Isolated Bacteria from the roots of barley were studied; two stages of processes Isolated and screening were applied in order to nd the best bacteria to remove kerosene from soil. The acve bacteria are isolated for kerosene degradaon process. It has been found that Klebsiella pneumoniae sp. have the highest kerosene degradaon which is 88.5%. The opmum condions of kerosene degradaon by Klebsiella pneumonia sp. are pH5, 48hr incubaon period, 35°C temperature and 10000ppm the best kerosene concentraon. The results 10000ppm showed that the maximum kerosene degradaon can reach 99.58% aer 48 h of incubaon. Higher Kerosene degradaon which was 99.83% was obtained at pH5. Kerosene degradaon was found

In this research the hard chromium electroplating process, which is one of the common methods of overlay coating was used, by using chromium acid as source of chromium and sulphuric acid as catalyst since the ratio between chromic acid and sulphuric acid is (100 : 1) consequently. Plating process was made by applying current of density (40 Amp / dm²) and the range of solution temperature was (50 – 55^oC) with different time periods (1-5 hr). A  low carbon steel type (Ck₁₅) was used as substrate for hard chromium electroplating. Solid carburization was carried out for hard chromium plating specimen at temperature (925^oC) with time duration (2 hr) to be followed with quenching and tempering

This search study the effect of particle size of graphite on the mechanical and thermal properties of epoxy composites, where graphite adopted with particle sizes (45,53,75) ?m, respectively, and the percentages by weight (0,1,3,5,7,9)% for each size of this three particle sizes.Mechanical properties represented by the bending (three-point bending) and through which the conclusion is bending stress and modulus of elasticity, thermal properties were either through thermal conductivity tests.The results showed that the ratio(1%) is the maximum value of bending stress at the three particle size and the (45 ?m) is the maximum.Thermal conductivity result show is the maximum value at ratio (1%) of particle size(53 ?m)

Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

In this study, poly4-(nicotinamido)-4-oxo-2-butenoic acid (PNOE) was prepared by the electro polymerization of 4-(nicotinamido)-4-oxo-2-butenoic acid (NOE) monomer on a 316 stainless steel (St.St) which acts as an anticorrosion coating.  Fourier transforms infrared (FTIR), atomic force microscopy (AFM), scanning electron microscopy (SEM), and cyclic voltammetry were used to diagnose the structure and the properties of the prepared polymer layer. The corrosion behavior of the uncoated and coated 316  St.St were evaluated by using an electro chemical polarization technique in 0.2 M hydrochloric acid  solution as a corrosive medium at a temperature range of 293 to 323 K. Nano materials, such as nano ZnO and graphene were added in di

GFRP was employed in constructions as an alternative to steel, which has many advantages like lightweight, large tensile strength and resist corrosion. Existing researches are insufficient in studying the influence of hybrid reinforced concrete composite columns encased by GFRP I-section (RCCCEG) and I-section steel (RCCCES). In this study twenty one (RC) specimens of a cross-section of 130 mm × 160 mm, with different length (long 1600 mm and short 750 mm) were encased by using I-section (steel and GFRP) and tested under various loading (concentric, eccentric and flexural loads). The test was focused on the influence of many parameters; load-carrying capacity, mode of failure, deformation and drawing an interaction diagram (N-

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d