Physical Sciences and Mathematics Commons^™

Model Performance For Predicting Trends And Analyzing The Impacts Of Sea Surface Temperature Changes In The Gulf Of Thailand, Tanatpong Udomchaipitak, Nathaphon Boonnam

Journal of Marine Science and Technology–Taiwan

This study focuses on assessing and improving the predictive performance of sea surface temperature (SST) in the Gulf of Thailand under unique environmental challenges. Data from the Hybrid Coordinate Ocean Model (HYCOM) were utilized, covering the period from July 1994 to June 2024 at depths ranging from 0 to 30 meters. After cleaning the data using the Interquartile Range (IQR) method, the processed dataset was tested using four models: Recurrent Neural Network (RNN) architectures, including Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), as well as Convolutional Neural Networks (CNNs). Model performance was enhanced by tuning the parameters over …

Explorations Of Dna-Single-Walled Carbon Nanotube Interactions To Develop Multiplexed Molecularly Specific Biosensors For Inflammation, Amelia K. Ryan

Dissertations and Theses

Inflammatory cytokines such as interleukin-6 (IL-6) and interleukin-12 (IL-12) are central regulators of immune signaling and key biomarkers of disease, yet existing assays for their detection remain slow, invasive, and lack multiplexing ability. This dissertation advances the development of single-walled carbon nanotube (SWCNT) optical nanosensors capable of real-time, multiplexed, and molecularly specific cytokine detection through innovative use of single-stranded DNA (ssDNA) interfaces.

First, an IL-6-specific DNA aptamer was employed as both a dispersing agent and recognition probe for SWCNT fluorescence sensing. Sequence modifications, including anchor domains, truncations, and thermally induced refolding, were systematically tested to optimize sensitivity and selectivity. The …

Development Of An Quadcopter Unmanned Aerial Vehicle For Atmospheric Remote Sensing, Omar J. Addasi

Dissertations and Theses

This paper explores the development of a quadcopter unmanned aerial vehicle (UAV, a.k.a. drone) for atmospheric remote sensing of temperature, pressure, humidity, and PM2.5 particulate matter quantities. A 3-D printed drone body is designed and flight tuning is performed. An optimal length for an upward extending mast for the drone body is determined. Low cost, lightweight sensors are compared against higher precision sensors in both static and dynamic conditions. In addition, an initial investigation into the design of a pressure sensor based anemometer is performed.

Classification Of Variable Stars Using Convolutional Neural Network, Abhina Premachandran Bindu

Dissertations and Theses

This research focuses on developing Convolutional Neural Networks (CNNs), for the process of classifying and identifying variable stars through the analysis of unprocessed light curves from Transiting Exoplanet Survey Satellite (TESS). As astronomical data is becoming increasingly complex, and as advanced missions deploy sophisticated instruments for data collection, both the quality and quantity of the data are improving at a rapid pace. This has created an urgent need to automate the analysis process using efficient and effective methods, such as those based on machine learning. While previous research has explored machine learning approaches, there has been limited focus on implementing …

Metasurfaces And Their Applications In Photonic Devices, Shuwei Guo

Dissertations and Theses

Metasurfaces are flat artificial optical elements composed of dielectric and/or metallic nanostructures. They can manipulate light in unprecedented ways by altering amplitude, phase, and polarization at subwavelength scales. The ability of these two-dimensional elements to perform multiple optical functions within compact optical systems—while offering high functionality, small form factors, and easy integration into optoelectronic devices—has sparked significant interest across various fields and industries. These applications span imaging, sensing, nonlinear and quantum optics, optical computing, automotive technology, augmented and virtual reality, and more.

In this dissertation, we explore and design new multifunctional metasurfaces with a focus on manipulating spectral responses. First, …

Using Deep Neural Nets In Writer Identification & Analysis, Aditya Majithia

Dissertations and Theses

This thesis focuses on developing automated deep learning methods for writer identification and writer attribute prediction from handwriting. It introduces two novel architectures: Convolutional Transformer Encoder (CTE) and Convolutional Swin Encoder (CSE). CTE is designed for determining authorship from handwritten text, be it modern or historical handwriting. CTE tracks subtle features and cues from handwriting strokes to distinguish authorship. It is the first of its kind capable to operate on historical handwritten fragments, setting it apart from existing methods that rely on entire document pages. CSE is designed to determine multiple attributes of an author such as authorship, gender, age …

Utilizing Deep Learning Audio Models For Blind And Low Vision Crosswalk Assistance, Wayne Lam

Dissertations and Theses

Navigating urban environments poses significant challenges for blind and low vision (BLV) individuals, particularly at street intersections where determining when it is safe to cross can be life-threatening. In New York City, where pedestrian fatalities are on the rise and only 2% of intersections are equipped with Accessible Pedestrian Signals (APS), alternative solutions are urgently needed. This thesis proposes an audio-based deep learning approach to support BLV individuals at crosswalks by detecting traffic movement direction and idling states using spatial sound. With 4-channel audio capturing capabilities of wearables, such as Meta Project Aria glasses, we explore state-of-the-art sound event localization …

Cognitive Map Generation For Vision And Language Navigation, Alexander Sandoval Mesa

Dissertations and Theses

Visual-Language Navigation (VLN) presents significant challenges for autonomous agents, such as robots and virtual assistants, particularly in complex, dynamic environments where the seamless integration of visual perception and natural language understanding is critical. Traditional VLN systems often struggle with effectively aligning language instructions and visual scene understanding, limiting their adaptability and navigation efficiency.

This thesis proposes a novel Cognitive Map-based framework that addresses these challenges by transforming natural language navigation instructions into structured graph representations. The Cognitive Map consists of nodes representing waypoints, landmarks, decision points, and edges encoding spatial relationships and navigational actions. These maps are generated using Large …

Integrating Satellite-Based Precipitation Analysis: A Case Study In Norfolk, Virginia, Imiya M. Chathuranika, Dalya Ismael

Engineering Technology Faculty Publications

In many developing cities, the scarcity of adequate observed precipitation stations, due to constraints such as limited space, urban growth, and maintenance challenges, compromises data reliability. This study explores the use of satellite-based precipitation products (SbPPs) as a solution to supplement missing data over the long term, thereby enabling more accurate environmental analysis and decision-making. Specifically, the effectiveness of SbPPs in Norfolk, Virginia, is assessed by comparing them with observed precipitation data from Norfolk International Airport (NIA) using common bias adjustment methods. The study applies three different methods to correct biases caused by sensor limitations and calibration discrepancies and then …

A Comprehensive Academic And Industrial Survey Of Blockchain Technology For The Energy Sector Using Fuzzy Einstein Decision-Making, Umit Cali, Annabelle Lee, Barry Hayes, Claudio Lima, D. Jonathan Sebastian-Cardenas, David Flynn, Emre Kantar, Farrokh Rahimi, Kaung Si Thu, Marco Pasetti, Marthe Fogstad Dynge, Merlinda Andoni, Muhammet Deveci, Murat Kuzlu, Raquel Alanso, Kim-Kwang Raymond Choo, Sambeet Mishra, Shammya Shananda Saha, Sonam Norbu, Srinikhil Gourisetti, Ugur Halden, Vahid Hosseinezhad, Valentin Robu

Engineering Technology Faculty Publications

The global energy sector is undergoing a significant transformation driven by decarbonization and digitalization, leading to the emergence of Distributed Ledger Technology (DLT) — particularly blockchain — as a promising tool for enhancing transparency, security, and efficiency in modern power systems. This study aims to provide a comprehensive academic and industrial survey of blockchain applications in the energy sector and develop a robust decision-making framework to identify and prioritize the most promising real-world use cases based on multidisciplinary criteria. A three-stage methodology was adopted: (i) a literature and market review encompassing over 300 academic publications and commercial blockchain initiatives in …

Integrating Sustainable Practices Into Lean Engineering: Applying The Engineering For One Planet Framework In Manufacturing Engineering Technology Education, Dalya Ismael, Vukica M. Jovanovic, Murat Kuzlu, Charles Lowe, Lisa Bosman

Engineering Technology Faculty Publications

A growing number of manufacturers are recognizing significant financial and environmental benefits from adopting sustainable business practices. Sustainable manufacturing refers to the production of goods through processes that are economically sound, minimize environmental impact, and conserve energy and natural resources. Lean engineering, a comprehensive approach to decision-making and leadership within manufacturing organizations, has proven effective in driving sustainable practices. Key strategies include waste elimination, value identification, value stream mapping, flow creation, pull system establishment, and continuous improvement. Both lean manufacturing and sustainability share a common focus on minimizing waste. Lean principles address seven types of waste: transport, inventory, motion, waiting, …

Using Quanser Platform To Introduce Engineering Technology Students To Autonomous Vehicles, Otilia Popescu, Logan Beaver, Murat Kuzlu, Krishnanand Kaipa

Engineering Technology Faculty Publications

The area of autonomous vehicles is not new, but the latest advances in various technologies gave it a new boost in the last decade and it keeps growing in interest. However, undergraduate curricula rarely include courses specific to this area, which is considered mostly an interdisciplinary graduate field. While various programs introduce students to the background needed to understand and approach the field, specific work on autonomous vehicle projects is left for extra curriculum activities or student clubs, and eventually for senior (capstone) projects. This paper presents the work of a team of electrical engineering technology students on an autonomous …

5g-Enabled Iot Gateway For Educational Purposes, Murat Kuzlu

Engineering Technology Faculty Publications

The project aims to develop and implement a 5G-IoT gateway for efficient management and interconnection of IoT devices through advanced sensing and communication technologies. Sensing technologies encompass modern approaches for detecting and measuring physical properties with high accuracy across manufacturing, smart grids, healthcare, smart cities, and other domains. Communication technologies represent the latest developments in high-speed data transmission, offering enhanced reliability and network capacity. This 5G-IoT gateway functions as an educational platform, providing students and educators with hands-on experience in emerging technologies. The system creates opportunities for practical learning and research in telecommunication technologies by enabling direct engagement with 5G …

A Wall Of Smoke: Understanding The Drivers Of The June 2023 Canadian Wildfire Smoke Event For New York City, Gregory S. Randazzo

Dissertations and Theses

The 2023 Canadian wildfire season was notable for its extent and the dense smoke it produced. Motivated by the resulting air quality impacts in the New York City region, we explore how the total particulate matter output from the Quebec fires influenced PM2.5 concentrations downstream in New York City. Using injection height data from the Regional Advanced Baseline Imager + VIIRS Emissions dataset, we relate the tropospheric injection heights of the fires with the broader synoptic context and surface PM2.5 concentrations. Using data from the NYS Mesonet Profiler Network, radiosondes, and ERA5 reanalysis, we document the connection between an anomalous …

Using Trace Gas Measurements As A Transport Diagnostic For Tropical Convection: A Combined Model And Observation Study, Albane Hoxha

Dissertations and Theses

No abstract provided.

Building Obsolescence: Key Factors Influencing Demolition Decisions For Commercial Buildings, Azlan Shah Ali, Zakaria Norhanim, Zulkifly Umi-Kalsum, Zaki Faiz

Research Publications (2021 to 2025)

Buildings, while primarily serving to provide shelter, can deteriorate over time without proper maintenance and planning, leading to obsolescence, a significant threat to their functionality. This study investigates the factors contributing to building obsolescence and how they influence the selection of adaption strategies, focusing on commercial buildings as a case study. Questionnaire data were gathered from 386 business owners and occupants of obsolete buildings in Klang Valley, Malaysia, to capture their perspectives on the issue. Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) were employed to rank obsolescence factors and solution options on strategies on obsolescence factors. PCA results …

Carbon Sequestration Through Conservation Tillage In Sandy Soils Of Arid And Semi-Arid Climates: A Meta-Analysis, Samantha Lynn Colunga, Leila Wahab, Alejandro Fierro-Cabo, Engil Isadora Pujol Pereira

School of Earth, Environmental, & Marine Sciences Faculty Publications

Highlights

• Under CST, SOC increased by 12.74 ± 1.46 % in sandy soils with 5 of the 6 practices contributing to this rise.
• SOC increased up to 15 years post-CST conversion, but more research is needed to assess long-term effects.
• SOC increased by 13% in soils with over 56% sand content under CST.
• SOC increased by 15% in the 0-20 cm depth under CST, with no significant increase at greater depths.
• SOC increased under CST when nitrogen was applied at rates up to 100 kg N ha⁻¹.

Abstract

This meta-analysis assessed soil organic carbon (SOC) percent changes in sandy soils, …

Evaluating Annual Precipitation Extremes In The Us Great Plains Using Prism Data, Sumiaya Amin Preota, Gaurav Talukdar, Sam Zipper

School of Earth, Environmental, & Marine Sciences Faculty Publications

Understanding hydroclimatic extremes in the U.S. Great Plains (USGP) is crucial for effective water resource management, resiliency of agricultural systems, and mitigation of climate change impacts. This study examines changing hydroclimatic conditions in the USGP, with a focus on annual-resolution precipitation trends and extremes over the past 119 years (1904–2022) using precipitation data from the gridded PRISM climate dataset. We categorized annual-scale precipitation totals into six categories of hydroclimatic extremes: (1) isolated wet extremes, (2) isolated dry extremes, (3) dry-to-dry recurring extremes, (4) wet-to-wet recurring extremes, (5) dry-to-wet whiplash extremes, and (6) wet-to-dry whiplash extremes. “Recurring” and “whiplash” are both …

Nesting Population Trend Of The Leatherback Sea Turtle In Bocas Del Toro Province And Comarca Ngäbe-Buglé, Panama For The Period 2002–2022, Sonia Gutiérrez Parejo, Susan E. Piacenza, Raúl García, Cristina Ordóñez, Roldán A. Valverde

School of Earth, Environmental, & Marine Sciences Faculty Publications

Sea turtle biologists have made sustained efforts to understand the global status of leatherback sea turtle populations. However, despite progress in assessments, demographics, and ecology, key uncertainties persist in tracking leatherback population trends. Trend analyses have historically focused on nesting beaches, with nest counts providing a widely used index for population abundance. Here, we analysed 20 years of annual nest abundance at four main nesting beaches (Soropta, Bluff, Playa Larga and Chiriquí) in Bocas del Toro province and the Comarca Ngäbe-Buglé, Panama, which constitute the largest nesting leatherback sea turtle population in Central America. We conducted daily nest counts during …

Photoswitchable Inhibitors Of Eaat3, Karly Suhr

Electronic Theses & Dissertations (2024 - present)

Azobenzene is a photoswitchable molecule known for its high conversion yield and repeatability. The inclusion of an azobenzene moiety with a known inhibitor of your target of interest allows for greater study of function as well as potential therapies. Three derivatives were designed from azobenzene and known inhibitor of EAATs, TBOA, to synthesize photoswitchable inhibitors of EAATs. Further investigation into the function of EAATs and development of a specific inhibitor for EAAT3, an important glutamate transporter in the brain required for proper function, can then be conducted. Photoisomerization studies on the derivatives were conducted using UV/vis spectroscopy and NMR spectroscopy. …

Demonstration And Assessment Of Dark Field And Phase X-Ray Computed Tomography, Wadiah Hamed Allahyani

Electronic Theses & Dissertations (2024 - present)

Conventional computed tomography produces a 2D slice or 3D image from multiple conventional images to avoid overlapping structures and increase visualization of the internal features of the object. A set up, macro controls and processing for computed tomography was created for the Center for X-ray Optics for the first time, and demonstrated in this work. Adding differential phase contrast to conventional x-ray images highlights edges. Two more channels of information, dark field and integrated phase, improve the contrast and increase the signal-to-noise ratios of the image. Combining these channels with computed tomography is an important development. This work is the …

Large Scale Machine Learning Over Knowledge Graphs, Bedirhan Gergin

Electronic Theses & Dissertations (2024 - present)

Knowledge graphs (KGs) have become popular across various fields, providing convenient access to web-based knowledge while storing and formalizing domain-specific information. By analyzing KGs, patterns, connections, and dependencies can be identified across different data sources, enabling the inference of new knowledge from given facts. As the use of KGs expands, the size of modern KGs has grown significantly, making them impossible to process within the main memory of a single computer. Distributed computing offers a viable solution to this challenge by leveraging the combined capabilities of multiple servers within a cluster. This thesis explores how distributed computing can be effectively …

Dynamics Of Mesoscale Offshore Wind Flows From An Observational And Modeling Perspective: Implications For Offshore Wind Energy, Elizabeth J. Mccabe

Electronic Theses & Dissertations (2024 - present)

Mid-latitude coastal regions of the United States, such as the New York Bight (NYB), are playing a major role in the development of offshore wind energy. However, mesoscale dynamics of local and regional circulations in these offshore waters are poorly understood. The sea breeze, especially in the NYB, will play a key role in the development of offshore wind energy, given the favorable wind speeds and high capacity factors during periods of peak demand. With limited vertical wind profile observations available offshore, the ability to accurately forecast and understand the spatiotemporal extent of the sea breeze and often associated low-level …

Analysis Of Extreme Rainfall And Streamflow Events In The Catskill/Delaware Catchment Using The New York State Mesonet, Ada Ellingworth

Electronic Theses & Dissertations (2024 - present)

Extreme rainfall and streamflow often lead to increased turbidity in reservoirs in the Catskill/Delaware catchment, which is part of the New York City water supply system. To better understand extreme events that lead to increased turbidity, this study takes a dual approach: first, we identify hydrologic conditions during extremes to understand when and why extremes occur. Next, we evaluate an identified extreme case to evaluate mesoscale model skill in this region. Measurements from the New York State Mesonet and United States Geological Survey are used to identify hydrologic conditions from 2017-2024 associated with three extreme event types: rainfall, streamflow, and …

Analysis Of Cytokine Data In A Case-Control Study Of Me/Cfs, Navya Amaratunga

Electronic Theses & Dissertations (2024 - present)

This study investigated the role of cytokines in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), a debilitating multi-system disease with unknown etiology. Using data from a case-control study (60 cases, 61 controls) previously collected by Dr. Roxana Moslehi’s lab, serum levels of 48 cytokines were analyzed. Statistical analyses, including T-tests, Wilcoxon Rank Sum tests, and logistic regression (unadjusted and adjusted for medication use), were performed to identify differences between cases and controls.

Results revealed a statistically significant difference in mean Fractalkine levels between cases and controls (p=0.031). Borderline significant differences were also observed for IL-6 (p=0.046) and MIP-1α (p=0.046). Unadjusted logistic regression …

Establishing A Conventional Linac-Based Electron Flash Beam, Justin Defrancisco

Theses and Dissertations

Problems: A rediscovered radiotherapy technique, FLASH, involves increasing the dose rate to >40 Gy/s. For a given dose, FLASH is shown to decrease the normal tissue complication probability without affecting the tumor control probability. More preclinical studies are necessary to confirm and enable these desirable properties on humans. Current preclinical investigations have diverse constraints, requiring FLASH apparatuses with flexible parameters and accurate control. However, there are limited FLASH platforms available, the existing ones are costly. Our institution is not in possession of any such infrastructure. Even if available, dosimetry and beam control in FLASH are extremely lacking. There is …

Modeling The Impacts Of The Current And Projected Temperatures On Spongy Moth Population Dynamics, Adrienne B. Spring

Theses and Dissertations

The spongy moth (Lymantria dispar) is an invasive forest pest that has caused significant ecological damage across the United States. Its invasion front is shaped by a number of factors, including temperature in both the northern and southern regions. With ongoing climate change, areas that were previously uninhabitable may become increasingly favorable for moth population establishment and expansion, while other areas may experience thermal stress limiting persistence. This study develops a temperature-driven population model to analyze how temperature affects the spongy moth population dynamics along the invasion front. This model incorporates temperature effects on fecundity, stage-specific survival rates, …

A Fault-Tolerant Exchange-Coupled Spin-Ensemble Qubit At Elevated-Temperatures, Aniruddha Chakraborty

Theses and Dissertations

This thesis introduces a novel qubit architecture: the ferromagnetic exchange-coupled spin ensemble qubit (E-qubit), designed to address the noise-induced instability. In this work, the time evolution of the ensemble’s density matrix is studied using the Liouville–von Neumann equation. To benchmark against a single-spin qubit, the gate fidelity of an E-qubit is computed in the presence of thermal noise. Coherence time is also analyzed under identical thermal condition and a linear scaling is observed with qubit size . The results show that, at 6 K , the gate fidelity error (0.7 % ) of the seven- spin ensemble is an order …

Investigating The Temperature Effects On Aedes Aegypti And Dengue Virus In Central Argentina: Perspectives From Mathematical Modeling, Morgan H. Jackson

Theses and Dissertations

Dengue virus (DENV) causes over 390 million infections and around 40,000 deaths worldwide each year. DENV is primarily transmitted by the mosquito Aedes aegypti, and both the life cycle of these mosquitoes and DENV transmission are significantly impacted by temperature. In the temperate region of Central Argentina, where dengue outbreaks first began in 2009, outbreaks only occur following new introductions of DENV from other regions. Due to the relationships between temperature and DENV and temperature and Ae. aegypti, the risk of an outbreak changes throughout the year. Here, we develop and analyze mathematical models for both mosquito population dynamics and …

Periodic Trends In The Electronic And Magnetic Structure Of Superatomic 3d Transition Metal Chalcogenide Clusters, Gabriel Bohannon

Theses and Dissertations

We have systematically investigated the electronic structure of octahedral transition metal chalcogenide clusters, TM₆S₈(CO)₆, in which the transition metal atoms are from the 3d series in order to identify if periodic properties emerge. We were motivated by the identification of closed electronic shells with electron counts of 96, 100 and 114 in similar clusters from the 4d and 5d transition metal series. Further motivation was the finding of a dual-shell closing in the Fe₆S₈(CN)₆^5- cluster. This cluster is stabilized with a large spin magnetic moment due to the …