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Software Engineering In The Age Of Coding Agents: Failure Modes And Rejection Patterns, Mahd Mohd Hindi

Theses

This thesis investigates the real-world behavior of LLM-driven coding agents that generate code changes and submit pull requests (PRs) to public software repositories. As these tools evolve from autocomplete-style assistants into more autonomous agents, their contributions increasingly interact with socio-technical review processes (human reviewers, bots, CI/CD gates, and project norms). The thesis focuses on understanding why agent-generated PRs are accepted or rejected and what these outcomes reveal about current agent limitations in practical development workflows.

The main objective of this thesis is to systematically characterize rejection patterns and failure modes of agent-generated pull requests in real repositories. Specifically, the thesis …

A High-Fidelity Multimodal Synthetic Dataset Generation Framework For Off-Road Unstructured Terrain Navigation Training Of Autonomous Robots, Liyana Wijayathunga, Dulitha Dabare, Alexander Rassau, Douglas Chai, Syed Mohammed Shamsul Islam

Research outputs 2022 to 2026

The success of deep learning methods in a wide range of application areas has inspired many recent developments in the urban and off-road autonomous navigation domain. In particular, techniques for semantic scene understanding, a key aspect of the navigation pipeline, have been researched extensively, resulting in many real-world and synthetic datasets. However, in comparison to urban semantic segmentation datasets, the availability of datasets for off-road environments remains sparse. In this paper, we aim to overcome this challenge by introducing a methodology capable of efficiently generating photorealistic synthetic datasets for off-road environments with support for multiple sensor modalities. The developed approach …

Graph Convolution Neural Network And Deep Q-Network Optimization-Based Intrusion Detection With Explainability Analysis, Kelvin Mwiga, Mussa Dida, Leandros Maglaras, Ahmad Mohsin, Helge Janicke, Iqbal H. Sarker

Research outputs 2022 to 2026

As networks expand in size and complexity, coupled with an exponential increase in intrusions on network and IoT systems, this leads to traditional models failing to capture increasingly intricate correlations among network components accurately. Graph Convolution Networks (GCNs) have recently acquired prominence for their capacity to represent nodes, edges, or entire graphs by aggregating information from adjacent nodes. However, the correlations between nodes and their neighbours, as well as related edges, differ. Assigning higher weights to nodes and edges with high similarity improves model accuracy and expressiveness. In this paper, we propose the GCN-DQN model, which integrates GCN with a …

An Explainable Transformer-Based Model For Phishing Email Detection: A Large Language Model Approach, Mohammad Amaz Uddin, Md Mahiuddin, Iqbal H. Sarker

Research outputs 2022 to 2026

Phishing email is a serious cyber threat that tries to deceive users by sending false emails with the intention of stealing confidential information or causing financial harm. Attackers, often posing as trustworthy entities, exploit technological advancements and sophistication to make the detection and prevention of phishing more challenging. Despite extensive academic research, phishing detection remains an ongoing and formidable challenge in the cybersecurity landscape. In this research paper, we present a fine-tuned transformer-based masked language model, RoBERTa (Robustly Optimized BERT Pretraining Approach), for phishing email detection. In the detection process, we employ a phishing email dataset and apply the preprocessing …

Explainable Artificial Intelligence Models For Detecting Suspicious Bank Transactions, Narasimha Kumar Narasapuram, Syed Afaq Ali Shah, Mohd Fairuz Shiratuddin, Ferdous Sohel

Research outputs 2022 to 2026

Detecting financial crime is a complex challenge due to evolving criminal strategies and fragmented detection systems, particularly in the areas of money laundering and fraud. While it is easy to implement, traditional rule-based approaches lack adaptability to new threats, and machine learning models, though more effective, often function as opaque "black boxes," limiting their practical use in regulated domains like banking, where interpretability and accountability are essential. This research presents a novel framework that combines intrinsic and post-hoc XAI techniques to detect suspicious bank transactions. Intrinsic methods provide model-inherent transparency, while post-hoc methods offer behavior-level explanations, enabling robust cross-verification of …

N-Dqn: Neutrosophic Deep Q-Network For Uncertainty-Aware Forecasting And Decision Optimization, Rania Lutfi

Neutrosophic Systems with Applications

Uncertainty remains a critical challenge in dynamic spatiotemporal forecasting. This study proposes the Neutrosophic Deep Q-Network (N-DQN), a framework that integrates neutrosophic logic with deep reinforcement learning to enhance decision optimization under uncertainty. Features are modeled through truth, indeterminacy, and falsity membership functions, enabling robust handling of ambiguous data. The framework incorporates attention-guided preprocessing and horizon-aware optimization to adapt predictions across short- and long-term intervals. Experiments on benchmark traffic datasets (METR-LA and PEMS-BAY) demonstrate improved forecasting accuracy and reduced error rates compared with established baselines. The results highlight the scalability and resilience of N-DQN, positioning it as a promising approach …

Current Research Progress On Electrode Materials For All-Vanadium Redox Flow Batteries, Wen-Qi Wang, Jie Jin, Li-Min Wang, Xin-Yue Liu, Tao Cheng, Yong Hou, Han Xue, Zhi-Yu Wang, Bo Liu, Jia-Bao Liu, Xu-Bin Lu

Journal of Electrochemistry

The redox active species in all-vanadium redox flow batteries (VRFBs) reside in the electrolyte, while the heterogeneous reactions occur on the electrode surface; the electrode is therefore the decisive platform for dynamic adsorption, electron transfer, and ion conversion, especially for the VO²⁺/VO₂⁺ and V²⁺/V³⁺ couples. One of the major challenges for VRFBs is the slow charge transfer in VO²⁺/VO₂⁺ and V²⁺/V³⁺ reactions, mainly caused by poor catalytic performance of electrodes and weak adhesion of catalysts to electrodes. This review focuses on the key challenges and recent …

An Electrochemiluminescence-Based Arsenic (Iii) Sensor Using Luminol On Screen-Printed Gold Electrodes, Harmesa Harmesa, Isnaini Rahmawati, Andrea Fiorani, Yasuaki Einaga, Eny Kusrini, A’An Johan Wahyudi, Asep Saefumillah, Tribidasari A Ivandini

Journal of Electrochemistry

Electrochemiluminescence (ECL) of luminol has been studied on a screen-printed gold electrode for a simple and sensitive detection of arsenic ions (As(III)). Cyclic voltammetry (CV) was applied as the proposed technique to study luminol’s electrochemical behavior and to evaluate the arsenic’s effect in the ECL system, while hydrogen peroxide (H₂O₂) served as a co-reactant to enhance luminol’s light emission under alkaline conditions. To achieve optimal electrode performance, key parameters including pH, scan rate, and the concentrations of H₂O₂ and luminol were carefully optimized. The presence of As(III) induced a quenching effect on the …

Control Of Pore Nucleation And Rearrangement Kinetics During Aluminium Anodizing In Phosphoric Acid Electrolyte, Ilya V. Roslyakov, Nikita A. Shirin, Dmitry M. Tsymbarenko, Sergei N. Pavlov, Sergey E. Kushnir, Nikolay V. Lyskov, Kirill S. Napolskii

Journal of Electrochemistry

Anodic aluminium oxide (AAO) porous films with an interpore distance of several hundred nanometers are of great interest due to their unique interaction with visible and near-infrared light, and high thermal stability up to 1500 °C. These porous films are prepared by aluminium anodizing at high voltages in weak acids, leading to a slow kinetics of initial stages of porous structure formation. Here, we propose an approach to accelerate AAO formation in electrolytes based on weak acids such as phosphoric acid. Aluminium foils, pre-patterned using first anodizing under different conditions and subsequent selective dissolution of a sacrificial AAO layer, were …

Experiments Towards A Neutron Target For Measurements In Inverse Kinematics, S. F. Dellmann, Caroline M. Harrington, O. R. Cantrell, A. L. Cooper, A. Couture, D, V, Gorelov, I Knapová, S. M. Mosby, R. Reifarth, A. Alvarez, A. Aprahamian, J. Butz, I. J. Bos, Michael T. Febbraro, T. Hankins, B. M. Harvey, T. Heftrich, M. Le, Juan J. Manfredi, A. B. Mcintosh, K. V. Manukyan, M. Matney, S. Regener, D. Robertson, A. Simon, D. Sokolovic, E. Stech, G. Tabacaru, W. Tan, M. Wiescher, S. Yennello

Faculty Publications

Neutron-induced reactions play an important role in fundamental nuclear physics, nuclear astrophysics, and applications. In the case of reactions on rare isotopes, there are limited options for direct experimental measurements. The Neutron Target Demonstrator project at Los Alamos National Laboratory seeks to test the feasibility of moderating spallation neutrons within a 1 m³graphite cube to create a standing neutron target for neutron-induced reaction measurements in inverse kinematics. This paper presents the results of experimental neutron flux distribution tests using neutron sources (ranging from 1 keV to 50 MeV) created by accelerators at the University of Notre Dame and …

Single-Valued, Double-Valued, Triple-Valued, Quadruple-Valued, And Quintuple-Valued Neutrosophic Graph, Takaaki Fujita, Arif Mehmood, Arkan A. Ghaib

Neutrosophic Systems with Applications

Concepts such as fuzzy sets, neutrosophic sets, rough sets, and plithogenic sets have been extensively studied as formal tools for modeling uncertainty, and they have found broad applications across many disciplines. A Double-Valued Neutrosophic Set (DVNS) extends the classical neutrosophic framework by splitting indeterminacy into two distinct components: one leaning toward truth and the other leaning toward falsity. In recent years, further refinements—namely Triple-Valued, Quadruple-Valued, and Quintuple-Valued Neutrosophic Sets—have also been introduced and investigated. These uncertainty models have naturally been lifted to graph-theoretic settings, where vertices and edges represent entities and relationships under ambiguity. Although fuzzy graphs and neutrosophic graphs …

Evaluating Domains' Trustworthiness Based On Uncertainty-Driven Methodologies In The Era Of Sixth Generation, Zekra Sakr, Mona Mohamed

Neutrosophic Systems with Applications

The onset of today's innovations pledges to have a beneficial influence on contemporary civilization in an era of intelligent revolutions, setting a precedent for unrivaled efficiency, creativity, and connectedness. The integration between these technologies contributes to the mutual benefit of each one, wherein this relation is a so-called ``reciprocal partnership''. For instance, the sixth generation (6G) wireless networks permit blockchain nodes to coordinate huge volumes of transaction data in real-time. On the other hand, blockchain is considered a secure valve because spectrum sharing can be automated with blockchain and smart contracts. Accordingly, analyzing and evaluating the contribution of these technologies …

Neutrosophic Finsler–Cohomological Framework For Engineering Systems Under Uncertainty, Mona Gharib, Ghulam Muhammad, Muhammad Idrees, Zeeshan Gul

Neutrosophic Systems with Applications

This paper introduces a novel mathematical framework that combines Neutrosophic Finsler Geometry with Neutrosophic Cohomology for evaluating the performance of Brushless Direct Current (BLDC) motors under uncertain and indeterminate operating conditions. Classical motor performance models typically assume precise measurements of torque, current, and efficiency; however, in real-world settings, these parameters are often affected by noise, incomplete information, and conflicting observations. By embedding motor operating states into a neutrosophic Finsler space, the proposed approach captures variations not only in magnitude but also in direction, uncertainty, and conflict of performance metrics. In addition, neutrosophic Cohomology is employed to characterize global invariants of …

An Uncertainty-Aware Entropy-Oreste Framework For Big Data Platform Selection In Complex Multi-Sector Environments, Ahmed M. Ali, Ibrahim Alrashdi, Karam M. Sallam

Neutrosophic Systems with Applications

The increasing reliance on Big Data platforms across various industries has necessitated the development of systematic decision-support frameworks to guide their evaluation and selection. Given the diversity of available platforms, each offering different capabilities, scalability, and computational efficiency, choosing the optimal solution remains a complex challenge. This research proposes a novel analytical framework that integrates Spherical Fuzzy Sets (SFS) with the Entropy and ORESTE methods to address uncertainty and enhance the accuracy and robustness of Big Data platform evaluation. This hybrid integration, not previously applied to Big Data platform selection, enables objective criteria weighting through the Entropy method and comprehensive …

Triphenylmethane-Derived Levelers For High-Speed Redistribution Layer Copper Electroplating Of Tailored Surface Morphologies, Zi-Hao Song, Wei-Bin Wang, Xiao-Hui Liu, Xiao-Min Han, Yi Zhou, Rui Huang, Yan-Xia Jiang, Zhe Li, Xiao-Wei Liu, Mei-Ling Xiao, Hong-Gang Liao, Wei-Lin Xu, Rong Sun

Journal of Electrochemistry

Redistribution Layer (RDL), composed of layered dielectrics and electroplated copper materials, is a basic structure to rearrange numerous I/O pads on the chip surface in wafer-level advanced packaging. As the key chemicals in electrolyte baths, electroplating additives have undergone continuous development to meet the industrial needs for high-speed and fine-line/fine-pitch applications. Meanwhile, the intricate relationships between additive chemical structures and electroplated copper properties are yet to be well understood. In this work, a pair of triphenylmethane-based dye molecules, i.e., gentian violet (GV) and methyl green (MG), was comparatively investigated as levelers for high-speed RDL copper electroplating. Compared to GV, significantly …

Evaluating Regularized Logistic Regression And K-Nn On Mnist Under Increasing Random Missingness, Daniel Markwei

Data Science and Data Mining

This paper investigates the effect of random missingness on the performance of regularized multinomial logistic regression and the k-nearest neighbors (k-NN) classifier for handwritten digit recognition on the MNIST dataset. In particular, we study L1-regularized (LASSO) logistic regression and L2-regularized (Ridge) logistic regression alongside k-NN. Varying percentages of random missingness were introduced into the original dataset, and each model was evaluated in terms of its classification performance. The results show that random missingness degrades the performance of all three classifiers. Overall, k-NN consistently achieves higher accuracy than both L1- and L2-regularized logistic regression across all missingness levels; however, its performance …

Client Feedback Effects On Enjoyment, Motivation And Self-Efficacy In A Project-Based Learning Course, Krista Stacey, David M. Bourrie

University Faculty and Staff Publications

This paper reports a mixed-methods evaluation of how feedback/project source (faculty-led versus client-led) shapes student outcomes in a two-course undergraduate game and simulation development sequence (N = 29 across two academic years). Quantitative measures (enjoyment, intrinsic motivation, self-efficacy) were collected with a six-point Likert survey and analyzed, but due to small sample sizes were not used to empirically evaluate the constructs. Instead, qualitative data comprised of de-identified focus-group transcripts and open-ended survey responses were analyzed with a keyword-assisted codebook and manual validation. Year 1 (faculty feedback) exhibited more consistent post-course gains, especially in self-efficacy, while Year 2 (client feedback) produced …

Cultural Science Night, Jiyoon Yoon

Mavs Open Press Open Educational Resources - Archive

This book is to learn water and weather by integrating with other cultures. This textbook is organized around two interconnected components. The first component provides cultural knowledge of China, India, Korea, and Mexico. The second component focuses on culturally responsive science instruction created for the Cultural Science Night event, an occasion in which teachers present hands-on, culturally responsive science activities in collaboration with students.

If you need an accessibility accommodation or have questions about the use of this text, please contact Mavs Open Press.

Exosome Engineering For Blocking Gut Dysbiosis And Inducing Cell Death Mechanisms In Glioblastoma Multiforme, Ahalya Muraleedharan, Karthik Rangavajhula, Swapan K. Ray

Faculty Publications

Glioblastoma multiforme (GBM) is the most lethal primary brain tumor in adults. Emerging evidence endorses that gut dysbiosis contributes to GBM progression through the gut–brain axis (GBA), promoting inflammation and therapeutic resistance via abnormal short-chain fatty acid production and cytokine dysregulation. Exosomes, naturally occurring nanovesicles (30–150 nm), offer promising therapeutic potential due to their blood–brain barrier permeability, biocompatibility, and versatile cargo capacity. This review examines exosome engineering strategies for dual targeting: inhibiting alterations in gut microbiome and inducing regulated cell death mechanisms such as apoptosis and ferroptosis in GBM. We describe exosome engineering with detailed focus on cargo loading approaches …

Egain Tube Memristors Offering Reliable Switching On A Biological Time Scale, Yuriy V. Pershin, Liya Patel, Bapi Bera, Doug Aaron, Stephen A. Sarles

Faculty Publications

Memristive devices have been considered promising candidates for nature-inspired computing and in-memory information processing. However, experimental devices developed to date typically show significant variability and function at different time scales than biological neurons and synapses. This study presents a memristive device comprised of liquid-metal eutectic gallium indium (EGaIn) contained within a mm-scale tube that operates via a bulk, voltage-dependent switching mechanism and exhibits distinct unipolar resistive switching characteristics that occur on a biological time scale (tens of milliseconds). The switching mechanism involves voltage-controlled growth and dissolution of an oxide layer on the surface of the liquid metal in contact with …

Urban–Rural Disparities In Metabolic Risk Factors For Hypertension Among The Elderly In Indonesia, Susiana Nugraha, Puri Wulandari

Kesmas

Hypertension remains a major public health challenge among the elderly in low- and middle-income countries. This cross-sectional study examined demographic and metabolic factors associated with hypertension among the elderly living in urban and rural areas of West and Central Java Provinces, Indonesia. This study included 1,920 adults aged ≥60 years who had resided in the study areas for at least six months, were able to communicate effectively, and provided informed consent. Data were collected between March and August 2023 using stratified multistage random sampling, structured questionnaires, and biochemical measurements. Multivariable logistic regression revealed distinct patterns of association across settings. In …

Factors Associated With Antiretroviral Therapy Adherence In Patients With Hiv At A Public Hospital In Central Jakarta, Indonesia, Kareena Sari Fatimah, Laily Hanifah, Chandrayani Simanjorang, Nayla Kamilia Fithri

Kesmas

Patients with human immunodeficiency virus (HIV) are required to take antiretroviral therapy (ART) to suppress the virus. However, suboptimal adherence remains a critical barrier that can lead to treatment failure and persistent transmission risks. This study aimed to identify factors associated with ART adherence in patients with HIV. This quantitative study with a cross-sectional design consisted of patients with HIV aged >18 years who received care at the voluntary counseling and testing clinic of a public hospital in Jakarta, Indonesia. Purposive sampling was used. This study used HIV care and ART overview forms as instruments. Data were analyzed using multiple …

Identical Vanishing Of Coefficients In The Series Expansion Of Eta Quotients, Modulo 4, 9 And 25, Tim Huber, James Mclaughlin, Dongxi Ye

School of Mathematical & Statistical Sciences Faculty Publications

Let A(q)=:∑∞n=0anqn and B(q)=:∑∞n=0bnqn be two eta quotients. In some previous papers, the present authors considered the problem of when

an=0⟺bn=0.

In the present paper we consider the “mod m” version of this problem, i.e. for which eta quotients A(q) and B(q) and for which integers m>1 do we have (non-trivially) that

an≡0(modm)⟺bn≡0(modm)?

(We say “non-trivially” as there are trivial situations where an≡bn(modm) for all n≥0). The m for which we found non-trivial (in the sense just mentioned) results were m=p2, p=2,3 and 5. For m=4 and m=9, we found results which …

How A 2 To 5-Year Experimental Lake Powell And Lake Mead Release Program Tied To Reservoir Inflows Can Be A Win For Adaptive Risk Management, Brittany Fager, Anabelle Myers, Erik Porse, David Rosenberg

Civil and Environmental Engineering Faculty Publications

Lake Powell and Lake Mead are at risk of drawdown to their minimum power and dead pools in the next few years because current and proposed shortage and release operations tied to reservoir storage and sometimes prior natural flow cannot keep pace with U.S. Bureau of Reclamation’s numerous scenarios of more volatile, declining, and longer-lasting periods of low flows. One experimental program to reduce risk can instead adapt reservoir releases to monitored changes in physical reservoir inflow and reservoir evaporation. First, stabilize reservoir storage by temporarily setting reservoir release to the physical reservoir inflow minus evaporation (the available water). Second, …

Re: Conditional Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Revised Butte Hill Revegetation Specifications (Dated August 15, 2025), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

2022 Bpsou Stormwater Evaluation And Maintenance Report Annual Stormwater Report For Bpsou Stormwater Structures, Butte-Silver Bow Department Of Reclamation And Environmental Services

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

We Can Track Waves In The Atmosphere From The Bear Lake Observatory And The International Space Station, Connor Waite

Research on Capitol Hill

Both space weather and tropospheric weather can create waves in Earth’s atmosphere called traveling ionospheric disturbances (TIDs) that can: 

• Disrupt GPS navigation by several meters 
• Cause radio blackouts affecting aviation and emergency services 
• Interfere with satellite communications 
• Impact the growing space industry 

Plants Have A Chemical Defense To Protect Themselves From Herbivory, Isis Cordova

Research on Capitol Hill

All plants produce compounds for survival. My work focuses on how plants remember past attacks and whether that memory leads to stronger/faster responses.

Early Detection Of Harmful Algal Blooms (Habs) Using Qpcr And Predictive Modeling, Emily Samuels

Research on Capitol Hill

Harmful algal blooms (HABs) threaten drinking water, recreation, and public health in Utah Lake and waterbodies due to cyanotoxin production. Current monitoring methods detect toxins only after blooms are already established.

A New Tool Predicts The Risk Of Surface Damage And Subsequent Spacecraft Charging, Trace Taylor, Ashley Bahora

Research on Capitol Hill

We measured secondary electron yield (SEY), a key factor in spacecraft charging, across multiple materials under different surface conditions. SEY is a measure of how many electrons a surface releases when hit by radiation.