Engineering Commons^™

Investigating The Use Of Recurrent Neural Networks In Modeling Guitar Distortion Effects, Caleb Koch, Scott Hawley, Andrew Fyfe

[Archive] Belmont University Research Symposium (BURS)

Guitar players have been modifying their guitar tone with audio effects ever since the mid-20th century. Traditionally, these effects have been achieved by passing a guitar signal through a series of electronic circuits which modify the signal to produce the desired audio effect. With advances in computer technology, audio “plugins” have been created to produce audio effects digitally through programming algorithms. More recently, machine learning researchers have been exploring the use of neural networks to replicate and produce audio effects initially created by analog and digital effects units. Recurrent Neural Networks have proven to be exceptional at modeling audio effects …

Sustainable Atos - Flying To Net Zero, Eva Maleviti, Bettina Mrusek

Publications

Pathways to Net Zero- Targets

Improve fuel-efficiency by an average of 2% per year - 2020 to 2030

Reduction in total carbon dioxide emissions to net-zero by 2050.

After 2026 carbon allowances will be zero for EU.

Healthcare Disparities Among Incarcerated Populations: A Quality Improvement Project, Mariam Bradley, Morgan Callihan, Sandra Frederick, Riley Hall, Marty Helms, Aaliyah Manson, Katelyn Martha, Madison Mason, Suzi White

2023 Celebration of Student Scholarship - Poster Presentations

A population that has been consistently subject to unequal treatment when receiving medical attention is the population of prisoners or jail inmates. It is essential to explore the discrepancies prisoners face and the effects it has on their health. The objective of this research was to bring to light the disparities incarcerated patients experience, and how to eliminate these. In order to develop a better understanding of the prejudiced actions incarcerated patients face in the healthcare spectrum, numerous studies have been analyzed.

Are Gender And Social Disparities Associated With Stem Persistence In Kentucky Colleges?, Riley E. Hicks, Wilson Gonzalez-Espada

2023 Celebration of Student Scholarship - Poster Presentations

Children have the right to receive a quality education, but concerns about county disparities in school funding, facilities, and resources exist. This is known as the "zip code effect". Because high school STEM classes require lab space, materials, equipment, and specialized teachers, disparities in school funding can impact students who want STEM careers.

Visual Pollution Classification Using Convolutional Neural Networks, Jacob Vogelpohl, Heba Elgazzar

2023 Celebration of Student Scholarship - Poster Presentations

Visual pollution is an impairment on an individual's ability to enjoy their surroundings. It usually takes the form of a messy and chaotic environment that can cause overstimulation of the visual senses. This includes trash, advertisements, construction, electric cables, and similar objects. Convolutional Neural Networks (CNNs) are a form of artificial intelligence that use supervised learning to process and classify images. In this research, a CNN processed images of city streets and classified them as polluted or not polluted based on the visual characteristics that it learned from during its training period. The CNN achieved a training accuracy of 98% …

Predicting The Mechanism And Products Of Cs2 Capture By Nh3 - An Exemplar Benchmark Study, Shelbie A. Black, David A. Dixon, Zachary R. Lee

2023 Celebration of Student Scholarship - Poster Presentations

Carbon disulfide is a toxic gas emitted from industrial plants and a common greenhouse gas. Acute poisonings from carbon disulfide are rare, but recurring exposure to low doses can have long term health effects. Currently, there are two approaches being considered for the removal of acid gas pollutants: (1) sequester these gases from the atmosphere or (2) remove these gases directly upon combustion (post-combustion). Potential energy surfaces (PES) for a series of CS2 capture reactions by NH3 in the presence H2O were calculated at the MP2/a(D+d) evel in the gas phase. G3(MP2) and FPD calculations are in progress. Extensive thermodynamic …

Computational Design Of Fiber-Optic Probes For Biosensing, Suwarna Karna

Electrical Engineering Theses

This thesis presents a study on the optical characteristics of hollow-core photonic crystal fibers (HC-PCFs) with a band gap cladding structure and their applications in optical fiber sensing. This 800B HC-PCF exhibited excellent optical properties and has a flexible structure, which makes them suitable for a wide range of industrial applications. Finite element simulations and structural optimization designs were conducted using the surface plasmon resonance (SPR) technique to determine the optimal performance parameters of the 800B HC-PCF. The fiber was further modified using the SPR technique to improve its practical detection capabilities. The performance of the modified fiber was observed …

A Simulation Of The Impacts Of Climate Change On Civil Aircraft Takeoff Performance, Thomas D. Pellegrin

Doctoral Dissertations and Master's Theses

Climate change affects the near-surface environmental conditions that prevail at airports worldwide. Among these, air density and headwind speed are major determinants of takeoff performance, and their sensitivity to global warming carries potential operational and economic implications for the commercial air transport industry. Previous archival and prospective research observed a weakening in headwind strength and predicted an increase in near-surface temperatures, respectively, resulting in an increase in takeoff distances and weight restrictions. The main purpose of the present study was to update and generalize the extant prospective research using a more representative sample of worldwide airports, a wider range of …

Defining Safe Training Datasets For Machine Learning Models Using Ontologies, Lynn C. Vonder Haar

Doctoral Dissertations and Master's Theses

Machine Learning (ML) models have been gaining popularity in recent years in a wide variety of domains, including safety-critical domains. While ML models have shown high accuracy in their predictions, they are still considered black boxes, meaning that developers and users do not know how the models make their decisions. While this is simply a nuisance in some domains, in safetycritical domains, this makes ML models difficult to trust. To fully utilize ML models in safetycritical domains, there needs to be a method to improve trust in their safety and accuracy without human experts checking each decision. This research proposes …

Drinking Water Contaminants: Bacteria, Bruce I. Dvorak, Becky O. Schuerman

Department of Civil and Environmental Engineering: Faculty Publications

Testing drinking water for fecal bacteria or Escherichia coli (E. coli) is commonly used as an indicator of the presence of pathogenic microorganisms. The presence of pathogenic (disease-causing) microorganisms is a concern when considering the safety of drinking water. Pathogenic microorganisms can cause flu-like systems, intestinal infections, dysentery, hepatitis, typhoid fever, cholera, and other illnesses.

Method Design For Separation Of Non-Canonical Dna Structures Via Capillary Electrophoresis, Erin V. Chen , '23

Senior Theses, Projects, and Awards

G-quadruplex DNA structures are highly relevant subjects of biochemical study, implicated in human diseases and cancer. Conventional methods for G-quadruplex DNA structure separation are time-consuming, environmentally unfriendly, and low throughput. Thus, there is a pressing need for alternative methods of separation to be developed for G-quadruplex DNAs. Here we present work in designing a separation method using the capillary electrophoresis instrument. Capillary electrophoresis is a highly automated, reusable, and quantitative technique that separates analytes based on their size and charge. A capillary method for G-quadruplex separation would be a valuable analytical tool to supplement the biophysical methods available by addressing …

Targeting Lncrna Ddit4-As1 Sensitizes Triple Negative Breast Cancer To Chemotherapy Via Suppressing Of Autophagy, Ting Jiang, Jiaojiao Zhu, Shilong Jiang, Zonglin Chen, Ping Xu, Rong Gong, Changxin Zhong, Yueying Cheng, Xinyuan Sun, Wenjun Yi, Jinming Yang, Wenhu Zhou, Yan Cheng

Markey Cancer Center Faculty Publications

In this study, it is found that the lncRNA, DNA damage inducible transcript 4 antisense RNA1 (DDIT4-AS1), is highly expressed in triple-negative breast cancer (TNBC) cell lines and tissues due to H3K27 acetylation in the promoter region, and promotes the proliferation, migration, and invasion of TNBC cells via activating autophagy. Mechanistically, it is shown that DDIT4-AS1 induces autophagy by stabilizing DDIT4 mRNA via recruiting the RNA binding protein AUF1 and promoting the interaction between DDIT4 mRNA and AUF1, thereby inhibiting mTOR signaling pathway. Furthermore, silencing of DDIT4-AS1 enhances the sensitivity of TNBC cells to chemotherapeutic agents such as paclitaxel both …

Semantics-Based Data Security Models, Theppatorn Rhujittawiwat

Theses and Dissertations

In this dissertation, we studied how an adversary could attack databases and how the system could prevent or recover from such an attack. Our motivation to improve the current security capabilities of database management systems. We provided better recovery capabilities of database management systems by incorporating data provenance. We also expand our study to express security and privacy needs of data in the Internet of Things (IoT) environments such as a smart home environment. For this, we proposed a stream data security model to theoretically represent the data in the IoT network. We built a dynamic authorization model on our …

Hydrothermal Liquefaction Of Saccharina Latissima For The Production Of Biofuel, Mayokun A. Oke

Mechanical Engineering Theses

We performed hydrothermal liquefaction of brown macroalga (Saccharina latissima) in the presence of homogenous and heterogenous catalysts such as KOH, Na₂CO₃, Pd/C, HZSM-5, Ce/HZSM-5, and Ni/SiO₂-Al₂O₃ in hot compressed water, to investigate their effects on product yield and composition in the biocrude. To investigate hydrocarbon production, we used methanol as co-solvent (methanol-to-water 1/4 vol.%) and as the only liquefaction solvent. We carried out the experiments in a batch reactor at 330^oC and 120-130 bar, and varying temperature, algae-to-water ratio, residence time, and pretreatment method. The biocrude yields …

Para Cima Y Pa’ Abajo: Building Bridges Between Hci Research In Latin America And In The Global North, Pedro Reynolds-Cuéllar, Marisol Wong-Villacres, Karla A. Badillo-Urquiola, Mayra Donaji Barrera-Machuca, Franceli L. Cibrian, Marianela Ciolfi Felice, Carolina Fuentes, Laura Sanely Gaytán-Lugo, Vivian Genaro Motti, Monica Perusquía-Hernández, Oscar A. Lemus

Engineering Faculty Articles and Research

The Human-computer Interaction (HCI) community has the opportunity to foster the integration of research practices across the Global South and North to begin overcoming colonial relationships. In this paper, we focus on the case of Latin America (LATAM), where initiatives to increase the representation of HCI practitioners lack a consolidated understanding of the practices they employ, the factors that influence them, and the challenges that practitioners face. To address this knowledge gap, we employ a mixed-methods approach, comprising a survey (66 respondents) and in-depth interviews (19 interviewees). Our analyses characterize a set of research perspectives on how HCI is practiced …

Grid Independence Studies Of Eddy-Resolving Models At The Scale Of A River Reach Along A Transect In Marble Canyon Of The Colorado River, Arizona, Rosa Elena España Urresty

Open Access Theses & Dissertations

This study presented a novel approach for evaluating the impact of changes in spatial resolution on field-scale models to identify turbulent flow patterns in hydraulic features in canyon-bound rivers. The methodological framework incorporated seven different computational domain resolutions to analyze the sensitivity of field-scale models to spatial resolution changes by employing techniques such as turbulent kinetic energy spectrum, spatiotemporal analysis of eddy structures, divergent Kullback-Leibler (KL) divergence, Nash-Sutcliffe (NS) model efficiency coefficient, wavelet power spectrum, and GCI calculation. Statistical and physical-based skill metrics are employed to quantifying information loss to evaluate a set of domain resolutions. Grid independence studies have …

Utilizing Deep Learning Methods In The Identification And Synthesis Of Gene Regulations, Jiandong Wang

Theses and Dissertations

Gene expression is the fundamental differentiation and development process of life. Although all cells in an organism have essentially the same DNA, cell types and activities vary due to changes in gene expression. Gene expression can be influenced by many gene regulations. RNA editing contributes to the variety of RNA and proteins by allowing single nucleotide substitution. Reverse transcription can alter the expression status of genes by inducing genetic diversity and polymorphism via novel insertions, deletions, and recombination events. Gene regulation is critical to normal development because it enables cells to respond rapidly to environmental changes. However, identifying gene regulations …

Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Background: The removal of hair and ruler marks is critical in handcrafted image analysis of dermoscopic skin lesions. No other dermoscopic artifacts cause more problems in segmentation and structure detection. Purpose: The aim of the work is to detect both white and black hair, artifacts and finally inpaint correctly the image. Method: We introduce a new algorithm: SharpRazor, to detect hair and ruler marks and remove them from the image. Our multiple-filter approach detects hairs of varying widths within varying backgrounds, while avoiding detection of vessels and bubbles. The proposed algorithm utilizes grayscale plane modification, hair enhancement, segmentation using tri-directional …

Nftdisk: Visual Detection Of Wash Trading In Nft Markets, Xiaolin Wen, Yong Wang, Xuanwu Yue, Feida Zhu, Min Zhu

Research Collection School Of Computing and Information Systems

With the growing popularity of Non-Fungible Tokens (NFT), a new type of digital assets, various fraudulent activities have appeared in NFT markets. Among them, wash trading has become one of the most common frauds in NFT markets, which attempts to mislead investors by creating fake trading volumes. Due to the sophisticated patterns of wash trading, only a subset of them can be detected by automatic algorithms, and manual inspection is usually required. We propose NFTDisk, a novel visualization for investors to identify wash trading activities in NFT markets, where two linked visualization modules are presented: a radial visualization module with …

Data-Driven Modeling Of Student Performance In The Time Of Distance Learning, Iman Saad Megdadi

Theses

One of the important aspects that all academic institutions work towards improving is Student Performance. It is obviously the primary indicator of success or failure of institutions. Student performance predictions are vital to instructors and educational decision makers to help, across all levels, tailor learning according to the students’ needs. Therefore, it is essential for Higher Education Institutions to predict student performance in distance learning which has been, and remains, the primary method of learning in some countries due to Corona Virus pandemic. For this reason, this research is going to predetermine a fitting definition of student performance in time …

Cyclic Behavior Of Transitional Fine-Grained Soils In Northern Willamette Valley, Frank Jarman

Civil and Environmental Engineering Master's Project Reports

As discussed within studies from Idriss and Boulanger (2008) and Bray and Sancio (2006), the undrained cyclic shear behavior of low-plasticity fine-grained soils will transition between liquefaction (sand-like behavior) to cyclic softening (clay-like behavior) over a narrow range of plasticity index (PI). Despite not being sufficiently understood, the cyclic behavior of low plasticity silts has become an increasingly important field of study due to the significant impact it has on ground deformations and infrastructure failure in areas that are seismically active. Laboratory tests were performed on soils by third party consultants on a site located in the northern Willamette Valley, …

Measuring Radiation Protection: Partners From Across The Nuclear Enterprise Evaluate The Radiation Protection Of Us Army Vehicles, Andrew W. Decker, Robert Prins

Faculty Publications

Recent mounting nuclear threats and postures from adversary nation-states, such as Russia, China, North Korea, and Iran, represent a clear danger to the interests and security of the United States of America and its Allies. To meet these threats, the 2022 Nuclear Posture Review requires the Department of Defense (DoD) to design, develop, and manage a combat-credible U.S. military which, among other prioritizations, is survivable. A survivable force can generate combat power despite adversary attacks. As such, the US Army must prepare today to set the conditions for successful conventional warfare on the nuclear battlefields of tomorrow. Our Army cannot …

Unleash The Heat: Exploring Geothermal Energy Perspectives And Energy Literacy In São Miguel, Azores, Lena Mcdonough

Independent Study Project (ISP) Collection

The green energy transition is moving ahead in EU countries at very different paces, and there are some key challenges that all regions currently face in trying to phase fossil fuels out of their energy mixes. One of these challenges is that most regions simply cannot harness enough renewable energy sources and simultaneously have the storage technology for creating a baseload power source as reliable as oil, coal and natural gas. That is, unless you sit in the middle of the Atlantic Ocean on the boundary of three tectonic plates, with a continuous and reliable renewable energy source beneath your …

Effects Of Various Dietary Carbohydrate Sources On The Growth Performance And Body Composition Of The Dog Conch, Laevistrombus Canarium, Jen-Hong Chu

Journal of Marine Science and Technology–Taiwan

This study investigates the effects of dietary supplementation with various carbohydrate sources on the growth and dietary nutrient utilization efficiency of a 0.72-g dog conch, Laevistrombus canarium. Five treatment diets had supplementation with alpha-starch (Sta), dextrin (Dex), pullulan gum (Pg), xanthan gum (Xg), and carboxymethyl cellulose (CMC). At the end of the feeding trial, the best growth performance (weight gain, 442.23%) and diet efficiency (protein efficiency ratio, 1.25, and feed conversion ratio [FCR], 2.04) were exhibited by the dog conch fed the Sta diet, whereas the lowest growth performance was observed in the dog conch fed the Xg and CMC …

Cost Advantages Of Far East/Europe Trunk Route Deployment With Port Selection In East Asia, Tai Hui-Huang, Chang Chin-Wei

Journal of Marine Science and Technology–Taiwan

To cater to the gradually increasing sizes of ships, several traditional container ports in East Asia built deep-water wharves to attract shipping carriers to berth, a decision that is considered highly reasonable because it allows for shipping carriers to gain a cost advantage. For traditional Far East/Europe (F/E) trunk routes, shipping carriers must deploy vessels that are large enough at hub ports to maintain low transshipment costs. However, for a port to attract shipping carriers, it should be able to first meet the cargo demand of these carriers. The port would also need to improve the loading ratio to enjoy …

Influence Of Vacuum Condition On Rapid Chloride Migration (Rcm) Test For Chloride Penetration Resistance Of Concrete, Chih-Yen Lin, Chun-Fu Chang, Chung-Chia Yang

Journal of Marine Science and Technology–Taiwan

NT Build 492 regulates that the pressure be set at 7.5–37.5 torr and be maintained for 3 h for vacuum processing. This large range of acceptable vacuum pressure is awkward for research, and 3 h of pump-down time may be excessive. In this study, vacuum conditions were divided into vacuum pressure and pump-down time groups: various vacuum pressures and pump-down times were used to preprocess specimens to explore the effect of vacuum conditions on the RCM test. The salt ponding test was also conducted to identify the optimal vacuum conditions. It is shown that the relationship between vacuum pressure and …

Exhaust Noise Elimination Using Silencers Fortified With Perforated Tubes, Extended Tubes, Penetrable Resin Inlet And Orifice Plate, Min-Chie Chiu, Ho-Chih Cheng

Journal of Marine Science and Technology–Taiwan

Pneumatic equipment in marine diesel engine and associated piping system often emit extremely high level of noises when releasing pressure. Concerning the crew’s hearing health, discovering an efficient noise silencing device becomes essential. A silencer fortified with extended tubes, perforated tubes, orifice plate, and penetrable resin inlet is presented in order to competently dampen the blown-up noises. A simplified objective function by means of FEM, Artificial Neural Networks (ANNs), and a Genetic Algorithm (GA) is established to enable the numerical calculation when using a finite element method. Three silencer designs, silencer A (with element A, a penetrable resin inlet), B …

Deep Learning–Based, Oceantdlx Sea Ice Detection Model For Sar Image, Liu Lin, Li Wanwu, Li Hang, Sun Yi

Journal of Marine Science and Technology–Taiwan

This study constructs four deep-learning OceanTDLx series models and uses a WinR-AdaGrad gradient descent algorithm to train and optimize the constructed models. Through an analysis of the loss, accuracy, and time consumption of the four models (i.e., OceanTDL2, OceanTDL3, OceanTDL5 and OceanTDL8), we reveal that the models’ performance does not improve when the number of layers is increased and that OceanTDL5 provides the optimal performance. OceanTDL5 is compared with OceanTDA9 (a model that we previously constructed), and the curves for training loss_batch and training accuracy_batch indicate that OceanTDL5 is more suitable than OceanTDA9 for detecting distributed targets, particularly semi-melted sea …

Application Of Unmanned Aerial Vehicle–Based Infrared Images In Determining Characteristics Of Sea Surface Temperature Distribution, Hsing-Yu Wang, Hui-Ming Fang, Yun-Chih Chiang

Journal of Marine Science and Technology–Taiwan

This study investigated the temperature field of a body of water by using rotary-wing unmanned aerial vehicles (DJI Mavic 2 Enterprise Dual) comprising visible light and infrared cameras to determine sea temperature distribution. With a flight height of 150 m, image overlap of 80%, and image resolution of 4.75 cm/pixel, the proposed method was more effective than the conventional portable conductivity–temperature–depth device in rapidly measuring sea surface temperature and determining sea temperature distribution. The discharged heated water of the Hoping Power Plant traveled 100–330 m from the wastewater outfall and then gradually diffused in the range of 100–490 m before …

A Cloud Based Model Symbiotic Organism Search Algorithm For Placement Of Distributed Energy Resources In The Electrical Secondary Distribution Networks, Shamte Kawambwa, Daudi Mnyanghwalo

Tanzania Journal of Science

Abstract The increased penetration of distributed energy resources (DERs) technologies to residential users has fostered the need for DERs integration and control methods in the secondary distribution networks (SDN). In order to reap the potential advantages of DERs and achieve their inclusion in the electrical power system while avoiding their negative impacts, the DERs should be optimally placed and sized. Considering the nature of electrical networks and DER operations, the DERs placement is a nondeterministic polynomial hard (NP-hard) optimization problem. Metaheuristic algorithms are efficient for solving DER placement problems. Metaheuristic algorithms for DER placement in SDN involve high computational effort, …