Quantitative voxel-to-voxel comparison of TriBeam and DCT strontium titanate three-dimensional data sets

2015 ◽  
Vol 48 (4) ◽  
pp. 1034-1046 ◽  
Author(s):  
William C. Lenthe ◽  
McLean P. Echlin ◽  
Andreas Trenkle ◽  
Melanie Syha ◽  
Peter Gumbsch ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Strontium Titanate ◽  
Spatial Resolution ◽  
Reference Frames ◽  
Three Dimensional ◽  
Data Sets ◽  
Reconstruction Method ◽  
Data Set ◽  
Time Resolved ◽  
Tomographic Data

Recently, techniques for the acquisition of three-dimensional tomographic and four-dimensional time-resolved data sets have emerged, allowing for the analysis of mm3volumes of material with nm-scale resolution. The ability to merge multi-modal data sets acquiredviamultiple techniques for the quantitative analysis of structure, chemistry and phase information is still a significant challenge. Large three-dimensional data sets have been acquired by time-resolved diffraction contrast tomography (DCT) and a new TriBeam tomography technique with high spatial resolution to address grain growth in strontium titanate. A methodology for combining three-dimensional tomographic data has been developed. Algorithms for the alignment of orientation reference frames, unification of sampling grids and automated grain matching have been integrated, and the resulting merged data set permits the simultaneous analysis of all tomographic data on a voxel-by-voxel and grain-by-grain basis. Quantitative analysis of merged data sets collected using DCT and TriBeam tomography shows that the spatial resolution of the DCT technique is limited near grain boundaries and the sample edge, resolving grains down to 10 µm diameter for the reconstruction method used. While the TriBeam technique allows for higher-resolution analysis of boundary plane location, it is a destructive tomography approach and can only be employed at the conclusion of a four-dimensional experiment.

scholarly journals Water vapor mapping by fusing InSAR and GNSS remote sensing data and atmospheric simulations

2015 ◽  
Vol 19 (12) ◽  
pp. 4747-4764 ◽  
Author(s):  
F. Alshawaf ◽  
B. Fersch ◽  
S. Hinz ◽  
H. Kunstmann ◽  
M. Mayer ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapor ◽  
Data Fusion ◽  
Spatial Resolution ◽  
Heterogeneous Data ◽  
Spatial Density ◽  
Data Sets ◽  
Data Set ◽  
Fixed Rank Kriging ◽  
Fixed Rank

Abstract. Data fusion aims at integrating multiple data sources that can be redundant or complementary to produce complete, accurate information of the parameter of interest. In this work, data fusion of precipitable water vapor (PWV) estimated from remote sensing observations and data from the Weather Research and Forecasting (WRF) modeling system are applied to provide complete grids of PWV with high quality. Our goal is to correctly infer PWV at spatially continuous, highly resolved grids from heterogeneous data sets. This is done by a geostatistical data fusion approach based on the method of fixed-rank kriging. The first data set contains absolute maps of atmospheric PWV produced by combining observations from the Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). These PWV maps have a high spatial density and a millimeter accuracy; however, the data are missing in regions of low coherence (e.g., forests and vegetated areas). The PWV maps simulated by the WRF model represent the second data set. The model maps are available for wide areas, but they have a coarse spatial resolution and a still limited accuracy. The PWV maps inferred by the data fusion at any spatial resolution show better qualities than those inferred from single data sets. In addition, by using the fixed-rank kriging method, the computational burden is significantly lower than that for ordinary kriging.

Static Laue Diffraction Studies on Acetylcholinesterase

1998 ◽  
Vol 54 (6) ◽  
pp. 1359-1366 ◽  
Author(s):  
Raimond B. G. Ravelli ◽  
Mia L. Raves ◽  
Zhong Ren ◽  
Dominique Bourgeois ◽  
Michel Roth ◽  
...  
Keyword(s):  
Structural Change ◽  
Exposure Time ◽  
Active Site ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Reversible Inhibitor ◽  
Data Set ◽  
Time Resolved ◽  
X Ray ◽  
Density Maps

Acetylcholinesterase (AChE) is one of nature's fastest enzymes, despite the fact that its three-dimensional structure reveals its active site to be deeply sequestered within the molecule. This raises questions with respect to traffic of substrate to, and products from, the active site, which may be investigated by time-resolved crystallography. In order to address one aspect of the feasibility of performing time-resolved studies on AChE, a data set has been collected using the Laue technique on a trigonal crystal of Torpedo californica AChE soaked with the reversible inhibitor edrophonium, using a total X-ray exposure time of 24 ms. Electron-density maps obtained from the Laue data, which are of surprisingly good quality compared with similar maps from monochromatic data, show essentially the same features. They clearly reveal the bound ligand, as well as a structural change in the conformation of the active-site Ser200 induced upon binding.

3D ray+Born migration/inversion—Part 2: Application to the SEG/EAGE overthrust experiment

Geophysics ◽  
2003 ◽  
Vol 68 (4) ◽  
pp. 1357-1370 ◽  
Author(s):  
Stéphane Operto ◽  
Gilles Lambaré ◽  
Pascal Podvin ◽  
Philippe Thierry
Keyword(s):  
Spatial Resolution ◽  
Seismic Data ◽  
Velocity Model ◽  
Nonuniform Distribution ◽  
Data Sets ◽  
Data Set ◽  
Quantitative Estimates ◽  
3D Processing ◽  
Type Data ◽  
New Formula

The SEG/EAGE overthrust model is a synthetic onshore velocity model that was used to generate several large synthetic seismic data sets using acoustic finite‐difference modeling. From this database, several realistic subdata sets were extracted and made available for testing 3D processing methods. For example, classic onshore‐type data‐acquisition geometries are available such as a swath acquisition, which is characterized by a nonuniform distribution of long offsets with azimuth and midpoints. In this paper, we present an application of 2.5D and 3D ray‐Born migration/inversion to several classical data sets from the SEG/EAGE overthrust experiment. The method is formulated as a linearized inversion of the scattered wavefield. The method allows quantitative estimates of short wavelength components of the velocity model. First, we apply a 3D migration/inversion formula formerly developed for marine acquisitions to the swath data set. The migrated sections exhibit significant amplitude artifacts and acquisition footprints, also revealed by the shape of the local spatial resolution filters. From the analysis of these spatial resolution filters, we propose a new formula significantly improving the migrated dip section. We also present 3D migrated results for the strike section and a small 3D target containing a channel. Finally, the applications demonstrate, that the ray+Born migration formula must be adapted to the acquisition geometry to obtain reliable estimates of the true amplitude of the model perturbations. This adaptation is relatively straightforward in the frame of the ray+Born formalism and can be guided by the analysis of the resolution operator.

scholarly journals Accuracy of Low-Cost Alternative Facial Scanners: A Prospective Cohort Study.

2021 ◽  
Author(s):  
Alexander K. Bartella ◽  
Josefine Laser ◽  
Mohammad Kamal ◽  
Dirk Halama ◽  
Michael Neuhaus ◽  
...  
Keyword(s):  
Low Cost ◽  
Three Dimensional ◽  
Neck Surgery ◽  
Clinical Analysis ◽  
Smart Device ◽  
Data Sets ◽  
Average Deviation ◽  
Technical Improvement ◽  
Data Set ◽  
Significant Difference

Abstract Introduction: Three-dimensional facial scan images have been showing an increasingly important role in peri-therapeutic management of oral and maxillofacial and head and neck surgery cases. Face scan images can be open using optical facial scanners utilizing line-laser, stereophotography, structured light modality, or from volumetric data obtained from cone beam computed tomography (CBCT). The aim of this study is to evaluate, if two low-cost procedures for creating a three-dimensional face scan images are able to produce a sufficient data set for clinical analysis. Materials and methods: 50 healthy volunteers were included in the study. Two test objects with defined dimensions were attached to the forehead and the left cheek. Anthropometric values were first measured manually, and consecutively, face scans were performed with a smart device and manual photogrammetry and compared to the manually measured data sets.Results: Anthropometric distances on average deviated 2.17 mm from the manual measurement (smart device scanning 3.01 mm vs. photogrammetry 1.34 mm), with 7 out of 8 deviations were statistically significant. Of a total of 32 angles, 19 values showed a significant difference to the original 90° angles. The average deviation was 6.5° (smart device scanning 10.1° vs. photogrammetry 2.8°).Conclusion: Manual photogrammetry with a regular photo-camera shows higher accuracy than scanning with smart device. However, the smart device was more intuitive in handling and further technical improvement of the cameras used should be watched carefully.

scholarly journals QUALITY ASSESSMENT OF A NATIONWIDE DATA SET CONTAINING AUTOMATICALLY RECONSTRUCTED 3D BUILDING MODELS

2021 ◽  
Vol XLVI-4/W4-2021 ◽  
pp. 17-24
Author(s):  
B. Dukai ◽  
R. Peters ◽  
S. Vitalis ◽  
J. van Liempt ◽  
J. Stoter
Keyword(s):  
Quality Assessment ◽  
Quality Metrics ◽  
Data Sets ◽  
Reconstruction Method ◽  
Data Set ◽  
Building Models ◽  
Source Data ◽  
Relative Quality ◽  
Building Reconstruction

Abstract. Fully automated reconstruction of high-detail building models on a national scale is challenging. It raises a set of problems that are seldom found when processing smaller areas, single cities. Often there is no reference, ground truth available to evaluate the quality of the reconstructed models. Therefore, only relative quality metrics are computed, comparing the models to the source data sets. In the paper we present a set of relative quality metrics that we use for assessing the quality of 3D building models, that were reconstructed in a fully automated process, in Levels of Detail 1.2, 1.3, 2.2 for the whole of the Netherlands. The source data sets for the reconstruction are the Dutch Building and Address Register (BAG) and the National Height Model (AHN). The quality assessment is done by comparing the building models to these two data sources. The work presented in this paper lays the foundation for future research on the quality control and management of automated building reconstruction. Additionally, it serves as an important step in our ongoing effort for a fully automated building reconstruction method of high-detail, high-quality models.

scholarly journals Impact of climate, vegetation, soil and crop management variables on multi-year ISBA-A-gs simulations of evapotranspiration over a Mediterranean crop site

2015 ◽  
Vol 8 (10) ◽  
pp. 3033-3053 ◽  
Author(s):  
S. Garrigues ◽  
A. Olioso ◽  
D. Carrer ◽  
B. Decharme ◽  
J.-C. Calvet ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Surface Model ◽  
Data Sets ◽  
Data Set ◽  
Area Index ◽  
Hydrodynamic Parameters ◽  
Land Surface Parameter ◽  
Crop Succession

Abstract. Generic land surface models are generally driven by large-scale data sets to describe the climate, the soil properties, the vegetation dynamic and the cropland management (irrigation). This paper investigates the uncertainties in these drivers and their impacts on the evapotranspiration (ET) simulated from the Interactions between Soil, Biosphere, and Atmosphere (ISBA-A-gs) land surface model over a 12-year Mediterranean crop succession. We evaluate the forcing data sets used in the standard implementation of ISBA over France where the model is driven by the SAFRAN (Système d'Analyse Fournissant des Renseignements Adaptés à la Nivologie) high spatial resolution atmospheric reanalysis, the leaf area index (LAI) time courses derived from the ECOCLIMAP-II land surface parameter database and the soil texture derived from the French soil database. For climate, we focus on the radiations and rainfall variables and we test additional data sets which include the ERA-Interim (ERA-I) low spatial resolution reanalysis, the Global Precipitation Climatology Centre data set (GPCC) and the MeteoSat Second Generation (MSG) satellite estimate of downwelling shortwave radiations. The evaluation of the drivers indicates very low bias in daily downwelling shortwave radiation for ERA-I (2.5 W m−2) compared to the negative biases found for SAFRAN (−10 W m−2) and the MSG satellite (−12 W m−2). Both SAFRAN and ERA-I underestimate downwelling longwave radiations by −12 and −16 W m−2, respectively. The SAFRAN and ERA-I/GPCC rainfall are slightly biased at daily and longer timescales (1 and 0.5 % of the mean rainfall measurement). The SAFRAN rainfall is more precise than the ERA-I/GPCC estimate which shows larger inter-annual variability in yearly rainfall error (up to 100 mm). The ECOCLIMAP-II LAI climatology does not properly resolve Mediterranean crop phenology and underestimates the bare soil period which leads to an overall overestimation of LAI over the crop succession. The simulation of irrigation by the model provides an accurate irrigation amount over the crop cycle but the timing of irrigation occurrences is frequently unrealistic. Errors in the soil hydrodynamic parameters and the lack of irrigation in the simulation have the largest influence on ET compared to uncertainties in the large-scale climate reanalysis and the LAI climatology. Among climate variables, the errors in yearly ET are mainly related to the errors in yearly rainfall. The underestimation of the available water capacity and the soil hydraulic diffusivity induce a large underestimation of ET over 12 years. The underestimation of radiations by the reanalyses and the absence of irrigation in the simulation lead to the underestimation of ET while the overall overestimation of LAI by the ECOCLIMAP-II climatology induces an overestimation of ET over 12 years. This work shows that the key challenges to monitor the water balance of cropland at regional scale concern the representation of the spatial distribution of the soil hydrodynamic parameters, the variability of the irrigation practices, the seasonal and inter-annual dynamics of vegetation and the spatiotemporal heterogeneity of rainfall.

Least-squares Gaussian beam migration

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. S87-S100 ◽  
Author(s):  
Hao Hu ◽  
Yike Liu ◽  
Yingcai Zheng ◽  
Xuejian Liu ◽  
Huiyi Lu
Keyword(s):  
Least Squares ◽  
Gaussian Beam ◽  
Spatial Resolution ◽  
Field Data ◽  
Synthetic Data ◽  
Data Sets ◽  
Data Set ◽  
Seismic Acquisition ◽  
Gaussian Beam Migration ◽  
Least Squares Migration

Least-squares migration (LSM) can be effective to mitigate the limitation of finite-seismic acquisition, balance the subsurface illumination, and improve the spatial resolution of the image, but it requires iterations of migration and demigration to obtain the desired subsurface reflectivity model. The computational efficiency and accuracy of migration and demigration operators are crucial for applying the algorithm. We have developed a test of the feasibility of using the Gaussian beam as the wavefield extrapolating operator for the LSM, denoted as least-squares Gaussian beam migration. Our method combines the advantages of the LSM and the efficiency of the Gaussian beam propagator. Our numerical evaluations, including two synthetic data sets and one marine field data set, illustrate that the proposed approach could be used to obtain amplitude-balanced images and to broaden the bandwidth of the migrated images in particular for the low-wavenumber components.

Semi-Automated Roller Parameters Extraction from Terrestrial Lidar

2021 ◽  
Vol 87 (12) ◽  
pp. 879-890
Author(s):  
Sagar S. Deshpande ◽  
Mike Falk ◽  
Nathan Plooster
Keyword(s):  
Rotation Axis ◽  
Moving Average ◽  
Three Dimensional ◽  
Data Sets ◽  
Steel Mill ◽  
Data Set ◽  
Terrestrial Lidar ◽  
Two Dimensional Image ◽  
Average Rotation

Rollers are an integral part of a hot-rolling steel mill. They transport hot metal from one end of the mill to another. The quality of the steel highly depends on the surface quality of the rollers. This paper presents semi-automated methodologies to extract roller parameters from terrestrial lidar points. The procedure was divided into two steps. First, the three-dimensional points were converted to a two-dimensional image to detect the extents of the rollers using fast Fourier transform image matching. Lidar points for every roller were iteratively fitted to a circle. The radius and center of the fitted circle were considered as the average radius and average rotation axis of the roller, respectively. These parameters were also extracted manually and were compared to the measured parameters for accuracy analysis. The proposed methodology was able to extract roller parameters at millimeter level. Erroneously identified rollers were identified by moving average filters. In the second step, roller parameters were determined using the filtered roller points. Two data sets were used to validate the proposed methodologies. In the first data set, 366 out of 372 rollers (97.3%) were identified and modeled. The second, smaller data set consisted of 18 rollers which were identified and modelled accurately.

Geostatistical Joint Interpretation of Gravity and Magnetotelluric Data of the US Cordillera

2021 ◽  
Author(s):  
Mohammad Shehata ◽  
Hideki Mizunaga
Keyword(s):  
Gravity Data ◽  
Three Dimensional ◽  
Data Sets ◽  
Spatial Expansion ◽  
Magnetotelluric Data ◽  
Data Set ◽  
Entire Area ◽  
Mean Values ◽  
Local Means ◽  
The Us

<p>Long-period magnetotelluric and gravity data were acquired to investigate the US cordillera's crustal structure. The magnetotelluric data are being acquired across the continental USA on a quasi-regular grid of ∼70 km spacing as an electromagnetic component of the National Science Foundation EarthScope/USArray Program. International Gravimetreique Bureau compiled gravity Data at high spatial resolution. Due to the difference in data coverage density, the geostatistical joint integration was utilized to map the subsurface structures with adequate resolution. First, a three-dimensional inversion of each data set was applied separately.</p><p>The inversion results of both data sets show a similarity of structure for data structuralizing. The individual result of both data sets is resampled at the same locations using the kriging method by considering each inversion model to estimate the coefficient. Then, the Layer Density Correction (LDC) process's enhanced density distribution was applied to MT data's spatial expansion process. Simple Kriging with varying Local Means (SKLM) was applied to the residual analysis and integration. For this purpose, the varying local means of the resistivity were estimated using the corrected gravity data by the Non-Linear Indicator Transform (NLIT), taking into account the spatial correlation. After that, the spatial expansion analysis of MT data obtained sparsely was attempted using the estimated local mean values and SKLM method at the sections where the MT survey was carried out and for the entire area where density distributions exist. This research presents the integration results and the stand-alone inversion results of three-dimensional gravity and magnetotelluric data.</p>

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