Analytic expressions for far fields and radiation fluxes caused by a moving source in some anisotropic dispersive media

1990 ◽  
Vol 2 (9) ◽  
pp. 1968-1978
Author(s):  
H. M. Lai ◽  
C. S. Ng
Author(s):  
Ahmed M Abdel-Ghanya ◽  
Ibrahim M Al-Helal

Plastic nets are extensively used for shading purposes in arid regions such as in the Arabian Peninsula. Quantifying the convection exchange with shading net and understanding the mechanisms (free, mixed and forced) of convection are essential for analyzing energy exchange with shading nets. Unlike solar and thermal radiation, the convective energy, convective heat transfer coefficient and the nature of convection have never been theoretically estimated or experimentally measured for plastic nets under arid conditions. In this study, the convected heat exchanges with different plastic nets were quantified based on an energy balance applied to the nets under outdoor natural conditions. Therefore, each net was tacked onto a wooden frame, fixed horizontally at 1.5-m height over the floor. The downward and upward solar and thermal radiation fluxes were measured below and above each net on sunny days; also the wind speed over the net, and the net and air temperatures were measured, simultaneously. Nets with different porosities, colors and texture structures were used for the study. The short and long wave’s radiative properties of the nets were pre-determined in previous studies to be used. Re and Gr numbers were determined and used to characterize the convection mechanism over each net. The results showed that forced and mixed convection are the dominant modes existing over the nets during most of the day and night times. The nature of convection over nets depends mainly on the wind speed, net-air temperature difference and texture shape of the net rather than its color and its porosity.


2020 ◽  
Vol 2020 (10) ◽  
pp. 310-1-310-7
Author(s):  
Khalid Omer ◽  
Luca Caucci ◽  
Meredith Kupinski

This work reports on convolutional neural network (CNN) performance on an image texture classification task as a function of linear image processing and number of training images. Detection performance of single and multi-layer CNNs (sCNN/mCNN) are compared to optimal observers. Performance is quantified by the area under the receiver operating characteristic (ROC) curve, also known as the AUC. For perfect detection AUC = 1.0 and AUC = 0.5 for guessing. The Ideal Observer (IO) maximizes AUC but is prohibitive in practice because it depends on high-dimensional image likelihoods. The IO performance is invariant to any fullrank, invertible linear image processing. This work demonstrates the existence of full-rank, invertible linear transforms that can degrade both sCNN and mCNN even in the limit of large quantities of training data. A subsequent invertible linear transform changes the images’ correlation structure again and can improve this AUC. Stationary textures sampled from zero mean and unequal covariance Gaussian distributions allow closed-form analytic expressions for the IO and optimal linear compression. Linear compression is a mitigation technique for high-dimension low sample size (HDLSS) applications. By definition, compression strictly decreases or maintains IO detection performance. For small quantities of training data, linear image compression prior to the sCNN architecture can increase AUC from 0.56 to 0.93. Results indicate an optimal compression ratio for CNN based on task difficulty, compression method, and number of training images.


2020 ◽  
Author(s):  
Mike Hugo

The proposed \gls{cimpl} strategy is customized toward binaural portable amplifier frameworks with receiver exhibits in every unit. The technique uses the roundabout insights (roundabout mean and round difference) of \gls{impd} across various amplifier sets. These \gls{impd}s are right off the bat mapped to time delays through a difference weighted direct fit, at that point mapped to azimuth \gls{doa} and finally data of various mouthpiece sets is consolidated. The fluctuation is helped through the various changes and goes about as an unwavering quality list of the evaluated point. Both the subsequent edge and fluctuation are taken care of into a wrapped Kalman channel, which gives a smoothed gauge of the \gls{doa}. The proposed strategy improves the exactness of the followed point of a solitary moving source contrasted and the benchmark technique gave by the LOCATA challenge, and it runs around multiple times quicker.


2021 ◽  
Vol 11 (9) ◽  
pp. 3844
Author(s):  
Konstantinos P. Prokopidis ◽  
Dimitrios C. Zografopoulos

A novel finite-difference time-domain formulation for the modeling of general anisotropic dispersive media is introduced in this work. The method accounts for fully anisotropic electric or magnetic materials with all elements of the permittivity and permeability tensors being non-zero. In addition, each element shows an arbitrary frequency dispersion described by the complex-conjugate pole–residue pairs model. The efficiency of the technique is demonstrated in benchmark numerical examples involving electromagnetic wave propagation through magnetized plasma, nematic liquid crystals and ferrites.


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