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Scalable Community Detection Using Distributed Louvain Algorithm, Naw Safrin Sattar
Scalable Community Detection Using Distributed Louvain Algorithm, Naw Safrin Sattar
University of New Orleans Theses and Dissertations
Community detection (or clustering) in large-scale graph is an important problem in graph mining. Communities reveal interesting characteristics of a network. Louvain is an efficient sequential algorithm but fails to scale emerging large-scale data. Developing distributed-memory parallel algorithms is challenging because of inter-process communication and load-balancing issues. In this work, we design a shared memory-based algorithm using OpenMP, which shows a 4-fold speedup but is limited to available physical cores. Our second algorithm is an MPI-based parallel algorithm that scales to a moderate number of processors. We also implement a hybrid algorithm combining both. Finally, we incorporate dynamic load-balancing in …
Detection Of Sand Boils From Images Using Machine Learning Approaches, Aditi S. Kuchi
Detection Of Sand Boils From Images Using Machine Learning Approaches, Aditi S. Kuchi
University of New Orleans Theses and Dissertations
Levees provide protection for vast amounts of commercial and residential properties. However, these structures degrade over time, due to the impact of severe weather, sand boils, subsidence of land, seepage, etc. In this research, we focus on detecting sand boils. Sand boils occur when water under pressure wells up to the surface through a bed of sand. These make levees especially vulnerable. Object detection is a good approach to confirm the presence of sand boils from satellite or drone imagery, which can be utilized to assist in the automated levee monitoring methodology. Since sand boils have distinct features, applying object …