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At least 145 records · Page 8

Rapid Glacier Retreat Rates Observed in West Antarctica

The Pope, Smith, and Kohler glaciers, in the Amundsen Sea Embayment of West Antarctica, have experienced enhanced ocean-induced ice-shelf melt, glacier acceleration, ice thinning, and grounding line retreat in the past thirty years. Here we present observations of the grounding line retreat of these glaciers since 2014 using a constellation of interferometric radar satellites combined with precision surface elevation data. We find that the grounding lines develop spatially-variable, kilometre-scale, tidally-induced migration zones. After correction for tidal effects, we detect a sustained pattern of retreat coincident with high melt rates of un-grounded ice, marked by episodes of more rapid retreat. In 2017, Pope Glacier retreated 3.5 km in 3.6 months, or 11.7 km/yr. In 2016-2018, Smith West retreated at 2 km/yr and Kohler at 1.3 km/yr. While the retreat slowed down in 2018-2020, these retreat rates are faster than anticipated by numerical models on yearly time scales. We hypothesize that the rapid retreat is caused by un-represented, vigorous ice-ocean interactions acting within newly-formed cavities at the ice-ocean boundary.

Climate change↗

Immunity-Based Aircraft Fault Detection System

In the study reported in this paper, we have developed and applied an Artificial Immune System (AIS) algorithm for aircraft fault detection, as an extension to a previous work on intelligent flight control (IFC). Though the prior studies had established the benefits of IFC, one area of weakness that needed to be strengthened was the control dead band induced by commanding a failed surface. Since the IFC approach uses fault accommodation with no detection, the dead band, although it reduces over time due to learning, is present and causes degradation in handling qualities. If the failure can be identified, this dead band can be further A ed to ensure rapid fault accommodation and better handling qualities. The paper describes the application of an immunity-based approach that can detect a broad spectrum of known and unforeseen failures. The approach incorporates the knowledge of the normal operational behavior of the aircraft from sensory data, and probabilistically generates a set of pattern detectors that can detect any abnormalities (including faults) in the behavior pattern indicating unsafe in-flight operation. We developed a tool called MILD (Multi-level Immune Learning Detection) based on a real-valued negative selection algorithm that can generate a small number of specialized detectors (as signatures of known failure conditions) and a larger set of generalized detectors for unknown (or possible) fault conditions. Once the fault is detected and identified, an adaptive control system would use this detection information to stabilize the aircraft by utilizing available resources (control surfaces). We experimented with data sets collected under normal and various simulated failure conditions using a piloted motion-base simulation facility. The reported results are from a collection of test cases that reflect the performance of the proposed immunity-based fault detection algorithm.

Dasgupta, D.↗

Performance Bounds on Two Concatenated, Interleaved Codes

A method has been developed of computing bounds on the performance of a code comprised of two linear binary codes generated by two encoders serially concatenated through an interleaver. Originally intended for use in evaluating the performances of some codes proposed for deep-space communication links, the method can also be used in evaluating the performances of short-block-length codes in other applications. The method applies, more specifically, to a communication system in which following processes take place: At the transmitter, the original binary information that one seeks to transmit is first processed by an encoder into an outer code (Co) characterized by, among other things, a pair of numbers (n,k), where n (n > k)is the total number of code bits associated with k information bits and n k bits are used for correcting or at least detecting errors. Next, the outer code is processed through either a block or a convolutional interleaver. In the block interleaver, the words of the outer code are processed in blocks of I words. In the convolutional interleaver, the interleaving operation is performed bit-wise in N rows with delays that are multiples of B bits. The output of the interleaver is processed through a second encoder to obtain an inner code (Ci) characterized by (ni,ki). The output of the inner code is transmitted over an additive-white-Gaussian- noise channel characterized by a symbol signal-to-noise ratio (SNR) Es/No and a bit SNR Eb/No. At the receiver, an inner decoder generates estimates of bits. Depending on whether a block or a convolutional interleaver is used at the transmitter, the sequence of estimated bits is processed through a block or a convolutional de-interleaver, respectively, to obtain estimates of code words. Then the estimates of the code words are processed through an outer decoder, which generates estimates of the original information along with flags indicating which estimates are presumed to be correct and which are found to be erroneous. From the perspective of the present method, the topic of major interest is the performance of the communication system as quantified in the word-error rate and the undetected-error rate as functions of the SNRs and the total latency of the interleaver and inner code. The method is embodied in equations that describe bounds on these functions. Throughout the derivation of the equations that embody the method, it is assumed that the decoder for the outer code corrects any error pattern of t or fewer errors, detects any error pattern of s or fewer errors, may detect some error patterns of more than s errors, and does not correct any patterns of more than t errors. Because a mathematically complete description of the equations that embody the method and of the derivation of the equations would greatly exceed the space available for this article, it must suffice to summarize by reporting that the derivation includes consideration of several complex issues, including relationships between latency and memory requirements for block and convolutional codes, burst error statistics, enumeration of error-event intersections, and effects of different interleaving depths. In a demonstration, the method was used to calculate bounds on the performances of several communication systems, each based on serial concatenation of a (63,56) expurgated Hamming code with a convolutional inner code through a convolutional interleaver. The bounds calculated by use of the method were compared with results of numerical simulations of performances of the systems to show the regions where the bounds are tight (see figure).

Moision, Bruce↗

Pattern Recognition Algorithm for High-Sensitivity Odorant Detection in Unknown Environments

In a realistic odorant detection application environment, the collected sensory data is a mix of unknown chemicals with unknown concentrations and noise. The identification of the odorants among these mixtures is a challenge in data recognition. In addition, deriving their individual concentrations in the mix is also a challenge. A deterministic analytical model was developed to accurately identify odorants and calculate their concentrations in a mixture with noisy data.

Duong, Tuan A.↗

Transducer model produces facilitation from opposite-sign flanks

Small spots, lines and Gabor patterns can be easier to detect when they are superimposed upon similar spots, lines and Gabor patterns. Traditionally, such facilitation has been understood to be a consequence of nonlinear contrast transduction. Facilitation has also been reported to arise from non-overlapping patterns with opposite sign. We point out that this result does not preclude the traditional explanation for superimposed targets. Moreover, we find that facilitation from opposite-sign flanks is weaker than facilitation from same-sign flanks. Simulations with a transducer model produce opposite-sign facilitation.

NASA Discipline Space Human Factors↗

Optimization of Training Sets For Neural-Net Processing of Characteristic Patterns From Vibrating Solids

An artificial neural network is disclosed that processes holography generated characteristic pattern of vibrating structures along with finite-element models. The present invention provides for a folding operation for conditioning training sets for optimally training forward-neural networks to process characteristic fringe pattern. The folding pattern increases the sensitivity of the feed-forward network for detecting changes in the characteristic pattern The folding routine manipulates input pixels so as to be scaled according to the location in an intensity range rather than the position in the characteristic pattern.

Decker, Arthur J.↗

Vibration detection using lasers

Interference displacement patterns produced when light from a laser illuminates diffusely reflecting, vibrating surface are observed and photographed. Standing wave modes on model surface can be interpreted in order to yield amplitude and frequency of vibrations. Flat, white surfaces yield best interference patterns, even over considerable surface curvature.

Massey, G. A.↗

Global tropospheric and total ozone monitoring with a Double-Etalon Fabry-Perot interferometer

Knowledge of the global scale distribution of atmospheric ozone and its temporal variability can be achieved using a satellite-based nadir-viewing device making high spectral resolution measurements with high signal-to-noise ratios. This would enable observation in the pressure-broadened wings of strong O3 lines while minimizing the impact of undesirable signal contributions associated with, for example, the terrestrial surface and interfering species. The Fabry-Perot interferometer (FPI) provides high spectral resolution and high throughput capabilities that are essential for this measurement task. The periodic nature of the Fabry-Perot instrument function can be advantageous when observation of periodic spectra is desired. However, for most applications, additional optical elements are necessary to reduce the effect of unwanted passbands. This is frequently accomplished using additional Fabry-Perot etalons in a series configuration in conjunction with a bandpass filter. This paper discusses a Fabry-Perot interferometer conceptual instrument design to achieve tropospheric and total ozone monitoring capability from a satellite-based nadir-viewing geometry. The design involves a double-etalon fixed-gap series configuration FPI along with an ultra-narrow bandpass filter to achieve single-order operation with an overall spectral resolution of approximately .068 cm(exp -1). The impact of inter-etalon reflections has been reduced to acceptable levels by placement of a slightly attenuating medium in between the etalons. A passive device is selected for low power consumption, and continuous day/night coverage, independent of solar zenith angle, is enabled by observing within the strong 9.6 micron ozone infrared band. The IR-FPI detection will be performed through implementation of the new Circle to Line Interferometer Optical (CLIO) system, developed by researchers at the Space Physics Research Laboratory (SPRL) of the University of Michigan, to accomplish focal plane fringe detection; the CLIO system converts the circular interferometric fringes into a linear pattern which then can be detected by conventional linear array detectors. A multiplex signal advantage is achievable as all necessary frequencies can be measured simultaneously using a multichannel configuration. Through proper selection of channel spectral regions, the FPI optimized for tropospheric O3 measurements can simultaneously observe a stratospheric component and thus the total O3 column abundance.

Larar, Allen M.↗

Phenomena Portal: Large- Scale Visual Exploration of Atmospheric Phenomena

The Earth science community is experiencing a high influx of remote sensing data due to recent advancements in sensor technology. This enables the community to extend their research on a larger scale than ever before. Unfortunately, traditional data processing techniques do not scale well to these new, high volume data sources. State-of-the-art machine learning (ML) pipelines have been proven to overcome these burdens in various other fields but are underexploited within the physical sciences community. Moreover, ML is reliant on labeled data, which is currently sparsely available, owing to the fact that ML adoption is still in the early stages within the Earth and atmospheric science communities. To address these issues, we developed the Phenomena Portal, a visual exploration tool that uses ML to detect various atmospheric phenomena on a global scale. This allows the Earth and atmospheric science communities to view trends of occurrences of phenomena, identify potential relationships between them, and analyze spatiotemporal patterns over time. These detections can also serve as initial labeled data for ML research pertaining to the respective phenomena. The tool also incorporates feedback from subject matter experts to further improve the model detection accuracy, thereby facilitating human-in-the-loop. This presentation will provide an overview of the ML model development and cloud deployment. We also discuss the capabilities of the user interface for displaying the detections.

Muthukumaran Ramasubramanian↗

Using Fuzzy Clustering for Real-time Space Flight Safety

To ensure space flight safety, it is necessary to monitor myriad sensor readings on the ground and in flight. Since a space shuttle has many sensors, monitoring data and drawing conclusions from information contained within the data in real time is challenging. The nature of the information can be critical to the success of the mission and safety of the crew and therefore, must be processed with minimal data-processing time. Data analysis algorithms could be used to synthesize sensor readings and compare data associated with normal operation with the data obtained that contain fault patterns to draw conclusions. Detecting abnormal operation during early stages in the transition from safe to unsafe operation requires a large amount of historical data that can be categorized into different classes (non-risk, risk). Even though the 40 years of shuttle flight program has accumulated volumes of historical data, these data don t comprehensively represent all possible fault patterns since fault patterns are usually unknown before the fault occurs. This paper presents a method that uses a similarity measure between fuzzy clusters to detect possible faults in real time. A clustering technique based on a fuzzy equivalence relation is used to characterize temporal data. Data collected during an initial time period are separated into clusters. These clusters are characterized by their centroids. Clusters formed during subsequent time periods are either merged with an existing cluster or added to the cluster list. The resulting list of cluster centroids, called a cluster group, characterizes the behavior of a particular set of temporal data. The degree to which new clusters formed in a subsequent time period are similar to the cluster group is characterized by a similarity measure, q. This method is applied to downlink data from Columbia flights. The results show that this technique can detect an unexpected fault that has not been present in the training data set.

Lee, Charles↗

Information Theoretic Extraction of EEG Features for Monitoring Subject Attention

The goal of this project was to test the applicability of information theoretic learning (feasibility study) to develop new brain computer interfaces (BCI). The difficulty to BCI comes from several aspects: (1) the effective data collection of signals related to cognition; (2) the preprocessing of these signals to extract the relevant information; (3) the pattern recognition methodology to detect reliably the signals related to cognitive states. We only addressed the two last aspects in this research. We started by evaluating an information theoretic measure of distance (Bhattacharyya distance) for BCI performance with good predictive results. We also compared several features to detect the presence of event related desynchronization (ERD) and synchronization (ERS), and concluded that at least for now the bandpass filtering is the best compromise between simplicity and performance. Finally, we implemented several classifiers for temporal - pattern recognition. We found out that the performance of temporal classifiers is superior to static classifiers but not by much. We conclude by stating that the future of BCI should be found in alternate approaches to sense, collect and process the signals created by populations of neurons. Towards this goal, cross-disciplinary teams of neuroscientists and engineers should be funded to approach BCIs from a much more principled view point.

Principe, Jose C.↗

An analysis of fracture trace patterns in areas of flat-lying sedimentary rocks for the detection of buried geologic structure

Two study areas in a cratonic platform underlain by flat-lying sedimentary rocks were analyzed to determine if a quantitative relationship exists between fracture trace patterns and their frequency distributions and subsurface structural closures which might contain petroleum. Fracture trace lengths and frequency (number of fracture traces per unit area) were analyzed by trend surface analysis and length frequency distributions also were compared to a standard Gaussian distribution. Composite rose diagrams of fracture traces were analyzed using a multivariate analysis method which grouped or clustered the rose diagrams and their respective areas on the basis of the behavior of the rays of the rose diagram. Analysis indicates that the lengths of fracture traces are log-normally distributed according to the mapping technique used. Fracture trace frequency appeared higher on the flanks of active structures and lower around passive reef structures. Fracture trace log-mean lengths were shorter over several types of structures, perhaps due to increased fracturing and subsequent erosion. Analysis of rose diagrams using a multivariate technique indicated lithology as the primary control for the lower grouping levels. Groupings at higher levels indicated that areas overlying active structures may be isolated from their neighbors by this technique while passive structures showed no differences which could be isolated.

Podwysocki, M. H.↗

Quantifying Void Ratio Variation in Sand using Computed Tomography

A series of displacement-controlled, conventional, drained axisymmetric (triaxial) experiments were conducted on dry Ottawa sand specimens at very low effective confining stresses in a microgravity environment aboard the Space Shuttle during the NASA STS-89 mission. Post-flight analysis included studying the internal fabric and failure patterns of these specimens using Computed Tomography (CT). The CT scans of three specimens subjected to different compression levels (uncompressed specimen, a specimen compressed to 3.3% nominal axial strain (epsilon(sub a)), and a specimen compressed to 25% epsilon(sub a)) are presented to investigate the evolution of instability patterns and to quantify void ratio variation. The progress of failure is described and discussed. Also, specimens' densities were calibrated using standard ASTM procedures and void ratio spatial variation was calculated and represented by contour maps and histograms. The CT technique demonstrated good ability to detect specimen inhomogeneities, localization patterns, and quantifying void ratio variation within sand specimens.

Alshibli, Khalid A.↗

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/~ge/gedihome.html Supplementary information: http://www.chip.org/~ge/gedihome.html.

Database Management Systems↗

Generating Weighted Test Patterns for VLSI Chips

Improved built-in self-testing circuitry for very-large-scale integrated (VLSI) digital circuits based on version of weighted-test-pattern-generation concept, in which ones and zeros in pseudorandom test patterns occur with probabilities weighted to enhance detection of certain kinds of faults. Requires fewer test patterns and less computation time and occupies less area on circuit chips. Easy to relate switching activity in outputs with fault-detection activity by use of probabilistic fault-detection techniques.

Siavoshi, Fardad↗

Subaru Imaging of Asymmetric Features in a Transitional Disk in a Transitional Disk in Upper Scorpius

We report high-resolution (0.07 arcsec) near-infrared polarized intensity images of the circumstellar disk around the star 2MASS J16042165−2130284 obtained with HiCIAO mounted on the Subaru 8.2 m telescope. We present our H-band data, which clearly exhibit a resolved, face-on disk with a large inner hole for the first time at infrared wavelengths.We detect the centrosymmetric polarization pattern in the circumstellar material as has been observed in other disks. Elliptical fitting gives the semimajor axis, semiminor axis, and position angle (P.A.) of the disk as 63 AU, 62 AU, and −14◦, respectively. The disk is asymmetric, with one dip located at P.A.s of ∼85◦. Our observed disk size agrees well with a previous study of dust and CO emission at submillimeter wavelength with Submillimeter Array. Hence, the near-infrared light is interpreted as scattered light reflected from the inner edge of the disk. Our observations also detect an elongated arc (50 AU) extending over the disk inner hole. It emanates at the inner edge of the western side of the disk, extending inward first, then curving to the northeast. We discuss the possibility that the inner hole, the dip, and the arc that we have observed may be related to the existence of unseen bodies within the disk

protoplanetary disks↗

Subaru Imaging of Asymmetric Features in a Transitional Disk in Upper Scorpius

We report high-resolution (0.07 arcsec) near-infrared polarized intensity images of the circumstellar disk around the star 2MASS J16042165.2130284 obtained with HiCIAO mounted on the Subaru 8.2 m telescope. We present our H-band data, which clearly exhibit a resolved, face-on disk with a large inner hole for the first time at infrared wavelengths. We detect the centrosymmetric polarization pattern in the circumstellar material as has been observed in other disks. Elliptical fitting gives the semi-major axis, semi-minor axis, and position angle (P.A.) of the disk as 63 AU, 62 AU, and -14deg, respectively. The disk is asymmetric, with one dip located at P.A.s of approx. 85deg. Our observed disk size agrees well with a previous study of dust and CO emission at submillimeter wavelength with Submillimeter Array. Hence, the near-infrared light is interpreted as scattered light reflected from the inner edge of the disk. Our observations also detect an elongated arc (50 AU) extending over the disk inner hole. It emanates at the inner edge of the western side of the disk, extending inward first, then curving to the northeast. We discuss the possibility that the inner hole, the dip, and the arc that we have observed may be related to the existence of unseen bodies within the disk.

Mayama, S.↗

Pathfinding for Airspace with Autonomous Vehicles (PAAV) Overview for RTCA SC-228

The Pathfinding for Airspace with Autonomous Vehicles (PAAV) sub-project started in 2021 under NASA’s Air Traffic Management – eXploration (ATM-X) project. ATM-X as a project is conducting research to support the growth of traditional aviation and new entrants. This presentation discusses the background of the PAAV project as well as it’s current areas of focus around uncrewed aircraft system (UAS) operations. The areas include the development of a flight test ecosystem, detect and avoid, traffic pattern integration, aircraft-to-aircraft communications, and contingency management. The aim of these research areas is to help inform the development of performance standards and FAA-approved procedures for integrating UAS into the national airspace system (NAS). The presentation seeks to describe the PAAV research objectives in sufficient detail to allow the committee to provide feedback on the sub-project's approach and main areas of interest.

uncrewed aircraft systems↗