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Cognitive Conflict In Iconic Visual Representations: Comparing Conventional And Ai Approaches, Endrayana Putut Laksminto Emanuel, Herfa Maulina Dewi Soewardini, Radhitya Duta Pradana, Sikky El Walida

Jurnal Pendidikan Sains

Background of study: The rapid integration of Artificial Intelligence (AI) in higher education has transformed mathematical problem-solving practices, yet it introduces potential discrepancies in students’ visual understanding, particularly in geometric contexts, leading to commognitive conflicts in visual mediators. Aims and scope of paper: This study aims to analyze and compare the sources of commognitive conflict in iconic visual representations when students solve flat shape problems using conventional methods versus AI-assisted approaches. Methods: A qualitative design was employed involving 20 first-year mathematics education students divided into two groups (AI-assisted and conventional). Data were collected through students’ written work and semi-structured interviews …

Improving Energy Reliability In Mining Areas Through Modelling And Control Of Resonance Phenomena In Solar-Integrated Power Systems, Yurii Papaika, Gennadiy Pivnyak, Maksim Malyshko, Yuliya Pazynich, Natalia Howaniec, Adam Smolinski

Journal of Sustainable Mining

This study addresses the emergency and operational transient processes that arise when integrating large-scale solar power plants (SPPs) into electrical load nodes, particularly under conditions of limited power system capacity. With the increasing penetration of distributed generation in Ukraine's energy landscape, challenges related to electromagnetic compatibility and harmonic resonance are becoming more prominent. The research builds upon the foundational work of leading Ukrainian scientific schools and focuses on the specific resonance phenomena observed during the operation of solar inverters in medium-voltage networks, especially in regions with high industrial and mining Energy demand. A novel algorithm is proposed for determining the …

Empirical Benchmarks For Interpreting Effect Sizes In Violent Crime Interventions, Kohta James Matsukawa Hansen

Theses and Dissertations

Criminal justice researchers apply Cohen’s (1988) benchmarks to classify effect sizes as small, medium, or large, despite these standards never being meant for broad, decontextualized use (Cohen, 1988; Gies et al., 2024; Goulet-Pelletier & Cousineau, 2018; Lakens, 2013; Milner et al., 2023). Repeatedly doing so may weaken statistical validity, distort findings, and impede effective policymaking. This study introduces the first effect size benchmarks specifically designed for violent crime interventions.

Using a quasi-meta-analysis framework, 1,605 effect sizes from 104 violent crime intervention studies from the CrimeSolutions clearinghouse were converted to Cohen’s d. Three new discrete benchmarking methods were created using a …

Asymmetrical S-Curve For Residual Load Sways Suppression For Double-Pendulum Rotary Crane Using Bayesian Optimization, Haryson Johanes Nyobuya

Tanzania Journal of Science

In rotary crane operations, one of the main difficulties lies in suppressing the load sway during its movement. This can be achieved using only horizontal boom motion, offering a solution that is energy-saving, simple, and safe. However, this approach renders the system under actuated, making the suppression objective more difficult to achieve. In this study, a double-pendulum model is adopted to capture the coupled dynamics of the suspended load and hook, which shows a realistic basis for sway suppression. An asymmetric S-curve velocity trajectory is proposed to shape the horizontal boom motion, effectively minimizing residual vibrations without requiring direct sway …

Quantitative Analysis Of Cholera Dynamics And The Impact Of Integrated Control Measures., Kazeem Abidoye Odeyemi, Mutairu Kayode Kolawole

Tanzania Journal of Science

A comprehensive mathematical evaluation of cholera dynamics, emphasizing the crucial role of optimal control strategies which include vaccination, treatment in endemic region and environmental hygiene in controlling the disease spread in Western and Mid-Eastern regions of African setting. Through analysis of the local and global stability of the model and assessing the reproduction number (��0), this research highlights how targeted interventions can influence transmission rates of cholera disease. Sensitivity analysis identifies key parameters driving cholera dynamics, underlining the urgency of timely and adequate intervention. Utilizing the innovative Homotopy Perturbation Method for the numerical simulation, the study explores the interplay between …

Ais26s: Genai And Llms For Cybersecurity, Political Sciences, Transportation Security, And Resiliency, Latifur Khan

Paul English Applied Artificial Intelligence (AI) Institute Publications

This presentation examines the role of generative artificial intelligence (GenAI) and large language models (LLMs) in addressing complex challenges across cybersecurity, political science, and transportation security. Dr. Latifur Khan discusses how advanced AI methods can be applied to threat detection, data analysis, and decision-making in high-risk and data-intensive environments. The talk highlights interdisciplinary applications of LLMs, emphasizing their ability to extract insights from large-scale data, improve system resilience, and support intelligent infrastructure. Emerging research directions and practical implications for real-world deployment are also discussed.

Direct Energy Cascade Of 2d Quantum Turbulence In Supersolids, Lukas Farthing

Miners Solving for Tomorrow Research Conference

The non-equilibrium turbulent response of periodically driven three-dimensional ultracold dipolar gases is induced by an external time-dependent ring potential. To model this system and monitor its non-equilibrium quantum dynamics, we invoke an extended Gross-Pitaevskii framework containing the first-order quantum correction to the mean-field energy functional. The shape of the external perturbing potential is chosen to trigger angular roton excitations, driving the supersolid configuration out of equilibrium and attaining a turbulent state. Following the generation of shallow vortical defects in the bulk, a direct cascade front manifests, transporting energy from larger to smaller length scales. This leads to a non-equilibrium quasi-steady …

Dynamical Transition From A Two-Dimensional Soliton To A Rogue Wave In Quantum Droplets, Punit Sesha Sai Turlapati

Miners Solving for Tomorrow Research Conference

We investigate the nonequilibrium dynamics of two-dimensional quantum droplets: ultracold self-bound many-body states stabilized by the interplay of mean-field attractive interactions and repulsive quantum fluctuations. Flat-top ground state droplets are subject to an external potential, an attractive well and a repulsive barrier. Under the influence of the attractive well, we observe signatures of a Townes soliton formation, which for increasing strength of the well transitions into a two-dimensional rogue wave structure, a time-periodic highly localized configuration with amplitude three times larger than the background. The barrier instead favors a dynamical splitting of the droplet. We have developed a parallelized simulation …

Vortex Generation In Dipolar Supersolids, Jacob Harl

Miners Solving for Tomorrow Research Conference

Ultracold atomic gases offer highly tunable platforms for exploring complex quantum many-body phenomena. In addition, dipolar quantum gases of magnetic atoms featuring long-range anisotropic interactions are exquisite systems for realizing exotic phases-of-matter in an experimentally controlled way. A prototypical example is the supersolid state which simultaneously exhibits frictionless flow of superfuids and crystalline density modulation of solids. In this realm, we investigate the dynamical generation of vortex topological defects by imprinting a suitable phase jump in quasi-two-dimensional dipolar supersolids. This protocol enables the nucleation of a dark soliton which consecutively becomes unstable via the eponymous snake instability due to its …

Asphalt Pavement Rejuvenation Investigated By Nuclear Magnetic Resonance Relaxometry, Catherine Skaggs

Miners Solving for Tomorrow Research Conference

Asphalt is a relatively inexpensive material commonly used for road pavements; however, asphalt ages from exposure to oxygen and UV radiation, leading to loss of elasticity, which leads to cracks and potholes. To slow or reverse asphalt aging, pavement preservation treatments are in use. It’s unclear whether these treatments truly rejuvenate the pavement structure or merely offer a short-term benefit. Nuclear Magnetic Resonance (NMR) relaxometry is an analytical technique that uses the recovery of excited nuclear magnetization as a parameter to gain insights into molecular environments. Recovery-time distributions gathered from asphalt materials show differences between regular and rejuvenated asphalt samples, …

Conflogger: Enhance Systems’ Configuration Diagnosability Through Configuration Logging, Shiwen Shan, Yintong Huo, Yuxin Su, Zhining Wang, Dan Li, Zibin Zheng

Research Collection School Of Computing and Information Systems

Modern configurable systems offer customization via intricate configuration spaces, yet such flexibility introduces pervasive configuration-related issues such as misconfigurations and latent softwarebugs. Existing diagnosability supports focus on post-failure analysis of software behavior to identify configuration issues, but none of these approaches look into whether the software clue sufficient failure information for diagnosis. To fill in the blank, we propose the idea of configuration logging to enhance existing logging practices at the source code level. We develop ConfLogger, the first tool that unifies configuration-aware static taint analysis with LLM-based log generation to enhance software configuration diagnosability. Specifically, our method 1) identifies …

Propaganda Ai: An Analysis Of Semantic Divergence In Large Language Models, Nay Myat Min, Long H. Pham, Yige Li, Jun Sun

Research Collection School Of Computing and Information Systems

Large language models (LLMs) can exhibit concept-conditioned semantic divergence: common high-level cues (e.g., ideologies, public figures) elicit unusually uniform, stance-like responses that evade token-trigger audits. This behavior falls in a blind spot of current safety evaluations, yet carries major societal stakes, as such concept cues can steer content exposure at scale. We formalize this phenomenon and present RAVEN (Response Anomaly Vigilance), a black-box audit that flags cases where a model is simultaneously highly certain and atypical among peers by coupling semantic entropy over paraphrastic samples with cross-model disagreement. In a controlled LoRA fine-tuning study, we implant a concept-conditioned stance using …

Where Did It Go Wrong? Attributing Undesirable Llm Behaviors Via Representation Gradient Tracing, Zhe Li, Wei Zhao, Yige Li, Jun Sun

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have demonstrated remarkable capabilities, yet their deployment is frequently undermined by undesirable behaviors such as generating harmful content, factual inaccuracies, and societal biases. Diagnosing the root causes of these failures poses a critical challenge for AI safety. Existing attribution methods, particularly those based on parameter gradients, often fall short due to prohibitive noisy signals and computational complexity. In this work, we introduce a novel and efficient framework that diagnoses a range of undesirable LLM behaviors by analyzing representation and its gradients, which operates directly in the model's activation space to provide a semantically meaningful signal linking …

Reducing Class-Wise Performance Disparity Via Margin Regularization, Beier Zhu, Kesen Zhao, Jiequan Cui, Qianru Sun, Yuan Zhou, Xun Yang, Hanwang Zhang

Research Collection School Of Computing and Information Systems

Deep neural networks often exhibit substantial disparities in class-wise accuracy, even when trained on class-balanced data—posing concerns for reliable deployment. While prior efforts have explored empirical remedies, a theoretical understanding of such performance disparities in classification remains limited. In this work, we present Margin Regularization for performance disparity Reduction (MR2 ), a theoretically principled regularization for classification by dynamically adjusting margins in both the logit and representation spaces. Our analysis establishes a margin-based, class-sensitive generalization bound that reveals how per-class feature variability contributes to error, motivating the use of larger margins for “hard” classes. Guided by this insight, MR2 optimizes …

Llmqua: Practical Backdoor Injection On Large Language Model Quantization, Xiangxiang Chen, Peixin Zhang, Jun Sun, Jin Song Dong, Wenhai Wang, Jingyi Wang

Research Collection School Of Computing and Information Systems

Quantization is widely used to enable local deployment of large language models (LLMs) on resource-constrained devices. Recent work (e.g., QuRA) shows quantization can be exploited via rounding manipulation to implant backdoors. However, such an attack has been evaluated only on small models and does not directly apply to LLMs due to three key constraints: (1) limited poisoning data from small, task-agnostic calibration sets; (2) layer-wise quantization restricting adversarial access to global representations; and (3) lack of gradient access in quantization pipelines, blocking gradient-based attacks.We propose LLMQuA, a practical quantization-phase backdoor attack tailored to the LLM setting. LLMQuA (i) injects backdoors …

Prompting Frameworks For Large Language Models: A Survey, Xiaoxia Liu, Jingyi Wang, Jun Sun, Xiaohan Yuan, Guoliang Dong, Peng Di, Wenhai Wang, Dongxia Wang

Research Collection School Of Computing and Information Systems

Since the launch of ChatGPT, a powerful AI Chatbot developed by OpenAI, large language models (LLMs) have made significant advancements in both academia and industry, bringing about a fundamental engineering paradigm shift in many areas. While LLMs are powerful, it is also crucial to best use their power where “prompt” plays a core role. However, the booming LLMs themselves, including excellent APIs like ChatGPT, have several inherent limitations: (1) temporal lag of training data, and (2) the lack of physical capabilities to perform external actions. Recently, we have observed the trend of utilizing prompt-based tools to better utilize the power …

Who You Explain To Matters: Learning By Explaining To Conversational Agents With Different Pedagogical Roles, Zhengtao Xu, Junti Zhang, Anthony Tang, Yi-Chieh Lee

Research Collection School Of Computing and Information Systems

Conversational agents are increasingly used in education for learning support. An application is “learning by explaining”, where learners explain their understanding to an agent. However, existing research focuses on single roles, leaving it unclear how different pedagogical roles influence learners’ interaction patterns, learning outcomes and experiences. We conducted a between-subjects study (N=96) comparing agents with three pedagogical roles (Tutee, Peer, Challenger) and a control condition while learning an economics concept. We found that different pedagogical roles shaped learning dynamics, including interaction patterns and experiences. Specifically, the Tutee agent elicited the most cognitive investment but led to high pressure. The Peer …

Bis(Μ-1,4-Dihydropyridin-4-One-Κ2o:O)Di-Μperchlorato-Κ4o:O0-Bis[Aqua(1,4-Dihydropyridin-4-One-Κo)Copper(Ii)] Tetraaquabis(1,4-Dihydropyridin-4-One-Κo)Copper(Ii) Tetrakis(Perchlorate) 1,4-Dihydropyridin-4-One Disolvate, Mark M. Turnbull, Christopher Landee, Jan L. Wikaira

Chemistry

The reaction of copper(II) perchlorate hexahydrate with 4-pyridone and pyrazine in 1-propanol serendipitously yielded crystals of the solvated title double salt, [Cu(C5H5NO)2(H2O)4][Cu2(ClO4)2(C5H5NO)4(H2O)2](ClO4)4·2C5H5NO, as a biproduct. The copper cations in both the monometallic complex and the dimeric species exhibit classic Jahn-Teller-like elongations. All coordinating 4-pyridone molecules are in the κ-O coordination mode. The dimeric component exhibits both bridging 4-pyridone and perchlorate ligands. Both complexes and the 4-pyridone molecules are bound together by a network of classical hydrogen bonds. The non-coordinating perchlorate ions were modeled as three-site disordered and one of the coordinating 4-pyridone molecules was modeled as two-site disordered. © 2026 …

Non-Redundant Rovibrational Hamiltonians By Molien Generating Functions And Gröbner-Basis Reduction, Leandro Ajo

University Libraries Undergraduate Research Award

High-resolution molecular spectroscopy requires an effective Hamiltonian whose operator content is both complete, containing every term allowed by molecular symmetry and nonredundant, free of any algebraically dependent operators that would cause ill-conditioned parameter fits. Traditional derivations based on Van Vleck contact transformations satisfy neither criterion automatically. This paper develops a rigorous, algorithmic pipeline that guarantees both properties simultaneously. Starting from the permutation– inversion (PI) group GPI of a molecule (Longuet-Higgins, 1963), we apply Molien’s theorem (Molien, 1897) to the symplectic normal-coordinate representation to obtain the vibrational generating function Φvib(t); integrate over the Haar measure of SO(3) (Weyl, 1946) to obtain …

Fingerprinting Voice Commands Of Vpn-Protected Smart Speakers, Xiaoguang Guo, Keyang Yu, Qi Li, Dong Chen

Computer Science Faculty Research and Publications

Extensive recent research has shown that it is surprisingly easy to infer Amazon Alexa voice commands over their network traffic data. To prevent these traffic analytics (TA)-based inference attacks, smart home owners are considering deploying virtual private networks (VPNs) to safeguard their smart speakers. In this work, we design a new machine learning-powered attack framework—VoiceAttack that could still accurately fingerprint voice commands on VPN-encrypted voice speaker network traffic. We evaluate VoiceAttack under 5 different real-world settings using Amazon Alexa and Google Home. Our results show that VoiceAttack could correctly infer voice command sentences with a Matthews Correlation Coefficient (MCC) of …

Designing A Novel Inhibitor For Cobalamin-Independent Methionine Synthase, Damon Virgo

Undergraduate Honors Papers

Microbial infections are some of the leading causes of death in the population at large, and antimicrobial-resistant “superbugs” have become a growing issue, so there is a great need to explore new and alternative pathways for fighting these diseases. One method for doing this is by exploring Methionine synthase (MetSyn), which plays a critical role in cellular one-carbon metabolism, catalyzing the methylation of homocysteine to form methionine, an essential amino acid required for protein synthesis and methyl group transfer reactions. Key differences between the B12-independant fungal MetSyn enzyme and the B12-dependant mammalian form can allow for selective targeting of the …

Phase 5 - Post Implementation, Anna Pugerud

Distinguished Student Scholarship Collection

This paper presents a post‑implementation analysis and system design plan for digitizing animal health records within the Animal Health Services (AHS) department. The project addresses inefficiencies, data inaccuracies, and physical storage limitations associated with paper‑based documentation by proposing the adoption of a Software as a Service (SaaS) digital records solution. Through stakeholder interviews, observations, and document analysis, the project identifies functional, non‑functional, and system requirements necessary to support streamlined reporting, treatment tracking, and regulatory compliance. The analysis outlines feasibility across technical, economic, and organizational dimensions, demonstrating that the proposed system can reduce documentation time, improve response times, and lower operational …

Skyforge End Effector, Sarah Alexander, Coleman Bubar

Senior Project

Large space structures are necessary for space advancement. However, construction is difficult with the current methods; SkyForge is a robot intended for orbital assembly. The robot will walk on and build the structure by utilizing the end effectors to grasp and position parts.

2026 April - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

Hi All,

The main story of April 2026 was the hot and dry pattern that impacted Tennessee for most of the month and which was a continuation of this same pattern from March. Temperature anomalies across the state in April were slightly less than what we observed in March, but mean temperatures still ranged from 4-8°F above normal for April. Based on mean temperatures for the month, April 2026 was the warmest April on record in Knoxville’s 153-year weather history (beating out April 2017 by 0.2°F) and Nashville’s 152-year weather history (beating out April 2017 by 1.2°F). April 2026 was …

Agglomeration Of Particles Streaming Down A Zigzag, Juan Llamas

Posters - 2026

Zigzags or “letdown ladders” limit the flow speed of dry grains as they flow downward by gravity when loading silos, ships, barges, railcars, or trucks.

• Reduce cracking and shattering of grains.

• Increase grain shelf life.

• Increase grain resale value. • Increase ability of grain to germinate.

• Reduce generation of grain dust, an explosion and environmental hazard.

How can we design a zigzag that we know will not plug?

Fear In The Forecast: Do You Believe The Government Controls The Weather?, Gabriella Bartsch

Honors Papers and Posters

Weather manipulation by the government is among the most widely believed conspiracy theories in America, with over 49 percent of Americans subscribing to this belief. As belief in weather-related conspiracies continues to gain traction, understanding the political and social factors that drive these beliefs becomes increasingly essential. In this study, data from the Chapman Survey of American Fears, a representative national sample of U.S. adults, as well as a qualitative content analysis of X/Twitter posts from 2020 to 2026, are used. This research examines how political partisanship and conspiratorial predisposition are reflected in media consumption and levels of institutional trust, …

Fluid-Mediated Particle Transport: Revisiting Snowstorm Simulations In 2d With An Updated Pressure Calculation Algorithm, E. Maldonado, Michael W. Roth

The Compass: Earth Science Journal of Sigma Gamma Epsilon

We develop and present computer simulations of snowfall and snowfall management near buildings using deflection fins. Our approach first entails a numerical solution to the Navier – Stokes fluid dynamics equations in order to determine wind velocity profiles with and without deflection fins. Subsequent to finding the velocity field, snow particles are introduced and are subject to Newton’s Laws in order to allow transport, sticking to surfaces, landing and ultimately accumulation. We revisit previous work, presenting and discussing program construction and validation, along with cursory systematic studies of varying geometrical parameters in the simulation. The utility of the simulations is …

Ai Interpretability In Healthcare Communication, Ananya Jeyappragash

Dartmouth College Master’s Theses

Artificial intelligence has increasingly been adopted in healthcare, largely for specialized tasks and under significant human oversight. The use of large black-box systems raises important concerns about transparency in high-stakes environments such as clinical decision-making. Clinical communication is fundamentally human-centered, and failures in judgment can have serious consequences for patient care. Overestimating the reasoning abilities of large language models may lead to undue trust in fabricated or “hallucinated” outputs, while rejecting AI-assisted tools altogether may preserve inefficient workflows and contribute to missed or delayed diagnoses. These concerns reflect a broader tradeoff between accuracy and interpretability: although more complex models may …

Experimental And Computational Investigations Of Li-Ion And Na-Ion Battery Cathode Materials, Shintaro Inaba , ‘26

Senior Theses, Projects, and Awards

Batteries allow storage of chemical energy and controlled conversion of energy as electricity. Known to mankind since the eighteenth century, batteries have been vital in manufacturing, service industry, and use of portable electronics and electric vehicles. These systems utilize rechargeable batteries, where redox reactions are practically reversible. Lithium-ion batteries (LIBs) and sodium-ion batteries (SIBs) are two rechargeable systems that are widely explored in the field of electrochemistry and electrical engineering due to their abundance of materials, relative safety, energy density and power density. Discovery and optimization of those battery materials are crucial in improving their performance and accelerating commercialization. In …

"Leaf It To The Trees": Assessing The Cooling Effects Of Tree Canopy On Campus Microclimates, Andrea Sophia Realyvasquez

Posters - 2026

Urban heat island (UHI) effects are becoming increasingly common worldwide, with lived experiences and media coverage highlighting the negative consequences of urban development for humans and the environment. Urbanization, like many other aspects of society, should not remain stagnant and outside the scope of innovation. Understanding the interplay between urban morphology and temperature distributions is crucial in informing effective policy development (AbbegCoproski et al. 2024). tion to a political approach to reducing surface temperatures, there is the social aspect of difficulty in evading UHI in microclimates. University campuses are among the many areas that struggle to overcome old infrastructure and …