The Electro-Fenton oxidation process is one of the essential advanced electrochemical oxidation processes used to treat Phenol and its derivatives in wastewater. The Electro-Fenton oxidation process was carried out at an ambient temperature at different current density (2, 4, 6, 8 mA/cm2) for up to 6 h. Sodium Sulfate at a concentration of 0.05M was used as a supporting electrolyte, and 0.4 mM of Ferrous ion concentration (Fe2+) was used as a catalyst. The electrolyte cell consists of graphite modified by an electrodepositing layer of PbO2 on its surface as anode and carbon fiber modified with Graphene as a cathode. The results indicated that Phenol concentration decreases with an increase in current density, and the minimum Phenol concentration obtained after 6 h of electrolysis at 8 mA/cm2 is equal to 7.82 ppm starting from an initial concentration about 155 ppm. The results obtained from the kinetic study of Phenol oxidation at different current density showed that the reaction followed pseudo first-order kinetics regarding current density. Energetic parameters like specific power consumption and current efficiency were also estimated at different current density. The results showed that an increase in current density caused an increase in the specific power consumption of the process and decreased current efficiency.
The disposal of the waste material is the main goal of this investigation by transformation to high-fineness powder and producing self-consolidation concrete (SCC) with less cost and more eco-friendly by reducing the cement weight, taking into consideration the fresh and strength properties. The reference mix design was prepared by adopting the European guide. Five waste materials (clay brick, ceramic, granite tiles, marble tiles, and thermostone blocks) were converted to high-fine particle size distribution and then used as 5, 10, and 15% weight replacements of cement. The improvement in strength properties is more significant when using clay bricks compared to other activated waste
Optical Mark Recognition (OMR) is an important technology for applications that require speedy, high-accuracy processing of a huge volume of hand-filled forms. The aim of this technology is to reduce manual work, human effort, high accuracy in assessment, and minimize time for evaluation answer sheets. This paper proposed OMR by using Modify Bidirectional Associative Memory (MBAM), MBAM has two phases (learning and analysis phases), it will learn on the answer sheets that contain the correct answers by giving its own code that represents the number of correct answers, then detection marks from answer sheets by using analysis phase. This proposal will be able to detect no selection or select more than one choice, in addition, using M
... Show MoreThe Adaptive Optics technique has been developed to obtain the correction of atmospheric seeing. The purpose of this study is to use the MATLAB program to investigate the performance of an AO system with the most recent AO simulation tools, Objected-Oriented Matlab Adaptive Optics (OOMAO). This was achieved by studying the variables that impact image quality correction, such as observation wavelength bands, atmospheric parameters, telescope parameters, deformable mirror parameters, wavefront sensor parameters, and noise parameters. The results presented a detailed analysis of the factors that influence the image correction process as well as the impact of the AO components on that process
thirty adult NewZealand rabbits used in this study, they were divided in to two groups (control and treaded with Helium — Neon laser). A square skin flap done on the medial aspect of the auricle of both sides, a square piece of cartilage incised, pealed out from each auricle and fixed in the site of the other, then the flaps sutured .The site of the operation in the rabbits of the treated group were irradiated using a Helium —Neon laser with (5mw) power for (10 days) began after the operation directly, (3 rabbits) from each group used for collection of specimens for histopathological examination at the weeks (1,2,3,4, & 6) weeks post the operation .The results revealed Early invasion of the matrix with elastic fibers which continue to t
... Show MoreSemantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po
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.
Surveillance cameras are video cameras used for the purpose of observing an area. They are often connected to a recording device or IP network, and may be watched by a security guard or law enforcement officer. In case of location have less percentage of movement (like home courtyard during night); then we need to check whole recorded video to show where and when that motion occur which are wasting in time. So this paper aims at processing the real time video captured by a Webcam to detect motion in the Scene using MATLAB 2012a, with keeping in mind that camera still recorded which means real time detection. The results show accuracy and efficiency in detecting motion