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Applied Ergonomics
Applied Ergonomics is a concise text focusing on the practical applications of ergonomics and is derived from the annual, ground-breaking, successful conference of the same name. This is not a conference proceedings but a text of applications, filling a niche in the ergonomics professional market for a book that is strong on the applications side o
Cognitive Reliability and Error Analysis Method (CREAM)
The growing dependence of working environments on complex technology has created many challenges and lead to a large number of accidents. Although the quality of organization and management within the work environment plays an important role in these accidents, the significance of individual human action (as a direct cause and as a mitigating factor) is undeniable. This has created a need for new, integrated approaches to accident analysis and risk assessment.This book detailing the use of CREAM is, therefore, both timely and useful. It presents an error taxonomy which integrates individual, technological and organizational factors based on cognitive engineering principles. In addition to the necessary theoretical foundation, it provides a step-by-step description of how the taxonomy can be applied to analyse as well as predict performance using a context-dependent cognitive model.CREAM can be used as a second-generation human reliability analysis (HRA) approach in probabilistic safety assessment (PSA), as a stand-alone method for accident analysis and as part of a larger design method for interactive systems. In particular, the use of CREAM will enable system designers and risk analysts to: • identify tasks that require human cognition and therefore depend on cognitive reliability• determine the conditions where cognitive reliability and ensuing risk may be reduced• provide an appraisal of the consequences of human performance on system safety which can be used in PSA.
Distributed Algorithms
A comprehensive guide to distributed algorithms that emphasizes examples and exercises rather than mathematical argumentation. This book offers students and researchers a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models. It avoids mathematical argumentation, often a stumbling block for students, teaching algorithmic thought rather than proofs and logic. This approach allows the student to learn a large number of algorithms within a relatively short span of time. Algorithms are explained through brief, informal descriptions, illuminating examples, and practical exercises. The examples and exercises allow readers to understand algorithms intuitively and from different perspectives. Proof sketches, arguing the correctness of an algorithm or explaining the idea behind fundamental results, are also included. An appendix offers pseudocode descriptions of many algorithms. Distributed algorithms are performed by a collection of computers that send messages to each other or by multiple software threads that use the same shared memory. The algorithms presented in the book are for the most part “classics,” selected because they shed light on the algorithmic design of distributed systems or on key issues in distributed computing and concurrent programming. Distributed Algorithms can be used in courses for upper-level undergraduates or graduate students in computer science, or as a reference for researchers in the field.