Physical Sciences and Mathematics Commons^™

Segment-Wise Time-Varying Dynamic Bayesian Network With Graph Regularization, Xing Yang, Chen Zhang, Baihua Zheng

Research Collection School Of Computing and Information Systems

Time-varying dynamic Bayesian network (TVDBN) is essential for describing time-evolving directed conditional dependence structures in complex multivariate systems. In this article, we construct a TVDBN model, together with a score-based method for its structure learning. The model adopts a vector autoregressive (VAR) model to describe inter-slice and intra-slice relations between variables. By allowing VAR parameters to change segment-wisely over time, the time-varying dynamics of the network structure can be described. Furthermore, considering some external information can provide additional similarity information of variables. Graph Laplacian is further imposed to regularize similar nodes to have similar network structures. The regularized maximum a …

Pickup And Multi-Delivery Problem With Time Windows, Pham Tuan Anh, Aldy Gunawan, Vincent F. Yu, Tuan C. Chau

Research Collection School Of Computing and Information Systems

This paper addresses a new variant of Pickup and Delivery Problem with Time Windows (PDPTW) for enhancing customer satisfaction. In particular, a huge number of requests is served in the system, where each request includes a pickup node and several delivery nodes instead of a pair of pickup and delivery nodes. It is named Pickup and Multi-Delivery Problem with Time Windows (PMDPTW). A mixed-integer programming model is formulated with the objective of minimizing total travel costs. Computational experiments are conducted to test the correctness of the model with a newly generated benchmark based on the PDPTW benchmark instances. Results show …

Conversation Disentanglement With Bi-Level Contrastive Learning, Chengyu Huang, Zheng Zhang, Hao Fei, Lizi Liao

Research Collection School Of Computing and Information Systems

Conversation disentanglement aims to group utterances into detached sessions, which is a fundamental task in processing multi-party conversations. Existing methods have two main drawbacks. First, they overemphasize pairwise utterance relations but pay inadequate attention to the utterance-to-context relation modeling. Second, a huge amount of human annotated data is required for training, which is expensive to obtain in practice. To address these issues, we propose a general disentangle model based on bi-level contrastive learning. It brings closer utterances in the same session while encourages each utterance to be near its clustered session prototypes in the representation space. Unlike existing approaches, our …

Authentic Assessments For Digital Education: Learning Technologies Shaping Assessment Practices, Tristan Lim, Swapna Gottipati, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

Assessment is a powerful lever that affects learning. To better inform educators on authentic assessment practices within digital education in the higher education landscape, this paper takes us through a meta-analysis of existing literature between 2011 to 2021. The study evaluates the following research question: “How are emerging technologies shaping authentic assessment practices within digital education for higher education for the period between 2011 and 2023”. To aid with the forecasting, we utilize the EDUCAUSE Horizon Reports, which provide the predictions of emerging technology. This study affirms the importance of immersive learning technologies, followed by ubiquitous and adaptive learning technologies …

What Should Streamers Communicate In Livestream E-Commerce? The Effects Of Social Interactions On Live Streaming Performance, Danyang Song, Xi Chen, Zhiling Guo, Xiao Liu Liu, Ruijin. Jin

Research Collection School Of Computing and Information Systems

Compared with traditional e-commerce, livestreaming e-commerce is characterized by direct and intimate communication between streamers and consumers that stimulates instant social interactions. This study focuses on streamers’ three types of information exchange (i.e., product information, social conversation, and social solicitation) and examines their roles in driving both short-term and long-term livestreaming performance (i.e., sales and customer base growth). We find that the informational role of product information (nonpromotional and promotional) is beneficial not only to sales performance, but also to the growth of the customer base. We also find that social conversation has a relationship-building effect that positively impacts both …

Bank Error In Whose Favor? A Case Study Of Decentralized Finance Misgovernance, Ping Fan Ke, Ka Chung Boris Ng

Research Collection School Of Computing and Information Systems

Decentralized Finance (DeFi) emerged rapidly in recent years and provided open and transparent financial services to the public. Due to its popularity, it is not uncommon to see cybersecurity incidents in the DeFi landscape, yet the impact of such incidents is under-studied. In this paper, we examine two incidents in DeFi protocol that are mainly caused by misgovernance and mistake in the smart contract. By using the synthetic control method, we found that the incident in Alchemix did not have a significant effect on the total value locked (TVL) in the protocol, whereas the incident in Compound caused a 6.13% …

Mining Competitively-Priced Bundle Configurations, Ezekiel Ong Young, Hady W. Lauw

Research Collection School Of Computing and Information Systems

We examine the bundle configuration problem in the presence of competition. Given a competitor's bundle configuration and pricing, we determine what to bundle together, and at what prices, to maximize the target firm's revenue. We highlight the difficulty in pricing bundles and propose a scalable alternative and an efficient search heuristic to refine the approximate prices. Furthermore, we extend the heuristics proposed by previous work to accommodate the presence of a competitor. We analyze the effectiveness of our proposed models through experimentation on real-life ratings-based preference data.

Singlish Checker: A Tool For Understanding And Analysing An English Creole Language, Lee-Hsun Hsieh, Nam Chew Chua, Agus Trisnajaya Kwee, Pei-Chi Lo, Yang-Yin Lee, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

As English is a widely used language in many countries of different cultures, variants of English also known as English creoles have also been created. Singlish is one such English creole used by people in Singapore. Nevertheless, unlike English, Singlish is not taught in schools nor encouraged to be used in formal communications. Hence, it remains to be a low resource language with a lack of up-to-date Singlish word dictionary and computational tools to analyse the language. In this paper, we therefore propose Singlish Checker, a tool that is able to help detecting Singlish text, Singlish words and phrases. To …

Quote: Quality-Oriented Testing For Deep Learning Systems, Jialuo Chen, Jingyi Wang, Xingjun Ma, Youcheng Sun, Jun Sun, Peixin Zhang, Peng Cheng

Research Collection School Of Computing and Information Systems

Recently, there has been a significant growth of interest in applying software engineering techniques for the quality assurance of deep learning (DL) systems. One popular direction is deep learning testing, i.e., given a property of test, defects of DL systems are found either by fuzzing or guided search with the help of certain testing metrics. However, recent studies have revealed that the neuron coverage metrics, commonly used by most existing DL testing approaches, are not necessarily correlated with model quality (e.g., robustness, the most studied model property), and are also not an effective measurement on the confidence of the model …

On The Robustness Of Diffusion In A Network Under Node Attacks, Alvis Logins, Yuchen Li, Panagiotis Karras

Research Collection School Of Computing and Information Systems

How can we assess a network's ability to maintain its functionality under attacks Network robustness has been studied extensively in the case of deterministic networks. However, applications such as online information diffusion and the behavior of networked public raise a question of robustness in probabilistic networks. We propose three novel robustness measures for networks hosting a diffusion under the Independent Cascade or Linear Threshold model, susceptible to attacks by an adversarial attacker who disables nodes. The outcome of such a process depends on the selection of its initiators, or seeds, by the seeder, as well as on two factors outside …

Characterization Of Losses In Superconducting Radio-Frequency Cavities By Combined Temperature And Magnetic Field Mapping, Ishwari Prasad Parajuli

Physics Theses & Dissertations

Superconducting radio-frequency (SRF) cavities are one of the fundamental building blocks of modern particle accelerators. To achieve the highest quality factors (10¹⁰-10¹¹), SRF cavities are operated at liquid helium temperatures. Magnetic flux trapped on the surface of SRF cavities during cool-down below the critical temperature is one of the leading sources of residual RF losses. Instruments capable of detecting the distribution of trapped flux on the cavity surface are in high demand in order to better understand its relation to the cavity material, surface treatments and environmental conditions. We have designed, developed, and commissioned two novel …

Towards Privacy And Security Concerns Of Adversarial Examples In Deep Hashing Image Retrieval, Yanru Xiao

Computer Science Theses & Dissertations

With the explosive growth of images on the internet, image retrieval based on deep hashing attracts spotlights from both research and industry communities. Empowered by deep neural networks (DNNs), deep hashing enables fast and accurate image retrieval on large-scale data. However, inheriting from deep learning, deep hashing remains vulnerable to specifically designed input, called adversarial examples. By adding imperceptible perturbations on inputs, adversarial examples fool DNNs to make wrong decisions. The existence of adversarial examples not only raises security concerns for real-world deep learning applications, but also provides us with a technique to confront malicious applications.

In this dissertation, we …

Machine Learning-Based Event Generator, Yasir Alanazi

Computer Science Theses & Dissertations

Monte Carlo-based event generators have been the primary source for simulating particle collision experiments for the study of interesting physics scenarios. Monte Carlo generators rely on theoretical assumptions, which limit their ability to capture the full range of possible correlations between particle’s momenta. In addition, the simulations of the complete pipeline often take minutes to generate a single event even with the help of supercomputers.

In recent years, much attention has been devoted to the development of machine learning event generators. They demonstrate attractive advantages, including fast simulations, data compression, and being agnostic of theoretical assumptions. However, most of the …

Investigation Of Gaas Double Heterostructures For Photonic Heat Engines, Nathan Giannini-Hutchin

Optical Science and Engineering ETDs

The creation of a laser cooled semiconductor device has been a long sought achievement. GaAs-based devices have emerged as a promising candidate for the realization of this goal. Efforts to improve the efficiency of such devices have enabled the material to exhibit external quantum efficiencies (EQE, a measure of the probability that an excitation leads to the emission of a photon) of 99.5\%. Despite this impressive feat, a laser coolable device remains elusive.

To investigate the obstacles to such a device, the material characteristics of GaAs-based double heterostructures (DHS) are theoretically and experimentally examined. Through this study, a GaAs $\vert$ …

Smartphone Usage Before And During Covid-19: A Comparative Study Based On Objective Recording Of Usage Data, Khansa Chemnad, Sameha Alshakhsi, Mohamed Basel Almourad, Majid Altuwairiqi, Keith Phalp, Raian Ali

All Works

Most studies that claimed changes in smartphone usage during COVID-19 were based on self-reported usage data, e.g., that collected through a questionnaire. These studies were also limited to reporting the overall smartphone usage, with no detailed investigation of distinct types of apps. The current study investigated smartphone usage before and during COVID-19. Our study used a dataset from a smartphone app that objectively logged users’ activities, including apps accessed and each app session start and end time. These were collected during two periods: pre-COVID-19 (161 individuals with 77 females) and during COVID-19 (251 individuals with 159 females). We report on …

Internal Waves Of Port Everglades: Experimental And Numerical Studies To Characterize Ambient Magnetic Signals, Johanna Riley Evans

Theses and Dissertations

Ocean dynamics are an important contributing factor to measurable environmental magnetic noise. Seawater is conductive and as an internal wave oscillates across Earth’s magnetic field, a small yet detectable induced magnetic field develops. A significant source of underwater magnetic noise off the southeast coast of Florida comes from internal waves. Characterizing the magnetic signals present required a combination of computational modeling effort and field experiments. For this research, undersea sensors were monitored as a continuous field experiment and a computational fluid dynamic (CFD) magneto-hydrodynamic (MHD) model was customized to simulate internal wave-induced magnetic fields at the site. I developed the …

Unified Model Of Lightning & Electrostatic Discharges Across The Solar System, Annelisa Blackwell Esparza

Theses and Dissertations

As we increase the number of probes on other objects within our solar system, it becomes all the timelier to understand the physics of electrostatic discharges (ESDs). Since these probes will have sensitive instruments on-board, we will need to apply our existing knowledge of ESDs to extraterrestrial environments to protect these investments from deterioration. On Earth, even small-scale ESDs can permanently destroy critical components within electronics, while large-scale ESDs (e.g., lightning strikes) are capable of debilitating entire power grids. The characteristic timescale of an ESD is small compared to the timescales of cloud charging and storm evolution. This lets us …

Fractional Sobolev Embedding With Radial Potential, Yu Su, Zhaosheng Feng

School of Mathematical & Statistical Sciences Faculty Publications

We present some embedding results of fractional Ds,2(RN) space with radial potential. To overcome the difficulty of non-compactness, we obtain the Lions-type theorems by means of the refined Sobolev inequality with the Morrey norm. Then we apply the obtained results to study the existence of ground state solution for fractional equations with radial potential.

Estimating Sewage Flow Rate In Jefferson County, Kentucky, Using Machine Learning For Wastewater-Based Epidemiology Applications., Dhiraj Kanneganti, Lauren E. Reinersman, Rochelle H. Holm, Ted Smith

Faculty and Staff Scholarship

Direct measurement of the flow rate in sanitary sewer lines is not always feasible and is an important parameter for the normalization of data used in wastewater-based epidemiology applications. Machine learning to estimate past wastewater influent flow rates supporting public health applications has not been studied. The aim of this study was to assess wastewater treatment plant influent flow rates when compared with weather data and to retrospectively estimate flow rates in Louisville, Kentucky (USA), based on other data types using machine learning. A random forest model was trained using a range of variables, such as feces-related indicators, weather data …

Design Of Ethical Autonomous Agents For Unmanned Aerial Vehicles Using Fuzzy Logic, Gavin Giovanni Smith

Theses and Dissertations

Autonomous systems have, over the years become part of our everyday lives. These systems have been deployed to executed a diverse range of applications in different industries; finance, healthcare, military, and in particular, the flight industry. With the rise of UAVs, new opportunities arose, but with those opportunities came new pitfalls within any industry. For UAVs, one of the pitfalls came in the form of ethical decisionmaking, which led to a variety of questions. Can the Autonomous systems within UAVs be designed with ethics in mind? Which ethical guidelines would we use to implement such a system? How would we …

Using Landsat Satellite Imagery To Estimate Groundcover In The Grainbelt Of Western Australia, Justin Laycock, Nick Middleton, Karen Holmes

Resource management technical reports

Maintaining vegetative groundcover is an important component of sustainable agricultural systems and plays a critical function for soil and land conservation in Western Australia’s (WA) grainbelt (the south-west cropping region). This report describes how satellite imagery can be used to quantitatively and objectively estimate total vegetative groundcover, both in near real time and historically across large areas. We used the Landsat seasonal fractional groundcover products developed by the Joint Remote Sensing Research Program from the extensive archive of Landsat imagery. These products provide an estimate of the percentage of green vegetation, non-green vegetation and bare soil for each 30 m …

Groundwater Modelling Of The Newman Area For Managed Aquifer Recharge Assessment, Wolfgang Schmid, Rodrigo Rojas, Michael J. Donn, Christopher Schelfhout Dr, Mathias Raiber, Olga Barron

Natural resources commissioned reports

This report contributes to the Transforming Agriculture in the Pilbara (TAP) initiative that has been developed to undertake the detailed studies in the Pilbara to bring suitable medium to large scale irrigation land to market for private investment. The research objective was to explore opportunities for irrigated agriculture north of Newman (Eastern Pilbara), deploying managed aquifer recharge (MAR) to secure water for irrigation. MAR source water identified was from mine dewatering surplus, generated from the large BHP Iron Ore operation in the Newman region. The objectives of this report were to:

• conceptualise the groundwater system and associated processes in the …

Region Detection & Segmentation Of Nissl-Stained Rat Brain Tissue, Alexandro Arnal

Open Access Theses & Dissertations

People who analyze images of biological tissue rely on the segmentation of structures as a preliminary step. In particular, laboratories studying the rat brain delineate brain regions to position scientific findings on a brain atlas to propose hypotheses about the rat brain and, ultimately, the human brain. Our work intersects with the preliminary step of delineating regions in images of brain tissue via computational methods.

We investigate pixel-wise classification or segmentation of brain regions using ten histological images of brain tissue sections stained for Nissl substance. We present a deep learning approach that uses the fully convolutional neural network, U-Net, …

Glacier Segmentation From Remote Sensing Imagery Using Deep Learning, Bibek Aryal

Open Access Theses & Dissertations

Large-scale study of glaciers improves our understanding of global glacier change and is imperative for monitoring the ecological environment, preventing disasters, and studying the effects of global climate change. In recent years, remote sensing imagery has been preferred over riskier and resource-intensive field visits for tracking landscape level changes like glaciers. However, periodic manual labeling of glaciers over a large area is not feasible due to the considerable amount of time it requires while automatic segmentation of glaciers has its own set of challenges. Our work aims to study the challenges associated with segmentation of glaciers from remote sensing imagery …

Reprocessing Groundwater Resistivity Surveys In The Lower Mesilla Basin, New Mexico, And Texas, Leslie Bernal

Open Access Theses & Dissertations

The Mesilla Basin is part of the Rio Grande Basin System. Its northern boundary is definedby the Doña Ana Mountains in New Mexico and to the south by Sierra San Blas, Sierra Almirez, and Sierra La Candelaria in Mexico, where the basin changes its name to Conejos-Médanos. It supplies water for irrigation and public use to the cities of Las Cruces, NM, El Paso, TX, and Ciudad Juárez, Mexico. The southern part of the basin in the U.S. territory, known as the Lower Mesilla Basin, is bounded to the east by the Franklin Mountains, to the west by the Potrillo …

Achieving Safe Use Of Advanced Materials In Drinking Water Through Novel Nano Analytics And Enabling Electrification Using Green Catalyst, Kenneth Ray Flores

Open Access Theses & Dissertations

The accumulation of engineered nanomaterials (ENMs) in environmental sectors will continue to increase as more applications are discovered for their unique properties and characteristics. Additionally, the presence of nanomaterials in the environment becomes exacerbated as more consumer products containing nanoparticles are approved for use. It is debated whether the toxic effects of nanoparticles stem from the particles themselves, ionic species, or formation of secondary particles. Therefore, understanding the behavior of nanoparticles in the environment becomes key to discerning the toxicological effects of nanoparticles. Many advancements have been made with ICP-MS to understand the behavior of nanoparticles in the environmental systems, …

Nano-Engineered Soft Magnets: Potential Application In Water Treatment, Hyperthermia And Molecular (Organic) Magnets, Yohannes Weldemariam Getahun

Open Access Theses & Dissertations

Scrutinizing the remarkable and tunable properties of magnetic materials at a nanoscale size "There's Plenty of Room at the Bottom..." Richard Feynman, this study attempts to find sustainable solutions to some of the deteriorating environmental, health, and energy problems the world is encountering. Due to their simple preparation, surface adaptability, and tunable magnetic and optical properties, magnetic nanoparticles have been extensively investigated in water treatment, cancer therapy, data storage, and more. However, relying on non-reusable and chemical-based treatment agents in water, complex and costly cancer treatment procedures and molecular magnets that operate far below room temperature limited those attempts from …

Molecularly Inspired Organic Macrocycles Catalyzed Water Splitting Reaction For Sustainable Fuel Production, Yulu Ge

Open Access Theses & Dissertations

Hydrogen fuel generation through electrochemical water splitting is considered as an advanced energy conversion technology driven by sustainable energy. High activity and cost effective electrocatalysts that are able to drive down the energy cost needed for both two half reactions, namely, hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) are required to fulfill the energy transfer process. Exploring new electrocatalysts with enhanced OER and HER activity and stability is crucial for renewable energy applications. Porphyrin and macrocycle derivatives are versatile and can electrochemically catalyze water splitting efficiently. In our work, we use porphyrin as platform for both HER and …

Evaluation Of Effect Of Preprocessing Algorithms On Resting State Fmri Data, Hortencia Josefina Hernandez

Open Access Theses & Dissertations

Graph theory modeling is a common modeling approach in neurobiology research studies. These models are useful since they describe patterns of connection for regions of interest in the brain using resting state fMRI images. The standard rule of thumb is to threshold the observed activation levels prior to model building. It is reasonable to assume that the use of this threshold affects the statistical distribution of commonly reported centrality metrics from the graph theory model, such as degree, betweenness, and closeness. In this study we examine the differential effect of using the standard approaches versus alternative direct thresholds and incorporation …

The Qualification Of Sealability And Creep Relaxation Of Additively Manufactured Zytel Gaskets For Pem Fuel Cells, Robert Lazarin

Open Access Theses & Dissertations

The purpose of this thesis is to study the feasibility of low-cost additive manufacturing of gaskets for proton exchange membrane fuel cells exposed to extreme temperature conditions ranging from -55°C to 100°C. With the growing popularity and decreasing costs of additive manufacturing technologies, specifically Material Extrusion (ME), research is being conducted to determine the feasibility of ME components. Thermally cycled PEMFCs may exhibit accelerated gasket deterioration, therefore, the mechanical stability of material extruded gaskets following a harsh thermal cycle must be assessed. The feasibility of the material extruded gaskets will be proven by manufacturing optimization and mechanical testing. The target …