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Articles 1531 - 1560 of 2149
Full-Text Articles in Software Engineering
Extracting Development Tasks To Navigate Software Documentation, Christoph Treude, Martin P. Robillard, Barthélémy Dagenais
Extracting Development Tasks To Navigate Software Documentation, Christoph Treude, Martin P. Robillard, Barthélémy Dagenais
Research Collection School Of Computing and Information Systems
Knowledge management plays a central role in many software development organizations. While much of the important technical knowledge can be captured in documentation, there often exists a gap between the information needs of software developers and the documentation structure. To help developers navigate documentation, we developed a technique for automatically extracting tasks from software documentation by conceptualizing tasks as specific programming actions that have been described in the documentation. More than 70 percent of the tasks we extracted from the documentation of two projects were judged meaningful by at least one of two developers. We present TaskNavigator, a user interface …
Heuristic Collective Learning For Efficient And Robust Emergence Of Social Norms, Jianye Hao, Jun Sun, Dongping Huang, Yi Cai, Chao Yu
Heuristic Collective Learning For Efficient And Robust Emergence Of Social Norms, Jianye Hao, Jun Sun, Dongping Huang, Yi Cai, Chao Yu
Research Collection School Of Computing and Information Systems
In multiagent systems, social norms is a useful technique in regulating agents’ behaviors to achieve coordination or cooperation among agents. One important research question is to investigate how a desirable social norm can be evolved in a bottom-up manner through local interactions. In this paper, we propose two novel learning strategies under the collective learning framework: collective learning EV-l and collective learning EV-g, to efficiently facilitate the emergence of social norms. Experimental results show that both learning strategies can support the emergence of desirable social norms more efficiently in a much broader range of multiagent interaction scenarios than previous work, …
Relative Localization Of Rfid Tags Using Spatial-Temporal Phase Profiling, Longfei Shangguan, Zheng Yang, Alex X. Liu, Zimu Zhou, Yunhao Liu
Relative Localization Of Rfid Tags Using Spatial-Temporal Phase Profiling, Longfei Shangguan, Zheng Yang, Alex X. Liu, Zimu Zhou, Yunhao Liu
Research Collection School Of Computing and Information Systems
Many object localization applications need the relative locations of a set of objects as oppose to their absolute locations. Although many schemes for object localization using Radio Frequency Identification (RFID) tags have been proposed, they mostly focus on absolute object localization and are not suitable for relative object localization because of large error margins and the special hardware that they require. In this paper, we propose an approach called Spatial-Temporal Phase Profiling (STPP) to RFID based relative object localization. The basic idea of STPP is that by moving a reader over a set of tags during which the reader continuously …
Non-Invasive Detection Of Moving And Stationary Human With Wifi, Chenshu Wu, Zheng Yang, Zimu Zhou, Xuefeng Liu, Yunhao Liu, Jiannong Cao
Non-Invasive Detection Of Moving And Stationary Human With Wifi, Chenshu Wu, Zheng Yang, Zimu Zhou, Xuefeng Liu, Yunhao Liu, Jiannong Cao
Research Collection School Of Computing and Information Systems
Non-invasive human sensing based on radio signals has attracted a great deal of research interest and fostered a broad range of innovative applications of localization, gesture recognition, smart health-care, etc., for which a primary primitive is to detect human presence. Previous works have studied the detection of moving humans via signal variations caused by human movements. For stationary people, however, existing approaches often employ a prerequisite scenario-tailored calibration of channel profile in human-free environments. Based on in-depth understanding of human motion induced signal attenuation reflected by PHY layer channel state information (CSI), we propose DeMan, a unified scheme for non-invasive …
Discovering The Rise And Fall Of Software Engineering Ideas From Scholarly Publication Data, Subhajit Datta, Santonu Sarkar, Sajeev A. S. M., Nishant Kumar
Discovering The Rise And Fall Of Software Engineering Ideas From Scholarly Publication Data, Subhajit Datta, Santonu Sarkar, Sajeev A. S. M., Nishant Kumar
Research Collection School Of Computing and Information Systems
For researchers and practitioners of a relatively young discipline like software engineering, an enduring concern is to identify the acorns that will grow into oaks -- ideas remaining most current in the long run. Additionally, it is interesting to know how the ideas have risen in importance, and fallen, perhaps to rise again. We analyzed a corpus of 19,000+ papers written by 21,000+ authors across 16 software engineering publication venues from 1975 to 2010, to empirically determine the half-life of software engineering research topics. We adapted existing measures of half-life as well as defined a specific measure based on publication …
Ambient Rendezvous: Energy Efficient Neighbor Discovery Via Acoustic Sensing, Keyu Wang, Zheng Yang, Zimu Zhou, Yunhao Liu, Lionel M. Ni
Ambient Rendezvous: Energy Efficient Neighbor Discovery Via Acoustic Sensing, Keyu Wang, Zheng Yang, Zimu Zhou, Yunhao Liu, Lionel M. Ni
Research Collection School Of Computing and Information Systems
The continual proliferation of mobile devices has stimulated the development of opportunistic encounter-based networking and has spurred a myriad of proximity-based mobile applications. A primary cornerstone of such applications is to discover neighboring devices effectively and efficiently. Despite extensive protocol optimization, current neighbor discovery modalities mainly rely on radio interfaces, whose energy and wake up delay required to initiate, configure and operate these protocols hamper practical applicability. Unlike conventional schemes that actively emit radio tones, we exploit ubiquitous audio events to discover neighbors passively. The rationale is that spatially adjacent neighbors tend to share similar ambient acoustic environments. We propose …
Active Semi-Supervised Defect Categorization, Ferdian Thung, Xuan-Bach D. Le, David Lo
Active Semi-Supervised Defect Categorization, Ferdian Thung, Xuan-Bach D. Le, David Lo
Research Collection School Of Computing and Information Systems
Defects are inseparable part of software development and evolution. To better comprehend problems affecting a software system, developers often store historical defects and these defects can be categorized into families. IBM proposes Orthogonal Defect Categorization (ODC) which include various classifications of defects based on a number of orthogonal dimensions (e.g., symptoms and semantics of defects, root causes of defects, etc.). To help developers categorize defects, several approaches that employ machine learning have been proposed in the literature. Unfortunately, these approaches often require developers to manually label a large number of defect examples. In practice, manually labelling a large number of …
Elblocker: Predicting Blocking Bugs With Ensemble Imbalance Learning, Xin Xia, David Lo, Emad Shihab, Xinyu Wang, Xiaohu Yang
Elblocker: Predicting Blocking Bugs With Ensemble Imbalance Learning, Xin Xia, David Lo, Emad Shihab, Xinyu Wang, Xiaohu Yang
Research Collection School Of Computing and Information Systems
Context: Blocking bugs are bugs that prevent other bugs from being fixed. Previous studies show that blocking bugs take approximately two to three times longer to be fixed compared to non-blocking bugs. Objective: Thus, automatically predicting blocking bugs early on so that developers are aware of them, can help reduce the impact of or avoid blocking bugs. However, a major challenge when predicting blocking bugs is that only a small proportion of bugs are blocking bugs, i.e., there is an unequal distribution between blocking and non-blocking bugs. For example, in Eclipse and OpenOffice, only 2.8% and 3.0% bugs are blocking …
Tasknav: Task-Based Navigation Of Software Documentation, Christoph Treude, Mathieu Sicard, Marc Klocke, Martin P. Robillard
Tasknav: Task-Based Navigation Of Software Documentation, Christoph Treude, Mathieu Sicard, Marc Klocke, Martin P. Robillard
Research Collection School Of Computing and Information Systems
To help developers navigate documentation, we introduce Task Nav, a tool that automatically discovers and indexes task descriptions in software documentation. With Task Nav, we conceptualize tasks as specific programming actions that have been described in the documentation. Task Nav presents these extracted task descriptions along with concepts, code elements, and section headers in an auto-complete search interface. Our preliminary evaluation indicates that search results identified through extracted task descriptions are more helpful to developers than those found through other means, and that they help bridge the gap between documentation structure and the information needs of software developers. Video: https://www.youtube.com/watch?v=opnGYmMGnqY.
Multi-Agent Task Assignment For Mobile Crowdsourcing Under Trajectory Uncertainties, Cen Chen, Shih-Fen Cheng, Hoong Chuin Lau, Archan Misra
Multi-Agent Task Assignment For Mobile Crowdsourcing Under Trajectory Uncertainties, Cen Chen, Shih-Fen Cheng, Hoong Chuin Lau, Archan Misra
Research Collection School Of Computing and Information Systems
In this work, we investigate the problem of mobile crowdsourcing, where workers are financially motivated to perform location-based tasks physically. Unlike current industry practice that relies on workers to manually browse and filter tasks to perform, we intend to automatically make task recommendations based on workers' historical trajectories and desired time budgets. However, predicting workers' trajectories is inevitably faced with uncertainties, as no one will take exactly the same route every day; yet such uncertainties are oftentimes abstracted away in the known literature. In this work, we depart from the deterministic modeling and study the stochastic task recommendation problem where …
Flutcha: Using Fluency To Distinguish Humans From Computers, Kotaro Hara, Mohammad Taghi Hajiaghayi, Benjamin B. Benderson
Flutcha: Using Fluency To Distinguish Humans From Computers, Kotaro Hara, Mohammad Taghi Hajiaghayi, Benjamin B. Benderson
Research Collection School Of Computing and Information Systems
Improvements in image understanding technologies aremaking it possible for computers to pass traditionalCAPTCHA tests with high probability. This suggests theneed for new kinds of tasks that are easy to accomplishfor humans but remain difficult for computers. In thispaper, we introduce Fluency CAPTCHA (FluTCHA), anovel method to distinguish humans from computersusing the fact that humans are better than machines atimproving the fluency of sentences. We propose a wayto let users work on FluTCHA tests and simultaneouslycomplete useful linguistic tasks. Evaluation studiesdemonstrate the feasibility of using FluTCHA todistinguish humans from computers.
Rclinker: Automated Linking Of Issue Reports And Commits Leveraging Rich Contextual Information, Tien-Duy B. Le, Mario Linares Vasquez, David Lo, Denys Poshyvanyk
Rclinker: Automated Linking Of Issue Reports And Commits Leveraging Rich Contextual Information, Tien-Duy B. Le, Mario Linares Vasquez, David Lo, Denys Poshyvanyk
Research Collection School Of Computing and Information Systems
Links between issue reports and their corresponding commits in version control systems are often missing. However, these links are important for measuring the quality of a software system, predicting defects, and many other tasks. Several approaches have been designed to solve this problem by automatically linking bug reports to source code commits via comparison of textual information in commit messages and bug reports. Yet, the effectiveness of these techniques is oftentimes suboptimal when commit messages are empty or contain minimum information; this particular problem makes the process of recovering traceability links between commits and bug reports particularly challenging. In this …
Matchmaking Game Players On Public Transport, Nairan Zhang, Youngki Lee, Rajesh Krishna Balan
Matchmaking Game Players On Public Transport, Nairan Zhang, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
This paper extends our recent work, called GameOn, which presented a system for allowing public transport commuters to engage in multiplayer games with fellow commuters traveling on the same bus or train. An important challenge for GameOn is to group players with reliable connections into the same game. In this case, the meaning of reliability has two dimensions. First, the network connectivity (TCP, UDP etc.) should be robust. Second, the players should be collocated with each other for a sufficiently long duration so that a game session will not be terminated by players leaving the public transport modality such as …
Gameon: P2p Gaming On Public Transport, Nairan Zhang, Youngki Lee, Meera Radhakrishnan, Rajesh Krishna Balan
Gameon: P2p Gaming On Public Transport, Nairan Zhang, Youngki Lee, Meera Radhakrishnan, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Mobile games, and especially multiplayer games are a very popular daily distraction for many users. We hypothesise that commuters travelling on public buses or trains would enjoy being able to play multiplayer games with their fellow commuters to alleviate the commute burden and boredom. We present quantitative data to show that the typical one-way commute time is fairly long (at least 25 minutes on average) as well as survey results indicating that commuters are willing to play multiplayer games with other random commuters. In this paper, we present GameOn, a system that allows commuters to participate in multiplayer games with …
Towards Practical Graph-Based Verification For An Object-Oriented Concurrency Model, Alexander Heußner, Christopher M. Poskitt, Claudio Corrodi, Benjamin Morandi
Towards Practical Graph-Based Verification For An Object-Oriented Concurrency Model, Alexander Heußner, Christopher M. Poskitt, Claudio Corrodi, Benjamin Morandi
Research Collection School Of Computing and Information Systems
To harness the power of multi-core and distributed platforms, and to make the development of concurrent software more accessible to software engineers, different object-oriented concurrency models such as SCOOP have been proposed. Despite the practical importance of analysing SCOOP programs, there are currently no general verification approaches that operate directly on program code without additional annotations. One reason for this is the multitude of partially conflicting semantic formalisations for SCOOP (either in theory or by-implementation). Here, we propose a simple graph transformation system (GTS) based run-time semantics for SCOOP that grasps the most common features of all known semantics of …
Tlv: Abstraction Through Testing, Learning, And Validation, Jun Sun, Hao Xiao, Yang Liu, Shang-Wei Lin, Shengchao Qin
Tlv: Abstraction Through Testing, Learning, And Validation, Jun Sun, Hao Xiao, Yang Liu, Shang-Wei Lin, Shengchao Qin
Research Collection School Of Computing and Information Systems
A (Java) class provides a service to its clients (i.e., programs which use the class). The service must satisfy certain specifications. Different specifications might be expected at different levels of abstraction depending on the client's objective. In order to effectively contrast the class against its specifications, whether manually or automatically, one essential step is to automatically construct an abstraction of the given class at a proper level of abstraction. The abstraction should be correct (i.e., over-approximating) and accurate (i.e., with few spurious traces). We present an automatic approach, which combines testing, learning, and validation, to constructing an abstraction. Our approach …
Maximizing Lifetime In Clustered Wsns With Energy Harvesting Relay: Profiling And Modeling, Pengfei Zhang, Hwee-Pink Tan, Gaoxi Xiao, Yi Yu
Maximizing Lifetime In Clustered Wsns With Energy Harvesting Relay: Profiling And Modeling, Pengfei Zhang, Hwee-Pink Tan, Gaoxi Xiao, Yi Yu
Research Collection School Of Computing and Information Systems
Inspired by clustering and energy harvesting techniques, we study multiple-cluster wireless sensor networks with energy harvesting (EH) sensors serving as relay for cluster heads. In this paper, we derive the model for realistic energy harvesting rate. Then we propose distributed matching algorithm for EHs to serve as relay for CHs. The proposed algorithm could find optimal/near-optimal CH-EH matching in short time and still achieve good performance. We evaluate the performance of our method through theoretical analysis as well as simulation.
An Empirical Assessment Of Bellon's Clone Benchmark, Alan Charpentier, Jean-Rémy Falleri, David Lo, Laurent Reveillere
An Empirical Assessment Of Bellon's Clone Benchmark, Alan Charpentier, Jean-Rémy Falleri, David Lo, Laurent Reveillere
Research Collection School Of Computing and Information Systems
Context: Clone benchmarks are essential to the assessment and improvement of clone detection tools and algorithms. Among existing benchmarks, Bellon's benchmark is widely used by the research community. However, a serious threat to the validity of this benchmark is that reference clones it contains have been manually validated by Bellon alone. Other persons may disagree with Bellon's judgment. Objective: In this paper, we perform an empirical assessment of Bellon's benchmark. Method: We seek the opinion of eighteen participants on a subset of Bellon's benchmark to determine if researchers should trust the reference clones it contains. Results: Our experiment shows that …
High-Throughput Reliable Multicast In Multi-Hop Wireless Mesh Networks, Xin Zhao, Jun Guo, Chun Tung Chou, Archan Misra, Sanjay K. Jha
High-Throughput Reliable Multicast In Multi-Hop Wireless Mesh Networks, Xin Zhao, Jun Guo, Chun Tung Chou, Archan Misra, Sanjay K. Jha
Research Collection School Of Computing and Information Systems
This paper presents a cross-layer approach for enabling high-throughput reliable multicast in multi-hop wireless mesh networks. The building block of our approach is a multicast routing metric, called the expected multicast transmission count (EMTX). EMTX is designed to capture the combined effects of MAC-layer retransmission-based reliability, wireless broadcast advantage, and link quality awareness. The EMTX of single-hop transmission of a multicast packet from a sender is the expected number of multicast transmissions (including retransmissions) required for its next-hop recipients to receive the packet successfully. We formulate the EMTX-based multicast problem with the objective of minimizing the sum of EMTX over …
Sensorem – An Efficient Mobile Platform For Wireless Sensor Network Visualization, Jin Ming Koh, Marcus Sak, Hwee Xian Tan, Huiguang Liang, Fachmin Folianto, Tony Quek
Sensorem – An Efficient Mobile Platform For Wireless Sensor Network Visualization, Jin Ming Koh, Marcus Sak, Hwee Xian Tan, Huiguang Liang, Fachmin Folianto, Tony Quek
Research Collection School Of Computing and Information Systems
No abstract provided.
Queuevadis: Queuing Analytics Using Smartphones, Tadashi Okoshii, Lu Yu, Chetna Vig, Youngki Lee, Rajesh Krishna Balan, Archan Misra
Queuevadis: Queuing Analytics Using Smartphones, Tadashi Okoshii, Lu Yu, Chetna Vig, Youngki Lee, Rajesh Krishna Balan, Archan Misra
Research Collection School Of Computing and Information Systems
We present QueueVadis, a system that addresses the problem of estimating, in real-time, the properties of queues at commonplace urban locations, such as coffee shops, taxi stands and movie theaters. Abjuring the use of any queuing-specific infrastructure sensors, QueueVadis uses participatory mobile sensing to detect both (i) the individual-level queuing episodes for any arbitrarily-shaped queue (by a characteristic locomotive signature of short bursts of "shuffling forward" between periods of "standing") and (ii) the aggregate-level queue properties (such as expected wait or service times) via appropriate statistical aggregation of multi-person data. Moreover, for venues where multiple queues are too close …
Mobility Increases Localizability: A Survey On Wireless Indoor Localization Using Inertial Sensors, Zheng Yang, Chenshu Wu, Zimu Zhou, Xinglin Zhang, Xu Wang, Yunhao Liy
Mobility Increases Localizability: A Survey On Wireless Indoor Localization Using Inertial Sensors, Zheng Yang, Chenshu Wu, Zimu Zhou, Xinglin Zhang, Xu Wang, Yunhao Liy
Research Collection School Of Computing and Information Systems
Wireless indoor positioning has been extensively studied for the past two decades and continuously attracted growing research efforts in mobile computing context. As the integration of multiple inertial sensors (e.g., accelerometer, gyroscope, and magnetometer) to nowadays smartphones in recent years, human-centric mobility sensing is emerging and coming into vogue. Mobility information, as a new dimension in addition to wireless signals, can benefit localization in a number of ways, since location and mobility are by nature related in physical world. In this article, we survey this new trend of mobility enhancing smartphone-based indoor localization. Specifically, we first study how to measure …
Markov Decision Processes With Applications In Wireless Sensor Networks: A Survey, Abu Mohammad Alsheikh, Dinh Thai Hoang, Dusit Niyato, Hwee-Pink Tan
Markov Decision Processes With Applications In Wireless Sensor Networks: A Survey, Abu Mohammad Alsheikh, Dinh Thai Hoang, Dusit Niyato, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are used to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process …
Evaluating Defect Prediction Using A Massive Set Of Metrics, Xiao Xuan, David Lo, Xin Xia, Yuan Tian
Evaluating Defect Prediction Using A Massive Set Of Metrics, Xiao Xuan, David Lo, Xin Xia, Yuan Tian
Research Collection School Of Computing and Information Systems
To evaluate the performance of a within-project defect prediction approach, people normally use precision, recall, and F-measure scores. However, in machine learning literature, there are a large number of evaluation metrics to evaluate the performance of an algorithm, (e.g., Matthews Correlation Coefficient, G-means, etc.), and these metrics evaluate an approach from different aspects. In this paper, we investigate the performance of within-project defect prediction approaches on a large number of evaluation metrics. We choose 6 state-of-the-art approaches including naive Bayes, decision tree, logistic regression, kNN, random forest and Bayesian network which are widely used in defect prediction literature. And we …
Exploring Discriminative Features For Anomaly Detection In Public Spaces, Shriguru Nayak, Archan Misra, Kasthuri Jeyarajah, Philips Kokoh Prasetyo, Ee-Peng Lim
Exploring Discriminative Features For Anomaly Detection In Public Spaces, Shriguru Nayak, Archan Misra, Kasthuri Jeyarajah, Philips Kokoh Prasetyo, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Context data, collected either from mobile devices or from user-generated social media content, can help identify abnormal behavioural patterns in public spaces (e.g., shopping malls, college campuses or downtown city areas). Spatiotemporal analysis of such data streams provides a compelling new approach towards automatically creating real-time urban situational awareness, especially about events that are unanticipated or that evolve very rapidly. In this work, we use real-life datasets collected via SMU's LiveLabs testbed or via SMU's Palanteer software, to explore various discriminative features (both spatial and temporal - e.g., occupancy volumes, rate of change in topic{specific tweets or probabilistic distribution of …
Effect Of Machine Translation In Interlingual Conversation: Lessons From A Formative Study, Kotaro Hara, Shamsi T. Iqbal
Effect Of Machine Translation In Interlingual Conversation: Lessons From A Formative Study, Kotaro Hara, Shamsi T. Iqbal
Research Collection School Of Computing and Information Systems
Language barrier is the primary challenge for effectivecross-lingual conversations. Spoken language translation(SLT) is perceived as a cost-effective alternative to lessaffordable human interpreters, but little research has beendone on how people interact with such technology. Using aprototype translator application, we performed a formativeevaluation to elicit how people interact with the technologyand adapt their conversation style. We conducted two setsof studies with a total of 23 pairs (46 participants).Participants worked on storytelling tasks to simulate naturalconversations with 3 different interface settings. Ourfindings show that collocutors naturally adapt their style ofspeech production and comprehension to compensate forinadequacies in SLT. We conclude the paper …
Code Coverage And Test Suite Effectiveness: Empirical Study With Real Bugs In Large Systems, Pavneet Singh Kochhar, Ferdian Thung, David Lo
Code Coverage And Test Suite Effectiveness: Empirical Study With Real Bugs In Large Systems, Pavneet Singh Kochhar, Ferdian Thung, David Lo
Research Collection School Of Computing and Information Systems
During software maintenance, testing is a crucial activity to ensure the quality of program code as it evolves over time. With the increasing size and complexity of software, adequate software testing has become increasingly important. Code coverage is often used as a yardstick to gauge the comprehensiveness of test cases and the adequacy of testing. A test suite quality is often measured by the number of bugs it can find (aka. kill). Previous studies have analysed the quality of a test suite by its ability to kill mutants, i.e., artificially seeded faults. However, mutants do not necessarily represent real bugs. …
Using Infrastructure-Provided Context Filters For Efficient Fine-Grained Activity Sensing, Vigneshwaran Subbaraju, Sougata Sen, Archan Misra, Satyadip Chakraborty, Rajesh Krishna Balan
Using Infrastructure-Provided Context Filters For Efficient Fine-Grained Activity Sensing, Vigneshwaran Subbaraju, Sougata Sen, Archan Misra, Satyadip Chakraborty, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
While mobile and wearable sensing can capture unique insights into fine-grained activities (such as gestures and limb-based actions) at an individual level, their energy overheads are still prohibitive enough to prevent them from being executed continuously. In this paper, we explore practical alternatives to addressing this challenge-by exploring how cheap infrastructure sensors or information sources (e.g., BLE beacons) can be harnessed with such mobile/wearable sensors to provide an effective solution that reduces energy consumption without sacrificing accuracy. The key idea is that many fine-grained activities that we desire to capture are specific to certain location, movement or background context: infrastructure …
The Case For Smartwatch-Based Diet Monitoring, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee
The Case For Smartwatch-Based Diet Monitoring, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
We explore the use of gesture recognition on a wrist-worn smartwatch as an enabler of an automated eating activity (and diet monitoring) system. We show, using small-scale user studies, how it is possible to use the accelerometer and gyroscope data from a smartwatch to accurately separate eating episodes from similar non-eating activities, and to additionally identify the mode of eating (i.e., using a spoon, bare hands or chopsticks). Additionally, we investigate the likelihood of automatically triggering the smartwatch's camera to capture clear images of the food being consumed, for possible offline analysis to identify what (and how much) the user …
Improving Public Transit Accessibility For Blind Riders By Crowdsourcing Bus Stop Landmark Locations With Google Street View: An Extended Analysis, Kotaro Hara, Shiri Azenkot, Megan Campbell, Cynthia L. Bennett, Vicki Le, Sean Pannella, Robert Moore, Kelly Minckler, Rochelle H. Ng, Jon E. Froehlich
Improving Public Transit Accessibility For Blind Riders By Crowdsourcing Bus Stop Landmark Locations With Google Street View: An Extended Analysis, Kotaro Hara, Shiri Azenkot, Megan Campbell, Cynthia L. Bennett, Vicki Le, Sean Pannella, Robert Moore, Kelly Minckler, Rochelle H. Ng, Jon E. Froehlich
Research Collection School Of Computing and Information Systems
Low-vision and blind bus riders often rely on known physical landmarks to help locate and verify bus stoplocations (e.g., by searching for an expected shelter, bench, or newspaper bin). However, there are currentlyfew, if any, methods to determine this information a priori via computational tools or services. In thisarticle, we introduce and evaluate a new scalable method for collecting bus stop location and landmarkdescriptions by combining online crowdsourcing and Google Street View (GSV). We conduct and report onthree studies: (i) a formative interview study of 18 people with visual impairments to inform the designof our crowdsourcing tool, (ii) a comparative …