RANDOMNESS IN INTEGRATED CIRCUITS WITH APPLICATIONS IN DEVICE IDENTIFICATION AND RANDOM NUMBER GENERATION AUGUST 2007 DANIEL E. HOLCOMB B.S., UNIVERSITY OF MASSACHUSETTS AMHERST M.S.E.C.E., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Wayne P. Burleson RFID applications create a need for low-cost security and privacy in potentially hostile environments. To support security and pri...

Fern gametophytes and young sporophytes often provide too little material for DNA extraction and are particularly difficult to identify to genus. Here we developed an efficient procedure called 'Tissue-direct PCR', in which a slice of fern tissue is mixed with PCR reagents and primers, allowing certain genomic regions to be amplified directly in the thermal cycler. For these diminutive and feat...

The chloroplast genome of most land plants is highly conserved. In contrast, physical and gene mapping studies have revealed a highly rearranged chloroplast genome in species representing four families of ferns. In all four, there has been a rare duplication of the psbA gene and the order of the psbA, 16S, and 23S rRNA genes has been inverted. Our analysis shows that the described rearrangement...

This paper presents an algorithm for the classification of head pose in low resolution video. Invariance to skin, hair and background colours is achieved by classifying using an ensemble of randomised ferns which have been trained on labelled images. The ferns are used to simultaneously classify the head pose and to identify the most likely hypothesis for the mapping between colours and labels....

8 The main challenge of facial landmark localization in real-world application is that the large changes of head pose and facial expressions cause substantial image appearance variations. To avoid high dimensional facial shape regression, we propose a hierarchical pose regression approach, estimating the head rotation, face components, and facial landmarks hierarchically. The regression process...