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Deep Weakly-Supervised Anomaly Detection, Guansong Pang, Chunhua Shen, Huidong Jin, Anton Van Den Hengel Aug 2023

Deep Weakly-Supervised Anomaly Detection, Guansong Pang, Chunhua Shen, Huidong Jin, Anton Van Den Hengel

Research Collection School Of Computing and Information Systems

Recent semi-supervised anomaly detection methods that are trained using small labeled anomaly examples and large unlabeled data (mostly normal data) have shown largely improved performance over unsupervised methods. However, these methods often focus on fitting abnormalities illustrated by the given anomaly examples only (i.e., seen anomalies), and consequently they fail to generalize to those that are not, i.e., new types/classes of anomaly unseen during training. To detect both seen and unseen anomalies, we introduce a novel deep weakly-supervised approach, namely Pairwise Relation prediction Network (PReNet), that learns pairwise relation features and anomaly scores by predicting the relation of any two …

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Ai For Connectivism Learning: Undergraduate Students’ Experiences Of Chatgpt In Advanced Programming Courses, Swapna Gottipati, Kyong Jin Shim, Venky Shankararaman Aug 2023

Ai For Connectivism Learning: Undergraduate Students’ Experiences Of Chatgpt In Advanced Programming Courses, Swapna Gottipati, Kyong Jin Shim, Venky Shankararaman

Research Collection School Of Computing and Information Systems

Advanced programming skills are required for computing courses on merging topics, and students often struggle to develop these skills to solve complex problems. To address this challenge, faculty members provide additional lectures, practice sessions, and educational technology tools. This paper discusses the challenges faced by computer science students in developing advanced programming skills and explores the use of AI chatbots, specifically ChatGPT, as a support tool for learning. We study the engagement and effectiveness of ChatGPT in helping students learn advanced programming skills using two engagement learning frameworks (CIE and MELT) for evaluation. The study involves designing a computing lab …

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Sulfur Cycling Connects Microbiomes And Biogeochemistry In Deep-Sea Hydrothermal Plumes, Zhichao Zhou, Patricia Q. Tran, Alyssa M. Adams, Kristopher Kieft, John A. Breier, Caroline S. Fortunato, Cody S. Sheik, Julie A. Huber, Meng Li, Gregory J. Dick, Karthik Anantharaman Aug 2023

Sulfur Cycling Connects Microbiomes And Biogeochemistry In Deep-Sea Hydrothermal Plumes, Zhichao Zhou, Patricia Q. Tran, Alyssa M. Adams, Kristopher Kieft, John A. Breier, Caroline S. Fortunato, Cody S. Sheik, Julie A. Huber, Meng Li, Gregory J. Dick, Karthik Anantharaman

School of Earth, Environmental, & Marine Sciences Faculty Publications

In globally distributed deep-sea hydrothermal vent plumes, microbiomes are shaped by the redox energy landscapes created by reduced hydrothermal vent fluids mixing with oxidized seawater. Plumes can disperse over thousands of kilometers and their characteristics are determined by geochemical sources from vents, e.g., hydrothermal inputs, nutrients, and trace metals. However, the impacts of plume biogeochemistry on the oceans are poorly constrained due to a lack of integrated understanding of microbiomes, population genetics, and geochemistry. Here, we use microbial genomes to understand links between biogeography, evolution, and metabolic connectivity, and elucidate their impacts on biogeochemical cycling in the deep sea. Using …

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Spatial Mapping Of The Dna Adducts In Cancer, Kimiko L Krieger, Elise K Mann, Kevin J Lee, Elyse Bolterstein, Deborah Jebakumar, Michael M Ittmann, Valeria L Dal Zotto, Mohamed Shaban, Arun Sreekumar, Natalie R Gassman Aug 2023

Spatial Mapping Of The Dna Adducts In Cancer, Kimiko L Krieger, Elise K Mann, Kevin J Lee, Elyse Bolterstein, Deborah Jebakumar, Michael M Ittmann, Valeria L Dal Zotto, Mohamed Shaban, Arun Sreekumar, Natalie R Gassman

Faculty, Staff and Students Publications

DNA adducts and strand breaks are induced by various exogenous and endogenous agents. Accumulation of DNA damage is implicated in many disease processes, including cancer, aging, and neurodegeneration. The continuous acquisition of DNA damage from exogenous and endogenous stressors coupled with defects in DNA repair pathways contribute to the accumulation of DNA damage within the genome and genomic instability. While mutational burden offers some insight into the level of DNA damage a cell may have experienced and subsequently repaired, it does not quantify DNA adducts and strand breaks. Mutational burden also infers the identity of the DNA damage. With advances …

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Enabling Affordances Of Blockchain In Agri-Food Supply Chains: A Value-Driver Framework Using The Q-Methodology, Pouyan Jahanbin, Stephen C. Wingreen, Ravishankar Sharma, Behrang Ijadi, Marlon M. Reis Aug 2023

Enabling Affordances Of Blockchain In Agri-Food Supply Chains: A Value-Driver Framework Using The Q-Methodology, Pouyan Jahanbin, Stephen C. Wingreen, Ravishankar Sharma, Behrang Ijadi, Marlon M. Reis

All Works

The application of blockchain beyond cryptocurrencies has received increasing attention from industry and scholars alike. Given predicted looming food crises, some of the most impactful deployments of blockchains are likely to concern food supply chains. This study outlined how blockchain adoption can result in positive affordances in the food supply chain. Using Q methodology, this study explored the current status of the agri-food supply chain and how blockchain technology could be useful in addressing existing challenges. This theorization leads to the proposition of the 3TIC value-driver framework for determining the enabling affordances of blockchain that would increase shared value for …

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Dual Ni/Co-Hemin Metal-Organic Framework-Prgo For High-Performance Asymmetric Hybrid Supercapacitor, Kimia Zarean Mousaabadi, Ali A. Ensafi, Erfan Naghsh, Jin-Song Hu, Behzad Rezaei Aug 2023

Dual Ni/Co-Hemin Metal-Organic Framework-Prgo For High-Performance Asymmetric Hybrid Supercapacitor, Kimia Zarean Mousaabadi, Ali A. Ensafi, Erfan Naghsh, Jin-Song Hu, Behzad Rezaei

Chemistry & Biochemistry Faculty Publications and Presentations

In this study, we conducted direct synthesis of a dual metal–organic framework (Ni/Co-Hemin MOF) on phosphorous-doped reduced graphene oxide (PrGO) to serve as an active material in high-performance asymmetrical supercapacitors. The nanocomposite was utilized as an active material in supercapacitors, exhibiting a noteworthy specific capacitance of 963 C g−1 at 1.0 A g−1, along with a high rate capability of 68.3% upon increasing the current density by 20 times, and superior cycling stability. Our comprehensive characterization and control experiments indicated that the improved performance can be attributed to the combined effect of the dual MOF and the …

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Geometric Morphometric Analysis Of Modern Viperid Vertebrae Facilitates Identification Of Fossil Specimens, Lance D. Jessee Aug 2023

Geometric Morphometric Analysis Of Modern Viperid Vertebrae Facilitates Identification Of Fossil Specimens, Lance D. Jessee

Electronic Theses and Dissertations

Snake vertebrae are common in the fossil record, whereas cranial remains are generally fragile and rare. Consequently, vertebrae are the most commonly studied fossil element of snakes. However, identification of snake vertebrae can be problematic due to extensive variation. This study utilizes 2-D geometric morphometrics and canonical variates analysis to 1) reveal variation between genera and species and 2) classify vertebrae of modern and fossil eastern North American Agkistrodon and Crotalus. The results show that vertebrae of Agkistrodon and Crotalus can reliably be classified to genus and species using these methods. Based on the statistical analyses, four of the …

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Extraction, Purification, And Characterization Of Potential Bioactive Compounds Produced By Janthinobacterium Lividum Tajx1901, Andy Elorm Agbakpo Aug 2023

Extraction, Purification, And Characterization Of Potential Bioactive Compounds Produced By Janthinobacterium Lividum Tajx1901, Andy Elorm Agbakpo

Electronic Theses and Dissertations

Underexplored environments such as soil samples continue to be an untapped source of bacterial strains with great potential to produce secondary metabolites for medicinal applications. As a result, these microorganisms represent a broad and yet unknown reservoir of new strains capable of producing these novel compounds. The current research primarily seeks to perform the isolation, purification, and characterization of secondary metabolites from a soil bacterium (Janthinobacterium lividum TAJX1901). The isolated soil bacterium was successfully cultured on rich media agar plates, followed by extraction using methanol and chloroform. The purification methods utilized include flash column chromatography, preparative thin-layer chromatography, and …

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Isolation And Structural Determination Of Bioactive Metabolites From The Soil Bacterium, Arthrobacter Sp. Tajx1902, Amonah Arije Aug 2023

Isolation And Structural Determination Of Bioactive Metabolites From The Soil Bacterium, Arthrobacter Sp. Tajx1902, Amonah Arije

Electronic Theses and Dissertations

As antimicrobial resistance persistently disrupts the treatment of microbial infection, natural product chemistry has played a significant role in identifying novel drugs with novel modes of action critical to getting ahead of resistance. The primary goal of this project is to extract and identify potential novel antimicrobial natural products produced by Arthrobacter sp. Although underexplored, Arthrobacter sps. have been known to produce bioactive compounds with versatility; one such is a depsipeptide with quorum-sensing inhibitory activity.1 In this research, an Arthrobacter sp. TAJX1902, isolated from a soil sample, showed inhibitory activity against a filamentous indicator bacterium and a violacein-producing Janthinobacterium …

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Real-Time, Deep-Learning Aided Lensless Microscope, Jimin Wu, Vivek Boominathan, Ashok Veeraraghavan, Jacob T Robinson Aug 2023

Real-Time, Deep-Learning Aided Lensless Microscope, Jimin Wu, Vivek Boominathan, Ashok Veeraraghavan, Jacob T Robinson

Faculty, Staff and Students Publications

Traditional miniaturized fluorescence microscopes are critical tools for modern biology. Invariably, they struggle to simultaneously image with a high spatial resolution and a large field of view (FOV). Lensless microscopes offer a solution to this limitation. However, real-time visualization of samples is not possible with lensless imaging, as image reconstruction can take minutes to complete. This poses a challenge for usability, as real-time visualization is a crucial feature that assists users in identifying and locating the imaging target. The issue is particularly pronounced in lensless microscopes that operate at close imaging distances. Imaging at close distances requires shift-varying deconvolution to …

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Next-Generation Nanopore Sensors Based On Conductive Pulse Sensing For Enhanced Detection Of Nanoparticles, Samuel Confederat, Seungheon Lee, Derr Vang, Dimitrios Soulias, Fabio Marcuccio, Timotheus I. Peace, Martin Andrew Edwards, Pietro Strobbia, Devleena Samanta, Christoph Wälti, Paolo Actis Aug 2023

Next-Generation Nanopore Sensors Based On Conductive Pulse Sensing For Enhanced Detection Of Nanoparticles, Samuel Confederat, Seungheon Lee, Derr Vang, Dimitrios Soulias, Fabio Marcuccio, Timotheus I. Peace, Martin Andrew Edwards, Pietro Strobbia, Devleena Samanta, Christoph Wälti, Paolo Actis

Chemistry & Biochemistry Faculty Publications and Presentations

Nanopore sensing has been successfully used to characterize biological molecules with single-molecule resolution based on the resistive pulse sensing approach. However, its use in nanoparticle characterization has been constrained by the need to tailor the nanopore aperture size to the size of the analyte, precluding the analysis of heterogeneous samples. Additionally, nanopore sensors often require the use of high salt concentrations to improve the signal-to-noise ratio, which further limits their ability to study a wide range of nanoparticles that are unstable at high ionic strength. Here, a new paradigm in nanopore research that takes advantage of a polymer electrolyte system …

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Exploring The Impact Of Study Abroad On Students’ Intercultural Competence: The Case Of Myanmar, Cherry Kyaw San, Khin Mar Htwe Aug 2023

Exploring The Impact Of Study Abroad On Students’ Intercultural Competence: The Case Of Myanmar, Cherry Kyaw San, Khin Mar Htwe

Journal of Comparative & International Higher Education

No abstract provided.

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Generalization Through Diversity: Improving Unsupervised Environment Design, Wenjun Li, Pradeep Varakantham, Dexun Li Aug 2023

Generalization Through Diversity: Improving Unsupervised Environment Design, Wenjun Li, Pradeep Varakantham, Dexun Li

Research Collection School Of Computing and Information Systems

Agent decision making using Reinforcement Learning (RL) heavily relies on either a model or simulator of the environment (e.g., moving in an 8x8 maze with three rooms, playing Chess on an 8x8 board). Due to this dependence, small changes in the environment (e.g., positions of obstacles in the maze, size of the board) can severely affect the effectiveness of the policy learned by the agent. To that end, existing work has proposed training RL agents on an adaptive curriculum of environments (generated automatically) to improve performance on out-of-distribution (OOD) test scenarios. Specifically, existing research has employed the potential for the …

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Camper: An Effective Framework For Privacy-Aware Deep Entity Resolution, Yuxiang Guo, Lu Chen, Zhengjie Zhou, Baihua Zheng, Ziquan Fang, Zhikun Zhang, Yuren Mao, Yunjun Gao Aug 2023

Camper: An Effective Framework For Privacy-Aware Deep Entity Resolution, Yuxiang Guo, Lu Chen, Zhengjie Zhou, Baihua Zheng, Ziquan Fang, Zhikun Zhang, Yuren Mao, Yunjun Gao

Research Collection School Of Computing and Information Systems

Entity Resolution (ER) is a fundamental problem in data preparation. Standard deep ER methods have achieved state-of-the-art efectiveness, assuming that relations from diferent organizations are centrally stored. However, due to privacy concerns, it can be difcult to centralize data in practice, rendering standard deep ER solutions inapplicable. Despite eforts to develop rule-based privacy-preserving ER methods, they often neglect subtle matching mechanisms and have poor efectiveness as a result. To bridge efectiveness and privacy, in this paper, we propose CampER, an efective framework for privacy-aware deep entity resolution. Specifcally, we frst design a training pair self-generation strategy to overcome the absence …

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Crowdfl: Privacy-Preserving Mobile Crowdsensing System Via Federated Learning, Bowen Zhao, Ximeng Liu, Wei-Neng Chen, Robert H. Deng Aug 2023

Crowdfl: Privacy-Preserving Mobile Crowdsensing System Via Federated Learning, Bowen Zhao, Ximeng Liu, Wei-Neng Chen, Robert H. Deng

Research Collection School Of Computing and Information Systems

As an emerging sensing data collection paradigm, mobile crowdsensing (MCS) enjoys good scalability and low deployment cost but raises privacy concerns. In this paper, we propose a privacy-preserving MCS system called CROWDFL by seamlessly integrating federated learning (FL) into MCS. At a high level, in order to protect participants' privacy and fully explore participants' computing power, participants in CROWDFL locally process sensing data via FL paradigm and only upload encrypted training models to the server. To this end, we design a secure aggregation algorithm (SecAgg) through the threshold Paillier cryptosystem to aggregate training models in an encrypted form. Also, to …

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Fintech Data Infrastructure For Esg Disclosure Compliance, Randall E. Duran, Peter Tierney Aug 2023

Fintech Data Infrastructure For Esg Disclosure Compliance, Randall E. Duran, Peter Tierney

Research Collection School Of Computing and Information Systems

Regulations related to the disclosure of environmental, governance, and social (ESG) factors are evolving rapidly and are a major concern for financial compliance worldwide. Information technology has the potential to reduce the effort and cost of ESG disclosure compliance. However, comprehensive and accurate ESG data are necessary for disclosures. Currently, the availability and quality of underlying data for ESG disclosures vary widely and are often deficient. The process involved with obtaining ESG data is also often inefficient and prone to error. This paper compares the models used and the evolution of Fintech data infrastructure developed to support financial services with …

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Document-Level Relation Extraction Via Separate Relation Representation And Logical Reasoning, Heyan Huang, Changsen Yuan, Qian Liu, Yixin Cao Aug 2023

Document-Level Relation Extraction Via Separate Relation Representation And Logical Reasoning, Heyan Huang, Changsen Yuan, Qian Liu, Yixin Cao

Research Collection School Of Computing and Information Systems

Document-level relation extraction (RE) extends the identification of entity/mentions’ relation from the single sentence to the long document. It is more realistic and poses new challenges to relation representation and reasoning skills. In this article, we propose a novel model, SRLR, using Separate Relation Representation and Logical Reasoning considering the indirect relation representation and complex reasoning of evidence sentence problems. Specifically, we first expand the judgment of relational facts from the entity-level to the mention-level, highlighting fine-grained information to capture the relation representation for the entity pair. Second, we propose a logical reasoning module to identify evidence sentences and conduct …

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Context-Aware Event Forecasting Via Graph Disentanglement, Yunshan Ma, Chenchen Ye, Zijian Wu, Xiang Wang, Yixin Cao, Tat-Seng Chua Aug 2023

Context-Aware Event Forecasting Via Graph Disentanglement, Yunshan Ma, Chenchen Ye, Zijian Wu, Xiang Wang, Yixin Cao, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Event forecasting has been a demanding and challenging task throughout the entire human history. It plays a pivotal role in crisis alarming and disaster prevention in various aspects of the whole society. The task of event forecasting aims to model the relational and temporal patterns based on historical events and makes forecasting to what will happen in the future. Most existing studies on event forecasting formulate it as a problem of link prediction on temporal event graphs. However, such pure structured formulation suffers from two main limitations: 1) most events fall into general and high-level types in the event ontology, …

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Grasp Based Metaheuristic To Solve The Mixed Fleet E-Waste Collection Route Planning Problem, Aldy Gunawan, Dang V.A. Nguyen, Pham K.M. Nguyen, Pieter. Vansteenwegen Aug 2023

Grasp Based Metaheuristic To Solve The Mixed Fleet E-Waste Collection Route Planning Problem, Aldy Gunawan, Dang V.A. Nguyen, Pham K.M. Nguyen, Pieter. Vansteenwegen

Research Collection School Of Computing and Information Systems

The digital economy has brought significant advancements in electronic devices, increasing convenience and comfort in people’s lives. However, this progress has also led to a shorter life cycle for these devices due to rapid advancements in hardware and software technology. As a result, e-waste collection and recycling have become vital for protecting the environment and people’s health. From the operations research perspective, the e-waste collection problem can be modeled as the Heterogeneous Vehicle Routing Problem with Multiple Time Windows (HVRP-MTW). This study proposes a metaheuristic based on the Greedy Randomized Adaptive Search Procedure complemented by Path Relinking (GRASP-PR) to solve …

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The 4th International Workshop On Talent And Management Computing (Tmc'2023): Editorial, Hengshu Zhu, Hui Xiong, Yong Ge, Ee-Peng Lim Aug 2023

The 4th International Workshop On Talent And Management Computing (Tmc'2023): Editorial, Hengshu Zhu, Hui Xiong, Yong Ge, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

In today's competitive and fast-evolving business environment, it is a critical time for organizations to rethink how to deal with the talent and management related tasks in a quantitative manner. Indeed, thanks to the era of big data, the availability of large-scale talent data provides unparalleled opportunities for business leaders to understand the rules of talent and management, which in turn deliver intelligence for effective decision making and management for their organizations. In the past few years, talent and management computing have increasingly attracted attentions from KDD communities, and a number of research/applied data science efforts have been devoted. To …

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Vehicle Routing Problem With Parcel Locker And Public Transportation: Goods Delivery Using Mass-Rapid-Transit System, Pham K.M. Nguyen, Vincent F. Yu, Aldy Gunawan Aug 2023

Vehicle Routing Problem With Parcel Locker And Public Transportation: Goods Delivery Using Mass-Rapid-Transit System, Pham K.M. Nguyen, Vincent F. Yu, Aldy Gunawan

Research Collection School Of Computing and Information Systems

The logistics industry is experiencing significant transformations with the emergence of modern technologies, well-established civil infrastructure, and mixed transportation methods. These changes are driven by the increase in mobility, sustainability, and eco-friendliness of logistics processes. As a result, recent works have focused on incorporating mixed fleets and omnichannel systems to the original vehicle routing problem which boosts the delivery system's efficiency, effectiveness, reliability, and customer satisfaction while reducing operational costs simultaneously. We augment the existing studies by proposing a new mathematical model that combines common mass rapid transit systems and delivery fleets to solve the traditional vehicle routing problem with …

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Sparsity Brings Vulnerabilities: Exploring New Metrics In Backdoor Attacks, Jianwen Tian, Kefan Qiu, Debin Gao, Zhi Wang, Xiaohui Kuang, Gang Zhao Aug 2023

Sparsity Brings Vulnerabilities: Exploring New Metrics In Backdoor Attacks, Jianwen Tian, Kefan Qiu, Debin Gao, Zhi Wang, Xiaohui Kuang, Gang Zhao

Research Collection School Of Computing and Information Systems

Nowadays, using AI-based detectors to keep pace with the fast iterating of malware has attracted a great attention. However, most AI-based malware detectors use features with vast sparse subspaces to characterize applications, which brings significant vulnerabilities to the model. To exploit this sparsityrelated vulnerability, we propose a clean-label backdoor attack consisting of a dissimilarity metric-based candidate selection and a variation ratio-based trigger construction. The proposed backdoor is verified on different datasets, including a Windows PE dataset, an Android dataset with numerical and boolean feature values, and a PDF dataset. The experimental results show that the attack can slash the accuracy …

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Single-View View Synthesis With Self-Rectified Pseudo-Stereo, Yang Zhou, Hanjie Wu, Wenxi Liu, Zheng Xiong, Jing Qin, Shengfeng He Aug 2023

Single-View View Synthesis With Self-Rectified Pseudo-Stereo, Yang Zhou, Hanjie Wu, Wenxi Liu, Zheng Xiong, Jing Qin, Shengfeng He

Research Collection School Of Computing and Information Systems

Synthesizing novel views from a single view image is a highly ill-posed problem. We discover an effective solution to reduce the learning ambiguity by expanding the single-view view synthesis problem to a multi-view setting. Specifically, we leverage the reliable and explicit stereo prior to generate a pseudo-stereo viewpoint, which serves as an auxiliary input to construct the 3D space. In this way, the challenging novel view synthesis process is decoupled into two simpler problems of stereo synthesis and 3D reconstruction. In order to synthesize a structurally correct and detail-preserved stereo image, we propose a self-rectified stereo synthesis to amend erroneous …

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Balancing Utility And Fairness In Submodular Maximization, Yanhao Wang, Yuchen Li, Francesco Bonchi, Ying Wang Aug 2023

Balancing Utility And Fairness In Submodular Maximization, Yanhao Wang, Yuchen Li, Francesco Bonchi, Ying Wang

Research Collection School Of Computing and Information Systems

Submodular function maximization is a fundamental combinatorial optimization problem with plenty of applications – including data summarization, influence maximization, and recommendation. In many of these problems, the goal is to find a solution that maximizes the average utility over all users, for each of whom the utility is defined by a monotone submodular function. However, when the population of users is composed of several demographic groups, another critical problem is whether the utility is fairly distributed across different groups. Although the utility and fairness objectives are both desirable, they might contradict each other, and, to the best of our knowledge, …

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Multi-Granularity Detector For Vulnerability Fixes, Truong Giang Nguyen, Cong, Thanh Le, Hong Jin Kang, Ratnadira Widyasari, Chengran Yang, Zhipeng Zhao, Bowen Xu, Jiayuan Zhou, Xin Xia, Ahmed E. Hassan, David Lo, David Lo Aug 2023

Multi-Granularity Detector For Vulnerability Fixes, Truong Giang Nguyen, Cong, Thanh Le, Hong Jin Kang, Ratnadira Widyasari, Chengran Yang, Zhipeng Zhao, Bowen Xu, Jiayuan Zhou, Xin Xia, Ahmed E. Hassan, David Lo, David Lo

Research Collection School Of Computing and Information Systems

With the increasing reliance on Open Source Software, users are exposed to third-party library vulnerabilities. Software Composition Analysis (SCA) tools have been created to alert users of such vulnerabilities. SCA requires the identification of vulnerability-fixing commits. Prior works have proposed methods that can automatically identify such vulnerability-fixing commits. However, identifying such commits is highly challenging, as only a very small minority of commits are vulnerability fixing. Moreover, code changes can be noisy and difficult to analyze. We observe that noise can occur at different levels of detail, making it challenging to detect vulnerability fixes accurately. To address these challenges and …

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A Comparative Study Of Vinti-Based Orbit Propagation And Estimation For Cubesats In Very Low Earth Orbits, Ethan Michael Senecal Aug 2023

A Comparative Study Of Vinti-Based Orbit Propagation And Estimation For Cubesats In Very Low Earth Orbits, Ethan Michael Senecal

Mechanical & Aerospace Engineering Theses & Dissertations

In recent years, there has been a growing interest in CubeSats and very low Earth orbit (VLEO) space missions. Mission SeaLion, a collaborative CubeSat mission between Old Dominion University, the U.S. Coast Guard Academy, and U.S. Air Force Institute of Technology, planned to launch a 3U CubeSat into VLEO. The VLEO mission is a particularly challenging environment for navigation and orbit propagation because drag introduces a significant perturbation for orbit models such as SGP4. Additionally, mission requirements left no capacity for attitude determination or control, further reducing knowledge of drag behavior of the satellite in flight. This deficiency is a …

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Towards Intelligent Runtime Framework For Distributed Heterogeneous Systems, Polykarpos Thomadakis Aug 2023

Towards Intelligent Runtime Framework For Distributed Heterogeneous Systems, Polykarpos Thomadakis

Computer Science Theses & Dissertations

Scientific applications strive for increased memory and computing performance, requiring massive amounts of data and time to produce results. Applications utilize large-scale, parallel computing platforms with advanced architectures to accommodate their needs. However, developing performance-portable applications for modern, heterogeneous platforms requires lots of effort and expertise in both the application and systems domains. This is more relevant for unstructured applications whose workflow is not statically predictable due to their heavily data-dependent nature. One possible solution for this problem is the introduction of an intelligent Domain-Specific Language (iDSL) that transparently helps to maintain correctness, hides the idiosyncrasies of lowlevel hardware, and …

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Deep Virtual Pion Pair Production, Dilini Lakshani Bulumulla Aug 2023

Deep Virtual Pion Pair Production, Dilini Lakshani Bulumulla

Physics Theses & Dissertations

This experiment investigates the deep virtual production of both σ− and ρ− mesons, with a particular focus on the microscopic structure of the σ mesons. While the ρ meson is an ordinary qq¯ pair, the σ meson is composed of not only the typical qq¯ pair, making it a topic of controversy for nearly six decades. Although the existence of the σ− meson is now well established, its microscopic structure remains poorly understood. The primary objective of this thesis is to contribute to the understanding of the σ meson by analyzing its deep virtual production. The main focus of this …

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Chinese International Graduate Student Agency In A Neo-Racism Context: A Narrative Analysis, Minghui Hou Aug 2023

Chinese International Graduate Student Agency In A Neo-Racism Context: A Narrative Analysis, Minghui Hou

Educational Leadership & Workforce Development Theses & Dissertations

The United States is the top destination for Chinese international students, receiving around 372,532 students from China from the academic year 2019 to 2020. The host institutions and countries have benefited from economic gains, diverse cultures, global competence, and human capital. The motivation of recruiting international students is framed in a global imaginary that is embedded in colonialism and neoliberalism. International students are often framed as cash cows and objects. Meanwhile, international students, particularly Chinese international students have been experiencing discrimination, prejudice, and exclusion due to their nationality and culture. The purpose of this narrative inquiry study was to examine …

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Multi-Dimensional Surface Water Quality Analyses In The Manawatu River Catchment, New Zealand, Imokhai T. Tenebe, Jason P. Julian, Praise God C. Emenike, Nathaniel Dede-Bamfo, Omeje Maxwell, Samuel E. Sanni, Eunice O. Babatunde, Darlan D. Alves Aug 2023

Multi-Dimensional Surface Water Quality Analyses In The Manawatu River Catchment, New Zealand, Imokhai T. Tenebe, Jason P. Julian, Praise God C. Emenike, Nathaniel Dede-Bamfo, Omeje Maxwell, Samuel E. Sanni, Eunice O. Babatunde, Darlan D. Alves

Faculty Research, Scholarly, and Creative Activity

Land Use and Land Cover (LULC) properties give vital information about pollution signatures in rivers, and they help develop best management practices (BMPs) for effective water resource management. This work employs multivariate statistical methods, receptor modeling, connectivity analysis, and univariate trend analysis to investigate pollution sources across spatiotemporal scales in the Manawatu River, New Zealand. A positive matrix factorization (PMF) method was applied to interpret possible contamination sources. A 25-year dataset (1989–2014) comprising 12 water quality variables from three sites was used. Runoff connectivity analyses identified high-producing grassland (HG) as the most dominant pollution class in all sub-catchments. Univariate analyses …

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