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.
A simple straightforward mathematical method has been developed to cluster grid nodes on a boundary segment of an arbitrary geometry that can be fitted by a relevant polynomial. The method of solution is accomplished in two steps. At the first step, the length of the boundary segment is evaluated by using the mean value theorem, then grids are clustered as desired, using relevant linear clustering functions. At the second step, as the coordinates cell nodes have been computed and the incremental distance between each two nodes has been evaluated, the original coordinate of each node is then computed utilizing the same fitted polynomial with the mean value theorem but reversibly.
The method is utilized to predict
... Show MoreThe time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al
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تسعى المحاسبة الى مسايرة القفزات الهائلة والمتسارعة في تطور العلوم الصرفة والتطبيقية والتقدم التكنولوجي، والتي ادت على ظهور مفاهيم جديدة الغت مسلمات وبديهيات كانت سائدة لمدة طويلة، فعلى سبيل المثال: كان مخزون المواد الاولية والبضاعة التامة في المؤسسات الصناعية او التجارية يشكل العمود الفقري لها بتكاليفه ومشاكله، حتى اذا ما جاء نظام (JIT) الغى بتطبيقاته هذه المفاهيم واعتمد م
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The role of filamentous bacteria represented by Streptomycessp was studied as biological treatment for activated sludge AL- Restomia treatment unit in Baghdad city. The result shows reducing in phosphate concentration where apprise in started entrance the treatment unit 12.083 mg/L fast the unit stages reached to 8.426 mg /L where nitrate concentration apprises 3.59 mg/l and ending in 2.43 mg/L The concentration of ammonia apprises 1358 mg/L and reached to 140 mg/L. also the TDS concentration reduced from 1426 to 1203 mg/L where nutrient which represented (SO4, Mg, Ca, Na, K) reduced by range 30.883- 23.337 , 194- 121 , 440- 321 , 109.03- 101.53 and 16.85- 15.4mg/L respectively COD reduce from427.263- 82mg/L with absorbance0.018- 0.027
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The impact of applying the K-W-L self-scheduling technique on first-year intermediate students' learning of basic volleyball skills, Ayad Ali Hussein*, Israa Fouad Salih
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Background: Nutrition can affect periodontal disease through contributing to microbial growth in the gingival crevice, affecting the immunological response to bacterial antigens and assisting the repair mechanism of the connective tissue at the local site after injury from plaque and calculus. The aim of this study was to assess the prevalence of Oral hygiene (plaque and calculus) and gingivitis in relation to age, gender and nutritional status. Materials and methods: The sample included (444) kindergarten children at age of (4 and 5 years old) males and females from urban areas in Al-Ramadi city. The assessment of nutritional status was performed using anthropometr
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