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Objective: To illustrate the efficiency of cumulative sum (CUSUM) in pre-warning of the influenza peak in Beijing., Methods: CUSUM was used to analyze the data of influenza like illness (ILI), and the results of the influenza laboratory surveillance was regarded as the gold standard to judge the approaching of the influenza peak., Results: The surveillance was launched in 421 hospitals in Beijing during the 2009 to 2010 influenza season, while the influenza laboratory surveillance was launched by 7 collaborative laboratories. From Jun. 2009 to Apr. 2010, the average ILI percentage in the 421 hospitals was 2.56%. In the study, 19 262 pharyngeal swab samples were collected from the ILI cases in 11 hospitals and 5 045 of them were tested positive for the influenza virus, with the novel swine-origin influenza A H1N1 virus dominating. After analyzing of the ILI surveillance data with CUSUM, it was found that the ILI surveillance in Beijing could make a satisfactory early warning for the approaching of the influenza peak referring to the gold standard based on the influenza laboratory results., Conclusion: It could give the prediction and early warning for the influenza peak efficiently and precisely, by using CUSUM to analyze the influenza surveillance data of Beijing.

The offensive/defensive problem of unmanned aerial vehicle (UAV) in an uncertain environment was presented by analyzing the uncertain information of target value and damage probability. An offensive/defensive payoff function of UAV in the case of uncertain information was established based on the information value of friend and enemy's missiles, and the offensive/defensive game payoff matrix was built. The Nash equilibrium of the game was obtained by combining the particle swarm optimization algorithm and the interval number multiple attribute ranking method in the case of uncertain information. A new method for UAV offensive/defensive game to achieve optimal strategy was proposed. Finally the feasibility and effectiveness of the method was verified by simulation. [ABSTRACT FROM AUTHOR]

Increasing the accuracy of pseudorange (PR) generation is one of the key technologies in developing real-time high dynamic globol navigation satellite system(GNSS) signal simulator. In this work, the proposed method takes user trajectory coordinates as input, and uses Keplerian parameters to calculate satellite positions for constellation simulation and parameter generation. To achieve high accuracy true range, the coordinate differences due to ECEF rotation should be considered during iterative calculation of PR. For PR generation, a cubic spline based algorithm is proposed to calculate the 3rd order PR polynomial coefficients directly. Above measures avoid the complexity and inaccuracy in existing algorithms which need to calculate satellite-user line-of-sight dynamic parameters such as high order derivatives for PR errors, satellite positions and user position respectively. Simulation result shows that the fitting error of proposed method is below 0.1 mm [ABSTRACT FROM AUTHOR]