Engineering Commons^™

Content Adaption And Design In Mobile Learning Of Wind Instruments, Neha Priyadarshani

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People in today's world seek things that are simple to use. Learning is one of the most crucial aspects of the ongoing digital transformation. Everything is now accessible with a single click on mobile devices, making access to instructional materials faster, easier, and more comfortable. It takes time and effort to build abilities and become an expert in the fields of learning, training, and teaching; and music learning demands a great deal of both practice and mentoring. Initially, music teachers and band directors must maintain a steady attention and devote a significant amount of time to manually teaching materials. This …

Development Of A Robust And Tunable Aircraft Guidance Algorithm, Jacob R. Spangenberg

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A set of guidance control laws is developed for application to a reduced order dynamic aircraft model. A feedback control formulation utilizing a linear quadratic regulator (LQR) is developed, together with methods for easing the design burden associated with gain tuning. Metrics are developed to assess the stability margin of the controller over the full flight envelope of a notional unmanned aerial vehicle (UAV) model. A feedforward control path is then added to the architecture. The performance of the guidance control laws is assessed through time domain step response metrics as well as through execution of a design mission. The …

Mathematical Formula Recognition And Automatic Detection And Translation Of Algorithmic Components Into Stochastic Petri Nets In Scientific Documents, Elisavet Elli Kostalia

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A great percentage of documents in scientific and engineering disciplines include mathematical formulas and/or algorithms. Exploring the mathematical formulas in the technical documents, we focused on the mathematical operations associations, their syntactical correctness, and the association of these components into attributed graphs and Stochastic Petri Nets (SPN). We also introduce a formal language to generate mathematical formulas and evaluate their syntactical correctness. The main contribution of this work focuses on the automatic segmentation of mathematical documents for the parsing and analysis of detected algorithmic components. To achieve this, we present a synergy of methods, such as string parsing according to …

Utilizing Rotational Energy In Wind Turbine Blades With The Flywheel Mechanism And Predicting The Power Output By Neural Networking, Anamika Mishra

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As we expand and innovate for better and safer living, there will always be a need for new energy sources. By replacing fossil fuels, renewable energy is becoming a viable option for primary power generation. That is why researchers are turning their attention to renewable energy sources and ways of making the most of them. WIND ENERGY is a promising renewable and clean energy source harvested from the wind which is plentiful on the planet. We already have the technology to harvest it, but the efficiency and power output are not optimal. In this thesis, to enhance the energy harvesting …

Evaluating The Performance Of Using Speaker Diarization For Speech Separation Of In-Person Role-Play Dialogues, Raveendra Medaramitta

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Development of professional communication skills, such as motivational interviewing, often requires experiential learning through expert instructor-guided role-plays between the trainee and a standard patient/actor. Due to the growing demand for such skills in practices, e.g., for health care providers in the management of mental health challenges, chronic conditions, substance misuse disorders, etc., there is an urgent need to improve the efficacy and scalability of such role-play based experiential learning, which are often bottlenecked by the time-consuming performance assessment process. WSU is developing ReadMI (Real-time Assessment of Dialogue in Motivational Interviewing) to address this challenge, a mobile AI solution aiming to …

Goal Management In Multi-Agent Systems, Venkatsampath Raja Gogineni

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Autonomous agents in a multi-agent system coordinate to achieve their goals. However, in a partially observable world, current multi-agent systems are often less effective in achieving their goals. In much part, this limitation is due to an agent's lack of reasoning about other agents and their mental states. Another factor is the agent's inability to share required knowledge with other agents and the lack of explanations in justifying the reasons behind the goal. This research addresses these problems by presenting a general approach for agent goal management in unexpected situations. In this approach, an agent applies three main concepts: goal …

Altered Skeletal Muscle Excitation-Contraction Coupling In The R6/2 Transgenic Mouse Model For Huntington's Disease, Daniel R. Miranda

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Huntington’s disease (HD) has classically been categorized as a neurodegenerative disorder. However, the expression of the disease-causing mutated huntingtin gene in skeletal muscle may contribute to the symptoms of HD, namely those that involve involuntary muscle contraction. In the R6/2 transgenic mouse model of HD, we previously observed ion channel defects that could contribute to involuntary muscle contraction. Here, in R6/2 muscle we investigated the consequence of these ion channel defects on action potentials (APs), the first step in excitation-contraction (EC) coupling. We found that the ion channel defects were associated with depolarizing the baseline membrane potential during AP trains. …

Texture-Driven Image Clustering In Laser Powder Bed Fusion, Alexander H. Groeger

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The additive manufacturing (AM) field is striving to identify anomalies in laser powder bed fusion (LPBF) using multi-sensor in-process monitoring paired with machine learning (ML). In-process monitoring can reveal the presence of anomalies but creating a ML classifier requires labeled data. The present work approaches this problem by printing hundreds of Inconel-718 coupons with different processing parameters to capture a wide range of process monitoring imagery with multiple sensor types. Afterwards, the process monitoring images are encoded into feature vectors and clustered to isolate groups in each sensor modality. Four texture representations were learned by training two convolutional neural network …

Reconfigurable Antenna Array Using The Pin-Diode-Switched Printed Square Spiral Element, Corey M. Stamper

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A dual-band array of reconfigurable elements is modeled and simulated. The array consists of four single square spiral microstrip antennas that are corporately fed and are used as a unit cell. The single square spiral uses two PIN diodes as switching elements to achieve reconfiguration. The array has four switch states that can operate over four discrete frequencies in the S and C bands. The unit cell radiation pattern is used with the pattern multiplication model to quickly simulate the array pattern of larger arrays. A 3 x 3 array of the unit cells is modeled with only the center …

Development Of A Robust And Tunable Aircraft Guidance Algorithm, Jacob R. Spangenberg

Browse all Theses and Dissertations

A set of guidance control laws is developed for application to a reduced order dynamic aircraft model. A feedback control formulation utilizing a linear quadratic regulator (LQR) is developed, together with methods for easing the design burden associated with gain tuning. Metrics are developed to assess the stability margin of the controller over the full flight envelope of a notional unmanned aerial vehicle (UAV) model. A feedforward control path is then added to the architecture. The performance of the guidance control laws is assessed through time domain step response metrics as well as through execution of a design mission. The …

Texture-Driven Image Clustering In Laser Powder Bed Fusion, Alexander H. Groeger

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The additive manufacturing (AM) field is striving to identify anomalies in laser powder bed fusion (LPBF) using multi-sensor in-process monitoring paired with machine learning (ML). In-process monitoring can reveal the presence of anomalies but creating a ML classifier requires labeled data. The present work approaches this problem by printing hundreds of Inconel-718 coupons with different processing parameters to capture a wide range of process monitoring imagery with multiple sensor types. Afterwards, the process monitoring images are encoded into feature vectors and clustered to isolate groups in each sensor modality. Four texture representations were learned by training two convolutional neural network …

Augmenting Structure/Function Relationship Analysis With Deep Learning For The Classification Of Psychoactive Drug Activity At Class A G Protein-Coupled Receptors, Hannah Willow Shows

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G protein-coupled receptors (GPCRs) initiate intracellular signaling pathways via interaction with external stimuli. [1-5] Despite sharing similar structure and cellular mechanism, GPCRs participate in a uniquely broad range of physiological functions. [6] Due to the size and functional diversity of the GPCR family, these receptors are a major focus for pharmacological applications. [1,7] Current state-of-the-art pharmacology and toxicology research strategies rely on computational methods to efficiently design highly selective, low toxicity compounds. [9], [10] GPCR-targeting therapeutics are associated with low selectivity resulting in increased risk of adverse effects and toxicity. Psychoactive drugs that are active at Class A GPCRs used …

Utilizing Rotational Energy In Wind Turbine Blades With The Flywheel Mechanism And Predicting The Power Output By Neural Networking, Anamika Mishra

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As we expand and innovate for better and safer living, there will always be a need for new energy sources. By replacing fossil fuels, renewable energy is becoming a viable option for primary power generation. That is why researchers are turning their attention to renewable energy sources and ways of making the most of them. WIND ENERGY is a promising renewable and clean energy source harvested from the wind which is plentiful on the planet. We already have the technology to harvest it, but the efficiency and power output are not optimal. In this thesis, to enhance the energy harvesting …

Evaluating The Performance Of Using Speaker Diarization For Speech Separation Of In-Person Role-Play Dialogues, Raveendra Medaramitta

Browse all Theses and Dissertations

Development of professional communication skills, such as motivational interviewing, often requires experiential learning through expert instructor-guided role-plays between the trainee and a standard patient/actor. Due to the growing demand for such skills in practices, e.g., for health care providers in the management of mental health challenges, chronic conditions, substance misuse disorders, etc., there is an urgent need to improve the efficacy and scalability of such role-play based experiential learning, which are often bottlenecked by the time-consuming performance assessment process. WSU is developing ReadMI (Real-time Assessment of Dialogue in Motivational Interviewing) to address this challenge, a mobile AI solution aiming to …

Mathematical Formula Recognition And Automatic Detection And Translation Of Algorithmic Components Into Stochastic Petri Nets In Scientific Documents, Elisavet Elli Kostalia

Browse all Theses and Dissertations

A great percentage of documents in scientific and engineering disciplines include mathematical formulas and/or algorithms. Exploring the mathematical formulas in the technical documents, we focused on the mathematical operations associations, their syntactical correctness, and the association of these components into attributed graphs and Stochastic Petri Nets (SPN). We also introduce a formal language to generate mathematical formulas and evaluate their syntactical correctness. The main contribution of this work focuses on the automatic segmentation of mathematical documents for the parsing and analysis of detected algorithmic components. To achieve this, we present a synergy of methods, such as string parsing according to …

Goal Management In Multi-Agent Systems, Venkatsampath Raja Gogineni

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Autonomous agents in a multi-agent system coordinate to achieve their goals. However, in a partially observable world, current multi-agent systems are often less effective in achieving their goals. In much part, this limitation is due to an agent's lack of reasoning about other agents and their mental states. Another factor is the agent's inability to share required knowledge with other agents and the lack of explanations in justifying the reasons behind the goal. This research addresses these problems by presenting a general approach for agent goal management in unexpected situations. In this approach, an agent applies three main concepts: goal …

Detecting Server-Side Web Applications With Unrestricted File Upload Vulnerabilities, Jin Huang

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Vulnerable web applications fundamentally undermine website security as they often expose critical infrastructures and sensitive information behind them to potential risks and threats. Web applications with unrestricted file upload vulnerabilities allow attackers to upload a file with malicious code, which can be later executed on the server by attackers to enable various attacks such as information exfiltration, spamming, phishing, and spreading malware. This dissertation presents our research in building two novel frameworks to detect server-side applications vulnerable to unrestricted file uploading attacks. We design the innovative model that holistically characterizes both data and control flows using a graphbased data structure. …

The Effect Of Winding Curvature And Core Permeability On The Power Losses And Leakage Inductance Of High-Frequency Transformers, Daniel J. Whitman

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At the frequencies used in switching dc-dc converters, the skin and proximity effects have a significant effect on both the losses and leakage inductance of the transformers used in these circuits. Analytical expressions that have been derived to calculate ac resistance and leakage inductance have primarily used a 1-D approximation. They also have used Cartesian coordinates or approximations that are equivalent to Cartesian coordinates, as well as usually assuming an ideal core of infinite permeability. The classical result in the case of the resistance/losses is Dowell’s equation, and there are analogous results for leakage inductance. This dissertation derives new equations …

Acute Oxygen-Sensing By The Carotid Bodies : The Thermal Microdomain Model, Ryan Joseph Rakoczy

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The carotid bodies (CB) are peripheral chemoreceptors that detect changes in arterial oxygenation and, via afferent inputs to the brainstem, correct the pattern of breathing to restore blood gas homeostasis. Elucidating the “signal” that couples carotid body sensory type I cell (CBSC) hypoxic mitochondrial inhibition with potassium channel closure has proven to be an arduous task; to date, a multitude of oxygen-sensing chemotransduction mechanisms have been described and altercated (Varas, Wyatt & Buckler, 2007; Gao et al, 2017; Rakoczy & Wyatt, 2018). Herein, we provide preliminary evidence supporting a novel oxygen-sensing hypothesis suggesting CBSC hypoxic chemotransductive signaling may in part …

Noninvasive Blood Flow And Oxygenation Measurements In Diseased Tissue, Benjamin S. Rinehart

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The research presented in this dissertation focused on the application of optical imaging techniques to establish blood flow and oxygen saturation as effective biomarkers for two disease cases, Autism Spectrum Disorder (ASD) and Huntington’s Disease (HD). The BTBR mouse model of ASD was utilized to validate measurements of cerebral blood flow and oxygenation as biomarkers for autism. The R6/2 mouse model of juvenile HD was utilized to validate measurements of skeletal muscle blood flow following tetanic muscle contractions induced by electrical nerve stimulation. Next, a noncontact, camera-based system to measure blood flow and oxygen saturation maps was implemented to improve …

Cooling Under Applied Stress Rejuvenates Amorphous Alloys And Enhances Their Ductility, Nikolai Priezjev

Mechanical and Materials Engineering Faculty Publications

The effect of tensile stress applied during cooling of binary glasses on the potential energy states and mechanical properties is investigated using molecular dynamics simulations. We study the three-dimensional binary mixture that was first annealed near the glass transition temperature and then rapidly cooled under tension into the glass phase. It is found that at larger values of applied stress, the liquid glass former freezes under higher strain and its potential energy is enhanced. For a fixed cooling rate, the maximum tensile stress that can be applied during cooling is reduced upon increasing initial temperature above the glass transition point. …

Covid-19 And Mental Health/Substance Use Disorders On Reddit: A Longitudinal Study, Amanuel Alambo, Swati Padhee, Tanvi Banerjee, Krishnaprasad Thirunarayan

Computer Science and Engineering Faculty Publications

COVID-19 pandemic has adversely and disproportionately impacted people suffering from mental health issues and substance use problems. This has been exacerbated by social isolation during the pandemic and the social stigma associated with mental health and substance use disorders, making people reluctant to share their struggles and seek help. Due to the anonymity and privacy they provide, social media emerged as a convenient medium for people to share their experiences about their day to day struggles. Reddit is a well-recognized social media platform that provides focused and structured forums called subreddits, that users subscribe to and discuss their experiences with …

Multi-Echo Quantitative Susceptibility Mapping For Strategically Acquired Gradient Echo (Stage) Imaging, Sara Gharabaghi, Saifeng Liu, Ying Wang, Yongsheng Chen, Sagar Buch, Mojtaba Jokar, Thomas Wischgoll, Nasser H. Kashou, Chunyan Zhang, Bo Wu, Jingliang Cheng, E. Mark Haacke

Computer Science and Engineering Faculty Publications

Purpose: To develop a method to reconstruct quantitative susceptibility mapping (QSM) from multi-echo, multi-flip angle data collected using strategically acquired gradient echo (STAGE) imaging. Methods: The proposed QSM reconstruction algorithm, referred to as “structurally constrained Susceptibility Weighted Imaging and Mapping” scSWIM, performs an ℓ1 and ℓ2 regularization-based reconstruction in a single step. The unique contrast of the T1 weighted enhanced (T1WE) image derived from STAGE imaging was used to extract reliable geometry constraints to protect the basal ganglia from over-smoothing. The multi-echo multi-flip angle data were used for improving the contrast-to-noise ratio in QSM through a weighted averaging scheme. The …

A Nonlinear Distortion Removal Based On Deep Neural Network For Underwater Acoustic Ofdm Communication With The Mitigation Of Peak To Average Power Ratio, Xuefei Ma, Waleed Raza, Zhiqiang Wu, Muhammad Bilal, Ziqi Zhou, Amir Ali

Electrical Engineering Faculty Publications

Machine learning and deep learning algorithms have proved to be a powerful tool for developing data-driven signal processing algorithms for challenging engineering problems. This paper studies the modern machine learning algorithm for modeling nonlinear devices like power amplifiers (PAs) for underwater acoustic (UWA) orthogonal frequency divisional multiplexing (OFDM) communication. The OFDM system has a high peak to average power ratio (PAPR) in the time domain because the subcarriers are added coherently via inverse fast Fourier transform (IFFT). This causes a higher bit error rate (BER) and degrades the performance of the PAs; hence, it reduces the power efficiency. For long-range …

Developing An Equivalent Solid Material Model For Bcc Lattice Cell Structures Involving Vertical And Horizontal Struts, Tahseen A. Alwattar, Ahsan Mian

Mechanical and Materials Engineering Faculty Publications

In this study, a body-centered cubic (BCC) lattice unit cell occupied inside a frame structure to create a so-called “InsideBCC” is considered. The equivalent quasi-isotropic properties required to describe the material behavior of the InsideBCC unit cell are equivalent Young’s modulus ( E e ) , equivalent shear modulus ( G e ) , and equivalent Poisson’s ratio ( ν e ) . The finite element analysis (FEA) based computational approach is used to simulate and calculate the mechanical responses of InsideBCC unit cell, which are the mechanical responses of the equivalent solid. Two separates finite element models are then …

Additive Manufacturing And How 3d Printing Is Fighting Covid-19, Raghavan Srinivasan, Ahsan Mian, Joy Gockel, Laura M. Luehrmann

Mechanical and Materials Engineering Faculty Publications

This is the fourth installment in the Shelter in Place (SiP) Lecture series. This installment covers the creative ways that 3D printing has supported efforts to combat the pandemic. It covers the basics of what 3D printing is, some of the various creative projects that have used 3D printing to combat the pandemic, among other topics and questions by the pandemic.

Defect Characterization Of Additively Manufactured Parts, Sabrina D'Alesandro, Joy Gockel, Andrew Harvey

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials

This document describes various image processing techniques to be used for defect characterization of additively manufactured parts. This will help the reader gain knowledge of materials science engineering and the nuances in analyzing data from image processing software.

Additive manufacturing is shaping the manufacturing world through simplistic household printers’ to more complex metal printers used for a variety of applications. Specifically, laser powder bed fusion (LPBF) is an additive manufacturing process that deposits metal powder over the build plate and melts it with a laser in the shape of the build part. In order to make LPBF more efficient with …

How Do Surgeon Preferences And Technique Variances Affect Outcome?, Anastasia Axiopoulou, Caroline G. L. Cao, Katherine Lin Md, Keith Watson Md

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials

The goal of the research project is to create a blue-print of a robot-assisted hysterectomy procedure to support design and evaluation of technology to enhance system performance. To create this blue-print, we will conduct a task analysis, model the cognitive task flow and decision making, and develop a simulation of the hysterectomy procedure. The surgical simulation will be used as a platform to train surgeons on robotic-assisted hysterectomies, as well as to assess learning and performance. Additionally, it will be used to design and develop techniques and novel technology to support surgeons in their performance of the surgery. Current research …

Identifying Easy Indicators Of Dementia, Swati Padhee, Tanvi Banerjee, Valerie L. Shalin, Krishnaprasad Thirunarayan

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials

Alzheimer’s Disease (AD) is a degenerative chronic neurodegenerative disease that affects millions of people and whose care costs billions of dollars. There is growing evidence that variations in speech and language may be early indicators of dementia. One of the most initial symptoms of dementia is speech impairment, including difficulty in finding words and changes to the grammatical structure. These early indicators can be detected by having the patients perform a picture description task, such as the Cookie Theft task from the Boston Diagnostic Aphasia Examination. However, much of the state-of-the-art NLP for dementia has been limited due to the …

Measuring Nomophobia And Exploration Of Consequences And Comorbidities, Sarah Marie Fryman, William L. Romine

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials

Excessive use of smartphones has coined the term “Nomophobia”, or fear of not being able to use your smartphone. For many, these devices have become an extension of ourselves, which raises hesitation on whether or not society has become addicted to smartphones. Specific diagnostic criteria for smartphone addiction have yet to be settled, and even appropriate to use the word “addiction” when describing excessive usage of smartphones is controversial.

We therefore explore utilize current measures to explore the symptoms of nomophobia and their hierarchy, as well as comorbidities including social anxiety, self-esteem, distracted driving and sleep quality. A total of …