k-anonymity is an important model in the field of privacy protection and it is an effective method to prevent privacy disclosure in micro-data release. However, it is ineffective for the attribute disclosure by the homogeneity attack. The existing models based on k-anonymity have solved this problem to a certain extent, but they did not distinguish the different values of the sensitive attribut...

One of the important key applications learning analytics is offering an opportunity to institutions track student’s academic activities and provide them with real-time adaptive consultations if student performance diverts towards inadequate outcome. Still, numerous barriers exist while developing implementing such kind applications. Machine algorithms emerge as useful tools endorse by building ...

Title: HOW DID YOU GET IN? ATTRIBUTIONS OF PREFERENTIAL SELECTION IN COLLEGE ADMISSIONS Archie L. Bates, III, Doctor of Philosophy, 2006 Directed By: Professor Katherine J. Klein Department of Psychology Minorities are often suspected beneficiaries (e.g., Heilman, 1994) of affirmative action—that is, they are individuals who attribute or perceive that others attribute their selection for a job ...

Most of data in Multi-attribute decision making (MADM) problems are changeable rather than constant and stable. Therefore, sensitivity analysis after problem solving can effectively contribute to making accurate decisions. In this paper, we offer a new method for sensitivity analysis in multi-attribute decision making problems in which if the weights of one attribute changes, then we can dete...