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George Pangalos

Researcher at Aristotle University of Thessaloniki

Publications -  82
Citations -  809

George Pangalos is an academic researcher from Aristotle University of Thessaloniki. The author has contributed to research in topics: Information system & Database design. The author has an hindex of 11, co-authored 76 publications receiving 787 citations. Previous affiliations of George Pangalos include AHEPA University Hospital & University of Rhode Island.

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Proceedings ArticleDOI

Flexible team-based access control using contexts

TL;DR: The integration of contextual information with team-based access control is discussed, which allows models such as TMAC to be flexible and express a variety of access policies that can provide tight and just-in-time permission activation.
Proceedings ArticleDOI

A flexible content and context-based access control model for multimedia medical image database systems

TL;DR: The proposed access control model preserves the advantages of scaleable security administration that RBAC-style models offer and yet offers the flexibility to specify complex access restrictions based on the semantic content of the images, the attributes of the user accessing the image, the relationship between the user and the patient whose images are to be accessed and the time.
Journal ArticleDOI

Rheological Properties of News Inks

TL;DR: In this article, the effect of ink composition on steadystate and time-dependent behavior in simple shear, as well as on extensional flow behavior was examined, and the inks studied were formulated to represent a spectrum of compositions typical of North American news inks.
Journal ArticleDOI

Access control based on attribute certificates for medical intranet applications.

TL;DR: Access control in clinical intranet applications can be successfully and securely managed through the use of digital certificates and the DIMEDAC security policy.
Journal ArticleDOI

A Methodology for Reliability Analysis in Health Networks

TL;DR: A novel approach for predicting system reliability in the early stage of designing RHN systems is presented, with the analysis of severity classes of failures and the application of stochastic modeling using discrete-time Markov chain in RHNs.