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At least 163 records · Page 9

Proposed characterization of tornadoes and hurricanes by area and intensity

Results of the 1968 through 1970 Tornado Watch Experiment conducted jointly by NASA and NOAA suggested the necessity of characterizing individual tornadoes in order to improve the identity of tornado-producing nephsystems. An attempt was made, therefore, to categorize each tornado by its intensity and area. Fujita-scale wind and corresponding damage categories were devised to classify tornadoes as Gale (F0), Weak (F1), Strong (F2), Severe (F3), Devastating (F4), and Incredible (F5). Additionally, individual tornado areas were also categorized as Trace (TR), Decimicro (DM), Micro (MI), Meso (ME), Marco (MA), Giant (GI), and Decagiant (DG), thus permitting characterizing of a tornado by a combination of intensity and area, such as weak decimicro tornado, severe meso tornado, or incredible giant tornado. A test characterization of 156 Japanese tornadoes in 1950-69 was accomplished for comparison with 893 U.S. tornadoes in 1965. Unexpectedly, the percentage distribution of intensity and individual area of U.S. and Japanese tornadoes is very similar except for large and/or intense ones. Intensity distribution within the Dallas and Fargo tornadoes of 1957 was also studied in detail. It was also found that the F-scale variation along the paths of family tornadoes shows an intensity oscillation with a 45-min interval.

Fujita, T. T.↗

Environment mapping with spacecraft photography: A Central Australian example

Boundary delineation from space photographs as a precursor to area typing was studied for characterization of land use for resource mapping near Alice Springs, Australia, where both boundary detection and categorization are complicated by the variations of the landscape. The detection and meaning of boundaries, and sources of confusion during categorization are discussed.

Simonett, D. S.↗

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.↗

Coastal zone classification from satellite imagery

The author has identified the following significant results. Studies of cover distribution along Delaware's coast, especially in tidal wetlands, were made, utilizing semi-automated analysis of LANDSAT-1 MSS digital data. Cover maps with eleven vegetation and other cover categories were produced with accuracy of identification above 80% in all categories. Recent studies have tested a new technique for training automated analysis which uses ground measured reflectance and atmospheric correction techniques to derive signatures for specific categories in preference to the relative radiance signatures derived from training sets within LANDSAT data itself. Initial tests using a four category scheme indicate that training data based on absolute measured reflectance and atmospheric correction of LANDSAT data can produce comparable accuracy of categorization to that achieved using more conventional relative radiance training. The analysis of the same four categories produced average categorization accuracies of 82.1% by conventional reflative radiance training and 81.9% by use of absolute reflectance signatures.

Klemas, V.↗

Classifying and monitoring water quality by use of satellite imagery

A technique in which LANDSAT measurements from very clear lakes are subtracted from measurements from other lakes in order to remove atmospheric and surface noise effects to obtain a residual signal dependent only on the material suspended in the water is described. This residual signal is used by the Multispectral Data Analysis System as a basis for producing color categorized imagery showing lakes by type and concentration of suspended material. Several hundred lakes in the Madison and Spooner, Wisconsin area were categorized for tannin or non-tannin waters and for the degree of algae, silt, weeds, and bottom effects.

Scherz, J. P.↗

An analysis and comparison of LANDSAT-1, Skylab (S-192) and aircraft data for delineation of land-water cover types of the Green Swamp, Florida

The author has identified the following significant results. LANDSAT 1 and Skylab (S192) data from the Green Swamp area of central Florida were categorized into five classes: water, cypress, other wetlands, pine, and pasture. These categories were compared with similar categories on a detailed vegetative map made using low altitude aerial photography. Agreement of LANDSAT and Skylab categorized data with the vegetation map was 87 percent and 83 percent respectively. The Green Swamp vegetative categories may be widespread but often consist of numerous small isolated areas, because LANDSAT has a greater resolution than Skylab, it is more favorable for mapping the small vegetative categories.

Higer, A. L.↗

Classifying and monitoring water quality by use of satellite imagery

A technique is developed to eliminate the atmosphere and surface noise effects on Landsat signals of water bodies by manipulating the total signal from Landsat in such a way that only the volume reflectance is left as a residual. With the Landsat signal from a lake and the known volume reflectance for its clear water it is possible to eliminate the surface and atmospheric effects and have residual signals that are indicative only of the type and concentration of the material in other lakes. Laboratory values are more precise than field values because in the field one must contend with indirect skylight and wave action which can be removed in the laboratory. The volume reflectance of distilled water or a very clear lake approaching distilled water was determined in the laboratory by the use of the Bendix radiant power measuring instrument. The Bendix multispectral data analysis system provided a color categorized image of several hundred lakes in a Wisconsin area. These lakes were categorized for tannin and nontannin waters and for the degrees of algae, silt, weeds, and bottom effects present.

Scherz, J. P.↗

Analysis of suspended solids by single-particle scattering

Light scattering by individual particulates is used in a multiple-detector system to categorize the composition of suspended solids in terms of broad particulate categories. The scattering signatures of red clay and taconite tailings, the two primary particulate contaminants in western Lake Superior, along with two types of asbestiform fibers, amphibole and chrysolite, were studied in detail. A method was developed to predict the concentration of asbestiform fibers in filtration plant samples for which electron microscope analysis was done concurrently. Fiber levels as low as 50,000 fibers/liter were optically detectable. The method has application in optical categorization of samples for remote sensing purposes and offers a fast, inexpensive means for analyzing water samples from filtration plants for specific particulate contaminants.

Diehl, S. R.↗

Study of sensor spectral responses and data processing algorithms and architectures for onboard feature identification

A computational model of the deterministic and stochastic processes involved in remote sensing is used to study spectral feature identification techniques for real-time onboard processing of data acquired with advanced earth-resources sensors. Preliminary results indicate that: Narrow spectral responses are advantageous; signal normalization improves mean-square distance (MSD) classification accuracy but tends to degrade maximum-likelihood (MLH) classification accuracy; and MSD classification of normalized signals performs better than the computationally more complex MLH classification when imaging conditions change appreciably from those conditions during which reference data were acquired. The results also indicate that autonomous categorization of TM signals into vegetation, bare land, water, snow and clouds can be accomplished with adequate reliability for many applications over a reasonably wide range of imaging conditions. However, further analysis is required to develop computationally efficient boundary approximation algorithms for such categorization.

Huck, F. O.↗

Elicitation of motion sickness by head movements in the microgravity phase of parabolic flight maneuvers

Susceptibility to motion sickness was tested in 44 subjects during parabolic flight maneuvers in a KC-135 aircraft. The subjects were categorized as: (1) insusceptible; (2) moderately susceptible; or (3) highly susceptible to motion sickness during exposure to varying degrees of gravito-inertial force. After categorization, three types of head movements were evaluated to determine the effect on the subjects' baseline susceptibility. Ten cycles of head movements were made in three different parabolas until nausea was reached or 40 parabolas had been completed. All types of head movements significantly increased susceptibility for all categories; eyes-open conditions were always more stressful than eyes-closed conditions for each type of head movement. It is concluded that head movements in microgravity can elicit symptoms of motion sickness. It is suggested that head movements play an etiological role in space motion sickness. In ground based studies where head movements are necessary to elicit symptoms, they are also necessary to elicit adaptation to the microgravity environment.

Lackner, J. R.↗

Color measurement and discrimination

Theories of color measurement attempt to provide a quantative means for predicting whether two lights will be discriminable to an average observer. All color measurement theories can be characterized as follows: suppose lights a and b evoke responses from three color channels characterized as vectors, v(a) and v(b); the vector difference v(a) - v(b) corresponds to a set of channel responses that would be generated by some real light, call it *. According to theory a and b will be discriminable when * is detectable. A detailed development and test of the classic color measurement approach are reported. In the absence of a luminance component in the test stimuli, a and b, the theory holds well. In the presence of a luminance component, the theory is clearly false. When a luminance component is present discrimination judgements depend largely on whether the lights being discriminated fall in separate, categorical regions of color space. The results suggest that sensory estimation of surface color uses different methods, and the choice of method depends upon properties of the image. When there is significant luminance variation a categorical method is used, while in the absence of significant luminance variation judgments are continuous and consistant with the measurement approach.

Wandell, B. A.↗

Grid generation for the solution of partial differential equations

A general survey of grid generators is presented with a concern for understanding why grids are necessary, how they are applied, and how they are generated. After an examination of the need for meshes, the overall applications setting is established with a categorization of the various connectivity patterns. This is split between structured grids and unstructured meshes. Altogether, the categorization establishes the foundation upon which grid generation techniques are developed. The two primary categories are algebraic techniques and partial differential equation techniques. These are each split into basic parts, and accordingly are individually examined in some detail. In the process, the interrelations between the various parts are accented. From the established background in the primary techniques, consideration is shifted to the topic of interactive grid generation and then to adaptive meshes. The setting for adaptivity is established with a suitable means to monitor severe solution behavior. Adaptive grids are considered first and are followed by adaptive triangular meshes. Then the consideration shifts to the temporal coupling between grid generators and PDE-solvers. To conclude, a reflection upon the discussion, herein, is given.

Eiseman, Peter R.↗

Grid generation for the solution of partial differential equations

A general survey of grid generators is presented with a concern for understanding why grids are necessary, how they are applied, and how they are generated. After an examination of the need for meshes, the overall applications setting is established with a categorization of the various connectivity patterns. This is split between structured grids and unstructured meshes. Altogether, the categorization establishes the foundation upon which grid generation techniques are developed. The two primary categories are algebraic techniques and partial differential equation techniques. These are each split into basic parts, and accordingly are individually examined in some detail. In the process, the interrelations between the various parts are accented. From the established background in the primary techniques, consideration is shifted to the topic of interactive grid generation and then to adaptive meshes. The setting for adaptivity is established with a suitable means to monitor severe solution behavior. Adaptive grids are considered first and are followed by adaptive triangular meshes. Then the consideration shifts to the temporal coupling between grid generators and PDE-solvers. To conclude, a reflection upon the discussion, herein, is given.

Eiseman, Peter R.↗

Detection and avoidance of errors in computer software

The acceptance test errors of a computer software project to determine if the errors could be detected or avoided in earlier phases of development. GROAGSS (Gamma Ray Observatory Attitude Ground Support System) was selected as the software project to be examined. The development of the software followed the standard Flight Dynamics Software Development methods. GROAGSS was developed between August 1985 and April 1989. The project is approximately 250,000 lines of code of which approximately 43,000 lines are reused from previous projects. GROAGSS had a total of 1715 Change Report Forms (CRFs) submitted during the entire development and testing. These changes contained 936 errors. Of these 936 errors, 374 were found during the acceptance testing. These acceptance test errors were first categorized into methods of avoidance including: more clearly written requirements; detail review; code reading; structural unit testing; and functional system integration testing. The errors were later broken down in terms of effort to detect and correct, class of error, and probability that the prescribed detection method would be successful. These determinations were based on Software Engineering Laboratory (SEL) documents and interviews with the project programmers. A summary of the results of the categorizations is presented. The number of programming errors at the beginning of acceptance testing can be significantly reduced. The results of the existing development methodology are examined for ways of improvements. A basis is provided for the definition is a new development/testing paradigm. Monitoring of the new scheme will objectively determine its effectiveness on avoiding and detecting errors.

Kinsler, Les↗

Self-organization via active exploration in robotic applications

We describe a neural network based robotic system. Unlike traditional robotic systems, our approach focussed on non-stationary problems. We indicate that self-organization capability is necessary for any system to operate successfully in a non-stationary environment. We suggest that self-organization should be based on an active exploration process. We investigated neural architectures having novelty sensitivity, selective attention, reinforcement learning, habit formation, flexible criteria categorization properties and analyzed the resulting behavior (consisting of an intelligent initiation of exploration) by computer simulations. While various computer vision researchers acknowledged recently the importance of active processes (Swain and Stricker, 1991), the proposed approaches within the new framework still suffer from a lack of self-organization (Aloimonos and Bandyopadhyay, 1987; Bajcsy, 1988). A self-organizing, neural network based robot (MAVIN) has been recently proposed (Baloch and Waxman, 1991). This robot has the capability of position, size rotation invariant pattern categorization, recognition and pavlovian conditioning. Our robot does not have initially invariant processing properties. The reason for this is the emphasis we put on active exploration. We maintain the point of view that such invariant properties emerge from an internalization of exploratory sensory-motor activity. Rather than coding the equilibria of such mental capabilities, we are seeking to capture its dynamics to understand on the one hand how the emergence of such invariances is possible and on the other hand the dynamics that lead to these invariances. The second point is crucial for an adaptive robot to acquire new invariances in non-stationary environments, as demonstrated by the inverting glass experiments of Helmholtz. We will introduce Pavlovian conditioning circuits in our future work for the precise objective of achieving the generation, coordination, and internalization of sequence of actions.

Ogmen, H.↗

The structure and formation of natural categories

Categorization and concept formation are critical activities of intelligence. These processes and the conceptual structures that support them raise important issues at the interface of cognitive psychology and artificial intelligence. The work presumes that advances in these and other areas are best facilitated by research methodologies that reward interdisciplinary interaction. In particular, a computational model is described of concept formation and categorization that exploits a rational analysis of basic level effects by Gluck and Corter. Their work provides a clean prescription of human category preferences that is adapted to the task of concept learning. Also, their analysis was extended to account for typicality and fan effects, and speculate on how the concept formation strategies might be extended to other facets of intelligence, such as problem solving.

Fisher, Douglas↗

Ageing airplane repair assessment program for Airbus A300

Summary as a result of a commitment between the FAA and ATA the Airworthiness Assurance Task Force (AATF) steering committee requested the transport aircraft manufacturers to develop a program to assess the repairs on in-service aircraft since recent Supplemental Structural Inspection Programs (SSIP) had not been addressed to assessing repairs. The intent of the assessment program is to remove all existing ambiguities and to achieve a sufficient level of safety across the fleet by applying actual fatigue and damage tolerance criteria defined by FAR 25.571 to repaired structures. A general three stage program has been developed with major aircraft manufacturers and airlines cooperation including area/component classification, repair categorization and inspection/removal requirement establishment which is the basis for model specific repair assessment programs. This paper describes the current status of the repair categorization activities and includes all details about the methodologies developed for determination of the inspection program for the skin on pressurized fuselages. For inspection threshold determination two methods are defined based on fatigue life approach, i.e. a simplified and a detailed method. The detailed method considers 15 different parameters to assess the influences of material, geometry, size, location, aircraft usage and workmanship on the fatigue life of the repair and the original structure. For definition of the inspection intervals a general method is developed which applies to all concerned repairs. For this the initial flaw concept is used by considering 6 parameters and the detectable flaw sizes depending on proposed nondestructive inspection methods. An alternative method is provided for small repairs allowing visual inspection with shorter intervals.

Aging Aircraft↗

Prelaunch processing scientific payloads since Challenger - Lessons learned exercise

The 'lessons learned' process that follows each NASA payload-processing operation is described with attention given to the development of a knowledge base from the results. The process is based on the subjective evaluation of operations problems by test-team members following a mission. The lessons learned from four Space Shuttle missions - STS-26R, -29R, -30R, and -30 - are examined with categorizations of incidents which is based on operational, documentation, hardware, and software categories. Recommendations for ways to address the incidents are categorized similarly, with operational categories such as admonitory, documentation modifications, and support changes. A basic numerical dataset is developed based on the results, and the data show that STS-26R had the highest number of incidents. The process is found to be an effective educational tool in payload-processing operations because it disseminates key individual experiences.

Schuiling, R. L.↗