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At least 595 records · Page 33

Automated strip-mine and reclamation mapping from ERTS

The author has identified the following significant results. Computer processing techniques were applied to ERTS-1 computer-compatible tape (CCT) data acquired in August 1972 on the Ohio Power Company's coal mining operation in Muskingum County, Ohio. Processing results succeeded in automatically classifying, with an accuracy greater than 90%: (1) stripped earth and major sources of erosion; (2) partially reclaimed areas and minor sources of erosion; (3) water with sedimentation; (4) water without sedimentation; and (5) vegetation. Computer-generated tables listing the area in acres and square kilometers were produced for each target category. Processing results also included geometrically corrected map overlays, one for each target category, drawn on a transparent material by a pen under computer control. Each target category is assigned a distinctive color on the overlay to facilitate interpretation. The overlays, drawn at a scale of 1:250,000 when placed over an AMS map of the same area, immediately provided map locations for each target. These mapping products were generated at a tenth of the cost of conventional mapping techniques.

Rogers, R. H.↗

Knowledge structure representation and automated updates in intelligent information management systems

A continuing effort to apply rapid prototyping and Artificial Intelligence techniques to problems associated with projected Space Station-era information management systems is examined. In particular, timely updating of the various databases and knowledge structures within the proposed intelligent information management system (IIMS) is critical to support decision making processes. Because of the significantly large amounts of data entering the IIMS on a daily basis, information updates will need to be automatically performed with some systems requiring that data be incorporated and made available to users within a few hours. Meeting these demands depends first, on the design and implementation of information structures that are easily modified and expanded, and second, on the incorporation of intelligent automated update techniques that will allow meaningful information relationships to be established. Potential techniques are studied for developing such an automated update capability and IIMS update requirements are examined in light of results obtained from the IIMS prototyping effort.

Corey, Stephen↗

From requirements to acceptance tests

From user requirements definition to accepted software system, the software project management wants to be sure that the system will meet the requirements. For the development of a telecommunication satellites Control Centre, C.N.E.S. has used new rules to make the use of tracing matrix easier. From Requirements to Acceptance Tests, each item of a document must have an identifier. A unique matrix traces the system and allows the tracking of the consequences of a change in the requirements. A tool has been developed, to import documents into a relational data base. Each record of the data base corresponds to an item of a document, the access key is the item identifier. Tracing matrix is also processed, providing automatically links between the different documents. It enables the reading on the same screen of traced items. For example one can read simultaneously the User Requirements items, the corresponding Software Requirements items and the Acceptance Tests.

Baize, Lionel↗

CLIPS enhanced with objects, backward chaining and explanation facilities

In this project we extend C Language Production System (CLIPS), an existing Expert System shell, by creating three new options. Specifically, first we create a compatible with CLIPS environment that allows for defining objects and object hierarchies, second we provide means to implement backward chaining in a pure forward chaining environment, and finally we give some simple explanation facilities for the derivations the system has made. Objects and object hierarchies are extended so that facts can be automatically inferred, and placed in the fact base. Backward chaining is implemented by creating run time data structures which hold the derivation process allowing for a depth first search. The backward chaining mechanism works not only with ground facts, but also creates bindings for every query that involves variables, and returns the truth value of such a query as well as the relevant variable bindings. Finally, the WHY and HOW explanation facilities allow for a complete examination of the derivation process, the rules triggered, and the bindings created. The entire system is integrated with the original CLIPS code, and all of its routines can be invoked as CLIPS commands.

Aldrobi, M.↗

Dynamic Deformation Measurements of an Aeroelastic Semispan Model

The techniques used to acquire, reduce, and analyze dynamic deformation measurements of an aeroelastic semispan wind tunnel model are presented. Single-camera, single-view video photogrammetry (also referred to as videogrammetric model deformation, or VMD) was used to determine dynamic aeroelastic deformation of the semispan 'Models for Aeroelastic Validation Research Involving Computation' (MAVRIC) model in the Transonic Dynamics Tunnel at the NASA Langley Research Center. Dynamic deformation was determined from optical retroreflective tape targets at five semispan locations located on the wing from the root to the tip. Digitized video images from a charge coupled device (CCD) camera were recorded and processed to automatically determine target image plane locations that were then corrected for sensor, lens, and frame grabber spatial errors. Videogrammetric dynamic data were acquired at a 60-Hz rate for time records of up to 6 seconds during portions of this flutter/Limit Cycle Oscillation (LCO) test at Mach numbers from 0.3 to 0.96. Spectral analysis of the deformation data is used to identify dominant frequencies in the wing motion. The dynamic data will be used to separate aerodynamic and structural effects and to provide time history deflection data for Computational Aeroelasticity code evaluation and validation.

Graves, Sharon S.↗

An Expert Assistant for Computer Aided Parallelization

The prototype implementation of an expert system was developed to assist the user in the computer aided parallelization process. The system interfaces to tools for automatic parallelization and performance analysis. By fusing static program structure information and dynamic performance analysis data the expert system can help the user to filter, correlate, and interpret the data gathered by the existing tools. Sections of the code that show poor performance and require further attention are rapidly identified and suggestions for improvements are presented to the user. In this paper we describe the components of the expert system and discuss its interface to the existing tools. We present a case study to demonstrate the successful use in full scale scientific applications.

Jost, Gabriele↗

High-Performance Scanning Acousto-Ultrasonic System

A high-performance scanning acousto-ultrasonic system, now undergoing development, is designed to afford enhanced capabilities for imaging microstructural features, including flaws, inside plate specimens of materials. The system is expected to be especially helpful in analyzing defects that contribute to failures in polymer- and ceramic-matrix composite materials, which are difficult to characterize by conventional scanning ultrasonic techniques and other conventional nondestructive testing techniques. Selected aspects of the acousto-ultrasonic method have been described in several NASA Tech Briefs articles in recent years. Summarizing briefly: The acousto-ultrasonic method involves the use of an apparatus like the one depicted in the figure (or an apparatus of similar functionality). Pulses are excited at one location on a surface of a plate specimen by use of a broadband transmitting ultrasonic transducer. The stress waves associated with these pulses propagate along the specimen to a receiving transducer at a different location on the same surface. Along the way, the stress waves interact with the microstructure and flaws present between the transducers. The received signal is analyzed to evaluate the microstructure and flaws. The specific variant of the acousto-ultrasonic method implemented in the present developmental system goes beyond the basic principle described above to include the following major additional features: Computer-controlled motorized translation stages are used to automatically position the transducers at specified locations. Scanning is performed in the sense that the measurement, data-acquisition, and data-analysis processes are repeated at different specified transducer locations in an array that spans the specimen surface (or a specified portion of the surface). A pneumatic actuator with a load cell is used to apply a controlled contact force. In analyzing the measurement data for each pair of transducer locations in the scan, the total (multimode) acousto-ultrasonic response of the specimen is utilized. The analysis is performed by custom software that extracts parameters of signals in the time and frequency domains. The computer hardware and software provide both real-time and postscan processing and display options. For example, oscilloscope displays of waveforms and power spectral densities are available in real time. Images can be computed while scanning continues. Signals can be digitally preprocessed and/or post-processed by filtering, windowing, time-segmenting, and running-waveform-averaging algorithms. In addition, the software affords options for off-line simulation of the waveform-data-acquisition and scanning processes. In tests, the system has been shown to be capable of characterizing microstructural changes and defects in SiC/SiC and C/SiC ceramic-matrix composites. Delaminations, variations in density, microstructural changes attributable to infiltration by silicon, and crack-space indications (defined in the next sentence) have been revealed in images formed from several time- and frequency-domain parameters of scanning acousto-ultrasonic signals. The crack-space indications were image features that were not revealed by other nondestructive testing methods and are so named because they turned out to mark locations where cracking eventually occurred.

Roth, Don↗

Developing a Vision for Maturing the Heliophysics Infrastructure towards Open Science: The DIARieS Analysis Ecosystem

In the dawn of open science and the upcoming requirements, we speak about the existing state of Heliophysics infrastructure and detail the evolution required to address capability or interconnection shortcomings. Such a daunting barrier calls for an analysis ecosystem with multi-faceted capability. We propose such an ecosystem, called DIARieS, to be built upon five conceptual pillars: Discovery, Implementation, Analysis, Reproducibility, and Sharing of results. The combination of these concepts in a single platform will enable users to more intuitively combine recent advances in technology to create ‘DIARieS’ of their workflows, which can be easily made open to others in the community. The DIARieS ecosystem will also increase our efficiency by streamlining our various workflow processes, including automatic incorporation of the impending requirements of open science. The various components of the ecosystem will simplify software installation and data implementation, including automatically generated citation lists based on the components included. Automatic containerization and version control of the ecosystem will make the custom workflows easily reproducible. Employing widget technology will ease the difficulty of producing publication and commercial quality visualizations and applying common analyses techniques. Incorporating multiple technologies will streamline the various sharing methods common in our work environments today. Overall, the totality of capabilities to be offered by this analysis ecosystem will drastically simplify the application of open science principles to our work in addition to improving our efficiency and ease of collaboration. This talk summarizes a vision of the proposed ecosystem, which is described in more detail in Ringuette et al. (2022: https://doi.org/10.1016/j.asr.2022.05.012).

infrastructure↗

Developing a Vision for Maturing the Heliophysics Infrastructure towards Open Science

In the dawn of open science and the upcoming requirements, we speak about the existing state of Heliophysics infrastructure and detail the evolution required to address capability or interconnection shortcomings. Such a daunting barrier calls for an analysis ecosystem with multi-faceted capability. We propose such an ecosystem, called DIARieS, to be built upon five conceptual pillars: Discovery, Implementation, Analysis, Reproducibility, and Sharing of results. The combination of these concepts in a single platform will enable users to more intuitively combine recent advances in technology to create ‘DIARieS’ of their workflows, which can be easily made open to others in the community. The DIARieS ecosystem will also increase our efficiency by streamlining our various workflow processes, including automatic incorporation of the impending requirements of open science. The various components of the ecosystem will simplify software installation and data implementation, including automatically generated citation lists based on the components included. Automatic containerization and version control of the ecosystem will make the custom workflows easily reproducible. Employing widget technology will ease the difficulty of producing publication and commercial quality visualizations and applying common analyses techniques. Incorporating multiple technologies will streamline the various sharing methods common in our work environments today. Overall, the totality of capabilities to be offered by this analysis ecosystem will drastically simplify the application of open science principles to our work in addition to improving our efficiency and ease of collaboration.

Infrastructure↗

Automatic Digitization and Orientation of Scanned Mesh Data for Floor Plan and 3D Model Generation

This paper describes a novel approach for generating accurate floor plans and 3D models of building interiors using scanned mesh data. Unlike previous methods, which begin with a high resolution point cloud from a laser range-finder, our approach begins with triangle mesh data, as from a Microsoft HoloLens. It generates two types of floor plans, a “pen-and-ink” style that preserves details and a drafting-style that reduces clutter. It processes the 3D model for use in applications by aligning it with coordinate axes, annotating important objects, dividing it into stories, and removing the ceiling. Its performance is evaluated on commercial and residential buildings, with experiments to assess quality and dimensional accuracy. Our approach demonstrates promising potential for automatic digitization and orientation of scanned mesh data, enabling floor plan and 3D model generation in various applications such as navigation, interior design, furniture placement, facilities management, building construction, and HVAC design.

Sharma, Ritesh↗

Management of natural resources through automatic cartographic inventory

The author has identified the following significant results. Significant results of the ARNICA program (February - December 1973) were: (1) The quantitative processing of ERTS-1 data was developed along two lines: the study of geological structures and lineaments of Spanish Catalonia, and the phytogeographical study of the forest region of the Landes of Gascony (France). In both cases it is shown that the ERTS-1 imagery can be used in establishing zonings of equal quantitative interpretation value. (2) In keeping with the operational transfer program proposed in previous reports between exploration of the imagery and charting of the object, a precise data processing method was developed, concerning more particularly the selection of digital equidensity samples computer display and rigorous referencing.

Rey, P. A.↗

Automatic terrain elevation mapping and registration

Optimum radar illumination geometries for stereoscopic analysis of surface topography are determined. Correlation and image processing experiments on synthetic aperture radar (SAR) data for improved information extraction are conducted. Model of the geometry of the multiple SIR-B views of the Earth are developed the sensitivity of the derived terrain altitude data to the various system parameters is established. The limits of accuracy of terrain data achievable with shuttle imaging radar (SIR-B) are derived. Algorithms for matching multiple SIR-B images to generate digital terrain maps are developed. Finally, the use of such terrain maps in geometric correction and registration of SIR-B and LANDSAT Thematic Mapper data is demonstrated.

Ramapriyan, H. K.↗

Scaling Automatic Vector Data Alignment to Satellite Imagery

Given the tremendous volume of accessible Earth Observation (EO) data, there is a need to develop scalable Geospatial Artificial Intelligence (GeoAI) solutions for time-sensitive applications. Scalability in this context refers to rapidly processing large-scale EO data using high performance computing resources. Accurate mapping of the built environment from remote sensing (RS) imagery has been one of the crucial components in GeoAI workflows for a wide spectrum of humanitarian applications. Derived vector data of built environment is often leveraged for disaster preparedness and response activities. However, factors such as differences in ortho-rectification, atmospheric conditions and human error, results in spatial misalignment between vector data and the timely available RS imagery. Model training for downstream tasks such as object detection, change analysis, etc., is negatively impacted due to such spatial misalignment. Although there has been progress towards automatic alignment of vector data, the lack of scalability remains an open research challenge. This paper proposes to leverage parallel computing to optimize an automatic vector data alignment workflow. It further employs CPU-level multi-core parallelism for improving the performance of the workflow for scalable built environment mapping. We report observations and discuss findings from the preliminary experiments performed on the Summit Supercomputer.

Potnis, Abhishek↗

Systematic characterization of protein folding pathways using diffusion maps: Application to Trp-cage miniprotein

Understanding the mechanisms by which proteins fold from disordered amino-acid chains to spatially ordered structures remains an area of active inquiry. Molecular simulations can provide atomistic details of the folding dynamics which complement experimental findings. Conventional order parameters, such as root-mean-square deviation and radius of gyration, provide structural information but fail to capture the underlying dynamics of the protein folding process. It is therefore advantageous to adopt a method that can systematically analyze simulation data to extract relevant structural as well as dynamical information. The nonlinear dimensionality reduction technique known as diffusion maps automatically embeds the high-dimensional folding trajectories in a lower-dimensional space from which one can more easily visualize folding pathways, assuming the data lie approximately on a lower-dimensional manifold. The eigenvectors that parametrize the low-dimensional space, furthermore, are determined systematically, rather than chosen heuristically, as is done with phenomenological order parameters. We demonstrate that diffusion maps can effectively characterize the folding process of a Trp-cage miniprotein. By embedding molecular dynamics simulation trajectories of Trp-cage folding in diffusion maps space, we identify two folding pathways and intermediate structures that are consistent with the previous studies, demonstrating that this technique can be employed as an effective way of analyzing and constructing protein folding pathways from molecular simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations

We developed a new class of physics-informed generative adversarial networks (PI-GANs) to solve forward, inverse, and mixed stochastic problems in a unified manner based on a limited number of scattered measurements. Unlike standard GANs relying solely on data for training, here we encoded into the architecture of GANs the governing physical laws in the form of stochastic differential equations (SDEs) using automatic differentiation. In particular, we applied Wasserstein GANs with gradient penalty (WGAN-GP) for its enhanced stability compared to vanilla GANs. We first tested WGAN-GP in approximating Gaussian processes of different correlation lengths based on data realizations collected from simultaneous reads at sparsely placed sensors. We obtained good approximation of the generated stochastic processes to the target ones even if there is a mismatch between the input noise dimensionality and the effective dimensionality of the target stochastic processes. We also studied the overfitting issue for both the discriminator and the generator, and we found that overfitting occurs also in the generator in addition to the discriminator as previously reported. Subsequently, we considered the solution of elliptic SDEs requiring approximations of three stochastic processes, namely the solution, the forcing, and the diffusion coefficient. Here again, we assumed data collected from simultaneous reads at a limited number of sensors for the multiple stochastic processes. Furthermore, three generators were used for the PI-GANs: two of them were feed forward deep neural networks (DNNs), while the other one was the neural network induced by the SDE. For the case where we have one group of data, we employed one feed forward DNN as the discriminator, while for the case of multiple groups of data we employed multiple discriminators in PI-GANs. We solved forward, inverse, and mixed problems without changing the framework of PI-GANs, obtaining both the means and the standard deviations of the stochastic solution and the diffusion coefficient in good agreement with benchmarks. In this work, we have demonstrated the effectiveness of PI-GANs in solving SDEs for about 120 dimensions. In principle, PI-GANs could tackle very high dimensional problems given more sensor data with low-polynomial growth in computational cost.

97 MATHEMATICS AND COMPUTING↗

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presented to demonstrate the implementation details and system innovations.

58 GEOSCIENCES↗

A Multi­Discipline Approach to Digitizing Historic Seismograms

Retriever Technology has developed and has made available free of charge a seismogram digitization software package called SKATE (Seismogram Kit for Automatic Trace Extraction). We have developed an extensive set of algorithms that process seismogram image files, provide editing tools, and output time series data. The software is available online and free of charge at seismo.redfish.com. To demonstrate the speed and cost effectiveness of the software, we have processed over 30,000 images.

47 OTHER INSTRUMENTATION↗

Digital Signal Processing Using Deep Neural Networks

Currently there is great interest in the utility of deep neural networks (DNNs) for the physical layer of radio frequency (RF) communications. In this manuscript we describe a custom DNN specially designed to solve problems in the RF domain. Our model leverages the mechanisms of feature extraction and attention through the combination of an autoencoder convolutional network with a transformer network, to accomplish several important communications network and digital signals processing (DSP) tasks. We also present a new open dataset and physical data augmentation model that enables training of DNNs that can perform automatic modulation classification, infer, and correct transmission channel effects, and directly demodulate baseband RF signals.

42 ENGINEERING↗