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150 records · Page 9

Compact Autonomous Hemispheric Vision System

Solar System Exploration camera implementations to date have involved either single cameras with wide field-of-view (FOV) and consequently coarser spatial resolution, cameras on a movable mast, or single cameras necessitating rotation of the host vehicle to afford visibility outside a relatively narrow FOV. These cameras require detailed commanding from the ground or separate onboard computers to operate properly, and are incapable of making decisions based on image content that control pointing and downlink strategy. For color, a filter wheel having selectable positions was often added, which added moving parts, size, mass, power, and reduced reliability. A system was developed based on a general-purpose miniature visible-light camera using advanced CMOS (complementary metal oxide semiconductor) imager technology. The baseline camera has a 92 FOV and six cameras are arranged in an angled-up carousel fashion, with FOV overlaps such that the system has a 360 FOV (azimuth). A seventh camera, also with a FOV of 92 , is installed normal to the plane of the other 6 cameras giving the system a > 90 FOV in elevation and completing the hemispheric vision system. A central unit houses the common electronics box (CEB) controlling the system (power conversion, data processing, memory, and control software). Stereo is achieved by adding a second system on a baseline, and color is achieved by stacking two more systems (for a total of three, each system equipped with its own filter.) Two connectors on the bottom of the CEB provide a connection to a carrier (rover, spacecraft, balloon, etc.) for telemetry, commands, and power. This system has no moving parts. The system's onboard software (SW) supports autonomous operations such as pattern recognition and tracking.

Pingree, Paula J.↗

Optical recognition of statistical patterns

Optical implementation of the Fukunaga-Koontz transform (FKT) and the Least-Squares Linear Mapping Technique (LSLMT) is described. The FKT is a linear transformation which performs image feature extraction for a two-class image classification problem. The LSLMT performs a transform from large dimensional feature space to small dimensional decision space for separating multiple image classes by maximizing the interclass differences while minimizing the intraclass variations. The FKT and the LSLMT were optically implemented by utilizing a coded phase optical processor. The transform was used for classifying birds and fish. After the F-K basis functions were calculated, those most useful for classification were incorporated into a computer generated hologram. The output of the optical processor, consisting of the squared magnitude of the F-K coefficients, was detected by a T.V. camera, digitized, and fed into a micro-computer for classification. A simple linear classifier based on only two F-K coefficients was able to separate the images into two classes, indicating that the F-K transform had chosen good features. Two advantages of optically implementing the FKT and LSLMT are parallel and real time processing.

Lee, S. H.↗

Topics in inference and decision-making with partial knowledge

Two essential elements needed in the process of inference and decision-making are prior probabilities and likelihood functions. When both of these components are known accurately and precisely, the Bayesian approach provides a consistent and coherent solution to the problems of inference and decision-making. In many situations, however, either one or both of the above components may not be known, or at least may not be known precisely. This problem of partial knowledge about prior probabilities and likelihood functions is addressed. There are at least two ways to cope with this lack of precise knowledge: robust methods, and interval-valued methods. First, ways of modeling imprecision and indeterminacies in prior probabilities and likelihood functions are examined; then how imprecision in the above components carries over to the posterior probabilities is examined. Finally, the problem of decision making with imprecise posterior probabilities and the consequences of such actions are addressed. Application areas where the above problems may occur are in statistical pattern recognition problems, for example, the problem of classification of high-dimensional multispectral remote sensing image data.

Safavian, S. Rasoul↗

NASA Tech Briefs, July 2012

Topics covered include: Instrument Suite for Vertical Characterization of the Ionosphere-Thermosphere System; Terahertz Radiation Heterodyne Detector Using Two-Dimensional Electron Gas in a GaN Heterostructure; Pattern Recognition Algorithm for High-Sensitivity Odorant Detection in Unknown Environments; Determining Performance Acceptability of Electrochemical Oxygen Sensors; Versatile Controller for Infrared Lamp and Heater Arrays; High-Speed Scanning Interferometer Using CMOS Image Sensor and FPGA Based on Multifrequency Phase-Tracking Detection; Ultra-Low-Power MEMS Selective Gas Sensors; Compact Receiver Front Ends for Submillimeter-Wave Applications; Dynamically Reconfigurable Systolic Array Accelerator; Blocking Losses With a Photon Counter; Motion-Capture-Enabled Software for Gestural Control of 3D Mod; Orbit Software Suite; CoNNeCT Baseband Processor Module Boot Code SoftWare (BCSW); Trajectory Software With Upper Atmosphere Model; ALSSAT Version 6.0; Employing a Grinding Technology to Assess the Microbial Density for Encapsulated Organisms; Demonstration of Minimally Machined Honeycomb Silicon Carbide Mirrors; Polyimide Aerogel Thin Films; Nanoengineered Thermal Materials Based on Carbon Nanotube Array Composites; Composite Laminate With Coefficient of Thermal Expansion Matching D263 Glass; Robust Tensioned Kevlar Suspension Design; Focal Plane Alignment Utilizing Optical CMM; Purifying, Separating, and Concentrating Cells From a Sample Low in Biomass; Virtual Ultrasound Guidance for Inexperienced Operators; Beat-to-Beat Blood Pressure Monitor; Non-Contact Conductivity Measurement for Automated Sample Processing Systems; An MSK Radar Waveform; Telescope Alignment From Sparsely Sampled Wavefront Measurements Over Pupil Subapertures; Method to Remove Particulate Matter from Dusty Gases at Low Pressures; Terahertz Quantum Cascade Laser With Efficient Coupling and Beam Profile; Measurement Via Optical Near-Nulling and Subaperture Stitching; 885-nm Pumped Ceramic Nd:YAG Master Oscillator Power Amplifier Laser System; Airborne Hyperspectral Imaging System; Heat Shield Employing Cured Thermal Protection Material Blocks Bonded in a Large-Cell Honeycomb Matrix; and Asymmetric Supercapacitor for Long-Duration Power Storage.

Source record↗

Neural activation during response competition

The flanker task, introduced by Eriksen and Eriksen [Eriksen, B. A., & Eriksen, C. W. (1974). Effects of noise letters upon the identification of a target letter in a nonsearch task. Perception & Psychophysics, 16, 143--149], provides a means to selectively manipulate the presence or absence of response competition while keeping other task demands constant. We measured brain activity using functional magnetic resonance imaging (fMRI) during performance of the flanker task. In accordance with previous behavioral studies, trials in which the flanking stimuli indicated a different response than the central stimulus were performed significantly more slowly than trials in which all the stimuli indicated the same response. This reaction time effect was accompanied by increases in activity in four regions: the right ventrolateral prefrontal cortex, the supplementary motor area, the left superior parietal lobe, and the left anterior parietal cortex. The increases were not due to changes in stimulus complexity or the need to overcome previously learned associations between stimuli and responses. Correspondences between this study and other experiments manipulating response interference suggest that the frontal foci may be related to response inhibition processes whereas the posterior foci may be related to the activation of representations of the inappropriate responses.

Brain Mapping/methods↗

Runway Texture and Grid Pattern Effects on Rate-of-Descent Perception

To date, perceptual errors occur in determining descent rate from a computer-generated image in flight simulation. Pilots tend to touch down twice as hard in simulation than in flight, and more training time is needed in simulation before reaching steady-state performance. Barnes suggested that recognition of range may be the culprit, and he cited that problems such as collimated objects, binocular vision, and poor resolution lead to poor estimation of the velocity vector. Brown's study essentially ruled out that the lack of binocular vision is the problem. Dorfel added specificity to the problem by showing that pilots underestimated range in simulated scenes by 50% when 800 ft from the runway threshold. Palmer and Petitt showed that pilots are able to distinguish between a 1.7 ft/sec and 2.9 ft/sec sink rate when passively observing sink rates in a night scene. Platform motion also plays a role, as previous research has shown that the addition of substantial platform motion improves pilot estimates of vertical velocity and results in simulated touchdown rates more closely resembling flight. This experiment examined how some specific variations in the visual scene properties affect a pilot's perception of sink rate. It extended another experiment that focused on the visual and motion cues necessary for helicopter autorotations. In that experiment, pilots performed steep approaches to a runway. The visual content of the runway and its surroundings varied in two ways: texture and rectangular grid spacing. Four textures, included a no-texture case, were evaluated. Three grid spacings, including a no-grid case, were evaluated. The results showed that pilot better controlled their vertical descent rates when good texture cues were present. No significant differences were found for the grid manipulation. Using those visual scenes a simple psychophysics, experiment was performed. The purpose was to determine if the variations in the visual scenes allowed pilots to better perceive vertical velocity. To determine that answer, pilots passively viewed a particular visual scene in which the vehicle was descending at two different rates. Pilots had to select which of the two rates they thought was the fastest rate. The difference between the two rates changed using a staircase method, depending on whether or not the pilot was correct, until a minimum threshold between the two descent rates was reached. This process was repeated for all of the visual scenes to decide whether or not the visual scenes did allow pilots to perceive vertical velocity better among them. All of the data have yet to be analyzed; however, neither the effects of grid nor texture revealed any statistically significant trends. On further examination of the staircase method employed, a possibility exists that the lack of an evident trend may be due to the exit criterion used during the study. As such, the experiment will be repeated with an improved exit criterion in February. Results of this study will be presented in the submitted paper.

Schroeder, J. A.↗