Department of Mathematics, Statistics and Computer Science
COLLOQUIUM ANNOUNCEMENT
Meryem Karaman
MSCS Department – Marquette University
A Mathematical Model for Analyzing Temporal Processing Effects of
Fourier Encoding Anomalies and Their Correction in fMRI Data
The images in both functional magnetic resonance imaging (fMRI) and functional connectivity MRI (fcMRI) are acquired
in time-series and non-negligible temporal processing steps, such as dynamic magnetic field correction, slice timing
correction, image registration and temporal filtering are applied to the acquired data. With the knowledge that the spatial
processing of fMRI data induces artificial correlations, one can expect temporal processing operators to alter the signal
and noise properties of the data as well. The goal of this study is to mathematically model time series preprocessing
operators as well as spatial processing operators and Fourier encoding anomaly correction operator by further expanding
the previous work which considered the effects of individual image preprocessing [Journal of Neuroscience Methods
181(2009):268-282]. The proposed model allows one to compute exact image-space statistics to be incorporated into the
statistical fMRI activation models, and thus provides more accurate activation statistics. The linear framework is first
demonstrated with a low dimensional phantom data. The effects of the operators are then illustrated in a realistically
simulated agar phantom data set.
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Farzana Rahman
MSCS Department – Marquette University
I Am Not a Goldfish in a Bowl:
Privacy Preservation in RFID Based Healthcare Systems
Radio frequency identification technology (RFID) has received considerable attention within the healthcare for almost a
decade now. The technology’s promise to efficiently track hospital supplies, medical equipment, medications and patients
is an attractive proposition to the healthcare industry. However, the prospect of wide spread use of RFID tags in the
healthcare sector has also triggered discussions regarding privacy, particularly because RFID data in transit may easily be
intercepted. RFID technology has not really seen its true potential in healthcare since privacy concerns raised by the tag
bearers are not properly addressed by the existing RFID authentication protocols. The two major types of privacy
preservation techniques that are required in an RFID based healthcare is: 1) a privacy preserving authentication protocol is
required while sensing RFID tags for different identification and monitoring purposes, 2) a privacy preserving access
control mechanism is required to restrict unauthorized access of private information while providing healthcare services
using the tag ID. In this research work, we propose a framework (PriSens-HSAC) that makes an effort to address the
above mentioned two privacy issues. Our experiment and evaluation shows that PriSens protocol allows an RFID
application to preserve much better privacy compared to the other existing techniques.
1:00 p.m., January 25, 2013
1313 W. Wisconsin Avenue, Cudahy Hall, Room 401, Milwaukee, WI 53201-1881
Pre-Colloquium refreshments served in Room 342 at 12:30 p.m.
For further information: http://www.mscs.mu.edu/mscs/resources/colloquium.html,
or contact Dr. Rong Ge #414-288-6344, Rong.Ge@marquette.edu.