This final report describes research on developing new technologies and approaches for countering Improvised Explosive Devices (IEDs). The work comprised eight projects, including two prediction projects, one that developed methods for identifying explosive materials using x-ray emission spectra, and another that developed similarity based learning architectures to improve pattern recognition for real time decision-making. One of five detection projects researched a nonlinear spectroscopic technique of sum frequency generation as a ...
The verification of high-resolution mesoscale numerical weather predictions presents unique challenges. Traditional verification metrics - root mean square error, etc., which rely on single point verification often give incomplete or misleading assessments of model performance. Small-scale features are often miss-represented (aliasing) or, due to much lower predictability than large-scale features, cause an unwarranted penalty by conventional verification measures due to small spatial or temporal errors. Both the model developer and ...
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