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Epitaxial Quantum Dot Scintillators With Monolithic Photodetector Integration: Physics, Fabrication And Characterization Of Materials And Devices, Allan Oreave Minns

Electronic Theses & Dissertations (2024 - present)

This dissertation discloses the physics, fabrication, and characterization of high-performance scintillator detectors based on epitaxial InAs quantum dots (QDs) in GaAs. The detector crystals grown include monolithically integrated In_0.35GaAs photodetectors with Al_0.92-0.6In_0.03-0.35Ga_0.05As metamorphic buffer layers (MBL). A device fabrication process was developed for the lithographic patterning, chemical etching, contact metallization and readout integration of materials grown by means of molecular beam epitaxy (MBE) on 3-inch GaAs (001) wafers. Low capacitance integration with readout electronics was achieved through wire bonds to custom printed circuit boards (PCBs) with commercial components.

The relationship between device …

Mobile Air Quality Assessment Using Public Transportation: A Community-Focused Study In The Capital Region, Allen Pronith Reddy Yeddula

Electronic Theses & Dissertations (2024 - present)

The monitoring of air quality plays a crucial role in establishment of concentrations of air pollutants over space and time in relation to human health, urban planning, and environmental conservation. This research offers a new strategy of monitoring the air quality in the Capital Region of New York State utilizing public transit buses as air quality moving sampling platforms. To assess the level of pollutants, a Capital District Transportation Authority (CDTA) bus network was used across the urban, suburban, and rural areas thus filling a research gap where public transit has most of the time been disregarded as a mobile …

Assessment Of Surface Area Application Ratios For Beach Sand Treated Via Surface Percolated Micp-Bioslurry For Erosion Mitigation, Connor J. Marlin

UNF Graduate Theses and Dissertations

Rapid shoreline erosion associated with sea-level rise is an ongoing threat to coastal infrastructure. Traditional stabilization techniques, such as revetments, seawalls, and periodic nourishment, often prove costly, ecologically disruptive, or provide only temporary protection. Microbially Induced Calcite Precipitation (MICP) and its operational variant, bioslurry, present a biologically inspired alternative capable of forming a cemented surface crust that reduces soil erodibility. Previous laboratory studies typically prescribed a solution dosage as a percentage of pore volume (%PV). While geotechnically sound, this metric is poorly suited to field deployment across a large area. This thesis evaluates surface-area-based dosing (L/m²) as the primary dosage …

Computational Pangenomics And Machine Learning For Genotype-Phenotype Analysis, Tejaswi Vemuri

UNF Graduate Theses and Dissertations

Phenotypes are the observable characteristics of an individual organism. Predicting quantitative phenotypes from genomic variation remains challenging when causal signals span both local motifs and distal regulatory contexts. Building on Frequented Regions (FRs)—subsequences conserved across genomes and extracted from a pangenome graph generated from a large collection of closely related species—we compare several modeling strategies across 35 Saccharomyces cerevisiae growth phenotypes: Random Forest (RF) on FR counts (called RFCounts), RF on FR sequences, 1D convolutional neural networks (CNN) on FR sequences, Long Short-Term Memory (LSTM) networks on FR sequences, a Genomewide Association Study (GWAS) baseline, and a sequence-based transformer model, …

Influence Of Crabgrass Root Exudates On The Hydrocarbons Degrading Microorganisms In Crude Oil Contaminated Soil, Sinha Changsiriwatana, Kwang Mo Yang, Toemthip Poolpak, Prayad Pokethitiyook

Applied Environmental Research

Understanding plant‒microbial interactions in petroleum-contaminated soil is critical for enhancing phytoremediation technology. In this study, the root exudate of crabgrass (Digitaria ciliaris) was collected hydroponically, and its dominant composition was identified via GC‒MS. A soil microcosm study was subsequently conducted to evaluate the influence of crabgrass root exudates on microbial growth, dehydrogenase activity, and biodegradation of total petroleum hydrocarbons by the petroleum-degrading bacteria Micrococcus luteus WN01 and Acinetobacter lwoffii A07. The amendment of crabgrass root exudates significantly promoted microbial degradation in both A. lwoffii A07 (47.98%) and M. luteus WN01 (62.78%), which were 8.47% and 15.78% greater than …

Macroplastic Characteristics And Assessment Of The Plastic Abundance Index (Pai) Of Beach Sediments In Prigi Bay, East Java, Indonesia, Adinda P.A. Nevandhra, Seftiawan S. Rijal, Syarifah H.J. Sari, Defri Yona

Applied Environmental Research

Macroplastics, defined as plastic debris ranging from 2.5 to 100 cm, pose significant threats to aquatic ecosystems, as they can breakdown into smaller particles. These materials are widely dispersed across marine environments, including coastal areas. This study aimed to compare and assess the abundance of macroplastics in the foreshore and backshore zones of four beaches around Prigi Bay, East Java, Indonesia, via the plastic abundance index (PAI). Macro-plastics were collected via a 5×5 m quadrat transect method. The results revealed that single-use plastics, particularly packaging and sachets, dominated both zones, accounting for 86% and 91% of the total number of …

The Use Of Machine Learning Algorithms For Water Quality Index Prediction In The Sai Gon River, Vietnam, Thuy Nguyen Thi Diem, Mai Nguyen Thi Huynh, Tra Tran Quang

Applied Environmental Research

Accurate prediction of the water quality index (WQI) lays the groundwork for integrated river basins and sustainable water resource management. Recent and accelerated advances in machine learning have led to various promising applications in water quality assessment. The present study leverages the predictive performance of several ML algorithms, including extreme gradient boosting (XGB), the gradient boosting model (GBM), support vector regression (SVR), and the radial basic function (RBF), to predict the WQI at three monitoring sites on the Sai Gon River from 2015–2019. In comparison, the results indicate that the XGB model outperforms the other models when eight parameters, including …

Effects Of Herbicides On 2,4-D-Resistant Soil Microorganisms In Maize Cultivation In Lopburi Province, Thailand, Boontarik Chimchart, Jitra Kokaew, Amnat Eamvijarn, Kanokon Bunpha, Sontaya Khamtib, Monchai Manassila, Tawatchai Inboonchuay

Applied Environmental Research

This study aimed to assess the impact of herbicide application on soil micro-organism density and to identify microorganisms resistant to 2,4-D-dimethyl-ammonium (2,4-D) for potential biodegradation. Research was conducted in maize plots in Lopburi Province, where 2,4-D was applied at a rate of 120 g of active ingredient per 160 m2. The soil samples were collected at various intervals: before application; 2 and 4 hours postapplication; and 1, 3, and 7 days after application. The analyses included soil property and microorganism population analyses. The results indicated that 2,4-D applications significantly increased bacteria and fungi in the treated plots compared with those …

Kinetics Of Hexavalent Chromium Adsorption And Reduction By Living Cells Of The Marine Bacterium Bacillus Cereus, Jittima Charoenpanich, Wachiraphorn Cherdchoo, Jutamas Pantab, Jariya Supakrit

Applied Environmental Research

This study identified Bacillus cereus, an efficient Cr(VI) bioreducer, isolated from marine sediment in Thailand. Batch experiments verified the complete removal of 25 mg L-1Cr(VI) from synthetic wastewater (pH 7.0) after 6 days at 37 °C, 50 rpm,and a biomass concentration of 25% (v/v) culture inoculum. The Freundlich isotherm model demonstrated the best correlation with the Cr(VI) adsorption equilibrium data in the 25–100 mg L-1concentration range (R2= 0.9831). Kinetic analyses indicated that the removal of Cr(VI) by living B. cereusfollowed a pseudo-second-order adsorption model (R2= 0.9875) and a pseudo-second-order reduction model (R2= 0.9807). The adsorption rate can be accuratelycharacterizedvia the …

Evaluation Of The Maneuverability Of An 85m Fishing Trawler (Focusing On Dynamic Stability), Chun-Ki Lee, Su-Hyung Kim

Journal of Marine Science and Technology–Taiwan

Most fishing vessels are less than 100 meters in length, so IMO maneuverability standards do not apply. As a result, studies on the maneuverability of fishing vessels are considerably fewer compared to those on merchant ships. However, with technological advancements, the size of fishing vessels continues to grow, and as more fishermen are on board, accidents could lead to fatal casualties. In response, the authors determined that research on the maneuverability of fishing vessels is urgently needed. Thus, the authors conducted a maneuverability evaluation on a fisheries training vessel with the hull shape of a fishing trawler, 85 meters in …

A Hybrid Image Filtering Approach For Improving Edge Detection Of Riverbed Particles With Complex Textures, Po-Wei Lin, Hsun-Chuan Chan

Journal of Marine Science and Technology–Taiwan

The distribution of particle size in gravel-bed rivers affects the flow condition, sediment transport, and river morphology. However, conventional particle size analysis is laborious and time-consuming. To enhance the efficiency of particle size analysis, image-based methods have been widely explored, but complex particle textures increase the difficulty in identifying particle edges during image analysis. This study develops a filtering approach based on the rolling guidance filter and leverages the differences in grayscale gradients between particle edges and textures to design a guidance image tailored for the rolling guidance filter. This design enables the filter to preserve particle edges while smoothing …

Comparison Of Canopy Materials To Improve The Performance Of Sea Anchors Used For Fishing Operations, Namgu Kim, Su-Hyung Kim, Yoo-Won Lee, Kyung-Jin Ryu

Journal of Marine Science and Technology–Taiwan

Sea anchors used for fishing operations help improve catch rates by stabilizing vessel drift speeds to match tidal or ocean currents. The underwater resistance experienced by a sea anchor's canopy significantly impacts its performance, yet there has been limited research on canopy materials. This study investigates how different canopy materials can enhance sea anchor performance. Specifically, we tested sea anchors made from three fabrics: the currently used polyamide (PA) material, PA material with increased yarn density in the weft direction, and polyester (PES). Using Korean national standards, we compared the yarn density, weight, water absorption capacity, drying rate, air permeability, …

Research On Ship Track Prediction Based On Ipso-Cnn, Xiangen Bai, Nuo Chen, Xiaofeng Xu

Journal of Marine Science and Technology–Taiwan

With the rapid development of the global economy, international imports and exports have become increasingly important. Timely and effective tracking and prediction of ship trajectories are important in the face of complex maritime traffic. Based on AIS data, this study establishes a ship trajectory prediction model combining improved particle swarm optimization (IPSO) and a convolutional neural network (CNN) that uses the ship's historical navigation trajectory data to predict the future navigation trajectory. The historical ship trajectory data of the Port of Ningbo-Zhoushan were selected for the experiment, and the IPSO-CNN model experiment results were compared with those of other models. …

Evorgcn: Harnessing Esm-2 Evolutionary Embeddings With Relational Gcns For High-Fidelity Protein-Protein Interaction Prediction, Mohit Kunder

Master's Projects

Accurately predicting protein-protein interactions (PPIs) is essential for understanding cellular function and advancing biomedical discovery. We model PPIs as graphs, where nodes represent proteins and edges denote interactions. Using interaction data from the STRING database, we use two samples of it, namely the benchmark datasets—SH27K and SH148K—filtered by confidence score and annotated by interaction mode (multiple relations). In this project, we present EvoRGCN, a graph-based machine learning framework for PPI prediction that integrates both sequence-level (ESM-2 embeddings) and network-level information. We incorporate various Graph Neural Network architectures, including Graph Convolutional Networks, Graph Attention Networks, and Relational Graph Convolutional Networks. Our …

Metal-Organic Thin Film Coated On Optical Fiber, Nahideh Salehifar

Doctoral Dissertations

This dissertation explores the development of metal-organic framework (MOF)-based optical fiber sensors for detecting volatile organic compounds (VOCs) at low concentrations (parts-per-billion to parts-per-million). In the first part of the study, theoretical calculations were performed using effective medium approximation (EMA) models, including Lorentz–Lorentz, Maxwell–Garnett, and Bruggeman equations, to predict the refractive index changes of MOFs upon gas adsorption. These models were applied to MOFs such as ZIF-7, ZIF-8, ZIF-90, MIL-101(Cr), and HKUST-1 to evaluate their potential for gas sensing.

In the second part of the dissertation, experimental work was conducted to validate the theoretical predictions. MOF-coated optical fibers were fabricated …

Design Of Real-Time And Energy-Efficient Driver Assist Systems Using Electroencephalogram And Neuromorphic Computing, Nathan Alan Lutes

Doctoral Dissertations

Despite the technological breakthroughs in advanced driver assist systems, distracted driving persists as a major challenge to roadway safety. This investigation advances the body of knowledge towards a solution by developing an individualized driver-state detection method using electroencephalogram (EEG) and neuromorphic computing to provide a less invasive and more energy efficient ADAS solution. It furthermore explores the changes in brain functional connectivity under distracted conditions to better understand brain state information that could be used for neuro-feedback intervention systems. The first contribution introduces the concept of using Convolutional Spiking Neural Networks (CSNNs) for recognition of patterns with movement-intention predictive power …

Enhanced Optimization Of Mass Transfer For Carbon Capture And Wastewater Remediation In Algal Systems Through Algorithmic And Bioprocessing Techniques, Peter Ofuje Obidi

Doctoral Dissertations

The scalability and industrial deployment of algal cultivation systems are limited by suboptimal mass transfer, constraining their effectiveness in carbon capture and wastewater remediation. This research investigated these challenges through integrated optimization methodologies that combine algorithmic frameworks with enhanced bioprocessing techniques to enhance efficiency, economy, and scalability. A System-of-Systems (SoS) meta-architecture was developed using genetic algorithms and fuzzy assessor functions to demonstrate a pathway toward cost reduction. Rigorous mechanical and chemical characterizations were quantitatively analyzed to reveal existing optimization strategies and further evaluated the best strategies to use in enhancing mass transfer for improved biomass yield. The work also integrates …

Automation To Autonomy: Temporal Dynamics Of Trust And Visual Attention Allocation Did Not Evolve, Tetsuya Sato, Eric Chancey, Yusuke Yamani

Psychology Faculty Publications

Emerging work environments are expected to implement autonomy that performs various functions without human input. Previous works has shown that trust in automation is negatively correlated with visual attention allocation, indicating that trust is a dynamic construct. Moreover, trust in automation and trust in autonomy appears to evolve in similar ways. However, recent work has demonstrated differences between trust in automation and trust in autonomy within Kaber’s (2018) theoretical framework (Sato et al., 2023b). Yet, it is uncertain whether the development of trust and visual attention allocation differs between automation and autonomy. The present study examined the temporal dynamics of …

Intelligent Tutoring Systems In The Age Of Llm-Based Agentic Frameworks - Adapting Small On-Device Language Models For Fact-Checking And Student Compliance Detection, Evan Vahid Naderi

Honors Undergraduate Theses

As large language models (LLMs) demonstrate increasingly sophisticated language understanding capabilities, they offer transformative potential for educational technology, particularly in developing more responsive intelligent tutoring systems (ITS). To develop these systems, a synthesis that balances theoretical frameworks with practical, cutting-edge, and deployable technology would be useful. This thesis aims to advance the field of ITSs theoretically by viewing the modern advancements in natural language processing within the context of the foundational frameworks important to the fields of self-regulated learning, ITSs, and cognitive agents. Then, building on prior research on the ITS MetaTutor \citep{Azevedo2022}, this research focuses on how functions of …

Your Foot Is Not A Brick: Using A Multi-Segment Foot Model To Explore The Actions Of The Ankle-Foot Complex During Uneven Terrain Gait., Tayler Jon Hoekstra

Dissertations and Theses

The field of biomechanics has seen continued development of models to be used and circumstances to be considered. An increasing number of more complex models for the foot known as multi-segment foot models (MSFMs) have created opportunities to better understand the compensatory motion of this vital portion of human anatomy. This research seeks to utilize one such MSFM model to increase understanding in how human ambulation changes in uneven terrain environments. Unique inner-foot joints defined by the Rizzoli foot model (RFM) were measured for and compared for subjects traversing both even and uneven terrain to quantify joints that experienced significant …

The Pre-Polarization And Concentration Of Cells Near Micro-Electrodes Using Ac Electric Fields Enhances The Electrical Cell Lysis In A Sessile Drop, Kishor Kaphle, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Cell lysis is the starting step of many biomedical assays. Electric field-based cell lysis is widely used in many applications, including point-of-care (POC) applications, because it provides an easy one-step solution. Many electric field-based lysis methods utilize micro-electrodes to apply short electric pulses across cells. Unfortunately, these cell lysis devices produce relatively low cell lysis efficiency as electric fields do not reach a significant portion of cells in the sample. Additionally, the utility of syringe pumps for flow cells in and out of the microfluidics channel causes cell loss and low throughput cell lysis. To address these critical issues, we …

Mxenes In Biosensing: Enhancing Sensitivity And Flexibility - A Review Of Properties, Applications, And Future Directions, Ali Mohammad Amani, Lobat Tayebi, Ehsan Vafa, Alireza Jahanbin, Milad Abbasi, Ahmed Vaez, Hesam Kamyab, Lalitha Gnanasekaran, Shreeshivadasan Chelliapan

Electrical & Computer Engineering Faculty Publications

MXenes are a novel type of nanostructured material that has received a lot of attention for their potential applications in bioanalysis owing to their unique features. These materials, made from transition metal nitrides, carbides, or carbonitrides, have a number of advantages, including high hydrophilicity, a large surface area, strong metallic conductivity, superior ion transport capabilities, biocompatibility, and low diffusion barriers. Their surfaces are easily manipulated, making them more adaptable for a variety of applications, including biosensing. The outstanding properties of MXenes have attracted researchers of different fields, including renewable energy, fuel cells, supercapacitors, electronics, and catalysis. In the context of …

A Comprehensive Exploration Of 6g Wireless Communication Technologies, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Md. Shahriar Uzzal, H. M. Dipu Kabir

Electrical & Computer Engineering Faculty Publications

As the telecommunications landscape braces for the post-5G era, this paper embarks on delineating the foundational pillars and pioneering visions that define the trajectory toward 6G wireless communication systems. Recognizing the insatiable demand for higher data rates, enhanced connectivity, and broader network coverage, we unravel the evolution from the existing 5G infrastructure to the nascent 6G framework, setting the stage for transformative advancements anticipated in the 2030s. Our discourse navigates through the intricate architecture of 6G, highlighting the paradigm shifts toward superconvergence, non-IP-based networking protocols, and information-centric networks, all underpinned by a robust 360-degree cybersecurity and privacy-by-engineering design. Delving into …

Incorporating Insulin Into Alginate-Chitosan 3d-Printed Scaffolds: A Comprehensive Study On Structure, Mechanics, And Biocompatibility For Cartilage Tissue Engineering, Afsaneh Jahani, Mohammad Sagdegh Nourbakhsh, Ali Moradi, Marzieh Mohammadi, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Osteoarthritis is a leading cause of disability worldwide, challenging current treatments to limited cartilage self-healing capacity. Cartilage tissue engineering (CTE) integrates cells, scaffolds, and signaling molecules, with Insulin being utilized as a differentiation biomolecule due to cost-effectiveness, dose-dependent influence on chondrogenesis, suitable biological activity, and ability to activate relevant receptors. Yet, administering differentiation biomolecules through conventional scaffolds poses a persistent challenge. Alginate (Alg) is commonly employed in CTE for its biocompatibility, though it lacks sufficient mechanical properties. Chitosan (Cs), while enhancing scaffold mechanical properties, but does not independently provide optimal support for chondrogenesis. While Alg-Cs scaffolds have garnered attention, challenges …

Optimizing Ai Language Models: A Study Of Chatgpt-4 Vs. Chatgpt-4o, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Md Fayaz Bin Hossen, Muhammad Rezaur Rahman, Md. Shahadat Jaman

Electrical & Computer Engineering Faculty Publications

This paper presents a comparative analysis of OpenAI's GPT-4 and its optimized variant, GPT-4o, focusing on their architectural differences, performance, and real-world applications. GPT-4, built upon the Transformer architecture, has set new standards in natural language processing (NLP) with its capacity to generate coherent and contextually relevant text across a wide range of tasks. However, its computational demands, requiring substantial hardware resources, make it less accessible for smaller organizations and real-time applications. In contrast, GPT-4o addresses these challenges by incorporating optimizations such as model compression, parameter pruning, and memory-efficient computation, allowing it to deliver similar performance with significantly lower computational …

Personalized Prediction Of Tumor Recurrence With Image-Guided Physics-Informed Computational Model In High-Grade Gliomas, Walia Farzana, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

High grade gliomas are infiltrating tumors characterized by their diffusive invasion and proliferative growth. Across and within patients heterogeneity of tumors makes it challenging to determine tumor spatial extent after surgical resection. Traditionally, tumor growth predictions after surgical resections rely on generalized models and population-based observations, which do not account for individual patient differences. To address this gap, we propose a personalized approach with image-guided computational model (digital twin) that incorporates physics-based modeling to predict tumor recurrence. Our digital twin involves an inverse modeling step, followed by a recurrence model that accounts for varying surgical effects. The physics-guided inverse model …

A Method For Ultrasound Servo Tracking For Puncture Needle, Shitong Ye, Bo Yang, Hao Quan, Shan Liu, Minyu Tang, Jiawei Tian

Electrical & Computer Engineering Faculty Publications

Computer-aided surgical navigation technology helps and guides doctors to complete the operation smoothly, which simulates the whole surgical environment with computer technology, and then visualizes the whole operation link in three dimensions. At present, common image-guided surgical techniques such as computed tomography (CT) and X-ray imaging (X-ray) will cause radiation damage to the human body during the imaging process. To address this, we propose a novel Extended Kalman filter-based model that tracks the puncture needle-point using an ultrasound probe. To address the limitations of Kalman filtering methods based on position and velocity, our method of Kalman filtering uses the position …

A Customized Large Single-Piece Bifrontal Implant For Post-Craniectomy Defect Reconstruction: A Case Study, Omid Ghaderzadeh, Ehsan Amirbeyk, Seyed Roholah Ghodsi, Zahra Namazi, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Background: Large bifrontal defects pose unique reconstruction challenges due to their complex curvature and mechanical requirements. This case demonstrated how computer-aided design/manufacturing (CAD/CAM) enabled precise single-piece polymethyl methacrylate (PMMA) implant fabrication, thereby overcoming traditional limitations. Case presentation: A 25-year-old male who had undergone bifrontal decompressive craniectomy suffered a severe traumatic brain injury. The autologous bone flap had been temporarily stored in a subcutaneous fat area of the abdomen for 3 months to preserve its viability. A secondary cranioplasty was then performed using titanium miniplates and self-tapping screws for final fixation. After 2 years, the patient developed empyema and a brain …

Development Of 2d Microfluidics Surface With Low-Frequency Electric Fields For Cell Separation Applications, Madushan Wickramasinghe, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Cell separation techniques are widely used in many biomedical and clinical applications for the development of screening, diagnosis and therapeutic tests. Current 3D microfluidics-based cell separation methods have limited applications in part due to low throughput and technical complexity. To address these critical needs, we have developed a 2D microfluidics surface which is the miniaturized version of a 3D microfluids cell separation device. Using low-frequency electric fields (1–10 Vpp and 1 kHz–20 MHz), we have first studied dielectrophoresis, AC electro-osmosis and capillary flow within a sessile drop, and finally utilized the results to develop the 2D cell separation surface. Our …

Novel Micro-And Nanoformulations Of Paclitaxel For Targeting Metastatic Breast, Non-Small Cell Lung, And Pancreatic Cancers, Lobat Tayebi, Mehran Alavi

Electrical & Computer Engineering Faculty Publications

Nonlinear pharmacokinetics resulting from high lipophilic and low oral bioavailability, and hypersensitivity reactions and hyperlipidemia caused by formulation by Cremophor EL have limited clinical effectiveness of paclitaxel (Taxol). In this way, there is the critical necessity of innovative drug delivery systems (DDSs) to mitigate severe side effects and overcome clinical limitations of paclitaxel. In recent years, various micro- and nanoformulations, specifically polymeric nanoparticles (NPs) and lipid NPs, have been presented and approved by the Food and Drug Administration (FDA). In addition, other nanoformulations, such as polymeric nanoparticles (NPs), micelles, liposomes, and mesoporous silica nanoparticles, have shown promising results in vitro …