scholarly journals 3D Measurement Simulation and Relative Pointing Error Verification of the Telescope Mount Assembly Subsystem for the Large Synoptic Survey Telescope

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3023 ◽  
Author(s):  
Unai Mutilba ◽  
Gorka Kortaberria ◽  
Fernando Egaña ◽  
Jose Yagüe-Fabra
Keyword(s):  
Laser Tracker ◽  
Optical Telescope ◽  
Pointing Error ◽  
Verification Method ◽  
Subsystem Level ◽  
Alignment System ◽  
Fit For Purpose ◽  
Large Telescopes ◽  
Error Verification ◽  
Better Than

An engineering validation of a large optical telescope consists of executing major performing tests at the subsystem level to verify the overall engineering performance of the observatory. Thus, the relative pointing error verification of the telescope mount assembly subsystem is of special interest to guarantee the absolute pointing performance of the large synoptic survey telescope. This paper presents a new verification method for the relative pointing error assessment of the telescope mount assembly, based on laser tracker technology and several fiducial points fixed to the floor. Monte-Carlo-based simulation results show that the presented methodology is fit for purpose, even if floor movement occurs due to temperature variation during the measurement acquisition process. A further research about laser tracker technology integration into the telescope structure may suggest that such laser tracker technology could be permanently installed in the telescope in order to provide an active alignment system that aims to detect and correct possible misalignment between mirrors or to provide the required mirror positioning verification accuracy after maintenance activities. The obtained results show that two on-board laser tracker systems combined with eight measurement targets could result in measurement uncertainties that are better than 1 arcsec, which would provide a reliable built-in metrology tool for large telescopes.

scholarly journals ESA’s X-Ray Astronomy Mission, XMM

1990 ◽  
Vol 123 ◽  
pp. 129-140
Author(s):  
B.G. Taylor ◽  
A. Peacock
Keyword(s):  
Resolving Power ◽  
Science Program ◽  
Eccentric Orbit ◽  
Ccd Cameras ◽  
Optical Telescope ◽  
X Ray ◽  
Medium Resolution ◽  
Reflection Gratings ◽  
Better Than

AbstractESA’s X-ray Astronomy Mission, XMM, scheduled for launch in 1998, is the second of four cornerstones of ESA’s long term science program Horizon 2000. Covering the range from about 0.1 to 10 keV, it will provide a high throughput of 5000 cm2 at 7 keV with three independant telescopes, and have a spatial resolution better than 30 arcsec. Broadband spectrophotometry is provided by CCD cameras while reflection gratings provide medium resolution spectroscopy (resolving power of about 400) in the range 0.3–3 keV. Long uninterrupted observations will be made from the 24 hr period, highly eccentric orbit, reaching a sensitivity approaching 10−15 erg cm−2 s−1 in one orbit. A 30 cm UV/optical telescope is bore-sighted with the x-ray telescopes to provide simultaneous optical counterparts to the numerous serendipitous X-ray sources which will be detected during every observation.

A New Approach Based on the Bee Optimization Algorithm for Ontology Alignment

2019 ◽  
Vol 9 (4) ◽  
pp. 13-22
Author(s):  
Fatima Ardjani ◽  
Djelloul Bouchiha
Keyword(s):  
Similarity Measures ◽  
Optimization Method ◽  
Ontology Alignment ◽  
New Approach ◽  
Alignment System ◽  
Alignment Process ◽  
Joint Consideration ◽  
Bee Colonies ◽  
Web Research ◽  
Better Than

The ontology alignment process aims at generating a set of correspondences between entities of two ontologies. It is an important task, notably in the semantic web research, because it allows the joint consideration of resources defined in different ontologies. In this article, the authors developed an ontology alignment system called ABCMap+. It uses an optimization method based on artificial bee colonies (ABC) to solve the problem of optimizing the aggregation of three similarity measures of different matchers (syntactic, linguistic and structural) to obtain a single similarity measure. To evaluate the ABCMap+ ontology alignment system, authors considered the OAEI 2012 alignment system evaluation campaign. Experiments have been carried out to get the best ABCMap+'s alignment. Then, a comparative study showed that the ABCMap+ system is better than participants in the OAEI 2012 in terms of Recall and Precision.

Research on Fixture Locating Error Verification Based on Statistics Method

2014 ◽  
Vol 556-562 ◽  
pp. 4255-4259
Author(s):  
Wen Li Han ◽  
Fa Ping Zhang ◽  
Bo Gao ◽  
De Hui Zhai ◽  
Hao Li
Keyword(s):  
Random Numbers ◽  
Fixture Design ◽  
Location Error ◽  
Analysis Method ◽  
Verification Method ◽  
Factors Influencing ◽  
Locating Error ◽  
Statistical Analysis Method ◽  
Assembly Error ◽  
Error Verification

Fixture Tolerance is one of the most important factors influencing the machined part accuracy. However caused by the manufacturing error and the assembly error of locator, the workpiece location error should not be neglected, which has led to fixture accuracy decay. A location error verification method is presented to improve the workpiece location accuracy. First, the origin of location error and the transfer process of error between locators and the workpiece are given. Second, random numbers and statistical analysis method are used to simulate locators’ errors. Finally, the location layout optimization model and the process are given. This method can be used to verify the location error and fixture design process.

scholarly journals On the Importance of Active Image Stabilisation

1984 ◽  
Vol 79 ◽  
pp. 367-378
Author(s):  
J.E. Noordam
Keyword(s):  
Point Source ◽  
Speckle Interferometry ◽  
Aperture Synthesis ◽  
Atmospheric Conditions ◽  
Optical Telescope ◽  
Aperture Diameter ◽  
Logical Approach ◽  
Optical Aperture ◽  
Large Telescopes ◽  
Mirror Telescope

AbstractThe performance of an optical telescope can be improved considerably by opening the shutter only at moments of good seeing. The resulting instantaneous highresolution images must be corrected for shift before adding them all together. The optimum aperture diameter for which this technique works well is 1 meter or less, depending on atmospheric conditions. Image stabilisation not only improves the resolution and thus the point-source sensitivity, but it is also expected to improve the performance of speckle interferometry and optical aperture synthesis. This makes its implementation on large telescopes desirable. While it is certainly possible to do this by treating a large filled aperture like a set of independent subapertures, a much more logical approach would be to build an array of 1-meter telescopes, preferably mounted in a single large frame so that it can be pointed in all directions without extensive pathlength compensation. Such a “Many Mirror Telescope” has many advantages, and is feasible because image stabilisation helps to solve the beam-combining problem.

Comparative Analysis of Proprioception in Left and Right Arms

1965 ◽  
Vol 17 (2) ◽  
pp. 149-157 ◽  
Author(s):  
Maria Wyke
Keyword(s):  
Comparative Analysis ◽  
Head And Neck ◽  
Sensory Input ◽  
The Body ◽  
Limb Movements ◽  
Pointing Error ◽  
Left And Right ◽  
The Right ◽  
Genetically Determined ◽  
Better Than

Using the “kinaesthetic memory for the target” technique, differences in the accuracy of pointing to a target with the right and left arms are analysed. The effect of rotation of the head to left and right upon this process is also studied. With the head normally orientated, it was found that pointing with the right arm is significantly better than with the left. Accuracy of pointing is greater with the target directly in front of the body than when it lies to either left or right side. When the head is rotated, the direction of the pointing error is inversely related to the direction of rotation. The study suggests that the precision of control over arm (in the absence of vision) is related to the varying ability of individual subjects to correlate limb movements with the prevailing orientation of the body, especially of the head and neck. This is additional to the influences of genetically-determined handedness and of the sensory input from the moving limb.

scholarly journals Reliability Measurement without Limits

2008 ◽  
Vol 34 (3) ◽  
pp. 319-326 ◽  
Author(s):  
Dennis Reidsma ◽  
Jean Carletta
Keyword(s):  
Machine Learning ◽  
Computational Linguistics ◽  
Random Noise ◽  
Reliability Measures ◽  
The Real ◽  
Fit For Purpose ◽  
Reliability Measurement ◽  
Better Than

In computational linguistics, a reliability measurement of 0.8 on some statistic such as κ is widely thought to guarantee that hand-coded data is fit for purpose, with 0.67 to 0.8 tolerable, and lower values suspect. We demonstrate that the main use of such data, machine learning, can tolerate data with low reliability as long as any disagreement among human coders looks like random noise. When the disagreement introduces patterns, however, the machine learner can pick these up just like it picks up the real patterns in the data, making the performance figures look better than they really are. For the range of reliability measures that the field currently accepts, disagreement can appreciably inflate performance figures, and even a measure of 0.8 does not guarantee that what looks like good performance really is. Although this is a commonsense result, it has implications for how we work. At the very least, computational linguists should look for any patterns in the disagreement among coders and assess what impact they will have.

A Vertical X-ray Stepper for SOR Lithography

1991 ◽  
Vol 3 (4) ◽  
pp. 346-353
Author(s):  
Sunao Ishihara ◽  
◽  
Atsunobu Une ◽  
Munenori Kanai ◽  
Masanori Suzuki ◽  
...  
Keyword(s):  
Optical Heterodyne ◽  
Air Bearing ◽  
X Ray ◽  
Thrust Bearings ◽  
Alignment System ◽  
Radial Thrust ◽  
Better Than

A vertical x-ray stepper for SOR lithography has been developed. The stepper exposes wafers in a normal atmosphere to vertically-scanned SOR with continuous alignment control during exposure. The key devices of the stepper are a vertical X-Y stage and an opticalheterodyne alignment system. The X-Y stage uses airlubricated components, including air bearing lead screws, linear sliders and radial/thrust bearings. The optical-heterodyne alignment system detects the displacement between the mask and wafer gratings with precision of 8.3nm. Several exposure experiments proved that the alignment capability is better than ±0.1μm for a 3σ-value.

Off-line Chinese Signature Verification Using Convolutional Neural Network

2019 ◽  
Vol 13 (4) ◽  
pp. 348-355
Author(s):  
Shao Hong ◽  
Xu Rongze ◽  
Guo Xiaopeng ◽  
Cui Wencheng
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Information Science ◽  
Signature Verification ◽  
Network Architectures ◽  
Verification Method ◽  
Signature Recognition ◽  
Access Control System ◽  
Unique Individual ◽  
Better Than

Background: The unique individual biological characteristics is used for identification in biometrics, which is safe and difficult to forge. Therefore, it can help to enhance the safety of access control system. Since the developing of modern information science and technology, computerbased signature verification system enables signature verification more efficiently and automatically in comparison with traditional human identification method. Methods: In order to improve the accuracy of Chinese signature verification, an off-line Chinese signature verification method based on deep convolutional neural network is proposed. First, the machine learning library Tensorflow is build, and the volunteers are invited to establish the offline Chinese signature dataset. Second, the dataset is pre-processed, including denoising, binarization and size normalization. Finally, three different CNN architectures (AlexNet, GoogleNet, VGGNet) are adopted to implement the signature verification. Results: Experimental results show that the performance of AlexNet is better than that of the other two convolutional neural network architectures, the accuracy of classification has been up to 99.77%, and verification rate is 87.5%. Conclusion: Compared with the traditional offline Chinese signature recognition method, the method based on the convolutional neural network Alex Net-f is better than other methods to some extent, and avoids the complicated feature engineering.

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