ﻻ يوجد ملخص باللغة العربية
The StarScan machine at the U.S. Naval Observatory (USNO) completed measuring photographic astrograph plates to allow determination of proper motions for the USNO CCD Astrograph Catalog (UCAC) program. All applicable 1940 AGK2 plates, about 2200 Hamburg Zone Astrograph plates, 900 Black Birch (USNO Twin Astrograph) plates, and 300 Lick Astrograph plates have been measured. StarScan comprises of a CCD camera, telecentric lens, air-bearing granite table, stepper motor screws, and Heidenhain scales to operate in a step-stare mode. The repeatability of StarScan measures is about 0.2 micrometer. The CCD mapping as well as the global table coordinate system has been calibrated using a special dot calibration plate and the overall accuracy of StarScan x,y data is derived to be 0.5 micrometer. Application to real photographic plate data shows that position information of at least 0.65 micrometer accuracy can be extracted from course grain 103a-type emulsion astrometric plates. Transformations between direct and reverse measures of fine grain emulsion plate measures are obtained on the 0.3 micrometer level per well exposed stellar image and coordinate, which is at the limit of the StarScan machine.
In this paper we try to organize machine teaching as a coherent set of ideas. Each idea is presented as varying along a dimension. The collection of dimensions then form the problem space of machine teaching, such that existing teaching problems can
We report on measurements performed on an apparatus aimed to study the Casimir force in the cylinder-plane configuration. The electrostatic calibrations evidence anomalous behaviors in the dependence of the electrostatic force and the minimizing pote
We propose a fleet of nanosatellites to perform an all-sky monitoring and timing based localisation of gamma-ray transients. The fleet of at least nine 3U cubesats shall be equipped with large and thin CsI(Tl) scintillator based soft gamma-ray detect
University of Sofia, Faculty of Physics, Atomic Physics Department, 5, James Bourchier Boulevard, BG-1164 Sofia, Bulgaria Ghent University, Department of Physics and Astronomy, Proeftuinstraat 86, BE-9000 Ghent, Belgium Bulgarian Academy of Sciences,
A machine learning approach has been implemented to measure the electron temperature directly from the emission spectra of a tokamak plasma. This approach utilized a neural network (NN) trained on a dataset of 1865 time slices from operation of the D