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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 use of software fault trees for requirements identification and analysis in an Intrusion Detection System (IDS) is described.
A dynamic programming based approach for data compression of a ID sequence is presented. The compression of an input sequence of size N to that of a smaller size k is achieved by dividing the input sequence into k subsequences and replacing the subsequences by their respective average values. The partitioning of the input sequence is carried with the intention of reducing the mean squared error in the reconstructed sequence. The complexity involved in finding the partitions which would result in such an optimal compressed sequence is reduced by using the dynamic programming approach, which is presented.
The purpose of this study was to test the hypothesis that the content of endothelial nitric oxide synthase (eNOS) protein (eNOS protein/g total artery protein) increases with decreasing artery diameter in the coronary arterial tree. Content of eNOS protein was determined in porcine coronary arteries with immunoblot analysis. Arteries were isolated in six size categories from each heart: large arteries [301- to 2,500-microm internal diameter (ID)], small arteries (201- to 300-microm ID), resistance arteries (151- to 200-microm ID), large arterioles (101- to 150-microm ID), intermediate arterioles (51- to 100-microm ID), and small arterioles(<50-microm ID). To obtain sufficient protein for analysis from small- and intermediate-sized arterioles, five to seven arterioles 1-2 mm in length were pooled into one sample for each animal. Results establish that the number of smooth muscle cells per endothelial cell decreases from a number of 10 to 15 in large coronary arteries to 1 in the smallest arterioles. Immunohistochemistry revealed that eNOS is located only in endothelial cells in all sizes of coronary artery and in coronary capillaries. Contrary to our hypothesis, eNOS protein content did not increase with decreasing size of coronary artery. Indeed, the smallest coronary arterioles had less eNOS protein per gram of total protein than the large coronary arteries. These results indicate that eNOS protein content is greater in the endothelial cells of conduit arteries, resistance arteries, and large arterioles than in small coronary arterioles.
This CD contains files that support the talk (see CASI ID 20100021404). There are 24 models that relate to the ADAPT system and 1 Excel worksheet. In the paper an investigation into the use of Bayesian networks to construct large-scale diagnostic systems is described. The high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems are described in the talk. The data in the CD are the models of the 24 different power systems.
This follow-on to NASA Contractor Report 195447, Microgravity Experiments Safety and Integration Requirements Document Tree, provides the details for accessing the systems that contain the official, electronic versions of the documents initially researched in NASA Contractor Report 195447. The data in this report serves as a valuable information source for the NASA Lewis Research Center Project Documentation Center (PDC), as well as for all developers of space experiments. The PDC has acquired the hardware, software, ID's, and passwords necessary to access most of these systems and is now able to provide customers with current document information as well as immediate delivery of available documents in either electronic or hard copy format.
We describe an on-line system for automated classification of X-ray sources, ClassX, and present preliminary results of classification of the three major catalogs of ROSAT sources, RASS BSC, RASS FSC, and WGACAT, into six class categories: stars, white dwarfs, X-ray binaries, galaxies, AGNs, and clusters of galaxies. ClassX is based on a machine learning technology. It represents a system of classifiers, each classifier consisting of a considerable number of oblique decision trees. These trees are built as the classifier is 'trained' to recognize various classes of objects using a training sample of sources of known object types. Each source is characterized by a preselected set of parameters, or attributes; the same set is then used as the classifier conducts classification of sources of unknown identity. The ClassX pipeline features an automatic search for X-ray source counterparts among heterogeneous data sets in on-line data archives using Virtual Observatory protocols; it retrieves from those archives all the attributes required by the selected classifier and inputs them to the classifier. The user input to ClassX is typically a file with target coordinates, optionally complemented with target IDs. The output contains the class name, attributes, and class probabilities for all classified targets. We discuss ways to characterize and assess the classifier quality and performance and present the respective validation procedures. Based on both internal and external validation, we conclude that the ClassX classifiers yield reasonable and reliable classifications for ROSAT sources and have the potential to broaden class representation significantly for rare object types.
In this paper, we investigate the use of Bayesian networks to construct large-scale diagnostic systems. In particular, we consider the development of large-scale Bayesian networks by composition. This compositional approach reflects how (often redundant) subsystems are architected to form systems such as electrical power systems. We develop high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems. The largest among these 24 Bayesian networks contains over 1,000 random variables. Another BN represents the real-world electrical power system ADAPT, which is representative of electrical power systems deployed in aerospace vehicles. In addition to demonstrating the scalability of the compositional approach, we briefly report on experimental results from the diagnostic competition DXC, where the ProADAPT team, using techniques discussed here, obtained the highest scores in both Tier 1 (among 9 international competitors) and Tier 2 (among 6 international competitors) of the industrial track. While we consider diagnosis of power systems specifically, we believe this work is relevant to other system health management problems, in particular in dependable systems such as aircraft and spacecraft. (See CASI ID 20100021910 for supplemental data disk.)