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 the field of civil engineering, the adoption and use of Falling Weight Deflectometers (FWDs) is seen as a response to the ever changing and technology-driven world. Specifically, FWDs refer to devices that aid in evaluating the physical properties of a pavement. This paper has assessed the concepts of data processing, storage, and analysis via FWDs. The device has been found to play an important role in enabling the operators and field practitioners to understand vertical deflection responses upon subjecting pavements to impulse loads. In turn, the resultant data and its analysis outcomes lead to the backcalculation of the state of stiffness, with initial analyses of the deflection bowl occurring in conjunction with the measured or assum
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Myriophyllum spicatum distribution in Al-Burgga marsh, Hor Al-Hammar was described in relation to some of the physical-chemical properties for its habitat (water depth, light penetration, water temperature, water salinity, pH, dissolved oxygen, Ca+2, Mg+2, reactive NO2=, reactive NO3-1, and reactive PO4-3) during 2011, seasonally. CANOCO ordination program (CCA) was used to analyse the data. Its vegetation cover percentage was with its peak at summer, its value was 90 %, while the lowest value was 20 % in winter. Statistically, Positive relationships for WT, sal., Ca+2, Mg+2, reactive NO2=, reactive NO3-1, and reactive PO4-3 with the vegetation cover percentage were observed. While, negative relationships for WD, pH, and DO with the ve
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60 cases of Bacteremia were documented at Ibn Al-Baladi hospital during 6 months (1-1-2002 to 1-7-2002), with an incidence of 5.2 were gram-negative organisms and most common one was Salmonella and Klebsiella. Incidence was significantly higher in male than female .Antimicrobial sensitivity tests revealed that isolated bacteria are with multiple drug resistance to commonly used antimicrobial agents. Salmonella showed high resistance to cephaloxin, co-trimoxazole and amoxicillin and also Klebsiella showed resistance to cephaloxin and amoxicillin.
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Persistence of antibiotics in the aquatic environment has raised concerns regarding their potential influence on potable water quality and human health. This study analyzes the presence of antibiotics in potable water from two treatment plants in Baghdad City. The collected samples were separated using a solid-phase extraction method with hydrophilic-lipophilic balance (HLB) cartridge before being analyzed. The detected antibiotics in the raw and finished drinking water were analyzed and assessed using high-performance liquid chromatography (HPLC), with fluorometric detector and UV detector. The results confirmed that different antibiotics including fluoroquinolones and
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Clean energy applications widely recognize Proton Exchange Membrane Fuel Cells (PEMFCs) for their high efficiency and environmental compatibility. Accurate parameter identification of PEMFC models is essential for enhancing system performance and reliability, particularly under dynamic operating conditions. This paper presents a novel optimization-based approach called Heterogeneous Comprehensive Learning-Bald Eagle Search (HCLBES) with enhanced exploration and exploitation capabilities for the effective modeling of PEMFC. The algorithm combines the exploration strength of the Bald Eagle Search with comprehensive learning and heterogeneity mechanisms to achieve a balanced global and local search space. In this algorithm, the number
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This study deals with the impact of leadership styles in its three main dimensions (democratic, autocratic, lenient) as an independent variable of the dimensions of functional combustion (emotional stress, inhumanity, personal achievement). The research sought to achieve a set of goals, the most prominent of which are: studying the reality of the researched organization to identify the leadership patterns used in its management and its impact on the phenomenon of functional combustion, Moreover, knowing the extent of support for these established patterns and their contribution to mitigating the phenomenon of functional combustion in the organization's environment, and testing the impact of these leadership patte
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The current research aims to identify the level of mental alertness among students of the Department of Chemistry in the Faculty of Education for Pure Sciences – Ibn Al-Haytham during the academic year (2022-2023). To achieve this goal, a descriptive approach was followed. The research community was identified as all chemistry students across the four grades (first, second, third, and fourth). A sample from each grade was selected for the current research. A tool was prepared to measure mental alertness within the research sample. The researcher adopted the scale by Baer, Smith, Kristemoyer, & Tany (2006), which was developed by Al-Buhairi et al. (2014), ensuring its validity, reliability, and psychometric characteristics, making i
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