Computer and Systems Architecture Commons^™

Uav-Based Sensor Integration For In-Situ Lake Water Quality Monitoring, Alec R. Campbell

Biological and Agricultural Engineering Undergraduate Honors Theses

Surface water monitoring is often constrained by limited spatial and temporal coverage due to the labor-intensive nature of traditional sampling methods, particularly in environments that are difficult to access or pose safety risks. Unmanned aerial vehicles (UAVs) offer a promising solution by enabling more frequent, spatially distributed, and cost-effective data collection. This study presented the design, development, and field evaluation of a UAV-based system for real-time, in-situ water quality monitoring. The system integrated multiple sensors, including oxidation-reduction potential (ORP), RGB spectrometry, pH, electrical conductivity (EC), dissolved oxygen (DO), and a multispectral spectrometer within a UAV platform.

Field testing was conducted …

Design Considerations Of A Gpu, Nicholas M. Devilliers

Electrical Engineering and Computer Science Undergraduate Honors Theses

With the current era of AI technology, the era of single instruction multiple data has become an increasingly viable solution to accelerate training. The problem is that while software to use GPUs and other hardware accelerators, designing GPUs and ASIC devices has become increasingly more expensive and there aren’t great examples of generic GPUs that anyone can use and modify. In this thesis, there are four design considerations that will be discussed and how they affect the result of a generic GPU. The four considerations that were talked about in the thesis are, word width, arithmetic type, number of stages, …

Leveraging P4 Programmable-Hardware Switches For In-Network Pmu Packet Recovery, Evan Michael Bonar

Electrical Engineering and Computer Science Undergraduate Honors Theses

Phasor Measurement Unit (PMU) systems are essential for real-time power grid monitor- ing but often face data loss due to network delays, equipment malfunctions, or transmis- sion errors. Traditional centralized recovery solutions introduce significant latency and scalability challenges. This thesis presents a P4-based in-network recovery mechanism that embeds detection and recovery directly into the data plane of P4-enabled programmable switches, significantly reducing recovery time and infrastructure complexity. Using the Aurora 610 switch, the system detects missing packets via sequence number analysis and recovers magnitudes with an efficient register-based algorithm.

Evaluation demonstrates high accuracy and low latency, achieving a mean absolute …

Remodel-Fpga: Reconfigurable Memory-Centric Array Processor Architecture For Deep-Learning Acceleration On Fpga, Md Arafat Kabir

Graduate Theses and Dissertations

Deep-Learning has become a dominant computing paradigm across a broad range of application domains. Different architectures of Deep-Networks like CNN, MLP, and RNN have emerged as the prominent machine-learning approaches for today’s application domains. These architectures are heavily data-dependent, requiring frequent access to memory. As a result, these applications suffer the most from the memory bottleneck of the von Neumann architectures. There is an imminent need for memory-centric architectures for deep-learning and big-data analytic applications that are memory intensive. Modern Field Programmable Gate Arrays (FPGAs) are ideal programmable substrates for creating customized Processor in/near Memory (PIM) accelerators. Modern FPGAs contain …

Towards Side-Channel Infrastructure For Software Implementations Of Pqc Algorithms, Tristen Teague

Graduate Theses and Dissertations

Post-Quantum Cryptography (PQC) is a new class of asymmetric cryptography algorithms that are supposed to be secure against both classical computers and quantum computers through Shor’s algorithm. Since PQC algorithms are currently being standardized, they will replace older standardized asymmetric algorithms (such as RSA) and will be deployed within the digital infrastructure. Before implementations of the PQC algorithms are placed into the infrastructure, they must undergo evaluation of both performance and security. One such security issue that needs large investigation before deployment are side-channels. Side-channel attacks (SCA) are a method of gathering information from the implementation, such as power-consumption and …

Hardware Trojan Detection Utilizing Graph Neural Networks And Structural Checking, Hunter Nauman

Graduate Theses and Dissertations

The integrated circuit (IC) industry has experienced exponential growth, particularly in the complexity and scale of hardware designs. To sustain this growth, faster development cycles and cost-effective solutions have been the focus for many companies. One strategy to maintain this growth is through the incorporation of third-party intellectual property (IP) into the IC design process. Outsourcing the production of sub-components reduces development time and enables faster time-to-market, however, this approach also introduces the threat of Hardware Trojans. Hardware Trojans, defined as any malicious modification or addition to an IC, pose significant security risks due to their small size, low activation …

Cybersecurity In Critical Infrastructure Systems: Emulated Protection Relay, Mitchell Bylak

Computer Science and Computer Engineering Undergraduate Honors Theses

Cyber-attacks on Critical Systems Infrastructure have been steadily increasing across the world as the capabilities of and reliance on technology have grown throughout the 21st century, and despite the influx of new cybersecurity practices and technologies, the industry faces challenges in its cooperation between the government that regulates law practices and the private sector that owns and operates critical infrastructure and security, which has directly led to an absence of eas- ily accessible information and learning resources on cybersecurity for use in public environments and educational settings. This honors research thesis addresses these challenges by submitting the development of an …

Deep Learning Frameworks For Accelerated Magnetic Resonance Image Reconstruction Without Ground Truths, Ibsa Kumara Jalata

Graduate Theses and Dissertations

Magnetic Resonance Imaging (MRI) is typically a slow process because of its sequential data acquisition. To speed up this process, MR acquisition is often accelerated by undersampling k-space signals and solving an ill-posed problem through a constrained optimization process. Image reconstruction from under-sampled data is posed as an inverse problem in traditional model-based learning paradigms. While traditional methods use image priors as constraints, modern deep learning methods use supervised learning with ground truth images to learn image features and priors. However, in some cases, ground truth images are not available, making supervised learning impractical. Recent data-centric learning frameworks such as …

Trojan Detection Expansion Of Structural Checking, Zachary Chapman

Graduate Theses and Dissertations

With the growth of the integrated circuit (IC) market, there has also been a rise in demand for third-party soft intellectual properties (IPs). However, the growing use of such Ips makes it easier for adversaries to hide malicious code, like hardware Trojans, into these designs. Unlike software Trojan detection, hardware Trojan detection is still an active research area. One proposed approach to this problem is the Structural Checking tool, which can detect hardware Trojans using two methodologies. The first method is a matching process, which takes an unknown design and attempts to determine if it might contain a Trojan by …

Towards Multi-Modal Interpretable Video Understanding, Quang Sang Truong

Graduate Theses and Dissertations

This thesis introduces an innovative approach to video comprehension, which simulates human perceptual mechanisms and establishes a comprehensible and coherent narrative representation of video content. At the core of this approach lies the creation of a Visual-Linguistic (VL) feature for an interpretable video portrayal and an adaptive attention mechanism (AAM) aimed at concentrating solely on principal actors or pertinent objects while modeling their interconnections. Taking cues from the way humans disassemble scenes into visual and non-visual constituents, the proposed VL feature characterizes a scene via three distinct modalities: (i) a global visual environment, providing a broad contextual comprehension of the …

Svar: A Virtual Machine For Portable Code On Reconfigurable Accelerators, Nathaniel Fredricks

Computer Science and Computer Engineering Undergraduate Honors Theses

The SPAR-2 array processor was designed as an overlay architecture for implementation on Xilinx Field Programmable Gate Arrays (FPGAs). As an overlay, the SPAR-2 array processor can be configured to take advantage of the specific resources available on different FPGAs. However once configured, the SPAR-2 requires programmer’s to have knowledge of the low level architecture, and write platform-specific code. In this thesis SVAR, a hardware/software co-designed virtual machine, is proposed that runs on the SPAR-2. SVAR allows programmers to write portable, platform-independent code once and have it interpreted for any specific configuration. Results are presented that verify the virtual machine …

Reverse Engineering Post-Quantum Cryptography Schemes To Find Rowhammer Exploits, Sam Lefforge

Computer Science and Computer Engineering Undergraduate Honors Theses

Post-quantum cryptography is a necessary countermeasure to protect against attacks from quantum computer. However, the post-quantum cryptography schemes are potentially vulnerable to side channel attacks. One such method of attacking involves creating bit-flips in victim memory through a process called Rowhammer. These attacks can vary in nature, but can involve rowhammering bits to raise the encryption scheme's decryption failure rate, or modifying the scheme's random seed. With a high enough decryption failure rate, it becomes feasible to generate sufficient information about the secret key to perform a key recovery attack. This thesis proposed two attacks on proposed post-quantum cryptography algorithms, …

Digital Simulations Of Memristors Towards Integration With Reconfigurable Computing, Ivris Raymond

Computer Science and Computer Engineering Undergraduate Honors Theses

The end of Moore’s Law has been predicted for decades. Demand for increased parallel computational performance has been increased by improvements in machine learning. This past decade has demonstrated the ever-increasing creativity and effort necessary to extract scaling improvements in CMOS fabrication processes. However, CMOS scaling is nearing its fundamental physical limits. A viable path for increasing performance is to break the von Neumann bottleneck. In-memory computing using emerging memory technologies (e.g. ReRam, STT, MRAM) offers a potential path beyond the end of Moore’s Law. However, there is currently very little support from industry tools for designers wishing to incorporate …

A Memory-Centric Customizable Domain-Specific Fpga Overlay For Accelerating Machine Learning Applications, Atiyehsadat Panahi

Graduate Theses and Dissertations

Low latency inferencing is of paramount importance to a wide range of real time and userfacing Machine Learning (ML) applications. Field Programmable Gate Arrays (FPGAs) offer unique advantages in delivering low latency as well as energy efficient accelertors for low latency inferencing. Unfortunately, creating machine learning accelerators in FPGAs is not easy, requiring the use of vendor specific CAD tools and low level digital and hardware microarchitecture design knowledge that the majority of ML researchers do not possess. The continued refinement of High Level Synthesis (HLS) tools can reduce but not eliminate the need for hardware-specific design knowledge. The designs …

A Versatile Python Package For Simulating Dna Nanostructures With Oxdna, Kira Threlfall

Computer Science and Computer Engineering Undergraduate Honors Theses

The ability to synthesize custom DNA molecules has led to the feasibility of DNA nanotechnology. Synthesis is time-consuming and expensive, so simulations of proposed DNA designs are necessary. Open-source simulators, such as oxDNA, are available but often difficult to configure and interface with. Packages such as oxdna-tile-binding pro- vide an interface for oxDNA which allows for the ability to create scripts that automate the configuration process. This project works to improve the scripts in oxdna-tile-binding to improve integration with job scheduling systems commonly used in high-performance computing environments, improve ease-of-use and consistency within the scripts compos- ing oxdna-tile-binding, and move …

Side-Channel Analysis On Post-Quantum Cryptography Algorithms, Tristen Teague

Computer Science and Computer Engineering Undergraduate Honors Theses

The advancements of quantum computers brings us closer to the threat of our current asymmetric cryptography algorithms being broken by Shor's Algorithm. NIST proposed a standardization effort in creating a new class of asymmetric cryptography named Post-Quantum Cryptography (PQC). These new algorithms will be resistant against both classical computers and sufficiently powerful quantum computers. Although the new algorithms seem mathematically secure, they can possibly be broken by a class of attacks known as side-channels attacks (SCA). Side-channel attacks involve exploiting the hardware that the algorithm runs on to figure out secret values that could break the security of the system. …

Comparative Study Of Snort 3 And Suricata Intrusion Detection Systems, Cole Hoover

Computer Science and Computer Engineering Undergraduate Honors Theses

Network Intrusion Detection Systems (NIDS) are one layer of defense that can be used to protect a network from cyber-attacks. They monitor a network for any malicious activity and send alerts if suspicious traffic is detected. Two of the most common open-source NIDS are Snort and Suricata. Snort was first released in 1999 and became the industry standard. The one major drawback of Snort has been its single-threaded architecture. Because of this, Suricata was released in 2009 and uses a multithreaded architecture. Snort released Snort 3 last year with major improvements from earlier versions, including implementing a new multithreaded architecture …

Comparing Actively Managed Mutual Fund Categories To Index Funds Using Linear Regression Forecasting And Portfolio Optimization, Luke Weiner

Industrial Engineering Undergraduate Honors Theses

The global investment industry offers a wide variety of investment products especially for individual investors. One such product, index funds, which are younger than actively managed mutual funds, have typically outperformed managed funds. Despite this phenomenon, investors have displayed a tendency to continue investing in actively managed funds. Although only a small percentage of actively managed funds outperform index funds, the costs of actively managed funds are significantly higher. Also, managed fund performances are most often determined by their fund category such as growth or real estate. I wanted to answer the following question for individual investors: can we …

Structural Checking Tool Restructure And Matching Improvements, Derek Taylor

Graduate Theses and Dissertations

With the rising complexity and size of hardware designs, saving development time and cost by employing third-party intellectual property (IP) into various first-party designs has become a necessity. However, using third-party IPs introduces the risk of adding malicious behavior to the design, including hardware Trojans. Different from software Trojan detection, the detection of hardware Trojans in an efficient and cost-effective manner is an ongoing area of study and has significant complexities depending on the development stage where Trojan detection is leveraged. Therefore, this thesis research proposes improvements to various components of the soft IP analysis methodology utilized by the Structural …

Optimized Damage Assessment And Recovery Through Data Categorization In Critical Infrastructure System., Shruthi Ramakrishnan

Graduate Theses and Dissertations

Critical infrastructures (CI) play a vital role in majority of the fields and sectors worldwide. It contributes a lot towards the economy of nations and towards the wellbeing of the society. They are highly coupled, interconnected and their interdependencies make them more complex systems. Thus, when a damage occurs in a CI system, its complex interdependencies make it get subjected to cascading effects which propagates faster from one infrastructure to another resulting in wide service degradations which in turn causes economic and societal effects. The propagation of cascading effects of disruptive events could be handled efficiently if the assessment and …

Modeling Damage Spread, Assessment, And Recovery Of Critical Systems, Justin Burns

Graduate Theses and Dissertations

Critical infrastructure systems have recently become more vulnerable to attacks on their data systems through internet connectivity. If an attacker is successful in breaching a system’s defenses, it is imperative that operations are restored to the system as quickly as possible. This thesis focuses on damage assessment and recovery following an attack. A literature review is first conducted on work done in both database protection and critical infrastructure protection, then the thesis defines how damage affects the relationships between data and software. Then, the thesis proposes a model using a graph construction to show the cascading affects within a system …

Live Access Control Policy Error Detection Through Hardware, Bryce Mendenhall

Graduate Theses and Dissertations

Access Control (AC) is a widely used security measure designed to protect resources and infrastructure in an information system. The integrity of the AC policy is crucial to the protection of the system. Errors within an AC policy may cause many vulnerabilities such as information leaks, information loss, and malicious activities. Thus, such errors must be detected and promptly fixed. However, current AC error detection models do not allow for real-time error detection, nor do they provide the source of errors. This thesis presents a live error detection model called LogicDetect which utilizes emulated Boolean digital logic circuits to provide …

Contrastive Learning For Unsupervised Auditory Texture Models, Christina Trexler

Computer Science and Computer Engineering Undergraduate Honors Theses

Sounds with a high level of stationarity, also known as sound textures, have perceptually relevant features which can be captured by stimulus-computable models. This makes texture-like sounds, such as those made by rain, wind, and fire, an appealing test case for understanding the underlying mechanisms of auditory recognition. Previous auditory texture models typically measured statistics from auditory filter bank representations, and the statistics they used were somewhat ad-hoc, hand-engineered through a process of trial and error. Here, we investigate whether a better auditory texture representation can be obtained via contrastive learning, taking advantage of the stationarity of auditory textures to …

Automated Report Based System To Encourage A Greener Commute To Campus, Ronald Velasquez

Computer Science and Computer Engineering Undergraduate Honors Theses

This project consists of the design and implementation of a tool to encourage greener commutes to the University of Arkansas. Trends in commuting of the last few years show a decline in not so environment-friendly commute modes. Nevertheless, ensuring that this trend continues is vital to assure a significant impact. The created tool is an automated report system. The report displays information about different commute options. A Google form allows users to submit report requests, and a web app allows the sustainability office to process them in batches. This system was built in the Apps Script platform. It implements several …

An Automated Method To Enrich Consumer Health Vocabularies Using Glove Word Embeddings And An Auxiliary Lexical Resource, Mohammed Ibrahim, Susan Gauch, Omar Salman, Mohammed Alqahtani

Computer Science and Computer Engineering Faculty Publications and Presentations

Background

Clear language makes communication easier between any two parties. A layman may have difficulty communicating with a professional due to not understanding the specialized terms common to the domain. In healthcare, it is rare to find a layman knowledgeable in medical terminology which can lead to poor understanding of their condition and/or treatment. To bridge this gap, several professional vocabularies and ontologies have been created to map laymen medical terms to professional medical terms and vice versa.

Objective

Many of the presented vocabularies are built manually or semi-automatically requiring large investments of time and human effort and consequently the …

Computational Frameworks For Multi-Robot Cooperative 3d Printing And Planning, Laxmi Prasad Poudel

Graduate Theses and Dissertations

This dissertation proposes a novel cooperative 3D printing (C3DP) approach for multi-robot additive manufacturing (AM) and presents scheduling and planning strategies that enable multi-robot cooperation in the manufacturing environment. C3DP is the first step towards achieving the overarching goal of swarm manufacturing (SM). SM is a paradigm for distributed manufacturing that envisions networks of micro-factories, each of which employs thousands of mobile robots that can manufacture different products on demand. SM breaks down the complicated supply chain used to deliver a product from a large production facility from one part of the world to another. Instead, it establishes a network …

Signal Processing And Data Analysis For Real-Time Intermodal Freight Classification Through A Multimodal Sensor System., Enrique J. Sanchez Headley

Graduate Theses and Dissertations

Identifying freight patterns in transit is a common need among commercial and municipal entities. For example, the allocation of resources among Departments of Transportation is often predicated on an understanding of freight patterns along major highways. There exist multiple sensor systems to detect and count vehicles at areas of interest. Many of these sensors are limited in their ability to detect more specific features of vehicles in traffic or are unable to perform well in adverse weather conditions. Despite this limitation, to date there is little comparative analysis among Laser Imaging and Detection and Ranging (LIDAR) sensors for freight detection …

Promoting Diversity In Academic Research Communities Through Multivariate Expert Recommendation, Omar Salman

Graduate Theses and Dissertations

Expert recommendation is the process of identifying individuals who have the appropriate knowledge and skills to achieve a specific task. It has been widely used in the educational environment mainly in the hiring process, paper-reviewer assignment, and assembling conference program committees. In this research, we highlight the problem of diversity and fair representation of underrepresented groups in expertise recommendation, factors that current expertise recommendation systems rarely consider. We introduce a novel way to model experts in academia by considering demographic attributes in addition to skills. We use the h-index score to quantify skills for a researcher and we identify five …

Development Of A Reference Design For Intrusion Detection Using Neural Networks For A Smart Inverter, Ammar Mohammad Khan

Graduate Theses and Dissertations

The purpose of this thesis is to develop a reference design for a base level implementation of an intrusion detection module using artificial neural networks that is deployed onto an inverter and runs on live data for cybersecurity purposes, leveraging the latest deep learning algorithms and tools. Cybersecurity in the smart grid industry focuses on maintaining optimal standards of security in the system and a key component of this is being able to detect cyberattacks. Although researchers and engineers aim to design such devices with embedded security, attacks can and do still occur. The foundation for eventually mitigating these attacks …

Low-Power And Reconfigurable Asynchronous Asic Design Implementing Recurrent Neural Networks, Spencer Nelson

Graduate Theses and Dissertations

Artificial intelligence (AI) has experienced a tremendous surge in recent years, resulting in high demand for a wide array of implementations of algorithms in the field. With the rise of Internet-of-Things devices, the need for artificial intelligence algorithms implemented in hardware with tight design restrictions has become even more prevalent. In terms of low power and area, ASIC implementations have the best case. However, these implementations suffer from high non-recurring engineering costs, long time-to-market, and a complete lack of flexibility, which significantly hurts their appeal in an environment where time-to-market is so critical. The time-to-market gap can be shortened through …