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Articles 1 - 30 of 32
Full-Text Articles in Physical Sciences and Mathematics
Divide-And-Conquer Distributed Learning: Privacy-Preserving Offloading Of Neural Network Computations, Lewis C.L. Brown
Divide-And-Conquer Distributed Learning: Privacy-Preserving Offloading Of Neural Network Computations, Lewis C.L. Brown
Graduate Theses and Dissertations
Machine learning has become a highly utilized technology to perform decision making on high dimensional data. As dataset sizes have become increasingly large so too have the neural networks to learn the complex patterns hidden within. This expansion has continued to the degree that it may be infeasible to train a model from a singular device due to computational or memory limitations of underlying hardware. Purpose built computing clusters for training large models are commonplace while access to networks of heterogeneous devices is still typically more accessible. In addition, with the rise of 5G networks, computation at the edge becoming …
Design And Comparison Of Asynchronous Fft Implementations, Julie Bigot
Design And Comparison Of Asynchronous Fft Implementations, Julie Bigot
Graduate Theses and Dissertations
Fast Fourier Transform (FFT) is a widely used digital signal processing technology in a large variety of applications. For battery-powered embedded systems incorporating FFT, its physical implementation is constrained by strict power consumption, especially during idle periods. Compared to the prevailing clocked synchronous counterpart, quasi-delay insensitive asynchronous circuits offer a series of advantages including flexible timing requirement and lower leakage power, making them ideal choices for these systems. In this thesis work, various FFT configurations were implemented in the low-power Multi-Threshold NULL Convention Logic (MTNCL) paradigm. Analysis illustrates the area and power consumption trends along the changing of the number …
Multivariate Fairness For Paper Selection, Reem Alsaffar
Multivariate Fairness For Paper Selection, Reem Alsaffar
Graduate Theses and Dissertations
Peer review is the process by which publishers select the best publications for inclusion in a journal or a conference. Bias in the peer review process can impact which papers are selected for inclusion in conferences and journals. Although often implicit, race, gender and other demographics can prevent members of underrepresented groups from presenting at major conferences. To try to avoid bias, many conferences use a double-blind review process to increase fairness during reviewing. However, recent studies argue that the bias has not been removed completely. Our research focuses on developing fair algorithms that correct for these biases and select …
Electrical Modeling For Dynamic Performance Prediction And Optimization Of Mcpms Layout, Quang Minh Le
Electrical Modeling For Dynamic Performance Prediction And Optimization Of Mcpms Layout, Quang Minh Le
Graduate Theses and Dissertations
In recent years, the fast development of Multichip Power Modules (MCPM) packaging and Wide Bandgap (WBG) technology has enabled higher voltage and current ratings, better thermal performance, lower parasitic parameters, and higher mechanical reliability. However, the design of the MCPM layout is a multidisciplinary problem leading to many time-consuming analyses and tedious design processes. Because of these challenges, the design automation tool for MCPM layout has become an emerging research area and gained much attention from the power electronics community. The two critical objectives of a design automation tool for MCPM layout are fast and accurate models for design insights …
Movie Reviews Sentiment Analysis Using Bert, Gibson Nkhata
Movie Reviews Sentiment Analysis Using Bert, Gibson Nkhata
Graduate Theses and Dissertations
Sentiment analysis (SA) or opinion mining is analysis of emotions and opinions from texts. It is one of the active research areas in Natural Language Processing (NLP). Various approaches have been deployed in the literature to address the problem. These techniques devise complex and sophisticated frameworks in order to attain optimal accuracy with their focus on polarity classification or binary classification. In this paper, we aim to fine-tune BERT in a simple but robust approach for movie reviews sentiment analysis to provide better accuracy than state-of-the-art (SOTA) methods. We start by conducting sentiment classification for every review, followed by computing …
Data-Driven Deep Learning-Based Analysis On Thz Imaging, Haoyan Liu
Data-Driven Deep Learning-Based Analysis On Thz Imaging, Haoyan Liu
Graduate Theses and Dissertations
Breast cancer affects about 12.5% of women population in the United States. Surgical operations are often needed post diagnosis. Breast conserving surgery can help remove malignant tumors while maximizing the remaining healthy tissues. Due to lacking effective real-time tumor analysis tools and a unified operation standard, re-excision rate could be higher than 30% among breast conserving surgery patients. This results in significant physical, physiological, and financial burdens to those patients. This work designs deep learning-based segmentation algorithms that detect tissue type in excised tissues using pulsed THz technology. This work evaluates the algorithms for tissue type classification task among freshly …
Data-Driven Research On Engineering Design Thinking And Behaviors In Computer-Aided Systems Design: Analysis, Modeling, And Prediction, Molla Hafizur Rahman
Data-Driven Research On Engineering Design Thinking And Behaviors In Computer-Aided Systems Design: Analysis, Modeling, And Prediction, Molla Hafizur Rahman
Graduate Theses and Dissertations
Research on design thinking and design decision-making is vital for discovering and utilizing beneficial design patterns, strategies, and heuristics of human designers in solving engineering design problems. It is also essential for the development of new algorithms embedded with human intelligence and can facilitate human-computer interactions. However, modeling design thinking is challenging because it takes place in the designer’s mind, which is intricate, implicit, and tacit. For an in-depth understanding of design thinking, fine-grained design behavioral data are important because they are the critical link in studying the relationship between design thinking, design decisions, design actions, and design performance. Therefore, …
Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson
Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson
Graduate Theses and Dissertations
This research proposes problems, models, and solutions for the scheduling of space robot on-orbit servicing. We present the Multi-Orbit Routing and Scheduling of Refuellable On-Orbit Servicing Space Robots problem which considers on-orbit servicing across multiple orbits with moving tasks and moving refuelling depots. We formulate a mixed integer linear program model to optimize the routing and scheduling of robot servicers to accomplish on-orbit servicing tasks. We develop and demonstrate flexible algorithms for the creation of the model parameters and associated data sets. Our first algorithm creates the network arcs using orbital mechanics. We have also created a novel way to …
The Effects Of Side-Channel Attacks On Post-Quantum Cryptography: Influencing Frodokem Key Generation Using The Rowhammer Exploit, Michael Jacob Fahr
The Effects Of Side-Channel Attacks On Post-Quantum Cryptography: Influencing Frodokem Key Generation Using The Rowhammer Exploit, Michael Jacob Fahr
Graduate Theses and Dissertations
Modern cryptographic algorithms such as AES and RSA are effectively used for securing data transmission. However, advancements in quantum computing pose a threat to modern cryptography algorithms due to the potential of solving hard mathematical problems faster than conventional computers. Thus, to prepare for quantum computing, NIST has started a competition to standardize quantum-resistant public-key cryptography algorithms. These algorithms are evaluated for strong theoretical security and run-time performance. NIST is in the third round of the competition, and the focus has shifted to analyzing the vulnerabilities to side-channel attacks. One algorithm that has gained notice is the Round 3 alternate …
Constraint-Aware, Scalable, And Efficient Algorithms For Multi-Chip Power Module Layout Optimization, Imam Al Razi
Constraint-Aware, Scalable, And Efficient Algorithms For Multi-Chip Power Module Layout Optimization, Imam Al Razi
Graduate Theses and Dissertations
Moving towards an electrified world requires ultra high-density power converters. Electric vehicles, electrified aerospace, data centers, etc. are just a few fields among wide application areas of power electronic systems, where high-density power converters are essential. As a critical part of these power converters, power semiconductor modules and their layout optimization has been identified as a crucial step in achieving the maximum performance and density for wide bandgap technologies (i.e., GaN and SiC). New packaging technologies are also introduced to produce reliable and efficient multichip power module (MCPM) designs to push the current limits. The complexity of the emerging MCPM …
Effective Knowledge Graph Aggregation For Malware-Related Cybersecurity Text, Phillip Ryan Boudreau
Effective Knowledge Graph Aggregation For Malware-Related Cybersecurity Text, Phillip Ryan Boudreau
Graduate Theses and Dissertations
With the rate at which malware spreads in the modern age, it is extremely important that cyber security analysts are able to extract relevant information pertaining to new and active threats in a timely and effective manner. Having to manually read through articles and blog posts on the internet is time consuming and usually involves sifting through much repeated information. Knowledge graphs, a structured representation of relationship information, are an effective way to visually condense information presented in large amounts of unstructured text for human readers. Thusly, they are useful for sifting through the abundance of cyber security information that …
Deep Learning Applications In Industrial And Systems Engineering, Winthrop Harvey
Deep Learning Applications In Industrial And Systems Engineering, Winthrop Harvey
Graduate Theses and Dissertations
Deep learning - the use of large neural networks to perform machine learning - has transformed the world. As the capabilities of deep models continue to grow, deep learning is becoming an increasingly valuable and practical tool for industrial engineering. With its wide applicability, deep learning can be turned to many industrial engineering tasks, including optimization, heuristic search, and functional approximation. In this dissertation, the major concepts and paradigms of deep learning are reviewed, and three industrial engineering projects applying these methods are described. The first applies a deep convolutional network to the task of absolute aerial geolocalization - the …
Active Learning With Cybersecurity, Carole Shook
Active Learning With Cybersecurity, Carole Shook
TFSC Publications and Presentations
A global campus grant was obtained in Spring 2020 to develop modules for Cybersecurity. This presentation encompasses the use of Cyberciege and case studies that require active learning of students.
Supervised Representation Learning For Improving Prediction Performance In Medical Decision Support Applications, Phawis Thammasorn
Supervised Representation Learning For Improving Prediction Performance In Medical Decision Support Applications, Phawis Thammasorn
Graduate Theses and Dissertations
Machine learning approaches for prediction play an integral role in modern-day decision supports system. An integral part of the process is extracting interest variables or features to describe the input data. Then, the variables are utilized for training machine-learning algorithms to map from the variables to the target output. After the training, the model is validated with either validation or testing data before making predictions with a new dataset. Despite the straightforward workflow, the process relies heavily on good feature representation of data. Engineering suitable representation eases the subsequent actions and copes with many practical issues that potentially prevent the …
Robust And Fair Machine Learning Under Distribution Shift, Wei Du
Robust And Fair Machine Learning Under Distribution Shift, Wei Du
Graduate Theses and Dissertations
Machine learning algorithms have been widely used in real world applications. The development of these techniques has brought huge benefits for many AI-related tasks, such as natural language processing, image classification, video analysis, and so forth. In traditional machine learning algorithms, we usually assume that the training data and test data are independently and identically distributed (iid), indicating that the model learned from the training data can be well applied to the test data with good prediction performance. However, this assumption is quite restrictive because the distribution shift can exist from the training data to the test data in many …
Comparative Study Of Snort 3 And Suricata Intrusion Detection Systems, Cole Hoover
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 …
Gauging The State-Of-The-Art For Foresight Weight Pruning On Neural Networks, Noah James
Gauging The State-Of-The-Art For Foresight Weight Pruning On Neural Networks, Noah James
Computer Science and Computer Engineering Undergraduate Honors Theses
The state-of-the-art for pruning neural networks is ambiguous due to poor experimental practices in the field. Newly developed approaches rarely compare to each other, and when they do, their comparisons are lackluster or contain errors. In the interest of stabilizing the field of pruning, this paper initiates a dive into reproducing prominent pruning algorithms across several architectures and datasets. As a first step towards this goal, this paper shows results for foresight weight pruning across 6 baseline pruning strategies, 5 modern pruning strategies, random pruning, and one legacy method (Optimal Brain Damage). All strategies are evaluated on 3 different architectures …
A Novel Data Lineage Model For Critical Infrastructure And A Solution To A Special Case Of The Temporal Graph Reachability Problem, Ian Moncur
Graduate Theses and Dissertations
Rapid and accurate damage assessment is crucial to minimize downtime in critical infrastructure. Dependency on modern technology requires fast and consistent techniques to prevent damage from spreading while also minimizing the impact of damage on system users. One technique to assist in assessment is data lineage, which involves tracing a history of dependencies for data items. The goal of this thesis is to present one novel model and an algorithm that uses data lineage with the goal of being fast and accurate. In function this model operates as a directed graph, with the vertices being data items and edges representing …
Optimized Damage Assessment And Recovery Through Data Categorization In Critical Infrastructure System., Shruthi Ramakrishnan
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 …
Ransomware And Malware Sandboxing, Byron Denham
Ransomware And Malware Sandboxing, Byron Denham
Computer Science and Computer Engineering Undergraduate Honors Theses
The threat of ransomware that encrypts data on a device and asks for payment to decrypt the data affects individual users, businesses, and vital systems including healthcare. This threat has become increasingly more prevalent in the past few years. To understand ransomware through malware analysis, care must be taken to sandbox the ransomware in an environment that allows for a detailed and comprehensive analysis while also preventing it from being able to further spread. Modern malware often takes measures to detect whether it has been placed into an analysis environment to prevent examination. In this work, several notable pieces of …
A Versatile Python Package For Simulating Dna Nanostructures With Oxdna, Kira Threlfall
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 …
An Investigation Into, And The Construction Of, An Operable Windows Notifier, Grey Hixson
An Investigation Into, And The Construction Of, An Operable Windows Notifier, Grey Hixson
Computer Science and Computer Engineering Undergraduate Honors Theses
The Office of Sustainability at the University of Arkansas identified that building occupants that have control over operable windows may open them at inappropriate times. Windows opened in a building with a temperature and air differential leads to increased HVAC operating costs and building occupant discomfort. This led the Associate Vice Chancellor of Facilities at the University of Arkansas to propose the construction of a mobile application that a building occupant can use to make an informed decision before opening their window. I have formulated a series of research objectives in conjunction with the Director of the Office of Sustainability …
Using Bluetooth Low Energy And E-Ink Displays For Inventory Tracking, David Whelan
Using Bluetooth Low Energy And E-Ink Displays For Inventory Tracking, David Whelan
Computer Science and Computer Engineering Undergraduate Honors Theses
The combination of Bluetooth Low energy and E-Ink displays allow for a low energy wire-less display. The application of this technology is far reaching especially given how the Bluetooth Low Energy specification can be extended. This paper proposes an extension to this specification specifically for inventory tracking. This extension combined with the low energy E-Ink display results in a smart label that can keep track of additional meta data and inventory counts for physical inventory. This label helps track the physical inventory and can help mitigate any errors in the logical organization of inventory.
Side-Channel Analysis On Post-Quantum Cryptography Algorithms, Tristen Teague
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. …
Implementing The Cms+ Sports Rankings Algorithm In A Javafx Environment, Luke Welch
Implementing The Cms+ Sports Rankings Algorithm In A Javafx Environment, Luke Welch
Industrial Engineering Undergraduate Honors Theses
Every year, sports teams and athletes get cut from championship opportunities because of their rank. While this reality is easier to swallow if a team or athlete is distant from the cut, it is much harder when they are right on the edge. Many times, it leaves fans and athletes wondering, “Why wasn’t I ranked higher? What factors when into the ranking? Are the rankings based on opinion alone?” These are fair questions that deserve an answer. Many times, sports rankings are derived from opinion polls. Other times, they are derived from a combination of opinion polls and measured performance. …
Framework Of Hardware Trojan Detection Leveraging Structural Checking Tool, Rafael Dacanay Del Carmen
Framework Of Hardware Trojan Detection Leveraging Structural Checking Tool, Rafael Dacanay Del Carmen
Graduate Theses and Dissertations
Since there is a significant demand for obtaining third-party soft Intellectual Property (IP) by first-party integrated circuit (IC) vendors, it is becoming easier for adversaries to insert malicious logic known as hardware Trojans into designs. Due to this, vendors need to find ways to screen the third-party IPs for possible security threats and then mitigate them. The development of the Structural Checking (SC) tool provides a solution to this issue. This tool analyzes the structure of an unknown soft IP design and creates a network of all the signals within the design and how they are connected to each other. …
Using Ai To Examine Nocturnal Moth Pollination, Conor Moriarty
Using Ai To Examine Nocturnal Moth Pollination, Conor Moriarty
Biological Sciences Undergraduate Honors Theses
The importance of insect-mediated agriculture cannot be understated especially in the wake of pollinator population declines. Most research of insect-mediated pollination is focused on diurnal pollinators like the honeybee (Apis mellifera). Deepening our understanding of how other pollinators, such as nocturnal pollinators, can benefit agriculture and ecosystems will be very important as honeybee populations decline. I explored nocturnal moth interactions with flowering apple flowers during their pollination season to better understand how these nocturnal pollinators interact with the plants. To accomplish this, I used a University of Arkansas farm area with a dedicated apple orchard. I gathered my raw data …
Demonstration Of Cyberattacks And Mitigation Of Vulnerabilities In A Webserver Interface For A Cybersecure Power Router, Benjamin Allen
Demonstration Of Cyberattacks And Mitigation Of Vulnerabilities In A Webserver Interface For A Cybersecure Power Router, Benjamin Allen
Computer Science and Computer Engineering Undergraduate Honors Theses
Cyberattacks are a threat to critical infrastructure, which must be secured against them to ensure continued operation. A defense-in-depth approach is necessary to secure all layers of a smart-grid system and contain the impact of any exploited vulnerabilities. In this undergraduate thesis a webserver interface for smart-grid devices communicating over Modbus TCP was developed and exposed to SQL Injection attacks and Cross-Site Scripting attacks. Analysis was performed on Supply-Chain attacks and a mitigation developed for attacks stemming from compromised Content Delivery Networks. All attempted attacks were unable to exploit vulnerabilities in the webserver due to its use of input sanitization …
Analysis Of Gpu Memory Vulnerabilities, Jarrett Hoover
Analysis Of Gpu Memory Vulnerabilities, Jarrett Hoover
Computer Science and Computer Engineering Undergraduate Honors Theses
Graphics processing units (GPUs) have become a widely used technology for various purposes. While their intended use is accelerating graphics rendering, their parallel computing capabilities have expanded their use into other areas. They are used in computer gaming, deep learning for artificial intelligence and mining cryptocurrencies. Their rise in popularity led to research involving several security aspects, including this paper’s focus, memory vulnerabilities. Research documented many vulnerabilities, including GPUs not implementing address space layout randomization, not zeroing out memory after deallocation, and not initializing newly allocated memory. These vulnerabilities can lead to a victim’s sensitive data being leaked to an …
A Study Of Software Development Methodologies, Kendra Risener
A Study Of Software Development Methodologies, Kendra Risener
Computer Science and Computer Engineering Undergraduate Honors Theses
Software development methodologies are often overlooked by software engineers as aspects of development that are handled by project managers alone. However, if every member of the team better understood the development methodology being used, it increases the likelihood that the method is properly implemented and ultimately used to complete the project more efficiently. Thus, this paper seeks to explore six common methodologies: the Waterfall Model, the Spiral Model, Agile, Scrum, Kanban, and Extreme Programming. These are discussed in two main sections in the paper. In the first section, the frameworks are isolated and viewed by themselves. The histories, unique features, …