Computer Engineering Commons^™

Securing The Void: Assessing The Dynamic Threat Landscape Of Space, Brianna Bace, Dr. Unal Tatar

Military Cyber Affairs

Outer space is a strategic and multifaceted domain that is a crossroads for political, military, and economic interests. From a defense perspective, the U.S. military and intelligence community rely heavily on satellite networks to meet national security objectives and execute military operations and intelligence gathering. This paper examines the evolving threat landscape of the space sector, encompassing natural and man-made perils, emphasizing the rise of cyber threats and the complexity introduced by dual-use technology and commercialization. It also explores the implications for security and resilience, advocating for collaborative efforts among international organizations, governments, and industry to safeguard the space sector.

Commercial Enablers Of China’S Cyber-Intelligence And Information Operations, Ethan Mansour, Victor Mukora

Military Cyber Affairs

In a globally commercialized information environment, China uses evolving commercial enabler networks to position and project its goals. They do this through cyber, intelligence, and information operations. This paper breaks down the types of commercial enablers and how they are used operationally. It will also address the CCP's strategy to gather and influence foreign and domestic populations throughout cyberspace. Finally, we conclude with recommendations for mitigating the influence of PRC commercial enablers.

Human Motion-Inspired Inverse Kinematics Algorithm For A Robotics-Based Human Upper Body Model, Urvish Trivedi

USF Tampa Graduate Theses and Dissertations

The goal of this research is to develop a human motion-inspired inverse kinematics algorithm framework specifically designed for a Robotics-Based Human Upper Body Model (RHUBM). This framework offers solutions to challenges in various fields. In humanoid robotics, the framework addresses the problem of unnatural robot movement by enabling the development of motion planning algorithms that incorporate human-like movements. For prosthetics, the framework tackles the challenge of amputee difficulty in learning and controlling prosthetics by providing a user-friendly interface that predicts and visualizes upper limb movements, enabling learning and practice. In rehabilitation therapy, the framework tackles …

Exploring The Use Of Enhanced Swad Towards Building Learned Models That Generalize Better To Unseen Sources, Brandon M. Weinhofer

USF Tampa Graduate Theses and Dissertations

Deep learning models, typically, take significant time to train. Classifier ensembles are areliable way to increase classifier accuracy and perhaps generalizability to unseen sources of data. These classifiers can be combined with a simple voting scheme. The problem is that having multiple models can very heavily increase training time. Snapshot ensembles have been shown to provide a boost in performance by creating an ensemble of classifiers with different weights during the training of a single deep learned model. This can somewhat solve the problem of the increased training time as you do not have to train separate models. As Machine …

Programmable And Scalable Bit-Sliced Vlsi Architecture For Decision Tree Based Machine Learning Edge Inference, Raaga Sai Somesula

USF Tampa Graduate Theses and Dissertations

As the volume and diversity of Internet-of-Things (IoT) data continues to grow, traditional cloud-based processing methods face significant challenges, including latency, bandwidth constraints, and privacy concerns. Our research focuses on employing decision trees (DTs) as an intelligent filtering mechanism on the edge. Preliminary comparisons across four datasets revealed DTs are significantly more efficient than multilayer perceptrons (MLP), saving 97-98\% in area and power, leading to the selection of DT for our proposed architecture for lightweight IoT devices. We propose a novel programmable and scalable custom application specific integrated circuit (ASIC) architecture designed for Decision Tree based ML inference. Each bit-slice …

Under Pressure: The Soft Robotic Clap-And-Fling Of Cuvierina Atlantica, Daniel Mead

USF Tampa Graduate Theses and Dissertations

Evolution over billions of years has led to unique animals of all types. The tiny sea butterfly is one that remains mostly anonymous because of its size and low place on the food chain, but it is a swimming creature that when examined closely reveals a surprise. Shockingly, it has a swimming motion nearly identical to small insects flying at intermediate Reynolds numbers, referred to as the clap-and-fling. The centimeter long pteropod flapping briskly at 5Hz escapes attention with its size and speed. Modeling the clap-and-fling motion of the sea butterfly at a larger scale allows the benefits and uniqueness …

Finops-Driven Cloud Optimization Models For Enterprise Applications, Manikantha Varaprasad Inakollu

Computer Science and Engineering Faculty Publications

Cloud computing has revolutionized enterprise IT infrastructure, yet escalating costs and resource inefficiencies threaten to undermine these benefits. This research examines FinOps-driven optimization models that enable organizations to balance cloud performance, cost efficiency, and business value. The study addresses the critical challenge enterprises face in managing cloud expenditures while maintaining operational excellence. Through comprehensive analysis of FinOps principles and practical optimization frameworks, we develop models that integrate financial accountability, technical efficiency, and business alignment. Our research demonstrates that organizations implementing structured FinOps practices achieve 25-40% cost reductions without compromising application performance. The study contributes both theoretical frameworks for understanding cloud …

Enhancing Erp Auditability And Compliance Using Permissioned Blockchain, A Framework For Transparent And Immutable Enterprise Resource Planning Systems., Manikantha Varaprasad Inakollu

Computer Science and Engineering Faculty Publications

Enterprise Resource Planning systems serve as the backbone of modern organizational operations, yet their centralized architecture creates significant challenges for auditability and regulatory compliance. This research proposes a permissioned blockchain framework to enhance ERP auditability by creating immutable, transparent, and traceable records of all system transactions and modifications. The study addresses critical gaps in current ERP systems where transaction histories can be altered, audit trails prove insufficient, and compliance verification remains cumbersome. Through examination of existing ERP limitations and blockchain capabilities, we develop an integrated architecture that maintains operational efficiency while providing cryptographic assurance of data integrity. Our framework employs …

Brain-Inspired Spatio-Temporal Learning With Application To Robotics, Thiago André Ferreira Medeiros

USF Tampa Graduate Theses and Dissertations

The human brain still has many mysteries and one of them is how it encodes information. The following study intends to unravel at least one such mechanism. For this it will be demonstrated how a set of specialized neurons may use spatial and temporal information to encode information. These neurons, called Place Cells, become active when the animal enters a place in the environment, allowing it to build a cognitive map of the environment. In a recent paper by Scleidorovich et al. in 2022, it was demonstrated that it was possible to differentiate between two sequences of activations of a …

Machine Learning For Electronic Design Automation: Specification Mining And High-Level Synthesis, Md Rubel Ahmed

USF Tampa Graduate Theses and Dissertations

The rapid growth of complex system-on-chip (SoC) designs has presented unprecedented opportunities and challenges in electronic design automation (EDA). This dissertation explores two facets of electronic design automation: message flow specification mining using data mining and natural language processing (NLP) and high-level synthesis (HLS) acceleration using different machine learning (ML) methods. It also discusses an ML model co-optimization method for energy-efficient hardware implementation.

Effective SoC design validation relies heavily on message flow specifications. This dissertation presents an efficient technique for synthesizing finite state automaton (FSA) models from SoC execution traces. The synthesized models can provide valuable insights into the on-chip …

Deep Learning-Based Automatic Stereology For High- And Low-Magnification Images, Hunter Morera

USF Tampa Graduate Theses and Dissertations

Quantification of the true number of stained cells in specific brain regions is an important metric in many fields of biomedical research involving cell degeneration, cytotoxicology, cellular inflammation, and drug development for a wide range of neurological disorders and mental illnesses. Unbiased stereology is the current state-of-the-art method for collecting the cell count data from tissue sections. These studies require trained experts to manually focus through a z-stack of microscopy images and count (click) on a hundred or more cells per case, making this approach time consuming (~1 hour per case) and prone to human error (i.e., inter-rater variability). Thus, …

Iot Architecture For Enhancing Wayfinding And Accessibility In Smart Cities, Myles Keller

USF Tampa Graduate Theses and Dissertations

This research explores the potential of the Internet of Things (IoT) in enhancing urban wayfinding, particularly for the blind and visually impaired (BVI). Utilizing IoT's multi-layered architecture, smart cities deploy integrated sensors and devices to address urban challenges, with wayfinding as a key focus. While various accessible wayfinding methods have been explored, there exists a gap for more efficient solutions. Within this context, a collision warning system was developed for the BVI, integrated within a broader body sensor network (BSN) framework. Building on this, the study presents AWayNet, an RFID-based network, as a transformative solution. Simulations in the CARLA Simulator …

Analyzing Multi-Robot Leader-Follower Formations In Obstacle-Laden Environments, Zachary J. Hinnen

USF Tampa Graduate Theses and Dissertations

Observations in biological formation from nature likes flocks of birds, herds of mammals and packs of wolves have inspired the innovation of robotic architectures. This thesis presents an approach that aims to use robotic systems to mimic leader-follower behaviors in the navigation and formation of sparse and dense environments. The goal of this work is to extend and further analyze the original work of Weitzenfeld et al [3] to evaluate new swarm and pack based multi-robot architectures with the inclusion of obstacle avoidance and variations in group formations. The multiple robot architecture is based off a wolf pack with a …

Cyber-Physical Multi-Robot Systems In A Smart Factory: A Networked Ai Agents Approach, Zixiang Nie

USF Tampa Graduate Theses and Dissertations

This dissertation focuses on addressing the technical challenges of non-stationarity in smart factories through the use of cyber-physical AI agents. Industry 4.0 and smart manufacturing with smart factories as a central role, have a growing demand for Just-in-Time (JIT) and on-demand production, as well as mass customization—all while maintaining high productivity, resource efficiency and resilience. This research positions Multi-Robot Systems (MRS)-driven smart factories. The heterogeneous production and transportation robots in an MRS collaborate to form multiple real-time adjusted production flows achieving the flexibility to accommodate such on-demand, mass customization.

However, the implementation of MRS introduces new sets of challenges, including …

Enhancing And Securing Wireless Medical Technology For Diagnosis And Treatment Of Lower Urinary Tract Dysfunction, Farhath Zareen

USF Tampa Graduate Theses and Dissertations

Lower urinary tract dysfunction (LUTD) is a debilitating medical condition that affects millions of individuals worldwide. Urodynamics is the current gold standard for diagnosing LUTD but uses non-physiologically fast, retrograde cystometric filling to obtain a brief snapshot of bladder function. Current state-of-the-art research in bladder monitoring includes ambulatory urodynamics using wireless implantable devices to evaluate bladder function during natural filling for long-term monitoring. However, there are various challenges and limitations to this multi-sensor approach. This research focuses on developing frameworks for automated event detection, data analysis, and optimization of long-term bladder recordingsto improve the diagnosis and treatment of LUTD. In …

Optimization Techniques For Machine Learning Inference And Near Memory Image Processing In Hardware For Highly Constrained Iot Edge Nodes, Rajeev Joshi

USF Tampa Graduate Theses and Dissertations

The growing demand for fast and energy-efficient hardware for resource-constrained Internet of Things (IoT) edge devices has highlighted the limitations of conventional computing architectures. This research focuses on addressing the demand for fast, optimized, and energy-efficient machine learning inference engines as well as image processing in IoT edge applications. In this work, we address three challenging research problems and devise efficient solutions. Our investigation involved comprehensive exploration and analysis, leading to the proposal of effective approaches for overcoming these demanding issues. Through our work, we contribute novel solutions that offer improved efficiency and effectiveness in handling these research problems.

First, …

Secure Lightweight Cryptographic Hardware Constructions For Deeply Embedded Systems, Jasmin Kaur

USF Tampa Graduate Theses and Dissertations

Lightweight cryptography plays a vital role in securing resource-constrained deeply-embedded systems such as implantable and wearable medical devices, smart fabrics, smart homes, radio frequency identification tags, sensor networks, and privacy-constrained usage models. The National Institute of Standards and Technology (NIST) initiated a standardization process for lightweight cryptography, a relatively-long multi-year effort, which eventually concluded in February 2023. Side-channel attacks (SCAs) exploit the vulnerabilities of a system by observing and analyzing side-channel information leakages. Fault analysis attacks are a type of active SCAs, where an intelligent adversary injects bit/byte faults into the implementation of a cryptographic cipher to recover the secret …

Enhancing The Safety And Reliability Of Closed-Loop Medical Control Systems, Shakil Mahmud

USF Tampa Graduate Theses and Dissertations

The Internet of Medical Things (IoMT) is a rapidly advancing field that relies heavily on semi- or closed-loop Wearable and Implantable Medical Devices (WIMDs). In recent years, there has been renewed interest in clinical automation, with researchers looking for innovative solutions for Physiological Closed-Loop Control Systems (PCLCS). However, these devices can have various security issues, including vulnerabilities in software and firmware, physical attacks, weak encryption/authentication, and compromised system components. Government agencies, including the US Food and Drug Administration (FDA) and European Medicines Agency (EMA), emphasize the importance of ensuring the safety and reliability of PCLCS since malfunctioning medical devices can …

An Empirical Investigation Of Network Topology On Majority Illusion, Behavior Adoption, And Polarization, Sreeja Sreekantan Nair

USF Tampa Graduate Theses and Dissertations

Social influence plays a significant role in shaping opinions and behaviors both online and inthe physical world. The ways in which we interact with others and the information we receive can significantly influence our beliefs and attitudes towards different issues. While online social media provide platforms for such interactions, the underlying network structure can impact various social influence phenomena, including majority illusion, behavior adoption, and polarization.

This dissertation examines the role of network topology in three social influence processes:majority illusion, behavior adoption, and polarization. The majority illusion refers to a perception bias that occurs when individuals believe that an opinion …

Only Pick Once-Multi-Object Picking Algorithms For Picking Exact Number Of Objects Efficiently, Zihe Ye

USF Tampa Graduate Theses and Dissertations

Picking up multiple objects at once is a grasping skill that makes a human worker efficient in many domains. However, the State of Arts Robot Grasping skill has not developed such ability to compete with human.This paper presents a system to pick a requested number of objects by only picking once (OPO). The proposed Only-Pick-Once System (OPOS) contains several graph-based algorithms that convert the layout of objects into a graph, cluster nodes in the graph, rank and select candidate clusters based on their topology. OPOS also has a multi-object picking predictor based on a convolutional neural network for estimating how …

Insect Classification And Explainability From Image Data Via Deep Learning Techniques, Tanvir Hossain Bhuiyan

USF Tampa Graduate Theses and Dissertations

Since the dawn of the Industrial Revolution, humanity has always tried to make labor more efficient and automated, and this trend is only continuing in the modern digital age. With the advent of artificial intelligence (AI) techniques in the latter part of the 20th century, the speed and scale with which AI has been leveraged to automate tasks defy human imagination. Many people deeply entrenched in the technology field are genuinely intrigued and concerned about how AI may change many of the ways in which humans have been living for millennia. Only time will provide the answers. This dissertation is …

Robot Learning To Pour Solid Objects Accurately, Juan Wilches, Yu Sun

Florida Conference on Recent Advances in Robotics

Pouring is an efficient way to transfer objects from
one container to another. This abstract summarizes a method
to accurately pour solid objects, such as ice cubes. It leverages
visual and proprioceptive feedback together with contextual
information to control the forward and backward rotation of the
pouring container. These feedback signals are fed to a recurrent
neural network that produces the control signal. The proposed
approach can achieve a human-like pouring accuracy in both a
simulation and a real setup.

Multi-Object Grasping -- Stochastic Grasping From A Pile, Tianze Chen, Adheesh Shenoy, Yu Sun

Florida Conference on Recent Advances in Robotics

Grasping multiple objects at once from a pile is common for humans. It makes us efficient in pick and transfer tasks. It is essential for a robot to gain multi-object grasping capability (MOG). This paper defines the multi-object grasping problem and introduces several novel multi-object grasping techniques. These techniques include probability-based pre-grasp potential calculation, a stochastic flexing/extending routine, obtaining end-grasp types, and estimating the number of objects in a grasp. It also proposes a new stochastic grasping strategy for grasping a desired number of objects.

Live Audiovisual Remote Assistance System (Laras) For Person With Visual Impairments, Zachary Frey, Nghia Vo, Varaha Maithreya, Tais Mota, Urvish Trivedi, Redwan Alqasemi, Rajiv Dubey

Florida Conference on Recent Advances in Robotics

According to "The World Report on Vision" by World Health Organization (WHO) [1], there are more than 2.2 billion people who have near or distant vision Impairments, out of which 36 million people are classified as entirely blind. This report also emphasizes the importance of social and communal support in enabling individuals with vision impairments to integrate into society and reach their full potential. While performing daily activities and navigating the environment, people with visual impairments (PVIs) often require direct or synchronous assistance [2]. Consequently, there is a growing need for automated solutions to assist in this regard. However, existing …

Assistive Robotic Platform For Non‐Urgent Household Tasks: A New Design, Amanda Serger, Normandy Tanguilan, Hakki Erhan Sevil

Florida Conference on Recent Advances in Robotics

Humans overcome minor household inconveniences daily without fully recognizing how challenging these tasks could be for individuals such as elderly people or people with disabilities. Those people often times struggle to complete tasks, for instance opening a door or reaching for an item, leading them to rely on caregivers for help. During the COVID-19 pandemic, this caregiver support becomes an unsafe and unreliable solution that can result in a greater risk, thus the need for another solution arises: robotic technology. Recent developments in the robotics field have paved the way for this research, aiming to design a home assistance robot …

Reinforcement Learning And Place Cell Replay In Spatial Navigation, Chance Hamilton, Pablo Scleidorovich Phd, Alfredo Weitzenfeld Phd

Florida Conference on Recent Advances in Robotics

In the last decade, studies have demonstrated that hippocampal place cells influence rats’ navigational learning ability. Moreover, researchers have observed that place cell sequences associated with routes leading to a reward are reactivated during rest periods. This phenomenon is known as Hippocampal Replay, which is thought to aid navigational learning and memory consolidation. These findings in neuroscience have inspired new robot navigation models that emulate the learning process of mammals. This study presents a novel model that encodes path information using place cell connections formed during online navigation. Our model employs these connections to generate sequences of
state-action pairs to …

Biologically Inspired Multi-Robot System Based On Wolf Hunting Behavior, Zachary Hinnen, Chance Hamilton, Alfredo Weitzenfeld

Florida Conference on Recent Advances in Robotics

Studies involving the group predator behavior of wolves have inspired multiple robotic architectures to mimic these biological behaviors in their designs and research. In this work, we aim to use robotic systems to mimic wolf packs' single and group behavior. This work aims to extend the original research by Weitzenfeld et al [7] and evaluate under a new multi-robot robot system architecture. The multiple robot architecture includes a 'Prey' pursued by a wolf pack consisting of an 'Alpha' and 'Beta' robotic group. The Alpha Wolf' will be the group leader, searching and tracking the 'Prey.' At the same time, the …

Programming By Demonstration Using Learning Based Approach: A Mini Review, Atul Acharya, Rajiv Dubey, Redwan Alqasemi

Florida Conference on Recent Advances in Robotics

Wheelchair-mounted robotic arms are used in rehabilitation robotics to help physically impaired people perform ADL (Activity of daily living) tasks. However, the dexterity of manipulation tasks makes the teleoperation of the robotic arm challenging for the user, as it is difficult to control all degrees of freedom with a handheld joystick or a screen touch device. PbD (Programming by demonstration) allows the user to demonstrate the desired behavior and enables the system to learn from the demonstrations and adapt to a new environment. This learned model can perform a new set of actions in a new environment. Learning from a …

Security-Enhanced Serial Communications, John White, Alexander Beall, Joseph Maurio, Dane Fichter, Dr. Matthew Davis, Dr. Zachary Birnbaum

Military Cyber Affairs

Industrial Control Systems (ICS) are widely used by critical infrastructure and are ubiquitous in numerous industries including telecommunications, petrochemical, and manufacturing. ICS are at a high risk of cyber attack given their internet accessibility, inherent lack of security, deployment timelines, and criticality. A unique challenge in ICS security is the prevalence of serial communication buses and other non-TCP/IP communications protocols. The communication protocols used within serial buses often lack authentication and integrity protections, leaving them vulnerable to spoofing and replay attacks. The bandwidth constraints and prevalence of legacy hardware in these systems prevent the use of modern message authentication and …

Enhancing The Battleverse: The People’S Liberation Army’S Digital Twin Strategy, Joshua Baughman

Military Cyber Affairs

No abstract provided.