Engineering Commons^™

A Framework-Based Cross-Institutional Cpd For Academic Staff In Gen-Ai Literacy, Critical Inquiry And Authentic Assessment, Roisin Donnelly, Ita Kennelly

Books/Book Chapters

Generative-Artificial Intelligence (Gen-AI) has emerged as a transformative force profoundly influencing, if not revolutionizing the way we now teach and how students learn in higher education (HE). Despite the initial flurry of early research studies following the raising of public awareness of Gen-AI (and in particular ChatGPT), enduring pragmatic questions remain for academic staff on how best to protect and promote student learning, how to meaningfully support assessment integrity from a curriculum perspective, and additionally how to effectively use Gen-AI technologies to aid learning and foster deeper critical thinking.

Optimizing Energy-Efficient Grid Performance: Integrating Electric Vehicles, Dstatcom, And Renewable Sources Using The Hippopotamus Optimization Algorithm, Mohamed Abdelaziz, A.A. Ali, R.A. Swief, Rasha Elazab

Renewable Electrical Energy Engineering

The rapid increase in renewable energy integration and electric vehicle (EV) adoption creates significant challenges for the stability and efficiency of power distribution networks. This study addresses the need for optimized placement and sizing of Electric Vehicle Charging Stations (EVCSs), photovoltaic (PV) systems, and Distribution Static Compensators (DSTATCOMs) to enhance grid performance. The motivation for this work arises from the fluctuating nature of renewable energy generation and the unpredictable demands of EV charging, which strain existing infrastructure. To address these challenges, we propose a novel optimization framework that introduces the Renewable Distributed Generation Hosting Factor (RDG-HF) and Electric Vehicle Hosting …

Effects Of Psycho-Attitudinal Characteristics On Drivers’ Behavior: A Driving Simulator Study, Francesco Galante, Filomena Mauriello, Simone Fucito, Mariano Pernetti, Alfonso Montella

Kentucky Transportation Center Presentations

Human factors are crucial in causing traffic crashes and researchers try to identify and understand these factors to explore patterns of risky driving behavior and its consequences. It is clear that human factors play a crucial role in the causation of traffic accidents, and researchers are trying to identify and understand these factors. That is why it is important to explore the patterns that identify drivers prone to risky driving behavior and the possible negative consequences of that behavior At this aim, an experiment was conducted using the VERA dynamic driving simulator at the Road Safety Laboratory of the University …

Hempcrete Curtain Walls, Anh Bui

2024 Awards for Excellence in Student Research and Creative Activity - Documents

This research aims to scrutinize the performance, durability, and viability of hempcrete in curtain wall applications—an exploration critical to advancing sustainable construction practices. Comprising hemp hurds and lime binders, hempcrete stands as an emerging sustainable building material with promising ecological benefits. Despite its potential, there exists a notable research gap concerning its application in curtain walls, which demand rigorous structural and weatherproofing standards. The primary objective is to subject full-scale hempcrete curtain wall assemblies to ASTM standard test methods, comparing their performance with conventional materials like stone and glass. The research hypothesis posits that hempcrete will exhibit satisfactory strength, fire …

Adaptively Managing Lake Powell Releases To Respond To Reservoir Inflow And Evaporation, Motasem Abualqumboz, Braden Chamberlain, David Rosenberg

Civil and Environmental Engineering Student Research

Across the Western U.S., reservoir levels are declining towards protection elevations because of aridity amplified by long-standing operations that release more water than inflow. This paper has the purpose to sketch the effects of reservoir operations that release less water than inflow and evaporation. We use the case of Glen Canyon Dam/Lake Powell on the Colorado River, U.S.A. We programed a new rule in the trusted basin simulation model maintained by the U.S. Bureau of Reclamation. The rule releases 95% of inflow in each time step. The 5% reduction is typically greater than reservoir evaporation. Lake Powell levels stabilize and …

Dice Are Blessed Or Cursed, Warren Campbell, Cameron Miller

SEAS Faculty Publications

Dice are cursed or blessed; that is, they roll low or high, but they are never fair. They cannot be manufactured with uniform density and geometric precision. This is particularly true of 20-sided dice or D20s. Faces are smaller than 6-sided dice, and manufacturing tolerances are similar. However, some dice are fairer than others. In our studies of plastic-mold dice about 1 in 4 test fair in 3000 rolls. We have used different statistical tests, including chi-square, modified Kolmogorov Smirnov, and double binomial tests. Of these, the method that consistently performed better is the chi-square goodness of fit test. The …

Electrochromic Polymers: From Electrodeposition To Hybrid Solid Devices, Haradou Sare, Dongmei Dong

College of Science & Mathematics Departmental Research

This paper reports on the linear colorimetric and electrochromic (EC) characteristics of electrodeposited polyaniline (PANI) films. This paper also investigates the infrared EC properties of acid-doped PANI films. The electrochemical polymerization method was employed to create a porous and thin PANI film layer onto PET-ITO substrates. This layer was capped with WO3 film to create a gel electrolyte sandwich structure that demonstrates the compatibility of PANI films with cathodic WO3 films in full devices. The electrodeposition of the film was fabricated by applying different voltages and time, with the optimal film quality achieved with the 1.7 V voltage and a …

Investigating The Role Of Anesthesia In Radiation Therapy, William Walter Daley

ENGS 88 Honors Thesis (AB Students)

Purpose:

Cancer claims 7.6 million lives worldwide annually, affecting millions more. Conventional (CONV) radiation therapy (RT) is a key weapon in the oncological arsenal. A novel mode of radiation delivery, utilizing ultra-high dose rates (UHDR), is associated with enhancing the RT therapeutic ratio by selectively sparing normal tissue without sparing tumor tissue. However, there are many roadblocks to the clinical implementation of UHDR RT —namely the lack of standardization of experimental conditions and the inconsistency of published and unpublished results. This thesis investigates variables that affect preclinical biological outcomes to radiation.

Materials/Methods:

Eight groups of 10 C57BL/6 mice were stratified …

Hydrogen Production From Microbial Electrolysis Cells Powered With Microbial Fuel Cells, Dina Aboelela

Biochemical Engineering

No abstract provided.

Evaluating Medium Decision Tree Model, Support Vector Machine Rational Quadratic Gaussian Process Regression To Estimate The Total Organic Carbon Of Shale Gas Reservoirs, Attia Attia, Sayed Gomaa, Mohamed Mongy Eng., Ramadan Emara Prof., Ashraf Fahmy Prof.

Petroleum Engineering and Gas

As a result of an energy crisis due to the Russian-Ukrainian war, the eyes of great countries such as America and others began to turn strongly towards exploiting unconventional resources to increase the oil and gas production. The first step in exploiting unconventional sources is to estimate the Total Organic Carbon (TOC). TOC measurements are expensive as well as time consuming, as samples of cuttings or core samples must be present to do the required lab tests. This issue encouraged the researchers to develop mathematical correlation to estimate the TOC. The paper aims at evaluating three of machine learning models …

Studying Contribution Of Associated Stakeholders In Risk Control Of Modularized Construction Under Different Project Delivery Methods: A Graph-Restricted Cooperative Games Approach, Mohamad Abdul Nabi, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Modularization is associated with various project benefits including cost savings, schedule reduction, improved quality, among others. However, successful implementation of modular projects requires early collaboration and proactive management of various associated risks. Both project communication structures and early engagement of all project stakeholders have a great impact on risk mitigation efficiency in modular construction. The goal of this paper is to study the stakeholders' contribution in risk control of modular construction projects under different delivery methods. To this end, the authors followed a multistep methodology including (1) literature analysis to assign 17 modular risks among the various project stakeholders; (2) …

The Trouble With Technology, John O'Connor

Conference Papers

In contemporary education, technology is either hailed as the panacea for affordable mass education or dreaded as a threat to our humanity. At the European Culture and Technology Laboratory, technology is understood in the context of the Ancient Greek origin of the word: technē—meaning a system or a method of making or doing, an art or a craft; a technique or a practice, even a way of thinking. The tools humans use are not merely a means of intervention in our environment but also a way of becoming human and thus, technology has a fundamental impact on our identity and …

Freyr⁺: Harvesting Idle Resources In Serverless Computing Via Deep Reinforcement Learning, Hanfei Yu, Hao Wang, Jian Li, Xu Yuan, Seung Jong Park

Computer Science Faculty Research & Creative Works

Serverless computing has revolutionized online service development and deployment with ease-to-use operations, auto-scaling, fine-grained resource allocation, and pay-as-you-go pricing. However, a gap remains in configuring serverless functions - the actual resource consumption may vary due to function types, dependencies, and input data sizes, thus mismatching the static resource configuration by users. Dynamic resource consumption against static configuration may lead to either poor function execution performance or low utilization. This paper proposes Freyr+, a novel resource manager (RM) that dynamically harvests idle resources from over-provisioned functions to accelerate under-provisioned functions for serverless platforms. Freyr+ monitors each function's resource utilization in real-time …

Share: A Framework For Secondary Qualitative Data Analysis, Shawn Jordan, Holly Matusovich, Jennifer Case, Lisa Benson, David Delaine, Rachel Kajfez, Susan Lord, Marie Paretti, Edward Young, Yevgeniya V. Zastavker

School of Engineering: Faculty Scholarship

Although secondary analysis of qualitative data is not a new research approach, it is not yet commonly used in engineering education research. Heaton (2008, p. 34) describes secondary qualitative data analysis (SDA) as involving “the re-use of pre-existing qualitative data derived from previous research studies.” Within this broad definition, one form of SDA that is especially uncommon in engineering education research (EER) is the practice in which researchers who were not part of the original project team work with qualitative data they did not help collect and potentially even apply theories and analytic lenses that were not part …

A Recruited Participant Study Of Pedestrian Infrastructure, Amy Wyman, Hisham Jashami, David S. Hurwitz

Kentucky Transportation Center Presentations

No abstract provided.

Spatio-Temporal Analysis Of Pedestrian-Vehicle Conflicts In Urban Intersections Based On Trajectory Data, Qinyi Hu, Jaeyoung Jay Lee

Kentucky Transportation Center Presentations

No abstract provided.

Synthesis Of Gold Nanoparticle-Coated Graphite Electrodes For The Improved Detection Of Arsenic In Water Samples, Erika Hagen, Thom Spence Phd

[Archive] Belmont University Research Symposium (BURS)

Drinking water, especially tap, is often contaminated with some concentration of heavy metal ions, with two important ones being lead and arsenic. These ions often find their way into the water through household plumbing and service lines, municipal waste disposal, or natural mineral deposits. This is becoming a major concern for public health care professionals as consuming high levels of heavy metals can be detrimental to health. The acceptable limit of lead in drinking water is 15 parts per billion (ppb), however, many devices for analyzing samples are not able to reliably detect heavy metals at that level, at least …

Bert-Based Detection Of Ai-Generated Text For Content Verification, Soham Biren Katlariwala

2024 REYES Proceedings

With advancements in AI-driven natural language generation, distinguishing between AI-generated and human-written text has become imperative for ensuring content authenticity across industries. This study explores the effectiveness of Bidirectional Encoder Representations from Transformers (BERT) in addressing this classification challenge. Utilizing a diverse dataset and robust preprocessing techniques, BERT achieved a peak F1-score of 0.94364, outperforming traditional models such as Logistic Regression and Support Vector Machines. The results underscore the potential of transformer-based models in addressing real-world con- tent verification problems. Future enhancements include fine-tuning and expanding datasets for greater generalizability.

Predicting Compressive Strength Of Concrete Incorporating Fly Ash, Blast Furnace Slag, And Superplasticizer Using Machine Learning Techniques, Muhammad Faisal Yaqub

2024 REYES Proceedings

Concrete is the second most essential element in the construction industry, and its strength requirements vary based on the specific conditions of each project. However, determining the compressive strength of concrete involves laboratory tests, which wastes a lot of time and money. Researchers have developed machine learning models that predict the compressive strength of cement-based concrete having various mixes. In this research, the compressive strength of concrete incorporating fly ash, blast furnace slag, and superplasticizer is predicted using different machine learning models, namely, Linear Regression, Random Forest Regression, Decision Tree Regression, Extreme Gradient Boosting, Light Gradient Boosting, AdaBoost, and CatBoost …

Exploring Clustering Patterns In Msmes And Large Enterprises In Maharashtra: Analyzing Industrial Dynamics Using Cluster Coefficient And Other Economic Indicators, Priyanshu Bist

2024 REYES Proceedings

The paper discusses an attempt to explore and assess the economic clustering in Maharashtra by focusing on the MSMEs (Micro, Small and Medium Enterprises) and large enterprises in six major districts, namely Konkan, Nashik, Pune, Aurangabad, Amravati, and Nagpur. Cluster coefficients, total number of workers, and other economic indicators of units were considered to understand how industries are spread and perform regionally. Our research was a combination of exploratory and descriptive research, ensuring the data to be garnered had already been collected from the reports and records of the governments concerned and of industries. This entails that we have a …

Evaluating Fourth-Grader’S Perception Of Engineering Through A Community-Engaged Project (Evaluation), Olivia Ryan, Maija A. Benitz

Engineering, Computing & Construction Management Faculty Publications

To meet the complex challenges of the future, there needs to be an increase in the number of students pursuing , STEM and engineering. To grow those numbers, students must have an understanding and interest in engineering in order to pursue it as a career option. However, literature has shown that children hold misconceptions about the engineering profession, which can deter potential future engineers from the field. This underscores the importance of introducing engineering concepts at a young age. Over the past ten years, the Next Generation Science Standards (NGSS) have been integrated into state school curricula, increasing the emphasis …

Addressing Microplastic Environmental Data Gaps Through Undergraduate Research, Michelle Kryl, Ashlee Lewandoski, Grace Diblasio, Ethan Howard, Lillian C. Jeznach

Engineering, Computing & Construction Management Faculty Publications

Plastic pollution from freshwater and atmospheric sources into coastal and marine environments is complex and the extent is largely unquantified. Such a gap in knowledge of marine microplastic sources, fate, and transport requires a spectrum of engineers and scientists, so that technical, social, and policy solutions can be developed. Citizen scientists are low cost and can collect an abundance of field data. Experienced scientists can complete costly but advanced analytical analyses on a smaller sample of plastics. This project engages engineering and science undergraduate students (moderate experience) in microplastic data collection and analysis to fill gaps in microplastic data for …

Secure Similar Patients Query With Homomorphically Evaluated Thresholds, Mounika Pratapa, Aleksander Essex

Electrical and Computer Engineering Publications

Patient-centric precision medicine requires the analysis of large volumes of genomic data to tailor treatments and medications based on individual-level characteristics. Because the amount of data held by a single institution is limited, researchers may want access to genomic data held by other institutions. Owing to the inherent privacy implications of genomic data, performing comparisons on encrypted data is preferable in certain settings. The Similar patient query (SPQ) is an application that enables a secure search across genomic databases for patients with similar genetic makeup. Query results can be used to draw meaningful conclusions regarding suitable therapies.

However, existing protocols …

Deep Transfer Learning For Detection Of Upper And Lower Body Movements: Transformer With Convolutional Neural Network, Kyle Lacroix, Davoud Gholamiangonabadi, Ana Luisa Trejos, Katarina Grolinger

Electrical and Computer Engineering Publications

When humans repeat the same motion, the tendons, muscles, and nerves can be damaged, causing Repetitive Stress Injuries (RSI). If the repetitive motions that lead to RSI are recognized early, actions can be taken to prevent these injuries. As Human Activity Recognition (HAR) aims to identify activities employing wearable or environment sensors, HAR is the first step toward identifying repetitive motions. Deep learning models, such as Convolutional Neural Networks (CNNs), have seen great success in recognizing activities for participants whose data are used in the model training; however, their accuracy drops for new participants as people move in different ways. …

Federated Learning For Sentiment Analysis In Presence Of Non-Iid Data: Sensitivity Of Deep Learning Models, Davoud Gholamiangonabadi, Katarina Grolinger

Electrical and Computer Engineering Publications

In sentiment analysis, data are commonly distributed across many devices, and traditional machine learning requires transferring these data to a central location exposing data to security and privacy risks. Federated Learning (FL) avoids this transfer by training a model without requiring the clients/devices to share their local data; however, FL performance drops when data are not Independent and Identically Distributed (non-IID), such as when label distribution or data size vary across clients. Although techniques for non-IID data have been proposed primarily in the image domain, the sensitivity of various deep learning models to non-IID data needs to be examined. Consequently, …

Low-Cost Open-Source Melt Flow Index System For Distributed Recycling And Additive Manufacturing, Dawei Liu, Aditi Basdeo, Catalina Suescun Gonzalez, Alessia Romani, Hakim Boudaoud, Cécile Nouvel, Fabio A. Cruz Sanchez, Joshua M. Pearce

Electrical and Computer Engineering Publications

The increasing adoption of distributed recycling via additive manufacturing (DRAM) has facilitated the revalorization of materials derived from waste streams for additive manufacturing. Recycled materials frequently contain impurities and mixed polymers, which can degrade their properties over multiple cycles. This degradation, particularly in rheological properties, limits their applicability in 3D printing. Consequently, there is a critical need for a tool that enables the rapid assessment of the flowability of these recycled materials. This study presents the design, development, and manufacturing of an open-source melt flow index (MFI) apparatus. The open-source MFI was validated with tests on virgin polylactic acid pellets, …

Sensorized Autonomous Manipulation Platform For Underwater, Matthew Stein, Matthew Satriale, Andrew Vo

Student Research Symposium

Researchers from Brown University, University of Massachusetts Lowell (UML), and the Office of Naval Research (ONR) are developing autonomous underwater robots for naval applications. The robots must be able to autonomously complete the tasks it encounters. Roger Williams University developed a submersible instrumented back plane and four interchangeable task modules. The sensorized task platform quantitatively measures task performance for researcher evaluation.

Deep Learning Based Optical Flow Analysis Of High-Speed Flows, Daniel H. Zhang, Zifeng Yang

Mechanical and Materials Engineering Faculty Publications

Two-dimensional Rayleigh scattering imaging is utilized to quantify the high-speed flow velocity by employing deep learning based optical flow analysis, along with density fields from Rayleigh scattering intensity profiles.

Evaluation Of Driveway Assistance Device (Dad) Systems In One-Lane Two-Way Work Zone, Mm Shakiul Haque, Aemal J. Khattak, Li Zhao

Mid-America Transportation Center: Final Reports and Technical Briefs

Lane closure on two-lane highways due to the presence of work zones negatively impacts traffic safety and operational efficiency. Additionally, traffic from access points (e.g., commercial and residential driveways, or minor side roads) within work zones make operations more complicated and inefficient. Deploying a driveway assistance device (DAD) system can enable more efficient traffic control for work zones with access points. While traffic agencies are becoming interested in DAD deployments, research on such systems is relatively sparse. This research was the first in-depth operational investigation of the DAD system under different signal strategies, traffic conditions, and work zone characteristics. This …

Plant And Soil Effects Of Alternative Sources Of Phosphorus Over Three Years Of Application, Anna Karpinska, Thomais Kakouli-Duarte, S M. Ashekuzzaman, John Byrne, Achim Schmalenberger, Patrick J. Forrestal

Publications

Plant growth and food security depend heavily on phosphorus (P). Recovering and recycling P from animal, municipal, and food waste streams can significantly reduce dependency on traditional mineral P. This is particularly pertinent in the EU regions with limited native P supplies. The agronomic performance of including P-based recycling-derived fertilisers (two struvite and two ashes) or cattle slurry was compared to a conventional mineral P fertilisation programme along with no P and no fertiliser controls over three years. A field-scale experiment was set up to evaluate the perennial ryegrass dry matter yield (DMY), P uptake, and soil test P effects. …