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The Department of National Defence , commonly abbreviated as DND, is a Canadian government department responsible for defending Canada's interests and values at home and abroad.National Defence is the largest department of the Government of Canada in terms of budget as well as staff. The Department is headed by the Deputy Minister of National Defence, who is the Department’s senior civil servant, and reports directly to the Minister of National Defence. The Department of National Defence exists to aid the minister in carrying out his responsibilities, and acts as the civilian support system for the Canadian Armed Forces. Under the National Defence Act, the Canadian Forces is completely separate and distinct from the Department of National Defence.The Department of National Defence is currently headed by Deputy Minister Richard B. Fadden. Wikipedia.

Mellema G.R.,Canadian Department of National Defence
15th International Conference on Information Fusion, FUSION 2012 | Year: 2012

Target tracking has traditionally focussed on the use of kinematic information such as bearing, range, position, or speed. In some cases it is possible to extract additional target information that may be useful in the maintenance of reliable tracks or the establishment of target type or identity. Several methods have been proposed for the use of feature information in target tracking. In this paper we discuss and evaluate featureassisted tracking using a feature component in the cumulative likelihood ratio used for track initiation and maintenance in a multihypothesis (MHT) tracker. The data set used in the evaluation, PACsim, was specifically developed to investigate the use and value of feature information in multistatic tracking and has been the subject of collaborative analysis by the Multistatic Tracking Working Group (MSTWG). © 2012 ISIF (Intl Society of Information Fusi). Source

Gammon M.A.,Canadian Department of National Defence | Gammon M.A.,Yildiz Technical University
Ocean Engineering | Year: 2011

A fishing boat hull is used as an example of how hull form optimization can be accomplished using a Multi-Objective Genetic Algorithm (MOGA). The particular MOGA developed during this study allows automatic selection of a few Pareto Optimal results for examination by the designers while searching the complete Pareto Front. The optimization uses three performance indices for resistance, seakeeping and stability to modify the hull shape to obtain optimal hull offsets as well as optimal values for the principal parameters of length, beam and draft. The modification of the 148/1-B fishing boat hull, the parent hull form of the stanbul Technical University (TÜ) series of fishing boats, is presented by first fixing the principal parameters and allowing the hull offsets to change, and secondly by simultaneously allowing variation of both the principal parameters and the hull offsets. Improvements in all three objectives were found. For further research the methodology can be modified to allow for the addition of other performance objectives, such as cost or specific mission objectives, as well as the use of enhanced performance prediction solvers. In addition, one or more hulls could be evaluated by experiment to validate the results of using this particular optimization approach. © 2011 Elsevier Ltd. All rights reserved. Source

Boutros T.,Canadian Department of National Defence | Liang M.,University of Ottawa
Mechanical Systems and Signal Processing | Year: 2011

Over the last few decades, the research for new fault detection and diagnosis techniques in machining processes and rotating machinery has attracted increasing interest worldwide. This development was mainly stimulated by the rapid advance in industrial technologies and the increase in complexity of machining and machinery systems. In this study, the discrete hidden Markov model (HMM) is applied to detect and diagnose mechanical faults. The technique is tested and validated successfully using two scenarios: tool wear/fracture and bearing faults. In the first case the model correctly detected the state of the tool (i.e., sharp, worn, or broken) whereas in the second application, the model classified the severity of the fault seeded in two different engine bearings. The success rate obtained in our tests for fault severity classification was above 95%. In addition to the fault severity, a location index was developed to determine the fault location. This index has been applied to determine the location (inner race, ball, or outer race) of a bearing fault with an average success rate of 96%. The training time required to develop the HMMs was less than 5 s in both the monitoring cases. © 2010 Elsevier Ltd. All rights reserved. Source

Birsan M.,Canadian Department of National Defence
IEEE Transactions on Magnetics | Year: 2011

Previous magnetic dipole localization algorithms using gradient data attempt to find the position of the magnetic source at the measurement time only. Based on the direct inversion of the magnetic gradient tensor, these methods provide results that can be highly sensitive to temporal noise in data. To avoid a temporally scattered solution, a recursive approach is proposed that is promising for estimating the trajectory and the magnetic moment components of a target modeled as a magnetic dipole source using data collected with a gradiometer. In this study, the determination of target position, magnetic moment, and velocity is formulated as a Bayesian estimation problem for dynamic systems, which could be solved using a sequential Monte Carlo based approach known as the "particle filter." This filter represents the posterior distribution of the state variables by a system of particles which evolve and adapt recursively as new information becomes available. In addition to the conventional particle filter, the proposed tracking and classification algorithm uses the unscented Kalman filter (UKF) to generate the prior distribution of the unknown parameters. The proposed method is then demonstrated by applying it to real data collected when an automobile was passing by a gradiometer either on a straight or a curved track. The results indicate that the recursive method is less sensitive to noise than the direct inversion solution, even if not all the components of the gradient tensor were used. © 2006 IEEE. Source

Hiltz J.A.,Canadian Department of National Defence
Journal of Analytical and Applied Pyrolysis | Year: 2014

Fluorocarbon elastomers are specified for a number of applications where excellent high temperature and chemical resistance is required. To ensure that a fluoroelastomer with the required properties for a particular application is used, characterization techniques that allow the positive identification of the elastomer are required. In this paper the characterization of four fluoroelastomer formulations - a vinylidene fluoride/hexafluoropropene (VDF/HFP) dipolymer, a vinylidene fluoride/hexafluoropropene/tetrafluoroethylene terpolymer, and two vinylidene fluoride/perfluoro(methyl vinyl ether)/tetrafluoroethylene (VDF/PMVE/TFE) tetrarpolymers - is described. The characterization techniques included pyrolysis gas chromatography/mass spectrometry (py-GC/MS), Fourier transform infrared (FT-IR) spectrometry, differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). Py-GC/MS was the only characterization technique that could identify the four formulations unambiguously. The positive identification was based on differences in the pyrolytic degradation products of the flouroelastomer formulations. © 2014 Published by Elsevier B.V. All rights reserved. Source

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