Computer Engineering Commons^™

Information Dissemination And Perpetual Network, Harshit Srivastava

USF Tampa Graduate Theses and Dissertations

Social networks have attracted increasing attention from both physical and social scientists. Social networks are essential elements in societies, serving as channels for exchanging various benefits, such as innovation, information, and social support. Moreover, research in social networks helps explain macro-level social phenomena, such as social polarization and social contagion. An understanding of social networks has significant implications, such as improving social welfare and political participation. Modeling social network formation has typically employed game theory or agent-based modeling. These studies typically propose simple and tractable micro-level rules for link formation mechanisms and show that these rules have implications for known …

Towards More Task-Generalized And Explainable Ai Through Psychometrics, Alec Braynen

USF Tampa Graduate Theses and Dissertations

In this work, we propose that adopting the methods, principles, and guidelines of the field of psychometrics can help the Artificial Intelligence (AI) community to build more task-generalizable and explainable AI. Three arguments are presented and explored. These arguments are that psychometrics can help by providing 1) a framework for formulating better datasets, 2) psychometric AI data that can lead to models of generalization in AI, and 3) explainable AI through more informative evaluations.

A review of psychometrics and psychological generalization is performed, along with an overview of evaluation, generalization, and explainability in AI. Various ideas are presented throughout for …

Generative Spatio-Temporal And Multimodal Analysis Of Neonatal Pain, Md Sirajus Salekin

USF Tampa Graduate Theses and Dissertations

Neonates can not express their pain like an adult person. Due to the lacking of proper muscle growth and inability to express non-verbally, it is difficult to understand their emotional status. In addition, if the neonates are under any treatment or left monitored after any major surgeries (post-operative), it is more difficult to understand their pain due to the side effect of medications and the caring system (i.e. intubated, masked face, covered body with blanket, etc.). In a clinical environment, usually, bedside nurses routinely observe the neonate and measure the pain status following any standard clinical pain scale. But current …

Preventing Variadic Function Attacks Through Argument Width Counting, Brennan Ward

USF Tampa Graduate Theses and Dissertations

Format String attacks, first noted in June 2000 [1], are a type of attack in which anadversary has control of the string argument (the format string) passed to a string format function (such as printf). Such control allows the attacker to read and write arbitrary program memory. To prevent these attacks, various methodologies have been proposed, each with their own costs and benefits. I present a novel solution to this problem through argument width counting, ensuring that such format functions cannot access stack memory beyond the space where arguments were placed. Additionally, I show how this approach can be expanded …

Adaptive Multi-Scale Place Cell Representations And Replay For Spatial Navigation And Learning In Autonomous Robots, Pablo Scleidorovich

USF Tampa Graduate Theses and Dissertations

Place cells are one of the most widely studied neurons thought to play a vital role in spatial cognition. Extensive studies show that their activity in the rodent hippocampus is highly correlated with the animal’s spatial location, forming “place fields” of smaller sizes near the dorsal pole and larger sizes near the ventral pole. Despite advances, it is yet unclear how this multi-scale representation enables navigation in complex environments.

In this dissertation, we analyze the place cell representation from a computational point of view, evaluating how multi-scale place fields impact navigation in large and cluttered environments. The objectives are to …

Exploration Of Energy Efficient Computing For Data-Intensive Applications, Md Adnan Zaman

USF Tampa Graduate Theses and Dissertations

The recent surge of data-intensive applications has stretched the performance and energy limit of today’s traditional computing system. The massive amount of data generated by data-intensive applications is not processed at the same speed due to bandwidth mismatch between the faster processing unit and slower memory. Memory access and communication bandwidth can be identified as the primary bottlenecks. Consequently, these two bottlenecks make up most of the total energy consumption. In light of this, we explore energy-efficient computing for data-intensive applications. We examine different aspects of two computing systems, such as in-memory computing and AI-enabled edge computing, more popularly known …

On The Reliability Of Wearable Sensors For Assessing Movement Disorder-Related Gait Quality And Imbalance: A Case Study Of Multiple Sclerosis, Steven Díaz Hernández

USF Tampa Graduate Theses and Dissertations

Approximately 33 million American adults had a movement disorder associated with medication use, ear infections, injury, or neurological disorders in 2008, with over 18 million people affected by neurological disorders worldwide. Physical therapists assist people with movement disorders by providing interventions to reduce pain, improve mobility, avoid surgeries, and prevent falls and secondary complications of neurodegenerative disorders. Current gait assessments used by physical therapists, such as the Multiple Sclerosis Walking Scale, provide only semi-quantitative data, and cannot assess walking quality in detail or describe how one’s walking quality changes over time. As a result, quantitative systems have grownas useful tools …

Analyzing Decision-Making In Robot Soccer For Attacking Behaviors, Justin Rodney

USF Tampa Graduate Theses and Dissertations

In robotics soccer, decision-making is critical to the performance of a team’s SoftwareSystem. The University of South Florida’s (USF) RoboBulls team implements behavior for the robots by using traditional methods such as analytical geometry to path plan and determine whether an action should be taken. In recent works, Machine Learning (ML) and Reinforcement Learning (RL) techniques have been used to calculate the probability of success for a pass or goal, and even train models for performing low-level skills such as traveling towards a ball and shooting it towards the goal[1, 2]. Open-source frameworks have been created for training Reinforcement Learning …

Secure Hardware Constructions For Fault Detection Of Lattice-Based Post-Quantum Cryptosystems, Ausmita Sarker

USF Tampa Graduate Theses and Dissertations

The advent of quantum computers and the exponential speed-up of quantum computation will render classical cryptosystems insecure, as that can solve current encryptions in minutes, resulting in a catastrophic failure of privacy preservation and data security. Through the standardizing of quantum-resistant public-key cryptography algorithms, the National Institute of Standards and Technology (NIST) is evaluating potential candidates to thwart such quantum attacks. In this dissertation, countermeasures against fault attacks are proposed to secure various lattice-based cryptosystems, one of the most promising post-quantum cryptosystems. Fault detection architectures for crucial building blocks of lattice-based cryptosystems, i.e., number-theoretic transform, ring polynomial multiplication, and ring …

Humanoid Robot Motion Control For Ramps And Stairs, Tommy Truong

USF Tampa Graduate Theses and Dissertations

Humanoid robot research and development have been an ongoing effort since the 1900sand can be broken down to two problems. A mechanical problem, getting a humanoid robot to move human-like or a software problem, getting a humanoid robot to behave human-like. These problems of moving and behaving human-like can be often solved using control theory as research advances. For the premise of this research, we explore how to balance and walk on non-flat terrain for the humanoid robot Darwin-Op. Since the focus was on the control theory, the vision control to detect the non-flat terrain was a side objective. The …

Learning State-Dependent Sensor Measurement Models To Improve Robot Localization Accuracy, Troi André Williams

USF Tampa Graduate Theses and Dissertations

This dissertation proposes a novel method called state-dependent sensor measurement models (SDSMMs). Such models dynamically predict the state-dependent bias and uncertainty of sensor measurements, ultimately improving fundamental robot tasks such as localization. In our first investigation, we introduced the state-dependent sensor measurement model framework, described their properties, stated the input and output of these models, and described how to train them. We also explained how to integrate such models with an Extended Kalman Filter and a Particle Filter, two popular robot state estimation algorithms. We validated the proposed framework through a series of localization tasks. The results showed that our …

Trilateration-Based Localization In Known Environments With Object Detection, Valeria M. Salas Pacheco

USF Tampa Graduate Theses and Dissertations

Many strategies for localization have been proposed, the majority of which rely on distance calculations and estimates. The proposed approach is a method that combines image-based single-camera localization techniques and the principle of trilateration to perform localization in a known indoor environment. By using a camera, the proposed system can detect custom objects using object detection in an indoor environment and calculate an approximation of the camera’s position. To recognize the location, previous information such as the size of the environment and the coordinates and sizes of the objects in the environment are given as input to the system together …

Adaptive Mobile Eeg Noise Cancellation Using 2d Convolutional Autoencoders For Bci Authentication, Tyree Lewis

USF Tampa Graduate Theses and Dissertations

Electroencephalography (EEG) signals can be used for many purposes and has the potential to be adapted to various systems. When EEG is recorded from users, these studies are performed primarily in an indoor environment, while the user is stationary. This is due to the levels of noise that are experienced when recording EEG data, to minimize errors in the data. This thesis aims to adapt tasks that are performed indoors to an external environment by removing both noise and artefacts in EEG, using a 2D Convolutional Autoencoder (CAE). The data is recorded from subjects is passed into the 2D CAE …

Secure Vlsi Hardware Design Against Intellectual Property (Ip) Theft And Cryptographic Vulnerabilities, Matthew Dean Lewandowski

USF Tampa Graduate Theses and Dissertations

Over the last two decades or so, VLSI hardware is increasingly subject to sophisticated attacks on both the supply chain and design fronts. There is no explicit trust that the manufacturers/providers are not producing counterfeit designs or that cryptographic algorithms we know to be secure in software are also secure in hardware. The novelty and key contributions of this work are as follows: 1) a continually refined method for Intellectual Property (IP) Protection that provides an approach for verification of IP ownership, 2) demonstrate how to break the PRESENT-80 cryptographic algorithm with significantly limited resources, and 3) provide a multitude …

Data-Oriented Approaches Towards Mobile, Network And Secure Systems, Shangqing Zhao

USF Tampa Graduate Theses and Dissertations

With the rapid evolvement of information science, data-oriented research has solicited a new philosophy for the future mobile network and security design, since it can not only encourage new designs achieving more efficient and reliable networks, but also pose new challenges towards security designs. In this dissertation, we propose four novel data-oriented designs or frameworks to prompt or calibrate the performance with respect to efficiency, reliability, and security.

In the wireless domain, packet corruption and packet collision are two major threats that jeopardize the performance of a mobile network. To cope with the packet corruption, we propose the STAteful inter-Packet …

Interrelation Of Thermal Stimulation With Haptic Perception, Emotion, And Memory, Mehdi Hojatmadani

USF Tampa Graduate Theses and Dissertations

Haptics is an interdisciplinary field of science that deals with how humans perceive and respond to different sensory cues perceived through touch. Thermal haptics as a branch deals with how humans perceive the temperature sensation and respond to that. The process in which thermal perception occurs is well known to researchers. What seems missing in the literature is how temperature interacts or sometimes intervenes in other physiological and psychological aspects of our lives. In this research, a series of studies are presented where the main focus was how temperature and brain interact with each other to impede or enhance our …

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 …

Analysis Of Denial Of Service Attacks In Emerging Software Defined Network Infrastructures, Andrea P. Wright

USF Tampa Graduate Theses and Dissertations

Software defined networking (SDN) improves upon traditional networking protocol technologies by decoupling the data and control planes and moving all control provisioning decisions to a centralized SDN controller entity. This concept has matured over the last decade, having gained strong industry traction, and is now being widely deployed within enterprise and carrier networks to streamline network services provisioning and reduce costs. Overall, centralized control delivers much more cost-effective and flexible networking setups that can support a wide range of customized user-driven network management applications, e.g., traffic engineering, security, survivability, admission control, policy control, etc.

However, the separation of the data …

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 …

Pain Recognition Performance On A Single Board Computer, Iyonna L. Tynes

USF Tampa Graduate Theses and Dissertations

Emotion recognition is a quickly growing field of study due to the increased interest in building systems which can classify and respond to emotions. Recent medical crises, such as the opioid overdose epidemic in the United States and the global COVID-19 pandemic has emphasized the importance of emotion recognition applications is areas like Telehealth services. Considering this, this thesis focuses specifically on pain recognition. The problem of pain recognition is approached from both a hardware and software perspective, as we propose a real-time pain recognition system, from facial images, that is deployed on an NVIDIA Jetson Nano single-board computer. We …

Micro-Architectural Countermeasures For Control Flow And Misspeculation Based Software Attacks, Love Kumar Sah

USF Tampa Graduate Theses and Dissertations

Embedded system applications in diverse sectors such as transportation, healthcare, homeautomation, etc., have been gathering, processing, and transporting data using embedded computers connected to vast networks. As the usage of these embedded devices in daily life is increasing exponentially, security of these devices is a growing concern amongst the users. An alarming rise in recent cyber-attacks has deepened such concern. In the recent past, software-based attacks are more sophisticated and larger in scale than previously known. An embedded processor depends on a compiler to use the architecture efficiently. The compiler generates object code to efficiently utilize the micro-architecture for storage …

Design And Implementation Of Intuitive Human-Robot Teleoperation Interfaces, Lei Wu

USF Tampa Graduate Theses and Dissertations

We have designed and implemented a novel human-robot teleoperation interface based on an intuitive reference frame and hybrid inverse kinematics to perform activities of daily living(ADL) using multiple input devices.

Persons with disabilities often rely on caregivers or family members to assist in their daily living activities. Providing robotic assistants with easy and intuitive user interfaces to assist with ADL can improve their quality of life and lift some of the burdens on caregivers and family members. Current human-robot interface solutions, such as joysticks, Kinect based gesture recognition, and touchscreen-based solutions, including smartphones, are still far from being able to …

Edge Computing For Deep Learning-Based Distributed Real-Time Object Detection On Iot Constrained Platforms At Low Frame Rate, Lakshmikavya Kalyanam

USF Tampa Graduate Theses and Dissertations

In the era of IoT (Internet of Things) and edge computing, there is a rising need for real-time applications in the domain of computer vision. The increase in hardware computing capabilities gave rise to applications of neural networks in various fields. Implementing IoT with neural networks in domains such as image and video recognition has shown promising performance when deployed in complex environments. There is an emerging demand for applications that require data computation in real-time with low latency. In an effort to address these issues, while keeping in mind the computing capabilities of IoT devices, we seek to develop …

Roboat - Rescue Operations Bot Operating In All Terrains, Akshay Gulhane

USF Tampa Graduate Theses and Dissertations

Natural calamities are on a rise with each passing year. Disasters like floods and fire take many lives all around the world, especially in remote areas or less developed countries. One such incident was the Kerala Floods in India where rescue services had difficulty reaching to all the people on time since a huge landmass (more than 9 districts) was flooded and hence villagers or other people risked their lives to save others in danger without proper safety equipment. Amazon Rainforest Fires was another example for a major destruction of an ecosystem. The main reason for lack of facilities in …

Control Of A Human Arm Robotic Unit Using Augmented Reality And Optimized Kinematics, Carlo Canezo

USF Tampa Graduate Theses and Dissertations

There are more than 350000 amputees in the US who suffer loss of functionality in their daily living activities, and roughly 100000 of them are upper arm amputees. Many of these amputees use prostheses to compensate part of their lost arm function, including power prostheses. Research on 6-7 degree of freedom powered prostheses is still relatively new, and most commercially available powered prostheses are typically limited to 1 to 3 degrees of freedom. Due to the myriad of possible options for various powered protheses from different manufacturers, each configuration is governed by a distinct control scheme typically specific to the …

Detecting Symptoms Of Chronic Obstructive Pulmonary Disease And Congestive Heart Failure Via Cough And Wheezing Sounds Using Smart-Phones And Machine Learning, Anthony Windmon

USF Tampa Graduate Theses and Dissertations

Chronic Obstructive Pulmonary Disease (COPD) and Congestive Heart Failure (CHF) are progressive disorders, and major health concerns among today’s aging population. COPD causes a large mucus buildup in the lungs, leading to chronic cough and difficulty to breathe. CHF causes fluid buildup in the lower lungs due to the failing heart, causing cough and difficulty to breath. People who are clinically diagnosed with COPD or CHF are expected to regularly monitor their symptoms and follow complex medical recommendations in an effort to prevent exacerbation. In this dissertation, we elaborate upon three different machine learning based techniques that we developed for …

Machine Learning For The Internet Of Things: Applications, Implementation, And Security, Vishalini Laguduva Ramnath

USF Tampa Graduate Theses and Dissertations

Artificial intelligence and ubiquitous sensor systems have seen tremendous advances in recent times, resulting in groundbreaking impact across domains such as healthcare, entertainment, and transportation through a collective ecosystem called the Internet of Things. The advent of 5G and improved wireless networks will further accelerate the research and development of tools in deep learning, sensor systems, and computing platforms by providing improved network latency and bandwidth. While tremendous progress has been made in the Internet of Things, current work has largely focused on building robust applications that leverage the data collected through ubiquitous sensor nodes to provide actionable rules and …

Relational Joins On Gpus For In-Memory Database Query Processing, Ran Rui

USF Tampa Graduate Theses and Dissertations

Relational join processing is one of the core functionalities in database management systems. Implementing join algorithms on parallel platforms, especially modern GPUs, has gain a lot of momentum in the past decade. This dissertation addresses the following issues on GPU join algorithms. First, we present empirical evaluations of a state-of-the-art work on GPU-based join processing. Since 2008, the compute capabilities of GPUs have increased following a pace faster than that of the multi-core CPUs. We run a comprehensive set of experiments to study how join operations can benefit from such rapid expansion of GPU capabilities. We also present improved GPU …

Managing Off-Grid Power Use For Solar Fueled Residences With Smart Appliances, Prices-To-Devices And Iot, Donnelle L. January

USF Tampa Graduate Theses and Dissertations

Electricity availability has a profound impact in day to day life. Activities such as lighting homes, charging cellphones, and running appliances all depend on electricity use. Around 1 billion people around the world do not have access to electricity, and the majority of these people hail from developing countries in remote areas. Moreover, many of these remote areas lack utility grid access due to the infeasible cost of extending the grid to remote communities. To combat this, various projects on microgrids have been implemented in order to distribute power to these off-grid areas. Nanogrids are defined as “a single domain …