Engineering Commons^™

Performance Evaluation Of Routing Protocols And Ml-Based Enhancements For Uav-Assisted Post-Disaster Communication Networks, Prachi Choudhary

Doctoral Dissertations and Master's Theses

During natural disasters, the existing communication systems collapse, and the disaster-affected areas become disconnected without any means of exchanging information. The collapse of existing communication networks poses challenges for First-Responders (FRs) in locating survivors during Search and Rescue (SAR) operations and for survivors to communicate for emergency aid. To alleviate post-disaster consequences and save lives, Uncrewed Air Vehicles (UAVs), commonly known as drones, can be employed to establish adaptable and reliable emergency communication networks. UAVs offer portability and rapid deployment, making them effective in crises. This thesis presents two main contributions: 1) Evaluation and Comparison of Routing Protocol Performance: The …

12.02.2024 Orsp Connect, Liz Williamson

ORED Newsletter

Email Address Matters

All of Us Researcher Symposium

Welcome Anya Goldman

Optimized Fabrication Of Dendritic Mesoporous Silica Nanoparticles As Efficient Delivery System For Cancer Immunotherapy, Varsha Godakhindi, Mostafa Yazdimamaghani, Sudip Kumar Dam, Farzana Ferdous, Andrew Z. Wang, Mubin Tarannum, Jonathan Serody, Juan L. Vivero-Escoto

Chemical and Biochemical Engineering Faculty Research & Creative Works

In the past decade, cancer immunotherapy has revolutionized the field of oncology. Major immunotherapy approaches such as immune checkpoint inhibitors, cancer vaccines, adoptive cell therapy, cytokines, and immunomodulators have shown great promise in preclinical and clinical settings. Among them, immunomodulatory agents including cancer vaccines are particularly appealing; however, they face limitations, notably the absence of efficient and precise targeted delivery of immune-modulatory agents to specific immune cells and the potential for off-target toxicity. Nanomaterials can play a pivotal role in addressing targeting and other challenges in cancer immunotherapy. Dendritic mesoporous silica nanoparticles (DMSNs) can enhance the efficacy of cancer vaccines …

Leveraging Machine Learning For Defect Detection In Irrigation Concrete Canal Lining In Egypt: Advancing Construction Quality And Efficiency, Mohamed Nabawy

Civil Engineering

Abstract:

Defects during the construction phase of projects pose significant challenges, particularly in terms of

safety, cost overruns, delays, and labor inefficiencies. In irrigation concrete canal lining construction

with mega investments, early detection of defects is critical to ensuring quality and project success.

This study explores the application of machine learning (ML) for onsite defect detection, focusing

on the development and deployment of an object detection mobile application specifically tailored

for identifying visible defects in concrete canal lining construction. Leveraging the machine learning

capabilities of Microsoft Azure, a custom object detection model was trained and validated to

recognize defects such …

Direct Methanol Fuel Cells Using Pure Methanol, Ryan Spragg

McKelvey School of Engineering Graduate Student Theses & Dissertations

Fuel cell technology has attained significant appeal as a form of renewable energy in recent years due to its diverse applications, various fuel types, and lower greenhouse gas emissions. Of the various fuel cell types, direct methanol fuel cells (DMFCs) hold a set of distinct advantages for stationary and small portable applications. These advantages include faster refueling compared to battery charging, high gravimetric energy density, and ease of production and use compared to hydrogen. However, the DMFC has numerous technical hurdles that prevent its widespread adoption into the commercial market. Namely, the slow reaction kinetics in the anode and the …

Custom Cathode Optimization For Electropolishing Additively Manufactured 316l Stainless Steel, Kasandra Escarcega Herrera

Mechanical Engineering ETDs

Laser powder bed fusion (LPBF) has become increasingly popular for its ability to rapidly manufacture complex metallic parts. However, the surface properties of as-built LPBF parts may degrade overall performance due to tortuous surface features. Consequently, post-processing like electropolishing (EP) to reduce the surface asperities is often needed for LPBF parts to perform as expected. Utilizing experimental and computational approaches, this project aims to more uniformly EP complex shaped parts made from LPBF 316L. For the experimental approach, parts with a three-dimensional T-shape were printed out of 316L stainless steel and EP using an acidic-based and a polyethylene glycol/NaCl-based electrolyte. …

Ge/Sige Quantum Wells: Material For The Post-Moore Era, Troy Alexander Hutchins-Delgado

Optical Science and Engineering ETDs

This dissertation demonstrates high-quality germanium quantum wells on a 200 mm silicon wafer platform, enabling novel device possibilities. Partnering with a commercial silicon-germanium epitaxy supplier, we obtained shallow, undoped germanium quantum wells with high-crystalline quality, confirmed through x-ray diffraction, secondary ion mass spectroscopy, high-resolution scanning transmission electron microscopy, and energy dispersive x-ray spectroscopy. Hall bar devices fabricated on single quantum wells revealed that surface preparation can tune transport properties while maintaining peak mobilities around 10⁵ cm²V⁻¹s⁻¹. Manganese-germanide spintronic contacts were integrated via solid-state reaction, with contact quality assessed through Schottky diodes, transfer length …

Data Intensive Method For Processing Defect Detection And Mitigation For Composites, Deepak Kumar

Doctoral Dissertations and Master's Theses

Composite manufacturing without processing defects is a crucial step in satisfying the production, performance, and quality requirements of composite materials in various industries. Autoclave processing enables manufacturing of high-quality composite parts with excellent mechanical properties, whereas additive manufacturing (AM) offers adaptability to complex designs and streamlined processes. However, each method presents unique challenges; despite the benefits, autoclave processes can still result in processing defects, and AM is particularly susceptible to processing anomalies owing to the novelty of the process. Ensuring the quality and reliability of composite manufacturing is essential to fully capitalize on the advantages offered by both techniques. Artificial …

Highly Porous Nanocarriers For Osmolyte Delivery And Drought Mitigation In Wheat And Ryegrass, David Britt

Funded Research Records

No abstract provided.

Drainage Area Limitations Of Single Watershed, Peak Flow Estimates From Nrcs Methods, Timothy Alexander Maughan

Theses and Dissertations

Most roadway design sections of state Departments of Transportation predict peak flow for culvert design using Natural Resources Conservation Service (NRCS) TR-20 methodology. Even though the approach is more than 50 years old, there is no clear guideline for how large a single watershed drainage area may be while remaining appropriate for predicting peak discharge with this method. Our objective is to identify the drainage area where TR-20 peak flow predictions significantly deviate from flow frequency predictions. We aim to recommend to the Nebraska Department of Transportation (NDOT) a range of basin drainage areas appropriate for predicting peak flow using …

Traveling-Wave Vibration Control And Comparison Of Individuals With Insomnia And Good Sleepers Using Eeg Spectral Power And Sample Entropy, Joseph T. Lecheminant

Theses and Dissertations

This thesis explores the intersection of whole-body vibration (WBV) and neurophysiological analysis to improve sleep quality and understanding of insomnia. The work is divided into two primary areas: the development of a novel traveling-wave vibration system for sleep enhancement and the analysis of electroencephalography (EEG) metrics in individuals with insomnia versus good sleepers. A vibrating sleep system capable of generating programmable traveling-wave patterns is designed and prototyped. Through iterative development and user trials, the system enables highly controlled mechanical stimulation in the form of traveling-wave vibration. Key advancements include independent amplitude and speed modulation and customizable wave patterns. Simple wave …

An Experimental Investigation Of Signal Processing Techniques For Vibration-Based Structural Health Monitoring In Residential Buildings Subjected To Base Excitation, Fedaa Ali

Electrical Engineering Theses

Coastal regions, particularly in the southeastern United States, are consistently confronted with the ongoing threat of hurricane-induced damage to their buildings. Consequently, there is a pressing need to concentrate efforts on the evaluation and prediction of structural integrity and reliability in such environments. This is paramount for minimizing losses and enhancing public safety in the face of these challenging climatic conditions. Current structural health monitoring systems are typically customized for specific buildings, rendering them excessively expensive and impractical for residential structures. This research presents a comprehensive study of signal processing techniques and damage detection for an economical yet efficient structural …

Etherealbreathing: A Holographic Biofeedback Game To Support Relaxation In Autistic Children, Arturo Morales Téllez, Isabel López Hurtado, Franceli L. Cibrian, Monica Tentori

Engineering Faculty Articles and Research

Biofeedback training for box breathing is becoming increasingly accessible due to advancements in consumer-grade breathing sensors. However, there is limited research on their design and applications for specialized populations. This study evaluates a novel biofeedback holographic game, EtherealBreathing, designed to support autistic children. In EtherealBreathing, children practice box breathing to collect virtual elements to maintain the Earth's balance, using a wearable sensor to measure chest expansion for breath detection. A deployment study with 20 autistic children revealed that EtherealBreathing effectively promotes box breathing, leading to better health-related outcomes, such as lowering participants’ heart and respiratory rates than traditional practices. Biofeedback …

Cellular Air Quality Sensors With Lora Backchannel A Robust Sensor Suited For Remote Deployment In Harsh Environments, Joseph R. Miera

Theses and Dissertations

Air quality significantly impacts health and overall quality of life, making its measurement essential. However, most affordable air quality devices are designed only for use within WiFi range and cannot handle extreme temperatures, limiting their usefulness for people in remote or extreme environments, such as regions with harsh winter climates. This limitation is concerning, as winter often brings worse air quality due to temperature inversions that trap pollutants and increase fuel burning for heating. Inversion is a problem as close to home as Utah Valley, and as far away as Ulaanbaatar, Mongolia. Most low-cost air quality sensors are not built …

Yield Comparison Of Three Melon (Cucumis Melo L.) Varieties Cultivated With Dutch Bucket And Drip Irrigation Systems, Widiya Puji Kumalasari, Suwarto, Etik Wukir Tini, Endang Warih Minarni

Jurnal Kultivasi

Melon is one of the horticultural commodities with considerable economic potential. Cultivation through hydroponic systems can provide efficiency and increase production if complemented by superior varieties. This study aims to identify the best hydroponic system and melon variety combination with the highest yield. The research was conducted from November 2023 to April 2024 at the screen house in Pasir Kulon Village, Karanglewas District, Banyumas Regency, at 110 m above sea level. The study used a split-plot factorial design with a basic design of a Completely Randomized Block Design. The first factor was the hydroponic system, consisting of S1 = Dutch …

A Novel, Direct Matrix Solver For Supersonic Boundary Element Method Systems, Cory D. Goates, Doug Hunsaker

Mechanical and Aerospace Engineering Faculty Publications

For problems with very fine surface meshes, typically the most time-consuming step of a boundary element method (BEM, also called a panel method) is solving the final linear system of equations. Many have already studied how to efficiently solve the dense, asymmetric systems which arise in elliptic BEMs. However, this has not been studied for a supersonic aerodynamic BEM, for which the governing PDE is hyperbolic. Due to this hyperbolic character, the matrix equation which arises from a supersonic BEM has a large number of identically zero elements. But the resulting linear system of equations is also not sparse in …

The Role Of Customers In Strategic Information Technology (It) Initiatives, Siddharth Aggarwal

Doctoral Dissertations and Projects

This study focused on a small organization in the United States of America. The organization has IT departments that cater to the IT needs of its internal and external customers through IT products and services. Such organizations run full life cycles of product management and product development and often face off with situations to prioritize the use of their limited resources. Ideally, organizations focus on strategic IT initiatives that might be in the company's and its customers' best interest. However, instances occur when IT-driven initiatives lose that focus and might end up diverting resources toward the latest shiny technology and …

Bilayer Asymmetric-Based Metal-Organic Frameworks Membrane For Blue Energy Conversion, Rockson Kwesi Tonnah, Milton Chai, Mohammad Khedri, Milad Razbin, Reza Maleki, Amir Razmjou, Mohsen Asadnia

Research outputs 2022 to 2026

The conversion of Gibbs free energy at the interface of solutions with salinity gradients into electrical energy is essentially a means of mitigating environmental pollution and bolstering the availability of new energy sources to enhance the renewable energy portfolio. However, a three-dimensional (3D) sub-nanofluidic membrane with high ion conductivity and selectivity for a reverse electrodialysis (RED) based osmotic energy conversion in both aqueous and organic solutions remains largely unexplored. Herein, we engineered a bilayer metal organic frameworks (MOFs) membrane with polystyrene sulfonated angstrom-size channels in UiO-66-NH2 base layer and isoreticular MIL-88B membrane as the top layer to enhance permselectivity and …

An Evaluation Of Features Extracted From Facial Images In The Context Of Accurate Age Estimation⋆, Malik Awais Khan, Aurelia Power, Peter Corcoran, Christina Thorpe

Conference papers

Age estimation by face image recognition can be used in numerous ways with regression models to manage access control, improve security, and guarantee the protection of children online. The approaches used for predicting age—including data selection, cleaning techniques, feature extraction, algorithm choice, and hyperparameter tuning—often struggles with generalization. Furthermore, a lot of methods neglect to specifically address how extracted face features might be used for prediction. To address the lack of racial diversity we acquired a dataset consisting of different races from literature. We also examined the ability of local, global and hybrid facial features to predict ages. Two variants …

Physics-Informed Transfer Learning For Process Control, Samuel Arce Munoz

Theses and Dissertations

In the realm of process control, managing complex systems with limited prior knowledge presents significant challenges, particularly in environments where traditional mechanistic models are either unavailable or computationally prohibitive. This work explores the integration of deep transfer learning with system identification and Model Predictive Control (MPC) to develop control strategies that are both data-efficient and computationally streamlined. Initially, Long Short-Term Memory (LSTM) networks are employed to create approximate MPC controllers by leveraging transfer learning from a source system to a target system, demonstrating that transfer learning can achieve comparable performance to traditional MPC methods with reduced training data. Building upon …

Securing Legacy Multivalue Pick Systems Modernized By Restful Web Service Apis, Jacob S. Lee

Theses and Dissertations

With more applications accessible on the Web, organizations with mission-critical legacy systems have had to find a way to stay relevant and competitive by modernizing with RESTful APIs. REST architecture, serving as a guideline rather than a strict protocol, offers significant advantages in terms of scalability, flexibility, and independence; however, its widespread adoption has also led to notable security vulnerabilities and weaknesses. Additionally, there is not one all-encompassing security testing methodology to follow when testing RESTful APIs. For this reason, a new security testing methodology was developed for legacy MultiValue Pick systems that implement the REST API component, MVConnect. The …

Enhanced Wind Velocity Imputation Near Building Structures Using Advanced Machine Learning Techniques, Istiak Ahammed, Sujeen Song, Gang Hu, Jinwoo An, Bubryur Kim

Civil Engineering Faculty Publications

The evaluation of instantaneous wind flow patterns nearest to building architecture is crucial to ensuring structural stability, architectural integrity, and pedestrian safety. Particle image velocimetry (PIV), a technique for studying fluid flow by tracing particles, provides accurate predictions of instantaneous wind velocities (IWV). However, PIV encounters challenges in specific regions due to laser light-based experimentation, leading to missing data. Consequently, investigating the wind circulation pattern around buildings becomes more challenging. Numerous ML techniques have been employed to impute missing wind velocities at random building locations with minimal structural impact. This paper focuses on addressing this concern by utilizing a machine …

The Assessment Of Liquefaction Surface Ejecta Predictions On A New Large Dataset From The 2012 Emilia Romagna, Italy Earthquakes, Holten T. Flinders

Theses and Dissertations

The presence of a non-liquefied crust overlying a liquefied layer has been found to have a significant effect on sand ejecta and surficial liquefaction damage, as observed by Ishihara (1985). Following the 2010-2011 Canterbury seismic sequence in New Zealand, almost no foundation deformation occurred in areas with liquefaction susceptible soils overlain by at least a 3 m-thick crust [3]. In contrast, the 2012 Emilia-Romagna earthquake in Italy provided surface evidence of liquefaction despite 6- to 10 m-thick crusts. Several researchers have proposed liquefaction prediction models [e.g. LPI [6], Ishihara Curves [8], LSN [9], LPIISH [10] and the methods proposed by …

Identifying Subject Bias In Wifi-Based Human Activity Recognition Evaluation Methods, Amany Elkelany, Robert J. Ross, Susan Mckeever

Conference papers

WiFi-based Human Activity Recognition (HAR) has emerged as a promising approach for monitoring and analysing human activities in a non-intrusive manner, leveraging WiFi signals for activity classification. Despite advancements, existing WiFi-based HAR research lacks consideration of subject (human) bias. This results in learning models performing well on individuals used in the training samples but failing to generalise to new/unseen subjects, in contrast to known good practices in machine learning. In this paper, we address this oversight directly by systematically examining the evaluation methodology for the WiFi-based HAR context. Specifically, we investigate the impact of Leave-One-Subject-Out Cross-Validation (LOSOCV) in a hybrid …

Towards Rare Event And Anomaly Prediction In Manufacturing: Bridging Methodological Gaps In Industrial Applications, Chathurangi Shyalika, Renjith Prasad, Ruwan Wickramarachchi, Amit Sheth

Publications

Rare event prediction is critical in industrial applications, including real-world Industry 4.0 applications. These events, defined by their low occurrence frequency, are often difficult to predict due to the skewed data distribution, which complicates modeling and evaluation. In our research, we provide a comprehensive review of current approaches to rare event prediction across four key dimensions: rare event data, data processing techniques, algorithmic approaches, and evaluation methodologies [1]. By analyzing diverse datasets with multiple modalities, including numerical, image, text, and audio, we categorize the primary challenges and present the gaps in current research. Specifically, we present three novel research contributions …

Predicting Chaotic Systems With Quantum Echo-State Networks, Erik Connerty, Ethan N. Evans, Gerasimos Angelatos, Vignesh Narayanan

Publications

Recent advancements in artificial neural networks have enabled impressive tasks on classical computers, but they demand significant computational resources. While quantum computing offers potential beyond classical systems, the advantages of quantum neural networks (QNNs) remain largely unexplored. In this work, we present and examine a quantum circuit (QC) that implements and aims to improve upon the classical echo-state network (ESN), a type of reservoir-based recurrent neural networks (RNNs), using quantum computers. Typically, ESNs consist of an extremely large reservoir that learns high-dimensional embeddings, enabling prediction of complex system trajectories. Quantum echo-state networks (QESNs) aim to reduce this need for prohibitively …

Investigating The Effect Of Active Living Wall On Indoor Air Quality And Energy Consumption: Case Study In Uaeu Closed Offices, Atina Ghunaim

Thesis/ Dissertation Defenses

Extreme hot climates can significantly affect indoor air quality (IAQ) and ventilation, resulting in higher energy demands. Numerous studies have demonstrated that outdoor greening, such as trees and landscaped areas, can reduce a building’s energy consumption. However, less research has been conducted on the impact of indoor vegetation on energy use and air quality. Indoor vegetation decreases carbon dioxide (CO₂) concentration by absorbing and releasing oxygen (O₂), while the evapotranspiration process further enhances (IAQ) and reduces energy expenditure. The United Arab Emirates has dry arid climate and summers with high humidity levels, causing individuals to stay longer indoors, which is …

Understanding Confusion: A Case Study Of Training A Machine Model To Predict And Interpret Consensus From Volunteer Labels, Ramanakumar Sankar, Kameswara Mantha, Cooper Nesmith, Lucy Fortson, Shawn R. Brueshaber, Candice Hansen-Koharcheck, Glenn Orton

Michigan Tech Publications

Citizen science has become a valuable and reliable method for interpreting and processing big datasets, and is vital in the era of ever-growing data volumes. However, there are inherent difficulties in the generating labels from citizen scientists, due to the inherent variability between the members of the crowd, leading to variability in the results. Sometimes, this is useful — such as with serendipitous discoveries, which corresponds to rare/unknown classes in the data — but it might also be due to ambiguity between classes. The primary issue is then to distinguish between the intrinsic variability in the dataset and the uncertainty …

Enhancement Of Ambient Air Quality Index Forecasting Using Optimized Ensemble Model, Vanitha M

Theses and Dissertations

Forecasting ambient air quality is essential for environmental sustainability and public health, especially in heavily populated regions such as China, India, and the United States where air pollution remains a serious concern. Traditional forecasting models often struggle to accurately represent air quality data because of its complex patterns and nonlinear interactions. To address these challenges and improve forecast performance, this research proposes a comprehensive strategy that integrates parallel heterogeneous ensemble modeling with Bayesian optimization.

The study begins with a seasonal machine learning–based imputation technique (SeasonalMLImpute) designed to handle missing data in meteorological and air quality parameters. This method is evaluated …

Microstructured Microstructure: Effects Of Concentration Variations On Shock Initiation Of Hmx-Based Plastic Explosives, Dana D. Dlott, Lawrence Salvati, Siva Kumar Valluri

Mechanical and Aerospace Engineering Faculty Research & Creative Works

We studied shock-compressed plastic-bonded explosives (PBX) consisting of HMX (cyclotetramethylene-tetranitramine) with PDMS (poly-dimethylsiloxane) binder, where we varied the HMX weight percent (wt%) up to a maximum of 60 wt%. In this lower-concentration regime, HMX particle clustering causes the PBX structure to consist of HMX clusters and PDMS islands. Structural analysis by optical microscopy allowed us to compute a radial correlation function that gives the mean distance from an average HMX particle to the nearest polymer island. Short-duration 20 GPa shocks (4 ns) created hot spots, and time-resolved thermal emission was used to obtain the growth rate of the subsequent deflagration. …