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.
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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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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
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The research aims to identify the obstacles facing the application of electronic management in our university libraries, including the central library of the University of Baghdad and the central library of Al-Mustansiriya University, the research sample, as they are among the main libraries that used electronic technologies in managing some of their work and in providing their services, and they have a website via the Internet. The research relied on the case study method to identify the obstacles by visiting the two libraries, interviewing their managers and employees responsible for the departments, and answering inquiries about the obstacles that prevent the application of electronic management in order to identify them and find appropr
... Show Moreتسعى 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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A study of some biological aspects of the crustacean Isopod procellio scaber was carried out for the period April 2003 to march 2004 . The study consisted reproductive and morphological characteristies such as size , weight and length of the body . The result showed that the highest population density of P. scaber was 1120 individual/m2 in September 2003 and less density 403 ind/m2 in February 2004. The density was generally high in Spring and Autumn, low in Summer and Winter months.An increase of the sexual ratio appear in the females number compared to males number (p < 0.05) during most of year. Present study showed non significant increase in the length and dry weight for females compared to males in most of year months. There wer
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Background: Routine supplementation of vitamin D to infants is justifiable since vitamin D deficiency, and its consequences are highly prevalent not only in developing countries but worldwide. Maintaining a normal level of vitamin D is crucial in order to have a normal skeletal, as well as, extra-skeletal health. Knowledge of mothers regarding importance of vitamin D supplementation affect the health of their babies in a positive manner if accompanied by appropriate practice.
Objective: To determine the level of knowledge, attitude and practice of Iraqi mothers of under or equal 12 months old infants in Baghdad, AL-Rusafa, regarding vitamin D supplementation for their infants.
Typ
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