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 any natural area or water body, evapotranspiration is one of the main outcomes in the water balance equation. It is also a crucial component of the hydrologic cycle and considers as the main requirement in the planning and designing of any irrigation project. The climatic parameters for the Ishaqi area are calculated from the available date of Samarra and Al-Khlais meteorological stations according to a method for the period (1982–2017) according to Fetter method. The results of the mean of rainfall, relative humidity temperature, evaporation, sunshine, and wind speed of the Ishaqi area are 171.96 mm, 49.67%, 24.86 C°, 1733.61 mm, 8.34 h/day, and 2.3 m/sec, respectively. Values of Potential Evapotranspiration are determined by
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The current study aims to cover the health topics in the Iraqi journalism , to know the concern 's level of the Iraqi journalism when covering the health subjects and to know the size of its performance under the diversity of visual and audio medias. The researcher has discussed his research by wording it with a set of inquiries that should be answered via the research and study. He could have determined that by the following:
What is the concern's level of Iraqi journalism over the health subjects? What are the forms and press arts that are functionalized by the Iraqi journalism as to get the health message to the republics? What is t
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The researchers in this study, which aimed to find out Degree contribution of Iraqi
women in development from the perspective faculty members of the complex Jadriya
University in Baghdad, and the the impact of demographic variables (gender, college, place of
living, school level,) for its contribution.
The study population consisted of some faculty members Jadiriyah compound in
Baghdad's University for the academic year 20012/2013. This study followed a descriptive
approach the field, and the analytical method, the study sample consisted of (250) teaching all
of College of Science for girls and education for girls, and to achieve objective of the study
was the development of a questionnaire, was sure of its sincer
This study was achieved to investigate the accumulation of some heavy metals included: Cadmium, Lead and Nickel in the tissues (gill, intestine, liver, muscles and skin) of Silurus triostegus Heckel, 1843 (Siluriformes, Siluridae) and its larval stage of the nematode Contracaecum sp. (Rhabditida, Anisakidae). As well as to assess the infection patterns of Contracaecum among S. triostegus specimens which were purchased fresh from the local market in Baghdad. One hundred and nine nematodes specimens in larval stage were recovered from the fish host; the overall prevalence of Contracaecum sp. was 38.6%. The sex of the host was not significantly (P ˃ 0.05) associated with the infection of this nematode. Results showed that the ov
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This study was achieved to investigate the accumulation of some heavy metals included: Cadmium, Lead and Nickel in the tissues (gill, intestine, liver, muscles and skin) of Silurus triostegus Heckel, 1843 (Siluriformes, Siluridae) and its larval stage of the nematode Contracaecum sp. (Rhabditida, Anisakidae). As well as to assess the infection patterns of Contracaecum among S. triostegus specimens which were purchased fresh from the local market in Baghdad. One hundred and nine nematodes specimens in larval stage were recovered from the fish host; the overall prevalence of Contracaecum sp. was 38.6%. The sex of the host was not significantly (P ˃ 0.05) associated with the infection of this nematode.
Results showed that the overall me
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MR Younus, Al-A'DAB, 2011
All over the world and in different societies and cultures , people are always looking for different ways of favourable , gentle smooth and soft communication .The 'powerful linguistic devices ' that are embedded in the daily English language is called "euphemism". It plays an important and vital role in daily communication. It represents a significant part of English . It is used to express any aspect of everyday realities such as the business world , mass media , etc. The comprehension of such realities can not be verified unless a reasonable command of euphemism is achieved.
Euphemism is defined according to various perspectives and views. It is " that figure of speech which consists in the substitution of a word or expression of c
Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa
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