Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data analysis cluster”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Applications of wavelet-based compression to multidimensional Earth science data

A data compression algorithm involving vector quantization (VQ) and the discrete wavelet transform (DWT) is applied to two different types of multidimensional digital earth-science data. The algorithms (WVQ) is optimized for each particular application through an optimization procedure that assigns VQ parameters to the wavelet transform subbands subject to constraints on compression ratio and encoding complexity. Preliminary results of compressing global ocean model data generated on a Thinking Machines CM-200 supercomputer are presented. The WVQ scheme is used in both a predictive and nonpredictive mode. Parameters generated by the optimization algorithm are reported, as are signal-to-noise (SNR) measurements of actual quantized data. The problem of extrapolating hydrodynamic variables across the continental landmasses in order to compute the DWT on a rectangular grid is discussed. Results are also presented for compressing Landsat TM 7-band data using the WVQ scheme. The formulation of the optimization problem is presented along with SNR measurements of actual quantized data. Postprocessing applications are considered in which the seven spectral bands are clustered into 256 clusters using a k-means algorithm and analyzed using the Los Alamos multispectral data analysis program, SPECTRUM, both before and after being compressed using the WVQ program.

Bradley, Jonathan N.↗
NASA NTRS2008

Tool Support for Parametric Analysis of Large Software Simulation Systems

The analysis of large and complex parameterized software systems, e.g., systems simulation in aerospace, is very complicated and time-consuming due to the large parameter space, and the complex, highly coupled nonlinear nature of the different system components. Thus, such systems are generally validated only in regions local to anticipated operating points rather than through characterization of the entire feasible operational envelope of the system. We have addressed the factors deterring such an analysis with a tool to support envelope assessment: we utilize a combination of advanced Monte Carlo generation with n-factor combinatorial parameter variations to limit the number of cases, but still explore important interactions in the parameter space in a systematic fashion. Additional test-cases, automatically generated from models (e.g., UML, Simulink, Stateflow) improve the coverage. The distributed test runs of the software system produce vast amounts of data, making manual analysis impossible. Our tool automatically analyzes the generated data through a combination of unsupervised Bayesian clustering techniques (AutoBayes) and supervised learning of critical parameter ranges using the treatment learner TAR3. The tool has been developed around the Trick simulation environment, which is widely used within NASA. We will present this tool with a GN&C (Guidance, Navigation and Control) simulation of a small satellite system.

Schumann, Johann↗
NASA NTRS2012

An In-Depth Study of the Abundance Pattern in the Hot Interstellar Medium in NGC 4649

We present our X-ray imaging spectroscopic analysis of data from deep Suzuku and XMM-Newton Observatory exposures of the Virgo Cluster elliptical galaxy NGC 4649 (M60), focusing on the abundance pattern in the hot interstellar medium (ISM). All measured elements show a radial decline in abundance, with the possible exception of O. We construct steady state solutions to the chemical evolution equations that include infall in addition to stellar mass return and SNIa enrichment, and consider recently published SNIa yields. By adjusting a single model parameter to obtain a match to the global abundance pattern in NGC 4649 we infer that accretion of subsolar metallicity external gas has reduced the overall ISM metallicity and diluted the effectiveness of SNIa to skew the pattern towards low alpha/Fe ratios, and estimate the combination of SNIa rate and level of dilution. Evidently, newly-introduced gas is heated as it is integrated into. and interacts with, the hot gas that is already present. These results indicate a complex flow and enrichment history for NGC 4649, reflecting the continual evolution of elliptical galaxies beyond the formation epoch. The heating and circulation of accreted gas may help reconcile this dynamic history with the mostly passive evolution of elliptical stellar populations. In an appendix we examine the effects of the recent updated atomic database AtomDB in spectral fitting of thermal plasmas with hot ISM temperatures in the elliptical galaxy range.

Lowenstein, Michael↗
NASA NTRS2012

An In-Depth Study of the Abundance Pattern in the Hot Interstellar Medium in NGC 4649

We present our X-ray imaging spectroscopic analysis of data from deep Suzaku and XMM-Newton Observatory exposures of the Virgo Cluster elliptical galaxy NGC 4649 (M60), focusing on the abundance pattern in the hot interstellar medium (ISM). All measured elements show a radial decline in abundance, with the possible exception of Oxygen. We construct steady state solutions to the chemical evolution equations that include infall in addition to stellar mass return and Type Ia supernovae (SNIa) enrichment, and consider recently published SNIa yields. By adjusting a single model parameter to obtain a match to the global abundance pattern in NGC 4649 we infer that introduction of subsolar metallicity external gas has reduced the overall ISM metallicity and diluted the effectiveness of SNIa to skew the pattern towards low alpha/Fe ratios, and estimate the combination of SNIa rate and level of dilution. Evidently, newly-introduced gas is heated as it is integrated into, and interacts with, the hot gas that is already present. These results indicate a complex flow and enrichment history for NGC 4649, reflecting the continual evolution of elliptical galaxies beyond the formation epoch. The heating and circulation of accreted gas may help reconcile this dynamic history with the mostly passive evolution of elliptical stellar populations. In an appendix we examine the effects of the recent updated atomic database AtomDB in spectral fitting of thermal plasmas with hot ISM temperatures in the elliptical galaxy range.

Loewenstein, Michael↗
NASA NTRS2011

Parallel Wavefront Analysis for a 4D Interferometer

This software provides a programming interface for automating data collection with a PhaseCam interferometer from 4D Technology, and distributing the image-processing algorithm across a cluster of general-purpose computers. Multiple instances of 4Sight (4D Technology s proprietary software) run on a networked cluster of computers. Each connects to a single server (the controller) and waits for instructions. The controller directs the interferometer to several images, then assigns each image to a different computer for processing. When the image processing is finished, the server directs one of the computers to collate and combine the processed images, saving the resulting measurement in a file on a disk. The available software captures approximately 100 images and analyzes them immediately. This software separates the capture and analysis processes, so that analysis can be done at a different time and faster by running the algorithm in parallel across several processors. The PhaseCam family of interferometers can measure an optical system in milliseconds, but it takes many seconds to process the data so that it is usable. In characterizing an adaptive optics system, like the next generation of astronomical observatories, thousands of measurements are required, and the processing time quickly becomes excessive. A programming interface distributes data processing for a PhaseCam interferometer across a Windows computing cluster. A scriptable controller program coordinates data acquisition from the interferometer, storage on networked hard disks, and parallel processing. Idle time of the interferometer is minimized. This architecture is implemented in Python and JavaScript, and may be altered to fit a customer s needs.

Rao, Shanti R.↗
NASA NTRS1996

Gravity Induced Formation of Concentration Gradients in Supersaturated Binary Solutions

Experimental and theoretical studies of the formation of solute concentration gradient in supersaturated binary solutions in a gravitational field were carried out. The formation of solute concentration gradient was associated with the gravity induced redistribution of subcritical solute clusters. The birth-death process of the new solute-rich phase domains (subcritical solute clusters) was described in terms of the time-dependent Ginzburg Landau model developed for metastable state relaxation in binary (solute + solvent) non-critical solutions in the presence of a gravitational field. A new mathematical Ansatz was developed for solution of the model equations. This Ansatz has allowed to approach for the first time the following important problems: (1) Microstructure of solute distribution inside of the subcritical solute clusters. The analytical results obtained demonstrate that solute inside of the subcritical solute clusters is heterogeneously distributed with a spatially periodic structure. (2) Macrostructure of the solute subcritical clusters distribution in a gravitational field. The subcritical solute clusters are found to be distributed heterogeneously in a gravitational field. This heterogeneity, which is due to the heterogeneous birth-death process of the subcritical solute clusters in a gravitational field, initiates a noticeable solute concentration gradient in vertical columns of supersaturated binary solutions. An analysis and comparison of theoretical results and experimental data related to the solute concentration gradient formation in a gravitational field are presented. It is also demonstrated that the critical radius of solute clusters (radius of nucleation) and induction time are gravity-dependent.

Izmailov, Alexander F.↗
NASA NTRS2008

Formation of Clustered DNA Damage after High-LET Irradiation: A Review

Radiation can cause as well as cure cancer. The risk of developing radiation-induced cancer has traditionally been estimated from cancer incidence among survivors of the atomic bombs in Hiroshima and Nagasaki. These data provide the best estimate of human cancer risk over the dose range for low linear energy transfer (LET) radiations, such as X- or gamma-rays. The situation of estimating the real biological effects becomes even more difficult in the case of high LET particles encountered in space or as the result of domestic exposure to particles from radon gas emitters or other radioactive emitters like uranium-238. Complex DNA damage, i.e., the signature of high-LET radiations comprises by closely spaced DNA lesions forming a cluster of DNA damage. The two basic groups of complex DNA damage are double strand breaks (DSBs) and non-DSB oxidative clustered DNA lesions (OCDL). Theoretical analysis and experimental evidence suggest there is increased complexity and severity of complex DNA damage with increasing LET (linear energy transfer) and a high mutagenic or carcinogenic potential. Data available on the formation of clustered DNA damage (DSBs and OCDL) by high-LET radiations are often controversial suggesting a variable response to dose and type of radiation. The chemical nature and cellular repair mechanisms of complex DNA damage have been much less characterized than those of isolated DNA lesions like an oxidized base or a single strand break especially in the case of high-LET radiation. This review will focus on the induction of clustered DNA damage by high-LET radiations presenting the earlier and recent relative data.

Hada, Megumi↗
NASA NTRS2018

K-Means Cluster Study for Radiofrequency Propagation Characterization

The objective of this study is to design a simple method for mining radio frequency (RF) propagation data. The study explored the characteristics of a large dataset of propagation experiments conducted over the span of years and using several ground stations around the world. Furthermore, this study developed simple predictive models that can be used for link characterization and overall propagation behavior description, without the need for physical measurements on-site. It is understood that such statistical learning has several drawbacks in terms of accuracy and precision. K-means clustering was used to characterize the data set in a way never explored before in an attempt to create useful tools that reduce cost, time and risk. K-means clustering was used to characterize the data set. Cosine distance was used as a method to determine the optimal number for clustering each feature. Dependence and independence analysis was performed to explore intra and inter-sensitivity between the presented features, with respect to each other and time. Several predicative models were generated and evaluated with respect to a test set to assess a measure of prediction accuracy and precision. A simple method for data analysis was developed and tested as the basis for further studies and future refinement to produce optimal performing models.

Cognitive↗
NASA NTRS1984

Landsat-4 MSS and Thematic Mapper data quality and information content analysis

Landsat-4 Thematic Mapper and Multispectral Scanner data were analyzed to obtain information on data quality and information content. Geometric evaluations were performed to test band-to-band registration accuracy. Thematic Mapper overall system resolution was evaluated using scene objects which demonstrated sharp high contrast edge responses. Radiometric evaluation included detector relative calibration, effects of resampling, and coherent noise effects. Information content evaluation was carried out using clustering, principal components, transformed divergence separability measure, and numerous supervised classifiers on data from Iowa and Illinois. A detailed spectral class analysis (multispectral classification) was carried out on data from the Des Moines, IA area to compare the information content of the MSS and TM for a large number of scene classes.

Anuta, P. E.↗
NASA NTRS1975

M-DAS: System for multispectral data analysis

M-DAS is a ground data processing system designed for analysis of multispectral data. M-DAS operates on multispectral data from LANDSAT, S-192, M2S and other sources in CCT form. Interactive training by operator-investigators using a variable cursor on a color display was used to derive optimum processing coefficients and data on cluster separability. An advanced multivariate normal-maximum likelihood processing algorithm was used to produce output in various formats: color-coded film images, geometrically corrected map overlays, moving displays of scene sections, coverage tabulations and categorized CCTs. The analysis procedure for M-DAS involves three phases: (1) screening and training, (2) analysis of training data to compute performance predictions and processing coefficients, and (3) processing of multichannel input data into categorized results. Typical M-DAS applications involve iteration between each of these phases. A series of photographs of the M-DAS display are used to illustrate M-DAS operation.

Johnson, R. H.↗
NASA NTRS1993

Venus small volcano classification and description

The high resolution and global coverage of the Magellan radar image data set allows detailed study of the smallest volcanoes on the planet. A modified classification scheme for volcanoes less than 20 km in diameter is shown and described. It is based on observations of all members of the 556 significant clusters or fields of small volcanoes located and described by this author during data collection for the Magellan Volcanic and Magmatic Feature Catalog. This global study of approximately 10 exp 4 volcanoes provides new information for refining small volcano classification based on individual characteristics. Total number of these volcanoes was estimated to be 10 exp 5 to 10 exp 6 planetwide based on pre-Magellan analysis of Venera 15/16, and during preparation of the global catalog, small volcanoes were identified individually or in clusters in every C1-MIDR mosaic of the Magellan data set. Basal diameter (based on 1000 measured edifices) generally ranges from 2 to 12 km with a mode of 34 km, and follows an exponential distribution similar to the size frequency distribution of seamounts as measured from GLORIA sonar images. This is a typical distribution for most size-limited natural phenomena unlike impact craters which follow a power law distribution and continue to infinitely increase in number with decreasing size. Using an exponential distribution calculated from measured small volcanoes selected globally at random, we can calculate total number possible given a minimum size. The paucity of edifice diameters less than 2 km may be due to inability to identify very small volcanic edifices in this data set; however, summit pits are recognizable at smaller diameters, and 2 km may represent a significant minimum diameter related to style of volcanic eruption. Guest, et al, discussed four general types of small volcanic edifices on Venus: (1) small lava shields; (2) small volcanic cones; (3) small volcanic domes; and (4) scalloped margin domes ('ticks'). Steep-sided domes or 'pancake domes', larger than 20 km in diameter, were included with the small volcanic domes. For the purposes of this study, only volcanic edifices less than 20 km in diameter are discussed. This forms a convenient cutoff since most of the steep-sided domes ('pancake domes') and scalloped margin domes ('ticks') are 20 to 100 km in diameter, are much less numerous globally than are the smaller diameter volcanic edifices (2 to 3 orders of magnitude lower in total global number), and do not commonly occur in large clusters or fields of large numbers of edifices.

Aubele, J. C.↗
NASA NTRS1972

The structure of the coma cluster of galaxies.

Analysis of radial velocities in the coma cluster (many of them new) in conjunction with previous data on the density distribution. The cluster extends more than 200 min in radius, with bright and faint galaxies distributed in nearly the same way. Some spirals are members. Several different determinations of M/L give values around 250. The cluster is stabilized by a 'missing mass' some seven times the mass of the galaxies, which must be distributed in the same way as the galaxies.

Rood, H. J.↗
NASA NTRS1978

Correlation of chemistry with normal albedo in the Crisium region

The region in the vicinity of the Luna 24 handling site (40-70 deg E; 0-20 deg N) is studied by means of the Apollo orbital fluorescent X-ray Al/Si and Mg/Al data and earth-based normal albedo measurements. By means of unsupervised non-parametric cluster analysis this region is divided into eight surface units. One of these units centered in the Proclus region deviates from the usual trend of increasing normal albedo with increasing Al/Si values and decreasing Mg/Al values

Bielefeld, M. J.↗
NASA NTRS1987

File Usage Analysis and Resource Usage Prediction: a Measurement-Based Study

A probabilistic scheme was developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The coefficient of correlation between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.-S.↗
NASA NTRS1987

Predictability of process resource usage: A measurement-based study of UNIX

A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.↗
NASA NTRS1989

Predictability of process resource usage - A measurement-based study on UNIX

A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient betweeen the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82 percent of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.↗
NASA NTRS1991

Unsupervised segmentation of polarimetric SAR data using the covariance matrix

An unsupervised selection of polarimetric features useful for the segmentation and analysis of polarimetric synthetic aperture radar (SAR) data is presented. The technique is based on multidimensional clustering of the parameters composing the polarimetric covariance matrix of the data. Clustering is performed on the logarithm of these quantities. Once the polarimetric cluster centers have been determined, segmentation of the polarimetric data into regions is performed using a maximum likelihood polarimetric classifier. Segmentation maps are further improved using a Markov random field to describe the statistics of the regions and computing the maximum of the product of the local conditional densities. Examples with real polarimetric SAR imagery are given to illustrate the potential of this method.

Rignot, Eric↗