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 current study, a direct method was used to create a new series of charge-transfer complexes of chemicals. In a good yield, new charge-transfer complexes were produced when different quinones reacted with acetonitrile as solvent in a 1:1 mole ratio with N-phenyl-3,4-selenadiazo benzophenone imine. By using analysis techniques like UV, IR, and 1H, 13C-NMR, every substance was recognized. The analysis's results matched the chemical structures proposed for the synthesized substances. Functional theory of density (DFT)
has been used to analyze the molecular structure of the produced Charge-Transfer Complexes, and the energy gap, HOMO surfaces, and LUMO surfaces have all been created throughout the geometry optimization process ut
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Nonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a
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In this research , we study the inverse Gompertz distribution (IG) and estimate the survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes
The 3-aminoacetophenone and 4-aminoantipyrine were used as precursors to prepare new six ligands. The three new ligands (L1,L2 and L3) were synthesis by reacting one mole of 3-aminoacetophenone with one mole of (Acetyl chloride), (benzoyl chloride), (4-methoxybenzoyl chloride) and ammonium thiocyanat in acetone as a solvent, they are:- L1 (AAA) =[N-(3-acetylphenylcarbamothioyl)acetamide] L2 (BAA) =[N-(3-acetylphenylcarbamothioyl)benzamide] L3 (MAA) =[N-(3-acetylphenylcarbamothioyl)-4-methoxy benzamide] Also three new derivatives of 4-aminoantipyrine were synthesis by reacting one mole of 4-aminoantipyrine with one mole of (Acetyl chloride), (benzoyl chloride), (4-methoxybenzoyl chloride) and ammonium thio
... Show MoreThe activity of Alanine aminopeptidase( AAP ) was measured in the urine of healthy and urinary tract cancer patients , the results showed higher activity of (AAP) in patients compared to healthy . AAP was Purified from the urine of healthy and patients with urinary tract cancer by dialysis and gel filtration (Sephadex G – 50) and two isoenzymes of (AAP) were separated from urine by using ion-exchang resin (DEAE – Sephadex A – 50 ) in previous study. The kinetics studies showed that both isoenzymes I and II obeyed Michaelis – Menton equation . with optimal concentration of alanine-4-nitroanilide as substrate for isoenzymes I and II which was (2 x 10-3 mol/L ). The two isoenzymes obeyed Arrhenius equation up two 37° C and t
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The beet armyworm (BAW), Spodoptera exigua (Lepidoptera: Noctuidae) is a highly destructive pest of vegetables and field crops. Management of beet armyworm primarily relies on synthetic pesticides, which is threatening the beneficial community and environment. Most importantly, the BAW developed resistance to synthetic pesticides with making it difficult to manage. Therefore, alternative and environment-friendly pest management tactics are urgently required. The use of pesticidal plant extracts provides an effective way for a sustainable pest management program. To evaluate the use of pesticidal plant extracts against BAW, we selected six plant species (Lantana camara, Aloe vera, Azadirachta indica, Cymbopogon citratus, Nicotiana tabacum ,
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The present work reports the performance of three types of polyethersulfone (PES) membrane in the removal of highly polluting and toxic lead Pb2+ and cadmium Cd2+ ions from a single salt. This study investigated the effect of operating variables, including pH, types of PES membrane, and feed concentration, on the separation process. The transport parameters and mass transfer coefficient (k) of the membranes were estimated using the combined film theory-solution-diffusion (CFSD), combined film theory-Spiegler-Kedem (CFSK), and combined film theory-finely-porous (CFFP) membrane transport models. Various parameters were used to estimate the enrichment factors, concentration polarization modulus, and Péclet number. The pH values signif
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This study shows that it is possible to fabricate and characterize green bimetallic nanoparticles using eco-friendly reduction and a capping agent, which is then used for removing the orange G dye (OG) from an aqueous solution. Characterization techniques such as scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDAX), X-Ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) were applied on the resultant bimetallic nanoparticles to ensure the size, and surface area of particles nanoparticles. The results found that the removal efficiency of OG depends on the G‑Fe/Cu‑NPs concentration (0.5-2.0 g.L-1), initial pH (2‑9), OG concentration (10-50 mg.L-1), and temperature (30-50 °C). The batch experiments showed
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Green synthesis is depending on preparation of nano composited SiO2/V2O5 by using the modified sol-gel method depending on rice husk ash as a source for the extraction of silica gel and the product powder of nano composited SiO2/V2O5 characterization by many techniques such as X-ray diffraction spectroscopy (XRD), field emission scanning electron microscopy (FESEM), and N2 adsorptions/desorption isotherms (BET). This study also includs the biological effectiveness of SiO2/V2O5 and its effect on inhibiting bacterial growth after the prepared nanomaterial was applied to wound dressings, which gave a promising result for its use as
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