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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Spectral alteration effects in chondritic gas-rich breccias - Implications for S-Class and Q-Class asteroids

Reflection spectra were obtained from sawed or freshly broken surfaces of gas-rich matrix regions in a number of ordinary chondrites (Dubrovnik, Cangas de Onis, Olivenza, and Dimmitt) which are believed to represent lithified portions of asteroid regoliths that were once directly exposed to space, with the purpose of relating these chondrites to Class S asteroids. However, the observations did not detect curved red continuum characteristic for Class S asteroid spectra, suggesting that it is unlikely for any well-observed Class S asteroid to be a source of ordinary chondrites. It is suggested that the newly discovered spectral class 'Q', of which asteroid 1982 Apollo is the prototype, provides a viable alternative of a parent body.

Bell, Jeffrey F.↗
NASA NTRS1994

Class I and class II major histocompatibility molecules play a role in bone marrow-derived macrophage development

Class I and class II major histocompatibility complex (MHC) molecules play significant roles in T cell development and immune function. We show that MHCI- and MHCII-deficient mice have low numbers of macrophage precursors and circulating monocytes, as well as abnormal bone marrow cell colony-stimulating factor type 1 secretion and bone composition. We suggest that MHCI and MHCII molecules play a significant role in macrophage development.

Non-NASA Center↗
NASA NTRS1993

Case study of binary and ternary synthetic discriminant function filters with similar in-class and out-of-class images

A simulation study is reported of the performance of two designs of ternary synthetic discriminant function (SDF) filters. The filters are compared to binary SDFs in terms of the probability of correct identification P(ID) between in-class and out-of-class image sets. Compared to binary synthetic discriminant function (BSDF) filters, both ternary SDF filters designs offer improved performance in P(ID) and thus allow extension of the maximum filter direction range when evaluated in the presence of white image noise. Larger distortion range filters translate to fewer correlations required to perform image identification, and thus higher system speed. The TSDF(SNR) filters had the highest of system performance, while TSDF(d) filters were able to improve discrimination to a degree, but their optimal designs had essentially the same SNR performance as the BSDF filters.

Downie, John D.↗
NASA NTRS1994

McIntosh active-region class similarities and suggestions for mergers

McIntosh active-region classifications reported during a five-year period were examined to determine similarities among the classes. Two methods were used extensively to determine these similarities. The number of transitions among classes were used to determine the most frequent transitions out of each class, and the alternative classes reported for the same region by different sites were used to establish which classes were neighboring classes. These transition frequencies and neighboring classes were used to identify classes that could be eliminated or merged with other classes. Class similarities were used to investigate the relative importance of several pairs of decisions that occur within a single McIntosh parameter. In particular, the redundancy of parameters in some classes was examined, and the class similarities were used to identify which of these parameters could be eliminated. Infrequently reported classes were also considered, and suggestions for mergers were made when similarities between classes could be identified.

Bornmann, P. L.↗
NASA NTRS1999

Gamma-Ray Burst Class Properties

Guided by the Supervised pattern recognition algorithm C4.5, we examine the three gamma-ray burst classes identified by Mukherjee et al. C4.5 provides strong statistical support for this classification. However, with C4.5 and our knowledge of the BATSE instrument, we demonstrate that Class 3 (intermediate fluence, intermediate duration, soft) does not have to be a distinct source population: statistical/systematic errors in measuring burst attributes combined with the well-known hardness/intensity correlation can cause low peak flux Class I (high fluence, long, intermediate hardness) bursts to take on Class 3 characteristics naturally. Based on our hypothesis that the third class is not a distinct one, we provide rules so that future events can be placed in either Class I or Class 2 (low fluence, short, hard). Using classified bursts from the BATSE 4B Catalog, we plot log(N>P) vs. log(P) curves and study spectral features of each class. We find that the two classes are relatively distinct on the basis of spectral parameters, alpha, Beta, and E(sub peak) alone. Although this does not indicate a better basis for classification, it does suggest that different physical conditions exist for Class I and Class 2 bursts. In the process of studying burst class characteristics, we identify a new bias that affects measurement of burst fluences and durations. Using a simple model of how burst duration can be underestimated, we generally characterize how this fluence duration bias affects BATSE measurements, and demonstrate the type of effect it can have on the BATSE fluence vs. peak flux diagram.

Hakkila, Jon↗
NASA NTRS2014

Aeroflex Technology as Class-Y Demonstrator

Modern space field programmable gate array (FPGA) devices with increased functional density and operational frequency, such as Xilinx Virtex 4 (V4) and S (V5), are packaged in non-hermetic ceramic flip chip forms. These next generation space parts were not qualified to the MIL-PRF-38535 Qualified Manufacturer Listing (QML) class-V when they were released because class-V was only intended for hermetic parts. In order to bring Xilinx V5 type packages into the QML system, it was suggested that class-Y be set up as a new category. From 2010 through 2014, a JEDEC G12 task group developed screening and qualification requirements for Class-Y products. The Document Standardization Division of the Defense Logistics Agency (DLA) has completed an engineering practice study. In parallel with the class-Y efforts, the NASA Electronic Parts and Packaging (NEPP) program has funded JPL to study potential reliability issues of the class-Y products. The major hurdle of this task was the absence of adequate research samples. Figure 1-1 shows schematic diagrams of typical structures of class-Y type products. Typically, class-Y products are either in ceramic flip chip column grid array (CGA) or land grid array (LGA) form. In class-Y packages, underfill and heat spread adhesive materials are directly exposed to the spacecraft environment due to their non-hermeticity. One of the concerns originally raised was that the underfill material could degrade due to the spacecraft environment and negatively impact the reliability of the package. In order to study such issues, it was necessary to use ceramic daisy chain flip chip package samples so that continuity of flip chip solder bumps could be monitored during the reliability tests. However, none of the commercially available class-Y daisy chain parts had electrical connections through flip chip solder bumps; only solder columns were daisy chained, which made it impossible to test continuity of flip chip solder bumps without using extremely costly functional parts. Among space parts manufacturers who were interested in producing class-Y products, Aeroflex Microelectronic Solutions-HiRel had been developing assembly processes using their internal R&D classy type samples. In early 2012, JPL and Aeroflex initiated a collaboration to study reliability of the Aeroflex technology as a class-Y demonstrator.

Suh, Jong-ook↗
NASA NTRS2000

Gamma-Ray Burst Class Properties

Guided by the supervised pattern recognition algorithm C4.5 developed by Quinlan in 1986, we examine the three gamma-ray burst classes identified by Mukherjee et al. in 1998. C4.5 provides strong statistical support for this classification. However, with C4.5 and our knowledge of the Burst and Transient Source Experiment (BATSE) instrument, we demonstrate that class 3 (intermediate fluence, intermediate duration, soft) does not have to be a distinct source population: statistical/systematic errors in measuring burst attributes combined with the well-known hardness/intensity correlation can cause low peak flux class 1 (high fluence, long, intermediate hardness) bursts to take on class 3 characteristics naturally. Based on our hypothesis that the third class is not a distinct one, we provide rules so that future events can be placed in either class 1 or class 2 (low fluence, short, hard). We find that the two classes are relatively distinct on the basis of Band's work in 1993 on spectral parameters alpha, beta, and E (sub peak) alone. Although this does not indicate a better basis for classification, it does suggest that different physical conditions exist for class 1 and class 2 bursts. In the process of studying burst class characteristics, we identify a new bias affecting burst fluence and duration measurements. Using a simple model of how burst duration can be underestimated, we show how this fluence duration bias can affect BATSE measurements and demonstrate the type of effect it can have on the BATSE fluence versus peak flux diagram.

Hakkila, Jon↗
NASA NTRS1975

Single-class classification

Often, when classifying multispectral data, only one class or crop is of interest, such as wheat in the Large Area Crop Inventory Experiment (LACIE). Usual procedures for designing a Bayes classifier require that labeled training samples and therefore ground truth be available for the 'class of interest' plus all confusion classes defined by the multispectral data. This paper will consider the problem of designing a two-class Bayes classifier which will classify data into the 'class of interest' or the 'other' classes but will require only labeled training samples from the 'class of interest' to design the classifier. Thus, this classifier minimizes the need for ground truth. For these reasons, the classifier is referred to as a single-class classifier. A procedure for evaluating the overall performance of the single-class classifier in terms of the probability of error will be discussed.

Minter, T. C.↗
NASA NTRS1976

Bayes estimation on parameters of the single-class classifier

Normal procedures used for designing a Bayes classifier to classify wheat as the major crop of interest require not only training samples of wheat but also those of nonwheat. Therefore, ground truth must be available for the class of interest plus all confusion classes. The single-class Bayes classifier classifies data into the class of interest or the class 'other' but requires training samples only from the class of interest. This paper will present a procedure for Bayes estimation on the mean vector, covariance matrix, and a priori probability of the single-class classifier using labeled samples from the class of interest and unlabeled samples drawn from the mixture density function.

Lin, G. C.↗