Accurate Ground Positioning Obtained From 3d Data Matching Between Airborne and Terrestrial Data for Ground Validation of Satellite Laser

2019 ◽  
Author(s):  
Akira Kato ◽  
Hiroyuki Wakabayashi ◽  
Matt Bradford ◽  
Andrew Hudak ◽  
L. Monika Moskal ◽  
...  
Keyword(s):  
Data Matching ◽  
3D Data ◽  
Ground Validation ◽  
Terrestrial Data

Direct phase determination in electron crystallography: small organic molecules

1992 ◽  
Vol 50 (2) ◽  
pp. 1166-1167
Author(s):  
Douglas L. Dorset
Keyword(s):  
Organic Molecules ◽  
Data Sets ◽  
Temperature Structure ◽  
3D Analysis ◽  
Intensity Data ◽  
Electron Crystallography ◽  
Phase Determination ◽  
Measured Intensity ◽  
3D Data

The quantitative use of electron diffraction intensity data for the determination of crystal structures represents the pioneering achievement in the electron crystallography of organic molecules, an effort largely begun by B. K. Vainshtein and his co-workers. However, despite numerous representative structure analyses yielding results consistent with X-ray determination, this entire effort was viewed with considerable mistrust by many crystallographers. This was no doubt due to the rather high crystallographic R-factors reported for some structures and, more importantly, the failure to convince many skeptics that the measured intensity data were adequate for ab initio structure determinations.We have recently demonstrated the utility of these data sets for structure analyses by direct phase determination based on the probabilistic estimate of three- and four-phase structure invariant sums. Examples include the structure of diketopiperazine using Vainshtein's 3D data, a similar 3D analysis of the room temperature structure of thiourea, and a zonal determination of the urea structure, the latter also based on data collected by the Moscow group.

Time consumption and quality of an automated fusion tool for SPECT and MRI images of the brain

2003 ◽  
Vol 42 (05) ◽  
pp. 215-219
Author(s):  
G. Platsch ◽  
A. Schwarz ◽  
K. Schmiedehausen ◽  
B. Tomandl ◽  
W. Huk ◽  
...  
Keyword(s):  
Data Sets ◽  
3D Mri ◽  
Clinical Routine ◽  
Fusion Procedure ◽  
3D Data ◽  
Mri Scans ◽  
2D Data ◽  
Time Required ◽  
The Brain ◽  
Manual Correction

Summary: Aim: Although the fusion of images from different modalities may improve diagnostic accuracy, it is rarely used in clinical routine work due to logistic problems. Therefore we evaluated performance and time needed for fusing MRI and SPECT images using a semiautomated dedicated software. Patients, material and Method: In 32 patients regional cerebral blood flow was measured using 99mTc ethylcystein dimer (ECD) and the three-headed SPECT camera MultiSPECT 3. MRI scans of the brain were performed using either a 0,2 T Open or a 1,5 T Sonata. Twelve of the MRI data sets were acquired using a 3D-T1w MPRAGE sequence, 20 with a 2D acquisition technique and different echo sequences. Image fusion was performed on a Syngo workstation using an entropy minimizing algorithm by an experienced user of the software. The fusion results were classified. We measured the time needed for the automated fusion procedure and in case of need that for manual realignment after automated, but insufficient fusion. Results: The mean time of the automated fusion procedure was 123 s. It was for the 2D significantly shorter than for the 3D MRI datasets. For four of the 2D data sets and two of the 3D data sets an optimal fit was reached using the automated approach. The remaining 26 data sets required manual correction. The sum of the time required for automated fusion and that needed for manual correction averaged 320 s (50-886 s). Conclusion: The fusion of 3D MRI data sets lasted significantly longer than that of the 2D MRI data. The automated fusion tool delivered in 20% an optimal fit, in 80% manual correction was necessary. Nevertheless, each of the 32 SPECT data sets could be merged in less than 15 min with the corresponding MRI data, which seems acceptable for clinical routine use.

Agile Development with 3D Data Modeling

2015 ◽  
Vol 10 (6) ◽  
pp. 558 ◽  
Author(s):  
Kristian Sestak ◽  
Zdenek Havlice
Keyword(s):  
Data Modeling ◽  
Agile Development ◽  
3D Data

3D Object Recognition and Relative Localization using a 3D sensor Embedded on a Mobile Robot

2020 ◽  
Author(s):  
Gopi Krishna Erabati
Keyword(s):  
Pose Estimation ◽  
Autonomous Systems ◽  
Microsoft Kinect ◽  
Object Localization ◽  
Initial Alignment ◽  
Relative Localization ◽  
3D Data ◽  
Industry Automation ◽  
Ofthe Object ◽  
3D Descriptors

The technology in current research scenario is marching towards automation forhigher productivity with accurate and precise product development. Vision andRobotics are domains which work to create autonomous systems and are the keytechnology in quest for mass productivity. The automation in an industry canbe achieved by detecting interactive objects and estimating the pose to manipulatethem. Therefore the object localization ( i.e., pose) includes position andorientation of object, has profound ?significance. The application of object poseestimation varies from industry automation to entertainment industry and fromhealth care to surveillance. The objective of pose estimation of objects is verysigni?cant in many cases, like in order for the robots to manipulate the objects,for accurate rendering of Augmented Reality (AR) among others.This thesis tries to solve the issue of object pose estimation using 3D dataof scene acquired from 3D sensors (e.g. Kinect, Orbec Astra Pro among others).The 3D data has an advantage of independence from object texture and invarianceto illumination. The proposal is divided into two phases : An o?ine phasewhere the 3D model template of the object ( for estimation of pose) is built usingIterative Closest Point (ICP) algorithm. And an online phase where the pose ofthe object is estimated by aligning the scene to the model using ICP, providedwith an initial alignment using 3D descriptors (like Fast Point Feature Transform(FPFH)).The approach we develop is to be integrated on two di?erent platforms :1)Humanoid robot `Pyrene' which has Orbec Astra Pro 3D sensor for data acquisition,and 2)Unmanned Aerial Vehicle (UAV) which has Intel Realsense Euclidon it. The datasets of objects (like electric drill, brick, a small cylinder, cake box)are acquired using Microsoft Kinect, Orbec Astra Pro and Intel RealSense Euclidsensors to test the performance of this technique. The objects which are used totest this approach are the ones which are used by robot. This technique is testedin two scenarios, fi?rstly, when the object is on the table and secondly when theobject is held in hand by a person. The range of objects from the sensor is 0.6to 1.6m. This technique could handle occlusions of the object by hand (when wehold the object), as ICP can work even if partial object is visible in the scene.

Spectroscopy-Based Mapping with Scanning Microwave Impedance Microscopy

2018 ◽  
Author(s):  
Peter De Wolf ◽  
Zhuangqun Huang ◽  
Bede Pittenger
Keyword(s):  
Single Point ◽  
Electrical Characterization ◽  
Principal Component ◽  
High Sensitivity ◽  
Data Cube ◽  
Nanometer Scale ◽  
Learning Approaches ◽  
Data Set ◽  
3D Data ◽  
Higher Dimensional

Abstract Methods are available to measure conductivity, charge, surface potential, carrier density, piezo-electric and other electrical properties with nanometer scale resolution. One of these methods, scanning microwave impedance microscopy (sMIM), has gained interest due to its capability to measure the full impedance (capacitance and resistive part) with high sensitivity and high spatial resolution. This paper introduces a novel data-cube approach that combines sMIM imaging and sMIM point spectroscopy, producing an integrated and complete 3D data set. This approach replaces the subjective approach of guessing locations of interest (for single point spectroscopy) with a big data approach resulting in higher dimensional data that can be sliced along any axis or plane and is conducive to principal component analysis or other machine learning approaches to data reduction. The data-cube approach is also applicable to other AFM-based electrical characterization modes.

Dielectric Breakdown in Printed Circuit Boards at Elevated Temperatures

1996 ◽  
Author(s):  
P. Singh ◽  
G.T. Galyon ◽  
J. Obrzut ◽  
W.A. Alpaugh
Keyword(s):  
Experimental Data ◽  
Thermal Degradation ◽  
Printed Circuit Boards ◽  
Printed Circuit Board ◽  
Elevated Temperatures ◽  
Dielectric Breakdown ◽  
Circuit Board ◽  
Circuit Boards ◽  
Printed Circuit ◽  
Data Matching

Abstract A time delayed dielectric breakdown in printed circuit boards, operating at temperatures below the epoxy resin insulation thermo-electrical limits, is reported. The safe temperature-voltage operating regime was estimated and related to the glass-rubber transition (To) of printed circuit board dielectric. The TG was measured using DSC and compared with that determined from electrical conductivity of the laminate in the glassy and rubbery state. A failure model was developed and fitted to the experimental data matching a localized thermal degradation of the dielectric and time dependency. The model is based on localized heating of an insulation resistance defect that under certain voltage bias can exceed the TG, thus, initiating thermal degradation of the resin. The model agrees well with the experimental data and indicates that the failure rate and truncation time beyond which the probability of failure becomes insignificant, decreases with increasing glass-rubber transition temperature.

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