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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The intention of the scheduling system developed at the Fraunhofer-Institute for Material Flow and Logistics is the support of a scheduler working in a job-shop. Due to the existing requirements for a job-shop scheduling system the usage of flexible knowledge representation and processing techniques is necessary. Within this system the attempt was made to combine the advantages of symbolic AI-techniques with those of neural networks.
This paper describes an ongoing program to augment such an expert system gas turbine startup advisor, known as the EPRI SA VANT System, by including an intelligent training package. It will give a brief background on the SA VANT development and an overview of its evolution into a full-blown Gas Turbine Information System (GTIS) for rapid access of on-line documentation, diagnostics, and training. In particular, the paper will address: (1) the conversion of the knowledge base used by the SA VANT startup advisor so that it can be used for both training and job aiding; and (2) the hypertext-oriented user manuals being incorporated into the system for rapidly accessing on-line documentation at the job site.
The increasing reliability of parallel systems and clusters of computers has resulted in these systems becoming more attractive for true production workloads. Today, the primary obstacle to production use of clusters of computers is the lack of a functional and robust Job Management System for parallel applications. This document provides a checklist of NAS requirements for job queuing and scheduling in order to make most efficient use of parallel systems and clusters for parallel applications. Future requirements are also identified to assist software vendors with design planning.
We consider the differences between the available general purpose parameter study and job submission tools. These tools necessarily share many features, but frequently with differences in the way they are designed and implemented For this class of features, we will only briefly outline the essential differences. However we will focus on the unique features which distinguish the ILab parameter study and job submission tool from other packages, and which make the ILab tool easier and more suitable for use in our research and engineering environment.
Computational grids hold great promise in utilizing geographically separated heterogeneous resources to solve large-scale complex scientific problems. However, a number of major technical hurdles, including distributed resource management and effective job scheduling, stand in the way of realizing these gains. In this paper, we propose a novel grid superscheduler architecture and three distributed job migration algorithms. We also model the critical interaction between the superscheduler and autonomous local schedulers. Extensive performance comparisons with ideal, central, and local schemes using real workloads from leading computational centers are conducted in a simulation environment. Additionally, synthetic workloads are used to perform a detailed sensitivity analysis of our superscheduler. Several key metrics demonstrate that substantial performance gains can be achieved via smart superscheduling in distributed computational grids.
Optimal system for automatic drive control of flying shears in metallurgical plant jobbing mill
Computer program LABCON controls the budget system in a component test laboratory whose workload is made up from many individual budget allocations. A common denominator is applied to an incoming job, to which all effort is charged and accounted for.
Methods for early identification of heart disease and related job stresses
Personnel performance evaluation as employee job motivation in government R and D activities
An intra-installation model is formulated that correlates demographic, health and job related variables to the various types and amounts of leave and overtime taking behavior of employees. Statistical comparison of composite health ratings assigned to subjects based upon clinical criteria and bio-statistical data show that those employees who take the most annual leave as well as sick leave are the ones that have the poorest health ratings; employees who put in the most overtime have also the poorest health records. Stress effects of peak activity periods increase use of sick leave immediately after peak activity but not the use of annual leave.
A mathematical model for job scheduling in a specified context is presented. The model uses both linear programming and combinatorial methods. While designed with a view toward optimization of scheduling of facility and plant operations at the Deep Space Communications Complex, the context is sufficiently general to be widely applicable. The general scheduling problem including options for scheduling objectives is discussed and fundamental parameters identified. Mathematical algorithms for partitioning problems germane to scheduling are presented.
The functions of the JOB BUILDER remote batch processing subsystem are described. Instructions are given for using it as a component of a display system developed by personnel of the System Programming Laboratory, Institute of Space Research, USSR Academy of Sciences.
A couple of weeks ago, the American Psychological Association and the National Institute of Occupational Safety and Health held a conference in Washingtion, D.C. entitled 'Stress in the 90's'. At this conference the Office of Personnel Management (OPM) conducted a session on 'Programs and Resources for the Control of Job Stress in the Federal Workplace'. I am going to present an overview of that three-hour session and some related information from the conference. My discussion covers stress terminology and models, selected programs and resources, evaluation research, some concerns about our progress, and plans to expand our efforts at OPM.
Efficient management of large-scale, distributed data storage and processing systems is a major challenge for many computational applications. Many of these systems are characterized by multi-resource tasks processed across a heterogeneous network. Conventional approaches, such as load balancing, work well for centralized, single resource problems, but breakdown in the more general case. In addition, most approaches are often based on heuristics which do not directly attempt to optimize the world utility. In this paper, we propose an agent based control system using the theory of collectives. We configure the servers of our network with agents who make local job scheduling decisions. These decisions are based on local goals which are constructed to be aligned with the objective of optimizing the overall efficiency of the system. We demonstrate that multi-agent systems in which all the agents attempt to optimize the same global utility function (team game) only marginally outperform conventional load balancing. On the other hand, agents configured using collectives outperform both team games and load balancing (by up to four times for the latter), despite their distributed nature and their limited access to information.
In an informal meeting with students, I will give an overview of NASA and discuss who works for NASA: astronauts, scientists, engineers, managers and secretaries, and how they are selected, hired and employed. I will discuss the process for applying for NASA jobs, including student programs.
In an informal meeting with students, I will give an overview of NASA and discuss who works for NASA: astronauts, scientists, engineers, managers and secretaries, and how they are selected, hired and employed. I will discuss the process for applying for NASA jobs, including student programs.
Hydraulic system performance predicted by actual load simulation, using fluid motors and connected flywheel
Vocational guidance booklet for directing young students to careers in space industry