Enhancing Knowledge and Bounce Rate in SERPs Using Micro-Data

Internet has revolutionized the human life. SEs (Search Engines) are one of the major tools being used for finding information over the Internet. SEs enlist the information into links as per relevance to the searched query. A searcher usually visits the top web links retrieved on SERPs (Search Engine Results Pages) in response to a search query. With the evolving nature of Internet and the increasing number of competitors; it is hard to maintain high ranking in SERPs even for professional correspondents. However, correspondents can apply the techniques of web micro-data to achieve high CTR (Click through Rate) in SERPs. Ranking in major SEs is still a critical factor, although in certain cases such as movies, books, recipes rich snippets proved profitable for webmasters. This study aims to address the gap in micro-data moving from top category such as Animals to their limited scope. Animals with information such as name, price, category will have high CTR and hence more user satisfaction for specified result will lead to high ranking in SERPs

Detection of Tuberculosis using Hybrid Features from Chest Radiographs

Tuberculosis is a contagious disease, but it’s diagnosis is still a difficult and challenging task as it is considered a big threat everywhere on the planet. Literature shows that underdeveloped countries widely use chest radiographs (X ray images) for the diagnosis of tuberculosis. Low accuracy of results and high cost are the two main reasons due to which most of the available methods are not useful for radiologists. In our research, we proposed a detection technique in which features extraction is performed on the basis of their texture, intensity and shape. For evaluating the performance of our proposed methodology, Montgomery Country (MC) dataset is used. It is a publically available data set which consists of 138 CXRs; among them, 80 CXRs are normal and 58 CXRs are malignant. The results of the proposed technique have outperformed state of the art methodologies on the MC dataset as it has shown 81.16% accuracy