Digital Commons Network^™

A Mold Mating Surface Temperature Monitoring System For Injection Molding Using Infrared Thermography And Mahalanobis Distance, Yoshio Fukushima, Makoto Fukushima, Sho Shibuya, Keigo Kudo, Yuta Abe

ASEAN Journal on Science and Technology for Development

In plastic injection molding, minimizing defects is crucial for sustainable and stable manufacturing because resin behavior and molding conditions fluctuate due to variations in material lots, seasonal shifts, and factory environmental factors such as temperature and humidity. Among various process parameters, mold temperature　- specifically the mold mating surface temperature immediately after part ejection-　 plays a critical role in mitigating these variations and maintaining consistent product quality. However, embedding conventional sensors into the mating surface is structurally difficult. While non-contact infrared thermography is an effective alternative, shiny metallic mold surfaces suffer from low emissivity, leading to inaccurate readings. Furthermore, high-end …

2-Point Focused Laser Differential Interferometry Measurements Of A Parallel Jet In Supersonic Flow, Joshua Gary, Joseph Villarreal, Davide Vigano

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Turbulence in compressible flows plays a central role in applications such as air-fuel mixing in supersonic combustors and is significantly more complex than incompressible turbulence due to the presence of fluctuating thermodynamic quantities. As such, models like the Strong Reynolds Analogy (SRA) are used to relate these quantities. However, SRA validity has been examined primarily in boundary-layer flows. In this work, a newly developed Two-Point Focused Laser Differential Interferometry (2-FLDI) system is implemented in a two-dimensional parallel supersonic jet. The diagnostic is described in detail, including optical alignment procedures, calibration methods, and data analysis techniques. Measurements acquired at multiple streamwise …

Pillpetz: A Smarter Way To Encourage Medication Adherence In Children, John H. Begley

CMC Senior Theses

Medication adherence is usually framed as a problem of patient behavior, but this thesis argues that it is equally a problem of design. Children who take daily medication face barriers that adults often do not: developing executive function, dependence on caregivers, shifting school and home routines, privacy concerns, and stigma around being perceived as different. The standard prescription bottle, by contrast, was designed primarily for dispensing efficiency, safety, and accidental ingestion prevention—not for sustained daily use by a developing child.

This thesis proposes PillPetz, a smart pill case and digital companion that uses routine, play, dose confirmation, and caregiver-connected support …

Stall Detection In Hydraulic Excavator Operations Using Heuristics And Machine Learning: A Case Study, Mateo Fernando Montenegro Defaz, Kwame Awuah-Offei, Yixiang Gao

Mining Engineering Faculty Research & Creative Works

This work aims to develop a reliable algorithm for stall detection during excavator digging by analyzing key operational variables such as velocity and angular displacements from machine monitoring data. The work develops and validates a heuristic algorithm to detect stalling events and trains a support vector machine classification algorithm to distinguish between "normal" digging cycles and cycles with stalling. This work is a novel attempt at using a classification algorithm to categorize digging cycles into normal and those with stalling events based on machine monitoring data alone. The developed classification algorithm achieved a sensitivity of 100%, indicating it correctly identified …

Corrigendum To “3d Semi-Analytical Thermo-Elasto-Plastic Model For Additive Manufacturing”(Additive Manufacturing, (2026), 127, C, (105308), (S2214860426002344), 10.1016/J.Addma.2026.105308), Tao Liu, Ming C. Leu, Edward C. Kinzel, Chinedum Okwudire

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The author regret about the correction in the Equation B(1) in original article. The corrected version of the Equation B(1) is given below,(1.1)∂uxxx,ξ∂x=116πμ1−ν4ν−1x−ξxR3−3x−ξx3R5−8ν−5x−ξxR13+34ν−3x−ξx3R15−18x−ξxzξzR15+30x−ξx3zξzR17−12ν−12ν−1x−ξxR1R1+z+ξz2+4ν−12ν−1x−ξx3R13R1+z+ξz2+8ν−12ν−1x−ξx3R12R1+z+ξz3 The authors would like to apologise for any inconvenience caused. DOI of original article: < 10.1016/j.addma.2026.105308>

Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems, Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

In sensor-driven dynamic systems, missing data can severely degrade parameter estimation accuracy. This article investigates the impact of missing data on phase estimation in a mass-spring-damper system using an information-theoretic framework based on the Cramér-Rao Lower Bound (CRLB). Closed-form CRLB expressions are derived for four scenarios: complete data, missing completely at random (MCAR) deletion, MCAR-based imputation, and missing at random (MAR) missingness via a selection-weighted formulation. These bounds are used as theoretical benchmarks to evaluate classical imputation methods (last observation carried forward (LOCF), linear interpolation) and advanced approaches (Kalman filtering, Rauch-Tung-Striebel (RTS) smoothing, Bayesian inference, and transformer-based imputation) through Monte …

Evaluating The Impact Of Cognitive Distraction On Spaceflight-Relevant Task Performance Using Surface Electromyography And Motion Capture, Allyson K. Mitchell

UNF Graduate Theses and Dissertations

Cognitive distraction poses a risk to astronaut performance during complex, multitasking operations in spaceflight environments. This study examined the effects of cognitive load on neuromuscular coordination and task execution using surface electromyography (sEMG) and motion capture. Thirteen participants performed spaceflight-relevant tasks under undistracted and distracted conditions, with distraction induced through verbal questioning. EMG signals from eight upper-extremity muscles were processed using envelope filtering, peak normalization, and time normalization to enable inter-subject comparison, and group-level mean activation with standard deviation was analyzed. While overall muscle activation was similar between conditions, phase-dependent differences were observed, with undistracted trials showing higher activation during …

High Temperature Diffraction From Aerodynamically Levitated Materials, Chris J. Benmore, Stephen K. Wilke, David Lipke, Richard Weber

Materials Science and Engineering Faculty Research & Creative Works

Aerodynamic levitation combined with laser beam heating has become an established technique for studying the structure of materials at ultra-high temperatures and under non-equilibrium conditions. This article briefly highlights some recent technical and scientific advancements in understanding the relationships between a material's behavior and its structure, investigated using diffraction methods. It focuses on three evolving frontiers: sophisticated sample environments for accessing metastable states and reactive chemistries, high-flux photon and neutron probes to reveal atomic structure, and advanced computational modeling frameworks. Free from contamination, containerless processing (levitation) can minimize heterogeneous nucleation at the interface, enabling access to deeply supercooled melts or …

Investigating The Effects Of Pressure On Fe And Co Intercalated 2h-Tas2 Through First-Principle Calculations, Ronald E. Putnam Jr.

UNF Graduate Theses and Dissertations

Using first-principles methods, we investigate the effects of applied isotropic pressure on the electronic and magnetic properties of intercalated Fe1/3TaS2 and Co1/3TaS2. Fe1/3TaS2 has been shown to be a ferromagnet that undergoes structural and magnetic phase transitions under applied pressure. The magnetic phase transitions are observed to be linked to the structural shift, and a mixture of magnetic phase states is present between 3 GPa and 6 GPa. Co1/3TaS2 was found to be antiferromagnetic, as confirmed by experimental work. One- and two-unit-cell systems of Co1/3TaS2 are analyzed, both showing band splitting that disappears under pressure. The application of pressure forces …

Development Of Thermal Joints For Conduction-Cooling Applications, J. Lewis, G. Ciovati

Mechanical & Aerospace Engineering Faculty Publications

In support of the development of conduction-cooled superconducting radiofrequency (SRF) niobium cavities for use in continuous-wave linear accelerators, an experimental study of thermal contact resistance was performed on bolted joints using high-purity niobium, aluminium, and copper along with Apiezon N grease and indium foil as interfacial materials. The geometry of each joint investigated aims at replicating the design adopted in conduction-cooled SRF cavities currently under development at Jefferson Lab. The materials' thermal conductivity and the joints' thermal resistance were measured in the temperature range of 3.5 - 10 K. The results showed that the low thermal contact resistance of 2-4 …

Enhancing The Performance Of Disk-Based Key-Value Stores: From Learned Index Acceleration To I/O-Efficient Hybrid Caching, Sujit Maharjan

Computer Science and Engineering Dissertations - Archive

The exponential growth of data in modern computing environments has rendered the efficient extraction of information from massive datasets a critical systemic requirement. Key-value (KV) storage systems serve as the backbone for these operations; however, their performance is consistently bottlenecked by two primary functional requirements: identifying the data's location and managing the physical cost of accessing the storage device. Data locations are typically identified via an index, while disk I/O is minimized through caching. This dissertation presents LearnedStore, TurboIndex, and ReadBooster, which break these performance bottlenecks by introducing architectural modifications to the index and cache. LearnedStore accelerates operations by adapting …

Adaptive Synchronization In Digital Twin–Enabled Iot Systems: A Unified Framework For Energy, Fidelity, And Latency Trade-Offs, Uzma Zehra

Computer Science and Engineering Theses

Digital twin technology has emerged as a foundational paradigm for enabling real-time monitoring, analysis, and control in Internet of Things (IoT) systems by maintaining virtual representations of physical processes. Its effectiveness, however, critically depends on timely and accurate synchronization between distributed sensing devices and their corresponding digital counterparts. Frequent synchronization improves reconstruction fidelity and system responsiveness but incurs significant communication energy consumption and network latency. In contrast, infrequent synchronization conserves communication resources but can lead to stale or inaccurate digital twin states, particularly in environments with rapidly changing dynamics. These opposing effects give rise to a fundamental trade-off among energy …

Generative Imaging For Computational Pathology, Md Jillur Rahman Saurav

Computer Science and Engineering Dissertations

Hematoxylin and eosin (H&E) staining remains central to cancer diagnosis, providing morphological information essential for pathological assessment. Immunohistochemistry (IHC) and newer multiplexed imaging technologies complement H&E by revealing molecular information critical for accurate tumor subtyping and treatment decisions. In practice, however, H&E and IHC are obtained from different consecutive sections that are not spatially aligned, comprehensive multiplexed panels are expensive and tissue-consumptive, and not all stains are available at every clinical site, limiting comprehensive molecular profiling and the full diagnostic potential of these technologies in clinical practice. This dissertation addresses these gaps through three complementary generative deep learning studies in …

Non-Contact Optical Spectroscopy For Metabolic And Vascular Characterizations Of Orthotopic Tongue Cancer Models In Vivo, Md Zahid Hasan, Jing Yan, Sumit Sarker, Pranto Soumik Saha, Caigang Zhu

Biomedical Engineering Faculty Publications

Most tissue optical spectroscopy platforms use a fiber probe for light delivery and collection, while the inconsistent probe-sample contact could induce significant distortions in the measured optical signals, which consequently bring analysis errors. Moreover, it will be practically difficult to use a fiber probe for measurements in some cases such as oral cancer investigations using small animal models. To address the critical challenge, we report a portable, lens-based, optical spectroscopy device capable of quantifying key vascular and metabolic parameters in vivo without probe-sample contact. We combined lenses based diffuse reflectance and fluorescence spectroscopy into one portable platform to enable multi-parametric …

Combined Autofluorescence And Diffuse Reflectance Spectroscopy For Rapid Metabolic And Vascular Characterizations Of Orthotopic Tongue Tumors In Vivo, Pranto Soumik Saha, Jing Yan, Sumit Sarker, Zahid Hasan, Caigang Zhu

Biomedical Engineering Faculty Publications

Precise label-free quantification of tissue metabolic and vascular dynamics in vivo represents a critical challenge for cancer therapy prediction and longitudinal treatment assessment. In this study, we demonstrated a portable autofluorescence and diffuse reflectance spectroscopy device along with novel spectroscopic algorithms to quantify tissue vascular and metabolic parameters of orthotopic head and neck cancer models in vivo. Tissue-mimicking phantom studies were used to verify the dual-modal optical spectroscopy and easy-to-use spectroscopic algorithms for rapid and accurate estimation of tissue oxygen saturation, total hemoglobin contents, and intrinsic optical redox ratio. Animal studies were conducted to demonstrate the feasibility of our …

Noninvasive Diffuse Optical Monitoring Of Cerebral Blood Flow And Oxygenation Responses To Intermittent Hypoxia In Neonatal Rats, Pegah Safavi, Mehrana Mohtasebi, Chowdhury Azimul Haque, Faezeh Akbari, Xuhui Liu, Yiqi Yuan, Li Chen, Lei Chen, Guoqiang Yu

Biomedical Engineering Faculty Publications

Significance: Intermittent hypoxia (IH) is common in preterm neonates and can cause hypoxic–ischemic brain injury. Simultaneous monitoring of cerebral blood flow (CBF) and oxygenation is essential to detect oxygen delivery-extraction mismatches and guide intervention.

Aim: We aimed to adapt and test an innovative diffuse speckle contrast flow oximetry (DSCFO) system for continuous monitoring of cerebral hemodynamics during IH in neonatal rats, a model approximating human neonates.

Approach: Two compact laser diodes and a miniature CMOS camera were integrated into a fiber-free probe for continuous monitoring of changes in relative CBF (rCBF) and oxy- and deoxy-hemoglobin concentrations (Δ[HbO₂] and …

Simulation And Characterization Of Fuel Cell System Incorporated Internet Of Things, Ahmad N. Alhjouj

Mechanical Engineering Theses

Small air-cooled proton exchange membrane fuel cell (PEMFC) systems are increasingly relevant for portable and distributed applications, yet practical modeling and monitoring methods remain limited: high-fidelity physics-based models are too costly for real-time use, while purely data-driven models discard physical interpretability. This thesis develops an experimentally grounded gray-box framework for the characterization, reduced-order modeling, and IoT-enabled monitoring of a small hydrogen PEMFC system. A low-order nonlinear state-space model couples an electrochemical voltage layer to a lumped thermal layer, with parameters identified in stages using self-adaptive differential evolution. Identifiability analysis shows that static loss parameters are well constrained, while dynamic parameters …

Scalable Quantum Network Routing Through Reinforcement Learning And Resource Optimization, Tasdiqul Islam

Computer Science and Engineering Dissertations

Long-distance quantum communication depends on distributing high-delity entanglement across quantum repeaters. Entangled states are fragile: they decohere in memory, are consumed when used, and lose delity after each swap. Quantum routing therefore diers from classical routing: an algorithm must decide not only the path, but when to generate, store, swap, and consume entanglement before they lose their usefulness. This dissertation studies scalable resource allocation and routing for quantum networks under delity, memory, and concurrency constraints. It rst addresses re- peater deployment with heuristics that nd near-optimal locations while cutting com- putation from days to seconds versus integer linear programming (ILP). …

Early Detection And Objective Assessment Of Neonatal Hypoxic-Ischemic Encephalopathy Severity, Soheila Norasteh

Bioengineering Dissertations

Hypoxic–ischemic encephalopathy (HIE) is a neonatal brain injury caused by reduced oxygen and blood flow to the brain around the time of birth. It remains a major cause of neonatal mortality and long-term neurodevelopmental impairment worldwide. Therapeutic hypothermia is the standard treatment for moderate-to severe HIE and improves outcomes when initiated within the first six hours of life. Therefore, accurate assessment of injury severity during this period is essential. Cur rently, HIE severity is determined primarily through neurological examination and classified as mild, moderate, or severe. However, these examinations are subjective, cannot provide continuous monitoring of brain function, and may …

Multidentate Surfactant-Dependent Synthesis Of Giant Iridium Superstructures, Ramjee Balasubramanian, Maeren E. Hill

Chemistry & Biochemistry Faculty Publications

Giant superstructures of iridium, comprised of smaller spherical and slightly larger anisotropic nanoparticles, were synthesized by reducing iridium chloride in the presence of resorcinarene, a class of tetrameric macrocyclic polyphenols, with sodium borohydride in ethanol in 30 min under mild conditions. These superstructures were characterized by a range of techniques including TEM, HRTEM, EDS and other spectroscopic methods. The impact of the macrocyclic surfactant, its features and reaction conditions in dictating the formation of giant iridium superstructures was evaluated. The packing density of nanoparticles in these giant iridium superstructures could be altered qualitatively by varying the duration of the reaction, …

Array Signal Processing And Machine Learning In 5g/6g Networks, Roopesh Kumar Polaganga

Electrical Engineering Dissertations - Archive

This dissertation investigates advanced methodologies in Array Signal Processing (ASP) and Machine Learning (ML) to enhance the performance, efficiency, and intelligence of next-generation wireless networks, with a primary focus on 5G and emerging 6G systems. As wireless networks face rapid traffic growth, increasingly heterogeneous service requirements, and more complex propagation environments, conventional design and optimization approaches become insufficient to meet evolving demands in reliability, capacity, spectral efficiency, and energy efficiency. On the network intelligence side, this work develops data-driven frameworks for causal discovery, scheduler enhancement, session-duration prediction, and Radio Resource Control (RRC) state optimization using real-world telecommunication network data. On …

Passive Communication Across Diverse Swarm Formations And Scales Utilizing Wake Signatures For Messaging And Object Inference, Bryan Varela

Open Access Master's Theses

Passive wake signatures in fluid flows can support perception and low-rate communication in swarms. In cluttered or contested underwater environments, conventional acoustic, radio, and optical links can be power-hungry, intermittent, or undesirable when low observability is required. Wake-mediated cues offer a local, directional channel that does not require line of sight because each agent naturally sheds coherent vortices that persist downstream and can be sampled by followers with only a small number of probes.

This study evaluates whether sparse downstream probes are sufficient to infer agent attributes and decode simple messages from wakes generated by established source shapes. Computational fluid …

Ensemble Dependence Of Mechanical Relaxation In Molecular Dynamics Simulation, Mason E. Hyde

Open Access Master's Theses

This thesis investigates whether the selection of thermodynamic ensemble introduces quantifiable differences in the stress relaxation modulus G(t), storage modulus G”(w), loss modulus G”(w), and phase angle d(w) computed from equilibrium molecular dynamics simulations of the AAA-1 asphalt model. A 72-molecule, 12-component representation of AAA-1 bitumen was simulated under three ensembles (NPT, NVT, and NVE) at three temperatures (400.15 K, 443.15 K, and 533.15 K) with three independent replications at each condition, yielding 27 total simulations. Stress autocorrelation functions were computed from each production trajectory and Fourier-transformed to obtain frequency-dependent rheological properties.

The computed properties …

Noninvasive Optical Assessment Of Tissue Hemodynamics In Preterm Infants And Mastectomy Skin Flaps, Samaneh Rabienia Haratbar

Theses and Dissertations--Biomedical Engineering

Adequate tissue blood flow and oxygenation are essential for maintaining cellular viability and normal organ function. Disruptions in microvascular perfusion and oxygen delivery contribute to ischemia- and hypoxia-related diseases, including stroke, cancer, retinopathy of prematurity (ROP), and mastectomy skin flap necrosis. Reliable, noninvasive approaches for assessing tissue hemodynamics are therefore critical for improving diagnosis and therapeutic decision-making, particularly in settings where conventional methods are limited. This dissertation investigates the clinical and physiological importance of measuring tissue blood flow and oxygenation across neonatal and surgical applications using both clinical monitoring and advanced optical imaging techniques. In the first study, high-speed pulse …

Evaluating Training Effectiveness And Learning Transfer In The Kentucky Transportation Cabinet Safety Academy, Amanda L. Casolare

Theses and Dissertations--Civil Engineering

Effective evaluation of safety training is crucial to ensure that learning translates into safe work practices, particularly in high-risk public sector environments. The Kentucky Transportation Cabinet (KYTC) is developing a Safety Academy to enhance hazard recognition, risk management, and safety leadership within the organization. However, the Safety Academy has not yet been implemented, and formal evaluation methods for training have not been established. This study aimed to examine evidence-based training evaluation techniques and develop recommendations for evaluating the KYTC Safety Academy prior to program implementation.

This study employed an applied pre-implementation research design grounded in a comprehensive review of safety …

Mental Health And Help-Seeking In Engineering Education: Beliefs, Norms, And Intervention Pathways For Undergraduate Students, Matthew D. Whitwer

Theses and Dissertations--Chemical and Materials Engineering

Engineering education is at a critical juncture where supporting student mental health is essential for fostering persistence, equity, and the development of a resilient and innovative workforce. While engineering students experience high levels of distress and low rates of mental health treatment seeking (known as a mental health treatment gap), there is a gap in knowledge around how this compares to that of students in other fields of study. Further, while efforts have been made to improve the mental health treatment gap in engineering, they are limited by a lack of actionable, theory-based targets. Therefore, this dissertation aims to characterize …

A Specification-Driven Framework For Self-Supervised Learning In Specialized Vision Domains, Mahmut S. Gokmen

Theses and Dissertations--Computer Science

Self-supervised learning (SSL) has emerged as a principled approach to visual representation learning that derives supervisory signal directly from unlabeled data, enabling foundation models to be trained at scale without manual annotation. Deployments in medical imaging and biometric recognition have demonstrated the potential of this paradigm, yet the assumptions that make SSL effective on natural image benchmarks fail systematically in specialized domains. Generic SSL pipelines encode a tacit assumption that the most informative correspondence is spatial proximity within a single acquisition. In specialized domains this assumption breaks at the level of the data-generating process: the signal that carries domain-specific information …

Linking S‑Pillar Empirical Criteria With Boundary And Finite Element Models For Underground Stone Pillar Analysis, Benjamin Diddle

Theses and Dissertations--Mining Engineering

The objective of this thesis is to strengthen the relationship between empirically based stone pillar design methods and two numerical modeling techniques by calibrating boundary element and finite element models to the S‑Pillar empirical criteria and observed pillar behavior in underground stone mines. The first component of the research investigates the displacement‑discontinuity boundary element method implemented in LaModel, quantifying the influence of the lamination thickness and element size on stone pillar safety factor predictions. Results showed that optimal thickness depends on overburden modulus, while larger element sizes introduce significant SF differences from S-Pillar values once the grid size exceeds 5 …

Multiphysics Transport In Porous Thermal Protection Systems: Experimental Characterization Of Gas Permeability And Radiative Properties, Yejajul Hakim

Theses and Dissertations--Mechanical and Aerospace Engineering

Porous thermal protection systems (TPS) used in hypersonic vehicles exhibit coupled gas and radiative transport across multiple regimes and length scales. Accurate performance prediction requires reliable characterization of permeability, slip-flow behavior, and radiative transport properties, particularly for low-permeability and charred materials where existing data are limited. This dissertation presents experimental methods for characterizing multiphysics transport in porous TPS materials. A modular flow system was developed to measure permeability and slip behavior in both virgin and charred materials under relevant environments. A transient pressure decay method enables accurate permeability estimation in low-permeability regimes and provides insight into effective pore structure. Results …

Reciprocity-Based Transfer Function Techniques For Acoustic Source Reconstruction, Spring Isolator Characterization And Structural Damping Assessment, David Pum Thian Lal Paite Neihguk

Theses and Dissertations--Mechanical and Aerospace Engineering

Reciprocity implies that a system responds identically when the source and receiver positions are interchanged. This dissertation applies this principle to address three practical challenges in noise and vibration characterization, where conventional approaches are limited by inaccessible interfaces, constrained excitation conditions, or metrics that do not fully capture vibroacoustic behavior.

The first study develops and validates an inverse method to characterize ducted acoustic sources using acoustic free velocity. Acoustic reciprocity is applied to simplify transfer function measurements. The method is extended to large cross-section ducts, where the source is reconstructed as a collection of point sources along a plane. Validation …