Autoimmunity is a philosophical term that enhances the fields of life-sciences, and links out to the unnatural behaviour of an individual. It is caused by the defenses of an organism that deceive its own tissues. Obviously, the immune system should protect the body against invading cells with types of white blood cells called antibodies. Nevertheless, when an autoimmune disease attacks, it causes perilous actions like suicide. Psychologically, Jacques Derrida (1930-2004) calls autoimmunity a double suicide, because it harms the self and the other. In this case, the organ disarms betraying cells, as the immune system cannot provide protection. From a literary perspective, Derrida has called autoimmunity as deconstruction for over forty years

Nowadays, still images are used everywhere in the digital world. The shortages of storage capacity and transmission bandwidth make efficient compression solutions essential. A revolutionary mathematics tool, wavelet transform, has already shown its power in image processing. The major topic of this paper, is improve the compresses of still images by Multiwavelet based on estimation the high Multiwavelet coefficients in high frequencies sub band  by interpolation instead of sending all Multiwavelet coefficients. When comparing the proposed approach with other compression methods Good result obtained

Although the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose .

                In this paper  a new image restoration scheme is proposed, the scheme contains two separate steps : Fourier-domain inverse filtering  and wavelet-domain image denoising. The first stage is Wiener filtering of the input image , the filtered image is inputted to adaptive threshold wavelet

The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing.  Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds.  This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin

The goal of fusing multi-focus images is to obtain one image that has all the significant features from each input. The fusion process is needed because of the limitations of the optical lens depth of field that is used to capture images, so images of various focused regions are produced. In this paper, a multi-focus image fusion algorithm is proposed. It is based on utilizing the biorthogonal wavelet transform to extract details and edges from the input images by making the approximation subband equal zero and applying an inverse transform to get images that have only edges, lines, and details. The average gradient metric, which is used to represent sharpness and clarity, is calculated as an activity measurement for each NxN block

Background: H1N1 influenza pandemic or swine flu was an influenza pandemic first described in Iraq in October 2009 .The virus appeared to be anew strain of H1N1 causes wide range of morbidity and mortality among different genders and age groups as part of worldwide pandemics.Seasonal flu is a contagious respiratory illness caused by influenza viruses that infect the nose, throat, and lungs. It can cause mild to severe illness, and at times can lead to death. The best way to prevent the flu is by getting a flu vaccine each year.

Objectives: Is to determine the morbidity and mortality in different age groups in patients with H1N1 influenza versus those patients with seasonal influenza who were admitted at the same time to AL-kindy

The survey showed sample opinions of officials in the general company for vegetable oils industry, and the statement of the order of the effect of these dimensions depending on the degree of importance, the questionnaire was used as a key tool in collecting data and information of the sample consisted of 30 officials, arithmetic mean, standard deviation, percentages, Spearman correlation coefficient and the global statistical analysis as a statistical methods that based on statistical program (SPSS), The researcher came to several conclusions, most important that there is high agreement by the respondents of the importance of the dimensions of building a mental picture of the company and to attract the consumer's attention, Also research