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.
Background: The best material for dental implants is polyetherketoneketone (PEKK). However, this substance is neither osteoinductive nor osteoconductive, preventing direct bone apposition. Modifying the PEKK with bioactive elements like strontium hydroxyapatite is one method to overcome this (Sr-HA). Due to the technique's capacity to provide better control over the coating's properties, RF magnetron sputtering has been found to be a particularly useful technique for deposition.
Materials and methods : With specific sputtering conditions, the RF magnetron technique was employed to provide a homogeneous and thin coating on Polyetherketoneketone substrates.. the coatings were characterized by Contact angle, adhesion test, X-ray dif
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In this research, a detailed finite-element (FE) analysis of the combined influence of the drilled-hole position, the shape of the hole, and the fillet design on the structural and dynamic performance of spur gears is investigated. ANSYS R16.2 was used to create a three-dimensional numerical model that can be used to assess the bending stress distribution and vibration response under realistic loading conditions. A trochoidal fillet and four circular fillet radii (0.5, 1.0, 1.5 and 2.0 mm) were studied to determine their effect on the stress concentration behavior. FE-guided hole-suggestion process was introduced which is an automated process in which low-stress zones to be cut away are identified so as to allo
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Al-Naymi, N.A.Sh., H.A.S. AL-Nuaimi and M.R. Nashaat. 2022. Toxicity Stress of the Durah Power Plant Ash and its Effect on the Alga Chlorococcum humicola (Naeg) Rabenhorst 1868. Arab Journal of Plant Protection, 40(2): 188-192. https://doi.org/10.22268/AJPP-040.2.188192 This study illustrates the acute toxic effect of ash released from Durah power plant (DPP) on the biology of the phytoplankton species Chlorococcum humicola in Iraq. The results showed that the median lethal concentration for killing 50% of the Alga population (LC50) was 0.15 and 0.13 ppt (parts per thousand) for 24 and 48 hours exposure to crude ash concentrations, respectively. In contrast, no LC50 value was recorded for 72 and 96 hrs after exposure. The reduction
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This study investigates the impact of copper sulfate (CuSO4) doping and glycerin plasticization on the structural, electrical, dielectric, and optical properties of poly(vinyl alcohol) (PVA), polyvinyl pyrrolidone (PVP), and glycerin gel polymer electrolytes (GPEs). The GPEs were prepared using a solution casting method with varying CuSO4 concentrations (5 and 10 wt.%). X-ray diffraction analysis revealed the semi-crystalline nature of the polymer blend and also confirmed the presence of CuSO4. Fourier transform infrared spectroscopy confirmed the miscibility of PVA, PVP, and glycerin through interchain hydrogen bonding and indicated the successful incorporation of Cu2+ ions into the polymer blend matrix. The PVA/PVP/glycerin blend containi
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Little is known about hesitancy to receive the COVID‐19 vaccines. The objectives of this study were (1) to assess the perceptions of healthcare workers (HCWs) and the general population regarding the COVID‐19 vaccines, (2) to evaluate factors influencing the acceptance of vaccination using the health belief model (HBM), and (3) to qualitatively explore the suggested intervention strategies to promote the vaccination.
This was a cross‐sectional study based on electronic survey data that was collected in Iraq during December first‐19th, 2020. The electronic surve
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