In this paper, a literature survey was introduced to study of enhancing the hazy images , because most of the images captured in outdoor images have low contrast, color distortion, and limited visual because the weather conditions such as haze and that leads to decrease the quality of images capture. This study is of great importance in many applications such as surveillance, detection, remote sensing, aerial image, recognition, radar, etc. The published researches on haze removal are divided into several divisions, some of which depend on enhancement the image, some of which depend on the physical model of deformation, and some of them depend on the number of images used and are divided into single-image and multiple images dehazing model

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 power generation of solar photovoltaic (PV) technology is being implemented in every nation worldwide due to its environmentally clean characteristics. Therefore, PV technology is significantly growing in the present applications and usage of PV power systems. Despite the strength of the PV arrays in power systems, the arrays remain susceptible to certain faults. An effective supply requires economic returns, the security of the equipment and humans, precise fault identification, diagnosis, and interruption tools. Meanwhile, the faults in unidentified arc lead to serious fire hazards to commercial, residential, and utility-scale PV systems. To ensure secure and dependable distribution of electricity, the detection of such ha

Ketoprofen has recently been proven to offer therapeutic potential in preventing cancers such as colorectal and lung tumors, as well as in treating neurological illnesses. The goal of this review is to show the methods that have been used for determining ketoprofen in pharmaceutical formulations. Precision product quality control is crucial to confirm the composition of the drugs in pharmaceutical use. Several analytical techniques, including chromatographic and spectroscopic methods, have been used for determining ketoprofen in different sample forms such as a tablet, capsule, ampoule, gel, and human plasma. The limit of detection of ketoprofen was 0.1 ng/ ml using liquid chromatography with tandem mass spectrometry, while it was 0

Most of the water pollutants with dyes are leftovers from industries, including textiles, wool and others. There are many ways to remove dyes such as sorption, oxidation, coagulation, filtration, and biodegradation, Chlorination, ozonation, chemical precipitation, adsorption, electrochemical processes, membrane approaches, and biological treatment are among the most widely used technologies for removing colors from wastewater. Dyes are divided into two types: natural dyes and synthetic dyes.

A​‍​‌‍​‍‌ gantry robot is one of the most common types of industrial robots with linear movement. This type of robot is also known as a Cartesian or linear robot. It is an automated industrial system that moves along linear paths, enabling it to create a 3D envelope of the space in which it operates. A robot of this type has a standardised configuration process because it can have several sets of axes, such as X, Y and Z. The gantry robot picks up products from several places, so it can search through various locations. Afterwards, it carefully deposits the products on a conveyor belt for the next stage of the procedure or final ​‍​‌‍​‍‌shipment. This integration enables continuous and automated material flow

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.