Stimulative effect of 10 mW He-Ne laser on the phagocytic activity of human polymorphonuclear leukocytes( PMNs) has been studied in vitro. Normal polymorphonuclear leucocytes were isolated from the human peripheral blood. A mixture of 0.25 ml of Hanks solution, 0.25 ml of serum, 0.25 ml of Candida albicans suspension and 0.25 ml of PMNs suspension was prepared. The samples of mixture of PMNs and Candida were subdivided in 1 ml ependrof tubes and irradiated to He-Ne laser for 1, 3, 5, 10 and 20 min. The diameter of the irradiated area was 0.8 cm. For calculation of Phagocytic index before and after irradiation, the samples were incubated (37°C) at 5, 15, 30, 60 min. The slides of samples were prepared and stained using Giemsa stain. The results showed that the bio-stimulative effect of 10 mW He-Ne laser on the phagocytic activity of( PMNs) is more observable at 3 min exposure time with 5 mW/cm2 power density. Many action mechanisms were reviewed and discussed in the term of possible photo- acceptor when cells are irradiated to laser.
Image quality plays a vital role in improving and assessing image compression performance. Image compression represents big image data to a new image with a smaller size suitable for storage and transmission. This paper aims to evaluate the implementation of the hybrid techniques-based tensor product mixed transform. Compression and quality metrics such as compression-ratio (CR), rate-distortion (RD), peak signal-to-noise ratio (PSNR), and Structural Content (SC) are utilized for evaluating the hybrid techniques. Then, a comparison between techniques is achieved according to these metrics to estimate the best technique. The main contribution is to improve the hybrid techniques. The proposed hybrid techniques are consisting of discrete wavel
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Due to the continuing demand for larger bandwidth, the optical transport becoming general in the access network. Using optical fiber technologies, the communications infrastructure becomes powerful, providing very high speeds to transfer a high capacity of data. Existing telecommunications infrastructures is currently widely used Passive Optical Network that apply Wavelength Division Multiplexing (WDM) and is awaited to play an important role in the future Internet supporting a large diversity of services and next generation networks. This paper presents a design of WDM-PON network, the simulation and analysis of transmission parameters in the Optisystem 7.0 environment for bidirectional traffic. The simulation shows the behavior of optical
... Show MoreSoftware testing is a vital part of the software development life cycle. In many cases, the system under test has more than one input making the testing efforts for every exhaustive combination impossible (i.e. the time of execution of the test case can be outrageously long). Combinatorial testing offers an alternative to exhaustive testing via considering the interaction of input values for every t-way combination between parameters. Combinatorial testing can be divided into three types which are uniform strength interaction, variable strength interaction and input-output based relation (IOR). IOR combinatorial testing only tests for the important combinations selected by the tester. Most of the researches in combinatorial testing appli
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Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file. In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,
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The production of biodiesel generates soap impurities that hinder biodiesel performance and complicate its purification. This study presents a novel approach for soap removal from biodiesel using NiO–doped ZnO nanoparticle (NP) adsorbent. The NPs are synthesized using a gliding arc discharge (GAD) method as a non-thermal plasma source (NTP). NiO doping reduced the bandgap energy by 74%, reduced the crystallite size, and increased the surface area by 78%, entailing lattice strain and structural modifications. Soap removal efficiency was 99.7% for NiO–doped ZnO within 16 min, compared with 95.5% for ZnO. Soap uptake as high as 2320 mg/g NiO–doped ZnO was reported, which could be equally fitted by Langmuir and Freundlich isotherms su
... Show MoreProduction of fatty acid esters (biodiesel) from oleic acid and 2-ethylhexanol using sulfated zirconia as solid catalyst for the production of biodiesel was investigated in this work.
The parameters studied were temperature of reaction (100 to 130°C), molar ratio of alcohol to free fatty acid (1:1 to 3:1), concentration of catalyst (0.5 to 3%wt), mixing speed (500 to 900 rpm) and types of sulfated zirconia (i.e modified, commercial, prepared catalyst according to literature and reused catalyst). The results show the best conversion to biodiesel was 97.74% at conditions of 130°C, 3:1, 2wt% and 650 rpm using modified catalyst respectively. Also, modified c
... Show MoreAn oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification
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Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc
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In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.
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