Digital Commons Network^™

A Scoping Review Of Sycophancy In Large Language Models: Operational And Theoretical Recognition, Kallen Zhou, Manning Littlejohn, Isabella Garrard

Endeavors: Mississippi State Undergraduate Research Journal

As large language models (LLMs) usage grows across different domains, sycophancy, the tendency for output to align with users, is increasingly being recognized as a primary issue arising from applying LLMs into critical areas. Current research has provided a variety of theoretical definitions, mitigation techniques, and quantification for sycophancy. However, there is little to no consistency across different papers. This scoping review seeks to connect different works on LLM sycophancy by identifying themes in theoretical definitions, measurement methods, and inducement techniques of sycophancy. By analyzing 26 papers (preprints, conference proceedings, and journal articles) from arXiv, ACL Anthology, and Scopus, this …

Generalized Delayed Black–Scholes Formula, Bi Gole Hubert Le, Auguste Aman

Journal of Stochastic Analysis

The aim of this paper is to derive an explicit pricing formula for European options when the underlying asset follows a linear generalized delay differential equation in two distinct financial markets. The pricing methodology is based on the construction of an equivalent martingale measure using Girsanov’s theorem. Our models preserve both the no-arbitrage condition and market completeness. As such, this work extends the framework previously developed by Arriojas et al. in [16], providing a broader class of delay-based option pricing models.

Novel Connotations Of Green Exploration Oriented To Mine Ecological Restoration, Hu Zhenqi, Zhang Fan, Zhao Yanling, Liang Yusheng

Coal Geology & Exploration

Background Mineral resource exploitation inevitably causes ecological damage, while its green solution is rooted in green exploration. Currently, green exploration refers to activities aimed at avoiding, eliminating, or mitigating ecological pollution and damage caused by exploration operations, as well as those intended for the restoration of the ecosystem damaged in the exploration process. However, besides focusing on the exploration process, green exploration should provide geological guarantees for ecological restoration following resource exploitation. [Methods] In this study, the novel connotations of green exploration are proposed first. In other words, green exploration, which should be oriented to the demand for mine …

Exploration Of Talent Cultivation System And Practical Model For Simulation And Optimization Of Intelligent Manufacturing System, Xinyu Li, Zheng Duan, Liang Gao, Chunjiang Zhang, Peigen Li

Journal of System Simulation

To address problems such as the insufficient integration of science and education in the talent cultivation system for traditional manufacturing system simulation and optimization, the insufficient integration of industry and education in cultivation goals and approaches, and the lack of full-chain industrial-level practical cultivation means, a "1223" reform scheme for innovative talent cultivation in the intelligent manufacturing system was formed. Research and practice were carried out focusing on the talent cultivation system, cultivation approaches, and practical cultivation resources for the simulation and optimization of the intelligent manufacturing system. Significant outcomes were achieved in aspects of innovative talent cultivation, faculty and …

Four-Dimensional Gradient Integration: Reform And Practice On Modeling And Simulation Courses For Management Disciplines, Bin Wu, Huagang Tong, Zhiyong Cui, Feiyi Yan

Journal of System Simulation

In the process of course implementation, local universities generally face problems such as students' weak mathematical and physical foundations, disconnection between teaching content and technological frontiers, single teaching method, and fragmented cultivation of practical capability. Based on long-term teaching reform practice, a four-dimensional gradient integration teaching model of "value guidance, knowledge restructuring, scenario innovation, and capability progression" was proposed, and its theoretical logic, implementation path, and practical effect were systematically elaborated. This model can effectively stimulate students' intrinsic motivation for learning, promote the digital and intelligent updating of teaching content, expand the teaching scenario of industry-education integration, and realize …

Learning Trajectories Of Online Batch Selection Methods, Luke Green

Theses and Dissertations

Modern deep neural networks achieve strong performance on large-scale datasets, but often require substantial training time. Online batch selection methods seek to reduce this cost by updating models on informative subsets of each batch rather than on all available examples. Recently introduced methods leverage teacher models and report substantial speedups, particularly in noisy-label settings. However, comparisons are often based on the number of epochs required to reach a target test accuracy, a coarse metric that is sensitive to implementation details and may obscure important differences in learning dynamics. In this thesis, we implement several online batch selection methods in a …

Disciplinary System Of Artificial Intelligence: Connotation, Architecture, And Development Suggestions, Academic Divisions Of The Chinese Academy Of Sciences Discipline Group Of Advisory Project On Ai-Empowered Scientific Research

Bulletin of Chinese Academy of Sciences (Chinese Version)

The discipline of artificial intelligence studies the theories, methods, systems, applications, enabling functions, ethics, and governance of artificial intelligence, and is a typical interdisciplinary field. With the rapid development of artificial intelligence in recent years, its disciplinary connotations and system architecture urgently require renewed examination. Based on the analysis of development trends of artificial intelligence, this paper elucidates the connotations of the AI discipline from four perspectives: theoretical methods, forms of intelligence, disciplinary integration, and application empowerment. It further proposes a disciplinary system framework for artificial intelligence comprising foundational supporting disciplines, core body of knowledge, major forms of intelligence, and …

Development Of An Adaptive Pelican Crossing Model Using Fuzzy Logic In Mixed Traffic Conditions, Manazil Adam, Andyka Kusuma, R. Jachrizal Sumabrata

Smart City

Traffic management at at-grade pedestrian crossing facilities (pelican crossings) in highly populated areas, such as the Universitas Indonesia Station, faces significant inefficiency challenges. During peak hours, the fixed-time system is frequently disabled and replaced with subjective manual control by security personnel, thereby triggering irregular stop-and-go cycles and a high accumulation of vehicle delays. This study aims to develop a hybrid adaptive control model integrating Computer Vision, Genetic Algorithm (GA), and Fuzzy Logic to optimize intersection performance under mixed traffic conditions. The research methodology begins with the extraction of traffic and pedestrian characteristic data, calculated manually through recorded field observations. This …

You Mean What? Commognitive Conflict In Resolving Contextual Logarithm Problems, Endrayana Putut Laksminto Emanuel, Fatkul Anam, Radhitya Duta Pradana, Anik Kirana, Sikky El Walida

Jurnal Pendidikan Sains

Students’ approaches to solving contextual mathematics problems involving logarithms vary significantly due to differences in their prior mathematical understanding. These differences may trigger commognitive conflict during the interpretation and reasoning processes when students attempt to construct mathematical meaning from contextual situations. This qualitative study aimed to explore how commognitive conflict emerges as a mechanism of mathematical interpretation in students’ discourse while solving logarithmic contextual problems. Twenty students participated in the study and were grouped based on their performance. One student was selected as the main research subject for an in-depth analysis. The findings reveal that commognitive conflict appeared in two …

Learning In Infants Using Intrinsically Motivated Goal Conditioned Reinforcement Learning, T I Darsan

Master’s Dissertations

Traditional artificial intelligence models learn by passively digesting large datasets. In contrast, human infants discover skills by actively interacting with their bodies and environments without explicit external rewards. This thesis introduces the Composer Architecture, a machine learning framework designed to mimic this autonomous, open-ended development. The Composer architecture operates in a multi-stage loop, the latent model using Contrastive Learning Through Time (CLTT) to compress high-dimensional raw data from visual, proprioceptive, and touch sensors into a low-dimensional space. To preserve data relationships and prevent topological collapse, a Softmax activation forces these latent representations to lie smoothly on a probability simplex. A …

State Government, The Forgotten Cyber Actor, Joshua D. Strubel

Doctoral Dissertations and Projects

Cyber incidents are among the most pervasive threats facing the United States, with the FBI recording over 859,000 reported attacks and an estimated $16.6 billion in losses in 2024 alone. Despite widespread recognition that effective cyber defense requires a whole-nation approach, the existing research literature overwhelmingly focuses on federal policy, leaving state governments as largely overlooked actors. This study addresses that gap by examining the research question: How does state cybersecurity policy affect malicious cyber actors' frequency of operations? Drawing on multilinear regression analysis augmented by Random Forest machine learning models, this study evaluates the relationship between state-level cyber deterrence …

Adaptive Intervention Strategies In Co-Evolving Multiplex Networks: A Reinforcement Learning Approach To Real-Time Misinformation Containment, Anjali Ashokrao Bhadre Dr., Harshvardhan Prabhakar Ghongade Dr.

Northeast Journal of Complex Systems (NEJCS)

The growing transmission of misinformation via social media creates serious challenges to public health, democracy and social cohesion. To date, methods used to contain misinformation rely upon static representations of networks and set rules for interventions. In contrast, this study presents the first Multiplex Adaptive Reinforcement Intervention Network (MARIN), a framework for real-time adaptive intervention in the context of dynamic misinformation transmission using co-evolving multiplex networks and deep reinforcement learning. Unlike past studies that have assumed static network structures, MARIN has the ability to allow for dynamic changes in network topology as a result of both misinformation transmission and intervention …

Improving Approach Of Evolutionary Strategies For Clustering Technique Enhancement, Duaa Mahde Saleh, Hasanen S. Abdullah, Ahmad Zamsuri

Journal of Soft Computing and Computer Applications

The existence of the information has been the essential aspect of the whole society. Information is concentrated in all forms to be effectively utilized. Clustering — an unsupervised learning technique. It is based on data similarity that gives rise to issues in collection, challenges and instability in data structure. It proposes an advanced evolutionary method by combining two approaches. Firstly, it adopts the evolutionary approach and integrates the advantages between two methods to design one. Among them are Differential Evolution (DE) and Genetic Algorithm (GA), Evolutionary Strategy (ES) and Genetic Programming (GP), and Evolutionary Programming (EP) and Particle Swarm Optimization …

Skin Lesion Classification Using Cnn Model And Augmented Dataset, Mohammed Nawzad Mohammed-Ramzi, Aso M. Aladdin

Journal of Soft Computing and Computer Applications

Skin cancer is a deadly disease. Skin lesion classification is a critical challenge due to its prevalent and deadly nature. Skin lesions are difficult for dermatologists to detect using eye examination, which is time-consuming and variable. A deep learning model of skin lesions classification has been proposed using a Convolutional Neural Network (CNN) trained on the HAM10000 dataset of 10,015 dermatoscopies. To improve resilience and address the dataset's extreme class imbalance, data augmentation techniques such as geometric transformations, brightness/contrast adjustments, blurring, noise addition, histogram equalization, color space alterations, and elastic deformations are used. With a carefully balanced 10% test set, …

Cardiovascular Disease Subtypes And Alzheimer's Disease: Phenotypic And Genetic Associations In The Uk Biobank And All Of Us Research Program, Aili Toyli, Chen Zhao, Kuan Jui Su, Hui Shen, Hong Wen Deng, Qing Hui Chen, Qiuying Sha, Weihua Zhou

Michigan Tech Publications

BACKGROUND: Cardiovascular disease (CVD) and Alzheimer's disease (AD) are major public health concerns that share overlapping risk factors and potential mechanistic pathways. Although vascular contributions to cognitive decline are well documented, the specific relationships between AD and different CVD subtypes remain poorly understood. METHODS: In this cross-sectional study, we examined associations between AD and 11 CVD subtypes using logistic regression models in 2 large biobanks: the UK Biobank (n=502 133) and the All of Us Research Program (n=287 011). Models were adjusted for demographic, lifestyle, and clinical covariates. We also explored genetic overlap between AD and CVD traits through proximity-based …

The Dynamics Of Educational Change: A Complex Systems Perspective, Preethi Nanjundan, Lijo Thomas, Abith K. Sunil

Northeast Journal of Complex Systems (NEJCS)

The perception of university teachers toward educational reforms plays an important role in determining the success of changes introduced in the education sector. This study focuses on teachers’ attitudes toward change, their emotional responses, and their overall views on educational reforms. Across the world, many educational reforms have failed to achieve their expected outcomes in improving teaching practices and student learning. As education systems are highly complex, the approach toward implementing reforms has also changed over time. Some reforms are introduced gradually, while others involve major innovations within the system. Complexity theory provides useful insights and tools that help educators …

Lock Scheduling Decisions And Strategy Optimization Under Operation Interruption Scenarios, Junhe Li, Qiang Zhang, Junpeng Jiang, Jiangchao Bao

Journal of Marine Science and Technology–Taiwan

Locks are critical nodes in inland waterway transportation systems that concentrate vessel traffic between upstream and downstream reaches, making their operations highly sensitive to hydrological conditions. Therefore, disruptions caused by droughts, floods, or routine maintenance can easily trigger congestion. To address this issue, this study systematically examines the interrelationships among the number of ships awaiting passage, scheduling strategies, the trade-off between lock chamber utilization and ship waiting time, the influence of ship entry sequences on user satisfaction, and the combined effects of these factors on overall lock scheduling performance. Based on these analyses, an integrated decision-making model for two-stage ship …

Face-To-Face Versus Distance Education In Competence-Based Maritime Education And Training, Clara Borén, Marcella Castells-Sanabra, Manel Grifoll

Journal of Marine Science and Technology–Taiwan

The COVID-19 pandemic created significant challenges for higher education, with universities being shut down and face-to-face teaching and assessment shifting to an online format. This presented an opportunity to focus on the continuity of learning through distance education, especially in the maritime context, due to the on-board training requirements, and even though five years have passed, this shift has reshaped the education landscape, proving that remote learning has come to stay.

At the Barcelona School of Nautical Studies, we have developed a weather routing software in the framework of distance education and teaching innovation. We conducted a teaching trial alternatively …

Gamma Belief Functions And Fuzzy Sets And Application To Combining Predictive Models, Liping Liu

University Research

Extending classic finite frameworks to continuous settings, this paper proposes the concept of gamma belief functions and gamma fuzzy sets. It shows that both the combination of gamma belief functions and the intersection of gamma fuzzy sets remain within the gamma family, enabling their application in combining gamma probability judgments in decision making and gamma regression models in ensemble learning. Using both simulated and real datasets, and under both constant and varying dispersion assumptions, experimental results show that the combined gamma regression models closely approximate the reference models learned from the full datasets, aligning with the objectives of bootstrapping. Notably, …

(Re)Claiming Homeplace: Dance As Embodied Resistance & Healing For Health & Spatial Justice, Preeya G. Kannan

University Honors Theses

This thesis argues that dance functions as both an upstream public health intervention and a form of radical spatial resistance; creating healing, agency, and belonging among historically marginalized communities. Drawing on bell hooks' concept of homeplace, Jasbir Puar's assemblage theory, Nancy Krieger's eco-social theory, and Katherine McKittrick's Black geographies, I position the body as both an ecological and political landscape shaped by histories of colonialism, racial capitalism, displacement, and resilience.

Through this community-based participatory research study, Homeplace, I explore dance as a form of social prescription that centers liberation rather than pathology. Movement is often reduced in public health discourse …

Beyond The Best Prompt: A Coverage View Of Multilingual Reasoning, Harshiv Mistry

University Honors Theses

Multilingual LLMs reason more accurately in English than in other languages, and recent work links part of this gap to reasoning behavior: native-language traces contain fewer cognitive behaviors (verification, backtracking, subgoal setting, backward chaining) that support effective problem solving. We test whether prompting for these behaviors at inference time narrows the gap, across seven conditions varying chain-of-thought, instruction and reasoning language, and cognitive-behavior descriptions, on two models, three languages. We find that English-scaffolded reasoning is the strongest single strategy on both models, closing the Hindi gap on Qwen, though the explicit scaffold's value over plain chain-of-thought is model-dependent. Beyond aggregate …

Digital Bodily Autonomy: Consent Issues, Labor Displacement, And Legal Understandings Of Ai Generated Deepfake Pornography, Mariah Barrett

Undergraduate Theses, Capstones, and Recitals

In the United States, nonconsensual pornographic deepfakes are becoming an increasingly prevalent problem as AI deepfake creation software improves and becomes widely available. Despite this, patchwork legislation across the country is inconsistent and conflicting regarding this issue. In this paper, I explore the background of pornography and obscenity laws and demonstrate how these frameworks are not properly constructed to apply to the digital sphere. Then, I address major themes within deepfake literature such as consent issues, bodily autonomy, labor displacement, and verifiable identity as a commodity through the case study of OnlyFans. I explore current and proposed legislation within the …

Data Governance Maturity, Ai Integration, And Equity In Colorado K-12 Public Schools, John R. Curtin

Electronic Theses and Dissertations

Colorado's 179 K-12 public school districts operate as autonomous governance units, each responsible for securing and managing student data assets that span health, financial, residential, and academic records. The accelerating integration of artificial intelligence (AI) and machine learning (ML) tools into administrative workflows, productivity software, and instructional platforms has fundamentally altered the risk landscape for student data, yet governance frameworks at the state, district, and school levels have not kept pace. This dissertation investigates whether Colorado's decentralized educational governance structure is institutionally capable of producing equitable, secure, and sustainable data governance outcomes in the AI era.

Drawing on Institutional Theory …

Evaluation And Distillation Of Source Code Generation Tasks By Large Language Models, Danny Brahman

Electronic Theses and Dissertations

Large Language Models (LLMs) are predominantly assessed based on their common sense reasoning, language comprehension, and logical reasoning abilities. While models trained in specialized domains like mathematics or coding have demonstrated remarkable advancements in logical reasoning, there remains a significant gap in evaluating their code generation capabilities. Existing benchmark datasets fall short in pinpointing specific strengths and weaknesses, impeding targeted enhancements in models’ reasoning abilities to synthesize code.

To bridge this gap, this thesis introduces two novel contributions: CodeEval and CodeQual. CodeEval is an innovative, pedagogical benchmarking method that mirrors the evaluation processes encountered in academic programming courses. It comprises …

Predicting Cybermindfulness With The Cyber-Health Belief Model, James Robinson, Yan Tian, Thomas Skill

Journal of Cybersecurity Education, Research and Practice

This study describes the development of a Cyber-Health Belief Model (CHBM). The health belief model (HBM) is a message strategy that is widely and successfully used in public health research [1] and has been extended into phish training. Most phish training programs assume  end users are victimized because they have insufficient information to defend themselves. While near-term training effectiveness has shown to be effective, evidence for sustained behavioral change is thin [4]-[7].  This problem indicates that the traditional approaches need to be reconsidered and that new models are needed.  Recent research suggests attentional deficits, cyber-fatigue and fatalism and a sense …

The Intersection Between Mindfulness And Cybersecurity: A Tool To Reduce Burnout And Improve Operational Effectiveness, Ivo Ricardo Dias Rosa

Journal of Cybersecurity Education, Research and Practice

Abstract: This paper offers a conceptual discussion of how mindfulness, understood as present moment awareness and deliberate attention regulation, can support cybersecurity professionals. Drawing on a narrative synthesis of workplace mindfulness, burnout, and high pressure decision making literature, we map plausible self regulation mechanisms to typical cyber defense tasks. Rather than presenting new empirical data, we develop an explanatory framework linking attention, reactivity, and recovery to decision quality, team communication, and adherence to incident playbooks. We focus on two connected outcomes: reducing burnout in roles with sustained cognitive and emotional demands, and improving operational effectiveness during critical situations such as …

Describing Hidden Curriculum In An Undergraduate Computing Context, Joseph R. Teahen, Briana C. Bettin, Leo Ureel

Michigan Tech Publications

Hidden Curriculum (HC) is the set of essential knowledge, skills, and norms students are expected to know, but never explicitly taught. HC is disproportionately experienced across identities and communities. In computing education, most research addresses immediately identifiable HC within the researcher's context. While such work is important, without proper HC descriptive studies, we could miss more subtle HC that affects student success. This work presents results from interviews with undergraduate computing faculty, students, and peer mentors on their HC experiences. The results demonstrate several categories of HC including development tools, professional skills, institutional navigation, social well-being, and physical well-being. These …

Rape Pregnancies And Consequent Ptsd Resulting From The Overturn Of Roe V. Wade, Emma Lindenfelser, Yulia Garaeva, Nenette Nti-Agyemang, Ellen Davis, Anna Kabwa, Alexandra M Calaman

Binghamton University Undergraduate Journal

Prior to the 1973 Roe v. Wade ruling, access to safe legal abortions was limited and often restricted along racial, economic, and geographic lines. Nearly fifty years later, women’s health policy evolved again following the 2022 Dobbs v. Jackson Women’s Health Organization decision overturning Roe v. Wade. This court ruling decimated federal protections of abortion. This paper presents the research that the 2022 Dobbs judicial decision may contribute to and exacerbate rape-related PTSD on 1 out of 20 American who are unable to access a safe abortion after a rape-related pregnancy. Pregnant women living in conservative states that have outlawed …

Rehabvr: A Virtual Reality System For Upper-Body Orthopaedic Physical Therapy Rehabilitation, Winnie Brenda Wanjiru Waiya

Computer Science Senior Theses

Physical therapy is a central component of rehabilitation for musculoskeletal conditions, yet adherence to prescribed treatment remains persistently poor. Jack et al. identified pain, boredom, and insufficient feedback as key barriers to treatment adherence in physiotherapy outpatient settings,¹ and Rucinski et al. confirmed that non-adherence rates in orthopaedic populations remain between 50 and 70%, with patients who disengage facing elevated risk of reoperation, progressive functional decline, and poor clinical outcomes.² According to the World Health Organization, approximately 1.71 billion people globally live with musculoskeletal conditions,³ with shoulder pain specifically carrying a community prevalence ranging from 0.67 to 55.2% worldwide and …

Chatgpt, Where Should I Go? A Qualitative Exploration Of How Large Language Models Are Experienced As Support For Travel Planning, Mohammad Amin Kuhail, Asbjørn Følstad, Saifeddin Alimamy

All Works

Large language models (LLMs) are increasingly used for travel planning. Yet, little is known about how travellers experience and interact with such language models. This qualitative study explores how users employ LLMs to plan trips, drawing on the hedonic/pragmatic model of user experience to examine functional and affective dimensions. We collected data from 104 participants with prior experience using LLMs for travel advice through open-ended questionnaire responses. Thematic analysis revealed three key insights: (1) users value the pragmatic benefits of LLMs, such as efficiency, clarity, and confidence in decision-making, while also appreciating hedonic qualities, including inspiration, enjoyment, and authenticity; (2) …