Today, dimethyl ether (DME) is changing to ordinarily worn as a superb aerosol propellant and refrigerant for its eco-friendly characteristics. Lately, with the development of novel chemical energy in the coal industries, it has become a fascinating field of research as an alternative green fuel for diesel machines due to the high cetane number. The DME synthesis processes include catalytic dehydrating methanol in an adiabatic fixed-bed reactor. In this study, to investigate the chemical conditions of the methanol dehydration reaction, CFD simulations of the adiabatic reactor have been assessed. The advantage of the work is a sensitivity analysis was run to find the effect of pressure, kinetics, and velocity on the reactor performan

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.

Abstract Objectives: Malocclusion was and remains one of the most common problems which affects the psyche and social status of the individual, so the estimation of the malocclusion severity and needs a percentage of orthodontic treatment of Iraqi patients is the aim of this study. Method: A randomly selected 150 pairs of study models (48 male and 102 female) were involved in this study for patients attending an orthodontic clinic at College of Dentistry/ University of Baghdad seeking for treatment. The DAI scores were collected according to WHO guidelines directly from the study model with a digital caliper, score was calculated using the regression equation of 10 occlusal traits. The dental casts were classified into four groups to determ

       In this paper, a fixed point theorem of nonexpansive mapping is established to study the existence and sufficient conditions for the controllability of nonlinear fractional control systems in reflexive Banach spaces. The result so obtained have been modified and developed in arbitrary space having Opial’s condition by using fixed point theorem deals with nonexpansive mapping defined on a set has normal structure. An application is provided to show the effectiveness of the obtained result.

This paper compare  the accurecy of HF propagation  prediction programs for  HF circuits links between Iraq and  different points world wide  during August 2018 when  solar cycle 24 (start 2009 end 2020) is at minimun activity and also find out the best communication mode  used. The prediction   programs like Voice of America Coverage Analysis Program (VOACAP) and ITU Recommendation RS 533 (REC533 )  had been used to generat HF circuit link  parameters like Maximum Usable Frequency ( MUF) and Frequency of Transsmision (FOT) .Depending  on the predicted parameters (data)  , real radio contacts had been done using a radio transceiver from Icom  model IC 7100 with 100W RF

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

In this study, we tackle the understudied area of Artificial Intelligence (AI) and its role in examining how modern revolutions may affect political systems across the Middle Eastern region. despite hundreds of studies documenting Middle Eastern uprisings over the past three decades, there has been little effort to harness AI to better understand or predict these multifaceted events. This study seeks to address this gap by assessing the performance of AI-intelligence in analyzing (broadly) revolutionary processes and their effects on regional political systems. The research uses a mixedmethod methodology that involves a systematic literature review of contemporary scholarly articles, and an analytics study using AI tools. Our results show t

Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect