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.
A new chelate complexes of Co(II),Ni(II),Zn(II) and Cd(II) were prepared by reacting these ions with the ligand 2-[4- Carboxy methyl phenyl azo]-4,5-diphenyl imidazole (4CMeI) The preparation were conducted after fixing the optimum conditions such as (pH) and concentration .UV- visible spectra of these complex solutions were studied for a range of (pH) and concentration which obey lampert-Beers Law.The structures of complexes were deduced according to mole ratio method which were obtained from the spectroscopic studies of the complex solutions .The ratios of metal: ligand obtained were (1:2) for all complexes..(UV-Vis) absorption spectra and The infrared spectra of the chelating complexes were studied ,this may indicate that coordination be
... Show MoreThe formation of Co(II), Ni(II), Cu(II), Zn(II), and Cd(II)-complexes (C1-C5) respectively was studied with new Schiff base ligand [benzyl(2-hydroxy-1-naphthalidene) hydrazine carbodithioate derived from reaction of 2-hydroxy-1-naphthaldehyde and benzyl hydrazine carbodithioate. The suggested structures of the ligand and its complexes have been determined by using C.H.N.S analyzer, thermal analysis, FT-IR, U.V-Visible, 1HNMR, 13CNMR , conductivity measurement , magnetic susceptibility and atomic absorption. According to these studies, the ligand coordinates as a tridentate with metal ions through nitrogen atom of azomethane , oxygen atom of hydroxyl, and sulfur atom of thione
... Show MoreThe Co (II), Ni (II) ,Cu(II), Zn(II) ,Cd(II) and Hg(II) complexes of mixed of amino acid (L-Alanine ) and Trimethoprim antibiotic were synthesized. The complexes were characterized using melting point, conductivity measurement and determination the percentage of the metal in the complexes by flame (AAS). Magnetic susceptibility, Spectroscopic Method [FTIR and UV-Vis]. The general formula have been given for the prepared mixed ligand complexes [M(Ala)2(TMP)(H2O)] where L- alanine (abbreviated as (Ala ) = (C5H9NO2) deprotonated primary ligand, L- Alanine ion .= (C5H8NO2 -) Trimethoprim (abbreviated as (TMP ) = C10H11N3O3S M(II) = Co (II),Ni(II) ,Cu(II), Zn(II) ,Cd(II) and Hg(II). The results showed that the deprotonated L- Alanine by KOH (Ala
... Show MoreThe paper tackles two topics. The first is about the term "Ремейк" which is very common in contemporary Russian literature; it has counterparts such as " Обработка" and " Переделка", where these two may indicate any of the following meanings (remake, reformulate, rewrite, treatment, modification, change). It has been shown that this term does not have a stable definition. Also, the role of this term in literary studies has been mentioned along with how it has come to its peak of use in post-modern literature.
The second is that I have taken a sample of well-known works in Russian literature " On the Eve, On the Eve " by the contemporary Russian writer YevgueniBobov, and shown the effort of the writer
... Show MoreThe adsorption ability of Iraqi initiated calcined granulated montmorillonite to adsorb Symmetrical Schiff Base Ligand 4,4’-[hydrazine-1, 2-diylidenebis (methan-1-yl-1-ylidene)) bis (2-methoxyphenol)] derived from condensation reaction of hydrazine hydrate and 4-hydroxy-3-methoxybenzaldehyde, from aqueous solutions has been investigated through columnar method.The ligand (H2L) adsorption found to be dependent on adsorbent dosage, initial concentration and contact time.All columnar experiments were carried out at three different pH values (5.5, 7and 8) using buffer solutions at flow rate of (3 drops/ min.),at room temperature (25±2)°C. The experimental isotherm data were analyzed using Langmuir, Freundlich and Temkin equations. The monol
... Show MoreThe trading banks in Iraq invest their funds according to regulations imposed by the Central Bank in Iraq in different financial fields like stock exchanges, acquire stocks as assets that could be sold at any time as well as make loans and contributing in corporations establishment also magnitude foreign capital through direct contacts with foreign exchange markets.
We can summarize the problem of this paper as shortage in mathematical models that used in studying and analyzing these investments and according to this problem we used (a constructed mathematical model ) consists of three major indicators: profitability of total investment assets which is divided into three sub-indicators: owners equity risk indicator, debits risk i
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