Digital Commons Network^™

Type-2 Neutrosophic Numbers For Impact Evaluation Of Sports On The Psychological And Emotional Regulation Of Rural Children, Ming Yuan, Jing Huang, Xinhuan Duan, Xin Hu

Neutrosophic Sets and Systems

No abstract provided.

Application Of Interval Neutrosophic Logic Model For Diagnosis Of Cattle Disease, Lola Safarova, Dilnoz Muhamediyeva, Sokhibjan Muminov, Seyyed Ahmad Edalatpanah

Neutrosophic Sets and Systems

No abstract provided.

Introducing Plithogenic Stochastic Processes With An Application To Poisson Process, Abdulrahman Astambli, Mohamed Bisher Zeina, Moustafa Mazhar Ranneh

Neutrosophic Sets and Systems

No abstract provided.

Integrating Industry Needs With Language Training From Classroom To Profession: English Translation Courses Measurement In Neutrosophic Number Operator, Yujia Guo

Neutrosophic Sets and Systems

No abstract provided.

A Comparative Review Of The Fuzzy, Intuitionistic And Neutrosophic Numbers In Solving Uncertainty Matrix Equations, Myra Suphelea Asmizal, Wan Suhana Wan

Neutrosophic Sets and Systems

No abstract provided.

Modest Insights From Grammar To Growth: A Neutrosophic Numbers Model For Measuring English Teaching Outcomes In University Contexts In A Preliminary Approach, Yisen Zhao

Neutrosophic Sets and Systems

No abstract provided.

Triangular Offnorm With Multi-Criteria Decision-Making Method For College Political And Ideological Instruction On Intelligent Learning Platforms, Haiying Wang

Neutrosophic Sets and Systems

No abstract provided.

Probabilistic Interval Neutrosophic Hesitant Fuzzy Set For Strategic Estimation Of Communication Instruction And Critical Analysis Of Journalism Teaching Practices In Higher Education, Yuan Heng

Neutrosophic Sets and Systems

No abstract provided.

Collective Analysis, Sydney L. Reichin, Angie Benda, James C. Peters, Joel S. Elson, Samuel Hunter

Reports, Projects, and Research

This report serves as Deliverable 7: Collective Analysis, as tasked by the Department of Homeland Security (DHS). The primary goal of this effort was to review literature (both academic and practitioner-based) related to threats found in K-12 schools, and to validate findings from the literature with interviews with subject matter experts (SMEs). Interviews discussed threats and vulnerabilities SMEs face along with their needs for future risk assessments. This review provides insights within and across interviews from SMEs and resource coding, identifying common and emerging themes that schools experience. The findings will inform the development of a comprehensive K-12 risk assessment …

Phl 110e.50: Introduction To Ethics, Charles B. Hayes

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Phl 321e.50: Philosophy And Biomedical Ethics, Mark J. Hanson

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Writ 201.52: College Writing Ii - Intermediate Rhetoric And Storytelling, Kelly R. Schirmann

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Comparison Of Gravity Waves Observed By Atmospheric Waves Experiment (Awe) And Simulated By High-Resolution Waccm-X, Jiarong Zhang, Han-Li Liu, Yucheng Zhao, Dominique Pautet, Ludger Scherliess, Michael Taylor

Space Dynamics Laboratory Publications

Outline

Data: AWE and High-Resolution Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (HR-WACCMX) simulation

• Quantify gravity wave (GW) activity
• Compare GW activity observed by AWE and simulated by high-resolution WACCMX
• GW activity over Western Europe

Design And Development Of Hip Implants For Longevity Through Integrating Advanced Groove Structures And Additive Manufacturing, Asarudheen Abdudeen

Dissertations

This doctoral research concerns the design and optimization of hip implants (HIs) to enhance performance, durability, and improve patient outcomes by addressing the key issues of wear, deformation, and stress distribution. Innovative surface groove designs have been introduced to both a solid and a hollow femoral head with the aim of reducing friction and wear. The addition of grooves, with both a hemispherical and rectangular cross-section, onto the femoral head reduced friction, as debris produced by the inner liner was trapped within the grooves, significantly reducing adhesive wear. A numerical simulation study compared the effects of surface modifications both grooves …

Examining The Legal Responsibilities And Key Challenges Of Personal Representatives In Malaysian Inheritance Management, Muhammad Amrullah Drs Nasrul, Anis A'Fifah Zairin Zain, Wan Noraini Wan Mohd Salim

The Indonesian Journal of Socio-Legal Studies

Personal representative connotes a person authorised under the law to manage the estate of the deceased person. The personal representative is responsible to gather all the assets belonging to the deceased and distribute the assets to the beneficiaries legally. The process of inheritance management in Malaysia requires a formal application to be made to the administrative bodies for the appointment of a personal representative, either as an executor or administrator. However, instances of misappropriation of the deceased’s estate by personal representatives have raised serious concerns, affecting the proper administration of estates and the rights of beneficiaries This study emphasises on …

Navigating Crisis: An Intersectional Analysis Of Marginalized Women’S Role In Sustaining Community Cooperatives Through The Covid-19 Pandemic, Rizky Septiana Widyaningtyas

The Indonesian Journal of Socio-Legal Studies

This study analyzes the challenges faced by PEKKA women in Bantul regarding economic empowerment amid the Indonesian government's social restriction policies. It also explores the strategies these women have implemented to survive and strengthen community cooperatives during and after the pandemic. Using a socio-legal method with an intersectional approach, the results indicate that the pandemic and social distancing measures have significantly impacted the economies of female-headed households compared to those supported by both husbands and wives. This impact is particularly pronounced for women who run small businesses that had to close during the pandemic. PEKKA women work collectively in community …

Peak Policy Lab Or Chasing Windmills? The Overlooked Issue Of Misaligned Policy Design, Adam Wellstead, Sarah Giest, Ishani Mukherjee

Research Collection School of Social Sciences

Policy innovation labs (PILs) are relatively new policy actors and are part of a larger global “labification” movement. They are touted as spaces for the novel development and testing of policy solutions. PILs have evolved into various forms–including those at different levels of government (central, sub-national, and local), sectoral (such as food, transportation, and environment), and cross-sectoral labs (social innovation and data labs). After a decade, some practitioners lament the effectiveness of their efforts and question if policy labs are indeed engines of innovation and change. We argue that the approach to policy design by PILs, in part, is an …

Contested: Consistency-Aided Tested Code Generation With Llm, Jinhao Dong, Jun Sun, Wenjie Zhang, Jinsong Dong, Dan Hao

Research Collection School Of Computing and Information Systems

Recent advancements in large language models (LLMs) have significantly improved code generation, which generates code snippets automatically based on natural language requirements. Despite achieving state-of-the-art performance, LLMs often struggle to generate accurate and reliable code, requiring developers to spend substantial effort debugging and evaluating the generated output. Researchers have proposed leveraging Consistency to select code that passes more tests (inter-consistency) and demonstrates consistent behavior across more counterparts (intra-consistency). However, since the tests themselves are also generated by LLMs, relying on majority voting based on incorrect tests leads to unreliable results. To address this, we propose a lightweight interaction framework that …

Enhancing Vulnerability Detection Via Inter-Procedural Semantic Completion, Bozhi Wu, Chengjie Liu, Zhiming Li, Yushi Cao, Jun Sun, Shang-Wei Lin

Research Collection School Of Computing and Information Systems

Inspired by advances in deep learning, numerous learning-based approaches for vulnerability detection have emerged, primarily operating at the function level for scalability. However, this design choice has a critical limitation: many vulnerabilities span multiple functions, causing function-level approaches to lose the semantics of called functions and fail to capture true vulnerability patterns. To address this issue, we propose VulnSC, a novel framework designed to enhance learning-based approaches by complementing inter-procedural semantics. VulnSC retrieves the source code of called functions for datasets and leverages large language models (LLMs) with well-designed prompts to generate summaries for these functions. The datasets, enhanced with …

Lessons Learned From Sandboxing, Piloting And Policy Experimentation With Ai And Other Digital Initiatives: Part 1, Summary Report, Steven M. Miller

Research Collection School Of Computing and Information Systems

This report, "Lessons Learned from Sandboxing, Piloting and Policy Experimentation with AI and Other Digital Initiatives," captures insights and experiences from project experts involved in recent digital innovation initiatives with the governments of Bangladesh, Maldives, and Kazakhstan, and from project experts actively involved with the use of AI for delivering government digital services in the EU, New Zealand, Rwanda, Singapore, United States, and Uzbekistan. The ten in-depth interview write-ups produced from these nine different country settings provide a small but highly informative sample of rich descriptions of some of the important realities, approaches, nuances, issues and challenges related to testing …

Cashift: Benchmarking Log-Based Cloud Attack Detection Under Normality Shift, Jiongchi Yu, Xiaofei Xie, Qiang Hu, Bowen Zhang, Ziming Zhao, Yun Lin, Lei Ma, Ruitao Feng, Frank Liau

Research Collection School Of Computing and Information Systems

With the rapid advancement of cloud-native computing, securing cloud environments has become an important task. Log-based Anomaly Detection (LAD) is the most representative technique used in different systems for attack detection and safety guarantee, where multiple LAD methods and relevant datasets have been proposed. However, even though some of these datasets are specifically prepared for cloud systems, they only cover limited cloud behaviors and lack information from a whole-system perspective. Another critical issue to consider is normality shift, which implies that the test distribution could differ from the training distribution and highly affect the performance of LAD. Unfortunately, existing works …

Regtrieve: Reducing System-Level Regression Errors For Machine Learning Systems Via Retrieval-Enhanced Ensemble, Junming Cao, Xuwen Xiang, Mingfei Cheng, Bihuan Chen, Xinyan Wang, You Lu, Chaofeng Sha, Xiaofei Xie, Xin Peng

Research Collection School Of Computing and Information Systems

Multiple machine learning (ML) models are often incorporated into real-world ML systems. However, updating an individual model in these ML systems frequently results in regression errors, where the new model performs worse than the old model for some inputs. While model-level regression errors have been widely studied, little is known about how regression errors propagate at system level. To address this gap, we propose RegTrieve, a novel retrieval-enhanced ensemble approach to reduce regression errors at both model and system level. Our evaluation across various model update scenarios shows that RegTrieve reduces system-level regression errors with almost no impact on system …

Hvi: A New Color Space For Low-Light Image Enhancement, Qingsen Yan, Yixu Feng, Cheng Zhang, Guansong Pang, Kangbiao Shi, Peng Wu, Wei Dong, Jinqiu Sun, Yanning Zhang

Research Collection School Of Computing and Information Systems

Low-Light Image Enhancement (LLIE) is a crucial computer vision task that aims to restore detailed visual information from corrupted low-light images. Many existing LLIE methods are based on standard RGB (sRGB) space, which often produce color bias and brightness artifacts due to inherent high color sensitivity in sRGB. While converting the images using Hue, Saturation and Value (HSV) color space helps resolve the brightness issue, it introduces significant red and black noise artifacts. To address this issue, we propose a new color space for LLIE, namely Horizontal/Vertical-Intensity (HVI), defined by polarized HS maps and learnable inten sity. The former enforces …

Why Does My Transaction Fail? A First Look At Failed Transactions On The Solana Blockchain, Xiaoye Zheng, Zhiyuan Wan, David Lo, Difan Xie, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Solana is an emerging blockchain platform, recognized for its high throughput and low transaction costs, positioning it as a preferred infrastructure for Decentralized Finance (DeFi), Non-Fungible Tokens (NFTs), and other Web 3.0 applications. In the Solana ecosystem, transaction initiators submit various instructions to interact with a diverse range of Solana smart contracts, among which are decentralized exchanges (DEXs) that utilize automated market makers (AMMs), allowing users to trade cryptocurrencies directly on the blockchain without the need for intermediaries. Despite the high throughput and low transaction costs of Solana, the advantages have exposed Solana to bot spamming for financial exploitation, resulting …

Less Is More: On The Importance Of Data Quality For Unit Test Generation, Junwei Zhang, Xing Hu, Shan Gao, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Unit testing is crucial for software development and maintenance. Effective unit testing ensures and improves software quality, but writing unit tests is time-consuming and labor-intensive. Recent studies have proposed deep learning (DL) techniques or large language models (LLMs) to automate unit test generation. These models are usually trained or fine-tuned on large-scale datasets. Despite growing awareness of the importance of data quality, there has been limited research on the quality of datasets used for test generation. To bridge this gap, we systematically examine the impact of noise on the performance of learning-based test generation models. We first apply the open …

Adapting Large Language Models For Parameter-Efficient Log Anomaly Detection, Ying Fu Lim, Jiawen Zhu, Guansong Pang

Research Collection School Of Computing and Information Systems

Log Anomaly Detection (LAD) seeks to identify atypical patterns in log data that are crucial to assessing the security and condition of systems. Although Large Language Models (LLMs) have shown tremendous success in various fields, the use of LLMs in enabling the detection of log anomalies is largely unexplored. This work aims to fill this gap. Due to the prohibitive costs involved in fully fine-tuning LLMs,we explore the use of parameter-efficient fine-tuning techniques (PEFTs) for adapting LLMs to LAD.To have an in-depth exploration of the potential of LLM-driven LAD, we present a comprehensive investigation of leveraging two of the most …

"Some Level Of Skill For Life": Secondary Teacher Librarians Supporting Student Information Literacy Skill Transfer Beyond Secondary School, Kasey L. Garrison, Kay Oddone

Communications in Information Literacy

Students entering higher education are expected to transfer information literacy skills and knowledge developed through their primary schooling and sharpened in their secondary years. However, the constant evolution of the information landscape means the mastery of these skills presents challenges for students to develop and teachers to teach. Through interviews, this phenomenological study examines the perspectives and practices of 19 Australian secondary teacher librarians supporting student information literacy skill transfer in school and life contexts and considers important changes in the teaching of these skills. Findings suggest time and content overload are preventing integration across subjects and limiting students’ ability …

June 2025 News Releases, University Of Montana--Missoula. Office Of University Relations

University of Montana News Releases, 1928, 1956-present

No abstract provided.

Nursing Education Research In Sub-Saharan Africa: A Systematic Review And Bibliometric Analysis, Beth Waweru, Peter Gatiti, Serah Wachira

School of Nursing & Midwifery, East Africa

Nursing education is pivotal for ensuring competent healthcare professionals, and its improvement is essential for enhancing the quality of health care systems globally. This study focuses on nursing education research in Sub-Saharan Africa (SSA) over the last decade, employing both bibliometric analysis and systematic review methodologies. The bibliometric analysis reveals an evolving landscape of nursing education research in SSA, offering insights into trends, key countries, journals, and predominant research themes. Notably, the study identifies a scarcity of literature using bibliometric approaches in nursing research, addressing this gap by providing a comprehensive overview of the field.The systematic review, guided by the …

(Law) School To Prison Pipeline, Cheyenne Petrich

Minnesota Journal of Law & Inequality

No abstract provided.