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.
The study aimed to reveal the possibility of predicting academic procrastination through both Cognitive distortions and time management among students of Al-Aqsa Community College, as well as to reveal the level of both cognitive distortions, time management, and academic procrastination. Additionally, it aimed to identify the size of the correlation between cognitive distortions, time management, and academic procrastination. The study sample consisted of (250) students from Al-Aqsa community college students. The results of the study concluded that the mean for each level of cognitive distortions and academic procrastination is average. The mean level of time management is high. There is a statistically significant positive relationshi
... Show MoreThis paper proposes feedback linearization control (FBLC) based on function approximation technique (FAT) to regulate the vibrational motion of a smart thin plate considering the effect of axial stretching. The FBLC includes designing a nonlinear control law for the stabilization of the target dynamic system while the closed-loop dynamics are linear with ensured stability. The objective of the FAT is to estimate the cubic nonlinear restoring force vector using the linear parameterization of weighting and orthogonal basis function matrices. Orthogonal Chebyshev polynomials are used as strong approximators for adaptive schemes. The proposed control architecture is applied to a thin plate with a large deflection that stimulates the axial loadi
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Background: Dental anomalies might occur due to abnormal events during teeth development caused by environmental or genetic factors during histo differentiation or morph differentiation stages of embryological development. Aims of the study: To evaluate the distribution of developmental dental anomalies according to age and gender in relation to nutritional status in children attending College of Dentistry /University of Baghdad. Materials and method: After examination 5760 children aged 5-12 years of both genders only 147child with dental anomalies were found, all developmental dental anomalies that were clinically observable were recorded. The developmental dental anomalies which diagnosed in this study were supernumerary, missing teeth,
... Show MoreIn the present work, a set of indoor Radon concentration measurements was carried out in a number of rooms and buildings of Science College in the University of Mustansiriyah for the first time in Iraq using RAD-7 detector which is an active method for short time measuring compared with the passive method in solid state nuclear track detectors (SSNTD's). The results show that, the Radon concentrations values vary from 9.85±1.7 Bq.m-3 to 94.21±34.7 Bq.m-3 with an average value 53.64±26 Bq.m-3 which is lower than the recommended action level 200-300 Bq/m3 [ICRP, 2009].
The values of the annual effective dose (A.E.D) vary from 0.25 mSv/y to 2.38 mSv/y, with an average value 1.46±0.67 mSv/y which is lower than the recommended the rang
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Type 1 diabetes mellitus (T1DM) is an autoimmune disease frequently associated with autoimmune thyroid disease (AITD). The study is conducted at the Specialized Center for Endocrinology and Diabetes-Baghdad at Al-karkh side, during December 2013 up to April 2014. In this study, we investigate the prevalence of anti-thyroid peroxidase (anti-TPO) antibody in(80) type1 diabetic patients with (AITD) and (30) healthy controls .Blood samples are taken for investigation of thyroid tests by using Vitek Immunodiagnstic Assay System (VIDAS).Enzeme Linked Immunosorbent Assay (ELISA) is used to detect anti-thyroid antibody(anti-TPO). The results show that age, gender and BMI (body mass index) are similar in both groups, p>0.05. Among 80 type1 diabetic
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