Model-based approaches have proven fruitful in the design and implementation of intelligent systems that provide automated diagnostic functions. A wide variety of models are used in these approaches to represent the p...
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ISBN:
(纸本)1563478935
Model-based approaches have proven fruitful in the design and implementation of intelligent systems that provide automated diagnostic functions. A wide variety of models are used in these approaches to represent the particular domain knowledge, including analytic state-based models, input-output transfer function models, fault propagation models, and qualitative and quantitative physics-based models. Diagnostic applications are built around three main steps: observation, comparison, and diagnosis. If the modeling begins in the early stages of system development, engineering models such as fault propagation models can be used for testability analysis to aid definition and evaluation of instrumentation suites for observation of system behavior. Analytical models can be used in the design of monitoring algorithms that process observations to provide information for the second step in the process, comparison of expected behavior of the system to actual measured behavior. In the final diagnostic step, reasoning about the results of the comparison can be performed in a variety of ways, such as dependency matrices, graph propagation, constraint propagation, and state estimation. Realistic empirical evaluation and comparison of these approaches is often hampered by a lack of standard data sets and suitable testbeds. In this paper we describe the Advanced Diagnostics and Prognostics Testbed (ADAPT) at NASA Ames Research center. The purpose of the testbed is to measure, evaluate, and mature diagnostic and prognostic health management technologies. This paper describes the testbed's hardware, software architecture, and concept of operations. A simulation testbed that accompanies ADAPT, and some of the diagnostic and decision support approaches being investigated are also discussed.
This paper provides an overview of the research in railway scheduling and dispatching. A distinction is made between tactical scheduling, operational scheduling and re-scheduling. Tactical scheduling refers to master ...
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ISBN:
(纸本)9783939897002
This paper provides an overview of the research in railway scheduling and dispatching. A distinction is made between tactical scheduling, operational scheduling and re-scheduling. Tactical scheduling refers to master scheduling, whereas operational scheduling concerns scheduling at a later stage. Re-scheduling focuses on the re-planning of an existing timetable when deviations from it have occurred. 48 approaches published between 1973 and 2005 have been reviewed according to a framework that classifies them with respect to problem type, solution mechanism, and type of evaluation. 26 of the approaches support the representation of a railway network rather than a railway line, but the majority has been experimentally evaluated for traffic on a line. 94 % of the approaches have been subject to some kind of experimental evaluation, while approximately 4 % have been implemented. The solutions proposed vary from myopic, priority-based algorithms, to traditional operations research techniques and the application of agent technology.
This talk provides a personal perspective on the evolution of empirical softwareengineering. The evolution has included the focus of the studies, e.g., from attempting to demonstrate the effectiveness of various proc...
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ISBN:
(纸本)1595932186
This talk provides a personal perspective on the evolution of empirical softwareengineering. The evolution has included the focus of the studies, e.g., from attempting to demonstrate the effectiveness of various processes to the building of knowledge around a domain or a set of processes. The study designs have changed from strictly quantitative studies to all forms of controlled experiments, quasi-experiments, preexperimental designs, case studies, field studies, and focus group activities. There has been recognition of the importance and influence of context variables and the domain in interpreting the results of studies. The issue of meta-analysis has become more important and is still an elusive goal. A community of empiricists has evolved that allows for the replication of studies leading to the identification of context variables. But there still does not exist a community consensus on the right ways to build bodies of knowledge or a "blessed" set of approaches. We argue over what is appropriate evidence when we review papers. We struggle with the concept of experimental replication. We do not know how to break an empirical study into significant small enough chunks for publication in the various standard forums. We have not convinced the softwareengineering community that empirical study is a necessary or even valuable research paradigm for the field. What other problems that remain? How can they be solved? What will the future hold for empirical study? This talk will address these issues and propose a possible path towards a mature empirical softwareengineering discipline.
Identifying misbehaviors is an important challenge for monitoring, fault diagnosis and intrusion detection in wireless sensor networks. A key problem is how to minimise the communication overhead and energy consumptio...
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The benefits offered by the use of formal methods are not limited to avoidance of specification errors and elimination of ambiguities only - a formal specification also provides a sound basis for generating test suite...
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In advance reservation environment, failure discovery strategy is very important to keep the normal running of whole system. One job's overtime (exceeding its booked time) may lead to a serious of jobs' abnorm...
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This paper presents a new topological localization system for mobile robot navigation based on salient visual regions. These salient regions are obtained by computing the opponencies of color and texture among multi-s...
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