Meng Shuai

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Wireless sensor networks are expected to be deployed on urban roadways to monitor the traffic continuously. One of the requirements of traffic monitoring is displaying the traffic states of the front roadways, which can guide the drivers to choose the right way and avoid potential traffic congestions. In this scenario, the information of traffic state(More)
Outliers are common in data collection applications with wireless sensor networks, which consist of a large number of sensor nodes, embedded in physical space. The limited power supplies and noisy sensor data put challenges for outlier detection and cleaning in sensor networks. In this paper, we propose utilizing spatial and temporal dependencies that exist(More)
Traffic flow prediction is a basic function of Intelligent Transportation System. Due to the complexity of traffic phenomenon, most existing methods build complex models such as neural networks for traffic flow prediction. As a model may lose effect with time lapse, it is important to update the model on line. However, the high computational cost of(More)
Geospatial Web Services are data-oriented services, which include a variety of complex data models and metadata. Discovering the appreciate services with related geospatial datasets among a large number of available ones is a key task in the Geospatial Web Services domain. This paper proposes a peer-to-peer (P2P) based approach for discovering geospatial(More)
In this paper, through constructing a differential path, we analyze the collision process of the compression function Blue Midnight Wish(BMW). BMW is one of the fastest SHA-3 candidates in the second round of the competition. Each word of the compression function Blue Midnight Wish is 32-bit. The differential attack has complexity of about 2<sup>32</sup>.(More)