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20th ACM SIGSPATIAL International Conference on Advances in Geographic Information systems, ACM SIGSPATIAL GIS 2012

作者： Wei, Hong Wang, Yin Forman, George Zhu, Yanmin Guan, Haibing Shanghai Key Lab. of Scalable Computing and Systems Shanghai Jiao Tong University China Hewlett-Packard Labs. Palo Alto CA United States

ISBN: (纸本)9781450316910

This paper describes a map matching program submitted to the ACM SIGSPATIAL Cup 2012. We first summarize existing map matching algorithms into three categories, and compare their performance thoroughly. In general, global max-weight methods using the Viterbi dynamic programming algorithm are the most accurate but the accuracy varies at different sampling intervals using different weight functions. Our submission selects a hybrid that improves upon the best two weight functions such that its accuracy is better than both and the performance is robust against varying sampling rates. In addition, we employ many optimization techniques to reduce the overall latency, as the scoring heavily emphasizes on speed. Using the training dataset with manually corrected ground truth, our Java-based program matched all 14,436 samples in 5 seconds on a dual-core 3.3 GHz iCore 3 processor, and achieved 98.9% accuracy. © 2012 ACM.

关键词： Dynamic programming

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EEG-based fatigue classification by using parallel hidden Markov model and pattern classifier combination

EEG-based fatigue classification by using parallel hidden Ma...

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19th International Conference on Neural Information Processing, ICONIP 2012

作者： Sun, Hui Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE-Microsoft Key Lab. for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE Key Laboratory of Systems Biomedicine Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China

ISBN: (纸本)9783642344770

Fatigue is the most important reason leading to traffic accidents. In order to ensure traffic safety, various methods based on electroencephalogram (EEG) are proposed. But most of them, either regression or classification, are focused on the relationship between feature space and observation values, so the changing patterns of features are ignored or discarded. In this paper, we propose a new fatigue classification method by using parallel hidden-Markov-model and pattern classifier combination techniques, where each model represents a particular fatigue-high-related feature. In the experiment, subjects are asked to accomplish some simple tasks, and both their fatigue states and their EEG signals are recorded simultaneously. Experimental results indicate that the mean error rate obtained by using our new method are 11.15% for classifying 3 states and 16.91% for classifying 4 states, respectively, while the existing approach can only reach 16.45% and 23.55% under the same condition. © 2012 Springer-Verlag.

关键词： Electroencephalography

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Workload-aware opportunistic routing in multi-channel, multi-radio wireless mesh networks

Workload-aware opportunistic routing in multi-channel, multi...

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2012 9th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, SECON 2012

作者： Wu, Fan Vaidya, Nitin Department of Computer Science and Engineering Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University China ECE Coordinated Science Lab University of Illinois Urbana-Champaign United States

ISBN: (纸本)9781467319058

Opportunistic routing emerged as a novel technique to cope with the problem of highly unpredictable and lossy wireless channels in urban wireless mesh networks. However, existing opportunistic routing protocols only consider single-radio wireless nodes, and assume that all the nodes work on the same channel, without exploiting possible concurrent transmissions by multi-radio nodes over orthogonal channels provided by IEEE 802.11 protocols. Examples show that simply integrating existing channel assignment schemes and the opportunistic routing technique may not achieve satisfactory system performance. In this paper, we present WACA, which is a Workload-Aware Channel Assignment algorithm for opportunistic routing in multi-channel, multi-radio wireless mesh networks. Evaluation results show that WACA always achieves highest average throughput among the evaluated algorithms, and its median throughput is at least 16.1% higher than the compared ones. © 2012 IEEE.

关键词： Mesh generation

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Online vigilance analysis combining video and electrooculography features

Online vigilance analysis combining video and electrooculogr...

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19th International Conference on Neural Information Processing, ICONIP 2012

作者： Du, Ruo-Fei Liu, Ren-Jie Wu, Tian-Xiang Lu, Bao-Liang Center for Brain-like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE-Microsoft Key Lab. for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE Key Laboratory of Systems Biomedicine Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China

ISBN: (纸本)9783642344992

In this paper, we propose a novel system to analyze vigilance level combining both video and Electrooculography (EOG) features. For one thing, the video features extracted from an infrared camera include percentage of closure (PERCLOS) and eye blinks, slow eye movement (SEM), rapid eye movement (REM) are also extracted from EOG signals. For another, other features like yawn frequency, body posture and face orientation are extracted from the video by using Active Shape Model (ASM). The results of our experiments indicate that our approach outperforms the existing approaches based on either video or EOG merely. In addition, the prediction offered by our model is in close proximity to the actual error rate of the subject. We firmly believe that this method can be widely applied to prevent accidents like fatigued driving in the future. © 2012 Springer-Verlag.

关键词： Eye movements

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On guaranteed detectability for surveillance sensor networks

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International Journal of Distributed Sensor Networks 2012年第7期2012卷 1-15页

作者： Zhu, Yanmin Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China Shanghai Key Lab of Scalable Computing and Systems Shanghai 200240 China

Surveillance is an important class of applications for wireless senor networks (WSNs), whose central task is to detect events of interest. Existing approaches seriously suffer from blind spots and low energy efficiency. In this paper, we propose a fully distributed algorithm GAP for energy-efficient event detection for surveillance applications. Employing the probabilistic approach, GAP actively tunes the active probability and minimizes the energy consumption of each sensor. The unique features of GAP are threefold. First, it provides guaranteed detectability for any event occurring in the sensing field. Second, it exposes a convenient interface of the user to specify the desired detectability. Finally, it supports differentiated service to empower better surveillance for critical spots. Without relying on costly time synchronization, GAP is a lightweight distributed protocol and is truly scalable to network scale and sensor density. Theoretical analysis and comprehensive simulation experiments are conducted, which jointly demonstrate that GAP is able to provide guaranteed detectability while significantly prolonging the system lifetime compared with other schemes. Copyright © 2012 Yanmin Zhu.

关键词： Energy efficiency

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Immune clonal algorithm based feature selection for epileptic EEG signal classification

Immune clonal algorithm based feature selection for epilepti...

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2012 11th International Conference on Information Science, Signal Processing and their Applications, ISSPA 2012

作者： Peng, Yong Lu, Bao-Liang Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE-Microsoft Key Lab. for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong Univ. 800 Dongchuan Road Shanghai 200240 China

ISBN: (纸本)9781467303828

Detecting epileptic EEG signal automatically and accurately is significant in evaluating patients with epilepsy. In this study, the immune clonal algorithm (ICA) is employed to perform automatic feature selection, reducing the number of features the classifier deals with and improving the classification accuracy. In the experiment, EEG signal was decomposed into five sub-band components by a discrete wavelet transform. Features were extracted as input to train three classifiers (NB, SVM, KNN and LDA) to judge whether the EEG signal was epileptic or not. Then, ICA was introduced to select a feature subset to train the classifiers. Experimental results show that the classification accuracy based on selected features is significantly higher than that on original features. We also analyzed the relative importance of each feature. © 2012 IEEE.

关键词： Discrete wavelet transforms

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Optimal adaptive antijamming in wireless sensor networks

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International Journal of Distributed Sensor Networks 2012年第12期2012卷 1-9页

作者： Zhu, Yanmin Li, Xiangpeng Li, Bo Department of Computer Science and Engineering Shanghai Jiao Tong University Minhang Shanghai 200240 China Shanghai Key Lab of Scalable Computing and Systems Shanghai Jiao Tong University Minhang Shanghai 200240 China Department of Computer Science and Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

Wireless sensor networks have been widely applied to various application domains such as environmental monitoring and surveillance. Because of reliance on the open transmission media, a sensor network may suffer from radio jamming attacks, which are easy to launch but difficult to defend. Attacked by jamming signals, a sensor network may experience corrupted packets and low network throughput. A number of defense techniques have been proposed. However, each defense technique is suitable for only a limited range of network and jamming conditions. This paper proposes an adaptive approach to antijamming for sensor networks by combining the strength of state-of-the-art antijamming techniques, which enables each node to adaptively select the optimal antijamming technique for different jamming conditions. The great challenge is that the sensor network undergoes varying jamming conditions over time. We address this challenge by formulating the antijamming problem of the sensor network as a Markov decision process and propose an efficient algorithm for computing the best antijamming strategy. By comprehensive simulation experiments, we demonstrate that a sensor network using the derived antijamming strategy can well defend from radio jamming attacks and in the meanwhile retain high energy efficiency. © 2012 Yanmin Zhu et al.

关键词： Sensor nodes

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Long Duration Broadcast Authentication for Wireless Sensor Networks

Long Duration Broadcast Authentication for Wireless Sensor N...

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IEEE Vehicular Technology Conference

作者： Yongsheng Liu Jie Li Minyi Guo Graduate School of System and Information Engineering University of Tsukuba Tsukuba Science City 305-8573 Japan Shanghai Key Lab of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai P.R. China

ISBN: (纸本)9781467309899

In the resource constrained Wireless Sensor Networks (WSNs), the broadcast authentication is widely fulfilled by the emerging delayed authentication technique. The one level backward one-way key chain in the delayed authentication technique limits heavily the duration of the broadcast authentication. In this paper, we propose a long duration broadcast authentication scheme for WSNs. The proposed scheme uses a novel hierarchical key chain to extend the duration of broadcast authentication to be as long as the whole lifetime of WSNs. Moreover, the overhead of the proposed scheme is significantly reduced compared to that with one level key chain. Extensive experimental results show that the novel hierarchical key chain fully outperforms the one level key chain in terms of memory and computation.

关键词： Wireless Sensor WSNs chain fully Wireless sensor networks Authentication

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On Optimal Relay Placement for Urban Vehicular Networks

On Optimal Relay Placement for Urban Vehicular Networks

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IEEE International Conference on Communications Workshops

作者： Youchen Bao Yanmin Zhu Shanghai Jiao Tong University Shanghai Key Lab of Scalable Computing and Systems

ISBN: (纸本)9781612842325

This paper considers the problem of optimal relay placement for urban monitoring in wireless vehicular networks. The placement of relays is greatly impacted by vehicle distribution and mobility, which makes it difficult to determine the optimal locations. We theoretically prove that the relay placement problem (RPP) is NP-hard even when the vehicle traces are assumed as a priori knowledge. We first propose an approximate algorithm for the RPP with given vehicle traces (D-RPP). This algorithm is proved to achieve an approximation ratio of (1-1/e), where e is the natural logarithm base. To solve the RPP without a priori knowledge about future vehicle traces (N-RPP), we first show that there is strong regularity with vehicle mobility by entropy analysis. Then, we propose an algorithm for solving the N-RPP, which exploits regularity extracted from historical traces. Extensive simulations based on real trace datasets show that the D-RPP algorithm produces performance close to the optimum. keywords-wireless vehicular networks, wireless relays, optimal placement, approximation algorithms.

关键词： Wireless vehicular networks Wireless relays Optimal placement Approximation algorithms

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A game-theoretic approach to anti-jamming in sensor networks

A game-theoretic approach to anti-jamming in sensor networks

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16th IEEE International Conference on Parallel and Distributed systems, ICPADS 2010

作者： Zhu, Yanmin Jian, Yuan Shanghai Key Lab. of Scalable Computing and Systems China Shanghai Jiao Tong University China

ISBN: (纸本)9780769543079

Jamming is a serious security threat to a wireless sensor network since the network relies on open wireless radio channel. A jamming attacker launches jamming attacks easily by transmitting high-power signals and all legitimate sensor nodes interfered by jamming signals suffer corrupted packet transmissions. More importantly, the jammer is typically strategic and chooses its jamming strategy in response to the possible defense strategy taken by the sensor network. In this paper we model the interaction between the sensor network and the attacker as a non-cooperative non-zero-sum static game. In such a game, the sensor network has a set of strategies of controlling its probability of accessing the wireless channel and the attacker manipulates its jamming by controlling its jamming probability after sensing a transmission activity. We propose an efficient algorithm for computing the optimal strategies for jamming attack and network defense. A critical issue is that there may exist a number of possible strategy profiles of Nash equilibria. To address this issue, we further propose to choose realistic Nash equilibria by applying Pareto-dominance and risk dominance. Our numerical results demonstrate that the strategies chosen by Pareto-dominance and risk dominance achieve the expected performance. Our results presented in the paper provides valuable defense guidance for wireless sensor networks against jamming attacks. © 2010 IEEE.

关键词： Game theory

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