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Model-Driven Testing: Using the UML Testing Profile
by Paul Baker Zhen Ru Dai Jens Grabowski Ina Schieferdecker Clay WilliamsWritten by the original members of an industry standardization group, this book shows you how to use UML to test complex software systems. It is the definitive reference for the only UML-based test specification language, written by the creators of that language. It is supported by an Internet site that provides information on the latest tools and uses of the profile. The authors introduce UTP step-by-step, using a case study that illustrates how UTP can be used for test modeling and test specification.
A Model for Islamic Development: An Approach in Islamic Moral Economy (Studies in Islamic Finance, Accounting and Governance series)
by Shafiullah Jan Mehmet AsutayThis book explores and analyses economic development within Islamic Moral Economy (IME), which is proposed as an alternative economic and social system to capitalism and socialism. It presents a new model of Islamic development based on the substantive morality of Islam via micro dynamics expressed through an Islamic framework of spiritual development. Shafiullah Jan and Mehmet Asutay argue that the observed development failures of Muslim countries to provide basic necessities and an environment free of oppression and injustice can be overcome with an authentic Islamic development framework and its corresponding value system explored in the book, rather than the existing Eurocentric theory and policy making. In addition, it identifies the theological, political, social and economic boundaries for changing society to produce IME oriented development. Utilising a novel approach to development in Islam, through its substantive ethical and moral framework, the authors critically examine and evaluate the progress of Islamic banking and finance institutions in relation to its aspirations as identified by IME. Advanced Islamic economics and finance scholars will find this a useful source as it explores the intersection between Islamic development and the moral economy. The book will also be a valuable reference for those seeking to align public policies with ethical and moral Islamic frameworks.
Model-Free Prediction and Regression: A Transformation-Based Approach to Inference (Frontiers in Probability and the Statistical Sciences)
by Dimitris N. PolitisThe Model-Free Prediction Principle expounded upon in this monograph is based on the simple notion of transforming a complex dataset to one that is easier to work with, e.g., i.i.d. or Gaussian. As such, it restores the emphasis on observable quantities, i.e., current and future data, as opposed to unobservable model parameters and estimates thereof, and yields optimal predictors in diverse settings such as regression and time series. Furthermore, the Model-Free Bootstrap takes us beyond point prediction in order to construct frequentist prediction intervals without resort to unrealistic assumptions such as normality.Prediction has been traditionally approached via a model-based paradigm, i.e., (a) fit a model to the data at hand, and (b) use the fitted model to extrapolate/predict future data. Due to both mathematical and computational constraints, 20th century statistical practice focused mostly on parametric models. Fortunately, with the advent of widely accessible powerful computing in the late 1970s, computer-intensive methods such as the bootstrap and cross-validation freed practitioners from the limitations of parametric models, and paved the way towards the `big data' era of the 21st century. Nonetheless, there is a further step one may take, i.e., going beyond even nonparametric models; this is where the Model-Free Prediction Principle is useful.Interestingly, being able to predict a response variable Y associated with a regressor variable X taking on any possible value seems to inadvertently also achieve the main goal of modeling, i.e., trying to describe how Y depends on X. Hence, as prediction can be treated as a by-product of model-fitting, key estimation problems can be addressed as a by-product of being able to perform prediction. In other words, a practitioner can use Model-Free Prediction ideas in order to additionally obtain point estimates and confidence intervals for relevant parameters leading to an alternative, transformation-based approach to statistical inference.
Model Income Tax Treaties
by Kees van RaadIn this booklet a comparative survey is offered offour model income tax conventions: the OECD drafts of 1963 and 1977, the United Nations Model of 1980 and the proposed United States Treasury's model of 1981. In order to facilitate the compari son, the text of the 1977 OECD draft is used as reference. Additions and alternatives in any of the other models to this 1977 OECD text are italicized. Omissions from the 1977 OECD model in the other drafts are indicated either by a blank space (where an entire paragraph has been suppressed) or by brackets [] ( in case of smaller omissions). The Hague, May 1983 Kees van Raad OECD 1963 OECD 1977 OECD DRAFT DOUBLE TAXA OECD MODEL DOUBLE TAXA TION CONVENTION ON INCOME TION CONVENTION ON INCOME AND CAPITAL AND CAPITAL 1963 1977 TITLE[] TITLE OF THE CONVENTION Convention between (State A) and (State Convention between (State A) and (State B) for the avoidance of double taxation B) for the avoidance of double taxation with respect to taxes on income and on with respect to taxes on income and m capital capital 1 PREAMBLE OF THE CONVENTION CHAPTER I CHAPTER I SCOPE OF THE CONVENTION SCOPE OF THE CONVENTION Article 1 Article 1 PERSONAL SCOPE PERSONAL SCOPE This Convention shall apply to persons This Convention shall apply to persons who are residents of one or both of the who are residents of one or both of the Contracting States. Contracting States.
The Model Law Approach to International Commercial Arbitration: A Primer
by Mark CampbellTaking the UNCITRAL Model Law on International Commercial Arbitration as its basis, this concise and accessible book presents a cutting-edge account of the international arbitral process. Applying a chronological approach, the book will enable readers to gain an understanding of the arbitral process from start to finish.Chapters explore key topics including the general structure of international commercial arbitration, the Model Law, arbitration agreements, the arbitral tribunal, the conduct of arbitral proceedings, and challenges to and enforcement of arbitral awards. The book also highlights key underlying principles in international arbitration such as party autonomy, the finality of awards and the need to limit court intervention. It also examines the harmonising aim of the Model Law, demonstrating how it acts as a blueprint for legislation on international commercial arbitration, and ties in relevant case law to give a holistic picture of international commercial arbitration in action.This book will prove indispensable to academics and students of international commercial law, arbitration and dispute resolution, who are seeking clarity on the legal framework governing the arbitral process. Legal practitioners will similarly benefit from this clear and concise guide to the application of the Model Law.
Model Management and Analytics for Large Scale Systems
by Bedir Tekinerdogan Önder Babur Loek Cleophas Mark Van Den Brand Mehmet AksitModel Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management.Identifies key problems and offers solution approaches and tools that have been developed or are necessary for model management and analyticsExplores basic theory and background, current research topics, related challenges and the research directions for model management and analyticsProvides a complete overview of model management and analytics frameworks, the different types of analytics (descriptive, diagnostics, predictive and prescriptive), the required modelling and method steps, and important future directions
A model of Austrian economics
by Hendrik HagedornAfter the most recent financial crisis it has become clear that there exists a crisis also in economics as a science. The prevailing paradigms have failed to anticipate and to understand the financial crisis. New approaches are therefore needed. Of particular interest should be approaches that combine insights from those parts of economics that are largely neglected by the mainstream. Hendrik Hagedorn presents a model that synthesizes elements of Austrian, post-Keynesian, and evolutionary economics. Thus, an economic paradigm is developed that challenges neoclassical economics as a whole.
Model Policies and Procedures for Not-for-Profit Organizations
by Edward J. McMillanWhat every not-for-profit must know about accounting, tax, and reporting requirements In the challenging world of not-for-profit management, executives are held responsible for virtually every aspect of their organization's activities, such as legal issues, marketing, lobbying, editorial, membership operations, budgeting, and, of course, finance. For one person to be an authority in every area, however, is virtually impossible. Completely revised and expanded, the Fourth Edition of this invaluable tool is useful as a guide to nonprofit accountants, financial managers, and executives new to the area of financial management. Addressing the accounting, internal control, and office administration issues that confront executives in nonprofit organizations, this book: * Helps professionals develop formal policies in accounting and finance * Shows how to strengthen an organization's financial procedures while assuring board members that they are meeting fiduciary responsibilities * Provides more than 200 sample policies and forms both in the book and on the accompanying Web site offering downloadable and customizable versions of those forms * Covers major topics including accounting and financial policies, office administration policies, and internal control and risk reduction policies * Contains dozens of new model accounting and financial policies and forms, covering Sarbanes-Oxley issues, codes of ethics, identity theft, fraud, binding arbitrations, compensation committees, new bank rules, fiduciary obligations of board members, and many more topics Model Policies and Procedures for Not-for-Profit Organizations, Fourth Edition offers provocative strategies for financial management and serves as a road map to sound fiscal and organizational structure for nonprofit organizations.
Model Policies and Procedures for Not-for-Profit Organizations
by Edward J. McMillanThe completely revised and expanded third edition of Model Accounting and Financial Policies Procedures Handbook will help nonprofit executives strengthen their organization's financial procedures while assuring board members that they are meeting fiduciary responsibilities. This process is streamlined by the more than 150 sample policies and forms included both in this book and on the accompanying web site (offering dowloadable and customizable versions of those forms). Major topics include internal financial statement forms, a chart of accounts, and accounting and financial policies and procedures manual, a glossary, and a full index.
Model Reduction Methods for Vector Autoregressive Processes (Lecture Notes in Economics and Mathematical Systems #536)
by Ralf Brüggemann1. 1 Objective of the Study Vector autoregressive (VAR) models have become one of the dominant research tools in the analysis of macroeconomic time series during the last two decades. The great success of this modeling class started with Sims' (1980) critique of the traditional simultaneous equation models (SEM). Sims criticized the use of 'too many incredible restrictions' based on 'supposed a priori knowledge' in large scale macroeconometric models which were popular at that time. Therefore, he advo cated largely unrestricted reduced form multivariate time series models, unrestricted VAR models in particular. Ever since his influential paper these models have been employed extensively to characterize the underlying dynamics in systems of time series. In particular, tools to summarize the dynamic interaction between the system variables, such as impulse response analysis or forecast error variance decompo sitions, have been developed over the years. The econometrics of VAR models and related quantities is now well established and has found its way into various textbooks including inter alia Llitkepohl (1991), Hamilton (1994), Enders (1995), Hendry (1995) and Greene (2002). The unrestricted VAR model provides a general and very flexible framework that proved to be useful to summarize the data characteristics of economic time series. Unfortunately, the flexibility of these models causes severe problems: In an unrestricted VAR model, each variable is expressed as a linear function of lagged values of itself and all other variables in the system.
The Model Thinker: What You Need to Know to Make Data Work for You
by Scott E. PageHow anyone can become a data ninja From the stock market to genomics laboratories, census figures to marketing email blasts, we are awash with data. But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models--from linear regression to random walks and far beyond--that can turn anyone into a genius. At the core of the book is Page's "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.
The Model Thinker: What You Need to Know to Make Data Work for You
by Scott E. PageWork with data like a pro using this guide that breaks down how to organize, apply, and most importantly, understand what you are analyzing in order to become a true data ninja.From the stock market to genomics laboratories, census figures to marketing email blasts, we are awash with data. But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models—from linear regression to random walks and far beyond—that can turn anyone into a genius. At the core of the book is Page's "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.
A Model to Forecast Future Paradigms: Volume 1: Introduction to Knowledge Is Power in Four Dimensions
by Bahman Zohuri Farhang Mossavar-RahmaniIn this volume, the authors’ two-fold objective is to lay out a methodology and approach that allows the reader to learn how to utilize existing technology in the form of computer software and hardware for forecasting and decision-making and to discuss factors that affect upcoming events that, in turn, shape future paradigms. With the sheer volume of information available and the ever-greater ease of access, it is becoming increasingly difficult to introduce an appropriate methodology of decision-making that is fast enough to be effective. The demand for real-time information processing and related data—both structured and unstructured—is on the rise. This rise makes it challenging to implement correct decision-making within enterprises at a level that keeps organizations robust and resilient against natural and man-made disasters. This volume provides an understanding of these factors and will help decision-makers be better prepared to face future challenges and will assist them in coping with unexpected circumstances. This volume is divided into two parts. Part one discusses a "technological infrastructure" so that readers can gain a greater understanding based on the knowledge of tomorrow’s computing functionality. The second part goes on to discuss the key indicators in the areas of population, culture, economics, climate change, and the impacts of technology in commerce and socially—which all need to be considered when forecasting a future paradigm. The authors will follow this introductory volume with additional volumes that review and analyse other critical indicators in the areas of geopolitics, the nature of political power around the globe, and other applications of technology and energy.
A Model to Forecast Future Paradigms: Volume 1: Introduction to Knowledge Is Power in Four Dimensions
by Bahman Zohuri Farhang Mossavar-RahmaniIn this volume, the authors’ two-fold objective is to lay out a methodology and approach that allows the reader to learn how to utilize existing technology in the form of computer software and hardware for forecasting and decision-making and to discuss factors that affect upcoming events that, in turn, shape future paradigms. With the sheer volume of information available and the ever-greater ease of access, it is becoming increasingly difficult to introduce an appropriate methodology of decision-making that is fast enough to be effective. The demand for real-time information processing and related data—both structured and unstructured—is on the rise. This rise makes it challenging to implement correct decision-making within enterprises at a level that keeps organizations robust and resilient against natural and man-made disasters. This volume provides an understanding of these factors and will help decision-makers be better prepared to face future challenges and will assist them in coping with unexpected circumstances. This volume is divided into two parts. Part one discusses a "technological infrastructure" so that readers can gain a greater understanding based on the knowledge of tomorrow’s computing functionality. The second part goes on to discuss the key indicators in the areas of population, culture, economics, climate change, and the impacts of technology in commerce and socially—which all need to be considered when forecasting a future paradigm. The authors will follow this introductory volume with additional volumes that review and analyse other critical indicators in the areas of geopolitics, the nature of political power around the globe, and other applications of technology and energy.
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics 2022 (Conference Proceedings of the Society for Experimental Mechanics Series)
by Zhu MaoModel Validation and Uncertainty Quantification, Volume 3: Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022, the third volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on:Uncertainty Quantification and Propagation in Structural DynamicsBayesian Analysis for Real-Time Monitoring and MaintenanceUncertainty in Early Stage DesignQuantification of Model-Form UncertaintiesFusion of Test and AnalysisMVUQ in Action
Modeling a New Computer Framework for Managing Healthcare Organizations: Balancing and Optimizing Patient Satisfaction, Owner Satisfaction, and Medical Resources
by Soraia OueidaThe medical sector has been growing exponentially over the last decade and healthcare services are becoming more complex and costly. In order to continue efficiently and effectively managing patient safety, quality, and the effectiveness of the healthcare systems, new methodologies are needed. This book provides a platform to address this growing need and to improve practice. With the introduction of a new computer platform package for the management of medical organizations and healthcare systems, Modeling a New Computer Framework for Managing Healthcare Organizations aims to improve management techniques and increase overall satisfaction scores of patients, owners, and medical resources. The platform outlined will improve the daily operation of a healthcare system, focusing on the emergency department, and can be used to study the operation flow of a unit for performance optimization. It offers a user-friendly interface and proposed programming language, along with a visual and simple practice to collect and understand statistical outputs. Essential reading for decision makers on different levels in the healthcare organization hierarchy, this book can also be used by management to improve the performance of the organization and decision makers to hire resources, enhance workflows or both. It guides designers and system implementers in a step-by-step approach to make optimal decisions for resource allocation and helps designers and management to detect deficiencies in ongoing processes and fix or enhance them.
Modeling a New Computer Framework for Managing Healthcare Organizations: Balancing and Optimizing Patient Satisfaction, Owner Satisfaction, and Medical Resources
by Soraia OueidaThe medical sector has been growing exponentially over the last decade and healthcare services are becoming more complex and costly. In order to continue efficiently and effectively managing patient safety, quality, and the effectiveness of the healthcare systems, new methodologies are needed. This book provides a platform to address this growing need and to improve practice. With the introduction of a new computer platform package for the management of medical organizations and healthcare systems, Modeling a New Computer Framework for Managing Healthcare Organizations aims to improve management techniques and increase overall satisfaction scores of patients, owners, and medical resources. The platform outlined will improve the daily operation of a healthcare system, focusing on the emergency department, and can be used to study the operation flow of a unit for performance optimization. It offers a user-friendly interface and proposed programming language, along with a visual and simple practice to collect and understand statistical outputs. Essential reading for decision makers on different levels in the healthcare organization hierarchy, this book can also be used by management to improve the performance of the organization and decision makers to hire resources, enhance workflows or both. It guides designers and system implementers in a step-by-step approach to make optimal decisions for resource allocation and helps designers and management to detect deficiencies in ongoing processes and fix or enhance them.
Modeling, Analysis, Design, and Control of Stochastic Systems (Springer Texts in Statistics)
by V. G. KulkarniAn introductory level text on stochastic modelling, suited for undergraduates or graduates in actuarial science, business management, computer science, engineering, operations research, public policy, statistics, and mathematics. It employs a large number of examples to show how to build stochastic models of physical systems, analyse these models to predict their performance, and use the analysis to design and control them. The book provides a self-contained review of the relevant topics in probability theory: In discrete and continuous time Markov models it covers the transient and long term behaviour, cost models, and first passage times; under generalised Markov models, it covers renewal processes, cumulative processes and semi-Markov processes. All the material is illustrated with many examples, and the book emphasises numerical answers to the problems. A software package called MAXIM, which runs on MATLAB, is available for downloading.
Modeling and Analysis of Enterprise and Information Systems: From Requirements to Realization
by Qing Li Yuliu ChenModeling and Analysis of Enterprise and Information Systems – From Requirements to Realization discusses the basic principles of enterprise architecture and enterprise modeling. After an introduction to the field the General Enterprise Modeling Architecture is presented. The new architecture includes a set of models and methods. It describes different aspects of the system and covers its life cycle. Its models are structuralized models with multi-layers and multi-views. They are descriptions and cognitions of the system at the top level and provide tools and methodology to understand, design, develop and implement the system. This book is intended for researchers and graduate students in the field of industrial engineering, management engineering and information engineering. Enterprise Models discussed in this book provide a rich source in enterprise diagnosis, business process reengineering and information system implementation. Dr. Qing Li and Prof. Yu-Liu Chen both teach at the Department of Automation, Tsinghua University.
Modeling and Analysis of Real-Time and Embedded Systems with UML and MARTE: Developing Cyber-Physical Systems (The MK/OMG Press)
by Bran Selic Sebastien GerardModeling and Analysis of Real-Time and Embedded Systems with UML and MARTE explains how to apply the complex MARTE standard in practical situations. This approachable reference provides a handy user guide, illustrating with numerous examples how you can use MARTE to design and develop real-time and embedded systems and software. Expert co-authors Bran Selic and Sébastien Gérard lead the team that drafted and maintain the standard and give you the tools you need apply MARTE to overcome the limitations of cyber-physical systems. The functional sophistication required of modern cyber-physical systems has reached a point where traditional code-centric development methods are proving less and less capable of delivering a reliable product in a timely manner. In Modeling and Analysis of Real-Time and Embedded Systems with UML and MARTE, you will learn how to take advantage of modern model-based engineering methods and corresponding industry standards to overcome these limitations. These methods take full advantage of computer-supported automation allowing timely detection of design flaws to reduce engineering risk, leading thereby to better overall product quality and greater productivity.Understand the design rationale behind the MARTE standard needed to take full advantage of its many powerful modeling capabilities Best apply the various MARTE features for the most common use cases encountered in the design of real-time and embedded softwareLearn how MARTE can be used together with the SysML language for the design of complex cyber-physical systemsDiscover how MARTE can be used for different kinds of computer-supported engineering analyses to predict key system characteristics early in development Customize MARTE for a specific domain or project
Modeling and Analysis of Stochastic Systems (Chapman & Hall/CRC Texts in Statistical Science)
by Vidyadhar G. KulkarniBuilding on the author’s more than 35 years of teaching experience, Modeling and Analysis of Stochastic Systems, Third Edition, covers the most important classes of stochastic processes used in the modeling of diverse systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. The third edition has been updated with several new applications, including the Google search algorithm in discrete time Markov chains, several examples from health care and finance in continuous time Markov chains, and square root staffing rule in Queuing models. More than 50 new exercises have been added to enhance its use as a course text or for self-study. The sequence of chapters and exercises has been maintained between editions, to enable those now teaching from the second edition to use the third edition. Rather than offer special tricks that work in specific problems, this book provides thorough coverage of general tools that enable the solution and analysis of stochastic models. After mastering the material in the text, readers will be well-equipped to build and analyze useful stochastic models for real-life situations.
Modeling and Analysis of Stochastic Systems (Chapman & Hall/CRC Texts in Statistical Science)
by Vidyadhar G. KulkarniBuilding on the author’s more than 35 years of teaching experience, Modeling and Analysis of Stochastic Systems, Third Edition, covers the most important classes of stochastic processes used in the modeling of diverse systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. The third edition has been updated with several new applications, including the Google search algorithm in discrete time Markov chains, several examples from health care and finance in continuous time Markov chains, and square root staffing rule in Queuing models. More than 50 new exercises have been added to enhance its use as a course text or for self-study. The sequence of chapters and exercises has been maintained between editions, to enable those now teaching from the second edition to use the third edition. Rather than offer special tricks that work in specific problems, this book provides thorough coverage of general tools that enable the solution and analysis of stochastic models. After mastering the material in the text, readers will be well-equipped to build and analyze useful stochastic models for real-life situations.
Modeling and Benchmarking Supply Chain Leadership: Setting the Conditions for Excellence
by Joseph L WaldenWhat is motivational dysfunction? You have seen it, you may even have experienced it, and you have certainly felt the effects of this dysfunction in your workplace. Often undiagnosed, employees suffering from motivational dysfunction have lowered motivation caused by a lack of excitement for their job. This serious issue can cost companies billions
Modeling and Control of Discrete-event Dynamic Systems: with Petri Nets and Other Tools (Advanced Textbooks in Control and Signal Processing)
by Branislav Hrúz MengChu ZhouDiscrete-event dynamic systems (DEDs) permeate our world. They are of great importance in modern manufacturing processes, transportation and various forms of computer and communications networking. This book begins with the mathematical basics required for the study of DEDs and moves on to present various tools used in their modeling and control. Industrial examples illustrate the concepts and methods discussed, making this book an invaluable aid for students embarking on further courses in control, manufacturing engineering or computer studies.
Modeling and Control of Logical Discrete Event Systems (The Springer International Series in Engineering and Computer Science #300)
by Ratnesh Kumar Vijay K. GargThe field of discrete event systems has emerged to provide a formal treatment of many of the man-made systems such as manufacturing systems, communica tion networks. automated traffic systems, database management systems, and computer systems that are event-driven, highly complex, and not amenable to the classical treatments based on differential or difference equations. Discrete event systems is a growing field that utilizes many interesting mathematical models and techniques. In this book we focus on a high level treatment of discrete event systems. where the order of events. rather than their occurrence times, is the principal concern. Such treatment is needed to guarantee that the system under study meets desired logical goals. In this framework, dis crete event systems are modeled by formal languages or, equivalently, by state machines. The field of logical discrete event systems is an interdisciplinary field-it in cludes ideas from computer science, control theory, and operations research. Our goal is to bring together in one book the relevant techniques from these fields. This is the first book of this kind, and our hope is that it will be useful to professionals in the area of discrete event systems since most of the material presented has appeared previously only in journals. The book is also designed for a graduate level course on logical discrete event systems. It contains all the necessary background material in formal language theory and lattice the ory. The only prerequisite is some degree of "mathematical maturity".