Physical Sciences and Mathematics Commons^™

Gts: Gpu-Based Tree Index For Fast Similarity Search, Yifan Zhu, Ruiyao Ma, Baihua Zheng, Xiangyu Ke, Lu Chen, Yunjun Gao

Research Collection School Of Computing and Information Systems

Similarity search, the task of identifying objects most similar to a given query object under a specific metric, has gathered significant attention due to its practical applications. However, the absence of coordinate information to accelerate similarity search and the high computational cost of measuring object similarity hinder the efficiency of existing CPU-based methods. Additionally, these methods struggle to meet the demand for high throughput data management. To address these challenges, we propose GTS, a GPU-based tree index designed for the parallel processing of similarity search in general metric spaces, where only the distance metric for measuring object similarity is known. …

Jollygesture: Exploring Dual-Purpose Gestures In Vr Presentations, Gun Woo Warren Park, Anthony Tang, Fanny Chevalier

Research Collection School Of Computing and Information Systems

Virtual reality (VR) offers new opportunities for presenters to use expressive body language to engage their audience. Yet, most VR presentation systems have adopted control mechanisms that mimic those found in face-to-face presentation systems. We explore the use of gestures that have dual-purpose: first, for the audience, a communicative purpose; second, for the presenter, a control purpose to alter content in slides. To support presenters, we provide guidance on what gestures are available and their effects. We realize our design approach in JollyGesture, a VR technology probe that recognizes dual-purpose gestures in a presentation scenario. We evaluate our approach through …

Usability Versus Collectibility In Nft: The Case Of Web3 Domain Names, Ping Fan Ke, Yi Meng Lau

Research Collection School Of Computing and Information Systems

This study examines the market’s inclination towards usability and collectibility aspects of Non-Fungible Tokens (NFTs) within Web3 domain name marketplaces, drawing insights from resale records. Our findings reveal a prevailing preference for usability, as evidenced by consistently higher average resale prices observed for Ethereum Name Service (ENS) domains compared to Linagee Name Registrar (LNR) domains. However, domains with diminished usability, such as those containing non-ASCII characters, tend to attract investors due to their enhanced collectibility. Our analysis on the effect from previous resale suggests a potential aversion towards second-hand acquisitions among NFT investors when value derives primarily from usability, while …

Predicting Mild Cognitive Impairment Through Ambient Sensing And Artificial Intelligence, Ah-Hwee Tan, Weng Yan Ying, Budhitama Subagdja, Anni Huang, Shanthoshigaa D, Tony Chin-Ian Tay, Iris Rawtaer

Research Collection School Of Computing and Information Systems

This paper reports an emerging application leveraging ambient and artificial intelligence techniques for in-home sensing and cognitive health assessment. The application involves a prospective longitudinal study, wherein non-pervasive sensing devices are installed in homes of over 63 real users undergoing clinical cognitive assessment, and digital signals of the users’ activities and behaviour are transmitted to a central cloud-based data server for further processing and analysis. Based on the sensor readings, we identify a set of digital biomarkers covering four key aspects of daily living, namely physical, activity, cognitive, and sleep, and develop a suite of customized feature extraction methods for …

Architectural Elements Contributing To Interpretability Of Deep Neural Networks (Dnns), Emily Barnes, James Hutson

Faculty Scholarship

The interpretability of Deep Neural Networks (DNNs) has become a critical focus in artificial intelligence and machine learning, particularly as DNNs are increasingly used in high-stakes applications like healthcare, finance, and autonomous driving. Interpretability refers to the extent to which humans can understand the reasons behind a model's decisions, which is essential for trust, accountability, and transparency. However, the complexity and depth of DNN architectures often compromise interpretability as these models function as "black boxes." This article reviews key architectural elements of DNNs that affect their interpretability, aiming to guide the design of more transparent and trustworthy models. The primary …

Simultaneous Chandra And Hst Observations Of The Quiescent Neutron Star Low-Mass X-Ray Binaries In 47 Tucanae, M. Van Den Berg, Liliana E. Rivera Sandoval, C O. Heinke, H. N. Cohn, P. M. Lugger, J. E. Grindlay, P. D. Edmonds, J. Anderson, A. Catuneanu

Physics & Astronomy Faculty Publications

We present simultaneous Chandra X-ray Observatory and Hubble Space Telescope observations of three certain (X5, X7, W37) and two likely (X4, W17) quiescent neutron star low-mass X-ray binaries (qLMXBs) in the globular cluster 47 Tuc. We study these systems in the X-ray, optical, and near-ultraviolet (NUV) using the simultaneous data and additional non-contemporaneous HST data. We have discovered a blue and variable NUV counterpart to W17. We have not securely identified the eclipsing qLMXB W37 in the optical or NUV. Deeper high-resolution imaging is needed to further investigate the faint NUV excess near the centre of the W37 error circle. …

Electrocoagulation As A Pretreatment For Reverse Osmosis For Potable Water From Brackish Groundwater, Mahmood Jebur, Yu-Hsuan Chiao, Hideto Matsuyama, S. Ranil Wickramasinghe

Chemical Engineering Faculty Publications and Presentations

Reverse osmosis (RO) is a widely utilized method for water treatment and desalination. Our study examined the application of an electrocoagulation (EC) and RO hybrid system for treating actual brackish groundwater (BGW), focusing on reducing RO scaling by EC pretreatment. A series of EC operating conditions were investigated, such as applied voltage, pH, EC reaction time, and type of electrode. The commercial software WAVE was utilized to analyze the water quality to assess the scaling potential of the EC pretreated feed stream for the San Antonio Water System (SAWS) BGW desalination plant. The SAWS BGW desalination process involves a three-stage …

Hydroponic Nutrient Solution Temperature Impacts Tulane Virus Persistence Over Time, Gayatri R. Dhulappanavar, Kristen E. Gibson

Food Science Faculty Publications and Presentations

Controlled environment agriculture (CEA), or indoor agriculture, encompasses non-traditional farming methods that occur inside climate-controlled structures (e.g., greenhouses, warehouses, high tunnels) allowing for year-round production of fresh produce such as leaf lettuce. However, recent outbreaks and recalls associated with hydroponically grown lettuce contaminated with human pathogens have raised concerns. Few studies exist on the food safety risks during hydroponic cultivation of leaf lettuce; thus, it is important to identify contributing risk factors and potential mitigation strategies to prevent foodborne transmission via hydroponically grown produce. In this study, the concentration of infectious Tulane virus (TV), a human norovirus surrogate, in hydroponic …

Visualizing Privately Protected Data: Exploring The Privacy-Utility Trade-Offs, Sarah Hayi Alkaabi

Theses

In a data-driven era, achieving a balance between privacy and utility is crucial. Organizations often utilize data for research, analysis, and enhancement of services, which emphasizes the significance of effective privacy-preserving techniques to protect individuals' privacy and comply with regulations. This equilibrium is vital in data visualization to derive insightful decisions from data representations. The goal is to evaluate the trade-off between privacy preservation and data utility, understanding how differentially private parameters impact effective visualizations. Valuable insights will guide strategies for achieving optimal privacy-preserving visualization techniques. The study aims to investigate the effects on privacy and data utility in different …

Agricultural Groundcover Update May 2024, Justin Laycock

Natural resources published reports

• In May, over 9% (1,410,000 ha) of the arable farmland in the south-west of Western Australia had less than 50% vegetative groundcover, which is inadequate to prevent wind erosion.
• Northern grainbelt had the highest risk of wind erosion and over 26% of this farmland had inadequate groundcover, predominantly found on landscapes known for sandy soils.
• About 1.3% (208,900 ha) of arable land had a high to very high risk of wind erosion because groundcover was less than 30%. Half of this land was in the West Midlands Ag Soil Zone.

Agricultural Groundcover Update April 2024, Justin Laycock

Natural resources published reports

• In April, over 12% (1,876,000 ha) of the arable farmland in the south-west of Western Australia had less than 50% vegetative groundcover, which is inadequate to prevent wind erosion.
• Northern grainbelt had the highest risk of wind erosion and over 26% of this farmland had inadequate groundcover, predominantly found on landscapes known for sandy soils.
• About 1.5% (238,900 ha) of arable land had a high to very high risk of wind erosion because groundcover was less than 30%.

Development And Applications Of Flexible Piezoelectric Nanogenerators Using Batio3, Pdms, And Mwcnts For Energy Harvesting And Sensory Integration In Smart Systems, Islam Uddin Shipu, Dipasree Bhowmick, Nondon Lal Dey

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)

Mechanical energy is a versatile and accessible green energy source, increasingly harnessed to power small-scale devices via innovative flexible piezoelectric nanogenerators (F- PNGs). These devices convert mechanical energy into electricity using lightweight materials such as Barium Titanate (BaTiO3), poly dimethyl siloxane (PDMS), and multi-walled carbon nanotubes (MWCNTs). In this design, BaTiO3 nanoparticles were embedded in a composite film with PDMS and MWCNTs, sandwiched between two copper electrodes. The BaTiO3/PDMS/MWCNT composite PENGs, synthesized for this study, produce an output voltage of ∼8 V through periodic cyclic beating. This represents an increase of about 16% compared to the PENGs without MWCNT doping. …

Phase Error Scaling Law In Two-Wavelength Adaptive Optics, Milo W. Hyde Iv, Matthew Kalensky, Michael J. Spencer

Faculty Publications

We derive a simple, physical, closed-form expression for the optical-path difference (OPD) of a two-wavelength adaptive-optics (AO) system. Starting from Hogge and Butts’ classic OPD variance integral expression, we apply Mellin transform techniques to obtain series and asymptotic solutions to the integral. For realistic two-wavelength AO systems, the former converges slowly and has limited utility. The latter, on the other hand, is a simple formula in terms of the separation between the AO sensing (i.e., the beacon) and compensation (or observation) wavelengths. We validate this formula by comparing it to the OPD variances obtained from the aforementioned series and direct …

Trace Element Contamination In Urban Soils: Testing And Management, Melissa Chilinski, Melanie Stock, Paul R. Grossl, Eli Oliver

All Current Publications

Trace elements, often referred to as heavy metals, naturally occur in the soil at low levels. Certain land use histories can elevate the concentrations of trace elements to levels that present health risks. Understanding which elements and soil test values may impact human or crop health is an important aspect of gardening and micro-farming, particularly in urban environments that are at increased risk of soil contamination. This fact sheet provides instructions on interpreting soil test results for trace elements through the Total Element Composition EPA 3050B Soil Test (#S19) at Utah State University Analytical Laboratory.

Quantics Tensor Trains: The Study Of A Continuous Lattice Model And Beyond, Aleix Bou Comas

Dissertations, Theses, and Capstone Projects

This four-chapter dissertation studies the efficient discretization of continuous variable functions with tensor train representation. The first chapter describes all the methodology used to discretize functions and store them efficiently. In this section, the algorithm tensor renormalization group is explained for self-containment purposes. The second chapter centers around the XY model. Quantics tensor trains are used to describe the transfer matrix of the model and compute one and two-dimensional quantities. The one dimensional magnitudes are compared to analytical results with an agreement close to machine precision. As for two dimensions, the analytical results cannot be computed. However, the critical temperature …

Three Essays Applying Dynamic Models In Economics, Finance, And Machine Learning, Lucas C. Dowiak

Dissertations, Theses, and Capstone Projects

This dissertation is a composition in three parts. Collectively, these essays investigate dynamic methods and their application in the fields of Economics, Finance, and Machine Learning. It pulls liberally from all three. In particular, this dissertation makes repeated use of multi-state modeling frameworks popular in Economics to bring a faceted view to the underlying data and detect its hidden heterogeneity. The challenge of modeling financial assets and estimating their dependence is another focus. For stimulus, concepts in the Machine Learning field are brought in to aid or compete with established econometric techniques.

Econometric Applications of the Hierarchical Mixture-of-Experts

In this …

Positron Emission Tomography In Oncology And Environmental Science, Samantha Delaney

Dissertations, Theses, and Capstone Projects

The last half century has played witness to the onset of molecular imaging for the clinical assessment of physiological targets. While several medical imaging modalities allow for the visualization of the functional and anatomical properties of humans and living systems, few offer accurate quantitation and the ability to detect biochemical processes with low-administered drug mass doses. This limits how physicians and scientists may diagnose and treat medical issues, such as cancer, disease, and foreign agents.

A promising alternative to extant invasive procedures and suboptimal imaging modalities to assess the nature of a biological environment is the use of positron emission …

Listening For Lemurs: Translating Black-And-White Ruffed Lemur (Varecia Variegata) Vocalizations Into Conservation Insights Through Acoustic Monitoring, Carly H. Batist

Dissertations, Theses, and Capstone Projects

The field of bioacoustic monitoring has undergone a significant evolution in recent years, driven by technological innovations that have revolutionized how researchers study animal vocalizations. Traditionally, bioacoustics was rooted in active acoustic monitoring (AAM), involving human observers using recorders in the field to study animal sounds and understand species' vocal communication. However, the emergence of passive acoustic monitoring (PAM) has introduced a new complementary approach, utilizing specialized recorders placed in ecosystems to autonomously capture sounds at wide spatial and temporal scales. My dissertation adopts a translational approach to bioacoustic monitoring, integrating both AAM and PAM techniques to study and survey …

Context In Computer Vision: A Taxonomy, Multi-Stage Integration, And A General Framework, Xuan Wang

Dissertations, Theses, and Capstone Projects

Contextual information has been widely used in many computer vision tasks, such as object detection, video action detection, image classification, etc. Recognizing a single object or action out of context could be sometimes very challenging, and context information may help improve the understanding of a scene or an event greatly. However, existing approaches design specific contextual information mechanisms for different detection tasks.

In this research, we first present a comprehensive survey of context understanding in computer vision, with a taxonomy to describe context in different types and levels. Then we proposed MultiCLU, a new multi-stage context learning and utilization framework, …

Modeling And Dynamics Of Capillary Bridges, Moyosore Odunsi

Dissertations, Theses, and Capstone Projects

Capillary bridges are ubiquitous in nature and have important implications in processes like inkjet printing. They are an important area of study not only because of their industrial applications but because many of the questions in capillary bridge research are applicable to other systems. For example, they exhibit pinning and unpinning patterns that are similar to those in sliding droplets. The rules underlying this pinning are essential to predicting liquid shapes and understanding how contact lines move across surfaces. Many previous studies have focused on axisymmetric capillary bridges and neglected to model the tangential forces that arise due to asymmetry. …

Parabolic And Non-Parabolic Surfaces With Small Or Large End Spaces Via Fenchel-Nielsen Parameters, Michael Antony Pandazis

Dissertations, Theses, and Capstone Projects

We consider conditions on the Fenchel-Nielsen parameters of a Riemann surface X that determine whether or not a surface X is parabolic. Fix a geodesic pants decomposition of a surface and call the boundary geodesics in the decomposition cuffs. For a zero or half-twist flute surface, we prove that parabolicity is equivalent to the surface having a covering group of the first kind. Using that result, we give necessary and sufficient conditions on the Fenchel-Nielsen parameters of a half-twist flute surface X with increasing cuff lengths such that X is parabolic. As an application, we determine whether or not each …

Communication Challenges In Underwater Wireless Networks: Mac Protocols And Software Solutions, Dmitrii Dugaev

Dissertations, Theses, and Capstone Projects

Underwater wireless networks (UWNs) represent a diverse and intriguing research domain, encompassing a wide array of scientific and industrial applications. This dissertation delves into the communication challenges at the Medium Access Control (MAC) layer within UWNs, stemming from the distinctive signal propagation conditions and the harshness of the deployment environment. The manuscript provides comprehensive coverage of key aspects of UWNs, including potential applications, communication protocols, methodologies employed in such networks, and existing software solutions that facilitate simulation, emulation, and real testbed scenarios for underwater research endeavors. Furthermore, this research introduces innovative software and communication solutions designed to facilitate the seamless …

Higher Diffeology Theory, Emilio Minichiello

Dissertations, Theses, and Capstone Projects

Finite dimensional smooth manifolds have been studied for hundreds of years, and a massive theory has been built around them. However, modern mathematicians and physicists are commonly dealing with objects outside the purview of classical differential geometry, such as orbifolds and loop spaces. Diffeology is a new framework for dealing with such generalized smooth spaces. This theory (whose development started in earnest in the 1980s) has started to catch on amongst the wider mathematical community, thanks to its simplicity and power, but it is not the only approach to dealing with generalized smooth spaces. Higher topos theory is another such …

Effect Of Magnetic Draping On Satellite Galaxies In Clusters, Vanessa Brown

Dissertations, Theses, and Capstone Projects

Galaxy evolution has been observed to be influenced by environment. Satellite galaxies orbiting within clusters can experience changes in morphology and composition through various mechanisms such as ram-pressure stripping (RPS), which removes a galaxy’s interstellar medium as it passes through the cluster via direct interaction with the hot intracluster medium gas. An open question is whether intracluster magnetic fields affect galaxy evolution, for example by forming a magnetic layer around infalling galaxies (called magnetic draping) and mitigating gas removal by RPS. Using the code GADGET-3, we compare global properties and mass distributions within identical cluster simulations run with and without …

Development And Application Of Magnus Expansion Based Propagators For Problems In Spectroscopy And Quantum Dynamics, Taner M. Ture

Dissertations, Theses, and Capstone Projects

Stable and accurate numerical propagators of time-evolution equations in quantum mechanics are required to capture correct dynamical behavior, especially in the long time limit. Magnus expansion (ME) provides a general way to expand the real time propagator of a time dependent Hamiltonian within the exponential such that the unitarity is satisfied at any order. Integrators are developed by truncating the ME and using explicit integration of Lagrange interpolation formulas for the time dependent Hamiltonian within each time interval. The derived approximations are studied in a numerical test and compared to other available expressions. The sixth order expression is applied to …

Sigma_N-Correct Forcing Axioms, Benjamin P. Goodman

Dissertations, Theses, and Capstone Projects

I introduce a new family of axioms extending ZFC set theory, the Sigma_n-correct forcing axioms. These assert roughly that whenever a forcing name a' can be forced by a poset in some forcing class Gamma to have some Sigma_n property phi which is provably preserved by all further forcing in Gamma, then a' reflects to some small name such that there is already in V a filter which interprets that small name so that phi holds. Sigma_1-correct forcing axioms turn out to be equivalent to classical forcing axioms, while Sigma_2-correct forcing axioms for Sigma_2-definable forcing classes are consistent relative to …

Speeding Up Coded Distributed Machine Learning, Xian Su

Dissertations, Theses, and Capstone Projects

The advancement of artificial intelligence has facilitated the generation of vast datasets, whose size often exceeds tens of terabytes. Meanwhile, machine learning has become the most important technique for big data analytics, and sophisticated models with thousands or even millions of parameters are designed to leverage big data. However, processing big data and training large models necessitate significant storage and computational resources, which has been a bottleneck in the development of artificial intelligence. Distributed computing, such as MapReduce, has been proposed to surmount the computational bottlenecks associated with single-machine analysis.

Although distributed computing harnesses the collective power of numerous less …

Explicit Composition Identities For Higher Composition Laws In The Quadratic Case, Ajith A. Nair

Dissertations, Theses, and Capstone Projects

The theory of Gauss composition of integer binary quadratic forms provides a very useful way to compute the structure of ideal class groups in quadratic number fields. In addition to that, Gauss composition is also important in the problem of representations of integers by binary quadratic forms. In 2001, Bhargava discovered a new approach to Gauss composition which uses 2x2x2 integer cubes, and he proved a composition law for such cubes. Furthermore, from the higher composition law on cubes, he derived four new higher composition laws on the following spaces - 1) binary cubic forms, 2) pairs of binary quadratic …

Unconventional Computing With Photonic Oscillator Networks, Mostafa Honari Latifpour

Dissertations, Theses, and Capstone Projects

The ever-increasing demand for data processing and the challenges in scaling traditional computing architectures are driving intensive research into alternative computing paradigms. Optical computing has garnered renewed attention since the 2010s, driven by its potential to accelerate specialized computational tasks such as combinatorial optimization and neural networks.

Coherent light sources including lasers and parametric oscillators have been around for decades and become indispensable tools in modern technology, but these photonic oscillators are also nonlinear dynamical systems that can exhibit emergent, complex phenomena, especially when coupled in arrays. These nonlinear optical systems have recently been shown to be capable of doing …

Aspects Of Parity Breaking In Classical And Quantum Fluids, Dylan J. Reynolds

Dissertations, Theses, and Capstone Projects

Parity-breaking is ubiquitous across many scales of physics, from the rotation of galaxies at the largest of scales, to the cyclotron orbits of electrons at the microscopic scale. In describing the collective dynamics of many particle systems, parity breaking effects typically originate from some form of chirality, such as angular momentum, at the level of the constituent particles. External forces can also induce chiral motion, with the primary examples being the Lorentz and Coriolis forces.

The effects of parity breaking are perhaps most strikingly seen in active matter, systems of complex particles that tend to convert energy into some directed …