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学者姓名：赵季中
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Abstract ：
Chinese character is composed of spatial arrangement of strokes. A portion of these strokes combines to form phonetic component, which provides a clue to the pronunciation of the entire character, the others combine to form semantic component, which indicates semantic level information for speech context. How closely the connection between the internal strokes of Chinese characters and speech? In this paper, we propose Speech2Stroke, a end-to-end model that exploits the phonetic and morphologic level information of pictographic words. Specifically, we generate strokes directly from the speech by Speech2Stroke. The performance of Speech2Stroke is evaluated by the specific stroke error rate(SER). The SER of the optimal model can achieve 20.61%. Through the experiments and analysis, we show that our model has the ability to capture the alignment between audio and the internal structures of pictographic characters. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
Keyword ：
Computers Computer science Engineering Industrial engineering Semantics
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| GB/T 7714 | Zhang, Yinhui , Xi, Wei , Yang, Zhao et al. Speech2Stroke: Generate Chinese Character Strokes Directly from Speech [C] . 2021 : 83-94 . |
| MLA | Zhang, Yinhui et al. "Speech2Stroke: Generate Chinese Character Strokes Directly from Speech" . (2021) : 83-94 . |
| APA | Zhang, Yinhui , Xi, Wei , Yang, Zhao , Men, Sitao , Jiang, Rui , Yang, Yuxin et al. Speech2Stroke: Generate Chinese Character Strokes Directly from Speech . (2021) : 83-94 . |
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| GB/T 7714 | Wang, Ge , Qian, Chen , Shangguan, Longfei et al. HMO: Ordering RFID Tags With Static Devices in Mobile Environments (vol 19, pg 74, 2020) [J]. | IEEE TRANSACTIONS ON MOBILE COMPUTING , 2021 , 20 (4) : 1746-1746 . |
| MLA | Wang, Ge et al. "HMO: Ordering RFID Tags With Static Devices in Mobile Environments (vol 19, pg 74, 2020)" . | IEEE TRANSACTIONS ON MOBILE COMPUTING 20 . 4 (2021) : 1746-1746 . |
| APA | Wang, Ge , Qian, Chen , Shangguan, Longfei , Ding, Han , Han, Jinsong , Cui, Kaiyan et al. HMO: Ordering RFID Tags With Static Devices in Mobile Environments (vol 19, pg 74, 2020) . | IEEE TRANSACTIONS ON MOBILE COMPUTING , 2021 , 20 (4) , 1746-1746 . |
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Abstract ：
This paper presents an anti-spoofing design to verify whether a voice command is spoken by one live legal user, which supplements existing speech recognition systems and could enable new application potentials when many crucial voice commands need a higher-standard verification in applications. In the literature, verifying the liveness and legality of the command's speaker has been studied separately. However, to accept a voice command from a live legal user, prior solutions cannot be combined directly due to two reasons. First, previous methods have introduced various sensing channels for the liveness detection, while the safety of a sensing channel itself cannot be guaranteed. Second, a direct combination is also vulnerable when an attacker plays a recorded voice command from the legal user and mimics this user to speak the command simultaneously. In this paper, we introduce an anti-spoofing sensing channel to fulfill the design. More importantly, our design provides a generic interface to form the sensing channel, which is compatible to a variety of widely-used signals, including RFID, Wi-Fi and acoustic signals. This offers a flexibility to balance the system cost and verification requirement. We develop a prototype system with three versions by using these sensing signals. We conduct extensive experiments in six different real-world environments under a variety of settings to examine the effectiveness of our design. © 2021 ACM.
Keyword ：
Speech recognition
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| GB/T 7714 | Zhao, Cui , Li, Zhenjiang , Ding, Han et al. Anti-Spoofing Voice Commands: A Generic Wireless Assisted Design [J]. | Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies , 2021 , 5 (3) . |
| MLA | Zhao, Cui et al. "Anti-Spoofing Voice Commands: A Generic Wireless Assisted Design" . | Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5 . 3 (2021) . |
| APA | Zhao, Cui , Li, Zhenjiang , Ding, Han , Xi, Wei , Wang, Ge , Zhao, Jizhong . Anti-Spoofing Voice Commands: A Generic Wireless Assisted Design . | Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies , 2021 , 5 (3) . |
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Abstract ：
This paper presents a non-invasive design, namely RF-ray, to recognize the shape and material of an object simultaneously. RF-ray puts the object approximate to an RFID tag array, and explores the propagation effect as well as coupling effect between RFIDs and the object for sensing. In contrast to prior proposals, RF-ray is capable to recognize unseen objects, including unseen shape-material pairs and unseen materials within a certain container. To make it real, RF-ray introduces a sensing capability enhancement module and leverages a two-branch neural network for shape profiling and material identification respectively. Furthermore, we incorporate a Zero-Shot Learning based embedding module that incorporates the well-learned linguistic features to generalize RF-ray to recognize unseen materials. We build a prototype of RF-ray using commodity RFID devices. Comprehensive real-world experiments demonstrate our system can achieve high object recognition performance. © 2021 ACM.
Keyword ：
Backpropagation Linguistics Object recognition Radio frequency identification (RFID)
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| GB/T 7714 | Ding, Han , Zhai, Linwei , Zhao, Cui et al. RF-ray: Joint RF and Linguistics Domain Learning for Object Recognition [J]. | Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies , 2021 , 5 (3) . |
| MLA | Ding, Han et al. "RF-ray: Joint RF and Linguistics Domain Learning for Object Recognition" . | Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5 . 3 (2021) . |
| APA | Ding, Han , Zhai, Linwei , Zhao, Cui , Hou, Songjiang , Wang, Ge , Xi, Wei et al. RF-ray: Joint RF and Linguistics Domain Learning for Object Recognition . | Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies , 2021 , 5 (3) . |
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Abstract ：
Rain removal is an important operation in intelligent visual surveillance systems. Many rain removal algorithms based on convolution neural networks (CNNs) are rarely deployed on resource constrained devices. One of the limiting factors is that memory access leads to high energy consumption. To reduce memory access during computation, previous works usually use a fixed computation pattern for different layers in CNN. For different and massive input and output feature maps, fixed computation pattern would lower the power efficiency. Thus, we propose a reconfigurable architecture to support different convolution mapping method. We use hybrid data reuse pattern to reduce energy consumption by 2.4-5.9 times over fixed computation pattern. The hardware is synthesized in the area of 9.83 mm(2) at TSMC 65 nm technology and can restore a 1280 x 720 real world image in 0.57 s which achieves 56.1 x and 2.1 x speed-up comparing to CPU and GPU implementations. The simulation results show that the power efficiency is 287.7 GOPS/W running rain removal network.
Keyword ：
Convolutional neural network hardware implementation rain removal reconfigurable architecture
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| GB/T 7714 | Rao, Lei , Zhang, Bin , Zhao, Jizhong . An Energy-Efficient Accelerator for Rain Removal Based on Convolutional Neural Network [J]. | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS , 2021 , 68 (8) : 2957-2961 . |
| MLA | Rao, Lei et al. "An Energy-Efficient Accelerator for Rain Removal Based on Convolutional Neural Network" . | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 68 . 8 (2021) : 2957-2961 . |
| APA | Rao, Lei , Zhang, Bin , Zhao, Jizhong . An Energy-Efficient Accelerator for Rain Removal Based on Convolutional Neural Network . | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS , 2021 , 68 (8) , 2957-2961 . |
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Abstract ：
Security over mobile Internet-of-Things (IoT) devices is critical due to the open nature of distributed wireless communication. To efficiently establish a secure connection between two communication parties, a fast mobile key extraction protocol, KEEP, is proposed. KEEP fastly generates similar bit sequences from two communication parties' measurements of channel-state information (CSI) of different subcarriers. Then, a distributed "verification-recombination" mechanism is introduced to generate the same encryption key from bit sequences without the public-key authentication, digital signature, or key distribution center of the other party. We implemented real-world experiments using commercial off-the-shelf 802.11n devices to evaluate the performance of KEEP in various scenarios. Theoretical analysis and experimental verification show that KEEP is more secure, effective, and reliable than the state-of-the-art methods.
Keyword ：
11n Standard Correlation Distributed computing IEEE 802 Internet of Things Internet of Things (IoT) key generation OFDM Privacy Protocols Wireless communication
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| GB/T 7714 | Xi, Wei , Duan, Meichen , Bai, Xiuxiu et al. KEEP: Secure and Efficient Communication for Distributed IoT Devices [J]. | IEEE INTERNET OF THINGS JOURNAL , 2021 , 8 (16) : 12758-12770 . |
| MLA | Xi, Wei et al. "KEEP: Secure and Efficient Communication for Distributed IoT Devices" . | IEEE INTERNET OF THINGS JOURNAL 8 . 16 (2021) : 12758-12770 . |
| APA | Xi, Wei , Duan, Meichen , Bai, Xiuxiu , Zhao, Kun , Mo, Lufeng , Zhao, Jizhong . KEEP: Secure and Efficient Communication for Distributed IoT Devices . | IEEE INTERNET OF THINGS JOURNAL , 2021 , 8 (16) , 12758-12770 . |
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Abstract ：
Spatial crowdsourcing (SC) has gained much attention in recent years. On SC platforms, requesters can publish spatial tasks on a specific topic such as taking photos at certain locations which is reflected by some tags of the task, and workers can choose tasks according to their tags. An interesting phenomenon is that workers often form groups based on their social relationships and common interests to perform same tasks. A nature question often raised when a task is published is how to predict which (or how many) workers are attracted by the task if its tags are specified. In particular, the tags of a new task affect the willingness of the workers to choose it. On the other hand, workers are also affected by the willingness of their co-workers or friends when deciding to choose a task or not. In this paper, we study the problem of potential workers estimation for a spatial crowdsourcing task, the Worker Collaborative Group Estimation (WCGE) problem, and model whether workers will join the group of a task as a game. We present efficient algorithms to find the Nash Equilibrium of the game and estimate the potential workers for the new task. Using synthetic datasets, we experimentally study the performance of proposed solutions. Our solutions can also help understand big geospatial data for self-driving cars and more intelligent transportation applications. © 2020 Elsevier B.V.
Keyword ：
Computer applications Crowdsourcing Neural networks
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| GB/T 7714 | Wang, Zhi , Li, Yubing , Zhao, Kun et al. Worker Collaborative group estimation in spatial crowdsourcing [J]. | Neurocomputing , 2021 , 428 : 385-391 . |
| MLA | Wang, Zhi et al. "Worker Collaborative group estimation in spatial crowdsourcing" . | Neurocomputing 428 (2021) : 385-391 . |
| APA | Wang, Zhi , Li, Yubing , Zhao, Kun , Shi, Wei , Lin, Liangliang , Zhao, Jizhong . Worker Collaborative group estimation in spatial crowdsourcing . | Neurocomputing , 2021 , 428 , 385-391 . |
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Abstract ：
With the wide applications of smart devices and mobile computing, smart home becomes a hot issue in the household appliance industry. The controlling and interaction approach plays a key role in users' experience and turns into one of the most important selling points for profit growth. Considering the robustness and privacy protection, wearable devices equipped with MEMS, e.g., smartphones, smartwatches, or smart wristbands, are thought of one of the most feasible commercial solutions for interaction. However, the low-cost built-in MEMS sensors do not perform well in capturing finely grained human activity directly. In this paper, we propose a method that leverages the arm constraint and historical information recorded by MEMS sensors to estimate the maximum likelihood action in a two-phases model. First, in the arm posture estimation phase, we leverage the kinematics model to analyze the maximum likelihood position of users' arms. Second, in the trajectory recognition phase, we leverage the gesture estimation model to identify the key actions and output the instructions to devices by SVM. Our substantial experiments show that the proposed solution can recognize eight kinds of postures defined for man-machine interaction in the smart home application scene, and the solution implements efficient and effective interaction using low-cost smartwatches, and the interaction accuracy is >87%. The experiments also show that the algorithm proposed in this paper can be well applied to the perceptual control of smart household appliances, and has high practical value for the application design of the perceptual interaction function of household appliances. © 2013 IEEE.
Keyword ：
Ambient intelligence Automation Costs Data privacy Domestic appliances Maximum likelihood estimation User experience Wearable computers
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| GB/T 7714 | Li, Yubing , Zhao, Kun , Duan, Meichen et al. Control Your Home with a Smartwatch [J]. | IEEE Access , 2020 , 8 : 131601-131613 . |
| MLA | Li, Yubing et al. "Control Your Home with a Smartwatch" . | IEEE Access 8 (2020) : 131601-131613 . |
| APA | Li, Yubing , Zhao, Kun , Duan, Meichen , Shi, Wei , Lin, Liangliang , Cao, Xinyi et al. Control Your Home with a Smartwatch . | IEEE Access , 2020 , 8 , 131601-131613 . |
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Abstract ：
Passive Radio Frequency Identification (RFID) tags have been widely applied in many applications, such as logistics, retailing, and warehousing. In many situations, the order of objects is more important than their absolute locations. However, state-of-art ordering methods need a continuing movement of tags and readers, which limit the application domain and scalability. In this paper, we propose a 2-dimension ordering approach for passive tags that requires no device movement. Instead, our method utilizes signal changes caused by arbitrary movement of human beings around tags, who carry no device for horizontal dimension ordering. Hence, our method is called Human Movement based Ordering (HMO). The basic idea of HMO is that when people pass between the reader antenna and tags, the received signal strength will change. By observing the time-series RSS changes of tags, HMO can obtain the order of tags along with a specific horizontal direction. For vertical dimension, we employ a linear programming method that is tolerant of tiny errors in practice. We implement HMO with commodity off-the-shelf RFID devices. The experimental results show that HMO can achieve up to 88.71 and 90.86 percent average accuracies in the signal- and multi-person cases, respectively.
Keyword ：
IEEE members Logistics Mobile antennas Mobile computing Receiving antennas relative localization RFID RFID tags
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| GB/T 7714 | Wang, Ge , Qian, Chen , Shangguan, Longfei et al. HMO: Ordering RFID Tags with Static Devices in Mobile Environments [J]. | IEEE TRANSACTIONS ON MOBILE COMPUTING , 2020 , 19 (1) : 74-89 . |
| MLA | Wang, Ge et al. "HMO: Ordering RFID Tags with Static Devices in Mobile Environments" . | IEEE TRANSACTIONS ON MOBILE COMPUTING 19 . 1 (2020) : 74-89 . |
| APA | Wang, Ge , Qian, Chen , Shangguan, Longfei , Ding, Han , Han, Jinsong , Cui, Kaiyan et al. HMO: Ordering RFID Tags with Static Devices in Mobile Environments . | IEEE TRANSACTIONS ON MOBILE COMPUTING , 2020 , 19 (1) , 74-89 . |
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Abstract ：
Delivering service intelligence to billions of connected devices is the next step in edge computing. Wi-Fi, as the de facto standard for high-throughput wireless connectivity, is highly vulnerable to packet-injection-based identity spoofing attacks (PI-ISAs). An attacker can spoof as the legitimate edge coordinator and perform denial of service (DoS) or even man-in-the-middle (MITM) attacks with merely a laptop. Such vulnerability leads to serious systematic risks, especially for the core edge/cloud backbone network.In this paper, we propose PHYAlert, an identity spoofing attack alert system designed to protect a Wi-Fi-based edge network. PHYAlert profiles the wireless link with the rich dimensional Wi-Fi PHY layer information and enables real-time authentication for Wi-Fi frames. We prototype PHYAlert with commercial off-the-shelf (COTS) devices and perform extensive experiments in different scenarios. The experiments verify the feasibility of spoofing detection based on PHY layer information and show that PHYAlert can achieve an 8x improvement in the false positive rate over the conventional signal-strength-based solution.
Keyword ：
Channel state information Identity spoofing attack Wi-Fi Wireless intrusion detection
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| GB/T 7714 | Jiang, Zhiping , Zhao, Kun , Li, Rui et al. PHYAlert: identity spoofing attack detection and prevention for a wireless edge network [J]. | JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS , 2020 , 9 (1) . |
| MLA | Jiang, Zhiping et al. "PHYAlert: identity spoofing attack detection and prevention for a wireless edge network" . | JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS 9 . 1 (2020) . |
| APA | Jiang, Zhiping , Zhao, Kun , Li, Rui , Zhao, Jizhong , Du, Junzhao . PHYAlert: identity spoofing attack detection and prevention for a wireless edge network . | JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS , 2020 , 9 (1) . |
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