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.
Literature reviews of reports concerning the parasitic fauna of fishes of Al-Diwaniyah province, Iraq till the end of December 2018 showed that a total of 43 parasite species are so far known from 13 valid fish species investigated for parasitic infections. The parasitic fauna included one euglenozoan, two myzozoans, six ciliophorans, three myxozoans, three trematodes, nine monogeneans, four cestodes, six nematodes, three acanthocephalans and six crustaceans. The infection with the trematodes, one monogenean, two cestodes and one nematode occurred with larval stages, while the remaining infections were either with trophozoites or adult parasites. Among the inspected fishes, Carasobarbus luteus was infected wit
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The construction sector consumes large amounts of energy during the lifetime of a building. This consumption starts with manufacturing and transferring building materials to the sites and demolishing this building after a long time of occupying it. The topic of energy conservation and finding the solution inside the building spaces become an important and urgent necessity. It is known that the roof is exposed to a high amount of thermal loads compared to other elements in a building envelope, so this needs some solutions and treatments to control the flow of the heat through them. These solutions and treatments may be achieved by using nanomaterials. Recently, nanomaterials have high properties, so that this made them go
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The present work aimed to make a comparative investigation between three different ionospheric models: IRI-2020, ASAPS and VOACAP. The purpose of the comparative study is to investigate the compatibility of predicting the Maximum Usable Frequency parameter (MUF) over mid-latitude region during the severe geomagnetic storm on 17 March 2015. Three stations distributed in the mid-latitudes were selected for study; these are (Athens (23.50o E, 38.00o N), Jeju (124.53o E, 33.6o N) and Pt. Arguello (239.50o W, 34.80o N). The daily MUF outcomes were calculated using the tested models for the three adopted sites, for a span of five-day (the day of the event and two days preceding and following the event day). The calculated datasets were co
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Hepatitis C virus (HCV) is a liver disease that affects14 million people. Feasible research was conducted for identifying the genotypes and allele frequency of some single nucleotide polymorphisms (SNPs) of the IL-28β genes and their predictive role in disease incidence in Iraqi patients. The SNPs (rs28416813, rs4803219, rs11881222, and rs8103142) of IL-28β have been associated with susceptibility to several diseases. Ninety eight (98) HCV patients were included in this research; with average age ± SE (42.28 ± 3.44) years. Also, 80 healthy people (with average age ± SE (29.40 ± 2.84) years) were included as a control group. The SNPs were detected by allele-specific PCR (polymerase chain reaction) using specific primers. The re
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MM Abdulwahhab, kufa Journal for Nursing sciences, 2017 - Cited by 1
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