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Daqing Zhang

Bio: Daqing Zhang is an academic researcher from Peking University. The author has contributed to research in topics: Context (language use) & Mobile computing. The author has an hindex of 67, co-authored 331 publications receiving 16675 citations. Previous affiliations of Daqing Zhang include Institut Mines-Télécom & Institute for Infocomm Research Singapore.


Papers
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Journal ArticleDOI
TL;DR: Wu et al. as mentioned in this paper proposed WiTraj, a device-free indoor motion tracking system using commodity WiFi devices, which leverages multiple receivers placed at different viewing angles to capture human walking and then intelligently combines the best views to achieve a robust trajectory reconstruction, and distinguishes walking from in-place activities, which are typically interleaved in daily life, so that non-walking activities do not cause tracking errors.
Abstract: WiFi-based device-free motion tracking systems track persons without requiring them to carry any device. Existing work has explored signal parameters such as time-of-flight (ToF), angle-of-arrival (AoA), and Doppler-frequency-shift (DFS) extracted from WiFi channel state information (CSI) to locate and track people in a room. However, they are not robust due to unreliable estimation of signal parameters. ToF and AoA estimations are not accurate for current standards-compliant WiFi devices that typically have only two antennas and limited channel bandwidth. On the other hand, DFS can be extracted relatively easily on current devices but is susceptible to the high noise level and random phase offset in CSI measurement, which results in a speed-sign-ambiguity problem and renders ambiguous walking speeds. This paper proposes WiTraj, a device-free indoor motion tracking system using commodity WiFi devices. WiTraj improves tracking robustness from three aspects: 1) It significantly improves DFS estimation quality by using the ratio of the CSI from two antennas of each receiver, 2) To better track human walking, it leverages multiple receivers placed at different viewing angles to capture human walking and then intelligently combines the best views to achieve a robust trajectory reconstruction, and, 3) It differentiates walking from in-place activities, which are typically interleaved in daily life, so that non-walking activities do not cause tracking errors. Experiments show that WiTraj can significantly improve tracking accuracy in typical environments compared to existing DFS-based systems. Evaluations across 9 participants and 3 different environments show that the median tracking error $<2.5\%$<2.5% for typical room-sized trajectories.

13 citations

Proceedings ArticleDOI
18 Mar 2013
TL;DR: MemPhone, a new system that addresses various human memory needs by using the mobile tagging technique, can augment memory externalization and recall, and build object-based social networks (OBSNs) to enhance memory sharing.
Abstract: Human memory is important yet often not easy to be handled in daily life. Many challenges are raised, such as how to enhance memory recall and reminiscence, how to facilitate memory sharing in terms of people's social nature. This paper proposes MemPhone, a new system that addresses various human memory needs by using the mobile tagging (e.g., RFID, barcodes) technique. By linking human memory or experience with associated physical objects, MemPhone can i) augment memory externalization and recall, and ii) build object-based social networks (OBSNs) to enhance memory sharing. By embedding physical contexts into SNs, the OBSN can strengthen friendships by enabling serendipity discovering and nurture new connections among people with shared memories. Early studies indicate that our system can facilitate memory recall and shared memory discovery.

13 citations

Journal ArticleDOI
01 Jun 2016
TL;DR: A generic data collection framework called PicPick is proposed, which presents a multifaceted task model that allows for varied MCP task specification and a pyramid tree (PTree) method is further proposed to select an optimal set of pictures from picture streams based on multi-dimensional constraints.
Abstract: Mobile crowd photography (MCP) is a widely used technique in crowd sensing. In MCP, a picture stream is generated when delivering intermittently to the backend server by participants. Pictures contributed later in the stream may be semantically or visually relevant to previous ones, which can result in data redundancy. To meet diverse constraints (e.g., spatiotemporal contexts, single or multiple shooting angles) on the data to be collected in MCP tasks, a data selection process is needed to eliminate data redundancy and reduce network overhead. This issue has little been investigated in existing studies. To address this requirement, we propose a generic data collection framework called PicPick. It first presents a multifaceted task model that allows for varied MCP task specification. A pyramid tree (PTree) method is further proposed to select an optimal set of pictures from picture streams based on multi-dimensional constraints. Experimental results on two real-world datasets indicate that PTree can effectively reduce data redundancy while maintaining the coverage requests, and the overall framework is flexible.

13 citations

Proceedings ArticleDOI
Jiahui Wu1, Gang Pan1, Daqing Zhang2, Shijian Li1, Zhaohui Wu1 
26 Sep 2010
TL;DR: This video demonstrates a mobile phone that can sense what you are pointing to and can act as a physical ubiquitous interaction device in real world, called MagicPhone.
Abstract: Mobile phones are becoming a kind of must-have portable devices for people. This video demonstrates a mobile phone that can sense what you are pointing to and can act as a physical ubiquitous interaction device in real world, called MagicPhone. If you want to interact with an appliance around you, you just simply point the MagicPhone to it and then operate. The MagicPhone uses both the built-in accelerometer and magnetometer to sense the pointing orientation. Using MagicPhone, you only need to point to a device and sliding your finger, to show a picture on a display, to send a document to a laptop, to share slides on a projector, and to print a photo. In addition, MagicPhone can control a selected device with accelerometer-based gestures, e.g. changing TV channels. It also can serve as a mouse to draw a picture or play clicking games.

13 citations

Journal ArticleDOI
TL;DR: A task-adaptative model-agnostic meta-learning framework to learn city-specific prior initializations from multiple cities, capable of handling the multimodal data distribution and accelerating the adaptation in new cities compared to other methods is proposed.
Abstract: Optimal store placement aims to identify the optimal location for a new brick-and-mortar store that can maximize its sale by analyzing and mining users’ preferences from large-scale urban data. In ...

12 citations


Cited by
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01 Jan 2002

9,314 citations

Journal ArticleDOI
TL;DR: This paper surveys context awareness from an IoT perspective and addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT.
Abstract: As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.

2,542 citations

Proceedings ArticleDOI
22 May 2017
TL;DR: This work quantitatively investigates how machine learning models leak information about the individual data records on which they were trained and empirically evaluates the inference techniques on classification models trained by commercial "machine learning as a service" providers such as Google and Amazon.
Abstract: We quantitatively investigate how machine learning models leak information about the individual data records on which they were trained. We focus on the basic membership inference attack: given a data record and black-box access to a model, determine if the record was in the model's training dataset. To perform membership inference against a target model, we make adversarial use of machine learning and train our own inference model to recognize differences in the target model's predictions on the inputs that it trained on versus the inputs that it did not train on. We empirically evaluate our inference techniques on classification models trained by commercial "machine learning as a service" providers such as Google and Amazon. Using realistic datasets and classification tasks, including a hospital discharge dataset whose membership is sensitive from the privacy perspective, we show that these models can be vulnerable to membership inference attacks. We then investigate the factors that influence this leakage and evaluate mitigation strategies.

2,059 citations