At thermal energies near stellar conditions, nuclear reactions are sensitive to resonance strengths of the nuclear reaction cross-section. In this paper, the resonance strengths of  nuclear reaction were evaluated numerically by means of nuclear reaction rate calculations using a written Matlab code, at the energies of interest in stellar nuclear reactions. The results were compared with standard reaction before and after application of a statistical analyses, to select the best parameters that made theoretical results as close as possible to the standard values. Fitting was made for different temperature ranges up to 10 GK, 0.6 GK and 0.25 GK. The evaluated results showed that as the temperature range becomes narrower, more error is ad

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

The textile industries play a prominent role in reviving the national economy, but they are currently suffering from several problems, including the high costs of their activities, the low quality of their production processes, and accordingly, the hexagonal diffraction approach came to help analyze production activities to determine which of them are the most expensive and do not have a benefit or cost greater than Its benefit as a result of waste and losses that accompany its implementation. And by applying to the Iraqi mechanical carpet factory, the research reached several conclusions, the most important of which is the presence of several sources of waste and loss, such as activities and operations that do not add value, whi

This study aims to design unified  electronic information system to manage students attendance in Lebanese French university/Erbil, as a system that simplifies the process of entering and counting the students absence, and generate absence reports to expel students who passed  the acceptable limit of being absent, and by that we can replace the traditional way of  using papers to count absence,  with  a complete electronically system for managing students attendance, in a way that makes the results accurate and unchangeable by the students.

            In order to achieve the study's objectives, we designed an information syst

Abstract This research scrutinizes the impact of external magnetic field strength variations on plasma jet parameters to enhance its performance and flexibility. Plasma jets are widely used for their high thermal and kinetic energy in both medical and industrial fields. The study employs optical emission spectroscopy to measure electron temperature, electron density, and plasma frequency in a plasma jet subjected to varying magnetic field strengths (25, 50, 100, 150, and 250 mT). The results indicate that a stronger magnetic field results in higher electron temperature (1.485 to 1.991 eV), electron density (5.405 × 1017 to 7.095 × 1017), and plasma frequency 7.382 × 1012 to 8.253 × 1012 Hz. As well as the research investigates the influ

This study involves the design of 24 mixtures of fiber reinforced magnetic reactive powder concrete containing nano Silica. Tap water has been used in mixing 12 of these mixtures, while the other 12 have been mixed using magnetic water. Nano Silica (NS) with ratios (1, 1.5, 2, 2.5 and 3) % were used. The results showed that the mixture containing 2.5%NS gives the highest compressive strength at age 7 days. Many different other tests were carried out, the results showed that the fiber reinforced magnetic reactive powder concrete containing 2.5% NS (FRMRPCCNS)  has the higher bulk density, dynamic modulus of elasticity, ultrasonic pulse velocity  electrical resistivity and lesser absorption than fiber reinforced

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete