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.
Shiranish has been studied at Hijran section near Erbil city, NE Iraq. Fifty two thin-sections were prepared to study them under polarized microscope, to determine the petrographic component, organic content and digenetic processes. Rock units subdivided into four rock beds, as follows: dolostone, foraminiferal biomicrite, poorly washed biomicrite and micrite. Vertical succession of Shiranish Formation refers to off-shore quite marine environment.
Abstract We have been studied and analysis the electronic current at the interfaces of Au/PTCDA system according to simple quantum mode for the electronics transition rate due to postulate quantum theory. Calculation of electronic current were performed at interface of Au/PTCDA as well as for investigation the feature of electronic density at this devices. The transition of electronic current study under assume the electronic state of Au and PTCDA were continuum and the states of electrons must be closed to energy level for Au at Fermi state, and the potential at interface feature depended on structure of Au and PTCDA material. The electronic transition current feature was dependent on the driving force energy that results of absorption ene
... Show MoreShiranish Formation (Late Campanian- Maastrichtian) that cropping out north east Iraq, is studied by microfacies analysis of 52 thin section collected from Hijran Section, about 10 km west Shaqlawa Town, Governorate of Erbil. According to petrography, mineralogy and organic contents, rocks are subdivided to crystalline carbonate and microfacies units (biowackstone, packstone, and mudstone facies). Biowackstone facies have high ratio of the rock components, while the other facies have low ratio. Microfacies analysis led to relatively quiet deep marine environment.
Objective: Diarrhea is a symptom of a variety of conditions may attack the child. It considered one of
mam causes of mortality rates especially in low socio- economic level countries. The child can be
easily got dehydration and pass from loss of too much body fluid and due to the Common thoueht of
increasing the incidence of diarrhea during summer season, this study is done to find out the relation
between the high incidences rate of diarrhea and weather variation
Methodology: This survey conducted in AL- Markazi Child's Teaching Hospital for the year 2005 the
data were gathered from hospital records for the period (January - December) and age groups
taxonomy used by hospital applied. Descriptive statistical analysis
This study aimed to evaluate the sustainable efficiency and calculate the sustainable value, opportunity cost and revenue to cost of potato production farms in Baghdad Governorate. Data were collected from a random sample of 102 spring potato producers in Baghdad governorate for the year 2022, the value-added function was estimated using three levels: economic (seeds and space), and social (education level), while environmental represented by (residual and volatile of nitrogen). Effective resources were calculated to extract the sustainability value- SV appeared on an average of 18023.15 thousand Iraqi dinars. Positive relationship with residual nitrogen and productivity, and Inverse relationship to the amount of volatile nitrogen.
... Show MoreThe charge transfer at C23H17F8N8O2PRu, C44H30BF4N5O4Ru, C56H52CL5N5OOsP2 and C76H88F80N24O11P10Ru4 nitrosyl complexes are investigation and studies theoretically using the quantum consideration. Charge transfer behavior largely rely to the electric properties of nitrosyl complexes system whose depending on the main important parameters for the transmission rate constant such that: orientation transition energy, overlapping coupling coefficient, driving force energy, height barrier and Temperature T (K). Data results have been evaluated using a MATLAB program. Results show that rate of charge transfer increases due to increases the orientation transition energy.
Construction projects are complicated in nature and require many considerations in contractor selection. One of the complicated interactions is that between performance with the project size, and contractor financial status, and size of projects contracted. At the prequalification stage, the financial requirements restrict the contractors to meet minimum limits in financial criteria such as net worth, working capital and annual turnover, etc. In construction projects, however, there are cases when contractors meet these requirements but show low performance in practice. The model used in the study predicts the performance by training of a neural network. The data used in the study are 72 of the most recent roadw
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