Computational Engineering Commons^™

Strainer: State Transcript Rating For Informed News Entity Retrieval, Thomas M. Gerrity

Master's Theses

Over the past two decades there has been a rapid decline in public oversight of state and local governments. From 2003 to 2014, the number of journalists assigned to cover the proceedings in state houses has declined by more than 30\%. During the same time period, non-profit projects such as Digital Democracy sought to collect and store legislative bill and hearing information on behalf of the public. More recently, AI4Reporters, an offshoot of Digital Democracy, seeks to actively summarize interesting legislative data.

This thesis presents STRAINER, a parallel project with AI4Reporters, as an active data retrieval and filtering system for …

Evaluating And Improving Domain-Specific Programming Education: A Case Study With Cal Poly Chemistry Courses, Will Fuchs

Master's Theses

Programming is a key skill in many domains outside computer science. When used judiciously, programming can empower people to accomplish what might be impossible or difficult with traditional methods. Unfortunately, students, especially non-CS majors, frequently have trouble while learning to program. This work reports on the challenges and opportunities faced by Physical Chemistry (PChem) students at Cal Poly, SLO as they learn to program in MATLAB. We assessed the PChem students through a multiple-choice concept inventory, as well as through “think-aloud” interviews. Additionally, we examined the students’ perceptions of and attitudes towards programming. We found that PChem students are adept …

Dynamic Response Of Elastic Two-Story Steel Moment Frame Scaled Structure Equipped With Viscous Dampers, Garrett L. Barker, Alexander L. Poirier

Architectural Engineering

The authors of this report are Architectural Engineering undergraduate students at California Polytechnic State University, San Luis Obispo. Damping is a complex, experimentally derived value that is affected by many structural properties and has a profound effect on the dynamic response of structures. Deducing the inherent damping of a steel moment frame and affecting the damping ratio with viscous dampers are two topics explored in this paper. Dampers are commonly implemented in resilient structures that perform better in a design basis earthquake, reducing the seismic cost and downtime. Undergraduate coursework does not delve into the factors that affect damping and …

Single-Pass Inline Pipeline 3d Reconstruction Using Depth Camera Array, Zhexiong Shang, Zhigang Shen

Department of Construction Engineering and Management: Faculty Publications

A novel inline inspection (ILI) approach using depth cameras array (DCA) is introduced to create high-fidelity, dense 3D pipeline models. A new camera calibration method is introduced to register the color and the depth information of the cameras into a unified pipe model. By incorporating the calibration outcomes into a robust camera motion estimation approach, dense and complete 3D pipe surface reconstruction is achieved by using only the inline image data collected by a self-powered ILI rover in a single pass through a straight pipeline. The outcomes of the laboratory experiments demonstrate one-millimeter geometrical accuracy and 0.1-pixel photometric accuracy. …

Meta-Algorithms In Machine Learning, Vishnu Pendyala

Open Educational Resources

This presentation explores how to make the best of models impacted by bias and variance. Meta-learning minimizes loss. Ensemble methods, including Bagging, Adaboost, Random Forest, Gradient Boosting, and Stacking, are discussed. These methods perturb data (X or Y) using techniques like bootstrap sampling, k-fold sampling, weighted sampling, and random subspaces. Models are generated in parallel or sequentially, with aggregation strategies such as mean, mode, weighted response, and metamodel. The presentation also touches upon deep learning and one-shot learning, and explains how distances become less meaningful in high dimensions.

More details: https://events.vtools.ieee.org/m/315184

Video Recording: https://ieeetv.ieee.org/video/meta-algorithms-in-machine-learning

Semantic Segmentation To Extract Coronary Arteries In Invasive Coronary Angiograms, Chen Zhao, Robert Bober, Haipeng Ang, Jinshan Tang, Minghao Dong, Chaoyang Zhang, Zhuo He, Weihua Zhou, Et. Al.

Michigan Tech Publications, Part 1

Accurate semantic segmentation of each coronary artery using invasive coronary angiography (ICA) is important for stenosis assessment and coronary artery disease (CAD) diagnosis. In this paper, we propose a multi-step semantic segmentation algorithm based on analyzing arterial segments extracted from ICAs. The proposed algorithm firstly extracts the entire arterial binary mask (binary vascular tree) using a deep learning-based method. Then we extract the centerline of the binary vascular tree and separate it into different arterial segments. Finally, by extracting the underlying arterial topology, position, and pixel features, we construct a powerful coronary artery segment classifier based on a support vector …

Implementation Of A Least Squares Method To A Navier-Stokes Solver, Jada P. Lytch, Taylor Boatwright, Ja'nya Breeden

Rose-Hulman Undergraduate Mathematics Journal

The Navier-Stokes equations are used to model fluid flow. Examples include fluid structure interactions in the heart, climate and weather modeling, and flow simulations in computer gaming and entertainment. The equations date back to the 1800s, but research and development of numerical approximation algorithms continues to be an active area. To numerically solve the Navier-Stokes equations we implement a least squares finite element algorithm based on work by Roland Glowinski and colleagues. We use the deal.II academic library , the C++ language, and the Linux operating system to implement the solver. We investigate convergence rates and apply the least squares …

A Novel Method For Sensitivity Analysis Of Time-Averaged Chaotic System Solutions, Christian A. Spencer-Coker

Theses and Dissertations

The direct and adjoint methods are to linearize the time-averaged solution of bounded dynamical systems about one or more design parameters. Hence, such methods are one way to obtain the gradient necessary in locally optimizing a dynamical system’s time-averaged behavior over those design parameters. However, when analyzing nonlinear systems whose solutions exhibit chaos, standard direct and adjoint sensitivity methods yield meaningless results due to time-local instability of the system. The present work proposes a new method of solving the direct and adjoint linear systems in time, then tests that method’s ability to solve instances of the Lorenz system that exhibit …

Finite-Difference-Time-Domain Simulation Of Ultrafast Experiments, Alpha Ma

Macalester Journal of Physics and Astronomy

The Finite-Difference-Time-Domain (FDTD) method is a numerical method that calculates electric fields or magnetic fields by interleaving them in space and time. Using a python package called “MEEP”, I was able to write optical simulations of ultrafast experiments, especially the Terahertz Pump-Probe experiments. The goal of this project was to use FDTD simulation to measure the transmission of an electro-magnetic pulse passing through a thin film of conducting material on a dielectric substrate in order to study the characteristic conductivity of potential solar cell materials.

Numerical Analysis Of Taylor Impact With Various Nose Shapes, Jean C. Santiago Padilla, Erik M. Chappell

ME 4233/6233 Fundamentals of FEA

The Taylor impact test is an experimental technique used to determine dynamic material response and to validate constitutive models used in numerical simulations. It generally consists of shooting a cylinder rod of a select material against a rigid target at different velocities. After impact, the plastic deformation of the cylinder is recorded and is directly compared to numerical predictions. Another application for Taylor impact was proposed by Li et al. (2021) where the nose shape of the cylinder is modified to create different loading environments that can test electronic equipment in penetration weapons. FEA models where designed in ABAQUS/Explicit to …

Human-Centered Explainable Artificial Intelligence For Anomaly Detection In Quality Inspection: A Collaborative Approach To Bridge The Gap Between Humans And Ai, Srikanth Vemula

Theses & Dissertations

In the quality inspection industry, the use of Artificial Intelligence (AI) continues to advance to produce safer and faster autonomous systems that can perceive, learn, decide, and act independently. As observed by the researcher interacting with the local energy company over a one-year period, these AI systems’ performance is limited by the machine’s current inability to explain its decisions and actions to human users. Especially in energy companies, eXplainable-AI (XAI) is critical to achieve speed, reliability, and trustworthiness with human inspection workers. Placing humans alongside AI will establish a sense of trust that augments the individual’s capabilities at the workplace. …

Using Bluetooth Low Energy And E-Ink Displays For Inventory Tracking, David Whelan

Computer Science and Computer Engineering Undergraduate Honors Theses

The combination of Bluetooth Low energy and E-Ink displays allow for a low energy wire-less display. The application of this technology is far reaching especially given how the Bluetooth Low Energy specification can be extended. This paper proposes an extension to this specification specifically for inventory tracking. This extension combined with the low energy E-Ink display results in a smart label that can keep track of additional meta data and inventory counts for physical inventory. This label helps track the physical inventory and can help mitigate any errors in the logical organization of inventory.

Speaker Diarization And Identification From Single-Channel Classroom Audio Recording Using Virtual Microphones, Antonio Gomez

Electrical and Computer Engineering ETDs

Speaker identification in noisy audio recordings, specifically those from collaborative learning environments, can be extremely challenging. There is a need to identify individual students talking in small groups from other students talking at the same time. To solve the problem, we assume the use of a single microphone per student group without any access to previous large datasets for training.

This dissertation proposes a method of speaker identification using cross-correlation patterns associated to an array of virtual microphones, centered around the physical microphone. The virtual microphones are simulated by using approximate speaker geometry observed from a video recording. The patterns …

Strain-Based Design Of Steel-Polymer-Steel Composite Pipes, Vul Thang

LSU New Orleans Theses and Dissertations

Many offshore single-wall pipelines and structural failures have occurred in the past. As a result, lives were lost, and billions of dollars were spent. In addition, natural disasters such as earthquake fault zones can cause a large volume of soil movement. This can easily damage single-wall pipelines or piles of fixed offshore platforms in the earthquake fault zone.

Currently, the single-wall pipelines are used for the offshore and onshore oil and gas industry. This research investigated the use of double-wall composite pipe steel-polymer-steel (SPS) in place of single-wall pipe to prevent such failures. The double-wall composite pipe has a larger …

Computational Study Of Dense Gas Dispersion In Urban Areas, Rasna Sharmin

All Dissertations

A series of steady-state simulations have been conducted to investigate removal of dense gas from a simple square canyon formed between two square cross-section obstacles. Due to urbanization and industrialization, there always lies a high risk of exposure to harmful pollutants which can result from accidental release of toxic gasses. Those are often denser than the atmosphere. and can easily get trapped in between buildings in urban canopies. It is important to have full understanding of flushing mechanism of dense fluid inside urban canopies by steady turbulent flow because the exposure to these toxic dense gasses can be catastrophic. There …

Characterization Of Friction Element Welding Using Finite Element Modeling, Ankit Varma

All Dissertations

Friction element welding (FEW) has been advocated as a solution to weld different materials together, with the ability to join high-strength materials for a range of thicknesses with low input energy and a short processing time. This work develops a coupled thermal-mechanical finite element model to better understand the physical mechanisms involved in the process and to predict temperature and material flow during the process. Furthermore, microstructural analysis is performed for the steel layer using a scanning electron microscope and Vickers microhardness tester to understand the variation in its grain structure and hardness. Results from the finite element model and …

Tell It Slant: Investigating The Engagement, Discourse, And Popularity Of Data Visualization In Online Communities, Emma Baker

McKelvey School of Engineering Graduate Student Theses & Dissertations

Data visualizations are increasingly accessible to people online, often to non-specialized audiences. However, what we know about how people make sense of data and engage with the visualized content is typically limited to observations from controlled user studies, sometimes with highly-specialized participants. As a result, there is a limited vocabulary to describe how visualizations as a technique of information sharing permeate organic communities. This thesis investigates how data visualization systems infiltrate online social settings and characterizes the conditions under which users engage or do not engage with them. We captured conversations on Reddit from March 2, 2021 to December 31, …

A Low-Cost, Arduino-Based Platform For Emulating Energy Harvesting In Wireless Sensor Networks, Braden A. Miller

ONU Student Research Colloquium

This paper presents an Arduino-based platform for emulating energy harvesting in Wireless Sensor Networks (WSNs) as a form of hardware-in-the-loop simulation. The platform makes use of a battery monitoring circuit and code implemented on the Arduino as an alternative to using significantly more expensive fully equipped energy harvesting nodes. Using embedded code to emulate the energy harvesting process allows for various energy harvesting models and processes to be tested using the same platform. The main contributions of this paper are the experimental data and analyses demonstrating the energy use characterization of the Arduino-based platform in a three-node relay network using …

Estimating Animal Pose Using Deep Learning A Trained Deep Learning Model Outperforms Morphological Analysis, Sanghoon Lee, Jarod Banzon, Kevin Le, Dal Hyung Kim

Computer Sciences and Electrical Engineering Faculty Research

INTRODUCTION: Analyzing animal behavior helps researchers understand their decision-making process and helper tools are rapidly becoming an indispensable part of many interdisciplinary studies. However, researchers are often challenged to estimate animal pose because of the limitation of the tools and its vulnerability to a specific environment. Over the years, deep learning has been introduced as an alternative solution to overcome these challenges.

OBJECTIVES: This study investigates how deep learning models can be applied for the accurate prediction of animal behavior, comparing with traditional morphological analysis based on image pixels.

METHODS: Transparent Omnidirectional Locomotion Compensator (TOLC), a tracking device, is used …

Introducing Normal Forms To Students: A Comparison Of Theory-First Vs. Project-First Educational Approaches, Dakota C. Cookenmaster, Jacob A. Bahn

Campus Research Month

One of the primary challenges instructors face when educating scientists and engineers is the introduction of important theory, both to show its essential nature in research as well as its practicality. This paper analyzes two pedagogical methods for the instruction of database normal forms. The first of these methods is a theory-based approach that relies on written works and practices to introduce the concept. The second of these focuses on a project-based approach which aligns with normal form standards as students implement a database schema. This paper compares these in a small study and advises an appropriate method for educators.