Engineering Commons^™

Design And Characterization Of A Novel Eef2k Degrader With Potent Therapeutic Efficacy Against Triple-Negative Breast Cancer, Changxin Zhong, Rongfeng Zhu, Ting Jiang, Sheng Tian, Xiaobao Zhao, Xiaoya Wan, Shilong Jiang, Zonglin Chen, Rong Gong, Linhao He, Jin-Ming Yang, Na Ye, Yan Cheng

Markey Cancer Center Faculty Publications

Dysregulated eEF2K expression is implicated in the pathogenesis of many human cancers, including triple-negative breast cancer (TNBC), making it a plausible therapeutic target. However, specific eEF2K inhibitors with potent anti-cancer activity have not been available so far. Targeted protein degradation has emerged as a new strategy for drug discovery. In this study, a novel small molecule chemical is designed and synthesized, named as compound C1, which shows potent activity in degrading eEF2K. C1 selectively binds to F8, L10, R144, C146, E229, and Y236 of the eEF2K protein and promotes its proteasomal degradation by increasing the interaction between eEF2K and the …

Assessing Blockchain’S Potential To Ensure Data Integrity And Security For Ai And Machine Learning Applications, Aiasha Siddika

Master of Science in Information Technology Theses

The increasing use of data-centric approaches in the fields of Machine Learning and Artificial Intelligence (ML/AI) has raised substantial issues over the security, integrity, and trustworthiness of data. In response to this challenge, Blockchain technology offered a promising and practical solution, as its inherent characteristics as a decentralized distributed ledger, coupled with cryptographic processes, offer an unprecedented level of data confidentiality and immutability. This study examines the mutually beneficial connection between Blockchain technology and ML/AI, using Blockchain's inherent capacity to protect against unauthorized alterations of data during the training phase of ML models. The method involves building valid blocks of …

Melanoma Detection Based On Deep Learning Networks, Sanjay Devaraneni

Electronic Theses, Projects, and Dissertations

Our main objective is to develop a method for identifying melanoma enabling accurate assessments of patient’s health. Skin cancer, such as melanoma can be extremely dangerous if not detected and treated early. Detecting skin cancer accurately and promptly can greatly increase the chances of survival. To achieve this, it is important to develop a computer-aided diagnostic support system. In this study a research team introduces a sophisticated transfer learning model that utilizes Resnet50 to classify melanoma. Transfer learning is a machine learning technique that takes advantage of trained models, for similar tasks resulting in time saving and enhanced accuracy by …

Automated Medical Notes Labelling And Classification Using Machine Learning, Akhil Prabhakar Thota

Electronic Theses, Projects, and Dissertations

The amount of data generated in medical records, especially in a modern context, is growing significantly. As the amount of data grows, it is very useful to classify the data into relevant classes for further interventions. Different methods that are not automated are very time-consuming and require manual effort have been tried for this before.

Recently deep learning has been used for this task but due to the complexity of the dataset, specifically due to inter-class similarities in the dataset and specific terminology having different meanings in medical contexts has caused significant problems in having a definitive approach to medical …

Improving Credit Card Fraud Detection Using Transfer Learning And Data Resampling Techniques, Charmaine Eunice Mena Vinarta

Electronic Theses, Projects, and Dissertations

This Culminating Experience Project explores the use of machine learning algorithms to detect credit card fraud. The research questions are: Q1. What cross-domain techniques developed in other domains can be effectively adapted and applied to mitigate or eliminate credit card fraud, and how do these techniques compare in terms of fraud detection accuracy and efficiency? Q2. To what extent do synthetic data generation methods effectively mitigate the challenges posed by imbalanced datasets in credit card fraud detection, and how do these methods impact classification performance? Q3. To what extent can the combination of transfer learning and innovative data resampling techniques …

Quiz Web Application, Dipti Rathod

Electronic Theses, Projects, and Dissertations

The Quiz web application is designed to facilitate the process of quiz creation and participation. This web application mainly consists of three roles: Admin, Instructor, and Student. Each role has specific features, functionalities, and permissions. With a user-friendly interface, the admin role can handle the departments, courses, and instructors. This web application also ensures smooth quiz management, allowing the instructors to schedule the upcoming quizzes, create the questions, and manage the students with ease. Student roles have features like taking quizzes and seeing their results. Additionally, this web application includes a significant feature to prevent cheating during online tests, ensuring …

Enhancing Accident Investigation Using Traffic Cctv Footage, Aksharapriya Peddi

Electronic Theses, Projects, and Dissertations

This Culminating Experience Project investigated how the densenet-161 model will perform on accident severity prediction compared to proposed methods. The research questions are: (Q1) What is the impact of usage of augmentation techniques on imbalanced datasets? (Q2) How will the hyper parameter tuning affect the model performance? (Q3) How effective is the proposed model compared to existing work? The findings are: Q1. The effectiveness of our model depends on the implementation of augmentation techniques that pay attention to handling imbalanced datasets. Our dataset poses a challenge due to distribution of classes in terms of accident severity. To address this challenge …

1-Methyl-4-Phenyl-1,2,3,6-Tetrahydropyridine (Mptp)-Treated Adult Zebrafish As A Model For Parkinson’S Disease, Emmeline Bagwell

All Theses

The use of adult zebrafish, Danio rerio, as a model for human neurodegenerative diseases has proven valuable in pharmaceutical development and genetic disease research due to their high genetic homology to humans, cost-effective husbandry, and quick life cycle breeding times. Despite their promise, most zebrafish research has focused on embryonic stage organisms, primarily due to the ease of direct handling protocols and rapid progression through developmental stages. Recognizing the limitations of early-stage organisms in modeling adult diseases, recent efforts have shifted the applicability of zebrafish models, particularly for Parkinson's Disease, due to the nature of the disease impacting patients 55 …

Enhancing Peanut Harvesting: Evaluating Factors That Influence Yield And Developing A Web-Based Field Drying Forecast Tool, Charles Burkett

All Theses

Peanuts have one of the largest economic impacts of agronomic crops in the State of South Carolina. Peanut harvest operations involve several steps (digging, curing, combining) using equipment unique to peanut production, including peanut digger/shaker/inverters. This thesis evaluates several aspects of peanut harvest operations, including how precision agriculture technologies can enhance decision-making and enhance production. Several studies were conducted to analyze how various aspects of peanut harvesting operations contribute to decrease losses in yield and revenue. The first study evaluated the influence of operator experience on mean absolute guidance line deviation during peanut digging operations and the associated effects on …

Barriers To Integrating Magnetic Resonance Imaging Systems In Emergency Medical Service Ambulances For Stroke Care, Arvind Kolangarakath

All Theses

Stroke is a life-threatening condition that can cause permanent damage by stopping blood flow in the brain. Quick and precise intervention is imperative, as every second lost increases tissue deterioration and impacts patient outcomes. Several technological advancements such as Magnetic Resonance Imaging (MRI), have revolutionized stroke care by enabling more accurate and quicker diagnoses in hospitals. Portable head MRI scanners with lower magnetic fields are a recent innovation capable of providing neuroimaging at the point of care within hospital settings. Integrating such a device into ambulances could potentially enhance stroke care during transit, facilitating prompt diagnosis and prognosis. However, few …

Creation And Validation Of A Novel Bayesian Calibration Method With Griddy Gibbs Sampling, Hannah Stewart

All Theses

Computer models of physical systems are widely used in lieu of, or in tandem with, experimental testing. It is critical to verify the accuracy of computer models through the process of calibration. Typical calibration methods are often computationally expensive and therefore cannot be performed in real time. This thesis presents a novel Bayesian calibration method using a Griddy Gibbs sampling algorithm to improve calibration speeds. This method was verified in two applications: a location-dependent dataset in the heat transfer analysis of an engine piston, and time-dependent tire forces in a drum test. The proposed method was directly compared to a …

Detection Of Myofascial Trigger Points With Ultrasound Imaging And Machine Learning, Benjamin Formby

All Theses

Myofascial Pain Syndrome (MPS) is a common chronic muscle pain disorder that affects a large portion of the global population, seen in 85-93% of patients in specialty pain clinics [10]. MPS is characterized by hard, palpable nodules caused by a stiffened taut band of muscle fibers. These nodules are referred to as Myofascial Trigger Points (MTrPs) and can be classified by two states: active MTrPs (A-MTrPs) and latent MtrPs (L-MTrPs). Treatment for MPS involves massage therapy, acupuncture, and injections or painkillers. Given the subjectivity of patient pain quantification, MPS can often lead to mistreatment or drug misuse. A deterministic way …

Cyber-Threat Detection Strategies Governed By An Observer And A Neural-Network For An Autonomous Electric Vehicle, Douglas Scruggs

All Theses

A pathway to prevalence for autonomous electrified transportation is reliant upon accurate and reliable information in the vehicle’s sensor data. This thesis provides insight as to the effective cyber-attack placements on an autonomous electric vehicle’s lateral stability control system (LSCS). Here, Data Integrity Attacks, Replay Attacks, and Denial-of-Service attacks are placed on the sensor data describing the vehicle’s actual yaw-rate and sideslip angle. In this study, there are three different forms of detection methods. These detection methods utilize a residual metric that incorporate sensor data, a state-space observer, and a Neural-Network. The vehicle at hand is a four-motor drive autonomous …

Custom-Designed And Collaborative Unmanned Systems With Learning-Based Applications, Robert Zanone

All Theses

This paper presents a culmination of work utilizing custom-designed autonomous vehicles and learning based simulations applied to real world applications across three distinct research domains. The first focuses on deploying autonomous drones in an agricultural setting for plant phenotyping. A telescoping arm is used to deploy a camera into the plant foilage for under-the-canopy imaging. The system utilizes on-board image processing to identify early-stage issues such as diseases, bacteria, and pests in crop plants to provide data for crop loss mitigation. The system takes advantage of the maneuverability of drones allowing for quick random sampling when traversing large areas.

In …

Material World, Nicole Weldy

All Theses

My thesis, Material World, delves into the use of the crochet unit as a construction technique for building forms. Through this, I aim to organize different materials in a way that responds to the challenges posed by the physical world. My artistic process is centered around honoring the inherent qualities of thread and uses these qualities to create form, lightness, and linearity. At the same time, I remain receptive to transformative processes such as combining three-dimensional (3D) printed lines and lace stiffener to push the boundaries of what thread can do. By combining manual craftsmanship with technology materialized as …

Safe Navigation Of Quadruped Robots Using Density Functions, Andrew Zheng

All Theses

Safe navigation of mission-critical systems is of utmost importance in many modern autonomous applications. Over the past decades, the approach to the problem has consisted of using probabilistic methods, such as sample-based planners, to generate feasible, safe solutions to the navigation problem. However, these methods use iterative safety checks to guarantee the safety of the system, which can become quite complex. The navigation problem can also be solved in feedback form using potential field methods. Navigation function, a class of potential field methods, is an analytical control design to give almost everywhere convergence properties, but under certain topological constraints and …

Development Of A User-Friendly Shelf-Life Model To Evaluate The Suitability Of Sustainable Materials In Roasted And Ground Coffee Fractional Packs, Matthew Baxley

All Theses

Roasted and ground coffee is a shelf stable product yet quite sensitive to oxidative staling. A consumer acceptance-based shelf-life modeling system was proposed with intent for the rapid determination of suitable coffee packages. This model requires as input the oxygen consumption rate (OCR) of the coffee, barrier values of packages, and the size of the packaging. Within the time period tested, it was shown that this model accurately predicted the oxygen uptake of coffee over time. Four bio-based packaging systems with barrier layers including mPLA, mPE, mcellophane, and paper were compared against a control (mPET). These materials displayed a range …

Experimental Investigation Of Low Thermal Inertia Thermal Barrier Coatings For Spark Ignition Engines, John Gandolfo

All Theses

The application of thermal barrier coatings (TBCs) in spark ignition (SI) engines has historically been avoided due to the knock penalty associated with higher surface temperatures induced by the ceramic layer. However, advances in low thermal inertia coatings (i.e., temperature swing coatings) that combine low thermal conductivity with low volumetric heat capacity can prevent excessively high surface temperatures during the intake stroke and reduce or avoid knock while improving performance and efficiency. This thesis experimentally evaluates the effectiveness of these low thermal inertia coatings in a single-cylinder research engine representative of modern SI engines.

First, four pistons coated with a …

Medical Simulation-Based Sensor Methods For Ultrasound-Guided Dialysis Cannulation Skill Assessment, Devansh Shukla

All Theses

End-stage kidney disease (EKSD) is the final, permanent stage of chronic kidney disease (CKD), where the body's kidneys cannot filter blood sufficiently. Hemodialysis treats ESKD by filtering wastes and water from your blood externally via a dialyzer. Patients on hemodialysis require a vascular access, typically an arteriovenous fistula (AVF) or arteriovenous graft (AVG) for dialysis, which is used three times a week for about four hours a session. These life-saving therapies can be quite tedious, especially for elderly patients and patients with co-morbidities. As such, successful cannulation is extremely important to ensure the longevity of the patient's vascular access and …

Convolution And Autoencoders Applied To Nonlinear Differential Equations, Noah Borquaye

Electronic Theses and Dissertations

Autoencoders, a type of artificial neural network, have gained recognition by researchers in various fields, especially machine learning due to their vast applications in data representations from inputs. Recently researchers have explored the possibility to extend the application of autoencoders to solve nonlinear differential equations. Algorithms and methods employed in an autoencoder framework include sparse identification of nonlinear dynamics (SINDy), dynamic mode decomposition (DMD), Koopman operator theory and singular value decomposition (SVD). These approaches use matrix multiplication to represent linear transformation. However, machine learning algorithms often use convolution to represent linear transformations. In our work, we modify these approaches to …

Surface Antibody Changes Protein Corona Both In Human And Mouse Serum But Not Final Opsonization And Elimination Of Targeted Polymeric Nanoparticles, Sara Capolla, Federico Colombo, Luca De Maso, Prisca Mauro, Paolo Bertoncin, Thilo Kähne, Alexander Engler, Luis Núñez, Gustavo Larsen, Et Al.

Department of Chemical and Biomolecular Engineering: Faculty Publications

Background: Nanoparticles represent one of the most important innovations in the medical field. Among nanocarriers, polymeric nanoparticles (PNPs) attracted much attention due to their biodegradability, biocompatibility, and capacity to increase efficacy and safety of encapsulated drugs. Another important improvement in the use of nanoparticles as delivery systems is the conjugation of a targeting agent that enables the nanoparticles to accumulate in a specific tissue. Despite these advantages, the clinical translation of therapeutic approaches based on nanoparticles is prevented by their interactions with blood proteins. In fact, the so-formed protein corona (PC) drastically alters the biological identity of the particles. Adsorbed …

Aicropcam: Deploying Classification, Segmentation, Detection, And Counting Deep-Learning Models For Crop Monitoring On The Edge, Nipuna Chamara, Geng (Frank) Bai, Yufeng Ge

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Precision Agriculture (PA) promises to meet the future demands for food, feed, fiber, and fuel while keeping their production sustainable and environmentally friendly. PA relies heavily on sensing technologies to inform site-specific decision supports for planting, irrigation, fertilization, spraying, and harvesting. Traditional point-based sensors enjoy small data sizes but are limited in their capacity to measure plant and canopy parameters. On the other hand, imaging sensors can be powerful in measuring a wide range of these parameters, especially when coupled with Artificial Intelligence. The challenge, however, is the lack of computing, electric power, and connectivity infrastructure in agricultural fields, preventing …

Determining The Presence And Size Of Shoulder Lesions In Sows Using Computer Vision, Shubham Bery, Tami M. Brown-Brandl, Bradley T. Jones, Gary A. Rohrer, Sudhendu Raj Sharma

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Shoulder sores predominantly arise in breeding sows and often result in untimely culling. Reported prevalence rates vary significantly, spanning between 5% and 50% depending upon the type of crate flooring inside a farm, the animal’s body condition, or an existing injury that causes lameness. These lesions represent not only a welfare concern but also have an economic impact due to the labor needed for treatment and medication. The objective of this study was to evaluate the use of computer vision techniques in detecting and determining the size of shoulder lesions. A Microsoft Kinect V2 camera captured the top-down depth and …

An Exhaustive Review Of Neutrosophic Logic In Addressing Image Processing Issues, Samia Mandour

Neutrosophic Systems with Applications

Since the importance of images in our lives and the advancements in computer data gathering methods, anyone can collect a large number of images, but most of them cannot be processed manually. Image processing therefore becomes appealing since various types of data may be represented and processed digitally. Image processing has become the most popular processing method, employed in security camera films, healthcare images, images from remote sensors, and naturalistic image/videos because of fast computers and processors. In order to raise cognitive function and speed up decision-making, image processing is crucial to many information access systems. Since ambiguity now permeates …

Neural Airport Ground Handling, Yaoxin Wu, Jianan Zhou, Yunwen Xia, Xianli Zhang, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

Airport ground handling (AGH) offers necessary operations to flights during their turnarounds and is of great importance to the efficiency of airport management and the economics of aviation. Such a problem involves the interplay among the operations that leads to NP-hard problems with complex constraints. Hence, existing methods for AGH are usually designed with massive domain knowledge but still fail to yield high-quality solutions efficiently. In this paper, we aim to enhance the solution quality and computation efficiency for solving AGH. Particularly, we first model AGH as a multiple-fleet vehicle routing problem (VRP) with miscellaneous constraints including precedence, time windows, …

Affordances Of Mobile Technology To Facilitate Learning In Undergraduate Thermal-Fluid Sciences, Maeve Raphael Bakic

Boise State University Theses and Dissertations

In recent years, the pandemic has affected learning at all levels, in particular higher education, where higher levels of independence and self-motivation are required during distance learning. In engineering in particular, distance learning adds another degree of difficulty to an already complex field. Comprehension in engineering requires the repeated use of diagrams, high-level charts, and practice problems. Mobile devices, combined with a technology-enhanced curriculum, provide an excellent platform for learning in engineering as it allows for clear illustration and the transfer of complex ideas at any time and place. In alignment with the social-constructivist framework, these facets of mobile technology …

Role Of Mechanical Signaling In Bone Tissue, Scott Aaron Birks

Boise State University Theses and Dissertations

As the global population ages and life expectancy continues to rise, osteoporosis continues to be a growing worldwide health concern. The International Osteoporosis Foundation reports 1 in 3 women over the age of 50 years and 1 in 5 men worldwide will experience osteoporotic fractures in their lifetime, costing between 5 and 6.5 trillion USD annually in Canada, Europe, and the United States alone. The need for preventative measures to reduce age-related bone loss is clear, not only to improve quality of life for countless individuals but also to relieve the economic burden this condition imposes.

Exercise is a proven …

2023 Summer-Fall Graduate Recognition Program, Propulsion Research Center, Robert Frederick

PRC Graduate Recognition

This program includes the graduate recognition program for summer and fall 2023. Includes photographs, upcoming events, recent publications, and student profiles.

A System Theoretic Process Analysis Framework And Model Based Approach For Resilient Space Architecture Design, Eric T. Sommer

Theses and Dissertations

As the capabilities provided by space-based systems offer significant contributions toward defense applications, potential adversaries stand to gain significant value in disrupting them. Therefore, the United States must pursue the development and operation of resilient space architectures, capable of delivering capabilities in the face of disruptions. To support this development, systems engineering methods require innovation to effectively ensure design of complex space architectures to meet their objectives. This thesis recommends and demonstrates a System-Theoretic Process Analysis (STPA) framework to qualitatively analyze space architectures. The analysis outputs identify design considerations, requirements, and constraints required for resilience. To enable a model-based systems …

Synergistic Strategies In Sinter-Based Material Extrusion (Mex) 3d Printing Of Copper: Process Development, Product Design, Predictive Maps And Models., Kameswara Pavan Kumar Ajjarapu

Electronic Theses and Dissertations

3D printing pure copper with high electrical conductivity and exceptional density has long been challenging. While laser-based additive manufacturing technologies suffered due to copper's highly reflective nature towards laser beams, parts printed via binder-assisted technologies failed to reach over 90% IACS (International Annealed Copper Standard), electrical conductivity. Although promising techniques such as binder jetting, filament, and pellet-based 3D printing that can print copper exist, they however still face difficulties in achieving both high sintered densities and electrical conductivity values. This is due to a lack of comprehensive understanding of property evolution from green to sintered states and the strategies that …