scholarly journals Phase-only Beam Broadening in Large Transmit Arrays Using Complex-Weight Gradient Descent

2014 ◽  
Author(s):  
Jeffrey O. Coleman ◽  
W. M. Dorsey
Keyword(s):  
Gradient Descent ◽  
Transmit Arrays ◽  
Beam Broadening

P20 phosphor on polyimide as a large area high-resolution transmission screen for slow scan CCD systems

1995 ◽  
Vol 53 ◽  
pp. 20-21
Author(s):  
C. C. Ahn ◽  
S. Karnes ◽  
M. Lvovsky ◽  
C. M. Garland ◽  
H. A. Atwater ◽  
...  
Keyword(s):  
Mechanical Stability ◽  
High Energy ◽  
Practical Implementation ◽  
Line Pair ◽  
Modulation Transfer ◽  
Large Area ◽  
Ccd Imaging ◽  
Transmission Electron ◽  
The One ◽  
Beam Broadening

The bane of CCD imaging systems for transmission electron microscopy at intermediate and high voltages has been their relatively poor modulation transfer function (MTF), or line pair resolution. The problem originates primarily with the phosphor screen. On the one hand, screens should be thick so that as many incident electrons as possible are converted to photons, yielding a high detective quantum efficiency(DQE). The MTF diminishes as a function of scintillator thickness however, and to some extent as a function of fluorescence within the scintillator substrates. Fan has noted that the use of a thin layer of phosphor beneath a self supporting 2μ, thick Al substrate might provide the most appropriate compromise for high DQE and MTF in transmission electron microcscopes which operate at higher voltages. Monte Carlo simulations of high energy electron trajectories reveal that only little beam broadening occurs within this thickness of Al film. Consequently, the MTF is limited predominantly by broadening within the thin phosphor underlayer. There are difficulties however, in the practical implementation of this design, associated mostly with the mechanical stability of the Al support film.

Comparison of SVM, RF and SGD Methods for Determination of Programmer's Performance Classification Model in Social Media Activities

2020 ◽  
Vol 4 (2) ◽  
pp. 329-335
Author(s):  
Rusydi Umar ◽  
Imam Riadi ◽  
Purwono
Keyword(s):  
Social Media ◽  
Gradient Descent ◽  
Classification Model ◽  
Stochastic Gradient Descent ◽  
Support Vector ◽  
Svm Algorithm ◽  
Vector Machines ◽  
Performance Patterns ◽  
A Company

The failure of most startups in Indonesia is caused by team performance that is not solid and competent. Programmers are an integral profession in a startup team. The development of social media can be used as a strategic tool for recruiting the best programmer candidates in a company. This strategic tool is in the form of an automatic classification system of social media posting from prospective programmers. The classification results are expected to be able to predict the performance patterns of each candidate with a predicate of good or bad performance. The classification method with the best accuracy needs to be chosen in order to get an effective strategic tool so that a comparison of several methods is needed. This study compares classification methods including the Support Vector Machines (SVM) algorithm, Random Forest (RF) and Stochastic Gradient Descent (SGD). The classification results show the percentage of accuracy with k = 10 cross validation for the SVM algorithm reaches 81.3%, RF at 74.4%, and SGD at 80.1% so that the SVM method is chosen as a model of programmer performance classification on social media activities.

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