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.
Polycystic ovary syndrome(PCOS) is a heterogeneous disorder of uncertain etiology , it is the most common endocrinopathy in women and most common cause of anovulatery infertility ,characterized by chronic anovulation and hyperandrogenemia .The present study was designed to investigate the effect of silymarin which is known to have antioxidant and insulin sensitivity effects on the levels of glucose, insulin ,testosterone ,leutinizing hormone(LH) and progesterone .Ovulation rate and Homeostasis Model Assessment of insulin Resistance (HOMA) ratio were determined .A 3-months of treatment were conducted in 60 PCOS patients in three well-matched groups .The first one (n=20),received silymarin(750mg/day) .The second group received
... Show MoreEvolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E
... Show MoreResearch Summary
This research is an attempt to explain the Qur’anic verses of the vision in the practical divine vision on the Day of Resurrection, and the legal texts narrated from the Companions regarding the vision of the Prophet, may God’s prayers and peace be upon him, regarding the vision of the Prophet, may God bless him and grant him peace, regarding the vision of the Prophet, may God’s prayers and peace be upon him, regarding the vision of the Prophet, may God bless him and grant him peace He was greeted with regard to vision, and he explained the two sayings of Ibn Abbas and Aisha on the same subject, including an area of conflict between them.
The study aims at finding out:
1. The students' attitude towards the mixed learning at the university.
2. The statistically significant differences in attitude towards the mixed learning at the university according to the specialization variable.
3. The statistically significant differences in attitude towards the mixed learning at the university according to the gender variable.
The researcher has constructed a scale for measuring the students' attitude towards the mixed learning at the university.
After assuring its validity and reliability, the scale has been given to a sample of (100) students. The sample is selected randomly from (4) colleges of the university of Baghdad, (2) for scientific specialization and (2)for h
The study aims to examine the emotional innovation, constructive thinking, foresight, and meditation among university students. Besides, attempts to explore the relationship between emotional innovation and constructive thinking, the relationship between emotional innovation and foresight, and meditation, the relationship between constructive thinking and foresight, and meditation, finally, the relationship among emotional innovation, constructive thinking, foresight, and meditation of university students regarding the variables of gender and major. A total of (400) students were selected as a sample for the study. The results revealed that university students have a high level of emotional innovation that induce them to take positive ro
... Show Morestudy aimed to recognize The relationship between Intrinsic Motivation Academy and Time Management among University students and measure Intrinsic Motivation Academy And Time Management for sample and Balancing Degrees of Basic Research on the two scales According to the Variable genders and Specialization, The sample consisted (350) students by (230) female (120) male , and the sample responded scales of Intrinsic Motivation Academy for (Alwan & Attaat2009) and Time Management (Building tool), The Results of this study show that: There are statistically significant differences according to gender variable in Intrinsic Motivation Academy and Time Management in favor of the male, and there are statistica
... Show More