Physical Sciences and Mathematics Commons^™

Hyperbolic Graph Topic Modeling Network With Continuously Updated Topic Tree, Ce Zhang, Rex Ying, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Connectivity across documents often exhibits a hierarchical network structure. Hyperbolic Graph Neural Networks (HGNNs) have shown promise in preserving network hierarchy. However, they do not model the notion of topics, thus document representations lack semantic interpretability. On the other hand, a corpus of documents usually has high variability in degrees of topic specificity. For example, some documents contain general content (e.g., sports), while others focus on specific themes (e.g., basketball and swimming). Topic models indeed model latent topics for semantic interpretability, but most assume a flat topic structure and ignore such semantic hierarchy. Given these two challenges, we propose a …

Knowledge Representation For Conceptual, Motivational, And Affective Processes In Natural Language Communication, Seng Beng Ho, Zhaoxia Wang, Boon-Kiat Quek, Erik Cambria

Research Collection School Of Computing and Information Systems

Natural language communication is an intricate and complex process. The speaker usually begins with an intention and motivation of what is to be communicated, and what outcomes are expected from the communication, while taking into consideration the listener’s mental model to concoct an appropriate sentence. Likewise, the listener has to interpret the speaker’s message, and respond accordingly, also with the speaker’s mental model in mind. Doing this successfully entails the appropriate representation of the conceptual, motivational, and affective processes that underlie language generation and understanding. Whereas big-data approaches in language processing (such as chatbots and machine translation) have performed well, …

Mastering Stock Markets With Efficient Mixture Of Diversified Trading Experts, Shuo Sun, Xinrun Wang, Wanqi Xue, Xiaoxuan Lou, Bo An

Research Collection School Of Computing and Information Systems

Quantitative stock investment is a fundamental financial task that highly relies on accurate prediction of market status and profitable investment decision making. Despite recent advances in deep learning (DL) have shown stellar performance on capturing trading opportunities in the stochastic stock market, the performance of existing DL methods is unstable with sensitivity to network initialization and hyperparameter selection. One major limitation of existing works is that investment decisions are made based on one individual neural network predictor with high uncertainty, which is inconsistent with the workflow in real-world trading firms. To tackle this limitation, we propose AlphaMix, a novel three-stage …

A Survey On Proactive Dialogue Systems: Problems, Methods, And Prospects, Yang Deng, Wenqiang Lei, Wai Lam, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Proactive dialogue systems, related to a wide range of real-world conversational applications, equip the conversational agent with the capability of leading the conversation direction towards achieving pre-defined targets or fulfilling certain goals from the system side. It is empowered by advanced techniques to progress to more complicated tasks that require strategical and motivational interactions. In this survey, we provide a comprehensive overview of the prominent problems and advanced designs for conversational agent's proactivity in different types of dialogues. Furthermore, we discuss challenges that meet the real-world application needs but require a greater research focus in the future. We hope that …

Lean Manufacturing Approach To Increase Packaging Efficiency, Lina Gozali, Irsandy Kurniawan, Aldo Salim, Iveline Anne Marie, Benny Tjahjono, Yun Chia Liang, Aldy Gunawan, Nnovia Hardjo Sie, Yuliani Suseno

Research Collection School Of Computing and Information Systems

The company upon which this paper is based engages in flexible packaging production, especially pharmaceutical products with guaranteed quality, trusted by consumers. Its production process includes printing, laminating, and assembling processes. Production activities are done manually and automatically using machines, so various types of waste are often found in these processes, making the level of plant efficiency nonoptimal. This study aims to identify wastes occurring in the production process, especially the production of pollycelonium with three colour variants as the highest demand product, by applying lean manufacturing concepts. The Current Value Stream Mapping (CVSM) used to map the production process …

The Temporal Evolution Of Subduction Initiation In The Samail Ophiolite: High-Precision U–Pb Zircon Petrochronology Of The Metamorphic Sole, Matthew Rioux, Joshua M. Garber, Michael Searle, James L. Crowley, Sally Stevens, Mark Schmitz, Andrew Kylander-Clark, Kayla Leal, Tyler Ambrose, Andrew J. Smye

Geosciences Faculty Publications and Presentations

High-precision dating of the metamorphic sole of ophiolites can provide insight into the tectonic evolution of ophiolites and subduction zone processes. To understand subduction initiation beneath a young, well-preserved and well-characterized ophiolite, we performed coupled zircon laser-ablation inductively coupled mass spectrometry trace element analyses and high-precision isotope dilution-thermal ionization mass spectrometry U–Pb dating on 25 samples from the metamorphic sole of the Samail ophiolite (Oman-United Arab Emirates). Zircon grains from amphibolite- to granulite-facies (0.8–1.3 GPa, ~700–900°C), garnet- and clinopyroxene-bearing amphibolite samples (n = 18) show systematic trends of decreasing heavy rare earth element slope (HREE; Yb/Dy) with decreasing Yb …

Effects Of Discharge And Morphology On Fluvial Sound, Scott J. Gauvain

Boise State University Theses and Dissertations

Rivers, streams, and tributaries play a critical role in the global water cycle and their dispersion of freshwater is essential for widespread human consumption, crop irrigation, waste management, and hydropower generation. Currently, there is a need for innovative, non-invasive, and low-cost methods of surface freshwater discharge gauging. With careful site selection, recording the acoustics produced by streamflow could be used reliably and inexpensively to infer changes in local discharge. An important knowledge gap currently preventing the use of acoustics for stream gauging is the unknown relationships by which stream sounds depend on discharge and stream morphology. To address this, I …

Influence Of Urbanization And Climate On Irrigation Diversions And Return Flows In The Lower Boise River Basin, Bridget M. Bittmann

Boise State University Theses and Dissertations

The western US is facing both the rapid urbanization of agricultural lands and a changing climate, producing subsequent changes to irrigation water demand and availability. Adaptive water management requires knowledge regarding how and why water usage and availability is changing; however, managers often do not possess the tools or resources for the necessary analysis. These environmental changes are also place-based, meaning that water managers cannot directly use studies from other basins to actively manage theirs. Co-produced, actionable research can help fill this knowledge gap and provide the necessary information for adaptive management. The Lower Boise River Basin (LBRB) in southwestern …

Association Of Lockdown Policies With Covid-19 Early Case Growth Rates In The United States, Anna Barefield

Boise State University Theses and Dissertations

The COVID-19 pandemic has impacted essentially the entire globe, infecting over 755 million people worldwide and resulting in over 6.8 million deaths to date. Different countries have had varying levels of success in managing the spread of the pandemic, and the success or lack thereof could be explained by the impact of government intervention, such as lockdown policies, mask mandates, and social distancing advisories. The United States responded particularly poorly to the early pandemic outbreak as compared to other similar countries, due to its lack of coordinated planning to implement effective policies, with large variations in action taken by each …

Evaluating Learning Geometric Concepts To Generate Predicate Abstract Domains In Static Program Analysis, Patrick Chadbourne

Boise State University Theses and Dissertations

Accuracy of static analysis over predicate abstract domains depends on the partitions of predicates. More precise predicates approximate concrete values of program variables resulting in more accurate analysis. Manual reasoning about these partitions must be done on a case-by-case basis and is time consuming and difficult.

This work explores learning geometric concepts to automate discovery of predicate domain candidates.

The proposed framework uses run-time data from program executions to gather training data for a PAC-learner to generate separating hyperplanes that can be projected onto predicate domains.

The thesis implements the framework and performs evaluations of it effectiveness on a set …

A History Of The Hurwitz Problem Concerning Branched Coverings, James Alexander Byars

Boise State University Theses and Dissertations

From a d-sheeted branched covering f : M → N, where M and N are surfaces, one can read off the branch datum

D(f) = {M, N, d, (A₁, . . . , A_r)},

where A_i = [e_i1, . . . , e_{in_i}] is a partition of d. Furthermore, a relationship between the Euler characteristics between M and N is known, called the Riemann-Hurwitz formula

𝒳(M) = d𝒳(N) − v(D(f …

Picking Up Steam: A Year Long Infrasonic Record Of Steamboat Geyser. Minor And Major Paroxysms Of The Multi-Phase Eruptions At Steamboat Geyser, Yellowstone National Park, Margaret Holahan

Boise State University Theses and Dissertations

The renewed activity of the world’s tallest geyser, Steamboat Geyser (Yellowstone National Park) in 2018, offers the opportunity to utilize long-term continuous infrasound and low-frequency acoustic monitoring to quantify eruptive behaviors. Eruption parameters including onset timing, duration, phase transitions between steam and water, instantaneous sound intensity, eruptive power, energy content, and spectral character, may be used to characterize individual eruption styles and reveal eruption trends. I interpret the character of the acoustic radiation through corroboration of first-hand observations and time-lapse video. I find that infrasound (acoustic energy below 20 Hz) is a particularly effective tool for tracking the evolving eruption …

Integrating Climate And Wildfire Education In The Classroom: Development And Implementation Of K-12 Place-Based Wildfire Educational Modules, Danielle Marquette

Boise State University Theses and Dissertations

In the United States, even though most parents would like their children to be educated about climate change, and most teachers support including climate change in K-12 curriculum, many schools fail to educate students about the causes, consequences, solutions, and personal connections to climate change. Teaching anthropogenic climate change through the local context is one of the most effective methods of teaching climate change. In Idaho the lengthening fire season and the increasing occurrence of larger, more severe fires is a tangible impact of climate change. Yet students from Idaho and other high wildfire risk states in the western United …

Robust Digital Nucleic Acid Memory, Golam Md Mortuza

Boise State University Theses and Dissertations

The rapid growth of data generation from electronic devices has created a critical demand for efficient and sustainable data storage solutions. Traditional storage systems face challenges regarding reliability, energy consumption, and scalability, necessitating the exploration of alternative technologies. This dissertation explores the potential of Deoxyribonucleic Acid (DNA) as an alternative storage medium, along with the associated challenges and potential solutions.

This dissertation focuses on Digital Nucleic Acid Memory (dNAM), which utilizes Single Molecule Localization Microscopy (SMLM) to encode and store data within DNA structures called DNA origami. SMLM surpasses the limitations of light’s diffraction limit, enabling the imaging of biological …

Fair Layouts In Information Access Systems: Provider-Side Group Fairness In Ranking Beyond Ranked Lists, Amifa Raj

Boise State University Theses and Dissertations

Information access systems, such as search engines and recommender systems, often display results in ranked order based on their estimated relevance. The fairness of these rankings has received attention as an important evaluation criteria along with traditional metrics capturing constructs such as utility or accuracy. Fairness has many facets, including provider and consumer-side fairness at both group and individual levels. Research on provider-side group fairness involve concerns regarding measurement and optimization of fairness in ranking. Although there are several fair ranking metrics to measure provider-side group fairness based on various “sensitive attributes”, multiple open challenges still exist in this area …

Characteristics Of Stream Source Water Contributions And Associated Geochemical Signatures Along A Climate And Vegetation Gradient In A Glacierized Landscape, Southcentral Alaska, Hannah K. Richardson

Boise State University Theses and Dissertations

Mountain-derived snow and ice melt are essential for global water resources, and over one-sixth of the population depends on melt for freshwater. Rising air temperatures are causing vegetation to replace snow- and ice-covered landscapes and precipitation regimes to change. Collectively, these changes will alter the hydrology of mountain environments, although the exact impacts to hydrologic regimes are poorly understood. The source waters of streamflow (i.e. the proportion of ice melt, snowmelt, rain, and groundwater) dictate the timing and magnitude and affect temperature, sediment, and nutrient fluxes. By examining differences in source waters across basins with varying land covers and precipitation …

Expression And Purification Of Polyketide Synthase Domains To Investigate Protein-Protein Interactions In Polyketide Biosynthetic Pathways, Mujeeb Adeyinka Wakeel

Masters Theses

Polyketide synthases (PKSs) are multienzyme proteins catalyzing the production of the polyketide class of natural products with vast structural diversity. Type II PKSs catalyze polyketide biosynthesis using discrete (standalone) enzymes (domains), while type I PKSs use covalently linked enzymes arranged in a module to catalyze polyketide production. It is hypothesized that type II PKSs are the precursors to type I PKSs, proposing that the genes encoding individual discrete enzymes in type II PKSs fused to give the multienzyme modules of type I PKSs. We reasoned that the intramolecular-like reactions occurring in type I PKS modules might be a driving force …

Redox-Active Polymerization Catalysts And Their Applications, Nicholas M. Shawver

Masters Theses

Traditional catalyst systems are reliable means to produce polymers with well-defined architectures and thermomechanical properties; however, they are often limited by a narrow monomer scope and their ability access few, if any, advanced polymer architectures. To address this limitation, a new class of catalysts have recently emerged that feature redox-active moieties that may access advanced architectures through catalyst electronic modulation that arises from redox events occurring on the ligand scaffold or at the active metal center itself. For example, researchers have explored the ability of redox-active catalysts to impart “on-off” kinetic control during ring-opening polymerizations and their ability to access …

Terrain And Adversary-Aware Autonomous Robot Navigation, Aniekan Ufot Inyang

Electronic Theses and Dissertations

In autonomous robot navigation, the robot is able to understand the environment around it for intelligent navigation. From its world model of this environment, it generates a global plan for navigation from a position to a goal based on different factors. This research aims to implement autonomous robot navigation by learning terrain affordances: traversability (moving quickly) and concealment (staying hidden from an adversary) using the Preference-based Inverse Reward Learning (PbIRL) methodology. The PbIRL methodology reduces the barrier of generating initial demonstration data to learn the terrain affordances by using a human expert’s preferences to learn individual weights over the terrain …

Unilinear Residuated Lattices, Xiao Zhuang

Electronic Theses and Dissertations

We characterize all residuated lattices that have height equal to 3 and show that the variety they generate has continuum-many subvarieties. More generally, we study unilinear residuated lattices: their lattice is a union of disjoint incomparable chains, with bounds added. We give the characterization of all unilinear residuated lattices. By presenting the constructions and axiomatizations for different classes of unilinear residuated lattices, we conclude that the study of unilinear residuated lattices can be reduced to the study of the ⊤-unital ones. Using the classification of unilinear residuated lattices, the idempotent unilinear residuated lattices are studied and amalgamation property and strong …

Synergy And Antagonism In Log-Linear Models, Md Nahid Hasan

UNLV Theses, Dissertations, Professional Papers, and Capstones

Synergy and antagonism have been extensively studied in the context of the statistical analysis of drug combinations given to treat a disease. “Synergy” (“antagonism”, resp.) in a drug combination occurs when the desirable effect of two drugs given together for treating a disease is greater than (less than, resp.) the effect of each drug given separately.

In this dissertation, however, we study “synergy” and “antagonism” in log-linear models. We also give a thorough review and extend several epidemiological definitions of synergy and antagonism for categorical data, and we connect these definitions to the definitions of synergy and antagonism in log-linear …

Development And Characterization Of Lead & Lead-Free Perovskite Solar Cell Materials, Rubaiya Murshed

UNLV Theses, Dissertations, Professional Papers, and Capstones

In recent years, perovskite photovoltaic technology has offered enormous viability and dimensionality in solar cell research. As a light-harvesting active layer, Perovskite generated remarkable development in device efficiency of 25.7% for the single-junction solar cell, and over 33% for the perovskite/silicon tandem solar cell. Also, perovskite-perovskite tandem solar cell (also called all-perovskite tandem solar cell) shows great potential in device performance and achieved a power conversion efficiency (PCE) of 26.4%. Transitioning photovoltaic technology from the laboratory to commercial products, high PCE, low cost, long lifetime, and low toxicity are some of the critical factors to consider during material selection. Pb-halide …

Magmatic Processes Leading To Compositional Diversity In The Mars Crust, Amanda Marie Ostwald

UNLV Theses, Dissertations, Professional Papers, and Capstones

The ancient Mars crust can yield insights into planet formation and evolution that Earth cannot. Direct investigation of the martian surface is limited to studies on meteorites and rover-obtained analyses. The nakhlites and chassignites, two classes of martian meteorites, are together the largest suite of martian meteorites derived from a single location on the surface. As such, they present a rare opportunity to study the Mars crust in detail using samples bearing a contextual relationship. Rover studies have found a surprising amount of compositional diversity in surface materials, the formation mechanisms of which are not well-constrained. This dissertation leverages meteorites …

Benchmarking And Practical Evaluation Of Machine And Statistical Learning Methods In Credit Scoring: A Method Selection Perspective, Gwen Verbeck

UNLV Theses, Dissertations, Professional Papers, and Capstones

Predictive models are important tools used in all scientific fields. Machine learning (ML) algorithms and statistical models are widely used for decision-making because of their capability to tackle intricate and unique problems. In domains where data are high-dimensional and contain irrelevant and redundant features, ML algorithms are known to have superior performance over traditional (statistical) learning methods. However, researchers and analysts are often faced with a myriad of techniques to choose from, with no clear consensus on which will perform best for their specific task. Considering resource limitations, exhaustive exploration of all available methods is impractical and often fails to …

Development Of A Metapgs For Accurate Prediction Of Osteoporotic Fracture, Xiangxue Xiao

UNLV Theses, Dissertations, Professional Papers, and Capstones

Introduction: Early identification of individuals at high-risk for osteoporotic fractures who may benefit from preventive intervention is essential. However, the predictive accuracy of the currently used fracture risk assessment tool remains suboptimal. The first aim of this research is to construct genome-wide polygenic scores for the femoral neck (PGS_FNBMD_idpred) and total body BMD (PGS_TBBMD_idpred) and to estimate their potential in identifying individuals with a high risk of osteoporotic fractures. The second aim is to validate the predictive performance of two previously established PGSs (PGS_FNBMD_idpred and PGS_TBBMD_idpred) in an external cohort …

Lidar Monitoring Of Annual And Storm-Driven Episodic Erosion At Rainsford Island, Alan H. Bartels

Graduate Masters Theses

Boston Harbor and its thirty-four islands are subject to erosion, driven by rain, winds, and waves. Climate change threatens to increase erosion over time as sea levels rise and the frequency and intensity of storms increase. Understanding the dynamics of coastal erosion is key to guiding the design of coastal shoreline protections, the research of which a goal of Stone Living Laboratory at the University of Massachusetts Boston. To better understand the impact of both annual weather and episodic severe storms, the high-resolution Riegl VZ400i LiDAR was deployed four times over 14 months from July 22, 2021 to October 19, …

Corporate Trade War Uncertainty And Patent Bubble, Xu Yang, Nan Hu, Peng Liang

Research Collection School Of Computing and Information Systems

This paper draws upon resource dependence theory and investigates how trade policy uncertainty affects firm strategic innovation management in China. Adopting a machine learning approach called Word2Vec from computational linguistics, we construct and validate a measure of firm-level managers’ perceived trade war uncertainty (TWU). We find that TWU has a positive effect on the number of total patent applications, but this positive effect is totally driven by low-quality patents instead of high-quality patents. Moreover, we document that firms have stronger incentives for such strategic innovation behavior when the underlying firms are more financially constrained, and/or when the management is more …

Two Low-Complexity Efficient Beamformers For An Irs- And Uav-Aided Directional Modulation Network, Yeqing Lin, Feng Shu, Yuxiang Zheng, Jing Liu, Rongen Dong, Xun Chen, Yue Wu, Shihao Yan, Jiangzhou Wang

Research outputs 2022 to 2026

As excellent tools for aiding communication, an intelligent reflecting surface (IRS) and an unmanned aerial vehicle (UAV) can extend the coverage area, remove the blind area, and achieve a dramatic rate improvement. In this paper, we improve the secrecy rate (SR) performance of directional modulation (DM) networks using an IRS and UAV in combination. To fully explore the benefits of the IRS and UAV, two efficient methods are proposed to enhance the SR performance. The first approach computes the confidential message (CM) beamforming vector by maximizing the SR, and the signal-to-leakage-noise ratio (SLNR) method is used to optimize the IRS …

Open Data From The Third Observing Run Of Ligo, Virgo, Kagra, And Geo, R. Abbott, H. Abe, F. Acernese, Teviet Creighton, Mario C. Diaz, Francisco Llamas, Soma Mukherjee, Gaukhar Nurbek, Volker Quetschke, Wenhui Wang

Physics and Astronomy Faculty Publications and Presentations

The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in 2019 April and lasting six months, O3b starting in 2019 November and lasting five months, and O3GK starting in 2020 April and lasting two weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main data set, consisting of the gravitational-wave strain time series …

Ultrasonic Study Of Water Adsorbed In Nanoporous Glasses, Jason Ogbebor, John J. Valenza, Peter I. Ravikovitch, Ashoka Karunarathne, Giovanni Muraro, Maxim Lebedev, Boris Gurevich, Alexei F. Khalizov, Gennady Y. Gor

Research outputs 2022 to 2026

Thermodynamic properties of fluids confined in nanopores differ from those observed in the bulk. To investigate the effect of nanoconfinement on water compressibility, we perform water sorption experiments on two nanoporous glass samples while concomitantly measuring the speed of longitudinal and shear ultrasonic waves in these samples. These measurements yield the longitudinal and shear moduli of the water-laden nanoporous glass as a function of relative humidity that we utilize in the Gassmann theory to infer the bulk modulus of the confined water. This analysis shows that the bulk modulus (inverse of compressibility) of confined water is noticeably higher than that …