The research involves using phenol – formaldehyde (Novolak) resin as matrix for making composite material, while glass fiber type (E) was used as reinforcing materials. The specimen of the composite material is reinforced with (60%) ratio of glass fiber.

      The impregnation method is used in test sample preparation, using molding by pressure presses.

      All samples were exposure to (Co⁶⁰) gamma rays of an average energy (2.5)Mev. The total doses were (208, 312 and 728) KGy.

      The mechanical tests (bending, bending strength, shear force, impact strength and surface indentation) were performed on un irradiated and irrad

In this research , we study the inverse Gompertz distribution (IG) and estimate the  survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes

In this research , we study the inverse Gompertz distribution (IG) and estimate the  survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes

     The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,

     Atenolol was used with povidone iodine to prove the efficiency, reliability and repeatability of the long distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis. The method is based on reaction between atenolol and povidone iodine in an aqueous medium. Optimum parameters was studied to increase the sensitivity development of method. Calibration graph was linear in the range of 2-19 mmol/L for cell A and 5-19 mmol/L for cell B. Limit of detection 146.4848 ng/55 µL and 2.6600 µg/200 µL respectively to cell A and cell  B. Correlation coefficient (r) 0.9957 for cell A and 0.9974 for cell. Relative standard deviation (RSD %) was lower than 1%, (n=8) for the determination of

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

  In this study light elements 10B , 10Be for 10B(n,p)10Be reaction as well as proton energy from 0.987 MeV to 2.028 MeV with threshold energy (1.04MeV) are used according to the available data of reaction cross sections. The more recent cross sections data of 10Be(p,n)10B reaction is reproduced in fin steps in the specified energy range , as well as cross section (p,n) values were derived from the published data of (n,p) as a function of energy in the same fine energy steps by using the reciprocity theory of principle inverse reaction . This calculation involves only the first excited state of  10B , 10Be in the reactions 10Be(p,n)10B and  10B(n,p)10Be. 

This study shows that it is possible to fabricate and characterize green bimetallic nanoparticles using eco-friendly reduction and a capping agent, which is then used for removing the orange G dye (OG) from an aqueous solution. Characterization techniques such as scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDAX), X-Ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) were applied on the resultant bimetallic nanoparticles to ensure the size, and surface area of particles nanoparticles. The results found that the removal efficiency of OG depends on the G‑Fe/Cu‑NPs concentration (0.5-2.0 g.L-1), initial pH (2‑9), OG concentration (10-50 mg.L-1), and temperature (30-50 °C). The batch experiments showed

Abstract

The aim of this research is to formulate a proposed strategy for developing graduate studies at King Khalid University to support the achievement of the Kingdom's vision (2030). The research used the descriptive survey approach. The research community consisted of all graduate students at King Khalid University. The research was conducted on a random sample included (623) Male and female students, this research relied on the questionnaire as the main tool for collecting its data. The results revealed that the research sample believes that all the proposals included in this research are very important for the development of postgraduate studies at King Khalid University to support the achievement of the K

        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,