The recent advancement in data mining technology to analyze vast amount of data has played an important role in several areas of Business processing. Data mining also opens new threats to privacy and information security if not done or used properly. The main problem is that from non-sensitive data, one is able to infer sensitive information, including personal information, fact or even patterns which are generated by any algorithm of data mining. In order to focusing on privacy preserving association rule mining, the simplistic solution to address the problem of privacy is presented. The solution is to survey different aspects which are discussed in the several research papers and after analyzing those research papers conclude a new solution which is best in efficiency and performance. Before analyzing the algorithms, the data structure of database and sensitive association rule mining set have been analyzed to build the more effective model.
Localization and segmentation are important task in medical image analysis. As we know detection of optic nerves is also a major problem in automated retinal image analysis system. Image segmentation of medical image is very complex and crucial step, in this series segmentation of retinal image is more complex in comparison of others. For the retinal image segmentation we use gradient descent method. Recent research is focus on better accuracy rate. This paper gives a bird's eye over all the detection technique toward fair segmentation of optic nerves using gradient descent method (GDM). For initialization of local contour we use Signed pressure force function (SPF) which is region-based active contour model.
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