THE CHARACTERISTICS OF THUNDERSTORM FREQUENCY VARIATION AND THEIR POSSIBLE RELATION WITH THE ADJUSTMENT OF CROP DISTRIBUTION IN THE LEIZHOU PENINSULA

In order to research possible influences of the adjustment of plant distribution on the development frequency of thunderstorms over the Leizhou Peninsula, mathematic statistic methods, including correlation analyses, 11 kinds of fitting models and all-variable regression methods, were used for analyses and research. The results show that the average trend of the number of annual thunderstorm days is descending obviously, and there are thunderstorms in all seasons, in which warm post-midday thunderstorms have taken up the most part, and high frequency is found from May to September, and the starting and ending dates of thunderstorms have a great annual discrepancy. The vegetation structure has been improved along with the reduction of rice fields and the area increment of sugarcane and fruits planting, which results in the decrease of the number of thunderstorm days; the change in the characteristics of winter spare fields, which is caused by the planting of vegetables, limits the formation of thunderstorms in early winter and late spring. Meanwhile, the area adjustment of peanut planting has little influence on the variation of thunderstorm days. The adjustment of principal crop distribution, such as rice, sugarcane, fruits and vegetables, may have obvious influence on the formation of thunderstorms, and sugarcane has the largest effect, followed in turn by rice, vegetables and fruits, and the adjustment of crop distribution has little influence on the starting and ending dates of thunderstorms.

Study on financial loss and its adjustment in earthquake insurance

In the paper, we briefly introduce the development and present situation of earthquake insurance in China and foreign countries, and the evaluation of earthquake losses on the basis of seismic risk and structural vulnerability analyses. The emphasis is given to the probabilistic density function of earthquake loss adjustment for a single building under the given insurance policy and the overall variance of estimated earthquake losses aggregated from various locations with keen interest in the insurance industries. The correlation coefficient for the damages among single structures in the United States is also introduced to interpret the risk of loss concentration in the earthquake insurance. The paper provides a scientific basis for adjusting earthquake loss and premium rate, and it also provides a useful reference for the application and expansion of earthquake insurance in China.

Problems of Personal Income Tax System and Suggestions： from Function of Tax Adjustment Income Gap

China has a late start in personal income tax, and for many years through six times of revision, it still fails to really achieve the purpose of narrowing the gap between the rich and the poor and adjusting income distribution. What follows is an analysis of personal adjustment tax income from the proportion of Gini coefficient, Engels coefficient and salaried class of personal income tax, and an explanation of problems and countermeasures of salaried class expense deduction standard, tax rate design, high-income crowd tax regulation.

Distributed sparse bundle adjustment algorithm based on three-dimensional point partition and asynchronous communication

Sparse bundle adjustment(SBA) is a key but time-and memory-consuming step in three-dimensional(3 D) reconstruction. In this paper, we propose a 3 D point-based distributed SBA algorithm(DSBA) to improve the speed and scalability of SBA. The algorithm uses an asynchronously distributed sparse bundle adjustment(A-DSBA)to overlap data communication with equation computation. Compared with the synchronous DSBA mechanism(SDSBA), A-DSBA reduces the running time by 46%. The experimental results on several 3 D reconstruction datasets reveal that our distributed algorithm running on eight nodes is up to five times faster than that of the stand-alone parallel SBA. Furthermore, the speedup of the proposed algorithm(running on eight nodes with 48 cores) is up to41 times that of the serial SBA(running on a single node).

A low-overhead asynchronous consensus framework for distributed bundle adjustment

Generally,the distributed bundle adjustment(DBA)method uses multiple worker nodes to solve the bundle adjustment problems and overcomes the computation and memory storage limitations of a single computer.However,the performance considerably degrades owing to the overhead introduced by the additional block partitioning step and synchronous waiting.Therefore,we propose a low-overhead consensus framework.A partial barrier based asynchronous method is proposed to early achieve consensus with respect to the faster worker nodes to avoid waiting for the slower ones.A scene summarization procedure is designed and integrated into the block partitioning step to ensure that clustering can be performed on the small summarized scene.Experiments conducted on public datasets show that our method can improve the worker node utilization rate and reduce the block partitioning time.Also,sample applications are demonstrated using our large-scale culture heritage datasets.