Computer Sciences Commons^™

The Is Social Continuance Model: Using Conversational Agents To Support Co-Creation, Naif Alawi

USF Tampa Graduate Theses and Dissertations

With the rise of Agentic IS Artifact and the increasing integration of this technology within organizations, our understanding of the impact of this technology on individuals remains limited. Although IS use literature provides important guidance for organization to increase employees’ willingness to work with new technology implementations, the utilitarian view of prior IS use limits its application in light of the new evolving social interaction between humans and Agentic IS Artifacts. To that end, we contribute to the IS use literature by implementing a social view to understand the impact of Agentic IS Artifacts on an individual’s perception and behavior. …

Design, Deployment, And Validation Of Computer Vision Techniques For Societal Scale Applications, Arup Kanti Dey

USF Tampa Graduate Theses and Dissertations

Artificial Intelligence techniques have ensued a significant impact on our daily lives. Numerous applications in so many diverse fields have been made possible by AI algorithms today, and there are many more yet to come. In this dissertation, we design, deploy and validate computer vision algorithms for innovative and high-impact societal scale applications.We specifically focus on two applications in this dissertation: Detection of distracted driving and Detection of breeding habitats of mosquito vectors.

Distracted driving on roads is a major problem around the world. Distracted driving is the case where a driver diverts his/her focus from the road and engages …

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 …

Knowledge Extraction And Inference Based On Visual Understanding Of Cooking Contents, Ahmad Babaeian Babaeian Jelodar

USF Tampa Graduate Theses and Dissertations

In this dissertation, we discuss our work on analyzing cooking content for the ultimate goal ofautomatic robotic manipulation. For a robot to perform a cooking task, it will need to both have an understanding of the scene and utilize prior knowledge. We will explore two main sub-problems: knowledge extraction and inference, and visual understanding of the scene in this dissertation. Visual understanding of a scene, requires algorithms that can visually infer information from a single image or video. Many algorithms in the area of image classification, object detection, or activity recognition can be used in this area. Although great advances …

Designing A Health Coach-Augmented Mhealth System For The Secondary Prevention Of Coronary Heart Disease, Avijit Sengupta

USF Tampa Graduate Theses and Dissertations

This dissertation presents research that employs design science research (DSR) methodology to develop and evaluate a high-fidelity prototype of a home-based cardiac rehabilitation (HBCR) system to support self-management of chronic cardiovascular diseases like coronary heart disease (CHD) and to offer secondary prevention against other chronic diseases with similar risk factors. While the population of coronary heart disease (CHD) patients requiring cardiac rehabilitation (CR) continues to expand, lack of access and other barriers to center based cardiac rehabilitation (CBCR) presents a huge challenge. A mobile phone and wearable device based technological system can offer an HBCR program for CHD. By following …

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 …

Recognizing Patterns From Vital Signs Using Spectrograms, Sidharth Srivatsav Sribhashyam

USF Tampa Graduate Theses and Dissertations

Spectrograms extract frequency components from a signal. Spectrograms have beenin use for a long time mainly to analyze frequency components in audio signals. Typically, these audio signals have a very high sampling rate, various frequency components and high frequency variability with time. Vital signs on other hand have very low sampling rate with no frequency variability. This work explores if spectrograms can be used to analyze and recognize patterns from vital signs signals.

As mentioned above, spectrograms deal with frequencies. More the variability of frequency, better the patterns emerge when spectrograms are applied on the signals. As vital signs lack …

A Constitutive-Based Deep Learning Model For The Identification Of Active Contraction Parameters Of The Left Ventricular Myocardium, Igor Augusto Paschoalotte Nobrega

USF Tampa Graduate Theses and Dissertations

Modern breakthroughs in biomedical engineering, computer science, and data mining have created new opportunities for detecting important mechanical properties of soft tissues that can be employed to identify possible signs of diseases or physiological difficulties. However, the scarcity of different mechanical properties obtained through noninvasive testing emphasizes the importance of incorporating authentic biological data into computer models capable of replicating the behavior of soft tissues.

The field of continuum theory of large deformation hyperactivity permits the formulation of highly descriptive mathematical research and computational models capable of perfectly describing the minute mechanical characteristics of soft materials. By including features about …

Designing Targeted Mobile Advertising Campaigns, Kimia Keshanian

USF Tampa Graduate Theses and Dissertations

With the proliferation of smart, handheld devices, there has been a multifold increase in the ability of firms to target and engage with customers through mobile advertising. Therefore, not surprisingly, mobile advertising campaigns have become an integral aspect of firms’ brand building activities, such as improving the awareness and overall visibility of firms' brands. In addition, retailers are increasingly using mobile advertising for targeted promotional activities that increase in-store visits and eventual sales conversions. However, in recent years, mobile or in general online advertising campaigns have been facing one major challenge and one major threat that can negatively impact the …

Montage Music Videos: Racial Utopianism Vs. Abstract Cowboys And The Question Of Cultural Montage, Alan E. Blanchard

USF Tampa Graduate Theses and Dissertations

Along with the explosion of consumer goods in America over the past century came the human impulse to alter these objects to produce new meanings the manufacturers never intended: commercial products become amateur artists’ raw material. We see this with custom cars and the curious blending of clothes. Inevitably, digital commercial products, like music videos, would undergo a similar treatment as seen in DJ Cummerbund’s “mashup” videos “Old Staind Road” and “Blurry in the USA” where he is painting with audio tracks and sculpting with video clips to create new digital art with new meanings uncoupled from industry’s original intent …

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, …

Optimization And Machine Learning Methods For Solving Combinatorial Problems In Urban Transportation, Aigerim Bogyrbayeva

USF Tampa Graduate Theses and Dissertations

This dissertation investigates three applications of emerging technologies for urban trans- portation. In the first chapter, we design a new market for fractional ownership of au- tonomous vehicles (AVs), in which an AV is co-leased by a group of individuals. We present a practical iterative auction based on the combinatorial clock auction to match the interested customers together and determine their payments. In designing such an auction, we con- sider continuous-time items (time slots) which are defined by bidders, and naturally exploit driverless mobility of AVs to form co-leasing groups. To relieve the computational burdens of both bidders and the …

Affectivetda: Using Topological Data Analysis To Improve Analysis And Explainability In Affective Computing, Hamza Elhamdadi

USF Tampa Graduate Theses and Dissertations

We present an approach utilizing Topological Data Analysis to study the structure of face poses used in affective computing, i.e., the process of recognizing human emotion. The approach uses conditional comparison of different emotions, both respective and irrespective of time, with multiple topological distance metrics, dimension reduction techniques, and face subsections (e.g., eyes, nose, mouth, etc.). The results confirm that our topology-based approach captures known patterns, distinctions between emotions, and distinctions between individuals, which is an important step towards more robust and explainable emotion recognition by machines.

Turkic Interlingua: A Case Study Of Machine Translation In Low-Resource Languages, Jamshidbek Mirzakhalov

USF Tampa Graduate Theses and Dissertations

Machine Translation (MT) has the potential to bridge the gap between the developed world and the marginalized communities by making information more accessible in real-time. While there are over 7000 spoken languages in the world, only about a hundred have access to high-quality MT systems and even fewer enjoy the benefits of more advanced language technologies. Unfortunately, resource scarcity and the lack of digital infrastructure are only some of the many challenges associated with globalizing NLP. Many large-scale multilingual studies and datasets often get little to no feedback from native speakers or linguistic experts of the languages involved, leading to …

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 …

Analysis Of Contextual Emotions Using Multimodal Data, Saurabh Hinduja

USF Tampa Graduate Theses and Dissertations

Affective computing builds and evaluates systems that can recognize, interpret, and simulate human emotion. It is an interdisciplinary field, which includes computer science, psychology, and many others. For years, human emotion has been studied in psychology but recently has become a prominent field in computer science. Largely, the field of affective computing has been focused on analyzing static facial expressions to recognize human emotions, without taking bias (e.g. gender, data bias), context, or temporal information into account. Psychology has shown the difficulty of analyzing emotions without incorporating this type of information. In this dissertation, we have proposed new approaches to …

Efficient Post-Quantum And Compact Cryptographic Constructions For The Internet Of Things, Rouzbeh Behnia

USF Tampa Graduate Theses and Dissertations

IoT systems often rely on low-end devices to send measurements to other parties and depending on the setting, unauthorized alteration and/or privacy violation of these measures can have catastrophic consequences (e.g., embedded medical sensors). Therefore, providing efficient authentication, integrity, and confidentiality in these settings is vital. While conventional cryptographic measures (e.g., ECDSA) can be used to meet these security requirements, despite their elegant design, they are often too computationally expensive for low-end devices. This is further exacerbated when security against quantum computers is taken into the account.

In this dissertation, we propose a series of new efficient conventional and post-quantum …

Automatic Detection Of Vehicles In Satellite Images For Economic Monitoring, Cole Hill

USF Tampa Graduate Theses and Dissertations

With the growing supply of satellites capturing images of the planet, governments andinvestors are looking for ways in which these new images may be used to determine which businesses are struggling and thriving. Recent works have shown that parking lot fill rates can provide valuable information about businesses’ earnings, however, the task of manually annotating the number of vehicles in a parking lot is expensive and time-consuming. Systems which can automate this process are therefore valuable as they are faster and cheaper than human labor. In this thesis, the problem of detection of small objects in large low-resolution images is …

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 …

A Comparative Study Of Male And Female Undergraduate Computer Science Students’ Educational Pathways, Stephanie Fitzsimmons

USF Tampa Graduate Theses and Dissertations

Science, Technology, Engineering and Mathematics (STEM), including Computer Science (CS) are fields that are in great demand globally. This study’s purpose was to explore the nature of the educational pathways, critical factors and commonalities/differences leading to CS undergraduate enrollment through the male and female perspectives focusing on personal/home, academic/attitude and psychological factors underlying the Social Cognitive Career Theory factors. Purposive sampling method was used for this multi-case study, comprised of CS undergraduate upperclassman. Participants shared their perspectives on their CS educational pathway via three interviews and journals. Thematic analysis of narrative for both individual and cumulative group analysis, plus researcher …

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 …

Recognizing Emotion In The Wild Using Multimodal Data, Shivam Srivastava

USF Tampa Graduate Theses and Dissertations

In this work, I will present our approach of using multi-modal data for recognizing human emotion and behavior in the wild. The study is divided into four tasks: group emotion recognition, driver gaze prediction, student engagement prediction, and emotion recognition using physiological signals. We explore multiple approaches including classical machine learning tools such as random forests, state-of-the-art deep neural networks, and multiple fusion and ensemble-based approaches. We also show that similar approaches can be used across tracks as many of the features generalize well to the different problems (e.g. facial features).

Exploring The Use Of Neural Transformers For Psycholinguistics, Antonio Laverghetta Jr.

USF Tampa Graduate Theses and Dissertations

Deep learning has the potential to help solve numerous problems in cognitive science andeducation, by providing us a way to model the cognitive profiles of individual people. If this were possible, it would allow us to design targeted tests and suggest specific remediation based on each individual’s needs. On the flip side, employing techniques from psychology can give us insight into the underlying skillsets neural networks have acquired during training, addressing the interpretability concern. This thesis explores these ideas in the context of transformer language models, which have achieved state-of-the-art results on virtually every natural language processing (NLP) task. First, …

Countermeasures Against Various Network Attacks Using Machine Learning Methods, Yi Li

USF Tampa Graduate Theses and Dissertations

With the rapid development of a computer network, our lives are already inseparable from it. Wireless Fidelity (Wi-Fi) is in use everywhere; more and more devices are connected to the Internet, and many companies and individuals tend to store their data and information online. Furthermore, it is now very convenient to communicate with each other through email and text messages. However, widespread networks also provide more attack surfaces for attackers. There are a variety of network attacks aimed at information theft. To better defend against those network attacks, one needs to have a broad knowledge of existing attacks. In this …

System Support Of Concurrent Database Query Processing On A Gpu, Hao Li

USF Tampa Graduate Theses and Dissertations

The unrivaled computing capabilities of modern GPUs meet the demand of processing massive amounts of data seen in many application domains. While traditional HPC systems support applications as standalone entities that occupy the entire GPU, we propose a GPU-based DBMS (G-DBMS) that can run multiple tasks concurrently. To that end, system-level management mechanisms like resource allocation and buffer manager are needed to build such a concurrent database query processing system and fully unleash the GPUs’ computing power. However, CUDA does not provide enough OS-level functionalities to support it. Thus our research is focusing on implementing the optimization of resource allocation …

Discrete Models And Algorithms For Analyzing Dna Rearrangements, Jasper Braun

USF Tampa Graduate Theses and Dissertations

In this work, language and tools are introduced, which model many-to-many mappings that comprise DNA rearrangements in nature. Existing theoretical models and data processing methods depend on the premise that DNA segments in the rearrangement precursor are in a clear one-to-one correspondence with their destinations in the recombined product. However, ambiguities in the rearrangement maps obtained from the ciliate species Oxytricha trifallax violate this assumption demonstrating a necessity for the adaptation of theory and practice.

In order to take into account the ambiguities in the rearrangement maps, generalizations of existing recombination models are proposed. Edges in an ordered graph model …

Multimodal Data Fusion And Attack Detection In Recommender Systems, Mehmet Aktukmak

USF Tampa Graduate Theses and Dissertations

The commercial platforms that use recommender systems can collect relevant information to produce useful recommendations to the platform users. However, these sources usually contain missing values, imbalanced and heterogeneous data, and noisy observations. Such characteristics render the process of exploiting the information nontrivial, as one should carefully address them during the data fusion process. In addition to the degenerative characteristics, some entries can be fake, i.e., they can be the outcomes of malicious intents to manipulate the system. These entries should be eliminated before incorporation to any recommendation task. Detecting such malicious attacks quickly and accurately and then mitigating them …

Unifying Security Policy Enforcement: Theory And Practice, Shamaria Engram

USF Tampa Graduate Theses and Dissertations

Security policies stipulate restrictions on the behaviors of systems to prevent themfrom behaving in harmful ways. One way to ensure that systems satisfy the constraints of a security policy is through the use of security enforcement mechanisms. To understand the fundamental limitations of such mechanisms, formal methods are employed to prove properties and reason about their behaviors. The particular formalism employed, however, typically depends on the time at which a mechanism operates.

Mechanisms operating before a program's execution are static mechanisms, and mechanisms operating during a program's execution are dynamic mechanisms. Static mechanisms are fundamentally limited in the types of …

Digital Identity: A Human-Centered Risk Awareness Study, Toufic N. Chebib

USF Tampa Graduate Theses and Dissertations

Cybersecurity threats and compromises have been at the epicenter of media attention; their risk and effect on people’s digital identity is something not to be taken lightly. Though cyber threats have affected a great number of people in all age groups, this study focuses on 55 to 75-year-olds, as this age group is close to retirement or already retired. Therefore, a notable compromise impacting their digital identity can have a major impact on their life.

To help guide this study, the following research question was formulated, “What are the risk perceptions of individuals, between the ages of 55 and 75 …

The Efficiency And Accuracy Of Yolo For Neonate Face Detection In The Clinical Setting, Jacqueline Hausmann

USF Tampa Graduate Theses and Dissertations

There are many face detection classification models available for download and use in the modern technological world. Based in the field of deep neural networks, these off-the-shelf solutions are generally inadequate to solve real world challenges. This work presents how current approaches biased towards detecting adult human faces must be modified in order to better accommodate face detection of the neonate in a NICU setting.

YOLO is a powerful object detection algorithm. Due to optimizations such as Cross mini-batch Normalization, Modified Spatial Attention Modules, Modified Path Aggregation Networks, Self-Adversarial Training, Mosaic Data Augmentation, DropBox Regularization, Multi-Input Weighted Residual Connections and …