Search NASA⌕ Search

SEARCH · Search NASA

Results for “pattern detection”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Effects of antenna beam chromaticity on redshifted 21 cm power spectrum and implications for hydrogen epoch of reionization array

Unaccounted for systematics from foregrounds and instruments can severely limit the sensitivity of current experiments from detecting redshifted 21 cm signals from the Epoch of Reionization (EoR). Upcoming experiments are faced with a challenge to deliver more collecting area per antenna element without degrading the data with systematics. This paper and its companions show that dishes are viable for achieving this balance using the Hydrogen Epoch of Reionization Array (HERA) as an example. Here, we specifically identify spectral systematics associated with the antenna power pattern as a significant detriment to all EoR experiments which causes the already bright foreground power to leak well beyond ideal limits and contaminate the otherwise clean EoR signal modes. A primary source of this chromaticity is reflections in the antenna-feed assembly and between structures in neighboring antennas. Using precise foreground simulations taking wide-field effects into account, we provide a generic framework to set cosmologically motivated design specifications on these reflections to prevent further EoR signal degradation. We show that HERA will not be impeded by such spectral systematics and demonstrate that even in a conservative scenario that does not perform removal of foregrounds, HERA will detect the EoR signal in line-of-sight k-modes, k{sub ∥}≳0.2 h Mpc{sup −1}, with high significance. Under these conditions, all baselines in a 19-element HERA layout are capable of detecting EoR over a substantial observing window on the sky.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Respiration Signal Pattern Analysis for Doppler Radar Sensor with Passive Node and Its Application in Occupancy Sensing of a Stationary Subject

Doppler radar node occupancy sensors are promising for applications in smart buildings due to their simple circuits and price advantage compared to quadrature radar sensors. However, single-channel sensitivity limitations may result in low sensitivity and misinterpreted motion rates if the detected subject is at or close to “null” points. We designed and tested a novel method to eliminate such limits, demonstrating that passive nodes can be used to detect a sedentary person regardless of position. This method is based on characteristics of chest motion due to respiration, found via both simulations and experiments based on a sinusoidal model and a more realistic model of cardiorespiratory motion. In addition, respiratory rate variability is considered to distinguish a true human presence from a mechanical target. Sensor node data were collected simultaneously with an infrared camera system, which provided a respiration signal reference, to test the algorithm with 19 human subjects and a mechanical target. The results indicate that a human presence was detected with 100% accuracy and successfully differentiated from a mechanical target in a controlled environment. The developed method can greatly improve the occupancy detection accuracy of single-channel radar-based occupancy sensors and facilitate their adoption in smart building applications.

Song, Chenyan↗
NASA NTRS1985

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

Guseman, L. F., Jr.↗
NASA NTRSDate not supplied

Detecting And Characterizing Archetypes of Unintended Consequences in Engineered Systems

When designing engineered systems, the potential for unintended consequences of design policies or design decisions exists despite best intentions. Conditions that might cause the formation of unintended consequences are often known only in hindsight. However, since these conditions are associated with a single event, it is difficult to uncover the general patterns of conditions leading to unintended consequences. In this research, patterns of conditions associated with unintended consequences are learned from historical data and represented in the form of archetypes. While previous work using systems theoretic modeling has identified high-level archetypes, this work leverages a self-organizing map to learn archetypes of unintended consequences from human-tagged risk factors in a large data set of lessons learned from adverse events at NASA. The sixty-six identified archetypes contain patterns of conditions such as complexity and human-machine interaction associated with the formation of unintended consequences. To validate the archetypes, a sample of the archetypes is represented using system dynamics in order to illustrate that the identified archetypes are specialized versions of known high-level archetypes of unintended consequences. While the research is based upon a specific dataset, the archetypes apply to any engineered system and the pattern of leading indicators open a new path to manage unintended consequences and mitigate the magnitude of potentially adverse outcomes.

Hannah S Walsh↗
DOE OSTI2023

Scalable Incremental Checkpointing using GPU-Accelerated De-Duplication

Writing large amounts of data concurrently to stable storage is a typical I/O pattern of many HPC workflows. This pattern introduces high I/O overheads and results in increased storage space utilization especially for workflows that need to capture the evolution of data structures with high frequency as checkpoints. In this context, many applications, such as graph pattern matching, perform sparse updates to large data structures between checkpoints. For these applications, incremental checkpointing techniques that save only the differences from one checkpoint to another can dramatically reduce the checkpoint sizes, I/O bottlenecks, and storage space utilization. However, such techniques are not without challenges: it is non-trivial to transparently determine what data has changed since a previous checkpoint and assemble the differences in a compact fashion that does not result in excessive metadata. State-of-art data reduction techniques (e.g., compression and de-duplication) have significant limitations when applied to modern HPC applications that leverage GPUs: slow at detecting the differences, generate a large amount of metadata to keep track of the differences, and ignore crucial spatiotemporal checkpoint data redundancy. This paper addresses these challenges by proposing a Merkle tree-based incremental checkpointing method to exploit GPUs' high memory bandwidth and massive parallelism. Experimental results at scale show a significant reduction of the I/O overhead and space utilization of checkpointing compared with state-of-the-art incremental checkpointing and compression techniques.

Tan, Nigel↗
DOE OSTI2015

An optimization of the FPGA trigger based on the artificial neural network for a detection of neutrino-origin showers

Observations of ultra-high energy neutrinos became a priority in experimental astro-particle physics. Up to now, the Pierre Auger Observatory did not find any candidate on a neutrino event. This imposes competitive limits to the diffuse flux of ultra-high energy neutrinos in the EeV range and above. A very low rate of events potentially generated by neutrinos is a significant challenge for a detection technique and requires both sophisticated algorithms and high-resolution hardware. A trigger based on a artificial neural network was implemented into the Cyclone{sup R} V E FPGA 5CEFA9F31I7. The prototype Front-End boards for Auger-Beyond-2015 with Cyclone{sup R} V E can test the neural network algorithm in real pampas conditions in 2015. Showers for muon and tau neutrino initiating particles on various altitudes, angles and energies were simulated in CORSICA and Offline platforms giving pattern of ADC traces in Auger water Cherenkov detectors. The 3-layer 12-10-1 neural network was taught in MATLAB by simulated ADC traces according the Levenberg-Marquardt algorithm. Results show that a probability of a ADC traces generation is very low due to a small neutrino cross-section. Nevertheless, ADC traces, if occur, for 1-10 EeV showers are relatively short and can be analyzed by 16-point input algorithm. For 100 EeV range traces are much longer, but with significantly higher amplitudes, which can be detected by standard threshold algorithms. We optimized the coefficients from MATLAB to get a maximal range of potentially registered events and for fixed-point FPGA processing to minimize calculation errors. Currently used Front-End boards based on no-more produced ACEXR PLDs and obsolete Cyclone{sup R} FPGAs allow an implementation of relatively simple threshold algorithms for triggers. New sophisticated trigger implemented in Cyclone{sup R} V E FPGAs with large amount of DSP blocks, embedded memory running with 120 - 160 MHz sampling may support to discover neutrino events in the Pierre Auger Observatory. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Power grid frequency prediction using spatiotemporal modeling

Understanding power system dynamics is essential for interarea oscillation analysis and the detection of grid instabilities. The FNET/GridEye is a GPS-synchronized wide-area frequency measurement network that provides an accurate picture of the normal real-time operational condition of the power system-dynamics, giving rise to new and intricate spatiotemporal patterns of power loads. We propose to model FNET/GridEye grid frequency data from the U.S. Eastern Interconnection with a spatiotemporal statistical model. We predict the frequency data at locations without observations, a critical need during disruption events where measurement data are inaccessible. Spatial information is accounted for either as neighboring measurements in the form of covariates or with a spatiotemporal correlation model captured by a latent Gaussian field. Finally, the proposed method is useful in estimating power system dynamic response from limited phasor measurements and holds promise for predicting instability that may lead to undesirable effects such as cascading outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Combining Mass Spectrometry of Picoliter Samples with a Multicompartment Electrodynamic Trap for Probing the Chemistry of Droplet Arrays

Single droplet levitation provides contactless access to the microphysical and chemical properties of micrometer-sized samples. Most applications of droplet levitation to chemical and biological systems use nondestructive optical techniques to probe droplet properties. To provide improved chemical specificity, we coupled a multicompartment quadrupole electrodynamic trap (QET) with single droplet mass spectrometry. Our QET continuously traps a monodisperse droplet population (tens to hundreds of droplets) and allows for the simultaneous sizing of a single droplet using its Mie scattering pattern. Single droplets are subsequently ejected into the ionization region of an ambient pressure inlet mass spectrometer. We optimized two complementary soft ionization techniques for picoliter aqueous droplets: (1) paper spray (PS) ionization and (2) thermal desorption glow discharge (TDGD) ionization. Both techniques detect oxygenated organic acids in single droplets, with signal-to-noise ratios >100 and detection limits on the order of 10 pg. Sensitivity and reproducibility across single droplets are driven by the droplet deposition location and spray stability in PS-MS and the ionization region humidity and analyte evaporation rate in TDGD-MS. Importantly, the analyte evaporation rate can control the TDGD-MS quantitative capability because high evaporation rates result in significant ion suppression. Additionally, this effect is mitigated by optimizing the vaporization temperature, droplet size range, and analyte volatility. We demonstrate quantitative and reproducible measurements with a droplet internal standard (<10% RSD) and compare the sensitivity of PS-MS and TDGD-MS. Finally, we demonstrate the application of QET-MS to the study of heterogeneous chemical kinetics with the reaction of gas phase O 3 and aqueous maleic acid droplets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Synergistic Removal of Zinc and Copper in Greenhouse Waste Effluent by Struvite

Struvite (MgNH 4 PO 4 ·6H 2 O) can be recovered from wastewaters for mitigation of phosphorus content. However, the interaction of dissolved constituents with struvite is rarely evaluated. Removal of heavy metals and total organic carbon (TOC) in a greenhouse wastewater (GW) by struvite was investigated in this work. Presynthesized struvite was added to GW and removal of Zn (689 μg/L), Cu (151 μg/L), and TOC (51 mg/L) monitored from 1 to 26 d. Metal uptake in sodium nitrate solutions was used to assess competition, and the influence of other GW constituents on sorption. Struvite was also directly precipitated from GW (PPT). Recovered GW solids had 64–247 mg/kg Zn, 12–54 mg/kg Cu, and 1721–8806 mg/kg TOC, with lowest loadings for PPT and highest for 26 d solids. X-ray absorption spectroscopy detected polymerized Zn-phosphate, induced by dissolved phosphorus in GW, and Cu copolymerization, initially limited by aqueous Cu-organic complexation. Sorbed Cu shifts Fourier transform infrared-sensitive phosphate bands and changes the intensities of reflections in X-ray diffraction patterns of struvite more so than Zn. Struvite from GW is more susceptible to thermal decomposition than unreacted struvite, evolving CO(g), CO 2 (g), NH 3 (g), and H 2 O(g). Therefore, struvite from GW sorbs metals and organics, and can release sorbed and structural components to the aqueous and gas phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

All-in-all-out magnetic domain size in pyrochlore iridate thin films as probed by local magnetotransport

Pyrochlore iridates have attracted growing attention because of a theoretical prediction of a possible topological semimetal phase originating from all-in-all-out spin ordering. Related to the topological band structure, recent findings of the magnetic domain wall conduction have stimulated investigations of magnetic domain distribution in this system. Here, we investigate the size of magnetic domains in Eu{sub 2}Ir{sub 2}O{sub 7} single crystalline thin films by magnetoresistance (MR) using microscale Hall bars. Two distinct magnetic domains of the all-in-all-out spin structure are known to exhibit linear MR but with opposite signs, which enables us to estimate the ratio of the two domains in the patterned channel. The linear MR for 80 × 60 μm{sup 2} channel is nearly zero after zero-field cooling, suggesting random distribution of domains smaller than the channel size. In contrast, the wide distribution of the value of the linear MR is detected in 2 × 2 μm{sup 2} channel, reflecting the detectable domain size depending on each cooling-cycle. Compared to simulation results, we estimate the average size of a single all-in-all-out magnetic domain as 1–2 μm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Development of a wide bandwidth heterodyne dispersion interferometer for electron density measurement of atmospheric pressure plasmas

One of the challenges of electron density measurements of an atmospheric pressure plasma (APP) with a laser interferometer is the significant and unwanted phase shift caused by changes in the neutral gas density. These unwanted phase shifts can be mitigated and plasma density measured using an interferometer architecture called a dispersion interferometer (DI). A DI is composed of two nonlinear orientation patterned GaAs crystals for frequency doubling and measures the phase shift induced by a plasma in the interference signal between two second-harmonic beams. Measurement of plasma dynamics or a short plasma pulse in less than a millisecond is enabled with heterodyne detection in a DI using an acousto-optic cell with a frequency of 40 MHz. This heterodyne DI (HDI) is targeted to measure APPs in an electron density range of 10 20 –10 24 m −3 . Finally, the HDI achieves a line-integrated density resolution of 2 × 10 15 m −2 (a phase resolution of 0.005°) with a time constant of 1 μs using ensemble averaging techniques.

atmospheric pressure plasma↗
DOE OSTI2016

Science with the space-based interferometer LISA. IV: probing inflation with gravitational waves

We investigate the potential for the LISA space-based interferometer to detect the stochastic gravitational wave background produced from different mechanisms during inflation. Focusing on well-motivated scenarios, we study the resulting contributions from particle production during inflation, inflationary spectator fields with varying speed of sound, effective field theories of inflation with specific patterns of symmetry breaking and models leading to the formation of primordial black holes. The projected sensitivities of LISA are used in a model-independent way for various detector designs and configurations. We demonstrate that LISA is able to probe these well-motivated inflationary scenarios beyond the irreducible vacuum tensor modes expected from any inflationary background.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

SU-F-T-549: Validation of a Method for in Vivo 3D Dose Reconstruction for SBRT Using a New Transmission Detector

Purpose: Recently, there has been increased clinical use of stereotactic body radiation therapy (SBRT). SBRT treatments will strongly benefit from in vivo patient dose verification, as any errors in delivery can be more detrimental to the radiobiology of the patient as compared to conventional therapy. In vivo dose measurements, a commercially available quality assurance platform which is able to correlate the delivered dose to the patient’s anatomy and take into account tissue inhomogeneity, is the COMPASS system (IBA Dosimetry, Germany) using a new transmission detector (Dolphin, IBA Dosimetry). In this work, we evaluate a method for in vivo 3D dose reconstruction for SBRT using a new transmission detector, which was developed for in vivo dose verification for intensity-modulated radiation therapy (IMRT). Methods: We evaluated the accuracy of measurement for SBRT using simple small fields (2×2−10×10 cm2), a multileaf collimator (MLC) test pattern, and clinical cases. The dose distributions from the COMPASS were compared with those of EDR2 films (Kodak, USA) and the Monte Carlo simulations (MC). For clinical cases, we compared MC using dose-volume-histograms (DVHs) and dose profiles. Results: The dose profiles from the COMPASS for small fields and the complicated MLC test pattern agreed with those of EDR2 films, and MC within 3%. This showed the COMPASS with Dolphin system showed good spatial resolution and can measure small fields which are required for SBRT. Those results also suggest that COMPASS with Dolphin is able to detect MLC leaf position errors for SBRT. In clinical cases, the COMPASS with Dolphin agreed well with MC. The Dolphin detector, which consists of ionization chambers, provided stable measurement. Conclusion: COMPASS with Dolphin detector showed a useful in vivo 3D dose reconstruction for SBRT. The accuracy of the results indicates that this approach is suitable for clinical implementation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Automated Threat Recognition For Aviation Security Applications

We have developed a framework for automated threat recognition (ATR) of explosive threat materials for both single-energy and dual-energy X-ray CT systems. Under this framework, two different types of ATR have been developed. The first type of ATR employs supervised machine learning with statistical characterization of target materials for threat identification training. The reliance only on statistical characterization information for threat training uniquely enables this style of ATR to adapt quickly to evolving threats. The second type of ATR employs deep learning through convolutional neural networks. Convolutional neural networks are attractive due to their human-like capacity for learning and strong ability to identify trends and patterns. Although this method is more powerful than the first type, it requires large amounts of training data and therefore is less agile. Each ATR performs threat characterization at the voxel neighborhood level. This approach avoids the use of threat shape as a detection criterion, which is prohibited by DHS and TSA guidelines.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Geographic patterns and determinants of antibiotic resistomes in coastal sediments across complex ecological gradients

Coastal areas are highly influenced by terrestrial runoffs and anthropogenic disturbances, commonly leading to ecological gradients from bay, nearshore, to offshore areas. Although the occurrence and distribution of sediment antibiotic resistome are explored in various coastal environments, little information is available regarding geographic patterns and determinants of coastal sediment antibiotic resistomes across ecological gradients at the regional scale. Here, using high-throughput quantitative PCR, we investigated the geographic patterns of 285 antibiotic resistance genes (ARGs) in coastal sediments across a ~ 200 km scale in the East China Sea. Sediment bacterial communities and physicochemical properties were characterized to identify the determinants of sediments antibiotic resistome. Higher richness and abundance of ARGs were detected in the bay samples compared with those in nearshore and offshore samples, and significant negative correlations between the richness and/or abundance of ARGs and the distance to coastline (DTC) were identified, whereas different types of ARGs showed inconsistency in their relationships with DTC. The composition of antibiotic resistome showed significant correlations with nutrition-related variables (including NH 4 + -N, NO 3 − -N, and total phosphorus) and metals/metalloid (including As, Cu, Ni, and Zn), suggesting that terrestrial disturbances largely shape the antibiotic resistome. The Bipartite network showed strong associations between ARGs and mobile genetic elements (MGEs), and Partial Least Squares Path Modeling further revealed that terrestrial disturbance strength (as indicated by DTC) directly affected abiotic environmental conditions and bacterial community composition, and indirectly affected antibiotic resistome via MGEs. These findings provide insights into regional variability of sediment antibiotic resistome and its shaping path across complex ecological gradients, highlighting terrestrial disturbances as determinative forces in shaping coastal sediment antibiotic resistomes.

Xiong, Shangling↗
NASA NTRS1973

Dynamics of suspended sediment in Lake Ontario

The author has identified the following significant results. The suspended sediment plumes generated by the Welland Canal and the Genesee River are identifiable in most band 5 frames received from ERTS-1. In descending order of value for plume detection in Lake Ontario are bands 4, 6, and 7. Little or no information content relative to plume detection is available in band 7. The Oswego River plume was not visible during low flow periods; however, it was identifiable immediately following storms. Increased suspended sediment loading emanating from storm runoff increases turbidity levels to the point where the plume becomes visible in the ERTS-1 imagery. Despite the fact that it is detectable from high altitude (60,000 feet) photography, the Niagara River plume was not visible in any of the ERTS-1 frames. Numerous examples of shoreline erosion were evident in the December 7, 1972, imagery of western Lake Ontario. Near shore lake circulation patterns are usually apparent whenever turbidity plumes are sensed by the satellite.

Pluhowski, E. J.↗