Computational Engineering Commons^™

Resources Based Planning Framework For Infrastructure Maintenance And Rehabilitation Projects, Heba Gad

Theses and Dissertations

Infrastructure maintenance and rehabilitation projects involve activities scattered over a large geographical area (e.g., scattered road segments maintenance, telecom towers maintenance program, etc.). Planning such projects require a resource-based approach that accounts for the implications of resource mobility between activities’ locations in terms of time & cost. Existing scheduling techniques fall short of addressing the unique challenges of the scattered nature of these projects in combination with organization's limited resources availability. To address this need, this research presents a resources-based planning framework for infrastructure maintenance and rehabilitation scattered projects with the objective of enhancing resources utilization achieving time and cost …

Do Plants Have The Cognitive Complexity For Sentience?, Ricard V. Solé

Animal Sentience

Are plants sentient? Like other aspects of the cognitive potential of plants, this is a controversial issue, often driven by analogies and seldom supported on solid theoretical grounds. Sentience is understood in cognitive sciences as the capacity to feel. I suggest that because of plants’ evolved adaptations to morphological plasticity, sessile nature and ecological constraints, they are unlikely to have the requisite cognitive complexity for sentience.

Machine Learning-Based Data And Model Driven Bayesian Uncertanity Quantification Of Inverse Problems For Suspended Non-Structural System, Zhiyuan Qin

All Dissertations

Inverse problems involve extracting the internal structure of a physical system from noisy measurement data. In many fields, the Bayesian inference is used to address the ill-conditioned nature of the inverse problem by incorporating prior information through an initial distribution. In the nonparametric Bayesian framework, surrogate models such as Gaussian Processes or Deep Neural Networks are used as flexible and effective probabilistic modeling tools to overcome the high-dimensional curse and reduce computational costs. In practical systems and computer models, uncertainties can be addressed through parameter calibration, sensitivity analysis, and uncertainty quantification, leading to improved reliability and robustness of decision and …

Explainable Physics-Informed Deep Learning For Rainfall-Runoff Modeling And Uncertainty Assessment Across The Continental United States, Sadegh Sadeghi Tabas

All Dissertations

Hydrologic models provide a comprehensive tool to calibrate streamflow response to environmental variables. Various hydrologic modeling approaches, ranging from physically based to conceptual to entirely data-driven models, have been widely used for hydrologic simulation. During the recent years, however, Deep Learning (DL), a new generation of Machine Learning (ML), has transformed hydrologic simulation research to a new direction. DL methods have recently proposed for rainfall-runoff modeling that complement both distributed and conceptual hydrologic models, particularly in a catchment where data to support a process-based model is scared and limited.

This dissertation investigated the applicability of two advanced probabilistic physics-informed DL …

Preserving User Data Privacy Through The Development Of An Android Solid Library, Alexandria Lim

Computer Science and Computer Engineering Undergraduate Honors Theses

In today’s world where any and all activity on the internet produces data, user data privacy and autonomy are not prioritized. Companies called data brokers are able to gather data elements of personal information numbering in the billions. This data can be anything from purchase history, credit card history, downloaded applications, and service subscriptions. This information can be analyzed and inferences can be drawn from analysis, categorizing people into groups that range in sensitivity — from hobbies to race and income classes. Not only do these data brokers constantly overlook data privacy, this mass amount of data makes them extremely …

Development Of A Computational Model To Investigate Pathways And The Effects Of Treatment In Fanconi Anemia, Sabrina Kellett

Biological Sciences Undergraduate Honors Theses

Fanconi Anemia (FA) is a rare type of anemia that is not easily studied and can have very detrimental effects. This disease compromises the bone marrow, resulting in decreased hemopoiesis. Symptoms of FA also include abnormalities in the brain and spinal cord, incorrect formation of the kidneys, abnormal formation of the heart and lungs, and a dramatically increased risk of developing cancer. FA can be caused by various mutations in any of the 22 genes that encode for proteins involved in what is called the FA DNA repair pathway. In healthy individuals, this pathway specifically repairs interstrand cross-links (ICLs) recognized …

Detecting Pathobiomes Using Machine Learning, Valerie Jackson, Valerie Jackson

Industrial Engineering Undergraduate Honors Theses

Machine learning is a field with high growth potential due to the overall continuous progressions, developments, advancements, and improvements caused by the way it is used to help interpret and use large amounts of data [1]. One type of data that can be collected and analyzed by these machine learning models is data that is associated with DNA and information that the DNA gives. The research will be focusing specifically on using machine learning technology to detect pathobiomes indicative of salmonella pork. The pathobiome associated with salmonella is very similar to others, and this causes a problem for classification/detection with …

What If Plants Compute?, Jordi Vallverdú

Animal Sentience

The unexpended cognitive capacities of plants suggest the possibility of combining them with advances in computation. It is important to explore such a new field of research despite the incompleteness of the empirical support for it.

Towards Nlp-Based Conceptual Modeling Frameworks, David Shuttleworth, Jose Padilla

Modeling, Simulation and Visualization Student Capstone Conference

This paper presents preliminary research using Natural Language Processing (NLP) to support the development of conceptual modeling frameworks. NLP-based frameworks are intended to lower the barrier of entry for non-modelers to develop models and to facilitate communication across disciplines considering simulations in research efforts. NLP drives conceptual modeling in two ways. Firstly, it attempts to automate the generation of conceptual models and simulation specifications, derived from non-modelers’ narratives, while standardizing the conceptual modeling process and outcome. Secondly, as the process is automated, it is simpler to replicate and be followed by modelers and non-modelers. This allows for using a common …

Lidar Buoy Detection For Autonomous Marine Vessel Using Pointnet Classification, Christopher Adolphi, Dorothy Dorie Parry, Yaohang Li, Masha Sosonkina, Ahmet Saglam, Yiannis E. Papelis

Modeling, Simulation and Visualization Student Capstone Conference

Maritime autonomy, specifically the use of autonomous and semi-autonomous maritime vessels, is a key enabling technology supporting a set of diverse and critical research areas, including coastal and environmental resilience, assessment of waterway health, ecosystem/asset monitoring and maritime port security. Critical to the safe, efficient and reliable operation of an autonomous maritime vessel is its ability to perceive on-the-fly the external environment through onboard sensors. In this paper, buoy detection for LiDAR images is explored by using several tools and techniques: machine learning methods, Unity Game Engine (herein referred to as Unity) simulation, and traditional image processing. The Unity Game …

The Effectiveness Of Visualization Techniques For Supporting Decision-Making, Cansu Yalim, Holly A. H. Handley

Modeling, Simulation and Visualization Student Capstone Conference

Although visualization is beneficial for evaluating and communicating data, the efficiency of various visualization approaches for different data types is not always evident. This research aims to address this issue by investigating the usefulness of several visualization techniques for various data kinds, including continuous, categorical, and time-series data. The qualitative appraisal of each technique's strengths, weaknesses, and interpretation of the dataset is investigated. The research questions include: which visualization approaches perform best for different data types, and what factors impact their usefulness? The absence of clear directions for both researchers and practitioners on how to identify the most effective visualization …

The Legacy Of Colonization And Civil Societies In South Africa, Erika Frydenlund, Melissa Miller-Felton, Bolu Ayankojo

Modeling, Simulation and Visualization Student Capstone Conference

This research analyzes the unique ways that civil societies operate in Sub-Saharan Africa in the context of post-apartheid Cape Town, South Africa. Decades after the demise of apartheid, remnants of inequality remain without the promise of actionable change. We used a computational modeling approach to understand the dynamics of migrants in the receiving community as derived from qualitative interviews conducted with 24 stakeholders in Cape Town, South Africa between 2020 and 2021. Our findings show that the presence of NGOs can promote access to resources and reduce xenophobia if they can have the right influence on government policies.

Enhancement Of Deep Learning Protein Structure Prediction, Ruoming Shen

Modeling, Simulation and Visualization Student Capstone Conference

Protein modeling is a rapidly expanding field with valuable applications in the pharmaceutical industry. Accurate protein structure prediction facilitates drug design, as extensive knowledge about the atomic structure of a given protein enables scientists to target that protein in the human body. However, protein structure identification in certain types of protein images remains challenging, with medium resolution cryogenic electron microscopy (cryo-EM) protein density maps particularly difficult to analyze. Recent advancements in computational methods, namely deep learning, have improved protein modeling. To maximize its accuracy, a deep learning model requires copious amounts of up-to-date training data.

This project explores DeepSSETracer, a …

A Comparison Of Nonverbal And Paraverbal Behaviors In Simulated And Virtual Patient Encounters, Sarah Powers, Mark W. Scerbo, Matthew Pacailler, Macy Kisiel, Baillie Hirst, Ginger S. Watson, Lauren Hamel, Fred Kron

Modeling, Simulation and Visualization Student Capstone Conference

The present study assessed whether trainees display similar nonverbal and paraverbal behaviors when interacting with a simulated (SP) and virtual patient (VP). Sixty second slices of time following four interactions were rated for the presence and frequency of three nonverbal and paraverbal behaviors. Results revealed that students exhibited fewer behaviors in the VP interaction, possibly due to differences social inhibition or fidelity between the two formats.

An Algorithm For Finding Data Dependencies In An Event Graph, Erik J. Jensen

Modeling, Simulation and Visualization Student Capstone Conference

This work presents an algorithm for finding data dependencies in a discrete-event simulation system, from the event graph of the system. The algorithm can be used within a parallel discrete-event simulation. Also presented is an experimental system and event graph, which is used for testing the algorithm. Results indicate that the algorithm can provide information about which vertices in the experimental event graph can affect other vertices, and the minimum amount of time in which this interference can occur.

Statistical Approach To Quantifying Interceptability Of Interaction Scenarios For Testing Autonomous Surface Vessels, Benjamin E. Hargis, Yiannis E. Papelis

Modeling, Simulation and Visualization Student Capstone Conference

This paper presents a probabilistic approach to quantifying interceptability of an interaction scenario designed to test collision avoidance of autonomous navigation algorithms. Interceptability is one of many measures to determine the complexity or difficulty of an interaction scenario. This approach uses a combined probability model of capability and intent to create a predicted position probability map for the system under test. Then, intercept-ability is quantified by determining the overlap between the system under test probability map and the intruder’s capability model. The approach is general; however, a demonstration is provided using kinematic capability models and an odometry-based intent model.

Implementation Of A Pre-Assessment Module To Improve The Initial Player Experience Using Previous Gaming Information, Rafael David Segistan Canizales

Electronic Thesis and Dissertation Repository

The gaming industry has become one of the largest and most profitable industries today. According to market research, the industry revenues will pass $200 Billion and are expected to reach another $20 Billion in 2024. With the industry growing rapidly, players have become more demanding, expecting better content and quality. This means that game studios need new and innovative ways to make their games more enjoyable. One technique used to improve the player experience is DDA (Dynamic Difficulty Adjustment). It leverages the current player state to perform different adjustments during the game to tune the difficulty delivered to the player …

Extracting A Body Of Knowledge As A First Step Towards Defining A United Software Engineering Curriculum Guideline, Anton Kiselev

Doctoral Dissertations and Master's Theses

In general, the computing field is a rapidly changing environment, and as such, software engineering education must be able to adjust quickly to new needs. Industry adapts to technologies as fast as it can, but the critical issue is a need for recent graduates with the necessary expertise and knowledge of new trends, technologies, and practical experience. The industries that employ graduates of computing degree programs aim to hire those who are familiar with the latest technical traits, tools, and methodologies to meet these needs, and the software engineering curriculum needs to respond quickly to these needs. Still, unfortunately, software …

Autonomous 3d Urban And Complex Terrain Geometry Generation And Micro-Climate Modelling Using Cfd And Deep Learning, Tewodros F. Alemayehu

Electronic Thesis and Dissertation Repository

Sustainable building design requires a clear understanding and realistic modelling of the complex interaction between climate and built environment to create safe and comfortable outdoor and indoor spaces. This necessitates unprecedented urban climate modelling at high temporal and spatial resolution. The interaction between complex urban geometries and the microclimate is characterized by complex transport mechanisms. The challenge to generate geometric and physics boundary conditions in an automated manner is hindering the progress of computational methods in urban design. Thus, the challenge of modelling realistic and pragmatic numerical urban micro-climate for wind engineering, environmental, and building energy simulation applications should address …

Empirical Analysis Of Machine Learning Algorithms In Fake News Detection, Bhagyalaxmi Devi, Sudhir Senapati

International Journal of Computer and Communication Technology

Social media is the finest venue for thinking and expressing in the modern world. And this is the best place to share information about your identity, culture, religion, and customs. It entails an immediate information interchange that covers news from every industry. These days, social media has a big impact on how we live and how society functions. Currently, social media is the best medium for expressing your thoughts. Social media has also evolved into a channel for disseminating information about nearby events. how the locals in the other place are made aware of what is going on there. People …