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.
During 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
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During 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
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Objective: is to determine the level of awareness concerning the reproductive health among adolescent girls in
Baghdad City.
Methodology: A cross sectional study was performed in order to assess the level of awareness regarding reproductive
health among 180 adolescent school girls in the age 12-18 years from five secondary schools in Al-Seder Sector in
Baghdad city, the data was collected by direct interview using constructed questionnaire to obtain socio-demographic
characteristics and level of awareness related to reproductive health. The study started from September 2012 to
January 2013.
Results: the results show that the highest percentage of girls (47.7%) was in age (17-18) year's age, (54.5%) at 4th class
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Jamal Basha: His Administrative and Political Effort in Baghdad
The practice of self medication is continuously increasing worldwide due to its important roles in curing minor conditions or symptoms. This study was conducted to evaluate the factors associated with self medication practice of Iraqi respondents residing in Baghdad City. This study was designed as cross sectional study in which data was collected via direct interviews with respondents using a previously prepared questionnaire. This study investigated 348 respondents from different age groups. The majority of respondents were male aged between 30-60 years, married with secondary or academic level of education and employed with accepted monthly income. The main reason for practicing self medication was previous experience with the same condi
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Pregnancy at an early age of life is a major challenge. The consequences of this problem have an impact on the quality of life of the young mother and her family, and determines an important risk for her offspring. The son of a teenage mother has, in general, greater risks than that of a mother of more than 20 years. The aim of this study is to determine the prevalence and outcome of teenage pregnancy. A descriptive data base study was conducted at Al-Elwia Maternity Teaching hospital in the period from January 1, 2019 to the end of June 2019 within the age between 12 and 19 years old. The mean age of the mother was 17.4 ±1.5 years. The mean age of the father was 23.9 ± 5.7 years with (69.5%) with Vaginal delivery and most of the
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Due to the deterioration of water quality within the last few years because of the increase of water consumption and the waste water production and disposal into the river The water quality in both surface and ground water resources was negatively affected .The concept of water quality index is used as a tool for water quality classification in Tigris River within Baghdad City .Twenty two parameters of pollution were selected to measure the water quality indices of Tigris river within Baghdad city .Those parameters were measured during (2000-2004)as average monthly values ,three water treatment plants were selected out of the eight water treatment plants that exist along the river.Al Kharkh water treatment plant to reflect the water quality
... Show MoreBackground: Birth defects are the leading cause of both neonatal and post-neonatal deaths, as an estimated 240,000 neonates die in their first month of life worldwide each year. In Iraq, local studies have shown varying frequencies and types of congenital anomalies. Objectives: To provide new insight into the incidence and types of congenital anomalies and to explore their possible risk factors in Baghdad City. Methods: In this cross-sectional observational study, a total of 2007 neonates were enrolled from six hospitals in Baghdad during the period extending between September and December 2020. Hospital records and personal interviews were used for data collection. These data included the neonates' demographic and clinical characte
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