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Formal Methods for Open Object-Based Distributed Systems
Author: Elie Najm
language: en
Publisher: Springer Science & Business Media
Release Date: 2003-11-10
This volume contains the proceedings of FMOODS 2003, the 6th IFIP WG 6. 1 International Conference on Formal Methods for Open Object-Based Distributed Systems. The conference was held in Paris, France on November 19–21, 2003. The event was the sixth meeting of this conference series, which is held roughly every year and a half, the earlier events having been held in Paris, Canterbury, Florence, Stanford, and Twente. ThegoaloftheFMOODSseriesofconferencesistobringtogetherresearchers whose work encompasses three important and related ?elds: – formal methods; – distributed systems; – object-based technology. Such a convergence is representative of recent advances in the ?eld of distributed systems,andprovideslinksbetweenseveralscienti?candtechnologicalcommu- ties, as represented by the conferences FORTE/PSTV, CONCUR, and ECOOP. The objective of FMOODS is to provide an integrated forum for the p- sentation of research in the above-mentioned ?elds, and the exchange of ideas and experiences in the topics concerned with the formal methods support for open object-based distributed systems. For the call for papers, aspects of int- est of the considered systems included, but were not limited to: formal models; formal techniques for speci?cation, design or analysis; component-based design; veri?cation, testing and validation; semantics of programming, coordination, or modeling languages; type systems for programming, coordination or modelling languages; behavioral typing; multiple viewpoint modelling and consistency - tween di?erent models; transformations of models; integration of quality of s- vice requirements into formal models; formal models for security; and appli- tions and experience, carefully described.
Risk and Hazard Management for Festivals and Events
Events of all types are produced every day for all manner of purposes, attracting all sorts of people. To provide a safe and secure setting in which people gather is imperative. Event risk and hazard management must be fully integrated into all event plans and throughout the event management process. Hazard management is the planning process required for the effective management of potential adverse incidents and areas of uncertainty. It involves intensive, detailed planning and cooperation to apply control systems to minimise hazards associated with venues, outdoor sites, work procedures, facilities, equipment and crowds of spectators. It involves planning for emergencies and security, and compliance with legal constraints and requirements. Risk and Hazard Management for Festivals and Events provides students with a comprehensive, fully integrated planning and management mechanism that can be applied to events of all types and size. The Event Safety Management System provides guidelines and processes for proactive methods to identify, assess and control hazardous conditions and practices. The system incorporates design of festival venues and sites, and unites the operational functions of crowd control, communications, security, terrorism prevention processes and emergency response protocols. Explanation of the causes of crowd disasters and studies into crowd behaviour are supported with international case studies. Written in an accessible, practical way, this book is essential reading for all events students and event managers.
Thinking With Data
The chapters in Thinking With Data are based on presentations given at the 33rd Carnegie Symposium on Cognition. The Symposium was motivated by the confluence of three emerging trends: (1) the increasing need for people to think effectively with data at work, at school, and in everyday life, (2) the expanding technologies available to support people as they think with data, and (3) the growing scientific interest in understanding how people think with data. What is thinking with data? It is the set of cognitive processes used to identify, integrate, and communicate the information present in complex numerical, categorical, and graphical data. This book offers a multidisciplinary presentation of recent research on the topic. Contributors represent a variety of disciplines: cognitive and developmental psychology; math, science, and statistics education; and decision science. The methods applied in various chapters similarly reflect a scientific diversity, including qualitative and quantitative analysis, experimentation and classroom observation, computational modeling, and neuroimaging. Throughout the book, research results are presented in a way that connects with both learning theory and instructional application. The book is organized in three sections: Part I focuses on the concepts of uncertainty and variation and on how people understand these ideas in a variety of contexts. Part II focuses on how people work with data to understand its structure and draw conclusions from data either in terms of formal statistical analyses or informal assessments of evidence. Part III focuses on how people learn from data and how they use data to make decisions in daily and professional life.