Exemplar-based Linear Discriminant Analysis for Robust Object Tracking

Tracking-by-detection has become an attractive tracking technique, which treats tracking as a category detection problem. However, the task in tracking is to search for a specific object, rather than an object category as in detection. In this paper, we propose a novel tracking framework based on exemplar detector rather than category detector. The proposed tracker is an ensemble of exemplar-based linear discriminant analysis (ELDA) detectors. Each detector is quite specific and discriminative, because it is trained by a single object instance and massive negatives. To improve its adaptivity, we update both object and background models. Experimental results on several challenging video sequences demonstrate the effectiveness and robustness of our tracking algorithm.Comment: ICIP201

Multiple-Level Power Allocation Strategy for Secondary Users in Cognitive Radio Networks

In this paper, we propose a multiple-level power allocation strategy for the secondary user (SU) in cognitive radio (CR) networks. Different from the conventional strategies, where SU either stays silent or transmit with a constant/binary power depending on the busy/idle status of the primary user (PU), the proposed strategy allows SU to choose different power levels according to a carefully designed function of the receiving energy. The way of the power level selection is optimized to maximize the achievable rate of SU under the constraints of average transmit power at SU and average interference power at PU. Simulation results demonstrate that the proposed strategy can significantly improve the performance of SU compared to the conventional strategies.Comment: 12 page

Gold nanoparticle mediated membrane permeabilization of phytochemical into breast cancer cells

"May 2014."Thesis supervisor: Dr. John Viator.Includes vita.Includes bibliographical references (pages 50-54)

Estimating the location of the center of resistance of canines

Objective:  To develop a method to quickly estimate the location of center of resistance (CR) in mesial-distal (MD) and buccal-lingual (BL) directions from the tooth's image. Materials and Methods:  The maxillary cone-beam computed tomography (CBCT) scans of 18 patients were used. Finite element (FE) models of the canines and their surrounding tissues were built based on their CBCT scans to calculate the locations of CR. Root length, centroid of the contact surface (CCS), and centroid of projection of the contact surface (CPCS) were also obtained from the images. The CCS and CPCS locations were projected on the tooth's long axis, which were represented as percentages of the root length measured from the root's apex. Results:  Using the FE results as the standards, the errors of using CCS or CPCS to estimate CR were calculated. The average location of CR calculated using the FE method was 60.2% measured from the root’s apex in the MD direction and 58.4% in the BL direction. The location of the CCS was 60.9%. The difference in CR was 0.7% in the MD direction and 2.5% in the BL direction. The location of CPCS was 60.2% in the MD direction and 59.1% in the BL direction, which resulted in a 0.1% and 0.8% difference with the reference CR, respectively. The average difference of CR in the MD and BL directions was small but statistically significant (P < .05). Conclusion:  The locations of the CR of a human canine in the MD and BL directions can be estimated by finding the CPCSs in those directions