognized researchers who have been commissioned to survey a specific topic or emerging area of logistics. The first chapter, by Riopel, Langevin, and Campbell, develops a framework for the entire book. It classifies logistics decisions and highlights the relevant linkages to logistics decisions. The intricacy of these linkages demonstrates how thoroughly the decisions are interrelated and underscores the complexity of managing logistics activities. Each of the following chapters focus on quantitative methods for the design and optimization of logistics systems.
Logic, language, information and computation ; 15th International Workshop, WoLLIC 2008 Edinburgh, UK, July 1-4, 2008 Proceedings
The papers cover all pertinent subjects in computer science with particular interest in cross-disciplinary topics. Typical areas of interest are: foundations of computing and programming; novel computation models and paradigms; broad notions of proof and belief; formal methods in software and hardware development; logical approach to natural language and reasoning; logics of programs, actions and resources; foundational aspects of information organization, search, flow, sharing, and protection.
Logic for Programming, Artificial Intelligence, and Reasoning ; Vol. 3452 : 11th International Workshop, LPAR 2004, Montevideo, Uruguay, March 14-18, 2005, Proceedings
Contains the papers presented at the 11th International Conference on Logic for Programming, Arti'cial Intelligence, and Reasoning (LPAR), held from March 14 to 18, 2005, in Montevideo, Uruguay, together with the 5th - ternational Workshop on the Implementation of Logics (organized by Stephan Schulz and Boris Konev) and the Workshop on Analytic Proof Systems (or- nized by Matthias Baaz). The call for papers attracted 77 paper submissions, each of which was - viewed by at least three expert reviewers. The ?nal decisions on the papers were taken during an electronic Program Committee meeting held on the Internet. The Internet-based submission, reviewing, and discussion software EasyChair, provided by the second PC co-chair, supported each stage of the reviewing p- cess.
Location, Transport and Land-Use : Modelling Spatial-Temporal Information
Shows the use of statistical tools for forecasting and analyzing implications of land-use decisions. The idea is that la- use on a map is necessarily a consequence of individual, and often conflicting, siting decisions over time.
Local Pattern Detection ; International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers
Introduction The dramatic increase in available computer storage capacity over the last 10 years has led to the creation of very large databases of scienti?c and commercial information. The need to analyze these masses of data has led to the evolution of the new field knowledge discovery in databases (KDD) at the intersection of machine learning, statistics and database technology. Being interdisciplinary by nature, the field offers the opportunity to combine the expertise of different fields into a common objective. Moreover, within each field diverse methods have been developed and justified with respect to different quality criteria. We have to investigate how these methods can contributet o solving the problem of KDD. Traditionally, KDD was seeking to end global models for the data that - plain most of the instances of the database and describe the general structure of the data. Examples are statistical time series models, cluster models, logic programs with high coverageor classi?cation models like decision trees or linear decision functions. In practice, though, the use of these models often is very l- ited, because global models tend to end only the obvious patterns in the data, 1 which domain experts already are aware of . What is really of interest to the users are the local patterns that deviate from the already-known background knowledge. David Hand, who organized a workshop in 2002, proposed the new field of local patterns.
Little and Falace's Dental Management of the Medically Compromised Patient ; 9th ed.
Learn how to provide dental care to any patient, regardless of existing medical conditions. Little and Falace’s Dental Management of the Medically Compromised Patient, 9th Edition, has been thoroughly revised to give you the information you need to assess common problems, and make safe and healthy dental management decisions. The new addition includes expanded coverage of women’s health issues and introduces a process for developing a medical-risk source. Also, each chapter features vivid illustrations and well-organized tables to give you in-depth details and overall summaries to help you get to the root of your future patients’ needs.
Liquidity, markets and trading in action : An interdisciplinary perspective
This book addresses four standard business school subjects: microeconomics, macroeconomics, finance and information systems as they relate to trading, liquidity, and market structure. It provides a detailed examination of the impact of trading costs and other impediments of trading that the authors call “frictions”. It also presents an interactive simulation model of equity market trading, TraderEx, that enables students to implement trading decisions in different market scenarios and structures. Addressing these topics shines a bright light on how a real-world financial market operates, and the simulation provides students with an experiential learning opportunity that is informative and fun.
Life centered financial planning : How to deliver value that will never be undervalued
Life-Centered Financial Planning: How to Deliver Value That Will Never Be Undervalued shows financial planners and advisors how to radically improve the service they provide to their clients by tying their decisions and strategies to their clients’ life events, stages, and goals.
Learning Theory ; Vol. 4005 ; 19th Annual Conference on Learning Theory, COLT 2006, Pittsburgh, PA, USA, June 22-25, 2006, Proceedings
Constitutes the refereed proceedings of the 19th Annual Conference on Learning Theory, COLT 2006, held in Pittsburgh, Pennsylvania, USA in June 2006. The 43 revised full papers presented together with 2 articles on open problems and 3 invited lectures were carefully reviewed and selected from a total of 102 submissions. The papers cover a wide range of topics including clustering, un- and semisupervised learning, statistical learning theory, regularized learning and kernel methods, query learning and teaching, inductive inference, learning algorithms and limitations on learning, online aggregation, online prediction and reinforcement learning.
Learning theory ; 20th Annual Conference on Learning theory, COLT 2007, San Diego, CA, USA, June 13-15, 2007, Proceedings
It covers unsupervised, semisupervised and active learning, statistical learning theory, inductive inference, regularized learning, kernel methods, SVM, online and reinforcement learning, learning algorithms and limitations on learning, dimensionality reduction, as well as open problems.
Learning Classifier Systems ; International Workshops, IWLCS 2003-2005, Revised Selected Papers
The work embodied in this volume was presented across three consecutive e- tions of the International Workshop on Learning Classi?er Systems that took place in Chicago (2003), Seattle (2004), and Washington (2005). The Genetic and Evolutionary Computation Conference, the main ACM SIGEvo conference, hosted these three editions.
Learning and Adaption in Multi-Agent Systems ; 1st International Workshop, LAMAS 2005, Utrecht, The Netherlands, July 25, 2005, Revised Selected Papers
Contains selected and revised papers of the International Workshop on Lea- ing and Adaptation in Multi-Agent Systems (LAMAS 2005), held at the AAMAS 2005 Conference in Utrecht, The Netherlands, July 26. An important aspect in multi-agent systems (MASs) is that the environment evolves over time, not only due to external environmental changes but also due to agent int- actions. For this reason it is important that an agent can learn, based on experience, and adapt its knowledge to make rational decisions and act in this changing environment autonomously. Machine learning techniques for single-agent frameworks are well established. Agents operate in uncertain environments and must be able to learn and act - tonomously. This task is, however, more complex when the agent interacts with other agents that have potentially different capabilities and goals. The single-agent case is structurally different from the multi-agent case due to the added dimension of dynamic interactions between the adaptive agents. Multi-agent learning, i.e., the ability of the agents to learn how to cooperate and compete, becomes crucial in many domains. Autonomous agents and multi-agent systems (AAMAS) is an emerging multi-disciplinary area encompassing computer science, software engineering, biology, as well as cognitive and social sciences. A t- oretical framework, in which rationality of learning and interacting agents can be - derstood, is still under development in MASs, although there have been promising ?
Le raisonnement bayésien : Modélisation et inférence = Bayesian reasoning : Modeling and inference
Describes in detail the practice of the Bayesian statistical approach using many examples chosen for their educational interest. The first part gives the general principles of statistical modeling making it possible to supervise but also to come to the aid of the imagination of the apprentice modeler. By examining examples of increasing difficulty, the reader forges the keys to building their own model. The second part presents the most useful calculation algorithms for estimating the unknowns of the model. Each inference method is presented and illustrated by numerous application cases.
Le choix bayésien: Principes et pratique
Covers the so-called Bayesian approach to statistical inference and in particular its decision-making aspects. The bases of this axiomatics (choice of the a priori, optimal decisions, tests and regions of confidence) are discussed in detail, as well as more recent openings of Bayesian analysis such as the choice of models, the use of numerical methods. Stochastic approximation (MCMC), the theory of noninformative laws (Berger-Bernardo axioms) and the relation to the classical theory of admissibility. Each chapter is completed by an extensive series of exercises of increasing difficulty and by bibliographical notes on the themes addressed. This book can be used in a Master's program in Applied Mathematics, Biometrics, Econometrics or any other program that uses quantitative information processing techniques. It only requires a basic course in probability theory and mathematical statistics as a preliminary.
Law and the Semantic Web : Legal Ontologies, Methodologies, Legal Information Retrieval, and Applications
As part of this objective, ICT (information and communication technologies) services should become available for every citizen, and for all schools, homes and businesses. The book you have in front of you is about Semantic Web technology and law. Law is something omnipresent; all citizens — at some points in their lives — have to deal with it. In addition, law involves a large group of professionals, and is a mul- billion business world wide. Information technology is important because it that can improve citizens’ interaction with law, as well as improve legal professionals’ work environment. Legal professionals dedicate a significant amount of their time to finding, reading, analyzing and synthesizing information in order to take decisions, and prepare advice and trials, among other tasks. As part of the “Semantic-Based Knowledge and Content Systems” Strategic Objective, the European Commission is funding projects to construct technology to make the Semantic Web vision come true. 1 The articles in this book are related to two current foci of the Strategic Objective : • Knowledge acquisition and modelling, capturing knowledge from raw information and multimedia content in webs and other distributed repositories to turn poorly structured information into machi- processable knowledge.
Launching & Building a Brand For Dummies
In Launching & Building a Brand For Dummies, Amy Will—who launched her first business at just 24-years-old and has been the brains behind four strong and buzzworthy brands—covers everything from crafting a powerful brand identity and planning that all-important launch to being prepared to scale up as you begin to take off. She reveals crucial lessons from her personal experience in launching five companies, as well as detailing case studies from some of the strongest brands out there, accompanied by insights and advice from successful founders and branding experts.
Large-Scale Knowledge Resources. Construction and Application ; 3rd International Conference on Large-Scale Knowledge Resources, LKR 2008, Tokyo, Japan, March 3-5, 2008. Proceedings
At the start of the 21st century,we are now well on the way to wards aknowled- intensive society, in which knowledge plays ever more important roles. Thus, research interest should inevitably shift from information to knowledge, with the problems of building, organizing, maintaining and utilizing knowledge - coming centralissues in a wide varietyof felds. The 21stCentury COE program “Framework for Systematization and Application of Large-scale Knowledge - sources (COE-LKR)” conducted by the Tokyo Institute of Technology is one of several early attempts worldwide to address these important issues. Inspired by this project, LKR2008 aimed at bringing together diverse contributions in cognitive science, computer science, education and linguistics to explore design, construction, extension, maintenance, validation and application of knowledge.
Large-scale group decision-making : State-to-the-art clustering and consensus paths
The proposed consensus models focus on the treatment of non-cooperative behaviors in the consensus-reaching process and explores the influence of trust loss on the consensus-reaching process.The logic behind is as follows: firstly, a clustering algorithm is adopted to reduce the dimension of decision-makers, and then, based on the clusters’ opinions obtained, a consensus-reaching process is carried out to obtain a decision result acceptable to the majority of decision-makers.
Landscape Performance Modeling Using Rhino and Grasshopper
A guidebook for landscape architects to learn the fundamental practices and use of the computational software Rhino 3D and the plugin Grasshopper for parametric modeling, landscape inventory, and performative analysis. This process visually connects intangible and abstract information with physical and spatial relationships to signify the impact ecological, climate, and cultural factors have on landscape performance and decision making.
Landscape Analysis and Visualisation : Spatial Models for Natural Resource Management and Planning
This book presents a collection and synthesis of many of these perspectives — perhaps it could only be produced in a land urb- ised in the tiniest of pockets, and yet so daunting with respect to the way non-populated landscapes dwarf its cities. Many travel to Australia to its cities and never see the landscapes — but it is these that give the country its power and imagery. It is the landscapes that so impress on us the need to consider how our intervention, through activities ranging from resource exploitation and settled agriculture to climate change, poses one of the greatest crises facing the modern world. In this sense, Australia and its landscape provide a mirror through which we can glimpse the extent to which our intervention in the world threatens its very existence.
