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Tam M.,Washington State University | Tam M.,Canada Border Services Agency | Hill Jr. H.H.,Washington State University
Analyst | Year: 2011

A novel analytical method, called Liquid Phase Ion Mobility Spectrometry (LiPIMS) was demonstrated, where aqueous phase analytes were ionized and introduced into non-aqueous liquids, transported by an external electric field from the point of generation to a collection electrode. Ions were produced from a unique liquid phase ionization process, called Electrodispersion Ionization. Spectra of analyte ions illustrated the potential of LiPIMS as a new separation technique. Experimental data showed that electrodispersion ionization was effective in generating nanoampere level of ion current in hexane and benzene from aqueous samples. By controlling the ionization voltage in relation to the sample flow rate, it was possible to operate the electrodispersion ionization source in both continuous and pulsed ionization modes. Unique LiPIMS spectra of aqueous samples of tetramethylammonium bromide, tetrabutylammonium bromide and bradykinin were presented and their respected liquid phase ion mobility values were determined. © The Royal Society of Chemistry 2011. Source


Gorodnichy D.O.,Canada Border Services Agency
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2010

It is not uncommon for contemporary biometric systems to have more than one match below the matching threshold, or to have two or more matches having close matching scores. This is especially true for those that store large quantities of identities and/or are applied to measure loosely constrained biometric traits, such as in identification from video or at a distance. Current biometric performance evaluation standards however are still largely based on measuring single-score statistics such as False Match, False Non-Match rates and the trade-off curves based thereon. Such methodology and reporting makes it impossible to investigate the risks and risk mitigation strategies associated with not having a unique identifying score. To address the issue, Canada Border Services Agency has developed a novel modality-agnostic multi-order performance analysis framework. The framework allows one to analyze the system performance at several levels of detail, by defining the traditional single-score-based metrics as Order-1 analysis, and introducing Order- 2 and Order-3 analysis to permit the investigation of the system reliability and the confidence of its recognition decisions. Implemented in a toolkit called C-BET (Comprehensive Biometrics Evaluation Toolkit), the framework has been applied in a recent examination of the state-of-the art iris recognition systems, the results of which are presented, and is now recommended to other agencies interested in testing and tuning the biometric systems. © 2010 Copyright SPIE - The International Society for Optical Engineering. Source


Radtke P.V.W.,University of Quebec | Granger E.,University of Quebec | Sabourin R.,University of Quebec | Gorodnichy D.O.,Canada Border Services Agency
Information Fusion | Year: 2014

Several ensemble-based techniques have been proposed to design pattern recognition systems when data has imbalanced class distributions, although class proportions may change over time according to the operational environment. For instance, in video surveillance applications, face recognition (FR) is employed to detect the presence of target individuals of interest in potentially complex and changing environments. Systems for FR in video surveillance are typically designed a priori with a limited amount of reference target data and prior knowledge of underlying class distributions. However, the relatively proportion of target and non-target faces captured during operations varies over time. Estimating the actual proportion of data from the input data stream could allow to dynamically adapt ensembles to reflect operational conditions. In this paper, the selection and fusion of ensembles produced through Boolean Combination (BC) of classifiers is periodically adapted based on the class proportions estimated from input streams. BC techniques have been shown to efficiently integrate the responses of multiple diversified classifiers in the ROC space, yet the impact on performance of imbalanced data distributions is difficult to observe from ROC curves. Given a diversified pool of classifiers and a desired false positive rate (fpr), the new Skew-Sensitive Boolean Combination (SSBC) technique exploits the Precision-Recall Operating Characteristic (PROC) space, leading to a higher level of performance. A set of BCs of base classifiers is initially produced with imbalanced reference data in the PROC space, where each BC curve corresponds to different level of imbalance (a growing number of non-target samples versus a fixed number of target ones). Then, during operations, the closest adjacent levels of class imbalance are periodically estimated using the Hellinger distance between the data distribution of inputs and that of imbalance levels, and used to approximate the most accurate BC of classifiers from operational points of these curves. Simulation results on Faces In Action video surveillance data indicate that ensemble-based FR systems using the SSBC technique outperform the same systems using traditional BC techniques with Random Under-Sampling and One-Sided Selection. It allows to dynamically select BCs that provide a higher level of precision (and F1 value) for target individuals, and a significantly smaller difference between desired and actual fpr. Performance of this adaptive approach is also comparable to the costly full recalculation of BCs (as required by a BC technique to accommodate a specific level of imbalance), but for a computational complexity that is considerably lower. Finally, SSBC is shown to achieve a high level of discrimination between target and non-target individuals when face tracking is exploited to accumulate ensemble predictions for facial captures that correspond to a same person in the video scene. © 2013 Elsevier B.V. All rights reserved. Source


Gerson H.,Canada Border Services Agency
Alytes | Year: 2012

Little is known about amphibian species in international trade. Canadian customs documentation for importation of live amphibians, frogs' legs and medicinal amphibian products was reviewed to determine the species imported into Canada. Descriptions of amphibian species in trade, origins and quantities are provided. Recommendations are made to improve the species-specific trade data collected by regulatory authorities with a view to addressing conservation concerns for amphibians. Source


Gorodnichy D.O.,Canada Border Services Agency | Hoshino R.,Canada Border Services Agency
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

We present a calibration algorithm that converts biometric matching scores into probability-based confidence scores. Using the context of iris biometrics, we show - theoretically and by experiments - that in addition to attaching a meaningful confidence measure to the output, this calibration technique yields the best possible detection error trade-off (DET) curves, both at the score level and at the decision level, thus maximizing the overall performance of the biometric system. © 2010 Springer-Verlag Berlin Heidelberg. Source

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