NTL-SAFETY AND SECURITY-SAFETY AND SECURITY;NTL-SAFETY AND SECURITY-Highway Safety;
Abstract:
The ever increasing size of datasets used for data mining and machine learning applications has placed a renewed emphasis on algorithm performance and processing strategies. This research addresses algorithms for ranking variables in a dataset, as well as for ranking values of a specific variable. We propose two new techniques, called Max Gain (MG) and Sum Max Gain Ratio (SMGR), which are well-correlated with existing techniques, yet are much more intuitive. MG and SMGR were developed for the public safety domain using categorical traffic accident data. Unlike the typical abstract statistical techniques for ranking variables and values, the proposed techniques can be motivated as useful intuitive metrics for non-statistician practitioners in a particular domain. Additionally, the developed techniques are generally more efficient than the more traditional statistical approaches.
Automated vehicle (AV) technologies may significantly improve driving safety, but only if they are widely adopted and used appropriately. Adoption and...
This report describes the development of an automated computer vision system that identities and inventories road signsfrom imagery acquired from the ...
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