L¿any 1997 la Universidad de Oriente de Santiago de Cuba i la Universitat Jaume I establiren un conveni de col¿laboració amb l¿objectiu de promoure la docència i la investigació, com també la formació dels professors universitaris d¿ambdues universitats. Deu anys més tard, i després de l¿èxit de la col¿laboració, en aquest llibre es reuneixen alguns dels treballs d¿investigació desenvolupats pels alumnes participants en el programa de doctorat «Sistemes Informàtics Avançats».

This book discusses how model-based approaches can improve the daily practice of software professionals. This is known as Model-Driven Software Engineering (MDSE) or, simply, Model-Driven Engineering (MDE). MDSE practices have proved to increase efficiency and effectiveness in software development, as demonstrated by various quantitative and qualitative studies. MDSE adoption in the software industry is foreseen to grow exponentially in the near future, e.g., due to the convergence of software development and business analysis. The aim of this book is to provide you with an agile and flexible tool to introduce you to the MDSE world, thus allowing you to quickly understand its basic principles and techniques and to choose the right set of MDSE instruments for your needs so that you can start to benefit from MDSE right away. The book is organized into two main parts. The first part discusses the foundations of MDSE in terms of basic concepts (i.e., models and transformations), driving principles, application scenarios, and current standards, like the well-known MDA initiative proposed by OMG (Object Management Group) as well as the practices on how to integrate MDSE in existing development processes. The second part deals with the technical aspects of MDSE, spanning from the basics on when and how to build a domain-specific modeling language, to the description of Model-to-Text and Model-to-Model transformations, and the tools that support the management of MDSE projects. The second edition of the book features: a set of completely new topics, including: full example of the creation of a new modeling language (IFML), discussion of modeling issues and approaches in specific domains, like business process modeling, user interaction modeling, and enterprise architecture complete revision of examples, figures, and text, for improving readability, understandability, and coherence better formulation of definitions, dependencies between concepts and ideas addition of a complete index of book content In addition to the contents of the book, more resources are provided on the book's website http://www.mdse-book.com, including the examples presented in the book.

In the Guide to the Software Engineering Body of Knowledge (SWEBOK(R) Guide), the IEEE Computer Society establishes a baseline for the body of knowledge for the field of software engineering, and the work supports the Society's responsibility to promote the advancement of both theory and practice in this field. It should be noted that the Guide does not purport to define the body of knowledge but rather to serve as a compendium and guide to the knowledge that has been developing and evolving over the past four decades. Now in Version 3.0, the Guide's 15 knowledge areas summarize generally accepted topics and list references for detailed information. The editors for Version 3.0 of the SWEBOK(R) Guide are Pierre Bourque (Ecole de technologie superieure (ETS), Universite du Quebec) and Richard E. (Dick) Fairley (Software and Systems Engineering Associates (S2EA)).

The very rapid pace of advances in biomedical research promises us a wide range of new drugs, medical devices, and clinical procedures. The extent to which these discoveries will benefit the public, however, depends in large part on the methods we choose for developing and testing them. Modern Methods of Clinical Investigation focuses on strategies for clinical evaluation and their role in uncovering the actual benefits and risks of medical innovation. Essays explore differences in our current systems for evaluating drugs, medical devices, and clinical procedures; health insurance databases as a tool for assessing treatment outcomes; the role of the medical profession, the Food and Drug Administration, and industry in stimulating the use of evaluative methods; and more. This book will be of special interest to policymakers, regulators, executives in the medical industry, clinical researchers, and physicians.

Now with a new chapter that focuses on what great bosses really do. Dr. Sutton reveals new insights that he's learned since the writing of Good Boss, Bad Boss. Sutton adds revelatory thoughts about such legendary bosses as Ed Catmull, Steve Jobs, A.G. Lafley, and many more, and how you can implement their techniques. If you are a boss who wants to do great work, what can you do about it? Good Boss, Bad Boss is devoted to answering that question. Stanford Professor Robert Sutton weaves together the best psychological and management research with compelling stories and cases to reveal the mindset and moves of the best (and worst) bosses. This book was inspired by the deluge of emails, research, phone calls, and conversations that Dr. Sutton experienced after publishing his blockbuster bestseller The No Asshole Rule. He realized that most of these stories and studies swirled around a central figure in every workplace: THE BOSS. These heart-breaking, inspiring, and sometimes funny stories taught Sutton that most bosses - and their followers - wanted a lot more than just a jerk-free workplace. They aspired to become (or work for) an all-around great boss, somebody with the skill and grit to inspire superior work, commitment, and dignity among their charges. As Dr. Sutton digs into the nitty-gritty of what the best (and worst) bosses do, a theme runs throughout Good Boss, Bad Boss - which brings together the diverse lessons and is a hallmark of great bosses: They work doggedly to "stay in tune" with how their followers (and superiors, peers, and customers too) react to what they say and do. The best bosses are acutely aware that their success depends on having the self-awareness to control their moods and moves, to accurately interpret their impact on others, and to make adjustments on the fly that continuously spark effort, dignity, and pride among their people.

Collection of 48 science fiction stories by Isaac Asimov.

This book addresses two significant research areas in an interdependent fashion. It is first of all a comprehensive but concise text that covers the recently developed and widely applicable methods of qualitative choice analysis, illustrating the general theory through simulation models of automobile demand and use. It is also a detailed study of automobile demand and use, presenting forecasts based on these powerful new techniques. The book develops the general principles that underlie qualitative choice models that are now being applied in numerous fields in addition to transportation, such as housing, labor, energy, communications, and criminology. The general form, derivation, and estimation of qualitative choice models are explained, and the major models - logit, probit, and GEV - are discussed in detail. And continuous/discrete models are introduced. In these, qualitative choice methods and standard regression techniques are combined to analyze situations that neither alone can accurately forecast. Summarizing previous research on auto demand, the book shows how qualitative choice methods can be used by applying them to specific auto-related decisions as the aggregate of individuals' choices. The simulation model that is constructed is a significant improvement over older models, and should prove more useful to agencies and organizations requiring accurate forecasting of auto demand and use for planning and policy development. The book concludes with an actual case study based on a model designed for the investigations of the California Energy Commission. Kenneth Train is Visiting Associate Professor in Economics at the University of California, Berkeley, and Director of Economic Research at Cambridge Systematics, Inc., also in Berkeley. Qualitative Choice Analysisis included in The MIT Press Transportation Studies Series, edited by Marvin L. Manheim.