Digital Commons Network^™

Research On Safety Monitoring System For Digital Twin Fully Mechanized Mining Face In Thin Coal Seams, Ya Liu, Zhaoyun Zhang, Cheng An, Canguang Zheng

Journal of System Simulation

Abstract: To solve the problems of opaque production processes, difficult expression of production information, and high difficulty in real-time model driving and safety monitoring in fully mechanized mining faces of thin coal seams, studying the use of digital twin technology and risk early warning models to solve beyond-visual-range visual production operations and safety monitoring control of the working face has important theoretical and practical value. This paper studied the construction methods of the digital twin system for fully mechanized mining faces in thin coal seams and discussed the construction of high-precision three-dimensional models, the real-time collection and processing conversion of …

Operational Agency: A Permeable Legal Fiction For Tracing Culpability In Ai Systems, Anirban Mukherjee, Hannah H. Chang

Research Collection Lee Kong Chian School Of Business

Modern artificial intelligence (AI) systems act with a high degree of independence yet lack legal personhood—a paradox that fractures doctrines grounded in human-centric notions of mens rea and actus reus. This Article introduces Operational Agency (OA)—a permeable legal fiction structured as an ex post evidentiary framework—and Operational Agency Graph (OAG)—a tool for mapping causal interactions among human actors, organizations, and AI systems. OA evaluates an AI’s observable operational characteristics: its goal-directedness (as a proxy for intent), predictive processing (as a proxy for foresight), and safety architecture (as a proxy for standard of care). OAG operationalizes that analysis by embedding these …

Research On Multi-Objective Hybrid Flow-Shop Scheduling With Order Splitting, Junjie Yu, Weixi Ji, Chen Chen, Jingyu Lu, Chaoyang Zhang

Journal of System Simulation

Abstract: To address the order splitting multi-objective hybrid flow-shop scheduling problem (OSMOHFSP), a dual-objective optimization model was formulated with the objectives of minimizing makespan and total order tardiness. Fixed sub-batch specification constraints were incorporated to reflect common splitting limitations in actual production. A sub-batch generation strategy based on a candidate set of sub-batch specifications was designed to efficiently filter feasible splitting combinations, effectively reducing the search space dimensionality and computational complexity. A hybrid multi-objective metaheuristic algorithm integrating NSGA-II and SA was proposed. The global search capability was enhanced by constructing two crossover and four mutation operators. An improved SA embedding …

Ultra-Short-Term Photovoltaic Power Prediction Method Based On Spatio-Temporal Feature Enhancement Of Ground-Based Cloud Images, Zhiwei Kou, Fengyue Xin, Xiaoming Cui, Yu Yin, Feifan Li, Yongsheng Qi

Journal of System Simulation

Abstract: In view of the time lag in ground-based cloud image acquisition and the insufficient accuracy of existing photovoltaic power prediction models, an ultra-short-term photovoltaic power prediction method named spatial-temporal feature enhancement-ground-based cloud image-improved LSTM (STFE-GCI-ILSTM), which is based on spatio-temporal feature enhancement-ground-based cloud images-improved long short-term memory (LSTM) network was proposed. A ground-based cloud image prediction model with multi-scale spatio-temporal feature enhancement (STFE-GCI) was constructed. By spatial feature enhancement, temporal feature enhancement, and multi-scale feature fusion technologies, the deep spatio-temporal features of historical cloud image sequences were extracted to generate future predicted cloud image sequences, thereby eliminating the time …

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 …

Survey On Learning-Based Dynamic Fault Localization: From Traditional Machine Learning To Large Language Models, Chunyan Liu, Yan Lei, Huan Xie, Jinping Wang, Yue Yu, David Lo

Research Collection School Of Computing and Information Systems

Learning-based dynamic fault localization techniques play a crucial role in the field of software engineering. These techniques dynamically execute test cases to meticulously extract useful knowledge from the execution information in the program, with the aim of identifying fault locations by leveraging machine learning, deep learning, and large language models. Currently, there is already a flourishing body of research that is intensely focused on learning-based dynamic fault localization. Research literature can be categorized into two main aspects for learning-based dynamic fault localization: data-based enhancements (i.e., the datasets) and model-based enhancements (i.e., the suspiciousness algorithms). Thus, we conduct an extensive literature …

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 …

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 …

A Framework For Top-K Queries With Constrained Preferences, Kyriakos Mouratidis, Nikolaos Chaloulakos, Bo Tang

Research Collection School Of Computing and Information Systems

Traditional rank-aware processing assumes a dataset that contains available options to cover a specific need (e.g., restaurants, hotels, etc) and users who browse that dataset via top-k queries with linear scoring functions, i.e., by ranking the options according to the weighted sum of their attributes, for a set of given weights. In practice, however, user preferences (weights) may only be estimated with bounded accuracy, or may be inherently imprecise due to the inability of a human user to specify exact weight values with absolute accuracy. Motivated by this, we define the constrained-preference top-k (CT) query. Given an approximate description of …

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 …

Train In Vain: Functionality-Preserving Poisoning To Prevent Unauthorized Use Of Code Datasets, Yuan Xiao, Yuchen Chen, Jiaming Wang, Wei Song, Jun Sun, Shiqing Ma, Yanzhou Mu, Juan Zhai, Chunrong Fang, Jin Song Dong, Zhenyu Chen

Research Collection School Of Computing and Information Systems

The widespread availability of large-scale code datasets has accelerated the development of code large language models (CodeLLMs), raising concerns about unauthorized dataset usage. Dataset poisoning offers a proactive defense by reducing the utility of such unauthorized training. However, existing poisoning methods often require full-dataset poisoning and introduce transformations that break code compilability. In this paper, we introduce FunPoison, a functionality-preserving poisoning approach that injects short, compilable weak-use fragments into executed code paths. FunPoison leverages reusable statement-level templates with automatic repair and conservative safety checking to ensure side-effect freedom, while a type-aware synthesis module preserves type correctness, suppresses static-analysis warnings, and …

Knowledge-State Generative Agents For Pre-Assessment Question Evaluation, Ping Fan Ke, Yi Meng Lau, Siaw Ling Lo

Research Collection School Of Computing and Information Systems

This paper introduces a Knowledge‑State Generative Agent framework for evaluating the quality of pre‑assessment questions. The framework employs large language model (LLM)–based agents prompted to adopt a teacher persona to simulate the responses of students with and without mastery of targeted knowledge components. A preliminary empirical study using archival data from 424 students enrolled in an Information Systems Management course indicates that the proposed approach yields interpretable metrics under Classical Test Theory. Results further show that agents instantiated with the relevant mastered knowledge components exhibit systematically higher performance than agents lacking such mastery. In addition, the study suggests that teacher-persona …

Life Cycle Of Lithium-Ion Battery Recycling Systems Enable Carbon Capture, Utilization, And Storage: A Review, Nabeel Al-Qirim, Mohammad Kamrul Hasan, Hussam Al Hamadi, Akm Ahasan Habib, Shayla Islam

All Works

The lithium-ion battery (LIB) is the primary component of electric vehicles (EVs), and its environmental consequences are significant for the eventual widespread adoption of EVs. Recycling used LIBs protects the environment and allows for the reuse of valuable materials. To achieve the goal of a circular economy, LIB recycling processes that conserve environmentally friendly resources and maintain sustainability need to be developed. The critical technology for achieving global climate goals is carbon capture, utilization, and storage (CCUS), which makes it possible to significantly lower carbon dioxide (CO2) emissions across power and industrial systems. The LIB recycling and CCUS are becoming …

Current State And Needs Of Clinical Laboratories In Latin America: A Cross-Country Assessment., Alejandro R. Molinelli, Elizabeth L. Palavecino, José C. Jara-Aguirre, Kerry Cosby, Allison Targowski, Barbara Goldsmith, Rosa Sierra-Amor, Juan D. García, Alicia Algeciras-Schimnich, Eugenio H. Zabaleta, Veronica I. Luzzi, Jessica M. Colón-Franco

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

The Association for Diagnostics & Laboratory Medicine (ADLM) aims to improve health by providing education to laboratory scientists worldwide. Different regions of the world face unique challenges shaped by their national and regional contexts. However, the needs of clinical laboratories worldwide remain largely understudied. To address this gap, we conducted a comprehensive needs assessment survey among laboratory professionals in the Latin American region. The survey was distributed to over 2708 individuals across Latin American countries and yielded 148 responses. Most respondents were from urban areas (74%) and worked in private hospital laboratories (45%), with microbiology (25%) and chemistry (23%) identified …

From Gap To Growth: Academic Librarian Perspectives On Why Collaboration And Curriculum Matter, Stephanie Hallam

Library Faculty Scholarship

Incoming undergraduate students possess information literacy skillsets impacted by several factors, such as prior development of information literacy skills, librarian-faculty collaboration, and GenAI advancements. Academic librarians’ perspectives on undergraduate students’ library use and information literacy skills were examined via a 2025 survey of 337 undergraduate academic librarians. Using the Pearson bivariate method, the authors identified themes pertaining to the challenges students face as well as librarian-proposed solutions. Open responses from librarians provide additional insights. The results showed that librarians desire faculty partnerships and collaborative library instruction to improve information literacy skills and library use.

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 …

Hope College Magazine, Volume 58, Number 1: Summer 2026, Hope College

Hope College Magazine

No abstract provided.

Supporting Firefighter Families: Addressing Occupational Disruptions Through An Occupation-Centered Approach, Tiana M. Gomez, Jazminne Orozco Arteaga, Karen Park

Summer 2026 OTD Capstone Symposium

Firefighting involves long shifts, unpredictable schedules, sleep disruption, and repeated exposure to occupational stressors that may affect not only firefighters but also their families. This doctoral capstone examined how the occupational demands of firefighting influence family roles, routines, habits, participation, and overall well-being. A convergent mixed-methods study included active or retired firefighters (n = 18) and adult firefighter family members (n = 10), with three participants also completing optional semi-structured interviews. Quantitative survey data were analyzed descriptively, while interview transcripts and open-ended responses were analyzed thematically using the Model of Human Occupation as a guiding framework. Findings demonstrated disruptions in …

Flow Conditioning And Vortex Reduction For Vertical Pump Inlets, Charles M. Burt

BioResource and Agricultural Engineering

There are 3 general hydraulic problems for vertical pump inlets. All can cause problems with pump impeller cavitation, reduced flow rates, lower pump efficiencies, and vibrations.

Household Water Use For Circular Transitions: Elasticity Estimates And Circular Economy Signals From Metro Manila, Albert E. Lamberte, Abed Alaswad, Luciano C. Batista

Angelo King Institute for Economic and Business Studies (AKI)

The study examines household water demand in Metro Manila and evaluates how demand behavior and infrastructure access shape the transition from a linear to a circular water and wastewater economy. Estimated prices, ranging from -0.441 to 0.468, and income elasticities, which are between 0.550 and 0.572, for those with and without access to both water and sewerage systems reveal consistently inelastic demand. Thus, water is treated as a necessity with limited behavioral responsiveness to tariff changes. The similarity of elasticities across service groups suggests that behavioral factors are not the primary constraint to circularity. Instead, the findings highlight that infrastructure …

Building Adaptive Leaders: Examining The Relationship Between Undergraduate Co-Curricular Leadership Roles, Change Readiness, And Leadership Self-Efficacy, Reneldo N. Randall

Educational Leadership & Workforce Development Theses & Dissertations

The contemporary workforce is characterized by ongoing organizational change, requiring individuals to demonstrate adaptability and the capacity to lead within evolving conditions. Institutions of higher education increasingly emphasize leadership development as a mechanism for preparing students for these demands; however, limited empirical research has examined how participation in formal co-curricular undergraduate leadership roles relates to students’ readiness to engage with organizational change. This study addresses the gap by examining the relationship between leadership self-efficacy and resistance to change among undergraduate student leaders.

Guided by the Leadership Identity Development (LID) model, this quantitative study employed a non-experimental, correlational design. Data were …

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 …

The Nature Of Divine Knowledge, Matthew Frise

Faith and Philosophy: Journal of the Society of Christian Philosophers

No abstract provided.

Comparison Of The 1c2 Reference Filtered Cigar To The 1r6f Reference Filtered Cigarette, Amrita Machwe, Samuel B. Clark, Halle Harned, Tanvi Sawardekar, Stacey A. Slone, Huihua Ji, David K. Orren

Markey Cancer Center Faculty Publications

Introduction: Filtered cigars are a class of tobacco products that can be consumed similarly as conventional cigarettes. Here we have compared tobacco smoke condensates prepared from the 1C2 reference filtered cigar with those from the 1R6F reference cigarette with respect to effects on cell proliferation and viability and AhR-mediated gene expression. Methods: Tobacco smoke condensates were prepared using ISO, Health Canada Intense (HCI) or Cigar Smoking (CSR) regimens and certain HPHCs were measured. Cell proliferation and viability assays were performed on immortalized human bronchial or oral epithelial cell lines. AHR-mediated gene expression was measured using a mouse hepatoma cell line …

How Much Should A Conversational Recommender System Converse?, Akshit Kumar, Vahideh Manshadi, Akhilesh Tumu

Cowles Foundation Discussion Papers

Conversational recommender systems powered by generative AI can enhance personalization by facilitating information elicitation through follow-up questions. However, engaging in these conversations imposes a communication cost on users. As platforms with different objectives and monetization models deploy these systems, a central question is: how does the platform’s objective and sellers’ strategic response shape the design of these systems in terms of their elicitation strategy? We develop a parsimonious model of conversational elicitation in which interaction generates noisy preference information and imposes a communication cost borne by the user. A user-welfare-maximizing platform elicits more information when accurate niche matching yields large …

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. …

Ms4 Swmpp 2026, John Kay

Municipal Separate Storm Sewer System (MS4) Permit

Stormwater discharges from Sandia National Laboratories/New Mexico (SNL/NM) are eligible for coverage under the National Pollutant Discharge Elimination System (NPDES) Municipal Separate Storm Sewer System (MS4) Permit. This Stormwater Management Plan (SWMP) was prepared by National Technology and Engineering Solutions of Sandia (NTESS) for the Department of Energy (DOE) National Nuclear Security Administration (NNSA) Sandia Field Office (SFO), owner of SNL/NM, located in Albuquerque, NM.

Career Pathways Program Annual Report For Ay 2025/26, Wie Yusuf

Career Pathways

Career Pathways launched in August 2017 as the university-wide initiative to provide career and professional development to graduate students. It encompasses both the Preparing Future Faculty (PFF) and the Preparing Future Professionals (PFP) Certificates. The Preparing Future Faculty Certificate was established in 2007, while the Preparing Future Professionals Certificate was launched in 2017, concurrently with the introduction of Career Pathways. The Career Pathways program prepares graduate students for a successful transition into thriving careers. With the PFP Certificate, the emphasis has been on addressing the existing gap in career and professional development for master’s and doctoral students with career plans …

Check Before You Trust: Teaching K–12 Students To Evaluate Digital Information, Elexia Hertel

Resources for Educators

[First paragraph]

Students in K–12 schools encounter digital information every day, but they are not always prepared to decide whether that information is credible, useful, biased, incomplete, or misleading. This chapter is written specifically for K–12 school library and classroom instruction, not for academic library users or college-level research instruction. Its primary audience is upper elementary, middle school, and early high school learners who are beginning to conduct research, cite sources, compare online information, and participate in digital life.