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.
The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr
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Abstract
The current study was conducted to assess the effect of advancing age on total serum IgE level in asthmatic patients. To this purpose, 90 asthmatic patients and 30 healthy individuals ( control group ) were enrolled. Asthmatic patients were categorized into four groups. Group A consisted of asthmatic patients (9) whose age was more than 20 and up to 30 y. Group B contained asthmatics (13) of age more than 30 and up to 40 y. Group C comprised those (23) of more than 40 and up to 50 y. Group D consisted asthmatic patients (45) of age more than 50 y. Total serum IgE level significantly changed in group D patients when compared with those of
This study has evaluated the humoral immune response in Golden Hamsters experimentally infected with Leishmania donovani along (4) times of follow up (15, 30, 60, 90) days after infection. Indirect haemagglutination test was used to determine the antibody titer through the various stages of the study. Also the progress of the infection was studied depending on some of the visceral changes caused by the parasite, like weight of liver, length & weight of spleen & the count of Leishmania parasites in spleen were measured. Results has shown that there was an increase in antibody titer & the maximum value was recorded at the 4th day of follow up (90 days after infection) as well as that there was an increase in the length of the spleen, weight
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp
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Background: intravenous regional anaesthesia (IVRA) is an effective method of producing anaesthesia of the extremities. Disadvantages are the rapid loss of anaesthesia after the deflation of the tourniquet and the rapid development of postoperative pain. It is important to search for agents with longer durations of action, better nerve fibre selectivity, lesser degrees of motor blockade and lower incidences of systemic toxicity.Objectives: This study was designed to evaluate and compare the clinical effects of intravenous regional anaesthesia, with lidocaine alone, or in a combination with ketamine and atracurium for better analgesia, and to examine the possible clinical advantages of using muscle relaxants (i.e., atracurium) with intrav
... Show MoreQ fever is an infectious disease of animals and humans, caused by globally distributed C. burnetii. In Iraq, there are no previous studies associated with the detection of the organism in cattle. An overall of 130 lactating cows were submitted to direct collection of milk samples. Initially, the samples of milk were tested using the molecular polymerase chain reaction (PCR) assay targeting three genes (16S rRNA, IS1111a transposase, and htpB). However, positive results (18.46%; 24/130) were detected only with the 16s rRNA gene. Concerning risk factors, the highest prevalence of C. burnetii was showed in the district of Badra (42.86%), whereas the lowest - in Al-Numaniyah and Al-Suwaira districts (P=0.025). There was no significant v
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The current study aims to examine the experience of female students with disabilities who studying in university in kingdom of Saudi Arabia. To this end, the researcher used semi-structured interview as an instrument to collect the study data which regards as one of the descriptive approach tools. The sample comprised (12) disabled-female students from multidiscipline within both college of arts and college of education. To analyze the collected data, the author utilized a thematic analysis method following six steps as stated by (Braun and Clark, 2006). The findings revealed that disabled students have a high self-confidence which push them forward to take part in activities that hold on campus. Besides, significant variation were shown
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Non-additive measures and corresponding integrals originally have been introduced by Choquet in 1953 (1) and independently defined by Sugeno in 1974 (2) in order to extend the classical measure by replacing the additivity property to non-additive property. An important feature of non –additive measures and fuzzy integrals is that they can represent the importance of individual information sources and interactions among them. There are many applications of non-additive measures and fuzzy integrals such as image processing, multi-criteria decision making, information fusion, classification, and pattern recognition. This paper presents a mathematical model for discussing an application of non-additive measures and corresp
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Background: The treatment of dental tissues proceeding to adhesive procedures is a crucial step in the bonding protocol and decides the clinical success ofrestorations. This study was conducted in vitro, with the aim of evaluating thenanoleakage on the interface between the adhesive system and the dentine treated by five surface modalities using scanning electron microscopy and energydispersiveX-ray spectrometry. Materials and methods: Twenty five extracted premolars teeth were selected in the study. Standardized class V cavities were prepared on the buccal and lingual surfaces then the teeth divided into five main groups of (5 teeth in each group n=10) according to the type of dentine surface treatment that was used: Group (A): dentine was
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