Risk Analysis of Big Data Based on Cloud Computing for the Inspection and Testing of Toxic and Hazardous Substances in Meat Products

Large-scale data emerge in food safety inspection and testing industry with the development of Internet technology in China.This paper was aimed at designing toxic and hazardous substance big data risk analysis algorithm in food safety inspection and testing based on cloud computing^([1]).Cloud computing platform was set up to store the massive extensive data with geographical distribution,dynamic and high complexity from the Internet,and MapReduce^([2]) computational framework in cloud computing was applied to process and compute parallel data.The risk analysis results were obtained by analyzing 1000000 meat products testing data collected from the laboratory management information system based on web.The results show that food safety index IFS < 1,which proves that the food safety state is in good condition.

Safety Analysis of Flow Parameters in a Rotor-stator Cavity

In order to ensure the safety of engine life limited parts （ELLP） according to airworthiness regulations, a numerical approach integrating one-way fluid structure interaction （FSI） and probabilistic risk assessment （PRA） is developed, by which the variation of flow parameters in a rotor-stator cavity on the safety of gas turbine disks is investigated. The results indicate that the flow parameters affect the probability of fracture of a gas turbine disk since they can change the distribution of stress and temperature of the disk. The failure probability of the disk rises with increasing rotation Reynolds number and Chebyshev number, but descends with increasing inlet Reynolds number. In addition, a sampling based sensitivity analysis with finite difference method is conducted to determine the sensitivities of the safety with respect to the flow parameters. The sensitivity estimates show that the rotation Reynolds number is the dominant variable in safety analysis of a rotor-stator cavity among the flow parameters.

Pedestrian risk analysis at uncontrolled midblock and unsignalised intersections

Transportation is defined as port to port transfer of person or goods by a medium which can be a vehicle or a person. Pedestrians being the most neglected mode of transportation in terms of safety and facility, face difficult situations while crossing near intersections and midblock crossings. It becomes more of a risk when the place of crossing is uncontrolled.But if behaviour of pedestrians while crossing is analysed in such conditions, it might be possible to create suitable solution to lessen the risk and ensure safety. In most of the cities, accepting suitable gaps between vehicles in uncontrolled midblock and intersection crossings pose threat to pedestrians＇ safety. The present study examines the safety of pedestrian crossing behaviour at midblock and unsignalised intersection crossings.Crossing time, speed, stages of crossing, number of interruptions while crossing, and the type of vehicles for which pedestrians accept the gap were extracted from the video. The tendency to show rolling gap behavior was observed and examined for different age and gender groups to analyse the risk involved in such type of crossings. The risks analysed from the study in correlation with the pedestrian demand in such uncontrolled crossings will help in design of safer pedestrian facilities. It was observed that the size of the vehicle has a significant influence on gap acceptance and crossing behaviour of pedestrians. Male pedestrians take more risks than female pedestrians in crossing unsignalized intersections. Middle aged pedestrian category poses 60.1% more chances of interrupted crossing than the other elder and young age categories of pedestrians. Male pedestrian category and the middle aged pedestrian category are more tended to accept the smallest gap between the vehicles showing a risky nature of crossing.