High-speed data system performance and error statistics at 4800 bps
GCF high-speed data system performance and error statistics at 4800 bps
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GCF high-speed data system performance and error statistics at 4800 bps
A statistical survey and a preliminary analysis are made of icing data collected from scheduled flights over the United States and Canada from November 1951 to June 1952 by airline aircraft equipped with NACA pressure-type icing-rate meters. This interim report presents information obtained from a continuing program sponsored by the NACA with the cooperation of the airlines. An analysis of over 600 icing encounters logged by three airlines operating in the United States, one operating in Canada and one operating up the coast to Alaska, is presented. The icing conditions encountered provided relative frequencies of many icing-cloud variables, such as horizontal extent, vertical thickness, temperatures, icing rate, liquid-water content, and total ice accumulation. Liquid-water contents were higher than data from earlier research flights in layer-type clouds but slightly lower than previous data from cumulus clouds. Broken-cloud conditions, indicated by intermittent icing, accounted for nearly one-half of all the icing encounters. About 90 percent of the encounters did not exceed a distance of 120 miles, and continuous icing did not exceed 50 miles for 90 percent of the unbroken conditions. Icing cloud thicknesses measured during climbs and descents were less than 4500 feet for 90 percent of the vertical cloud traverses.
The author has identified the following significant results. Wheat area, yield, and production statistics as derived from satellite image analysis, combined with a weather model, are presented for a ten county area in southwest Kansas. The data (representing the 1972-73 crop year) are compared for accuracy against both the USDA August estimate and its final (official) tabulation. The area estimates from imagery for both dryland and irrigated winter wheat were within 5% of the official figures for the same area, and predated them by almost one year. Yield on dryland wheat was estimated by the Thompson weather model to within 0.1% of the observed yield. A combined irrigated and dryland wheat production estimate for the ten county area was completed in July, 1973 and was within 1% of the production reported by USDA in February, 1974.
Data reduction and analysis procedures are discussed along with the physical and statistical descriptors used. The statistical modeling techniques are outlined and examples of the derived statistical characterization of rain cells in terms of the several physical descriptors are presented. Recommendations concerning analyses which can be pursued using the data base collected during the experiment are included.
Two statistical models are compared in the classification of crops recorded on color aerial photographs. A theory of error ellipses is applied to the pattern recognition problem. An elliptical boundary condition classification model (EBC), useful for recognition of candidate patterns, evolves out of error ellipse theory. The EBC model is compared with the minimum distance to the mean (MDM) classification model in terms of pattern recognition ability. The pattern recognition results of both models are interpreted graphically using scatter diagrams to represent measurement space. Measurement space, for this report, is determined by optical density measurements collected from Kodak Ektachrome Infrared Aero Film 8443 (EIR). The EBC model is shown to be a significant improvement over the MDM model.
Infrared data from GOES and HCMM satellites for areas in northern central and southern Florida were compared for February 1, 1979 to examine spatial variations of surface temperatures within GOES pixels using nested HCMM pixel surface temperatures. Standard deviations of HCMM pixel temperatures associated with mean temperature of a GOES pixel temperature during this period were found to be smallest for homogeneous water surfaces (about 0.5 K), to be slightly larger for homogeneous land surfaces (about 0.1 K), and to range up as high as 3.5 K for mixed water-land surfaces.
Commercially available software packages today allow users to quickly perform the routine evaluations of (1) descriptive statistics to numerically and graphically summarize both sample and population data, (2) inferential statistics that draws conclusions about a given population from samples taken of it, (3) probability determinations that can be used to generate estimates of reliability allowables, and finally (4) the setup of designed experiments and analysis of their data to identify significant material and process characteristics for application in both product manufacturing and performance enhancement. This paper presents examples of analysis and experimental design work that has been conducted using Statgraphics®(Registered Trademark) statistical software to obtain useful information with regard to solid rocket motor propellants and internal insulation material. Data were obtained from a number of programs (Shuttle, Constellation, and Space Launch System) and sources that include solid propellant burn rate strands, tensile specimens, sub‐scale test motors, full‐scale operational motors, rubber insulation specimens, and sub‐scale rubber insulation analog samples. Besides facilitating the experimental design process to yield meaningful results, statistical software has demonstrated its ability to quickly perform complex data analyses and yield significant findings that might otherwise have gone unnoticed. One caveat to these successes is that useful results not only derive from the inherent power of the software package, but also from the skill and understanding of the data analyst.
Due to the common use of Flash technology in many commercial and industrial Programmable Logic Devices (PLDs) such as FPGAs and mixed-signal microcontrollers, flash technology is being utilized in fuzed munition applications. This presents a long-term reliability issue for both DoD and NASA safety- and mission-critical applications. A thorough understanding of the data retention failure modes and statistics associated with Flash data retention is of vital concern to the fuze safety community. A key retention parameter for a flash cell is the threshold voltage (VTH), which is an indirect indicator of the amount of charge stored on the cells floating gate. Initial test results based on a study of charge loss in flash cells in an FPGA device is presented. Statistical data taken from a small sample set indicates quantifiable charge loss for devices stored at both room temperature and 150 C. Initial evaluation of the distribution of threshold voltage in a large sample set (800 devices) is presented. The magnitude of charge loss from exposure to electrostatic discharge and electromagnetic fields is measured and presented. Simulated data (and measured data as available) resultant from harsh-environment testing (neutron, heavy ion, EMP) is presented.
Due to the common use of Flash technology in many commercial and industrial Programmable Logic Devices (PLDs) such as FPGAs and mixed-signal microcontrollers, flash technology is being utilized in fuzed munition applications. This presents a long-term reliability issue for both DoD and NASA safety- and mission-critical applications. A thorough understanding of the data retention failure modes and statistics associated with Flash data retention is of vital concern to the fuze safety community. A key retention parameter for a flash cell is the threshold voltage (VTH), which is an indirect indicator of the amount of charge stored on the cells floating gate. Initial test results based on a study of charge loss in flash cells in an FPGA device is presented. Statistical data taken from a small sample set indicates quantifiable charge loss for devices stored at both room temperature and 150 C. Initial evaluation of the distribution of threshold voltage in a large sample set (800 devices) is presented. The magnitude of charge loss from exposure to electrostatic discharge and electromagnetic fields is measured and presented. Simulated data (and measured data as available) resultant from harsh-environment testing (neutron, heavy ion, EMP) is presented.
A series of flight tests and fast-time simulations were conducted, using the augmentor wing jet STOL research aircraft and the STOLAND 4D-RNAV system to add to the growing data base of 4D-RNAV system performance capabilities. To obtain statistically meaningful data a limited amount of flight data were supplemented by a statistically significant amount of data obtained from fast-time simulation. The results of these tests are reported. Included are comparisons of the 4D-RNAV estimated winds with actual winds encountered in flight, as well as data on along-track navigation and guidance errors, and time-of-arrival errors at the final approach waypoint. In addition, a slight improvement of the STOLAND 4D-RNAV system is proposed and demonstrated, using the fast-time simulation.
Aerospace vehicles are produced in limited quantities that do not always allow development of MIL-HDBK-5 A-basis design allowables. One method of examining production and composition variations is to perform 100% lot acceptance testing for aerospace Aluminum (Al) alloys. This paper discusses statistical trends seen in strength data for one Al alloy. A four-step approach reduced the data to residuals, visualized residuals as a function of time, grouped data with quantified scatter, and conducted analysis of variance (ANOVA).
Aerospace vehicles are produced in limited quantities that do not always allow development of MIL-HDBK-5 A-basis design allowables. One method of examining production and composition variations is to perform 100% lot acceptance testing for aerospace Aluminum (Al) alloys. This paper discusses statistical trends seen in strength data for one Al alloy. A four-step approach reduced the data to residuals, visualized residuals as a function of time, grouped data with quantified scatter, and conducted analysis of variance (ANOVA).
The minutes and associated documents prepared from presentations and meetings at the Fifth Calibration/Data Product Validation Panel meeting in Boulder, Colorado, April 8 - 10, 1992, are presented. Key issues include (1) statistical characterization of data sets: finding statistics that characterize key attributes of the data sets, and defining ways to characterize the comparisons among data sets; (2) selection of specific intercomparison exercises: selecting characteristic spatial and temporal regions for intercomparisons, and impact of validation exercises on the logistics of current and planned field campaigns and model runs; and (3) preparation of data sets for intercomparisons: characterization of assumptions, transportable data formats, labeling data files, content of data sets, and data storage and distribution (EOSDIS interface).
We are developing tools needed to enable the validation of the Geostationary Lightning Mapper (GLM). In order to develop and test these tools, we have need of a robust, high-fidelity set of GLM proxy data. Many steps have been taken to ensure that the proxy data are high quality. LIS is the closest analog that exists for GLM, so it has been used extensively in developing the GLM proxy. We have verified the proxy data both statistically and algorithmically. The proxy data are pixel (event) data, called Level 1B. These data were then clustered into flashes by the Lightning Cluster-Filter Algorithm (LCFA), generating proxy Level 2 data. These were then compared with the data used to generate the proxy, and both the proxy data and the LCFA were validated. We have developed tools to allow us to visualize and compare the GLM proxy data with several other sources of lightning and other meteorological data (the so-called shallow-dive tool). The shallow-dive tool shows storm-level data and can ingest many different ground-based lightning detection networks, including: NLDN, LMA, WWLLN, and ENTLN. These are presented in a way such that it can be seen if the GLM is properly detecting the lightning in location and time comparable to the ground-based networks. Currently in development is the deep-dive tool, which will allow us to dive into the GLM data, down to flash, group and event level. This will allow us to assess performance in comparison with other data sources, and tell us if there are detection, timing, or geolocation problems. These tools will be compatible with the GLM Level-2 data format, so they can be used beginning on Day 0.
Statistical analysis of photographic meteor data - Opiks luminous efficiency and supplemented Whipple weighting
Statistical analysis of photographic meteor data - Vernianis luminous efficiency and supplemented Whipple weighting
Compound decision theory is employed to develop a general statistical model for classifying image data using spatial context. The classification algorithm developed from this model exploits the tendency of certain ground-cover classes to occur more frequently in some spatial contexts than in others. A key input to this contextural classifier is a quantitative characterization of this tendency: the context function. Several methods for estimating the context function are explored, and two complementary methods are recommended. The contextural classifier is shown to produce substantial improvements in classification accuracy compared to the accuracy produced by a non-contextural uniform-priors maximum likelihood classifier when these methods of estimating the context function are used. An approximate algorithm, which cuts computational requirements by over one-half, is presented. The search for an optimal implementation is furthered by an exploration of the relative merits of using spectral classes or information classes for classification and/or context function estimation.
The Visual Data Analysis Package is a collection of programs and scripts that facilitate visual analysis of data available from NASA and NOAA satellites, as well as dropsonde, buoy, and conventional in-situ observations. The package features utilities for data extraction, data quality control, statistical analysis, and data visualization. The Hierarchical Data Format (HDF) satellite data extraction routines from NASA's Jet Propulsion Laboratory were customized for specific spatial coverage and file input/output. Statistical analysis includes the calculation of the relative error, the absolute error, and the root mean square error. Other capabilities include curve fitting through the data points to fill in missing data points between satellite passes or where clouds obscure satellite data. For data visualization, the software provides customizable Generic Mapping Tool (GMT) scripts to generate difference maps, scatter plots, line plots, vector plots, histograms, timeseries, and color fill images.