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Articles 33121 - 33150 of 291657

Full-Text Articles in Physical Sciences and Mathematics

Development Of Radiochemistry Of 52mn For Pet Imaging Applications, James Mokaya Omweri Jan 2024

Development Of Radiochemistry Of 52mn For Pet Imaging Applications, James Mokaya Omweri

All ETDs from UAB

No abstract provided.

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Early Detection Of Driving Maneuvers For Proactive Congestion Prevention, Debasree Das, Shameek Bhattacharjee, Sandip Chakraborty, Bivas Mitra, Sajal K. Das Jan 2024

Early Detection Of Driving Maneuvers For Proactive Congestion Prevention, Debasree Das, Shameek Bhattacharjee, Sandip Chakraborty, Bivas Mitra, Sajal K. Das

Computer Science Faculty Research & Creative Works

Road Traffic Congestion Affects Not Only the Commute Delay but Also a city's overall Social, Economic, and Environmental Growth. Existing Approaches for Road Congestion Mitigation Primarily Adopt a Reactive Approach by Detecting Congestion after It Occurs and Recommending Alternate Routes to the Vehicles, Which Fails to Prevent Congestion Cascading. in Contrast, We Propose a Pervasive Platform Called ProCon that Proactively Infers the Driving Micro-Behaviors that Can Contribute to Congestion Formation and Assist the Drivers in Avoiding Such Maneuvers in Real-Time during the Navigation. Thorough Evaluations over Multiple Real-Life and Simulated Datasets Indicate that ProCon Can Reduce Congestion for More Than …

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The Attitudes And Practices Of United Arab Emirates Consumers Towards Food Waste: A Nationwide Cross-Sectional Study, Lynne Kennedy, Samir Safi, Tareq M. Osaili, Ala Al Rajabi, Ayesha Alblooshi, Dima Al Jawarneh, Ahmed Al Kaabi, Fakhra Al Rubaei, Maitha Albreiki, Maryam Alfadli, Aseilah Alhefeiti, Moez Al Islam Ezzat Faris, Kholoud Allaham, Sameeha Junaidi, Moien A.B. Khan Jan 2024

The Attitudes And Practices Of United Arab Emirates Consumers Towards Food Waste: A Nationwide Cross-Sectional Study, Lynne Kennedy, Samir Safi, Tareq M. Osaili, Ala Al Rajabi, Ayesha Alblooshi, Dima Al Jawarneh, Ahmed Al Kaabi, Fakhra Al Rubaei, Maitha Albreiki, Maryam Alfadli, Aseilah Alhefeiti, Moez Al Islam Ezzat Faris, Kholoud Allaham, Sameeha Junaidi, Moien A.B. Khan

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Background: Reducing global food waste is an international environmental, health, and sus-tainability priority. Although significant reductions have been achieved across the food chain, progress by UAE households and consumers remain inadequate. This study seeks to understand the association between consumer attitudes, knowledge, and awareness relating to food waste practice of residents living in the UAE. to help inform policy and action for addressing this national priority. Methods: A cross-sectional study was conducted using a validated semi-structured online questionnaire through stratified sampling (n =1052). The Spearman correlation coefficient was performed to determine the correlations. Two independent regression analysis were used to …

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A Multi-Objective Grey Wolf Optimizer For Energy Planning Problem In Smart Home Using Renewable Energy Systems, Sharif Naser Makhadmeh, Mohammed Azmi Al-Betar, Feras Al-Obeidat, Osama Ahmad Alomari, Ammar Kamal Abasi, Mohammad Tubishat, Zenab Elgamal, Waleed Alomoush Jan 2024

A Multi-Objective Grey Wolf Optimizer For Energy Planning Problem In Smart Home Using Renewable Energy Systems, Sharif Naser Makhadmeh, Mohammed Azmi Al-Betar, Feras Al-Obeidat, Osama Ahmad Alomari, Ammar Kamal Abasi, Mohammad Tubishat, Zenab Elgamal, Waleed Alomoush

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This paper presents the energy planning problem (EPP) as an optimization problem to find the optimal schedules to minimize energy consumption costs and demand and enhance users’ comfort levels. The grey wolf optimizer (GWO), One of the most powerful optimization methods, is adjusted and adapted to address EPP optimally and achieve its objectives efficiently. The GWO is adapted due to its high performance in addressing NP-complex hard problems like the EPP, where it contains efficient and dynamic parameters that enhance its exploration and exploitation capabilities, particularly for large search spaces. In addition, new energy and real-world resources based on solar …

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Digraph Enabled Digital Twin And Label-Encoding Machine Learning For Scada Network's Cyber Attack Analysis In Industry 5.0, Nabeel Al-Qirim, Anoud Bani-Hani, Munir Majdalawieh, Hussam Al Hamadi, Mohammad Kamrul Hasan Jan 2024

Digraph Enabled Digital Twin And Label-Encoding Machine Learning For Scada Network's Cyber Attack Analysis In Industry 5.0, Nabeel Al-Qirim, Anoud Bani-Hani, Munir Majdalawieh, Hussam Al Hamadi, Mohammad Kamrul Hasan

All Works

False-Data Injection Attack (FDIA), Remote-Tripping Command Injection (RTCI), and System Reconfiguration Attack (SRA) on SCADA (Supervisory Control and Data Acquisition) networks impact industry 5.0 enabled smart grid components such as intelligent-electronic-device (IED), circuit-breaker, network-switch, and power transmission lines. Since the SCADA-network-based cyber-attacking flow is not in digital-twin form, it is impossible to simulate the effects of the attack. Furthermore, the string nature of these affected components' data makes it challenging to incorporate into machine-learning-enabled intelligence (CTI) processes. To visualize the attacking flow of FDIA, RTCI, and SRA cyber-attacks on SCADA networks, this paper presents a novel "Digital Twin and Machine …

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Generative Ai And Large Language Models: A New Frontier In Reverse Vaccinology, Kadhim Hayawi, Sakib Shahriar, Hany Alashwal, Mohamed Adel Serhani Jan 2024

Generative Ai And Large Language Models: A New Frontier In Reverse Vaccinology, Kadhim Hayawi, Sakib Shahriar, Hany Alashwal, Mohamed Adel Serhani

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Reverse vaccinology is an emerging concept in the field of vaccine development as it facilitates the identification of potential vaccine candidates. Biomedical research has been revolutionized with the recent innovations in Generative Artificial Intelligence (AI) and Large Language Models (LLMs). The intersection of these two technologies is explored in this study. In this study, the impact of Generative AI and LLMs in the field of vaccinology is explored. Through a comprehensive analysis of existing research, prospective use cases, and an experimental case study, this research highlights that LLMs and Generative AI have the potential to enhance the efficiency and accuracy …

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Catalytic Control Of The Nanomorphology And Mechanical Properties Of Aliphatic Shape-Memory Aerogels, A B M Shaheen Ud Doulah Jan 2024

Catalytic Control Of The Nanomorphology And Mechanical Properties Of Aliphatic Shape-Memory Aerogels, A B M Shaheen Ud Doulah

Doctoral Dissertations

"Shape-memory poly(isocyanurate-urethane) (PIR-PUR) aerogels are nanoporous solids that can return to their original shape after being compressed, through a heating actuation step. This thesis compares the effectiveness of various metal ions as catalysts in the formation of PIR-PUR aerogels, and explores the correlation between catalytic activity, nanomorphology, and mechanical properties of the resulting aerogels. The gelation rate was found to increase from Fe to Cu and then decline from Cu to Ga in the periodic table. CuCl2 was found to be the fastest catalyst, and FeCl3 the slowest. The morphology of the aerogels changed from bicontinuous to spheroidal …

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Dynamics And Inverse Problems For Nonlinear Schrödinger Equations, Christopher Hogan Jan 2024

Dynamics And Inverse Problems For Nonlinear Schrödinger Equations, Christopher Hogan

Doctoral Dissertations

"The cubic nonlinear Schrödinger equation (NLS) is a model of interest in the study of physical problems including nonlinear optics and Bose-Einstein condensates. Of particular interest is the study of cubic NLS with inhomogeneities such as localizations of the nonlinearity or terms introducing potential barriers. We first address some preliminaries and techniques useful in the study of the cubic NLS and its variations. We then consider the cubic NLS with a localized nonlinearity in dimensions d ≥ 2. We show that solutions with data given by small-amplitude wave packets accrue a nonlinear phase that determines the X-ray transform of the …

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Secure And Privacy-Preserving Federated Learning With Rapid Convergence In Leo Satellite Networks, Mohamed Elmahallawy Jan 2024

Secure And Privacy-Preserving Federated Learning With Rapid Convergence In Leo Satellite Networks, Mohamed Elmahallawy

Doctoral Dissertations

"The advancement of satellite technology has enabled the launch of small satellites equipped with high-resolution cameras into low Earth orbit (LEO), enabling the collection of extensive Earth data for training AI models. However, the conventional approach of downloading satellite-related data to a ground station (GS) for training a centralized machine learning (ML) model faces significant challenges. Firstly, the transmission of raw data raises security and privacy concerns, especially in military applications. Secondly, the download bandwidth is limited, which puts a stringent limit on image transmissions to the GS. Lastly, LEO satellites have sporadic visibility with the GS, and orbit the …

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Analytical Methods For Monitoring Traumatic Brain Injury Biomarkers/Treatment And Pharmaceutical Residual Solvents, Olajide Philip Adetunji Jan 2024

Analytical Methods For Monitoring Traumatic Brain Injury Biomarkers/Treatment And Pharmaceutical Residual Solvents, Olajide Philip Adetunji

Doctoral Dissertations

"The development of highly sensitive and efficient analytical methods utilizing advanced instrumentation is necessary to help improve disease diagnosis and therapeutics. A major neuro-consequence of traumatic brain injury (TBI) is oxidative stress from the generation of reactive oxygen species and the depletion of antioxidant defenses. Alteration in concentrations of certain small molecules also occurs with the disease progression and can help understand TBI pathophysiology. Two analytical methods employing liquid chromatography with tandem mass spectrometry (LC-MS/MS) were developed and validated to monitor the potential small-molecule TBI biomarkers at sub-ppb levels. Subsequently, the neuroprotective effect of an antioxidant prodrug, N-acetylcysteine amide (NACA), …

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Critical Behavior And Dynamics Of The Superfluid-Mott Glass Transition, Jack Russell Crewse Jan 2024

Critical Behavior And Dynamics Of The Superfluid-Mott Glass Transition, Jack Russell Crewse

Doctoral Dissertations

This work studies the effects of disorder on the thermodynamic critical behavior and dynamical properties of the superfluid-Mott glass quantum phase transition. After a brief introduction covering relevant fundamentals, we present the dissertation in the form of four separate but related publications. In the first two publications, we calculate the thermodynamic critical exponents of the superfluid-Mott glass quantum phase transition in both two and three spatial dimensions. The undiluted transition exhibits critical exponents that violate the Harris criterion, and thus the critical behavior is expected to change upon introducing disorder. We confirm this behavior via Monte Carlo simulation of a …

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High-Resolution Spectroscopy Of Interstellar Lines And Comets, Chemeda Tadese Ejeta Jan 2024

High-Resolution Spectroscopy Of Interstellar Lines And Comets, Chemeda Tadese Ejeta

Doctoral Dissertations

"The study of interstellar molecules such as CO is crucial because interstellar ices in the core of a pre-solar molecular cloud provide the starting point for volatile evolution in the protoplanetary disk. A record of the initial volatile composition of the protoplanetary disk can be obtained from the study of the chemical composition of cometary nuclei. Because of their long residence in the Oort cloud and infrequent passage through the inner solar system, long-period comets are one of the most primitive bodies in our solar system that can tell us about the composition of the early solar system. High-resolution infrared …

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Adversarial Transferability And Generalization In Robust Deep Learning, Tao Wu Jan 2024

Adversarial Transferability And Generalization In Robust Deep Learning, Tao Wu

Doctoral Dissertations

Despite its remarkable achievements across a multitude of benchmark tasks, deep learning (DL) models exhibit significant fragility to adversarial examples, i.e., subtle modifications applied to inputs during testing yet effective in misleading DL models. These meticulously crafted perturbations possess the remarkable property of transferability: an adversarial example that effectively fools one model often retains its effectiveness against another model, even if the two models were trained independently. This research delves into the characteristics influencing the transferability of adversarial examples from three distinct and complementary perspectives: data, model, and optimization. Firstly, from the data perspective, we propose a new method of …

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Crystal Structure Prediction Of Metal Chalcogenides, Qi Zhang Jan 2024

Crystal Structure Prediction Of Metal Chalcogenides, Qi Zhang

Doctoral Dissertations

A novel crystal structure prediction (CSP) method has been developed to predict energetically favorable (stable) structures based on targeted chemical compositions. It leverages the structural characteristics of recurring motifs featured in many crystals and symmetry restrictions from space groups to effectively lower the degrees of freedom of a system when conducting CSP simulations. The proposed method is applied to predicting low-energy structures of two metal chalcogenide systems: Li3PS4 and Na6Ge2Se6. Both systems feature rigid bodies in their structures as building blocks, making them particularly suited to the proposed method. The validity …

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Assessing Concepts, Procedures, And Cognitive Demand Of Chatgpt-Generated Mathematical Tasks, Bima Sapkota, Liza Bondurant Jan 2024

Assessing Concepts, Procedures, And Cognitive Demand Of Chatgpt-Generated Mathematical Tasks, Bima Sapkota, Liza Bondurant

School of Mathematical & Statistical Sciences Faculty Publications

In November 2022, ChatGPT, an Artificial Intelligence (AI) large language model (LLM) capable of generating human-like responses, was launched. ChatGPT has a variety of promising applications in education, such as using it as thought-partner in generating curricular resources. However, scholars also recognize that the use of ChatGPT raises concerns, such as outputs that are inaccurate, nonsensical, or vague. We, two mathematics teacher educators, engaged in a collaborative self-study using qualitative descriptive approaches to investigate the procedures, concepts, and cognitive demand of ChatGPT-generated mathematical tasks focused on fraction multiplication using the area model approach. We found that the ChatGPT-generated tasks were …

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Investigating Preservice Teachers’ Conceptualizations Of Mathematical Knowledge For Teaching Through Video Analysis, Bima Sapkota Jan 2024

Investigating Preservice Teachers’ Conceptualizations Of Mathematical Knowledge For Teaching Through Video Analysis, Bima Sapkota

School of Mathematical & Statistical Sciences Faculty Publications

Mathematics Preservice Teachers’ (M-PSTs) conceptions of Mathematical Knowledge for Teaching (MKT) enhance their reflective skills because they utilize such conceptions to reflect on how to contextualize content knowledge during secondary mathematics teaching. While previous studies suggested M-PSTs develop MKT, including pedagogical content knowledge by analyzing teaching in video lessons, how M-PSTs enhance their conceptions of MKT through such analysis is underexplored. I used a collective case study approach to investigate how four secondary M-PSTs conceptualized MKT when they analyzed and discussed teaching represented in a video lesson using the MKT framework. The findings indicated that the M-PSTs often described teacher …

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The Development Of An Automated Microscope Image Tracking And Analysis System, J. Walker Orr, Lillian Mcafee, Zach Heath, Marvin Hozi, Young Bok Abraham Kang Jan 2024

The Development Of An Automated Microscope Image Tracking And Analysis System, J. Walker Orr, Lillian Mcafee, Zach Heath, Marvin Hozi, Young Bok Abraham Kang

Faculty Publications - Department of Electrical Engineering and Computer Science

Microscopy image analysis plays a crucial role in understanding cellular behavior anduncovering important insights in various biological and medical research domains.Tracking cells within the time-lapse microscopy images is a fundamental techniquethat enables the study of cell dynamics, interactions, and migration. While manual celltracking is possible, it is time-consuming and prone to subjective biases that impactresults. In order to solve this issue, we sought to create an automated software solu-tion, named cell analyzer, which is able to track cells within microscopy images withminimal input required from the user. The program of cell analyzer was written inPython utilizing the open source computer …

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Assessment Of Potential Impacts Of Climate Change On Hydrology And Water Resource Availability In The Passaic River Basin, New Jersey, Felix Oteng Mensah Jan 2024

Assessment Of Potential Impacts Of Climate Change On Hydrology And Water Resource Availability In The Passaic River Basin, New Jersey, Felix Oteng Mensah

Theses, Dissertations and Culminating Projects

Streamflow dynamics in a basin is known to be a major driver of available water resources. In the context of climate change, it is expected that global warming will accelerate the global hydrologic cycle, which will drive more intense floods and droughts leading to changes in streamflow and water resource availability. Most researchers agree that the amount and intensity of precipitation have a direct impact on runoff. Yet, there is no consensus as to how warming can affect streamflow. Evapotranspiration (ET) plays a crucial role here. However, there is a shortage of real-world observations on it. And yet, ET is …

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A Memory Efficient Deep Recurrent Q-Learning Approach For Autonomous Wildfire Surveillance, Jeremy A. Cantor Jan 2024

A Memory Efficient Deep Recurrent Q-Learning Approach For Autonomous Wildfire Surveillance, Jeremy A. Cantor

UNF Graduate Theses and Dissertations

Previous literature demonstrates that autonomous UAVs (unmanned aerial vehicles) have the po- tential to be utilized for wildfire surveillance. This advanced technology empowers firefighters by providing them with critical information, thereby facilitating more informed decision-making processes. This thesis applies deep Q-learning techniques to the problem of control policy design under the objective that the UAVs collectively identify the maximum number of locations that are under fire, assuming the UAVs can share their observations. The prohibitively large state space underlying the control policy motivates a neural network approximation, but prior work used only convolutional layers to extract spatial fire information from …

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Media Haze Classification In Retinal Images Using Deep Learning, Jonathan O'Berry Jan 2024

Media Haze Classification In Retinal Images Using Deep Learning, Jonathan O'Berry

UNF Graduate Theses and Dissertations

Media Haze (MH) is a condition that affects an individual’s quality of life by affecting their eyes. Current practice is to detect MH by manually examining retinal fundus (retinal) images. The analysis of images being used as the prevalent technique for identifying the MH condition strongly suggests that automation of this process may be possible. In recent years, machine learning, specifically computer vision, has allowed for the automation of tasks relating to image analysis. This ability to automate has also recently been shown in the medical field for some eye conditions and diseases. This thesis centers around the problem of …

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Understanding And Augmenting Scientific Software Testing Practices, Kris Roker Jan 2024

Understanding And Augmenting Scientific Software Testing Practices, Kris Roker

UNF Graduate Theses and Dissertations

Scientific software can be broadly defined as software written to aid in conducting scientific research activities. As this software is often written by the scientists themselves, who often learned programming to build that software, some important aspects of software development may get less attention than they would have gotten on enterprise software developed by programmers. One area of development that often gets overlooked in this regard is testing. Thus, in this study, we seek to better understand the testing processes and propose methods to improve the effectiveness of those tests. We begin with examining the software's Continuous Integration/Delivery practices. This …

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2024 January - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University Jan 2024

2024 January - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

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The Coulomb Gauge In Non-Associative Gauge Theory, Sergey Grigorian Jan 2024

The Coulomb Gauge In Non-Associative Gauge Theory, Sergey Grigorian

School of Mathematical & Statistical Sciences Faculty Publications

The aim of this paper is to extend existence results for the Coulomb gauge from standard gauge theory to a non-associative setting. Non-associative gauge theory is based on smooth loops, which are the non-associative analogs of Lie groups. The main components of the theory include a finite-dimensional smooth loop L , its tangent algebra l , a finite-dimensional Lie group Ψ , that is the pseudoautomorphism group of L , a smooth manifold M with a principal Ψ -bundle P , and associated bundles Q and A with fibers L and l , respectively. A configuration in this theory is …

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Advancing The Understanding Of Clinical Sepsis Using Gene Expression–Driven Machine Learning To Improve Patient Outcomes, Asrar Rashid, Feras Al-Obeidat, Wael Hafez, Govind Benakatti, Rayaz A. Malik, Christos Koutentis, Javed Sharief, Joe Brierley, Nasir Quraishi, Zainab A. Malik, Arif Anwary, Hoda Alkhzaimi, Syed Ahmed Zaki, Praveen Khilnani, Raziya Kadwa, Rajesh Phatak, Maike Schumacher, M. Guftar Shaikh, Ahmed Al-Dubai, Amir Hussain Jan 2024

Advancing The Understanding Of Clinical Sepsis Using Gene Expression–Driven Machine Learning To Improve Patient Outcomes, Asrar Rashid, Feras Al-Obeidat, Wael Hafez, Govind Benakatti, Rayaz A. Malik, Christos Koutentis, Javed Sharief, Joe Brierley, Nasir Quraishi, Zainab A. Malik, Arif Anwary, Hoda Alkhzaimi, Syed Ahmed Zaki, Praveen Khilnani, Raziya Kadwa, Rajesh Phatak, Maike Schumacher, M. Guftar Shaikh, Ahmed Al-Dubai, Amir Hussain

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Sepsis remains a major challenge that necessitates improved approaches to enhance patient outcomes. This study explored the potential of machine learning (ML) techniques to bridge the gap between clinical data and gene expression information to better predict and understand sepsis. We discuss the application of ML algorithms, including neural networks, deep learning, and ensemble methods, to address key evidence gaps and overcome the challenges in sepsis research. The lack of a clear definition of sepsis is highlighted as a major hurdle, but ML models offer a workaround by focusing on endpoint prediction. We emphasize the significance of gene transcript information …

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On Combinatorics Of Voronoi Polytopes For Perturbations Of The Dual Root Lattices, Alexey Garber Jan 2024

On Combinatorics Of Voronoi Polytopes For Perturbations Of The Dual Root Lattices, Alexey Garber

School of Mathematical & Statistical Sciences Faculty Publications

The Voronoi conjecture on parallelohedra claims that for every convex polytope P that tiles Euclidean d-dimensional space with translations there exists a d-dimensional lattice such that P and the Voronoi polytope of this lattice are affinely equivalent. The Voronoi conjecture is still open for the general case but it is known that some combinatorial restrictions for the face structure of P ensure that the Voronoi conjecture holds for P. In this article, we prove that if P is the Voronoi polytope of one of the dual root lattices Dd*, E6*, E7* or E8*=E8 or their small perturbations, then every parallelohedron …

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Symmetries And Integrable Systems, Sen-Yue Lou, Bao-Feng Feng Jan 2024

Symmetries And Integrable Systems, Sen-Yue Lou, Bao-Feng Feng

School of Mathematical & Statistical Sciences Faculty Publications

Symmetry plays key roles in modern physics especially in the study of integrable systems because of the existence of infinitely many local and nonlocal generalized symmetries. In addition to the fundamental role to find exact group invariant solutions via Lie point symmetries, some important new developments on symmetries and conservation laws are reviewed. The recursion operator method is important to find infinitely many local and nonlocal symmetries of (1+1)-dimensional integrable systems. In this paper, it is pointed out that a recursion operator may be obtained from one key symmetry, say, a residual symmetry. For (2+1)-dimensional integrable systems, the master-symmetry approach …

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Modeling The Effect Of Observational Social Learning On Parental Decision-Making For Childhood Vaccination And Diseases Spread Over Household Networks, Tamer Oraby, Andras Balogh Jan 2024

Modeling The Effect Of Observational Social Learning On Parental Decision-Making For Childhood Vaccination And Diseases Spread Over Household Networks, Tamer Oraby, Andras Balogh

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we introduce a novel model for parental decision-making about vaccinations against a childhood disease that spreads through a contact network. This model considers a bilayer network comprising two overlapping networks, which are either Erdős–Rényi (random) networks or Barabási–Albert networks. The model also employs a Bayesian aggregation rule for observational social learning on a social network. This new model encompasses other decision models, such as voting and DeGroot models, as special cases. Using our model, we demonstrate how certain levels of social learning about vaccination preferences can converge opinions, influencing vaccine uptake and ultimately disease spread. In addition, …

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Heuristics For Anti-Cyclotomic ℤp-Extensions, Debanjana Kundu, Lawrence C. Washington Jan 2024

Heuristics For Anti-Cyclotomic ℤp-Extensions, Debanjana Kundu, Lawrence C. Washington

School of Mathematical & Statistical Sciences Faculty Publications

This paper studies Iwasawa invariants in anti-cyclotomic towers. We do this by proposing two heuristics supported by computations. First we propose the Intersection Heuristics: these model “how often” the p-Hilbert class field of an imaginary quadratic field intersects the anti-cyclotomic tower and to what extent. Second we propose the Invariants Heuristics: these predict that the Iwasawa invariants 𝜆 and 𝜇 usually vanish for imaginary quadratic fields where p is non-split.

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Hydrodynamics Of Drops And Particles Driven By Marangoni And Diffusiophoretic Forces, Subramaniam Chembai Ganesh Jan 2024

Hydrodynamics Of Drops And Particles Driven By Marangoni And Diffusiophoretic Forces, Subramaniam Chembai Ganesh

Dissertations and Theses

This study investigates the hydrodynamics of particles and drops driven by forces generated by an asymmetrical physical and chemical surrounding environment. In the first part, a novel colloidal motor design driven by surface tension forces is proposed, utilizing an active Janus particle encapsulated in an immiscible liquid drop to form a compound drop/particle. Marangoni forces induced by asymmetric solute adsorption at the liquid-liquid interface of the drop propels the compound system. The propulsion speeds of the motor are analyzed for various relative sizes and configurations of the Janus particle and the encapsulating drop and the effects of varying the transport …

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Using Pose Estimation Software To Predict Actions In Sabre Fencing, Micah Edwin Peters Ii Jan 2024

Using Pose Estimation Software To Predict Actions In Sabre Fencing, Micah Edwin Peters Ii

Honors College Theses

Fencing is a combat sport that uses three different swords: epee, foil, and sabre. Due to its fast-paced nature and employment of right of way, sabre fencing is often considered the most difficult of the three to learn. Computer vision and pose estimation software can be used to lower the barrier of entry to sabre fencing by identifying the different actions in sabre fencing. This project focuses on using open-source software to design a program that can identify the sabre parries as well as the main sabre movements. This program could be used to help newer fencers and spectators better …

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