Engineering Commons^™

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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. …

Accelerating Shock-Driven Reactions In Metal Nanocomposites, Siva Kumar Valluri, Edward L. Dreizin, Dana D. Dlott

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Metal powders are sought as energetic additives to conventional explosives. However, due to their sluggish reaction kinetics with external gaseous oxidizers, pure metals are replaced with metallic composites with intimately mixed condensed phase oxidizers prepared by arrested reactive milling (ARM). Such composites can be initiated by non-thermal, mechanical means; through shear mixing of fuel and oxidizer under a shock compressive load. Since the ARM preparatory technique allows for tuning multiple powder attributes such as fuel/oxidizer of interest, their degree of mixing, amount of oxidizer, particle porosity, among others, a parametric study is crucial in identifying suitable traits for fast reactions …

Hyperspectral Imaging For Temperature Measurements Of Hot Spots In Shocked Plastic-Bonded Explosives, Dhanalakshmi Sellan, Siva Kumar Valluri, Dana D. Dlott

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Hot spots are formed when energetic microstructures are shocked, and they play a critical role in shock sensitivity. It is important to know both the time-dependent size and temperature of the hot spots, in order to generate a kinetic model to describe reaction growth in plastic-bonded explosives (PBX). Here we use a recently developed technique where PBX is fabricated in the form of a thin wafer, embedded within a transparent polymer binder, and shocked with a laser-launched flyer plate that produces pressures of about 30 GPa range. In this method, every crystal of the cyclotetramethylene-tetranitramine (HMX)-based PBX can be observed …

Mems 411: Timed Mosquito Egg Container Design Project, Paige Warren, Witt Ciesla, Ethan Sobel

Mechanical Engineering Design Project Class

The goal of this project is to design and construct a device that allows for the controlled study of mosquito egg-laying behavior in response to artificial light and temperature variations. Specifically, the device will limit access to cups of standing water, which serve as egg-laying sites, to preprogrammed times of day over a 7-day period.
The device should ensure the following:

• Control Access: The container should be open and closed at predetermined intervals, allowing mosquitoes to access the cups of standing water only during these times.
• Programmability: It should be easy for a novice to specify the opening and closing …

Mems 411: Group V Ball Bearing Sorter, Matthew Hernandez, Sean Huffert, Ethan Delair

Mechanical Engineering Design Project Class

After a semester of hard work, Team V is proud to unveil its finished prototype for the 2024-2025 ASME Student Design Competition. The theme of this challenge was "Assembly Line Sorting and Packaging." The goal of this challenge was to make a device able to satisfy the criteria of sorting between six different bearings of different sizing and material properties, and meeting spatial and time limitations. This device needed to be fast, accurate, compact, and able to sort in bulk. Team V feels like we have met most of these requirements with our final design prototype. For this project, a …

Mems 411: Hydroponic Gardening System, Tiger Lu, Aj Shanahan, Jaquelin Guzman, Brandon Lacy

Mechanical Engineering Design Project Class

This report summarizes the engineering design process undertaken for the development of a hydroponic gardening system. The project began with selecting a concept, as a team, we decided to focus on designing a system tailored to community gardening needs. The report is organized into five main sections: Problem Understanding, Concept Generation, Concept Selection, Concept Embodiment, and Design Refinement. In the Problem Understanding phase, the team conducted extensive research on patents, codes and standards, user needs, design metrics, and project management. This foundational research was critical to ensure all aspects were considered before beginning the building process. User needs were identified …

Mems 411: Diving Surface Breaker, Chandler Gartner, Freddy Phillips, Maya Sumra, Olivia Slemmer

Mechanical Engineering Design Project Class

We have been recruited by the WashU diving team to design and construct a surface breaker for the Millstone Pool so the divers can have an affordable way to stay safe while practicing dives.

Mems 411: Electrostatic Precipitator Design For Washu Racing Composites Team, Robert J. Wild, Takato Muro, Jackson Ford, David Wiggin

Mechanical Engineering Design Project Class

The objective of this paper is to develop an effective method to remove carbon fiber particulates from the air in the WashU Racing garage using electrostatic precipitation.

Mems 411: Mailbox Assistant, Peter Scholl, Benjamin Cortes, Garbiel Arcas, Colin Zeiss

Mechanical Engineering Design Project Class

Oftentimes elderly people struggle with reaching into their curbside mailbox from their car, especially if the mail is pushed all the way to the back. With the Mailbox Assistant, sore shoulders can be saved through a drawer that slides out from the mailbox. This modification can be made to any mailbox without altering the outside appearance thus keeping it within HOA standards.

Mems 411: Asme Ball Bearing Sorter, Ryan Lively, Joseph Huster, Wil Collins

Mechanical Engineering Design Project Class

The ASME Student Design Competition focused on the design and construction of a ball bearing sorter. This ball bearing sorter must be capable of sorting 2 sizes of ball bearings, being 1/2 inch and 1/4 inch. For each size, there are 3 different bearing materials, brass, steel, and acetal plastic. The device is intended to have the bearings fed into a hopper, and then fully autonomously sort the bearings. The autonomous sorting was to transport the various bearings into 6 different packing stations, one for each size and material bearing. These packing stations must be easily removable. This design project …

Mems 411: Adjustable Desk, Catryn Cattoor, Natalia Pilpil, Jamie Burgasser, Adam Wong

Mechanical Engineering Design Project Class

Design and create a desk for a special education classroom of kindergarteners to third graders. The desk needs slanting capabilities, wheel chair accessibility, raising/lower capabilities, distraction prevention capabilities, and light board capabilities. These capabilities need to be configurable for students with different needs. This desk also needs to be very durable, safe, and mobile. The main motivation for this project is the desire to provide the teacher and her students with a single, cost-effective product that is safe, easy to use, and meets their desired needs.

Mems 411: Ball Bearing Sorter, Abdissa Effa, Juliet Whitehead, Ayub Shifa

Mechanical Engineering Design Project Class

The challenge is to design and fabricate a compact device capable of autonomously sorting and transporting ball bearings of varying materials (chrome steel, brass, nylon) and sizes (¼” and ½”) into designated packaging stations. The device must operate efficiently, accurately, and within the constraints of a 20x20x20-inch enclosure, meeting industrial assembly line standards of speed and precision while minimizing human intervention. It aims to address the need for high-rate sorting systems in manufacturing environments, ensuring accurate material identification and classification for streamlined operations.

Mems 411: Talking Goniometer, Jeffrey Reinhold, Matthew Ren, Corin Riahi, Moises Rodriguez

Mechanical Engineering Design Project Class

Our project is about designing a goniometer that will aid Rachel Apter, an occupational therapy graduate student, more easily determine the angles created by limbs bending about a joint. A goniometer is essentially a protractor designed to affix its base arm to a stationary limb and it’s rotating arm to a moving limb. The moving arm follows the moving limb, measuring the coupled limb’s range of motion. The main complaint centering around goniometers is that they are hard to read due to the small tick marks that indicate the angle. To fix this problem, the goniometer will be edited to …

Mems 411: Automated Assistive Toilet, Alex Scaff, Kenna Mcgahren, Daniel Sibley

Mechanical Engineering Design Project Class

How do we make toilets more accessible for all people - regardless of physical, mental, emotional impediments - while also ensuring simplicity and cost-effectiveness? Utilizing sensors, our toilet device is designed to automatically open and close the toilet lid upon approach, increasing ease of use and general hygiene of the user while being friendly to those who struggle with certain disabilities or impairments.

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 …

12.09.2024 Orsp Connect, Liz Williamson

ORED Newsletter

Employee Profiles

In Person Account Reconciliation and Tableau Training

NSF Proposals with Consultant or Professional Services