Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Databases and Information Systems (3441)
- Software Engineering (2143)
- Artificial Intelligence and Robotics (1665)
- Information Security (1057)
- Numerical Analysis and Scientific Computing (1024)
-
- Graphics and Human Computer Interfaces (921)
- Engineering (858)
- Social and Behavioral Sciences (661)
- Business (625)
- Theory and Algorithms (493)
- Computer Engineering (431)
- Operations Research, Systems Engineering and Industrial Engineering (400)
- Programming Languages and Compilers (379)
- OS and Networks (323)
- Communication (297)
- Social Media (240)
- Public Affairs, Public Policy and Public Administration (207)
- Transportation (185)
- Medicine and Health Sciences (178)
- Education (164)
- Management Information Systems (164)
- Data Storage Systems (160)
- E-Commerce (146)
- Health Information Technology (107)
- International and Area Studies (107)
- Asian Studies (106)
- Technology and Innovation (100)
- Digital Communications and Networking (96)
- Keyword
-
- Deep learning (123)
- Machine learning (121)
- Social media (74)
- Artificial intelligence (70)
- Reinforcement learning (69)
-
- Data mining (64)
- Privacy (61)
- Cloud computing (58)
- Deep Learning (56)
- Empirical study (54)
- Optimization (53)
- Security (53)
- Visualization (51)
- Software engineering (49)
- Training (49)
- Neural networks (48)
- Online learning (48)
- Task analysis (48)
- Anomaly detection (47)
- Singapore (47)
- Twitter (46)
- Feature extraction (45)
- Blockchain (44)
- Collaboration (44)
- Large Language Models (43)
- Semantics (43)
- Access control (41)
- Algorithms (40)
- Android (39)
- Machine Learning (38)
- Publication Year
- File Type
Articles 5221 - 5250 of 8481
Full-Text Articles in Computer Sciences
A Comparison Of Fundamental Network Formation Principles Between Offline And Online Friends On Twitter, Felicia Natali, Feida Zhu
A Comparison Of Fundamental Network Formation Principles Between Offline And Online Friends On Twitter, Felicia Natali, Feida Zhu
Research Collection School Of Computing and Information Systems
We investigate the differences between how some of the fundamental principles of network formation apply among offline friends and how they apply among online friends on Twitter. We consider three fundamental principles of network formation proposed by Schaefer et al.: reciprocity, popularity, and triadic closure. Overall, we discover that these principles mainly apply to offline friends on Twitter. Based on how these principles apply to offline versus online friends, we formulate rules to predict offline friendship on Twitter. We compare our algorithm with popular machine learning algorithms and Xiewei’s random walk algorithm. Our algorithm beats the machine learning algorithms on …
Data Analytics On Consumer Behavior In Omni-Channel Retail Banking, Card And Payment Services, Geng Dan
Data Analytics On Consumer Behavior In Omni-Channel Retail Banking, Card And Payment Services, Geng Dan
Research Collection School Of Computing and Information Systems
Innovations in financial services have created challenges for banks that Information Systems (IS) research can address. My interests involve transaction cost theory, substitution and complementarity theory, and consumer informedness theory to understand consumer behavior and firm performance in the omni-channel world of digital banking. At a high level, my research inquiry asks: How can financial institutions take advantage of the deep insights that data analytics and management science modeling create on consumer behavior and channel management decision-making? And how can changes in payments and services in retail banking be understood in spatial and temporal terms? I am working on three …
Object Pooling For Multimedia Event Detection And Evidence Localization, Ho Zhang, Chong-Wah Ngo, Chong-Wah Ngo
Object Pooling For Multimedia Event Detection And Evidence Localization, Ho Zhang, Chong-Wah Ngo, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Multimedia event detection (MED) and evidence hunting are two primary topics in the area of multimedia event search. The former serves to retrieve a list of relevant videos given an event query, whereas, the latter reasons why and how much the degree a retrieved video answers that query. Common practices deal with these two topics in separate methods, however, in this paper, we combine MED and evidence hunting into a joint framework. We propose a refined semantical representation named object pooling which can dynamically extract visual snippets corresponding to the location of when and where evidences might appear. The main …
Regular Symmetry Patterns, Anthony W. Lin, Truong Khanh Nguyen, Philipp Rümmer, Jun Sun
Regular Symmetry Patterns, Anthony W. Lin, Truong Khanh Nguyen, Philipp Rümmer, Jun Sun
Research Collection School Of Computing and Information Systems
Symmetry reduction is a well-known approach for alleviating the state explosion problem in model checking. Automatically identifying symmetries in concurrent systems, however, is computationally expensive. We propose a symbolic framework for capturing symmetry patterns in parameterised systems (i.e. an infinite family of finite-state systems): two regular word transducers to represent, respectively, parameterised systems and symmetry patterns. The framework subsumes various types of “symmetry relations” ranging from weaker notions (e.g. simulation preorders) to the strongest notion (i.e. isomorphisms). Our framework enjoys two algorithmic properties: (1) symmetry verification: given a transducer, we can automatically check whether it is a symmetry pattern of …
On Detecting Maximal Quasi Antagonistic Communities In Signed Graphs, Ming Gao, Ee-Peng Lim, David Lo, Philips Kokoh Prasetyo
On Detecting Maximal Quasi Antagonistic Communities In Signed Graphs, Ming Gao, Ee-Peng Lim, David Lo, Philips Kokoh Prasetyo
Research Collection School Of Computing and Information Systems
Many networks can be modeled as signed graphs. These include social networks, and relationships/interactions networks. Detecting sub-structures in such networks helps us understand user behavior, predict links, and recommend products. In this paper, we detect dense sub-structures from a signed graph, called quasi antagonistic communities (QACs). An antagonistic community consists of two groups of users expressing positive relationships within each group but negative relationships across groups. Instead of requiring complete set of negative links across its groups, a QAC allows a small number of inter-group negative links to be missing. We propose an algorithm, Mascot, to find all maximal quasi …
Top-K Dominating Queries On Incomplete Data, Xiaoye Miao, Yunjun Gao, Baihua Zheng, Gang Chen, Huiyong Cui
Top-K Dominating Queries On Incomplete Data, Xiaoye Miao, Yunjun Gao, Baihua Zheng, Gang Chen, Huiyong Cui
Research Collection School Of Computing and Information Systems
The top-k dominating (TKD) query returns the k objects that dominate the maximum number of objects in a given dataset. It combines the advantages of skyline and top-k queries, and plays an important role in many decision support applications. Incomplete data exists in a wide spectrum of real datasets, due to device failure, privacy preservation, data loss, and so on. In this paper, for the first time, we carry out a systematic study of TKD queries on incomplete data, which involves the data having some missing dimensional value(s). We formalize this problem, and propose a suite of efficient algorithms for …
Synergizing Specification Miners Through Model Fissions And Fusions, Le Bui Tien Duy, Le Dinh Xuan Bach, David Lo, Ivan Beschastnikh
Synergizing Specification Miners Through Model Fissions And Fusions, Le Bui Tien Duy, Le Dinh Xuan Bach, David Lo, Ivan Beschastnikh
Research Collection School Of Computing and Information Systems
Software systems are often developed and released without formal specifications. For those systems that are formally specified, developers have to continuously maintain and update the specifications or have them fall out of date. To deal with the absence of formal specifications, researchers have proposed techniques to infer the missing specifications of an implementation in a variety of forms, such as finite state automaton (FSA). Despite the progress in this area, the efficacy of the proposed specification miners needs to improve if these miners are to be adopted. We propose SpecForge, a new specification mining approach that synergizes many existing specification …
Investigating The Influence Of Offline Friendship On Twitter Networking Behaviors, Young Soo Kim, Felicia Natali, Feida Zhu, Ee-Peng Lim
Investigating The Influence Of Offline Friendship On Twitter Networking Behaviors, Young Soo Kim, Felicia Natali, Feida Zhu, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
We investigate the influence of offline friendship in three specific areas of Twitter networking behaviors: (a) network structure, (b) Twitter content and (c) interaction on Twitter. We observe some interesting findings through the empirical analysis of 2193 pairs of users who are online friends. When these pairs of users know each other offline, they are more likely to (1) respond to the online gesture of friendship from their friend, (2) share mutual online friends, (3) distribute and gather information in their friend’s Twitter network, (4) pay attention to their friend’s tweets, (5) post tweets that might be of interest to …
Posting Topics ≠ Reading Topics: On Discovering Posting And Reading Topics In Social Media, Wei Gong, Ee-Peng Lim, Feida Zhu
Posting Topics ≠ Reading Topics: On Discovering Posting And Reading Topics In Social Media, Wei Gong, Ee-Peng Lim, Feida Zhu
Research Collection School Of Computing and Information Systems
Social media users make decisions about what content to post and read. As posted content is often visible to others, users are likely to impose self-censorship when deciding what content to post. On the other hand, such a concern may not apply to reading social media content. As a result, the topics of content that a user posted and read can be different and this has major implications to the applications that require personalization. To better determine and profile social media users’ topic interests, we conduct a user survey in Twitter. In this survey, participants chose the topics they like …
Demo: Profiling Power Utilization Behaviours Of Smartwatch Applications, Joseph Joo Keng Chan, Lingxiao Jiang, Rajesh Krishna Balan, Youngki Lee, Archan Misra
Demo: Profiling Power Utilization Behaviours Of Smartwatch Applications, Joseph Joo Keng Chan, Lingxiao Jiang, Rajesh Krishna Balan, Youngki Lee, Archan Misra
Research Collection School Of Computing and Information Systems
Smartwatches complement the main mobile phone and are able to profile user-activity as well as provide links, updates and notifications with work or personal utilities (e.g. Email, Social Media, Messaging etc.). Although very promising, smartwatches are still limited by low battery life. This is due to the small size of the battery as well as the need to continuously perform sensing. Battery drain issues by apps as well as the system are a common complaint by users. Improved tools for power analysis and profiling of smartwatch apps can help both developers (by providing a platform for pre-release analysis) and users …
Demo: Real-World Deployment Of Seat Occupancy Detectors, Nguyen Huy Hoang Nguyen, Gihan Hettiarachchi, Youngki Lee, Rajesh Krishna Balan
Demo: Real-World Deployment Of Seat Occupancy Detectors, Nguyen Huy Hoang Nguyen, Gihan Hettiarachchi, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Detecting occupancy of seats in library is important for librarians to check seats’ usage, and for students to find available seats in crowded time. In our prior work [1], we presented in-lab micro benchmarks to show feasibility of capacitive sensing for seat occupancy detection. In this demo paper, we present larger scale real-world deployment of occupancy detection system and its performance.
Demo: Sensing Gamers' Emotions Using Physiological Sensors, Sinh Huynh, Rajesh Krishna Balan, Youngki Lee
Demo: Sensing Gamers' Emotions Using Physiological Sensors, Sinh Huynh, Rajesh Krishna Balan, Youngki Lee
Research Collection School Of Computing and Information Systems
Understanding emotions of gamers can benefit game designers in various ways. How gamers feel while they playing a game can be treated as valuable user feedback to improve the development process of that game. Sensing player emotions also enables game designers to create adaptive game that can adjust itself to provide best gaming experience based on player emotions. However, how to effectively evaluate emotions of gamers is still an open research challenge. Two common techniques to evaluate emotional state are using self-assessments such as questionnaires or interviews, and to recognize expressed emotions by analyzing videos or images of facial expression, …
Demo: Smartwatch Based Food Diary And Eating Analytics, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Youngki Lee, Rajesh Krishna Balan
Demo: Smartwatch Based Food Diary And Eating Analytics, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Youngki Lee, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Monitoring an individual’s daily dietary intake can provide various insights regarding the health of the individual. Applications such as My Fitness Pal exists, which allows individuals to monitor all items that the individual consumed. However, manual monitoring can be labour intensive. To overcome this limitation, wrist worn sensor based eating habit monitoring has been studied by various researchers. These systems can detect eating gesture, but they cannot determine what is being eaten. We have built a system which can (i) detect eating gesture using the smartwatch's inertial sensors (ii) use the smartwatch's camera to capture images of food consumed at …
Demo: Towards Immersive And Interactive Gym Exercises, Fazlay Rabbi, Taiwoo Park, Biyi Fang, Mi Zhang, Youngki Lee, Rajiv Ranganathan
Demo: Towards Immersive And Interactive Gym Exercises, Fazlay Rabbi, Taiwoo Park, Biyi Fang, Mi Zhang, Youngki Lee, Rajiv Ranganathan
Research Collection School Of Computing and Information Systems
We demonstrate JARVIS, a novel virtual coaching system based on virtual reality (VR) and Internet of Things (IoT) technologies. It creates a truly immersive gym exercising experience for machine-based strength training and guides users in a highly interactive manner. With these unique advantages, we believe that JARVIS has a potential to revolutionize personal fitness experiences.
Friendship Maintenance And Prediction In Multiple Social Networks, Roy Ka-Wei Lee, Ee-Peng Lim
Friendship Maintenance And Prediction In Multiple Social Networks, Roy Ka-Wei Lee, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Due to the proliferation of online social networks (OSNs), users find themselves participating in multiple OSNs. These users leave their activity traces as they maintain friendships and interact with other users in these OSNs. In this work, we analyze how users maintain friendship in multiple OSNs by studying users who have accounts in both Twitter and Instagram. Specifically, we study the similarity of a user's friendship and the evenness of friendship distribution in multiple OSNs. Our study shows that most users in Twitter and Instagram prefer to maintain different friendships in the two OSNs, keeping only a small clique of …
Powerforecaster: Predicting Power Impact Of Mobile Sensing Applications At Pre-Installation Time, Chulhong Min, Youngki Lee, Chungkuk Yoo, Seungwoo Kang, Inseok Hwang, Junehwa Song
Powerforecaster: Predicting Power Impact Of Mobile Sensing Applications At Pre-Installation Time, Chulhong Min, Youngki Lee, Chungkuk Yoo, Seungwoo Kang, Inseok Hwang, Junehwa Song
Research Collection School Of Computing and Information Systems
Today's smartphone application (hereinafter 'app') markets miss a key piece of information, power consumption of apps. This causes a severe problem for continuous sensing apps as they consume significant power without users' awareness. Users have no choice but to repeatedly install one app after another and experience their power use. To break such an exhaustive cycle, we propose PowerForecaster, a system that provides users with power use of sensing apps at pre-installation time. Such advanced power estimation is extremely challenging since the power cost of a sensing app largely varies with users' physical activities and phone use patterns. We observe …
Enabling Carrier Collaboration Via Order Sharing Double Auction: A Singapore Urban Logistics Perspective, Handoko Stephanus Daniel, Hoong Chuin Lau
Enabling Carrier Collaboration Via Order Sharing Double Auction: A Singapore Urban Logistics Perspective, Handoko Stephanus Daniel, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
A recent exploratory study on the collaborative urban logistics in Singapore suggests that cost reduction and privacy preservation are two main drivers that would motivate the participation of carriers in consolidating their last mile deliveries. With Singapore's mild restrictions on the vehicle types or the time windows for the last-mile delivery, we believe that with proper technology in place, an Urban Consolidation Center like the Tenjin Joint Distribution System in Fukuoka Japan may be implemented to achieve cost reduction with some degree of privacy preservation. Participating carriers keep their respective private orders and have the option to get their remaining …
Smart Ambient Sound Analysis Via Structured Statistical Modeling, Jialie Shen, Liqiang Nie, Tat Seng Chua
Smart Ambient Sound Analysis Via Structured Statistical Modeling, Jialie Shen, Liqiang Nie, Tat Seng Chua
Research Collection School Of Computing and Information Systems
In this paper, we introduce a novel framework called SASA (Smart Ambient Sound Analyser) to support different ambient audio mining tasks (e.g., audio classification and location estimation). To gain comprehensive ambient sound modelling, SASA extracts a variety of acoustic features from different sound components (e.g., music, voice and background), and translates them into structured information. This significantly enhances quality of audio content representation. Further, distinguished from existing approaches, SASA’s multilayered architecture seamlessly integrates mixture models and aPEGASOS (adaptive PEGASOS) SVM algorithm into a unified classification framework. The approach can leverage complimentary strengths of both models. Experimental results based on three …
On Analyzing Geotagged Tweets For Location-Based Patterns, Philips Kokoh Prasetyo, Palakorn Achananuparp, Ee Peng Lim
On Analyzing Geotagged Tweets For Location-Based Patterns, Philips Kokoh Prasetyo, Palakorn Achananuparp, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Geotagged social media is becoming highly popular as social media access is now made very easy through a wide range of mobile apps which automatically detect and augment social media posts with geo-locations. In this paper, we analyze two kinds of location-based patterns. The first is the association between location attributes and the locations of user tweets. The second is location association pattern which comprises a pair of locations that are co-visited by users. We demonstrate that through tracking the Twitter data of Singapore-based users, we are able to reveal association between users tweeting from school locations and the school …
Iot+Small Data: Transforming In-Store Shopping Analytics And Services, Meera Radhakrishnan, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Balan
Iot+Small Data: Transforming In-Store Shopping Analytics And Services, Meera Radhakrishnan, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Balan
Research Collection School Of Computing and Information Systems
We espouse a vision of small data-based immersive retail analytics, where a combination of sensor data, from personal wearable-devices and store-deployed sensors & IoT devices, is used to create real-time, individualized services for in-store shoppers. Key challenges include (a) appropriate joint mining of sensor & wearable data to capture a shopper’s product level interactions, and (b) judicious triggering of power-hungry wearable sensors (e.g., camera) to capture only relevant portions of a shopper’s in-store activities. To explore the feasibility of our vision, we conducted experiments with 5 smartwatch-wearing users who interacted with objects placed on cupboard racks in our lab (to …
Privacy-Preserving And Verifiable Data Aggregation, Ngoc Hieu Tran, Robert H. Deng, Hwee Hwa Pang
Privacy-Preserving And Verifiable Data Aggregation, Ngoc Hieu Tran, Robert H. Deng, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
There are several recent research studies on privacy-preserving aggregation of time series data, where an aggregator computes an aggregation of multiple users' data without learning each individual's private input value. However, none of the existing schemes allows the aggregation result to be verified for integrity. In this paper, we present a new data aggregation scheme that protects user privacy as well as integrity of the aggregation. Towards this end, we first propose an aggregate signature scheme in a multi-user setting without using bilinear maps. We then extend the aggregate signature scheme into a solution for privacy-preserving and verifiable data aggregation. …
Press: Personalized Event Scheduling Recommender System (Demonstration), Hoong Chuin Lau, Aldy Gunawan, Pradeep Varakantham, Wenjie Wang
Press: Personalized Event Scheduling Recommender System (Demonstration), Hoong Chuin Lau, Aldy Gunawan, Pradeep Varakantham, Wenjie Wang
Research Collection School Of Computing and Information Systems
This paper presents a personalized event scheduling recom-mender system, PRESS, for a large conference setting with multiple parallel tracks. PRESS is a mobile application that gathers personalized information from a user and recommends talks/demos to be attend. The input from a user include a list of keyword preferences and (optionally) preferred talks. We use the MALLET topic model package to analyze the set of conference papers and classify them based on automatically identified topics. We propose an algorithm to generate a list of recommended papers based on the user keywords and the MALLET topics. An optimization model is then applied …
Online Arima Algorithms For Time Series Prediction, Chenghao Liu, Hoi, Steven C. H., Peilin Zhao, Jianling Sun
Online Arima Algorithms For Time Series Prediction, Chenghao Liu, Hoi, Steven C. H., Peilin Zhao, Jianling Sun
Research Collection School Of Computing and Information Systems
Autoregressive integrated moving average (ARIMA) is one of the most popular linear models for time series forecasting due to its nice statistical properties and great flexibility. However, its parameters are estimated in a batch manner and its noise terms are often assumed to be strictly bounded, which restricts its applications and makes it inefficient for handling large-scale real data. In this paper, we propose online learning algorithms for estimating ARIMA models under relaxed assumptions on the noise terms, which is suitable to a wider range of applications and enjoys high computational efficiency. The idea of our ARIMA method is to …
Hidden Ciphertext Policy Attribute-Based Encryption Under Standard Assumptions, Tran Viet Xuan Phuong, Guomin Yang, Willy Susilo
Hidden Ciphertext Policy Attribute-Based Encryption Under Standard Assumptions, Tran Viet Xuan Phuong, Guomin Yang, Willy Susilo
Research Collection School Of Computing and Information Systems
We propose two new ciphertext policy attributebased encryption (CP-ABE) schemes where the access policy is defined by AND-gate with wildcard. In the first scheme, we present a new technique that uses only one group element to represent an attribute, while the existing ABE schemes of the same type need to use three different group elements to represent an attribute for the three possible values (namely, positive, negative, and wildcard). Our new technique leads to a new CP-ABE scheme with constant ciphertext size, which, however, cannot hide the access policy used for encryption. The main contribution of this paper is to …
Elderly Medication Adherence With The Internet Of Things, Xiaoping Toh, Hwee Xian Tan, Hwee-Pink Tan, Hwee-Pink Tan
Elderly Medication Adherence With The Internet Of Things, Xiaoping Toh, Hwee Xian Tan, Hwee-Pink Tan, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
With the growth in elderly population in Singapore, healthcare expenditure and prevalence of age-related illnesses are expected to increase. Non-adherence among the elderly is a common issue that leads to adverse health complications, particularly among those with chronic conditions. However, existing studies typically focus on identifying predictors of medication adherence, and provide neither user-friendly nor actionable solutions that can be easily adopted by the elderly. In this paper, we use the Internet of Things to monitor medication adherence and detect changes in medication consumption patterns among the elderly, thus enabling timely interventions by caregivers to take place. Sensor-enabled medication boxes …
Insights From Machine-Learned Diet Success Prediction, Ingmar Weber, Palakorn Achananuparp
Insights From Machine-Learned Diet Success Prediction, Ingmar Weber, Palakorn Achananuparp
Research Collection School Of Computing and Information Systems
To support people trying to lose weight and stay healthy, more and more fitness apps have sprung up including the ability to track both calories intake and expenditure. Users of such apps are part of a wider “quantified self“ movement and many opt-in to publicly share their logged data. In this paper, we use public food diaries of more than 4,000 long-term active MyFitnessPal users to study the characteristics of a (un-)successful diet. Concretely, we train a machine learning model to predict repeatedly being over or under self-set daily calories goals and then look at which features contribute to the …
Salient Pairwise Spatio-Temporal Interest Points For Real-Time Activity Recognition, Mengyuan Liu, Hong Liu, Qianru Sun, Tianwei Zhang, Runwei Ding
Salient Pairwise Spatio-Temporal Interest Points For Real-Time Activity Recognition, Mengyuan Liu, Hong Liu, Qianru Sun, Tianwei Zhang, Runwei Ding
Research Collection School Of Computing and Information Systems
Real-time Human action classification in complex scenes has applications in various domains such as visual surveillance, video retrieval and human robot interaction. While, the task is challenging due to computation efficiency, cluttered backgrounds and intro-variability among same type of actions. Spatio-temporal interest point (STIP) based methods have shown promising results to tackle human action classification in complex scenes efficiently. However, the state-of-the-art works typically utilize bag-of-visual words (BoVW) model which only focuses on the word distribution of STIPs and ignore the distinctive character of word structure. In this paper, the distribution of STIPs is organized into a salient directed graph, …
We Can Hear You With Wi-Fi!, Guanhua Wang, Yongpan Zou, Zimu Zhou, Kaishun Wu, Lionel M. Ni
We Can Hear You With Wi-Fi!, Guanhua Wang, Yongpan Zou, Zimu Zhou, Kaishun Wu, Lionel M. Ni
Research Collection School Of Computing and Information Systems
Recent literature advances Wi-Fi signals to “see” people’s motions and locations. This paper asks the following question: Can Wi-Fi “hear” our talks? We present WiHear, which enables Wi-Fi signals to “hear” our talks without deploying any devices. To achieve this, WiHear needs to detect and analyze fine-grained radio reflections from mouth movements. WiHear solves this micro-movement detection problem by introducing Mouth Motion Profile that leverages partial multipath effects and wavelet packet transformation. Since Wi-Fi signals do not require line-of-sight, WiHear can “hear” people talks within the radio range. Further, WiHear can simultaneously “hear” multiple people’s talks leveraging MIMO technology. We …
Ambiguityvis: Visualization Of Ambiguity In Graph Layouts, Yong Wang, Qiaomu Shen, Zhiguang Zhou, Min Zhu, Sixiao Yang, Qu Huamin
Ambiguityvis: Visualization Of Ambiguity In Graph Layouts, Yong Wang, Qiaomu Shen, Zhiguang Zhou, Min Zhu, Sixiao Yang, Qu Huamin
Research Collection School Of Computing and Information Systems
Node-link diagrams provide an intuitive way to explore networks and have inspired a large number of automated graph layout strategies that optimize aesthetic criteria. However, any particular drawing approach cannot fully satisfy all these criteria simultaneously, producing drawings with visual ambiguities that can impede the understanding of network structure. To bring attention to these potentially problematic areas present in the drawing. this paper presents a technique that highlights common types of visual ambiguities: ambiguous spatial relationships between nodes and edges, visual overlap between community structures, and ambiguity in edge bundling and metanodes. Metrics, including newly proposed metrics for abnormal edge …
A Tool-Free Calibration Method For Turntable-Based 3d Scanning Systems, Xufang Pang, Rynson W.H. Lau, Zhan Song, Shengfeng He, Shengfeng He
A Tool-Free Calibration Method For Turntable-Based 3d Scanning Systems, Xufang Pang, Rynson W.H. Lau, Zhan Song, Shengfeng He, Shengfeng He
Research Collection School Of Computing and Information Systems
Turntable-based 3D scanners are popular but require calibration of the turntable axis. Existing methods for turntable calibration typically make use of specially designed tools, such as a chessboard or criterion sphere, which users must manually install and dismount. In this article, the authors propose an automatic method to calibrate the turntable axis without any calibration tools. Given a scan sequence of the input object, they first recover the initial rotation axis from an automatic registration step. Then they apply an iterative procedure to obtain the optimized turntable axis. This iterative procedure alternates between two steps: refining the initial pose of …