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Computational Modeling & Simulation Engineering Theses & Dissertations

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Cyber Deception For Critical Infrastructure Resiliency, Md Ali Reza Al Amin Aug 2022

Cyber Deception For Critical Infrastructure Resiliency, Md Ali Reza Al Amin

Computational Modeling & Simulation Engineering Theses & Dissertations

The high connectivity of modern cyber networks and devices has brought many improvements to the functionality and efficiency of networked systems. Unfortunately, these benefits have come with many new entry points for attackers, making systems much more vulnerable to intrusions. Thus, it is critically important to protect cyber infrastructure against cyber attacks. The static nature of cyber infrastructure leads to adversaries performing reconnaissance activities and identifying potential threats. Threats related to software vulnerabilities can be mitigated upon discovering a vulnerability and-, developing and releasing a patch to remove the vulnerability. Unfortunately, the period between discovering a vulnerability and applying a …


Adaptive Risk Network Dependency Analysis Of Complex Hierarchical Systems, Katherine L. Smith Aug 2022

Adaptive Risk Network Dependency Analysis Of Complex Hierarchical Systems, Katherine L. Smith

Computational Modeling & Simulation Engineering Theses & Dissertations

Recently the number, variety, and complexity of interconnected systems have been increasing while the resources available to increase resilience of those systems have been decreasing. Therefore, it has become increasingly important to quantify the effects of risks and the resulting disruptions over time as they ripple through networks of systems. This dissertation presents a novel modeling and simulation methodology which quantifies resilience, as impact on performance over time, and risk, as the impact of probabilistic disruptions. This work includes four major contributions over the state-of-the-art which are: (1) cyclic dependencies are captured by separation of performance variables into layers which …


Data-Driven Operational And Safety Analysis Of Emerging Shared Electric Scooter Systems, Qingyu Ma Dec 2021

Data-Driven Operational And Safety Analysis Of Emerging Shared Electric Scooter Systems, Qingyu Ma

Computational Modeling & Simulation Engineering Theses & Dissertations

The rapid rise of shared electric scooter (E-Scooter) systems offers many urban areas a new micro-mobility solution. The portable and flexible characteristics have made E-Scooters a competitive mode for short-distance trips. Compared to other modes such as bikes, E-Scooters allow riders to freely ride on different facilities such as streets, sidewalks, and bike lanes. However, sharing lanes with vehicles and other users tends to cause safety issues for riding E-Scooters. Conventional methods are often not applicable for analyzing such safety issues because well-archived historical crash records are not commonly available for emerging E-Scooters.

Perceiving the growth of such a micro-mobility …


Methods For Detecting Floodwater On Roadways From Ground Level Images, Cem Sazara Jul 2021

Methods For Detecting Floodwater On Roadways From Ground Level Images, Cem Sazara

Computational Modeling & Simulation Engineering Theses & Dissertations

Recent research and statistics show that the frequency of flooding in the world has been increasing and impacting flood-prone communities severely. This natural disaster causes significant damages to human life and properties, inundates roads, overwhelms drainage systems, and disrupts essential services and economic activities. The focus of this dissertation is to use machine learning methods to automatically detect floodwater in images from ground level in support of the frequently impacted communities. The ground level images can be retrieved from multiple sources, including the ones that are taken by mobile phone cameras as communities record the state of their flooded streets. …


Feature Extraction And Design In Deep Learning Models, Daniel Perez Apr 2021

Feature Extraction And Design In Deep Learning Models, Daniel Perez

Computational Modeling & Simulation Engineering Theses & Dissertations

The selection and computation of meaningful features is critical for developing good deep learning methods. This dissertation demonstrates how focusing on this process can significantly improve the results of learning-based approaches. Specifically, this dissertation presents a series of different studies in which feature extraction and design was a significant factor for obtaining effective results. The first two studies are a content-based image retrieval system (CBIR) and a seagrass quantification study in which deep learning models were used to extract meaningful high-level features that significantly increased the performance of the approaches. Secondly, a method for change detection is proposed where the …


Enhanced Traffic Incident Analysis With Advanced Machine Learning Algorithms, Zhenyu Wang Dec 2020

Enhanced Traffic Incident Analysis With Advanced Machine Learning Algorithms, Zhenyu Wang

Computational Modeling & Simulation Engineering Theses & Dissertations

Traffic incident analysis is a crucial task in traffic management centers (TMCs) that typically manage many highways with limited staff and resources. An effective automatic incident analysis approach that can report abnormal events timely and accurately will benefit TMCs in optimizing the use of limited incident response and management resources. During the past decades, significant efforts have been made by researchers towards the development of data-driven approaches for incident analysis. Nevertheless, many developed approaches have shown limited success in the field. This is largely attributed to the long detection time (i.e., waiting for overwhelmed upstream detection stations; meanwhile, downstream stations …


Deep Learning For Remote Sensing Image Processing, Yan Lu Aug 2020

Deep Learning For Remote Sensing Image Processing, Yan Lu

Computational Modeling & Simulation Engineering Theses & Dissertations

Remote sensing images have many applications such as ground object detection, environmental change monitoring, urban growth monitoring and natural disaster damage assessment. As of 2019, there were roughly 700 satellites listing “earth observation” as their primary application. Both spatial and temporal resolutions of satellite images have improved consistently in recent years and provided opportunities in resolving fine details on the Earth's surface. In the past decade, deep learning techniques have revolutionized many applications in the field of computer vision but have not fully been explored in remote sensing image processing. In this dissertation, several state-of-the-art deep learning models have been …


Communication Capability For A Simulation-Based Test And Evaluation Framework For Autonomous Systems, Ntiana Sakioti Oct 2019

Communication Capability For A Simulation-Based Test And Evaluation Framework For Autonomous Systems, Ntiana Sakioti

Computational Modeling & Simulation Engineering Theses & Dissertations

The design and testing process for collaborative autonomous systems can be extremely complex and time-consuming, so it is advantageous to begin testing early in the design. A Test & Evaluation (T&E) Framework was previously developed to enable the testing of autonomous software at various levels of mixed reality. The Framework assumes a modular approach to autonomous software development, which introduces the possibility that components are not in the same stage of development. The T&E Framework allows testing to begin early in a simulated environment, with the autonomous software methodically migrating from virtual to augmented to physical environments as component development …


A Data-Driven Approach For Modeling Agents, Hamdi Kavak Apr 2019

A Data-Driven Approach For Modeling Agents, Hamdi Kavak

Computational Modeling & Simulation Engineering Theses & Dissertations

Agents are commonly created on a set of simple rules driven by theories, hypotheses, and assumptions. Such modeling premise has limited use of real-world data and is challenged when modeling real-world systems due to the lack of empirical grounding. Simultaneously, the last decade has witnessed the production and availability of large-scale data from various sensors that carry behavioral signals. These data sources have the potential to change the way we create agent-based models; from simple rules to driven by data. Despite this opportunity, the literature has neglected to offer a modeling approach to generate granular agent behaviors from data, creating …


Resilience For Asynchronous Iterative Methods For Sparse Linear Systems, Evan Coleman Apr 2019

Resilience For Asynchronous Iterative Methods For Sparse Linear Systems, Evan Coleman

Computational Modeling & Simulation Engineering Theses & Dissertations

Large scale simulations are used in a variety of application areas in science and engineering to help forward the progress of innovation. Many spend the vast majority of their computational time attempting to solve large systems of linear equations; typically arising from discretizations of partial differential equations that are used to mathematically model various phenomena. The algorithms used to solve these problems are typically iterative in nature, and making efficient use of computational time on High Performance Computing (HPC) clusters involves constantly improving these iterative algorithms. Future HPC platforms are expected to encounter three main problem areas: scalability of code, …


A Framework For Test & Evaluation Of Autonomous Systems Along The Virtuality-Reality Spectrum, Nathan D. Gonda Apr 2019

A Framework For Test & Evaluation Of Autonomous Systems Along The Virtuality-Reality Spectrum, Nathan D. Gonda

Computational Modeling & Simulation Engineering Theses & Dissertations

Test & Evaluation of autonomous vehicles presents a challenge as the vehicles may have emergent behavior and it is frequently difficult to ascertain the reason for software decisions. Current Test & Evaluation approaches for autonomous systems place the vehicles in various operating scenarios to observe their behavior. However, this introduces dependencies between design and development lifecycle of the autonomous software and physical vehicle hardware. Simulation-based testing can alleviate the necessity to have physical hardware; however, it can be costly when transitioning the autonomous software to and from a simulation testing environment. The objective of this thesis is to develop a …


Analysis Of Bulk Power System Resilience Using Vulnerability Graph, Md Ariful Haque Jul 2018

Analysis Of Bulk Power System Resilience Using Vulnerability Graph, Md Ariful Haque

Computational Modeling & Simulation Engineering Theses & Dissertations

Critical infrastructure such as a Bulk Power System (BPS) should have some quantifiable measure of resiliency and definite rule-sets to achieve a certain resilience value. Industrial Control System (ICS) and Supervisory Control and Data Acquisition (SCADA) networks are integral parts of BPS. BPS or ICS are themselves not vulnerable because of their proprietary technology, but when the control network and the corporate network need to have communications for performance measurements and reporting, the ICS or BPS become vulnerable to cyber-attacks. Thus, a systematic way of quantifying resiliency and identifying crucial nodes in the network is critical for addressing the cyber …


Adaptive Methods For Point Cloud And Mesh Processing, Zinat Afrose Jan 2018

Adaptive Methods For Point Cloud And Mesh Processing, Zinat Afrose

Computational Modeling & Simulation Engineering Theses & Dissertations

Point clouds and 3D meshes are widely used in numerous applications ranging from games to virtual reality to autonomous vehicles. This dissertation proposes several approaches for noise removal and calibration of noisy point cloud data and 3D mesh sharpening methods. Order statistic filters have been proven to be very successful in image processing and other domains as well. Different variations of order statistics filters originally proposed for image processing are extended to point cloud filtering in this dissertation. A brand-new adaptive vector median is proposed in this dissertation for removing noise and outliers from noisy point cloud data.

The major …


A Multi-Criteria And Dynamic Sustainability Assessment Of Crop Rotation Alternatives, Saturnina Fabian Nisperos Jan 2018

A Multi-Criteria And Dynamic Sustainability Assessment Of Crop Rotation Alternatives, Saturnina Fabian Nisperos

Computational Modeling & Simulation Engineering Theses & Dissertations

With the food security challenge faced by nations globally, agriculture sustainability has been a significant consideration for concerned agencies. Sustainability assessments are significant tools in providing support to stakeholders in their crop production planning. Agricultural sustainability assessment, however, is complex and it involves numerous criteria that can be conflicting. Limitations on crop rotation sustainability assessment methods include: non-dynamic assessment; lack of regard to cover crops and to the individual crop production preferences of farmers; and focused only on single-year and single-crop rotation. We sought to address these limitations by developing a multi-criteria and dynamic sustainability assessment model that considers the …


Modeling Energy Consumption Of High-Performance Applications On Heterogeneous Computing Platforms, Gary D. Lawson Jr. Oct 2017

Modeling Energy Consumption Of High-Performance Applications On Heterogeneous Computing Platforms, Gary D. Lawson Jr.

Computational Modeling & Simulation Engineering Theses & Dissertations

Achieving Exascale computing is one of the current leading challenges in High Performance Computing (HPC). Obtaining this next level of performance will allow more complex simulations to be run on larger datasets and offer researchers better tools for data processing and analysis. In the dawn of Big Data, the need for supercomputers will only increase. However, these systems are costly to maintain because power is expensive. Thus, a better understanding of power and energy consumption is required such that future hardware can benefit.

Available power models accurately capture the relationship to the number of cores and clock-rate, however the relationship …


Algorithms For Constructing Vehicle Trajectories In Urban Networks Using Inertial Sensors Data From Mobile Devices, Umana Ahmed Jul 2017

Algorithms For Constructing Vehicle Trajectories In Urban Networks Using Inertial Sensors Data From Mobile Devices, Umana Ahmed

Computational Modeling & Simulation Engineering Theses & Dissertations

Vehicle trajectories are an important source of information for estimating traffic flow characteristics. Lately, several studies have focused on identifying a vehicle’s trajectory in traffic network using data from mobile devices. However, these studies predominantly employed GPS coordinate information for tracking a vehicle’s speed and position in the transportation network. Considering the known limitations of GPS, such as, connectivity issues at urban canyons and underpasses, low precision of localization, high power consumption of device while GPS is in use, this research focuses on developing alternate methods for identifying a vehicle’s trajectory at an intersection and at a urban grid network …


Multi-Material Mesh Representation Of Anatomical Structures For Deep Brain Stimulation Planning, Tanweer Rashid Jul 2017

Multi-Material Mesh Representation Of Anatomical Structures For Deep Brain Stimulation Planning, Tanweer Rashid

Computational Modeling & Simulation Engineering Theses & Dissertations

The Dual Contouring algorithm (DC) is a grid-based process used to generate surface meshes from volumetric data. However, DC is unable to guarantee 2-manifold and watertight meshes due to the fact that it produces only one vertex for each grid cube. We present a modified Dual Contouring algorithm that is capable of overcoming this limitation. The proposed method decomposes an ambiguous grid cube into a set of tetrahedral cells and uses novel polygon generation rules that produce 2-manifold and watertight surface meshes with good-quality triangles. These meshes, being watertight and 2-manifold, are geometrically correct, and therefore can be used to …


Improved Ballistic Wind Prediction Using Projectile Tracking Data, William Arthur Kenney Jul 2017

Improved Ballistic Wind Prediction Using Projectile Tracking Data, William Arthur Kenney

Computational Modeling & Simulation Engineering Theses & Dissertations

The United States Air Force AC-130 gunships have been in operation since the Vietnam War and have seen frequent use during recent conflicts. They are able to employ gun weapon systems from above a target in a way that maximizes possible time on target. When firing, the gun operators must deal with miss distances caused by winds acting on the projectile in flight. Operators currently perform a “tweak” to predict a ballistic wind affecting fired rounds which is then used in the fire-control to correct for the real winds and bring shots onto target. This correction, a single-point wind prediction, …


Robust Algorithms For Estimating Vehicle Movement From Motion Sensors Within Smartphones, Ilyas Ustun Aug 2016

Robust Algorithms For Estimating Vehicle Movement From Motion Sensors Within Smartphones, Ilyas Ustun

Computational Modeling & Simulation Engineering Theses & Dissertations

Building sustainable traffic control solutions for urban streets (e.g., eco-friendly signal control) and highways requires effective and reliable sensing capabilities for monitoring traffic flow conditions so that both the temporal and spatial extents of congestion are observed. This would enable optimal control strategies to be implemented for maximizing efficiency and for minimizing the environmental impacts of traffic. Various types of traffic detection systems, such as inductive loops, radar, and cameras have been used for these purposes. However, these systems are limited, both in scope and in time. Using GPS as an alternative method is not always viable because of problems …


Development Of Visualization-Animation Software For Learning Transportation Algorithms, Ivan P. Makohon Jul 2016

Development Of Visualization-Animation Software For Learning Transportation Algorithms, Ivan P. Makohon

Computational Modeling & Simulation Engineering Theses & Dissertations

Recognizing the steady decline in US Science Technology Engineering Mathematics (STEM) interests and enrollments, the National Science Foundation (NSF) and the White House have developed national strategies and provided significant budget resources to STEM education research [1-2] in the past years, with the ultimate goals being to improve both the quality and number of highly trained US educators, student workforce in STEM topics, in today’s highly competitive global markets. With the explosion of the internet’s capability and availability, it is even more critical to effectively train this future USA-STEM work-force and/or to develop effective STEM related teaching tools to reach …


A Simulation-Based Layered Framework Framework For The Development Of Collaborative Autonomous Systems, Ioannis Sakiotis Jul 2016

A Simulation-Based Layered Framework Framework For The Development Of Collaborative Autonomous Systems, Ioannis Sakiotis

Computational Modeling & Simulation Engineering Theses & Dissertations

The purpose of this thesis is to introduce a simulation-based software framework that facilitates the development of collaborative autonomous systems. Significant commonalities exist in the design approaches of both collaborative and autonomous systems, mirroring the sense, plan, act paradigm, and mostly adopting layered architectures. Unfortunately, the development of such systems is intricate and requires low-level interfacing which significantly detracts from development time. Frameworks for the development of collaborative and autonomous systems have been developed but are not flexible and center on narrow ranges of applications and platforms. The proposed framework utilizes an expandable layered structure that allows developers to define …


Using Eye And Head Movements As A Control Mechanism For Tele-Operating A Ground-Based Robot And Its Payload, Kathryn C. Hicks Oct 2015

Using Eye And Head Movements As A Control Mechanism For Tele-Operating A Ground-Based Robot And Its Payload, Kathryn C. Hicks

Computational Modeling & Simulation Engineering Theses & Dissertations

To date, eye and head tracking has been used to indicate users' attention patterns while performing a task or as an aid for disabled persons, to allow hands-free interaction with a computer. The increasing accuracy and the reduced cost of eye- and head-tracking equipment make utilizing this technology feasible for explicit control tasks, especially in cases where there is confluence between the visual task and control.

The goal of this research was to investigate the use of eye-tracking as a more natural interface for the control of a camera-equipped, remotely operated robot in tasks that require the operator to simultaneously …


Proclivity Or Popularity? Exploring Agent Heterogeneity In Network Formation, Xiaotian Wang Apr 2015

Proclivity Or Popularity? Exploring Agent Heterogeneity In Network Formation, Xiaotian Wang

Computational Modeling & Simulation Engineering Theses & Dissertations

The Barabasi-Albert model (BA model) is the standard algorithm used to describe the emergent mechanism of a scale-free network. This dissertation argues that the BA model, and its variants, rarely take agent heterogeneity into account in the analysis of network formation. In social networks, however, people's decisions to connect are strongly affected by the extent of similarity. In this dissertation, the author applies an agent-based modeling (ABM) approach to reassess the Barabasi-Albert model. This study proposes that, in forming social networks, agents are constantly balancing between instrumental and intrinsic preferences. After systematic simulation and subsequent analysis, this study finds that …


Toward A Theory Of Multi-Method Modeling And Simulation Approach, Mariusz A. Balaban Apr 2015

Toward A Theory Of Multi-Method Modeling And Simulation Approach, Mariusz A. Balaban

Computational Modeling & Simulation Engineering Theses & Dissertations

The representation via simulation models can easily lead to simulation models too simple for their intended purpose, or with too much detail, making them hard to understand. This problem is related to limitations of the modeling and simulation methods. A multi-method Modeling and Simulation (M&S) approach has the potential for improved representation by taking advantage of methods' strengths and mitigating their weaknesses. Despite a high appeal for using multiple M&S methods, several related problems should be addressed first. The current level of theoretical, methodological, and pragmatic knowledge related to a multi-method M&S approach is limited. It is problematic that there …


Java Animated Software For Teaching The Frank-Wolfe Algorithm For Static Traffic Network Equilibrium, Zhi Li Apr 2015

Java Animated Software For Teaching The Frank-Wolfe Algorithm For Static Traffic Network Equilibrium, Zhi Li

Computational Modeling & Simulation Engineering Theses & Dissertations

The popular Frank-Wolfe (FW) algorithm for solving the network equilibrium problems plays an important role in transportation simulation. Not only has the basic Frank Wolfe algorithm been studied, but also other variations of the FW algorithm (such as Conjugate Frank Wolfe and Bi-Conjugate Frank Wolfe algorithms) have been extensively studied by the research communities.

In this work, the basic Frank Wolfe algorithm is re-visited for the purpose of developing a useful, user-friendly, and appealing Java computer animation for enhancing the teaching effectiveness of this fundamental transportation static network equilibrium algorithm. Since the shortest path (SP) algorithms (such as the well-known …


Multi-Surface Simplex Spine Segmentation For Spine Surgery Simulation And Planning, Rabia Haq Jan 2015

Multi-Surface Simplex Spine Segmentation For Spine Surgery Simulation And Planning, Rabia Haq

Computational Modeling & Simulation Engineering Theses & Dissertations

This research proposes to develop a knowledge-based multi-surface simplex deformable model for segmentation of healthy as well as pathological lumbar spine data. It aims to provide a more accurate and robust segmentation scheme for identification of intervertebral disc pathologies to assist with spine surgery planning. A robust technique that combines multi-surface and shape statistics-aware variants of the deformable simplex model is presented. Statistical shape variation within the dataset has been captured by application of principal component analysis and incorporated during the segmentation process to refine results. In the case where shape statistics hinder detection of the pathological region, user-assistance is …


A Framework And System For A Multi-Model Decision Aid For Sustainable Farming Practices, Kasi Bharath Vegesana Jan 2015

A Framework And System For A Multi-Model Decision Aid For Sustainable Farming Practices, Kasi Bharath Vegesana

Computational Modeling & Simulation Engineering Theses & Dissertations

Decision support systems (DSS) for farmers address the need for modeling multiple processes and scenarios that affect farmer decision making. Existing DSS have various drawbacks that stop them from being deployed as decision support tools. This research proposes a multi-model simulation framework that can be used to analyze farm management practices at the crop level, individual farm level and at the community level to show the impact and alternatives for smallholder farming practices. A generic crop growth model is proposed, based on existing equations. We run sensitivity analysis on the model to identify important variables. The outputs from the crop …


Discretized Agent-Based Model Of Infectious Disease Spread That Uses Contact Probability, Tyrell L. Gardner Oct 2014

Discretized Agent-Based Model Of Infectious Disease Spread That Uses Contact Probability, Tyrell L. Gardner

Computational Modeling & Simulation Engineering Theses & Dissertations

This study uses contact probability in an agent-based model to simulate the spread of an infectious disease. In order to perform the study, the agent-based model must first be discretized into events. Each agent in the model is given its own infectious disease state machine taken from the Susceptible-Exposed-Infected-Recovered (SEIR) model. The agents move between squares in a grid environment where each square represents a group. Groups have a contact probability as an attribute that is used to predict whether an agent comes in close contact with another agent. The transitions between the states in the SEIR model are easily …


Meshless Mechanics And Point-Based Visualization Methods For Surgical Simulations, Rifat Aras Jul 2014

Meshless Mechanics And Point-Based Visualization Methods For Surgical Simulations, Rifat Aras

Computational Modeling & Simulation Engineering Theses & Dissertations

Computer-based modeling and simulation practices have become an integral part of the medical education field. For surgical simulation applications, realistic constitutive modeling of soft tissue is considered to be one of the most challenging aspects of the problem, because biomechanical soft-tissue models need to reflect the correct elastic response, have to be efficient in order to run at interactive simulation rates, and be able to support operations such as cuts and sutures.

Mesh-based solutions, where the connections between the individual degrees of freedom (DoF) are defined explicitly, have been the traditional choice to approach these problems. However, when the problem …


Markov Chain Monte Carlo Bayesian Predictive Framework For Artificial Neural Network Committee Modeling And Simulation, Michael S. Goodrich Apr 2014

Markov Chain Monte Carlo Bayesian Predictive Framework For Artificial Neural Network Committee Modeling And Simulation, Michael S. Goodrich

Computational Modeling & Simulation Engineering Theses & Dissertations

A logical inference method of properly weighting the outputs of an Artificial Neural Network Committee for predictive purposes using Markov Chain Monte Carlo simulation and Bayesian probability is proposed and demonstrated on machine learning data for non-linear regression, binary classification, and 1-of-k classification. Both deterministic and stochastic models are constructed to model the properties of the data. Prediction strategies are compared based on formal Bayesian predictive distribution modeling of the network committee output data and a stochastic estimation method based on the subtraction of determinism from the given data to achieve a stochastic residual using cross validation. Performance for Bayesian …