vector characteristic
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2020 ◽  
Vol 49 (9) ◽  
pp. 14-21
Author(s):  
A. V. Kirpanev ◽  
N. A. Kirpanev ◽  
V. V. Shubnikov

The paper presents a research technique for studying an antenna-radome system based on nearfield measurements with a most common «roll over azimuth» spherical scanner. It is based on the relationship between the components of the plane wave spectrum and the spherical wave coefficients, in terms of which the radiation fields of the tested antenna and the antenna-radome system are represented. Expressions for the plane wave spectrum components at the pole of the spherical measurement surface are given. To assess the effect of the radome on the antenna characteristics, it is proposed to use the spectral vector characteristic of the radome passage. Methods for estimating the dielectric constant of the radome by determining the transmission coefficient of its wall at various points on the surface are proposed. It is shown that the use of a weakly directional antenna in the study of the radome characteristics simplifies the task, since the transmission coefficient is determined using the components of the electric field strengths in spherical coordinates.


2015 ◽  
Vol 08 (05) ◽  
pp. 1550015 ◽  
Author(s):  
Ali S. Saad ◽  
Gamal A. El-Hiti ◽  
Ali M. Masmali

The present work focuses on the development of a novel computer-based approach for tear ferning (TF) featuring. The original TF images of the recently developed five-point grading scale have been used to assign a grade for any TF image automatically. A vector characteristic (VC) representing each grade was built using the reference images. A weighted combination between features selected from textures analysis using gray level co-occurrence matrix (GLCM), power spectrum (PS) analysis and linear specificity of the image were used to build the VC of each grade. A total of 14 features from texture analysis were used. PS at different frequency points and number of line segments in each image were also used. Five features from GLCM have shown significant differences between the recently developed grading scale images which are: angular second moment at 0° and 45°, contrast, and correlation at 0° and 45° these five features were all included in the characteristic vector. Three specific power frequencies were used in the VC because of the discrimination power. Number of line segments was also chosen because of dissimilarities between images. A VC for each grade of TF reference images was constructed and was found to be significantly different from each other's. This is a basic and fundamental step toward an automatic grading for computer-based diagnosis for dry eye.


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