Computer Sciences Commons^™

Towards High Performing And Reliable Deep Convolutional Neural Network Models For Typically Limited Medical Imaging Datasets, Kaoutar Ben Ahmed

USF Tampa Graduate Theses and Dissertations

Artificial Intelligence (AI) is “The science and engineering of making intelligent machines, especially intelligent computer programs”. Artificial Intelligence has been applied in a wide range of fields including automobiles, space, robotics, and healthcare.

According to recent reports, AI will have a huge impact on increasing the world economy by 2030 and it's expected that the greatest impact will be in the field of healthcare. The global market size of AI in healthcare was estimated at USD 10.4 billion in 2021 and is expected to grow at a high rate from 2022 to 2030 (CAGR of 38.4%). Applications of AI in …

An Enterprise Risk Management Framework To Design Pro-Ethical Ai Solutions, Quintin P. Mcgrath

USF Tampa Graduate Theses and Dissertations

The effective use of Artificial Intelligence (AI) has immediate business benefits for an organization and its stakeholders through efficiency and quality gains, and the potential to explore and implement new business models. However, there are risks of unintended ethical consequences. Enterprise Risk Management (ERM) focuses on managing risk while maximizing business value from exploiting opportunities. Using applied ethics as a basis and the perspective that ethics includes both enabling human flourishing and not violating accepted norms, I argue that greater business value is achieved when an organization simultaneously targets the maximization of benefits and the minimization of harms for the …

Interdisciplinary Communication By Plausible Analogies: The Case Of Buddhism And Artificial Intelligence, Michael Cooper

USF Tampa Graduate Theses and Dissertations

Communicating interdisciplinary information is difficult, even when two fields are ostensibly discussing the same topic. In this work, I’ll discuss the capacity for analogical reasoning to provide a framework for developing novel judgments utilizing similarities in separate domains. I argue that analogies are best modeled after Paul Bartha’s By Parallel Reasoning, and that they can be used to create a Toulmin-style warrant that expresses a generalization. I argue that these comparisons provide insights into interdisciplinary research. In order to demonstrate this concept, I will demonstrate that fruitful comparisons can be made between Buddhism and Artificial Intelligence research.

Explainable And Cooperative Autonomy Across Networks Of Distributed Systems, Peter Joseph Jorgensen

USF Tampa Graduate Theses and Dissertations

Large networks of complex systems-of-systems are commonplace and evermore present in both mundane and extraordinary facets of human existence. From the exponential growth of connectivity via the internet and other information networks, to the miniaturization of computers and sensors, to cross-domain sensor and communication networks, these networks of distributed systems-of-systems (NDSS) present incredible benefits and challenges. Autonomy is perhaps the most important and most difficult to achieve enabling technology for efficient performance of the NDSS. Giving each individual agent in a network the ability to manage its internal state in dynamic operating environments and in pursuit of multiple complex and …

Securing Critical Cyber Infrastructures And Functionalities Via Machine Learning Empowered Strategies, Tao Hou

USF Tampa Graduate Theses and Dissertations

Machine learning plays a vital role in understanding threats, vulnerabilities, and security policies. In this dissertation, two machine learning empowered approaches on improving the security of critical cyber infrastructures and functionalities will be discussed.

The first work focuses on preventing attacks that use adversarial, active end-to-end topology inference to obtain the topology information of a target network. The topology of a network is fundamental for building network infrastructure functionalities. In many scenarios, enterprise networks may have no desire to disclose their topology information. To this end, we propose a Proactive Topology Obfuscation (ProTO) system that adopts a detect-then-obfuscate framework: (i) …

Video Anomaly Detection: Practical Challenges For Learning Algorithms, Keval Doshi

USF Tampa Graduate Theses and Dissertations

Anomaly detection in surveillance videos is attracting an increasing amount of attention. Despite the competitive performance of several existing methods, they lack theoretical performance analysis, particularly due to the complex deep neural network architectures used in decision making. Additionally, real-time decision making is an important but mostly neglected factor in this domain. Much of the existing methods that claim to be online, depend on batch or offline processing in practice. Furthermore, several critical tasks such as continual learning, model interpretability and cross-domain adaptability are completely neglected in existing works. Motivated by these research gaps, in this dissertation we discuss our …

Data-Driven Design And Analysis Of Next Generation Mobile Networks For Anomaly Detection And Signal Classification With Fast, Robust And Light Machine Learning, Muhammed Furkan Küçük

USF Tampa Graduate Theses and Dissertations

This research focuses on machine (and deep) learning applications (including clustering,anomaly detection and signal classification) for self-organizing and next generation mobile networks in wireless communications. Specifically, this dissertation document will address the three different topics.

First, in the study titled “Performance analysis of neural network topologies and hyperparameters for deep clustering”, we explore the relationship between the clustering performance and network complexity. Deep learning found its initial footing in supervised applications such as image and voice recognition successes of which were followed by deep generative models across similar domains. In recent years, researchers have proposed creative learning representations to utilize …

Computing Group-By And Aggregate In Massively Parallel Systems, Chengcheng Mou

USF Tampa Graduate Theses and Dissertations

The semiconductor industry has mainly exploited two routes for designing microprocessors. The multi-core route aims to speed up the performance of latency-oriented processing. In contrast, the many-thread route concentrates on throughput-oriented improvement of parallel processing. Many-thread microprocessors, such as Graphics Processing Units (GPUs), are leading the computing capability for this past a decade. According to the current hardware market, at the similar price range, the ratio of peak computing power between multi-core CPUs and many-thread GPUs is up to 15X. This large performance gap on data processing has motivated many practitioners in database community to exploit computation-intensive parts on GPU …

Relationships Among The Community Of Inquiry, Achievement Emotions, And Academic Achievement In Asynchronous Online Learning In Higher Education, David H. Tai

USF Tampa Graduate Theses and Dissertations

This research aimed to investigate how achievement emotions predict, mediate, and affect academic achievement in online learning. Online learning has been proliferating, but little is known about how emotion mediates cognition in the Community of Inquiry framework. Recent progress in cognitive neuroscience provided the theoretical foundation for researchers to investigate emotion's role in online learning, especially academic achievement. The researcher of this study adopted a quantitative non-experimental research design to investigate how achievement emotions mediated, predicted, and affected academic achievement in the Community of Inquiry framework. The Partial Least Square Structure Equation Modeling (PLS- SEM) method was adopted for statistical …

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 …

Improving Robustness Of Deep Learning Models And Privacy-Preserving Image Denoising, Hadi Zanddizari

USF Tampa Graduate Theses and Dissertations

Applications of deep learning models and convolutional neural networks have been rapidly increased. Although state-of-the-art CNNs provide high accuracy in many applications, recent investigations show that such networks are highly vulnerable to adversarial attacks. The black-box adversarial attack is one type of attack that the attacker does not have any knowledge about the model or the training dataset, but it has some input data set and theirlabels.

In this chapter, we propose a novel approach to generate a black-box attack in a sparse domain, whereas the most critical information of an image can be observed. Our investigation shows that large …

An Internet Of Medical Things (Iomt) Approach For Remote Assessment Of Head And Neck Cancer Patients, Ruchitha Chinthala

USF Tampa Graduate Theses and Dissertations

Internet-of-Medical-Things (IoMT) allows for a smart healthcare system to remotely monitor and assess patient’s progress at home. Head and neck cancers (HNC) are treated with various treatment options which are associated with significant side effects, mainly shoulder dysfunction, and trismus (spasm of jaw muscles). However, measurement of patient’s progress, and side effects while undergoing treatment, is limited to evaluation received based on scheduled appointments. Development of strategies to enhance monitoring during follow-up period is needed for earlier identification of problems such as trismus and shoulder dysfunction. In this interdisciplinary research, for the first time, we develop an IoMT enabling application, …

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 …

Predicting The Number Of Objects In A Robotic Grasp, Utkarsh Tamrakar

USF Tampa Graduate Theses and Dissertations

Picking up the desired number of objects at once from a pile is still very difficult to dofor a robot. The main challenge is predicting the number of objects in the grasp. This thesis describes several deep-learning-based prediction models that predict the number of objects in the grasp of a Barrett hand using the tactile sensors on its fingers and palm and its joint angles and torque (strain gauge) readings. The deep learning models include various architectures using autoencoders and vision transformers. We evaluated the models with a dataset of grasping 0, 1, 2, 3, and 4 spheres. Then, we …

Developing Reinforcement Learning Algorithms For Robots To Aim And Pour Solid Objects, Haoxuan Li

USF Tampa Graduate Theses and Dissertations

Pouring is one of the most commonly executed tasks in a variety of environments. Thereis less attention paid to pouring solid objects and avoiding spillage. Learning the dynamics for pouring solid objects can be a challenge because the collisions and static frictions between objects make their trajectories less predictable than liquid. Nonetheless, pouring solid objects is an important task in real life. In this work, we propose a solution to help robots aim and pour solid objects. The agents will learn how to interact with the environment and identify the optimal pouring trajectories, then manipulate the arm to aim at …

Pad Beyond The Classroom: Integrating Pad In The Scrum Workplace, Jade S. Weiss

USF Tampa Graduate Theses and Dissertations

Purpose: The “story” format used in Scrum ticket writing is confusing to developers and leadsto insufficient ticket content, which lends to miscommunication between team members and administrators, and disrupts workflow from the bottom up. A burgeoning methodology in Technical Writing, Purpose, Audience, Design (PAD) is an alternative ticket format that is easier to teach developers and improves the aforementioned conditions than the existing “story” format. The goal of this paper is to lay out why and how PAD can benefit developers on smaller Scrum teams who are tasked with writing their own tickets. This paper does not offer solutions for …

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 …

Managing Incomplete Data In The Patient Discharge Summary To Support Correct Hospital Reimbursements, Fadi Naser Eddin

USF Tampa Graduate Theses and Dissertations

The patient discharge summary is a document that conveys the patient's story to other healthcare practitioners, external users, and, most importantly from a financial perspective, health insurers. A defect or incompleteness in the patient's discharge summary will result in delays in the collection process through denial of the entire or partial reimbursement claim or, in the best-case scenario, delay until the discharge summary issue is resolved. The purpose of this project is to address the issue of the incompleteness of discharge summary from the perspective of healthcare providers, with the goal of understanding, diagnosing, and intervening in the research problem. …

Fighting Mass Diffusion Of Fake News On Social Media, Abdallah Musmar

USF Tampa Graduate Theses and Dissertations

Fake news has been considered one of the most challenging problems in the last few years. The effects of spreading fake news over social media platforms are widely observed across the globe as the depth and velocity of fake news reach far more than real news (Vosoughi et al., 2018). The plan for the following dissertation is to investigate the mass spread of fake news across social media and propose a framework to fight the spread of fake news by mixing preventive methods that could hinder the overall percentage of fake news sharing. We plan to create a study on …

Human-Centric Cybersecurity Research: From Trapping The Bad Guys To Helping The Good Ones, Armin Ziaie Tabari

USF Tampa Graduate Theses and Dissertations

The issue of cybersecurity has become much more prevalent over the last few years, with a number of widely publicised incidents, hacking attempts, and data breaches reaching the news. There is no sign of an abatement in the number of cyber incidents, and it would be wise to reconsider the way cybersecurity is viewed and whether a mindset shift is necessary. Cybersecurity, in general, can be seen as primarily a human problem, and it is for this reason that it requires human solutions and tradeoffs. In order to study this problem, using two perspectives; that of the adversaries and that …

Machine Learning For Species Habitat Analysis, Abigail Lavallin

USF Tampa Graduate Theses and Dissertations

Management and conservation initiatives will always be controlled by finite resources, whether financialor temporal. Understanding a species’ spatial ecology, and how its requirements vary across habitats and locations is key to a successful species management plan. During recent decades, it has been noted how many species populations have declined, despite conservation practices working to increase their numbers. The most prevalent impacts affecting fauna populations have come from anthropogenic change in the form of habitat loss and destruction, along with fragmentation, and global climate change. There is a clear need for management practices to now operate on an entire landscape instead …

Multi-Object Localization In Robotic Hand, Tsing Tsow

USF Tampa Graduate Theses and Dissertations

We have developed a machine learning approach to localized objects inside a robotic hand using only images from 2D cameras. Specifically, we used deep learning method (You Only Look Once, YOLO) and Iterative closest Point (ICP) to estimate the 3D coordinates of the objects in a robotic hand. This method will also output the number of objects inside the robotic hand in addition to the coordinates of the objects. We have demonstrated the performance with simulation and obtained typical accuracy within a few pixels (couple mm) and counting accuracy of about 76%. We have also applied it to real images, …

Informing Complexity: The Business Case For Managing Digital Twins Of Complex Process Facilities As A Valuable Asset, William Randell Mcnair

USF Tampa Graduate Theses and Dissertations

The Digital Twins of complex facilities, specifically 3D models created during their design, is a potentially valuable information asset. This three- article dissertation explores the business case for firms in the petrochemical process industry to manage throughout the facility lifecycle. A maturity model is provided to illustrate the stages of digital twin evolution and serves as a tool to help communicate each of the five levels of digital twin maturity achievable in various use cases. An industry analysis reviews existing literature and proposes a model to assess informing or insight value of digital twins from three perspectives. Next, an empirical …

Residential Curbside Recycle Context Analysis, Ntchanang Mpafe

USF Tampa Graduate Theses and Dissertations

Curbside recycling as a preferred mode of residential and municipal sustainability goals seems to have an overwhelming acceptance and adoption in the US. About 69.8 million out of 97.3 million (72%) single-family households in the United States have access to curbside recycling services (State of Curbside Recycling Report, 2020). Collectively, the programs divert about nine million tons of recyclables from landfill disposal each year (Cottom, 2019).

For a design that started in the 1980s in the US, its rapid universal adoption seems to have precluded a concerted effort in examining the coproduced nature (Households: service receptors and Municipalities: service providers) …

Automated Identification Of Stages In Gonotrophic Cycle Of Mosquitoes Using Computer Vision Techniques, Sherzod Kariev

USF Tampa Graduate Theses and Dissertations

In this paper, we design Computer Vision techniques to determine stages in the Gonotrophic cycle of mosquitoes. The dataset for our problem came from 125 adult female mosquitoes - each of which belonged to one of three species - Aedes aegypti, Culex quinquefasciatus, and Anopheles stephensi. The mosquitoes were raised in a lab and passed through all fourGonotrophic stages (Un-fed, Fully-fed, Semi-gravid, and Gravid). At each stage, their images were captured on a plain background via a Xiaomi smartphone, resulting in a dataset of 1784 images. The images were then augmented using standard techniques to generate a larger dataset of …

Using Hyper-Dimensional Spanning Trees To Improve Structure Preservation During Dimensionality Reduction, Curtis Thomas Davis

USF Tampa Graduate Theses and Dissertations

Understanding relations in hyper-dimensional data is a prevalent problem, which is often approached by using dimensionality reduction. The structure preserved from the original data is often dependent on the type of dimension reduction algorithm used, and it can produce results that vary substantially from one another. Visualizing hyper-dimensional data helps to understand the data, but it presents a problem, as our visualizations rely upon two or three-dimensional displays. Current dimension reduction methods, used to reduce hyper-dimensional data to low-dimensional data, often produce results that fail to preserve the structure as the complexity of the data increases. This reduction in dimension …

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 …

Employees Breaking Bad With Technology: An Exploratory Analysis Of Human Factors That Drive Cyberspace Insider Threats, Marcus L. Green

USF Tampa Graduate Theses and Dissertations

As implementation of computer systems has continued to grow in business contexts, employee-driven cyberspace infractions have also grown in number. Employee cyberspace behaviors have continued to have detrimental effects on company computer systems. Actions that violate company cybersecurity policies can be either malicious or unmalicious. Solutions, by and large, have been electronic and centered on hardware and software. Those proposing solutions have begun to shift their focus to human risk vulnerabilities.

This study was novel in that its focus was identification of individual, cultural, and technological risk factors that drive cyberspace insider threat activities. Identifying factors that reduce insider threat …

Managing Health Locus Of Control In Patient-Provider Relationships, James Wallace

USF Tampa Graduate Theses and Dissertations

Patient locus of control is a strong determinant of health outcomes, yet health care professionals do not typically address it in care plans. In fact, management of most medical conditions is hindered because the treating physician has little information about the patient’s locus of control. This research addresses the question “How can locus of control be used to enable health care practitioners to improve medical outcomes?”

Research Methodology. Using an engaged scholarship approach incorporating the Elaborated Action Design Research methodology, the research drives the guided, emergent design of a novel protocol and two separate artifacts for management of health locus …

Human-Centered Cybersecurity Research — Anthropological Findings From Two Longitudinal Studies, Anwesh Tuladhar

USF Tampa Graduate Theses and Dissertations

Cybersecurity is a pressing issue. Researchers have proposed numerous security solutions over the years in order to combat security issues but it is still common to find known, well understood security issues in production environments. In this thesis, I seek to find the underlying reasons to why existing security solutions and best practices are not consistently applied and how to improve the utilization of secure best practices. To this end, I adopt the anthropological research method of long term participant observation and embed myself in real-world settings in order to understand the existence of security issues and the perception of …