Globally, buildings use about 40% of energy. Many elements, such as the physical properties of the structure, the efficiency of the cooling and heating systems, the activity of the occupants, and the building’s sustainability, affect the energy consumption of a building. It is really difficult to predict how much energy a building will need. To improve the building’s sustainability and create sustainable energy sources to reduce carbon dioxide emissions from fossil fuel combustion, estimating the building's energy use is necessary. This paper explains the energy consumed in the lecture building of the Al-Khwarizmi College of Engineering, University of Baghdad (UOB), Baghdad, Iraq. The weather data and the building construction information were collected for a specific period and put into a specific data set. That data was used to find the value of energy consumption in the building using artificial intelligence and data analysis. A Python library called Scikit-learn is used to implement machine learning algorithms. In particular, the Multi-layer Perceptron regressor (MLPRegressor) algorithm was used to predict the consumption. The importance of this work lies in predicting the amount of energy consumed. The outcomes of this work can be used to predict the energy consumed by any building before it is built. The used methodology shows the ability to predict energy performance in educational buildings using previous results and train the model on them, and prediction accuracy depends on the amount of data available for the training in artificial intelligence (AI) steps to give the highest accuracy. The prediction was checked using root-mean-square error (RMSE) and coefficient of determination (R²) and we arrived at 0.16 and 0.97 for RMSE and R², respectively.
Population density represents an important indicator for determining the growth of the size of urban areas. Population density has a direct impact on the quality of life, and its excessive rise may lead to the deterioration of basic service facilities. The problem of the research is that the increase in the total population densities of the residential neighborhood may reflect negatively on the nature of the services provided to the residents in these shops, and thus the failure to achieve sustainability in the residential locality. The research assumes that the increase in population densities negatively affects the achievement of sustainability in the residential neighborhood.
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Background:The referral system constitutes a key element of health system. Effective referral system between different levels of health care delivery represents a cornerstone in addressing patients’ health needs.
Objectives:To assess the referral system Baghdad/ Al-Rusafa Health Directorate by evaluation the referral pattern and identify the quality of the referral letters and feedback reports.
Type of the study: This cross-sectional study .
Methodology : It was conducted in5PHCC in from 1st July 2015 - 31st December 2015 at Bagdad/Al-Rusafa health directorate. The study population (sampled population) included all ref
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تستهدف هذه الدراسة وبشكل أساس، الكشف عن طبيعة وخصائص البعد السياسي لهندسة/صناعة الخصائص الاجتماعية والسياسية للإنسان والمجتمع، بوصفها العملية المسؤولة عن تصميم هذه الخصائص وصناعتها وتغييرها جزئيا أو كليا، دون أبعادها الأخرى المتعددة والمتنوعة، لا لمجرد الانسياق وراء دوافع الرغبة الذاتية، أو اعتبارات التخصص الدقيق وأحكامه، لأن معهما أيضا، بل وقبلهما أحيانا، دوافع واعتبارات أخرى موضوع
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Abstract
The study aims to examine the relationships between cognitive absorption and E-Learning readiness in the preparatory stage. The study sample consisted of (190) students who were chosen randomly. The Researcher has developed the cognitive absorption and E-Learning readiness scales. A correlational descriptive approach was adopted. The research revealed that there is a positive statistical relationship between cognitive absorption and eLearning readiness.
Previous studies in Euro-American countries have shown that patients with chronic hepatitis C virus infection have increased levels of neuropsychiatric symptoms. While chronic hepatitis C virus infection has been reported in Arab countries such as Iraq, there is little studies about the neuropsychological burden associated with chronic hepatitis C among patients in the Arab region. The aim of the current study was to measure the prevalence and level of severity of depression, anxiety and stress among a sample of chronic hepatitis C patients in AL-Najaf province /Iraq. The current study was cross-sectional study carried out on (110) already diagnosed chronic viral hepatitis C patients who attended the Gastroenterology and Hepatology
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Background: Menstrual problems with all manifestations ranging from life-threatening bleeding to amen- orrhea are considered patterns of abnormal uterine bleeding (AUB), which is until now a popular reason for referral to the gynaecologic clinic and requires a special diagnostic tool. Objective: To assess the accuracy of hysteroscopy in diagnosing endometrial pathologies and to compare it with sonographic and histopathologic reports. Patients and Methods: A prospective study conducted in the Baghdad Teaching Hospital on 60 Iraqi females having varying complaints from abnormal uterine bleeding in pre- and post-menopausal women, infertility, and chronic pelvic pain with normal or abnormal ultrasound findings. Office hysteroscopy was done and
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Um-Al-Naaj region in Al-Hawiezah Marsh, Southern Iraq was chosen to study the environmental variations of some water characteristics during 2008, seasonally. The results showed clear seasonal changes in values of some environmental variables (temperature, depth, light penetration, turbidity, total suspended solids, pH, dissolved oxygen, reactive phosphate, reactive nitrite, and reactive nitrate), while there were no clear seasonal changes in electrical conductivity and salinity values. In addition, high nutrients concentrations and light penetration were noted. Statistical analysis showed significant positive relationship between air and water temperature; electrical conductivity and salinity. Water turbidity was significantly affecte
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Al-Chibayish Marsh (CM) is considered as the major part of Central Marshes area of this marsh is 1050 Km². The water quality of these marshes is suffering from salt accumulation due to intensive dam construction, limited supply of water from sources, climate change impacts, and the absence of outlet flow from these marshes, specifically at low flow periods. So, the current research aims to assess and improve these marshes' hydraulic behavior and water quality and define the best location for outlet drains. Field measurements and laboratory tests were conducted for two periods (November 2020 and February 2021) to define the (TDS) concentrations at nine different locations. Samples were also examined for water's phy
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