Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University of Baghdad in its colleges with scientific and human specializations. To measure the level of DC, a questionnaire was applied as a data collection tool to a sample of 400 male and female students, distributed based on gender and academic specialization. The results showed that the sample students did not have high DC. Their possession of DC related to AI applications and systems was to a moderate degree. The results indicated that there were differences in the responses of the study sample members due to the gender variable and the specialization variable, in favor of the female students with scientific specialization.
The study aimed to explore the school principals’ servant leadership practices for primary teachers’ perspectives in the Sultanate of Oman, furthermore to investigate the differences in those practices attributable to variables (gender, qualification, educational stage, years of experience, governorate). The study relied on the descriptive approach, by employing the survey research design using the questionnaire as a main tool for data collection, which included five dimensions of servant leadership (altruism, humility, enhancing teacher development, emotional healing, commitment to community development), Data collected from (1094) teachers in basic education schools, and they were chosen randomly. The results of the study indicated
... Show MoreThis research sheds light on one of the important and vital topics for the banking sectors (technical requirements for the application of economic intelligence) namely by (Hardware, equipment, communication networks, software, databases). And the dimensions of the strategic success of the banks represented by(Customer satisfaction, customer trust, quality of service, growth) In the three Iraqi private banks, namely(Assyria International Investment, Mansour Investment, International Development Investment and Finance). Its implementation is an urgent necessity in order to improve the quality of its banking services to win the satisfaction of its customers and their confidence and then grow to achieve stra
... Show MoreThis study aims at identifying the activation of the role of feminine leaders in educational decision-making in educational administrations in the Northern Borders Province in light of the Kingdom's vision 2030. It also aims to identify what educational leadership is, to study the conceptual framework of the contemporary education decision-making process, and to examine the reality of the problems of feminine leaders in educational decision-making in the educational administrations in the Northern Borders. In addition, it tries to develop a proposed vision to activate the role of feminine leaders in educational decision-making in Educational Administrations in the Northern Borders Province in light of Vision 2030. To achieve the objectiv
... Show Moreackground An autoimmune and inflammatory illness called rheumatoid arthritis (RA) occurs when your immune system mistakenly attacks normal cells in your body. Interleukin-35 is a brand-new cytokine that belongs to the immunosuppressive and anti-inflammatory IL-12 family. β -herpesvirus that produces inflammation and stays dormant in its host for life is the human cytomegalovirus. Human herpesvirus (HCMV) has been at the core of several RA-related theories. Objective The current study looked at the association between RA and serum IL-35 levels as well as the association between RA and CMV. Patients and methods Blood samples were taken in the Baghdad Teaching Hospital and Typical Rheumatology Unit from January 2022 to Mars 2022 for the curre
... Show MoreAssessing water quality provides a scientific foundation for the development and management of water resources. The objective of the research is to evaluate the impact treated effluent from North Rustumiyia wastewater treatment plant (WWTP) on the quality of Diyala river. The model of the artificial neural network (ANN) and factor analysis (FA) based on Nemerow pollution index (NPI). To define important water quality parameters for North Al-Rustumiyia for the line(F2), the Nemerow Pollution Index was introduced. The most important parameters of assessment of water variation quality of wastewater were the parameter used in the model: biochemical oxygen demand (BOD), chemical oxygen dem
In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For
... Show MoreIn this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi
... Show MoreSodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-201
... Show MoreIn this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe
... Show MoreForecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti
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