Digital Commons Network^™

Tourgether360: Exploring 360° Tour Videos With Others, Kartikaeya Kumar, Lev Poretski, Jiannan Li, Anthony Tang

Research Collection School Of Computing and Information Systems

Contemporary 360° video players do not provide ways to let people explore the videos together. Tourgether360 addresses this problem for 360° tour videos using a pseudo-spatial navigation technique that provides both an overhead “context” view of the environment as a minimap, as well as a shared pseudo-3D environment for exploring the video. Collaborators appear as avatars along a track depending on their position in the video timeline and can point and synchronize their playback. In this work, we describe the intellectual precedents for this work, our design goals, and our implementation approach of Tourgether360. Finally, we discuss future work based …

Probabilistic Path Prioritization For Hybrid Fuzzing, Lei Zhao, Pengcheng Cao, Yue Duan, Heng Yin, Jifeng Xuan

Research Collection School Of Computing and Information Systems

Hybrid fuzzing that combines fuzzing and concolic execution has become an advanced technique for software vulnerability detection. Based on the observation that fuzzing and concolic execution are complementary in nature, state-of-the-art hybrid fuzzing systems deploy “optimal concolic testing” and “demand launch” strategies. Although these ideas sound intriguing, we point out several fundamental limitations in them, due to unrealistic or oversimplified assumptions. Further, we propose a novel “discriminative dispatch” strategy and design a probabilistic hybrid fuzzing system to better utilize the capability of concolic execution. Specifically, we design a Monte Carlo-based probabilistic path prioritization model to quantify each path’s difficulty, and …

Learning Transferable Perturbations For Image Captioning, Hanjie Wu, Yongtuo Liu, Hongmin Cai, Shengfeng He

Research Collection School Of Computing and Information Systems

Present studies have discovered that state-of-the-art deep learning models can be attacked by small but well-designed perturbations. Existing attack algorithms for the image captioning task is time-consuming, and their generated adversarial examples cannot transfer well to other models. To generate adversarial examples faster and stronger, we propose to learn the perturbations by a generative model that is governed by three novel loss functions. Image feature distortion loss is designed to maximize the encoded image feature distance between original images and the corresponding adversarial examples at the image domain, and local-global mismatching loss is introduced to separate the mapping encoding representation …

Context Modeling With Evidence Filter For Multiple Choice Question Answering, Sicheng Yu, Hao Zhang, Wei Jing, Jing Jiang

Research Collection School Of Computing and Information Systems

Multiple-Choice Question Answering (MCQA) is one of the challenging tasks in machine reading comprehension. The main challenge in MCQA is to extract "evidence" from the given context that supports the correct answer. In OpenbookQA dataset [1], the requirement of extracting "evidence" is particularly important due to the mutual independence of sentences in the context. Existing work tackles this problem by annotated evidence or distant supervision with rules which overly rely on human efforts. To address the challenge, we propose a simple yet effective approach termed evidence filtering to model the relationships between the encoded contexts with respect to different options …

Benchmarking Library Recognition In Tweets, Ting Zhang, Divya Prabha Chandrasekaran, Ferdian Thung, David Lo

Research Collection School Of Computing and Information Systems

Software developers often use social media (such as Twitter) to shareprogramming knowledge such as new tools, sample code snippets,and tips on programming. One of the topics they talk about is thesoftware library. The tweets may contain useful information abouta library. A good understanding of this information, e.g., on thedeveloper’s views regarding a library can be beneficial to weigh thepros and cons of using the library as well as the general sentimentstowards the library. However, it is not trivial to recognize whethera word actually refers to a library or other meanings. For example,a tweet mentioning the word “pandas" may refer to …

On The Effectiveness Of Pretrained Models For Api Learning, Mohammad Abdul Hadi, Imam Nur Bani Yusuf, Thung Ferdian, Gia Kien Luong, Lingxiao Jiang, Fatemeh H. Fard, David Lo

Research Collection School Of Computing and Information Systems

Developers frequently use APIs to implement certain functionalities, such as parsing Excel Files, reading and writing text files line by line, etc. Developers can greatly benefit from automatic API usage sequence generation based on natural language queries for building applications in a faster and cleaner manner. Existing approaches utilize information retrieval models to search for matching API sequences given a query or use RNN-based encoder-decoder to generate API sequences. As it stands, the first approach treats queries and API names as bags of words. It lacks deep comprehension of the semantics of the queries. The latter approach adapts a neural …

Structure-Aware Visualization Retrieval, Haotian Li, Yong Wang, Aoyu Wu, Huan Wei, Huamin. Qu

Research Collection School Of Computing and Information Systems

With the wide usage of data visualizations, a huge number of Scalable Vector Graphic (SVG)-based visualizations have been created and shared online. Accordingly, there has been an increasing interest in exploring how to retrieve perceptually similar visualizations from a large corpus, since it can benefit various downstream applications such as visualization recommendation. Existing methods mainly focus on the visual appearance of visualizations by regarding them as bitmap images. However, the structural information intrinsically existing in SVG-based visualizations is ignored. Such structural information can delineate the spatial and hierarchical relationship among visual elements, and characterize visualizations thoroughly from a new perspective. …

Natural Attack For Pre-Trained Models Of Code, Zhou Yang, Jieke Shi, Junda He, David Lo

Research Collection School Of Computing and Information Systems

Pre-trained models of code have achieved success in many important software engineering tasks. However, these powerful models are vulnerable to adversarial attacks that slightly perturb model inputs to make a victim model produce wrong outputs. Current works mainly attack models of code with examples that preserve operational program semantics but ignore a fundamental requirement for adversarial example generation: perturbations should be natural to human judges, which we refer to as naturalness requirement. In this paper, we propose ALERT (Naturalness Aware Attack), a black-box attack that adversarially transforms inputs to make victim models produce wrong outputs. Different from prior works, this …

Detecting False Alarms From Automatic Static Analysis Tools: How Far Are We?, Hong Jin Kang, Khai Loong Aw, David Lo

Research Collection School Of Computing and Information Systems

Automatic static analysis tools (ASATs), such as Findbugs, have a high false alarm rate. The large number of false alarms produced poses a barrier to adoption. Researchers have proposed the use of machine learning to prune false alarms and present only actionable warnings to developers. The state-of-the-art study has identified a set of “Golden Features” based on metrics computed over the characteristics and history of the file, code, and warning. Recent studies show that machine learning using these features is extremely effective and that they achieve almost perfect performance. We perform a detailed analysis to better understand the strong performance …

Static Inference Meets Deep Learning: A Hybrid Type Inference Approach For Python, Yun Peng, Cuiyun Gao, Zongjie Li, Bowei Gao, David Lo, Qirun Zhang, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Type inference for dynamic programming languages such as Python is an important yet challenging task. Static type inference techniques can precisely infer variables with enough static constraints but are unable to handle variables with dynamic features. Deep learning (DL) based approaches are feature-agnostic, but they cannot guarantee the correctness of the predicted types. Their performance significantly depends on the quality of the training data (i.e., DL models perform poorly on some common types that rarely appear in the training dataset). It is interesting to note that the static and DL-based approaches offer complementary benefits. Unfortunately, to our knowledge, precise type …

Automated Identification Of Libraries From Vulnerability Data: Can We Do Better?, Stefanus A. Haryono, Hong Jin Kang, Abhishek Sharma, Asankhaya Sharma, Andrew E. Santosa, Ming Yi Ang, David Lo

Research Collection School Of Computing and Information Systems

Software engineers depend heavily on software libraries and have to update their dependencies once vulnerabilities are found in them. Software Composition Analysis (SCA) helps developers identify vulnerable libraries used by an application. A key challenge is the identification of libraries related to a given reported vulnerability in the National Vulnerability Database (NVD), which may not explicitly indicate the affected libraries. Recently, researchers have tried to address the problem of identifying the libraries from an NVD report by treating it as an extreme multi-label learning (XML) problem, characterized by its large number of possible labels and severe data sparsity. As input, …

Short Sellers And Insider Trading Profitability: A Natural Experiment, Xia Chen, Qiang Cheng, Ting Luo, Heng Yue

Research Collection School Of Accountancy

We examine the impact of short sellers on insider trading profitability using a natural experiment of a pilot program which relaxed short-selling constraints for randomly selected pilot stocks. We find that pilot firms experienced a significant decrease in insider trading profitability during the pilot program. The results are more pronounced for the pilot firms with poor information quality, and for the pilot firms without corporate restrictions on insider trading. Our evidence suggests that short sellers serve an important market disciplinary role by reducing insider trading profitability.

5 Ways To Turn The Pandemic Into An Opportunity For E-Commerce Disruption, Yuanto Kusnadi, Gary Pan

Research Collection School Of Accountancy

It is safe to say that the COVID-19 pandemic had upended life as we knew it. Schools embraced blended learning, brick-and-mortar businesses were shuttered, and mask wearing whilst at indoor venues remains the order of the day. Amid the chaos, one bright spot is the opportunity for e-commerce entrepreneurs to disrupt traditional businesses.

Contract's Covert Meddlers, Sarah Winsberg

Notre Dame Law Review

Scholars of contract law typically examine contracts as bargains between two parties. This approach elides an additional, key function of many contracts: to shape existing relationships to the satisfaction of a third party, often one more economically powerful than either of the two bargainers. Third-party litigants, especially creditors, have historically advocated for their own interests and interpretive paradigms so strongly that they have sometimes gained priority over the actual intentions of the two bargainers.

This Article recovers the story of how a group of frequent-flier third parties—mainly creditors of small businesses—shifted the rules of contracts between partners in early America. …

In Our Shoes, Mahogany Brim '22

Honor Scholar Theses

In Our Shoes has lived inside of me for a long time. As someone who has always been fully immersed in my own culture, I was born into this duality of identity. I realized early on that I existed in two different worlds: the one shaped by my Bajan identity and the one shaped by my American one. I wasn’t fully a Black American. I had deep ties to this tiny island in the Atlantic, famous for flying fish and Rihanna. And I wasn’t one of those immigrant children that had never set foot on the island that they were …

"Folk" Home-Lore: Storytelling And The Architecture Of The Home, Madeleine Pollara

Masters in Architecture Program: Theses

I have observed that architecture is not sufficiently understood. This problem is largely due to the fact that the language used to describe architecture is broad and convoluted. This language is also divided into two categories which describe the denotative and connotative nature of architecture. It is easier to understand the denotative nature of architecture than it is to understand the connotative nature. As a response to this issue, my project aims to explore the connotative nature of architecture through telling stories about the home from the architecture’s point of view. The purpose of my thesis is to explore the …

A Physical Model Of Deadmans Run, Quinn Brandt

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

A physical model of Deadmans Run and a pair of railroad bridges was constructed to assess the impacts of the bridges on flood flows. Lower Platte South Natural Resources District is planning a series of improvements to Deadmans Run to improve flood conveyance capacity and remove approximately 500 homes and businesses from the floodplain. The rail bridges are located less than a mile from the confluence of Deadmans Run and Salt Creek, meaning the bridges present a significant bottleneck to the planned improvements. The physical model was used to characterize the drag effects caused by the bridges, which was used …

Mmekg: Multi-Modal Event Knowledge Graph Towards Universal Representation Across Modalities, Yubo Ma, Zehao Wang, Mukai Li, Yixin Cao, Meiqi Chen, Xinze Li, Wenqi Sun, Kunquan Deng, Kun Wang, Aixin Sun, Jing Shao

Research Collection School Of Computing and Information Systems

Events are fundamental building blocks of realworld happenings. In this paper, we present a large-scale, multi-modal event knowledge graph named MMEKG. MMEKG unifies different modalities of knowledge via events, which complement and disambiguate each other. Specifically, MMEKG incorporates (i) over 990 thousand concept events with 644 relation types to cover most types of happenings, and (ii) over 863 million instance events connected through 934 million relations, which provide rich contextual information in texts and/or images. To collect billion-scale instance events and relations among them, we additionally develop an efficient yet effective pipeline for textual/visual knowledge extraction system. We also develop …

Prompt For Extraction? Paie: Prompting Argument Interaction For Event Argument Extraction, Yubo Ma, Zehao Wang, Yixin Cao, Mukai Li, Meiqi Chen, Kun Wang, Jing Shao

Research Collection School Of Computing and Information Systems

In this paper, we propose an effective yet efficient model PAIE for both sentence-level and document-level Event Argument Extraction (EAE), which also generalizes well when there is a lack of training data. On the one hand, PAIE utilizes prompt tuning for extractive objectives to take the best advantages of Pre-trained Language Models (PLMs). It introduces two span selectors based on the prompt to select start/end tokens among input texts for each role. On the other hand, it captures argument interactions via multi-role prompts and conducts joint optimization with optimal span assignments via a bipartite matching loss. Also, with a flexible …

Neighbor-Anchoring Adversarial Graph Neural Networks (Extended Abstract), Zemin Liu, Yuan Fang, Yong Liu, Vincent W. Zheng

Research Collection School Of Computing and Information Systems

While graph neural networks (GNNs) exhibit strong discriminative power, they often fall short of learning the underlying node distribution for increased robustness. To deal with this, inspired by generative adversarial networks (GANs), we investigate the problem of adversarial learning on graph neural networks, and propose a novel framework named NAGNN (i.e., Neighbor-anchoring Adversarial Graph Neural Networks) for graph representation learning, which trains not only a discriminator but also a generator that compete with each other. In particular, we propose a novel neighbor-anchoring strategy, where the generator produces samples with explicit features and neighborhood structures anchored on a reference real node, …

Message-Locked Searchable Encryption: A New Versatile Tool For Secure Cloud Storage, Xueqiao Liu, Guomin Yang, Willy Susilo, Joseph Tonien, Rongmao Chen, Xixiang Lv

Research Collection School Of Computing and Information Systems

Message-Locked Encryption (MLE) is a useful tool to enable deduplication over encrypted data in cloud storage. It can significantly improve the cloud service quality by eliminating redundancy to save storage resources, and hence user cost, and also providing defense against different types of attacks, such as duplicate faking attack and brute-force attack. A typical MLE scheme only focuses on deduplication. On the other hand, supporting search operations on stored content is another essential requirement for cloud storage. In this article, we present a message-locked searchable encryption (MLSE) scheme in a dual-server setting, which achieves simultaneously the desirable features of supporting …

Feasibility Studies In Indoor Localization Through Intelligent Conversation, Sheshadri Smitha, Linus Cheng, Kotaro Hara

Research Collection School Of Computing and Information Systems

We propose a model to achieve human localization in indoor environments through intelligent conversation between users and an agent. We investigated the feasibility of conversational localization by conducting two studies. First, we conducted a Wizard-of-Oz study with N = 7 participants and studied the feasibility of localizing users through conversation. We identified challenges posed by users’ language and behavior. Second, we collected N = 800 user descriptions of virtual indoor locations from N = 80 Amazon Mechanical Turk participants to analyze user language. We explored the effects of conversational agent behavior and observed that people describe indoor locations differently based …

An Evaluation Of Covid-19 Vaccination Rates Of The Patients At The Kentucky Racing Health Services Center., Aditya Mehta

College of Arts & Sciences Senior Theses

COVID-19 vaccines have been widely available to the U.S. public since early 2021. However, vaccination rates still vary considerably across geographical areas and different populations. The objective of this study was to research overall vaccination rates against COVID-19 for Latinx patients at the Kentucky Racing Health Services Center (KRHSC). Vaccination and booster data was collected from June to December 2021 for all unique patients visiting the center. It was initially hypothesized that these rates of vaccination and booster doses for the KRHSC patients would be lower than the data reported by Kentucky and Jefferson County. After a retrospective review, the …

Greetings From Eureka!: A Story Quartet And Critical Afterword., Roman Sauls

College of Arts & Sciences Senior Theses

This project details the narrative decisions made within a quarter of my own stories, with special attention paid to cross-story relationships, the dynamics of linked short story collections, and the elements of craft I have honed while at the University of Louisville. The nature of narrative structure and narrative time is discussed in the first story; the crafting of dialogue and the narrative texture conjured from that dialogue in the second; the interaction between a character's psychology and a story's setting in the third; and the relevance of both sensorial and visual motifs in the fourth. This thesis also discusses …

Early Mathematical Abilities Of 48-Month-Old Children With Williams Syndrome., Jenna N. Tinnell

College of Arts & Sciences Senior Theses

Williams syndrome (WS) is a genetic neurodevelopmental disorder associated with relative strengths in concrete vocabulary, nonverbal reasoning, and verbal short-term memory and considerable weaknesses in visuospatial construction and relational language. While the cognitive profile of WS has been studied extensively, there have been few studies of the early mathematical abilities of children with WS and the cognitive predictors of these abilities. The purpose of this study was to describe the early mathematical abilities of 48-month-olds with WS and determine the concurrent cognitive predictors of these abilities. The Differential Ability Scales–second edition (DAS-II) was used to determine cognitive and mathematical abilities …

The Madwoman In The Refrigerator And A Song Of Ice And Fire., Alex Herm

College of Arts & Sciences Senior Theses

There is an existing trope in the fantasy genre I call the madwoman in the refrigerator—in which a female character is killed, maimed, raped, depowered, and/or made to go mad or insane when she is no longer able to uphold the conventional genre expectations of her role in the narrative, such as the angel, monster, or angelic monster. It is a combination of the theory from Sandra Gilbert and Susan Gubar that women are demure angels when they are fulfilling stereotypical feminine roles in a narrative and when desire or agency is found, the woman is a monster, portrayed as …

Synthesis Of Allylic Synthons And Application Of Pyrrole Thiocarboxylic Acids In The Synthesis Of Pyrrole-Imidazole Alkaloids, Olatunji Seyi Ojo

Chemistry & Biochemistry Dissertations - Archive

The first part of this dissertation describes the synthesis of allylic compounds from terminal alkenes without the use of any catalysts or oxidants. One of the most versatile molecules in organic chemistry is allylic compounds. Their importance arises from their miscellaneous reactivity which makes them attractive to organic chemists. They are found in several molecules that have medicinal and synthetic utilities. The preparations of allylic compounds have been majorly through transition metal catalyzed process. The second part describes the formation of pyrrole-carboxamide in pyrrole-imidazole alkaloids. Pyrroleimidazole alkaloids have gained attention of synthetic chemists due to their potential therapeutical applications and …

“I Just Learn Differently”: The Experiences Of Dis/Abled Students Of Color Interpreting And Resisting Normalizing Forces In The Mathematics Classroom, Dina Mahmood

Education (PhD) Dissertations

This critical phenomenological study employs a disabilities studies in education and critical race theory (DisCrit) lens to unpack the learning experiences of seven dis/abled students of color in the secondary mathematics classroom. Based on data collected from individual and group interviews, the counter-stories presented in this study highlight the implicit and explicit ways that the normative forces of ableism and racism circulate in the secondary mathematics classroom. Through their education journey maps, the participants described forms of hyper-labeling, experiences of implicit and explicit biases from teachers and peers, and rigid conceptions of mathematics that constrained their success. The counter-stories are, …

Creating An Action Plan To Increase Diversity And Inclusion At Northwest Church Of Christ, Kenton Reeves Brown

Doctor of Ministry Theses and Dissertations

This project was designed to meet a need at the Northwest Church of Christ in Oklahoma City to help the church transition from a church that values diversity to one that realizes its vision of being diverse and inclusive. The scope of this project was to create an action plan to increase diversity and inclusion to present to the church leaders for their consideration. The theological foundation for the project comes from Paul’s convictions, expressed in Gal 1–2, that any who are in Christ should not be excluded or treated as a lower-class member of the community based on their …

The Criterion (2022)

The Criterion

No abstract provided.