This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

This study aimed to investigate the prevalence of intestinal helminth infections in humans and detect Toxocara spp. in cats, with a focus on assessing the impact of age and gender on infection rates. Traditional diagnostic methods have historically limited the accurate identification of helminth infections in humans. Analysis of 450 human stool samples revealed an overall helminth infection rate of 5.7% using conventional techniques. The specific infection rates were 0.4% for Strongyloides stercoralis, 0.6% for Schistosoma mansoni, 1.7% for Hymenolepis nana, and 2.8% for Ascaris lumbricoides. Notably, no infections were recorded in the 30–39 and ≥40-year age groups, while the highest infection rate (16.3%, P≤0.01) was observed in indi

Graphene oxide (GO) was prepared from graphite (GT) with Hammer method, the GO was reduced with hydrazine hydrate to produce a reduced graphene oxide (RGO). The RGO was reacted with thiocarbohydrazide (TCH) to functionalize the RGO with 4-amino-3-symbol-1h-1, 2, 4-triazol-5 (4H) –thion group and to obtain (RGOT). All the prepared nanomaterial and the product of the functionalization RGOT were characterized with Fourier transformer infrared (FT-IR) spectroscopy, X-ray diffraction (XRD) analysis. RGOT mixed with ultrasonic device at different pH values of phosphate buffer solution (PBS), the mixture used to modifying a screen printed carbon electrodes SPCE and with cyclic voltammetry the sensitivity of selectivity of the new modifying elect

The main problem established by a discovery of a thyroid nodule is to discriminate between a benign and malignant lesion. Differential diagnosis between follicular thyroid cancer (FTC) and benign follicular thyroid adenoma (FTA) is a great challenge for even an experienced pathologist and requires special effort. A developing number of some encouraging IHC markers for the differential diagnosis of thyroid lesions have emerged, including, Hector Battifora mesothelial (HBME-1) and galectin-3 (Gal-3). There was significant positive correlation between Galectin-3 and HBME-1 in follicular carcinoma and follicular variant of papillary carcinoma (r= 0.380, P= 0.041) and (r= 0.315, P=0.047) respectively. There was no significant correlation between