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Applying Scikit-learn of Machine Learning to Predict Consumed Energy in Al-Khwarizmi College of Engineering, Baghdad, Iraq
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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.

Publication Date
Wed May 16 2018
Journal Name
Route Educational And Social Science Journal I
Graphing skills of Chemistry students at Ibn Al-Haytham Education college of pure sciences in Baghdad
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The aim of this research is to investigate the skills of the chemistry students from the Ibn Al-Haytham Education college of pure sciences in Baghdad in understanding and constructing graphical representations of data. The research sample consisted of (101) male and female students in their fourth year of study during the 2016-2017 academic year. This sample represents 71% of the total number of students in this group.The research methodology used consisted of two parts relating to 19 issues. The first part is an objective multi choice type of test to measure the student’s skill in selecting the right representation of specific subject graph amongst many provided. The second part concentrated on measuring the student’s skill in construc

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Publication Date
Tue May 15 2018
Journal Name
Route Educational And Social Science Journal
Graphing skills of chemistry students at Ibn- Al- Haytham education college of pur sciences in Baghdad
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Publication Date
Fri Apr 30 2021
Journal Name
Al-kindy College Medical Journal
Al-Kindy College Medical Journal: Time to Move Forward
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It is well- known that the distinguished scholastic journal is a crucial cornerstone, which contributes to the scientific integrity of a particular academic institution. The establishment of the Al-Kindy College of Medicine (AKCM), University of Baghdad, in 1998 urged the need to issue Al-Kindy College Medical Journal (KCMJ).

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Publication Date
Mon Jun 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Using Sonic Log to Predict Abnormal Pressure Zones in Selected Oil Wells (Western of Iraq)
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Two oil wells were tested to find the abnormal pressure zones using sonic log technique. We found that well Abu-Jir-3 and Abu-Jir-5 had an abnormal pressure zones from depth 4340 to 4520 feet and 4200 to 4600 feet, respectively. The maximum difference between obtained results and the field measured results did not exceed 2.4%.
In this paper, the formation pressures were expressed in terms of pressure gradient which sometimes reached up to twice the normal pressure gradient.
Drilling and developing such formations were dangerous and expensive.
The plotted figures showed a clear derivation from the normal trend which confirmed the existence of abnormal pressure zones.

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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Possibility of applying international AACSB accreditation standards in the faculties of business and Economics- case study in the college of management and Economics-University of Baghdad
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Attention increased to the topic of academic accreditation by the university as a modern philosophy by which to improve its performance and provide high-quality education. Universities and colleges in general and Iraqi universities and colleges in particular have begun interest in accreditation and desire to get it. So starting from the pursuit of the Administration and Economics College / Baghdad University in obtaining accreditation of Association to Advance Collegiate Schools of Business (AACSB) The research is present which aims to determine the level of application (AACSB) International standards at the College of Administration and Economics / Baghdad University in preparation to get its accreditation in the future. Researc

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning
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Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

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Publication Date
Thu Mar 12 2020
Journal Name
Al-khwarizmi Engineering Journal
Improving Reverse Engineering Processes by using Articulated Arm Coordinate Measuring Machine
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The invention relates to a coordinate measuring machine (CMM) for determining a measuring position of a probe. The AACMM isdepends on the robotkinematics (forward and reverse) in their measurementprinciple, i.e., using the AACMM links and joint angles todetermine the exact workspace or part coordinates. Hence, themeasurements are obtained using an AACMM will be extremely accurate and precise since that ismerely dependent on rigid structural parameters and the only source of measurement error is due to human operators. In this paper, a new AACMM design was proposed. The new AACMM design addresses common issues such as solving the complex kinematics, overcoming the workspace limitation, avoiding singularity, and eliminating the effects of

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
A Comparative Study of Heavy Metals and Trace Elements Concentration in Milk Samples Consumed in Iraq
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The measurements of major and trace elements in different brands of milk powder selected from the Iraqis market via the X-ray fluorescence (XRF) Technique have been studied in the present work. The result of the measurements reveals the high concentrations of sodium, phosphorus, sulfur, chlorine, potassium, calcium and magnesium. Furthermore, low concentrations of aluminum, silicon, iron, bromine, molybdenum, iodine, barium, titanium, manganese, cobalt, chrome, nickel, copper, zinc and lead were detected. Neutron activation analysis (NAA) and Kjeldahl technique were also employed to determine the concentrations of nitrogen. It was found that the nitrogen concentration was in the range of (1.96 - 3.23) % which is within the permissible li

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Scopus (9)
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