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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Easy and Enticing: How a Collaborative Approach to Emerging Technology Adoption in the Commercial Building Sector Has Made Its Mark

In 2012, the U.S. Department of Energy (DOE), in collaboration with interested partners (e.g., applicable trade groups), initiated a novel market transformation approach, technology adoption campaigns, to speed the adoption of new technologies that save energy and money in buildings—first with lighting and later with other building technologies. This approach couples technical performance evaluation, guidance, data tracking and technical assistance with recognition for exemplary performance and best practices. Campaigns can be designed around emerging technologies that have significant, cost-effective national energy savings potential and where there is strong public- and private-sector interest in sharing performance criteria and outcomes. Participants in the campaigns share project data with the national laboratories and DOE, benefit from technical support and assistance from objective experts, and highly value recognition for their accomplishments. DOE and its campaign partners benefit from accelerated adoption of new energy-saving technologies and engagement with manufacturers and end users that allows for data collection and insights into technology research needs. This paper documents the success, challenges, lessons learned, and energy and cost savings of lighting campaigns, and in many cases compares these findings with other campaign efforts. This paper also presents recommendations for how other programs of various sizes can employ this model.

Myer, Michael↗
NASA NTRS2011

Optimization of Adaboost Algorithm for Sonar Target Detection in a Multi-Stage ATR System

JPL has developed a multi-stage Automated Target Recognition (ATR) system to locate objects in images. First, input images are preprocessed and sent to a Grayscale Optical Correlator (GOC) filter to identify possible regions-of-interest (ROIs). Second, feature extraction operations are performed using Texton filters and Principal Component Analysis (PCA). Finally, the features are fed to a classifier, to identify ROIs that contain the targets. Previous work used the Feed-forward Back-propagation Neural Network for classification. In this project we investigate a version of Adaboost as a classifier for comparison. The version we used is known as GentleBoost. We used the boosted decision tree as the weak classifier. We have tested our ATR system against real-world sonar images using the Adaboost approach. Results indicate an improvement in performance over a single Neural Network design.

Adaboost↗
NASA NTRS1974

On the recognition of complex structures: Computer software using artificial intelligence applied to pattern recognition

An approach to simultaneous interpretation of objects in complex structures so as to maximize a combined utility function is presented. Results of the application of a computer software system to assign meaning to regions in a segmented image based on the principles described in this paper and on a special interactive sequential classification learning system, which is referenced, are demonstrated.

Yakimovsky, Y.↗
DOE OSTI2021

ClimateNet: an expert-labeled open dataset and deep learning architecture for enabling high-precision analyses of extreme weather

Abstract. Identifying, detecting, and localizing extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Pattern recognition tasks such as classification, object detection, and segmentation (i.e., pixel-level classification) have remained challenging problems in the weather and climate sciences. While there exist many empirical heuristics for detecting extreme events, the disparities between the output of these different methods even for a single event are large and often difficult to reconcile. Given the success of deep learning (DL) in tackling similar problems in computer vision, we advocate a DL-based approach. DL, however, works best in the context of supervised learning – when labeled datasets are readily available. Reliable labeled training data for extreme weather and climate events is scarce. We create “ClimateNet” – an open, community-sourced human-expert-labeled curated dataset that captures tropical cyclones (TCs) and atmospheric rivers (ARs) in high-resolution climate model output from a simulation of a recent historical period. We use the curated ClimateNet dataset to train a state-of-the-art DL model for pixel-level identification – i.e., segmentation – of TCs and ARs. We then apply the trained DL model to historical and climate change scenarios simulated by the Community Atmospheric Model (CAM5.1) and show that the DL model accurately segments the data into TCs, ARs, or “the background” at a pixel level. Further, we show how the segmentation results can be used to conduct spatially and temporally precise analytics by quantifying distributions of extreme precipitation conditioned on event types (TC or AR) at regional scales. The key contribution of this work is that it paves the way for DL-based automated, high-fidelity, and highly precise analytics of climate data using a curated expert-labeled dataset – ClimateNet. ClimateNet and the DL-based segmentation method provide several unique capabilities: (i) they can be used to calculate a variety of TC and AR statistics at a fine-grained level; (ii) they can be applied to different climate scenarios and different datasets without tuning as they do not rely on threshold conditions; and (iii) the proposed DL method is suitable for rapidly analyzing large amounts of climate model output. While our study has been conducted for two important extreme weather patterns (TCs and ARs) in simulation datasets, we believe that this methodology can be applied to a much broader class of patterns and applied to observational and reanalysis data products via transfer learning.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Technology assessment and the Food and Drug Administration

The statutory standards underlying the activities of the FDA, and the problems the Agency faces in decision making are discussed from a legal point of view. The premarketing clearance of new drugs and of food additives, the two most publicized and criticized areas of FDA activity, are used as illustrations. The importance of statutory standards in technology assessment in a regulatory setting is developed. The difficulties inherent in the formulation of meaningful standards are recognized. For foods, the words of the statute are inadequate, and for drugs, a statutory recognition of the various other objectives would be useful to the regulator and the regulated.

Kaplan, A. H.↗
NASA NTRS1973

Small Interactive Image Processing System (SMIPS) users manual

The Small Interactive Image Processing System (SMIP) is designed to facilitate the acquisition, digital processing and recording of image data as well as pattern recognition in an interactive mode. Objectives of the system are ease of communication with the computer by personnel who are not expert programmers, fast response to requests for information on pictures, complete error recovery as well as simplification of future programming efforts for extension of the system. The SMIP system is intended for operation under OS/MVT on an IBM 360/75 or 91 computer equipped with the IBM-2250 Model 1 display unit. This terminal is used as an interface between user and main computer. It has an alphanumeric keyboard, a programmed function keyboard and a light pen which are used for specification of input to the system. Output from the system is displayed on the screen as messages and pictures.

Moik, J. G.↗
NASA NTRS1989

Image understanding and the man-machine interface II; Proceedings of the Meeting, Los Angeles, CA, Jan. 17, 18, 1989

Image understanding concepts and models, image understanding systems and applications, advanced digital processors and software tools, and advanced man-machine interfaces are among the topics discussed. Particular papers are presented on such topics as neural networks for computer vision, object-based segmentation and color recognition in multispectral images, the application of image algebra to image measurement and feature extraction, and the integration of modeling and graphics to create an infrared signal processing test bed.

Barrett, Eamon B.↗
NASA NTRS2009

Synthetic Foveal Imaging Technology

Synthetic Foveal imaging Technology (SyFT) is an emerging discipline of image capture and image-data processing that offers the prospect of greatly increased capabilities for real-time processing of large, high-resolution images (including mosaic images) for such purposes as automated recognition and tracking of moving objects of interest. SyFT offers a solution to the image-data processing problem arising from the proposed development of gigapixel mosaic focal-plane image-detector assemblies for very wide field-of-view imaging with high resolution for detecting and tracking sparse objects or events within narrow subfields of view. In order to identify and track the objects or events without the means of dynamic adaptation to be afforded by SyFT, it would be necessary to post-process data from an image-data space consisting of terabytes of data. Such post-processing would be time-consuming and, as a consequence, could result in missing significant events that could not be observed at all due to the time evolution of such events or could not be observed at required levels of fidelity without such real-time adaptations as adjusting focal-plane operating conditions or aiming of the focal plane in different directions to track such events. The basic concept of foveal imaging is straightforward: In imitation of a natural eye, a foveal-vision image sensor is designed to offer higher resolution in a small region of interest (ROI) within its field of view. Foveal vision reduces the amount of unwanted information that must be transferred from the image sensor to external image-data-processing circuitry. The aforementioned basic concept is not new in itself: indeed, image sensors based on these concepts have been described in several previous NASA Tech Briefs articles. Active-pixel integrated-circuit image sensors that can be programmed in real time to effect foveal artificial vision on demand are one such example. What is new in SyFT is a synergistic combination of recent advances in foveal imaging, computing, and related fields, along with a generalization of the basic foveal-vision concept to admit a synthetic fovea that is not restricted to one contiguous region of an image.

Hoenk, Michael↗
NASA NTRS2011

Signatures of Chemical Evolution in Protostellar Nebulae

A decade ago observers began to take serious notice of the presence of crystalline silicate grains in the dust flowing away from some comets. While crystallinity had been seen in such objects previously, starting with the recognitions by Campins and Ryan (1990) that the 10 micron feature of Comet Halley resembled that of the mineral forsterite, most such observations were either ignored or dismissed as no path to explain such crystalline grains was available in the literature. When it was first suggested that an outward flow must be present to carry annealed silicate grains from the innermost regions of the Solar Nebula out to the regions where comets could form (Nuth, 1999; 2001) this suggestion was also dismissed because no such transport mechanism was known at the time. Since then not only have new models of nebular dynamics demonstrated the reality of long distance outward transport (Ciesla, 2007; 2008; 2009) but examination of older models (Boss, 2004) showed that such transport had been present but had gone unrecognized for many years. The most unassailable evidence for outward nebular transport came with the return of the Stardust samples from Comet Wild2, a Kuiper-belt comet that contained micron-scale grains of high temperature minerals resembling the Calcium-Aluminum Inclusions found in primitive meteorites (Zolensky et aI., 2006) that formed at T > 1400K. Now that outward transport in protostellar nebulae has been firmly established, a re-examination of its consequences for nebular gas is in order that takes into account both the factors that regulate both the outward flow as well as those that likely control the chemical composition of the gas. Laboratory studies of surface catalyzed reactions suggest that a trend toward more highly reduced carbon and nitrogen compounds in the gas phase should be correlated with a general increase in the crystallinity of the dust (Nuth et aI., 2000), but is such a trend actually observable? Unlike the Fischer-Tropsch or the Haber-Bosch reactions used in industry, the surface catalyzed reactions seen in our laboratory do not produce a simple product stream of methane or ammonia, respectively. Instead, such reactions produce a wide range of both aliphatic and aromatic hydrocarbons, as well as reduced nitrogen compounds such as ammonia, amines, amides and imides, as gas phase products together with a heavy, macromolecular, kerogen-like surface coating that remains on the grains. While CO and N2 will certainly be depleted by conversion into more complex and less volatile species via reaction on grain surfaces, it may be very difficult to monitor such changes from outside the system.

Nuth, Joseph A., III↗
NASA NTRS1985

Orbital debris policy issues: Battelle involvement and some personal observations

The possible hazards presented by orbital debris have been a matter of concern since the early 1960s. The area of initial concern was the potential hazard of the Earth from reentering debris. In the very early days of the space program, it was believed that only specially protected objects would survive reentry. Subsequent events showed this to be incorrect. The recognition of the potential hazard of orbital debris to orbiting objects did not occur until the late 1970s. Concern over this potential hazard has increased, and has also given rise to a number of policy issues. These issues are, at present, largely unresolved.

Edgecombe, D. S.↗
NASA NTRS1990

Experiments in model-based matching using a relational pyramid representation

The relational pyramid representation is a hierarchical relational description of an object that can be used in recognition and pose estimation. In this representation, primitive features appear at the bottom of the pyramid, relations among primitives appear at level one, and, in general, relations among lower-level structures appear at the levels above the levels in which these structures were defined. A pose-estimation system is constructed that uses the relational pyramid representation for the view classes of a 3D object and for the description of the unknown view of an object extracted from an image. A previously described system uses summary information to rank and select view classes to which the unknown view is compared. This paper describes a best-first search procedure to find correspondences between the selected view class pyramid and the image pyramid.

Chu, Nancy T.↗
NASA NTRS1990

Use of laser range finders and range image analysis in automated assembly tasks

A proposition to study the effect of filtering processes on range images and to evaluate the performance of two different laser range mappers is made. Median filtering was utilized to remove noise from the range images. First and second order derivatives are then utilized to locate the similarities and dissimilarities between the processed and the original images. Range depth information is converted into spatial coordinates, and a set of coefficients which describe 3-D objects is generated using the algorithm developed in the second phase of this research. Range images of spheres and cylinders are used for experimental purposes. An algorithm was developed to compare the performance of two different laser range mappers based upon the range depth information of surfaces generated by each of the mappers. Furthermore, an approach based on 2-D analytic geometry is also proposed which serves as a basis for the recognition of regular 3-D geometric objects.

Alvertos, Nicolas↗
NASA NTRS1987

Object apprehension using vision and touch

Researchers define object apprehension as the determination of the properties of an object and the relationships among these properties. They contrast this with recognition, which goes a step further to attach a label to the object as a whole. Apprehension is fundamental to manipulation. This is true whether the manipulation is being carried out by an autonomous robot or is the result of teleoperation involving sensory feedback. Researchers present an apprehension paradigm using both vision and touch. In this model, they define a representation for object apprehension in terms of a set of primitives and features, along with their relationships. This representation is the mechanism by which the data from the two modalities are combined. It is also the mechanism which drives the apprehension process.

Bajcsy, R.↗
DOE OSTI2022

Optical emissivity dataset of multi-material heterogeneous designs generated with automated figure extraction

Optical device design is typically an iterative optimization process based on a good initial guess from prior reports. Optical properties databases are useful in this process but difficult to compile because their parsing requires finding relevant papers and manually converting graphical emissivity curves to data tables. Here, we present two contributions: one is a dataset of thermal emissivity records with design-related parameters, and the other is a software tool for automated colored curve data extraction from scientific plots. We manually collected 64 papers with 176 figures reporting thermal emissivity and automatically retrieved 153 colored curve data records. The automated figure analysis software pipeline uses Faster R-CNN for axes and legend object detection, EasyOCR for axes numbering recognition, and k-means clustering for colored curve retrieval. Additionally, we manually extracted geometry, materials, and method information from the text to add necessary metadata to each emissivity curve. Finally, we analyzed the dataset to determine the dominant classes of emissivity curves and determine the underlying design parameters leading to a type of emissivity profile.

47 OTHER INSTRUMENTATION↗
NASA NTRS1988

Planetary Geology: Goals, Future Directions, and Recommendations

Planetary exploration has provided a torrent of discoveries and a recognition that planets are not inert objects. This expanded view has led to the notion of comparative planetology, in which the differences and similarities among planetary objects are assessed. Solar system exploration is undergoing a change from an era of reconnaissance to one of intensive exploration and focused study. Analyses of planetary surfaces are playing a key role in this transition, especially as attention is focused on such exploration goals as returned samples from Mars. To assess how the science of planetary geology can best contribute to the goals of solar system exploration, a workshop was held at Arizona State University in January 1987. The participants discussed previous accomplishments of the planetary geology program, assessed the current studies in planetary geology, and considered the requirements to meet near-term and long-term exploration goals.

Source record↗
NASA NTRS1995

Stereo-Based Region-Growing using String Matching

We present a novel stereo algorithm based on a coarse texture segmentation preprocessing phase. Matching is performed using a string comparison. Matching sub-strings correspond to matching sequences of textures. Inter-scanline clustering of matching sub-strings yields regions of matching texture. The shape of these regions yield information concerning object's height, width and azimuthal position relative to the camera pair. Hence, rather than the standard dense depth map, the output of this algorithm is a segmentation of objects in the scene. Such a format is useful for the integration of stereo with other sensor modalities on a mobile robotic platform. It is also useful for localization; the height and width of a detected object may be used for landmark recognition, while depth and relative azimuthal location determine pose. The algorithm does not rely on the monotonicity of order of image primitives. Occlusions, exposures, and foreshortening effects are not problematic. The algorithm can deal with certain types of transparencies. It is computationally efficient, and very amenable to parallel implementation. Further, the epipolar constraints may be relaxed to some small but significant degree. A version of the algorithm has been implemented and tested on various types of images. It performs best on random dot stereograms, on images with easily filtered backgrounds (as in synthetic images), and on real scenes with uncontrived backgrounds.

Mandelbaum, Robert↗
DOE OSTI2023

System and method for identifying objects of interest in images based on likelihood map decluttering

An automatic threat recognition system and method is disclosed for scanning the x-ray CT image of an article to identify the objects of interest (OOIs) contained within the article, which are otherwise not always quickly apparent or discernable to an individual. The system uses a computer to receive information from two-dimensional (2D) image slices from a reconstructed computed tomography (CT) scan image and to produce a plurality of voxels for each slice of the 2D image. The computer analyzes the voxels to create a likelihood map (LM) representing likelihoods that voxels making up the CT image are associated with a material of interest (MOI). The computer further analyzes the LM to construct neighborhoods of voxels within the LM, and classifies each voxel neighborhood based on its features, thereby decluttering the LM to facilitate the process of connecting voxels of a like MOI together to form segments. The computer classifies each candidate segment based on its features, thereby identifying those segments that correspond to objects of interest.

Paglieroni, David W.↗
NASA NTRS1991

Recognition of fiducial marks applied to robotic systems

The objective was to devise a method to determine the position and orientation of the links of a PUMA 560 using fiducial marks. As a result, it is necessary to design fiducial marks and a corresponding feature extraction algorithm. The marks used are composites of three basic shapes, a circle, an equilateral triangle and a square. Once a mark is imaged, it is thresholded and the borders of each shape are extracted. These borders are subsequently used in a feature extraction algorithm. Two feature extraction algorithms are used to determine which one produces the most reliable results. The first algorithm is based on moment invariants and the second is based on the discrete version of the psi-s curve of the boundary. The latter algorithm is clearly superior for this application.

Georges, Wayne D.↗