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.
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Modeling the microclimate of a greenhouse located in Baghdad under its weather conditions to calculate the heating and cooling loads by computer simulation. Solar collectors with a V-corrugated absorber plate and an auxiliary heat source were used as a heating system. A rotary silica gel desiccant dehumidifier, a sensible heat exchanger, and an evaporative cooler were added to the collectors to form an open-cycle solar assisted desiccant cooling system. A dynamic model was adopted to predict the inside air and the soil surface temperatures of the greenhouse. These temperatures are used to predict the greenhouse heating and cooling loads through an energy balance method which takes into account the soil heat gain. This is not included in
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The V2O5 films were deposited on glass substrates which produce using "radio frequency (RF)"power supply and Argon gas technique. The optical properties were investigated by, UV spectroscopy at "radio frequency" (RF) power ranging from 75 - 150 Watt and gas pressure, (0.03, 0.05 and 0.007 Torr), and substrate temperature (359, 373,473 and 573) K. The UV-Visible analysis shows that the average transmittance of all films in the range 40-65 %. When the thickness has been increased the transhumance was decreased from (65-40) %. The values of energy band gap were lowered from (3.02-2.9 eV) with the increase of thickness the films in relation to an increase in power, The energy gap decreased (2.8 - 2.7) eV with an increase in the pressure and
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KE Sharquie, AA Noaimi, AS Alaboudi, Journal of Cosmetics, Dermatological Sciences and Applications, 2012 - Cited by 3
Bioindicators have an important role in assessing the quality of water bodies. Aquatic oligocheates, was used as a bioindicator to assess the sediment quality of Al-Hindyia and AL-Abbasyia river (branches of Euphrates River in Iraq). Two sites in each river have been chosen for this purpose, site S1 was located at Al-Hindyia River and S2 at Al-Abbasyia River. Some kinds of biological indices were used in this study, comprising the percentage of oligochaetes in benthic invertebrates, ranged from 20.3-60.16%. While the percentage of Tubificidae within benthic invertebrates was close 43.3-43.9%.Index of pollution D ranged from 0.13-0.21. The maximum percentage of aquatic oligochaetes to insects larvae of family
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Background: Breast cancer is the most frequently diagnosed malignancy and the second leading cause of mortality among women in Iraq forming 23% of cancer related deaths. The low survival from the disease is a direct consequence to the advanced stages at diagnoses. Aim: To document the composite stage of breast cancer among Iraqi patients at the time of diagnosis; correlating the observed findings with other clinical and pathological parameters at presentation. Patients and Methods: A retrospective study enrolling the clinical and pathological characteristics of 603 Iraqi female patients diagnosed with breast cancer. The composite stage of breast cancer was determined according to UICC TNM Classification System of Breast Cancer and the Ameri
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Background: This in vitro study evaluated the fracture resistance of weakened endodontically treated premolars with class II MOD cavities restored with different composite restorations (Low-shrinkage Filtek P90, nanohybrid Filtek Z250 XT and SDR bulk fill). The type and mode of fracture were also assessed for all the experimental groups. Materials and Method: Fifty human adult maxillary premolar teeth were selected for this study. Standardized extensive class II MOD cavities with endodontic treatment were prepared for all teeth, except those that were saved as intact control. The teeth were divided into five groups of ten teeth each (n=10): (Group 1) intact control group, (Group 2) unrestored teeth with endodontic treatment, (Group 3) resto
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