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.
Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned
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Asthma is a chronic respiratory disorder of airways characterized by inflammation, hyperresponsiveness, inflammatory cell infiltration, mucous secretion, and remodelling. Ammi majus is medicinal plant belong to family of Apiaceous which has anti-inflammatory and antioxidant activities. This study designed to investigate of anti-asthmatic activity of alcoholic extract of Ammi majus in improvement of asthma. Forty-eight healthy female mice divided to six groups Group I: the negative control group (distal water only), Group II: Positive control group (ovalbumin group), Group III: Ammi majus (64 mg/kg/day) with sensitization, Group IV:Ammi majus (128 mg/kg/day) with sensitization, Group V: Ammi majus (64 mg/kg/day) without sensitiza
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This study aims to assess the effect of adding twisted fins in a triple-tube heat exchanger used for latent heat storage compared with using straight fins and no fins. In the proposed heat exchanger, phase change material (PCM) is placed between the middle annulus while hot water is passed in the inner tube and outer annulus in a counter-current direction, as a superior method to melt the PCM and store the thermal energy. The behavior of the system was assessed regarding the liquid fraction and temperature distributions as well as charging time and energy storage rate. The results indicate the advantages of adding twisted fins compared with those of using straight fins. The effect of several twisted fins was also studied to discover
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The Atmospheric Infrared Sounder (AIRS) on EOS/Aqua satellite provides diverse measurements of Methane (CH4) distribution at different pressure levels in the Earth's atmosphere. The focus of this research is to analyze the vertical variations of (CH4) volume mixing ratio (VMR) time-series data at four Standard pressure levels SPL (925, 850, 600, and 300 hPa) in the troposphere above six cities in Iraq from January 2003 to September 2016. The analysis results of monthly average CH4VMR time-series data show a significant increase between 2003 and 2016, especially from 2009 to 2016; the minimum values of CH4 were in 2003 while the maximum values were in 2016. The vertical distribution of CH4<
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This article presents the simultaneous adsorption of bimetal Cu2+ and Zn2+ from an aqueous solution using activated carbon synthesized from a plum seed precursor by sulfuric acid and microwave activation: plum seeds chemically activated by 45% (w/w) sulfuric acid with 2:1 ratio for 4 h, then carbonized for 2 h at 700 °C and the product obtained activated in a microwave oven for 20 min at 700 W for final of activation. Plum seeds and activated carbon produced were characterized in terms of their physical and chemical composition using Brunauer–Emmett–Teller measurements, field emission scanning electr
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Breast cancer (BC) is first of the top 10 malignancies in Iraq. Dose‐volume histograms (DVHs) are most commonly used as a plan evaluation tool. This study aimed to assess DVH statistics using three‐dimensional conformal radiotherapies in BC in an adjuvant setting.
A retrospective study of 70 histologically confirmed women diagnosed with BC was reviewed. The study was conducted between November 2020 and May 2021, planning for treatment with adjuvant three‐dimensional conformal radiotherapies. The treatment plan used for each woman was based on an analysis of the volumetric dose, inclu
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