In this paper, we will present proposed enhance process of image compression by using RLE algorithm. This proposed yield to decrease the size of compressing image, but the original method used primarily for compressing a binary images [1].Which will yield increasing the size of an original image mostly when used for color images. The test of an enhanced algorithm is performed on sample consists of ten BMP 24-bit true color images, building an application by using visual basic 6.0 to show the size after and before compression process and computing the compression ratio for RLE and for the enhanced RLE algorithm.

Secured multimedia data has grown in importance over the last few decades to safeguard multimedia content from unwanted users. Generally speaking, a number of methods have been employed to hide important visual data from eavesdroppers, one of which is chaotic encryption. This review article will examine chaotic encryption methods currently in use, highlighting their benefits and drawbacks in terms of their applicability for picture security.

The escalating generation of industrial waste alongside the growing demand for high-performance, environmentally sustainable drilling fluids presents critical challenges to the oil and gas sector. Conventional drilling fluid additives are predominantly synthesized from virgin materials, contributing to resource depletion and environmental burden. Objectives: This study pioneers a circular economy approach by synthesizing silica nanoparticles (SiO2NPS) and alumina nanoparticles (Al2O3NPs) entirely from locally sourced industrial waste — bentonite clay and aluminum scrap, respectively — and evaluating their performance as functional additives in water-based drilling fluids (WBDFs). Novelty: To the best of our knowledge, this represents th

The implementation of nanotechnology in all industries is one of most significant research fields. Nanoparticles have shown a promising application in subsurface fields. On the other hand, various surfactants have been used in the oil industry to reduce oil/water interfacial tension and also widely used to stabilize the nano-suspensions. The primary objective of this study was to investigate the improvements of surfactants ability in term of interfacial tension (γ) reduction utilizing addition of silicon dioxide nanoparticles at different temperatures and salinity. The pendant drop technique has been used to measure γ and electrical conductivity has been used to measure the critical micelle concentration (CMC). The synergistic effects of

Utilizing the modern technologies in agriculture such as subsurface water retention techniques were developed to improve water storage capacities in the root zone depth. Moreover, this technique was maximizing the reduction in irrigation losses and increasing the water use efficiency. In this paper, a polyethylene membrane was installed within the root zone of okra crop through the spring growing season 2017 inside the greenhouse to improve water use efficiency and water productivity of okra crop. The research work was conducted in the field located in the north of Babylon Governorate in Sadat Al Hindiya Township seventy-eight kilometers from Baghdad city. Three treatments plots were used for the comparison using surface

Water pollution has created a critical threat to the environment.‎‎ A lot of research has been done ‎recently to use surface-enhanced Raman spectroscopy (SERS) to detect multiple pollutants in water. This study aims to use Ag colloid nanoflowers as liquid SERS enhancer. Tri sodium phosphate (Na₃PO₄) was investigated as a pollutant using liquid SERS ‎based on colloidal Ag ‎nanoflowers. The chemical method was used to synthesize nanoflowers from silver ‎ions. Atomic Force Microscope (AFM), Scanning Electron Microscope (SEM), and X-ray diffractometer (XRD) were employed to characterize the silver nanoflowers. This ‎nanoflowers SERS action in detecting Na₃PO₄ was reported and analyzed

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance