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There are various shortages of the traditional data center in cost, resource utilization, power consumption and operation. This paper studies the development trend of the virtual data center and its technical advantages, proposes a scheme of virtual system of smart transportation data center based on VMware vSphere. At the same time, oriented on requirements of traffic data stream management in city smart transportation system under the environment of cloud computing, aimed at massive, multi-source, real-time, dynamic uncertain data stream sent back from all kinds of cross regional intensive control perception device, this paper analyses the characteristics and correlation of actual city traffic operation and traffic data flow, researches evolution mechanism of uncertain data; construct traffic data flow model based on ontology, core metadata and theory of constraints. And on this basis, this paper uses virtualization and large data sets of parallel processing, considers load balancing and adaptive mechanism, combines fuzzy theory and dynamic multi object, multi constrained decision theory, to seek the efficient query algorithm for dynamic, complex and continuous transportation data stream.

Based on efficient continuous parallel query series algorithm supporting multi-objective optimization, by using visual graphics technology for traffic data streams for efficient real-time graphical visualization, it improve human-computer interaction, to realize real-time and visual data analysis and to improve efficiency and accuracy of the analysis. This paper employs data mining processing and statistical analysis on real-time traffic data stream, based on the parameters standards of various data mining algorithms, and by using computer graphics and image processing technology, converts graphics or images and make them displayed on the screen according to the system requirements, in order to track, forecast and maintain the operating condition of all traffic service systems effectively.

Good track geometry state ensures the safe operation of the railway passenger service and freight service. Railway transportation plays an important role in the Chinese economic and social development. This paper studies track irregularity standard deviation time series data and focuses on the characteristics and trend changes of track state by applying clustering analysis. Linear recursive model and linear-ARMA model based on wavelet decomposition reconstruction are proposed, and all they offer supports for the safe management of railway transportation.

RFID authentication plays a significant role in protecting the security and privacy of Internet of Things, whereas RFID tags' low resource feature limits its applications. We propose a low-cost mutual authentication protocol based on cryptoGPS scheme, with an efficient flexible key management scheme and a coupons injection protocol. A new low-cost multiplier is designed to save resource. The simulation by Synopsys Design Complier with Smic 0.25amu;m library, result shows that the tag just needs 3076 equivalent gates and the maximum time of single step is 7.35ms at 500kHz. It's clear that this protocol can meet the demand of RFID tag well.

This paper gives a new method in implement perception unit combining both micro and macro environment. The detailed micro information of user data is organized in triangular and the octree mechanism makes queries more effective. The macro environment was provided to vehicle, by traffic logic maps. This paper focuses on how to use the steering behaviors model in implementing traffic behaviors, such as accident avoiding, road following and lane changing, in order to make autonomous vehicle more intelligent.

Objective To investigate the clinical application of serum cysteine protease inhibitor C (Cystatin C, Cys-C) determination in early renal impairment in essential hypertensive by comparing the differences of renal function indices in essential hypertensive with different glomerular filtration rate (GFR) levels. Methods Two hundred and thirteen cases of essential hypertensive patients treated at the First Affiliated Hospital of Xinjiang Medical University from October 2011 to September 2012 were enrolled, there were one hundred and thirteen males and one hundred females, the average age of all the patients was (51.2 ± 12.7) years. the GFR was detected, all the patients were divided into three groups according to the GFR levels: renal moderate and severe impairment group (GFR Results Creatinine in renal moderate and severe impairment group was statistically higher than those in renal mild impairment group and normal renal function group (P Conclusions Cys-C is one of the important diagnostic indexes in early renal impairment in essential hypertensive. It contributes to predicting the decline of renal function in the early stage.