Digital Commons Network^™

Breaking The Reasoning Barrier: A Survey On Llm Complex Reasoning Through The Lens Of Self-Evolution, Tao He, Hao Li, Jingchang Chen, Runxuan Liu, Yixin Cao, Lizi Liao, Zihao Zheng, Zheng Chu, Jiafeng Liang, Ming Liu, Bing Qin

Research Collection School Of Computing and Information Systems

The release of OpenAI’s O1 and subsequent projects like DeepSeek R1 has significantly advanced research on complex reasoning in LLMs. This paper systematically analyzes existing reasoning studies from the perspective of self-evolution, structured into three components: data evolution, model evolution, and self-evolution. Data evolution explores methods to generate higher-quality reasoning training data. Model evolution focuses on training strategies to boost reasoning capabilities. Self-evolution research autonomous system evolution via iterating cycles of data and model evolution. We further discuss the scaling law of self-evolution and analyze representative O1-like works through this lens. By summarizing advanced methods and outlining future directions, this …

Simulating Before Planning: Constructing Intrinsic User World Model For User-Tailored Dialogue Policy Planning, Tao He, Lizi Liao, Ming Liu, Bing Qin

Research Collection School Of Computing and Information Systems

Recent advancements in dialogue policy planning have focused on optimizing system agent policies to achieve predefined goals, emphasizing strategy design, trajectory acquisition, and training efficiency. However, these approaches often overlook the critical role of user characteristics, which are essential in real-world scenarios like conversational search and recommendation, where interactions must adapt to individual user traits such as personality, preferences, and goals. To address this gap, we conduct a comprehensive study using task-specific user personas to evaluate dialogue policy planning under diverse user behaviors. Our analysis, based on these user profiles, reveals significant shortcomings in existing approaches, underscoring the necessity for …

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

Morehead State Press Release Archive, 1961 to the Present

Press releases for July of 2025.

Hot Donors In Cataclysmic Variables: The Case Of Ei Psc, Jan Kára, S. Zharikov, M. Wolf, N. Vaidman, A. Agishev, S. Khokhlov, C. E. Chavez

Physics & Astronomy Faculty Publications

Context. We present results of time-resolved optical spectroscopy and photometry of the short-orbital period dwarf nova EI Psc.

Aims. This study aims to determine fundamental system parameters of EI Psc, study properties of accretion structures in the system, and investigate its origin and current evolution state.

Methods. We analyse newly obtained time-resolved spectroscopic and photometric observations as well as archival data. We used light curve modelling, Doppler tomography, and MESA evolutionary models to study the characteristics of EI Psc.

Results. The system contains a relatively low temperature (T_eff = 6130 K) white dwarf with mass of M …

An Exponential Cone Integer Programming And Piece-Wise Linear Approximation Approach For 0-1 Fractional Programming, Hoang Giang Pham, Thuy Anh Ta, Tien Mai

Research Collection School Of Computing and Information Systems

We study a class of binary fractional programs commonly encountered in important application domains such as assortment optimization and facility location. These problems are known to be NP-hard to approximate within any constant factor, and existing solution approaches typically rely on mixed-integer linear programming or second-order cone programming reformulations. These methods often utilize linearization techniques (e.g., big-M or McCormick inequalities), which can result in weak continuous relaxations. In this work, we propose a novel approach based on an exponential cone reformulation combined with piecewise linear approximation. This allows the problem to be solved efficiently using standard cutting-plane or branch-and-cut procedures. …

Evaluating Chatgpt To Answer Multi-Modal Exercises In Computer Science Education, Eng Lieh Ouh, Kar Way Tan, Siaw Ling Lo, Benjamin Gan

Research Collection School Of Computing and Information Systems

This study investigates ChatGPT-4o's ability to answer multi-modal assessment exercises in computer science (CS) courses. While the use of large language models (LLMs) to answer text-based exercises are extensively researched, their ability to answer exercises involving artifacts of other modalities remains underexplored. To close this gap, we evaluate ChatGPT-4o's answers to 120 multi-modal CS exercises in programming, software design, human-computer interaction, statistical analysis, process analysis, and simulation. The multi-modal artifacts in these exercises include class diagrams, sequence diagrams, user interface images, analytical charts, workflow diagrams and object-flow diagrams. Our comparisons to the expected answers of these exercises show that ChatGPT-4o …

Empowering Weight Loss: A Pragmatic Randomized Controlled Trial Of A Theory-Driven Self-Regulation Mobile App For Young Adults With Excess Body Weight, H. S. J. Chew, J. W. Ngooi, R. C. Du, P. Z. Chan, M. Jansson, B. Zhu, Y. Cao, Chong-Wah Ngo, R. Foo, A. Shabbir, D. Ho, N. Sevdalis, K. Y. Ngiam

Research Collection School Of Computing and Information Systems

Background/Introduction: Obesity is projected to affect more than half of the global population by 2035, posing significant health and economic challenges. While lifestyle modification is considered a cornerstone of weight management, its effectiveness often relies on substantial support systems. Purpose: This study aimed to evaluate the effectiveness of a 12-week, standalone Temporal Self-Regulation Theory (TST)-based weight loss mobile application, which integrates self-regulation techniques, food logging, and dietary nudging, in promoting weight loss among young adults with excess body weight. Methods: A two-arm, parallel-group, 1:1 randomized controlled trial was conducted, adhering to the CONSORT-Outcomes 2022 Extension guidelines. Participants completed a face-to-face …

Cracking Aegis: An Adversarial Llm-Based Game For Raising Awareness Of Vulnerabilities In Privacy Protection, Jiaying Fu, Yiyang Lu, Zehua Yang, Fiona Fui-Hoon Nah, Ray Lc

Research Collection School Of Computing and Information Systems

Traditional methods for raising awareness of privacy protection often fail to engage users or provide hands-on insights into how privacy vulnerabilities are exploited. To address this, we incorporate an adversarial mechanic in the design of the dialogue-based serious game Cracking Aegis. Leveraging LLMs to simulate natural interactions, the game challenges players to impersonate characters and extract sensitive information from an AI agent, Aegis. A user study (n=22) revealed that players employed diverse deceptive linguistic strategies, including storytelling and emotional rapport, to manipulate Aegis. After playing, players reported connecting in-game scenarios with real-world privacy vulnerabilities, such as phishing and impersonation, and …

Political Ecologies Of Storage For The 21st Century, Sayd Randle, Matthew Archer

Research Collection College of Integrative Studies

New resource storage arrangements are proliferating rapidly both in terms of physical infrastructures-for the storage of things like "clean" energy, nuclear waste, carbon dioxide, fresh water, and data-and as part of a set of discursive moves that reinforce a vision of a near future world in which problems of climate change mitigation and adaptation in particular (but also issues like energy security, water security, industry growth, etc.) are solved through eco-modernist techno-fixes. This Symposium sketches the contours of a framework we term political ecologies of storage. In doing so, we treat storage as both a potent imaginary and a concrete …

Artificial Insights Or Historical Fidelity? Crafting An Ethical Framework For The Use Of Genai In The Restoration, Reconstruction And Recreation Of Movable Cultural Heritage, David Ocón, Chunzhi Yin, Jose Luna

Research Collection School of Social Sciences

This article explores the ethical considerations surrounding using Generative Artificial Intelligence (GenAI) in preserving movable cultural heritage, focusing specifically on its application in restoration, reconstruction, and recreation. While GenAI offers innovative methods for preserving and recreating cultural heritage, it also presents significant ethical challenges. The article reviews current studies on the role of GenAI in heritage preservation alongside relevant ethical guidelines and proposes a tailored ethical framework for its application in movable heritage. The framework addresses several critical ethical concerns, including cultural integrity and sensitivity, accuracy and authenticity, intellectual property rights, sustainability and social impact, and governance and ethical accountability. …

What Are Anomalies In A Network?, Kai Ming Ting, Zhong Zhuang, Guansong Pang, Zongyou Liu, Tianrun Liang, Qiuran Zhao

Research Collection School Of Computing and Information Systems

This article examines a collection of assumptions used in the current literature on node anomaly detection in a network. The examination raises the question: What are anomalies in a network? Our attempt to answer this question has provided some interesting findings and led to some open questions. This is the first article which formally defines anomalies in a network and introduces the concept of self-verifiability of a detector without ground-truths in a network. They enable existing detectors to be categorized into two types along the line whether they are self-verifiable or not. We suggest a method to evaluate self-verifiable detectors …

Literature Review Of Reverse Electrodialysis Technoeconomic And Environmental Analysis, Kevin Allen Wear

Water Resources Science and Technology Theses and Graduate Research Reports (Archived)

This thesis presents a theoretical analysis of Reverse Electrodialysis (RED) for electricity generation using produced water—a high-salinity byproduct from oil and gas extraction. Drawing from over seventy peer-reviewed studies, this research explores the potential of RED as a sustainable energy solution for industrial wastewater streams. Chapter 1 outlines the environmental and economic implications of produced water. Chapter 2 reviews ion transport theories and membrane technologies. Chapter 3 evaluates past implementations of RED and related membrane systems. Chapter 4 delivers a comprehensive synthesis of current literature, modeling RED performance under realworld salinity gradients, ion compositions, and membrane constraints. Chapter 5 discusses …

Sensor Lag Adjustments On A Mobile Meteorological Cart In Tropical Environments: A Case Study From An Urban Park In Singapore, Moshe Eliezer Mandelmilch, Sin Kang Yik, Beatrice H. Ho, Graces N. Y. Ching, Peter J. Crank, Winston T. L. Chow

Research Collection College of Integrative Studies

This study adds to the growing literature on mobile platforms by examining the performance of the Singapore MaRTy (SMaRTy) in conducting mobile micrometeorological measurements along a designated route in an urban park in Singapore, reflecting a pedestrian walking experience. The main objective of the study was to calculate the sensor lag for the mobile climate measurements: Air Temperature (TA), and Relative Humidity (RH) of SMaRTy along a designated route in an urban park in Singapore based on data from fixed stations (HOBO sensors) in two significant synoptic meteorological periods during the Northeast and Southwest monsoons. Statistically significant regression models were …

Do Supplier Ceo's National Cultural Origins Affect Supplier-Customer Relationships?, Peng Liang, Hasan Cavusoglu, Nan Hu

Research Collection School Of Computing and Information Systems

This study investigates how the national cultural origins of supplier chief executive officers (CEOs), as characterized by Hofstede’s cross-cultural dimensions, influence the duration of supplier–customer relationships. By analyzing the cultural origins of supplier CEOs from 20 countries over a 25-year period, we find that supplier CEOs with high long-term orientation (LTO) and high uncertainty avoidance (UNA) are associated with longer lasting supplier–customer relationships, while those with high individualism (IND) are associated with shorter relationship durations. These findings are robust to several alternative explanations of customer and supplier CEO variables. To address potential endogeneity—specifically, the concern that CEOs with certain cultural …

Unraveling Nonperturbative Qcd With Transverse Momentum Hadronic Structures, Tommaso Rainaldi

Physics Theses & Dissertations

The main purpose of this thesis is to investigate the theoretical foundations of the factorization theorems that involve transverse quark and gluon momentum distributions, and to better understand the interface between foundational questions and phenomenological applications. Many of these applications involve using transverse parton momentum dependent (TMD) correlation functions as tools for probing the complex nonperturbative structures of the hadrons.

We first introduce the concepts of collinear and TMD factorization in a toy-model theory and, by leveraging the comparative simplicity of such a model, we test the range of validity and limitations of the factorization approach. At the same time, …

The Relationships Between Expectancy-Value Beliefs, Communal Value Beliefs, Family Identity, And Academic Persistence Among First- And Continuing-Generation College Students, Douglas W. Snuffer

STEMPS Theses & Dissertations

First-generation college students (students for whom neither parent has a 4-year college degree) have lower college graduation rates than their continuing-generation peers (Cahalan et al., 2021; Fry, 2021). First-generation students may experience barriers to higher education, leading to lower levels of academic achievement motivation for college. Two of these barriers may include 1) cultural mismatch (Stephens, Fryberg, et al., 2012) with colleges via communal value (a value set that emphasizes community and family over the self) and 2) a strong sense of family identity, which lends itself to perceived family obligations (Fuligni et al., 2007). To examine the relationships between …

Using Radium Isotopes To Compare Nutrient Inputs Via Submarine Groundwater Discharge To Offshore Export On The West Florida Shelf, Andrew L. Lindgren

OES Theses and Dissertations

Radium isotopes have been used to trace submarine groundwater discharge (SGD) and associated nutrient and metal inputs into the coastal ocean. They have also been used to estimate rates of diffusive mixing and export fluxes of dissolved constituents offshore. However, use of both approaches in tandem to determine the fate of groundwater inputs after they enter the coastal ocean is still relatively unexplored. Radium isotopes and nutrients were measured in two cross-shelf cruises on the West Florida Shelf in different seasons and in quarterly sampling of offshore wells. Through 226Ra mass balance and 223Ra-derived diffusive mixing rates, inputs of nutrients …

Towards Efficient Privacy-Preserving Deep Learning: He-Friendly Structures, Flexible Pruning, He-Efficient Architectures, And Secure Transformer Token Drop, Yifei Cai

Electrical & Computer Engineering Theses & Dissertations

Deep learning (DL) has become a powerful tool for solving complex problems, but developing DL models typically requires vast datasets, high computational resources, and expert knowledge—barriers that limit accessibility. Machine Learning as a Service (MLaaS) addresses this challenge by allowing resource-rich providers to deliver pre-trained DL models as services. However, privacy concerns arise: clients hesitate to share sensitive data, while providers protect their proprietary models. To address this, privacy-preserving MLaaS integrates cryptographic techniques into DL computations, as seen in frameworks like Cryptonets, SecureML, GAZELLE, CrypTFlow2, Cheetah, and BOLT. Among them, Homomorphic Encryption (HE) enables computation on encrypted data but remains …

Novel Validation Of Hdr Brachy Therapy Dosimetry For Cervical Cancer Using Egs_Brachy Monte Carlo Simulations: A Comparative Analysis With Oncentra Treatment Planning System., Duong Thanh Tai, Nguyen Thi Anh Thu, Tran Thien Thanh, Pham Anh Tuan, Marc J P Chamberland, Peter Sandwall, David Bradley, James C L Chow

Oncology Articles

PURPOSE: This study aims to validate HDR brachytherapy dosimetry for cervical cancer patients utilizing the egs_brachy Monte Carlo (MC) simulation.

METHODS: Three cervical cancer patients treated with

RESULTS: TPS-calculated doses were greater than those obtained from MC simulations. For the CTV, the median percentage differences were 7.9% (Q1: 6.4%, Q3: 9.8%; range: 0.4%-10.4%) for D

CONCLUSION: CTV and critical organ doses calculated by the TPS were consistently greater than those obtained from MC simulations. This suggests that the TPS may overestimate dose distributions, especially in heterogeneous regions like the pelvis. These results emphasize the need for continued validation of TPS …

Where Should The Cancer Control Interventions Target: A Geospatial Hotspot Analysis For Major Cancer Mortality 2018 To 2022 In The United States, Chongliang Luo, Saira Khan, Liyan Jin, Aimee S James, Graham A Colditz, Bettina F Drake

2020-Current year OA Pubs

BACKGROUND: Identifying changes in geographic disparities of cancer mortality reveals locations where cancer prevention and control efforts should be focused/targeted. We use recent cancer surveillance data to demonstrate the geographic disparity of major cancer mortality rates in the United States and its shift compared with previous data.

METHODS: This cross-sectional study used the 2018 to 2022 county-level mortality rates of colorectal, lung, breast, and prostate cancers from the Centers for Disease Control mortality data. Counties with suppressed death counts were imputed by spatial regression models. Getis-Ord Gi* statistics were used to evaluate the spatial clustering of county mortality. Identified hotspot …

Real-World Continuous Smartwatch-Based User Authentication, N. Al-Naffakh, N. Clarke, F. Li, P. Haskell-Dowland

School of Engineering, Computing and Mathematics

User authentication is often regarded as the “gatekeeper” of cyber security. It has, however, long suffered from significant usability issues that have resulted in research focussing upon frictionless and transparent biometric approaches. Activity-based user authentication—a technique that authenticates a user by what they are physically doing at a specific point in time has attracted significant attention, particularly due to the increasing popularity of smartwatches. This research aims to overcome limitations in prior work by exploring the viability of the approach in real-world conditions. The study presents two principal experiments, one focused upon a constrained environment to provide a control and …

Hadronic Vacuum Polarization For The Muon G-2 From Lattice Qcd: Long-Distance And Full Light-Quark Connected Contribution, Alexei Bazavov, Claude Bernard, David Anthony Clarke, Christine Davies, Carleton Detar, Aida X. El-Khadra, María Elvira Gámiz Sánchez, Steven Gottlieb, Anthony V. Grebe, Leon Hostetler, William Jay, Hwancheol Jeong, Andreas Kronfeld, Shaun Lahert, Jack Laiho, Gerard Lepage, Michael Lynch, Andrew Lytle, Craig Mcneile, Ethan Neil, Curtis Peterson, James Simone, Jacob W Sitison, Ruth S. Van De Water, Alejandro Vaquero Avilés-Casco, Craig Mcneile

School of Engineering, Computing and Mathematics

We present results for the dominant light-quark connected contribution to the long-distance window of the hadronic vacuum polarization (HVP) contribution to the muon g-2 from lattice quantum chromodynamics. Specifically, with a new determination of the lattice scale on MILC's physical-mass HISQ ensembles, using the Ω^{-} baryon mass, we obtain a result of a_{μ}^{ll,LD}(conn)=400.2(2.3)_{stat}(3.7)_{syst}[4.3]_{total}×10^{-10}. Summing this result with our recent determinations of the light-quark connected contributions to the short- and intermediate-distance windows, we obtain a subpercent precision determination of the light-quark-connected contribution to HVP of a_{μ}^{ll}(conn)=655.2(2.3)_{stat}(3.9)_{syst}[4.5]_{total}×10^{-10}. Finally, as a consistency check, we verify that an independent analysis of the full contribution …

Volume 34, Number 2, Summer/Fall 2025, Office Of Communications, Illinois Wesleyan University

Illinois Wesleyan University Magazine, 2018-present

VOLUME 34 | NUMBER 2 | Summer/Fall 2025

ON OUR COVER:

The Illinois Wesleyan University archives, housed on the fourth floor of The Ames Library, holds many artifacts of IWU history, including the original university charter and a gold medal awarded to John Marden, clas of 1909, for his breakthrough work in atomic science and engineering.

18 175 Years of Illinois Wesleyan University. Celebrate IWU's history with a timeline of the last 175 years of our community's milestones.

26 Alumni Award Winners. Meet our Award Winners John Camardella '03, Natalie Lalagos '12, and Carol Willis '68.

The B2biers System: A Content-Based Perspective On Maximizing Influence And Subscription In Social Networks, Konstantinos Theocharidis, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

The popular problem of Influence Maximization (IM) asks for the k users who can maximize the influence of a fixed post in a social network. In contrast, the problem of Content- Aware Influence Maximization (CAIM) asks for the k features to form a viral tunable post in a social network starting its diffusion from a fixed set of initial adopters. CAIM paves the way for a number of novel problems to be studied that altogether can lead to the development of a system that would be valuable for advertisers who manage social network pages. This holds since features (brands) in …

Position: Trustworthy Ai Agents Require The Integration Of Large Language Models And Formal Methods, Yedi Zhang, Yufan Cai, Xinyue Zuo, Xiaokun Luan, Kailong Wang, Zhe Hou, Yifan Zhang, Zhiyuan Wei, Meng Sun, Jun Sun, Jing Sun, Jin Song Dong

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing broad aspects of daily life. Despite their remarkable performance, LLMs exhibit a fundamental limitation: hallucination—the tendency to produce misleading outputs that appear plausible. This inherent unreliability poses significant risks, particularly in high-stakes domains where trustworthiness is essential. On the other hand, Formal Methods (FMs), which share foundations with symbolic AI, provide mathematically rigorous techniques for modeling, specifying, reasoning, and verifying the correctness of systems. These methods have been widely employed in mission-critical domains such as aerospace, defense, and cybersecurity. However, the broader adoption of FMs remains constrained …

Unified Neural Backdoor Removal With Only Few Clean Samples Through Unlearning And Relearning, Nay Myat Min, Long H. Pham, Jun Sun

Research Collection School Of Computing and Information Systems

Deep neural networks have achieved remarkable success across various applications; however, their vulnerability to backdoor attacks poses severe security risks—especially in situations where only a limited set of clean samples is available for defense. In this work, we address this critical challenge by proposing ULRL (UnLearn and ReLearn for backdoor removal), a novel two-phase approach for comprehensive backdoor removal. Our method first employs an unlearning phase, in which the network’s loss is intentionally maximized on a small clean dataset to expose neurons that are excessively sensitive to backdoor triggers. Subsequently, in the relearning phase, these suspicious neurons are recalibrated using …

Advancing Food Nutrition Estimation Via Visual-Ingredient Feature Fusion, Huiyan Qi, Bin Zhu, Chong-Wah Ngo, Jingjing Chen, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Nutrition estimation is an important component of promoting healthy eating and mitigating diet-related health risks. Despite advances in tasks such as food classification and ingredient recognition, progress in nutrition estimation is limited due to the lack of datasets with nutritional annotations. To address this issue, we introduce FastFood, a dataset with 84,446 images across 908 fast food categories, featuring ingredient and nutritional annotations. In addition, we propose a new model-agnostic Visual-Ingredient Feature Fusion (VIF2 ) method to enhance nutrition estimation by integrating visual and ingredient features. Ingredient robustness is improved through synonym replacement and resampling strategies during training. The ingredient-aware …

Unbounded Multi-Hop Proxy Re-Encryption With Hra Security: An Lwe-Based Optimization, Xiaohan Wan, Yang Wang, Haiyang Xue, Mingqiang Wang

Research Collection School Of Computing and Information Systems

Proxy re-encryption (PRE) schemes enable a semi-honest proxy to transform a ciphertext of one user i to another user j while preserving the privacy of the underlying message. Multi-hop PRE schemes allow a legal ciphertext to undergo multiple transformations, but for lattice-based multi-hop PREs, the number of transformations is typically bounded due to the increase of error terms. Recently, Zhao et al. (ESORICS 2024) introduced a lattice-based unbounded multi-hop (homomorphic) PRE scheme that supports an unbounded number of hops. Nevertheless, their scheme only achieves the selective CPA security. In contrast, Fuchsbauer et al. (PKC 2019) proposed a generic framework for …

An Incentive Mechanism For Privacy Preserved Data Trading With Verifiable Data Disturbance, Man Zhang, Xinghua Li, Bin Luo, Yanbing Ren, Yinbin Miao, Ximeng Liu, Robert H. Deng

Research Collection School Of Computing and Information Systems

To motivate data owners’ (DOs’) trading willingness, the existing incentive mechanisms allow DOs to independently disturb data following data consumer's (DC’s) availability requirement. However, they cannot motivate DOs’ honest disturbance, which is attributed to DOs’ independent disturbance without any supervision. Thus, we implement an incentive mechanism for privacy preserved data trading with verifiable data disturbance where an honest-but-curious disturbance generator (DG) is additionally introduced to supervise DOs’ local disturbance and assist disturbance verification between DOs and DC. Specifically, DG generates the disturbance strategies and secretly distributes to DOs following private information retrieval, guaranteeing DOs's local disturbance's privacy and verifiability with …

Action Dubber: Timing Audible Actions Via Inflectional Flow, Wenlong Wan, Weiying Zheng, Tianyi Xiang, Guiqing Li, Shengfeng He

Research Collection School Of Computing and Information Systems

We introduce the task of Audible Action Temporal Localization, which aims to identify the spatiotemporal coordinates of audible movements. Unlike conventional tasks such as action recognition and temporal action localization, which broadly analyze video content, our task focuses on the distinct kinematic dynamics of audible actions. It is based on the premise that key actions are driven by inflectional movements; for example, collisions that produce sound often involve abrupt changes in motion. To capture this, we propose T A2Net, a novel architecture that estimates inflectional flow using the second derivative of motion to determine collision timings without relying on audio …