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Full-Text Articles in American Studies
Evaluation Of Digital Imaging Systems Used In Highway Applications, Alex Mraz
Evaluation Of Digital Imaging Systems Used In Highway Applications, Alex Mraz
USF Tampa Graduate Theses and Dissertations
Manual pavement condition surveys are gradually replaced by more comprehensive automated surveys conducted by multi-function highway evaluation vehicles. Highway evaluation vehicles are generally equipped with laser profiling, land navigation, and imaging sub-systems. The imaging system consists of three cameras; forward-view and side-view digital area-scan cameras for capturing images of traffic signs and right-of-way safety features, and a pavement digital line-scan or area-scan camera for capturing images of the pavement surface. In addition to the 3-laser and accelerometer-based profiling system, these vehicles are also equipped with differential global positioning equipment (DGPS) and an inertial measurement unit (IMU) for cross-slope, curvature and …
Characterization Of Preliminary Breast Tomosynthesis Data: Noise And Power Spectra Analysis, Madhusmita Behera
Characterization Of Preliminary Breast Tomosynthesis Data: Noise And Power Spectra Analysis, Madhusmita Behera
USF Tampa Graduate Theses and Dissertations
Early detection, diagnosis, and suitable treatment are known to significantly improve the chance of survival for breast cancer (BC) patients. To date, the most cost effective method for screening and early detection is screen-film mammography, which is also the only tool that has demonstrated its ability to reduce BC mortality. Full-field digital mammography (FFDM) is an extension of screen-film mammography that eliminates the need for film-processing because the images are detected electronically from their inception. Tomosynthesis is an emerging technology in digital mammography built on the FFDM framework, which offers an alternative to conventional two-dimensional mammography. Tomosynthesis produces three-dimensional (volumetric) …
Distributed Clustering For Scaling Classic Algorithms, Prodip Hore
Distributed Clustering For Scaling Classic Algorithms, Prodip Hore
USF Tampa Graduate Theses and Dissertations
Clustering large data sets recently has emerged as an important area of research. The ever-increasing size of data sets and poor scalability of clustering algorithms has drawn attention to distributed clustering for partitioning large data sets. Sometimes, centrally pooling the distributed data is also expensive. There might be also constraints on data sharing between different distributed locations due to privacy, security, or proprietary nature of the data. In this work we propose an algorithm to cluster large-scale data sets without centrally pooling the data. Data at distributed sites are clustered independently i.e. without any communication among them. After partitioning the …