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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Domain Specific Analysis Of Privacy Practices And Concerns In The Mobile Application Market, Fahimeh Ebrahimi Meymand
Domain Specific Analysis Of Privacy Practices And Concerns In The Mobile Application Market, Fahimeh Ebrahimi Meymand
LSU Doctoral Dissertations
Mobile applications (apps) constantly demand access to sensitive user information in exchange for more personalized services. These-mostly unjustified-data collection tactics have raised major privacy concerns among mobile app users. Existing research on mobile app privacy aims to identify these concerns, expose apps with malicious data collection practices, assess the quality of apps' privacy policies, and propose automated solutions for privacy leak detection and prevention. However, existing solutions are generic, frequently missing the contextual characteristics of different application domains. To address these limitations, in this dissertation, we study privacy in the app store at a domain level. Our objective is to …
Analysis And Modeling Of Hurricane Impacts On A Coastal Louisiana Lake Bottom, Angelina Freeman
Analysis And Modeling Of Hurricane Impacts On A Coastal Louisiana Lake Bottom, Angelina Freeman
LSU Doctoral Dissertations
Tropical cyclone impacts on wetland, terrestrial, and shelf systems have been previously studied and reasonably delineated, but little is known about the response of coastal lakes to storm events. For the first time, tropical cyclone impacts on a shallow coastal lake in the Louisiana coastal plain have been studied using direct lines of evidence and numerical modeling. Using side-scan sonar, CHIRP subbottom and echo sounder bathymetric profiles, the lake bottom and shallow subsurface of Sister Lake was imaged pre- and post-Hurricanes Katrina and Rita to provide a geologic framework for assessing the effects of these storms. Box cores were collected …
The Impact Of Overfitting And Overgeneralization On The Classification Accuracy In Data Mining, Huy Nguyen Anh Pham
The Impact Of Overfitting And Overgeneralization On The Classification Accuracy In Data Mining, Huy Nguyen Anh Pham
LSU Doctoral Dissertations
Current classification approaches usually do not try to achieve a balance between fitting and generalization when they infer models from training data. Such approaches ignore the possibility of different penalty costs for the false-positive, false-negative, and unclassifiable types. Thus, their performances may not be optimal or may even be coincidental. This dissertation analyzes the above issues in depth. It also proposes two new approaches called the Homogeneity-Based Algorithm (HBA) and the Convexity-Based Algorithm (CBA) to address these issues. These new approaches aim at optimally balancing the data fitting and generalization behaviors of models when some traditional classification approaches are used. …
A Neural Network Model For Classification Of Coastal Wetlands Vegetation Structure With Moderate Resolution Imaging Spectro-Radiometer (Modis) Data, Evaristo Joseph Liwa
A Neural Network Model For Classification Of Coastal Wetlands Vegetation Structure With Moderate Resolution Imaging Spectro-Radiometer (Modis) Data, Evaristo Joseph Liwa
LSU Doctoral Dissertations
Mapping coastal marshes is an important component in the management of coastal environments. Classification of marshes using remote sensing data has traditionally been performed by employing either parametric supervised classification algorithms or unsupervised classification algorithms. The implementation of these conversional classification methods is based on the underlying distributions concerning the probability density functions (PDF). Neural networks provide a practical approach to this classification because they are essentially non-parametric data transformations that are not restricted by any underlying assumptions. The major objective of this study was to evaluate the ability of neural networks using Moderate Resolution Imaging Spectro-radiometer (MODIS) data to …