This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta

Symptoms of posttraumatic stress disorder are associated with various variables such as the exposure to traumatic events, sex and age. Such events could lead to negative cognitions towards self and the world. These cognitions, in turn, may lead to traumatic related disorders.

The present study aims to identify the percentage of traumatised individuals according to sex and age category variables. It also aims to assess the average of spreading symptoms of posttraumatic stress disorder of traumatised individuals according to sex and age category variables. Likewise, it aims to test variables significance in cognitions towards the world and the self according to the level of the spread of posttraumatic stre

A simple, sensitive, accurate and economic spectrophotometric method has been developed for the determination of sulfacetamide (SFA) in pure form, synthetic sample and urine. The method is based on diazotization of primary amine group of sulfacetamide with sodium nitrite and hydrochloric acid followed by coupling with chromotropic acid in alkaline medium to obtain a stable orange colored chromogen which exhibit a maximum absorption (λmax) at   511.5 nm. Different variables affecting the completion of reaction have been carefully optimized following the classical univariate sequence and  modified simplex method (MSM). Under optimized conditions, Beer’s law obeyed in the concentration range of (0.5-  &nbs

In recent years, there has been a rapid development in research on high performance ceramics for mechanical, electrical and medical industries. This development will be shown for alumina as a representative for oxide ceramics powders.
Dry–pressing forming technique was used to prepare different ceramic compacts for alumina grafted by polymethacrylate polymers. All Alumina compact were fired firstly at 1200 ◌ْ C, then
at 1600 ◌ْ C.
Mechanical strength was examined in different means, some
depends on compression and other depends on impact. Hardness was
also measured .The results obtained were compared with that of
Alumina compact prepared under the same condition from Alumina
especially made for pressing .

In this study, silver nanoparticles (AgNPs) are synthesized using different chemical routes to obtain different sizes and shapes of nanoparticles by colloid chemistry with using stabilizing and reducing agent, which make them interesting for variety of physical applications. The morphology and structure of the synthesized AgNPs were characterized by UV-VIS spectra, Scanning Electron Microscopy (SEM) and Zeta potential to demonstrate that different sizes and shapes can by synthesized by different reductants in the presence of various stabilizing agents.

Normal concrete is weak against tensile strength, has low ductility, and also insignificant resistance to cracking. The addition of diverse types of fibers at specific proportions can enhance the mechanical properties as well as the durability of concrete. Discrete fiber commonly used, has many disadvantages such as balling the fiber, randomly distribution, and limitation of the Vf ratio used. Based on this vision, a new technic was discovered enhancing concrete by textile-fiber to avoid all the problems mentioned above. The main idea of this paper is the investigation of the mechanical properties of SCC, and SCM that cast with 3D AR-glass fabric having two different thicknesses (6, 10 mm), and different layers (1,2 laye

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with