Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,

Nonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines  estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property  to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a

120 samples were collected from children (ages between new born and 10 years) who infected with oral thrush. The results revealed that the Minimum Inhibitory Concentration (MIC) and Minimum Fungicidal Concentration (MFC) of extracted oil of lemon grass against C.albicans, C.tropicalis, C.keyfr, C.glabrata and C.guilliermondii were 1.25,1.25,1.25,2.5 and 2.5µl/ml and 2.5, 2.5, 2.5, 5 and 5 µl /ml respectively. while the (MIC) and (MFC) for the extraction oil of thyme against C.albicans, C.tropicalis, C.keyfr, C.glabrata and C.guilliermondii were 0.6, 0.6, 1.25, 1.25, and 1.25µl/ml and 1.25, 1.25, 2.5, 2.5, and 2.5µl/ml respectively . While the value of (MIC) and (MFC) for Nystatin against Candida species were 32 and 64 µg

Abstract

Magnetic abrasive finishing (MAF) is one of the advanced finishing processes, which produces a high level of surface quality and is primarily controlled by a magnetic field. This paper study the effect of the magnetic abrasive finishing system on the material removal rate (MRR) and surface roughness (Ra) in terms of magnetic abrasive finishing system for eight of input parameters, and three levels according to Taguchi array (L27) and using the regression model to analysis the output (results). These parameters are the (Poles geometry angle, Gap between the two magnetic poles, Grain size powder, Doze of the ferromagnetic abrasive powder, DC current, Workpiece velocity, Magnetic poles velocity, and Finishi

Corrosion of steel reinforcement is one of the biggest problems facing all countries in the world like bridges in the beach area and marine constructions which lead to study these problems and apply some economical solutions. According to the high cost of repair for these constructions, were studied the effect of using kind of chemical compounds sodium nitrite(NaNO₂) and sodium silicate(Na₂SiO₃) as corrosion inhibitors admixture for steel bars that immersed partially in electrolyte solution (water + sodium chloride in 3% conc.) (Approximately similar to the concentration of salt in sea water). The two inhibitors above added each one to the electrolyte solution at concentrations (0.5%, 1% and 2%) for both

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

   Thsst researcher problem of delays faced by researchers are all waiting to evaluate their standards by the experts who must take their views to extract the truth Virtual important step first step in building standards whatsoever, then the difference of opinion among experts about the paragraphs Whatever the scope of their functions, leading to confusion in maintaining these paragraphs or delete? Or ignore the views and opinion of the researcher to maintain the same? Or as agreed upon with the supervisor if he was a student? Especially if the concepts of a modern new building.
   Therefore, the researcher sought to try to find a solution to her problem to conduct an experiment to test building steps