This paper presents that the effect of single aperture size of metallic enclosure on electrical shielding effectiveness (ESE) at 0 – 1 GHz frequency range has been investigated by using both Robinson’s analytical formulation and artificial neural networks (ANN) methods that are multilayer perceptron (MLP) networks and a radial basis function neural network (RBFNN). All results including measurement have been compared each other in terms of aperture geometry of metallic enclosure. The geometry of single aperture varies from square to rectangular shape while the open area of aperture is fixed. It has been observed that network structure of MLP 3-40-1 in modeling with ANN modeled with fewer neurons in the sense of overlapping of faults and data and modeled accordingly. In contrast, the RBFNN 3-150-1 is the other detection that the network structure is modeled with more neurons and more. It can be seen from the same network-structured MLP and RBFNN that the MLP modeled better. In this paper, the impact of dimension of rectangular aperture on shielding performance by using RBFNN and MLP network model with ANN has been studied, as a novelty.
The computing performance optimization of the Short-Lag Spatial Coherence (SLSC) method applied to ultrasound data processing is presented. The method is based on the theory that signals from adjacent receivers are correlated, drawing on a simplified conclusion of the van Cittert-Zernike theorem. It has been proven that it can be successfully used in ultrasound data reconstruction with despeckling. Former works have shown that the SLSC method in its original form has two main drawbacks: time-consuming processing and low contrast in the area near the transceivers. In this study, we introduce a method that allows to overcome both of these drawbacks.
The presented approach removes the dependency on distance (the “lag” parameter value) between signals used to calculate correlations. The approach has been tested by comparing results obtained with the original SLSC algorithm on data acquired from tissue phantoms.
The modified method proposed here leads to constant complexity, thus execution time is independent of the lag parameter value, instead of the linear complexity. The presented approach increases computation speed over 10 times in comparison to the base SLSC algorithm for a typical lag parameter value. The approach also improves the output image quality in shallow areas and does not decrease quality in deeper areas.
This article applies radar interferometry technologies implemented in the ENVI SARscape and SNAP software environment provided by the processing of data from the Sentinel-1 satellite. The study was carried out based on six radar images of Sentinel-1A and Sentinel -1B taken from September 2017 until February 2018 with an interval of one month and on the radar-module of the already mentioned SNAP software. The main input data for solving the considered problem are radar images received from the satellite Sentinel-1B on the territory of Stebnyk-Truskavets for six months with an interval of one month. Monitoring of the Earth’s surface using radar data of the Sentinel-1A with a synthesized aperture is implemented with the application of interferometric methods of Persistent Scatterers and Small baselines interferometry for estimating small displacements of the Earth’s surface and structures. The obtained quantitative and qualitative indicators of monitoring do not answer the processes that take place and lead to vertical displacements the six months but do provide an opportunity to assess the extent and trends of their development. The specification in each case can be accomplished by ground methods, which greatly simplify the search for sites with critical parameters of vertical displacements which can have negative consequences and lead to an emergency.