Digital Commons Network^™

Soci: A Toolkit For Secure Outsourced Computation On Integers, Bowen Zhao, Jiaming Yuan, Ximeng Liu, Yongdong Wu, Hwee Hwa Pang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Secure outsourced computation is a key technique for protecting data security and privacy in the cloud. Although fully homomorphic encryption (FHE) enables computations over encrypted data, it suffers from high computation costs in order to support an unlimited number of arithmetic operations. Recently, secure computations based on interactions of multiple computation servers and partially homomorphic encryption (PHE) were proposed in the literature, which enable an unbound number of addition and multiplication operations on encrypted data more efficiently than FHE and do not add any noise to encrypted data; however, these existing solutions are either limited in functionalities (e.g., computation on …

Ngram-Oaxe: Phrase-Based Order-Agnostic Cross Entropy For Non-Autoregressive Machine Translation, Cunxiao Du, Zhaopeng Tu, Longyue Wang, Jing Jiang

Research Collection School Of Computing and Information Systems

Recently, a new training oaxe loss has proven effective to ameliorate the effect of multimodality for non-autoregressive translation (NAT), which removes the penalty of word order errors in the standard cross-entropy loss. Starting from the intuition that reordering generally occurs between phrases, we extend oaxe by only allowing reordering between ngram phrases and still requiring a strict match of word order within the phrases. Extensive experiments on NAT benchmarks across language pairs and data scales demonstrate the effectiveness and universality of our approach. Further analyses show that ngram noaxe indeed improves the translation of ngram phrases, and produces more fluent …

Mando: Multi-Level Heterogeneous Graph Embeddings For Fine-Grained Detection Of Smart Contract Vulnerabilities, Huu Hoang Nguyen, Nhat Minh Nguyen, Chunyao Xie, Zahra Ahmadi, Daniel Kudenko, Thanh Nam Doan, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Learning heterogeneous graphs consisting of different types of nodes and edges enhances the results of homogeneous graph techniques. An interesting example of such graphs is control-flow graphs representing possible software code execution flows. As such graphs represent more semantic information of code, developing techniques and tools for such graphs can be highly beneficial for detecting vulnerabilities in software for its reliability. However, existing heterogeneous graph techniques are still insufficient in handling complex graphs where the number of different types of nodes and edges is large and variable. This paper concentrates on the Ethereum smart contracts as a sample of software …

Ffl: Fine Grained Fault Localization For Student Programs Via Syntactic And Semantic Reasoning, Thanh Dat Nguyen, Cong Thanh Le, Duc-Minh Luong, Van-Hai Duong, Xuan Bach Le, David Lo, Quyet-Thang Huynh

Research Collection School Of Computing and Information Systems

Fault localization has been used to provide feedback for incorrect student programs since locations of faults can be a valuable hint for students about what caused their programs to crash. Unfortunately, existing fault localization techniques for student programs are limited because they usually consider either the program’s syntax or semantics alone. This motivates the new design of fault localization techniques that use both semantic and syntactical information of the program. In this paper, we introduce FFL (Fine grained Fault Localization), a novel technique using syntactic and semantic reasoning for localizing bugs in student programs. The novelty in FFL that allows …

Transrepair: Context-Aware Program Repair For Compilation Errors, Xueyang Li, Shangqing Liu, Ruitao Feng, Guozhu Meng, Xiaofei Xie, Kai Chen, Yang Liu

Research Collection School Of Computing and Information Systems

Automatically fixing compilation errors can greatly raise the productivity of software development, by guiding the novice or AI programmers to write and debug code. Recently, learning-based program repair has gained extensive attention and became the state of-the-art in practice. But it still leaves plenty of space for improvement. In this paper, we propose an end-to-end solution TransRepair to locate the error lines and create the correct substitute for a C program simultaneously. Superior to the counterpart, our approach takes into account the context of erroneous code and diagnostic compilation feedback. Then we devise a Transformer-based neural network to learn the …

Transitions Between Tobacco Products: Correlates Of Changes In Cigarette Smoking And E-Cigarette Use Among Exclusive Adult Smokers And Dual Users In Mexico, Katia Gallegos-Carrillo, Inti Barrientos-Gutiérrez, Edna Arillo-Santillán, Rosibel Rodríguez-Bolaños, Lizeth Cruz-Jiménez, Desirée Vidaña-Pérez, Yoo Jin Cho, Jim F. Thrasher Ph.D., Ma, Ms

Faculty Publications

This study examined transitions in tobacco products use among Mexican smokers and dual users. Data were analyzed from exclusive smokers (n = 2,946) and dual users (n = 1,643) recruited from an online consumer research panel and surveyed every-four months from November 2018 to April 2021. For exclusive smokers, estimated transitions were (time “t + 1” four months after prior survey): a) remain as exclusive smokers; b) dual use; c) exclusive e-cigarette use or quit both products. Among dual users, transitions analyzed were: a) remain as dual user; b) exclusive smoker; c) exclusive e-cigarette user or quit both products. Multinomial …

The Association Of Baseline Plasma Sars-Cov-2 Nucleocapsid Antigen Level And Outcomes In Patients Hospitalized With Covid-19, Katy Shaw-Saliba, Robin L Dewar, Neil R Aggarwal, Abdel G Babiker, Weizhong Chang, Nila J Dharan, Victoria J Davey, Elizabeth S Higgs, Norman Gerry, Adit A Ginde, J W Awori Hayanga, Helene Highbarger, Jeroen L Highbarger, Mamta K Jain, Virginia Kan, Kami Kim, Perrine Lallemand, Bradley G Leshnower, Joseph K Lutaakome, Gail Matthews, Ahmad Mourad, Eleftherios Mylonakis, Ven Natarajan, Maria L Padilla, Lavannya M Pandit, Roger Paredes, Sarah Pett, Srikanth Ramachandruni, M Tauseef Rehman, Brad T Sherman, D Clark Files, Samuel M Brown, Michael A Matthay, B Taylor Thompson, James D Neaton, H Clifford Lane, Jens D Lundgren

Faculty, Staff and Students Publications

BACKGROUND: Levels of plasma SARS-CoV-2 nucleocapsid (N) antigen may be an important biomarker in patients with COVID-19 and enhance our understanding of the pathogenesis of COVID-19.

OBJECTIVE: To evaluate whether levels of plasma antigen can predict short-term clinical outcomes and identify clinical and viral factors associated with plasma antigen levels in hospitalized patients with SARS-CoV-2.

DESIGN: Cross-sectional study of baseline plasma antigen level from 2540 participants enrolled in the TICO (Therapeutics for Inpatients With COVID-19) platform trial from August 2020 to November 2021, with additional data on day 5 outcome and time to discharge.

SETTING: 114 centers in 10 countries. …

Age Differential Response To Bevacizumab Therapy In Choroidal Neovascularization In Rabbits, Quynh Kieu, Wei Qian, Yingbin Fu, Xueding Wang, Yannis M Paulus

Faculty, Staff and Students Publications

Choroidal neovascularization (CNV) in young rabbits has been shown to have a rapid, robust response after treatment with bevacizumab, an anti-vascular endothelial growth factor (VEGF) medication. This investigation evaluates an age differential response to bevacizumab in older populations of rabbits using multimodal high resolution molecular imaging. Young (4 months old) and life span (14 months old) rabbits were given subretinal injections of Matrigel and VEGF to produce CNV. All CNV rabbit models were then treated with a bevacizumab intravitreal injection. Rabbits were then monitored longitudinally using photoacoustic microscopy (PAM), optical coherence tomography (OCT), color photography, and fluorescence imaging. Chain-like gold …

Adding Context To Source Code Representations For Deep Learning, Fuwei Tian, Christoph Treude

Research Collection School Of Computing and Information Systems

Deep learning models have been successfully applied to a variety of software engineering tasks, such as code classification, summarisation, and bug and vulnerability detection. In order to apply deep learning to these tasks, source code needs to be represented in a format that is suitable for input into the deep learning model. Most approaches to representing source code, such as tokens, abstract syntax trees (ASTs), data flow graphs (DFGs), and control flow graphs (CFGs) only focus on the code itself and do not take into account additional context that could be useful for deep learning models. In this paper, we …

Dualformer: Local-Global Stratified Transformer For Efficient Video Recognition, Yuxuan Liang, Pan Zhou, Roger Zimmermann, Shuicheng Yan

Research Collection School Of Computing and Information Systems

While transformers have shown great potential on video recognition with their strong capability of capturing long-range dependencies, they often suffer high computational costs induced by the self-attention to the huge number of 3D tokens. In this paper, we present a new transformer architecture termed DualFormer, which can efficiently perform space-time attention for video recognition. Concretely, DualFormer stratifies the full space-time attention into dual cascaded levels, i.e., to first learn fine-grained local interactions among nearby 3D tokens, and then to capture coarse-grained global dependencies between the query token and global pyramid contexts. Different from existing methods that apply space-time factorization or …

Self-Promoted Supervision For Few-Shot Transformer, Bowen Dong, Pan Zhou, Shuicheng Yan, Wangmeng Zuo

Research Collection School Of Computing and Information Systems

The few-shot learning ability of vision transformers (ViTs) is rarely investigated though heavily desired. In this work, we empirically find that with the same few-shot learning frameworks, e.g. MetaBaseline, replacing the widely used CNN feature extractor with a ViT model often severely impairs few-shot classification performance. Moreover, our empirical study shows that in the absence of inductive bias, ViTs often learn the low-qualified token dependencies under few-shot learning regime where only a few labeled training data are available, which largely contributes to the above performance degradation. To alleviate this issue, for the first time, we propose a simple yet effective …

Video Graph Transformer For Video Question Answering, Junbin Xiao, Pan Zhou, Tat-Seng Chua, Shuicheng Yan

Research Collection School Of Computing and Information Systems

This paper proposes a Video Graph Transformer (VGT) model for Video Quetion Answering (VideoQA). VGT’s uniqueness are two-fold: 1) it designs a dynamic graph transformer module which encodes video by explicitly capturing the visual objects, their relations, and dynamics for complex spatio-temporal reasoning; and 2) it exploits disentangled video and text Transformers for relevance comparison between the video and text to perform QA, instead of entangled crossmodal Transformer for answer classification. Vision-text communication is done by additional cross-modal interaction modules. With more reasonable video encoding and QA solution, we show that VGT can achieve much better performances on VideoQA tasks …

Mix-Dann And Dynamic-Modal-Distillation For Video Domain Adaptation, Yuehao Yin, Bin Zhu, Jingjing Chen, Lechao Cheng, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Video domain adaptation is non-trivial due to video is inherently involved with multi-dimensional and multi-modal information. Existing works mainly adopt adversarial learning and self-supervised tasks to align features. Nevertheless, the explicit interaction between source and target in the temporal dimension, as well as the adaptation between modalities, are unexploited. In this paper, we propose Mix-Domain-Adversarial Neural Network and Dynamic-Modal-Distillation (MD-DMD), a novel multi-modal adversarial learning framework for unsupervised video domain adaptation. Our approach incorporates the temporal information between source and target domains, as well as the diversity of adaptability between modalities. On the one hand, for every single modality, we …

Toward Personalized Answer Generation In E-Commerce Via Multi-Perspective Preference Modeling, Yang Deng, Yaliang Li, Wenxuan Zhang, Bolin Ding, Wai Lam

Research Collection School Of Computing and Information Systems

Recently, Product Question Answering (PQA) on E-Commerce platforms has attracted increasing attention as it can act as an intelligent online shopping assistant and improve the customer shopping experience. Its key function, automatic answer generation for product-related questions, has been studied by aiming to generate content-preserving while question-related answers. However, an important characteristic of PQA, i.e., personalization, is neglected by existing methods. It is insufficient to provide the same “completely summarized” answer to all customers, since many customers are more willing to see personalized answers with customized information only for themselves, by taking into consideration their own preferences toward product aspects …

Sustaining Patient Portal Continuous Use Intention And Enhancing Deep Structure Usage: Cognitive Dissonance Effects Of Health Professional Encouragement And Security Concerns, Murad Moqbel, Barbara Hewitt, Fiona Fui-Hoon Nah, Rosann M. Mclean

Research Collection School Of Computing and Information Systems

Sustaining patient portal use is a major problem for many healthcare organizations and providers. If this problem can be successfully addressed, it could have a positive impact on various stakeholders. Through the lens of cognitive dissonance theory, this study investigates the role of health professional encouragement as well as patients’ security concerns in influencing continuous use intention and deep structure usage among users of a patient portal. The analysis of data collected from 177 patients at a major medical center in the Midwestern region of the United States shows that health professional encouragement helps increase the continuous use intention and …

Towards Robust Models Of Code Via Energy-Based Learning On Auxiliary Datasets, Duy Quoc Nghi Bui, Yijun Yu

Research Collection School Of Computing and Information Systems

Existing approaches to improving the robustness of source code models concentrate on recognizing adversarial samples rather than valid samples that fall outside of a given distribution, which we refer to as out-of-distribution (OOD) samples. To this end, we propose to use an auxiliary dataset (out-of-distribution) such that, when trained together with the main dataset, they will enhance the model’s robustness. We adapt energy-bounded learning objective function to assign a higher score to in-distribution samples and a lower score to out-of-distribution samples in order to incorporate such out-of-distribution samples into the training process of source code models. In terms of OOD …

Codebert For Code Clone Detection: A Replication Study, Saad Arshad, Shamsa Abid, Shafay Shamail

Research Collection School Of Computing and Information Systems

Large pre-trained models have dramatically improved the state-of-the-art on a variety of natural language processing (NLP) tasks. CodeBERT is one such pre-trained model for natural language (NL) and programming language (PL) which captures the semantics in natural language and programming language, and produces general-purpose representations. While it has been shown to support natural language code search and code documentation generation tasks, its effectiveness for code clone detection is not explored in depth. In this paper, we aim to replicate and evaluate the performance of CodeBERT for code clone detection on multiple datasets with varying functionalities to understand (1) whether CodeBERT …

A Comparative Analysis Of Clone Detection Techniques On Semanticclonebench, Sohaib Masood Rabbani, Nabeel Ahmad Gulzar, Saad Arshad, Shamsa Abid, Shafay Shamail

Research Collection School Of Computing and Information Systems

Semantic code clone detection involves the detection of functionally similar code fragments which may otherwise be lexically, syntactically, or structurally dissimilar. The detection of semantic code clones has important applications in aspect mining and product line analysis. The accurate detection of semantic code clones is a challenging task and various techniques have been proposed. However, the evaluation of these techniques is performed using various datasets and we do not have a clear picture of the performance of these techniques relative to each other. Recently, SemanticCloneBench has been introduced as a benchmark for semantic clones. Now, we can use the SemanticCloneBench …

Pruning The Communication Bandwidth Between Reinforcement Learning Agents Through Causal Inference: An Innovative Approach To Designing A Smart Grid Power System, Xianjie Zhang, Yu Liu, Wenjun Li, Chen Gong

Research Collection School Of Computing and Information Systems

Electricity demands are increasing significantly and the traditional power grid system isfacing huge challenges. As the desired next-generation power grid system, smart grid can providesecure and reliable power generation, and consumption, and can also realize the system’s coordinatedand intelligent power distribution. Coordinating grid power distribution usually requiresmutual communication between power distributors to accomplish coordination. However, the powernetwork is complex, the network nodes are far apart, and the communication bandwidth is oftenexpensive. Therefore, how to reduce the communication bandwidth in the cooperative power distributionprocess task is crucially important. One way to tackle this problem is to build mechanismsto selectively send out …

Problems Of Distance, Communications, And Authority: How Charles V And Philip Ii Ruled The Global Spanish Empire, Cody Bryan Mitchell

Armstrong Undergraduate Journal of History

This essay explains how the Spanish (or Castilian) crown during the sixteenth and seventeenth centuries managed its worldwide empire. It emphasizes the contribution of, and the tension between, the crown’s two main strategies: political decentralization – or delegation – and imperial centralization. To begin, it contextualizes the issue by exploring the situation at the time and explains how the problems of distance and communication were closely linked. Secondly, drawing on the comments of both contemporary observers and modern historians, this paper examines the approaches used by the Spanish kings in ensuring the optimum reliability of their intelligence networks within Europe …

Architecture As Memory: Gothic Ruins In The Work Of Lyonel Feininger, 1928-1953, Daria Rose Evdokimova

Armstrong Undergraduate Journal of History

In the summer of 1928 Lyonel Feininger made his first drawings of the ruins of a local church in the German village of Hoff. Through a series of happenstance episodes these Gothic ruins grew to haunt the artist’s entire body of work: across various media (pencil, watercolor, ink, oil), across space (in person from the Baltic coast, and later in New York from memory), and time (the motif spans three crucial decades of the artist’s career). While everything else in Feininger’s life was sent into a chaotic flurry – the banning of his works by the Weimar government, shutdown of …

A Forgotten ‘Riot’: Discovering The Black Cat Tavern Raid’S Place In Queer History, Katelyn "Katie" Nash

Armstrong Undergraduate Journal of History

The Black Cat Tavern Raid of 1967 has long been relegated to the footnotes of history, and, when it is remembered, it is portrayed as a riot similar to the one that occurred at the Stonewall Inn two years later. Using archival and contemporary sources, this article explores the events surrounding the raid and subsequent protest and places them within the greater context of the 1960s. In addition, I contextualize and analyze the legacy of these events, explore their often overlooked contributions to queer history, and conclude that, while they are often overshadowed by Stonewall, they still deserve to be …

Calciphylaxis Arising Following Bariatric Surgery: A Case Series, Bethany Cucka, Bianca Biglione, Lauren Ko, Emily D Nguyen, Charbel C Khoury, Sagar U Nigwekar, Malcolm K Robinson, Daniela Kroshinsky

2020-Current year OA Pubs

No abstract provided.

Comments On Preliminary Draft 8 [Black Letter And Comments], Jane C. Ginsburg

Faculty Scholarship

PD8 represents a great deal of labor, for which the Reporters deserve recognition. As detailed below, however, PD8’s occasional departures from or omissions of statutory text may not only be misleading or confusing, but – as has been the case with prior drafts – often have the result, if not the purpose, of whittling down the scope of copyright protection. In addition to identifying those instances and explaining their consequences, the following comments will suggest clarifications to some of the Comments and Illustrations.

Phase Ib Study Of Eprenetapopt (Apr-246) In Combination With Pembrolizumab In Patients With Advanced Or Metastatic Solid Tumors, H Park, Et Al.

2020-Current year OA Pubs

BACKGROUND: We conducted a phase I, multicenter, open-label, dose-finding, and expansion study to determine the safety and preliminary efficacy of eprenetapopt (APR-246) combined with pembrolizumab in patients with advanced/metastatic solid tumors (ClinicalTrials.gov NCT04383938).

PATIENTS AND METHODS: For dose-finding, requirements were non-central nervous system primary solid tumor, intolerant to/progressed after ≥1 line of treatment, and eligible for pembrolizumab; for expansion: (i) gastric/gastroesophageal junction tumor, intolerant to/progressed after first-line treatment, and no prior anti-programmed cell death receptor-1 (PD-1)/programmed death-ligand 1 (PD-L1) therapy; (ii) bladder/urothelial tumor, intolerant to/progressed after first-line cisplatin-based chemotherapy, and no prior anti-PD-1/PD-L1 therapy; (iii) non-small-cell lung cancer (NSCLC) with …

Variability In Energy Expenditure Is Much Greater In Males Than Females, Lewis G Halsey, Susan B Racette, Et Al.

2020-Current year OA Pubs

In mammals, trait variation is often reported to be greater among males than females. However, to date, mainly only morphological traits have been studied. Energy expenditure represents the metabolic costs of multiple physical, physiological, and behavioral traits. Energy expenditure could exhibit particularly high greater male variation through a cumulative effect if those traits mostly exhibit greater male variation, or a lack of greater male variation if many of them do not. Sex differences in energy expenditure variation have been little explored. We analyzed a large database on energy expenditure in adult humans (1494 males and 3108 females) to investigate whether …

Recommendations For Establishing A Market For Invasive Green Crabs In New England, Eve Fischer, Jesse Minor, Marissa Mcmahan

All Faculty Scholarship

Green crabs are one of the most invasive marine species in the world. Their populations in New England have grown significantly due to climate change, increasing their environmental and socioeconomic impacts. Green crabs are voracious predators of soft shell clams, and have had a detrimental impact on the region’s valuable clam fisheries. They also prey on juvenile lobsters and other shellfish and compete with native crab species for resources. Green crabs burrow into and damage eelgrass beds, which are a vital habitat for many marine species and an important “blue carbon” sink. Due to their rapid rate of reproduction as …

The Space Density Of Intermediate-Redshift, Extremely Compact, Massive Starburst Galaxies, Kelly E. Whalen, Ryan C. Hickox, Alison L. Coil, Aleksandar M. Diamond-Stanic, James E. Geach, John Moustakas, Gregory H. Rudnick, David S.N. Rupke, Paul H. Sell, Christy A. Tremonti, Julie D. Davis, Serena Perrotta, Grayson C. Petter

All Faculty Scholarship

We present a measurement of the intrinsic space density of intermediate-redshift (z ∼ 0.5), massive (M * ∼ 1011 M ⊙), compact (R e ∼ 100 pc) starburst (ΣSFR ∼ 1000 M ⊙ yr−1 kpc−1) galaxies with tidal features indicative of them having undergone recent major mergers. A subset of them host kiloparsec-scale, > 1000 km s−1 outflows and have little indication of AGN activity, suggesting that extreme star formation can be a primary driver of large-scale feedback. The aim for this paper is to calculate their space density so we can place them in a better cosmological context. We do …

Improving Hypertension Self Management In African American Men, Elizabeth C. Felix

Electronic Theses and Dissertations

Hypertension is a cardiopulmonary condition linked to genetic, environmental, and social factors. Left untreated, it can lead to fatal conditions such as heart disease. In the United States, African Americans experience disproportionately high rates of hypertension, earlier onset of symptoms, greater severity, and higher related mortality rates. African Americans also statistically have more difficulty self-managing their hypertension than other demographics. The aim of this project was (a) to identify, define, and measure perceived barriers to self-management of hypertension among African American men and (b) to target these barriers and increase patient engagement through personalized intervention plans. The researcher recruited 24 …

A Path To Success: A Case Study Of Military Veterans At A Midwestern University, Jada N. Reynolds

Electronic Theses and Dissertations

Abstract The purpose of this study was to examine the lived experiences of military veterans transitioning from service members to civilian life. The study was conducted using semistructured interviews with eight transitioning veterans who had completed their bachelor’s degree from the same Midwestern U. S. university between 2017 and 2022. Retention theory, and transition theory were used as the guiding theories for this study. An intrinsic qualitative case study was used for data analysis, which resulted in the emerging themes (a) Transitioning from Military Service to Civilian Life, (b) Work-Life-Study Balance: Confronting Challenges, and (c) Supporting Military Veterans. This study …