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Articles 8791 - 8820 of 9227
Full-Text Articles in Engineering
Understanding The Role Of Recalcitrant Organic Phosphorus Mineralization On Harmful Algal Blooms At The Sediment-Water Interface Of Freshwater System, Tasnuva Farnaz
College of Graduate Studies: Theses & Dissertations
Over the past few decades, an enormous number of resources have been allocated to reduce the amount of phosphorus (P) entering the environment from both point and non-point sources. Nevertheless, the decrease in external P loading has not always resulted in a simultaneous decrease in the occurrence of harmful algal blooms (HABs) in waters contaminated with phosphorus. A two-part study is currently being conducted to investigate and measure the role of legacy recalcitrant P forms in the overall pool of soluble reactive phosphorus (SRP). However, the objective of this particular study is to evaluate the potential of Organic Phosphorus (PO) …
Understanding The Impact Of Process Interruption On Mechanical Properties In Metal Additive Manufacturing: A Comprehensive Investigation, Poojith C. Chigurupati
Understanding The Impact Of Process Interruption On Mechanical Properties In Metal Additive Manufacturing: A Comprehensive Investigation, Poojith C. Chigurupati
College of Graduate Studies: Theses & Dissertations
Metal additive manufacturing techniques enable rapid prototyping and on-demand manufacturing while improving supply chain resiliency. Changes in microstructure and micro-mechanical characteristics of 3D printed metal parts occur due to the influence of process interruptions on melting-solidification cycles during the layer evolution in additive manufacturing processes. The process interruption can deteriorate the structural integrity of the 3D printed parts and generate micro-flaws in the interruption region. Manufacturing post-processing techniques such as Heat-Treatment methods can enhance the mechanical properties of the parts. Since variations commonly happen at the layer level, the investigation of mechanical properties must be done such that these variations …
Natural Convection Heat Transfer Characteristics Of Sierpinski Carpet Fractal Fins In Horizontal And Vertical Orientations, Ayomide Ayoola
Natural Convection Heat Transfer Characteristics Of Sierpinski Carpet Fractal Fins In Horizontal And Vertical Orientations, Ayomide Ayoola
College of Graduate Studies: Theses & Dissertations
This study investigates the thermal performance of fins with perforations inspired by the Sierpinski carpet fractal pattern under natural convection conditions in both vertical and horizontal orientations. The objective is to analyze the effects of fractal iteration levels on three primary performance metrics: efficiency, effectiveness, and effectiveness per unit mass. Experimental evaluations were conducted for fractal fins from iterations 0 through 4, utilizing aluminum material, with each fin heated to controlled conditions. The results reveal that efficiency generally decreases with higher fractal iterations, reflecting increased thermal resistance associated with greater porosity and complex geometry. However, effectiveness per unit mass improves …
Investigation Of Topologically Protected Wave Propagation Near Dirac-Like Cones In Acoustic Metamaterials, Md Arif Iqbal Khan
Investigation Of Topologically Protected Wave Propagation Near Dirac-Like Cones In Acoustic Metamaterials, Md Arif Iqbal Khan
College of Graduate Studies: Theses & Dissertations
This study presents a novel approach to investigate an exceptionally rare acoustic phenomenon – topologically protected wave propagation (TPWP) within a solid-solid domain. While previous research has attempted to unravel the physics behind this phenomenon, most efforts have been grounded in the framework of condensed matter physics and quantum mechanics often requiring complex geometries to realize TPWP in solid-fluid interactions. In contrast, this thesis introduces a geometric tuning method that enables the achievement of TPWP with simpler geometric configurations within a solid-solid domain. Rather than explaining by the quantum trio - quantum anomalous hall effect, quantum valley hall effect, and …
Neurosymbolic Value-Inspired Ai (Why, What, And How), Amit Sheth, Kaushik Roy
Neurosymbolic Value-Inspired Ai (Why, What, And How), Amit Sheth, Kaushik Roy
Publications
The rapid progression of Artificial Intelligence (AI) systems, facilitated by the advent of Large Language Models (LLMs), has resulted in their widespread application to provide human assistance across diverse industries. This trend has sparked significant discourse centered around the ever-increasing need for LLM-based AI systems to function among humans as part of human society, sharing human values, especially as these systems are deployed in high-stakes settings (e.g., healthcare, autonomous driving, etc.). Towards this end, neurosymbolic AI systems are attractive due to their potential to enable easy-tounderstand and interpretable interfaces for facilitating valuebased decision-making, by leveraging explicit representations of shared values. …
Blind Source Separation And Denoising Of Underwater Acoustic Signals, Ruba Zaheer, Iftekhar Ahmad, Quoc Viet Phung, Daryoush Habibi
Blind Source Separation And Denoising Of Underwater Acoustic Signals, Ruba Zaheer, Iftekhar Ahmad, Quoc Viet Phung, Daryoush Habibi
Research outputs 2022 to 2026
Due to the addition of new underwater vessels and other natural noise contributors, the underwater environment is becoming congested and noisy. Undersea monitoring sonobuoys receive multiple mixed acoustic signals from different vessels that need to be separated and identified in the presence of underwater noise (UWN). It is extremely challenging to separate highly correlated acoustic signals from a noisy mixture without prior knowledge of mixing process and propagation channel. Also, in many cases, the separated signals from the noisy mixture doesn’t accurately describe the correct signal. This study proposes a novel multi-stage method to separate underwater acoustic source signals from …
The Phase Behaviour And Stability Of An Environmentally Friendly Oil-In-Water Emulsion Produced Using Balanites Aegyptiaca Oil And Green Emulsifiers, Sami A.M. Yagoub, Swee P. Yeap, Nurudeen P. Yekeen, Mohammed A. Ayoub
The Phase Behaviour And Stability Of An Environmentally Friendly Oil-In-Water Emulsion Produced Using Balanites Aegyptiaca Oil And Green Emulsifiers, Sami A.M. Yagoub, Swee P. Yeap, Nurudeen P. Yekeen, Mohammed A. Ayoub
Research outputs 2022 to 2026
Due to environmental concerns about extensively using chemical emulsifiers and hydrocarbon oil in emulsion systems formation, recent research has shifted to using natural emulsifiers and oil. This study produced green emulsion using Balanites aegyptiaca oil and various bio-emulsifiers (such as sodium alginate, carboxymethylcellulose, guar gum, and Saponin). Phase behavior and stability of the emulsion were tested at different NaCl concentrations over one month of ageing. The emulsion was also produced using Balanites aegyptiaca oil and synthetic emulsifiers (Tween 80 and Triton X-100). The critical micelle concentrations of emulsifiers were determined and used as the fixed concentration for the green emulsion …
Ethical Decision-Making In Older Drivers During Critical Driving Situations: An Online Experiment, Amandeep Singh, Sarah Yahoodik, Yovela Murzello, Samuel Petkac, Yusuke Yamani, Siby Samuel
Ethical Decision-Making In Older Drivers During Critical Driving Situations: An Online Experiment, Amandeep Singh, Sarah Yahoodik, Yovela Murzello, Samuel Petkac, Yusuke Yamani, Siby Samuel
Psychology Faculty Publications
The present study examined the impact of aging on ethical decision-making in simulated critical driving scenarios. 204 participants from North America, grouped into two age groups (18–30 years and 65 years and above), were asked to decide whether their simulated automated vehicle should stay in or change from the current lane in scenarios mimicking the Trolley Problem. Each participant viewed a video clip rendered by the driving simulator at Old Dominion University and pressed the space-bar if they decided to intervene in the control of the simulated automated vehicle in an online experiment. Bayesian hierarchical models were used to analyze …
Generation Expansion Planning In Isolated Power Systems: A Robust Approach With Dunkelflaute Assessment, Taraneh Ghanbarzadeh, Daryoush Habibi, Asma Aziz
Generation Expansion Planning In Isolated Power Systems: A Robust Approach With Dunkelflaute Assessment, Taraneh Ghanbarzadeh, Daryoush Habibi, Asma Aziz
Research outputs 2022 to 2026
Generation expansion planning is vital for decarbonizing power systems and ensuring a reliable and sustainable energy future. Strategically adding new generation and grid capacity is essential for supporting a seamless transition to renewable energy while reducing greenhouse gas emissions. However, achieving the optimal capacity mix of energy resources to ensure network reliability and economic efficiency presents significant challenges, particularly for isolated electricity grids. These challenges are exacerbated during periods of low renewable generation and due to the inherent intermittency of weather-dependent energy resources. This paper presents a comprehensive approach to optimizing long-term expansion planning for an isolated electricity grid, focusing …
Mhair: A Dataset Of Audio-Image Representations For Multimodal Human Actions, Muhammad Bilal Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar
Mhair: A Dataset Of Audio-Image Representations For Multimodal Human Actions, Muhammad Bilal Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar
Research outputs 2022 to 2026
Audio-image representations for a multimodal human action (MHAiR) dataset contains six different image representations of the audio signals that capture the temporal dynamics of the actions in a very compact and informative way. The dataset was extracted from the audio recordings which were captured from an existing video dataset, i.e., UCF101. Each data sample captured a duration of approximately 10 s long, and the overall dataset was split into 4893 training samples and 1944 testing samples. The resulting feature sequences were then converted into images, which can be used for human action recognition and other related tasks. These images can …
Sandstone Wettability And Mixed Gas Composition: Unraveling The Impact Of Co2 In Hydrogen Geo-Storage, Zoha D. Isfehani, Amirmansour J. Jafari, Jalal Fahimpour, Mirhasan Hosseini, Stefan Iglauer, Alireza Keshavarz
Sandstone Wettability And Mixed Gas Composition: Unraveling The Impact Of Co2 In Hydrogen Geo-Storage, Zoha D. Isfehani, Amirmansour J. Jafari, Jalal Fahimpour, Mirhasan Hosseini, Stefan Iglauer, Alireza Keshavarz
Research outputs 2022 to 2026
Underground hydrogen storage (UHS) is gaining interest as a secure, long-term solution for storing hydrogen in porous geological formations. In UHS, a cushion gas like CO2 is crucial to maintain the reservoir pressure and optimize recovery. The concept of wettability plays a fundamental role in determining the system's multi-phase displacement characteristics in the porous media. However, there is a gap in the existing literature regarding the wettability of sandstone rocks under geo-storage conditions when H2 and CO2 are injected as the bulk and cushion gases, respectively. To address this gap, we conducted a study investigating the wettability hysteresis phenomenon by …
Energy Management And Sizing Of A Stand-Alone Hybrid Renewable Energy System For Community Electricity, Fresh Water, And Cooking Gas Demands Of A Remote Island, Mim M. Ahmed, Barun K. Das, Pronob Das, Md S. Hossain, Md G. Kibria
Energy Management And Sizing Of A Stand-Alone Hybrid Renewable Energy System For Community Electricity, Fresh Water, And Cooking Gas Demands Of A Remote Island, Mim M. Ahmed, Barun K. Das, Pronob Das, Md S. Hossain, Md G. Kibria
Research outputs 2022 to 2026
Research into the off-grid hybrid energy system to provide reliable electricity to a remote community has extensively been done. However, simultaneous meeting electric, freshwater, and gas demands from the off-grid hybrid energy sources are very scarce in literature. Power- to-X (PtX) is gaining attention in recent days in the energy transition scenarios to generate green hydrogen, the primary product of the process as an energy carrier, which is deemed to replace conventional fuels to reach absolute carbon neutrality. In this study, renewable–based hybrid energy is developed to simultaneously meet the electricity, freshwater, and gas (cooking gas via methanation process) demands …
Economic Material For Large-Scale H2 Storage And H2-Co2 Separation, Hussein R. Abid, Alireza Keshavarz, Header Jaffer, Basim K. Nile, Stefan Iglauer
Economic Material For Large-Scale H2 Storage And H2-Co2 Separation, Hussein R. Abid, Alireza Keshavarz, Header Jaffer, Basim K. Nile, Stefan Iglauer
Research outputs 2022 to 2026
Hydrogen is a clean fuel that can potentially completely decarbonize the energy supply chain and mitigate global warming. Hydrogen – a highly volatile gas – however, needs to be separated from CO2 during H2 production, and also from cushion gas in H2 geo-storage projects; in addition, large-scale H2 storage is a key obstacle. We thus tested and chemically upgraded common sub-bituminous coal as a material for H2-CO2 separation and H2 storage. The coal adsorbed significant amounts of H2 and CO2 and demonstrated an excellent H2-CO2 separation efficiency if chemically modified. The work presented here thus provides fundamental data required for …
Serious Game-Based Training For Improved Utilization Of A Novel Temporalis Emg Interface For Controlling Powered Wheelchairs, Calvin Macdonald
Serious Game-Based Training For Improved Utilization Of A Novel Temporalis Emg Interface For Controlling Powered Wheelchairs, Calvin Macdonald
Honors Undergraduate Theses
Amyotrophic lateral sclerosis (ALS) is a terminal neurodegenerative disease that leads to a lack of independent mobility. One solution uses a unilateral surface EMG (sEMG) interface on the temporalis muscle to provide autonomous control of a powered wheelchair. Limbitless Journey, an EMG-controlled serious game, intends to provide users with a virtual environment to train in before use in a real-world scenario. A recent study analyzed the effect of video game training on the use of sEMG systems on the forearm, showing significant improvement in the usage of the interface but no difference between Free Play and structured play. The study …
Robotic Gas Source Localization And Distribution Mapping Via Deep Reinforcement Learning, Iliya Kulbaka
Robotic Gas Source Localization And Distribution Mapping Via Deep Reinforcement Learning, Iliya Kulbaka
UNF Graduate Theses and Dissertations
This research aims to advance the fields of Gas Source Localization (GSL) and Gas Distribution Mapping (GDM) by developing deep reinforcement learning (DRL) methodologies suitable for complex, real-world environments. GSL and GDM are crucial for applications such as environmental monitoring, hazardous material detection, and search-and-rescue missions, where safe and efficient exploration is essential. Traditional methods often fall short in dynamic settings influenced by factors like wind and obstacles. To address these limitations, this study proposes novel neural network architectures and learning frameworks for adaptive exploration and mapping, integrating Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) layers, and Deep Q-Networks …
A Method For Investigation Of Small-Scale Morphologic Change Around Low Crested Oyster-Based Structures, Makaya S. Malila
A Method For Investigation Of Small-Scale Morphologic Change Around Low Crested Oyster-Based Structures, Makaya S. Malila
UNF Graduate Theses and Dissertations
In recent years, a novel method for shoreline stabilization, Pervious Oyster Shell Habitat (POSH) units, comprised of recycled eastern oyster shells, has been developed. These mound-shaped structures have been deployed along several shoreline sites in Northeast Florida. This case study sought to develop and implement a method for investigation of small-scale morphologic change in the vicinity of these structures using smartphone LiDAR technology, surveying instruments, and 2D/3D mapping software. Results suggest that the POSH units are helping to mitigate erosion by trapping sediments around them. Moving forward, it may be possible to adapt the methodology used here to assess morphologic …
An Enhanced Evaluation Of Bioslurry For Use In Coastal Erosion Mitigation, Megan Elizabeth Dunton
An Enhanced Evaluation Of Bioslurry For Use In Coastal Erosion Mitigation, Megan Elizabeth Dunton
UNF Graduate Theses and Dissertations
This paper discusses the treatment of Florida beach sand by surface percolating Bioslurry, a microbially-induced calcite precipitation (MICP) variant that was developed and refined in recent years. Researchers examined how variations in pore volume and surface area affected the cemented depth of soil treated via surface percolation. Results suggested that while the pore volume is an important factor that governs cementation in soil treated via surface percolation, it does not appear to be the only controlling factor and treatment volume per unit surface area is another important factor to consider when treating soil with Bioslurry using surface percolation. The implications …
Investigating The Role Of Tesserae In Energy Absorption In Shark Cartilage, Molly Dobrow
Investigating The Role Of Tesserae In Energy Absorption In Shark Cartilage, Molly Dobrow
UNF Graduate Theses and Dissertations
Unlike mammals, shark endoskeletons are composed of cartilage, which is less stiff compared to bone. Despite this structural disadvantage, sharks have risen to become apex predators, with reported maximum posterior bite force estimates approximating 5914 N in bull sharks. Shark jaws are estimated to undergo high cycle loading within the organism’s lifecycle without evidence of failure. Fatigue resistance may relate to mineral distribution within a component of the endoskeletal system – tesserae. Tesserae are thin, roughly hexagonal tiles composed of calcium phosphate hydroxyapatite (HA) crystals and grow by accretion to eventually surround the hyaline cartilage core. Though tesserae dimensions are …
Finops-Driven Cloud Optimization Models For Enterprise Applications, Manikantha Varaprasad Inakollu
Finops-Driven Cloud Optimization Models For Enterprise Applications, Manikantha Varaprasad Inakollu
Computer Science and Engineering Faculty Publications
Cloud computing has revolutionized enterprise IT infrastructure, yet escalating costs and resource inefficiencies threaten to undermine these benefits. This research examines FinOps-driven optimization models that enable organizations to balance cloud performance, cost efficiency, and business value. The study addresses the critical challenge enterprises face in managing cloud expenditures while maintaining operational excellence. Through comprehensive analysis of FinOps principles and practical optimization frameworks, we develop models that integrate financial accountability, technical efficiency, and business alignment. Our research demonstrates that organizations implementing structured FinOps practices achieve 25-40% cost reductions without compromising application performance. The study contributes both theoretical frameworks for understanding cloud …
Enhancing Erp Auditability And Compliance Using Permissioned Blockchain, A Framework For Transparent And Immutable Enterprise Resource Planning Systems., Manikantha Varaprasad Inakollu
Enhancing Erp Auditability And Compliance Using Permissioned Blockchain, A Framework For Transparent And Immutable Enterprise Resource Planning Systems., Manikantha Varaprasad Inakollu
Computer Science and Engineering Faculty Publications
Enterprise Resource Planning systems serve as the backbone of modern organizational operations, yet their centralized architecture creates significant challenges for auditability and regulatory compliance. This research proposes a permissioned blockchain framework to enhance ERP auditability by creating immutable, transparent, and traceable records of all system transactions and modifications. The study addresses critical gaps in current ERP systems where transaction histories can be altered, audit trails prove insufficient, and compliance verification remains cumbersome. Through examination of existing ERP limitations and blockchain capabilities, we develop an integrated architecture that maintains operational efficiency while providing cryptographic assurance of data integrity. Our framework employs …
Tailored Micromagnet Sorting Gate For Simultaneous Multiple Cell Screening In Portable Magnetophoretic Cell-On-Chip Platforms, Jonghwan Yoon, Yumin Kang, Hyeonseol Kim, Abbas Ali, Keonmok Kim, Sri Ramulu Torati, Mi-Young Im, Changyeop Jeon, Byeonghwa Lim, Cheolgi Kim
Tailored Micromagnet Sorting Gate For Simultaneous Multiple Cell Screening In Portable Magnetophoretic Cell-On-Chip Platforms, Jonghwan Yoon, Yumin Kang, Hyeonseol Kim, Abbas Ali, Keonmok Kim, Sri Ramulu Torati, Mi-Young Im, Changyeop Jeon, Byeonghwa Lim, Cheolgi Kim
Center for Bioelectronics Publications
Conventional magnetophoresis techniques for manipulating biocarriers and cells predominantly rely on large-scale electromagnetic systems, which is a major obstacle to the development of portable and miniaturized cell-on-chip platforms. Herein, a novel magnetic engineering approach by tailoring a nanoscale notch on a disk micromagnet using two-step optical and thermal lithography is developed. Versatile manipulations are demonstrated, such as separation and trapping, of carriers and cells by mediating changes in the magnetic domain structure and discontinuous movement of magnetic energy wells around the circumferential edge of the micromagnet caused by a locally fabricated nano-notch in a low magnetic field system. The motion …
A Framework For Scientific Data Indexing, Searching And Sharing, Apoorva Mohite
A Framework For Scientific Data Indexing, Searching And Sharing, Apoorva Mohite
Master's Projects
Scientific data continues to grow. Wildfire simulation experiments performed by the WIRC team at SJSU have generated over 138 TB of data so far and it is expected to keep growing. It becomes difficult for researchers to search through that data to find the data of their interest. This data is stored on an HPC cluster that external users do not have access to. The WIRC team also conducts experiments and publishes their research, but the size of data makes it difficult to share these datasets. This project introduces a novel solution to indexing scientific data, searching through the data …
Fine-Tuning Large Language Models For Folder Structure Generation, Likhith Nemani
Fine-Tuning Large Language Models For Folder Structure Generation, Likhith Nemani
Master's Projects
Starting a new project is a significant challenge in the software development world. Building a new project skeleton and configurations will require vast amounts of time and effort. This project aims to overcome the difficulty presented by this challenge using advanced large language models, specifically fine-tuning LLMs. Our initial focus with the implementation is to use the powerful capabilities of advanced modern models to simplify and accelerate the complicated process of getting new projects started. The solution process begins with a user posting a README file to a predetermined repository. This README file then is used as a source for …
Credit Score-Based Lending System On The Ethereum Platform, Mayuri Shimpi
Credit Score-Based Lending System On The Ethereum Platform, Mayuri Shimpi
Master's Projects
Traditional banking systems act as intermediaries, assessing risks and profiting from interest rate differentials. Credit scores, provided by trusted bureaus, are commonly used to evaluate the creditworthiness of borrowers. Cryptocurrencies have emerged as a significant and innovative medium due to their decentralized nature, operating without reliance on a central authority, such as a government.
This report describes a project to implement the Autonomous Lending system on the Ethereum Platform (ALOE), as proposed in [1], aiming to seamlessly integrate traditional credit scoring methodologies for evaluating a borrower's risk of default. The objective of this project report is to establish a robust …
Ml-Based User Identification Through Mouse Dynamics, Rakshit Gupta
Ml-Based User Identification Through Mouse Dynamics, Rakshit Gupta
Master's Projects
User authentication and identification plays a crucial role in ensuring the security and integrity of digital systems. Traditional authentication methods, such as passwords and biometrics, have inherent limitations that can compromise system security. This research proposes a novel approach to user authentication by leveraging machine learning techniques and behavioral biometrics, specifically mouse dynamics. The primary objective is to develop a sophisticated framework that can accurately identify individuals based on their unique mouse behavior patterns. The study explores and compares multiple deep learning architectures, including Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and Transformer models, to generate embeddings from …
Analysis And Application Of Adaptive Ml Algorithms For Malware Classification, Rashmi Boddukuri
Analysis And Application Of Adaptive Ml Algorithms For Malware Classification, Rashmi Boddukuri
Master's Projects
Malware classification is the process of distinguishing malware samples into categories of malware families that it is associated with and remains a critical step in the process of mitigating malware-related threats. In recent years, machine learning techniques have emerged as a powerful tool for such malware classification tasks. In this study, we explore the application of adaptive machine learning models to malware classification in order to analyze and determine how they compare in performance to similar but non-adaptive algorithms. The results achieved in this study share insight into the strengths and limitations of adaptive learning models when applied towards malware …
Distinguishing Chatbot From Human, Gauri Anil Godghase
Distinguishing Chatbot From Human, Gauri Anil Godghase
Master's Projects
There have been many recent advances in the field of Generative Artificial Intelligence and Large Language Models, with GPT 3 or ChatGPT model being one of the frontrunners in this field. These large language models have become so powerful that it has become difficult to differentiate between text written by humans and machine-generated text. This paper proposes a solution to the problem of classification of the origin of data (human or chatbot) by using Machine Learning. In addition, the proposed solution also helps us analyze the text generated by such Language Models and understand the underlying patterns present in the …
Exploring Gender Bias In Large Language Models: Cross-Linguistic Comparisons And Evaluation Letters Analysis, Athira Kumar
Exploring Gender Bias In Large Language Models: Cross-Linguistic Comparisons And Evaluation Letters Analysis, Athira Kumar
Master's Projects
Large language models (LLMs) play a significant role in modern human-computer interaction. They have exploded in popularity recently, becoming widely used for various tasks. However, concerns persist regarding potential biases within these models. This project investigates gender bias in the popular LLMs - GPT-3.5, GPT-4, Gemini, and LLAMA. The first part of our study focuses on analyzing biases using ambiguous sentences across three languages - English, Malayalam, and Tamil. We evaluate the LLMs to see if they associate occupations with commonly held gender stereotypes, by using specific professions within our test sentences. Through the use of two low-resource languages, this …
Lexigen: Lexical-Driven Image Generation, Sangram Prashant Chincholkar
Lexigen: Lexical-Driven Image Generation, Sangram Prashant Chincholkar
Master's Projects
This research project proposes a novel approach to user-driven image editing via natural language descriptions. The aim is an accurate change of certain features of an image with respect to the descriptive text while maintaining, with equal concern, the integrity of the remaining parts of the image not affected by the description. The task is particularly relevant for fields like content creation, personalized design, and automated image editing that require both coherence of a visual scene and textual description. We propose a generative model, LexiGen, which perfectly integrates natural language descriptions with their corresponding visual changes within an image. The …
Adaptive Metric-Driven Load Balancing For Specialized Clusters Using Nginx, Juhi Raju Malkani
Adaptive Metric-Driven Load Balancing For Specialized Clusters Using Nginx, Juhi Raju Malkani
Master's Projects
Adaptive Metric-Driven Load Balancer is an innovative two-tier load-balancing system that uses NGINX and Prometheus to optimize resource allocation in specialized cloud clusters. This framework is built to give great performance and flexibility and runs on Google Kubernetes Engine (GKE), but it may also be deployed on local cloud environments for added security. The first tier of our system uses an NGINX-based load balancer to route incoming requests based on content type, sending traffic to hardware-optimized clusters for processing requests through specialized hardware. In our algorithm, the second tier dynamically modifies load distribution throughout each cluster by calculating pod weights …