Digital Commons Network^™

Merit Study Of Battery Or Hydrogen Energy Storage For Large Scale, Combined Wind And Solar Electricity Generation, Ashley K. Moore

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In the past several years, the energy sector has experienced a rapid increase in renewable energy installations due to declining capital costs for wind turbines, solar panels, and batteries. Wind and solar electricity generation are intermittent in nature which must be considered in an economic analysis if a fair comparison is to be made between electricity supplied from renewables and electricity purchased from the grid. Energy storage reduces curtailment of wind and solar and minimizes electricity purchases from the grid by storing excess electricity and deploying the energy at times when demand exceeds the renewable energy supply. The objective of …

Jcati Carbon Fiber Recycler: Crusher System, Devin Riley

All Undergraduate Projects

With a substantial rise in Carbon Fiber use across all industries, the need for a way to recycle the waste has grown as well. A group of Mechanical Engineering Technology students at Central Washington University funded by the Joint Center for Aerospace Technology (JCATI) have created a machine to recycle waste wing trimmings from the Boeing company’s airplanes. This machine consists of 5 different sub-assemblies being the oven, crusher, gear train, conveyor, and shredder. The purpose of this project was to decrease the deflection in the crusher caused by bulging in the housing and movement of the bearings. To decrease …

Rc Baja: Suspension And Steering, Baley Norton, John Lange

All Undergraduate Projects

Engineering students attending Central Washington University were tasked with developing and creating a functional RC car. This car would then compete in a state-wide competition while being developed over the course of three quarters with the competition being held in the spring. This was completed in teams of two that were assigned two of the four sections within this project who then independently designed and developed each section. This was broken down into having one teammate in charge of the drivetrain and chassis and having the other teammate working on the suspension and steering sections of the vehicle. Each section …

Data-Driven Strategies For Pain Management In Patients With Sickle Cell Disease, Swati Padhee

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This research explores data-driven AI techniques to extract insights from relevant medical data for pain management in patients with Sickle Cell Disease (SCD). SCD is an inherited red blood cell disorder that can cause a multitude of complications throughout an individual’s life. Most patients with SCD experience repeated, unpredictable episodes of severe pain. Arguably, the most challenging aspect of treating pain episodes in SCD is assessing and interpreting the patient’s pain intensity level due to the subjective nature of pain. In this study, we leverage multiple data-driven AI techniques to improve pain management in patients with SCD. The proposed approaches …

A Novel Knowledge-Based Federated Deep Learning Approach For Enhancing Security And Privacy Preservation In Iot Edge Computing Applications, Tabassum Simra

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The Internet of Things (IoT) infrastructure encompasses smart devices and real-time sensors connected through the Internet, facilitating the exchange of large datasets among these devices. This interconnected network of IoT sensors generates a significant volume of data for processing and analysis by embedded IoT Edge Computing systems. IoT Edge Computing systems enable efficient real-time analysis and data communications. Furthermore, IoT Edge Computing emerges to enhance the overall efficiency of IoT applications, making them adept at handling the dynamic demands of AI-based and large data-driven applications. The integration of IoT Edge Computing introduces several unique research challenges. Unfortunately, IoT Edge Computing …

Emotions In Engineering Education (Chapter 8), James L. Huff Ph.D., Johanna Lonngren, Ines Dirieto, Roland Tormey

Faculty Research and Publications

Contrary to common stereotypes, engineering education and practice are not purely rational activities. Emotions, just like cognition, play important roles in teaching, learning, and professional practice. Today, there is a nascent body of research exploring emotions in engineering education (EEE). However, much of the existing research does not adequately theorize emotions, and the range of theories and methods used is still relatively narrow. With this chapter, we hope to inspire more investigators to conduct EEE research and to explore currently underutilized theories, methods, and research foci. This chapter introduces the reader to the multidisciplinary field of emotion research, then focus …

Advancing An Integrative Perspective Of Identity In Engineering Education (Chapter 9), James L. Huff Ph.D., Monique S. Ross Ph.D.

Faculty Research and Publications

Existing research has used identity as a theoretical construct to help us understand a wide array of phenomena, such as engagement and persistence in engineering. By understanding the personal, social, and sociocultural forces that operate in the developmental processes of an individual, we understand how they come to make sense of who they are. Further, we come to learn how they position themselves in relation to what it means to be an engineer. However, identity research in engineering education has supported a diffuse set of theoretical perspectives that do not organically coalesce. This chapter advances an integrated conceptualization of engineering …

Streaming With Butterflies: A Whole School Stream Project, Carey L. Averill, Janet M. Herrelko

Journal of Catholic Education

This study explores the commitment of a school faculty to use the pedagogical practices needed to employ a project-based unit of Science, Technology, Religion, Engineering, Arts, and Mathematics (STREAM). The unit of study concentrated on environmental sustainability of butterflies through project-based learning (PBL). Teacher interviews were analyzed to reveal the similarities and differences, strengths and weaknesses in the teachers’ reactions to implementing a cross-curricula content unit designed for a pre-kindergarten (PK) to eighth grade school. Analysis of teacher data and classroom artifacts provided evidence of: content mastery at the student levels; implementation of scaffolding for developmental levels; and the need …

A New Approach To Encourage The Next Generation Of Female Engineers In Spain: A Young And Fresh Podcast To Attract More Girls To The Field: “Clau, Quiero Ser Ingeniera”, Marta Olea, Francisco Javier Jiménez Leube, Claudia Rebollo

Practice Papers

The underrepresentation of women in STEM fields is a complex issue with multiple factors that remain unclear. At Universidad Politécnica de Madrid (UPM), we have dedicated years to devising strategies aimed at attracting more girls to this domain. As the coordinating institution of the EELISA alliance, where we endeavor to define the European engineer, we confront gender inequality as one of the foremost challenges. To address this need, a 4th year student at UPM conceived an initiative: a podcast with three primary objectives. Firstly, it aims to highlight the accomplishments of female engineers who can serve as role models for …

Enhancing Student Veterans' Self-Efficacy And Sense Of Belonging In A Targeted Learning Community: Four Years Of Qualitative Results, Anthony W. Dean, Cynthia Tomovic, Vukica Jovanovic, Kim E. Bullington

Engineering Technology Faculty Publications

Eight semesters of qualitative data, collected over four academic years, are presented from a project that resulted in the development of a student professional learning community of high-achieving, low-income engineering and engineering technology student veterans. In the context of this project, student veterans received academic, professional, and financial support that helped them to be successful in school and to prepare them for a career in the STEM workforce. As adult learners, students in this learning community were a vital part of the curriculum development which resulted in increasing the students’ interest and buy-in. Typically, adult learners have lower levels of …

Associating High School Science, Technology, Engineering, And Math (Stem) Course-Taking With Future Earnings For Non-Stem Employed High School Graduates, Beth Marchant

Dissertations

Problem

Due to the current resurgence of attention given to high school students' taking courses in Science, Technology, Engineering, and Mathematics (STEM), research was needed to examine whether a relationship between the number of STEM courses a high school student, who graduates from high school and works in a non-STEM field, completes and the success of that student 10 years later. One measure of student success, future earnings, can be measured quantitatively and is included in the Education Longitudinal Survey of 2002 (ELS:2002) data set, an ideal source of information to evaluate this issue (Institute of Education Sciences, 2019b).

Method …

Brain Morphometry From Neuroimaging As A Biomarker For Alzheimer's Disease, Nonyelum Benedicta Aniebo

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Alzheimer’s disease (AD) is the seventh leading cause of death globally with an estimated 6.5 million Americans aged 65 and above living with Alzheimer’s dementia in 2022 and at a projected national cost of $321 billion. AD is characterized by a progressive and irreversible neurodegenerative dysfunction with clinical symptoms such as deterioration in cognition and memory loss. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a multi-site, public-private global research initiative that supports both investigation and development of treatments that slow or terminate AD progression. The study included 60 participants, comprising 30 AD and 30 control cohorts respectively. All participants were …

Accelerating Precision Station Keeping For Automated Aircraft, James D. Anderson

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Automated vehicles pose challenges in various research domains, including robotics, machine learning, computer vision, public safety, system certification, and beyond. These vehicles autonomously handle navigation and locomotion, often requiring minimal user interaction, and can operate on land, in water, or in the air. In the context of aircraft, one specific application is Automated Aerial Refueling (AAR). Traditional aerial refueling involves a "tanker" aircraft using a mechanism, such as a rigid boom arm or a flexible hose, to transfer fuel to another aircraft designated as the "receiver". For AAR, the boom arm may be maneuvered automatically, or in certain instances the …

Enrollment In Science, Technology, Engineering, And Math Courses After Enactment Of Texas' House Bill 5, Carlana Cla'shette Allen

Walden Dissertations and Doctoral Studies

Student participation and performance in science, technology, engineering, and math (STEM) have been an education concern in the United States for years. In 2013, Texas lawmakers passed House Bill 5 (HB5) to support increases in STEM awareness, particularly among ethnic minority and female students. To date, no studies have been conducted on the impact, if any, of HB5 on Texas high school students’ course selections in STEM areas. Further, it is unknown whether the impact that does exist is equally distributed across socioeconomic status (SES), race/ethnicity, and gender groups. The purpose of this nonexperimental correlational quantitative study was to determine …

The Analysis, Development And Calibration Of Prototype Hardware In Effort To Improve Brake Thermal Efficiency And Real-World Fuel Economy Of The International Supertruck, Matthew Taylor

All Graduate Theses, Dissertations, and Other Capstone Projects

The work performed for this project was in part of the effort of the Department of Energy Sponsored program called ‘SuperTruck’. The entirety of the Supertruck program encompasses total vehicle re-design to achieve 80% freight efficiency improvement (over the 2009MY baseline production vehicle). However, the other main goal for the program is to achieve 50% engine brake thermal efficiency. The work outlined in this document describes the efforts performed on base engine and thus mainly contributing towards 50% BTE. Though ultimately reducing BSFC by increasing BTE contributes to both outcomes. The engine development data discussed in this paper was collected …

Comparative Adjudication Of Noisy And Subjective Data Annotation Disagreements For Deep Learning, Scott David Williams

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Obtaining accurate inferences from deep neural networks is difficult when models are trained on instances with conflicting labels. Algorithmic recognition of online hate speech illustrates this. No human annotator is perfectly reliable, so multiple annotators evaluate and label online posts in a corpus. Labeling scheme limitations, differences in annotators' beliefs, and limits to annotators' honesty and carefulness cause some labels to disagree. Consequently, decisive and accurate inferences become less likely. Some practical applications such as social research can tolerate some indecisiveness. However, an online platform using an indecisive classifier for automated content moderation could create more problems than it solves. …

Enhancing Graph Convolutional Network With Label Propagation And Residual For Malware Detection, Aravinda Sai Gundubogula

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Malware detection is a critical task in ensuring the security of computer systems. Due to a surge in malware and the malware program sophistication, machine learning methods have been developed to perform such a task with great success. To further learn structural semantics, Graph Neural Networks abbreviated as GNNs have emerged as a recent practice for malware detection by modeling the relationships between various components of a program as a graph, which deliver promising detection performance improvement. However, this line of research attends to individual programs while overlooking program interactions; also, these GNNs tend to perform feature aggregation from neighbors …

Effective Systems For Insider Threat Detection, Muhanned Qasim Jabbar Alslaiman

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Insider threats to information security have become a burden for organizations. Understanding insider activities leads to an effective improvement in identifying insider attacks and limits their threats. This dissertation presents three systems to detect insider threats effectively. The aim is to reduce the false negative rate (FNR), provide better dataset use, and reduce dimensionality and zero padding effects. The systems developed utilize deep learning techniques and are evaluated using the CERT 4.2 dataset. The dataset is analyzed and reformed so that each row represents a variable length sample of user activities. Two data representations are implemented to model extracted features …

Fuzzing Php Interpreters By Automatically Generating Samples, Jacob S. Baumgarte

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Modern web development has grown increasingly reliant on scripting languages such as PHP. The complexities of an interpreted language means it is very difficult to account for every use case as unusual interactions can cause unintended side effects. Automatically generating test input to detect bugs or fuzzing, has proven to be an effective technique for JavaScript engines. By extending this concept to PHP, existing vulnerabilities that have since gone undetected can be brought to light. While PHP fuzzers exist, they are limited to testing a small quantity of test seeds per second. In this thesis, we propose a solution for …

Modeling, Simulation, And Hardware Testing Of A Noise-Canceller Adc Architecture, Ethan R. Rando

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Analog-to-Digital Converters (ADCs) are essential elements of most complex electronic devices. ADCs allow for an analog signal to be converted into the digital domain, and thus interpreted by a digital circuit or model. While ADCs are extremely common, they are not immune from common tradeoffs when being designed and implemented. The most prominent tradeoff when selecting or designing an ADC is whether to pursue a high conversion rate or a high resolution on the digital output. There are some ADC designs that allow for relatively high resolution while maintaining a respectable conversion rate, however these designs often come at the …

Unsupervised-Based Distributed Machine Learning For Efficient Data Clustering And Prediction, Vishnu Vardhan Baligodugula

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Machine learning techniques utilize training data samples to help understand, predict, classify, and make valuable decisions for different applications such as medicine, email filtering, speech recognition, agriculture, and computer vision, where it is challenging or unfeasible to produce traditional algorithms to accomplish the needed tasks. Unsupervised ML-based approaches have emerged for building groups of data samples known as data clusters for driving necessary decisions about these data samples and helping solve challenges in critical applications. Data clustering is used in multiple fields, including health, finance, social networks, education, and science. Sequential processing of clustering algorithms, like the K-Means, Minibatch K-Means, …

Rankine Cycle Investigation On Meeting Power And Thermal Requirements Of High-Speed Aircraft, Jacob J. Spark

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This work is investigating a dual mode Rankine cycle for aircraft applications, specifically meeting vehicle thermal and power requirements. This multiconfigurational approach allows the Thermal Management System (TMS) to be controlled based on aircraft needs. In this design, waste heat is removed from critical areas of the aircraft (e.g., propulsion, structure, subsystems) using the fuel as a heat sink. Hot fuel is then forced through a heat exchanger actively boiling water. The vapor byproduct is fed to a turbine coupled to a generator, providing power. The low-pressure steam is then condensed using cold fuel drawn from its tank; however, when …

Anomaly Detection In Multi-Seasonal Time Series Data, Ashton Taylor Williams

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Most of today’s time series data contain anomalies and multiple seasonalities, and accurate anomaly detection in these data is critical to almost any type of business. However, most mainstream forecasting models used for anomaly detection can only incorporate one or no seasonal component into their forecasts and cannot capture every known seasonal pattern in time series data. In this thesis, we propose a new multi-seasonal forecasting model for anomaly detection in time series data that extends the popular Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Our model, named multi-SARIMA, utilizes a time series dataset’s multiple pre-determined seasonal trends to increase …

Comparative Study Of Mof's In Phosphate Adsorption, Eniya Karunamurthy

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High concentrations of phosphate are known to adversely affect the environment. Excess phosphate can lead to eutrophication that eventually fosters uncontrollable growth of aquatic plants and algae. This can result in depletion of oxygen content which adversely impacts underwater organism’s survival rates. Metal organic frameworks (MOFs) consist of organic linkers in conjunction with metal ions or clusters arranged within a crystalline structure. They are highly porous and have larger surface area due to their ability to possess extensive void spaces while remaining bulky in nature. MOFs can absorb phosphate from aqueous solutions. We have investigated the use of commercially available …

Path-Safe: Enabling Dynamic Mandatory Access Controls Using Security Tokens, James P. Maclennan

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Deploying Mandatory Access Controls (MAC) is a popular way to provide host protection against malware. Unfortunately, current implementations lack the flexibility to adapt to emergent malware threats and are known for being difficult to configure. A core tenet of MAC security systems is that the policies they are deployed with are immutable from the host while they are active. This work looks at deploying a MAC system that leverages using encrypted security tokens to allow for redeploying policy configurations in real-time without the need to stop a running process. This is instrumental in developing an adaptive framework for security systems …

Digital Beamforming Array Phase Calibration Techniques For Multi-Pass Interferometric Sar, Kelly Cheung

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Calibration plays a critical role in the optimal performance of algorithms in digital beamforming arrays. Phase incoherency between elements results in poor beamforming with decreased gain and higher sidelobes, leading to a decrease in accuracy and sensitivity of measurements. A similar problem exists in performing multi-pass interferometric SAR (IFSAR) processing of SAR data stacks to generate topological maps of the scene, where phase errors translate to height errors. By treating each SAR image in the data stack like an element of a uniform linear array, this thesis explores several phase calibration techniques that can be used to calibrate digital beamforming …

Data-Driven Strategies For Disease Management In Patients Admitted For Heart Failure, Ankita Agarwal

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Heart failure is a syndrome which effects a patient’s quality of life adversely. It can be caused by different underlying conditions or abnormalities and involves both cardiovascular and non-cardiovascular comorbidities. Heart failure cannot be cured but a patient’s quality of life can be improved by effective treatment through medicines and surgery, and lifestyle management. As effective treatment of heart failure incurs cost for the patients and resource allocation for the hospitals, predicting length of stay of these patients during each hospitalization becomes important. Heart failure can be classified into two types: left sided heart failure and right sided heart failure. …

Understanding And Enhancing The Efficiency And Efficacy Of Machine Learning-Assisted Software Vulnerability Detection, Daniel J. Grahn

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As our world has become dependent upon software for nearly every aspect of modern society, software security has followed as an essential feature. The first line of defense against vulnerabilities is secure coding. While today’s programmers are carefully taught secure coding best practices, they can make mistakes or intentionally introduce vulnerable code. The traditional backstop to human errors and insider threats is the adoption of automated security analysis tools. These analysis tools have limitations. Static analysis suffers from high false positive rates that may cause annoyance and complacency among developers. Dynamic analysis can be difficult to set up and very …

Enrollment In Science, Technology, Engineering, And Math Courses After Enactment Of Texas' House Bill 5, Carlana Cla'shette Allen

Walden Dissertations and Doctoral Studies

Student participation and performance in science, technology, engineering, and math (STEM) have been an education concern in the United States for years. In 2013, Texas lawmakers passed House Bill 5 (HB5) to support increases in STEM awareness, particularly among ethnic minority and female students. To date, no studies have been conducted on the impact, if any, of HB5 on Texas high school students’ course selections in STEM areas. Further, it is unknown whether the impact that does exist is equally distributed across socioeconomic status (SES), race/ethnicity, and gender groups. The purpose of this nonexperimental correlational quantitative study was to determine …

Enrollment In Science, Technology, Engineering, And Math Courses After Enactment Of Texas' House Bill 5, Carlana Cla'shette Allen

Walden Dissertations and Doctoral Studies

Student participation and performance in science, technology, engineering, and math (STEM) have been an education concern in the United States for years. In 2013, Texas lawmakers passed House Bill 5 (HB5) to support increases in STEM awareness, particularly among ethnic minority and female students. To date, no studies have been conducted on the impact, if any, of HB5 on Texas high school students’ course selections in STEM areas. Further, it is unknown whether the impact that does exist is equally distributed across socioeconomic status (SES), race/ethnicity, and gender groups. The purpose of this nonexperimental correlational quantitative study was to determine …