Digital Commons Network^™

Simulation And Optimization Of Task Offloading In Mine Edge Computing For Low-Concurrency Devices, Zhaolu Guo, Qianhui Liu

Journal of System Simulation

Abstract: With the advancement of mine intelligence, task offloading technology has become a core technology of mine edge computing (MEC). For edge computing systems deployed with mine low-concurrency devices (MLCD), a discrete-event simulation model for MEC task offloading oriented to MLCD was constructed to solve the collaborative optimization problem of task processing latency and load balancing of mine edge servers (MES). By dynamically simulating the queuing, transmission, and computation processes of tasks, the objective of minimizing task processing latency was achieved. An improved evolutionary algorithm, ISBT-EA, was proposed, which integrated a task-characteristic-driven initialization strategy and local search operators, enhancing the …

Prediction Of Industrial Concentration Parameters Based On Caudformer Model, Kaipeng Xu, Yan Wang, Xin Zhang, Yang Liu, Zhenzhong Wang, Xiang Liu, Zhicheng Ji

Journal of System Simulation

Abstract: To solve the problems in the industrial concentration process of traditional Chinese medicine that traditional prediction methods are difficult to deal with complex characteristics such as nonlinearity, high-dimensional coupling, and highly skewed distribution and that existing deep learning models insufficiently consider causal relationships among variables, ignore frequency-domain periodic characteristics, and lack long-range dependency modeling capabilities, an improved multivariate time series prediction model CauDformer was proposed in this paper. Based on the iTransformer architecture, a causal multi-head self-attention mechanism (C-MHSA) was introduced to compulsorily constrain the dependency direction among variables by utilizing a lower triangular causal mask, guiding the model …

Bibliography For "Faculty Publications Book Display", Sally Park

Library Displays and Bibliographies

A bibliography created to support a display about faculty publications during summer 2026 at the Leatherby Libraries at Chapman University.

Developing Solvent-Based Recycling Methods At Ambient Conditions To Regenerate Bisphenol A Diglycidyl Ether And Recover Metal Oxides From Epoxy Nanocomposites, Heaven Smith

Rose-Hulman Undergraduate Research Publications

No abstract provided.

Highly Confident But Slightly Uncertain: A Long Overdue Reinvention Of The School Scientific Method, Teaching - Volume 4, Stephen Demeo

Publications and Research

In Volume 4, the last book of the series, I continue the argument for greater parity between conceptual knowledge—the "what" of science—and methodological knowledge—the "how" of science—but in the context of teacher instruction. To this end, two literature reviews are presented: One on how students build confidence, specifically regarding the reliability or consistency of measurement or results, and the other on scientific uncertainty. Research studies focusing on student misconceptions are summarized and organized from the elementary to the college level. These literature reviews describe invaluable ways for teachers to improve their instruction, while providing examples of experiments that can be …

Midweek Memo, Georgia Southern University

Midweek Memo

• Applaud 
• Remember 
• Share 
• Experience 
• Around the Nest

Understanding And Cultivating Algebraic Thinking: A Case Study Of Middle Grades Multilingual Learners, Damiale Johnson

Curriculum and Instruction (Ed.D.) Dissertations

Multilingual learners often encounter challenges in mathematics classrooms due to the linguistic and interpretive demands of mathematical discourse and problem-solving. This qualitative case study investigated how three seventh-grade multilingual learners developed and demonstrated algebraic thinking during collaborative mathematical problem-solving tasks. Specifically, the study examined students’ strategies and resources, the challenges they encountered, and how language, collaboration, and representation supported algebraic and functional reasoning.

Guided by situated learning theory, sociocultural developmental theory, and the Algebraic Habits of Mind framework, the study emphasized social interaction, language, and contextualized problem-solving. Participants were Spanish-speaking multilingual learners developing academic proficiency in English in a middle …

Chaotropic And Kosmotropic Effects Of Brines On Protein Structure: Habitability Across The Solar System, Shelby Dawn Osborne

Graduate Theses and Dissertations

Salts exhibit unique and specific effects on biomolecular structure depending on the physical nature of the salt (ion density, formation of hydration shells, direct binding to protein). This thesis implements biochemical, thermodynamic, and computational methods to investigate how the nature of the salt effects protein structure, which aids in defining the habitability of various brine solutions. By using simple proteins and solar system relevant salts, we inspect the physical reactions of proteins to these saltwater environments to understand which salts stabilize or destabilize protein structure. Several methods of experimentation are utilized to provide an understanding of the interaction relevant to …

Statistical Machine Learning For Calibrating Climate Model Wind Fields., Augustine Ouru

Graduate Theses and Dissertations

This thesis investigates statistical calibration methods for wind data from Global Climate Models (GCMs), with emphasis on wind speed and wind direction. The analysis uses 30 years of daily observed and GCM wind records from 9 spatial locations in the South East USA. Wind is represented in polar coordinates, but also often modeled in Cartesian coordinates. Four calibration models are compared: a marginal wind speed model, an independent Cartesian model. The calibration models are based on semi-parametric quantile regression, a flexible conditional density estimator fitted using neural networks. The neural network objective functions are optimized using maximum likelihood estimation (MLE) …

On The True Interstellar Anisotropy Of Tev Cosmic Rays And Its Implications For The Local Interstellar Medium, Noufel D. Maalal

Theses and Dissertations

Several ground-based cosmic ray (CR) air shower experiments have produced sky maps of intensity anisotropy in the energy range from 1 TeV to a few hundred TeVs with very high statistics and angular resolution. These measurements provide opportunities to study CR sources and propagation in the interstellar medium (ISM). Such studies present two major difficulties. Firstly, CRs are deflected by the heliospheric magnetic field on the last stretch of their journey to Earth. Secondly, measurements at different latitudes are difficult to compare, leading to uncertainties in latitudinal variations on the order of the observed anisotropy. Experiments usually assume latitudinal variations …

Cdt-1d Cnn Integration With Simpson-Sobolev Regularization For High-Frequency Options Trading: With Fem-Based Heston Option Pricing, Daniel M. Margolis, Johannes Tausch, Arthur K. Selender

Mathematics Theses and Dissertations

This dissertation presents a computational framework for high-frequency options trading that combines Cross-Data-Type 1-D Convolutional Neural Networks (CDT-1D CNN) with Simpson-Sobolev regularization for directional prediction, and finite element methods (FEM) for realistic option pricing during backtesting. The core innovation lies in developing a mathematically rigorous regularization approach that maintains the adaptability of modern deep learning while enabling accurate evaluation through stochastic volatility models. The primary contribution is the Simpson-Sobolev regularization scheme, which extends traditional Sobolev regularization by incorporating Simpson’s rule for numerical integration. This approach achieves higher-order accuracy in approximating the Sobolev norms that control function smoothness. Simpson’s rule attains …

Toward Intentional Praxis: A Design Thinking Multi-Case Study Of Cognitive-Constructive Toolkit Implementation In An Elementary Professional Learning Community, Azam Nathaniel

Dissertations

Among several learning theories that were dynamic and constantly evolving with time, cognitive and constructive theories were predominant in the field of education. However, these theories often included overlapping and contrasting concepts, contributing to confusion in terminology among teachers and limited explicit use in instructional practice. Within the context of K-12 education, teachers demonstrated conceptual awareness of cognitive and constructive learning theories; however, the theories were not a part of day-to-day conversations and were minimally identified in practice. Instead, the theories were implicitly applied as teachers balanced competing professional responsibilities, including daily routines, syllabus requirements, district standards, new initiatives, differentiated …

Ethos: A Computational Framework For Material Culture Research, Chelsea L. Grafe

Department of Textiles, Merchandising and Fashion Design: Dissertations, Theses, and Student Research

Museum catalog records make large collections searchable, but they do not always preserve the reasoning behind the claims they contain. A record may present a quilt's identity as settled while leaving the reasoning behind that claim invisible, making it difficult for later researchers to check, question, or reuse. This project asks whether museum catalog data can be analyzed in a way that keeps each analytical claim connected to the evidence that supports it. To test this question, the project applies a material-first computational framework named Ethos. Ethos formalizes an object-centered inquiry sequence in which material dependencies establish where analysis begins …

The Role Of Complexity In Structural Transfer: A Corpus Study From Turkish And Bulgarian, Sarah Joy Russell

Theses and Dissertations

This study the explores the need to examine the increasingly varied methods of quantifying morphological complexity in regards to their ability to influence structural borrowing across languages, with particular attention to the distinction between enumerative complexity (enumeration of all of the morphemes and distinctions in a system) and integrative complexity (entropy-based calculation of the class distinctions of the system). While existing models in contact linguistics often assume that structurally simpler languages are more likely to serve as sources of grammatical transfer, such accounts typically rely on enumerative measures of complexity alone and do not fully account for the role of …

The Nature Of Divine Knowledge, Matthew Frise

Faith and Philosophy: Journal of the Society of Christian Philosophers

No abstract provided.

Black Brilliance By Design: Culturally Affirming Strategies For High School And Postsecondary Success, Kirsten E. Thornton

Education Dissertations

College and career readiness and access programming aims to prepare students for postsecondary enrollment and success. The intentional implementation of college and career readiness programming was introduced to address the achievement gap in educational outcomes, including but not limited to: graduation rates, college enrollment, college retention, and viable career opportunities. However, Black students who graduate high school and are not adequately academically and socially prepared for postsecondary education compared to their white and non-white counterparts. Current college and career readiness frameworks lack a culturally-relevant lens necessary to effectively address the unique needs of the Black communities in achieving college readiness. …

Absorption Characteristics Of A Passive Damper-Augmented Timoshenko Beam Using A Wave-Decomposition Approach, Samikhshak Gupta, Vijaya Venkata Narasimha Sriram Malladi

Michigan Tech Publications

Local impedance variations in structural waveguides partially reflect and absorb incidentflexural waves, motivating wave-based strategies for passive vibration control. This studydevelops and experimentally validates a wave-energy framework to quantify and optimizeflexural wave absorption by Kelvin–Voigt attachments on a finite Timoshenko beam.A finite element model is validated against Scanning Laser Doppler Vibrometry measurementsfrom a clamped–clamped aluminum beam with a passive damper mounted nearone end, with dashpot parameters identified through two independent approaches andthe discrepancies attributed to parameter uncertainty. Wave decomposition of the simulatedand measured velocity fields yields the power reflection coefficient ρ(ω) and powerabsorption coefficient α(ω) over the 0–15.3 kHz band. …

Math 119: Math For Elementary School Teachers Syllabus, Seth Lehman

Open Educational Resources

OER course syllabus for Math 119, Math for Elementary School Teachers, at Queens College

Improving Vector Embedding Generation Throughput For Neural Information Retrieval Models, Conrad Tkacz

Theses and Dissertations from DePaul University

For decades, advancements in information retrieval technologies have changed how individuals discover data with computer systems. More recent advancements in artificial intelligence (AI) have also made the benefits of neural information retrieval systems available to millions. These information retrieval systems help empower future discoveries, though this is not the case for scientific data and High-Performance Computing (HPC) systems. HPC systems can generate enormous amounts of data, and no tools are currently available that can ingest data at the rates required to efficiently build an information retrieval system to explore scientific data. This thesis explores the current state of constructing a …

Mathematical Methods For Engineering And Physics, Andrei Ludu

OER Main

Imagine if you could see the hidden laws that shape everything around us—engineered structures, natural phenomena, even the technology we use every day. Wouldn’t you want to harness this knowledge to create groundbreaking engineering solutions that impact the world?

My young, bright engineering friends. In an age where codes, software, and artificial intelligence promise solutions at the click of a button, you wonder – why should I invest my precious time and brainpower struggling with abstract theorems and unworldly equations? You might be asking why deep math is still relevant, especially in an age dominated by sophisticated technology. Whether …

Trattato Dell’Alcibra Amuchabile (Anonimo): A Guided Translation, Gary Towsley, Olympia Nicodemi

Geneseo Authors

The Trattato dell’Alcibra Amuchabile is a pre-modern algebra text from c. 1365. It is written in a Tuscan dialect of Italian and is situated in the abbacus school tradition, schools that taught the mathematics needed for a mercantile society. Like all the algebra written in Italy at the time, it was inherited from al-Khwarizmi and, like his, written with no symbols—no x’s, y’s, plus signs, etc. It was what is sometimes called “rhetorical algebra.”  There is very little source  material available in English from this important era in the history of algebra. This book helps fill that gap. …

Constrained Assortment Optimization Under The Mixed-Logit Model, Hoang Giang Pham, Tien Mai

Research Collection School Of Computing and Information Systems

In this paper, we study the assortment optimization problem under the mixed-logit customer choice model. While assortment optimization has been a central topic in revenue management for decades, the mixed-logit model is widely regarded as one of the most general and flexible frameworks for modeling and predicting customer purchasing behavior. The assortment optimization problem is known to be NP-hard to be approximated to any constant factor, even in the unconstrained case. To address this challenge, we first explore the submodularity properties of a simplified version of the objective function to derive novel semi-constant factor approximation solutions for assortment problems under …

Late-Night And Early-Morning Train Scheduling With Non-Traffic Hour Maintenance Window In Urban Rail Transit Systems, Yaochen Ma, Hai Yang, Hai Wang

Research Collection School Of Computing and Information Systems

Regular maintenance during non-traffic hours (NTH) is vital for the resilience of urban rail transit (URT) systems, yet an insufficient NTH maintenance window poses a challenge for URT systems in various cities. For instance, the Hong Kong MTR Corporation has noted that the required NTH maintenance time often exceeds the available window, prompting service adjustments such as earlier late-night closures and/or later early-morning starts. To address this challenge, this study develops an optimal scheduling framework that links late-night and early-morning URT services through the NTH maintenance window requirement to maximize public welfare. A Decoupled Optimization Model (DOM) first derives closed-form …

Accountable Agents In Software Engineering: An Analysis Of Terms Of Service And A Research Roadmap, Christoph Treude

Research Collection School Of Computing and Information Systems

AI coding assistants and autonomous agents are becoming integral to software development workflows, reshaping how code is produced, reviewed, and maintained. While recent research has focused mainly on the capabilities and impacts of productivity of these systems, much less attention has been paid to accountability: who is responsible when agents generate, modify, or recommend code? In practice, accountability is defined through the Terms of Service (ToS) and related policy documents that govern the use of AI-powered development tools.In this vision paper, we present a comparative analysis of the Terms of Service for widely used AI coding assistants and agent-enabled development …

Operationalizing Ethics For Ai Agents: How Developers Encode Values Into Repository Context Files, Christoph Treude, Sebastian Baltes, Marc Cheong

Research Collection School Of Computing and Information Systems

As AI coding agents become embedded in software development workflows, developers are beginning to operationalize ethical principles by encoding behavioral rules into repository-level context files for AI agents, such as AGENTS.md files. Rather than examining the ethics of AI agents in the abstract, this vision paper investigates how ethics and values are already being translated for AI agents into actionable instructions that shape agent behavior. Through a preliminary investigation, we find that developers are already embedding guidance related to fairness, accessibility, sustainability, tone, and privacy. These artifacts function as a developer-authored governance layer, translating abstract principles into situated, natural-language directives …

A Dataset Of Agentic Ai Coding Tool Configurations, Matthias Galster, Seyedmoein Mohsenimofidi, Levi Böhme, Jai Lal Lulla, Muhammad Auwal Abubakar, Christoph Treude, Sebastian Baltes

Research Collection School Of Computing and Information Systems

Agentic AI coding tools such as Claude Code and OpenAI Codex execute multi-step coding tasks with limited human oversight. To steer these tools, developers create repository-level configuration artifacts (e.g., Markdown files) for configuration mechanisms such as Context Files, Skills, Rules, and Hooks. There is no curated dataset yet that captures these configurations at scale. This dataset, collected from open-source GitHub repositories, fills that gap. We selected 40,585 actively maintained repositories through metadata filtering, classified them using GPT-5.2 to identify 36,710 as belonging to engineered software projects, and systematically detected configuration artifacts in these repositories. The dataset covers 4,738 repositories across …

Spatiotemporal Sycophancy: Negation-Based Gaslighting In Video Large Language Models, Ziyao Tang, Pengkun Jiao, Bin Zhu, Huiyan Qi, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Video Large Language Models (Vid-LLMs) have demonstrated remarkable performance in video understanding tasks, yet their robustness under conversational interaction remains largely underexplored. In this paper, we identify spatiotemporal sycophancy, a failure mode in which Vid-LLMs retract initially correct, visually grounded judgments and conform to misleading user feedback under negation-based gaslighting. Rather than merely changing their answers, the models often fabricate unsupported temporal or spatial explanations to justify incorrect revisions. To systematically investigate this phenomenon, we propose a negation-based gaslighting evaluation framework and introduce GasVideo-1000, a curated benchmark designed to probe spatiotemporal sycophancy with clear visual grounding and temporal reasoning requirements. …

Oscbench: Benchmarking Object State Change In Text-To-Video Generation, Xianjing Han, Bin Zhu, Shiqi Hu, Franklin Mingzhe Li, Patrick Carrington, Roger Zimmermann, Jingjing Chen

Research Collection School Of Computing and Information Systems

Text-to-video (T2V) generation models have made rapid progress in producing visually high-quality and temporally coherent videos. However, existing benchmarks primarily focus on perceptual quality, text–video alignment, or physical plausibility, leaving a critical aspect of action understanding largely unexplored: object state change (OSC) explicitly specified in the text prompt. OSC refers to the transformation of an object’s state induced by an action, such as peeling a potato or slicing a lemon. In this paper, we introduce OSCBench, a benchmark specifically designed to assess OSC performance in T2V models. OSCBench is constructed from instructional cooking data and systematically organizes action–object interactions into …

Tranx-Adapter: Bridging Artifacts And Semantics Within Mllms For Robust Ai-Generated Image Detection, Wenbin Wang, Yuge Huang, Jianqing Xu, Yue Yu, Jiangtao Yan, Shouhong Ding, Pan Zhou, Yong Luo

Research Collection School Of Computing and Information Systems

Rapid advances in AI-generated image (AIGI) technology enable highly realistic synthesis, threatening public information integrity and security. Recent studies have demonstrated that incorporating texture-level artifact features alongside semantic features into multimodal large language models (MLLMs) can enhance their AIGI detection capability. However, our preliminary analyses reveal that artifact features exhibit high intra-feature similarity, leading to an almost uniform attention map after the softmax operation. This phenomenon causes attention dilution, thereby hindering effective fusion between semantic and artifact features. To overcome this limitation, we propose a lightweight fusion adapter, TranX-Adapter, which integrates a Task-aware Optimal-Transport Fusion that leverages the Jensen-Shannon divergence …

Rendering Data Unlearnable By Exploiting Llm Alignment Mechanisms, Ruihan Zhang, Jun Sun

Research Collection School Of Computing and Information Systems

Large language models (LLMs) are increasingly trained on massive, heterogeneous text corpora, raising serious concerns about the unauthorised use of proprietary or personal data during model training. In this work, we address the problem of data protection against unwanted model learning in a realistic blackbox setting. We propose Disclaimer Injection, a novel data-level defence that renders text unlearnable to LLMs. Rather than relying on model-side controls or explicit data removal, our approach exploits the models’ own alignment mechanisms: injecting carefully designed alignment-triggers to prevent effective learning. Through layer-wise analysis, we find that finetuning on such protected data induces persistent activation …