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Articles 10711 - 10740 of 302431

Full-Text Articles in Physical Sciences and Mathematics

Constrained Multiagent Reinforcement Learning For Large Agent Population, Jiajing Ling, Arambam James Singh, Duc Thien Nguyen, Akshat Kumar Sep 2023

Constrained Multiagent Reinforcement Learning For Large Agent Population, Jiajing Ling, Arambam James Singh, Duc Thien Nguyen, Akshat Kumar

Research Collection School Of Computing and Information Systems

Learning control policies for a large number of agents in a decentralized setting is challenging due to partial observability, uncertainty in the environment, and scalability challenges. While several scalable multiagent RL (MARL) methods have been proposed, relatively few approaches exist for large scale constrained MARL settings. To address this, we first formulate the constrained MARL problem in a collective multiagent setting where interactions among agents are governed by the aggregate count and types of agents, and do not depend on agents’ specific identities. Second, we show that standard Lagrangian relaxation methods, which are popular for single agent RL, do not …

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Threshold Attribute-Based Credentials With Redactable Signature, Rui Shi, Huamin Feng, Yang Yang, Feng Yuan, Yingjiu Li, Hwee Hwa Pang, Robert H. Deng Sep 2023

Threshold Attribute-Based Credentials With Redactable Signature, Rui Shi, Huamin Feng, Yang Yang, Feng Yuan, Yingjiu Li, Hwee Hwa Pang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Threshold attribute-based credentials are suitable for decentralized systems such as blockchains as such systems generally assume that authenticity, confidentiality, and availability can still be guaranteed in the presence of a threshold number of dishonest or faulty nodes. Coconut (NDSS'19) was the first selective disclosure attribute-based credentials scheme supporting threshold issuance. However, it does not support threshold tracing of user identities and threshold revocation of user credentials, which is desired for internal governance such as identity management, data auditing, and accountability. The communication and computation complexities of Coconut for verifying credentials are linear in the number of each user's attributes and …

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Continual Collaborative Filtering Through Gradient Alignment, Dinh Hieu Do, Hady Wirawan Lauw Sep 2023

Continual Collaborative Filtering Through Gradient Alignment, Dinh Hieu Do, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

A recommender system operates in a dynamic environment where new items emerge and new users join the system, resulting in ever-growing user-item interactions over time. Existing works either assume a model trained offline on a static dataset (requiring periodic re-training with ever larger datasets); or an online learning setup that favors recency over history. As privacy-aware users could hide their histories, the loss of older information means that periodic retraining may not always be feasible, while online learning may lose sight of users' long-term preferences. In this work, we adopt a continual learning perspective to collaborative filtering, by compartmentalizing users …

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Revisiting The Identification Of The Co-Evolution Of Production And Test Code, Weifeng Sun, Meng Yan, Zhongxin Liu, Xin Xia, Yan Lei, David Lo Sep 2023

Revisiting The Identification Of The Co-Evolution Of Production And Test Code, Weifeng Sun, Meng Yan, Zhongxin Liu, Xin Xia, Yan Lei, David Lo

Research Collection School Of Computing and Information Systems

Many software processes advocate that the test code should co-evolve with the production code. Prior work usually studies such co-evolution based on production-test co-evolution samples mined from software repositories. A production-test co-evolution sample refers to a pair of a test code change and a production code change where the test code change triggers or is triggered by the production code change. The quality of the mined samples is critical to the reliability of research conclusions. Existing studies mined production-test co-evolution samples based on the following assumption: if a test class and its associated production class change together in one commit, …

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Autodebloater: Automated Android App Debloating, Jiakun Liu, Xing Hu, Thung Ferdian, Shahar Maoz, Eran Toch, Debin Gao, David Lo Sep 2023

Autodebloater: Automated Android App Debloating, Jiakun Liu, Xing Hu, Thung Ferdian, Shahar Maoz, Eran Toch, Debin Gao, David Lo

Research Collection School Of Computing and Information Systems

Android applications are getting bigger with an increasing number of features. However, not all the features are needed by a specific user. The unnecessary features can increase the attack surface and cost additional resources (e.g., storage and memory). Therefore, it is important to remove unnecessary features from Android applications. However, it is difficult for the end users to fully explore the apps to identify the unnecessary features, and there is no off-the-shelf tool available to assist users to debloat the apps by themselves. In this work, we propose AutoDebloater to debloat Android applications automatically for end users. AutoDebloater is a …

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Real: A Representative Error-Driven Approach For Active Learning, Cheng Chen, Yong Wang, Lizi Liao, Yueguo Chen, Xiaoyong Du Sep 2023

Real: A Representative Error-Driven Approach For Active Learning, Cheng Chen, Yong Wang, Lizi Liao, Yueguo Chen, Xiaoyong Du

Research Collection School Of Computing and Information Systems

Given a limited labeling budget, active learning (al) aims to sample the most informative instances from an unlabeled pool to acquire labels for subsequent model training. To achieve this, al typically measures the informativeness of unlabeled instances based on uncertainty and diversity. However, it does not consider erroneous instances with their neighborhood error density, which have great potential to improve the model performance. To address this limitation, we propose Real, a novel approach to select data instances with Representative Errors for Active Learning. It identifies minority predictions as pseudo errors within a cluster and allocates an adaptive sampling budget for …

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Adavis: Adaptive And Explainable Visualization Recommendation For Tabular Data, Songheng Zhang, Yong Wang, Haotian Li, Huamin Qu Sep 2023

Adavis: Adaptive And Explainable Visualization Recommendation For Tabular Data, Songheng Zhang, Yong Wang, Haotian Li, Huamin Qu

Research Collection School Of Computing and Information Systems

Automated visualization recommendation facilitates the rapid creation of effective visualizations, which is especially beneficial for users with limited time and limited knowledge of data visualization. There is an increasing trend in leveraging machine learning (ML) techniques to achieve an end-to-end visualization recommendation. However, existing ML-based approaches implicitly assume that there is only one appropriate visualization for a specific dataset, which is often not true for real applications. Also, they often work like a black box, and are difficult for users to understand the reasons for recommending specific visualizations. To fill the research gap, we propose AdaVis, an adaptive and explainable …

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Perceptions And Barriers To Adopting Artificial Intelligence In K-12 Education: A Survey Of Educators In Fifty States, Karen Woodruff, James Hutson, Kathryn Arnone Sep 2023

Perceptions And Barriers To Adopting Artificial Intelligence In K-12 Education: A Survey Of Educators In Fifty States, Karen Woodruff, James Hutson, Kathryn Arnone

Faculty Scholarship

Artificial Intelligence (AI) is making significant strides in the field of education, offering new opportunities for personalized learning and access to education for a more diverse population. Despite this potential, the adoption of AI in K-12 education is limited, and educators’ express hesitancy towards its integration due to perceived technological barriers and misconceptions. The purpose of this study is to examine the perceptions of K-12 educators in all 50 states of the USA towards AI, policies, training, and resources related to technology and AI, their comfort with technology, willingness to adopt new technologies for classroom instruction, and needs assessment for …

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Carbon Isotope Chemostratigraphy, Geochemistry, And Biostratigraphy Of The Paleocene–Eocene Thermal Maximum, Deepwater Wilcox Group, Gulf Of Mexico (Usa), Glenn R. Sharman, Eugene Szymanski, Rebecca A. Hackworth, Alicia C.M. Kahn, Lawrence A. Febo, Jordan Oefinger, Gunnar M. Gregory Sep 2023

Carbon Isotope Chemostratigraphy, Geochemistry, And Biostratigraphy Of The Paleocene–Eocene Thermal Maximum, Deepwater Wilcox Group, Gulf Of Mexico (Usa), Glenn R. Sharman, Eugene Szymanski, Rebecca A. Hackworth, Alicia C.M. Kahn, Lawrence A. Febo, Jordan Oefinger, Gunnar M. Gregory

Geosciences Faculty Publications and Presentations

The Paleocene–Eocene Thermal Maximum (PETM) represents the most pronounced hyperthermal of the Cenozoic era and is hypothesized to have resulted in an intensification of the paleohydrologic cycle, including enhanced seasonality and increased sediment discharge to the coastal ocean. Although the PETM has been widely documented, there are few records from deposits that form the distal, deepwater components of large sediment-routing systems. This study presents new constraints on the stratigraphic placement of the PETM in the deepwater Gulf of Mexico basin through analysis of geochemical, carbon isotopic, and biostratigraphic data within a ∼124 m cored interval of the Wilcox Group. Biostratigraphic …

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Guar-Based Injectable Hydrogel For Drug Delivery And In Vitro Bone Cell Growth, Humandra Poudel, Ambar R. Rangumagar, Pooja Singh, Adeolu Oluremi, Nawab Ali, Fumiya Watanabe, Joseph Batta-Mpouma, Jin-Woo Kim, Ahona Ghosh, Anindya Ghosh Sep 2023

Guar-Based Injectable Hydrogel For Drug Delivery And In Vitro Bone Cell Growth, Humandra Poudel, Ambar R. Rangumagar, Pooja Singh, Adeolu Oluremi, Nawab Ali, Fumiya Watanabe, Joseph Batta-Mpouma, Jin-Woo Kim, Ahona Ghosh, Anindya Ghosh

Chemistry & Biochemistry Faculty Publications and Presentations

Injectable hydrogels offer numerous advantages in various areas, which include tissue engineering and drug delivery because of their unique properties such as tunability, excellent carrier properties, and biocompatibility. These hydrogels can be administered with minimal invasiveness. In this study, we synthesized an injectable hydrogel by rehydrating lyophilized mixtures of guar adamantane (Guar-ADI) and poly-β-cyclodextrin (p-βCD) in a solution of phosphate-buffered saline (PBS) maintained at pH 7.4. The hydrogel was formed via host-guest interaction between modified guar (Guar-ADI), obtained by reacting guar gum with 1-adamantyl isocyanate (ADI) and p-βCD. Comprehensive characterization of all synthesized materials, including the hydrogel, was performed using …

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Alkaline Pretreatment And Air Mixing For Improvement Of Methane Production From Anaerobic Co-Digestion Of Poultry Litter With Wheat Straw, Yuanhang Zhan, Jun Zhu, Yiting Xiao, Leland C. Schrader Sep 2023

Alkaline Pretreatment And Air Mixing For Improvement Of Methane Production From Anaerobic Co-Digestion Of Poultry Litter With Wheat Straw, Yuanhang Zhan, Jun Zhu, Yiting Xiao, Leland C. Schrader

Biological and Agricultural Engineering Faculty Publications and Presentations

Alkaline pretreatment (AL) and air mixing (air) both have the potential to improve anaerobic co-digestion (Co-AD) of poultry litter with wheat straw for methane production. In this study, the effects of the combination of AL (pH 12 for 12 h) and air mixing (12 mL·d−1) on the Co-AD process were investigated. The substrate hydrolysis was enhanced by AL, with soluble chemical oxygen demand increased by 4.59 times and volatile fatty acids increased by 5.04 times. The cumulative methane yield in the group of Co-AD by AL integrated with air (Co-(AL + air)), being 287 mL·(g VSadded) …

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Methods Of Evaluating Quantum Phase Estimation Circuit Output, Charles A. Woodrum Sep 2023

Methods Of Evaluating Quantum Phase Estimation Circuit Output, Charles A. Woodrum

Theses and Dissertations

The quantum phase estimation (QPE) algorithm is one of the most important quantum computing algorithms that has been developed. The QPE algorithm estimates the phase or phases of the eigenvalue or eigenvalues of a unitary operator. It is a critical step for applications like Shor’s algorithm for factoring and the HHL algorithm for solving linear systems of equations, but it remains difficult to implement on current quantum computers due to small numbers of logical qubits and high error rates. This investigation derives a more accurate estimation of the phase of a unitary operator than would otherwise be attained with the …

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Leveraging Galois Theory And Computational Results In The Search For Legendre Pairs, David M. Arquette Sep 2023

Leveraging Galois Theory And Computational Results In The Search For Legendre Pairs, David M. Arquette

Theses and Dissertations

With applications spanning myriad disciplines, Hadamard matrices have tremendous utility. Infinitely many have been discovered, but there is no general proof of their existence. Proving the Hadamard conjecture would provide a significant technological edge. Hadamard matrices are difficult to construct in general; however, they can be created directly from Legendre pairs (LPs). While LPs are not trivial to find, a breakthrough in this area would be pivotal in the quest to prove the Hadamard conjecture. Most recent efforts rely upon refined search algorithms, and we seek to either develop a better such algorithm or discover an altogether new theoretical construction. …

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Steady State Thermal Blooming With Convection: Modeling, Simulation And Analysis, Jeremiah S. Lane Sep 2023

Steady State Thermal Blooming With Convection: Modeling, Simulation And Analysis, Jeremiah S. Lane

Theses and Dissertations

The modeling, simulation, and analysis of high energy laser propagation is a research topic of significant interest to the defense community. A detailed understanding of the phenomenon of thermal blooming is crucial as it is detrimental to the propagation of lasers over long distances and in the presence of aerosols. The simulation of thermal blooming has historically relied on wave optics models and scaling laws for the fluid response to the laser. Since thermal blooming occurs in the presence of natural convection, however, there is a need for simulating this coupled fluid-beam effect using a first principles approach. In this …

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Numerical Simulation Of Nonlinear Wave Equations With Machine Learning, Kristina O. F. Williams Sep 2023

Numerical Simulation Of Nonlinear Wave Equations With Machine Learning, Kristina O. F. Williams

Theses and Dissertations

A machine learning procedure is proposed to create numerical schemes for solutions of certain types of nonlinear wave equations on coarse grids. This method trains stencil weights of a discretization of the equation, with the truncation error of the scheme as the objective function for training. A neural network is used as a model for the stencil weights. The method uses centered finite differences to initialize the optimization routine and a second-order implicit-explicit time solver as a framework. Symmetry conditions are enforced on the learned operator to ensure a stable method. The procedure is applied to the Korteweg - de …

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Improving Deep Reinforcement Learning Methodology For Autonomous Defense And Escort Of Military High-Value Assets, Joseph Liles Iv Sep 2023

Improving Deep Reinforcement Learning Methodology For Autonomous Defense And Escort Of Military High-Value Assets, Joseph Liles Iv

Theses and Dissertations

This dissertation explores the application of machine learning to the control of autonomous unmanned combat aerial vehicles (AUCAVs). In particular, this research applies deep reinforcement learning methodologies to a defensive air combat scenario wherein a fleet of AUCAVs protects a military high-value asset (HVA). A collection of air battle management scenarios along with an original simulation environment and a set of designed computational experiments support the approximation of high-quality decision policies by employing Markov decision processes, approximate dynamic programming algorithms, and deep neural networks for value function approximation.

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Advances In Quaternion-Valued Neural Networks, Jeremiah P. Bill Sep 2023

Advances In Quaternion-Valued Neural Networks, Jeremiah P. Bill

Theses and Dissertations

This dissertation investigates the construction, optimization, and application of quaternion neural networks (QNNs) to Department of Defense (DoD) related problem sets. QNNs are a type of neural network wherein the weights, biases, and input values are all represented as quaternion numbers. This work provides a critical evaluation of the myriad different quaternion backpropagation derivations that exist in the literature, testing the performance of each on a range of regression problem sets. The optimization dynamics of QNNs are explored, presenting visualizations of QNN loss surfaces and a novel method for assessing the “smoothness” of these loss surfaces. Finally, this dissertation presents …

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Advanced Statistical Methodology For The Modern Probability Of Detection, Christine E. Knott Sep 2023

Advanced Statistical Methodology For The Modern Probability Of Detection, Christine E. Knott

Theses and Dissertations

Probability of detection (POD) is an invaluable part of the calculations used by the USAF to validate the capabilities of nondestructive inspection systems for detecting defects in critical structural components on aircraft. A POD study consists of a designed experiment, linear modeling, and a probability of detection verses defect size curve. This curve is useful for determining how often an aircraft should be re-inspected. Some POD studies are unsuccessful in creating realistic POD curves because the statistical modeling used has two common limitations: (1) a lack of convergence leading to no solution and, (2) violated assumptions leading to incorrect solutions. …

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The Power Of Identity Cues In Text-Based Customer Service: Evidence From Twitter, Yang Gao, Huaxia Rui, Shujing Sun Sep 2023

The Power Of Identity Cues In Text-Based Customer Service: Evidence From Twitter, Yang Gao, Huaxia Rui, Shujing Sun

Research Collection School Of Computing and Information Systems

Text-based customer service is emerging as an important channel through which companies can assist customers. However, the use of few identity cues may cause customers to feel limited social presence and even suspect the human identity of agents, especially in the current age of advanced algorithms. Does such a lack of social presence affect service interactions? We studied this timely question by evaluating the impact of customers’ perceived social presence on service outcomes and customers’ attitudes toward agents. Our identification strategy hinged on Southwest Airlines’ sudden requirement to include a first name in response to service requests on Twitter, which …

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Dynamics Of Spin And Charge Of Color Centers In Diamond Under Cryogenic Conditions, Richard G. Monge Sep 2023

Dynamics Of Spin And Charge Of Color Centers In Diamond Under Cryogenic Conditions, Richard G. Monge

Dissertations, Theses, and Capstone Projects

Individual quantum systems in semiconductors are currently the most sought-after platform for applications in quantum science. Most notably, the nitrogen-vacancy (NV) center in diamond features a defect deep within the electronic bandgap, making it amenable for precise manipulation to help pave the way to perform fundamental quantum physics experimentation. The NV center also offers long coherence times and versatile spin-dependent fluorescent properties, making it an ideal candidate for a nanoscale magnetometer. Furthermore, multi-color excitation offers deterministic charge state manipulation. While ambient operation has been key to their appeal, bringing NVs to cryogenic conditions opens new opportunities for alternate forms of …

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The Role Of Nuclear Quantum Effects In Supercooled Water And Amorphous Ice, Ali H. Eltareb Sep 2023

The Role Of Nuclear Quantum Effects In Supercooled Water And Amorphous Ice, Ali H. Eltareb

Dissertations, Theses, and Capstone Projects

Water is one of the most important substances on Earth and plays a fundamental role in numerous scientific and engineering applications. Interestingly, water behaves much differently than other liquids. For example, water shows an anomalous density maximum at 277 K, the solid phase (ice) is less denser than the liquid, and its thermodynamic response functions, such as the specific heat CP and isothermal compressibility κT, also increase anomalously upon cooling. In the glassy state, water can exist in two different forms, low-density and high-density amorphous ice (LDA and HDA). While water has been scrutinized for many centuries, …

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Construction And Performance Optimization Of Bioconjugated Nanosensors For Early Detection Of Breast Cancer And Pro-Inflammatory Diseases, Pooja Gaikwad Sep 2023

Construction And Performance Optimization Of Bioconjugated Nanosensors For Early Detection Of Breast Cancer And Pro-Inflammatory Diseases, Pooja Gaikwad

Dissertations, Theses, and Capstone Projects

In recent years, nanosensors have emerged as a tool with strong potential in medical diagnostics. Single-walled carbon nanotube (SWCNT) based optical nanosensors have notably garnered interest due to the unique characteristics of their near-infrared fluorescence emission, including tissue transparency, photostability, and various chiralities with discrete absorption and fluorescence emission bands. Additionally, the optoelectronic properties of SWCNT are sensitive to the surrounding environment, which makes them suitable for in vitro and in vivo biosensing. Single-stranded (ss) DNA-wrapped SWCNTs have been reported as optical nanosensors for cancers and metabolic diseases. Breast cancer and cardiovascular diseases are the most common causes of death …

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An Australian Blue Carbon Method To Estimate Climate Change Mitigation Benefits Of Coastal Wetland Restoration, Catherine E. Lovelock, Maria F. Adame, Jennifer Bradley, Sabine Dittmann, Valerie Hagger, Sharyn M. Hickey, Lindsay B. Hutley, Alice Jones, Jeffrey J. Kelleway, Paul S. Lavery, Peter I. Macreadie, Damien T. Maher, Soraya Mcginley, Alice Mcglashan, Sarah Perry, Luke Mosley, Kerrylee Rogers, James Z. Sippo Sep 2023

An Australian Blue Carbon Method To Estimate Climate Change Mitigation Benefits Of Coastal Wetland Restoration, Catherine E. Lovelock, Maria F. Adame, Jennifer Bradley, Sabine Dittmann, Valerie Hagger, Sharyn M. Hickey, Lindsay B. Hutley, Alice Jones, Jeffrey J. Kelleway, Paul S. Lavery, Peter I. Macreadie, Damien T. Maher, Soraya Mcginley, Alice Mcglashan, Sarah Perry, Luke Mosley, Kerrylee Rogers, James Z. Sippo

Research outputs 2022 to 2026

Restoration of coastal wetlands has the potential to deliver both climate change mitigation, called blue carbon, and adaptation benefits to coastal communities, as well as supporting biodiversity and providing additional ecosystem services. Valuing carbon sequestration may incentivize restoration projects; however, it requires development of rigorous methods for quantifying blue carbon sequestered during coastal wetland restoration. We describe the development of a blue carbon accounting model (BlueCAM) used within the Tidal Restoration of Blue Carbon Ecosystems Methodology Determination 2022 of the Emissions Reduction Fund (ERF), which is Australia's voluntary carbon market scheme. The new BlueCAM uses Australian data to estimate abatement …

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Disordered Protein Aggregates Are Linked To Changes In The Histone Post-Translational Modification Landscape In Disease And Non-Disease Models, Samantha Cobos Sep 2023

Disordered Protein Aggregates Are Linked To Changes In The Histone Post-Translational Modification Landscape In Disease And Non-Disease Models, Samantha Cobos

Dissertations, Theses, and Capstone Projects

Proper protein folding is a delicate balance that is crucial for normal biological function. In mammals, protein misfolding and aggregation leads to loss of function of the original protein while in many cases being associated with neurodegenerative diseases, eventually leading to death of the organism. In yeast however, the aggregated prion state is associated with positive cellular outcomes, and cells can switch between the [PRION+] and [prion-] states. Understanding the factors that lead to changes in prion state conformation in yeast could lead to novel insight into the conditions controlling misfolding by neurodegenerative proteinopathies. We believe that by studying the …

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Soundness And Completeness Results For The Logic Of Evidence Aggregation And Its Probability Semantics, Eoin Moore Sep 2023

Soundness And Completeness Results For The Logic Of Evidence Aggregation And Its Probability Semantics, Eoin Moore

Dissertations, Theses, and Capstone Projects

The Logic of Evidence Aggregation (LEA), introduced in 2020, offers a solution to the problem of evidence aggregation, but LEA is not complete with respect to the intended probability semantics. This left open the tasks to find sound and complete semantics for LEA and a proper axiomatization for probability semantics. In this thesis we do both. We also develop the proof theory for some LEA-related logics and show surprising connections between LEA-related logics and Lax Logic.

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On The Order-Type Complexity Of Words, And Greedy Sidon Sets For Linear Forms, Yin Choi Cheng Sep 2023

On The Order-Type Complexity Of Words, And Greedy Sidon Sets For Linear Forms, Yin Choi Cheng

Dissertations, Theses, and Capstone Projects

This work consists of two parts. In the first part, we study the order-type complexity of right-infinite words over a finite alphabet, which is defined to be the order types of the set of shifts of said words in lexicographical order. The set of shifts of any aperiodic morphic words whose first letter in the purely-morphic pre-image occurs at least twice in the pre-image has the same order type as Q ∩ (0, 1), Q ∩ (0, 1], or Q ∩ [0, 1). This includes all aperiodic purely-morphic binary words. The order types of uniform-morphic ternary words were also studied, …

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Out-Of-Distribution Generalization Of Deep Learning To Illuminate Dark Protein Functional Space, Tian Cai Sep 2023

Out-Of-Distribution Generalization Of Deep Learning To Illuminate Dark Protein Functional Space, Tian Cai

Dissertations, Theses, and Capstone Projects

Dark protein illumination is a fundamental challenge in drug discovery where majority human proteins are understudied, i.e. with only known protein sequence but no known small molecule binder. It's a major road block to enable drug discovery paradigm shift from single-targeted which looks to identify a single target and design drug to regulate the single target to multi-targeted in a Systems Pharmacology perspective. Diseases such as Alzheimer's and Opioid-Use-Disorder plaguing millions of patients call for effective multi-targeted approach involving dark proteins. Using limited protein data to predict dark protein property requires deep learning systems with OOD generalization capacity. Out-of-Distribution (OOD) …

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What Is The Best Way To Develop A Website?, Nahomy Julieta Calderon Lopez Sep 2023

What Is The Best Way To Develop A Website?, Nahomy Julieta Calderon Lopez

Theses

This project is centered around empowering individuals with the knowledge and resources necessary for effective website development. The culmination of Thesis/Directed Project II is a user-friendly website designed to distill and present the insights gathered during Thesis/Directed Project I. This website features an engaging interactive quiz, aimed to help the users identify what is the best way, for them, to develop a website. The quiz has multiple questions, each with three distinct response options, the quiz guides users towards one of three key approaches for website development: Website Builders, Content Management System platforms, or Coding. Upon receiving their quiz results, …

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Powerful Radio Sources In The Southern Sky. Ii. A Swift X-Ray Perspective, Francesco Massaro, S. V. White, A. Paggi, A. Jimenez-Gallardo, Juan P. Madrid, C. Mazzucchelli, W. R. Forman, A. Capetti, C. C. Cheung Sep 2023

Powerful Radio Sources In The Southern Sky. Ii. A Swift X-Ray Perspective, Francesco Massaro, S. V. White, A. Paggi, A. Jimenez-Gallardo, Juan P. Madrid, C. Mazzucchelli, W. R. Forman, A. Capetti, C. C. Cheung

Physics and Astronomy Faculty Publications and Presentations

We recently constructed the G4Jy-3CRE, a catalog of extragalactic radio sources based on the GLEAM 4-Jy (G4Jy) sample, with the aim of increasing the number of powerful radio galaxies and quasars with similar selection criteria to those of the revised release of the Third Cambridge Catalog (3CR). The G4Jy-3CRE consists of a total of 264 radio sources mainly visible from the Southern Hemisphere. Here, we present an initial X-ray analysis of 89 G4Jy-3CRE radio sources with archival X-ray observations from the Neil Gehrels Swift Observatory. We reduced a total of 624 Swift observations, for about 0.9 Ms of integrated exposure …

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Phase Transitions And Thermal Stability Of The Magnetic Dual Chiral Density Wave Phase In Cold, Dense Qcd, William G. Gyory Sep 2023

Phase Transitions And Thermal Stability Of The Magnetic Dual Chiral Density Wave Phase In Cold, Dense Qcd, William G. Gyory

Dissertations, Theses, and Capstone Projects

The correct description of strongly interacting matter at extreme densities and low temperatures remains poorly understood. We analyze the magnetic dual chiral density wave (MDCDW) phase, an inhomogeneous chiral condensate that arises in cold, dense quark matter in a magnetic field. We first review the background theory and derive the free energy of the condensate. Then we show how the phase transitions can be studied using a generalized Ginzburg-Landau expansion, and we derive a convenient all-orders formula for the coefficients. Using these tools, we compute the order parameters, critical temperature, and threshold temperature over a range of chemical potentials and …

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