Engineering Commons^™

Optimal Additive Fabrication Of Patient-Specific Bone Tissue Scaffolds Through Material Formulation, Computational Flow Simulation, And Material Deposition Monitoring, Ethan O’Malley

Theses, Dissertations and Capstones

The advancement of additive manufacturing technologies has opened new avenues for fabricating biocompatible and structurally functional bone tissue scaffolds, essential in treating osseous fractures, defects, and diseases. This research aims to develop mechanically strong, dimensionally precise, and patient-specific porous bone tissue scaffolds that provide both structural integrity and biological functionality. Through three interconnected studies, several key challenges in the fabrication of these structures using the PME additive manufacturing process are addressed. First, the influence of polysaccharide and hydroxyapatite concentrations on the compressive modulus of PME-printed porous scaffolds is investigated. By creating structures with varying hydroxyapatite and polysaccharide compositions, the study …

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.

Inspire Newsletter Fall 2024, Missouri University Of Science And Technolgy Inspire - University Transportation Center

INSPIRE Newsletters

No abstract provided.

Data From: Active Transportation Counts From Existing On-Street Signal And Detection Infrastructure, Sirisha Kothuri, Patrick Allen Singleton, Mahyar Vahedi Saheli, Elizabeth Yates, Joseph P. Broach

Civil and Environmental Engineering Faculty Datasets

This study’s objective was to use data from existing traffic signal infrastructure to estimate pedestrian volumes. Pedestrian push-button actuations were collected from signal controller logs at 49 intersections in western Oregon and an additional 16 intersections in eastern Oregon. These actuations were then compared to observed pedestrian counts, totaling over 34,000 people, obtained from video recordings. After exploring various options, a simple quadratic relationship was modeled using a single measure of pedestrian signal activity: the number of push-button presses (filtered to remove multiple presses within 15 seconds). The model’s predictions showed a correlation of 0.86 with observed pedestrian volumes and …

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 …

Different Spectrum Of Space Radiation Induced Cognitive Impairments In Radiation-Naïve And Adapted Rats, Richard A. Britten, Arriyam S. Fesshaye, Alyssa Tidmore, Ella N. Tamgue, Paola A. Alvarado-Arriaga

Center for Integrative Neuroscience and Inflammatory Diseases (CINID) Faculty Publications

NASA's decision to resume manned deep space mission, first to the Moon and then Mars, necessitated a detailed assessment of the potential health effects that astronauts may experience on long-duration missions. Multiple studies suggest that there may be significant space radiation (SR)-induced impairment of neurocognitive processes, including advanced executive functions. However, given the multitude of SR-induced changes in the CNS, it is possible that completely different SR-induced sequelae will be induced in previously exposed individuals. Thus, current risk estimates are likely to be pertinent only for the early stages of a deep space mission, and even then only for astronauts …

Nebraska Summary #1285: Massey Ferguson 8s 205, Nebraska Tractor Test Lab

Nebraska Tractor Tests

ABOUT THE TEST REPORT AND USE OF THE DATA The test data contained in this report are a tabulation of the results of a series of tests. Due to the restricted format of these pages, only a limited amount of data and not all of the tractor specifications are included. The full OECD report contains usually about 30 pages of data and specifications. The test data were obtained for each tractor under similar conditions and therefore, provide a means of comparison of performance based on a limited set of reported data. EXPLANATION OF THE TEST PROCEDURES Purpose The purpose of …

Winona State University Improving Our World Blog: 2013-2022, Winona State University

Winona State University Blogs

The Winona State University (WSU) Improving Our World Blog articles and entries from September 2013-February 2022. Note: there may be format coding in the document.

Winona State University Rochester Blog:2014-2023, Winona State University

Winona State University Blogs

The Winona State University (WSU) Rochester Blog includes articles and entries from May 2014-March 2023. Note: there may be format coding in the document.

Winona State University Campus Life Blog: 2013-2022, Winona State University

Winona State University Blogs

The Winona State University (WSU) Campus Life Blog includes articles and entries from October 2013- October 2022. Note: there may be format coding in the document.

Winona State University Wellness Blog: 2013-2023, Winona State University

Winona State University Blogs

The Winona State University (WSU) Wellness blog includes articles and entries from February 2013-February 2023. Note: there may be format coding in the document.

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.

Research Trends And Impact Report On Aggregation-Induced Emission (Aie), 2001-2021, Elsevier Analytical Services

Public Reports

Since the concept of AIE was first proposed in China in 2001, it has gradually grown to a field of science that attracts dedicated researchers from around the world. Elsevier's data analytics team used AIE experts' interpretation of current theoretical, technological, and industrial development trends in the field for reference to collect AIE-related global scientific publications (from the Scopus database) to serve as a publication set in the field of AIE. This was undertaken to present, accurately and objectively, the development of AIE research over the past two decades and the latest scientific advancements in the field; to facilitate the …

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 …

Enhancing Robustness Of Graph Neural Network Against Adversarial Attacks By Balancing Local And Global Perspectives, Bibek Raj Joshi

Browse all Theses and Dissertations

Graph Neural Networks (GNNs) have increasingly gained popularity as tools for analyzing graph data in areas like biology, knowledge-graphs, social networks, biology, and recommendation systems. However, their vulnerability to adversarial attacks - small, targeted manipulations of graph structures or node features - raises serious concerns about their reliability in real-world applications. Existing defense strategies, such as adversarial training, edge filtering, low-rank approximations, and randomization-based methods, often suffer from high computational costs, scalability issues, or reduced clean-data performance. Unlike these methods, the proposed approach integrates multi-hop relationships, applies adaptive regularization, and maintains a balance between feature-based and structural embeddings, ensuring improved …

Meta-Learning-Based Model Stacking Framework For Hardware Trojan Detection In Fpga Systems, Mani Rupak Gurram

Browse all Theses and Dissertations

In today's technological landscape, hardware devices are integral to critical applications such as industrial automation, autonomous vehicles, and medical equipment, relying on advanced platforms like FPGAs for core functionalities. However, the multi-stage manufacturing process, often distributed across various foundries, introduces substantial security risks, notably the potential for hardware Trojan insertion. These malicious modifications compromise the reliability and safety of hardware systems. This research addresses the detection of hardware Trojans through side-channel analysis, utilizing power and electromagnetic signal data, combined with meta-learning techniques, specifically model stacking. By employing diverse base models and a meta-model to consolidate predictions, this non-invasive approach effectively …

Production Of Cerium Oxide And Zinc Sulfide Composites, Ted Autore

Browse all Theses and Dissertations

Zinc sulfide has an infrared cutoff in the LWIR, but its low hardness makes it susceptible to rain erosion and abrasion. A composite of cerium oxide and zinc sulfide that retains an infrared cutoff in the LWIR, and with hardness higher than pure zinc sulfide is a potential solution to the rain erosion and abrasion issue. Several different processes were undertaken in this project to produce such a composite. The different reactions between ZnS and CeO2 were researched, along with the effects of different processing parameters. Composite samples were made that had a better hardness than zinc sulfide but did …

Investigating The Impact Of Stress And Irradiation Flux On Latent Track Formation In Tio2 Under Swift Heavy Ion Irradiation: A Phase Field Study, Ebrahim Ebrahimi

Browse all Theses and Dissertations

Swift Heavy Ions (SHI) irradiation, characterized by high kinetic energy ions, induces significant material/structural modification, e.g., latent track. However, the intricate interaction among various physics, i.e., mechanical stress, phase transition, and heat transfer, has been ignored in the continuum-based approaches in favor of simplicity. Here, we developed a two-dimensional coupled phase-field inelastic-thermal spike (PF-iTS) model to investigate the effect of thermal crosstalk, elastic energy, and irradiation flux on latent track formation. A particular focus is placed on investigating the influence of internal mechanical stress on latent track formation. Simulation results reveal a shift in critical stopping energy and a reduction …

Architectural Optimization Of Emulator Embedded Neural Networks For Aerospace Vehicle Design, James L. Schmitz Ii

Browse all Theses and Dissertations

An approach for the architecture optimization of emulator embedded neural networks is proposed. While the emulator embedded neural network has been shown to provide accurate predictions with suitable emulators, there is still a challenge regarding how to select the optimal hyperparameters of network architectures, such as, the number of neurons, layers, types of activation functions, etc. The selection of hyperparameters greatly affects the performance of the neural network model training both in terms of accuracy and efficiency. To address this challenge, this study proposes an algorithm that tests a range of hyperparameters and selects the best performing set. The algorithm …

Using Unsupervised Machine Learning To Reduce The Energy Requirements Of Active Flow Control, Jared N. Kerestes

Browse all Theses and Dissertations

It is generally accepted that there exist two types of laminar separation bubbles (LSBs): short and long. The process by which a short LSB transitions to a long LSB is known as bursting. In this research, large eddy simulations (LES) are used to study the evolution of an LSB that develops along the suction surface of the L3FHW-LS at low Reynolds numbers. The L3FHW-LS is a new high-lift, high-work low-pressure turbine (LPT) blade designed at the Air Force Research Laboratory. The LSB is shown to burst over a critical range of Reynolds numbers. Bursting is discussed at length and its …

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.