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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This assay rapidly detects chlorpromazine hydrochloride using its ability to reduce gold ions to form nanoparticles. Its low cost, resilience to interferences and short analysis time could facilitate environmental monitoring and biomedical analysis.
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Background: Recurrent aphthous ulceration (RAU) is an inflammatory condition of unknown etiology characterized by painful recurrent (single or multiple) ulcerations of the oral mucosa. It is one of the most common and poorly understood mucosal disorders. It occurs more frequently in times of stress. Local and systemic conditions, genetic, immunologic, microbial factors, and oxidative stress may play a role in the pathogenesis of RAU. The objective of this study was to evaluate the free radical metabolism and antioxidant activity of RAU patients treated by lavender or flax oil paint.
Materials and Methods: Sixty-six RAU patients were enroll
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The fresh water green alga Chlorella vulgaris was selected to study its ability to degrade one of polycyclic aromatic hydrocarbon (PAHs)known is anthracene (ANT). ANT is widely used in artificial products such as wood preservatives; insecticides; dye and coating materials. This algae was cultivated in CH-10 medium under constant laboratory conditions and exposed to different concentrations (1, 3, and 5 mg/l) of anthracene for 3, 5, 7, 9 and 15 days, with the concentration of ANT measured by high performance liquid chromatographic analysis (HPLC). The results showed that C.vulgaris has high ability to reduce anthracene to 80% at 1mg/Lcon centration after 3 days and 100% after 5 days, while at 3 and 5 mg / L concent
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The aim of this study is to investigate the effect of environmental management accounting information (EMAI) on the design process of environmental and sustainable products of Iraqi industrial companies. This process has five different sub-processes: research process, analysis process, conceptual design process, detailed design process and design production process. The study uses the quantitative approach as the questionnaire was designed and distributed to 87 quality managers, production managers, design managers and financial managers. The MANOVA analysis shows that EMAI has a positive and significant effect on three of these processes, namely research process, analysis process and detailed design process, while EMAI has an insi
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Variation orders are an on-going phenomenon in construction and industry projects worldwide, particularly in the province of Sulaimani, where the project's damage from cost and schedule overrun because of variation orders. However, the effect on project costs and time overrun of variation order has yet to be identified. This study evaluates the impact of variation orders on the cost and time off in the Sulaimani governorate. Two hundred twenty-eight projects from various construction sectors built between 2007-2012 were adopted to calculate the contract cost and schedule overruns due to variation orders. Data analysis was applied in the study were descriptive statistics. One-way ANOVA was also applied to determine w
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This work investigates the effect of earthquakes on the stability of a collective pile subjected to seismic loads in the soil layer. Plaxis 3D 2020 finite element software modeled pile behavior in dry soils with sloping layers. The results showed a remarkable fluctuation between the earthquakes, where the three earthquakes (Halabja, El Centro, and Kobe) and the acceleration peak in the Kobe earthquake had a time of about 11 seconds. Different settlement results were shown, as different values were recorded for the three types of earthquakes. Settlement ratios were increased by increasing the seismic intensity; hence the maximum settlement was observed with the model under the effect of the Kobe earthquake (0.58 g), where
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This assay rapidly detects chlorpromazine hydrochloride using its ability to reduce gold ions to form nanoparticles. Its low cost, resilience to interferences and short analysis time could facilitate environmental monitoring and biomedical analysis.
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The last decade has seen a variety of modifications of glass-ionomer cements (GICs), such as inclusion of bioactive glass particles and dispensing systems. Hence, the aim was to systematically evaluate effect of mixing modes and presence of reactive glass additives on the physical properties of several GICs.
The physical properties of eight commercial restorative GICs; Fuji IX GP Extra (C&H), KetacTM Fill Plus Applicap (C&H), Fuji II LC (C&H), Glass Carbomer Ce
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