Engineering Commons^™

Reinforcement Learning For Imbalanced Data In Robotic Anomaly Detection Within Autonomous Manufacturing, Salma Messaoudi, Ahmed Bendaouia, El Hassan Abdelwahed, Mohammed Ameksa, Hajar Mousannif, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications

Ensuring reliable anomaly detection in industrial robots is critical for safe and autonomous manufacturing operations. However, it remains challenging due to temporal dependencies and class imbalance in sensor data. This study presents a reinforcement learning approach using Deep Q-Network (DQN) enhanced with Long Short-Term Memory (LSTM) and Gradient Boosting Machine (GBM) for robust anomaly detection in robotic systems. The proposed framework integrates an LSTM into the DQN policy to capture temporal patterns. It also introduces a novel GBM-based reward mechanism that mitigates class imbalance by applying SMOTE (Synthetic Minority Over-sampling Technique) after removing temporal dependencies. Experimental results demonstrate that this …

Characterizing Atmospheric Turbulence With The Lunar Step Response Method, Patrick D. Carattini, Caleb J. Stilp, Katelyn M. Atkinson, Stephen C. Cain

Faculty Publications

Most methods that astronomers use to characterize the strength of atmospheric turbulence in and around their observatories use differential image motion monitors observing a star to provide the necessary data for the measurement. With the Moon becoming a greater national priority, the need to characterize atmospheric paths between observatories on Earth and the Moon is potentially going to grow in the future. To this end, the differential image motion monitor is not an ideal instrument for characterizing turbulence along paths between observatories and the Moon as the bright Moon makes it difficult to detect and locate stars in its vicinity. …

Scheduling As An Organizational Capability, Felix Delmonte

Mechanical and Civil Engineering Faculty Publications

This study synthesizes evidence on schedule governance as an organizational capability integrating Lean practices, BIM, Digital Twin, and AI to convert scheduling into continuous, data driven decision making that links front line observations to executive risk appetite and funding choices, showing how 4D/5D BIM, clash detection, automated material takeoff, and IoT enabled twins shorten planning horizons, reduce design errors by up to 80%, improve timeline adherence by 20%–30%, and, when AI is applied, further cut delays by about 18% and procurement costs by approximately $2.5 million; a four layer Integrated Lean–Digital Framework is proposed to align strategic intent, collaborative digital …

Three-Dimensional Printing Of The Epineurium For Peripheral Nerve Repair: A Comprehensive Review Of Novel Scaffolds For Nerve Conduits, Alynah J. Adams, Iulianna C. Taritsa, Kaavian Shariati, Aaron Dadzie, Jose A. Foppiani, Maria Jose Escobar-Domingo, Daniela Lee, Angelica Hernandez-Alvarez, Kirsten Schuster, Helen Xun

School of Medicine Publications

Background: Nerve conduits are used to bridge peripheral nerve defects caused by trauma, iatrogenic injury, or oncologic disruption. Three-dimensional (3D) biomimetic scaffolds for peripheral nerve regeneration have advanced significantly in recent years, driven by improvements in printing technology and neuronal seeding techniques. We report on published designer conduits that can recreate the epineurium, a critical yet challenging-to-manufacture feature of nerve tissue.

Methods: A medical librarian conducted a literature search for our systematic review on EMBASE, Web of Science, and PUBMED, following PRISMA guidelines, for articles from January 2010 to January 2026 for the systematic review. Descriptive statistical analysis was performed …

Supporting Data For Novel Approach For Quantifying The Impact Of Coherent Structures On The Turbulent Kinetic Energy Decay Rate, Tim Berk, Ankit Gautam

Browse all Datasets

This project investigates the influence of coherent structures on the decay of turbulent kinetic energy (TKE). The work was conducted as part of the PhD research in Mechanical Engineering by Ankit Gautam at Utah State University.

Thermal Management And Lubrication Characteristics Of Tungsten Disulfide (Ws2) Vegetable-Based Nanolubricants, Jaime Taha-Tijerina, Dyana De Leon-Elizondo, Jade Mendieta, Leonardo Taha-Soto

Informatics and Engineering Systems Faculty Publications

Recent innovations with the aid of nanotechnology are more frequently seen in the industrial sectors. Lubricants are a high-end commodity resource used in many manufacturing processes; unfortunately, most of these lubricants are petroleum-based, which come with certain drawbacks, such as environmental aspects, handling issues and high costs. With the incorporation of nanostructures within fluids and lubricants, novel material alternatives are replacing conventional lubrication systems, maintaining the required thermophysical and tribological characteristics. This research provides an analysis of vegetable lubricant, castor oil (CO), and the effects of the incorporation of WS2 nanofiller at diverse filler fractions. A TEMPOS thermal analyzer device …

Decentralized Q-Learning Supervisory Control For Coordinated Multi-Loop Tuning In Pump Stations, David Brattley, Wayne Weaver

Michigan Tech Publications

This paper introduces a reinforced learning-based supervisory control architecture that oversees multiple Recursive Least Squares (RLS) based self-tuning pump controllers and determines when each loop is permitted to adapt its gains. The supervisor learns adaptation policies that minimize interaction between loops while preserving responsiveness to changing hydraulic conditions. A two-loop pump station simulation is used to evaluate performance under product changes and transient flow disturbances. The results show that the supervisory layer reduces the number of simultaneous adaptation events by over 70%, leading to a 32% lower pressure-tracking error and 45% fewer gain-induced oscillations compared to conventional independent adaptive control. …

Molecular Origins Of Non-Frozen Water In Polyelectrolyte Brushes, Ali Dhinojwala, Saveen Jayaweera, Md Golam Kibria, George Mallinos

University Research

Polyelectrolyte brushes (PEBs) are promising coatings for reducing ice adhesion and regulating water freezing at interfaces, yet direct measurements of nonfrozen water retention at subzero temperatures remain scarce. Here, we investigate the freezing behavior of water confined in poly([2-(methacryloyloxy)ethyl]trimethylammonium) (PMETA) brushes with chloride, iodide, and sulfate counterions using a custom-built low-temperature attenuated total reflectance infrared spectroscopy system. Furthermore, we quantify the fraction of water that was present within the brush that does not freeze as well as the changes in polymer volume fraction within the brush as a function of temperature. Spectroscopic analysis of water vibrational modes reveals that PMETA …

Beyond Catalysts And Membranes: Using Cell Assembly And Operating Strategies To Significantly Improve The Performance Of Aem Electrolyzers, Mahmoud Amirsalehi, Venkata Sai Sriram Mosali, Mohammed Al-Murisi, Shaghayegh Bashiri, Hari Gopi, Pongsarun Satjaritanun, Benjamin Britton, Karen Swider-Lyons, Mustain E. William

Faculty Publications

Green hydrogen, produced through water electrolysis, is a key enabler of a low-carbon energy future, and anion exchange membrane electrolyzers (AEMELs) have emerged as a promising technology due to their potential for ultra-low-cost operation. However, achieving low cell voltage at high current densities and maintaining long-term durability remain key AEMEL challenges. To address these issues, most research efforts to date have focused on developing advanced catalysts and membranes. In contrast, the influence of non-material factors, such as cell assembly parameters and operating conditions, remains underexplored, even though they can significantly impact performance. This study investigates how such variables affect AEMEL …

Demonstration Of Coherent Optical Phase-Shift Keying With A Watt-Class 1550 Nm Tapered Diode Laser Amplifier For Free-Space Optical Communication Applications, Charlotte K. Duda, Aaron Cross, Chadwick Lindstrom, Julie Smith

Space Dynamics Laboratory Publications

High-power semiconductor optical amplifiers (SOAs) are a promising alternative to erbium-doped fiber amplifiers (EDFAs), which typically amplify the weak signals used in free-space optical (FSO) communications. In this work, we demonstrate that an Aura TM SOA operating with 1 W output power can be used to transmit phase-shift key (PSK) protocols required of next-generation FSO communication networks. Firstly, we demonstrate successful transmission of binary phase-shift keying (BPSK) for bit rates up to 50 Gbps. Secondly, we demonstrate successful transmission of quadrature phase-shift keying (QPSK) for bit rates up to 100 Gbps. For both PSK protocols, we demonstrate comparable constellation error-vector …

Aiw26s: Github, Sireesha Kuchimanchi

Paul English Applied Artificial Intelligence (AI) Institute Publications

This workshop was part of the PEAAII and SAC AI Workshop Series at the University of Massachusetts Boston. The session introduced students to Git and GitHub as essential tools for software development and collaboration. Participants learned the fundamentals of version control, including repositories, commits, branching, push and pull operations, and pull requests. The workshop also covered best practices for creating strong GitHub portfolios, writing effective README files, contributing to open-source projects, and using GitHub to support professional development and career growth.

Fiber Optic Polarimetric Stress Sensor Improvements, Maxwell R. Richter, Max Randall, Mark C. Harrison

Engineering Faculty Articles and Research

The progression of diseases such as cancer has been correlated with tissue stiffness. For example, breast cancer tissue has been found to be stiffer than healthy mammary tissue. At present, stiffness measurement devices are not suitable for nondestructive, high-resolution measurements on small, delicate samples. We report a compact, portable, and sensitive fiber optic stress sensor that overcomes many of these limitations and is suitable for soft materials such as tissue. We demonstrate several improvements to a previous fiber stress sensor in physical hardware, software, and data analysis. We have designed and fabricated a custom enclosure to shield the sensitive setup …

What Is Passive And Active Release Retrofitting Rainwater Harvesting Systems?, Sarah E. Waickowski, Amy E. Scaroni, Beatriss H. Calhoun

Forestry and Natural Resources

Rainwater harvesting is the collection and temporary storage of rainwater for non-potable applications and stormwater management. Rainwater harvesting systems can be retrofitted with passive or active release to improve how well the systems manage stormwater runoff. This publication contains information that may be useful to municipalities, stormwater professionals, rainwater harvesting system owners and/or managers, homeowner associations, and stormwater educators, among others, on what is passive and active release, including their benefits and where to find more information.

Evaluating The Response Of Ageing Rc Bridge Piers To The 2023 Kahramanmaraş Earthquake Using Bouc-Wen Hysteretic Models, Negin Fayaz, S. Kocakaplan Sezgin, E. Ahmadi, M. M. Kashani, M. Zaker Esteghamati

Civil and Environmental Engineering Student Research

This study examines the seismic response of reinforced concrete (RC) bridge piers subjected to ground motion (GM) records from the 2023 Kahramanmaraş earthquake by comparing the impact of pulse-like versus no-pulse records. A suite of 300 nonlinear Bouc-Wen hysteretic models was developed to represent piers with varying nonlinear behavior. Each Bouc-Wen model was assessed under 24 pulse-like and 28 no-pulse GMs, resulting in 15,600 nonlinear time-history simulations. Subsequently, the relationship between Bouc-Wen parameters (i.e., period and yield displacement) and seismic responses (i.e., maximum displacement, residual displacement, and maximum acceleration) was analyzed. The results show that pulse-like records produce 5 times …

When The Student Surpasses The Teacher: Better Generalization In Ai-Based Seismic Waveform Quality Assessment Using Knowledge Distillation, Ali Namin, F. Jalaeifar, A. Kottke, M. Zaker Esteghamati

Civil and Environmental Engineering Student Research

This paper presents a knowledge distillation (KD)-based approach to reduce computational expenses and improve the generalizability of deep learning-based models for quality assessment of seismic waveforms. Using two different waveform datasets, teacher models are distilled into lightweight student models from two families of time-series-based and image-based models. Models from both student families are trained on a development dataset and evaluated on the testing portion of the development dataset, as well as on an entirely different external testing dataset. Results indicate that KD can provide student models with substantially reduced size (5%-10% of the teacher model's size) and latency while preserving, …

Sensing Negative-Cone Rotational Diffusion Of Dipole-Like Emitters, Yuanxin Qiu, Kaizhi A. Nie, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Fluorescence anisotropy and single-molecule orientation-localization microscopy (SMOLM) are powerful techniques that quantify the rotational diffusion of dipole-like emitters, which is important for sensing molecular interactions and chemical environments at the nanoscale. Numerous theoretical and experimental studies have thoroughly characterized single-molecule rotations even when those rotations are much faster than the detector integration time. Here, we extend the theory of measuring rotational diffusion to situations where a single dipole rotates uniformly everywhere outside of an isotropic cone of a certain size, termed a negative cone. This scenario corresponds to negative fluorescence anisotropy 𝑟 and has been observed in emitters exhibiting strong …

Dual-Function Plasmonic Structure For Logic Operations And Circular Polarization Detection, Marjan Bazian, Mark C. Harrison

Engineering Faculty Articles and Research

Many integrated photonic devices have a high potential for dual applications, making them more versatile components in photonic integrated circuits. In this study, we show that a plasmonic XOR gate structure, originally designed to perform logic operations, can also be used as a circular polarization detector. This multi-purpose capability stems from the phase-encoded input mechanism that controls the output response of the structure. We adapted this mechanism to select the output based on the polarization state of light. The design of this structure, utilizing the subwavelength field confinement of plasmonic waveguides, enables the integration of logic and detection functions into …

Computational Modeling Of Enhanced Nonlinear Optical Response In Plasmonic Waveguide Devices With Epsilon-Near-Zero Films, Kevin T. Le, Mark C. Harrison

Engineering Faculty Articles and Research

Silicon photonics faces fundamental limitations in nonlinear applications due to weak Kerr nonlinearity, substantial two-photon absorption, and coupling challenges with subwavelength structures. This work investigates epsilon-near-zero (ENZ) materials integrated into plasmonic waveguide architectures for enhanced nonlinear photonic devices. ENZ materials exhibit nonlinear refractive indices several orders of magnitude higher than conventional materials near their zero-permittivity wavelength, enabling giant optical effects over deeply sub-wavelength interaction lengths. We present finite element method simulations of plasmonic ENZ waveguides, investigating layer thickness optimization for nonlinear enhancement while minimizing optical losses. Initial modal analysis confirms superior field confinement in hybrid plasmonic-ENZ structures compared to conventional …

Investigating Confounding Factors In Shear Wave Speed Measurements Of Fibrotic Liver Tissues: A Computer Simulation Study, Emily J. Miller, Yongmei Jin, Jingfeng Jiang

Michigan Tech Publications

Screening patients with liver fibrosis and identifying those at risk of developing advanced liver fibrosis is of clinical interest. Shear wave elastography (SWE), a promising non-invasive screening tool used to distinguish healthy tissue from diseased tissue, measures tissue shear wave speed (SWS) to describe tissue stiffness and identify liver fibrosis. However, considerable variations in the reported results have been found. We propose that the heterogeneity of the liver tissue background, such as the presence of fatty liver tissue and the preferred local orientation of the scarred fibrotic liver tissues embedded into the liver parenchyma, may contribute to the uncertainty in …

Dynamic Deep Prompt Optimization For Defending Against Jailbreak Attacks On Llms, Doniyorkhon Obidov, Honggang Yu, Xiaolong Guo, Kaichen Yang

Michigan Tech Publications

Large Language Models (LLMs) demonstrate impressive capabilities across many applications but remain vulnerable to jailbreak attacks, which elicit harmful or unintended content. While model fine-tuning is an option for safety alignment, it is costly and prone to catastrophic forgetting. Prompt optimization has emerged as a promising alternative, yet existing prompt-based defenses typically rely on static modifications (e.g., fixed prefixes or suffixes) that cannot adapt to diverse and evolving attacks.

We propose Dynamic Deep Prompt Optimization (DDPO), the first jailbreak defense based on deep prompt optimization. DDPO uses the target LLM’s own intermediate layers as feature extractors to dynamically generate defensive …

Impediments To Transforming The Healthcare Delivery System: Shifting The Paradigm From Provider Centric To Patient Centric, Elizabeth A. Regan, Manasa Devi Chinta

Faculty Publications

Introduction: 

Stated aims for digital healthcare transformation frequently cite goals for better coordinated patient-centric systems. However, despite advances in medical science, digital technologies, health policies, and billions of dollars invested over the past 25 years, most healthcare providers are far from fully realizing the demonstrated benefits of today's digital technologies for improving patient care. Sharing information across healthcare systems remains challenging. Problems with fragmentation, quality, inequities, and rising costs of care delivery persist. A recent study of 1,026 U.S. hospital systems found that only 15.8 percent achieved a digital maturity level needed to provide digitally enabled healthcare services to better …

Influence Of Pulse Width On Energy Deposition And Temperature In Nanosecond-Pulsed Discharges, Christopher B. Reuter, Joshua B. Sinrud, Tanvir I. Farouk, Nicholas S. Dewey, Dmitri Kaganovich

Faculty Publications

Nanosecond-pulsed discharges are a promising method to enhance combustion but can generate significant levels of electromagnetic interference (EMI). Modifying the discharge pulse width is an unexplored option to reduce EMI, but few studies have examined how changing the pulse width affects discharge parameters such as energy and temperature. This study addresses this issue by systematically investigating how the pulse width affects the energy per pulse, breakdown time, rotational temperature, and vibrational temperature in air across different frequencies, flow velocities, and gap distances in a plasma-assisted flow tube. It is observed that the pulse width has a substantial impact on the …

Comment On The Draft Environmental Impact Statement For New Operations For Lake Powell And Lake Mead Post-2026, Bryan Williams, Caitlyn Andrus, Brittany Fager, Matthew Fugal, Parker Hansen, Ashley Jones, Shaun Joseph, Ashley Mcallister, Braden Wilding, David Rosenberg

Civil and Environmental Engineering Student Research

We appreciate the Bureau of Reclamation’s extensive effort in preparing the Post-2026 Draft Environmental Impact Statement (Draft EIS) for operational guidelines for Lake Powell, Lake Mead, and the Colorado River Basin. This commentary will address positives, questions, and concerns from the Draft EIS. We also share recommendations for consideration in the Final EIS.

Design And Evaluation Of A Collaborative Xr Framework With Abstract Building Blocks For Manufacturing System Prototyping, Shaun Macdonald, Bixun Chen, Yuanjie Xia, Rami Ghannam

School of Engineering Technology Faculty Publications

Manufacturing systems are complex installations designed and developed by stakeholders with differing expertise. However, system design primarily features traditional methods, long lead times, and siloed environments, which obstruct comprehension, communication, or collaboration. Prior research has used extended reality (XR) to prototype and visualise specific manufacturing applications; however, flexible system modelling remains complex. To address these issues and lay the foundation for future-facing manufacturing design as part of Industry 4.0, we introduce ARTIFY—a prototype XR framework for conceptual system prototyping. It features abstract building blocks that can be semantically reconfigured to support early-stage modelling of varied manufacturing systems in immersive environments. …

Co-Electrospinning Polyacrylonitrile (Pan) / Polymer Of Intrinsic Microporosity-1 (Pim-1) For Electrochemical-Based Sensor For Pyridine Detection And Absorption, Samar A. Salim

Nanotechnology Research Centre

The electrospinning of the polymer of intrinsic microporosity-1 (PIM-1) poses challenges due to its limited solubility and tendency to form bead-like structures at high concentrations. This work details the synthesis and analysis of electrospun composite fibers made from polyacrylonitrile (PAN) and PIM-1 for electrochemical applications. The data analysis confirmed the successful incorporation of PIM-1 into the PAN matrix. The fiber characteristics were significantly influenced by PIM-1 loading (1–10%), resulting in fiber diameters ranging from 0.8 to 1.7 μm. A 10% concentration of PIM-1 results in the formation of macropores with diameters ranging from 0.5 to 1.7 μm. Optical analysis using …

Hybrid Cnn–Gru-Based Demand–Supply Forecasting To Enhance Sustainability In Renewable-Integrated Smart Grids, Süleyman Emre Eyimaya, Necmi Altin

Faculty Publications

The rapid integration of renewable energy sources in smart grids has introduced significant uncertainty in both power generation and consumption patterns, posing challenges to environmental, economic, and operational sustainability. Accurate short-term forecasting of energy demand and supply is essential for achieving optimal scheduling, grid stability, and resilient operation in renewable-integrated power systems. This study proposes a hybrid deep learning framework combining Convolutional Neural Networks (CNN) and Gated Recurrent Units (GRU) for intelligent joint demand–supply forecasting in smart grids. The model was developed and implemented in MATLAB using real-world datasets comprising electricity consumption, photovoltaic (PV) generation, temperature, and irradiance variables. Comparative …

An Adaptive Immersive Training Framework For Miner Self-Escape Readiness In Underground Mining Emergencies, Muhammad Azeem Raza, Samuel Frimpong, Saima Ghazal

Mining Engineering Faculty Research & Creative Works

Underground mining environments are complex and hazardous operations where emergencies continue to happen. Underground mine emergencies require rapid, high-stakes decision-making under conditions of uncertainty, stress, and limited visibility. Conventional mine emergency training largely relies on instruction-based approaches which provide insufficient exposure to the cognitive and behavioral demands of real underground emergency situations. There has been an identified need to train miners for knowledge, skills, abilities, and other characteristics (KSAOs). This study proposes an Adaptive Immersive Training Framework (AITF), a cognitively grounded architecture that integrates cognitive task analysis (CTA), KSAOs, and situational awareness assessment for miner self-escape training and readiness. The …

Investigation Of Material Properties Of Thermoplastic And Thermoset Polymer Materials At Cryogenic Temperatures Using Molecular Dynamics, Swapnil S. Bamane, Sagar Patil, Khatereh Kashmari, Benjamin D. Jensen, Brett A. Bednarcyk, Evan J. Pineda, Jeffery Hinkley, Ozgur Keles, Jin Ho Kang, Gregory Odegard

Michigan Tech Publications

Cryogenic fluids, such as liquid hydrogen and liquid oxygen, are critical for space operations as rocket fuel and life support. The fluids need to be contained in tanks that can withstand the effects of cyclic thermal and pressure loading throughout their lifecycle. Polymer matrix composites (PMCs) are prime candidates for these tanks because of their low mass, which is important for fuel savings. Although advanced PMC systems have been developed for a wide range of engineering applications, insight is still needed to identify optimal polymer matrix materials for cryogenic structural applications. The objective of this study is to use molecular …

Move Fast And Don’T Break Things: Collaborative Privacy Governance In Higher Education, Tyler Schroder, Chad Fenner

Research & Publications

Student-developed applications increasingly replicate or replace official university platforms, often prioritizing speed over security and privacy. This “shadow IT” ecosystem emerges from gaps in institutional tools and is amplified by AI-assisted development, which can introduce insecure defaults. These informal systems risk exposing FERPA‑protected or sensitive institutional data, as seen in student‑built directory and club‑information apps that redistributed restricted information more permissively than intended. While most universities lack clear governance mechanisms for student developers, Yale’s structured, student‑specific data‑use policy offers a notable model. This paper examines these risks and proposes a collaborative, API‑first framework that supports innovation while enforcing privacy, security, …

Feasibility Of Using Recycled Waste Plastic In Concrete Pavements In Nebraska, Amasi Hajahja, Jamilla Teixeira, George Morcous

Nebraska Department of Transportation: Research Reports

Waste plastic (WP) is a growing environmental concern due to its non-biodegradable nature, large-scale production, and harmful impact on natural resources. With nearly 75% of WP in the U.S. ending up in landfills, effective recycling strategies are urgently needed. In parallel, the limited availability of natural aggregates highlights the need for alternative materials in concrete construction. This study investigates the feasibility of using recycled waste plastic (RWP) in concrete mixtures, both as aggregates and fibers for rigid pavement applications in Nebraska. Concrete mixtures were prepared by partially replacing natural fine aggregates with recycled plastic aggregates (RPA) at replacement levels of …