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At least 91 records · Page 5

Spatial and temporal filtering technique for processing lidar photocount data

Shot noise places a practical limit on the spatial and temporal resolution of lidar photocount data. A 2-D signal-processing technique that utilizes spatial and temporal filtering to reduce shot noise and increase resolution is described. The technique is applied to sodium lidar data collected during the fall of 1979 over Urbana, Illinois. Temporal filtering is shown to enhance the spatial resolution of the sodium profiles significantly by reducing shot noise by more than 10 dB. The signal-processing technique is applicable to a wide variety of lidar data.

Gardner, C. S.↗

Approximate spatial reasoning

A model for approximate spatial reasoning using fuzzy logic to represent the uncertainty in the environment is presented. Algorithms are developed which can be used to reason about spatial information expressed in the form of approximate linguistic descriptions similar to the kind of spatial information processed by humans. Particular attention is given to static spatial reasoning.

Dutta, Soumitra↗

Research into the influence of spatial variability and scale on the parameterization of hydrological processes

The objectives of the research were as follows: (1) Extend the Representative Elementary Area (RE) concept, first proposed and developed in Wood et al, (1988), to the water balance fluxes of the interstorm period (redistribution, evapotranspiration and baseflow) necessary for the analysis of long-term water balance processes. (2) Derive spatially averaged water balance model equations for spatially variable soil, topography and vegetation, over A RANGE OF CLIMATES. This is a necessary step in our goal to derive consistent hydrologic results up to GCM grid scales necessary for global climate modeling. (3) Apply the above macroscale water balance equations with remotely sensed data and begin to explore the feasibility of parameterizing the water balance constitutive equations at GCM grid scale.

Wood, Eric F.↗

Localized Defect Detection from Spatially Mapped, In-Situ Process Data With Machine Learning

In powder bed fusion additive manufacturing, machines are often equipped with in-situ sensors to monitor the build environment as well as machine actuators and subsystems. The data from these sensors offer rich information about the consistency of the fabrication process within a build and across builds. This information may be used for process monitoring and defect detection; however, little has been done to leverage this data from the machines for more than just coarse-grained process monitoring. In this work we demonstrate how these inherently temporal data may be mapped spatially by leveraging scan path information. We then train a XGBoost machine learning model to predict localized defects—specifically soot–using only the mapped process data of builds from a laser powder bed fusion process as input features. The XGBoost model offers a feature importance metric that will help to elucidate possible relationships between the process data and observed defects. Finally, we analyze the model performance spatially and rationalize areas of greater and lesser performance.

3D printing↗

Continental-scale niche differentiation of dominant topsoil archaea in drylands

Archaea represent a diverse group of microorganisms often associated with extreme environments. However, an integrated understanding of biogeographical patterns of the specialist Haloarchaea and the potential generalist ammonia-oxidizing archaea (AOA) across large-scale environmental gradients remains limited. Here, we hypothesize that niche differentiation determines their distinct distributions along environmental gradients. To test the hypothesis, we use a continental-scale research network including 173 dryland sites across northern China. Our results demonstrate that Haloarchaea and AOA dominate topsoil archaeal communities. As hypothesized, Haloarchaea and AOA show strong niche differentiation associated with two ecosystem types mainly found in China's drylands (i.e. deserts vs. grasslands), and they differ in the degree of habitat specialization. The relative abundance and richness of Haloarchaea are higher in deserts due to specialization to relatively high soil salinity and extreme climates, while those of AOA are greater in grassland soils. Our results further indicate a divergence in ecological processes underlying the segregated distributions of Haloarchaea and AOA. Haloarchaea are governed primarily by environmental-based processes while the more generalist AOA are assembled mostly via spatial-based processes. Our findings add to existing knowledge of large-scale biogeography of topsoil archaea, advancing our predictive understanding on changes in topsoil archaeal communities in a drier world.

54 ENVIRONMENTAL SCIENCES↗

Twenty Years of Terra MODIS Spatial Performance Using the Spectro-Radiometric Calibration Assembly

The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on-board the NASA’s Earth Observing System Terra satellite has continued successful Earth-sensing operations for over 20 years. To aid in its mission in providing calibrated science data to the worldwide user community, the MODIS instrument is equipped with several on-board calibrators designed to measure changes in the instrument response over time. One such calibrator is the Spectro-Radiometric Calibration Assembly (SRCA), which can provide a source signal for radiometric, spectral, or spatial characterization. When commanded into its spatial calibration mode, the SRCA is able to produce light across the MODIS band spectral range (0.412μm to 14.2μm) at a variety of signal levels thanks to several internal halogen lamps, an IR glow bar, and a neutral density filter. This signal, used in combination with commanded sub-sample measurements of the MODIS detectors, provides a basis for determining changes in the spatial performance of the MODIS spectral bands. This work summarizes the spatial calibration process using the SRCA and presents 20 years of Terra MODIS spatial performance characterized through co-registration between MODIS bands, detectors, and focal plane assemblies. Results from pre-launch testing using the Integration and Alignment Collimator and the SRCA are incorporated in the history of the Terra MODIS mission-long spatial performance. We also note modifications to the spatial characterization methodology brought on by changes to the SRCA’s operational configuration and changes to the MODIS spectral band performance, particularly after the recovery from the safe-mode event in February 2016. Results are compared against the MODIS design specifications.

MODIS↗

Master equation for plasmas.

Master equation derived for irreversible evolution of n-momenta distribution function for spatially homogeneous stable plasma

IRREVERSIBLE PROCESS↗

BOREAS HYD-8 Gross Precipitation Data

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-08 team made measurements of surface hydrological processes at the Southern Study Area-Old Black Spruce (SSA-OBS) Tower Flux site to support its research into point hydrological processes and the spatial variation of these processes. Data collected may be useful in characterizing canopy interception, drip, throughfall, moss interception, drainage, evaporation, and capacity during the growing season at daily temporal resolution. This particular data set contains the gross precipitation measurements for July to August 1996. Gross precipitation is the precipitation that falls that is not intercepted by tree canopies. These data are stored in ASCII text files. The HYD-08 gross precipitation data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Fernandes, Richard↗

Deep Cellular Recurrent Network for Efficient Analysis of Time-Series Data With Spatial Information

Efficient processing of large-scale time series data is an intricate problem in machine learning. Conventional sensor signal processing pipelines with hand engineered feature extraction often involve huge computational cost with high dimensional data. Deep recurrent neural networks have shown promise in automated feature learning for improved time-series processing. However, generic deep recurrent models grow in scale and depth with increased complexity of the data. This is particularly challenging in presence of high dimensional data with temporal and spatial characteristics. Consequently, this work proposes a novel deep cellular recurrent neural network (DCRNN) architecture to efficiently process complex multi-dimensional time series data with spatial information. Here, the cellular recurrent architecture in the proposed model allows for location-aware synchronous processing of time series data from spatially distributed sensor signal sources. Extensive trainable parameter sharing due to cellularity in the proposed architecture ensures efficiency in the use of recurrent processing units with high-dimensional inputs. This study also investigates the versatility of the proposed DCRNN model for classification of multi-class time series data from different application domains. Consequently, the proposed DCRNN architecture is evaluated using two time-series datasets: a multichannel scalp EEG dataset for seizure detection, and a machine fault detection dataset obtained in-house. The results suggest that the proposed architecture achieves state-of-the-art performance while utilizing substantially less trainable parameters when compared to comparable methods in the literature.

60 APPLIED LIFE SCIENCES↗

Multimodal Analysis of Spatially Heterogeneous Microstructural Refinement and Softening Mechanisms in Three-Pass Friction Stir Processed Al4Si Alloy

Multiple thermally and thermomechanically induced microstructural refinement mechanisms can be activated in metallic alloys when subjected to solid phase processing methods such as friction stir processing (FSP). In this work, we provide detailed descriptions of the relationship between region-specific microstructural refinement mechanisms and the variation in microhardness, through a systematic and multimodal microstructural characterization of an FSP-processed 75% cold-rolled Al-4 at.% Si model binary alloy. Spatially resolved high-energy synchrotron X-ray diffraction, electron backscattered diffraction, and scanning transmission electron microscopy were used to understand the spatially heterogeneous microstructural evolution due to FSP. Results provide insights into how mechanisms such as static recovery, static recrystallization, dynamic recovery and recrystallization, geometric and continuous dynamic recrystallization, and particle-stimulated static or dynamic grain nucleation may occur heterogeneously in the microstructure as a function of the distance from the stir zone in processed alloys, directly influencing the degree of softening. The systematic analysis of microstructures and hardness in the FSP-processed model binary alloy given in this work highlights the rich microstructural domains that can be uniquely harnessed through solid phase processing of metallic alloys.

Al4Si, Friction Stir Processing, Geometric Dynamic↗

The role of spatial attention in visual word processing

Subjects made lexical decisions on a target letter string presented above or below fixation. In Experiments 1 and 2, target location was cued 100 ms in advance of target onset. Responses were faster on validly than on invalidly cued trials. In Experiment 3, the target was sometimes accompanied by irrelevant stimuli on the other side of fixation; in such cases, responses were slowed (a spatial filtering effect). Both cuing and filtering effects on response time were additive with effects of word frequency and lexical status (words vs. nonwords). These findings are difficult to reconcile with claims that spatial attention is less involved in processing familiar words than in unfamiliar words and nonwords. The results can be reconciled with a late-selection locus of spatial attention only with difficulty, but are easily explained by early-selection models.

Mccann, Robert S.↗

Impact of Universal Plasma and Energetic Particle Processes on Icy Bodies of the Kuiper Belt and the Oort Cloud

Modeling of space plasma and energetic particle interactions with icy bodies of the outer solar system is simplified when there is commonality of the underlying source, acceleration, and transport processes in spatially distinct regions from the supersonic heliosphere through the heliosheath into the local interstellar medium (LISM). Current trends in the Voyager heliosheath measurements suggest strong commonality to processes in the LISM. The Fisk-Gloeckler "universal" spectrum at suprathermal energies apparently plays a strong role in coupling the plasma and high energy particle regimes in the spatial and energetic transitions from the outer heliosphere to the LISM. Dominant processes in consecutive energy regimes project to varying effects versus irradiation depth on exposed upper surfaces of airless small icy bodies and to upper atmospheres of larger bodies such as Titan and Pluto. Relative absence of the universal suprathermal spectrum in the mid-heliospheric region of the classical Kuiper Belt may profoundly affect surface color diversity of icy bodies in this region.

Cooper, John F.↗

A hybrid silicon membrane spatial light modulator for optical information processing

A new two dimensional, fast, analog, electrically addressable, silicon based membrane spatial light modulator (SLM) was developed for optical information processing applications. Coherent light reflected from the mirror elements is phase modulated producing an optical Fourier transform of an analog signal input to the device. The DMD architecture and operating parameters related to this application are presented. A model is developed that describes the optical Fourier transform properties of the DMD.

Pape, D. R.↗

Spatial and temporal variability of the extent of chemically processed stratospheric air

Simulations of the spatial and temporal variability of the extent of chemically processed air in the Arctic stratosphere have been carried out using a three-dimensional chemistry-transport model for the winters of 1979 and 1989. Chemically processed air is identified in the model as that in which the amounts of hydrogen chloride (HCl) calculated with parameterized loss for conditions appropriate to polar stratospheric cloud (PSC) formation are substantially smaller than those calculated in a model with gas phase chemistry only. It is seen that chemically processed air may be identified over much of the Arctic lower stratosphere from early January to late February, with HCl depletions being larger in 1989 than in 1979. Near the latitude of the Arctic circle, there is important spatial and temporal variability in the extent of chemically processed air. There is some evidence for transport to midlatitudes of processed air during these winters, but the HCl reductions are much smaller and more sporadic than those near the pole. At 62 and 42N, processed air is calculated to occur preferentially over the longitude regions from 60-120E and 270-330E.

Kaye, Jack A.↗

Trends in spatial correlations, two-phase coexistence, and criticality in a class of type-2 Schloegl models for autocatalysis

A class of type-2 Schloegl models is considered for particles on a square lattice with variable-range cooperativity. These models involve: (i) spontaneous particle annihilation at rate p; (ii) autocatalytic particle creation at unoccupied sites (i, j) with n ⩾ 2 particles within a specified neighborhood, Ω 𝑁 (i, j), of sites at rate $k_n$ = $\frac{^{(^n_2)}}{_{(^N_2)}}$ = $\frac{n{(n-1)}}{_{N(N-1)}}$; and (iii) possible spontaneous particle creation at unoccupied sites at “small” rate ɛ ⩾ 0. In some cases, Ω 𝑁 just includes all symmetry-equivalent sites at a single specific distance 𝑑 (in units of lattice constants) from the unoccupied site, e.g., 𝑑 = 1 (nearest-neighbor sites) where 𝑁 = 4, or 𝑑 = √5 (or √13 or…) where 𝑁 = 8. In other cases, Ω 𝑁 includes sites multiple distances from the unoccupied site, e.g., 𝑑 = {1,√2}, where 𝑁 = 8. Kinetic Monte Carlo (KMC) simulation reveals that these models exhibit a nonequilibrium discontinuous phase transition between high- and low-density states below a critical point, ɛ < ɛ c , with generic two-phase coexistence (2PC) at least for smaller 𝑁. With some exceptions, there is an approach toward mean-field behavior with increasing 𝑁 (so the regime of generic 2PC shrinks, and ɛ c approaches the mean-field value of 1/27). Additional insight into trends is provided by analysis of the exact master equations for the models via hierarchical truncation. These truncations utilize suitably tailored pair approximations which reflect the dominant nonequilibrium spatial correlations. These correlations in turn are shown to reflect the details of the autocatalytic particle creation process. For spatially heterogeneous states, the truncations produce coupled sets of lattice differential equations (LDE) which can describe orientation-dependent propagation of an interface between high- and low-density steady states for ɛ < ɛ c . Pair approximation values of 𝑝 = 𝑝 eq where the interface is stationary, and its orientation-dependence, are in semiquantitative agreement with KMC results. In conclusion, this comparison accounts for propagation failure in the LDE which complicates interpretation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Morphostatistical characterization of the spatial galaxy distribution through Gibbs point processes

ABSTRACT This paper proposes a morphostatistical characterization of the galaxy distribution through spatial statistical modelling based on inhomogeneous Gibbs point processes. The galaxy distribution is supposed to exhibit two components. The first one is related to the major geometrical features exhibited by the observed galaxy field, here, its corresponding filamentary pattern. The second one is related to the interactions exhibited by the galaxies. Gibbs point processes are statistical models able to integrate these two aspects in a probability density, controlled by some parameters. Several such models are fitted to real observational data via the ABC shadow algorithm. This algorithm provides simultaneous parameter estimation and posterior-based inference, hence allowing the derivation of the statistical significance of the obtained results.

79 ASTRONOMY AND ASTROPHYSICS↗

System considerations for an earth radiation budget scanning radiometer

The objective of the scanning radiometer of the Earth Radiation Budget Satellite System is to measure the longwave and reflected shortwave radiation from the earth on a gridwork of approximately 250 km square regions in order to obtain one-month averages of flux with global coverage to an accuracy of 14 W/sq m. A number of considerations in the choice of some of the design parameters of the scanner are discussed. The error sources which must be considered in the design of a scanning radiometer designed to measure regional radiation budget are examined. An analysis of the system performance through spatial averaging is presented. The analysis provides insight into the effects of field of view, time response, onboard processing and spatial averaging.

Smith, G. L.↗

Real time quantitative imaging for semiconductor crystal growth, control and characterization

A quantitative real time image processing system has been developed which can be software-reconfigured for semiconductor processing and characterization tasks. In thermal imager mode, 2D temperature distributions of semiconductor melt surfaces (900-1600 C) can be obtained with temperature and spatial resolutions better than 0.5 C and 0.5 mm, respectively, as demonstrated by analysis of melt surface thermal distributions. Temporal and spatial image processing techniques and multitasking computational capabilities convert such thermal imaging into a multimode sensor for crystal growth control. A second configuration of the image processing engine in conjunction with bright and dark field transmission optics is used to nonintrusively determine the microdistribution of free charge carriers and submicron sized crystalline defects in semiconductors. The IR absorption characteristics of wafers are determined with 10-micron spatial resolution and, after calibration, are converted into charge carrier density.

Wargo, Michael J.↗