The hero traditionally has such admirable traits as courage, fortitude,
chivalry and patriotism. In the literary works, the hero is the leading
character and the pivot around which all the characters and the events
revolve. The characteristics of the hero usually reflect the cultural values
of his time. Because, in each age, Man's attitudes towards himself and the
world change, different images of the hero emerge.
In Greek Mythology, the hero is frequently favoured by the gods;
therefore, he is himself semi-divine. The Greek hero is of princely birth
and is endowed with good physique, exceptional strength, skill in
athletics and battle, energy and eloquence, like Odysseus who is the hero
of the Odyssey, long epic poem traditionally ascribed to the Greek poet
Homer. Odysseus is the king of Ithaca and he is a valorous, mighty leader
who took part in the siege of Troy. On his way back to Ithaca, after the
end of the war, he passed through many dangerous adventures in which
he encountered ruthless monsters such as Cyclopes, a giant with one eye,
and Scylla, an equally dreadful monster with six head. 1
Image recognition is one of the most important applications of information processing, in this paper; a comparison between 3-level techniques based image recognition has been achieved, using discrete wavelet (DWT) and stationary wavelet transforms (SWT), stationary-stationary-stationary (sss), stationary-stationary-wavelet (ssw), stationary-wavelet-stationary (sws), stationary-wavelet-wavelet (sww), wavelet-stationary- stationary (wss), wavelet-stationary-wavelet (wsw), wavelet-wavelet-stationary (wws) and wavelet-wavelet-wavelet (www). A comparison between these techniques has been implemented. according to the peak signal to noise ratio (PSNR), root mean square error (RMSE), compression ratio (CR) and the coding noise e (n) of each third
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The basic solution to overcome difficult issues related to huge size of digital images is to recruited image compression techniques to reduce images size for efficient storage and fast transmission. In this paper, a new scheme of pixel base technique is proposed for grayscale image compression that implicitly utilize hybrid techniques of spatial modelling base technique of minimum residual along with transformed technique of Discrete Wavelet Transform (DWT) that also impels mixed between lossless and lossy techniques to ensure highly performance in terms of compression ratio and quality. The proposed technique has been applied on a set of standard test images and the results obtained are significantly encourage compared with Joint P
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In this paper, membrane-based computing image segmentation, both region-based and edge-based, is proposed for medical images that involve two types of neighborhood relations between pixels. These neighborhood relations—namely, 4-adjacency and 8-adjacency of a membrane computing approach—construct a family of tissue-like P systems for segmenting actual 2D medical images in a constant number of steps; the two types of adjacency were compared using different hardware platforms. The process involves the generation of membrane-based segmentation rules for 2D medical images. The rules are written in the P-Lingua format and appended to the input image for visualization. The findings show that the neighborhood relations between pixels o
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In this paper, visible image watermarking algorithm based on biorthogonal wavelet
transform is proposed. The watermark (logo) of type binary image can be embedded in the
host gray image by using coefficients bands of the transformed host image by biorthogonal
transform domain. The logo image can be embedded in the top-left corner or spread over the
whole host image. A scaling value (α) in the frequency domain is introduced to control the
perception of the watermarked image. Experimental results show that this watermark
algorithm gives visible logo with and no losses in the recovery process of the original image,
the calculated PSNR values support that. Good robustness against attempt to remove the
watermark was s
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With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases
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Background: Toxin-producing Shiga Escherichia coli has been identified as a new foodborne pathogen that poses a significant health risk to humans. Shiga toxin-producing Escherichia coli can be found in raw cow milk and its derivatives. A small number of Escherichia coli strains that produce shiga toxin are pathogenic. Aim of study: The study aimed to see if there were any virulence genes in 50 milk samples that were typical of Entero-haemorrhagic E. coli and evaluate the Myrtus communis effects on these bacteria. Materials and Method: Milk samples were used to isolate E. coli bacteria (n= 27), biochemically analyzed, and genetically screened for virulence genes using a multiplex (PCR). The hydro-alcoholic extraction of Myrtus communis leave
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Background: Acute lung injury (ALI) is among the most serious conditions characterized by an exacerbation of inflammatory response that can result from a persistent lung infection. Carvone is chiral monoterpenoid ketone present in the essential oils of dill, caraway, and spearmint. It shows antioxidant, anti-inflammatory, and antimicrobial effects among others. In this study, the lung anti-inflammatory and protective effects and potential mechanism of action of carvone were investigated in ALI induced by Lipopolysaccharide (LPS).
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