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.
Meta stable phase of SnO as stoichiometric compound is deposited utilizing thermal evaporation technique under high vacuum onto glass and p-type silicon. These films are subjected to thermal treatment under oxygen for different temperatures (150,350 and 550 °C ). The Sn metal transformed to SnO at 350 oC, which was clearly seen via XRD measurements, SnO was transformed to a nonstoichiometric phase at 550 oC. AFM was used to obtain topography of the deposited films. The grains are combined compactly to form ridges and clusters along the surface of the SnO and Sn3O3 films. Films were transparent in the visible area and the values of the optical band gap for (150,350 and 550 °C ) 3.1,
Abstract The aim of this study is to identify the role played by the university in reinforcing the culture of voluntary work in college students and sequencing these roles according to their priority. To achieve this aim, the researcher used the descriptive approach. After being informed of the literature background and of the previous studies related to the core aim of this recent study, the researcher has built up a questionnaire of (20) items investigating the role of university in reinforcing the culture of voluntary work in the college students. The standardized features of the questionnaire have been checked for the purpose of the questionnaire validity (virtual and constructive validity) and stability (reconstruction and Cronbach's A
... Show MoreIn this study, the relationship between the bare soil temperature with respect to its salinity is presented, the bare soil feature is considered only by eliminating all other land features by classifying the site location by using the support vector machine algorithm, in the same time the salinity index that calculated from the spectral response from the satellite bands is calibrated using empirical salinity value calculated from field soil samples. A 2D probability density function is used to analyze the relationship between the temperature rising from the minimum temperature (from the sunrise time) due to the solar radiation duration tell the time of the satellite capturing the scene image and the calibrated salinity index is presented. T
... Show MoreThis study was conducted to determine the relationship between test anxiety and cognitive representation among university students. To this end, 152 student (male, female) were chosen randomly from scientific and social departments to fill out the questionnaires of test anxiety and cognitive representation. The researcher utilized Independent Samples T-Test, Pearson product-moment correlation coefficient, Cronbach's alpha and T-Test in his study. The result revealed that there were negative and a weak correlation between test anxiety and cognitive representation among university students.
Two series of 1,3,4-oxadiazole derivatives at the sixth position of the 2,4-di-
Arbuscular mycorrhizal fungi and sulphur foam added either at direct seeding or at transplanting decreased the effects of nematode (Meloidogyne javanica) on eggplant growth, and improved plant health. Experiments were conducted to study the possible interactions between the Mycorrhizal fungi (Glomus mossae and Gigaspora spp.) and sulphur foam to control M. javanica on eggplant at seed or seedling stage. Experiment at seed stage treated with Mycorrhiza or sulphur foam alone or together stimulated the growth and reduced Nematode infestation significantly. Treated plant at seedling stage increased plant growth and reduced the number of galls /gm of root system. The interaction between Mycorrhiza and sulpher foam treatments was not significant
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