Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Databases and Information Systems (3560)
- Software Engineering (2205)
- Artificial Intelligence and Robotics (1897)
- Information Security (1108)
- Numerical Analysis and Scientific Computing (1060)
-
- Graphics and Human Computer Interfaces (947)
- Engineering (884)
- Social and Behavioral Sciences (808)
- Business (748)
- Theory and Algorithms (513)
- Computer Engineering (449)
- Programming Languages and Compilers (413)
- Operations Research, Systems Engineering and Industrial Engineering (407)
- OS and Networks (345)
- Communication (326)
- Social Media (264)
- Public Affairs, Public Policy and Public Administration (230)
- Medicine and Health Sciences (197)
- Education (194)
- Transportation (194)
- Management Information Systems (176)
- Data Storage Systems (167)
- E-Commerce (154)
- International and Area Studies (147)
- Technology and Innovation (146)
- Asian Studies (145)
- Health Information Technology (118)
- Higher Education (105)
- Keyword
-
- Machine learning (145)
- Deep learning (129)
- Artificial intelligence (124)
- Social media (82)
- Singapore (73)
-
- Reinforcement learning (72)
- Data mining (70)
- Privacy (67)
- Security (62)
- Cloud computing (60)
- Deep Learning (58)
- Empirical study (55)
- Software engineering (55)
- Optimization (54)
- Online learning (51)
- Visualization (51)
- Neural networks (50)
- Anomaly detection (49)
- Training (49)
- Twitter (49)
- Task analysis (48)
- Blockchain (47)
- Large Language Models (47)
- Natural language processing (47)
- Collaboration (46)
- Feature extraction (45)
- Algorithms (44)
- Access control (43)
- Machine Learning (43)
- Semantics (43)
- Publication Year
- Publication
-
- Research Collection School Of Computing and Information Systems (8479)
- Dissertations and Theses Collection (Open Access) (189)
- Research Collection Lee Kong Chian School Of Business (59)
- Research Collection Yong Pung How School Of Law (49)
- Research Collection School of Social Sciences (27)
-
- Asian Management Insights (26)
- Research Collection College of Integrative Studies (23)
- Perspectives@SMU (21)
- Research Collection School Of Accountancy (18)
- Dissertations and Theses Collection (15)
- FORCE 2026 (14)
- SMU Press Releases and News (12)
- MITB Thought Leadership Series (11)
- Research Collection School of Computing and Information Systems (11)
- Research Collection Library (10)
- Research@SMU: Connecting the Dots (10)
- PhD Student’s Publications Collection (8)
- LARC Research Publications (7)
- Research Collection School Of Economics (6)
- CCX Research (4)
- SMU Research Data (4)
- Student Publications (4)
- 2024 AI for Research Week (3)
- SCIS Student Publications (3)
- Centre for AI & Data Governance (2019-2025) (2)
- Research Collection Office of Research (2)
- CASTLe: Collection of Articles on Scholarship for Teaching and Learning (1)
- Centre for Computational Law (2022-2025) (1)
- Library Events (1)
- ROSA Journal Articles and Publications (1)
- Publication Type
- File Type
Articles 5071 - 5100 of 9025
Full-Text Articles in Computer Sciences
Breathprint: Breathing Acoustics-Based User Authentication, Jagmohan Chauhan, Yining Hu, Suranga Sereviratne, Archan Misra, Aruna Sereviratne, Youngki Lee
Breathprint: Breathing Acoustics-Based User Authentication, Jagmohan Chauhan, Yining Hu, Suranga Sereviratne, Archan Misra, Aruna Sereviratne, Youngki Lee
Research Collection School Of Computing and Information Systems
We propose BreathPrint, a new behavioural biometric signature based on audio features derived from an individual's commonplace breathing gestures. Specifically, BreathPrint uses the audio signatures associated with the three individual gestures: sniff, normal, and deep breathing, which are sufficiently different across individuals. Using these three breathing gestures, we develop the processing pipeline that identifies users via the microphone sensor on smartphones and wearable devices. In BreathPrint, a user performs breathing gestures while holding the device very close to their nose. Using off-the-shelf hardware, we experimentally evaluate the BreathPrint prototype with 10 users, observed over seven days. We show that users …
Measuring The Declared Sdk Versions And Their Consistency With Api Calls In Android Apps, Daoyuan Wu, Ximing Liu, Jiayun Xu, David Lo, Debin Gao
Measuring The Declared Sdk Versions And Their Consistency With Api Calls In Android Apps, Daoyuan Wu, Ximing Liu, Jiayun Xu, David Lo, Debin Gao
Research Collection School Of Computing and Information Systems
Android has been the most popular smartphone system, with multiple platform versions (e.g., KITKAT and Lollipop) active in the market. To manage the application’s compatibility with one or more platform versions, Android allows apps to declare the supported platform SDK versions in their manifest files. In this paper, we make a first effort to study this modern software mechanism. Our objective is to measure the current practice of the declared SDK versions (which we term as DSDK versions afterwards) in real apps, and the consistency between the DSDK versions and their app API calls. To this end, we perform a …
Employing Smartwatch For Enhanced Password Authentication, Bing Chang, Ximing Liu, Yingjiu Li, Pingjian Wang, Wen-Tao Zhu, Zhan Wang
Employing Smartwatch For Enhanced Password Authentication, Bing Chang, Ximing Liu, Yingjiu Li, Pingjian Wang, Wen-Tao Zhu, Zhan Wang
Research Collection School Of Computing and Information Systems
This paper presents an enhanced password authentication scheme by systematically exploiting the motion sensors in a smartwatch. We extract unique features from the sensor data when a smartwatch bearer types his/her password (or PIN), and train certain machine learning classifiers using these features. We then implement smartwatch-aided password authentication using the classifiers. Our scheme is user-friendly since it does not require users to perform any additional actions when typing passwords or PINs other than wearing smartwatches. We conduct a user study involving 51 participants on the developed prototype so as to evaluate its feasibility and performance. Experimental results show that …
Exploiting Android System Services Through Bypassing Service Helpers, Yachong Gu, Yao Cheng, Lingyun Ying, Yemian Lu, Qi Li, Purui Su
Exploiting Android System Services Through Bypassing Service Helpers, Yachong Gu, Yao Cheng, Lingyun Ying, Yemian Lu, Qi Li, Purui Su
Research Collection School Of Computing and Information Systems
Android allows applications to communicate with system service via system service helper so that applications can use various functions wrapped in the system services. Meanwhile, system services leverage the service helpers to enforce security mechanisms, e.g. input parameter validation, to protect themselves against attacks. However, service helpers can be easily bypassed, which poses severe security and privacy threats to system services, e.g., privilege escalation, function execution without users’ interactions, system service crash, and DoS attacks. In this paper, we perform the first systematic study on such vulnerabilities and investigate their impacts. We develop a tool to analyze all system services …
Local Gaussian Processes For Efficient Fine-Grained Traffic Speed Prediction, Truc Viet Le, Richard Oentaryo, Siyuan Liu, Hoong Chuin Lau
Local Gaussian Processes For Efficient Fine-Grained Traffic Speed Prediction, Truc Viet Le, Richard Oentaryo, Siyuan Liu, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Traffic speed is a key indicator for the efficiency of an urban transportation system. Accurate modeling of the spatiotemporally varying traffic speed thus plays a crucial role in urban planning and development. This paper addresses the problem of efficient fine-grained traffic speed prediction using big traffic data obtained from static sensors. Gaussian processes (GPs) have been previously used to model various traffic phenomena, including flow and speed. However, GPs do not scale with big traffic data due to their cubic time complexity. In this work, we address their efficiency issues by proposing localGPs to learn from and make predictions for …
Tackling Large-Scale Home Health Care Delivery Problem With Uncertainty, Cen Chen, Zachary Rubinstein, Stephen Smith, Hoong Chuin Lau
Tackling Large-Scale Home Health Care Delivery Problem With Uncertainty, Cen Chen, Zachary Rubinstein, Stephen Smith, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In this work, we investigate a multi-period Home HealthCare Scheduling Problem (HHCSP) under stochastic serviceand travel times. We first model the deterministic problemas an integer linear programming model that incorporatesreal-world requirements, such as time windows, continuityof care, workload fairness, inter-visit temporal dependencies.We then extend the model to cope with uncertainty in durations,by introducing chance constraints into the formulation.We propose efficient solution approaches, which providequantifiable near-optimal solutions and further handlethe uncertainties by employing a sampling-based strategy. Wedemonstrate the effectiveness of our proposed approaches oninstances synthetically generated by real-world dataset forboth deterministic and stochastic scenarios.
Augmenting Decisions Of Taxi Drivers Through Reinforcement Learning For Improving Revenues, Tanvi Verma, Pradeep Varakantham, Sarit Kraus, Hoong Chuin Lau
Augmenting Decisions Of Taxi Drivers Through Reinforcement Learning For Improving Revenues, Tanvi Verma, Pradeep Varakantham, Sarit Kraus, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Taxis (which include cars working with car aggregation systems such as Uber, Grab, Lyft etc.) have become a critical component in the urban transportation. While most research and applications in the context of taxis have focused on improving performance from a customer perspective, in this paper,we focus on improving performance from a taxi driver perspective. Higher revenues for taxi drivers can help bring more drivers into the system thereby improving availability for customers in dense urban cities.Typically, when there is no customer on board, taxi driverswill cruise around to find customers either directly (on thestreet) or indirectly (due to a …
Webapirec: Recommending Web Apis To Software Projects Via Personalized Ranking, Ferdian Thung, Richard J. Oentaryo, David Lo, Yuan Tian
Webapirec: Recommending Web Apis To Software Projects Via Personalized Ranking, Ferdian Thung, Richard J. Oentaryo, David Lo, Yuan Tian
Research Collection School Of Computing and Information Systems
Application programming interfaces (APIs) offer a plethora of functionalities for developers to reuse without reinventing the wheel. Identifying the appropriate APIs given a project requirement is critical for the success of a project, as many functionalities can be reused to achieve faster development. However, the massive number of APIs would often hinder the developers' ability to quickly find the right APIs. In this light, we propose a new, automated approach called WebAPIRec that takes as input a project profile and outputs a ranked list of web APIs that can be used to implement the project. At its heart, WebAPIRec employs …
Online Advertising, Retail Platform Openness, And Long Tail Sellers, Jianqing Chen, Zhiling Guo
Online Advertising, Retail Platform Openness, And Long Tail Sellers, Jianqing Chen, Zhiling Guo
Research Collection School Of Computing and Information Systems
It becomes increasingly popular that some large online retailers such as Amazon open their platforms to allow third-party retail competitors to sell on their own platforms. We develop an analytical model to examine this retailer market place model and its business impact. We assume that a leading retailer has both valuation advantage that may come from its reputation and information advantage that may come from its brand awarenewss. We find that the availability of relatively low-cost advertising through social media or search engine can effectively reduce the leading retailer's information advantage, and thus be an important driving force for its …
Online Repositioning In Bike Sharing Systems, Meghna Lowalekar, Pradeep Varakantham, Supriyo Ghosh, Sanjay Dominic Jena, Patrick Jaillet
Online Repositioning In Bike Sharing Systems, Meghna Lowalekar, Pradeep Varakantham, Supriyo Ghosh, Sanjay Dominic Jena, Patrick Jaillet
Research Collection School Of Computing and Information Systems
Due to increased traffic congestion and carbon emissions, Bike Sharing Systems (BSSs) are adopted in various cities for short distance travels, specifically for last mile transportation. The success of a bike sharing system depends on its ability to have bikes available at the "right" base stations at the "right" times. Typically, carrier vehicles are used to perform repositioning of bikes between stations so as to satisfy customer requests. Owing to the uncertainty in customer demand and day-long repositioning, the problem of having bikes available at the right base stations at the right times is a challenging one. In this paper, …
Sampling Based Approaches For Minimizing Regret In Uncertain Markov Decision Problems (Mdps), Asrar Ahmed, Pradeep Varakantham, Meghna Lowalekar, Yossiri Adulyasak, Patrick Jaillet
Sampling Based Approaches For Minimizing Regret In Uncertain Markov Decision Problems (Mdps), Asrar Ahmed, Pradeep Varakantham, Meghna Lowalekar, Yossiri Adulyasak, Patrick Jaillet
Research Collection School Of Computing and Information Systems
Markov Decision Processes (MDPs) are an effective model to represent decision processes in the presence of transitional uncertainty and reward tradeoffs. However, due to the difficulty in exactly specifying the transition and reward functions in MDPs, researchers have proposed uncertain MDP models and robustness objectives in solving those models. Most approaches for computing robust policies have focused on the computation of maximin policies which maximize the value in the worst case amongst all realisations of uncertainty. Given the overly conservative nature of maximin policies, recent work has proposed minimax regret as an ideal alternative to the maximin objective for robust …
Understanding Music Track Popularity In A Social Network, Jing Ren, Robert J. Kauffman
Understanding Music Track Popularity In A Social Network, Jing Ren, Robert J. Kauffman
Research Collection School Of Computing and Information Systems
Thousands of music tracks are uploaded to the Internet every day through websites and social networks that focus on music. While some content has been popular for decades, some tracks that have just been released have been ignored. What makes a music track popular? Can the duration of a music track’s popularity be explained and predicted? By analysing data on the performance of a music track on the ranking charts, coupled with the creation of machine-generated music semantics constructs and a variety of other track, artist and market descriptors, this research tests a model to assess how track popularity and …
Charitable Fundraising: Gaining Donors' Trust On Online Platforms, Deserinas Sulaeman
Charitable Fundraising: Gaining Donors' Trust On Online Platforms, Deserinas Sulaeman
Research Collection School Of Computing and Information Systems
Trust is crucial in the relationships between charitable fundraisers and potential donors. This study examines factors that can help fundraisers gain potential donors’ trust, which is crucial to the success of the campaigns. Examining charitable fundraising campaigns on an online platform, this study finds that trust issues can be mitigated by providing a campaign description that is more sophisticated, more informative, and with fewer errors. Additionally, setting a higher campaign funding goal tends to lead to a more successful campaign. These characteristics likely reflect a competent, committed, and passionate fundraiser. On the other hand, mere exposure to a wide set …
Processing Long Queries Against Short Text: Top-K Advertisement Matching In News Stream Applications, Dongxiang Zhang, Yuchen Li, Ju Fan, Lianli Gao, Fumin Shen, Heng Tao Shen
Processing Long Queries Against Short Text: Top-K Advertisement Matching In News Stream Applications, Dongxiang Zhang, Yuchen Li, Ju Fan, Lianli Gao, Fumin Shen, Heng Tao Shen
Research Collection School Of Computing and Information Systems
Many real applications in real-time news stream advertising call for efficient processing of long queriesagainst short text. In such applications, dynamic news feeds are regarded as queries to match against anadvertisement (ad) database for retrieving the k most relevant ads. The existing approaches to keywordretrieval cannot work well in this search scenario when queries are triggered at a very high frequency.To address the problem, we introduce new techniques to significantly improve search performance. First,we devise a two-level partitioning for tight upper bound estimation and a lazy evaluation scheme to delayfull evaluation of unpromising candidates, which can bring three to four …
Flexible Wildcard Searchable Encryption System, Yang Yang, Ximeng Liu, Robert H. Deng, Jian Weng
Flexible Wildcard Searchable Encryption System, Yang Yang, Ximeng Liu, Robert H. Deng, Jian Weng
Research Collection School Of Computing and Information Systems
Searchable encryption is an important technique for public cloud storage service to provide user data confidentiality protection and at the same time allow users performing keyword search over their encrypted data. Previous schemes only deal with exact or fuzzy keyword search to correct some spelling errors. In this paper, we propose a new wildcard searchable encryption system to support wildcard keyword queries which has several highly desirable features. First, our system allows multiple keywords search in which any queried keyword may contain zero, one or two wildcards, and a wildcard may appear in any position of a keyword and represent …
Well-Tuned Algorithms For The Team Orienteering Problem With Time Windows, Aldy Gunawan, Hoong Chuin Lau, Kun Lu, Lu Kun
Well-Tuned Algorithms For The Team Orienteering Problem With Time Windows, Aldy Gunawan, Hoong Chuin Lau, Kun Lu, Lu Kun
Research Collection School Of Computing and Information Systems
The Team Orienteering Problem with Time Windows (TOPTW) is the extension of the Orienteering Problem (OP) where each node is limited by a predefined time window during which the service has to start. The objective of the TOPTW is to maximize the total collected score by visiting a set of nodes with a limited number of paths. We propose two algorithms, Iterated Local Search and a hybridization of Simulated Annealing and Iterated Local Search (SAILS), to solve the TOPTW. As indicated in multiple research works on algorithms for the OP and its variants, determining appropriate parameter values in a statistical …
Collaboration In 360° Videochat: Challenges And Opportunities, Anthony Tang, Omid Fakourfar, Carman Neustaedter, Scott Bateman
Collaboration In 360° Videochat: Challenges And Opportunities, Anthony Tang, Omid Fakourfar, Carman Neustaedter, Scott Bateman
Research Collection School Of Computing and Information Systems
We designed a videochat experience where one participant can experience a remote environment from a 360° camera. This allows the remote user to view and explore the environment without necessitating interaction from the local participant. We designed and conducted an observational study to understand the experience, and the challenges that people might encounter. In a study with 32 participants (16 pairs), we found that remote participants could actively participate in the experience with the environment in ways that are not possible with current mobile video chat. However, we also found that participants had challenges in communicating location and orientation information …
On Self-Selection Biases In Online Product Reviews, Nan Hu, Paul A. Pavlou, Jie Zhang
On Self-Selection Biases In Online Product Reviews, Nan Hu, Paul A. Pavlou, Jie Zhang
Research Collection School Of Computing and Information Systems
Online product reviews help consumers infer product quality, and the mean (average) rating is often used as a proxy for product quality. However, two self-selection biases, acquisition bias (mostly consumers with a favorable predisposition acquire a product and hence write a product review) and underreporting bias (consumers with extreme, either positive or negative, ratings are more likely to write reviews than consumers with moderate product ratings), render the mean rating a biased estimator of product quality, and they result in the well-known J-shaped (positively skewed, asymmetric, bimodal) distribution of online product reviews. To better understand the nature and consequences of …
Scan: Multi-Hop Calibration For Mobile Sensor Arrays, Balz Maag, Zimu Zhou, Olga Saukh, Lothar Thiele
Scan: Multi-Hop Calibration For Mobile Sensor Arrays, Balz Maag, Zimu Zhou, Olga Saukh, Lothar Thiele
Research Collection School Of Computing and Information Systems
Urban air pollution monitoring with mobile, portable, low-cost sensors has attracted increasing research interest for their wide spatial coverage and affordable expenses to the general public. However, low-cost air quality sensors not only drift over time but also suffer from cross-sensitivities and dependency on meteorological effects. Therefore calibration of measurements from low-cost sensors is indispensable to guarantee data accuracy and consistency to be fit for quantitative studies on air pollution. In this work we propose sensor array network calibration (SCAN), a multi-hop calibration technique for dependent low-cost sensors. SCAN is applicable to sets of co-located, heterogeneous sensors, known as sensor …
Denoising Autoencoders For Fast Real-Time Traffic Estimation On Urban Road Networks, Soham Ghosh, Muhammad Tayyab Asif, Laura Wynter
Denoising Autoencoders For Fast Real-Time Traffic Estimation On Urban Road Networks, Soham Ghosh, Muhammad Tayyab Asif, Laura Wynter
Research Collection School Of Computing and Information Systems
We propose a new method for traffic state estimation applicable to large urban road networks where a significant amount of the real-time and historical data is missing. Our proposed approach involves estimating the missing historical data through low-rank matrix completion, coupled with an online estimation approach for estimating the missing real-time data. In contrast to the traditional approach, the proposed method does not require re-calibration every time new streaming data becomes available. Empirical results from two metropolitan cities show that the proposed two-step approach provides comparable accuracy to a state of the art benchmark method while achieving two orders of …
The Retransmission Of Rumor And Rumor Correction Messages On Twitter, Alton Y. K. Chua, Cheng-Ying Tee, Augustine Pang, Ee-Peng Lim
The Retransmission Of Rumor And Rumor Correction Messages On Twitter, Alton Y. K. Chua, Cheng-Ying Tee, Augustine Pang, Ee-Peng Lim
Research Collection Lee Kong Chian School Of Business
This article seeks to examine the relationships among source credibility, message plausibility, message type (rumor or rumor correction) and retransmission of tweets in a rumoring situation. From a total of 5,885 tweets related to the rumored death of the founding father of Singapore Lee Kuan Yew, 357 original tweets without an “RT” prefix were selected and analyzed using negative binomial regression analysis. The results show that source credibility and message plausibility are correlated with retransmission. Also, rumor correction tweets are retweeted more than rumor tweets. Moreover, message type moderates the relationship between source credibility and retransmission as well as that …
Exception Handling Bug Hazards In Android: Results From A Mining Study And An Exploratory Survey, Roberta Coelho, Lucas Almeida, Georgios Gousios, Arie Van Deursen, Christoph Treude
Exception Handling Bug Hazards In Android: Results From A Mining Study And An Exploratory Survey, Roberta Coelho, Lucas Almeida, Georgios Gousios, Arie Van Deursen, Christoph Treude
Research Collection School Of Computing and Information Systems
Adequate handling of exceptions has proven difficult for many software engineers. Mobile app developers in particular, have to cope with compatibility, middleware, memory constraints, and battery restrictions. The goal of this paper is to obtain a thorough understanding of common exception handling bug hazards that app developers face. To that end, we first provide a detailed empirical study of over 6,000 Java exception stack traces we extracted from over 600 open source Android projects. Key insights from this study include common causes for system crashes, and common chains of wrappings between checked and unchecked exceptions. Furthermore, we provide a survey …
Using Contextual Information To Predict Co-Changes, Igor Scaliante Wiese, Reginaldo Ré, Igor Steinmacher, Rodrigo Takashi Kuroda, Gustavo A. Oliva, Christoph Treude, Marco Aurélio Gerosa
Using Contextual Information To Predict Co-Changes, Igor Scaliante Wiese, Reginaldo Ré, Igor Steinmacher, Rodrigo Takashi Kuroda, Gustavo A. Oliva, Christoph Treude, Marco Aurélio Gerosa
Research Collection School Of Computing and Information Systems
Background: Co-change prediction makes developers aware of which artifacts will change together with the artifact they are working on. In the past, researchers relied on structural analysis to build prediction models. More recently, hybrid approaches relying on historical information and textual analysis have been proposed. Despite the advances in the area, software developers still do not use these approaches widely, presumably because of the number of false recommendations. We conjecture that the contextual information of software changes collected from issues, developers’ communication, and commit metadata captures the change patterns of software artifacts and can improve the prediction models. Objective: Our …
On The Similarities Between Random Regret Minimization And Mother Logit: The Case Of Recursive Route Choice Models, Tien Mai, Fabian Bastin, Emma Frejinger
On The Similarities Between Random Regret Minimization And Mother Logit: The Case Of Recursive Route Choice Models, Tien Mai, Fabian Bastin, Emma Frejinger
Research Collection School Of Computing and Information Systems
This paper focuses on the comparison of the random regret minimization (RRM) and mother logit models for analyzing the choice between alternatives having deterministic attributes. The mother logit model allows utilities of a given alternative to depend on attributes of other alternatives. It was designed to relax the independence from irrelevant alternatives (IIA) property while keeping the random terms independently and identically distributed extreme value distributed (McFadden et al., 1978).We adapt and extend the RRM model proposed by Chorus (2014) to the case of recursive logit (RL) route choice models (Fosgerau et al., 2013). We argue that these RRM models …
Is The Whole Greater Than The Sum Of Its Parts?, Liangyue Li, Hanghang Tong, Yong Wang, Conglei Shi, Nan Cao, Norbou Buchler
Is The Whole Greater Than The Sum Of Its Parts?, Liangyue Li, Hanghang Tong, Yong Wang, Conglei Shi, Nan Cao, Norbou Buchler
Research Collection School Of Computing and Information Systems
The PART-WHOLE relationship routinely finds itself in many disciplines, ranging from collaborative teams, crowdsourcing, autonomous systems to networked systems. From the algorithmic perspective, the existing work has primarily focused on predicting the outcomes of the whole and parts, by either separate models or linear joint models, which assume the outcome of the parts has a linear and independent effect on the outcome of the whole. In this paper, we propose a joint predictive method named PAROLE to simultaneously and mutually predict the part and whole outcomes. The proposed method offers two distinct advantages over the existing work. First (Model Generality), …
Inferring Motion Direction Using Commodity Wi-Fi For Interactive Exergames, Kun Qian, Chenshu Wu, Zimu Zhou, Yue Zheng, Yang Zheng, Yunhao Liu
Inferring Motion Direction Using Commodity Wi-Fi For Interactive Exergames, Kun Qian, Chenshu Wu, Zimu Zhou, Yue Zheng, Yang Zheng, Yunhao Liu
Research Collection School Of Computing and Information Systems
In-air interaction acts as a key enabler for ambient intelligence and augmented reality. As an increasing popular example, exergames, and the alike gesture recognition applications, have attracted extensive research in designing accurate, pervasive and low-cost user interfaces. Recent advances in wireless sensing show promise for a ubiquitous gesture-based interaction interface with Wi-Fi. In this work, we extract complete information of motion-induced Doppler shifts with only commodity Wi-Fi. The key insight is to harness antenna diversity to carefully eliminate random phase shifts while retaining relevant Doppler shifts. We further correlate Doppler shifts with motion directions, and propose a light-weight pipeline to …
Tum: Towards Ubiquitous Multi-Device Localization For Cross-Device Interaction, Han Xu, Zheng Yang, Zimu Zhou, Ke Yi, Chunyi Peng
Tum: Towards Ubiquitous Multi-Device Localization For Cross-Device Interaction, Han Xu, Zheng Yang, Zimu Zhou, Ke Yi, Chunyi Peng
Research Collection School Of Computing and Information Systems
Cross-device interaction is becoming an increasingly hot topic as we often have multiple devices at our immediate disposal in this era of mobile computing. Various cross-device applications such as file sharing, multi-screen display, and crossdevice authentication have been proposed and investigated. However, one of the most fundamental enablers remains unsolved: How to achieve ubiquitous multi-device localization? Though pioneer efforts have resorted to gesture-assisted or sensing-assisted localization, they either require extensive user participation or impose some strong assumptions on device sensing abilities. This introduces extra costs and constraints, and thus degrades their practicality. To overcome these limitations, we propose TUM, an …
Aspect Discovery From Product Reviews, Ying Ding
Aspect Discovery From Product Reviews, Ying Ding
Dissertations and Theses Collection
With the rapid development of online shopping sites and social media, product reviews are accumulating. These reviews contain information that is valuable to both businesses and customers. To businesses, companies can easily get a large number of feedback of their products, which is difficult to achieve by doing customer survey in the traditional way. To customers, they can know the products they are interested in better by reading reviews, which may be uneasy without online reviews. However, the accumulation has caused consuming all reviews impossible. It is necessary to develop automated techniques to efficiently process them. One of the most …
Mining Software Repositories For Automatic Software Bug Management From Bug Triaging To Patch Backporting, Yuan Tian
Dissertations and Theses Collection
Software systems are often released with bugs due to system complexity and inadequate testing. Bug resolving process plays an important role in development and evolution of software systems because developers could collect a considerable number of bugs from users and testers daily. For instance, during September 2015, the Eclipse project received approximately 2,500 bug reports, averaging 80 new reports each day. To help developers effectively address and manage bugs, bug tracking systems such as Bugzilla and JIRA are adopted to manage the life cycle of a bug through bug report. Since most of the information related to bugs are stored …
Proactive And Reactive Strategies To Handle Surges In Urban Crowds, Jiali Du
Proactive And Reactive Strategies To Handle Surges In Urban Crowds, Jiali Du
Dissertations and Theses Collection
Most urban infrastructures are built to cater a planned capacity, yet surges in usage do happen in times (can be either expected or unexpected), and this has long been a major challenge for urban planner. In this thesis, I propose to study approaches handle surges in urban crowd movement. In particular, the surges in demand studied are limited to situations where a large crowd of commuters/visitors gather in a small vicinity, and I am concerned with their movements both within the vicinity and out of the vicinity (the egress from the vicinity). Significant crowd build-ups and congestions can be observed …