Results for “Statistical sampling techniques” — Page 3

NASA NTRS2011

Multiple-Beam Detection of Fast Transient Radio Sources

A method has been designed for using multiple independent stations to discriminate fast transient radio sources from local anomalies, such as antenna noise or radio frequency interference (RFI). This can improve the sensitivity of incoherent detection for geographically separated stations such as the very long baseline array (VLBA), the future square kilometer array (SKA), or any other coincident observations by multiple separated receivers. The transients are short, broadband pulses of radio energy, often just a few milliseconds long, emitted by a variety of exotic astronomical phenomena. They generally represent rare, high-energy events making them of great scientific value. For RFI-robust adaptive detection of transients, using multiple stations, a family of algorithms has been developed. The technique exploits the fact that the separated stations constitute statistically independent samples of the target. This can be used to adaptively ignore RFI events for superior sensitivity. If the antenna signals are independent and identically distributed (IID), then RFI events are simply outlier data points that can be removed through robust estimation such as a trimmed or Winsorized estimator. The alternative "trimmed" estimator is considered, which excises the strongest n signals from the list of short-beamed intensities. Because local RFI is independent at each antenna, this interference is unlikely to occur at many antennas on the same step. Trimming the strongest signals provides robustness to RFI that can theoretically outperform even the detection performance of the same number of antennas at a single site. This algorithm requires sorting the signals at each time step and dispersion measure, an operation that is computationally tractable for existing array sizes. An alternative uses the various stations to form an ensemble estimate of the conditional density function (CDF) evaluated at each time step. Both methods outperform standard detection strategies on a test sequence of VLBA data, and both are efficient enough for deployment in real-time, online transient detection applications.

Thompson, David R.↗

NASA NTRS1983

Reduction of flow-measurement uncertainties in laser velocimeters with nonorthogonal channels

An analysis of certain geometrical limitations inherent in the application of laser velocimeters with nonorthogonal channels has led to the development of advanced-LDA-calibration and data-acquisition techniques that minimize systematic and statistical errors, respectively. The data-acquisition technique optimizes the number of velocity samples collected from three velocimeter channels as a function of local turbulence intensity, vector direction, and prescribed confidence interval. Linear velocity surveys and streamline traces measured in a turbulent flow field with a three-dimensional laser velocimeter are presented and the validity and accuracy of the theoretical analysis are discussed.

Snyder, P. K.↗

NASA NTRS1993

A deep x-ray survey of the Pleiades cluster and the B6-A3 main sequence stars in Orion

We have obtained deep ROSAT images of three regions within the Pleiades open cluster. We have detected 317 X-ray sources in these ROSAT PSPC images, 171 of which we associate with certain probable members of the Pleiades cluster. We detect nearly all Pleiades members with spectral types later than G0 and within 25 arcminutes of our three field centers where our sensitivity is highest. This has allowed us to derive for the first time the luminosity function for the G, K, and M dwarfs of an open cluster without the need to use statistical techniques to account for the presence of upper limits in the data sample. Because of our high X-ray detection frequency down to the faint limit of the optical catalog, we suspect that some of our unidentified X-ray sources are previously unknown, very low-mass members of the Pleiades. A large fraction of the Pleiades members detected with ROSAT have published rotational velocities. Plots of L(sub x)/L(sub bol) versus spectroscopic rotational velocity show tightly correlated 'saturation' type relations for stars with (B - V)(sub O) greater than 0.60. For each of several color ranges, X-ray luminosities rise rapidly with increasing rotation rate until v sin i approximately equals 15 km/s, and then remain essentially flat for rotation rates up to at least v sin i approximately equal to 100 km/s. The dispersion in rotation among low-mass stars in the Pleiades is by far the dominant contributor to the dispersion in L(subx) at a given mass. Only about 35 percent of the B.A. and early F stars in the Pleiades are detected as X-ray sources in our survey. There is no correlation between X-ray flux and rotation for these stars. The X-ray luminosity function for the early-type Pleiades stars appears to be bimodal, with only a few exceptions. We either detect these stars at fluxes in the range found for low-mass stars or we derive X-ray limits below the level found for most Pleiades dwarfs. The X-ray spectra for the early-type Pleiades stars detected by ROSAT are indistinguishable from the spectra of the low-mass Pleiades members. We believe that the simple explanation for this behavior is that the early-type Pleiades stars are not themselves intrinsic X-ray sources and that the X-ray sources and that the X-ray emission actually arises from low-mass companions to these stars.

Caillault, Jean-Pierre↗

NASA NTRS1994

A deep imaging survey of the Pleiades with ROSAT

We have obtained deep ROSAT images of three regions within the Pleiades open cluster. We have detected 317 X-ray sources in these ROSAT Position Sensitive Proportional Counter (PSPC) images, 171 of which we associate with certain or probable members of the Pleiades cluster. We detect nearly all Pleiades members with spectral types later than G0 and within 25 arcminutes of our three field centers where our sensitivity is highest. This has allowed us to derive for the first time the luminosity function for the G, K, amd M dwarfs of an open cluster without the need to use statistical techniques to account for the presence of upper limits in the data sample. Because of our high X-ray detection frequency down to the faint limit of the optical catalog, we suspect that some of our unidentified X-ray sources are previously unknown, very low-mass members of Pleiades. A large fraction of the Pleiades members detected with ROSAT have published rotational velocities. Plots of L(sub X)/L(sub Bol) versus spectroscopic rotational velocity show tightly correlated `saturation' type relations for stars with ((B - V)(sub 0)) greater than or equal to 0.60. For each of several color ranges, X-ray luminosities rise rapidly with increasing rotation rate until c sin i approximately equal to 15 km/sec, and then remains essentially flat for rotation rates up to at least v sin i approximately equal to 100 km/sec. The dispersion in rotation among low-mass stars in the Pleiades is by far the dominant contributor to the dispersion in L(sub X) at a given mass. Only about 35% of the B, A, and early F stars in the Pleiades are detected as X-ray sources in our survey. There is no correlation between X-ray flux and rotation for these stars. The X-ray luminosity function for the early-type Pleiades stars appears to be bimodal -- with only a few exceptions, we either detect these stars at fluxes in the range found for low-mass stars or we derive X-ray limits below the level found for most Pleiades dwarfs. The X-ray spectra for the early-type Pleiades stars detected by ROSAT are indistinguishable from the spectra of the low-mass Pleiades members. We believe that the simplest explanation for this behavior is that the early-type Pleiades stars are not themselves intrinsic X-ray sources and that the X-ray emission actually arises from low-mass companions to these stars.

Stauffer, J. R.↗

NASA NTRS2016

Analyzing and Predicting Effort Associated with Finding and Fixing Software Faults

Context: Software developers spend a significant amount of time fixing faults. However, not many papers have addressed the actual effort needed to fix software faults. Objective: The objective of this paper is twofold: (1) analysis of the effort needed to fix software faults and how it was affected by several factors and (2) prediction of the level of fix implementation effort based on the information provided in software change requests. Method: The work is based on data related to 1200 failures, extracted from the change tracking system of a large NASA mission. The analysis includes descriptive and inferential statistics. Predictions are made using three supervised machine learning algorithms and three sampling techniques aimed at addressing the imbalanced data problem. Results: Our results show that (1) 83% of the total fix implementation effort was associated with only 20% of failures. (2) Both safety critical failures and post-release failures required three times more effort to fix compared to non-critical and pre-release counterparts, respectively. (3) Failures with fixes spread across multiple components or across multiple types of software artifacts required more effort. The spread across artifacts was more costly than spread across components. (4) Surprisingly, some types of faults associated with later life-cycle activities did not require significant effort. (5) The level of fix implementation effort was predicted with 73% overall accuracy using the original, imbalanced data. Using oversampling techniques improved the overall accuracy up to 77%. More importantly, oversampling significantly improved the prediction of the high level effort, from 31% to around 85%. Conclusions: This paper shows the importance of tying software failures to changes made to fix all associated faults, in one or more software components and/or in one or more software artifacts, and the benefit of studying how the spread of faults and other factors affect the fix implementation effort.

software fix implementation effort↗

NASA NTRS1978

A statistical technique for determining rainfall over land employing Nimbus-6 ESMR measurements

Statistical analysis is performed by first sampling three categories of Nimbus 6 ESMR brightness temperatures (representing rain over land, wet land surfaces without rain, and dry land surfaces), then testing these populations for uniqueness. A classification algorithm to delineate rain over land is developed. It is found that synoptic-scale rainfall over land, where surface thermodynamic temperatures are greater than 5 C and the vegetation is bereft of dew, can indeed be delineated despite the large ESMR-6 instantaneous field of view. However, some ambiguity exists in distinguishing between rainfall areas and wet land surfaces.

Rodgers, E.↗

NASA NTRS2012

Uncertainty Quantification for Polynomial Systems via Bernstein Expansions

This paper presents a unifying framework to uncertainty quantification for systems having polynomial response metrics that depend on both aleatory and epistemic uncertainties. The approach proposed, which is based on the Bernstein expansions of polynomials, enables bounding the range of moments and failure probabilities of response metrics as well as finding supersets of the extreme epistemic realizations where the limits of such ranges occur. These bounds and supersets, whose analytical structure renders them free of approximation error, can be made arbitrarily tight with additional computational effort. Furthermore, this framework enables determining the importance of particular uncertain parameters according to the extent to which they affect the first two moments of response metrics and failure probabilities. This analysis enables determining the parameters that should be considered uncertain as well as those that can be assumed to be constants without incurring significant error. The analytical nature of the approach eliminates the numerical error that characterizes the sampling-based techniques commonly used to propagate aleatory uncertainties as well as the possibility of under predicting the range of the statistic of interest that may result from searching for the best- and worstcase epistemic values via nonlinear optimization or sampling.

Crespo, Luis G.↗

NASA NTRS1979

Multiclass Bayes error estimation by a feature space sampling technique

A general Gaussian M-class N-feature classification problem is defined. An algorithm is developed that requires the class statistics as its only input and computes the minimum probability of error through use of a combined analytical and numerical integration over a sequence simplifying transformations of the feature space. The results are compared with those obtained by conventional techniques applied to a 2-class 4-feature discrimination problem with results previously reported and 4-class 4-feature multispectral scanner Landsat data classified by training and testing of the available data.

Mobasseri, B. G.↗

NASA NTRS1994

Operations for Learning with Graphical Models

This paper is a multidisciplinary review of empirical, statistical learning from a graphical model perspective. Well-known examples of graphical models include Bayesian net- works, directed graphs representing a Markov chain, and undirected networks representing a Markov field. These graphical models are extended to model data analysis and empirical learning using the notation of plates. Graphical operations for simplifying and manipulating a problem are provided including decomposition, differentiation, and the manipulation of probability models from the exponential family. These operations adapt existing techniques from statistics and automatic differentiation to graphs. Two standard algorithm schemes for learning are reviewed in a graphical framework: Gibbs sampling and the expectation maximization algorithm. Some algorithms are developed in this graphical framework including a generalized version of linear regression, techniques for feed-forward networks, and learning Gaussian and discrete Bayesian networks from data. The paper concludes by sketching some implications for data analysis and summarizing some popular algorithms that fall within the framework presented. The main original contributions here are the decomposition techniques and the demonstration that graphical models provide a framework for understanding and developing complex learning algorithms.

Buntine, Wray L.↗

NASA NTRS2003

Estimates of the Lunar Surface Composition with Clementine Images and LSCC Data

There have been several approaches to develop remote sensing technique to estimate composition of the lunar surface using multispectral observations. We present a new approach based on statistical analysis of spectral and compositional data for lunar samples by the Lunar Soil Characterization Consortium (LSCC) and using the UVVIS Clementine data with 1 km resolution. This technique allows us to estimate and map the abundance of TiO2, SiO2, and FeO, pyroxene and plagioclase content, and maturity degree (Is/FeO).

Shkuratov, Yu.↗

NASA NTRS2011

Shuttle Hypervelocity Impact Database

With three flights remaining on the manifest, the shuttle impact hypervelocity database has over 2800 entries. The data is currently divided into tables for crew module windows, payload bay door radiators and thermal protection system regions, with window impacts compromising just over half the records. In general, the database provides dimensions of hypervelocity impact damage, a component level location (i.e., window number or radiator panel number) and the orbiter mission when the impact occurred. Additional detail on the type of particle that produced the damage site is provided when sampling data and definitive analysis results are available. The paper will provide details and insights on the contents of the database including examples of descriptive statistics using the impact data. A discussion of post flight impact damage inspection and sampling techniques that were employed during the different observation campaigns will be presented. Future work to be discussed will be possible enhancements to the database structure and availability of the data for other researchers. A related database of ISS returned surfaces that are under development will also be introduced.

Hyde, James I.↗

NASA NTRS1981

The magnifying glass - A feature space local expansion for visual analysis

The Magnifying Glass Transformation (MGT) technique is proposed, as a multichannel spectral operation yielding visual imagery which is enhanced in a specified spectral vicinity, guided by the statistics of training samples. An application example is that in which the discrimination among spectral neighbors within an interactive display may be increased without altering distant object appearances or overall interpretation. A direct histogram specification technique is applied to the channels within the multispectral image so that a subset of the spectral domain occupies an increased fraction of the domain. The transformation is carried out by obtaining the training information, establishing the condition of the covariance matrix, determining the influenced solid, and initializing the lookup table. Finally, the image is transformed.

Juday, R. D.↗

NASA NTRS1999

Experiments on Nucleation in Different Flow Regimes

The vast majority of metallic engineering materials are solidified from the liquid phase. Understanding the solidification process is essential to control microstructure, which in turn, determines the properties of materials. The genesis of solidification is nucleation, where the first stable solid forms from the liquid phase. Nucleation kinetics determine the degree of undercooling and phase selection. As such, it is important to understand nucleation phenomena in order to control solidification or glass formation in metals and alloys. Early experiments in nucleation kinetics were accomplished by droplet dispersion methods. Dilatometry was used by Turnbull and others, and more recently differential thermal analysis and differential scanning calorimetry have been used for kinetic studies. These techniques have enjoyed success; however, there are difficulties with these experiments. Since materials are dispersed in a medium, the character of the emulsion/metal interface affects the nucleation behavior. Statistics are derived from the large number of particles observed in a single experiment, but dispersions have a finite size distribution which adds to the uncertainty of the kinetic determinations. Even though temperature can be controlled quite well before the onset of nucleation, the release of the latent heat of fusion during nucleation of particles complicates the assumption of isothermality during these experiments. Containerless processing has enabled another approach to the study of nucleation kinetics. With levitation techniques it is possible to undercool one sample to nucleation repeatedly in a controlled manner, such that the statistics of the nucleation process can be derived from multiple experiments on a single sample. The authors have fully developed the analysis of nucleation experiments on single samples following the suggestions of Skripov. The advantage of these experiments is that the samples are directly observable. The nucleation temperature can be measured by noncontact optical pyrometry, the mass of the sample is known, and post processing analysis can be conducted on the sample. The disadvantages are that temperature measurement must have exceptionally high precision, and it is not possible to isolate specific heterogeneous sites as in droplet dispersions.

Bayuzick, R. J.↗

NASA NTRS1998

Experiments on Nucleation in Different Flow Regimes

The vast majority of metallic engineering materials are solidified from the liquid phase. Understanding the solidification process is essential to control microstructure, which in turn, determines the properties of materials. The genesis of solidification is nucleation, where the first stable solid forms from the liquid phase. Nucleation kinetics determine the degree of undercooling and phase selection. As such, it is important to understand nucleation phenomena in order to control solidification or glass formation in metals and alloys. Early experiments in nucleation kinetics were accomplished by droplet dispersion methods. Dilitometry was used by Turnbull and others, and more recently differential thermal analysis and differential scanning calorimetry have been used for kinetic studies. These techniques have enjoyed success; however, there are difficulties with these experiments. Since materials are dispersed in a medium, the character of the emulsion/metal interface affects the nucleation behavior. Statistics are derived from the large number of particles observed in a single experiment, but dispersions have a finite size distribution which adds to the uncertainty of the kinetic determinations. Even though temperature can be controlled quite well before the onset of nucleation, the release of the latent heat of fusion during nucleation of particles complicates the assumption of isothermality during these experiments. Containerless processing has enabled another approach to the study of nucleation kinetics. With levitation techniques it is possible to undercool one sample to nucleation repeatedly in a controlled manner, such that the statistics of the nucleation process can be derived from multiple experiments on a single sample. The authors have fully developed the analysis of nucleation experiments on single samples following the suggestions of Skripov. The advantage of these experiments is that the samples are directly observable. The nucleation temperature can be measured by noncontact optical pyrometry, the mass of the sample is known, and post-processing analysis can be conducted on the sample. The disadvantages are that temperature measurement must have exceptionally high precision, and it is not possible to isolate specific heterogeneous sites as in droplet dispersions. Levitation processing of refractory materials in ultra high vacuum provides an avenue to conduct these kinetic studies on single samples. Two experimental methods have been identified where ultra high vacuum experiments are possible; electrostatic levitation in ground-based experiments and electromagnetic processing in low earth orbit on TEMPUS. Such experiments, reported here, were conducted on zirconium. Liquid zirconium is an excellent solvent and has a high solubility for contaminants contained in the bulk material as well as those contaminants found in the vacuum environment. Oxides, nitrides, and carbides do not exist in the melt, and do not form on the surface of molten zirconium, for the materials and vacuum levels used in this study. Ground-based experiments with electrostatic levitation have shown that the statistical nucleation kinetic experiments are viable and yield results which are consistent with classical nucleation theory. The advantage of low earth orbit experiments is the ability to vary the flow conditions in the liquid prior to nucleation. The put-pose of nucleation experiments in TEMPUS was to examine.

Bayuzick, R. J.↗

NASA NTRS1999

Experiments on Nucleation in Different Flow Regimes

The vast majority of metallic engineering materials are solidified from the liquid phase. Understanding the solidification process is essential to control microstructure, which in turn, determines the properties of materials. The genesis of solidification is nucleation, where the first stable solid forms from the liquid phase. Nucleation kinetics determine the degree of undercooling and phase selection. As such, it is important to understand nucleation phenomena in order to control solidification or glass formation in metals and alloys. Early experiments in nucleation kinetics were accomplished by droplet dispersion methods [1-6]. Dilitometry was used by Turnbull and others, and more recently differential thermal analysis and differential scanning calorimetry have been used for kinetic studies. These techniques have enjoyed success; however, there are difficulties with these experiments. Since materials are dispersed in a medium, the character of the emulsion/metal interface affects the nucleation behavior. Statistics are derived from the large number of particles observed in a single experiment, but dispersions have a finite size distribution which adds to the uncertainty of the kinetic determinations. Even though temperature can be controlled quite well before the onset of nucleation, the release of the latent heat of fusion during nucleation of particles complicates the assumption of isothermality during these experiments. Containerless processing has enabled another approach to the study of nucleation kinetics [7]. With levitation techniques it is possible to undercool one sample to nucleation repeatedly in a controlled manner, such that the statistics of the nucleation process can be derived from multiple experiments on a single sample. The authors have fully developed the analysis of nucleation experiments on single samples following the suggestions of Skripov [8]. The advantage of these experiments is that the samples are directly observable. The nucleation temperature can be measured by noncontact optical pyrometry, the mass of the sample is known, and post processing analysis can be conducted on the sample. The disadvantages are that temperature measurement must have exceptionally high precision, and it is not possible to isolate specific heterogeneous sites as in droplet dispersions.

Bayuzick, Robert J.↗

NASA NTRS1980

Ozone data and mission sampling analysis

A methodology was developed to analyze discrete data obtained from the global distribution of ozone. Statistical analysis techniques were applied to describe the distribution of data variance in terms of empirical orthogonal functions and components of spherical harmonic models. The effects of uneven data distribution and missing data were considered. Data fill based on the autocorrelation structure of the data is described. Computer coding of the analysis techniques is included.

Robbins, J. L.↗

NASA NTRS1983

Preliminary statistical studies concerning the Campos RJ sugar cane area, using LANDSAT imagery and aerial photographs

The two phase sampling technique was applied to estimate the area cultivated with sugar cane in an approximately 984 sq km pilot region of Campos. Correlation between existing aerial photography and LANDSAT data was used. The two phase sampling technique corresponded to 99.6% of the results obtained by aerial photography, taken as ground truth. This estimate has a standard deviation of 225 ha, which constitutes a coefficient of variation of 0.6%.

Parada, N. D. J.↗

NASA NTRS1974

Remote sensing techniques for mapping range sites and estimating range yield

Image interpretation procedures for determining range yield and for extrapolating range information were investigated for an area of the Pine Ridge Indian Reservation in southwestern South Dakota. Soil and vegetative data collected in the field utilizing a grid sampling design and digital film data from color infrared film and black and white films were analyzed statistically using correlation and regression techniques. The pattern recognition techniques used were K-class, mode seeking, and thresholding. The herbage yield equation derived for the detailed test site was used to predict yield for an adjacent similar field. The herbage yield estimate for the adjacent field was 1744 lbs. of dry matter per acre and was favorably compared to the mean yield of 1830 lbs. of dry matter per acre based upon ground observations. Also an inverse relationship was observed between vegetative cover and the ratio of MSS 5 to MSS 7 of ERTS-1 imagery.

Benson, L. A.↗