This article presents a technique that arranges the elements of hierarchical representations of images according to a coarseness attribute. The choice of the attribute can be made according to prior knowledge about the content of the images and the intended application. The transformation is similar to filtering a hierarchy with a non-increasing attribute, and comprises the results of multiple ...

Mobile users of information systems are not always able to view needed information because visual attention is required elsewhere. Personal data assistants (PDAs) and other mobile information devices used by the typical mobile knowledge worker support mechanisms that allow for the “hearing” of information stored on these devices. However, few of these nonvisual mechanisms provide a way to save,...

Learning to transfer visual attributes requires supervision dataset. Corresponding images with varying attribute values with the same identity are required for learning the transfer function. This largely limits their applications, because capturing them is often a difficult task. To address the issue, we propose an unsupervised method to learn to transfer visual attribute. The proposed method ...

Now a day’s everyone storing there data in cloud because we can’t depends on hard drives if they crash one can’t have backup for ever data. Famous Cloud storage applications are Drop box, Google drive, Sky drive, Box, Amazon cloud drive, Surdoc and Apple icloud. In cloud data security is provided by various security algorithms. In our research we have chosen attribute based encryption technique...

Li, Jiangtao. Ph.D., Purdue University, May, 2006. Privacy Enhanced Automated Trust Negotiation. Major Professors: Mikhail J. Atallah and Ninghui Li. In automated trust negotiation, two parties exchange digitally signed credentials that contain attribute information to establish trust and make access control decisions. Because the information in question is often sensitive, credentials are prot...