AbstractThe research aims to identify the impact of the different methods in calculating the Items sensitivity coefficient on the standard characteristics of the Criterion-Referenced test in the measurement and evaluation material. The research sample consisted of (35) male and female students, who were chosen by the intentional method. The researcher prepared learning-teaching program in constructing the content of the measurement and evaluation material for non-specialized departments, prepared an achievement test in its equivalent forms, identified the results of agreement between the methods used in analyzing the items of the criterion-referenced test, and compared the standard characteristics of the achievement test, both according to the six methods used, which depend on one group. The researcher adopted a number of statistical methods, and after analyzing the data, the results showed that the most convergent methods for selecting items are (Cox and Vargas -reference compatibility –Brennan discrimination and Roudabush). There are statistically significant differences between the methods used in calculating the index coefficient of the items sensitivity on the characteristic of validity, and in order to identify the significance of the differences between the reliability coefficients according to the different methods of items analysis, the researcher used the ZTest equation to infer about the method’s preference and its effect on the reliability coefficient, by comparing the calculated Z-values with the tabular value at the significance level (0.05) and amounting to (1.96) to calculate the significance of the differences in the correlation coefficients. It was found that through all the calculated values for Z, they are not significant, which means that there are no statistically significant differences between each of (Cox and Vargas coefficient, reference compatibility coefficient, Phi coefficient, binary correlation coefficient, discrimination coefficient B (Brennan), and the coefficient of Roudabush to calculate index coefficient of the items sensitivity in its impact on the reliability of the achievement test, and the research showed a number of recommendations and suggestions..
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Objective: To compare distal tibia nonunion plating and grafting with and without platelet-rich plasma (PRP) regarding union rate, union time and complications Conclusion: Combining PRP with autologous bone graft results in a higher union rate, less healing duration, less post-operative pain, and more callus formation. (Rawal Med J 202;45:629- 632). Methodology: In this prospective comparative study, 32 patients with nonunion tibia from July 2017 January 2019 were divided into two groups: group A (16 cases) were treated by plating and grafting with PRP and group B (16 cases) were treated by plating and grafting only. Keywords: Tibial nonunion, bone graft, plateletrich plasma. Results: There was higher union rate in group A related to group
... Show MoreIndustrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m3 (B-400) to 300 kg/m3 (B-300) then to 200 kg/m3 (B-200). While (B-380) was produced using 380 kg/m3 cement and 20 kg/m3 nano-sil
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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