In this study, the use of non-thermal plasma theory to remove toxic gases emitted from a vehicle was experimentally investigated. A non-thermal plasma reactor was constructed in the form of a cylindrical tube made of Pyrex glass. Two stainless steel rods were placed inside the tube to generate electric discharge and plasma condition, by connecting with a high voltage power supply (up to 40 kV). The reactor was used to remove the contaminants of a 1.25-liter 4-cylinder engine at ambient conditions. Several tests have been carried out for a ranging speed from 750 to 4,500 rpm of the engine and varying voltages from 0 to 32 kV. The gases entering the reactor were examined by a gas analyzer and the gases concentration ratio

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Protection of the oil pipelineswhich extracted from the wells was found to shut the well and prevent the leakage of oil when broken using safety valve. This valve is automatically activated by loss of pressure between the well and pipelines, which take the pressure, signal from hydraulic pressure sensor through pressure control valve which has constant or variable value but it is regulated manually. The manual regulatory process requires the presence of monitoring workers continuously near the wells which are always found in remote areas. In this paper, a smart system has been proposed that work with proportional pressure control valve and also electronic pressure sensor through Arduino controller, which is programmed in a way that satisfie

The goal (purpose) from using development technology that require mathematical procedure related with high Quality & sufficiency of solving complex problem called Dynamic Programming with in recursive method (forward & backward) through  finding series of associated decisions for reliability function of Pareto distribution estimator by using two approach Maximum likelihood & moment .to conclude optimal policy

Objectives:  The present study aimed to assess the compulsion among health care providers during the pandemic of COVID-19.

Methodology:  a descriptive design was used in the present study.  This study was conducted from October 10th, 2020 through May 20th, 2021.  The study was conducted on a probability (convenient) sample of 248 physicians and nurses who work at Baghdad Teaching hospital in Baghdad city.  The instrument was used in this study is the COVID Stress Scale-Arabic version (CSS).

 Results:  The result of this study showed that 42 % of HCPs had moderate symptoms and 36% of them had mild compulsive symptoms, and

Among a collection of leafhoppers from Erbil Province in Kurdistan/Iraq, a new species of the genus Arboridia Zakhvatkin, 1946 was designated and described here as a new species  to  the science. The erection of this species was mainly built on the external characters included the male genitalia. Sites and dates of collections so as the host-plants were verified.

The paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be

In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho