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Digital Communications and Networking
Singapore Management University
Research Collection School Of Computing and Information Systems
- Keyword
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- Accuracy (1)
- Activity Recognition (1)
- Android (1)
- Angle of arrival (1)
- Atmospheric measurements (1)
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- Bike (1)
- Channel state information (1)
- Chosen-keyword attack (1)
- Content analysis (1)
- Counter rumor (1)
- Death hoax (1)
- Deep learning (1)
- Delays (1)
- EEG (1)
- Efficiency and feasibility (1)
- Exergame (1)
- Influence spread (1)
- Intent recognition (1)
- Mobile communication (1)
- Mobile computing (1)
- Mobile phone (1)
- Motion Direction Recognition (1)
- Multi-owner settings (1)
- Network measurement (1)
- Off-the-shelf Wi-Fi (1)
- Particle measurements (1)
- Phased array calibration (1)
- Result verification (1)
- Rumor correction (1)
- Searchable encryption (1)
Articles 1 - 12 of 12
Full-Text Articles in Computer Engineering
Vkse-Mo: Verifiable Keyword Search Over Encrypted Data In Multi-Owner Settings, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Junwei Zhang, Zhiquan Liu
Vkse-Mo: Verifiable Keyword Search Over Encrypted Data In Multi-Owner Settings, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Junwei Zhang, Zhiquan Liu
Research Collection School Of Computing and Information Systems
Searchable encryption (SE) techniques allow cloud clients to easily store data and search encrypted data in a privacy-preserving manner, where most of SE schemes treat the cloud server as honest-but-curious. However, in practice, the cloud server is a semi-honest-but-curious third-party, which only executes a fraction of search operations and returns a fraction of false search results to save its computational and bandwidth resources. Thus, it is important to provide a results verification method to guarantee the correctness of the search results. Existing SE schemes allow multiple data owners to upload different records to the cloud server, but these schemes have …
Bikemate: Bike Riding Behavior Monitoring With Smartphones, Weixi Gu, Zimu Zhou, Yuxun Zhou, Han Zou, Yunxin Liu, Costas J. Spanos, Lin Zhang
Bikemate: Bike Riding Behavior Monitoring With Smartphones, Weixi Gu, Zimu Zhou, Yuxun Zhou, Han Zou, Yunxin Liu, Costas J. Spanos, Lin Zhang
Research Collection School Of Computing and Information Systems
Detecting dangerous riding behaviors is of great importance to improve bicycling safety. Existing bike safety precautionary measures rely on dedicated infrastructures that incur high installation costs. In this work, we propose BikeMate, a ubiquitous bicycling behavior monitoring system with smartphones. BikeMate invokes smartphone sensors to infer dangerous riding behaviors including lane weaving, standing pedalling and wrong-way riding. For easy adoption, BikeMate leverages transfer learning to reduce the overhead of training models for different users, and applies crowdsourcing to infer legal riding directions without prior knowledge. Experiments with 12 participants show that BikeMate achieves an overall accuracy of 86.8% for lane …
An Analysis Of Rumor And Counter-Rumor Messages In Social Media, Dion Hoe-Lian Goh, Alton Y. K. Chua, Hanyu Shi, Wenju Wei, Haiyan Wang, Ee-Peng Lim
An Analysis Of Rumor And Counter-Rumor Messages In Social Media, Dion Hoe-Lian Goh, Alton Y. K. Chua, Hanyu Shi, Wenju Wei, Haiyan Wang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Social media platforms are one of the fastest ways to disseminate information but they have also been used as a means to spread rumors. If left unchecked, rumors have serious consequences. Counter-rumors, messages used to refute rumors, are an important means of rumor curtailment. The objective of this paper is to examine the types of rumor and counter-rumor messages generated in Twitter in response to the falsely reported death of a politician, Lee Kuan Yew, who was Singapore’s first Prime Minister. Our content analysis of 4321Twitter tweets about Lee’s death revealed six categories of rumor messages, four categories ofcounter-rumor messages …
Intent Recognition In Smart Living Through Deep Recurrent Neural Networks, Xiang Zhang, Lina Yao, Chaoran Huang, Quan Z. Sheng, Xianzhi Wang
Intent Recognition In Smart Living Through Deep Recurrent Neural Networks, Xiang Zhang, Lina Yao, Chaoran Huang, Quan Z. Sheng, Xianzhi Wang
Research Collection School Of Computing and Information Systems
Electroencephalography (EEG) signal based intent recognition has recently attracted much attention in both academia and industries, due to helping the elderly or motor-disabled people controlling smart devices to communicate with outer world. However, the utilization of EEG signals is challenged by low accuracy, arduous and time-consuming feature extraction. This paper proposes a 7-layer deep learning model to classify raw EEG signals with the aim of recognizing subjects’ intents, to avoid the time consumed in pre-processing and feature extraction. The hyper-parameters are selected by an Orthogonal Array experiment method for efficiency. Our model is applied to an open EEG dataset provided …
Enabling Phased Array Signal Processing For Mobile Wifi Devices, Kun Qian, Chenshu Wu, Zheng Yang, Zimu Zhou, Xu Wang, Yunhao Liu
Enabling Phased Array Signal Processing For Mobile Wifi Devices, Kun Qian, Chenshu Wu, Zheng Yang, Zimu Zhou, Xu Wang, Yunhao Liu
Research Collection School Of Computing and Information Systems
Modern mobile devices are equipped with multiple antennas, which brings various wireless sensing applications such as accurate localization, contactless human detection, and wireless human-device interaction. A key enabler for these applications is phased array signal processing, especially Angle of Arrival (AoA) estimation. However, accurate AoA estimation on commodity devices is non-trivial due to limited number of antennas and uncertain phase offsets. Previous works either rely on elaborate calibration or involve contrived human interactions. In this paper, we aim to enable practical AoA measurements on commodity off-the-shelf (COTS) mobile devices. The key insight is to involve users’ natural rotation to formulate …
Spatio-Temporal Analysis And Prediction Of Cellular Traffic In Metropolis, Xu Wang, Zimu Zhou, Zheng Yang, Yunhao Liu, Chunyi Peng
Spatio-Temporal Analysis And Prediction Of Cellular Traffic In Metropolis, Xu Wang, Zimu Zhou, Zheng Yang, Yunhao Liu, Chunyi Peng
Research Collection School Of Computing and Information Systems
Understanding and predicting cellular traffic at large-scale and fine-granularity is beneficial and valuable to mobile users, wireless carriers and city authorities. Predicting cellular traffic in modern metropolis is particularly challenging because of the tremendous temporal and spatial dynamics introduced by diverse user Internet behaviours and frequent user mobility citywide. In this paper, we characterize and investigate the root causes of such dynamics in cellular traffic through a big cellular usage dataset covering 1.5 million users and 5,929 cell towers in a major city of China. We reveal intensive spatio-temporal dependency even among distant cell towers, which is largely overlooked in …
Special Section: Technological Innovations For Communication And Collaboration In Social Spaces, Eric K. Clemons, Rajiv M. Dewan, Robert J. Kauffman, Thomas A. Weber
Special Section: Technological Innovations For Communication And Collaboration In Social Spaces, Eric K. Clemons, Rajiv M. Dewan, Robert J. Kauffman, Thomas A. Weber
Research Collection School Of Computing and Information Systems
Research on social communication and collaboration is of high importance today in Information Systems, especially for interdisciplinary inquiry that emphasizes topics related to strategy, information, technology, economics, and society. The articles that are showcased in this special section of the Journal of Management Information Systems address issues that arise in a number of important contemporary contexts.
Toward Accurate Network Delay Measurement On Android Phones, Weichao Li, Daoyuan Wu, Rocky K. C. Chang, Ricky K. P. Mok
Toward Accurate Network Delay Measurement On Android Phones, Weichao Li, Daoyuan Wu, Rocky K. C. Chang, Ricky K. P. Mok
Research Collection School Of Computing and Information Systems
Measuring and understanding the performance of mobile networks is becoming very important for end users and operators. Despite the availability of many measurement apps, their measurement accuracy has not received sufficient scrutiny. In this paper, we appraise the accuracy of smartphone-based network performance measurement using the Android platform and the network round-trip time (RTT) as the metric. We show that two of the most popular measurement apps-Ookla Speedtest and MobiPerf-have their RTT measurements inflated. We build three test apps that cover three common measurement methods and evaluate them in a testbed. We overcome the main challenge of obtaining a complete …
Perception And Reality: Measuring Digital Skills In Singapore, Swapna Gottipati
Perception And Reality: Measuring Digital Skills In Singapore, Swapna Gottipati
Research Collection School Of Computing and Information Systems
ICDL Asia carried out a digital literacy study in Singapore, looking at an essential skill for everyday life. The goal of the study was to discover the digital skills gaps among young people in Singapore. Singapore is considered to be a digitally advanced country where young people have access to the latest technology and gadgets. At the same time, it is imperative for young people to possess relevant digital skills for a future-ready and healthy economy. The studies consisted of two key parts: self-assessment and practical assessment of digital skills. Our findings show that, though the digital native fallacy exists …
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 …
Discovering Your Selling Points: Personalized Social Influential Tags Exploration, Yuchen Li, Kian-Lee Tan, Ju Fan, Dongxiang Zhang
Discovering Your Selling Points: Personalized Social Influential Tags Exploration, Yuchen Li, Kian-Lee Tan, Ju Fan, Dongxiang Zhang
Research Collection School Of Computing and Information Systems
Social influence has attracted significant attention owing to the prevalence of social networks (SNs). In this paper, we study a new social influence problem, called personalized social influential tags exploration (PITEX), to help any user in the SN explore how she influences the network. Given a target user, it finds a size-k tag set that maximizes this user’s social influence. We prove the problem is NP-hard to be approximated within any constant ratio. To solve it, we introduce a sampling-based framework, which has an approximation ratio of 1−ǫ 1+ǫ with high probabilistic guarantee. To speedup the computation, we devise more …