Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

The aim of this work is to design an algorithm which combines between steganography andcryptography that can hide a text in an image in a way that prevents, as much as possible, anysuspicion of the hidden textThe proposed system depends upon preparing the image data for the next step (DCT Quantization)through steganographic process and using two levels of security: the RSA algorithm and the digitalsignature, then storing the image in a JPEG format. In this case, the secret message will be looked asplaintext with digital signature while the cover is a coloured image. Then, the results of the algorithmare submitted to many criteria in order to be evaluated that prove the sufficiency of the algorithm andits activity. Thus, the proposed algorit

Visible light communication (VLC) is an upcoming wireless technology for next-generation communication for high-speed data transmission. It has the potential for capacity enhancement due to its characteristic large bandwidth. Concerning signal processing and suitable transceiver design for the VLC application, an amplification-based optical transceiver is proposed in this article. The transmitter consists of a driver and laser diode as the light source, while the receiver contains a photodiode and signal amplifying circuit. The design model is proposed for its simplicity in replacing the trans-impedance and transconductance circuits of the conventional modules by a simple amplification circuit and interface converter. Th

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

Background: One common undesirable side effect of orthodontic treatment with fixed appliances is the development of incipient caries lesions around brackets, particularly in patients with poor oral hygiene. Different methods have been used to prevent demineralization; the recent effort to improve the resistance against the demineralization is by the application of lasers. Materials and method: Thirty human premolars extracted for orthodontic purposes were used to test the effect of two energy level of ER-YAG laser on enamel resistance to demineralization. The brackets were bonded on the teeth and all the labial surface excluding 2 mm area gingival to the brackets were painted with acid resistance varnish. Three groups were generated. The fi

Dental caries (tooth decay) is one of the most prevalent infectious disease and although of multifactorial origin, Streptococcus mutans is considered the principal pathogen in its development (i.e. bacterial processes damage hard tooth structure (enamel, dentine and cementum), producing dental cavities (holes in the teeth). The bactericidal properties of the Nd:YAG laser has been researched analyzing its use in caries prevention and bacterial reduction. One hundred twenty five samples were collected from carious teeth and isolated bacteria were diagnosed using microscopic examination, culture, biochemical tests, and Api 20 strep system. The results of this study showed that a noticeable decrease in the viability of Streptococcus mutans w

Background: The Streptococcus genus are the predominant bacteria in the mouth and the Streptococcus sanguinis is one of them which performing a primary function for expansion of dental biofilm. Gingival and periodontal disorders are caused by dental biofilm, today, there is a necessity to discover naturally presenting antibacterial compounds from herbs with less side effects as a substitutive to the commonly handled chlorohexidine. Thus, the purpose of this study was to assess the antibacterial activity of thymus vulgaris oil on Streptococcus sanguinis bacteria In vitro. Materials and Methods: Human supragingival plaque samples were taken from 10 subjects, then morphological and microscopical examination, bioch

The development of information systems in recent years has contributed to various methods of gathering information to evaluate IS performance. The most common approach used to collect information is called the survey system. This method, however, suffers one major drawback. The decision makers consume considerable time to transform data from survey sheets to analytical programs. As such, this paper proposes a method called ‘survey algorithm based on R programming language’ or SABR, for data transformation from the survey sheets inside R environments by treating the arrangement of data as a relational format. R and Relational data format provide excellent opportunity to manage and analyse the accumulated data. Moreover, a survey syste