Cadmium has been known to be harmful to human healthy , manily Via contaminated drinking water , food supplies , tobacco and industrial pollutant . The aim of this study was to determine the toxicity of new Cadmium (II) complex ( Bis[ 5- ( P- nitrophenyl ) – ? 4 – Phenyl- 1,2,4- triazole -3- dithiocarbamatohydrazide] cadmium (II) Hydra ( 0.5) and compare it with anticancer drug cyclophosphamide ( CP) in female albino mice . This complex causes to several alterations in Enzymatic activity of Glutamate Pyruvate Transaminase (GPT) and Alkaline Phosphatase (ALP ) in three organs after the treatment of mice with different doses of a new cadmium (II) complex ( 0.09 / 0.25ml , 0.18/ 0.5ml and 0.25mg /0.7 ml /30 gm of mous

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

<span lang="EN-GB">Transmitting the highest capacity throughput over the longest possible distance without any regeneration stage is an important goal of any long-haul optical network system. Accordingly, Polarization-Multiplexed Quadrature Phase-Shift-Keying (PM-QPSK) was introduced lately to achieve high bit-rate with relatively high spectral efficiency. Unfortunately, the required broad bandwidth of PM-QPSK increases the linear and nonlinear impairments in the physical layer of the optical fiber network. Increased attention has been spent to compensate for these impairments in the last years. In this paper, Single Mode Fiber (SMF), single channel, PM-QPSK transceiver was simulated, with a mix of optical and electrical (Digi

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

A field experiment was carried out in the fields of the Field Crops Department - Faculty of Agricultural Engineering Sciences. The study included five inbred lines (ZM43W (ZE), ZM60, ZM49W3E, ZM19, CDCN5), given numbers 1, 2, 3, 4 and 5) to study the hybrid vigor and both general and special combing ability (GCA, SCA) of the half diallel mating method, for the spring and fall seasons (2016). The genetic analysis shows that all crosses gave a positive hybrid vigor for grain yield per unit area at the two population densities. the highest value is 116.20% for cross (3´5 )at low density, and 89.22% for cross( 1´4 )at high density. The hybrid vigor for all crosses is positive at two densities for dry matter yield, crop growth rate an

Background: Dyslipidemia is defined as an abnormally high level of various lipids in the blood. It is considered a major risk for atherosclerosis and coronary artery disease. Genetic susceptibility can have a significant influence on the development and progression of dyslipidemia. ApoB-100 R3500Q mutation and ApoE variants are among those genetic risks for dyslipidemia. This study aims to assess the possible contribution of ApoB and ApoE variants on lipid profile among a group of early-onset ischemic heart disease (IHD) patients in comparison to a group of controls. Methods: Forty patients with dyslipidemia and early-onset IHD without chronic conditions likely to cause derangement of lipid levels were recruited to this case-control study