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 informati

The study aimed to reveal the possibility of predicting academic procrastination through both Cognitive distortions and time management among students of Al-Aqsa Community College, as well as to reveal the level of both cognitive distortions, time management, and academic procrastination. Additionally, it aimed to identify the size of the correlation between cognitive distortions, time management, and academic procrastination. The study sample consisted of (250) students from Al-Aqsa community college students. The results of the study concluded that the mean for each level of cognitive distortions and academic procrastination is average. The mean level of time management is high. There is a statistically significant positive relationshi

A Geographic Information System (GIS) is a computerized database management system for accumulating, storage, retrieval, analysis, and display spatial data. In general, GIS contains two broad categories of information, geo-referenced spatial data and attribute data. Geo-referenced spatial data define objects that have an orientation and relationship in two or three-dimensional space, while attribute data is qualitative data that can be counted for recording and analysis. The main aim of this research is to reveal the role of GIS technology in the enhancement of bridge maintenance management system components such as the output results, and make it more interpretable through dynamic colour coding and more sophisticated visualization

Sheet piles are necessary with hydraulic structures as seepage cut-off to reduce the seepage. In this research, the computational work methodology was followed by building a numerical model using Geo-Studio program to check the efficiency of using concrete sheet piles as a cut-off or reducer for seepage with time if the sheet piles facing the drawdown technique. Al-Kifil regulator was chosen as a case study, an accurate model was built with a help of observed reading of the measuring devices, which was satisfactory and helped in checking the sheet piles efficiency. Through the study, three scenarios were adopted (with and without) drawdown technique, it was found that at the short time there's no effect of the drawdown technique on

    Heat exchanger is an important device in the industry for cooling or heating process. To increase the efficiency of heat exchanger, nanofluids are used to enhance the convective heat . transfer relative to the base fluid. - Al2O3/water nanofluid is used as cold stream in the shell and double concentric tube heat exchanger counter current to the hot stream basis oil. These nanoparticles were of particle size of 40 nm and it was mixed with a base fluid (water) at volume
concentrations of 0.002% and 0.004%. The results showed that each of Nusselt number and overall heat transfer coefficient increased as nanofluid concentrations increased. The pressure drop of nanofluid increased slightly than the base fluid because

The wind atlas analysis and application program, WAsP, is used to assess wind
energy potential، wind climate from geostrophic winds of a given area. In this paper,
metrological data from Ali Algharby station was used to predict the wind resource
and wind turbine energy production at Ali Algharby site.
Data from metrological station was used to draw up observed wind climates at the
anemometer site. Site contour map was digitized using WAsP Map Editortool.
Observed wind climate, digitized contour map, terrain roughness length, obstacle
groups and their porosity were used as input to the WAsP model. Vestas V182, 1.65
MW turbine was used. Weibull probability distribution graph of wind speed, power
density were dra

Cloud computing provides huge amount of area for storage of the data, but with an increase of number of users and size of their data, cloud storage environment faces earnest problem such as saving storage space, managing this large data, security and privacy of data. To save space in cloud storage one of the important methods is data deduplication, it is one of the compression technique that allows only one copy of the data to be saved and eliminate the extra copies. To offer security and privacy of the sensitive data while supporting the deduplication, In this work attacks that exploit the hybrid cloud deduplication have been identified, allowing an attacker to gain access to the files of other users based on very small hash signatures of

In this study asparaginase was extracted from fruit part of Capiscum annum then Asparaginase activity was detected and optimised. Optimum conditions for the activity of crude asparaginase were studied. Results showed maximum activity of asparaginase was achieved 140 u/ml when the enzyme was incubated with 200 mM of asparagines at 35 °C for 30 minutes in the presence of 0.05 M of potassium phosphate buffer solution at pH 8.

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

A -set in the projective line is a set of  projectively distinct points. From the fundamental theorem over the projective line, all -sets are projectively equivalent. In this research, the inequivalent -sets in have been computed and each -set classified to its -sets where  Also, the  has been splitting into two distinct -sets, equivalent and inequivalent.