21 research outputs found
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Classification of time series patterns from complex dynamic systems
An increasing availability of high-performance computing and data storage media at decreasing cost is making possible the proliferation of large-scale numerical databases and data warehouses. Numeric warehousing enterprises on the order of hundreds of gigabytes to terabytes are a reality in many fields such as finance, retail sales, process systems monitoring, biomedical monitoring, surveillance and transportation. Large-scale databases are becoming more accessible to larger user communities through the internet, web-based applications and database connectivity. Consequently, most researchers now have access to a variety of massive datasets. This trend will probably only continue to grow over the next several years. Unfortunately, the availability of integrated tools to explore, analyze and understand the data warehoused in these archives is lagging far behind the ability to gain access to the same data. In particular, locating and identifying patterns of interest in numerical time series data is an increasingly important problem for which there are few available techniques. Temporal pattern recognition poses many interesting problems in classification, segmentation, prediction, diagnosis and anomaly detection. This research focuses on the problem of classification or characterization of numerical time series data. Highway vehicles and their drivers are examples of complex dynamic systems (CDS) which are being used by transportation agencies for field testing to generate large-scale time series datasets. Tools for effective analysis of numerical time series in databases generated by highway vehicle systems are not yet available, or have not been adapted to the target problem domain. However, analysis tools from similar domains may be adapted to the problem of classification of numerical time series data
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Spallation Neutron Source Availability Top-Down Apportionment Using Characteristic Factors and Expert Opinion
Apportionment is the assignment of top-level requirements to lower tier elements of the overall facility. A method for apportioning overall facility availability requirements among systems and subsystems is presented. Characteristics that influence equipment reliability and maintainability are discussed. Experts, using engineering judgment, scored each characteristic for each system whose availability design goal is to be established. The Analytic Hierarchy Process (AHP) method is used to produce a set of weighted rankings for each characteristic for each alternative system. A mathematical model is derived which incorporates these weighting factors. The method imposes higher availability requirements on those systems in which an incremental increase in availability is easier to achieve, and lower availability requirements where greater availability is more difficult and costly. An example is given of applying this top-down apportionment methodology to the Spallation Neutron Source (SNS) facility
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Simulation analysis of control strategies for a tank waste retrieval manipulator system
A network simulation model was developed for the Tank Waste Retrieval Manipulator System, incorporating two distinct levels of control: teleoperation and supervisory control. The model included six error modes, an attentional resource model, and a battery of timing variables. A survey questionnaire administered to subject matter experts provided data for estimating timing distributions for level of control-critical tasks. Simulation studies were performed to evaluate system behavior as a function of control level and error modes. The results provide important insights for development of waste retrieval manipulators
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Establishing Availability Requirements Using Characteristics Factors and Expert Opinion
System design engineers must translate permitted overall facility downtime into detailed design and operating specifications for numerous systems and subsystems that make up the facility. The process of assigning reliability and maintainability requirements to individual equipment systems to attain a desired overall availability is known as availability apportionment. Apportionment is normally required early in conceptual design when little or no hardware information is available. Apportionment, when coupled with availability prediction, enables the selection of viable alternative configurations, identifies problem areas, and provides redirection of the program into more productive areas as necessary. A method for apportioning, or budgeting, overall facility availability requirements among systems and subsystems is presented. An example of applying this methodology to the Spallation Neutron Source (SNS) facility is given
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Models of human operators: Their need and usefulness for improvement of advanced control systems and control rooms
Models of human behavior and cognition (HB C) are necessary for understanding the total response of complex systems. Many such model have come available over the past thirty years for various applications. Many potential model users remain skeptical about their practically, acceptability, and usefulness. Such hesitancy stems in part from disbelief in the ability to model complex cognitive processes, and a belief that relevant human behavior can be adequately accounted for through the use of common-sense heuristics. This paper will highlight several models of HB C and identify existing and potential applications in attempt to dispel such notions. 26 refs
Eén zwaluw maakt nog geen zomer: Methodologische uitdagingen bij onderzoek naar cultuurverandering
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Incorporation of RAM techniques into simulation modeling
This work concludes that reliability, availability, and maintainability (RAM) analytical techniques can be incorporated into computer network simulation modeling to yield an important new analytical tool. This paper describes the incorporation of failure and repair information into network simulation to build a stochastic computer model represents the RAM Performance of two vehicles being developed for the US Army: The Advanced Field Artillery System (AFAS) and the Future Armored Resupply Vehicle (FARV). The AFAS is the US Army`s next generation self-propelled cannon artillery system. The FARV is a resupply vehicle for the AFAS. Both vehicles utilize automation technologies to improve the operational performance of the vehicles and reduce manpower. The network simulation model used in this work is task based. The model programmed in this application requirements a typical battle mission and the failures and repairs that occur during that battle. Each task that the FARV performs--upload, travel to the AFAS, refuel, perform tactical/survivability moves, return to logistic resupply, etc.--is modeled. Such a model reproduces a model reproduces operational phenomena (e.g., failures and repairs) that are likely to occur in actual performance. Simulation tasks are modeled as discrete chronological steps; after the completion of each task decisions are programmed that determine the next path to be followed. The result is a complex logic diagram or network. The network simulation model is developed within a hierarchy of vehicle systems, subsystems, and equipment and includes failure management subnetworks. RAM information and other performance measures are collected which have impact on design requirements. Design changes are evaluated through ``what if`` questions, sensitivity studies, and battle scenario changes
The missing link between information and action: hastenings and delays as universal reactions to performance feedback
The missing link between information and action: hastenings and delays as universal reactions to performance feedback
This chapter focuses on what the key decision makers in organizations decide after having received information on the current state of the organizational performance. Because of strong attributions to success and failure, it is impossible to predict in advance which concrete actions will occur. We can however find out what kinds of actions are decided upon by means of an organizational learning model that focuses on the hastenings and delays after performance feedback. As an illustration, the responses to performance signals by trainers and club owners in Dutch soccer clubs are analyzed