A Versatile Python Package For Simulating Dna Nanostructures With Oxdna,
2022
University of Arkansas, Fayetteville
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,
2022
University of Arkansas, Fayetteville
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,
2022
University of Arkansas, Fayetteville
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 …
Improving Intelligent Transportation Safety And Reliability Through Lowering Costs, Integrating Machine Learning, And Studying Model Sensitivity,
2022
Clemson University
Improving Intelligent Transportation Safety And Reliability Through Lowering Costs, Integrating Machine Learning, And Studying Model Sensitivity, Cavender Holt
All Theses
As intelligent transportation becomes increasingly prevalent in the domain of transportation, it is essential to understand the safety, reliability, and performance of these systems. We investigate two primary areas in the problem domain. The first area concerns increasing the feasibility and reducing the cost of deploying pedestrian detection systems to intersections in order to increase safety. By allowing pedestrian detection to be placed in intersections, the data can be better utilized to create systems to prevent accidents from occurring. By employing a dynamic compression scheme for pedestrian detection, we show the reduction of network bandwidth improved by 2.12× over the …
Comparing Actively Managed Mutual Fund Categories To Index Funds Using Linear Regression Forecasting And Portfolio Optimization,
2022
University of Arkansas, Fayetteville
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,
2022
University of Arkansas, Fayetteville
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.,
2022
University of Arkansas, Fayetteville
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,
2022
University of Arkansas, Fayetteville
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 …
The Development Of Tigra: A Zero Latency Interface For Accelerator Communication In Risc-V Processors,
2022
Clemson University
The Development Of Tigra: A Zero Latency Interface For Accelerator Communication In Risc-V Processors, Wesley Brad Green
All Dissertations
Field programmable gate arrays (FPGA) give developers the ability to design application specific hardware by means of software, providing a method of accelerating algorithms with higher power efficiency when compared to CPU or GPU accelerated applications. FPGA accelerated applications tend to follow either a loosely coupled or tightly coupled design. Loosely coupled designs often use OpenCL to utilize the FPGA as an accelerator much like a GPU, which provides a simplifed design flow with the trade-off of increased overhead and latency due to bus communication. Tightly coupled designs modify an existing CPU to introduce instruction set extensions to provide a …
Benchmarking Library Recognition In Tweets,
2022
Singapore Management University
Benchmarking Library Recognition In Tweets, Ting Zhang, Divya Prabha Chandrasekaran, Ferdian Thung, David Lo
Research Collection School Of Computing and Information Systems
Software developers often use social media (such as Twitter) to shareprogramming knowledge such as new tools, sample code snippets,and tips on programming. One of the topics they talk about is thesoftware library. The tweets may contain useful information abouta library. A good understanding of this information, e.g., on thedeveloper’s views regarding a library can be beneficial to weigh thepros and cons of using the library as well as the general sentimentstowards the library. However, it is not trivial to recognize whethera word actually refers to a library or other meanings. For example,a tweet mentioning the word “pandas" may refer to …
Enter The Battleverse: China's Metaverse War,
2022
University of South Florida
Enter The Battleverse: China's Metaverse War, Josh Baughman
Military Cyber Affairs
No abstract provided.
Live Access Control Policy Error Detection Through Hardware,
2022
University of Arkansas, Fayetteville
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 …
Design Of A Tracking Glove For Use In Virtual Reality Training Environments,
2022
Morehead State University
Design Of A Tracking Glove For Use In Virtual Reality Training Environments, Thomas A. Buteyn
Morehead State Theses and Dissertations
A thesis presented to the faculty of the College of Business and Technology at Morehead State University in partial fulfillment of the requirements for the degree Master of Science by Thomas A. Buteyn on April 25, 2022.
Identification Of Return-Oriented Programming Attacks Using Risc-V Instruction Trace Data,
2022
Air Force Research Laboratory
Identification Of Return-Oriented Programming Attacks Using Risc-V Instruction Trace Data, Daniel F. Koranek, Scott R. Graham, Brett J. Borghetti, Wayne C. Henry
Faculty Publications
An increasing number of embedded systems include dedicated neural hardware. To benefit from this specialized hardware, deep learning techniques to discover malware on embedded systems are needed. This effort evaluated candidate machine learning detection techniques for distinguishing exploited from non-exploited RISC-V program behavior using execution traces. We first developed a dataset of execution traces containing Return Oriented Programming (ROP) exploitation on the RISC-V Instruction Set Architecture (ISA) and then developed several deep learning bidirectional Long Short-Term Memory (LSTM) models capable of distinguishing exploited traces from non-exploited traces, each using subsets of features from the execution traces. An objective of this …
A Deep Reinforcement Learning Approach With Prioritized Experience Replay And Importance Factor For Makespan Minimization In Manufacturing,
2022
Louisiana State University and Agricultural and Mechanical College
A Deep Reinforcement Learning Approach With Prioritized Experience Replay And Importance Factor For Makespan Minimization In Manufacturing, Jose Napoleon Martinez
LSU Doctoral Dissertations
In this research, we investigated the application of deep reinforcement learning (DRL) to a common manufacturing scheduling optimization problem, max makespan minimization. In this application, tasks are scheduled to undergo processing in identical processing units (for instance, identical machines, machining centers, or cells). The optimization goal is to assign the jobs to be scheduled to units to minimize the maximum processing time (i.e., makespan) on any unit.
Machine learning methods have the potential to "learn" structures in the distribution of job times that could lead to improved optimization performance and time over traditional optimization methods, as well as to adapt …
Iot Clusters Platform For Data Collection, Analysis, And Visualization Use Case,
2022
Kennesaw State University
Iot Clusters Platform For Data Collection, Analysis, And Visualization Use Case, Soin Abdoul Kassif Baba M Traore
Symposium of Student Scholars
Climate change is happening, and many countries are already facing devastating consequences. Populations worldwide are adapting to the season's unpredictability they relay to lands for agriculture. Our first research was to develop an IoT Clusters Platform for Data Collection, analysis, and visualization. The platform comprises hardware parts with Raspberry Pi and Arduino's clusters connected to multiple sensors. The clusters transmit data collected in real-time to microservices-based servers where the data can be accessed and processed. Our objectives in developing this platform were to create an efficient data collection system, relatively cheap to implement and easy to deploy in any part …
Quadratic Neural Network Architecture As Evaluated Relative To Conventional Neural Network Architecture,
2022
University of South Carolina
Quadratic Neural Network Architecture As Evaluated Relative To Conventional Neural Network Architecture, Reid Taylor
Senior Theses
Current work in the field of deep learning and neural networks revolves around several variations of the same mathematical model for associative learning. These variations, while significant and exceptionally applicable in the real world, fail to push the limits of modern computational prowess. This research does just that: by leveraging high order tensors in place of 2nd order tensors, quadratic neural networks can be developed and can allow for substantially more complex machine learning models which allow for self-interactions of collected and analyzed data. This research shows the theorization and development of mathematical model necessary for such an idea to …
Seabem: An Artificial Intelligence Powered Web Application To Predict Cover Crop Biomass,
2022
University of Nebraska - Lincoln
Seabem: An Artificial Intelligence Powered Web Application To Predict Cover Crop Biomass, Aime Christian Tuyishime, Andrea Basche
Honors Program: Senior Projects (Public)
SEABEM, the Stacked Ensemble Algorithms Biomass Estimator Model, is a web application with a stacked ensemble of Machine Learning (ML) algorithms running on the backend to predict cover crop biomass for locations in Sub-Saharan. The SEABEM model was developed using a previously developed database of crop growth and yield that included site characteristics such as latitude, longitude, soil texture (sand, silt, and clay percentages), temperature, and precipitation. The goal of SEABEM is to provide global farmers, mainly small-scale African farmers, the knowledge they need before practicing and benefiting from cover crops while avoiding the expensive and time-consuming operations that come …
Analyzing Offline Social Engagements: An Empirical Study Of Meetup Events Related To Software Development,
2022
Singapore Management University
Analyzing Offline Social Engagements: An Empirical Study Of Meetup Events Related To Software Development, Abhishek Sharma, Gede Artha Azriadi Prana, Anamika Sawhney, Nachiappan Nagappan, David Lo
Research Collection School Of Computing and Information Systems
Software developers use a variety of social mediachannels and tools in order to keep themselves up to date,collaborate with other developers, and find projects to contributeto. Meetup is one of such social media used by softwaredevelopers to organize community gatherings. We in this work,investigate the dynamics of Meetup groups and events relatedto software development. Our work is different from previouswork as we focus on the actual event and group data that wascollected using Meetup API.In this work, we performed an empirical study of eventsand groups present on Meetup which are related to softwaredevelopment. First, we identified 6,327 Meetup groups related …
Choosing Wearable Internet Of Things Devices For Managing Safety In Construction Using Fuzzy Analytic Hierarchy Process As A Decision Support System,
2022
Marshall University
Choosing Wearable Internet Of Things Devices For Managing Safety In Construction Using Fuzzy Analytic Hierarchy Process As A Decision Support System, Sharique Khalid
Theses, Dissertations and Capstones
Many safety and health risks are faced daily by workers in the field of construction. There is unpredictability and risk embedded in the job and work environment. When compared with other industries, the construction industry has one of the highest numbers of worker injuries, illnesses, fatalities, and near-misses. To eliminate these risky events and make worker performance more predictable, new safety technologies such as the Internet of Things (IoT) and Wearable Sensing Devices (WSD) have been highlighted as effective safety systems. Some of these Wearable Internet of Things (WIoT) and sensory devices are already being used in other industries to …
