This study aims to explore the impact of the interaction of the university leadership and the university organizational environment on the performance level of the staff at Al-Maaqal university. This university was chosen as a field of study because it is a new university and needs studies that develops and contributes to improve its overall performance. The problem defined by the following question: to what extent does the interaction of the university leadership and the university organizational environment affect the performance level of the teaching staff at AlMaaqal University?). The method of this study adopted a major hypothesis in which there is a statistically significant effect of university leadership and university environment o

Background: Oil refinery workers are continuously exposed to numerous hazardous materials. Petroleum contains the heavy metals as a natural constituent or as additives. These metals induce the production of ROS which associated with an oxidative damage to DNA, proteins, and lipids. This study was conducted to assess the salivary levels of heavy metals, salivary oxidative status, oral immunological activity (salivary sIgA) and assessment of the oral findings among the workers of Al-Daura oil refinery in Baghdad city. Subjects, Materials and Methods: This study was done in Al-Daura oil refinery; samples consist of 60 workers involved in refinery processes (study group) and 20 non-workers (control group). Oral examination and saliva collection

Abstract

This study aims to identify the level of emotional intelligence among principals of basic education schools in Al-Dakhiliya Governorate. The descriptive approach was used. A questionnaire of two parts was utilized; its second part included (27) items divided into five dimensions related to emotional intelligence. The study sample consisted of (337) teachers representing 52% of the study sample were randomly selected. The study result showed that level of the emotional intelligence is high and the motivation dimension is the highest. There were no statistical differences at the level (α≤ 0.05) due to the impact of (the social type, the educational qualification, and the years of experience) in all the

The subject of the Internet of Things is very important, especially at present, which is why it has attracted the attention of researchers and scientists due to its importance in human life. Through it, a person can do several things easily, accurately, and in an organized manner. The research addressed important topics, the most important of which are the concept of the Internet of Things, the history of its emergence and development, the reasons for its interest and importance, and its most prominent advantages and characteristics. The research sheds light on the structure of the Internet of Things, its structural components, and its most important components. The research dealt with the most important search engines in the Intern

Greywater is a possible water source that can be improved for meeting the quality required for irrigation. Treatment of greywater can range from uncomplicated coarse filtration to advanced biological treatment. This article presents a simple design of a small scale greywater treatment plant, which is a series of physical and natural processes including screening, aeration, sedimentation, and filtration using granular activated carbon filter and differentiates its performance with sand filter. The performance of these units with the dual filter media of (activated carbon with sand) in treatment of greywater from Iraqi house in Baghdad city during 2019 and that collected from several points including washbasins, kitchen si

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.