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Full-Text Articles in Physical Sciences and Mathematics

Shunted Self-Attention Via Multi-Scale Token Aggregation, Sucheng Ren, Daquan Zhou, Shengfeng He, Jiashi Feng, Xinchao Wang Jun 2022

Shunted Self-Attention Via Multi-Scale Token Aggregation, Sucheng Ren, Daquan Zhou, Shengfeng He, Jiashi Feng, Xinchao Wang

Research Collection School Of Computing and Information Systems

Recent Vision Transformer (ViT) models have demonstrated encouraging results across various computer vision tasks, thanks to its competence in modeling long-range dependencies of image patches or tokens via self-attention. These models, however, usually designate the similar receptive fields of each token feature within each layer. Such a constraint inevitably limits the ability of each self-attention layer in capturing multi-scale features, thereby leading to performance degradation in handling images with multiple objects of different scales. To address this issue, we propose a novel and generic strategy, termed shunted selfattention (SSA), that allows ViTs to model the attentions at hybrid scales per …

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Co-Advise: Cross Inductive Bias Distillation, Sucheng Ren, Zhengqi Gao, Tiany Hua, Zihui Xue, Yonglong Tian, Shengfeng He, Hang Zhao Jun 2022

Co-Advise: Cross Inductive Bias Distillation, Sucheng Ren, Zhengqi Gao, Tiany Hua, Zihui Xue, Yonglong Tian, Shengfeng He, Hang Zhao

Research Collection School Of Computing and Information Systems

The inductive bias of vision transformers is more relaxed that cannot work well with insufficient data. Knowledge distillation is thus introduced to assist the training of transformers. Unlike previous works, where merely heavy convolution-based teachers are provided, in this paper, we delve into the influence of models inductive biases in knowledge distillation (e.g., convolution and involution). Our key observation is that the teacher accuracy is not the dominant reason for the student accuracy, but the teacher inductive bias is more important. We demonstrate that lightweight teachers with different architectural inductive biases can be used to co-advise the student transformer with …

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Learnings From A Pilot Hybrid Question Answering System: Cqas: Case Study Based On A Singapore Government Agency's Customer Service Centre, Hui Shan Lee, Shankararaman, Venky, Eng Lieh Ouh Jun 2022

Learnings From A Pilot Hybrid Question Answering System: Cqas: Case Study Based On A Singapore Government Agency's Customer Service Centre, Hui Shan Lee, Shankararaman, Venky, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

The Singapore Government first released their digital government blueprint in 2018 with the key message for all their agencies to be "digital to the core and served with heart". With this push, agencies are moving towards human-centric digital services, especially for individual citizens. During COVID-19, Singapore government agencies introduced many COVID-19 digital initiatives resulting in more incoming inquiries from citizens to respective agencies. This surge in inquiries created the challenge on the agencies' end to meet service level agreements. One widely adopted solution is the use of chatbot technology that directly interfaces with the customer. However, several organisations have faced …

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Codem: Conditional Domain Embeddings For Scalable Human Activity Recognition, Abu Zaher Md Faridee, Avijoy Chakma, Zahid Hasan, Nirmalya Roy, Archan Misra Jun 2022

Codem: Conditional Domain Embeddings For Scalable Human Activity Recognition, Abu Zaher Md Faridee, Avijoy Chakma, Zahid Hasan, Nirmalya Roy, Archan Misra

Research Collection School Of Computing and Information Systems

We explore the effect of auxiliary labels in improving the classification accuracy of wearable sensor-based human activity recognition (HAR) systems, which are primarily trained with the supervision of the activity labels (e.g. running, walking, jumping). Supplemental meta-data are often available during the data collection process such as body positions of the wearable sensors, subjects' demographic information (e.g. gender, age), and the type of wearable used (e.g. smartphone, smart-watch). This information, while not directly related to the activity classification task, can nonetheless provide auxiliary supervision and has the potential to significantly improve the HAR accuracy by providing extra guidance on how …

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Multimodal Zero-Shot Hateful Meme Detection, Jiawen Zhu, Roy Ka-Wei Lee, Wen Haw Chong Jun 2022

Multimodal Zero-Shot Hateful Meme Detection, Jiawen Zhu, Roy Ka-Wei Lee, Wen Haw Chong

Research Collection School Of Computing and Information Systems

Facebook has recently launched the hateful meme detection challenge, which garnered much attention in academic and industry research communities. Researchers have proposed multimodal deep learning classification methods to perform hateful meme detection. While the proposed methods have yielded promising results, these classification methods are mostly supervised and heavily rely on labeled data that are not always available in the real-world setting. Therefore, this paper explores and aims to perform hateful meme detection in a zero-shot setting. Working towards this goal, we propose Target-Aware Multimodal Enhancement (TAME), which is a novel deep generative framework that can improve existing hateful meme classification …

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Simultaneous Energy Harvesting And Gait Recognition Using Piezoelectric Energy Harvester, Dong Ma, Guohao Lan, Weitao Xu, Mahbub Hassan, Wen Hu Jun 2022

Simultaneous Energy Harvesting And Gait Recognition Using Piezoelectric Energy Harvester, Dong Ma, Guohao Lan, Weitao Xu, Mahbub Hassan, Wen Hu

Research Collection School Of Computing and Information Systems

Piezoelectric energy harvester, which generates electricity from stress or vibrations, is gaining increasing attention as a viable solution to extend battery life in wearables. Recent research further reveals that, besides generating energy, PEH can also serve as a passive sensor to detect human gait power-efficiently because its stress or vibration patterns are significantly influenced by the gait. However, as PEHs are not designed for precise measurement of motion, achievable gait recognition accuracy remains low with conventional classification algorithms. The accuracy deteriorates further when the generated electricity is stored simultaneously. To classify gait reliably while simultaneously storing generated energy, we make …

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Promoting Infrastructure Construction In Advance To Support Sci-Tech Self-Reliance And Self-Strengthening At Higher Level, Yang Wang, Yuanchun Zhou, Yanguang Wang, Jianhui Li, Fazhi Qi, Honglin He, Fangyu Liao May 2022

Promoting Infrastructure Construction In Advance To Support Sci-Tech Self-Reliance And Self-Strengthening At Higher Level, Yang Wang, Yuanchun Zhou, Yanguang Wang, Jianhui Li, Fazhi Qi, Honglin He, Fangyu Liao

Bulletin of Chinese Academy of Sciences (Chinese Version)

The research infrastructure is the basic and strategic platform of scientific and technological innovation. In the last decade, China's research infrastructure has achieved leapfrog development in the level of observation, manufacturing, management, data acquisition, data sharing and utilization, which supports China's scientific and technological innovation activities at a higher level. Looking into the future, the scientific research paradigm is transforming. The network, data, and computing platform will not only support the development of major science and technology infrastructure and field stations in larger, more accurate, and more advanced approach, but also contribute to the transformation of scientific research paradigm. It …

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Information Provenance For Mobile Health Data, Taylor A. Hardin May 2022

Information Provenance For Mobile Health Data, Taylor A. Hardin

Dartmouth College Ph.D Dissertations

Mobile health (mHealth) apps and devices are increasingly popular for health research, clinical treatment and personal wellness, as they offer the ability to continuously monitor aspects of individuals' health as they go about their everyday activities. Many believe that combining the data produced by these mHealth apps and devices may give healthcare-related service providers and researchers a more holistic view of an individual's health, increase the quality of service, and reduce operating costs. For such mHealth data to be considered useful though, data consumers need to be assured that the authenticity and the integrity of the data has remained intact---especially …

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Prospects For Legal Analytics: Some Approaches To Extracting More Meaning From Legal Texts, Kevin D. Ashley May 2022

Prospects For Legal Analytics: Some Approaches To Extracting More Meaning From Legal Texts, Kevin D. Ashley

University of Cincinnati Law Review

No abstract provided.

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Performance Comparison Between Relational And Non-Relational Databases In Tcms, Ahmad Yousef Imam May 2022

Performance Comparison Between Relational And Non-Relational Databases In Tcms, Ahmad Yousef Imam

Honors Capstone Projects and Theses

No abstract provided.

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Visualcommunity: A Platform For Archiving And Studying Communities, Suphanut Jamonnak, Deepshikha Bhati, Md Amiruzzaman, Ye Zhao, Xinyue Ye, Andrew Curtis May 2022

Visualcommunity: A Platform For Archiving And Studying Communities, Suphanut Jamonnak, Deepshikha Bhati, Md Amiruzzaman, Ye Zhao, Xinyue Ye, Andrew Curtis

Computer Science Faculty Publications

VisualCommunity is a platform designed to support community or neighborhood scale research. The platform integrates mobile, AI, visualization techniques, along with tools to help domain researchers, practitioners, and students collecting and working with spatialized video and geo-narratives. These data, which provide granular spatialized imagery and associated context gained through expert commentary have previously provided value in understanding various community-scale challenges. This paper further enhances this work AI-based image processing and speech transcription tools available in VisualCommunity, allowing for the easy exploration of the acquired semantic and visual information about the area under investigation. In this paper we describe the specific …

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An Investigation Into, And The Construction Of, An Operable Windows Notifier, Grey Hixson May 2022

An Investigation Into, And The Construction Of, An Operable Windows Notifier, Grey Hixson

Computer Science and Computer Engineering Undergraduate Honors Theses

The Office of Sustainability at the University of Arkansas identified that building occupants that have control over operable windows may open them at inappropriate times. Windows opened in a building with a temperature and air differential leads to increased HVAC operating costs and building occupant discomfort. This led the Associate Vice Chancellor of Facilities at the University of Arkansas to propose the construction of a mobile application that a building occupant can use to make an informed decision before opening their window. I have formulated a series of research objectives in conjunction with the Director of the Office of Sustainability …

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Implementing The Cms+ Sports Rankings Algorithm In A Javafx Environment, Luke Welch May 2022

Implementing The Cms+ Sports Rankings Algorithm In A Javafx Environment, Luke Welch

Industrial Engineering Undergraduate Honors Theses

Every year, sports teams and athletes get cut from championship opportunities because of their rank. While this reality is easier to swallow if a team or athlete is distant from the cut, it is much harder when they are right on the edge. Many times, it leaves fans and athletes wondering, “Why wasn’t I ranked higher? What factors when into the ranking? Are the rankings based on opinion alone?” These are fair questions that deserve an answer. Many times, sports rankings are derived from opinion polls. Other times, they are derived from a combination of opinion polls and measured performance. …

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Mapping Salt-Affected Land In The South-West Of Western Australia Using Satellite Remote Sensing, P A. Caccetta, John A. Simons, S Furby, Nicholas J. Wright, Richard J. George Dr May 2022

Mapping Salt-Affected Land In The South-West Of Western Australia Using Satellite Remote Sensing, P A. Caccetta, John A. Simons, S Furby, Nicholas J. Wright, Richard J. George Dr

Natural resources published reports

Dryland salinity is a pervasive form of land degradation that has resulted from the clearing of about 17 M ha of native vegetation and the introduction of predominately cereal and pasture-based farming systems in the South-West of Western Australia. The change in water balance caused by clearing deep rooted endemic woodlands increased recharge and resulted in rising groundwater levels. After a lag period, the regolith began filling and groundwater approached the soil surface, evaporating and depositing stored salts in the rootzone of salt sensitive crops. Groundwater levels also rise and affect areas of remnant native vegetation, streams, wet-lands and rural …

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Chinese Idiom Understanding With Transformer-Based Pretrained Language Models, Minghuan Tan May 2022

Chinese Idiom Understanding With Transformer-Based Pretrained Language Models, Minghuan Tan

Dissertations and Theses Collection (Open Access)


In this dissertation, I study the understanding of Chinese idioms using transformer-based pretrained language models. By ``understanding", I confine the topics to word embeddings learning, contextualized word representations learning, multiple-choice cloze-test reading comprehension and conditional text generation. Chinese idioms are fixed phrases that have special meanings usually derived from an ancient story. The meanings of these idioms are oftentimes not directly related to their component characters, which makes it hard to model them compared with standard phrases whose meanings are compositional. We initiate the work with studying idiom representations derived from pretrained language models, in particular, BERT. We adopt probing-based …

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Practitioners' Expectations On Automated Code Comment Generation, Xing Hu, Xin Xia, David Lo, Zhiyuan Wan, Qiuyuan Chen, Thomas Zimmermann May 2022

Practitioners' Expectations On Automated Code Comment Generation, Xing Hu, Xin Xia, David Lo, Zhiyuan Wan, Qiuyuan Chen, Thomas Zimmermann

Research Collection School Of Computing and Information Systems

Good comments are invaluable assets to software projects, as they help developers understand and maintain projects. However, due to some poor commenting practices, comments are often missing or inconsistent with the source code. Software engineering practitioners often spend a significant amount of time and effort reading and understanding programs without or with poor comments. To counter this, researchers have proposed various techniques to automatically generate code comments in recent years, which can not only save developers time writing comments but also help them better understand existing software projects. However, it is unclear whether these techniques can alleviate comment issues and …

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Patient Centric Solutions To Mitigate Information Need Of Obstetric Ultrasound Exam Among Pregnant Women: Design-Thinking Approach, Eman Alanazi May 2022

Patient Centric Solutions To Mitigate Information Need Of Obstetric Ultrasound Exam Among Pregnant Women: Design-Thinking Approach, Eman Alanazi

Theses and Dissertations

Design thinking approach is an approach used widely to solve problems by providing innovative solutions. In this dissertation I focused on the user experience research filed where I designed new obstetric ultrasound reports by adopting the design thinking approach to reach the main goal of the dissertation which is mitigating pregnant women information needs about obstetric ultrasound exam and improve their understanding and knowledge about the obstetric ultrasound report and the exam. I developed two versions of new designed report called SPOUR (Smart Patient-Oriented Obstetric Ultrasound Report). We have conducted five studies to reach the dissertation goal and designed two …

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The Analysis Of User Characteristics On Twitter During Early Stage Of The Covid-19 Pandemic: A Comparison Study Before And After Declaration Of The Covid-19 Pandemic, Mutasim Alfadhel May 2022

The Analysis Of User Characteristics On Twitter During Early Stage Of The Covid-19 Pandemic: A Comparison Study Before And After Declaration Of The Covid-19 Pandemic, Mutasim Alfadhel

Theses and Dissertations

In December 2019, the coronavirus disease 2019 (Covid-19) was officially reported as an acute respiratory infection, which was first identified in Wuhan, China. On March 11th, 2020, the World Health Organization (WHO) declared that Covid-19 could be characterized as a pandemic. Governments across the world imposed or recommended various non-medical interventions to reduce transmission of Covid-19, such as washing hands, wearing face masks, social distancing, and quarantining as well as lockdown measures including banning large gatherings, issuing stay-at-home orders, closing certain businesses, and imposing travel restrictions. The increase in social, behavioral, and economic issues that the disease has generated has …

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Using A Bert-Based Ensemble Network For Abusive Language Detection, Noah Ballinger May 2022

Using A Bert-Based Ensemble Network For Abusive Language Detection, Noah Ballinger

Computer Science and Computer Engineering Undergraduate Honors Theses

Over the past two decades, online discussion has skyrocketed in scope and scale. However, so has the amount of toxicity and offensive posts on social media and other discussion sites. Despite this rise in prevalence, the ability to automatically moderate online discussion platforms has seen minimal development. Recently, though, as the capabilities of artificial intelligence (AI) continue to improve, the potential of AI-based detection of harmful internet content has become a real possibility. In the past couple years, there has been a surge in performance on tasks in the field of natural language processing, mainly due to the development of …

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College Of Education Filemaker Extraction And End-User Database Development, Andrew Tran May 2022

College Of Education Filemaker Extraction And End-User Database Development, Andrew Tran

Electronic Theses, Projects, and Dissertations

The College of Education (CoE) at the California State University San Bernardino (CSUSB) developed a system to keep track of both state and national accreditation requirements using FileMaker 5, a database system. This accreditation data is crucial for reporting and record-keeping for the CSU Chancellor’s Office as well as the State of California. However, the database system was developed several decades ago, and software support has long since been dropped, causing the CoE’s legacy accreditation data to be at risk of being lost should the software or hardware suffer permanent failure. The purpose of this project was to perform extraction …

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Context Modeling With Evidence Filter For Multiple Choice Question Answering, Sicheng Yu, Hao Zhang, Wei Jing, Jing Jiang May 2022

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 …

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Topic-Guided Conversational Recommender In Multiple Domains, Lizi Liao, Ryuichi Takanobu, Yunshan Ma, Xun Yang, Minlie Huang, Tat-Seng Chua May 2022

Topic-Guided Conversational Recommender In Multiple Domains, Lizi Liao, Ryuichi Takanobu, Yunshan Ma, Xun Yang, Minlie Huang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Conversational systems have recently attracted significant attention. Both the research community and industry believe that it will exert huge impact on human-computer interaction, and specifically, the IR/RecSys community has begun to explore Conversational Recommendation. In real-life scenarios, such systems are often urgently needed in helping users accomplishing different tasks under various situations. However, existing works still face several shortcomings: (1) Most efforts are largely confined in single task setting. They fall short of hands in handling tasks across domains. (2) Aside from soliciting user preference from dialogue history, a conversational recommender naturally has access to the back-end data structure which …

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Structure-Aware Visualization Retrieval, Haotian Li, Yong Wang, Aoyu Wu, Huan Wei, Huamin. Qu May 2022

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. …

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Natural Attack For Pre-Trained Models Of Code, Zhou Yang, Jieke Shi, Junda He, David Lo May 2022

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 …

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Who Will Support My Project? Interactive Search Of Potential Crowdfunding Investors Through Insearch., Songheng Zhang, Yong Wang, Haotian Li, Wanyu Zhang May 2022

Who Will Support My Project? Interactive Search Of Potential Crowdfunding Investors Through Insearch., Songheng Zhang, Yong Wang, Haotian Li, Wanyu Zhang

Research Collection School Of Computing and Information Systems

Crowdfunding provides project founders with a convenient way to reach online investors. However, it is challenging for founders to find the most potential investors and successfully raise money for their projects on crowdfunding platforms. A few machine learning based methods have been proposed to recommend investors’ interest in a specific crowdfunding project, but they fail to provide project founders with explanations in detail for these recommendations, thereby leading to an erosion of trust in predicted investors. To help crowdfunding founders find truly interested investors, we conducted semi-structured interviews with four crowdfunding experts and presentsinSearch, a visual analytic system. inSearch allows …

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Rumorlens: Interactive Analysis And Validation Of Suspected Rumors On Social Media, Ran Wang, Kehan Du, Qianhe Chen, Yifei Zhao, Mojie Tang, Hongxi Tao, Shipan Wang, Yiyao Li, Yong Wang May 2022

Rumorlens: Interactive Analysis And Validation Of Suspected Rumors On Social Media, Ran Wang, Kehan Du, Qianhe Chen, Yifei Zhao, Mojie Tang, Hongxi Tao, Shipan Wang, Yiyao Li, Yong Wang

Research Collection School Of Computing and Information Systems

With the development of social media, various rumors can be easily spread on the Internet and such rumors can have serious negative effects on society. Thus, it has become a critical task for social media platforms to deal with suspected rumors. However, due to the lack of effective tools, it is often difficult for platform administrators to analyze and validate rumors from a large volume of information on a social media platform efficiently. We have worked closely with social media platform administrators for four months to summarize their requirements of identifying and analyzing rumors, and further proposed an interactive visual …

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Simple Or Complex? Together For A More Accurate Just-In-Time Defect Predictor, Xin Zhou, Donggyun Han, David Lo May 2022

Simple Or Complex? Together For A More Accurate Just-In-Time Defect Predictor, Xin Zhou, Donggyun Han, David Lo

Research Collection School Of Computing and Information Systems

Just-In-Time (JIT) defect prediction aims to automatically predict whether a commit is defective or not, and has been widely studied in recent years. In general, most studies can be classified into two categories: 1) simple models using traditional machine learning classifiers with hand-crafted features, and 2) complex models using deep learning techniques to automatically extract features. Hand-crafted features used by simple models are based on expert knowledge but may not fully represent the semantic meaning of the commits. On the other hand, deep learning-based features used by complex models represent the semantic meaning of commits but may not reflect useful …

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Arseek: Identifying Api Resource Using Code And Discussion On Stack Overflow, Gia Kien Luong, Mohammad Hadi, Thung Ferdian, Fatemeh H. Fard, David Lo May 2022

Arseek: Identifying Api Resource Using Code And Discussion On Stack Overflow, Gia Kien Luong, Mohammad Hadi, Thung Ferdian, Fatemeh H. Fard, David Lo

Research Collection School Of Computing and Information Systems

It is not a trivial problem to collect API-relevant examples, usages, and mentions on venues such as Stack Overflow. It requires efforts to correctly recognize whether the discussion refers to the API method that developers/tools are searching for. The content of the Stack Overflow thread, which consists of both text paragraphs describing the involvement of the API method in the discussion and the code snippets containing the API invocation, may refer to the given API method. Leveraging this observation, we develop ARSeek, a context-specific algorithm to capture the semantic and syntactic information of the paragraphs and code snippets in a …

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On The Transferability Of Pre-Trained Language Models For Low-Resource Programming Languages, Fuxiang Chen, Fatemeh H. Fard, David Lo, Timofey Bryksin May 2022

On The Transferability Of Pre-Trained Language Models For Low-Resource Programming Languages, Fuxiang Chen, Fatemeh H. Fard, David Lo, Timofey Bryksin

Research Collection School Of Computing and Information Systems

A recent study by Ahmed and Devanbu reported that using a corpus of code written in multilingual datasets to fine-tune multilingual Pre-trained Language Models (PLMs) achieves higher performance as opposed to using a corpus of code written in just one programming language. However, no analysis was made with respect to fine-tuning monolingual PLMs. Furthermore, some programming languages are inherently different and code written in one language usually cannot be interchanged with the others, i.e., Ruby and Java code possess very different structure. To better understand how monolingual and multilingual PLMs affect different programming languages, we investigate 1) the performance of …

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Unified Route Planning For Shared Mobility: An Insertion-Based Framework, Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Lei Chen, Ke. Xu May 2022

Unified Route Planning For Shared Mobility: An Insertion-Based Framework, Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Lei Chen, Ke. Xu

Research Collection School Of Computing and Information Systems

There has been a dramatic growth of shared mobility applications such as ride-sharing, food delivery, and crowdsourced parcel delivery. Shared mobility refers to transportation services that are shared among users, where a central issue is route planning. Given a set of workers and requests, route planning finds for each worker a route, i.e., a sequence of locations to pick up and drop off passengers/parcels that arrive from time to time, with different optimization objectives. Previous studies lack practicability due to their conflicted objectives and inefficiency in inserting a new request into a route, a basic operation called insertion. In addition, …

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