Implementation of TSFS (Transposition, Substitution, Folding, and Shifting) algorithm as an encryption algorithm in database security had limitations in character set and the number of keys used. The proposed cryptosystem is based on making some enhancements on the phases of TSFS encryption algorithm by computing the determinant of the keys matrices which affects the implementation of the algorithm phases. These changes showed high security to the database against different types of security attacks by achieving both goals of confusion and diffusion.

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

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

This work aims to develop a secure lightweight cipher algorithm for constrained devices. A secure communication among constrained devices is a critical issue during the data transmission from the client to the server devices. Lightweight cipher algorithms are defined as a secure solution for constrained devices that require low computational functions and small memory. In contrast, most lightweight algorithms suffer from the trade-off between complexity and speed in order to produce robust cipher algorithm. The PRESENT cipher has been successfully experimented on as a lightweight cryptography algorithm, which transcends other ciphers in terms of its computational processing that required low complexity operations. The mathematical model of

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

This research aims to analyze the indicators of spatial variation in the guide of health field in both Al-Adhamiyah and Rusafa districts according to the environmental and administrative units in 2016. The analysis was done by groups of health guide indicators. The objectives of the study were to identify the spatial variation of health services and assess the health situation for families following the environmental and administrative units of the studied area. Such objectives can be done by specifying the extent of the families’ consent to the type of services, measuring the cases of deprivation, and identifying the most deprived areas. The study has finally concluded that there is a clear spatial variation between the indicators and

The spray quality of two spraying agents with different physical properties was investigated under laboratory conditions to find whether the measurement of deposited drops could be affected by spraying those agents. The first spraying agent Moddus, which is a plant growth regulator, has a surface tension of 28 mN m-1 with almost half the value of the second spraying agent Kelpak (58 mN m-1). A mini boom sprayer containing three flat fan nozzles (XR 11003) was used in the test with three traveling speeds (4.74, 5.42 and 8.13 km. h-1). The test was performed to evaluate the quality of spray drops (spray coverage, spray density and stains diameter) after they were deposited on water sensitive papers (WSP). The results showed a higher ability o

The aim of the current study is to in evaluate the role of SOD activity in the previously reported oxidative stress in our laboratory(1), in the patients with different brain tumors. SOD activity was assayed according to riboflavin/NBT method and its specific activity was calculated in patients with benign and malignant brain tumors and control. Moreover the specific activity was compared in these samples according to gender and the occurrence of disease.Non significant elevation (P > 0.05) in SOD specific activity was observed in tissue of malignant tumors in comparison to that of in benign brain tumors. While a highly significant decrease (P < 0.001) of the specific activity was found in sera of malignant patients group in comparison to t