There have been many advances in the solar chimney power plant  since 1930 and the first pilot work was built in Spain (Manzanares) that produced 50 KW. The solar chimney power plant is considered of a clean power generation that needs to be investigated  to enhance the performance by studying the effect of changing the area of passage of air to enhance the velocity towards the chimney to maximize design velocity. In this experimental and numerical study, the reduction area of solar collector was investigated. The reduction area that mean changing the height of glass cover from the absorbing plate (h1=3.8cm, h2=2.6cm and h3=1.28cm). The numerical study was performed using ANSYS Fluent software package (version 14.0) to solve go

Water is the basis of the existence of all kinds of life, so obtaining it with good quality represents a challenge to human existence and development especially in the desert and remote cities because these areas contain small populations and water purification requires great materials and huge amounts of fossil fuels resulting pollution of the environment. Cheap and environmentally friendly desalination methods have been done by using solar distillations. Passive solar stills have low yields, so in this research, the problem is overcome by connecting four heat pipes which are installed on the parabolic concentrator reflector with passive solar still to increase the temperature of hot water to more than 90°C, as a resul

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

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

Because of vulnerable threats and attacks against database during transmission from sender to receiver, which is one of the most global security concerns of network users, a lightweight cryptosystem using Rivest Cipher 4 (RC4) algorithm is proposed. This cryptosystem maintains data privacy by performing encryption of data in cipher form and transfers it over the network and again performing decryption to original data. Hens, ciphers represent encapsulating system for database tables

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