Tracking of motor vehicles from aerial video imagery using the OT-MACH correlation filter

Accurately tracking moving targets in a complex scene involving moving cameras, occlusions and targets embedded in noise is a very active research area in computer vision. In this paper, an optimal trade-off maximum correlation height (OT-MACH) filter has been designed and implemented as a robust tracker. The algorithm allows selection of different objects as a target, based on the operator’s requirements. The user interface is designed so as to allow the selection of a different target for tracking at any time. The filter is updated, at a frequency selected by the user, which makes the filter more resistant to progressive changes in the object’s orientation and scale. The tracker has been tested on both colour visible band as well as infra-red band video sequences acquired from the air by the Sussex County police helicopter. Initial testing has demonstrated the ability of the filter to maintain a stable track on vehicles despite changes of scale, orientation and lighting and the ability to re-acquire the track after short losses due to the vehicle passing behind occlusions

Multiplexed DNA-Modified Electrodes

We report the use of silicon chips with 16 DNA-modified electrodes (DME chips) utilizing DNA-mediated charge transport for multiplexed detection of DNA and DNA-binding protein targets. Four DNA sequences were simultaneously distinguished on a single DME chip with 4-fold redundancy, including one incorporating a single base mismatch. These chips also enabled investigation of the sequence-specific activity of the restriction enzyme Alu1. DME chips supported dense DNA monolayer formation with high reproducibility, as confirmed by statistical comparison to commercially available rod electrodes. The working electrode areas on the chips were reduced to 10 μm in diameter, revealing microelectrode behavior that is beneficial for high sensitivity and rapid kinetic analysis. These results illustrate how DME chips facilitate sensitive and selective detection of DNA and DNA-binding protein targets in a robust and internally standardized multiplexed format

Efficacy of metabarcoding for identification of fish eggs evaluated with mock communities.

There is urgent need for effective and efficient monitoring of marine fish populations. Monitoring eggs and larval fish may be more informative than that traditional fish surveys since ichthyoplankton surveys reveal the reproductive activities of fish populations, which directly impact their population trajectories. Ichthyoplankton surveys have turned to molecular methods (DNA barcoding & metabarcoding) for identification of eggs and larval fish due to challenges of morphological identification. In this study, we examine the effectiveness of using metabarcoding methods on mock communities of known fish egg DNA. We constructed six mock communities with known ratios of species. In addition, we analyzed two samples from a large field collection of fish eggs and compared metabarcoding results with traditional DNA barcoding results. We examine the ability of our metabarcoding methods to detect species and relative proportion of species identified in each mock community. We found that our metabarcoding methods were able to detect species at very low input proportions; however, levels of successful detection depended on the markers used in amplification, suggesting that the use of multiple markers is desirable. Variability in our quantitative results may result from amplification bias as well as interspecific variation in mitochondrial DNA copy number. Our results demonstrate that there remain significant challenges to using metabarcoding for estimating proportional species composition; however, the results provide important insights into understanding how to interpret metabarcoding data. This study will aid in the continuing development of efficient molecular methods of biological monitoring for fisheries management

Pilot-aided ML schemes for joint beamforming and channel estimation in WCDMA systems

This paper proposes semi-blind channel estimation and interference cancellation schemes for the reception of pilot-aided signals in WCDMA systems. It is shown that the performance of classical training-based schemes is severely degraded due to the code-multiplexing (as opposed to time-multiplexing) of traffic and pilot signals. The time-dispersivity of the channel destroys the orthogonality between the traffic signal and the pilot, and consequently the traffic signal appears as a new interfering signal for the channel estimation/beamforming algorithm. In order to avoid this effect, we propose techniques that exploit both the presence of the training sequence and the structure of the traffic signal in a semi-blind fashion.Peer ReviewedPostprint (published version