Engineering Commons^™

Synthetic Data Generation For Accurate, Fair, And Private Recommender Systems, Derek B. Lilienthal

Master's Theses

A notorious challenge for recommender systems on online platforms is to accurately and fairly recommend items that align with users’ preferences while retaining user privacy. These systems often rely on historical data that is partially labeled and includes incomplete user information, leading to the over-representation of majority groups and disproportionately favoring popular items. Substituting user data with synthetic data can address these concerns, but accurately replicating real-world datasets has been a challenging problem. Recent advancements in generative AI have demonstrated the impressive capabilities of diffusion models in generating realistic data across several domains. In this work, we introduce two variations …

Analyzing The Usability, Performance, And Cost-Efficiency Of Deploying Ml Models On Various Cloud Computing Platforms, Hongyu Wang

Masters Theses (Archived)

With the enhanced computing capabilities and accessibility to cloud resources, major cloud computing providers such as Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure offer Machine Learning (ML) and AI services. Their primary purpose is to provide efficiency, scalability, and adaptability in modern software development and IT operations while reducing overall costs and operational complexity. However, prospective customers of the services often question which ML-AI service will best suit their organizational and business needs. This study compares and analyzes the usability, performance, and cost-efficiency of deploying Machine Learning (ML) models across three cloud platforms: GCP, AWS, and …

Controllable Physics-Informed Latent Space For Acoustic Wave Manipulation, Tristan Shah

Master's Theses

Partial Differential Equations (PDEs) are foundational descriptive tools in scientific and engineering disciplines, enabling the exploration of phenomena from material design to climate dynamics and the propagation of pandemics and wildfires. Establishing control of PDEs, especially when the underlying phenomena are only partially observable, holds great potential for fostering technological innovations. This ambition faces considerable obstacles, as a robust sample-based solution remains elusive. Addressing this challenge, this thesis introduces a framework leveraging physics-informed machine learning (ML) to enable control of PDEs. Central to this framework is an agent, equipped with sensors to perceive its environment, that generates a low-dimensional physics-informed …

A Hybrid Model For Assessing Safety Implementation And Project Success In The Construction Industry, Aya Hassan, Ali Hassan

Civil Engineering

Construction projects are prone to accidents and injuries, necessitating a focus on implementing safety programs. However, the implementation of such programs is influenced by various factors. Developing countries often have poor safety performance in their building sectors, with limited research in this area. This study aimed to identify essential safety program activities (SPAs) specific to the building sector. Through a literature review and survey, 25 SPAs were identified and validated via a pilot survey involving building sector experts. A questionnaire survey was conducted with 105 participants from the construction industry and academia. They were then categorized into four interconnected measurements …

Synergizing Bim And Value Engineering In The Construction Of Residential Projects: A Novel Integration Framework, Ahmed Gouda Mohamed, Mohamed Ahmed Nabawy Dr

Civil Engineering

This study explores integrating Building Information Modeling (BIM) and Value Engineering (VE) to enhance cost management and project value optimization in residential construction. The primary aim is to develop a comprehensive framework that synergizes 5th Dimension Building Information Modeling (5D BIM) with VE processes to identify and evaluate the most cost-effective construction alternatives. Employing a mixed-methods approach, this research includes an extensive review of existing practices, an integrated BIM-VE framework proposal, and the application of 5D BIM principles to improve visualization, cost estimation, and scheduling. The findings reveal that integrating BIM and VE significantly enhances project efficiency, quality, and cost-effectiveness. …

Simulation Of Calcium Carbonate Nucleation Processes In Confined C-S-H Nanopores With Different Calcium-Silicon Ratios, Jiao Yu, Kerui Wang, Peixuan Yang, Mengmeng Li, Biqin Dong, Zuquan Jin, Shuxian Hong, Hongyan Ma

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Carbonation curing technology plays an important role in carbon cycling and improving the properties of cement-based materials, while the nucleation and growth mechanism of calcium carbonate (CaCO₃) is still unclear. Based on molecular dynamics simulation, the formation process and nucleation mechanism of CaCO₃ in confined C-S-H nanopores with different calcium-silicon ratios were studied. The results show that the clustering behavior of CaCO₃ in C-S-H nanopores filled with saturated CaCO₃ solution can be divided into three phases, rapid agglomeration stage, slow cluster stage, and stable cluster stage. The aggregation is mainly dependent on ionic bonding for …

Tribological Analysis Of Heat Treatments On Medical Grade Cobalt Chromium Molybdenum Alloys, Samuel Edis Bowden

Theses and Dissertations

Cobalt chromium molybdenum (CoCrMo) has many material properties that make it desirable as a medical hip implant. Due to the range of heat treatments available and the resulting material properties that are present in medical device manufacturing using CoCrMo, many implants are not able to withstand both the chemical and physical wear necessary as a hip replacement. This research looks to examine various heat treatments and their resulting properties to find a desirable heat treatment for CoCrMo in hip implant bearing surfaces. This study was accomplished by using five distinct variations of heat treatment on forged CoCrMo alloy that would …

Tribology Of Mos2 Thin Films Stabilized By A Chromium Underlayer And Max Phase, Nihal Ahmed

Theses and Dissertations

MoS2 is a popular solid lubricant with limited application at room temperature due to its’ sensitivity to atmospheric oxygen and humidity. This thesis focuses on the stabilization of molybdenum disulfide (MoS2) coatings on aluminum substrates to enhance their tribological performance at room temperature. MoS2 exhibits exceptional lubricating properties in vacuum conditions, but its reactivity with atmospheric oxygen leads to the formation of abrasive molybdenum trioxide (MoO3), restricting its effectiveness in ambient environments. This thesis investigates the effects of a Chromium underlayer and the incorporation of MAX phase (Ti3SiC2) on the tribological performance and chemical stability of MoS2 solid lubricant. Physical …

An Exploration Of Dimensionality Reduction Of Dynamics On Lie Groups Via Structure-Aware Canonical Correlation Analysis, Wooyoung Chung

Master's Theses

Incorporating prior knowledge into a data-driven modeling problem can drastically improve performance, reliability, and generalization outside of the training sample. The stronger the structural properties, the more effective these improvements become. Manifolds are a powerful nonlinear generalization of Euclidean space for modeling finite dimensions. When additionally assuming that the manifold carries (Lie) group structure, this imposes a drastically stricter global constraint. The range of their applications is very wide and includes the important case of robotic tasks. We apply this idea to Canonical Correlation Analysis (CCA). In traditional CCA one constructs a hierarchical sequence of maximal correlations of up to …

Exploring The Link Between Travel Behavior And Mental Health, Emily Kae Youngs

Theses and Dissertations

This study explores the critical link between travel behavior and mental health, focusing on young adults who have expressed suicidal ideation. By analyzing how daily activities and movement patterns impact mental well being, the research aims to explore travel related mental health approaches for individuals. The importance of this work lies in its potential to improve the quality of life for individuals by informing more personalized and effective mental health strategies. Through comprehensive data analysis and statistical modeling, the research aims to uncover insights into how travel behavior influences motivation levels and mental well-being across different neurological and physiological groups. …

Central Tracking And Billing System For Insurance Bills, Kehinde Alabi

Harrisburg University Dissertations and Theses

In this article, we introduce a new centralized billing platform designed for insurance bills including auto insurance, health insurance, home insurance, life insurance, etc. This system consolidates all bills for individual users eliminating the need for them to manage and pay bills separately. Users stand to benefit from significant time and effort savings each month, reducing the likelihood of missed payments and associated late fees. Insurance billing organizations and banks can also capitalize on timely payments and reduced physical mailings, leading to cost savings and environmental benefits. The proposed system offers users the ability to track and review their historical …

Customized Agile Project Management For Scientific Computing: Addressing Challenges And Developing A Framework, Yashesh Sakharikar

Harrisburg University Dissertations and Theses

This paper presents a novel Agile framework tailored for scientific computing projects. Identifying gaps in existing methodologies, the research emphasizes the need for adaptable solutions in this dynamic field. The proposed framework, characterized by flexibility and stakeholder engagement, addresses specific challenges posed by scientific computing endeavors. Through a comprehensive literature review, the paper highlights the limitations of generic Agile practices and positions the proposed framework as a valuable contribution. The study motivates further exploration into specialized Agile approaches, promising enhanced efficiency and success in scientific computing projects.

Reinforcement Learning Based Planning And Control For Robotic Source Seeking Inspired By Fruit Flies, Gauravkumar Koradiya

Master's Theses

In the exploration of mobile sensing agents such as robots equipped with sensors, these agents have the potential to measure unknown scalar fields, ranging from chemical concentrations to temperature fluctuations. One of the primary interests is the robots’ ability to gravitate towards the peaks or troughs of these fields, a phenomenon termed as “source seeking”. This behavior is invaluable in practical scenarios, like detecting chemical leaks or locating survivors after catastrophes. However, the challenge becomes significantly more pronounced when operating in turbulent flow fields, where the erratic nature of odorant plumes makes predictions and simulations highly unreliable. Interestingly, fruit flies …

Domain Specific Aspect Extraction For Product Design, Divyam Sobti

Master's Theses

As technology advances, computers become increasingly proficient at interpreting and translating human language into machine-understandable text. With the help of algorithms in natural language processing (NLP), machines can now translate textual data. These algorithms help identify and extract specific text components known as aspects. The aspects represent specific attributes or topics within textual data. For instance, an Amazon review states,“ This phone has good battery life but poor camera quality,” and attributes like ‘battery life’ and ‘camera quality’ represent aspects in the text. Aspect extraction is a pivotal process involving identifying and isolating key features or topics within text. This …

Balancing Results From Ai-Based Geostatistics Versus Fuzzy Inference By Game Theory Bargaining To Improve A Groundwater Monitoring Network, Masoumeh Hashemi, Richard C. Peralta, Matt Yost

Plants, Soils and Climate Student Research

An artificial intelligence-based geostatistical optimization algorithm was developed to upgrade a test Iranian aquifer's existing groundwater monitoring network. For that aquifer, a preliminary study revealed that a Multi-Layer Perceptron Artificial Neural Network (MLP-ANN) more accurately determined temporally average water table elevations than geostatistical kriging, spline, and inverse distance weighting. Because kriging is usually used in that area for water table estimation, the developed algorithm used MLP-ANN to guide kriging, and Genetic Algorithm (GA) to determine locations for new monitoring well location(s). For possible annual fiscal budgets allowing 1-12 new wells, 12 sets of optimal new well locations are reported. Each …

Healthcare Assistance Challenges-Driven Neurosymbolic Ai, Kaushik Roy

Publications

Although Artificial Intelligence technology has proven effective in providing healthcare assistance by analyzing health data, it still falls short in supporting decision-making. This deficiency largely stems from the predominance of opaque neural networks, particularly in mental health care AI applications, which raise concerns about their unpredictable and unverifiable nature. This skepticism hinders the transition from information support to decision support. This presentation will explore neurosymbolic approaches that combine neural networks with symbolic control and verification mechanisms. These approaches aim to unlock AI’s full potential by enhancing information analysis and decision-making support for healthcare assistance.

A Measure Of Interactive Complexity In Network Models, Will Deter

Northeast Journal of Complex Systems (NEJCS)

This work presents an innovative approach to understanding and measuring complexity in network models. We revisit several classic characterizations of complexity and propose a novel measure that represents complexity as an interactive process. This measure incorporates transfer entropy and Jensen-Shannon divergence to quantify both the information transfer within a system and the dynamism of its constituents’ state changes. To validate our measure, we apply it to several well-known simulation models implemented in Python, including: two models of residential segregation, Conway’s Game of Life, and the Susceptible-Infected-Susceptible (SIS) model. Our results reveal varied trajectories of complexity, demonstrating the efficacy and sensitivity …

Uas-Enhanced Rock Mass Characterization Of The Left Abutment At Madison Dam, Ennis Montana, Karl Farber

Graduate Theses & Non-Theses

Recently, advancements in drone technology for mapping rock mass features have been on the rise and are becoming more of a staple for geotechnical site investigation. The safety of humans when collecting field data is a top priority and using drones, or unmanned aerial systems (UAS), can minimize those safety risks. Creating models that depict accurate data of rock mass discontinuities and possible failure modes in inaccessible areas has its challenges, but drones can provide a way of addressing those challenges. This study involves using UAS-based data collection to capture rock mass fractures at Madison Dam just North of Ennis, …

Raw Data For M5h2r1 Origami Flasher Deployment Tests, Philip Klocke

ScholarsArchive Data

These data sets contain raw force data from the deployment tests of a case study origami Flasher.

Engineering Cell-Free Protein Synthesis Biosensors For Point Of Care Use, Tyler Jordan Free

Theses and Dissertations

Diagnostic tests can dramatically improve and save lives. Survival rates and patient outcomes related to cancer and other diseases can be improved when routine testing guides personalized treatment. Highly accurate laboratory tests exist for thousands of biomarkers, including those of interest in this dissertation, but cost and complexity limit access to life-saving lab tests in many cases throughout the world. To fill this need and increase accessibility of diagnostics, in this report we report our engineering advancements towards portable biosensors for colorimetric detection of glutamine, endocrine disrupting compounds (EDC), and pathogenic RNA which are key biomarkers in cancer treatment monitoring, …

A Comparative Illustration Of Trip- And Activity-Based Modeling Techniques, Steven Hayden Atchley

Theses and Dissertations

Activity-based travel demand models are generally considered superior to their trip-based counterparts, as activity-based models (ABMs) explicitly model individuals in contrast to the aggregate nature of trip-based models. There have been a number of comparisons between trip- and activity-based models, but these comparisons focus almost exclusively on the technical ability of the two model types, while not considering the practical benefits an ABM may or may not have to a transportation agency. This research performs a more holistic comparison between trip- and activity-based models, focused specifically on the practical differences between model types, both in terms of usability and capability …

Green Synthesis Of Carbonized Chitosan-Fe3o4-Sio2 Nano-Composite For Adsorption Of Heavy Metals From Aqueous Solutions, Dalia A. Ali Eng, Rinad Galal Ali Eng.

Chemical Engineering

Water pollution with heavy metals owing to industrial and agricultural activities have become a critical dilemma to humans, plants as well as the marine environment. Therefore, it is of great importance that the carcinogenic heavy metals present in wastewater to be eliminated through designing treatment technologies that can remove multiple pollutants. A novel green magnetic nano-composite called (Carbonized Chitosan-Fe3O4-SiO2) was synthesized using Co-precipitation method to adsorb a mixture of heavy metal ions included; cobalt (Co2+), nickel (Ni2+) and copper (Cu2+) ions from aqueous solutions. The novelty of this study was the synthesis of a new

nano-composite which was green with …

63rd Annual Rocky Mountain Conference On Magnetic Resonance

Rocky Mountain Conference on Magnetic Resonance

Final program, abstracts, and information about the 63rd annual meeting of the Rocky Mountain Conference on Magnetic Resonance, co-endorsed by the Colorado Section of the American Chemical Society and the Society for Applied Spectroscopy. Held in the Copper Conference Center, Copper Mountain, Colorado, August 4-8, 2024.

Deep Learning For Improved Data-Driven Modeling Of Soft Robots For Model Predictive Control, Daniel Gray Cheney

Theses and Dissertations

The field of soft robotics is a growing research interest due to the unique benefits of soft robots over traditional robots, such as durability, compliance, and low-cost. These benefits allow soft robots to perform a variety of tasks that would be difficult for traditional robots, such as throwing, hammering, or whole-body manipulation. However, there is a significant variety of materials, actuators, and designs used in soft robotics. While helpful for completing more tasks, this variety also makes efficient modeling and control of soft robots difficult. In this thesis, an open-source repository, Modeling for Learned Dynamics (MoLDy), is presented. This repository …

Integrated Reference Single-Cell Rna Seq Atlas Of Healthy Human Female Tissues To Expand The Computational Drug Target Discovery Approaches For Female-Directed Non-Hormonal Contraceptives, Zhanel Nugmanova

Dartmouth College Master’s Theses

The ovary is vital for fertility and the maintenance of endocrine homeostasis. It contains heterogeneous cell populations, including oocyte, granulosa, stromal, endothelial, smooth muscle, and immune cell types. Creating a harmonized dataset that enables cross-tissue comparisons, including the ovary, is essential for identifying genes specific to ovarian cell types and for facilitating drug discovery for contraception and fertility purposes. There are very few resources that allow for the assessment of the expression of potential gene targets across human and mouse tissues for female-directed non-hormonal contraceptives. This is because most of these publicly available datasets are from post-menopausal women. Through our …

Mushroom Mycelium Foam Cushioning Properties In Protective Packaging Application, Xiaojing Liu

Journal of Applied Packaging Research

Mycelium, the root structure of mushrooms, has a unique biology that can be leveraged to grow materials that self-assemble into complex, fully-formed structures. Mycelium-based composite material has developed quickly to commercial applications for textiles, packaging, and food industry for its unique biodegradable feature. However, there is little deep research on mycelium-based material cushion properties in protective packaging. This research fills the gap and examines and evaluates mushroom mycelium foam cushion performance. The mycelium-based composites in this research came from Ecovative company. Several groups of foams with the desired size and shape were grown in the lab. Samples’ density and weight …

Modular Approach To Soft Mobile Robots, Dimuthu Kodippili Arachchige

College of Computing and Digital Media Dissertations

Soft robot locomotion is a highly promising but under-researched subfield within the field of soft robotics. The compliant limbs and bodies of soft robots offer numerous benefits, including the ability to regulate impacts, tolerate falls, and navigate through tight spaces. These robots have the potential to be used for various applications, such as search and rescue, inspection, surveillance, and more. The state-of-the-art still faces many challenges, including limited degrees of freedom, a lack of diversity in gait trajectories, insufficient limb dexterity, limited payload capabilities, lack of control methods, etc. To address these challenges, this research introduces a modular approach to …

Vco Calibration Techniques And Design Of A 0.12-V Ultra-Low Supply Analog-To-Digital Converter, Shea Smith

Theses and Dissertations

Many analog-to-digital converters (ADC) quantize inputs using a voltage-controlled-oscillator (VCO). These VCO-based ADCs leverage time-domain processing to shape quantization noise and mismatch, which further increases their appeal. Despite these advantages, achieving good performance with a VCO-based ADC remains a significant challenge due to the nonlinear transfer characteristics of the voltage-to-frequency (V-F) conversion. VCO-based ADCs widely utilize coarse-fine readout to save power and hardware compared to counter-only converters. However, the timing mismatch due to the clock skew between the coarse and fine quantizers can lead to significant reconstruction errors. Chapter 2 proposes a digital calibration circuit to detect and correct coarse-fine …

Proposing A Matrix For Selecting Security Tools For Small Businesses, Nathan Jonathon Rowbotham

Theses and Dissertations

Small businesses are increasingly under threat of cybersecurity attacks. An increasingly long list of tools with different purposes and coverage are available to help. But it can be difficult to choose which tools to use, particularly for a small business that may lack financial resources, expertise, and time. Research literature focuses on providing frameworks to follow to protect a business generally. Some research considers an aspect of creating a Security Operations Center. Other research describes the creation of a Security Operations Center as a Service with all the components the researchers deemed necessary. None of the current research literature seems …

Real-Time Dynamically Feasible B-Spline Trajectory Generation For Unmanned Aircraft, David Lavae Christensen

Theses and Dissertations

Onboard aircraft systems must frequently plan dynamically feasible paths or trajectories to safely and quickly reach their goal position. Optimized B-splines are promising because they can guarantee kinematic feasibility in a computationally efficient manner and can be applied to a variety of vehicle models. However, current B-spline solutions do not adequately constrain trajectories to the physical limitation of the vehicles they are planning for, or are often too conservative. Most are also limited to path smoothing or require pre-optimized timing parameters. This thesis develops a real-time B-spline optimization-based trajectory generator capable of minimizing time while respecting the velocity, acceleration, and …