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Full-Text Articles in Engineering
Kentucky Traffic Collision Facts 2013, Kentucky Transportation Center, Kentucky State Police
Kentucky Traffic Collision Facts 2013, Kentucky Transportation Center, Kentucky State Police
Kentucky Transportation Center Research Report
KENTUCKY’S TRAFFIC COLLISION FACTS report for 2013 is based on collision reports submitted to the Kentucky State Police Records Branch. As required by Kentucky Revised Statutes 189.635, “every law enforcement agency whose officers investigate a vehicle accident of which a report must be made…shall file a report of the accident…within ten days after investigation of the accident upon forms supplied by the bureau.” The stated purpose of this requirement is to utilize data on traffic collisions for such purposes as will improve the traffic safety program in the Commonwealth. Data contained in this report are based solely on the observations …
Analysis Of Long-Term Utah Temperature Trends Using Hilbert-Haung Transforms, Brent H. Hargis
Analysis Of Long-Term Utah Temperature Trends Using Hilbert-Haung Transforms, Brent H. Hargis
Theses and Dissertations
We analyzed long-term temperature trends in Utah using a relatively new signal processing method called Empirical Mode Decomposition (EMD). We evaluated the available weather records in Utah and selected 52 stations, which had records longer than 60 years, for analysis. We analyzed daily temperature data, both minimum and maximums, using the EMD method that decomposes non-stationary data (data with a trend) into periodic components and the underlying trend. Most decomposition algorithms require stationary data (no trend) with constant periods and temperature data do not meet these constraints. In addition to identifying the long-term trend, we also identified other periodic processes …
Three-Dimensional Modeling Of The Human Jaw/Teeth Using Optics And Statistics., Aly Saber Abdelrahim
Three-Dimensional Modeling Of The Human Jaw/Teeth Using Optics And Statistics., Aly Saber Abdelrahim
Electronic Theses and Dissertations
Object modeling is a fundamental problem in engineering, involving talents from computer-aided design, computational geometry, computer vision and advanced manufacturing. The process of object modeling takes three stages: sensing, representation, and analysis. Various sensors may be used to capture information about objects; optical cameras and laser scanners are common with rigid objects, while X-ray, CT and MRI are common with biological organs. These sensors may provide a direct or an indirect inference about the object, requiring a geometric representation in the computer that is suitable for subsequent usage. Geometric representations that are compact, i.e., capture the main features of the …
Applications Of Transit Signal Priority Technology For Transit Service, Frank Anthony Consoli
Applications Of Transit Signal Priority Technology For Transit Service, Frank Anthony Consoli
Electronic Theses and Dissertations
This research demonstrated the effectiveness of Transit Signal Priority (TSP) in improving bus corridor travel time in a simulated environment using real world data. TSP is a technology that provides preferential treatment to buses at signalized intersections. By considering different scenarios of activating bus signal priority when a bus is 3 or 5 minutes behind schedule, it was demonstrated that bus travel times improved significantly while there is little effect on delays for crossing street traffic. The case of providing signal priority for buses unconditionally resulted in significant crossing street delays for some signalized intersections with only minor improvement to …
Spatio-Temporal Prediction Of Root Zone Soil Moisture Using Multivariate Relevance Vector Machines, B. Zaman, Mac Mckee
Spatio-Temporal Prediction Of Root Zone Soil Moisture Using Multivariate Relevance Vector Machines, B. Zaman, Mac Mckee
Civil and Environmental Engineering Faculty Publications
oot zone soil moisture at one and two meter depths are forecasted four days into the future. In this article, we propose a new multivariate output prediction approach to root zone soil moisture assessment using learning machine models. These models are known for their robustness, efficiency, and sparseness; they provide a statistically sound approach to solving the inverse problem and thus to building statistical models. The multivariate relevance vector machine (MVRVM) is used to build a model that forecasts soil moisture states based upon current soil moisture and soil temperature conditions. The methodology combines the data at different depths from …