Entire DC Network | Open Access Articles | Digital Commons Network™

Clark Tailings Consolidated Waste Management Area (Ctcwma) Site Investigation Draft Data Summary Report 2019 Surface Water, Groundwater Seep, And Soil Characterization 2021-2023 Surface Water And Groundwater Seep Evaluation 2023 Waterloo Aps Soil And Groundwater Evaluation, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Epa Region 8 Optimized Ufp-Qapp Review Crosswalk, Environmental Protection Agency, Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – Third Quarter 2024, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Ab Initio Studies On Mechanical Properties Of Freestanding Ferroic Monolayers, John Malcolm Davis

Graduate Theses and Dissertations

This thesis explores the role of mechanical properties and elastic couplings in freestanding paradigmatic ferroic monolayers within the framework of density functional theory. This dissertation is comprised of three interconnected published studies: (i) establishing the elastic behavior across a temperature-driven phase transition in SnSe monolayers; (ii) thermally-driven phase transitions in graphene-like silicene, germanene, and stanene, examining the structural stability and band gap occlusion; and (iii) magnetoelastic coupling in an Ising-like CrSiTe3 monolayer, focused on assessing magnetic contributions to the material stiffness by establishing a proper non-magnetic reference.

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Pre-K Teachers’ Perceptions About Professional Learning: Influence On Instructional Methods, Classroom Management Skills, And Student Outcomes, Victoria Abakah Korsah

Electronic Theses and Dissertations

The purpose of this qualitative descriptive phenomenological study was to solicit pre-K teachers’ perceptions about professional development and its influences on instructional methodology, classroom management skills, and student outcomes. Interviews conducted with 11 teachers from childcare centers in a major urban city of Illinois provided insight into experiences of types of PL and development engagement, such as online courses, webinars, learning communities, coaching, mentoring, professional conferences, and content selection. Other experiences involved social-emotional learning, lesson planning, project-based learning, and how to teach children with special needs. The interview data collected from the participants yielded five themes using Colizzi’s data analysis …

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Navigating Barriers: The Experiences Of First-Generation, Low-Income, Hispanic Male Stem Majors Enrolled In Texas Universities, Katherine L. Autry

Electronic Theses and Dissertations

This qualitative descriptive study explored barriers, strategies, and career aspirations of 10 firstgeneration, low-income Hispanic male STEM students at Texas universities. Prior research highlighted systemic inequities affecting this group’s academic success. The study addressed how these students described educational barriers, strategies to overcome them, and influences on their STEM career aspirations. Data were collected via 10 semistructured Zoom interviews, online questionnaires, and open-ended questionnaires from participants at four Texas-based universities. Reflexive thematic analysis with NVivo software identified five themes: sociocultural and economic barriers, academic and institutional challenges, resilience and coping strategies, support systems, and influence on career aspirations and identity. …

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Lighttransfer: Your Long-Context Llm Is Secretly A Hybrid Model With Effortless Adaptation, Xuan Zhang, Fengzhuo Zhang, Cunxiao Du, Chao Du, Tianyu Pang, Wei Gao, Min Lin

Research Collection School Of Computing and Information Systems

Scaling language models to handle longer contexts introduces substantial memory challenges due to the growing cost of key-value (KV) caches. Motivated by the efficiency gains of hybrid models and the broad availability of pretrained large transformer backbones, we explore transitioning transformer models into hybrid architectures for a more efficient generation. In this work, we propose LightTransfer, a lightweight method that transforms models such as LLaMA into hybrid variants. Our approach identifies lazy layers -- those focusing on recent or initial tokens -- and replaces their full attention with streaming attention. This transformation can be performed without any training for long-context …

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Guiding Multiple Remote Users In Physical Tasks With Language-Driven Robotic Telepresence, Ruyi Li, Jingfei Guo, Xinyi Zhang, Xuji Zhang, Zeqing Li, Jiannan Li, Jiangtao Gong

Research Collection School Of Computing and Information Systems

Remote assistance through robotic telepresence could involve both control and memory challenges, particularly in one expert to multiple workers situation. In this work, we proposed a novelty language-driven interface to facilitate remote collaboration through telepresence robots. Through operations and maintenance expert interviews and a scenario simulation study, we identified key pain points in executing one-expert-multiple-workers remote guidance using the telepresence robot and proposed two design goals, which together consist of five sub-design goals with corresponding features. These features were integrated into a standard telepresence robot, resulting in the development of a Collaborative LLM-based Embodied Assistant Robot, named CLEAR Robot. A …

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Implementing Slack-Free Custom Penalty Function For Qubo On Gate-Based Quantum Computers, Xin Wei Lee, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Solving NP-hard constrained combinatorial optimization problems using quantum algorithms remains a challenging yet promising avenue toward quantum advantage. Variational Quantum Algorithms (VQAs), such as the Variational Quantum Eigensolver (VQE), typically require constrained problems to be reformulated as unconstrained ones using penalty methods. A common approach introduces slack variables and quadratic penalties in the QUBO formulation to handle inequality constraints. However, this leads to increased qubit requirements and often distorts the optimization landscape, making it harder to find high-quality feasible solutions. To address these issues, we explore a slack-free formulation that directly encodes inequality constraints using custom penalty functions, specifically the …

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Robface: A Test Suite For Efficient Robustness Evaluation Of Face Recognition Systems, Ruihan Zhang, Jun Sun

Research Collection School Of Computing and Information Systems

Face recognition is a widely used authentication technology in practice, where robustness is required. It is thus essential to have an efficient and easy-to-use method for evaluating the robustness of (possibly third-party) trained face recognition systems. Existing approaches to evaluating the robustness of face recognition systems are either based on empirical evaluation (e.g., measuring attacking success rate using state-of-the-art attacking methods) or formal analysis (e.g., measuring the Lipschitz constant). While the former demands significant user efforts and expertise, the latter is extremely time-consuming. In pursuit of a comprehensive, efficient, easy-to-use, and scalable estimation of the robustness of face recognition systems, …

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2025 September, Morehead State University. Office Of Communications & Marketing.

Morehead State Press Release Archive, 1961 to the Present

Press releases for September of 2025.

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Neuro-Ins: A Learning-Based One-Shot Node Insertion For Dynamic Routing Problems, Zhiqin Zhang, Jingfeng Yang, Zhiguang Cao, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The rise in instant delivery services necessitates efficient route planning in last-mile delivery scenarios, where new orders arrive dynamically and need to be integrated into existing routes. In such contexts, complete re-optimization of routes are not permitted, and node insertion to existing route sequences is the only viable option. However, many existing heuristics for node insertion, such as the Cheapest Insertion (CI) method, are myopic and often result in suboptimal solutions retrospectively. This paper presents Neuro-Ins, an initial yet novel attempt at harnessing a learning-based framework to handle the insertion of new orders for the Pickup and Delivery Problem (PDP). …

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Shortcuts Everywhere And Nowhere: Exploring Multi-Trigger Backdoor Attacks, Yige Li, Jiabo He, Hanxun Huang, Jun Sun, Xingjun Ma, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Backdoor attacks have become a significant threat to the pre-training and deployment of deep neural networks (DNNs). Although numerous methods for detecting and mitigating backdoor attacks have been proposed, most rely on identifying and eliminating the “shortcut” created by the backdoor, which links a specific source class to a target class. However, these approaches can be easily circumvented by designing multiple backdoor triggers that create shortcuts everywhere and therefore nowhere specific. In this study, we explore the concept of Multi-Trigger Backdoor Attacks (MTBAs), where multiple adversaries leverage different types of triggers to poison the same dataset. By proposing and investigating …

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Reimagining Academic Assessment In The Age Of Ai, Matthew Hammerton

Research Collection School of Social Sciences

In ‘Reimagining Academic Assessment in the Age of AI’, Matthew Hammerton examines the challenges and opportunities posed by generative AI for higher education assessment. He critiques common responses like banning AI, reverting to in-class exams, or abandoning essays altogether, arguing that they fail to preserve the deeper pedagogical goals of higher order, independent thinking. Instead, Hammerton proposes a guiding principle of intellectual responsibility: students should be accountable for explaining and defending each major choice in their work—regardless of whether they use AI tools. To operationalise this, he advocates for reintegrating oral examinations (‘vivas’) alongside written essays. In this model, students …

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Optimal Abort Policy For Mission-Critical Systems Under Imperfect Condition Monitoring, Qiuzhuang Sun, Jiawen Hu, Zhi-Sheng Ye

Research Collection College of Integrative Studies

Although most on-demand mission-critical systems are engineered to be reliable to support critical tasks, occasional failures may still occur during missions. To increase system survivability, a common practice is to abort the mission before an imminent failure. We consider optimal mission abort for a system whose deterioration follows a general three-state (normal, defective, failed) semi-Markov chain. The failure is assumed self-revealed, whereas the healthy and defective states have to be inferred from imperfect condition-monitoring data. Because of the non-Markovian process dynamics, optimal mission abort for this partially observable system is an intractable stopping problem. For a tractable solution, we introduce …

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Exact And Approximate Conformal Inference For Multi-Output Regression, Chancellor Johnstone, Eugene Ndiaye

Faculty Publications

It is common in machine learning to estimate a response y given covariate information x . However, these predictions alone do not quantify any uncertainty associated with said predictions. One way to overcome this deficiency is with conformal inference methods, which construct a set containing the unobserved response with a prescribed probability. Unfortunately, even with a one-dimensional response, conformal inference is computationally expensive despite recent encouraging advances. In this paper, we explore multi-output regression, delivering exact derivations of conformal inference p-values when the predictive model can be described as a linear function of y . Additionally, we introduce a multivariate …

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Comparative Analysis Of Different Magnetic Anomaly Datasets Using Navigation Performance With Flight Test Data, Aaron P. Nielsen, Brandon M. Blakely, Patrick Duff

Faculty Publications

Magnetic Anomaly Navigation (MagNav) is a map-based method of navigation which relies on accurately obtaining the anomaly field to a high level of precision to achieve good navigation results. This requires utilizing high quality sensors, accurately modeling disturbance fields from the aircraft & other sources, and creating high-fidelity maps. Aeromagnetic survey data or marine track survey data must be processed into a product that can be used as a reference for a magnetic navigator and a variety of techniques can be utilized for this processing. The data collection for different survey types reflects choices typically made to study the underlying …

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Blending Informing Literacy And Visual Literacy: Instructional Vignettes In Art, Architecture, And Design, Stephanie Beene, Sara Schumacher, Dana Statton Thompson, Mary Wegmann

University Libraries & Learning Sciences Faculty and Staff Publications

The ACRL Framework for Visual Literacy in Higher Education (Framework for Visual Literacy), based on empirical research into the trends, opportunities, and challenges facing the field of visual literacy in the twenty-first century,1 was codified in April 2022 and is an adaptable document to help learners grow their visual literacy competencies. In this chapter, written by four of the task force members charged with the creation of the Framework for Visual Literacy, we examine the relationship between the four themes in the Framework for Visual Literacy and the six frames of the ACRL Framework for Information Literacy for Higher Education …

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Design Of Robust Adaptive Nonlinear Backstepping Controller Enhanced By Deep Deterministic Policy Gradient Algorithm For Efficient Power Converter Regulation, Seyyed Morteza Ghamari, Asma Aziz, Mehrdad Ghahramani

Research outputs 2022 to 2026

Power converters play an important role in incorporating renewable energy sources into power systems. Among different converter designs, Buck and Boost converters are popular, as they use fewer components and deliver cost savings and high efficiency. However, Boost converters are known as non–minimum phase systems, imposing harder constraints for designing a robust converter. Developing an efficient controller for these topologies can be difficult since they exhibit nonlinearity and distortion in high frequency modes. The Lyapunov-based Adaptive Backstepping Control (ABSC) technology is used to regulate suitable outputs for these structures. This approach is an updated version of the technique that uses …

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Renewable-Based Isolated Power Systems: A Review Of Scalability, Reliability, And Uncertainty Modeling, Mehrdad Ghahramani, Daryoush Habibi, Seyyedmorteza Ghamari, Hamid Soleimani, Asma Aziz

Research outputs 2022 to 2026

Electric power systems are increasingly becoming more decentralized. Many communities depend on isolated power systems that operate independently of the main grid. Remote, islanded, and isolated systems face challenges due to the intermittency and unpredictability of renewable energy sources. This paper reviews the current status of renewable integration and control in stand-alone power systems. It examines techniques to enhance system reliability through energy storage, hybrid systems, and advanced predictive models. Additionally, the issues related to connecting stand-alone systems, focusing on reliability and renewable penetration, are discussed. The scalability of stand-alone power systems is analyzed based on classifications of small-, medium-, …

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Scale Model And Ship Simulator Towing Of The Iea 15 Mw Wind Turbine On The Umaine Volturnus-S Platform, Adam Roberts, Frédéric Le Pivert, Saied Kazemi, Tom Tosdevin, Adán López-Santander, Matthew J. Craven, Lars Johanning

School of Engineering, Computing and Mathematics

Floating offshore wind turbines are expected to be deployed in significant numbers across the globe in the coming decades, with wet towing of these structures between ports and farms a key operation in their installation, maintenance, and decommissioning. Platforms are likely to be towed across large distances, and accurate understanding of tow dynamics will be crucial to optimising these journeys to minimise costs, timescales, emissions, and risk. This paper presents experimental and ship simulator modelling of the oceanic towing of the IEA 15 MW turbine on the UMaine VolturnUS-S platform. The work provides indicative data for floating offshore wind turbines …

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Patterns Of Ecological Quality In Portuguese Transitional Waters Over The Last Five Decades: A Framework Based On Benthic Foraminifera For The Sado Estuary, J. Moreno, F. Moreno, F. Fatela, E. Leorri, M. Leira, P. Masqué, M. C. Freitas

Research outputs 2022 to 2026

This study aimed to examine the validity of benthic foraminifera-based indices – Foraminiferal Stress Index (FSI), diversity index Exp(H'bc), and Ecological Quality Ratio (EQR) – for evaluating estuarine environmental conditions and supporting palaeoecological reconstructions, focusing on the Sado estuary (southwest Portugal). Located near heavily industrialized urban areas and designated as a Nature Reserve, this estuary faces human pressures and high natural values, leading to management conflicts. Foraminiferal assemblages were analysed in surface sediment samples, with known concentrations of several metal(loid)s, and in dated core samples. Correlations were found between metal(loid)s, organic matter, grain size, and salinity (as a proxy for …

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The Immeasurable Value Of Plankton To Humanity, Maria Grigoratou, Susanne Menden-Deuer, Abigail Mcquatters-Gollop, George Arhonditsis, Luis Felipe Artigas, Sakina-Dorothée Ayata, Dalida Bedikoğlu, Beatrix E Beisner, Bingzhang Chen, Claire Davies, Lillian Diarra, Owoyemi W Elegbeleye, Jason D Everett, Tatiane M Garcia, Wendy C Gentleman, Rodrigo Javier Gonçalves, Tamar Guy-Haim, Svenja Halfter, Jana Hinners, Richard R Horaeb, Jenny A Huggett, Catherine L Johnson, Maria T Kavanaugh, Ana Lara-Lopez, Christian Lindemann, Celeste López-Abbate, Monique Messié, Klas Ove Möller, Enrique Montes, Frank E Muller-Karger

School of Biological and Marine Sciences

Plankton, a diverse group of aquatic organisms, make Earth livable, regulate aquatic life, and provide benefits to human societies such as access to clean water, food security, and well-being. They also support economies and inspire biotechnological innovations. This article aims to raise awareness of the value of plankton to humanity and serves as an informative guide for aquatic professionals, policymakers, and anyone interested in plankton. We present the value of plankton across six themes of human interest: biogeochemistry; ecology; climate; the evolution of science; economy; and culture, recreation, and well-being. Guided by the 2022 Intergovernmental Science-Policy Platform on Biodiversity and …

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Short–Range Hard–Sphere Potential And Coulomb Interaction: Deser–Trueman Formula For Rydberg States Of Exotic Atomic Systems, Gregory S. Adkins, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

In exotic atomic systems with hadronic constituent particles, it is notoriously difficult to estimate the strong-interaction correction to energy levels. It is well known that, due to the strength of the nuclear interaction, the problem cannot be solved using Wigner–Brillouin perturbation theory alone. Recently, high-angular-momentum Rydberg states of exotic atomic systems with hadronic constituents have been identified as promising candidates in the search for new physics in the low-energy sector of the Standard Model. We thus derive a generalized Deser–Trueman formula for the induced energy shift for a general hydrogenic bound state with principal quantum number n and orbital angular …

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Gti: Graph-Based Tree Index With Logarithm Updates For Nearest Neighbor Search In High-Dimensional Spaces, Ruoyao Ma, Yifan Zhu, Baihua Zheng, Lu Chen, Congcong Ge, Yunjun Gao

Research Collection School Of Computing and Information Systems

Nearest neighbor search (NNS) is fundamental for high-dimensional space retrieval and impacts various fields, such as pattern recognition, information retrieval, recommendation systems, and vector database management. Among existing NNS methods, graph-based methods often excel in query accuracy and efficiency. However, these methods face significant challenges, including high construction costs and difficulties with dynamic data updates. Recent efforts have focused on combining graph methods with hashing, quantization, and tree-based approaches to address these issues, but problems with large index sizes and update performance remain unresolved. In response, this paper proposes GTI, a novel, lightweight, and dynamic graph-based tree index for high-dimensional …

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Deep Graph Anomaly Detection: A Survey And New Perspectives, Hezhe Qiao, Hanghang Tong, Nanyang Technological University, Irwin King, Charu Aggarwal, Guansong Pang

Research Collection School Of Computing and Information Systems

Graph anomaly detection (GAD), which aims to identify unusual graph instances (e.g., nodes, edges, subgraphs, or graphs), has attracted increasing attention in recent years due to its significance in a wide range of applications. Deep learning approaches, graph neural networks (GNNs) in particular, have been emerging as a promising paradigm for GAD, owing to its strong capability in capturing complex structure and/or node attributes in graph data. Considering the large number of methods proposed for GNN-based GAD, it is of paramount importance to summarize the methodologies and findings in the existing GAD studies, so that we can pinpoint effective model …

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Probabilistic Modeling, Learnability And Uncertainty Estimation For Interaction Prediction In Movie Rating Datasets, Jennifer Poernomo, Nicole Gabrielle Lee Tan, Rodrigo Alves, Antoine Ledent

Research Collection School Of Computing and Information Systems

In this paper, we examine the hypothesis that the interactions recorded in many Recommendation Systems datasets are distributed according to a low-rank distribution, i.e. a mixture of factorizable distributions. Surprisingly, we find that on several popular datasets, a simple non-negative matrix factorization method equals or outperforms more modern methods such as LightGCN, which indicates that the sampling distribution over interactions is indeed low-rank. Furthermore, we mathematically prove that low-rank distributions are learnable with a sparse number of observations (where m/n and r refer to the number of users/items and the non-negative rank respectively) both in terms of the total variation …

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Privacy-Preserving Ridge Regression Over Encrypted Data Under Multiple Keys, Yanling Li, Junzuo Lai, Meng Sun, Beibei Song, Robert H. Deng

Research Collection School Of Computing and Information Systems

With the increase of private data being collected by data owners, it has been a trend for data owners to store the data on cloud computing platforms. The huge amounts of data in cloud servers bring fresh development opportunities to machine learning, which is applied to build a high-quality machine learning model based on a large training dataset. However, to ensure the privacy of data and facilitate retrieval, data owners often upload encrypted data under their public keys. But it creates new challenges for machine learning to learn a predictive model over these encrypted data under different keys. Most existing …

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Apidocbooster: An Extract-Then-Abstract Framework Leveraging Large Language Models For Augmenting Api Documentation, Chengran Yang, Jiakun Liu, Bowen Xu, Christoph Treude, Yunbo Lyu, Junda He, Ming Li, David Lo

Research Collection School Of Computing and Information Systems

API documentation is often the most trusted resource for programming. Many approaches have been proposed to augment API documentation by summarizing complementary information from external resources such as Stack Overflow. Existing extractive-based summarization approaches excel in producing faithful summaries that accurately represent the source content without input length restrictions. Nevertheless, they suffer from inherent readability limitations. On the other hand, our empirical study on the abstractive-based summarization method, i.e., GPT-4, reveals that GPT-4 can generate coherent and concise summaries but presents limitations in terms of informativeness and faithfulness. We introduce APIDocBooster, an extract-then-abstract framework that seamlessly fuses the advantages of …

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Static Analysis As A Feedback Loop: Enhancing Llm-Generated Code Beyond Correctness, Scott Blyth, Sherlock Licorish, Christoph Treude, Markus Wagner

Research Collection School Of Computing and Information Systems

Large language models (LLMs) have demonstrated impressive capabilities in code generation, achieving high scores on benchmarks such as HumanEval and MBPP. However, these benchmarks primarily assess functional correctness and neglect broader dimensions of code quality, including security, reliability, readability, and maintainability. In this work, we systematically evaluate the ability of LLMs to generate high-quality code across multiple dimensions using the PythonSecurityEval benchmark. We introduce an iterative static analysis-driven prompting algorithm that leverages Bandit and Pylint to identify and resolve code quality issues. Our experiments with GPT-4o show substantial improvements: security issues reduced from >40% to 13%, readability violations from >80% …

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Full-Text Articles in Entire DC Network

Clark Tailings Consolidated Waste Management Area (Ctcwma) Site Investigation Draft Data Summary Report 2019 Surface Water, Groundwater Seep, And Soil Characterization 2021-2023 Surface Water And Groundwater Seep Evaluation 2023 Waterloo Aps Soil And Groundwater Evaluation, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

Epa Region 8 Optimized Ufp-Qapp Review Crosswalk, Environmental Protection Agency, Emma Rott

Silver Bow Creek/Butte Area Superfund Site

Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – Third Quarter 2024, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

Ab Initio Studies On Mechanical Properties Of Freestanding Ferroic Monolayers, John Malcolm Davis

Graduate Theses and Dissertations

Pre-K Teachers’ Perceptions About Professional Learning: Influence On Instructional Methods, Classroom Management Skills, And Student Outcomes, Victoria Abakah Korsah

Electronic Theses and Dissertations

Navigating Barriers: The Experiences Of First-Generation, Low-Income, Hispanic Male Stem Majors Enrolled In Texas Universities, Katherine L. Autry

Electronic Theses and Dissertations

Lighttransfer: Your Long-Context Llm Is Secretly A Hybrid Model With Effortless Adaptation, Xuan Zhang, Fengzhuo Zhang, Cunxiao Du, Chao Du, Tianyu Pang, Wei Gao, Min Lin

Research Collection School Of Computing and Information Systems

Guiding Multiple Remote Users In Physical Tasks With Language-Driven Robotic Telepresence, Ruyi Li, Jingfei Guo, Xinyi Zhang, Xuji Zhang, Zeqing Li, Jiannan Li, Jiangtao Gong

Research Collection School Of Computing and Information Systems

Implementing Slack-Free Custom Penalty Function For Qubo On Gate-Based Quantum Computers, Xin Wei Lee, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Robface: A Test Suite For Efficient Robustness Evaluation Of Face Recognition Systems, Ruihan Zhang, Jun Sun

Research Collection School Of Computing and Information Systems

2025 September, Morehead State University. Office Of Communications & Marketing.

Morehead State Press Release Archive, 1961 to the Present

Neuro-Ins: A Learning-Based One-Shot Node Insertion For Dynamic Routing Problems, Zhiqin Zhang, Jingfeng Yang, Zhiguang Cao, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Shortcuts Everywhere And Nowhere: Exploring Multi-Trigger Backdoor Attacks, Yige Li, Jiabo He, Hanxun Huang, Jun Sun, Xingjun Ma, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Reimagining Academic Assessment In The Age Of Ai, Matthew Hammerton

Research Collection School of Social Sciences

Optimal Abort Policy For Mission-Critical Systems Under Imperfect Condition Monitoring, Qiuzhuang Sun, Jiawen Hu, Zhi-Sheng Ye

Research Collection College of Integrative Studies

Exact And Approximate Conformal Inference For Multi-Output Regression, Chancellor Johnstone, Eugene Ndiaye

Faculty Publications

Comparative Analysis Of Different Magnetic Anomaly Datasets Using Navigation Performance With Flight Test Data, Aaron P. Nielsen, Brandon M. Blakely, Patrick Duff

Faculty Publications

Blending Informing Literacy And Visual Literacy: Instructional Vignettes In Art, Architecture, And Design, Stephanie Beene, Sara Schumacher, Dana Statton Thompson, Mary Wegmann

University Libraries & Learning Sciences Faculty and Staff Publications

Design Of Robust Adaptive Nonlinear Backstepping Controller Enhanced By Deep Deterministic Policy Gradient Algorithm For Efficient Power Converter Regulation, Seyyed Morteza Ghamari, Asma Aziz, Mehrdad Ghahramani

Research outputs 2022 to 2026

Renewable-Based Isolated Power Systems: A Review Of Scalability, Reliability, And Uncertainty Modeling, Mehrdad Ghahramani, Daryoush Habibi, Seyyedmorteza Ghamari, Hamid Soleimani, Asma Aziz

Research outputs 2022 to 2026

Scale Model And Ship Simulator Towing Of The Iea 15 Mw Wind Turbine On The Umaine Volturnus-S Platform, Adam Roberts, Frédéric Le Pivert, Saied Kazemi, Tom Tosdevin, Adán López-Santander, Matthew J. Craven, Lars Johanning

School of Engineering, Computing and Mathematics

Patterns Of Ecological Quality In Portuguese Transitional Waters Over The Last Five Decades: A Framework Based On Benthic Foraminifera For The Sado Estuary, J. Moreno, F. Moreno, F. Fatela, E. Leorri, M. Leira, P. Masqué, M. C. Freitas

Research outputs 2022 to 2026

School of Biological and Marine Sciences

Short–Range Hard–Sphere Potential And Coulomb Interaction: Deser–Trueman Formula For Rydberg States Of Exotic Atomic Systems, Gregory S. Adkins, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

Gti: Graph-Based Tree Index With Logarithm Updates For Nearest Neighbor Search In High-Dimensional Spaces, Ruoyao Ma, Yifan Zhu, Baihua Zheng, Lu Chen, Congcong Ge, Yunjun Gao

Research Collection School Of Computing and Information Systems

Deep Graph Anomaly Detection: A Survey And New Perspectives, Hezhe Qiao, Hanghang Tong, Nanyang Technological University, Irwin King, Charu Aggarwal, Guansong Pang

Research Collection School Of Computing and Information Systems

Probabilistic Modeling, Learnability And Uncertainty Estimation For Interaction Prediction In Movie Rating Datasets, Jennifer Poernomo, Nicole Gabrielle Lee Tan, Rodrigo Alves, Antoine Ledent

Research Collection School Of Computing and Information Systems

Privacy-Preserving Ridge Regression Over Encrypted Data Under Multiple Keys, Yanling Li, Junzuo Lai, Meng Sun, Beibei Song, Robert H. Deng

Research Collection School Of Computing and Information Systems

Apidocbooster: An Extract-Then-Abstract Framework Leveraging Large Language Models For Augmenting Api Documentation, Chengran Yang, Jiakun Liu, Bowen Xu, Christoph Treude, Yunbo Lyu, Junda He, Ming Li, David Lo

Research Collection School Of Computing and Information Systems

Static Analysis As A Feedback Loop: Enhancing Llm-Generated Code Beyond Correctness, Scott Blyth, Sherlock Licorish, Christoph Treude, Markus Wagner

Research Collection School Of Computing and Information Systems