In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf

Abstract:

There is a close relationship between rigidity and distort structure of production and productivity and inflation rates. The effects of this relationship are distorted the contribution rate of the productive sectors and the disproportionate of exchange rate in foreign trade.

raising the general level of prices is one of the way that have been used by previous governments (inflationary financing or deficit financing) in order to speed up the process of capital formation, depending on the availability of economic resources idle.

The fabricating inflation for development does not represent a true understanding of the nature of the

Enhancing fatigue resistance in asphalt binders and mixtures is crucial for prolonging pavement lifespan and improving road performance. Recent advancements in nanotechnology have introduced various nanomaterials such as alumina (NA), carbon nanotubes (CNTs), and silica (NS) as potential asphalt modifiers. These materials possess unique properties that address challenges related to asphalt fatigue. However, their effectiveness depends on proper dispersion and mixing techniques. This review examines the mixing methods used for each nanomaterial to ensure uniform distribution within the asphalt matrix and maximize performance benefits. Recent research findings are synthesized to elucidate how these nanomaterials and their mixing proce

Background: Male infertility is a global concern and it tends to increase due to miscellaneous factors, such as environmental toxins and genetic and lifestyle choices. The aryl hydrocarbon receptor (AHR) has recently attracted attention due to its involvement in male infertility mechanisms and impact on sperm production and function. AHR, a versatile receptor expressed in various tissues, including the testes, regulates the genes involved in spermatogenesis. AHR activation is associated with cell cycle regulation and chromatin condensation during spermatogenesis. Objectives: This study aimed to investigate the influence of AHR activation on blood-testis barrier (BTB) integrity, focusing on the role of tight junction protein-1 (TJP1)

The tunnel’s stability during construction is a very important matter. Some methods have been proposed for stability evaluation, but the hazard warning levels (HWLs) are more applicable among these methods. Despite monitoring and applying HWLs, several collapses in Shibli twin tunnels in Iran have cast doubts on the accuracy of this criterion in the presence of water. In this study, the critical strains under different water contents were measured through uniaxial compressive strength tests on 11 different shale and marl samples. A comparison of laboratory tests and numerical results shows that the influence of the moisture content on the critical strain is negligible. In addition, the results show that there is no dir

In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re