The study is dealing with an application reengineering process clean solar cells in the Ministry of electricity,  as aimed at the possibility of the applicability and impact of re-engineering to achieve the level of performance of the Ministry's operations, with the application of the cleaning process  solar cells, developed, improved and found a correlation, statistically significant effect between variable re-engineering and performance as well as the application of process reengineering clean solar cells:1- Before the re-engineering process the total time for cleaning up and solar cell 20 minutes and number of columns performed per day 24 columns and total  columns750 which were completed per month that re

The assessment of the environmental impact of the cement industry using the Leopold Matrix is ​​to determine the negative and positive impacts on the environment resulting from this industry, and what are the long-term and short-term effects, direct and indirect, and the amount of these effects and potential risks, and that this evaluation process is done through a number of methods, including Matrix method, including (Leopold).

The importance of the research because the cement occupies is of great importance in the world, especially in our country, Iraq, in the sector of construction and modernity, and the toxic emissions and solid waste produced by the production of this material. <

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

There have been many advances in the solar chimney power plant  since 1930 and the first pilot work was built in Spain (Manzanares) that produced 50 KW. The solar chimney power plant is considered of a clean power generation that needs to be investigated  to enhance the performance by studying the effect of changing the area of passage of air to enhance the velocity towards the chimney to maximize design velocity. In this experimental and numerical study, the reduction area of solar collector was investigated. The reduction area that mean changing the height of glass cover from the absorbing plate (h1=3.8cm, h2=2.6cm and h3=1.28cm). The numerical study was performed using ANSYS Fluent software package (version 14.0) to solve go

In this paper it is required to enhance the performance of a mechanical system (here: a Hoisting System) where it is preferred to lift a different payloads with approximately the same speed of lifting and keeping at the same time the good performance, and this of course needs some intelligence of the system which will be responsible on measuring the present load and taking into account the speed and performance desired in order to achieve the requirements or the criteria. The process therefore is a Mechatronics System design which includes a measuring system, a control or automation technique, and an actuating system. The criteria built here in this research using a given Hoist system's characteristics and parameters and changing one of

Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

      In this research, carbon nanotubes (CNTs) is prepared  through the Hummers method with a slight change in some of the work steps, thus, a new method has been created for preparing carbon nanotubes which is similar to the original Hummers method that is used to prepare graphene oxide. Then, the suspension carbon nanotubes is transferred to a simple electrode position platform consisting of two electrodes and the cell body for the coating and reduction of the carbon nanotubes on ITO glass which represents the cathode electrode while platinum represents the anode electrode. The deposited layer of carbon nanotubes is examined through the scanning electron microscope technique (SEM), and the images throughout the research show the