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Articles 751 - 780 of 2149
Full-Text Articles in Software Engineering
Prediction Of Nocturia In Live Alone Elderly Using Unobtrusive In-Home Sensors, Barry Nuqoba, Hwee-Pink Tan
Prediction Of Nocturia In Live Alone Elderly Using Unobtrusive In-Home Sensors, Barry Nuqoba, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Nocturia, or the need to void (or urinate) one or more times in the middle of night time sleeping, represents a significant economic burden for individuals and healthcare systems. Although it can be diagnosed in the hospital, most people tend to regard nocturia as a usual event, resulting in underreported diagnosis and treatment. Data from self-reporting via a voiding diary may be irregular and subjective especially among the elderly due to memory problems. This study aims to detect the presence of nocturia through passive in-home monitoring to inform intervention (e.g., seeking diagnosis and treatment) to improve the physical and mental …
Adelaidecyc At Semeval-2020 Task 12: Ensemble Of Classifiers For Offensive Language Detection In Social Media, Mahen Herath, Thushari Atapattu, Hoang Anh Dung, Christoph Treude, Katrina Falkner
Adelaidecyc At Semeval-2020 Task 12: Ensemble Of Classifiers For Offensive Language Detection In Social Media, Mahen Herath, Thushari Atapattu, Hoang Anh Dung, Christoph Treude, Katrina Falkner
Research Collection School Of Computing and Information Systems
This paper describes the systems our team (AdelaideCyC) has developed for SemEval Task 12 (OffensEval 2020) to detect offensive language in social media. The challenge focuses on three subtasks – offensive language identification (subtask A), offense type identification (subtask B), and offense target identification (subtask C). Our team has participated in all the three subtasks. We have developed machine learning and deep learning-based ensembles of models. We have achieved F1-scores of 0.906, 0.552, and 0.623 in subtask A, B, and C respectively. While our performance scores are promising for subtask A, the results demonstrate that subtask B and C still …
Robust, Fine-Grained Occupancy Estimation Via Combined Camera & Wifi Indoor Localization, Anuradha Ravi, Archan Misra
Robust, Fine-Grained Occupancy Estimation Via Combined Camera & Wifi Indoor Localization, Anuradha Ravi, Archan Misra
Research Collection School Of Computing and Information Systems
We describe the development of a robust, accurate and practically-validated technique for estimating the occupancy count in indoor spaces, based on a combination of WiFi & video sensing. While fusing these two sensing-based inputs is conceptually straightforward, the paper demonstrates and tackles the complexity that arises from several practical artefacts, such as (i) over-counting when a single individual uses multiple WiFi devices and under-counting when the individual has no such device; (ii) corresponding errors in image analysis due to real-world artefacts, such as occlusion, and (iii) the variable errors in mapping image bounding boxes (which can include multiple possible types …
Jointly Optimizing Sensing Pipelines For Multimodal Mixed Reality Interaction, Darshana Rathnayake, Ashen De Silva, Dasun Puwakdandawa, Lakmal Meegahapola, Archan Misra, Indika Perera
Jointly Optimizing Sensing Pipelines For Multimodal Mixed Reality Interaction, Darshana Rathnayake, Ashen De Silva, Dasun Puwakdandawa, Lakmal Meegahapola, Archan Misra, Indika Perera
Research Collection School Of Computing and Information Systems
Natural human interactions for Mixed Reality Applications are overwhelmingly multimodal: humans communicate intent and instructions via a combination of visual, aural and gestural cues. However, supporting low-latency and accurate comprehension of such multimodal instructions (MMI), on resource-constrained wearable devices, remains an open challenge, especially as the state-of-the-art comprehension techniques for each individual modality increasingly utilize complex Deep Neural Network models. We demonstrate the possibility of overcoming the core limitation of latency--vs.--accuracy tradeoff by exploiting cross-modal dependencies -- i.e., by compensating for the inferior performance of one model with an increased accuracy of more complex model of a different modality. We …
Effort-Aware Just-In-Time Defect Identification In Practice: A Case Study At Alibaba, Meng Yan, Xin Xia, Yuanrui Fan, David Lo, Ahmed E. Hassan, Xindong Zhang
Effort-Aware Just-In-Time Defect Identification In Practice: A Case Study At Alibaba, Meng Yan, Xin Xia, Yuanrui Fan, David Lo, Ahmed E. Hassan, Xindong Zhang
Research Collection School Of Computing and Information Systems
Effort-aware Just-in-Time (JIT) defect identification aims at identifying defect-introducing changes just-in-time with limited code inspection effort. Such identification has two benefits compared with traditional module-level defect identification, i.e., identifying defects in a more cost-effective and efficient manner. Recently, researchers have proposed various effort-aware JIT defect identification approaches, including supervised (e.g., CBS+, OneWay) and unsupervised approaches (e.g., LT and Code Churn). The comparison of the effectiveness between such supervised and unsupervised approaches has attracted a large amount of research interest. However, the effectiveness of the recently proposed approaches and the comparison among them have never been investigated in an industrial setting.In …
Bugsinpy: A Database Of Existing Bugs In Python Programs To Enable Controlled Testing And Debugging Studies, Ratnadira Widyasari, Sheng Qin Sim, Camellia Lok, Haodi Qi, Jack Phan, Qijin Tay, Constance Tan, Fiona Wee, Jodie Ethelda Tan, Yuheng Yieh, Brian Goh, Ferdian Thung, Hong Jin Kang, Thong Hoang, David Lo, Eng Lieh Ouh
Bugsinpy: A Database Of Existing Bugs In Python Programs To Enable Controlled Testing And Debugging Studies, Ratnadira Widyasari, Sheng Qin Sim, Camellia Lok, Haodi Qi, Jack Phan, Qijin Tay, Constance Tan, Fiona Wee, Jodie Ethelda Tan, Yuheng Yieh, Brian Goh, Ferdian Thung, Hong Jin Kang, Thong Hoang, David Lo, Eng Lieh Ouh
Research Collection School Of Computing and Information Systems
The 2019 edition of Stack Overflow developer survey highlights that, for the first time, Python outperformed Java in terms of popularity. The gap between Python and Java further widened in the 2020 edition of the survey. Unfortunately, despite the rapid increase in Python's popularity, there are not many testing and debugging tools that are designed for Python. This is in stark contrast with the abundance of testing and debugging tools for Java. Thus, there is a need to push research on tools that can help Python developers.One factor that contributed to the rapid growth of Java testing and debugging tools …
Deepcommenter: A Deep Code Comment Generation Tool With Hybrid Lexical And Syntactical Information, Boao Li, Meng Yan, Xin Xia, Xing Hu, Ge Li, David Lo
Deepcommenter: A Deep Code Comment Generation Tool With Hybrid Lexical And Syntactical Information, Boao Li, Meng Yan, Xin Xia, Xing Hu, Ge Li, David Lo
Research Collection School Of Computing and Information Systems
As the scale of software projects increases, the code comments are more and more important for program comprehension. Unfortunately, many code comments are missing, mismatched or outdated due to tight development schedule or other reasons. Automatic code comment generation is of great help for developers to comprehend source code and reduce their workload. Thus, we propose a code comment generation tool (DeepCommenter) to generate descriptive comments for Java methods. DeepCommenter formulates the comment generation task as a machine translation problem and exploits a deep neural network that combines the lexical and structural information of Java methods. We implement DeepCommenter in …
Semi-Analytical Model For Design And Analysis Of On-Orbit Servicing Architecture, Koki Ho, Hai Wang, Paul A. De Trempe, Tristan Sarton Du Jonchay, Kento Tomita
Semi-Analytical Model For Design And Analysis Of On-Orbit Servicing Architecture, Koki Ho, Hai Wang, Paul A. De Trempe, Tristan Sarton Du Jonchay, Kento Tomita
Research Collection School Of Computing and Information Systems
Robotic on-orbit servicing (OOS) is expected to be a key technology and concept for future sustainable space exploration. This paper develops a novel semi-analytical model for OOS system analysis, responding to the growing needs and ongoing trend of robotic OOS. An OOS infrastructure system is considered whose goal is to provide responsive services to the random failures of a set of customer modular satellites distributed in space (e.g., at the geosynchronous orbit). The considered OOS architecture comprises a servicer that travels and provides module-replacement services to the customer satellites, an on-orbit depot to store the spares, and a series of …
Reducing Estimation Bias Via Triplet-Average Deep Deterministic Policy Gradient, Dongming Wu, Xingping Dong, Jianbing Shen, Steven C. H. Hoi
Reducing Estimation Bias Via Triplet-Average Deep Deterministic Policy Gradient, Dongming Wu, Xingping Dong, Jianbing Shen, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
The overestimation caused by function approximation is a well-known property in Q-learning algorithms, especially in single-critic models, which leads to poor performance in practical tasks. However, the opposite property, underestimation, which often occurs in Q-learning methods with double critics, has been largely left untouched. In this article, we investigate the underestimation phenomenon in the recent twin delay deep deterministic actor-critic algorithm and theoretically demonstrate its existence. We also observe that this underestimation bias does indeed hurt performance in various experiments. Considering the opposite properties of single-critic and double-critic methods, we propose a novel triplet-average deep deterministic policy gradient algorithm that …
An Empirical Study Of Release Note Production And Usage In Practice, Tingting Bi, Xin Xia, David Lo, John Grundy, Thomas Zimmermann
An Empirical Study Of Release Note Production And Usage In Practice, Tingting Bi, Xin Xia, David Lo, John Grundy, Thomas Zimmermann
Research Collection School Of Computing and Information Systems
The release note is one of the most important software artifacts that serves as a bridge for communication among stakeholders. Release notes contain a set of crucial information, such as descriptions of enhancements, improvements, potential issues, development, evolution, testing, and maintenance of projects throughout the whole development lifestyle. A comprehensive understanding of what makes a good release note and how to write one for different stakeholders would be highly beneficial. However, in practice, the release note is often neglected by stakeholders and has not to date been systematically investigated by researchers. In this paper, we conduct a mixed methods study …
Coinwatch: A Clone-Based Approach For Detecting Vulnerabilities In Cryptocurrencies, Qingze Hum, Wei Jin Tan, Shi Ying Tey, Latasha Lenus, Ivan Homoliak, Yun Lin, Jun Sun
Coinwatch: A Clone-Based Approach For Detecting Vulnerabilities In Cryptocurrencies, Qingze Hum, Wei Jin Tan, Shi Ying Tey, Latasha Lenus, Ivan Homoliak, Yun Lin, Jun Sun
Research Collection School Of Computing and Information Systems
Cryptocurrencies have become very popular in recent years. Thousands of new cryptocurrencies have emerged, proposing new and novel techniques that improve on Bitcoin's core innovation of the blockchain data structure and consensus mechanism. However, cryptocurrencies are a major target for cyber-attacks, as they can be sold on exchanges anonymously and most cryptocurrencies have their codebases publicly available. One particular issue is the prevalence of code clones in cryptocurrencies, which may amplify security threats. If a vulnerability is found in one cryptocurrency, it might be propagated into other cloned cryptocurrencies. In this work, we propose a systematic remedy to this problem, …
Perceptions, Expectations, And Challenges In Defect Prediction, Zhiyuan Wan, Xin Xia, Ahmed E. Hassan, David Lo, Jianwei Yin, Xiaohu Yang
Perceptions, Expectations, And Challenges In Defect Prediction, Zhiyuan Wan, Xin Xia, Ahmed E. Hassan, David Lo, Jianwei Yin, Xiaohu Yang
Research Collection School Of Computing and Information Systems
Defect prediction has been an active research area for over four decades. Despite numerous studies on defect prediction, the potential value of defect prediction in practice remains unclear. To address this issue, we performed a mixed qualitative and quantitative study to investigate what practitioners think, behave and expect in contrast to research findings when it comes to defect prediction. We collected hypotheses from open-ended interviews and a literature review, followed by a validation survey. We received 395 responses from practitioners. Some of our key findings include: 1) Over 90% of respondents are willing to adopt defect prediction techniques. 2) There …
Machine Learning Integrated Design For Additive Manufacturing, Jingchao Jiang, Yi Xiong, Zhiyuan Zhang, David W. Rosen
Machine Learning Integrated Design For Additive Manufacturing, Jingchao Jiang, Yi Xiong, Zhiyuan Zhang, David W. Rosen
Research Collection School Of Computing and Information Systems
For improving manufacturing efficiency and minimizing costs, design for additive manufacturing (AM) has been accordingly proposed. The existing design for AM methods are mainly surrogate model based. Due to the increasingly available data nowadays, machine learning (ML) has been applied to medical diagnosis, image processing, prediction, classification, learning association, etc. A variety of studies have also been carried out to use machine learning for optimizing the process parameters of AM with corresponding objectives. In this paper, a ML integrated design for AM framework is proposed, which takes advantage of ML that can learn the complex relationships between the design and …
A Theory Of The Engagement In Open Source Projects Via Summer Of Code Programs, Jefferson Silva, Igor Wiese, Daniel M. German, Christoph Treude, Marco A. Gerosa, Igor Steinmacher
A Theory Of The Engagement In Open Source Projects Via Summer Of Code Programs, Jefferson Silva, Igor Wiese, Daniel M. German, Christoph Treude, Marco A. Gerosa, Igor Steinmacher
Research Collection School Of Computing and Information Systems
Summer of code programs connect students to open source software (OSS) projects, typically during the summer break from school. Analyzing consolidated summer of code programs can reveal how college students, who these programs usually target, can be motivated to participate in OSS, and what onboarding strategies OSS communities adopt to receive these students. In this paper, we study the well-established Google Summer of Code (GSoC) and devise an integrated engagement theory grounded in multiple data sources to explain motivation and onboarding in this context. Our analysis shows that OSS communities employ several strategies for planning and executing student participation, socially …
Beyond Accuracy: Assessing Software Documentation Quality, Christoph Treude, Justin Middleton, Thushari Atapattu
Beyond Accuracy: Assessing Software Documentation Quality, Christoph Treude, Justin Middleton, Thushari Atapattu
Research Collection School Of Computing and Information Systems
Good software documentation encourages good software engineering, but the meaning of “good” documentation is vaguely defined in the software engineering literature. To clarify this ambiguity, we draw on work from the data and information quality community to propose a framework that decomposes documentation quality into ten dimensions of structure, content, and style. To demonstrate its application, we recruited technical editors to apply the framework when evaluating examples from several genres of software documentation. We summarise their assessments—for example, reference documentation and README files excel in quality whereas blog articles have more problems—and we describe our vision for reasoning about software …
Api Method Recommendation Via Explicit Matching Of Functionality Verb Phrases, Wenkai Xie, Xin Peng, Mingwei Liu, Christoph Treude, Zhenchang Xing, Xiaoxin Zhang, Wenyun Zhao
Api Method Recommendation Via Explicit Matching Of Functionality Verb Phrases, Wenkai Xie, Xin Peng, Mingwei Liu, Christoph Treude, Zhenchang Xing, Xiaoxin Zhang, Wenyun Zhao
Research Collection School Of Computing and Information Systems
Due to the lexical gap between functionality descriptions and user queries, documentation-based API retrieval often produces poor results. Verb phrases and their phrase patterns are essential in both describing API functionalities and interpreting user queries. Thus we hypothesize that API retrieval can be facilitated by explicitly recognizing and matching between the fine-grained structures of functionality descriptions and user queries. To verify this hypothesis, we conducted a large-scale empirical study on the functionality descriptions of 14,733 JDK and Android API methods. We identified 356 different functionality verbs from the descriptions, which were grouped into 87 functionality categories, and we extracted 523 …
Deep-Learning-Based App Sensitive Behavior Surveillance For Android Powered Cyber-Physical Systems, Haoyu Ma, Jianwen Tian, Kefan Qiu, David Lo, Debin Gao, Daoyuan Wu, Chunfu Jia, Thar Baker
Deep-Learning-Based App Sensitive Behavior Surveillance For Android Powered Cyber-Physical Systems, Haoyu Ma, Jianwen Tian, Kefan Qiu, David Lo, Debin Gao, Daoyuan Wu, Chunfu Jia, Thar Baker
Research Collection School Of Computing and Information Systems
Android as an operating system is now increasingly being adopted in industrial information systems, especially with Cyber-Physical Systems (CPS). This also puts Android devices onto the front line of handling security-related data and conducting sensitive behaviors, which could be misused by the increasing number of polymorphic and metamorphic malicous applications targeting the platform. The existence of such malware threats therefore call for more accurate identification and surveillance of sensitive Android app behaviors, which is essential to the security of CPS and IoT devices powered by Android. Nevertheless, achieving dynamic app behavior monitoring and identification on real CPS powered by Android …
Jito: A Tool For Just-In-Time Defect Identification And Localization, Fangcheng Qiu, Meng Yan, Xin Xia, Xinyu Wang, Yuanrui Fan, Ahmed E. Hassan, David Lo
Jito: A Tool For Just-In-Time Defect Identification And Localization, Fangcheng Qiu, Meng Yan, Xin Xia, Xinyu Wang, Yuanrui Fan, Ahmed E. Hassan, David Lo
Research Collection School Of Computing and Information Systems
In software development and maintenance, defect localization is necessary for software quality assurance. Current defect localization techniques mainly rely on defect symptoms (e.g., bug reports or program spectrum) when the defect has been exposed. One challenge task is: can we locate buggy program prior to the appearance of the defect symptom. Such kind of localization is conducted at an early stage (e.g., when buggy program elements are being checkedin) which can be an early step of continuous quality control.In this paper, we propose a Just-In-Time defect identification and lOcalization tool, named JITO, which can help developers to locate defective lines …
Enhancing Developer Interactions With Programming Screencasts Through Accurate Code Extraction, Lingfeng Bao, Shengyi Pan, Zhenchang Xing, Xin Xia, David Lo, Xiaohu Yang
Enhancing Developer Interactions With Programming Screencasts Through Accurate Code Extraction, Lingfeng Bao, Shengyi Pan, Zhenchang Xing, Xin Xia, David Lo, Xiaohu Yang
Research Collection School Of Computing and Information Systems
Programming screencasts have become a pervasive resource on the Internet, which is favoured by many developers for learning new programming skills. For developers, the source code in screencasts is valuable and important. However, the streaming nature of screencasts limits the choice that they have for interacting with the code. Many studies apply the Optical Character Recognition (OCR) technique to convert screen images into text, which can be easily searched and indexed. However, we observe that the noise in the screen images significantly affects the quality of OCRed code.In this paper, we develop a tool named psc2code, which has two components, …
Erica: Enabling Real-Time Mistake Detection And Corrective Feedback For Free-Weights Exercises, Meeralakshmi Radhakrishnan, Darshana Rathnayake, Koon Han Ong, Inseok Hwang, Archan Misra
Erica: Enabling Real-Time Mistake Detection And Corrective Feedback For Free-Weights Exercises, Meeralakshmi Radhakrishnan, Darshana Rathnayake, Koon Han Ong, Inseok Hwang, Archan Misra
Research Collection School Of Computing and Information Systems
We present ERICA, a digital personal trainer for users performing free weights exercises, with two key differentiators: (a) First, unlike prior approaches that either require multiple on-body wearables or specialized infrastructural sensing, ERICA uses a single in-ear "earable" device (piggybacking on a form factor routinely used by millions of gym-goers) and a simple inertial sensor mounted on each weight equipment; (b) Second, unlike prior work that focuses primarily on quantifying a workout, ERICA additionally identifies a variety of fine-grained exercising mistakes and delivers real-time, in-situ corrective instructions. To achieve this, we (a) design a robust approach for user-equipment association that …
Sfuzz: An Efficient Adaptive Fuzzer For Solidity Smart Contracts, Tai D. Nguyen, Long H. Pham, Jun Sun, Yun Lin, Minh Quang Tran
Sfuzz: An Efficient Adaptive Fuzzer For Solidity Smart Contracts, Tai D. Nguyen, Long H. Pham, Jun Sun, Yun Lin, Minh Quang Tran
Research Collection School Of Computing and Information Systems
Smart contracts are Turing-complete programs that execute on the infrastructure of the blockchain, which often manage valuable digital assets. Solidity is one of the most popular programming languages for writing smart contracts on the Ethereum platform. Like traditional programs, smart contracts may contain vulnerabilities. Unlike traditional programs, smart contracts cannot be easily patched once they are deployed. It is thus important that smart contracts are tested thoroughly before deployment. In this work, we present an adaptive fuzzer for smart contracts on the Ethereum platform called sFuzz. Compared to existing Solidity fuzzers, sFuzz combines the strategy in the AFL fuzzer and …
Selecting Third-Party Libraries: The Practitioners' Perspective, Enrique Larios Vargas, Maurício Aniche, Christoph Treude, Magiel Bruntink, Georgios Gousios
Selecting Third-Party Libraries: The Practitioners' Perspective, Enrique Larios Vargas, Maurício Aniche, Christoph Treude, Magiel Bruntink, Georgios Gousios
Research Collection School Of Computing and Information Systems
The selection of third-party libraries is an essential element of virtually any software development project. However, deciding which libraries to choose is a challenging practical problem. Selecting the wrong library can severely impact a software project in terms of cost, time, and development effort, with the severity of the impact depending on the role of the library in the software architecture, among others. Despite the importance of following a careful library selection process, in practice, the selection of third-party libraries is still conducted in an ad-hoc manner, where dozens of factors play an influential role in the decision. In this …
Viscene: A Collaborative Authoring Tool For Scene Descriptions In Videos, Rosiana Natalie, Ebrima Jarjue, Hernisa Kacorri, Kotaro Hara
Viscene: A Collaborative Authoring Tool For Scene Descriptions In Videos, Rosiana Natalie, Ebrima Jarjue, Hernisa Kacorri, Kotaro Hara
Research Collection School Of Computing and Information Systems
Audio descriptions can make the visual content in videos accessible to people with visual impairments. However, the majority of the online videos lack audio descriptions due in part to the shortage of experts who can create high-quality descriptions. We present ViScene, a web-based authoring tool that taps into the larger pool of sighted non-experts to help them generate high-quality descriptions via two feedback mechanisms - succinct visualizations and comments from an expert. Through a mixed-design study with N = 6 participants, we explore the usability of ViScene and the quality of the descriptions created by sighted non-experts with and without …
Livesnippets: Voice-Based Live Authoring Of Multimedia Articles About Experiences, Hyeongcheol Kim, Shengdong Zhao, Can Liu, Kotaro Hara
Livesnippets: Voice-Based Live Authoring Of Multimedia Articles About Experiences, Hyeongcheol Kim, Shengdong Zhao, Can Liu, Kotaro Hara
Research Collection School Of Computing and Information Systems
We transform traditional experience writing into in-situ voice-based multimedia authoring. Documenting experiences digitally in blogs and journals is a common activity that allows people to socially connect with others by sharing their experiences (e.g. travelogue). However, documenting such experiences can be time-consuming and cognitively demanding as it is typically done OUT-OF-CONTEXT (after the actual experience). We propose in-situ voice-based multimedia authoring (IVA), an alternative workflow to allow IN-CONTEXT experience documentation. Unlike the traditional approach, IVA encourages in-context content creations using voice-based multimedia input and stores them in multi-modal "snippets". The snippets can be rearranged to form multimedia articles and can …
Iot-Enabled Community Care For Ageing-In-Place: The Singapore Experience, Hwee-Pink Tan
Iot-Enabled Community Care For Ageing-In-Place: The Singapore Experience, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
The paradigm of ageing-in-place – where the elderly live and age in their own homes, independently and safely, with care provided by the community – is compelling, especially in societies that face both shortages in institutionalized eldercare resources, and rapidly ageing populations. When the number of elderly who live alone rises rapidly, support and care from their communities become increasing crucial. Internet of Things (IoT) technologies. They can become the fundamental enabler for smart community eldercare. In this presentation, I would like to share our experiences and learnings gathered from large-scale deployments of IoT systems in in-home and community spaces …
Hysia: Serving Dnn-Based Video-To-Retail Applications In Cloud, Huaizheng Zhang, Yuanming Li, Qiming Ai, Yong Luo, Yonggang Wen, Yichao Jin, Nguyen Binh Duong Ta
Hysia: Serving Dnn-Based Video-To-Retail Applications In Cloud, Huaizheng Zhang, Yuanming Li, Qiming Ai, Yong Luo, Yonggang Wen, Yichao Jin, Nguyen Binh Duong Ta
Research Collection School Of Computing and Information Systems
Combining video streaming and online retailing (V2R) has been a growing trend recently. In this paper, we provide practitioners and researchers in multimedia with a cloud-based platform named Hysia for easy development and deployment of V2R applications. The system consists of: 1) a back-end infrastructure providing optimized V2R related services including data engine, model repository, model serving and content matching; and 2) an application layer which enables rapid V2R application prototyping. Hysia addresses industry and academic needs in large-scale multimedia by: 1) seamlessly integrating state-of-the-art libraries including NVIDIA video SDK, Facebook faiss, and gRPC; 2) efficiently utilizing GPU computation; and …
White-Box Fairness Testing Through Adversarial Sampling, Peixin Zhang, Jingyi Wang, Jun Sun, Guoliang Dong, Xinyu Wang, Xingen Wang, Jin Song Dong, Dai Ting
White-Box Fairness Testing Through Adversarial Sampling, Peixin Zhang, Jingyi Wang, Jun Sun, Guoliang Dong, Xinyu Wang, Xingen Wang, Jin Song Dong, Dai Ting
Research Collection School Of Computing and Information Systems
Although deep neural networks (DNNs) have demonstrated astonishing performance in many applications, there are still concerns on their dependability. One desirable property of DNN for applications with societal impact is fairness (i.e., non-discrimination). In this work, we propose a scalable approach for searching individual discriminatory instances of DNN. Compared with state-of-the-art methods, our approach only employs lightweight procedures like gradient computation and clustering, which makes it significantly more scalable than existing methods. Experimental results show that our approach explores the search space more effectively (9 times) and generates much more individual discriminatory instances (25 times) using much less time (half …
Efficient Ciphertext-Policy Attribute-Based Encryption With Blackbox Traceability, Shengmin Xu, Jiaming Yuan, Guowen Xu, Yingjiu Li, Ximeng Liu, Yinghui Zhang, Zuobin Yang
Efficient Ciphertext-Policy Attribute-Based Encryption With Blackbox Traceability, Shengmin Xu, Jiaming Yuan, Guowen Xu, Yingjiu Li, Ximeng Liu, Yinghui Zhang, Zuobin Yang
Research Collection School Of Computing and Information Systems
Traitor tracing scheme is a paradigm to classify the users who illegal use of their decryption keys in cryptosystems. In the ciphertext-policy attribute-based cryptosystem, the decryption key usually contains the users’ attributes, while the real identities are hidden. The decryption key with hidden identities enables malicious users to intentionally leak decryption keys or embed the decryption keys in the decryption device to gain illegal profits with a little risk of being discovered. To mitigate this problem, the concept of blackbox traceability in the ciphertext-policy attribute-based scheme was proposed to identify the malicious user via observing the I/O streams of the …
Zoomwalls: Dynamic Walls That Simulate Haptic Infrastructure For Room-Scale Vr World, Yan Yixian, Kazuki Takashima, Anthony Tang, Takayuki Tanno, Kazuyuki Fujita, Yoshifumi Kitamura
Zoomwalls: Dynamic Walls That Simulate Haptic Infrastructure For Room-Scale Vr World, Yan Yixian, Kazuki Takashima, Anthony Tang, Takayuki Tanno, Kazuyuki Fujita, Yoshifumi Kitamura
Research Collection School Of Computing and Information Systems
We focus on the problem of simulating the haptic infrastructure of a virtual environment (i.e. walls, doors). Our approach relies on multiple ZoomWalls---autonomous robotic encounter-type haptic wall-shaped props---that coordinate to provide haptic feedback for room-scale virtual reality. Based on a user's movement through the physical space, ZoomWall props are coordinated through a predict-and-dispatch architecture to provide just-in-time haptic feedback for objects the user is about to touch. To refine our system, we conducted simulation studies of different prediction algorithms, which helped us to refine our algorithmic approach to realize the physical ZoomWall prototype. Finally, we evaluated our system through a …
Experience Report On The Use Of Technology To Manage Capstone Course Projects, Benjamin Gan, Eng Lieh Ouh
Experience Report On The Use Of Technology To Manage Capstone Course Projects, Benjamin Gan, Eng Lieh Ouh
Research Collection School Of Computing and Information Systems
This full paper presents an experience report describing lessons learnt from innovative practice use of technologies in an undergraduate computing capstone course. At our school, around fifty-five teams comprising of around 300 students take this course every year. With fifty-five teams, we needed a system to schedule presentations; improve communications; collaborate between stakeholders; share knowledge; monitor progress; team up students; match students to projects; improve grading process; showcase posters; and track improvements using analytics. The Learning Management Systems (LMS) is great to manage course content and grade submission. On the other hand, students are required to conduct agile sprint reviews …