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.
In this study, the stable isotop 18O and 2H has been used to investigate the interaction of surface water (SW), and groundwater (GW) in Al-Taji district/ Northern Baghdad for two seasons (March and August 2022). 16 Samples were collected from water resources in the Al-Taji district (Tigris channel, Tigris River, and groundwater), in each season water samples from 8 Tigris channel, 5 drilled wells, and 3 Tigris River were taken for the analysis of the isotopes 18O and 2H. The average analysis results of 18O and 2H in the Tigris channel, Tigris River, and groundwater were found to be -3.435‰ and -18.6094‰, -2.07167‰ and -17.81‰, -4.125‰ and -34.707‰ respectively. The results, generally, show a comparable range of isotope c
... Show More
(2)
This study is the first and new record to the spider Scytodes univittata Simon, 1882 (Araneae:Scytodidae)in Baghdad /Iraq , the spiders Scytodes univittata were collect from province Baghdad in Iraq , genus Scytodes belong to the family Scytodidae it is one of the most family are wide distribution around the world have 6 eyes and are slow moving , the genus Scytodes are known from the names spitting spiders ,.Female Scytodes univittata can be characteristic by :large round cephalothorax length:4.45 mm , abdomen length 3.50, total body length 7.95 mm and V-shaped of fovea, scutela triangle and large with long thin legs femur I have two row of spines then spineless are in IV femur , coloration is yello
... Show More
The beginning of COVID-19 in Wuhan, China in late December 2019 and its worldwide transmission has led the World Health Organization to formally address the pandemic. The pandemic has imposed influential impacts on different environmental, economic, social, health, and living aspects. Publishing in scholastic journals was not immune from these impacts.
(1)
The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti
... Show More
(1)
The study aims to identify the metamemory and perceptual speed among College students, the correlation between metamemory and perceptual speed among College students, and to which extend does metamemory contribute to perceptual speed among College students. The sample consisted of group of students were selected randomly by the researcher from five-different disciplines at the college of education for pure sciences. To collect study data, the researcher utilized two scales: perceptual speed scale that has translated to Arabic language by (Al-Shraqawi, Al- Shaikh, and Nadia Abed Al-Salam (1993). The second scale is metamemory scale (2002) which has translated to Arabic by Abu Ghazal (2007). The results revealed that college students have
... Show More
(21)
(17)
(8)
(6)
The need for Dewatering is very important in construction workshops field and sometimes it needs to pay more attention as a result of its impacts on causing additional settlement of nearby pile foundations. Dewatering construction may become a costly topic if ignored during project planning and designing .In this paper a simplified procedure maybe adopted to calculate the foundation settlement induced by using dewatering system which is required to lower the water table level to reach a dry condition during construction. Synthesized case study adopted at a specified location in Baghdad city and analysis are computed for two types of piles both of them are submerged with water. Results shows the effect of dewatering on pile foundatio
... Show More