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Articles 1531 - 1560 of 4266
Full-Text Articles in Entire DC Network
Visuo-Haptic Illusions For Linear Translation And Stretching Using Physical Proxies In Virtual Reality, Martin Feick, Niko Kleer, André Zenner, Anthony Tang, Antonio Kruger
Visuo-Haptic Illusions For Linear Translation And Stretching Using Physical Proxies In Virtual Reality, Martin Feick, Niko Kleer, André Zenner, Anthony Tang, Antonio Kruger
Research Collection School Of Computing and Information Systems
Providing haptic feedback when manipulating virtual objects is an essential part of immersive virtual reality experiences; however, it is challenging to replicate all of an object’s properties and characteristics. We propose the use of visuo-haptic illusions alongside physical proxies to enhance the scope of proxy-based interactions with virtual objects. In this work, we focus on two manipulation techniques, linear translation and stretching across different distances, and investigate how much discrepancy between the physical proxy and the virtual object may be introduced without participants noticing. In a study with 24 participants, we found that manipulation technique and travel distance significantly affect …
When Function Signature Recovery Meets Compiler Optimization, Yan Lin, Debin Gao
When Function Signature Recovery Meets Compiler Optimization, Yan Lin, Debin Gao
Research Collection School Of Computing and Information Systems
Matching indirect function callees and callers using function signatures recovered from binary executables (number of arguments and argument types) has been proposed to construct a more fine-grained control-flow graph (CFG) to help control-flow integrity (CFI) enforcement. However, various compiler optimizations may violate calling conventions and result in unmatched function signatures. In this paper, we present eight scenarios in which compiler optimizations impact function signature recovery, and report experimental results with 1,344 real-world applications of various optimization levels. Most interestingly, our experiments show that compiler optimizations have both positive and negative impacts on function signature recovery, e.g., its elimination of redundant …
Automatic Solution Summarization For Crash Bugs, Haoye Wang, Xin Xia, David Lo, John C. Grundy, Xinyu Wang
Automatic Solution Summarization For Crash Bugs, Haoye Wang, Xin Xia, David Lo, John C. Grundy, Xinyu Wang
Research Collection School Of Computing and Information Systems
The causes of software crashes can be hidden anywhere in the source code and development environment. When encountering software crashes, recurring bugs that are discussed on Q&A sites could provide developers with solutions to their crashing problems. However, it is difficult for developers to accurately search for relevant content on search engines, and developers have to spend a lot of manual effort to find the right solution from the returned results. In this paper, we present CRASOLVER, an approach that takes into account both the structural information of crash traces and the knowledge of crash-causing bugs to automatically summarize solutions …
On The Root Of Trust Identification Problem, Ivan De Oliveira Nunes, Xuhua Ding, Gene Tsudik
On The Root Of Trust Identification Problem, Ivan De Oliveira Nunes, Xuhua Ding, Gene Tsudik
Research Collection School Of Computing and Information Systems
Trusted Execution Environments (TEEs) are becoming ubiquitous and are currently used in many security applications: from personal IoT gadgets to banking and databases. Prominent examples of such architectures are Intel SGX, ARM TrustZone, and Trusted Platform Modules (TPMs). A typical TEE relies on a dynamic Root of Trust (RoT) to provide security services such as code/data confidentiality and integrity, isolated secure software execution, remote attestation, and sensor auditing. Despite their usefulness, there is currently no secure means to determine whether a given security service or task is being performed by the particular RoT within a specific physical device. We refer …
A Differential Testing Approach For Evaluating Abstract Syntax Tree Mapping Algorithms, Yuanrui Fan, Xin Xia, David Lo, Ahmed E. Hassan, Yuan Wang, Shanping Li
A Differential Testing Approach For Evaluating Abstract Syntax Tree Mapping Algorithms, Yuanrui Fan, Xin Xia, David Lo, Ahmed E. Hassan, Yuan Wang, Shanping Li
Research Collection School Of Computing and Information Systems
Abstract syntax tree (AST) mapping algorithms are widely used to analyze changes in source code. Despite the foundational role of AST mapping algorithms, little effort has been made to evaluate the accuracy of AST mapping algorithms, i.e., the extent to which an algorithm captures the evolution of code. We observe that a program element often has only one best-mapped program element. Based on this observation, we propose a hierarchical approach to automatically compare the similarity of mapped statements and tokens by different algorithms. By performing the comparison, we determine if eachof the compared algorithms generates inaccurate mappings for a statement …
Angrybert: Joint Learning Target And Emotion For Hate Speech Detection, Md Rabiul Awal, Rui Cao, Roy Ka-Wei Lee, Sandra Mitrović
Angrybert: Joint Learning Target And Emotion For Hate Speech Detection, Md Rabiul Awal, Rui Cao, Roy Ka-Wei Lee, Sandra Mitrović
Research Collection School Of Computing and Information Systems
Automated hate speech detection in social media is a challenging task that has recently gained significant traction in the data mining and Natural Language Processing community. However, most of the existing methods adopt a supervised approach that depended heavily on the annotated hate speech datasets, which are imbalanced and often lack training samples for hateful content. This paper addresses the research gaps by proposing a novel multitask learning-based model, AngryBERT, which jointly learns hate speech detection with sentiment classification and target identification as secondary relevant tasks. We conduct extensive experiments to augment three commonly-used hate speech detection datasets. Our experiment …
Automated Query Reformulation For Efficient Search Based On Query Logs From Stack Overflow, Kaibo Cao, Chunyang Chen, Sebastian Baltes, Christoph Treude, Xiang Chen
Automated Query Reformulation For Efficient Search Based On Query Logs From Stack Overflow, Kaibo Cao, Chunyang Chen, Sebastian Baltes, Christoph Treude, Xiang Chen
Research Collection School Of Computing and Information Systems
As a popular Q&A site for programming, Stack Overflow is a treasure for developers. However, the amount of questions and answers on Stack Overflow make it difficult for developers to efficiently locate the information they are looking for. There are two gaps leading to poor search results: the gap between the user's intention and the textual query, and the semantic gap between the query and the post content. Therefore, developers have to constantly reformulate their queries by correcting misspelled words, adding limitations to certain programming languages or platforms, etc. As query reformulation is tedious for developers, especially for novices, we …
Oidpr: Optimized Insulin Dosage Via Privacy‐Preserving Reinforcement Learning, Zuobin Ying, Yun Zhang, Shuanglong Cao, Shengmin Xu, Maode Ma
Oidpr: Optimized Insulin Dosage Via Privacy‐Preserving Reinforcement Learning, Zuobin Ying, Yun Zhang, Shuanglong Cao, Shengmin Xu, Maode Ma
Research Collection School Of Computing and Information Systems
The precision of insulin dosage is essential in the process of diabetes treatment. The fact is providing precise dosage is almost impossible for clinicians since blood sugar levels are dynamically affected by many factors. Even though some auxiliary dosing systems have been proposed, the required real‐time physical data about the health situation of diabetics is still hard to synchronize to the end‐devices instantly. The traditional personalized drug delivery frameworks for accurate dosing of insulin always collect and transmit medical data in cleartext, which raises privacy problems. In this article, we propose a framework for an optimized insulin dosage via privacy‐preserving …
Immigrant Families' Health-Related Information Behavior On Instant Messaging Platforms: Health-Related Information Exchange In Immigrant Family Groups On Instant Messaging Platforms, Lev Poretski, Taamannae Taabassum, Anthony Tang
Immigrant Families' Health-Related Information Behavior On Instant Messaging Platforms: Health-Related Information Exchange In Immigrant Family Groups On Instant Messaging Platforms, Lev Poretski, Taamannae Taabassum, Anthony Tang
Research Collection School Of Computing and Information Systems
For immigrant families, instant messaging family groups are a common platform for sharing and discussing health-related information. Immigrants often maintain contact with their family abroad and trust information in shared IM family groups more than the information from local authorities and sources. In this study, we aimed to understand health-related information behaviors of immigrant families in their IM family groups. Based on the interviews with 6 participants from immigrant families to Canada, we found that immigrant families’ discourse on IM platforms is motivated by love and care for other family members. The families used local and international sources of information, …
A Visual Analytics Approach To Facilitate The Proctoring Of Online Exams, Haotian Li, Min Xu, Yong Wang, Huan Wei, Huamin Qu
A Visual Analytics Approach To Facilitate The Proctoring Of Online Exams, Haotian Li, Min Xu, Yong Wang, Huan Wei, Huamin Qu
Research Collection School Of Computing and Information Systems
Online exams have become widely used in recent years to evaluate students’ performance in mastering the knowledge, especially during the pandemic of COVID-19. However, it is challenging to conduct proctoring for online exams due to the lack of face-to-face interactions. Also, prior research has shown that online exams are more vulnerable to various cheating behaviors, which can damage the credibility of online exams. In this paper, we present a novel vi- sual analytics approach to facilitate the proctoring of online exams by analyzing the exam video records and mouse movement data of each student. Specifically, we detect and visualize suspected …
Fine-Grained And Controllably Redactable Blockchain With Harmful Data Forced Removal, Huiying Hou, Shidi Hao, Jiaming Yuan, Shengmin Xu, Yunlei Zhao
Fine-Grained And Controllably Redactable Blockchain With Harmful Data Forced Removal, Huiying Hou, Shidi Hao, Jiaming Yuan, Shengmin Xu, Yunlei Zhao
Research Collection School Of Computing and Information Systems
Notoriously, immutability is one of the most striking properties of blockchains. As the data contained in blockchains may be compelled to redact for personal and legal reasons, immutability needs to be skillfully broken. In most existing redactable blockchains, fine-grained redaction and effective deletion of harmful data are mutually exclusive. To close the gap, we propose a fine-grained and controllably redactable blockchain with harmful data forced removal. In the scheme, the originator of the transaction has fine-grained control over who can perform the redaction and which portions of the transaction can be redacted. The redaction transaction is performed after collecting enough …
Dialogue State Tracking With Incremental Reasoning, Lizi Liao, Le Hong Long, Yunshan Ma, Wenqiang Lei, Tat-Seng Chua
Dialogue State Tracking With Incremental Reasoning, Lizi Liao, Le Hong Long, Yunshan Ma, Wenqiang Lei, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Tracking dialogue states to better interpret user goals and feed downstream policy learning is a bottleneck in dialogue management. Common practice has been to treat it as a problem of classifying dialogue content into a set of pre-defined slot-value pairs, or generating values for different slots given the dialogue history. Both have limitations on considering dependencies that occur on dialogues, and are lacking of reasoning capabilities. This paper proposes to track dialogue states gradually with reasoning over dialogue turns with the help of the back-end data. Empirical results demonstrate that our method outperforms the state-of-theart methods in terms of joint …
Low-Power Downlink For The Internet Of Things Using Ieee 802.11-Compliant Wake-Up Receivers, Johannes Blobel, Vu Huy Tran, Archan Misra, Falko Dressler
Low-Power Downlink For The Internet Of Things Using Ieee 802.11-Compliant Wake-Up Receivers, Johannes Blobel, Vu Huy Tran, Archan Misra, Falko Dressler
Research Collection School Of Computing and Information Systems
Ultra-low power communication is critical for supporting the next generation of battery-operated or energy harvesting battery-less Internet of Things (IoT) devices. Duty cycling protocols and wake-up receiver (WuRx) technologies, and their combinations, have been investigated as energy-efficient mechanisms to support selective, event-driven activation of devices. In this paper, we go one step further and show how WuRx can be used for an efficient and multi-purpose low power downlink (LPD) communication channel. We demonstrate how to (a) extend the wake-up signal to support low-power flexible and extensible unicast, multicast, and broadcast downlink communication and (b) utilize the WuRx-based LPD to also …
Characterization And Prediction Of Questions Without Accepted Answers On Stack Overflow, Mohamad Yazdaninia, David Lo, Ashkan Sami
Characterization And Prediction Of Questions Without Accepted Answers On Stack Overflow, Mohamad Yazdaninia, David Lo, Ashkan Sami
Research Collection School Of Computing and Information Systems
A fast and effective approach to obtain information regarding software development problems is to search them to find similar solved problems or post questions on community question answering (CQA) websites. Solving coding problems in a short time is important, so these CQAs have a considerable impact on the software development process. However, if developers do not get their expected answers, the websites will not be useful, and software development time will increase. Stack Overflow is the most popular CQA concerning programming problems. According to its rules, the only sign that shows a question poser has achieved the desired answer is …
Sguard: Towards Fixing Vulnerable Smart Contracts Automatically, Tai D. Nguyen, Long H. Pham, Jun Sun
Sguard: Towards Fixing Vulnerable Smart Contracts Automatically, Tai D. Nguyen, Long H. Pham, Jun Sun
Research Collection School Of Computing and Information Systems
Smart contracts are distributed, self-enforcing programs executing on top of blockchain networks. They have the potential to revolutionize many industries such as financial institutes and supply chains. However, smart contracts are subject to code-based vulnerabilities, which casts a shadow on its applications. As smart contracts are unpatchable (due to the immutability of blockchain), it is essential that smart contracts are guaranteed to be free of vulnerabilities. Unfortunately, smart contract languages such as Solidity are Turing-complete, which implies that verifying them statically is infeasible. Thus, alternative approaches must be developed to provide the guarantee. In this work, we develop an approach …
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, Achananuparp Palakorn, Ee Peng Lim, Steven 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, Achananuparp Palakorn, Ee Peng Lim, Steven 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 …
Interactive Search Vs. Automatic Search: An Extensive Study On Video Retrieval, Phuong-Anh Nguyen, Chong-Wah Ngo
Interactive Search Vs. Automatic Search: An Extensive Study On Video Retrieval, Phuong-Anh Nguyen, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This article conducts user evaluation to study the performance difference between interactive and automatic search. Particularly, the study aims to provide empirical insights of how the performance landscape of video search changes, with tens of thousands of concept detectors freely available to exploit for query formulation. We compare three types of search modes: free-to-play (i.e., search from scratch), non-free-to-play (i.e., search by inspecting results provided by automatic search), and automatic search including concept-free and concept-based retrieval paradigms. The study involves a total of 40 participants; each performs interactive search over 15 queries of various difficulty levels using two search modes …
Infercode: Self-Supervised Learning Of Code Representations By Predicting Subtrees, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang
Infercode: Self-Supervised Learning Of Code Representations By Predicting Subtrees, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Learning code representations has found many uses in software engineering, such as code classification, code search, code comment generation, and bug prediction. Although representations of code in tokens, syntax trees, dependency graphs, paths in trees, or the combinations of their variants have been proposed, existing learning techniques have a major limitation that these models are often trained on datasets labeled for specific downstream tasks, and the code representations may not be suitable for other tasks. Even though some techniques generate representations from unlabeled code, they are far from satisfactory when applied to downstream tasks. To overcome the limitation, this paper …
Smart Contract Security: A Practitioners' Perspective, Zhiyuan Wan, Xin Xia, David Lo, Jiachi Chen, Xiapu Luo, Xiaohu Yang
Smart Contract Security: A Practitioners' Perspective, Zhiyuan Wan, Xin Xia, David Lo, Jiachi Chen, Xiapu Luo, Xiaohu Yang
Research Collection School Of Computing and Information Systems
Smart contracts have been plagued by security incidents, which resulted in substantial financial losses. Given numerous research efforts in addressing the security issues of smart contracts, we wondered how software practitioners build security into smart contracts in practice. We performed a mixture of qualitative and quantitative studies with 13 interviewees and 156 survey respondents from 35 countries across six continents to understand practitioners' perceptions and practices on smart contract security. Our study uncovers practitioners' motivations and deterrents of smart contract security, as well as how security efforts and strategies fit into the development lifecycle. We also find that blockchain platforms …
Efficient And Verifiable Proof Of Replication With Fast Fault Localization, Haoran Yuan, Xiaofeng Chen, Guowen Xu, Jianting Ning, Joseph K. Liu, Robert H. Deng
Efficient And Verifiable Proof Of Replication With Fast Fault Localization, Haoran Yuan, Xiaofeng Chen, Guowen Xu, Jianting Ning, Joseph K. Liu, Robert H. Deng
Research Collection School Of Computing and Information Systems
Proof of replication technique has been widely used to verify whether the cloud service providers (CSPs) store multiple replications of a file with dedicated and unique storage space, which effectively prevents CSPs from colluding and storing only one copy of the file. In this field, many representative schemes have been proposed and applied to various scenarios. However, most of the existing schemes are based on the timing assumption (i.e., the verifier rejects the proof of replication if the prover's response is timeout) and do not explicitly consider the problem of batch verification and fault localization. This will bring unnecessary computational …
Characterising The Knowledge About Primitive Variables In Java Code Comments, Mahfouth Alghamdi, Shinpei Hayashi, Takashi Kobayashi, Christoph Treude
Characterising The Knowledge About Primitive Variables In Java Code Comments, Mahfouth Alghamdi, Shinpei Hayashi, Takashi Kobayashi, Christoph Treude
Research Collection School Of Computing and Information Systems
Primitive types are fundamental components available in any programming language, which serve as the building blocks of data manipulation. Understanding the role of these types in source code is essential to write software. Little work has been conducted on how often these variables are documented in code comments and what types of knowledge the comments provide about variables of primitive types. In this paper, we present an approach for detecting primitive variables and their description in comments using lexical matching and advanced matching. We evaluate our approaches by comparing the lexical and advanced matching performance in terms of recall, precision, …
How Do Software Developers Use Github Actions To Automate Their Workflows?, Timothy Kinsman, Mairieli Wessel, Marco Gerosa, Christoph Treude
How Do Software Developers Use Github Actions To Automate Their Workflows?, Timothy Kinsman, Mairieli Wessel, Marco Gerosa, Christoph Treude
Research Collection School Of Computing and Information Systems
Automated tools are frequently used in social coding repositories to perform repetitive activities that are part of the distributed software development process. Recently, GitHub introduced GitHub Actions, a feature providing automated work-flows for repository maintainers. Although several Actions have been built and used by practitioners, relatively little has been done to evaluate them. Understanding and anticipating the effects of adopting such kind of technology is important for planning and management. Our research is the first to investigate how developers use Actions and how several activity indicators change after their adoption. Our results indicate that, although only a small subset of …
Business-Driven Technical Debt Prioritization: An Industrial Case Study, Rodrigo Rebouças De Almeida, Rafael Do Nascimento Ribeiro, Christoph Treude, Uirá Kulesza
Business-Driven Technical Debt Prioritization: An Industrial Case Study, Rodrigo Rebouças De Almeida, Rafael Do Nascimento Ribeiro, Christoph Treude, Uirá Kulesza
Research Collection School Of Computing and Information Systems
Incorporating the business perspective into prioritizing technical debt is essential to contribute to decision making in industry. In this paper, we evolve and evaluate a businessdriven approach for technical debt prioritization. The approach was evaluated during a five-months industrial case study with business and technical stakeholders’ active participation. The results show that the approach contributed to aligning business criteria between the business and technical stakeholders. We also observed a downward trend in the amount of technical debt that affects high-value business assets. Moreover, we identified eight business factors that affect the decision making related to the prioritization of technical debt. …
Prototypical Contrastive Learning Of Unsupervised Representations, Junnan Li, Pan Zhou, Caiming Xiong, Steven C. H. Hoi
Prototypical Contrastive Learning Of Unsupervised Representations, Junnan Li, Pan Zhou, Caiming Xiong, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
This paper presents Prototypical Contrastive Learning (PCL), an unsupervised representation learning method that bridges contrastive learning with clustering. PCL not only learns low-level features for the task of instance discrimination, but more importantly, it encodes semantic structures discovered by clustering into the learned embedding space. Specifically, we introduce prototypes as latent variables to help find the maximum-likelihood estimation of the network parameters in an Expectation-Maximization framework. We iteratively perform E-step as finding the distribution of prototypes via clustering and M-step as optimizing the network via contrastive learning. We propose ProtoNCE loss, a generalized version of the InfoNCE loss for contrastive …
Urban Perception: Sensing Cities Via A Deep Interactive Multi-Task Learning Framework, Weili Guan, Zhaozheng Chen, Fuli Feng, Weifeng Liu, Liqiang Nie
Urban Perception: Sensing Cities Via A Deep Interactive Multi-Task Learning Framework, Weili Guan, Zhaozheng Chen, Fuli Feng, Weifeng Liu, Liqiang Nie
Research Collection School Of Computing and Information Systems
Social scientists have shown evidence that visual perceptions of urban attributes, such as safe, wealthy, and beautiful perspectives of the given cities, are highly correlated to the residents' behaviors and quality of life. Despite their significance, measuring visual perceptions of urban attributes is challenging due to the following facts: (1) Visual perceptions are subjectively contradistinctive rather than absolute. (2) Perception comparisons between image pairs are usually conducted region by region, and highly related to the specific urban attributes. And (3) the urban attributes have both the shared and specific information. To address these problems, in this article, we present a …
Spectest: Specification-Based Compiler Testing, Richard Schumi, Jun Sun
Spectest: Specification-Based Compiler Testing, Richard Schumi, Jun Sun
Research Collection School Of Computing and Information Systems
Compilers are error-prone due to their high complexity. They are relevant for not only general purpose programming languages, but also for many domain specific languages. Bugs in compilers can potentially render all programs at risk. It is thus crucial that compilers are systematically tested, if not verified. Recently, a number of efforts have been made to formalise and standardise programming language semantics, which can be applied to verify the correctness of the respective compilers. In this work, we present a novel specification-based testing method named SpecTest to better utilise these semantics for testing. By applying an executable semantics as test …
Newslink: Empowering Intuitive News Search With Knowledge Graphs, Yueji Yang, Yuchen Li, Anthony Tung
Newslink: Empowering Intuitive News Search With Knowledge Graphs, Yueji Yang, Yuchen Li, Anthony Tung
Research Collection School Of Computing and Information Systems
News search tools help end users to identify relevant news stories. However, existing search approaches often carry out in a "black-box" process. There is little intuition that helps users understand how the results are related to the query. In this paper, we propose a novel news search framework, called NEWSLINK, to empower intuitive news search by using relationship paths discovered from open Knowledge Graphs (KGs). Specifically, NEWSLINK embeds both a query and news documents to subgraphs, called subgraph embeddings, in the KG. Their embeddings' overlap induces relationship paths between the involving entities. Two major advantages are obtained by incorporating subgraph …
Dbl: Efficient Reachability Queries On Dynamic Graphs, Qiuyi Lyu, Yuchen Li, Bingsheng He, Bin Gong
Dbl: Efficient Reachability Queries On Dynamic Graphs, Qiuyi Lyu, Yuchen Li, Bingsheng He, Bin Gong
Research Collection School Of Computing and Information Systems
Reachability query is a fundamental problem on graphs, which has been extensively studied in academia and industry. Since graphs are subject to frequent updates in many applications, it is essential to support efficient graph updates while offering good performance in reachability queries. Existing solutions compress the original graph with the Directed Acyclic Graph (DAG) and propose efficient query processing and index update techniques. However, they focus on optimizing the scenarios where the Strong Connected Components (SCCs) remain unchanged and have overlooked the prohibitively high cost of the DAG maintenance when SCCs are updated. In this paper, we propose DBL, an …
Mixed Dish Recognition With Contextual Relation And Domain Alignment, Lixi Deng, Jingjing Chen, Chong-Wah Ngo, Qianru Sun, Sheng Tang, Yongdong Zhang, Tat-Seng Chua
Mixed Dish Recognition With Contextual Relation And Domain Alignment, Lixi Deng, Jingjing Chen, Chong-Wah Ngo, Qianru Sun, Sheng Tang, Yongdong Zhang, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Mixed dish is a food category that contains different dishes mixed in one plate, and is popular in Eastern and Southeast Asia. Recognizing the individual dishes in a mixed dish image is important for health related applications, e.g. to calculate the nutrition values of the dish. However, most existing methods that focus on single dish classification are not applicable to the recognition of mixed dish images. The main challenge of mixed dish recognition comes from three aspects: a wide range of dish types, the complex dish combination with severe overlap between different dishes and the large visual variances of same …
Do Users Care About Ad's Performance Costs? Exploring The Effects Of The Performance Costs Of In-App Ads On User Experience, Cuiyun Gao, Jichuan Zeng, Federica Sarro, David Lo, Irwin King, Michael R. Lyu
Do Users Care About Ad's Performance Costs? Exploring The Effects Of The Performance Costs Of In-App Ads On User Experience, Cuiyun Gao, Jichuan Zeng, Federica Sarro, David Lo, Irwin King, Michael R. Lyu
Research Collection School Of Computing and Information Systems
Context: In-app advertising is the primary source of revenue for many mobile apps. The cost of advertising (ad cost) is non-negligible for app developers to ensure a good user experience and continuous profits. Previous studies mainly focus on addressing the hidden performance costs generated by ads, including consumption of memory, CPU, data traffic, and battery. However, there is no research on analyzing users’ perceptions of ads’ performance costs to our knowledge.Objective: To fill this gap and better understand the effects of performance costs of in-app ads on user experience, we conduct a study on analyzing user concerns about ads’ performance …