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- Title
- DEEP LEARNING-ASSISTED EPILEPSY DETECTION AND PREDICTION.
- Creator
- Saem, Raghdah Aldahr, Ilyas, Mohammad, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
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Epilepsy is a multifaceted neurological disorder characterized by superfluous and recurrent seizure activity. Electroencephalogram (EEG) signals are indispensable tools for epilepsy diagnosis that reflect real-time insights of brain activity. Recently, epilepsy researchers have increasingly utilized Deep Learning (DL) architectures for early and timely diagnosis. This research focuses on resolving the challenges, such as data diversity, scarcity, limited labels, and privacy, by proposing...
Show moreEpilepsy is a multifaceted neurological disorder characterized by superfluous and recurrent seizure activity. Electroencephalogram (EEG) signals are indispensable tools for epilepsy diagnosis that reflect real-time insights of brain activity. Recently, epilepsy researchers have increasingly utilized Deep Learning (DL) architectures for early and timely diagnosis. This research focuses on resolving the challenges, such as data diversity, scarcity, limited labels, and privacy, by proposing potential contributions for epilepsy detection, prediction, and forecasting tasks without impacting the accuracy of the outcome. The proposed design of diversity-enhanced data augmentation initially averts data scarcity and inter-patient variability constraints for multiclass epilepsy detection. The potential features are extracted using a graph theory-based approach by analyzing the inherently dynamic characteristics of augmented EEG data. It utilizes a novel temporal weight fluctuation method to recognize the drastic temporal fluctuations and data patterns realized in EEG signals. Designing the Siamese neural network-based few-shot learning strategy offers a robust framework for multiclass epilepsy detection.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014523
- Subject Headings
- Deep learning (Machine learning), Epilepsy, Electroencephalography
- Format
- Document (PDF)
- Title
- DEVELOPMENT AND METHODOLOGY FOR AUV-BASED GEOMAGNETIC SURVEYS IN SUPPORT OF GEOPHYSICAL NAVIGATION.
- Creator
- Jepsen, Joshua, Dhanak, Manhar, Florida Atlantic University, Department of Ocean and Mechanical Engineering, College of Engineering and Computer Science
- Abstract/Description
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This thesis investigates geomagnetic survey methodology in support of the development of a geophysical navigation system for an Autonomous Underwater Vehicle (AUV). Traditional AUV navigation methods are susceptible to cumulative errors and often rely on external infrastructure, limiting their effectiveness in complex underwater environments. This research leverages geomagnetic field anomalies as an additional navigational reference to these traditional systems, particularly in the absence of...
Show moreThis thesis investigates geomagnetic survey methodology in support of the development of a geophysical navigation system for an Autonomous Underwater Vehicle (AUV). Traditional AUV navigation methods are susceptible to cumulative errors and often rely on external infrastructure, limiting their effectiveness in complex underwater environments. This research leverages geomagnetic field anomalies as an additional navigational reference to these traditional systems, particularly in the absence of Global Positioning System (GPS) and acoustics navigation systems. Geomagnetic surveys were conducted over known shipwreck sites off the coast of Fort Lauderdale, Florida, to validate the system's ability to detect and map magnetic anomalies. Data from these surveys were processed to develop high-resolution geomagnetic contour maps, which were then analyzed for accuracy, reliability, and modeling in identifying geomagnetic features.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014527
- Subject Headings
- Geomagnetism, Geophysical surveys, Autonomous underwater vehicles
- Format
- Document (PDF)
- Title
- INVESTIGATING THE EFFECTS OF TEMPERATURE ON THE UPTAKE, RETENTION, AND TROPHIC TRANSFER OF MICROPLASTICS IN BENTHIC COMMUNITIES.
- Creator
- Davis, Brianna D., McCoy, Michael W., Florida Atlantic University, Department of Marine Science and Oceanography, Charles E. Schmidt College of Science
- Abstract/Description
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Microplastics are a ubiquitous pollutant that has emphasized major concern for several benthic ecosystems and for the species that inhabit them especially as temperatures have begun to warm at an exponential rate. This study has investigated the abundance and trophic transfer intensity of microplastics through exposure experimentation to two different benthal organisms, the stone crab (Menippe mercenaria) and hard clam (Mercenaria mercenaria), under three different temperature gradients....
Show moreMicroplastics are a ubiquitous pollutant that has emphasized major concern for several benthic ecosystems and for the species that inhabit them especially as temperatures have begun to warm at an exponential rate. This study has investigated the abundance and trophic transfer intensity of microplastics through exposure experimentation to two different benthal organisms, the stone crab (Menippe mercenaria) and hard clam (Mercenaria mercenaria), under three different temperature gradients. Within a laboratory setting, hard clams were exposed to a concentration of different sizes and types of microplastics in three different temperatures to observe the accumulation rate of these particles from direct ingestion. The exposed clams were then fed to predatory stone crabs from the Indian River Lagoon, under the same three temperature treatments, to detect MP trophic transfer. To examine the disposition of ingested plastics, histology and fluorescent microscopy were used to quantify the locations and numbers of microplastics in the tissues.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014521
- Subject Headings
- Microplastics, Temperature, Mercenaria mercenariacc, Menippe mercenaria
- Format
- Document (PDF)
- Title
- EXAMINING THE EFFECTIVENESS OF FLORIDA’S EXTENDED DAY REQUIREMENT UNDER FLORIDA STATUTE §1011.62.
- Creator
- Washington, Jodi, Bogotch, Ira, Florida Atlantic University, Department of Educational Leadership and Research Methodology, College of Education
- Abstract/Description
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For nearly 60 years, politicians and policymakers have sought to improve the educational outcomes of students across their states and the country through legislated policies and programs. Despite their efforts, little progress has been made in improving the outcomes of the nation’s most vulnerable students. The achievement gap persists, and poverty divides the haves from the have-nots, especially in reading achievement. This study was designed to explore the impact of increasing time...
Show moreFor nearly 60 years, politicians and policymakers have sought to improve the educational outcomes of students across their states and the country through legislated policies and programs. Despite their efforts, little progress has been made in improving the outcomes of the nation’s most vulnerable students. The achievement gap persists, and poverty divides the haves from the have-nots, especially in reading achievement. This study was designed to explore the impact of increasing time allocated for reading instruction on student achievement in English Language Arts (ELA). Additional research questions were also included to determine if other factors impacted student achievement in ELA. The objective of this study was to determine if adding instructional time for any number of years improved student outcomes in reading.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014543
- Subject Headings
- Educational leadership, Education and state--Florida, Academic achievement, Language arts
- Format
- Document (PDF)
- Title
- FOUNDATION OF SAND: THE EISENHOWER DOCTRINE AND THE 1958 LEBANESE CRISIS.
- Creator
- Provenzano, Douglas, Hanne, Eric, Florida Atlantic University, Department of History, Dorothy F. Schmidt College of Arts and Letters
- Abstract/Description
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Occurring in the context of the Cold War, the 1958 Lebanese Crisis forced U.S. President Dwight D. Eisenhower and top policymakers to balance a multitude of factors when considering an appropriate response to the crisis. While Eisenhower claimed publicly that Operation Blue Bat was an intervention aimed at containing the every looming threat of communism, meeting records of top U.S. policy makers contradict such explanations and offer insight to the President’s true motivations. Eisenhower...
Show moreOccurring in the context of the Cold War, the 1958 Lebanese Crisis forced U.S. President Dwight D. Eisenhower and top policymakers to balance a multitude of factors when considering an appropriate response to the crisis. While Eisenhower claimed publicly that Operation Blue Bat was an intervention aimed at containing the every looming threat of communism, meeting records of top U.S. policy makers contradict such explanations and offer insight to the President’s true motivations. Eisenhower instead sought to maintain U.S. influence among a coalition of Middle Eastern conservative governments operating in a U.S. led regional military alliance. The crisis forced the President to reconcile his foreign policy objectives with the political and cultural reality of the region and prompted a major foreign policy reassessment in which Eisenhower turned away from top-down international alliance building and instead, worked to address the obvious need to court public opinion in the Arab world.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014501
- Subject Headings
- Eisenhower doctrine, Lebanon, Cold War, International relations
- Format
- Document (PDF)
- Title
- OPTIMIZATION OF BATTERY OPERATION USING ARTIFICIAL INTELLIGENCE TO MINIMIZE THE ELECTRICITY COST IN A MICROGRID WITH RENEWABLE ENERGY SOURCES AND ELECTRIC VEHICLES.
- Creator
- Colucci, Raymond A., Mahgoub, Imadeldin, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
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The increasing integration of renewable energy sources (RES) and electric vehicles (EVs) into microgrids presents both opportunities and challenges in terms of optimizing energy use and minimizing electricity costs. This dissertation explores the development of an advanced optimization framework using artificial intelligence (AI) to enhance battery operation in microgrids. The proposed solution leverages AI techniques to dynamically manage the charging and discharging of batteries,...
Show moreThe increasing integration of renewable energy sources (RES) and electric vehicles (EVs) into microgrids presents both opportunities and challenges in terms of optimizing energy use and minimizing electricity costs. This dissertation explores the development of an advanced optimization framework using artificial intelligence (AI) to enhance battery operation in microgrids. The proposed solution leverages AI techniques to dynamically manage the charging and discharging of batteries, considering fluctuating energy demands, variable electricity pricing, and intermittent RES generation. By employing a fuzzy logic-based control algorithm, the system intelligently allocates energy from solar power, grid electricity, and battery storage, while coordinating EV charging schedules to reduce peak demand charges. The optimization framework integrates predictive modeling for energy consumption and generation, alongside real-time data from weather forecasts and electricity markets, to make informed decisions. Additionally, the approach considers the trade-off between maximizing renewable energy usage and minimizing reliance on costly grid power during peak hours.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014502
- Subject Headings
- Electric vehicles, Electric vehicles--Batteries, Renewable energy, Artificial intelligence
- Format
- Document (PDF)
- Title
- THE GENETIC ASSESSMENT OF TWO MERGING ATLANTIC SPOTTED DOLPHIN (Stenella frontalis) COMMUNITIES ON GREAT BAHAMA BANK.
- Creator
- Knapp, Hayley Lynn, Baldwin, John, Florida Atlantic University, Department of Biological Sciences, Charles E. Schmidt College of Science
- Abstract/Description
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After an unexpected displacement of Atlantic spotted dolphins (Stenella frontalis) from Little Bahama Bank (LBB) to Great Bahama Bank (GBB) in 2013, the LBB immigrant and GBB resident spotted dolphins were observed socially merging and initiating courtship despite previous segregation on GBB post-displacement. This project assessed the genetic integration between them. Through microsatellite analyses and genetic differentiation, reciprocal gene flow appears to be occurring between the two...
Show moreAfter an unexpected displacement of Atlantic spotted dolphins (Stenella frontalis) from Little Bahama Bank (LBB) to Great Bahama Bank (GBB) in 2013, the LBB immigrant and GBB resident spotted dolphins were observed socially merging and initiating courtship despite previous segregation on GBB post-displacement. This project assessed the genetic integration between them. Through microsatellite analyses and genetic differentiation, reciprocal gene flow appears to be occurring between the two communities. One male was confidently assigned paternity and six males were selected as the most likely candidate males of calves. Three mottled males were designated as the most likely candidate males of calves, indicating that younger males may be reproductively successful.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014550
- Subject Headings
- Atlantic spotted dolphin, Haplotypes, Stenella frontalis, Great Bahama Bank (Bahamas)
- Format
- Document (PDF)
- Title
- THE ROLE OF THE PARATENIAL NUCLEUS AND NUCLEUS REUNIENS OF THE MIDLINE THALAMUS IN COGNITION AND AFFECT.
- Creator
- Rojas, Amanda Katherine Pajor, Vertes, Robert P., Florida Atlantic University, Center for Complex Systems and Brain Sciences, Charles E. Schmidt College of Science
- Abstract/Description
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The midline nuclei of the thalamus, previously characterized as “nonspecific” with undifferentiated connections with the cortex, have been shown to distribute in a specific and highly organized manner to subcortical and cortical structures. The midline thalamus consists of the paraventricular (PV) and paratenial (PT) nuclei, dorsally, and the reuniens (RE) and rhomboid (RH) nuclei, ventrally. The PV and RE nuclei have been examined to a far greater extent than either the PT or RH and have...
Show moreThe midline nuclei of the thalamus, previously characterized as “nonspecific” with undifferentiated connections with the cortex, have been shown to distribute in a specific and highly organized manner to subcortical and cortical structures. The midline thalamus consists of the paraventricular (PV) and paratenial (PT) nuclei, dorsally, and the reuniens (RE) and rhomboid (RH) nuclei, ventrally. The PV and RE nuclei have been examined to a far greater extent than either the PT or RH and have been shown to be involved in various affective and cognitive functions. Generally, PV is more associated with emotional and motivated behaviors such as arousal, feeding, drug addiction, fear, and anxiety, whereas RE is more involved in cognitive and mnemonic functions -- as RE represents a critical bridge between the medial prefrontal cortex (mPFC) and the hippocampal formation. As afferent projections to PT have not been systemically described, we examined the input to PT comparing it with that to PV, using retrograde anatomical tracer, fluorogold (FG). We found PT and PV are almost exclusively targeted by ‘limbic’ structures of the forebrain. Whereas afferents to PT and PV originate from very similar sources, PT receives stronger input from the cortex and PV from subcortical structures. Notably, PT receives prominent input from the mPFC and orbital (ORB) cortices, two regions associated with cognitive flexibility and decision making.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014505
- Subject Headings
- Cognition, Thalamus, Affect
- Format
- Document (PDF)
- Title
- REUSING AND RECORDING: THE PAST AND FUTURE SURVIVAL OF THE JUPITER INLET LIGHT STATION RADIO BEACON BUILDING.
- Creator
- Crowder, Hailie, Napora, Katharine, Florida Atlantic University, Department of Anthropology, Dorothy F. Schmidt College of Arts and Letters
- Abstract/Description
-
For much of the 20th century, mariners in the United States were able to utilize the radio beacon system to aid in navigation; however, in spite of its importance in U.S. nautical history, there has been very little historical or archaeological research published about the system. The Jupiter Inlet Light Station Radio Beacon Building, located at what is today known as the Jupiter Inlet Lighthouse Outstanding Natural Area (JILONA), was part of this coastal network of radio beacons. This thesis...
Show moreFor much of the 20th century, mariners in the United States were able to utilize the radio beacon system to aid in navigation; however, in spite of its importance in U.S. nautical history, there has been very little historical or archaeological research published about the system. The Jupiter Inlet Light Station Radio Beacon Building, located at what is today known as the Jupiter Inlet Lighthouse Outstanding Natural Area (JILONA), was part of this coastal network of radio beacons. This thesis involves the methodologies of historical research and terrestrial laser scanning and serves several purposes: to provide JILONA with information about and a digital point cloud of the radio beacon building for future use in a planned museum onsite, to create a much-needed historical narrative of the U.S. radio beacon system, and to aid the Florida Atlantic University Department of Anthropology in future terrestrial laser scanner and modeling efforts. Because the project was undertaken at the request of JILONA, this thesis is to be considered a work of public archaeology.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014540
- Subject Headings
- Jupiter Inlet Light (Fla.), Radio beacons, Archaeology
- Format
- Document (PDF)
- Title
- SPACE-TIME GRAPH-BASED VEHICULAR TRAJECTORY PLANNER: AN AUTONOMOUS INTERSECTION MANAGEMENT SYSTEM.
- Creator
- Mutlu, Caner, Cardei, Ionut, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
-
Every passenger vehicle must rely on a safe and optimal trajectory to eliminate traffic incidents and congestion as well as to reduce environmental impact, and travel time. Autonomous intersection management systems (AIMS) enable large scale optimization of vehicular trajectories with connected and autonomous vehicles (CAVs). The first contribution of this dissertation is the fastest trajectory planner (FTP) method which is geared for computing the fastest waypoint trajectories via performing...
Show moreEvery passenger vehicle must rely on a safe and optimal trajectory to eliminate traffic incidents and congestion as well as to reduce environmental impact, and travel time. Autonomous intersection management systems (AIMS) enable large scale optimization of vehicular trajectories with connected and autonomous vehicles (CAVs). The first contribution of this dissertation is the fastest trajectory planner (FTP) method which is geared for computing the fastest waypoint trajectories via performing graph search over a discretized space-time (ST) graph (Gt), thereby constructing collision-free space-time trajectories with variable vehicular speeds adhering to traffic rules and dynamical constraints of vehicles. The benefits of navigating a connected and autonomous vehicle (CAV) truly capture effective collaboration between every CAV during the trajectory planning step. This requires addressing trajectory planning activity along with vehicular networking in the design phase. For complementing the proposed FTP method in decentralized scenarios, the second contribution of this dissertation is an application layer V2V solution using a coordinator-based distributed trajectory planning method which elects a single leader CAV among all the collaborating CAVs without requiring a centralized infrastructure. The leader vehicular agent calculates and assigns a trajectory for each node CAV over the vehicular network for the collision-free management of an unsignalized road intersection. The proposed FTP method is tested in a simulated road intersection scenario for carrying out trials on scheduling efficiency and algorithm runtime. The resulting trajectories allow high levels of intersection sharing, high evacuation rate, with a low algorithm single-threaded runtime figures even with large scenarios of up to 1200 vehicles, surpassing comparable systems.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014539
- Subject Headings
- Autonomous vehicles, Computer engineering, Transportation
- Format
- Document (PDF)
- Title
- QUANTIZATIONS OF THE SCHWARZSCHILD INTERIOR FROM DIFFEOMORPHISM COVARIANCE AND OTHER CRITERIA.
- Creator
- Dias, Rafael Guolo, Engle, Jonathan S., Florida Atlantic University, Department of Physics, Charles E. Schmidt College of Science
- Abstract/Description
-
We propose an approach to the quantization of the interior of a Schwarzschild black hole, represented by a Kantowski-Sachs (KS) framework, by requiring its covariance under a notion of residual diffeomorphisms. We solve for the family of Hamiltonian constraint operators satisfying the associated covariance condition, in addition to parity covariance, preservation of the Bohr Hilbert space of Loop Quantum KS and a correct (naïve) classical limit. We further explore imposing minimality of the...
Show moreWe propose an approach to the quantization of the interior of a Schwarzschild black hole, represented by a Kantowski-Sachs (KS) framework, by requiring its covariance under a notion of residual diffeomorphisms. We solve for the family of Hamiltonian constraint operators satisfying the associated covariance condition, in addition to parity covariance, preservation of the Bohr Hilbert space of Loop Quantum KS and a correct (naïve) classical limit. We further explore imposing minimality of the number of terms, and compare the solution with other Hamiltonian constraints proposed for Loop Quantum KS in the literature, with special attention to a most recent case. In addition, we discuss a lapse commonly chosen to decouple the evolution of the two degrees of freedom of the model, yielding exact solubility of the model, and we show that such choice can indeed be quantized as an operator densely defined on the Bohr Hilbert space, but must include an infinite number of shift operators. Also, we show the reasons why we call the classical limit “naïve”, and point this out as a reason for one limitation of some present prescriptions.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014546
- Subject Headings
- Black holes (Astronomy), Quantum theory, Diffeomorphisms, Gravity
- Format
- Document (PDF)
- Title
- SYNERGETIC COMBINATION OF SEAWATER AND POLYMER-COATED NICKEL NANOPARTICLES FOR CO2 CAPTURE.
- Creator
- Abhishek, Kim, Myeongsub, Florida Atlantic University, Department of Ocean and Mechanical Engineering, College of Engineering and Computer Science
- Abstract/Description
-
Due to technological advancement, energy consumption and demand have been increasing significantly, primarily satisfied by fossil fuel utilization. The dependence on fossil fuels results in substantial greenhouse gas emissions, with CO₂ being the principal factor in global warming. Carbon capture technologies are employed to mitigate the escalated CO₂ emissions into the atmosphere. Among various carbon capture methods, amine scrubbing is widely utilized because of its high CO2 capture...
Show moreDue to technological advancement, energy consumption and demand have been increasing significantly, primarily satisfied by fossil fuel utilization. The dependence on fossil fuels results in substantial greenhouse gas emissions, with CO₂ being the principal factor in global warming. Carbon capture technologies are employed to mitigate the escalated CO₂ emissions into the atmosphere. Among various carbon capture methods, amine scrubbing is widely utilized because of its high CO2 capture efficiency and ease of adaptability to the existing power plants. This method, however, presents drawbacks, including increased toxicity, corrosiveness, and substantial freshwater use. To overcome these shortcomings and simultaneously develop an environmentally sustainable carbon capture solution, this study aims to evaluate the CO2 capture performance of seawater associated with polyvinylpyrrolidone (PVP) polymer-coated nickel nanoparticles (NiNPs) catalysts. Using high-speed bubble-based microfluidics, we investigated time-dependent size variations of CO2 bubbles in a flow-focusing microchannel, which is directly related to transient CO₂ dissolution into the surrounding solution. We hypothesize that the higher surface-to-volume ratio of polymer-coated NiNPs could provide a higher CO2 capture rate and solubility under the same environmental conditions. To test this hypothesis and to find the maximum performance of carbon capture, we synthesized polymer-coated NiNPs with different sizes of 5 nm, 10 nm, and 20 nm. The results showed that 5 nm polymer-coated NiNPs attained a CO₂ dissolution rate of 77% while it is 71% and 43% at 10 nm and 20 nm NPs, respectively. This indicates that our hypothesis is proven to be valid, suggesting that the smaller NPs catalyze CO2 capture effectively with using the same amount of material, which could be a game changer for future CO2 reduction technologies. This unique strategy promotes the future improvement of NiNPs as catalysts for CO2 capture from saltwater.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014557
- Subject Headings
- Nickel nanoparticles, Polyvinylpyrrolidone, Seawater, Carbon dioxide mitigation
- Format
- Document (PDF)
- Title
- TOPOLOGICAL MACHINE LEARNING WITH UNREDUCED PERSISTENCE DIAGRAMS.
- Creator
- Abreu, Nicole Juliana, Motta, Francis, Florida Atlantic University, Department of Mathematical Sciences, Charles E. Schmidt College of Science
- Abstract/Description
-
A common topological data analysis approach used in the experimental sciences involves creating machine learning pipelines that incorporate discriminating topological features derived from persistent homology (PH) of data samples, encoded in persistence diagrams (PDs) and associated topological feature vectors. Often the most computationally demanding step is computing PH through an algorithmic process known as boundary matrix reduction. In this work, we introduce several methods to generate...
Show moreA common topological data analysis approach used in the experimental sciences involves creating machine learning pipelines that incorporate discriminating topological features derived from persistent homology (PH) of data samples, encoded in persistence diagrams (PDs) and associated topological feature vectors. Often the most computationally demanding step is computing PH through an algorithmic process known as boundary matrix reduction. In this work, we introduce several methods to generate topological feature vectors from unreduced boundary matrices. We compared the performance of classifiers trained on vectorizations of unreduced PDs to vectorizations of fully-reduced PDs across several benchmark ML datasets. We discovered that models trained on PDs built from unreduced diagrams can perform on par and even outperform those trained on full-reduced diagrams. This observation suggests that machine learning pipelines which incorporate topology-based features may benefit in terms of computational cost and performance by utilizing information contained in unreduced boundary matrices.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014518
- Subject Headings
- Machine learning, Topology, Data sets
- Format
- Document (PDF)
- Title
- HUMAN ACTIVITY RECOGNITION: INTEGRATING SENSOR FUSION AND ARTIFICIAL INTELLIGENCE.
- Creator
- Alanazi, Munid, Ilyas, Mohammad, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
-
Human Activity Recognition (HAR) plays a crucial role in various applications, including healthcare, fitness tracking, security, and smart environments, by enabling the automatic classification of human actions based on sensor and visual data. This dissertation presents a comprehensive exploration of HAR utilizing machine learning, sensor-based data, and Fusion approaches. HAR involves classifying human activities over time by analyzing data from sensors such as accelerometers and gyroscopes....
Show moreHuman Activity Recognition (HAR) plays a crucial role in various applications, including healthcare, fitness tracking, security, and smart environments, by enabling the automatic classification of human actions based on sensor and visual data. This dissertation presents a comprehensive exploration of HAR utilizing machine learning, sensor-based data, and Fusion approaches. HAR involves classifying human activities over time by analyzing data from sensors such as accelerometers and gyroscopes. Recent advancements in computational technology and sensor availability have driven significant progress in this field, enabling the integration of these sensors into smartphones and other devices. The first study outlines the foundational aspects of HAR and reviews existing literature, highlighting the importance of machine learning applications in healthcare, athletics, and personal use. In the second study, the focus shifts to addressing challenges in handling large-scale, variable, and noisy sensor data for HAR systems. The research applies machine learning algorithms to the KU-HAR dataset, revealing that the LightGBM classifier outperforms others in key performance metrics such as accuracy, precision, recall, and F1 score. This study underscores the continued relevance of optimizing machine learning techniques for improved HAR systems. The study highlights the potential for future research to explore more advanced fusion techniques to fully leverage different data modalities for HAR. The third study focuses on overcoming common challenges in HAR research, such as varying smartphone models and sensor configurations, by employing data fusion techniques.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014496
- Subject Headings
- Artificial intelligence, Human activity recognition, Detectors
- Format
- Document (PDF)
- Title
- Human or AI?: Can AI Replace Human Graphic Designers.
- Creator
- Bacchus, Crystal, Johnson, Linda K., Florida Atlantic University, Department of Visual Arts and Art History, Dorothy F. Schmidt College of Arts and Letters
- Abstract/Description
-
Artificial intelligence is now a way of life meaning, it is hard to find any type of technology or technological advance that isn’t assisted by or powered by artificial intelligence and machine learning. From Siri on our iPhones to our computer tailored Netflix home screens to fast learning computerized and independent floor vacuums AI is everywhere you turn intruding on every aspect of daily functioning. As the pressure of said intrusion increases questions arise about whether all these...
Show moreArtificial intelligence is now a way of life meaning, it is hard to find any type of technology or technological advance that isn’t assisted by or powered by artificial intelligence and machine learning. From Siri on our iPhones to our computer tailored Netflix home screens to fast learning computerized and independent floor vacuums AI is everywhere you turn intruding on every aspect of daily functioning. As the pressure of said intrusion increases questions arise about whether all these advances can become crushing to humans. In some instances technology with AI components has been used to replace certain skill sets affecting the availability of employment surround jobs including, cashiers, hotel reception, customer service, taxi drivers, toll booths. And what about graphic design? Can a machine programmed with AI replace the creativity of a human spirit? The research explores the tension between automated (artificial intelligence + machine learning) and manual, human initiated methods and practices in graphic design… Can humans be removed from the process of graphic design? Expected outcome: No How can the case study exploration coupled with the examination of certain considerations including ethical practices, human creativity, quality and originality demonstrate the necessity of human involvement.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014545
- Subject Headings
- Graphic arts, Artificial intelligence
- Format
- Document (PDF)
- Title
- MARINE MICROBIAL INTERACTIONS: A TALE OF TWO CITIES.
- Creator
- Palau, Jackie Lin, McFarland, Malcolm, Florida Atlantic University, Department of Biological Sciences, Charles E. Schmidt College of Science
- Abstract/Description
-
Microbial partners provide beneficial and detrimental functions to their hosts and other microbes through the exchange of metabolites and info chemicals. Developing an understanding of these micro-interactions has considerable implications for human health, agriculture, and ecosystem protection. Here, the microbial interactions of two important marine organisms: the Forcepia sp. sponge, a source of the potential anticancer compound, lasonolide A (LSA), and Pyrodinium bahamense, a...
Show moreMicrobial partners provide beneficial and detrimental functions to their hosts and other microbes through the exchange of metabolites and info chemicals. Developing an understanding of these micro-interactions has considerable implications for human health, agriculture, and ecosystem protection. Here, the microbial interactions of two important marine organisms: the Forcepia sp. sponge, a source of the potential anticancer compound, lasonolide A (LSA), and Pyrodinium bahamense, a dinoflagellate which produces the potent neurotoxin, saxitoxin, were investigated. Chapter 1 introduces marine microbial interactions, their importance in the function of organisms and ecosystems, and their applications in human health, agriculture and ecosystem production. Chapter 2 describes the identification and capture of the lasonolide biosynthetic pathway from a metagenomic fosmid library. This chapter also describes the assembly of the pathway into an expression vector and attempts to sustainably produce LSA through heterologous expression. Chapter 3 describes the identification and characterization of the bacterial associates of Pyrodinium bahamense, a toxin producing dinoflagellate found in the northern Indian River Lagoon. This chapter also describes potential chemical and molecular interactions occurring between P. bahamense and its associated cultivable bacteria. Chapter 4 describes the investigation into the effects microbial associates have on the physiology of P. bahamense. The completion of this work further describes microbial interactions occurring in marine environments, their influences and functions in the physiology and evolution of marine organisms, and the tools available for their investigation and utilization for human and ecosystem benefit.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014532
- Subject Headings
- Marine microbiology, Pyrodinium bahamense, Microbial Interactions, lasonolide A
- Format
- Document (PDF)
- Title
- MULTI-CLASS CLASSIFICATION TECHNIQUE TO DETECT IOT ATTACKS IN REAL TIME.
- Creator
- Alrefaei, Ahmed, Ilyas, Mohammad, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
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The Internet of Things (IoT) has undergone remarkable expansion in recent years, leading to a proliferation of devices capable of connecting to the internet, collecting data, and sharing information. However, this rapid growth has also introduced a myriad of security challenges, resulting in an uptick in cyber-attacks targeting IoT infrastructures. To mitigate these threats and ensure the integrity of data, researchers have been actively engaged in the development of robust Intrusion...
Show moreThe Internet of Things (IoT) has undergone remarkable expansion in recent years, leading to a proliferation of devices capable of connecting to the internet, collecting data, and sharing information. However, this rapid growth has also introduced a myriad of security challenges, resulting in an uptick in cyber-attacks targeting IoT infrastructures. To mitigate these threats and ensure the integrity of data, researchers have been actively engaged in the development of robust Intrusion Detection Systems (IDS) utilizing various machine learning (ML) techniques. This dissertation presents a comprehensive overview of three distinct approaches toward IoT intrusion detection, each leveraging ML methodologies to enhance security measures. The first approach focuses on a multi-class classification algorithm, integrating models such as random forest, logistic regression (LR), decision tree (DT), and Xgboost. Through meticulous evaluation utilizing evaluation metrics including F1 score, recall, and precision under the Receiver Operating Characteristics (ROC) curve, this approach demonstrates a remarkable 99 % accuracy in detecting IoT attacks. In the second approach, a deep ensemble model comprising Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM) architectures is proposed for intrusion detection in IoT environments. Evaluation on the UNSW 2018 IoT Botnet dataset showcases the proficiency of this approach, achieving an accuracy of 98.4 % in identifying malicious activities. Lastly, the dissertation explores a real-time Intrusion Detection System (IDS) framework deployed within the Pyspark architecture, aimed at efficiently detecting IoT attacks while minimizing detection time.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014498
- Subject Headings
- Internet of things, Intrusion detection systems (Computer security), Deep learning (Machine learning)
- Format
- Document (PDF)
- Title
- WOMEN OF ACTION EMPOWERING WOMEN THROUGH VISUAL NARRATIVES.
- Creator
- Moraghebati, Ida, Cunningham, Stephanie, Florida Atlantic University, Department of Visual Arts and Art History, Dorothy F. Schmidt College of Arts and Letters
- Abstract/Description
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This thesis exhibition explores how Iranian women’s narratives might be reshaped for empowerment through the lens of Graphic Design. It challenges gender inequality by analyzing and examining historical and contemporary portrayals of women through case studies. To show women’s strength and resiliency, the thesis imagines an immersive experience that combines Iranian visual culture aesthetics with modern storytelling techniques. It promotes Graphic Design as a tool for social change. It adds...
Show moreThis thesis exhibition explores how Iranian women’s narratives might be reshaped for empowerment through the lens of Graphic Design. It challenges gender inequality by analyzing and examining historical and contemporary portrayals of women through case studies. To show women’s strength and resiliency, the thesis imagines an immersive experience that combines Iranian visual culture aesthetics with modern storytelling techniques. It promotes Graphic Design as a tool for social change. It adds to continuing conversations about women’s empowerment, cultural reclamation, and social advancement in Iran and, by extension, globally. The thesis exhibition envisions Graphic Design as a powerful tool for reshaping gender norms in Iranian society. It was inspired by the courage of women in movements such as Woman, Life, Freedom, which started in 2022 in Iran and other countries like Turkey, Syria, and Iraq, which demonstrate their fight for gender equality, self-determination, and the liberation of women from patriarchal and oppressive systems.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014541
- Subject Headings
- Iranians, Women's studies, Narratives
- Format
- Document (PDF)
- Title
- WRITING THE EARTH: THE RURAL INTELLECTUALISM OF JIM HARRISON.
- Creator
- Jones, Daniel Alexander, Hagood, Taylor, Florida Atlantic University, Department of English, Dorothy F. Schmidt College of Arts and Letters
- Abstract/Description
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An interdisciplinary study of the life and work of Jim Harrison. Through the lens of cultural and intellectual history, this dissertation places Harrison within the canon of American literature, from Emerson and Thoreau through Hemingway and Kerouac, and argues that the fundamental thread connecting these writers is their response to industrialization, suburbanization, and consumerism that undermine Americans’ connection to nature and limits an authentic experience with the world. In his...
Show moreAn interdisciplinary study of the life and work of Jim Harrison. Through the lens of cultural and intellectual history, this dissertation places Harrison within the canon of American literature, from Emerson and Thoreau through Hemingway and Kerouac, and argues that the fundamental thread connecting these writers is their response to industrialization, suburbanization, and consumerism that undermine Americans’ connection to nature and limits an authentic experience with the world. In his novels, novellas, and essays Jim Harrison explores the meaning of the well-lived life, reflecting on the importance of cultivating both a life of the hands and of the mind, of action and contemplation, of nature and literature.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014510
- Subject Headings
- Harrison, Jim, 1937-2016, Harrison, Jim, 1937-2016--Criticism and interpretation
- Format
- Document (PDF)
- Title
- Looking Into the Deep: Investigating Micro- and Nanoscale Biomineral Architecture of Marine Organisms Using Advanced Characterization Techniques.
- Creator
- Raja, Dawn May Somu, Merk, Vivian, Florida Atlantic University, Department of Ocean and Mechanical Engineering, College of Engineering and Computer Science
- Abstract/Description
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Living organisms synthesize and assemble complex bioinorganic composites with enhanced structure and properties to fulfill needs such as structural support and enhanced mechanical function. With the advent of advanced materials characterization techniques, these biomineral systems can be explored with high resolution to glean information on their composition, ultrastructure, assembly, and biomechanics. In this work, the endoskeletal features of two marine organisms are explored. Acantharia...
Show moreLiving organisms synthesize and assemble complex bioinorganic composites with enhanced structure and properties to fulfill needs such as structural support and enhanced mechanical function. With the advent of advanced materials characterization techniques, these biomineral systems can be explored with high resolution to glean information on their composition, ultrastructure, assembly, and biomechanics. In this work, the endoskeletal features of two marine organisms are explored. Acantharia are geographically widespread marine planktonic single-celled organisms. Their star-shaped SrSO4 endoskeleton consists of spicules emanating from a central junction, arranged to satisfy crystallochemical and spatial requirements of their orthorhombic crystal lattice. In this work, synchrotron X-ray nanotomography and deep-learning guided image segmentation methods were used to characterize the endoskeleton of 5 types of Acantharia and to extrapolate their growth mechanism. The results highlight the diverse morphology of the spicules and spicular junctions that Acantharia achieve whilst maintaining overall spatial arrangement. Fine structural features, such as interspicular interstices thought to play a role in the robustness of the overall endoskeleton, were resolved.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014526
- Subject Headings
- Biomineralization, Materials science, Acantharia, Shark cartilage
- Format
- Document (PDF)