The electric submersible pump, also known as ESP, is a highly effective artificial lift method widely used in the oil industry due to its ability to deliver higher production rates compared to other artificial lift methods. In principle, ESP is a multistage centrifugal pump that converts kinetic energy into dynamic hydraulic pressure necessary to lift fluids at a higher rate with lower bottomhole pressure, especially in oil wells under certain bottomhole condition fluid, and reservoir characteristics. However, several factors and challenges can complicate the completion and optimum development of ESP deployed wells, which need to be addressed to optimize its performance by maximizing efficiency and minimizing costs and uncertainties. To

Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

Background: Friedreich ataxia (FRDA) is the most common form of inherited ataxia, comprising one-half of all hereditary ataxias with a carrier rate between 1 in 60 to 1 in 90 and with a disease prevalence of 1 per 29,000. It can occur in two forms the classic form or in association with a vitamin E dependent ataxia. The precise role of Vitamin E in the nervous system is unknown; An Oxidative attack is suspected to play a role in Ataxia with Vitamin E deficiency, as well as in Friedreich ataxia. Vitamin E is the major free-radical-trapping antioxidant.

Objective: Theobjectives of the study is to asses vitamin E level in patients with Friedreichs ataxia phenotype in Iraqi patients.

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The present research aims to test the effect of cognitive complexity as an independent variable in organizational agility as a responsive variable among the leaders working at the headquarters of the Iraqi Petroleum Products Distribution Company.

 To conclude a number of recommendations that contribute in the organizational agility in the company, and due to the importance of this research in public organizations and its notable role in community organizations. The research was carried out on a random sample of 101 individuals out of a total of 308, which represents the high leaders in the company (general managers, head of departments, and division officials). A questionnaire was used as information