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Action Recognition In Still Images: Confluence Of Multilinear Methods And Deep Learning, Marjaneh Safaei Jan 2020

Action Recognition In Still Images: Confluence Of Multilinear Methods And Deep Learning, Marjaneh Safaei

Electronic Theses and Dissertations, 2020-2023

Motion is a missing information in an image, however, it is a valuable cue for action recognition. Thus, lack of motion information in a single image makes action recognition for still images inherently a very challenging problem in computer vision. In this dissertation, we show that both spatial and temporal patterns provide crucial information for recognizing human actions. Therefore, action recognition depends not only on the spatially-salient pixels, but also on the temporal patterns of those pixels. To address the challenge caused by the absence of temporal information in a single image, we introduce five effective action classification methodologies along …

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Machine Learning Based Rf Transmitter Characterization In The Presence Of Adversaries, Debashri Roy Jan 2020

Machine Learning Based Rf Transmitter Characterization In The Presence Of Adversaries, Debashri Roy

Electronic Theses and Dissertations, 2020-2023

The advances in wireless technologies have led to autonomous deployments of various wireless networks. As these networks must co-exist, it is important that all transmitters and receivers are aware of their radio frequency (RF) surroundings so that they can learn and adapt their transmission and reception parameters to best suit their needs. To this end, machine learning techniques have become popular as they can learn, analyze and even predict the RF signals and associated parameters that characterize the RF environment. In this dissertation, we address some of the fundamental challenges on how to effectively apply different learning techniques in the …

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Efficient String Algorithms With Applications In Bioinformatics, Sahar Hooshmand Jan 2020

Efficient String Algorithms With Applications In Bioinformatics, Sahar Hooshmand

Electronic Theses and Dissertations, 2020-2023

The work presented in this dissertation deals with establishing efficient methods for solving some algorithmic problems, which have applications to Bioinformatics. After a short introduction in Chapter 1, an algorithm for genome mappability problem is presented in Chapter 2. Genome mappability is a measure for the approximate repeat structure of the genome with respect to substrings of specific length and a tolerance to define the number of mismatches. The similarity between reads is measured by using the Hamming distance function. Genome mappability is computed for each position in the string and has several applications in designing high-throughput short-read sequencing experiments. …

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Learning Context-Sensitive Human Emotions In Categorical And Dimensional Domains, Pooyan Balouchian Jan 2020

Learning Context-Sensitive Human Emotions In Categorical And Dimensional Domains, Pooyan Balouchian

Electronic Theses and Dissertations, 2020-2023

Still image emotion recognition (ER) has been receiving increasing attention in recent years due to the tremendous amount of social media content on the Web. Many works offer both categorical and dimensional methods to detect image sentiments, while others focus on extracting the true social signals, such as happiness and anger. Deep learning architectures have delivered great suc- cess, however, their dependency on large-scale datasets labeled with (1) emotion, and (2) valence, arousal and dominance, in categorical and dimensional domains respectively, introduce challenges the community tries to tackle. Emotions offer dissimilar semantics when aroused in different con- texts, however "context-sensitive" …

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Improving The Security Of Critical Infrastructure: Metrics, Measurements, And Analysis, Jeman Park Jan 2020

Improving The Security Of Critical Infrastructure: Metrics, Measurements, And Analysis, Jeman Park

Electronic Theses and Dissertations, 2020-2023

In this work, we propose three important contributions needed in the process of improving the security of the critical infrastructure: metrics, measurement, and analysis. To improve security, metrics are key to ensuring the accuracy of the assessment and evaluation. Measurements are the core of the process of identifying the causality and effectiveness of various behaviors, and accurate measurement with the right assumptions is a cornerstone for accurate analysis. Finally, contextualized analysis essential for understanding measurements. Different results can be derived for the same data according to the analysis method, and it can serve as a basis for understanding and improving …

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Decentralized Adaptable Task Allocation For Ongoing Tasks, Vera Kazakova Jan 2020

Decentralized Adaptable Task Allocation For Ongoing Tasks, Vera Kazakova

Electronic Theses and Dissertations, 2020-2023

This thesis extends an existing bio-inspired model for decentralized task allocation and benchmarks it against alternative approaches to assess robustness in dynamic conditions, applicability to domains with ongoing and hierarchical tasks, and scalability to large teams of agents. The work addresses decentralized task allocation of simple non-communicating agents in dynamic environments of multiple tasks. Multi-area patrolling is used as the sample domain: specific number of agents is required to successfully patrol each area on each timestep, indefinitely, until the system's security needs. Agents must individually decide whether to patrol and where (i.e., task availability is not limited by task demand …

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Prediction Of Pedestrians' Red Light Violations Using Deep Learning, Shile Zhang Jan 2020

Prediction Of Pedestrians' Red Light Violations Using Deep Learning, Shile Zhang

Electronic Theses and Dissertations, 2020-2023

Pedestrians are regarded as Vulnerable Road Users (VRUs). Each year, thousands of pedestrians' deaths are caused by traffic crashes, which take up 16% of the total road fatalities and injuries in the U.S. (FHWA, 2018). Crashes can happen if there are interactions between VRUs and motorized transportation. And pedestrians' unexpected crossings, such as red-light violations at the signalized intersections, would expose them to motorized transportation and cause potential collisions. This thesis is intended to predict the pedestrians' red-light violation behaviors at the signalized crosswalks based on an LSTM (Long Short-term Memory) neural network. With video data collected from real traffic …

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Ultraviolet Irradiation Combined With Chlorine Dioxide Pre-Oxidation For Disinfection By-Product Control, Paula Campesino Jan 2020

Ultraviolet Irradiation Combined With Chlorine Dioxide Pre-Oxidation For Disinfection By-Product Control, Paula Campesino

Electronic Theses and Dissertations, 2020-2023

The use of ultraviolet (UV) light and chlorine dioxide (ClO2) as an advanced oxidation process (AOP) has been investigated at the bench-scale to understand the effects of their use on disinfection by-product (DBP) formation potential (FP) in chlorinated groundwater (GW) and surface water (SW) supplies. Two GWs and two SWs of varying qualities were subject to a series of AOP treatment sequences at the bench scale: sodium hypochlorite, to serve as a baseline; ClO2-Cl2, UV-Cl2, and UV-ClO2-Cl2. In these treatment sequences, Cl2 is used as a primary and secondary disinfectant. Several water quality parameters were measured throughout the experiments, including …

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Study On Ductile Fracture With Anisotropic And Strain Rate Effects In Manufacturing Processes, Hao Pan Jan 2020

Study On Ductile Fracture With Anisotropic And Strain Rate Effects In Manufacturing Processes, Hao Pan

Electronic Theses and Dissertations, 2020-2023

Ductile fracture is a topic of great importance in automotive and aerospace industries. Prediction of ductile fracture in engineering structures relies on developing robust material models under complex loading conditions. This dissertation addresses the anisotropic and strain rate effects in constitutive and ductile fracture models of lightweight metals. In the present modeling framework, the anisotropic plasticity behavior is modeled by combination of an initial anisotropic yield function and an isotropic hardening correction by Lode dependence. A new all-strain based anisotropic fracture model is proposed based on the approach of linear transformation on plastic strain rate tensor. The strain rate effects …

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Pathological Tremor As A Mechanical System: Modeling And Control Of Artificial Muscle-Based Tremor Suppression, Christopher Kelley Jan 2020

Pathological Tremor As A Mechanical System: Modeling And Control Of Artificial Muscle-Based Tremor Suppression, Christopher Kelley

Electronic Theses and Dissertations, 2020-2023

Central nervous system disorders produce the undesired, approximately rhythmic movement of body parts known as pathological tremor. This undesired motion inhibits the patient's ability to perform tasks of daily living and participate in society. Typical treatments are medications and deep brain stimulation surgery, both of which include risks, side effects, and varying efficacy. Since the pathophysiology of tremor is not well understood, empirical investigation drives tremor treatment development. This dissertation explores tremor from a mechanical systems perspective to work towards theory-driven treatment design. The primary negative outcome of pathological tremor is the undesired movement of body parts: mechanically suppressing this …

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In Pursuit Of Low-Dimensional Manifold Structures In High-Dimensional Data, Mahlagha Sedghi Jan 2020

In Pursuit Of Low-Dimensional Manifold Structures In High-Dimensional Data, Mahlagha Sedghi

Electronic Theses and Dissertations, 2020-2023

The ever-increasing availability of large-scale and high-dimensional data offers unprecedented opportunities for data-driven studies across widely differing domains ranging from marketing and web mining, to bioinformatics and space exploration. Yet, it also poses formidable challenges in face of storing, organizing and analyzing such data. Often though, high-dimensional data tend to lie close to some low-dimensional structures. Aside from substantial computational and storage conservations, discovering such structures also contributes to improved learning and inference performance. A majority of existing work assume linear data models which fail to effectively capture the complex patterns of real-world problems. Non-linear models on the other hand …

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An Experimental Validation Of A Revised Paschen's Law Relating To The Esd Of Aerospace Vehicle Surfaces, Manuela Morales Jan 2020

An Experimental Validation Of A Revised Paschen's Law Relating To The Esd Of Aerospace Vehicle Surfaces, Manuela Morales

Honors Undergraduate Theses

The experimental validation of a new theoretical model of Paschen’s law was developed. In order to do so, a supersonic wind tunnel apparatus was designed and fabricated to voltage discharge between two electrodes at different pressures and distances. This was possible using interchangeable nozzle and test sections. The wind tunnel included the implementation of an automated recording of current and voltage data via a LabVIEW™ program collected relevant data, which once analyzed, was used to support the revised Paschen Law developed by Dr.Houge et.al. Results showed that the modified Paschen’s law is consistent with experimental results.

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The Gamification Framework Of Military Flight Simulator For Effective Learning And Training Environment, Daeho Noh Jan 2020

The Gamification Framework Of Military Flight Simulator For Effective Learning And Training Environment, Daeho Noh

Electronic Theses and Dissertations, 2020-2023

The purpose of this thesis is to develop a framework for the gamification of flight simulators to provide an active learning and training environment for military jet pilots. Currently, with the development of visual displays and computer processing capabilities, the modern simulator has made great progress in visual and auditory terms that is incomparable to the past. In addition, functions that were previously implemented through supercomputers and complex hardware devices are now available through desktop computers at an affordable cost. Despite these advances, the simulators so far are thought to have been negligent in building an active learning and training …

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A Study Into Validating A Coupled Method Of Characteristics And Direct Simulation Monte Carlo Method Against Empirical Data, Andrew Brown Jan 2020

A Study Into Validating A Coupled Method Of Characteristics And Direct Simulation Monte Carlo Method Against Empirical Data, Andrew Brown

Electronic Theses and Dissertations, 2020-2023

The following will outline the methodology and results of validating a coupled Method of Characteristics (MOC) and Direct Simulation Monte Carlo (DSMC) method. This research focused specifically on modeling plume impingement, induced by Reaction Control System (RCS) thrusters that flew on the National Aeronautics and Space Administration's (NASA's) space shuttle Discovery. For each simulation, the continuum portion of the RCS thruster was simulated using MOC for solving hyperbolic Partial Differential Equations (PDEs) and computed with the NASA code, Reacting and Multi-phase Program (RAMP). The solution was then implemented as a starting condition into the NASA DSMC code, Direct Simulation and …

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Human Performance In Virtual Reality Environments And Its Exploration With Engineering Analytics, Fahad Alasim Jan 2020

Human Performance In Virtual Reality Environments And Its Exploration With Engineering Analytics, Fahad Alasim

Electronic Theses and Dissertations, 2020-2023

Engineering Analytics (EA) is a technique used to derive meaningful insight from gathered data. It is an approach that has arisen, and it includes the process of analyzing data using analytics tools from fields such as Big Data, Machine Learning (ML), traditional operations research, statistics, and numerical methods. Industrial Engineering is an engineering field concerned with how to design better, improve, and install integrated systems, uses EA to understand and continually improve, innovate, and build new processes. Therefore, EA and Virtual Reality (VR) technology can be used in combination with Electroencephalography (EEG), a physiological measurement, to investigate human areas. The …

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Assessing The Potential Of Implementing Blockchain In Supply Chains Using Agent-Based Simulation And Deep Learning, Mohammad Obeidat Jan 2020

Assessing The Potential Of Implementing Blockchain In Supply Chains Using Agent-Based Simulation And Deep Learning, Mohammad Obeidat

Electronic Theses and Dissertations, 2020-2023

In this decade, with the rise of data science accompanying the growth of e-commerce, many technologies have been developed. An example of these technologies is Blockchain, which has appeared to overcome security problems potentially. This research assesses Blockchain's implementation in supply chains through a methodology that uses deep learning and agent-based simulation. A case study was utilized to observe and validate research developments. The unique method predicts intrusions by using deep learning, and agent-based modeling reproduces artificial but convincing agents (e.g., customers, companies, hackers, and cyber pirates) in a computer-generated market. Trust and other relationships are systematically captured to represent …

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An Approach To Modeling Simulated Military Human-Agent Teaming, Maartje Hidalgo Jan 2020

An Approach To Modeling Simulated Military Human-Agent Teaming, Maartje Hidalgo

Electronic Theses and Dissertations, 2020-2023

With the rise of human-agent teaming (HAT), a new cycle of scientific discovery commenced. Through scientific discovery, a number of theories of constructs in HAT were developed, however, an overarching model is lacking that elucidates the relative importance of these constructs in relation to human performance. The main objective of this research was to develop a model of simulated military HAT and to validate it against selected empirical data. Experimental data borrowed from four simulated military HAT studies were used to test the proposed Core model. The Core model was assumed to be directly affecting task performance and consisted of …

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Investigation In Engineering Leadership Using System Engineering And Virtual Reality, Charles Davis Jan 2020

Investigation In Engineering Leadership Using System Engineering And Virtual Reality, Charles Davis

Electronic Theses and Dissertations, 2020-2023

System Engineering can help derive requirements and specifications to build virtual environments which are good to test behaviors and attitudes. Virtual simulations can have a strong impact because role-playing facilitates active learning, permits the acceptance of new concepts, and generates increased interest, enthusiasm, and motivation. Research over the last 50 years has shown that reasoning with and about context is an essential aspect of human cognition, permeating language, memory, and reasoning capabilities. This integral process is developed over a lifetime through experiential learning. In this research, we utilize systems engineering to capture guidelines from psychologist and concepts of technological leadership. …

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Design And Visual Servo Control Of A Mechanical Gripper For Autonomous Strawberry Harvesting, Jonah Mapes Jan 2020

Design And Visual Servo Control Of A Mechanical Gripper For Autonomous Strawberry Harvesting, Jonah Mapes

Electronic Theses and Dissertations, 2020-2023

With rising labor costs and high consumer demand, economic conditions are becoming increasingly favorable for mechanization in the strawberry industry. However, virtually all strawberry crops are still picked by hand because the harvesting process is very challenging to automate, and strawberries are susceptible to bruising. For these reasons, the development of a harvester which can avoid damaging the fruit is of interest. Conventional designs for robotic grippers are less than ideal, as precise positioning or force feedback capabilities are required to reduce the risk of bruising. As an alternative, a novel "camera-in-hand" gripper design is presented which effectively avoids bruising …

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Modeling Of Incident Type And Incident Duration Using Data From Multiple Years, Sudipta Dey Tirtha Jan 2020

Modeling Of Incident Type And Incident Duration Using Data From Multiple Years, Sudipta Dey Tirtha

Electronic Theses and Dissertations, 2020-2023

We develop a model system that recognizes the distinct traffic incident duration profiles based on incident type. Specifically, a copula-based joint framework with a scaled multinomial logit model (SMNL) system for incident type and a grouped generalized ordered logit (GGOL) model system for incident duration to accommodate for the impact of observed and unobserved effects on incident type and incident duration. The model system is estimated using traffic incident data from 2012 through 2017 for the Greater Orlando region, employing a comprehensive set of exogenous variables – incident characteristics, roadway characteristics, traffic condition, weather condition, built environment and socio-demographic characteristics. …

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Separating Content Selection From Surface Realization In Neural Text Summarization, Logan Lebanoff Jan 2020

Separating Content Selection From Surface Realization In Neural Text Summarization, Logan Lebanoff

Electronic Theses and Dissertations, 2020-2023

Text summarization is a rapidly growing field with many new innovations. End-to-end models using the sequence-to-sequence architecture achieve high scores according to automatic metrics on standard datasets. However, they frequently generate summaries that are factually inconsistent with the original article -- a vital problem to be solved before the summaries can be used in real-world applications. In addition, they are not generalizable to new domains, especially those with few training examples. In this dissertation, we propose to explicitly separate the two steps of content selection and surface realization in summarization. Content selection is the process of choosing important words/phrases/sentences from …

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Wave-Optics Simulation Of Correlated Speckle Fields, Derek Burrell Jan 2020

Wave-Optics Simulation Of Correlated Speckle Fields, Derek Burrell

Electronic Theses and Dissertations, 2020-2023

Laser speckle poses an ongoing challenge to optical systems that utilize coherent light for active illumination, including applications in holography, free-space communications, remote sensing and target tracking. Speckle averaging offers one potential path forward by reducing the contrast, thereby boosting signal-to-noise ratios. This approach becomes limited, however, by the degree of correlation between successive frames. Wave-optics simulations help to characterize performance gains through speckle averaging, and so it is important that existing models properly account for decorrelation rates of dynamic speckle. With that goal in mind, this research seeks to build a suite of computational wave-optics experiments that verify speckle …

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Enhancement Of Absorptance By Ultrafast Laser Pulse Shaping For Efficient Laser Processing Of Thin Polymers, Arifur Rahaman Jan 2020

Enhancement Of Absorptance By Ultrafast Laser Pulse Shaping For Efficient Laser Processing Of Thin Polymers, Arifur Rahaman

Electronic Theses and Dissertations, 2020-2023

Ultrashort-pulsed lasers have been used for high precision processing of a wide range of materials including dielectrics, semiconductors, metals, and polymers/polymer composites, enabling numerous applications ranging from micromachining, photonics to life sciences. However, there are challenges when applying this technology in the industry, which requires scale and throughput different from lab use. The goal of this research is to understand how ultrafast laser pulses interact with thin polymers/polymer composite materials and develop a method that is efficient for ultrafast laser processing of these materials. It is a common practice in industrial applications to run the laser at a high repetition …

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Discovery Of New Topological Quantum Materials By Photoemission, Md Mofazzel Hosen Jan 2020

Discovery Of New Topological Quantum Materials By Photoemission, Md Mofazzel Hosen

Electronic Theses and Dissertations, 2020-2023

A topological insulator (TI) is a novel electronic state of quantum matter characterize by a bulk insulating bandgap and spin-polarized metallic surface states. Recently, the idea of topology protected surface states extended to semimetallic/metallic systems such as Dirac and Weyl semimetals. Unlike topological insulators where only surface states are interesting and topologically protected, Dirac and Weyl semimetals feature unusual bands in both on the surface and bulk. Dirac semimetals show photon-like linear band dispersion and exhibit a variety of exotic properties that include surface Fermi arc, large magnetoresistance, and high carrier mobility, etc. Recently, a new type of topological phase …

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Development Of High-Power Single-Mode Yb-Doped Fiber Amplifiers And Beam Analysis, Steffen Wittek Jan 2020

Development Of High-Power Single-Mode Yb-Doped Fiber Amplifiers And Beam Analysis, Steffen Wittek

Electronic Theses and Dissertations, 2020-2023

High-power fiber laser systems enjoy a widespread use in manufacturing, medical, and defense applications as well as scientific research, due to their remarkable power scalability, high electrical to optical efficiency, compactness and ruggedness. However, single-mode fiber power scaling has stagnated in the past years, primarily due to the onset of nonlinear effects such as stimulated Brillouin/Raman scattering and transverse modal instabilities. This thesis addresses the analysis and mitigation of transverse modal instabilities in high-power fiber amplifiers. I describe the high-power fiber amplifier testbed that I set up to test fibers fabricated in house. I will show our results of a …

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Design Of An Annular Disc-Shaped Heat Pipe For Air-Cooled Steam Condensers, Ahmad Saleh Jan 2020

Design Of An Annular Disc-Shaped Heat Pipe For Air-Cooled Steam Condensers, Ahmad Saleh

Electronic Theses and Dissertations, 2020-2023

Limitations on water utilization are turning into an expanding issue for the power and electricity generation industry. As a contribution to the solution of water consumption problems, utility companies are shifting toward using air-cooled condensers (ACC) in replace to the typical water-cooling methods of once-through cooling and the surface condenser/wet-cooling tower combination. Although the ACC is a dry cooling method, the industry is quite hesitant to switch over to ACC mainly for three reasons: (a) lower power output, (b) higher capital cost, and (c) larger physical footprint. All these drawbacks are because of the high overall thermal resistance of condensing …

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"You Tell Me How They Work": First-Year College Composition Instructors' Purposes And Practices For Choosing And Using Worked Examples, Rena Perez Jan 2020

"You Tell Me How They Work": First-Year College Composition Instructors' Purposes And Practices For Choosing And Using Worked Examples, Rena Perez

Electronic Theses and Dissertations, 2020-2023

This thesis describes and analyzes the how and why behind first-year college composition (FYC) instructors' practices for choosing and using examples for teaching writing at UCF. In educational research, developments related to cognitive load theory, analogical transfer, and worked examples reject discovery learning pedagogy, instead advocating for providing examples to aid in problem-solving. Scholars in ill-structured disciplines have studied the use of worked examples (Kyun et al.; Ondrusek et al; Rourke and Sweller), paving the way for fields such as composition studies to apply this concept in new contexts. Although composition scholarship recommends the use of models or sample texts …

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Novel Computational Approaches For Multidimensional Brain Image Analysis, Harish Raviprakash Jan 2020

Novel Computational Approaches For Multidimensional Brain Image Analysis, Harish Raviprakash

Electronic Theses and Dissertations, 2020-2023

The overall goal of this dissertation is focused on addressing challenging problems in 1D, 2D/3D and 4D neuroimaging by developing novel algorithms that combine signal processing and machine learning techniques. One of these challenging tasks is the accurate localization of the eloquent language cortex in brain resection pre-surgery patients. This is especially important since inaccurate localization can lead to diminshed functionalities and thus, a poor quality of life for the patient. The first part of this dissertation addresses this problem in the case of drug-resistant epileptic patients. We propose a novel machine learning based algorithm to establish an alternate electrical …

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Fluoresence Spectra Study Of Sterically Strained Isomers Of C24h14 Polycyclic Aromatic (Pahs) & Characterization Of A Bio-Sourced, Fluoresent, Ratiometric Ph Indicator With Alkaline Pka, Samar Abd Alelah Jan 2020

Fluoresence Spectra Study Of Sterically Strained Isomers Of C24h14 Polycyclic Aromatic (Pahs) & Characterization Of A Bio-Sourced, Fluoresent, Ratiometric Ph Indicator With Alkaline Pka, Samar Abd Alelah

Electronic Theses and Dissertations, 2020-2023

This thesis is composed to two studies, each of which relies on recent advances in time-dependent density functional theory (TD-DFT) to accurately model fluorescence spectra. The first study focuses on evaluating the fluorescence spectrum of polycyclic aromatic hydrocarbons (PAHs) having a molecular weight of 302. Three isomers are analyzed including dibenzo[a,j]fluoranthene, dibenzo[a,k]fluoranthene and dibenzo[a,l]fluoranthene. These isomers differ in the placement of one of six aromatic rings and in the amount that each molecule deviates from planarity. The TD-DFT methods are used to compute spectra in an environment that simulates solvent (n-hexane). These computed spectra are compared to vibronically resolved experimental …

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Attosecond Transient Absorption Spectroscopy In The Water Window, Andrew Chew Jan 2020

Attosecond Transient Absorption Spectroscopy In The Water Window, Andrew Chew

Electronic Theses and Dissertations, 2020-2023

The push to study the atomic and molecular dynamics at ever smaller time scales has been the main driving force for developing laser systems with ever shorter pulse durations. Thus far, picosecond lasers and femtosecond lasers have been used with great success in femtochemistry to study molecular dynamics such as molecular rotation and vibration, which all occur in the tens to hundreds of femtosecond. To study electron dynamics however, which are on the order of attoseconds, one needs attosecond laser sources to be able to have the time resolution required to probe ultrafast electron dynamics such as AC Stark shifts, …

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