Engineering Commons^™

Novel Approach To Integrate Can Based Vehicle Sensors With Gps Using Adaptive Filters To Improve Localization Precision In Connected Vehicles From A Systems Engineering Perspective, Abhijit Vasili

USF Tampa Graduate Theses and Dissertations

Research and development in Connected Vehicles (CV) Technologies has increased exponentially, with the allocation of 75 MHz radio spectrum in the 5.9 GHz band by the Federal Communication Commission (FCC) dedicated to Intelligent Transportation Systems (ITS) in 1999 and 30 MHz in the 5.9 GHz by the European Telecommunication Standards Institution (ETSI). Many applications have been tested and deployed in pilot programs across many cities all over the world.

CV pilot programs have played a vital role in evaluating the effectiveness and impact of the technology and understanding the effects of the applications over the safety of road users. The …

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 …

Automated Wound Segmentation And Dimension Measurement Using Rgb-D Image, Chih-Yun Pai

USF Tampa Graduate Theses and Dissertations

Accurate pressure ulcer (PrU) measurement is critical in assessing the effectiveness of PrU treatment. The traditional measurement process is manual, subjective, and requires frequent contact with the wound. The manual measurement relies on human observation which makes the measurement inconsistent, and the frequent contact with the wound increases risk of contamination or infection. The purpose of this research was to develop an automatic Pressure Ulcer Monitoring System (PrUMS) using a depth camera to provide automated, non-contact wound measurement. In this dissertation, 1) a wound segmentation with traditional machine learning method, which combines the color classification using K-Nearest Neighbors and the …

Data-Driven Studies On Social Networks: Privacy And Simulation, Yasanka Sameera Horawalavithana

USF Tampa Graduate Theses and Dissertations

Social media datasets are fundamental to understanding a variety of phenomena, such as epidemics, adoption of behavior, crowd management, and political uprisings. At the same time, many such datasets capturing computer-mediated social interactions are recorded nowadays by individual researchers or by organizations. However, while the need for real social graphs and the supply of such datasets are well established, the flow of data from data owners to researchers is significantly hampered by privacy risks: even when humans’ identities are removed, or data is anonymized to some extent, studies have proven repeatedly that re-identifying anonymized user identities (i.e., de-anonymization) is doable …

Adaptive Network Slicing In Fog Ran For Iot With Heterogeneous Latency And Computing Requirements: A Deep Reinforcement Learning Approach, Almuthanna Nassar

USF Tampa Graduate Theses and Dissertations

In view of the recent advances in Internet of Things (IoT) devices and the emerging new breed of smart city applications and intelligent vehicular systems driven by artificial intelligence, fog radio access network (F-RAN) has been recently introduced for the next generation wireless communications. The capability of F-RAN has emerged to overcome the latency limitations of cloud-RAN (C-RAN) and assure the quality-of-service (QoS) requirements of the ultra-reliable-low-latency-communication (URLLC) for IoT applications. To this end, fog nodes (FNs) are equipped with computing, signal processing and storage capabilities to extend the inherent operations and services of the cloud to the edge. However, …

An Automated Framework For Connected Speech Evaluation Of Neurodegenerative Disease: A Case Study In Parkinson's Disease, Sai Bharadwaj Appakaya

USF Tampa Graduate Theses and Dissertations

Neurodegenerative diseases affect millions of people around the world. The progressive degeneration worsens the symptoms, heavily impacting the quality of life of the patients as well as the caregivers. Speech production is one of the physiological processes affected by neurodegenerative diseases like Alzheimer’s disease, amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD). Speech is the most basic form of communication, and the effect of neurodegeneration degrades speech production, thereby reducing social interaction and mental well-being. PD is the second most common neurodegenerative disease affecting speech production in 90% of the diagnosed individuals. Speech analysis methods for PD in clinical methods …

Efficient Hardware Constructions For Error Detection Of Post-Quantum Cryptographic Schemes, Alvaro Cintas Canto

USF Tampa Graduate Theses and Dissertations

Quantum computers are presumed to be able to break nearly all public-key encryption algorithms used today. The National Institute of Standards and Technology (NIST) started the process of soliciting and standardizing one or more quantum computer resistant public-key cryptographic algorithms in late 2017. It is estimated that the current and last phase of the standardization process will last till 2022-2024. Among those candidates, code-based and multivariate-based cryptography are a promising solution for thwarting attacks based on quantum computers. Nevertheless, although code-based and multivariate-based cryptography, e.g., McEliece, Niederreiter, and Luov cryptosystems, have good error correction capabilities, research has shown their hardware …

Strategies In Botnet Detection And Privacy Preserving Machine Learning, Di Zhuang

USF Tampa Graduate Theses and Dissertations

Peer-to-peer (P2P) botnets have become one of the major threats in network security for serving as the infrastructure that responsible for various of cyber-crimes. Though a few existing work claimed to detect traditional botnets effectively, the problem of detecting P2P botnets involves more challenges. In this dissertation, we present two P2P botnet detection systems, PeerHunter and Enhanced PeerHunter. PeerHunter starts from a P2P hosts detection component. Then, it uses mutual contacts as the main feature to cluster bots into communities. Finally, it uses community behavior analysis to detect potential botnet communities and further identify bot candidates. Enhanced PeerHunter is an …