Electronic Health Record (EHR) systems are used as an efficient and effective method of exchanging patients’ health information with doctors and other key stakeholders in the health sector to obtain improved patient treatment decisions and diagnoses. As a result, questions regarding the security of sensitive user data are highlighted. To encourage people to move their sensitive health records to cloud networks, a secure authentication and access control mechanism that protects users’ data should be established. Furthermore, authentication and access control schemes are essential in the protection of health data, as numerous responsibilities exist to ensure security and privacy in a network. So, the main goal of our s

A simple straightforward mathematical method has been developed to cluster grid nodes on a boundary segment of an arbitrary geometry that can be fitted by a relevant polynomial. The method of solution is accomplished in two steps. At the first step, the length of the boundary segment is evaluated by using the mean value theorem, then grids are clustered as desired, using relevant linear clustering functions. At the second step, as the coordinates cell nodes have been computed and the incremental distance between each two nodes has been evaluated, the original coordinate of each node is then computed utilizing the same fitted polynomial with the mean value theorem but reversibly.

The method is utilized to predict

Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni

The synthesis, characterization and mesomorphic properties of two new series of triazine-core based liquid crystals have been investigated. The amino triazine derivatives were characterized by elemental analysis, Fourier transforms infrared (FTIR), 1HNMR and mass spectroscopy. The liquid crystalline properties of these compounds were examined by differential scanning calorimetry (DSC) and polarizing optical microscopy (POM). DSC and POM confirmed nematic (N) and columnar mesophase textures of the materials. The formation of mesomorphic properties was found to be dependent on the number of methylene unit in alkoxy side chains.

Novel azo ligand based on tryptamine, and its metal complexes with antioxidant properties were synthesized through chemical methods and characterized through various techniques, including IR, Mass, UV-Vis spectroscopy, elemental analysis, conductivity, magnetic sensitivity, and thermogravimetric analysis. According to the IR spectra of the complexes, the azo-ligand, [5-(2-(3H- 1-indol-3-yl) ethyl) diazenyl) quinolin-8-ol] coordinates with metal ions through the nitrogen atom in the quinoline ring and the oxygen atom of the hydroxyl group. Thermal analysis techniques were employed to investigate the thermal behavior of the compounds. The results revealed that the metal complexes possess higher thermal stability compared to the free ligand. T

This research aims to investigate the thermal performance of different thermal composite insulators, wrapped around a closed-loop copper pipe (CLP). To achieve this aim a system was designed and manufactured. It is consisted of closed water tank insulated by Rock Wool, and supplied with two electric heaters, two thermostat, a flow meter, a water pump, digital temperature scales, and four series of (CLP).
Six insulators were prepared namely; composites of Impregnated Fiberglass with Elastoclad and foaming Rubber (FER), Impregnated Fiberglass with Elastoclad resin and Polymeric Membrane (FEM), Impregnated Fiberglass with Polyurethane thermoset resin and Foaming Rubber (FUR), Impregnated Fiberglass with Polyurethane thermoset resin and P

Aim: This study aimed to assessing orthodontic knowledge and attitude among general dentists and non-orthodontic specialists. Background: Early detection of orthodontic disorders is essentialin motivating patients to intervene prior to long term complications when the disorders are not recongised. Methods: A questionnaire was distributed amongst dentistsother than orthodontists. This questionnaire consisted of three sections. The first one aimed to collect demographic, educational level and practice type information. Further two sections consisted of closed-end questions designed to evaluateknowledge and attitude of orthodontics. Results: A total of 313 responses to the survey were submitted. No significant correlation was observed, e