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Articles 2491 - 2520 of 8597
Full-Text Articles in Entire DC Network
Face To Purchase: Predicting Consumer Choices With Structured Facial And Behavioral Traits Embedding, Zhe Liu, Xianzhi Wang, Lina Yao, Jake An, Lei Bai, Ee-Peng Lim
Face To Purchase: Predicting Consumer Choices With Structured Facial And Behavioral Traits Embedding, Zhe Liu, Xianzhi Wang, Lina Yao, Jake An, Lei Bai, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Predicting consumers’ purchasing behaviors is critical for targeted advertisement and sales promotion in e-commerce. Human faces are an invaluable source of information for gaining insights into consumer personality and behavioral traits. However, consumer's faces are largely unexplored in previous research, and the existing face-related studies focus on high-level features such as personality traits while neglecting the business significance of learning from facial data. We propose to predict consumers’ purchases based on their facial features and purchasing histories. We design a semi-supervised model based on a hierarchical embedding network to extract high-level features of consumers and to predict the top-N purchase …
Just-In-Time Defect Prediction On Javascript Projects: A Replication Study, Chao Ni, Xin Xia, David Lo, Xiaohu Yang, Ahmed E. Hassan
Just-In-Time Defect Prediction On Javascript Projects: A Replication Study, Chao Ni, Xin Xia, David Lo, Xiaohu Yang, Ahmed E. Hassan
Research Collection School Of Computing and Information Systems
Change-level defect prediction is widely referred to as just-in-time (JIT) defect prediction since it identifies a defect-inducing change at the check-in time, and researchers have proposed many approaches based on the language-independent change-level features. These approaches can be divided into two types: supervised approaches and unsupervised approaches, and their effectiveness has been verified on Java or C++ projects. However, whether the language-independent change-level features can effectively identify the defects of JavaScript projects is still unknown. Additionally, many researches have confirmed that supervised approaches outperform unsupervised approaches on Java or C++ projects when considering inspection effort. However, whether supervised JIT defect …
Automating App Review Response Generation Based On Contextual Knowledge, Cuiyun Gao, Wenjie Zhou, Xin Xia, David Lo, Qi Xie, Michael R. Lyu
Automating App Review Response Generation Based On Contextual Knowledge, Cuiyun Gao, Wenjie Zhou, Xin Xia, David Lo, Qi Xie, Michael R. Lyu
Research Collection School Of Computing and Information Systems
User experience of mobile apps is an essential ingredient that can influence the user base and app revenue. To ensure good user experience and assist app development, several prior studies resort to analysis of app reviews, a type of repository that directly reflects user opinions about the apps. Accurately responding to the app reviews is one of the ways to relieve user concerns and thus improve user experience. However, the response quality of the existing method relies on the pre-extracted features from other tools, including manually labelled keywords and predicted review sentiment, which may hinder the generalizability and flexibility of …
Cross-Modal Food Retrieval: Learning A Joint Embedding Of Food Images And Recipes With Semantic Consistency And Attention Mechanism, Hao Wang, Doyen Sahoo, Chenghao Liu, Ke Shu, Palakorn Achananuparp, Ee-Peng Lim, Steven C. H. Hoi
Cross-Modal Food Retrieval: Learning A Joint Embedding Of Food Images And Recipes With Semantic Consistency And Attention Mechanism, Hao Wang, Doyen Sahoo, Chenghao Liu, Ke Shu, Palakorn Achananuparp, Ee-Peng Lim, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Food retrieval is an important task to perform analysis of food-related information, where we are interested in retrieving relevant information about the queried food item such as ingredients, cooking instructions, etc. In this paper, we investigate cross-modal retrieval between food images and cooking recipes. The goal is to learn an embedding of images and recipes in a common feature space, such that the corresponding image-recipe embeddings lie close to one another. Two major challenges in addressing this problem are 1) large intra-variance and small inter-variance across cross-modal food data; and 2) difficulties in obtaining discriminative recipe representations. To address these …
Lessons Learnt Conducting Capture The Flag Cybersecurity Competition During Covid-19, Kee Hock Tan, Eng Lieh Ouh
Lessons Learnt Conducting Capture The Flag Cybersecurity Competition During Covid-19, Kee Hock Tan, Eng Lieh Ouh
Research Collection School Of Computing and Information Systems
This innovative practice full paper describes our experiences conducting cybersecurity capture the flag (CTF) competition for cybersecurity enthusiast participants (inclusive of both tertiary students and working professionals) local and abroad during the COVID-19 pandemic. Learning and appreciation of cybersecurity concepts for our participants with little to no technical background can be challenging. Gamification methods such as capture the flag competition style is a popular form of cybersecurity education to help participants overcome this challenge and identify talents. Participants get to apply theoretical concepts in a controlled environment, solve hands-on tasks in an informal, game-like setting and gain hands-on active learning …
An Exploratory Study On The Repeatedly Shared External Links On Stack Overflow, Jiakun Liu, Haoxiang Zhang, Xin Xia, David Lo, Ying Zou, Ahmed E. Hassan, Shanping Li
An Exploratory Study On The Repeatedly Shared External Links On Stack Overflow, Jiakun Liu, Haoxiang Zhang, Xin Xia, David Lo, Ying Zou, Ahmed E. Hassan, Shanping Li
Research Collection School Of Computing and Information Systems
On Stack Overflow, users reuse 11,926,354 external links to share the resources hosted outside the Stack Overflow website. The external links connect to the existing programming-related knowledge and extend the crowdsourced knowledge on Stack Overflow. Some of the external links, so-called as repeated external links, can be shared for multiple times. We observe that 82.5% of the link sharing activities (i.e., sharing links in any question, answer, or comment) on Stack Overflow share external resources, and 57.0% of the occurrences of the external links are sharing the repeated external links. However, it is still unclear what types of external resources …
Perceptions And Needs Of Artificial Intelligence In Health Care To Increase Adoption: Scoping Review, Han Shi Jocelyn Chew, Palakorn Achananuparp
Perceptions And Needs Of Artificial Intelligence In Health Care To Increase Adoption: Scoping Review, Han Shi Jocelyn Chew, Palakorn Achananuparp
Research Collection School Of Computing and Information Systems
Background: Artificial intelligence (AI) has the potential to improve the efficiency and effectiveness of health care service delivery. However, the perceptions and needs of such systems remain elusive, hindering efforts to promote AI adoption in health care. Objective: This study aims to provide an overview of the perceptions and needs of AI to increase its adoption in health care. Methods: A systematic scoping review was conducted according to the 5-stage framework by Arksey and O’Malley. Articles that described the perceptions and needs of AI in health care were searched across nine databases: ACM Library, CINAHL, Cochrane Central, Embase, IEEE Xplore, …
Enjoy Your Observability: An Industrial Survey Of Microservice Tracing And Analysis, Bowen Li, Xin Peng, Qilin Xiang, Hanzhang Wang, Tao Xie, Jun Sun, Xuanzhe Liu
Enjoy Your Observability: An Industrial Survey Of Microservice Tracing And Analysis, Bowen Li, Xin Peng, Qilin Xiang, Hanzhang Wang, Tao Xie, Jun Sun, Xuanzhe Liu
Research Collection School Of Computing and Information Systems
Microservice systems are often deployed in complex cloud-based environments and may involve a large number of service instances being dynamically created and destroyed. It is thus essential to ensure observability to understand these microservice systems’ behaviors and troubleshoot their problems. As an important means to achieve the observability, distributed tracing and analysis is known to be challenging. While many companies have started implementing distributed tracing and analysis for microservice systems, it is not clear whether existing approaches fulfill the required observability. In this article, we present our industrial survey on microservice tracing and analysis through interviewing developers and operation engineers …
Contextual Documentation Referencing On Stack Overflow, Sebastian Baltes, Christoph Treude, Martin P. Robillard
Contextual Documentation Referencing On Stack Overflow, Sebastian Baltes, Christoph Treude, Martin P. Robillard
Research Collection School Of Computing and Information Systems
Software engineering is knowledge-intensive and requires software developers to continually search for knowledge, often on community question answering platforms such as Stack Overflow. Such information sharing platforms do not exist in isolation, and part of the evidence that they exist in a broader software documentation ecosystem is the common presence of hyperlinks to other documentation resources found in forum posts. With the goal of helping to improve the information diffusion between Stack Overflow and other documentation resources, we conducted a study to answer the question of how and why documentation is referenced in Stack Overflow threads. We sampled and classified …
An Empirical Study Of Developers' Discussions About Security Challenges Of Different Programming Languages, Roland Croft, Yongzheng Xie, Mansooreh Zahedi, Muhammad Ali Babar, Christoph Treude
An Empirical Study Of Developers' Discussions About Security Challenges Of Different Programming Languages, Roland Croft, Yongzheng Xie, Mansooreh Zahedi, Muhammad Ali Babar, Christoph Treude
Research Collection School Of Computing and Information Systems
In collaborative software development projects, work items are used as a mechanism to coordinate tasks and track shared development work. In this paper, we explore how “tagging,” a lightweight social computing mechanism, is used to communicate matters of concern in the management of development tasks. We present the results from two empirical studies over 36 and 12 months, respectively, on how tagging has been adopted and what role it plays in the development processes of several professional development projects with more than 1,000 developers in total. Our research shows that the tagging mechanism was eagerly adopted by the teams, and …
Comparison Of The Mental Burden On Nursing Care Providers With And Without Mat-Type Sleep State Sensors At A Nursing Home In Tokyo, Japan: Quasi-Experimental Study, Sakiko Itoh, Hwee-Pink Tan, Kenichi Kudo, Yasuko Ogata
Comparison Of The Mental Burden On Nursing Care Providers With And Without Mat-Type Sleep State Sensors At A Nursing Home In Tokyo, Japan: Quasi-Experimental Study, Sakiko Itoh, Hwee-Pink Tan, Kenichi Kudo, Yasuko Ogata
Research Collection School Of Computing and Information Systems
Background: Increasing need for nursing care has led to the increased burden on formal caregivers, with those in nursing homes having to deal with exhausting labor. Although research activities on the use of internet of things devices to support nursing care for older adults exist, there is limited evidence on the effectiveness of these interventions among formal caregivers in nursing homes. Objective: This study aims to investigate whether mat-type sleep state sensors for supporting nursing care can reduce the mental burden of formal caregivers in a nursing home. Methods: This was a quasi-experimental study at a nursing home in Tokyo, …
Orchestration Or Automation: Authentication Flaw Detection In Android Apps, Siqi Ma, Juanru Li, Surya Nepal, Diethelm Ostry, David Lo, Sanjay K. Jha, Robert H. Deng, Elisa Bertino
Orchestration Or Automation: Authentication Flaw Detection In Android Apps, Siqi Ma, Juanru Li, Surya Nepal, Diethelm Ostry, David Lo, Sanjay K. Jha, Robert H. Deng, Elisa Bertino
Research Collection School Of Computing and Information Systems
Passwords are pervasively used to authenticate users' identities in mobile apps. To secure passwords against attacks, protection is applied to the password authentication protocol (PAP). The implementation of the protection scheme becomes an important factor in protecting PAP against attacks. We focus on two basic protection in Android, i.e., SSL/TLS-based PAP and timestamp-based PAP. Previously, we proposed an automated tool, GLACIATE, to detect authentication flaws. We were curious whether orchestration (i.e., involving manual-effort) works better than automation. To answer this question, we propose an orchestrated approach, AUTHEXPLOIT and compare its effectiveness GLACIATE. We study requirements for correct implementation of PAP …
Just-In-Time Defect Identification And Localization: A Two-Phase Framework, Meng Yan, Xin Xia, Yuanrui Fan, Ahmed E. Hassan, David Lo, Shanping Li
Just-In-Time Defect Identification And Localization: A Two-Phase Framework, Meng Yan, Xin Xia, Yuanrui Fan, Ahmed E. Hassan, David Lo, Shanping Li
Research Collection School Of Computing and Information Systems
Defect localization aims to locate buggy program elements (e.g., buggy files, methods or lines of code) based on defect symptoms, e.g., bug reports or program spectrum. However, when we receive the defect symptoms, the defect has been exposed and negative impacts have been introduced. Thus, one challenging task is: whether we can locate buggy program prior to appearance of the defect symptom at an early time (e.g., when buggy program elements are being checked-in). We refer to this type of defect localization as “Just-In-Time (JIT) Defect localization”. Although many prior studies have proposed various JIT defect identification methods to identify …
Action-Centric Relation Transformer Network For Video Question Answering, Jipeng Zhang, Jie Shao, Rui Cao, Lianli Gao, Xing Xu, Heng Tao Shen
Action-Centric Relation Transformer Network For Video Question Answering, Jipeng Zhang, Jie Shao, Rui Cao, Lianli Gao, Xing Xu, Heng Tao Shen
Research Collection School Of Computing and Information Systems
Video question answering (VideoQA) has emerged as a popular research topic in recent years. Enormous efforts have been devoted to developing more effective fusion strategies and better intra-modal feature preparation. To explore these issues further, we identify two key problems. (1) Current works take almost no account of introducing action of interest in video representation. Additionally, there exists insufficient labeling data on where the action of interest is in many datasets. However, questions in VideoQA are usually action-centric. (2) Frame-to-frame relations, which can provide useful temporal attributes (e.g., state transition, action counting), lack relevant research. Based on these observations, we …
Journey With Ting Peng Liang In Pacific Asia Information Systems Field, J. Lee, J. Jiang, P. Chau, A. Kankanhalli, M. Nelson, W. Huang, K. Wei, C. Sia, D. Vogel, M. Myers, G. Gable, N. Shen, C. Wei, S. Hung, Keng Siau, D. Liang
Journey With Ting Peng Liang In Pacific Asia Information Systems Field, J. Lee, J. Jiang, P. Chau, A. Kankanhalli, M. Nelson, W. Huang, K. Wei, C. Sia, D. Vogel, M. Myers, G. Gable, N. Shen, C. Wei, S. Hung, Keng Siau, D. Liang
Research Collection School Of Computing and Information Systems
Our respectful old friend Professor Ting-Peng Liang (in short, TP) whom we loved suddenly passed away on May 20, 2021. But we cannot forget his smile and passion, and his inerasable footprints in PACIS, PAJAIS, and AIS Community. He was the founder of PACIS, founding editor-in-chief of PAJAIS, and past president of AIS to list just a few. He was the pioneer who received the first AIS Fellow and the first LEO Award from Asia Pacific. That is why the leaders of the information systems field organized the first ever special tribute session in PACIS 2021 in memory of TP
Accessibility In Software Practice: A Practitioner's Perspective, Tingting Bi, Xin Xia, David Lo, John C. Grundy, Thomas Zimmermann, Denae Ford
Accessibility In Software Practice: A Practitioner's Perspective, Tingting Bi, Xin Xia, David Lo, John C. Grundy, Thomas Zimmermann, Denae Ford
Research Collection School Of Computing and Information Systems
Being able to access software in daily life is vital for everyone, and thus accessibility is a fundamental challenge for software development. However, given the number of accessibility issues reported by many users, e.g., in app reviews, it is not clear if accessibility is widely integrated into current software projects and how software projects address accessibility issues. In this article, we report a study of the critical challenges and benefits of incorporating accessibility into software development and design. We applied a mixed qualitative and quantitative approach for gathering data from 15 interviews and 365 survey respondents from 26 countries across …
Codematcher: Searching Code Based On Sequential Semantics Of Important Query Words, Chao Liu, Xin Xia, David Lo, Zhiwei Liu, Ahmed E. Hassan, Shanping Li
Codematcher: Searching Code Based On Sequential Semantics Of Important Query Words, Chao Liu, Xin Xia, David Lo, Zhiwei Liu, Ahmed E. Hassan, Shanping Li
Research Collection School Of Computing and Information Systems
To accelerate software development, developers frequently search and reuse existing code snippets from a large-scale codebase, e.g., GitHub. Over the years, researchers proposed many information retrieval (IR)-based models for code search, but they fail to connect the semantic gap between query and code. An early successful deep learning (DL)-based model DeepCS solved this issue by learning the relationship between pairs of code methods and corresponding natural language descriptions. Two major advantages of DeepCS are the capability of understanding irrelevant/noisy keywords and capturing sequential relationships between words in query and code. In this article, we proposed an IR-based model CodeMatcher that …
Why Do Smart Contracts Self-Destruct? Investigating The Selfdestruct Function On Ethereum, Jiachi Chen, Xin Xia, David Lo, John C. Grundy
Why Do Smart Contracts Self-Destruct? Investigating The Selfdestruct Function On Ethereum, Jiachi Chen, Xin Xia, David Lo, John C. Grundy
Research Collection School Of Computing and Information Systems
The selfdestruct function is provided by Ethereum smart contracts to destroy a contract on the blockchain system. However, it is a double-edged sword for developers. On the one hand, using the selfdestruct function enables developers to remove smart contracts (SCs) from Ethereum and transfers Ethers when emergency situations happen, e.g., being attacked. On the other hand, this function can increase the complexity for the development and open an attack vector for attackers. To better understand the reasons why SC developers include or exclude the selfdestruct function in their contracts, we conducted an online survey to collect feedback from them and …
Toward Video-Conferencing Tools For Hands-On Activities In Online Teaching, Audrey Labrie, Terrance Mok, Anthony Tang, Michelle Lui, Lora Oehlberg, Lev Poretski
Toward Video-Conferencing Tools For Hands-On Activities In Online Teaching, Audrey Labrie, Terrance Mok, Anthony Tang, Michelle Lui, Lora Oehlberg, Lev Poretski
Research Collection School Of Computing and Information Systems
Many instructors in computing and HCI disciplines use hands-on activities for teaching and training new skills. Beyond simply teaching hands-on skills like sketching and programming, instructors also use these activities so students can acquire tacit skills. Yet, current video-conferencing technologies may not effectively support hands-on activities in online teaching contexts. To develop an understanding of the inadequacies of current video-conferencing technologies for hands-on activities, we conducted 15 interviews with university-level instructors who had quickly pivoted their use of hands-on activities to an online context during the early part of the COVID-19 pandemic. Based on our analysis, we uncovered four pedagogical …
"More Than Deep Learning": Post-Processing For Api Sequence Recommendation, Chi Chen, Xin Peng, Bihuan Chen, Jun Sun, Zhenchang Xing, Xin Wang, Wenyun Zhao
"More Than Deep Learning": Post-Processing For Api Sequence Recommendation, Chi Chen, Xin Peng, Bihuan Chen, Jun Sun, Zhenchang Xing, Xin Wang, Wenyun Zhao
Research Collection School Of Computing and Information Systems
In the daily development process, developers often need assistance in finding a sequence of APIs to accomplish their development tasks. Existing deep learning models, which have recently been developed for recommending one single API, can be adapted by using encoder-decoder models together with beam search to generate API sequence recommendations. However, the generated API sequence recommendations heavily rely on the probabilities of API suggestions at each decoding step, which do not take into account other domain-specific factors (e.g., whether an API suggestion satisfies the program syntax and how diverse the API sequence recommendations are). Moreover, it is difficult for developers …
Kg4vis: A Knowledge Graph-Based Approach For Visualization Recommendation, Haotian Li, Yong Wang, Songheng Zhang, Yangqiu Song, Huamin. Qu
Kg4vis: A Knowledge Graph-Based Approach For Visualization Recommendation, Haotian Li, Yong Wang, Songheng Zhang, Yangqiu Song, Huamin. Qu
Research Collection School Of Computing and Information Systems
Visualization recommendation or automatic visualization generation can significantly lower the barriers for general users to rapidly create effective data visualizations, especially for those users without a background in data visualizations. However, existing rule-based approaches require tedious manual specifications of visualization rules by visualization experts. Other machine learning-based approaches often work like black-box and are difficult to understand why a specific visualization is recommended, limiting the wider adoption of these approaches. This paper fills the gap by presenting KG4Vis, a knowledge graph (KG)-based approach for visualization recommendation. It does not require manual specifications of visualization rules and can also guarantee good …
M2lens: Visualizing And Explaining Multimodal Models For Sentiment Analysis, Xingbo Wang, Jianben He, Zhihua Jin, Muqiao Yang, Yong Wang, Huamin Qu
M2lens: Visualizing And Explaining Multimodal Models For Sentiment Analysis, Xingbo Wang, Jianben He, Zhihua Jin, Muqiao Yang, Yong Wang, Huamin Qu
Research Collection School Of Computing and Information Systems
Multimodal sentiment analysis aims to recognize people's attitudes from multiple communication channels such as verbal content (i.e., text), voice, and facial expressions. It has become a vibrant and important research topic in natural language processing. Much research focuses on modeling the complex intra- and inter-modal interactions between different communication channels. However, current multimodal models with strong performance are often deep-learning-based techniques and work like black boxes. It is not clear how models utilize multimodal information for sentiment predictions. Despite recent advances in techniques for enhancing the explainability of machine learning models, they often target unimodal scenarios (e.g., images, sentences), and …
Do Sequels Outperform Or Disappoint? Insights From An Analysis Of Amazon Echo Consumer Reviews, Kyong Jin Shim, Siaw Ling Lo, Su Yee Liew
Do Sequels Outperform Or Disappoint? Insights From An Analysis Of Amazon Echo Consumer Reviews, Kyong Jin Shim, Siaw Ling Lo, Su Yee Liew
Research Collection School Of Computing and Information Systems
Rapid technological advances in recent years drastically transformed our world. Amidst modern technological inventions such as smart phones, smart watches and smart home devices, consumers of electronic digital devices experience greatly improved automation, productivity, and efficiency in conducting routine daily tasks, information searching, shopping as well as finding entertainment. In the last few years, the global smart speaker market has undergone significant growth. As technology continues to advance and smart speakers are equipped with innovative features, the adoption of smart speakers will increase and so will consumer expectations. This research paper presents an aspect-specific sentiment analysis of consumer reviews of …
Defining Smart Contract Defects On Ethereum, Jiachi Chen, Xin Xia, David Lo, John Grundy, Xiapu Luo, Ting Chen
Defining Smart Contract Defects On Ethereum, Jiachi Chen, Xin Xia, David Lo, John Grundy, Xiapu Luo, Ting Chen
Research Collection School Of Computing and Information Systems
Smart contracts are programs running on a blockchain. They are immutable to change, and hence can not be patched for bugs once deployed. Thus it is critical to ensure they are bug-free and well-designed before deployment. A Contract defect is an error, flaw or fault in a smart contract that causes it to produce an incorrect or unexpected result, or to behave in unintended ways. The detection of contract defects is a method to avoid potential bugs and improve the design of existing code. Since smart contracts contain numerous distinctive features, such as the gas system. decentralized, it is important …
On Discovering Motifs And Frequent Patterns In Spatial Trajectories With Discrete Fréchet Distance, Bo Tang, Man Lung Yiu, Kyriakos Mouratidis, Jiahao Zhang, Kai Wang
On Discovering Motifs And Frequent Patterns In Spatial Trajectories With Discrete Fréchet Distance, Bo Tang, Man Lung Yiu, Kyriakos Mouratidis, Jiahao Zhang, Kai Wang
Research Collection School Of Computing and Information Systems
The discrete Fréchet distance (DFD) captures perceptual and geographical similarity between two trajectories. It has been successfully adopted in a multitude of applications, such as signature and handwriting recognition, computer graphics, as well as geographic applications. Spatial applications, e.g., sports analysis, traffic analysis, etc. require discovering similar subtrajectories within a single trajectory or across multiple trajectories. In this paper, we adopt DFD as the similarity measure, and study two representative trajectory analysis problems, namely, motif discovery and frequent pattern discovery. Due to the time complexity of DFD, these tasks are computationally challenging. We address that challenge with a suite of …
Towards An Instant Structure-Property Prediction Quality Control Tool For Additive Manufactured Steel Using A Crystal Plasticity Trained Deep Learning Surrogate, Yuhui Tu, Zhongzhou Liu, Luiz Carneiro, Caitriona M. Ryan, Andrew C. Parnell, Sean B. Leen
Towards An Instant Structure-Property Prediction Quality Control Tool For Additive Manufactured Steel Using A Crystal Plasticity Trained Deep Learning Surrogate, Yuhui Tu, Zhongzhou Liu, Luiz Carneiro, Caitriona M. Ryan, Andrew C. Parnell, Sean B. Leen
Research Collection School Of Computing and Information Systems
The ability to conduct in-situ real-time process-structure-property checks has the potential to overcome process and material uncertainties, which are key obstacles to improved uptake of metal powder bed fusion in industry. Efforts are underway for live process monitoring such as thermal and image-based data gathering for every layer printed. Current crystal plasticity finite element (CPFE) modelling is capable of predicting the associated strength based on a microstructural image and material data but is computationally expensive. This work utilizes a large database of input–output samples from CPFE modelling to develop a trained deep neural network (DNN) model which instantly estimates the …
Learning From Web Recipe-Image Pairs For Food Recognition: Problem, Baselines And Performance, Bin Zhu, Chong-Wah Ngo, Wing-Kwong Chan
Learning From Web Recipe-Image Pairs For Food Recognition: Problem, Baselines And Performance, Bin Zhu, Chong-Wah Ngo, Wing-Kwong Chan
Research Collection School Of Computing and Information Systems
Cross-modal recipe retrieval has recently been explored for food recognition and understanding. Text-rich recipe provides not only visual content information (e.g., ingredients, dish presentation) but also procedure of food preparation (cutting and cooking styles). The paired data is leveraged to train deep models to retrieve recipes for food images. Most recipes on the Web include sample pictures as the references. The paired multimedia data is not noise-free, due to errors such as pairing of images containing partially prepared dishes with recipes. The content of recipes and food images are not always consistent due to free-style writing and preparation of food …
Lightweight And Expressive Fine-Grained Access Control For Healthcare Internet-Of-Things, Shengmin Xu, Yingjiu Li, Robert H. Deng, Yinghui Zhang, Xiangyang Luo, Ximeng Liu
Lightweight And Expressive Fine-Grained Access Control For Healthcare Internet-Of-Things, Shengmin Xu, Yingjiu Li, Robert H. Deng, Yinghui Zhang, Xiangyang Luo, Ximeng Liu
Research Collection School Of Computing and Information Systems
Healthcare Internet-of-Things (IoT) is an emerging paradigm that enables embedded devices to monitor patients vital signals and allows these data to be aggregated and outsourced to the cloud. The cloud enables authorized users to store and share data to enjoy on-demand services. Nevertheless, it also causes many security concerns because of the untrusted network environment, dishonest cloud service providers and resource-limited devices. To preserve patients' privacy, existing solutions usually apply cryptographic tools to offer access controls. However, fine-grained access control among authorized users is still a challenge, especially for lightweight and resource-limited end-devices. In this paper, we propose a novel …
Secure Cloud Data Deduplication With Efficient Re-Encryption, Haoran Yuan, Xiaofeng Chen, Jin Li, Tao Jiang, Jianfeng Wang, Robert H. Deng
Secure Cloud Data Deduplication With Efficient Re-Encryption, Haoran Yuan, Xiaofeng Chen, Jin Li, Tao Jiang, Jianfeng Wang, Robert H. Deng
Research Collection School Of Computing and Information Systems
Data deduplication technique has been widely adopted by commercial cloud storage providers, which is both important and necessary in coping with the explosive growth of data. To further protect the security of users' sensitive data in the outsourced storage mode, many secure data deduplication schemes have been designed and applied in various scenarios. Among these schemes, secure and efficient re-encryption for encrypted data deduplication attracted the attention of many scholars, and many solutions have been designed to support dynamic ownership management. In this paper, we focus on the re-encryption deduplication storage system and show that the recently designed lightweight rekeying-aware …
A Blockchain-Based Self-Tallying Voting Protocol In Decentralized Iot, Yannan Li, Willy Susilo, Guomin Yang, Yong Yu, Dongxi Liu, Xiaojiang Du, Mohsen Guizani
A Blockchain-Based Self-Tallying Voting Protocol In Decentralized Iot, Yannan Li, Willy Susilo, Guomin Yang, Yong Yu, Dongxi Liu, Xiaojiang Du, Mohsen Guizani
Research Collection School Of Computing and Information Systems
The Internet of Things (IoT) is experiencing explosive growth and has gained extensive attention from academia and industry in recent years. However, most of the existing IoT infrastructures are centralized, which may cause the issues of unscalability and single-point-of-failure. Consequently, decentralized IoT has been proposed by taking advantage of the emerging technology called blockchain. Voting systems are widely adopted in IoT, for example a leader election in wireless sensor networks. Self-tallying voting systems are alternatives to unsuitable, traditional centralized voting systems in decentralized IoT. Unfortunately, self-tallying voting systems inherently suffer from fairness issues, such as adaptive and abortive issues caused …