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.
<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver & kroeber, overlap, and pearson correlation
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Motives: This study examines the integration of Feng Shui principles into urban public spaces to enhance social interaction, livability, and environmental harmony. The case study focuses on the Al-Arabi and Al-Washash neighbourhoods in Baghdad, exploring how spatial characteristics influence engagement and energy circulation (Qi) within the urban network. The motivation arises from deficiencies in connectivity, shading, greenery, and water features, which limit social and aesthetic vibrancy. Aim: The objectives are to evaluate spatial and social dynamics through the Feng Shui Public-Space Index (FS-PSI), Space Syntax analysis, and resident surveys, and to propose strategies using Feng Shui design proxies to improve energy flow, acce
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The study included the determination of pollen grains features for 8 genera and 13 taxa of Mimosoideae subfamily grown in Baghdad/ Iraq by using each of light and scanning electron microscope. The samples of taxa were collected from various sites in Baghdad province in central Iraq located on 32 45° 0-33 45 0 N and 44 0 0- 44° 45 0 E. the results from this study revealed different pollen types as monad in each of Leucaena, Prosopis, and Neltuma, tetrad in Mimosa and polyads in Acacia, Albizia, Calliandra, Pithecellobium and Vachellia. Each taxa of these genera characterized by special palynological features as shape, size, number of polyads grain and conplateuration as well as other parameters included other dimensions, and these
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OpenStreetMap (OSM) is the world’s biggest publicly licensed geographic data collection. Because OSM is rapidly being used in a wide range of applications, researchers have focused their efforts on determining its quality. The OSM buildings data quality is still ambiguous, due to the limitations, and a few researchers have evaluated the OSM buildings data quality through difficulties where the authoritative data are not obtainable. The focus of this research is to analyze and assess the accuracy of OSM buildings including completeness, and positional accuracy methods. Two different study areas in Baghdad city-Iraq have been investigated: Al-Rasheed and Al-Karrada. The process of the (OSM) data evaluation involved identifying the correspon
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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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