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This article proposes to examine the situation of woman sports status in India. We need sportswomen of generation to achieve the reigns and encourage the coming generations. This new role made women, visible in the social space which enabled women to put down into the field of sports as well. By appearing at the institutional and other realms of sports in India the paper explains how the gendered practice of sports marginalizes women in multiple ways. Our society has to make towards a massive cultural reform where we hold a sound work ethic. Until that is done Indian women will be just giving way after a mirage, not medals, in international sporting events. Although the most welcome gains in opportunities and an ever growing publicity of women's sports, the effects of a long traditionally gender bias in sports still persist. It in the public space or in the private space women have been sounding off about the lack of coverage for sport by media since a very long time. This has made a real bad effect on the development of mutant. (1*) Media support and fan loyalty are also much more common in male sports than women. The article tried to explore this ambivalent attitude of Indian sporting women. Olympics: Indian team also female included and we are hop full to achieve a medal for India.

Africa : progress and problems -- Governance and leadership in Africa -- Ecological issues -- Aids and health issues -- Poverty and economic issues -- Education in Africa -- Human rights in Africa -- Wars in Africa -- Religion in Africa -- Helping Africa help itself : a global effort -- Ethnic groups in Africa -- Population and overcrowding -- The making of Africa -- Islam in Africa

The Wiener filter is widely used in image de-noising. It is used to reduce Gaussian noise. Although the Wiener filter removes noise from the image, it causes a loss of edge detail information, resulting in blurring of the image. The edge details are considered high-frequency components. The Wiener filter is unable to reconstruct these components. In this paper, the proposed filter based on the Wiener filter and the high-boost filter for medical images is presented. The proposed filter is applied to the degraded image. First, using Fourier Transformation, the degraded image and the high boost filter are converted in the frequency domain. Secondly, the wiener filter is applied to the image along with the high boost filter. Thirdly, the deconvolution process is achieved on the image with the high boost filter. Finally, to reconstruct the sharper image in the spatial domain, the inverse of the Fourier transformation is applied. The proposed filter works to suppress the additive noise at the same time. It can keep the image's edge details. Some focus operators are used, which are image contrast, gradient energy, histogram entropy, and spatial frequency, in order to test the proposed algorithm. Experimental results showed that the proposed filter gives good results compared with the traditional filters for medical images, especially dark images.

Maplesoft is a technical computation forms which is a heart of problem solving in mathematics especially in graph theory. Maplesoft has established itself as the computer algebra system for researchers. Maplesoft has more mathematical algorithms which is covering a wide range of applications. A new family ( ) of 6-bridge graph still not completely solved for chromatic number, chromatic polynomial and chromaticity. In this paper we apply maplesoft on a kind of 6-bridge graph ( ) to obtain chromatic number, chromatic polynomial and chromaticity. The computations are shown that graph contents 3 different colours for all vertices, 112410 different ways to colour a graph such that any two adjacent vertices have different colour by using 3 different colour, graph has isomorphic graph which has same chromatic polynomial of graph . The odd number of vertices located in one of these bridges made chromatic number 3. The chromatic number was the important factor that made the number of way 112410. A bijection function created isomorphic graph to graph and the chromatic polynomial of was ( ) ( ).

Combining multi-model images of the same scene that have different focus distances can produce clearer and sharper images with a larger depth of field. Most available image fusion algorithms are superior in results. However, they did not take into account the focus of the image. In this paper a fusion method is proposed to increase the focus of the fused image and to achieve highest quality image using the suggested focusing filter and Dual Tree-Complex Wavelet Transform. The focusing filter consist of a combination of two filters, which are Wiener filter and a sharpening filter. This filter is used before the fusion operation using Dual Tree-Complex Wavelet Transform. The common fusion rules, which are the average-fusion rule and maximum-fusion rule, were used to obtain the fused image. In the experiment, using the focus operators, the performance of the proposed fusion algorithm was compared with the existing algorithms. The results showed that the proposed method is better than these fusion methods in terms of the focus and quality.

Magnetic Resonance Imaging (MRI) is a medical indicative test utilized for taking images of the tissue points of interest of the human body. During image acquisition, MRI images can be damaged by many noise signals such as impulse noise. One reason for this noise may be a sharp or sudden disturbance in the image signal. The removal of impulse noise is one of the real difficulties. As of late, numerous image de-noising methods were produced for removing the impulse noise from images. Comparative analysis of known and modern methods of median filter family is presented in this paper. These filters can be categorized as follows: Standard Median Filter; Adaptive Median Filter; Progressive Switching Median Filter; Noise Adaptive Fuzzy Switching Median Filter; and Different Applied Median Filter. The de-noising technique performance for each one is evaluated and compared using Peak Signal Noise Ratio, Structural Similarity index Metric, and Beta metric as quantitative metrics. The experimental results showed that the latest de-noising technique, Different Applied Median Filter (DAMF), produced better results in removing impulse noise compared with the other de-noising techniques. However, this filter produced de-noised image with nonlinear edges in high-density noise. As a result, noise removal from images is one of the low-level images processing which is considered as a first step in many image applications. Therefore, the efficiency of any image processed depends on the efficiency of noise removal technique.