Physical Sciences and Mathematics Commons^™

Constructing Frameworks For Task-Optimized Visualizations, Ghulam Jilani Abdul Rahim Quadri

USF Tampa Graduate Theses and Dissertations

Visualization is crucial in today’s data-driven world to augment and enhance human understanding and decision-making. Effective visualizations must support accuracy in visual task performance and expressive data communication. Effective visualization design depends on the visual channels used, chart types, or visual tasks. However, design choices and visual judgment are co-related, and effectiveness is not one-dimensional, leading to a significant need to understand the intersection of these factors to create optimized visualizations. Hence, constructing frameworks that consider both design decisions and the task being performed enables optimizing visualization design to maximize efficacy. This dissertation describes experiments, techniques, and user studies to …

Graph-Based Latent Embedding, Annotation And Representation Learning In Neural Networks For Semi-Supervised And Unsupervised Settings, Ismail Ozsel Kilinc

USF Tampa Graduate Theses and Dissertations

Machine learning has been immensely successful in supervised learning with outstanding examples in major industrial applications such as voice and image recognition. Following these developments, the most recent research has now begun to focus primarily on algorithms which can exploit very large sets of unlabeled examples to reduce the amount of manually labeled data required for existing models to perform well. In this dissertation, we propose graph-based latent embedding/annotation/representation learning techniques in neural networks tailored for semi-supervised and unsupervised learning problems. Specifically, we propose a novel regularization technique called Graph-based Activity Regularization (GAR) and a novel output layer modification called …

Prevention And Detection Of Intrusions In Wireless Sensor Networks, Ismail Butun

USF Tampa Graduate Theses and Dissertations

Wireless Sensor Networks (WSNs) continue to grow as one of the most exciting and challenging research areas of engineering. They are characterized by severely constrained computational and energy

resources and also restricted by the ad-hoc network operational

environment. They pose unique challenges, due to limited power

supplies, low transmission bandwidth, small memory sizes and limited energy. Therefore, security techniques used in traditional networks cannot be directly adopted. So, new ideas and approaches are needed, in order to increase the overall security of the network. Security applications in such resource constrained WSNs with minimum overhead provides significant challenges, and is the …