Physical Sciences and Mathematics Commons^™

Dsdnet: Toward Single Image Deraining With Self-Paced Curricular Dual Stimulations, Yong Du, Junjie Deng, Yulong Zheng, Junyu Dong, Shengfeng He

Research Collection School Of Computing and Information Systems

A crucial challenge regarding the single image deraining task is to completely remove rain streaks while still preserving explicit image details. Due to the inherent overlapping between rain streaks and background scenes, the texture details could be inevitably lost when clearing rain away from the degraded image, making the two purposes contradictory. Existing deep learning based approaches endeavor to resolve the two issues successively in a cascaded framework or to treat them as independent tasks in a parallel structure. However, none of the models explores a proper interaction between rain distributions and hidden feature responses, which intuitively would provide more …

Mimusa: Mimicking Human Language Understanding For Fine-Grained Multi-Class Sentiment Analysis, Zhaoxia Wang, Zhenda Hu, Seng-Beng Ho, Erik Cambria, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Sentiment analysis is an important natural language processing (NLP) task due to a wide range of applications. Most existing sentiment analysis techniques are limited to the analysis carried out at the aggregate level, merely providing negative, neutral and positive sentiments. The latest deep learning-based methods have been leveraged to provide more than three sentiment classes. However, such learning-based methods are still black-box-based methods rather than explainable language processing methods. To address this gap, this paper proposes a new explainable fine-grained multi-class sentiment analysis method, namely MiMuSA, which mimics the human language understanding processes. The proposed method involves a multi-level modular …

Rntrajrec: Road Network Enhanced Trajectory Recovery With Spatial-Temporal Trans-Former, Yuqi Chen, Hanyuan Zhang, Weiwei Sun, Baihua Zheng

Research Collection School Of Computing and Information Systems

GPS trajectories are the essential foundations for many trajectory-based applications. Most applications require a large number of high sample rate trajectories to achieve a good performance. However, many real-life trajectories are collected with low sample rate due to energy concern or other constraints. We study the task of trajectory recovery in this paper as a means to increase the sample rate of low sample trajectories. Most existing works on trajectory recovery follow a sequence-to-sequence diagram, with an encoder to encode a trajectory and a decoder to recover real GPS points in the trajectory. However, these works ignore the topology of …

Exploring New Techniques For Precision Deuteration Of Alkenes And Alkynes, Zoua Pa Vang

Dissertations (1934 -)

Deuterium labeled compounds are often utilized in chemical research as internal standards in mass spectrometry, to study reaction mechanisms and in the pharmaceutical industry to slow the rate of metabolism. With the increase interest for deuterium labeled molecules, there is a renewed interest in selective methods for the installation of deuterium atoms into small organic molecules. However, current methods to incorporate deuterium atoms into organic molecules can lead to isotopic mixtures such as isotopologues and isotopomers. These isotopic species are indistinguishable due to their similar physical properties, leading to inseparable products by common purification techniques. Furthermore, common spectroscopic techniques to …

Informational Content Of Factor Structures In Simultaneous Discrete Response Models, Shakeeb Khan, Arnaud Maurel, Yichong Zhang

Research Collection School Of Economics

We study the informational content of factor structures in discrete triangular systems. Factor structures have been employed in a variety of settings in cross sectional and panel data models, and in this paper we attempt to formally quantify their informational content in a bivariate system often employed in the treatment effects literature. Our main findings are that under the factor structures often imposed in the literature, point identification of parameters of interest, such as both the treatment effect and the factor load, is attainable under weaker assumptions than usually required in these systems. For example, we show is that an …

Parsing-Conditioned Anime Translation: A New Dataset And Method, Zhansheng Li, Yangyang Xu, Nanxuan Zhao, Yang Zhou, Yongtuo Liu, Dahua Lin, Shengfeng He

Research Collection School Of Computing and Information Systems

Anime is an abstract art form that is substantially different from the human portrait, leading to a challenging misaligned image translation problem that is beyond the capability of existing methods. This can be boiled down to a highly ambiguous unconstrained translation between two domains. To this end, we design a new anime translation framework by deriving the prior knowledge of a pre-Trained StyleGAN model. We introduce disentangled encoders to separately embed structure and appearance information into the same latent code, governed by four tailored losses. Moreover, we develop a FaceBank aggregation method that leverages the generated data of the StyleGAN, …

Nftdisk: Visual Detection Of Wash Trading In Nft Markets, Xiaolin Wen, Yong Wang, Xuanwu Yue, Feida Zhu, Min Zhu

Research Collection School Of Computing and Information Systems

With the growing popularity of Non-Fungible Tokens (NFT), a new type of digital assets, various fraudulent activities have appeared in NFT markets. Among them, wash trading has become one of the most common frauds in NFT markets, which attempts to mislead investors by creating fake trading volumes. Due to the sophisticated patterns of wash trading, only a subset of them can be detected by automatic algorithms, and manual inspection is usually required. We propose NFTDisk, a novel visualization for investors to identify wash trading activities in NFT markets, where two linked visualization modules are presented: a radial visualization module with …

Bubbleu: Exploring Augmented Reality Game Design With Uncertain Ai-Based Interaction, Minji Kim, Kyungjin Lee, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

Object detection, while being an attractive interaction method for Augmented Reality (AR), is fundamentally error-prone due to the probabilistic nature of the underlying AI models, resulting in sub-optimal user experiences. In this paper, we explore the effect of three game design concepts, Ambiguity, Transparency, and Controllability, to provide better gameplay experiences in AR games that use error-prone object detection-based interaction modalities. First, we developed a base AR pet breeding game, called Bubbleu that uses object detection as a key interaction method. We then implemented three different variants, each according to the three concepts, to investigate the impact of each design …

Does Deep Learning Improve The Performance Of Duplicate Bug Report Detection? An Empirical Study, Yuan Jiang, Xiaohong Su, Christoph Treude, Chao Shang, Tiantian Wang

Research Collection School Of Computing and Information Systems

Do Deep Learning (DL) techniques actually help to improve the performance of duplicate bug report detection? Prior studies suggest that they do, if the duplicate bug report detection task is treated as a binary classification problem. However, in realistic scenarios, the task is often viewed as a ranking problem, which predicts potential duplicate bug reports by ranking based on similarities with existing historical bug reports. There is little empirical evidence to support that DL can be effectively applied to detect duplicate bug reports in the ranking scenario. Therefore, in this paper, we investigate whether well-known DL-based methods outperform classic information …

Giving Back: Contributions Congruent To Library Dependency Changes In A Software Ecosystem, Supatsara Wattanakriengkrai, Dong Wang, Raula Gaikovina Kula, Christoph Treude, Patanamon Thongtanunam, Takashi Ishio, Kenichi Matsumoto

Research Collection School Of Computing and Information Systems

The widespread adoption of third-party libraries for contemporary software development has led to the creation of large inter-dependency networks, where sustainability issues of a single library can have widespread network effects. Maintainers of these libraries are often overworked, relying on the contributions of volunteers to sustain these libraries. To understand these contributions, in this work, we leverage socio-technical techniques to introduce and formalise dependency-contribution congruence (DC congruence) at both ecosystem and library level, i.e., to understand the degree and origins of contributions congruent to dependency changes, analyze whether they contribute to library dormancy (i.e., a lack of activity), and investigate …

A Learner-Verifier Framework For Neural Network Controllers And Certificates Of Stochastic Systems, Krishnendu Chatterjee, Thomas A. Henzinger, Dorde Zikelic, Dorde Zikelic

Research Collection School Of Computing and Information Systems

Reinforcement learning has received much attention for learning controllers of deterministic systems. We consider a learner-verifer framework for stochastic control systems and survey recent methods that formally guarantee a conjunction of reachability and safety properties. Given a property and a lower bound on the probability of the property being satisfied, our framework jointly learns a control policy and a formal certificate to ensure the satisfaction of the property with a desired probability threshold. Both the control policy and the formal certificate are continuous functions from states to reals, which are learned as parameterized neural networks. While in the deterministic case, …

Code Will Tell: Visual Identification Of Ponzi Schemes On Ethereum, Xiaolin Wen, Kim Siang Yeo, Yong Wang, Ling Cheng, Feida Zhu, Min Zhu

Research Collection School Of Computing and Information Systems

Ethereum has become a popular blockchain with smart contracts for investors nowadays. Due to the decentralization and anonymity of Ethereum, Ponzi schemes have been easily deployed and caused significant losses to investors. However, there are still no explainable and effective methods to help investors easily identify Ponzi schemes and validate whether a smart contract is actually a Ponzi scheme. To fill the research gap, we propose PonziLens, a novel visualization approach to help investors achieve early identification of Ponzi schemes by investigating the operation codes of smart contracts. Specifically, we conduct symbolic execution of opcode and extract the control flow …

Climate Services: The Business Of Physical Risk, Madison Condon

Faculty Scholarship

A growing number of investors, insurers, financial services providers, and nonprofits rely on information about localized physical climate risks, like floods, hurricanes, and wildfires. The outcomes of these risk projections have significant consequences in the economy, including allocating investment capital, impacting housing prices and demographic shifts, and prioritizing adaptation infrastructure projects. The climate risk information available to individual citizens and municipalities, however, is limited and expensive to access. Further, many providers of climate services use black box models that make overseeing the scientific rigor of their methodologies impossible— a concern given scientific critiques that many may be obfuscating the uncertainty …

The Importance Of Accessible Government Data In Advancing Environmental Justice, Frank D. Lomonte, Daniel Delgado

William & Mary Environmental Law and Policy Review

Part I of this Article sets forth the history and animating principles of the environmental justice movement in the United States during the 1970s, which developed as an adjunct to the larger civil rights movement. Part II then turns to the role of documents and data in exposing where toxins present a risk to public health and where documentation habitually falls short. It discusses how freedom of information laws can unlock access to the documents and data that quantify environmental hazards but also how those laws fail to produce reliable results because of the influence of regulated industries. Part III …

Evaluating Species-Specific Replenishment Solution Effects On Plant Growth And Root Zone Nutrients With Hydroponic Arugula (Eruca Sativa L.) And Basil (Ocimum Basilicum L.), Lauren L. Houston, Ryan W. Dickson, Matthew B. Bertucci, Trenton L. Roberts

Horticulture Faculty Publications and Presentations

Managing nutrients in recirculating solutions can be challenging in hydroponic production, and poor management practices can rapidly result in root zone nutrient imbalances in reduced yield. Using mass balance principles to formulate hydroponic replenishment solutions is a proposed strategy to reduce nutrient imbalances and the need to periodically replace the hydroponic solution. Objectives were to (1) formulate species-specific nutrient replenishment solutions for arugula (Eruca sativa L.) and basil (Ocimum basilicum L.) using mass balance principles and (2) evaluate the effects of using these replenishment solutions on plant growth and root zone nutrients over time. In the first experiment, …

Lax Integrability And Solution Methods For The Nonlinear Schrödinger Equation With External Potentials: Exact Solutions And Applications, Laila Yahya Al Sakkaf

Dissertations

The investigation of a nonlinear differential equation (NLDE) integrability is the foundation for understanding and predicting the behavior of systems that are governed by that NLDE. The existence of a Lax pair (LP) representation is a reliable indicator of the indicator of the integrability of an NLDE. If an NLDE admits an LP, it is considered integrable in the LP sense, and this has important implications for the behavior and solutions of the system. The LP plays a crucial role in many powerful analytical solution methods for solving NLDEs. One such method is the Darboux transformation (DT), which allows for …

Exploring Post-Quantum Cryptographic Schemes For Tls In 5g Nb-Iot: Feasibility And Recommendations, Kadir Sabanci

Master's Theses (2009 -)

Narrowband Internet of Things (NB-IoT) is a wireless communication technology that enables a wide range of applications, from smart cities to industrial automation. As a part of the 5G extension, NB-IoT promises to connect billions of devices with low-power and low-cost requirements. However, with the advent of quantum computers, the incoming NB-IoT era is already under threat due to conventional cryptographic algorithms that might be adapted to secure devices in NB-IoT being susceptible to be broken soon. In this context, we investigate the feasibility of using post-quantum key exchange and signature algorithms for securing NB-IoT applications. We develop a realistic …

Open-Set Domain Adaptation By Deconfounding Domain Gaps, Xin Zhao, Shengsheng Wang, Qianru Sun

Research Collection School Of Computing and Information Systems

Open-Set Domain Adaptation (OSDA) aims to adapt the model trained on a source domain to the recognition tasks in a target domain while shielding any distractions caused by open-set classes, i.e., the classes “unknown” to the source model. Compared to standard DA, the key of OSDA lies in the separation between known and unknown classes. Existing OSDA methods often fail the separation because of overlooking the confounders (i.e., the domain gaps), which means their recognition of “unknown classes” is not because of class semantics but domain difference (e.g., styles and contexts). We address this issue by explicitly deconfounding domain gaps …

High-Dimensional Variable Selection Via Knockoffs Using Gradient Boosting, Amr Essam Mohamed

Dissertations

As data continue to grow rapidly in size and complexity, efficient and effective statistical methods are needed to detect the important variables/features. Variable selection is one of the most crucial problems in statistical applications. This problem arises when one wants to model the relationship between the response and the predictors. The goal is to reduce the number of variables to a minimal set of explanatory variables that are truly associated with the response of interest to improve the model accuracy. Effectively choosing the true influential variables and controlling the False Discovery Rate (FDR) without sacrificing power has been a challenge …

Socially Aware Natural Language Processing With Commonsense Reasoning And Fairness In Intelligent Systems, Sirwe Saeedi

Dissertations

Although Artificial Intelligence (AI) promises to deliver ever more user-friendly consumer applications, recent mishaps involving fake information and biased treatment serve as vivid reminders of the pitfalls of AI. AI can harbor latent biases and flaws that can cause harm in diverse and unexpected ways. It is crucial to understand the reasons for, mechanisms behind, and circumstances under which AI can fail. For instance, a lack of commonsense reasoning can lead to biased or unfair decisions made by Machine Learning (ML) systems. For example, if an ML system is trained on data that is biased or unrepresentative of the real …

Semantics-Based Data Security Models, Theppatorn Rhujittawiwat

Theses and Dissertations

In this dissertation, we studied how an adversary could attack databases and how the system could prevent or recover from such an attack. Our motivation to improve the current security capabilities of database management systems. We provided better recovery capabilities of database management systems by incorporating data provenance. We also expand our study to express security and privacy needs of data in the Internet of Things (IoT) environments such as a smart home environment. For this, we proposed a stream data security model to theoretically represent the data in the IoT network. We built a dynamic authorization model on our …

Bayesian Dependence Structure Analysis For Ordinal Data, Yang He

Theses and Dissertations

This dissertation explores different methods to study the dependence structure among many ordinal variables under the Bayesian framework.

Chapter 1 introduces ordinal data analysis methods, and the related literature works are briefly reviewed. An outline of the dissertation is put forward.

In Chapter 2, Gaussian copula graphical models with different priors of graphical Lasso, adaptive graphical Lasso, and spike-and-slab Lasso on the precision matrix are assessed and compared. The proposed models are well illustrated via simulations and a real ordinal survey data analysis.

In Chapter 3, adaptive spike-and-slab Lasso prior is proposed as an extension of Chapter 2. The developed …

Expanding Tailorable Nanomaterial Synthesis With Persistent Micelle Templates, Eric R. Williams

Theses and Dissertations

The control of block polymer micelle dimensions while in solution is critical for a range of emerging applications in diverse fields from drug delivery and nanoreactors to use as sacrificial templates for porous nanomaterials. When under kinetic control, micelles will maintain a constant average size and thus aggregation number (N_agg) through the suppression of chain exchange mechanisms. Such kinetic control effectively enables the decoupling of micelle dimensions from solution conditions. In other words, kinetically trapped micelles can resist reorganizations brough about by e.g., the addition of metal nanoparticles. However, such micelles are traditionally governed by a fickle �� …

Neoliberalismo Y La Mar: Los Efectos Del Sistema Neoliberal Y La Pesca Artesanal De Caleta Portales, Isaac Bronfine

Independent Study Project (ISP) Collection

This study is meant to explore the fundamental conflict between the neoliberal system implemented in Chilean society and the artisanal fishing sector, represented by Caleta Diego Portales in Valparaíso, Chile. The struggle of the artisanal fishing sector has been made more salient in the minds of the general Chilean public due to the estallido social or “social explosion” in 2019 which lead to a process of drafting a new constitution, and the recent corruption scandals regarding government officials and fishing law reforms.

Beginning with how neoliberal theory gained traction in intellectual spaces around the world, this study then examines how …

Coastal Morphology And Sediment Deposition On Adjacent Coral Reefs At Misali Island, Sophia Rosati

Independent Study Project (ISP) Collection

Terrestrial and marine ecosystems are frequently interpreted under separate lenses. On a 1 km wide island, however, these two sciences are inextricably tied. Misali Island, a small coralline island in the Indian Ocean, has been largely uninhabited for its entire history, making this coastal interface unique. In this study, Misali Island is used as a study region to demonstrate how natural processes are materializing in the Zanzibar Archipelago. Methods employed, both geological and marine, work to understand the erosional circumstances of Baobab Beach and the inherent effects on local coral reefs. Results show that Misali’s northeastern beachfront is currently under …

Accurately Valuing Blue Carbon Sequestration And Storage To Foster Coastal Conservation Via Evidence-Based Policymaking And Model Environmental Services Statute Methodologies, John Shelton Penton Jr

LSU Doctoral Dissertations

Blue carbon ecosystems, especially mangrove forests, provide one of nature’s most effective means for sequestering carbon from the atmosphere and storing it in subsurface soils. The six nearshore coastal morphologies found in tropical and subtropical regions each possess a conspicuous environmental signature that can be employed to accurately estimate and predict mangrove forests’ carbon storage in above-ground biomass, below-ground biomass, and the soils by system type. The consistent geomorphology and geophysical processes within each of these coastal environmental settings, that is, the wave and tidal forcings, the rate of coastal sediment accretions, nutrient load and limitations (e.g., nitrogen-to-phosphorus …

Security Attacks And Countermeasures In Smart Homes, Hasibul Alam, Emmett Tomai

Computer Science Faculty Publications and Presentations

The Internet of Things (IoT) application is visible in all aspects of humans’ day-to-day affairs. The demand for IoT is growing at an unprecedented rate, from wearable wristwatches to autopilot cars. The smart home has also seen significant advancements to improve the quality of lifestyle. However, the security and privacy of IoT devices have become primary concerns as data is shared among intelligent devices and over the internet in a smart home network. There are several attacks - node capturing attack, sniffing attack, malware attack, boot phase attack, etc., which are conducted by adversaries to breach the security of smart …

An Analysis Of Successful Sqlia For Future Evolutionary Prediction, Andrew Pechin

Senior Honors Theses

Web applications are a fundamental component of the internet, many interact with backend databases. Securing web applications and their databases from hackers should be a top priority for cybersecurity researchers. Structured Query Language (SQL) injection attacks (SQLIA) constitute a significant threat to web applications. They can hijack the backend databases to steal personally identifiable information (PII), initiate scams, or launch more sophisticated cyberattacks. SQLIA has evolved since its conception in the early 2000s and will continue to do so in the coming years. This paper analyzes past literature and successful SQLIA from specific time periods to identify themes and methods …

Unique Factorization In The Rings Of Integers Of Quadratic Fields: A Method Of Proof, Zachary Warren

Senior Honors Theses

It is a well-known property of the integers, that given any nonzero a ∈ Z, where a is not a unit, we are able to write a as a unique product of prime numbers. This is because the Fundamental Theorem of Arithmetic (FTA) holds in the integers and guarantees (1) that such a factorization exists, and (2) that it is unique. As we look at other domains, however, specifically those of the form O(√D) = {a + b√D | a, b ∈ Z, D a negative, squarefree integer}, we find that …

Longitudinal Changes In Alzheimer’S-Related Plasma Biomarkers And Brain Amyloid, Murat Bilgel, Abhay Moghekar, Henrik Zetterberg, Bruno Jedynak, Multiple Additional Authors

Mathematics and Statistics Faculty Publications and Presentations

Introduction Understanding longitudinal plasma biomarker trajectories relative to brain amyloid changes can help devise Alzheimer’s progression assessment strategies.

Methods We examined the temporal order of changes in plasma amyloid-β ratio (Aβ42/Aβ40), glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and phosphorylated tau ratios (p-tau181/Aβ42, p-tau231/Aβ42) relative to 11C-Pittsburgh compound B (PiB) positron emission tomography (PET) cortical amyloid burden (PiB−/+). Participants (n = 199) were cognitively normal at index visit with a median 6.1-year follow-up.

Results PiB groups exhibited different rates of longitudinal change in Aβ42/Aβ40 (β = 5.41 × 10-4, SE = 1.95 × 10-4, p = 0.0073). …