Engineering Commons^™

Lidar Mirror Detection Model For Autonomous Robotics, Sofiia Sarana

Women+ in Early Career Research Symposium

LiDAR sensors are widely used in autonomous robots and vehicles for mapping, navigation, and obstacle avoidance. Because mapping is a foundational capability in nearly all robotic systems, it must be both accurate and reliable. However, LiDAR frequently fails in environments containing mirrors or highly reflective surfaces, where distorted returns corrupt maps and generate false obstacles. Current solutions typically rely on additional sensors and computationally expensive sensor-fusion pipelines, which is costly and difficult to scale for compact robots with limited onboard resources. This paper presents a machine-learning–based LiDAR mirror detection model that identifies reflective surfaces directly from LiDAR data, reducing the …

When Irl Is Not An Option: Social Media Bans And The Exclusion Of Autistic Youth, Melanie Gruben, Ashley Sheil, Anne Ryan Duffy, Jacob Camillleri, Michelle O'Keeffe, Hazel Murray

Women+ in Early Career Research Symposium

After the roll-out of the social media ban in Australia in 2025, policy makers are considering psychosocial benefits and logistical implications. However, the needs of autistic people, who may rely more on the Internet for social connection earlier in life, should be taken into account. This white paper proposes a responsibility to support alternative means of social connection for autistic young people where bans are considered, as IRL (in real life) socialising is not always accessible.

A Human-Centred View Of Maritime Autonomous Surface Ships Operations Using The Shell Model, Natasya Habibah, Paul Hegarty, Breda Kenny

Women+ in Early Career Research Symposium

The concept of Maritime Autonomous Surface Ships (MASS) has existed for decades and is advancing rapidly as a result of developments in artificial intelligence. Despite these technological advancements, human involvement remains essential to ensure safety and reliability. This study applies the Software, Hardware, Environment, and Liveware (SHELL) model to develop a human-centric framework for examining the integration of human elements with intelligent and automated technologies in MASS. The framework considers software, with particular attention to regulatory aspects; hardware, including general system and sub-system architecture; environmental factors, including both natural and artificial, as well as dynamic and static elements; and liveware, …

Comparative Time Series Forecasting Of Pedestrian Footfall In Dublin City Centre, Mercy Koech

Women+ in Early Career Research Symposium

Research on urban populations has turned out to be a significant field of study for a long duration.Forecasting pedestrian footfall is important for urban management,retail planning,crime analysis and evaluating the influence of public gatherings.With the rise of smart cities and the proliferation of sensor technologies there now exists a rich supply of data that offers unprecedented insight into the behaviour of pedestrain traffic.This study undertakes a comprehensive analysis of timeseries forecasting methods to predict pedestrian footfall trends in Dublin City Centre a key urban area with diverse spatial characteristics and high foot traffic variability.Using data collected via PYRO-BOX Counters sensors …

Selfhealth: Continuous Semantic Intelligence For Privacy-Aware Lifelogging, Allie Tran

Women+ in Early Career Research Symposium

Lifelogging — the continuous digital recording of everyday experience through wearable cameras and sensors — has long promised benefits for memory augmentation, health monitoring, and lifestyle analysis. However, current systems follow a capture–store–retrieve model that delays analysis until after data collection, limiting their practical usefulness and creating significant privacy risks through prolonged retention of sensitive raw data. This paper argues that lifelogging should instead analyse data at the moment of capture, enabling timely, context-sensitive support and safer handling of personal information through privacy-by-design. We demonstrate the feasibility of this approach through SelfHealth, an early prototype system built on a custom …

Enhancing Engineering Education For Students With Intellectual Disabilities Through Universal Design For Learning, Bree Jimenez, Ginevra Courtade

Journal of Science Education for Students with Disabilities

This study explores the impact of a Universal Design for Learning (UDL) aligned engineering curriculum on teacher confidence and student engagement in special education classrooms, specifically focusing on students with intellectual and developmental disabilities (IDD). The research investigates how the curriculum, combined with targeted professional development (PD), supports teachers in delivering high-quality engineering instruction. Through a mixed methods approach, including surveys, interviews, focus groups, and classroom observations, data revealed significant improvements in teacher self-efficacy, particularly in areas such as scaffolding, differentiation, and accessibility. Teachers reported increased confidence in their ability to implement engineering lessons and foster engineering mindsets in their …

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 …

Multimodal Thermal And Mechanical Characterization Of Cryopreservation Effects In Biological Cells, Subhrajyoti Sourav Kumar Kundu

LSU Master's Theses

Cryopreservation is critical for long-term storage of cells, tissues, organs, and reproductive cells in medicine, biotechnology, and conservation. However, its success is limited by ice formation and cryoinjury, prompting extensive research into analytical tools for understanding and improving cryopreservation outcomes. We outline the principles of each technique and how they are used to detect key thermal and physical events such as ice nucleation, vitrification, devitrification, and cryoinjury. DSC enables quantitative thermal characterization including critical cooling/warming rates (ranging from 1-200°C/min for various systems) and glass transition temperatures. Cryomicroscopy provides direct real time visualization of ice crystal dynamics, distinguishing intracellular versus extracellular …

The Role Of Optical And Synthetic Aperture Radar Satellites In Military Intelligence, Khalifa Alnaqbi

Student Research Symposium (SRS)

The objective of this paper is to demonstrate that while optical and Synthetic Aperture Radar satellites are the two most powerful remote sensing tools in military intelligence, neither is sufficient on its own. This research aims to articulate their distinct operational roles and argue that their synergistic integration, together with other intelligence assets such as unmanned aerial vehicles, signals intelligence, and human intelligence, is essential for achieving comprehensive situational awareness in modern warfare. To establish this, the paper will first analyze the role of optical satellites in target identification and Synthetic Aperture Radar satellites in persistent detection and monitoring, detailing …

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 …

Advancing Computational Analysis Of Fluorescence Imaging For Head And Neck Cancer Surgical Guidance, Yao Chen

Dartmouth College Ph.D Dissertations

The main goal of surgery for head and neck squamous cell carcinoma (HNSCC) is to remove the tumor completely while preserving as much healthy tissue as possible to enhance patient survival and reduce complications. However, achieving clear surgical margins is difficult due to the complex anatomy of the head and neck and the reliance on a surgeon’s visual and tactile assessments. Recently, near-infrared (NIR) fluorescence molecular imaging has shown potential for better tumor visualization during surgery, using targeted imaging agents like epidermal growth factor receptor (EGFR) probes. This has led to the development of fluorescence-guided surgery (FGS), which helps surgeons …

Acoustic Levitation At Sub-Atmospheric Pressures And Reduced Temperatures: An Approach To Study Ice Crystal And Hypersonic Shockwave Interaction, Imteaz Osmani, David J. Delene, Hallie Boyer Chelmo

Graduate Research Achievement Day Posters

Micrometer-sized atmospheric ice crystals are commonly observed in high-altitude clouds. Inside clouds, they attach in different orientations, producing varied geometries, yet their formation mechanisms remain poorly understood. Their behavior under shock wave conditions remains underexplored due to lack of laboratory techniques capable of producing atmospherically realistic ice in controlled conditions. No experimental data and laboratory techniques exist to date on the interaction between atmospheric ice crystal aggregates and hypersonic shockwaves. To explore realistic atmospheric ice crystals’ thermodynamic and mechanical changes in hypersonic environments, we investigate the formation and behavior of ice crystal aggregates using acoustic levitation that avoids physical contact …

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 …

Using Facial Landmarks For Lip Motion Interpretation Applications, Kimi S. Wright

Theses and Dissertations

Facial motion, particularly lip movement, carries rich information about human speech that can be leveraged for a variety of computer vision and speech-processing tasks. Unlike other pixel-based methods, this work investigates the use of facial landmarks as a compact, privacy- preserving, and computationally efficient representation for lip-motion analysis. We evaluate landmark-based models across multiple tasks, including visual voice activity detection (VVAD), lip–audio synchroniza- tion, and visual speech recognition (VSR) for liveness detection. Using LRS3-VVAD1 and LRS22 datasets, we demonstrate that landmark-only models can achieve performance comparable to pixel-based systems for VVAD and synchronization, while significantly reducing parameter counts and inference …

Osha’S Knocking! A Descriptive Cross-Sectional Analysis Of Inspections At Private Universities In Florida., Acuna Gonzalez Santiago

Student Research Symposium (SRS)

Section 8 of the Occupational Safety and Health Act (OSH Act) empowers OSHA to conduct inspections and enforce standards prescribed in Title 29 of the Code of Federal Regulations; however, limited literature and lack of descriptive statistics exist regarding oversight and inspection patterns across Higher Education Institutions (HEI) in Florida. Assessing these patterns is paramount for aiding higher education stakeholders in evaluating their hazard identification and control techniques. This descriptive cross-sectional study examined OSHA's inspection database — January 1, 2015 to October 20, 2025 — indexed by NAICS code 611310, analyzing all 32 four-year non-profit HEI with at least 1,000 …

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 …

Enhancing Wildlife Strike Risk Assessment Through Large Language Model–Driven Data Analysis, Bill Deng Pan

Student Research Symposium (SRS)

Wildlife strikes remain a persistent safety and economic concern across global aviation operations, highlighting the need for advanced analytical methods to improve risk assessment and mitigation. Traditional statistical approaches to wildlife-strike data, while effective for structured variables such as altitude, phase of flight, or aircraft type, often overlook valuable insights embedded in the unstructured narrative components of strike reports. This study proposes the application of Large Language Models (LLMs) for the automated extraction, classification, and interpretation of information within the Federal Aviation Administration (FAA) Wildlife Strike Database. Using natural language processing (NLP) techniques, LLMs will be utilized to identify key …

Development Of Hypergraph Based Deep Neural Framework For Precise Cancer Subtyping And Meta Visualization, Pooja G Ms

Theses and Dissertations

Accurate Cancer Subtyping is a cornerstone of modern oncology essential for effective diagnosis and guiding personalized treatment. Histopathological Images (HIs) which capture the microscopic structure of tissues are widely used for cancer detection and subtyping. Even though deep learning has made significant advances, existing HI based subtyping methods often focus on specific cancer types, lacking a generic framework.

A unified framework that can classify multiple cancers with high specificity is desperately needed. In response to these limitations, this thesis proposes a robust multi-cancer, multi-class subtyping framework called DSHGNet (Depthwise Separable Hypergraph Convolutional Neural Network) which integrates Depthwise Separable Convolutional Neural …

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 …

Research Of Logic Elements Based On Complementary Bipolar Transistors, Nodira Batirdjanovna Alimova, Nilufar Baxtiyorovna Gulyamova

Chemical Technology, Control and Management

Important parameters for any type of inverter – a NOT logic gate – are the power consumption during switching and the supply voltage. The proposed connection of complementary (two different types) bipolar transistors reduces the current consumption and supply voltage by simultaneously using the cutoff and saturation modes of the bipolar transistors. It has been theoretically and experimentally established that an inverter using complementary bipolar transistors operates at low supply voltages, approximately 0.7 V. Power consumption is virtually independent of the inverter's static state. A method for calculating the transfer characteristic of an inverter using complementary bipolar transistors is developed, …