The study aimed to reveal the role of social capital represented by its dimensions (structural, relational, and cognitive) in strengthening the management of excellence in Azadi Hospital / Duhok. In order to reach the goal of the study, the study variables were highlighted in theory through framing concepts and literary contributions for researchers in this field, In the field, the questionnaire was used as a basic tool to collect data from the individuals in the research sample who were represented by officials and individuals working from administrators and technicians, as (120) forms were distributed to the respondents, and (110) were retrieved from them in a way that is valid for analysis. Several statistical methods have been used in dealing with data and testing study hypotheses, including central tendency measures, correlation coefficient, and the regression line equation, A set of conclusions was reached the most important of which was the existence of the relationship and the moral impact of social capital in all its dimensions in the distinction management in the researched hospital and all the effects were good, which explains to us that there is tangible interest by the hospital examined with social capital, which reflected positively on the process of excellence and management Its activities, The study is out with several proposals, the most prominent of which is to support the dimensions of social capital in the researched organization by spreading the culture of cooperation and supporting social relations and clarifying its role in promoting excellence in the performance of activities and increasing their effectiveness as well as The possibility of benefiting from the strengths of the researched hospital in relation to social capital, which had a clear impact on managing excellence.
This study was undertaken to diagnose routine settling problems within a third-party oil and gas companies’ Mono-Ethylene Glycol (MEG) regeneration system. Two primary issues were identified including; a) low particle size (<40 μm) resulting in poor settlement within high viscosity MEG solution and b) exposure to hydrocarbon condensate causing modification of particle surface properties through oil-wetting of the particle surface. Analysis of oil-wetted quartz and iron carbonate (FeCO₃) settlement behavior found a greater tendency to remain suspended in the solution and be removed in the rich MEG effluent stream or to strongly float and accumulate at the liquid-vapor interface in comparison to naturally water-wetted particles. As su
... Show MoreDuring 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
... Show MoreThis study included the isolation and identification of Aspergillus flavus isolates associated with imported American rice grains and local corn grains which collected from local markets, using UV light with 365 nm wave length and different media (PDA, YEA, COA, and CDA ). One hundred and seven fungal isolates were identified in rice and 147 isolates in corn.4 genera and 7 species were associated with grains, the genera were Aspergillus ,Fusarium ,Neurospora ,Penicillium . Aspergillus was dominant with occurrence of 0.47% and frequency of 11.75% in rice grains whereas in corn grains the genus Neurospora was dominant with occurrence of 1.09% and frequency 27.25% ,results revealed that 20 isolates out of 50 A. flavus isolates were able
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