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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The inhibitory effect of Eucalyptus rostrata leaves extraction was investigated on multiple-antibiotic-resistant pathogenic bacteria (E.coli and S. aureus), isolated from Iraqi patients. The minimum inhibitory concentrations in a final concentration of 10 mg/ml. Tow fold dilutions was done from (12.5- 100) mg/ ml to examine the antibacterial effect of different concentrations of the plant extract on both bacteria. The study results revealed that Eucalyptus rostrata extract has a potential inhibitory effect on both gram negative and gram positive species. The current study supports the traditional approach of using Eucalyptus rostrata leaves extraction in treatment trails against bacterial infections.
The current study deals with the performance of constructed wetland (CW) incorporating a microbial fuel cell (MFC) for wastewater treatment and electricity generation. The whole unit is referred to as CW-MFC. This technique involves two treatments; the first is an aerobic treatment which occurs in the upper layer of the system (cathode section) and the second is anaerobic biological treatment in the lower layer of the system (anode section). Two types of electrode material were tested; stainless steel and graphite. Three configurations for electrodes arrangement CW-MFC were used. In the first unit of CW-MFC, the anode was graphite plate (GPa) and cathode was also graphite plate (GPc), in the second CW-MFC unit, the anode was stainless st
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Abstract
This paper concerned with study the effect of a graphite micro powder mixed in the kerosene dielectric fluid during powder mixing electric discharge machining (PMEDM) of high carbon high chromium AISI D2 steel. The type of electrode (copper and graphite), the pulse current and the pulse-on time and mixing powder in kerosene dielectric fluid are taken as the process main input parameters. The material removal rate MRR, the tool wear ratio TWR and the work piece surface roughness (SR) are taken as output parameters to measure the process performance. The experiments are planned using response surface methodology (RSM) design procedure. Empirical models are developed for MRR, TWR and SR, using the analysis
... Show MoreThe present work reports on the performance of three types of nanofiltration membranes in the removal of highly polluting and toxic lead (Pb2+) and cadmium (Cd2+) from single and binary salt aqueous solutions simulating real wastewaters. The effect of the operating variables (pH (5.5-6.5), types of NF membrane and initial ions concentration (10-250 ppm)) on the separation process and water flux was investigated. It was observed that the rejection efficiency increased with increasing pH of solution and decreasing the initial metal ions concentrations. While the flux decreased with increasing pH of solution and increasing initial metal ions concentrations. The maximum rejection of lead and cadmium ion
... Show MoreThis study includes design and synthesis of new non-steroidal anti-inflammatory agents (NSAIDs) with expected cyclooxygenase-2 (COX-2) selective inhibition to achieve better activity and low gastric side effects. Two series of compounds have been designed and synthesized as potential NSAIDs,these are: Salicylamide derivatives (compounds 3,4,5 ) and Diflunisal derivatives (compounds 10&11). In vivo acute anti-inflammatory effect of one of the synthesized agents (compound 3) was evaluated in the rat using egg-white induced paw edema model of inflammation. Preliminary pharmacological study revealed that compound 3 exhibited less anti-inflammatory effect compared to that of aspirin after
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In this work, we presented a study of the structural formula for a new series of complexes with Ag(I), Cu(II), Zn(II), and Cd(II) derived from the guanine azo dye ligand 2-amino-8-((3-hydroxyphenyl)diazinyl)-1,7-dihydro-6H-purin-6-one (HAG), which is investigated using various physicochemical analyses, spectroscopic techniques (FT-IR, U.V-VIS, and 1H NMR), thermogravimetric analysis (TGA). In addition, elemental analyses, magnetic susceptibility, and molar conductance measurements were all stabilized. As well as the mole ratio, stability constant, and Gibbs free energy were studied for all complexes, where they showed high stability and spontaneous synthesis. The Cu(II) complex was suggested to have octahedral stere
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Data mining is a data analysis process using software to find certain patterns or rules in a large amount of data, which is expected to provide knowledge to support decisions. However, missing value in data mining often leads to a loss of information. The purpose of this study is to improve the performance of data classification with missing values, precisely and accurately. The test method is carried out using the Car Evaluation dataset from the UCI Machine Learning Repository. RStudio and RapidMiner tools were used for testing the algorithm. This study will result in a data analysis of the tested parameters to measure the performance of the algorithm. Using test variations: performance at C5.0, C4.5, and k-NN at 0% missi
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The new ligand N-[2-(2-Phenyl hydrazinyl)Phenyl]benzothiazol-2-amine (L) was prepared from the reaction of orthoaminohydrazo benzene with 2-mercaptobenzothiazole in mole ratio (1:1). It was characterized by elemental analysis (CHN), 1H, 13C-NMR, IR and UV-Vis. The complexes of the bivalent ions Co(II), Ni(II), Cu(II), Cd(II), Hg(II) and Pb(II) have been prepared and characterized. The structural feature were established by elemental analysis (CHN), IR, UV-Vis spectra, conductivity measurements, atomic absorption and magnetic susceptibility. All complexes have been showed octahedral geometry except Cu(II) complex showed square planer. Dissociation degree, stability constant and molar absorptivity (l. mol-1. cm-1) were calculated for all c
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