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At least 361 records · Page 20

Distortions in memory for visual displays

Systematic errors in perception and memory present a challenge to theories of perception and memory and to applied psychologists interested in overcoming them as well. A number of systematic errors in memory for maps and graphs are reviewed, and they are accounted for by an analysis of the perceptual processing presumed to occur in comprehension of maps and graphs. Visual stimuli, like verbal stimuli, are organized in comprehension and memory. For visual stimuli, the organization is a consequence of perceptual processing, which is bottom-up or data-driven in its earlier stages, but top-down and affected by conceptual knowledge later on. Segregation of figure from ground is an early process, and figure recognition later; for both, symmetry is a rapidly detected and ecologically valid cue. Once isolated, figures are organized relative to one another and relative to a frame of reference. Both perceptual (e.g., salience) and conceptual factors (e.g., significance) seem likely to affect selection of a reference frame. Consistent with the analysis, subjects perceived and remembered curves in graphs and rivers in maps as more symmetric than they actually were. Symmetry, useful for detecting and recognizing figures, distorts map and graph figures alike. Top-down processes also seem to operate in that calling attention to the symmetry vs. asymmetry of a slightly asymmetric curve yielded memory errors in the direction of the description. Conceptual frame of reference effects were demonstrated in memory for lines embedded in graphs. In earlier work, the orientation of map figures was distorted in memory toward horizontal or vertical. In recent work, graph lines, but not map lines, were remembered as closer to an imaginary 45 deg line than they had been. Reference frames are determined by both perceptual and conceptual factors, leading to selection of the canonical axes as a reference frame in maps, but selection of the imaginary 45 deg as a reference frame in graphs.

Tversky, Barbara↗

Automated Recognition of 3D Features in GPIR Images

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a directed-graph data structure. Relative to past approaches, this multiaxis approach offers the advantages of more reliable detections, better discrimination of objects, and provision of redundant information, which can be helpful in filling gaps in feature recognition by one of the component algorithms. The image-processing class also includes postprocessing algorithms that enhance identified features to prepare them for further scrutiny by human analysts (see figure). Enhancement of images as a postprocessing step is a significant departure from traditional practice, in which enhancement of images is a preprocessing step.

Park, Han↗

Global Geochemical Variation on the Lunar Surface: A Three-Element Approach

We present a method for displaying the relative abundances of three important elements (Th, Fe, and Ti) on the same map projection of the lunar surface. Using Th-, Fe-, and Ti-elemental abundances from orbital geochemical data and assigning each element a primary color, a false-color map of the lunar surface was created. This approach is similar to the ternary diagram approach presented by Davis and Spudis with some important differences, discussed later. For the present maps, Th abundances were measured by the Lunar Prospector (LP) Gamma-Ray Spectrometer(GRS).The new LPGRS low-altitude dataset was used in this analysis. Iron and Ti weight percentages were based on Clementine spectral reflectance data smoothed to the LP low altitude footprint. This method of presentation was designed to aid in the location and recognition of three principal lunar compositions: ferroan anorthosite (FAN), mare basalts (MB), and the Mg suite/ KREEP-rich rocks on the lunar surface, with special emphasis on the highlands and specific impact basins. In addition to the recognition of these endmember rock compositions, this method is an attempt to examine the relationship between elemental compositions that do not conform readily to previously accepted or observed endmember rocks in various specific regions of interest, including eastern highlands regions centered on 150 deg longitude, and a northern highlands Th-rich region observed. The LP low-altitude data has full width at half-maximum spatial resolution of about 40 km. The Clementine spectral reflectance datasets were adapted using an equal-area, gaussian smoothing routine to this footprint. In addition, these datasets, reported in weight percent of FeO and of Ti02, were adjusted to Fe and Ti weight percentages. Each dataset was then assigned one of the three primary colors: blue for Th, red for Fe, and green for Ti. For each element, the data range was normalized to represent the ratio of each point to the maximum in the dataset. (To view the color table, go to http://cass.jsc.nasa.gov/meetings/moon99/pdf/8033.pdf.) The full range of lunar longitudes is represented, but due to the lack of coverage of the Clementine data for latitudes > 70 deg and <-70 deg, the data for these regions is excluded. The differences between this approach and the ternary diagram approach of Davis and Spudis eliminate some of the uncertainty and ambiguity of the ternary diagram approach. Rather than using a ratio of Th to Ti normalized to CI chondritic ratios, and a ternary diagram with ternary apexes located at specific endmember compositional values, elemental compositions were used independently, eliminating the errors resulting from dividing numbers that can have high uncertainties, especially at low concentration. The three elements used in this method of presentation were chosen for several reasons. One reason for the inclusion of Th in this study is that it is an accurate indicator of KREEP. Iron and Ti concentrations are both low in highland regolith, causing any small fluctuations in Th to stand out very well. In addition, Fe and Ti are good compositional indicators of different mare basalts. Mixed with red for Fe, the green for Ti produces a yellow signal in high-Ti basalts. While universally high in Fe relative to the surrounding highlands, mare basalts have a diverse range of Ti values, making Ti concentration a valuable asset to the classification and identification of different basalt types. Finally, an important constraint in element selection is the availability of the global data, both from LP and Clementine results. Data for Th, Fe, and Ti are among the highest quality of existing lunar remote-sensing data. In addition, LP data for Fe and Ti will become available, enabling these data to be incorporated into the analysis. Using upper-limit values for end member rock compositions calculated from Korotev et al., attempts were made to locate the different endmember compositions of terranes on this diagram. Most strikingly, ferroan anorthosite (Th < and = 0.37 micro g/g; Fe (wt%)< and =2.29; Ti (wt%) < and = 0.22), which should appear as an almost black, reddish color, does not appear on the diagram at any noticeable frequency. Based on this analysis, the suggestion of extensive FAN regions on the lunar surface is not strong, especially at the presently accepted values for Fe and Th. However, to make sure this effect is not due to systematic errors, a thorough investigation of the precision, accuracy, and uncertainties of the Fe, Ti, and Th abundances needs to be carried out, especially at low concentrations. A particular region of interest is an area of high Th concentrations relative to Fe and Ti content north and east of Humboldtianum Crater. First observed by Lawrence et al., this region does not coincide with any visible impact structure and comprises one of the closest approximations to pure blue (high Th, very low Ti and Fe) on the lunar surface. Such an elemental composition does not lend itself readily to classification, and presents something of an anomaly. More detailed analysis of this region is needed to understand its structure and origin. There seems to be a longitudinal asymmetry in the Th concentrations of the highlands regolith. High-Th, low-Ti, and Fe regions are located between 135 deg and 180 deg longitude and between -30 deg and +30 deg latitude. While the Th levels are not high enough to attract attention in a single elemental display, the variation in the abundance of Th relative to Fe and Ti abundances can be clearly seen. The composition that these data suggest is not well represented in the sample return suite. In addition, these regions were largely missed by the Apollo orbital ground tracks, which only covered the outer edge of the areas of interest. The LP orbital Th data represent the first information about the Th concentrations in these regions of the highlands. Additional information contained in original.

Thomsen, D. R.↗

Morphological Analysis of Annual Recurrence of Dark Dune Spots on Southern Polar Region of Mars

Analysis of the Mars Global Surveyor narrow-angle images of the dark dune spots (DDSs) in three subsequent Martian winters and springs in Southern Polar Region resulted in the recognition that year by year DDSs reappeared on the same place with almost the same configuration. Comparison of the 1999 and 2001 high-resolution images showed a very interest recovery process.

Horvath, A.↗

Detailed Evaluation of MODIS Fire Radiative Power Measurements

Satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP) from open biomass burning, which affects many vegetated regions of the world on a seasonal basis. Knowledge of the biomass burning characteristics and emission source strengths of different (particulate and gaseous) smoke constituents is one of the principal ingredients upon which the assessment, modeling, and forecasting of their distribution and impacts depend. This knowledge can be gained through accurate measurement of FRP, which has been shown to have a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. Over the last decade or so, FRP has been routinely measured from space by both the MODIS sensors aboard the polar orbiting Terra and Aqua satellites, and the SEVIRI sensor aboard the Meteosat Second Generation (MSG) geostationary satellite. During the last few years, FRP has been gaining recognition as an important parameter for facilitating the development of various scientific studies relating to the quantitative characterization of biomass burning and their emissions. Therefore, we are conducting a detailed analysis of the FRP products from MODIS to characterize the uncertainties associated with them, such as those due to the MODIS bow-tie effects and other factors, in order to establish their error budget for use in scientific research and applications. In this presentation, we will show preliminary results of the MODIS FRP data analysis, including comparisons with airborne measurements.

Ichoku, Charles↗

Increased Intracranial Pressure and Visual Impairment Associated with Long-Duration Spaceflight

Although humans have been flying in space since the 1960s, more recent missions have revealed a new suite of physiological adaptations and consequences of space flight. Notably, 60% of long-duration crewmembers (ISS/MIR) and >25% of short-duration (Shuttle) crewmembers have reported subjective degradation in vision (based on debrief comments) (Gibson 2011). Decreased near-visual acuity was demonstrated in 46% of ISS/Mir and 21% of Shuttle crewmembers, resulting in a shift of up to 1-2 diopters in their refractive correction. It is likely that the recently revealed ophthalmic changes have been present since the first days of human space flight, but have been overlooked or attributed to other causations. The reported changes in vision have occurred at various time points throughout missions, with ranging degrees of visual degradation. Although some cases resolved upon return to Earth, several astronauts have not regained preflight visual acuity, indicating that the damage may be permanent. While observing these changes over the years, without other overt symptomology and with the given age range of the flying population, this has largely been attributed to an expected hyperopic shift due to aging. However, the availability of onboard analysis techniques, including visual acuity assessments, retinal imagery, and ultrasounds of the eye and optic nerve tracts, along with more detailed post-flight techniques, has led to the recent recognition of a wider syndrome. Along with vision changes, findings include flattening of the globe, swelling of the optic disc (papilledema), choroidal folds in the retina, swelling of the optic nerve sheath, and visual field defects. It is widely hypothesized that this constellation of findings may be explained by an elevation of intracranial pressure (ICP). Out of the 60% of long-duration astronauts that have reported a subjective degradation in vision, a subset (currently 10 astronauts) have developed this syndrome. The National Aeronautics and Space Administration (NASA) has made it a high priority to understand this syndrome and provide mitigation techniques to protect crewmembers from visual impairment. While there are many possible factors that could contribute to intracranial hypertension associated with spaceflight, the relative contribution of these, as well as the processes by which eye damage occurs as a result of intracranial hypertension, are not fully understood. The observed pathophysiological phenomena are extremely complex and it is likely that multiple factors contribute to their incidence, rather than one simple mechanism. This paper will define and examine the findings in detail, and expound upon the potential contributing factors and their relative contribution to this syndrome.

Marshall-Bowman, Karina↗

Supervised Learning Applied to Air Traffic Trajectory Classification

Given the recent increase of interest in introducing new vehicle types and missions into the National Airspace System, a transition towards a more autonomous air traffic control system is required in order to enable and handle increased density and complexity. This paper presents an exploratory effort of the needed autonomous capabilities by exploring supervised learning techniques in the context of aircraft trajectories. In particular, it focuses on the application of machine learning algorithms and neural network models to a runway recognition trajectory-classification study. It investigates the applicability and effectiveness of various classifiers using datasets containing trajectory records for a month of air traffic. A feature importance and sensitivity analysis are conducted to challenge the chosen time-based datasets and the ten selected features. The study demonstrates that classification accuracy levels of 90% and above can be reached in less than 40 seconds of training for most machine learning classifiers when one track data point, described by the ten selected features at a particular time step, per trajectory is used as input. It also shows that neural network models can achieve similar accuracy levels but at higher training time costs.

Bosson, Christabelle S.↗

Supervised Learning Applied to Air Traffic Trajectory Classification

Given the recent increase of interest in introducing new vehicle types and missions into the National Airspace System, a transition towards a more autonomous air traffic control system is required in order to enable and handle increased density and complexity. This paper presents an exploratory effort of the needed autonomous capabilities by exploring supervised learning techniques in the context of aircraft trajectories. In particular, it focuses on the application of machine learning algorithms and neural network models to a runway recognition trajectory-classification study. It investigates the applicability and effectiveness of various classifiers using datasets containing trajectory records for a month of air traffic. A feature importance and sensitivity analysis are conducted to challenge the chosen time-based datasets and the ten selected features. The study demonstrates that classification accuracy levels of 90% and above can be reached in less than 40 seconds of training for most machine learning classifiers when one track data point, described by the ten selected features at a particular time step, per trajectory is used as input. It also shows that neural network models can achieve similar accuracy levels but at higher training time costs.

Bosson, Christabelle↗

A sustainable cobalt separation with validation by techno-economic analysis and life-cycle assessment

Sustainable, cost-effective cobalt/nickel separations chemistry contributes to the realization of economically competitive lithium-ion battery recycling, as well as primary mining of cobalt and nickel. Such improvements can address supply chain challenges for cobalt, a critical element. Herein, we disclose a simple method for separating Co/Ni by second coordination-sphere molecular recognition. Selective cobalt precipitation is achieved using carbonate ions in an ammonia solution due to the outer-sphere, hydrogen bonding interactions between [Co(NH 3 ) 6 ] 3+ and CO 3 2− , evaluated with density functional theory calculations. We demonstrate this method on mixtures of Co/Ni chlorides comprising a 10-fold excess of Ni and provide comparisons with ore-processing systems. High purities (99.4(3)% Co; 98.2(4)% Ni) and recoveries (77(8)% Co; ∼100% Ni) were observed for both Co- and Ni-enriched products using optimized conditions. In conclusion, this method is potentially economically competitive based on initial techno-economic analysis (TEA) and life-cycle assessment (LCA) that also illustrate advantages in terms of sustainability.

cobalt↗

DECOVALEX-2023: An international collaboration for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems

The DECOVALEX initiative is an international research collaboration (www.decovalex.org), initiated in 1992, for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems. DECOVALEX stands for “DEvelopment of COupled Models and VALidation against EXperiments”. The creation of this international initiative was motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. DECOVALEX emphasizes joint analysis and comparative modeling of the complex perturbations and coupled processes in geologic repositories and how these impact long-term performance predictions. The most recent phase of the DECOVALEX Project, here referred to as DECOVALEX-2023, started in early 2020 and ended in late 2023. More than fifty research teams associated with 17 international DECOVALEX partner organizations participated in the comparative evaluation of eight modeling tasks covering a wide range of spatial and temporal scales, geological formations, and coupled processes. This Virtual Special Issue on DECOVALEX-2023 provides an in-depth overview of these collaborative research efforts and how these have advanced the state-of-the-art of understanding and modeling coupled THMC processes. While primarily focused on radioactive waste, much of the work included here has wider application to many geoengineering topics.

Coupled processes↗

Ring Image Analyzer

Ring Image Analyzer software analyzes images to recognize elliptical patterns. It determines the ellipse parameters (axes ratio, centroid coordinate, tilt angle). The program attempts to recognize elliptical fringes (e.g., Newton Rings) on a photograph and determine their centroid position, the short-to-long-axis ratio, and the angle of rotation of the long axis relative to the horizontal direction on the photograph. These capabilities are important in interferometric imaging and control of surfaces. In particular, this program has been developed and applied for determining the rim shape of precision-machined optical whispering gallery mode resonators. The program relies on a unique image recognition algorithm aimed at recognizing elliptical shapes, but can be easily adapted to other geometric shapes. It is robust against non-elliptical details of the image and against noise. Interferometric analysis of precision-machined surfaces remains an important technological instrument in hardware development and quality analysis. This software automates and increases the accuracy of this technique. The software has been developed for the needs of an R&TD-funded project and has become an important asset for the future research proposal to NASA as well as other agencies.

Strekalov, Dmitry V.↗

Pattern-recognition techniques applied to performance monitoring of the DSS 13 34-meter antenna control assembly

The results of applying pattern recognition techniques to diagnose fault conditions in the pointing system of one of the Deep Space network's large antennas, the DSS 13 34-meter structure, are discussed. A previous article described an experiment whereby a neural network technique was used to identify fault classes by using data obtained from a simulation model of the Deep Space Network (DSN) 70-meter antenna system. Described here is the extension of these classification techniques to the analysis of real data from the field. The general architecture and philosophy of an autonomous monitoring paradigm is described and classification results are discussed and analyzed in this context. Key features of this approach include a probabilistic time-varying context model, the effective integration of signal processing and system identification techniques with pattern recognition algorithms, and the ability to calibrate the system given limited amounts of training data. Reported here are recognition accuracies in the 97 to 98 percent range for the particular fault classes included in the experiments.

Mellstrom, J. A.↗

ERIM progress report on use of ERTS-1 data: Summary report of work on ten tasks

The author has identified the following significant results. Several of the tasks have produced significant results which are summarized: (1) Absolute water depth can be calculated from a ratio of signals from bands MSS 4 and MSS 5. (2) A 13 category terrain feature classification map of Yellowstone National Park has been produced using supervised pattern recognition techniques. (3) ERTS-1 data has been shown to provide a detection and monitoring capability for a number of water quality problems associated with off-shore ocean dumping sites and inland lakes. (4) A corrected ratio of bands MSS-5 and MSS-7 signals has been formed. (5) A concise format has been devised for storing the ratio signatures of geologic rock and mineral materials determined from laboratory reflectance spectra. (6) Results of work in information extraction demonstrate: signal variability exists among ERTS-1 detectors in any one spectral band that will impact users doing quantitative analysis on successive ERTS-1 images; a newly developed computer-aided procedure for correlating ERTS-1 pixels to ground features; the strong influence of atmospheric effects in ERTS-1 data; and area estimation accuracies are better using the ERIM proportion estimation algorithm than for conventional recognition techniques.

Thomson, F. J.↗

Automatic recognition of vector and parallel operations in a higher level language

A compiler for recognizing statements of a FORTRAN program which are suited for fast execution on a parallel or pipeline machine such as Illiac-4, Star or ASC is described. The technique employs interval analysis to provide flow information to the vector/parallel recognizer. Where profitable the compiler changes scalar variables to subscripted variables. The output of the compiler is an extension to FORTRAN which shows parallel and vector operations explicitly.

Schneck, P. B.↗

Coal gasification systems engineering and analysis. Appendix E: Cost estimation and economic evaluation methodology

The cost estimation and economic evaluation methodologies presented are consistent with industry practice for assessing capital investment requirements and operating costs of coal conversion systems. All values stated are based on January, 1980 dollars with appropriate recognition of the time value of money. Evaluation of project economic feasibility can be considered a two step process (subject to considerable refinement). First, the costs of the project must be quantified and second, the price at which the product can be manufacturd must be determined. These two major categories are discussed. The summary of methodology is divided into five parts: (1) systems costs, (2)instant plant costs, (3) annual operating costs, (4) escalation and discounting process, and (5) product pricing.

Source record↗

Automated Track Recognition and Event Reconstruction in Nuclear Emulsion

The major advantages of nuclear emulsion for detecting charged particles are its submicron position resolution and sensitivity to minimum ionizing particles. These must be balanced, however, against the difficult manual microscope measurement by skilled observers required for the analysis. We have developed an automated system to acquire and analyze the microscope images from emulsion chambers. Each emulsion plate is analyzed independently, allowing coincidence techniques to be used in order to reject back- ground and estimate error rates. The system has been used to analyze a sample of high-multiplicity Pb-Pb interactions (charged particle multiplicities approx. 1100) produced by the 158 GeV/c per nucleon Pb-208 beam at CERN. Automatically reconstructed track lists agree with our best manual measurements to 3%. We describe the image analysis and track reconstruction techniques, and discuss the measurement and reconstruction uncertainties.

Deines-Jones, P.↗

Pattern recognition systems and procedures

The objectives of the pattern recognition tasks are to develop (1) a man-machine interactive data processing system; and (2) procedures to determine effective features as a function of time for crops and soils. The signal analysis and dissemination equipment, SADE, is being developed as a man-machine interactive data processing system. SADE will provide imagery and multi-channel analog tape inputs for digitation and a color display of the data. SADE is an essential tool to aid in the investigation to determine useful features as a function of time for crops and soils. Four related studies are: (1) reliability of the multivariate Gaussian assumption; (2) usefulness of transforming features with regard to the classifier probability of error; (3) advantage of selecting quantizer parameters to minimize the classifier probability of error; and (4) advantage of using contextual data. The study of transformation of variables (features), especially those experimental studies which can be completed with the SADE system, will be done.

Nelson, G. D.↗

Scanning laser Doppler velocimeter system simulation for sensing aircraft wake vortices

A model that simulates the interaction of a laser-Doppler velocimeter with an aircraft wake flowfield is described. A hydrodynamic model is developed which represents the trailing vortex sheet and wind shear as discrete free vortices distributed over a two-dimensional grid. A sensor model is formulated for scanning both in range and in angle to produce a fan beam configuration without frequency translation. Output of this model is a frequency spectrum vs both range and angle. Once the spectrum is evaluated, simulations of the data analysis procedure are carried out. Patterns of various features of the signature are presented in range-elevation angle plots. The problem of locating the vortex centers is discussed as a pattern recognition problem and as a point target problem.

Thomson, J. A. L.↗