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.
On Saturday, May 13, 2023, a glorious day was engraved in the history of Al-Kindy College Medical Journal as it is the day of indexing the journal in the Scopus Database Journals. The journal has paced a strenuous journey to make that achievement.
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This search seeks to know the trends of academics in the field of Press and audio, video and read press about paper press compared with continued development and widespread deployment of web journalism. This research belongs to descriptive studies which depends on sample survey approach adopted by five-meter design measuring trends. It contains 28 items having applied honesty and reliability transaction and the scale form is distributed to the sample studied of about 110 professors and then the researcher collects them and then applying the appropriate statistical program to get the results. This search seeks to know the trends of academics in the field of Press and audio, video and read press about paper press compared with continu
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<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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The study aims at finding out:
1. The students' attitude towards the mixed learning at the university.
2. The statistically significant differences in attitude towards the mixed learning at the university according to the specialization variable.
3. The statistically significant differences in attitude towards the mixed learning at the university according to the gender variable.
The researcher has constructed a scale for measuring the students' attitude towards the mixed learning at the university.
After assuring its validity and reliability, the scale has been given to a sample of (100) students. The sample is selected randomly from (4) colleges of the university of Baghdad, (2) for scientific specialization and (2)for h
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Land use change, particularly the expansion of urban areas and associated human activities at the expense of natural and semi-natural areas, is a major ecological issue in urban areas around the world. Climate change being a very strong additional driver for changing the temperature and habitat in the cities. This also applies to Baghdad, Iraq, where urbanisation and climate change exerts a major pressure on the natural habitats of the city, and thus may affect the ability of city planners to adapt to future climate change scenarios. Here we present evidence of substantial growth in urban areas, increases in temperature, and degradation of natural vegetation within Baghdad city by using Remote Sensing techniques and an assessment for the
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Background The study covered thirty-three species which grown wildly in Iraq and a comparative study for all kinds of morphological characters were done. Principal Findings The most stable and important taxonomic characters were pointed out, diagrams, illustrations, scheduals, micrographs were also documented. Stamens, nutlets, basal leaves, bracts, bracteoles, calyces, corollas and their trichomes were very important taxanomic characters. The trichomes were variable in variable species therefore used as a diagnostic characters for the species. Conclusions New species Salvia margasurica Al-Musawi & Al-Hussaini was suggested to be new record for science. Keywords: Salvia, Morphology, Spec. Nov.
Vascular plants that have been identified during the study seasons in the Island. The cultivated plants were 126 species belong to 103 genera and to 49 families of the year 2001-2002 . The natural vegetation in this Island has been subjected to a total disturbance and subsidence due to the comprehensive turbidity of the Island environment.Number of names of that natural vegetation has been mentioned in the study within the weed plants.The results of the study of the period of flowering and their attitudes show clear seasonal differences. During the cold months of winter, the number of the cultivated and the natural plants was at the rate of 15%.These kinds of flowers require high level of care to increase their numbers. While in the spring
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