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New Jersey Institute of Technology

Theses/Dissertations

2022

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Full-Text Articles in Physical Sciences and Mathematics

Using Materialized Views For Answering Graph Pattern Queries, Michael Lan Dec 2022

Using Materialized Views For Answering Graph Pattern Queries, Michael Lan

Dissertations

Discovering patterns in graphs by evaluating graph pattern queries involving direct (edge-to-edge mapping) and reachability (edge-to-path mapping) relationships under homomorphisms on data graphs has been extensively studied. Previous studies have aimed to reduce the evaluation time of graph pattern queries due to the potentially numerous matches on large data graphs.

In this work, the concept of the summary graph is developed to improve the evaluation of tree pattern queries and graph pattern queries. The summary graph first filters out candidate matches which violate certain reachability constraints, and then finds local matches of query edges. This reduces redundancy in the representation …


Android Security: Analysis And Applications, Raina Samuel Dec 2022

Android Security: Analysis And Applications, Raina Samuel

Dissertations

The Android mobile system is home to millions of apps that offer a wide range of functionalities. Users rely on Android apps in various facets of daily life, including critical, e.g., medical, settings. Generally, users trust that apps perform their stated purpose safely and accurately. However, despite the platform’s efforts to maintain a safe environment, apps routinely manage to evade scrutiny. This dissertation analyzes Android app behavior and has revealed several weakness: lapses in device authentication schemes, deceptive practices such as apps covering their traces, as well as behavioral and descriptive inaccuracies in medical apps. Examining a large corpus of …


Carrier Transport Engineering In Wide Bandgap Semiconductors For Photonic And Memory Device Applications, Ravi Teja Velpula Dec 2022

Carrier Transport Engineering In Wide Bandgap Semiconductors For Photonic And Memory Device Applications, Ravi Teja Velpula

Dissertations

Wide bandgap (WBG) semiconductors play a crucial role in the current solid-state lighting technology. The AlGaN compound semiconductor is widely used for ultraviolet (UV) light-emitting diodes (LEDs), however, the efficiency of these LEDs is largely in a single-digit percentage range due to several factors. Until recently, AlInN alloy has been relatively unexplored, though it holds potential for light-emitters operating in the visible and UV regions. In this dissertation, the first axial AlInN core-shell nanowire UV LEDs operating in the UV-A and UV-B regions with an internal quantum efficiency (IQE) of 52% are demonstrated. Moreover, the light extraction efficiency of this …


Photonic Monitoring Of Atmospheric Fauna, Adrien P. Genoud Dec 2022

Photonic Monitoring Of Atmospheric Fauna, Adrien P. Genoud

Dissertations

Insects play a quintessential role in the Earth’s ecosystems and their recent decline in abundance and diversity is alarming. Monitoring their population is paramount to understand the causes of their decline, as well as to guide and evaluate the efficiency of conservation policies. Monitoring populations of flying insects is generally done using physical traps, but this method requires long and expensive laboratory analysis where each insect must be identified by qualified personnel. Lack of reliable data on insect populations is now considered a significant issue in the field of entomology, often referred to as a “data crisis” in the field. …


Integrated Machine Learning And Optimization Approaches, Dogacan Yilmaz Dec 2022

Integrated Machine Learning And Optimization Approaches, Dogacan Yilmaz

Dissertations

This dissertation focuses on the integration of machine learning and optimization. Specifically, novel machine learning-based frameworks are proposed to help solve a broad range of well-known operations research problems to reduce the solution times. The first study presents a bidirectional Long Short-Term Memory framework to learn optimal solutions to sequential decision-making problems. Computational results show that the framework significantly reduces the solution time of benchmark capacitated lot-sizing problems without much loss in feasibility and optimality. Also, models trained using shorter planning horizons can successfully predict the optimal solution of the instances with longer planning horizons. For the hardest data set, …


Helioseismic Diagnostics Of Active Regions And Their Magnetic Fields, John T. Stefan Dec 2022

Helioseismic Diagnostics Of Active Regions And Their Magnetic Fields, John T. Stefan

Dissertations

While two and a half decades of nearly constant observation by the Solar and Heliospheric Observatory (SOHO) and the Solar Dynamics Observatory (SDO) spacecraft have yielded key insights into the structure and dynamics of active regions, it is still unclear if active regions can be identified before emerging on the solar surface and, once emerged, whether the subsurface structure of an active region’s magnetic field can be measured. Regarding the dynamical processes associated with active regions, the height and mechanism of sunquake excitation remains poorly understood. To answer these questions, a comprehensive survey of active region magnetic fields and their …


Hydrodynamic Investigation Of The Discharge Of Complex Fluids From Dispensing Bottles Using Experimental And Computational Approaches, Baran Teoman Dec 2022

Hydrodynamic Investigation Of The Discharge Of Complex Fluids From Dispensing Bottles Using Experimental And Computational Approaches, Baran Teoman

Dissertations

The discharge of non-Newtonian, complex fluids through orifices of industrial tanks, pipes, dispensers, or packaging containers is a ubiquitous but often problematic process because of the complex rheology of such fluids and the geometry of the containers. This, in turn, reduces the discharge rate and results in residual fluid left in the container, often referred to as heel. Heel formation is undesired in general, since it causes loss of valuable material, container fouling, and cross-contamination between batches. Heel may be of significant concern not only in industrial vessels but also in consumer packaging. Despite its relevance, the research in this …


Interactions Of Amyloid Peptides With Lipid Membranes, Yanxing Yang Dec 2022

Interactions Of Amyloid Peptides With Lipid Membranes, Yanxing Yang

Dissertations

The aggregation of amyloid proteins into fibrils is a hallmark of several diseases including Alzheimer’s (AD), Parkinson’s, and Type II diabetes. This aggregation process involves the formation of small size oligomers preceding the formation of insoluble fibrils. Recent studies have shown that these oligomers are more likely to be responsible for cell toxicity than fibrils. A possible mechanism of toxicity involves the interaction of oligomers with the cell membrane compromising its integrity. In particular, oligomers may form pore-like structures in the cell membrane affecting its permeability or they may induce lipid loss via a detergent-like effect. This dissertation aims to …


Bioremediation Of Petroleum Hydrocarbons In Coastal Sediments, Charbel Abou Khalil Dec 2022

Bioremediation Of Petroleum Hydrocarbons In Coastal Sediments, Charbel Abou Khalil

Dissertations

The biodegradation of dispersed crude oil in the ocean is relatively rapid (a half-life of a few weeks). However, it is often much slower on shorelines, usually attributed to low moisture content, nutrient limitation, and higher oil concentrations in beaches than in dispersed plumes. Another factor may be the increased salinity of the upper intertidal and supratidal zones since these parts of the beach are potentially subject to prolonged evaporation and only intermittent inundation. Therefore, two laboratory experiments are conducted to investigate whether such an increase in porewater salinity results in additional inhibitory effects on oil biodegradation in seashores.

In …


Combustion Soot Nanoparticles: Mechanism Of Restructuring And Mechanical Properties, Ali Hasani Dec 2022

Combustion Soot Nanoparticles: Mechanism Of Restructuring And Mechanical Properties, Ali Hasani

Dissertations

Soot, a product of incomplete combustion of fossil fuels, is a global warming agent. The effect of soot particles on climate depends on their morphology. Freshly released soot particles are fractal lacey aggregates, but they often appear collapsed in atmospheric samples collected away from emission sources. A body of work has concluded that the collapse is caused by liquid shells when they form by vapor condensation around soot aggregates. However, some recent studies argue that soot remains fractal even when engulfed by the shells, collapsing only when the shells evaporate. To reconcile this disagreement, the effects of the condensation and …


Assessing The Health Effects Of Climate Change, Social Vulnerability, And Environmental Justice In Camden County, New Jersey, Daniil Ivanov Dec 2022

Assessing The Health Effects Of Climate Change, Social Vulnerability, And Environmental Justice In Camden County, New Jersey, Daniil Ivanov

Theses

Climate change negatively impacts health, while socially vulnerable and overburdened communities disproportionately experience climate change and negative health determinants. Camden County is used as a case study for analyzing environment, socioeconomics, and health. Environmental variables—PM2.5 and land cover of impervious surfaces, floodplains, and forests—were compared to the CDC Social Vulnerability Index (SVI) at the census tract level, finding significant correlations between land cover, air quality, and the SVI. The overburdened communities defined by the NJ Environmental Justice Law experienced a significantly higher incidence of emergency department visitation for respiratory, circulatory, and mental illnesses than non-overburdened communities. Health outcomes were compared …


Machine Learning-Based Data Analytics For Understanding Space Weather And Climate, Yasser Abduallah Dec 2022

Machine Learning-Based Data Analytics For Understanding Space Weather And Climate, Yasser Abduallah

Dissertations

This dissertation addresses multiple crucial problems in space weather and climate, presenting new machine learning-based data analytics algorithms and models for tackling the problems.

First, the dissertation presents two new approaches to predicting solar flares. One approach, called DeepSun, predicts solar flares by utilizing a machine-learning-as-a-service (MLaaS) platform. The DeepSun system provides a friendly interface for Web users and an application programming interface (API) for remote programming users. It adopts an ensemble learning method that employs several machine learning algorithms to perform multiclass flare prediction. The other approach, named SolarFlareNet, forecasts the occurrence of solar flares within the next 24 …


A Neural Analysis-Synthesis Approach To Learning Procedural Audio Models, Danzel Serrano Dec 2022

A Neural Analysis-Synthesis Approach To Learning Procedural Audio Models, Danzel Serrano

Theses

The effective sound design of environmental sounds is crucial to demonstrating an immersive experience. Classical Procedural Audio (PA) models have been developed to give the sound designer a fast way to synthesize a specific class of environmental sounds in a physically accurate and computationally efficient manner. These models are controllable due to the choice of parameters from analyzing a class of sound. However, the resulting synthesis lacks the fidelity for the preferred immersive experience; thus, the sound designer would rather search through an extensive database for real recordings of a target sound class. This thesis proposes the Procedural audio Variational …


Analyzing Fluctuation Of Topics And Public Sentiment Through Social Media Data, Haoyue Liu Aug 2022

Analyzing Fluctuation Of Topics And Public Sentiment Through Social Media Data, Haoyue Liu

Dissertations

Over the past decade years, Internet users were expending rapidly in the world. They form various online social networks through such Internet platforms as Twitter, Facebook and Instagram. These platforms provide a fast way that helps their users receive and disseminate information and express personal opinions in virtual space. When dealing with massive and chaotic social media data, how to accurately determine what events or concepts users are discussing is an interesting and important problem.

This dissertation work mainly consists of two parts. First, this research pays attention to mining the hidden topics and user interest trend by analyzing real-world …


Computation Of Risk Measures In Finance And Parallel Real-Time Scheduling, Yajuan Li Aug 2022

Computation Of Risk Measures In Finance And Parallel Real-Time Scheduling, Yajuan Li

Dissertations

Many application areas employ various risk measures, such as a quantile, to assess risks. For example, in finance, risk managers employ a quantile to help determine appropriate levels of capital needed to be able to absorb (with high probability) large unexpected losses in credit portfolios comprising loans, bonds, and other financial instruments subject to default. This dissertation discusses the computation of risk measures in finance and parallel real-time scheduling.

Firstly, two estimation approaches are compared for one risk measure, a quantile, via randomized quasi-Monte Carlo (RQMC) in an asymptotic setting where the number of randomizations for RQMC grows large, but …


Stochastic Modeling Of Flows In Membrane Pore Networks, Binan Gu Aug 2022

Stochastic Modeling Of Flows In Membrane Pore Networks, Binan Gu

Dissertations

Membrane filters provide immediate solutions to many urgent problems such as water purification, and effective remedies to pressing environmental concerns such as waste and air treatment. The ubiquity of applications gives rise to a significant amount of research in membrane material selection and structural design to optimize filter efficiency. As physical experiments tend to be costly, numerical simulation and analysis of fluid flow, foulant transport and geometric evolution due to foulant deposition in complex geometries become particularly relevant. In this dissertation, several mathematical modeling and analytical aspects of the industrial membrane filtration process are investigated. A first-principles mathematical model for …


Performance Analysis Of The Dominant Mode Rejection Beamformer, Enlong Hu Aug 2022

Performance Analysis Of The Dominant Mode Rejection Beamformer, Enlong Hu

Dissertations

In array signal processing over challenging environments, due to the non-stationarity nature of data, it is difficult to obtain enough number of data snapshots to construct an adaptive beamformer (ABF) for detecting weak signal embedded in strong interferences. One type of adaptive method targeting for such applications is the dominant mode rejection (DMR) method, which uses a reshaped eigen-decomposition of sample covariance matrix (SCM) to define a subspace containing the dominant interferers to be rejected, thereby allowing it to detect weak signal in the presence of strong interferences. The DMR weight vector takes a form similar to the adaptive minimum …


Low-Reynolds-Number Locomotion Via Reinforcement Learning, Yuexin Liu Aug 2022

Low-Reynolds-Number Locomotion Via Reinforcement Learning, Yuexin Liu

Dissertations

This dissertation summarizes computational results from applying reinforcement learning and deep neural network to the designs of artificial microswimmers in the inertialess regime, where the viscous dissipation in the surrounding fluid environment dominates and the swimmer’s inertia is completely negligible. In particular, works in this dissertation consist of four interrelated studies of the design of microswimmers for different tasks: (1) a one-dimensional microswimmer in free-space that moves towards the target via translation, (2) a one-dimensional microswimmer in a periodic domain that rotates to reach the target, (3) a two-dimensional microswimmer that switches gaits to navigate to the designated targets in …


Diagnostics Of Energy Release In Solar Flares With Radio Dynamic Imaging Spectroscopy, Yingjie Luo Aug 2022

Diagnostics Of Energy Release In Solar Flares With Radio Dynamic Imaging Spectroscopy, Yingjie Luo

Dissertations

Studies of the magnetic energy release and conversion process lie at the core of solar flare physics. Radio observations serve as a unique diagnostic method. In this dissertation, taking advantage of broadband radio dynamic imaging spectroscopy observations made by the Karl G. Jansky Very Large Array (VLA), studies are carried out on the flare energy release processes using different types of radio emissions.

The VLA is a general-purpose radio observatory located in New Mexico, which provides high-quality radio dynamic imaging spectroscopic observations with an ultra-fast time cadence. In the first study, stochastic decimetric radio spike bursts are observed by the …


Understanding The Role Of Magnetic Field Evolution In The Initiation And Development Of Solar Eruptions, Nian Liu Aug 2022

Understanding The Role Of Magnetic Field Evolution In The Initiation And Development Of Solar Eruptions, Nian Liu

Dissertations

This dissertation aims to understand the initiation and evolution of solar eruptions. The essential science questions to answer include: What is the role of magnetohydro dynamic (MHD) instabilities and magnetic reconnection in triggering and driving eruptions? What are the role of Kink Instability (KI) and Torus Instability (TI) in determining the successful and failed eruptions? What is the thermal behavior of flare precursors in the initiation stage of solar eruptions? Finally, how does the corona magnetic field respond to the flare eruptions? The dissertation mainly includes the following studies.

First, this dissertation presents a multi-instrument study of the two precursor …


Efficient And Scalable Triangle Centrality Algorithms In The Arkouda Framework, Joseph Thomas Patchett Aug 2022

Efficient And Scalable Triangle Centrality Algorithms In The Arkouda Framework, Joseph Thomas Patchett

Theses

Graph data structures provide a unique challenge for both analysis and algorithm development. These data structures are irregular in that memory accesses are not known a priori and accesses to these structures tend to lack locality.

Despite these challenges, graph data structures are a natural way to represent relationships between entities and to exhibit unique features about these relationships. The network created from these relationships can create unique local structures that can describe the behavior between members of these structures. Graphs can be analyzed in a number of different ways including at a high level in community detection and at …


Coupled Oscillators: Protein And Acoustics, Angelique N. Mcfarlane Aug 2022

Coupled Oscillators: Protein And Acoustics, Angelique N. Mcfarlane

Theses

This work encompassed three different vibrational energy transfer studies of coupled resonators (metal, topological, and microtubule comparison) inspired by the lattices of microtubules from regular and cancerous cells. COMSOL Multiphysics 5.4 was utilized to design the experiment. The simulation starts with an acoustic pressure study to examine the vibrational modes present in coupled cylinders, representing α-, β-tubulin heterodimers. The Metal Study consisted of 3 models (monomer, dimer, and trimer) to choose the correct height (40 mm) and mode (Mode 1) for study. The Topological Study was run to predict and understand how the lattice structure changes over a parametric sweep …


One-Stage Blind Source Separation Via A Sparse Autoencoder Framework, Jason Anthony Dabin May 2022

One-Stage Blind Source Separation Via A Sparse Autoencoder Framework, Jason Anthony Dabin

Dissertations

Blind source separation (BSS) is the process of recovering individual source transmissions from a received mixture of co-channel signals without a priori knowledge of the channel mixing matrix or transmitted source signals. The received co-channel composite signal is considered to be captured across an antenna array or sensor network and is assumed to contain sparse transmissions, as users are active and inactive aperiodically over time. An unsupervised machine learning approach using an artificial feedforward neural network sparse autoencoder with one hidden layer is formulated for blindly recovering the channel matrix and source activity of co-channel transmissions. The BSS sparse autoencoder …


Planning Methodology For Alternative Intersection Design And Selection, Liran Chen May 2022

Planning Methodology For Alternative Intersection Design And Selection, Liran Chen

Dissertations

The recent publication of the 6th Edition of the Highway Capacity Manual included a chapter on Ramp Terminals and Alternative Intersections that introduces various alternative intersection designs and assesses the performance of Median U-turn, Restricted crossing U-turn and Displaced left-turn intersections. Missing from the literature is an alternative intersection selection tool for identifying whether an alternative intersection would be successful under local conditions. With limited information of organized alternative intersection research, most planners must rely heavily on their personal judgement while selecting the most suitable intersection designs. As appealing as alternative intersections are, there is no comprehensive methodology for planners …


Understanding The Voluntary Moderation Practices In Live Streaming Communities, Jie Cai May 2022

Understanding The Voluntary Moderation Practices In Live Streaming Communities, Jie Cai

Dissertations

Harmful content, such as hate speech, online abuses, harassment, and cyberbullying, proliferates across various online communities. Live streaming as a novel online community provides ways for thousands of users (viewers) to entertain and engage with a broadcaster (streamer) in real-time in the chatroom. While the streamer has the camera on and the screen shared, tens of thousands of viewers are watching and messaging in real-time, resulting in concerns about harassment and cyberbullying. To regulate harmful content—toxic messages in the chatroom, streamers rely on a combination of automated tools and volunteer human moderators (mods) to block users or remove content, which …


Waves And Oscillations In A Sunspot: Observations And Modeling Of Noaa Ar 12470, Yi Chai May 2022

Waves And Oscillations In A Sunspot: Observations And Modeling Of Noaa Ar 12470, Yi Chai

Dissertations

Waves and oscillations are important solar phenomena not only because they can propagate and dissipate energy in the chromosphere, but also because they carry information about the structure of the atmosphere in which they propagate. Among these phenomena, the one of the most interesting ones occurs in the sunspot umbra. In this area, continuously propagating magnetohydrodynamic (MHD) waves generated from below the photosphere create the famous 3-minute sunspot umbral oscillations that affect the line profile of spectral lines due to temperature, density, and velocity changes of the plasma in the region. In the past decades, numerous observations and models have …


Nondestructive Evaluation Of 3d Printed, Extruded, And Natural Polymer Structures Using Terahertz Spectroscopy And Imaging, Alexander T. Clark May 2022

Nondestructive Evaluation Of 3d Printed, Extruded, And Natural Polymer Structures Using Terahertz Spectroscopy And Imaging, Alexander T. Clark

Dissertations

Terahertz (THz) spectroscopy and imaging are considered for the nondestructive evaluation (NDE) of various three-dimensional (3D) printed, extruded, and natural polymer structures. THz radiation is the prime candidate for many NDE challenges due to the added benefits of safety, increased contrast and depth resolution, and optical characteristic visualization when compared to other techniques. THz imaging, using a wide bandwidth pulse-based system, can evaluate the external and internal structure of most nonconductive and nonpolar materials without any permanent effects. NDE images can be created based on THz pulse attributes or a material’s spectroscopic characteristics such as refractive index, attenuation coefficient, or …


Investigation Of Topological Phonons In Acoustic Metamaterials, Wenting Cheng May 2022

Investigation Of Topological Phonons In Acoustic Metamaterials, Wenting Cheng

Dissertations

Topological acoustics is a recent and intense area of research. It merges the knowledge of mathematical topology, condensed matter physics, and acoustics. At the same time, it has been pointed out that quasiperiodicity can greatly enhance the periodic table of topological systems. Because quasiperiodic patterns have an intrinsic global degree of freedom, which exists in the topological space called the hull of a pattern, where the shape traced in this topological space is called the phason. The hull augments the physical space, which opens a door to the physics of the integer quantum Hall effect (IQHE) in arbitrary dimensions. In …


A Self-Learning Intersection Control System For Connected And Automated Vehicles, Ardeshir Mirbakhsh May 2022

A Self-Learning Intersection Control System For Connected And Automated Vehicles, Ardeshir Mirbakhsh

Dissertations

This study proposes a Decentralized Sparse Coordination Learning System (DSCLS) based on Deep Reinforcement Learning (DRL) to control intersections under the Connected and Automated Vehicles (CAVs) environment. In this approach, roadway sections are divided into small areas; vehicles try to reserve their desired area ahead of time, based on having a common desired area with other CAVs; the vehicles would be in an independent or coordinated state. Individual CAVs are set accountable for decision-making at each step in both coordinated and independent states. In the training process, CAVs learn to minimize the overall delay at the intersection. Due to the …


Local Learning Algorithms For Stochastic Spiking Neural Networks, Bleema Rosenfeld May 2022

Local Learning Algorithms For Stochastic Spiking Neural Networks, Bleema Rosenfeld

Dissertations

This dissertation focuses on the development of machine learning algorithms for spiking neural networks, with an emphasis on local three-factor learning rules that are in keeping with the constraints imposed by current neuromorphic hardware. Spiking neural networks (SNNs) are an alternative to artificial neural networks (ANNs) that follow a similar graphical structure but use a processing paradigm more closely modeled after the biological brain in an effort to harness its low power processing capability. SNNs use an event based processing scheme which leads to significant power savings when implemented in dedicated neuromorphic hardware such as Intel’s Loihi chip.

This work …