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 area comprises Injana Formation (Late Miocene), exposed on the hills nearby of Tharthar Lake and about 120 km north of Baghdad city. This study depends on sedimentologic and facies analysis to recognize paleoenvironment and recognize the kinds of vertebrate bone fossils during Late Miocene. Sedimentologic and facies analysis showed many sedimentary facies: facies (Se) of scoured erosional surface, facies of (Sp) cross- bedded sandstones, facies (Fs) of fine sandstone facies, facies of (Fc) claystone, and facies of (C) calcareous clay. Facies analysis referred to the sub environments which are: point bar, over bank and floodplain in addition to fining upward cycles of deposition, which refers to meandering flu
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Cyprinidae species are the most abundant and widely distributed fish species in the inland waters of Iraq. Cyprinids are complex species, and it is difficult to identify them on the basis of morphology. Thus, the morphological characteristics must be achieved and confirmed by molecular analysis. Twenty specimens of Cyprinion kais Heckel, 1843 (Piscies, Cypriniformes, Cyprinidae) were collected from two localities at Tigris River in the middle of Iraq: five specimens from Al-Tharthar Lake, Saladin Province, and 15 specimens from Al- Zubaydiyah sub-district, Wasit Province
Cyprinidae species are the most abundant and widely distributed fish species in the inland waters of Iraq. Cyprinids are complex species, and it is difficult to identify them on the basis of morphology. Thus, the morphological characteristics must be achieved and confirmed by molecular analysis. Twenty specimens of Cyprinion kais Heckel, 1843 (Piscies, Cypriniformes, Cyprinidae) were collected from two localities at Tigris River in the middle of Iraq: five specimens from Al-Tharthar Lake, Saladin Province, and 15 specimens from Al- Zubaydiyah sub-district, Wasit Province. The DNA sequences of C. kais were done using the mitochondrial DNA cytochrome b (cytb) gene. After analysis, the sequences were compared with sequences of ot
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The Research topic seeks to analyze the "political risk and its component Terrorism Index," which consists of five indicators index, a number of terrorist operations, and the number of dead and wounded, and the size of the physical losses, based search sub-index analysis of material losses for the index terrorism and its impact on the indicators listed on the Iraq Stock Exchange Finance. As for the practical side, it has been use style gradient unrestricted and link the sample represented by ten banks listed on the Iraq Stock Exchange. was Statement the correlation and interaction of variables of the studySearch results produced that the volume of material losses is the most important indicator in the influential force and it explain a v
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The purpose of the study is to analyze the extent of the impact of liquidity as an independent variable on profitability as an intermediate variable and the value of banks listed in the Iraq Stock Exchange as a dependent variable, as the research problem is summarized by the fact that most banks focus on profitability as a phased goal without focusing on maximizing its value as a strategic goal by enhancing the wealth of owners and shareholders. On the long term, the research community is represented by the banks listed on the Iraq Stock Exchange, while the research sample was deliberately chosen, which included three private banks such as Baghdad Commercial Bank, the Iraqi Commercial Bank and the Iraqi Investment Bank, an
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The research specified with study the relation between the market share for the sample research banks and the amount of the achieved revenues from the investment, where the dominated belief that there potentiality enhancing the revenue on investment with the increase of the banks shares in their markets after their success in achieving rates of successive growth in their sales of sales and to a suitable achieve market coverage for their products and they have dissemination and suitable promotion activity, the market share represented the competition for the banks, and the markets pay attention to the market share as a strategic objective and to maintain them also increasi
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Shear wave velocity is an important feature in the seismic exploration that could be utilized in reservoir development strategy and characterization. Its vital applications in petrophysics, seismic, and geomechanics to predict rock elastic and inelastic properties are essential elements of good stability and fracturing orientation, identification of matrix mineral and gas-bearing formations. However, the shear wave velocity that is usually obtained from core analysis which is an expensive and time-consuming process and dipole sonic imager tool is not commonly available in all wells. In this study, a statistical method is presented to predict shear wave velocity from wireline log data. The model concentrated to predict shear wave velocity fr
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