Digital Commons Network^™

Insect-Foundation: A Foundation Model And Large Multimodal Dataset For Vision-Language Insect Understanding, Thanh-Dat Truong, Hoang-Quan Nguyen, Xuan-Bac Nguyen, Ashley Dowling, Xin Li, Khoa Luu

Electrical Engineering and Computer Science Faculty Publications and Presentations

Multimodal conversational generative AI has shown impressive capabilities in various vision and language understanding through learning massive text-image data. However, current conversational models still lack knowledge about visual insects since they are often trained on the general knowledge of vision-language data. Meanwhile, understanding insects is a fundamental problem in precision agriculture, helping to promote sustainable development in agriculture. Therefore, this paper proposes a novel multimodal conversational model, Insect-LLaVA, to promote visual understanding in insect-domain knowledge. In particular, we first introduce a new large-scale Multimodal Insect Dataset with Visual Insect Instruction Data that enables the capability of learning the multimodal foundation …

Impact Of Feature Standardization On Heart Disease Prediction A Comparative Analysis Of Logistic Regression And Support Vector Machine Models, Norsyela Muhammad Noor Mathivanan, Eric Foo Zhi Xian, Debbie Foo Yong, Hiang Kiat Chua

Malaysian Journal of Computing (MJoC)

Cardiovascular diseases are among the leading causes of global mortality. Heart disease, in particular, remains a major contributor to this burden, highlighting the need for effective predictive models to enable early detection. This study investigates the impact of feature standardization using StandardScaler on the performance of two prominent machine learning models involving Logistic Regression (LR) and Support Vector Machine (SVM) for predicting heart disease. The research utilizes a dataset comprising demographic and clinical attributes of patients, focusing on the role of feature standardization in enhancing model performance. The study compares models trained on raw data and standardized data, applying performance …

Haar Cascade Algorithm For Microsleep Detection, Norkhushaini Awang, Ahmad Mirza Azhar

Malaysian Journal of Computing (MJoC)

Drowsy driving, particularly due to microsleep episodes, is a significant cause of traffic accidents, with existing solutions being often too costly or limited for widespread adoption. This project addresses this critical gap by developing a cost-effective, real-time Internet of Things (IoT)-based anti-microsleep alarm system. The system's development followed a fourstage process: Planning, Design, Development, and Evaluation. During the development phase, the system was built in Python using OpenCV and dlib for real-time facial analysis and the Haar Cascade algorithm for efficient facial feature detection. Key metrics like the Eye Aspect Ratio (EAR) and lip distance were monitored to identify signs …

Review And Gap Analysis On Mathematical Programming Models For Urban E Grocery Delivery, Nur Hazimah Basir, Adibah Shuib

Malaysian Journal of Computing (MJoC)

Online grocery shopping or e-grocery has becoming more relevant nowadays when consumers' shopping habit changed due to pandemic COVID-19 while e-Commerce rapidly transformed consumers’ lifestyle and buying behaviour in recent years, Consumers’ expectation for faster, better and cheaper delivery put e-grocers under rising pressure to improve delivery speed, achieving environmentally friendly delivery methods and addressing issues of making profit. There have been studies worldwide on development of more efficient e-grocery delivery system. However, studies concerning e-grocery delivery in Malaysia are still lacking especially on those utilizing mathematical programming models for delivery optimization. Our study focuses on the formulation of mixed …

E-Commerce Requirement Analysis And Design With Fogg Behavior Model Fbm, Fauziah Ahmad, Syafiyana Elysha Asmadi, Norjansalika Janom

Malaysian Journal of Computing (MJoC)

E-commerce platforms often struggle to convert user visits into meaningful actions, and this paper explores how the Fogg Behavior Model (FBM) can be used to design a more effective e-commerce (EC) platform. FBM focuses on three key factors that influence user behavior: motivation, ability, and triggers. It offers a structured framework for designing systems that not only meet functional needs but also enhance user engagement and actions. The Web Development Life Cycle (WDLC) method was employed to develop an EC platform for Carro Empire, a small business enterprise that wanted to improve its EC platform to attract and expand its …

Hamming Distance Of Generalised L-R Intuitionistic Fuzzy Number And Its Application, Muhammad Asyran Shafie, Nor Hanimah Kamis, Daud Mohamad, Seripah Awang Kechil

Malaysian Journal of Computing (MJoC)

This paper proposes a distance measure for generalised L-R intuitionistic fuzzy number (GLRIFN) which is Hamming distance, aiming to enhance the theoretical and practical tools available for decision-making under uncertainty. The properties of the Hamming distance of generalised L-R intuitionistic fuzzy number are also discussed in this study. GLRIFN extends traditional L-R intuitionistic fuzzy number by incorporating confidence level for both membership and non-membership functions, making them more reliable in the evaluation process. To demonstrate the practical utility of the proposed measure, it is applied within the Generalised L-R Intuitionistic Fuzzy Technique for Order of Preference by Similarity to Ideal …

Prevalence Of Risk Factors And Severity Level Of Diabetic Retinopathy In Uitm Medical Specialist Centre:An Ordinal Analysis, Aniza Ayuna Che Jani, Zuraida Khairudin, Nornadiah Mohd Razali, Nor Azimah Abd Aziz, Hezlin Aryani Abd Rahman, Nur Syamimi Haji Abu Bakar

Malaysian Journal of Computing (MJoC)

Diabetic Retinopathy (DR) has become a major concern as the number of diabetic patients who are diagnosed with DR has been on the rise each year. Hence, the adoption of a strategic approach is needed to determine the factors that contribute to the level of severity in DR patients. This research aims to determine the significant risk factors influencing the severity level of DR as well as to evaluate the classification rate between the severity level of 157 patients at UiTM Private Specialist Centre by employing the Ordinal Logistic Regression (OLR) analysis. The study revealed that there were 60 (38%) …

Utilizing Mathematical Software For The Teaching And Learning Of Mathematics In Malaysia, Naiim Fatimi Che Mansor, Saufianim Jana Aksah, Nor Aziyatul Izni, Khairul Huda Yusof, M. N. Mohammed

Malaysian Journal of Computing (MJoC)

The paper examines the effects of mathematical software on the academic performance of secondary school students, along with its roles in facilitating technological adaptation among the students in mathematics education. The study is motivated by persistent challenges in students’ mathematics achievement and the limited integration of technology in classroom practices, despite the increasing availability of digital tools in schools. Two main objectives guided the research are to evaluate the effectiveness of mathematical software in improving students’ comprehension of mathematics, and to measure the extent of technology integration among students in mathematics learning. A quantitative research design was employed, involving 100 …

Modified Hungarian Method For Lecturer To Course Assignment A Multi Objective Mathematical Programming Model, Nur Syahirah Ibrahim, Adibah Shuib, Zati Aqmar Zaharudin

Malaysian Journal of Computing (MJoC)

Efficient lecturer-to-course assignment is crucial for ensuring both faculty satisfaction and optimal teaching outcomes in higher education institutions. This study presents an advanced optimization model based on the Modified Hungarian Method (MHM) to address this challenge by integrating lecturers' preference levels and competency scores. While previous research has primarily focused on the traditional Hungarian Method (HM), limited attention has been given to its modified version. Moreover, the incorporation of preference-competency-based criteria in lecturer assignments is still lacking. To bridge these gaps, this study develops a mathematical programming approach to refine the MHM framework. The proposed model, called the Preference-Competency Multi-Objective …

Law Enforcement, Reproductive Health Information, And The Hipaa Privacy Rule, Stacey A. Tovino

Faculty Articles

On April 26, 2024, the federal Department of Health and Human Services (HHS) promulgated a final rule (Final Rule) amending the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule. The Final Rule prohibits HIPAA covered entities and business associates from using and disclosing protected health information (PHI) to conduct criminal, civil, or administrative investigations into an individual for the mere act of seeking, obtaining, providing, or facilitating lawful reproductive health care. The Final Rule also prohibits HIPAA covered entities and business associates from using and disclosing PHI to impose criminal, civil, and administrative liability on any individual, or to …

Governance In The Absence Of Government, Tracy Hresko Pearl

Faculty Articles

Artificial intelligence (AI) is advancing at an unprecedented pace, with generative systems exerting growing influence over social, economic, and political life. While Al offers opportunities for innovation and efficiency, it also poses risks ranging from misinformation and job displacement to existential threats if highly autonomous systems evade human control. Across industry, government, and civil society, there is broad consensus that Al requires oversight.

Yet traditional U.S. regulatory approaches face six significant barriers: (1) technology outpacing legislation, (2) limited Al expertise among policymakers, (3) regulatory capture, (4) political gridlock, (5) outdated governance structures, and (6) the inherent complexity of Al. Combined …

Contempt Power In The Province Of Maryland, Joshua T. Carback

University of Baltimore Law Forum

No abstract provided.

Air Traffic–Collegiate Training Initiative Program Feasibility In Kentucky, Gayle Marks, Bryan Gibson

Kentucky Transportation Center Research Report

Each day, Federal Aviation Administration (FAA) air traffic control specialists (ATCSs) handle over 44,000 flights and oversee 29 million square miles of the United States National Airspace System. However, staffing shortages have grown more acute over the past 10 years, which has led to delayed and cancelled flights, a higher number of close misses over a short period of time, and frustrating air travel experiences. While the FAA has redoubled its efforts to recruit more ATCSs, it has limited training capacity. To expand training options available to prospective ATCSs, the FAA is working with postsecondary educational institutions to expand its …

Robust Hashing For Improved Cnn Performance In Image-Based Malware Detection, Sanket Shekhar Kulkarni, Fabio Di Troia

Faculty Research, Scholarly, and Creative Activity

This paper presents a comparative study on the impact of robust hashing in enhancing image-based malware classification. While Convolutional Neural Networks (CNNs) have shown promise when working with image-based malware samples, their performance degrades significantly when obfuscation techniques are taken into consideration to hamper the malware classification or detection. To address this, we apply a robust hashing technique that generates invariant visual representations of malware samples, enabling improved generalization under obfuscation implemented as image salting. Using a custom obfuscation method to simulate polymorphic variants, we evaluate MobileNet, ResNet, and DenseNet architectures across five salting conditions (0% to 40%). The results …

Aligning Aviation Safety Reporting System Anomaly Codes For Crew Communication And Coordination With Human Factors Taxonomies, Jennifer Rose Herr

Doctoral Dissertations and Master's Theses

This study addresses the lack of theoretical grounding and definitions for the Aviation Safety Reporting System (ASRS) anomaly codes, particularly those related to pilot communication and coordination errors. To improve the conceptual consistency and analytical usability of ASRS data, the research developed a framework that maps ASRS codes to three established theory-based human factors taxonomies: the Human Factors Analysis and Classification System (HFACS), Threat and Error Management (TEM), and Aviation Causal Contributors for Error Reporting Systems (ACCERS). The study used qualitative text mining to systematically code communication and coordination errors submitted by Part 121 pilots for a stratified sample of …

Barriers And Best Practices In Diversity, Equity, And Inclusion (Dei) Initiatives: A Case Study From The United States Aerospace And Defense Industry, Jeremy A. Bailey

Doctoral Dissertations and Master's Theses

The main objective of this study was to unpack the barriers around diversity, equity, and inclusion (DEI) initiatives, and then provide best practices to improve DEI efforts in the aerospace and defense (A&D) industry. There has been a multitude of research conducted on DEI in the past few years. However, very little research has focused on DEI practices in the A&D industry. This case study focused on one large company in this industry to explore and understand various aspects of DEI initiative implementation. As organizations strive to meet industry and client objectives, as well as address employee needs, two research …

Additively Manufactured Bioinspired Microstructures For Active Surface Modification, Zefu Ren

Doctoral Dissertations and Master's Theses

Advancements in additive manufacturing have facilitated the development of bioinspired microstructures, which hold promise for applications, such as liquid transport, self-cleaning, and anti-icing. However, the controllability of these microstructures remains an area requiring further exploration. This research explores the design, fabrication, and active control of 3D-printed bioinspired microstructures for dynamic wettability modulation. First, the anisotropic scales of butterfly wings were replicated through optimized two-photon polymerization printing strategies, achieving directional droplet motion controlled by structural geometry and arrangement. The reversed wetting trend compared with natural wings revealed key insights into the structure–performance relationship. Next, microstructures were integrated with dielectric elastomer actuators …

Monte Carlo Simulation Models To Enhance Air Cargo Network Resilience And Sustainability, Shereen Marie Hashemi

Doctoral Dissertations and Master's Theses

This dissertation focuses on developing and validating an empirical set of simulation models for an air cargo network under large-scale disruption to test recovery strategies that improve resilience. Understanding and quantifying network resilience and recovery strategies is critical for ensuring sustainable operations. These operations become essential during disruptive events as air cargo is used to transport time-sensitive and critical goods. The collective research steps result in a Monte Carlo simulation framework to evaluate air cargo network resilience and identify strategies that enhance performance during disruptions.

The modeled system is a hub-and-spoke network centered on Memphis (MEM) with 23 domestic airports …

Leveraging Machine Learning And Causal Inference For Loan Default Prediction, Luca Guida

Doctoral Dissertations and Master's Theses

This research explores a systematic application of machine learning techniques combined with causal inference to predict loan defaults in peer-to-peer lending. Accurately forecasting loan defaults is crucial for mitigating financial risk and optimizing lending strategies. This analysis is based on multiple datasets of loan applications spanning over a decade, containing detailed financial and credit information about borrowers. Beginning with extensive Exploratory Data Analysis (EDA) coupled with scaling strategies, the research identifies key trends in loan performance across a large number of factors, such as interest rates or borrower creditworthiness, and one objective is to determine from the many available predictors …

Perturbation Solution Of Air-Water Mixture For Jet Noise Reduction, Juan Felipe Uribe Cifuentes

Doctoral Dissertations and Master's Theses

This work investigates passive jet-noise mitigation using externally positioned air–water curtains that attenuate radiated sound without altering the underlying jet dynamics. Two classes of multiphase media are examined: a gaseous carrier phase containing dispersed liquid droplets, and a liquid carrier phase containing entrained air bubbles. For both systems, suspended and dispersed regimes are represented through a generalized perturbation formulation derived from the volume-averaged multiphase equations, incorporating finite volume fractions, interphase momentum coupling, and slip between phases. Analytical and numerical solutions demonstrate that acoustic attenuation is primarily governed by dispersed-phase diameter, volume fraction, and excitation frequency, with additional sensitivity to phase-interaction …

Investigating Driver Perceptions Of Semi-Autonomous Vehicle Sensing And Response Characteristics, Molly Mersinger

Doctoral Dissertations and Master's Theses

As semi-autonomous vehicle (SAV) technologies become increasingly integrated into modern transportation, understanding how the public perceives their capabilities is essential for ensuring safe and effective human-automation interaction. This study examined drivers’ perceptions of SAV detection and discernment abilities across 28 driving conditions and how those perceptions related to expected vehicle behaviors in 17 corresponding scenarios. Exploratory and confirmatory factor analyses identified three perceptual dimensions: Traffic Infrastructure and Vehicle Recognition, Dynamic Roadway Hazards and Vulnerable Road Users, and Human Interaction and Contextual Cues. Moderate overlap between the first two dimensions suggested that participants viewed certain structured and dynamic roadway features as …

Meshless Discrete Velocity Boltzmann Model For Porous Media Flow, Amandine Maidenberg

Doctoral Dissertations and Master's Theses

This dissertation explores the combination of two sophisticated techniques for addressing computational fluid dynamics: the discrete velocity Boltzmann equation (DVBE) and the localized collocation meshless model with upwinding (U-LCMM). The DVBE is a high-level model that describes the foundations of transport phenomena by addressing the microscale motions of particles themselves and the effect of their aggregate behaviors on continuum principles. This equation integrates multiple scales of phenomena; while it can be used for fluid flow at Navier-Stokes scales, it can also resolve fine features that can only be described at the molecular level. This type of model is necessary for …

Adaptive Control For Spacecraft With Flexible Appendages With Unknown Parameters, Nicolo Woodward

Doctoral Dissertations and Master's Theses

Flexible spacecraft pose several challenges in control design due to the uncertain dynamical model and the underactuated nature of these systems. Adaptive and robust controllers are the common choice for these systems to either meet operational requirements like attitude pointing or to suppress vibrations. However, these controllers add complexity in the design of onboard Attitude Determination and Control Systems (ADCS) and the Reaction Control Systems (RCS) for spacecraft maneuvering. The objective of this research is to control a system that undergoes unpredictable and unknown disturbances through onboard derivation of an equivalent reduced order model designed around mounted sensors. The proposed …

Resilience Engineering Via Bifurcation And Ecological Network Analysis: Demonstrated In An Electric Power Case Study, Rogelio Gracia Otalvaro

Doctoral Dissertations and Master's Theses

Modern systems are increasingly complex, interconnected cyber-physical systems that combine digital controls with physical infrastructure. This integration, along with the constant introduction of new technologies and actors into the network, enables reliable operation but introduces vulnerabilities to unexpected and varied disruptions and cascading failures, making resilience a critical concern. Traditional risk management and resilience assessment methods often struggle with the nonlinearity and dynamic behavior of these systems. This dissertation proposes a novel approach combining Bifurcation Analysis (BA) and Ecological Network Analysis (ENA) to enhance the understanding and improvement of system resilience. BA, a mathematical method from dynamical systems theory, is …

Autonomous Landing Of An Unmanned Aerial Vehicle On An Unmanned Surface Vessel Using Model Predictive Control With An Adaptive-Covariance Extended Kalman Filter, Jorge Estupinan

Doctoral Dissertations and Master's Theses

This thesis presents the development of vision-based estimation and model predictive control (MPC) strategies to enable an Unmanned Aerial Vehicle (UAV) to land autonomously on an Unmanned Surface Vessel (USV) subjected to wave-induced motion. An innovative Adaptive-Covariance Extended Kalman Filter (AEKF) implementation was developed for the estimation of the 6 degree-of-freedom USV states using GPS and vision-based measurements of AprilTag markers on the USV landing platform. The AEKF employs an uncontrolled 6 degree-of-freedom nonlinear model augmented with second-order harmonic wave-induced motion dynamics. The AEKF implements two correction techniques: an adaptive covariance adjustment and an artificial covariance inflation regulated by a …

Unresolved Image Simulation For Space Situational Awareness Applications, Fox Coniglario

Doctoral Dissertations and Master's Theses

The knowledge of what lies in orbit around Earth is at best a guess. Decades of spaceflight, debris buildup, and vehicle collisions have contributed to a large number of objects that are simply not able to be catalogued. Ongoing efforts to catalog debris in orbit have reached limits by conventional measures and as such, research is active in the field of in-orbit space situational awareness. This thesis intends to help fill a hole in the development of such orbital platforms by assisting the development of image processing software pipelines though the simulation of unresolved space imagery. The simulation uses accurate …

Shsp Dean's Newsletter, Fall 2025, Robert W. Amler

SHSP Dean’s Newsletter

No abstract provided.

Portfolio And Appendix Chris M. Larson, Chris M. Larson

Graduate Student Portfolios, Professional Papers, and Capstone Projects

Abstract:

This is a collection of assignments and reflections of my work throughout the course of the Masters in Social Work program at the University of Montana. Included are assignments reflecting on the Indian Child Welfare Act, housing, barriers to care for Non-White and female veterans within the VA clinic, the quality of care in nursing homes, American Drug policy, confidentiality in the YWCA, training on interventions based on Cognitive Behavioral Therapy, cost benefit analysis of in home care programs, and a proposal for my practicum site Missoula Aging Services. It has reflections on the five elements of advanced practice, …

Fall Reduction Utilizing Fall Tailored Intervention For Patient Safety In Acute Care, Lauren Poindexter

All Doctor of Nursing Practice (DNP) Scholarly Projects

Problem: Hospitalized patient falls cause physical, psychological, and financial harm and persist despite prevention bundles. A Midwest Ohio acute medical unit experienced higher-than-benchmark fall rates (1.53–7.58 falls/1,000 patient days; unit rate 113% of the national median), with a rising trend in FY25. Reliance on the Schmid tool and existing interventions lacked structured patient/family engagement, as well as comprehensive medication assessment, leading to under-recognition of risk and limited nurse-driven prevention.

Aim of the Project: The aim of the project was to reduce inpatient fall rates and fall-related injuries on a medical unit by implementing the Agency for Healthcare Research and Quality …

Control And Cuckoldry In “Calypso” And “Circe”, Corinne Lafont , '26

Senior Theses, Projects, and Awards

Sex, femininity, and dirt in James Joyce’s Ulysses form what Julie Kristeva calls “abjection.” The abject is "the border where exact limits between same and other, subject and object, and even beyond these, between inside and outside, and disappearing—hence an Object of fear and fascination,” (Kristeva 1980, 185) evident by Leopold Bloom’s identity as a cuckold. Alternately approached with loss, disconnection, and anxiety, the text reveals that Leopold Bloom craves his abject to distance himself from physical and emotional rejection. “Calypso” establishes how his abject operates as a defense mechanism to self-defile before others can approach any realized sexual bond. …