“出现度”在重点保护野生植物资源调查中的应用

<正> 绩溪清凉峰省级自然保护区处于安徽省绩溪县、歙县和浙江省临安市接壤地带,总面积3000ha,跨30°00′-30°10′N,118°40′-118°55′E,属中亚热带湿润区,保护对象是山地混合森林生态系统,生物地理分区属2.1.2和Ⅰ(Ⅰ)4A(2)。

Analysis of Dynamic Characteristics of the 21st Century Maritime Silk Road

The 21st century Maritime Silk Road(MSR) proposed by China strongly promotes the maritime industry. In this paper, we use wind and ocean wave datasets from 1979 to 2014 to analyze the spatial and temporal distributions of the wind speed, significant wave height(SWH), mean wave direction(MWD), and mean wave period(MWP) in the MSR. The analysis results indicate that the Luzon Strait and Gulf of Aden have the most obvious seasonal variations and that the central Indian Ocean is relatively stable. We analyzed the distributions of the maximum wind speed and SWH in the MSR over this 36-year period. The results show that the distribution of the monthly average frequency for SWH exceeds 4 m(huge waves) and that of the corresponding wind speed exceeds 13.9 ms^(-1)(high wind speed). The occurrence frequencies of huge waves and high winds in regions east of the Gulf of Aden are as high as 56% and 80%, respectively. We also assessed the wave and wind energies in different seasons. Based on our analyses, we propose a risk factor(RF) for determining navigation safety levels, based on the wind speed and SWH. We determine the spatial and temporal RF distributions for different seasons and analyze the corresponding impact on four major sea routes. Finally, we determine the spatial distribution of tropical cyclones from 2000 to 2015 and analyze the corresponding impact on the four sea routes. The analysis of the dynamic characteristics of the MSR provides references for ship navigation as well as ocean engineering.

Statistical Analyses of Sea State Conditions in South China Sea

The statistical characterization of sea conditions in the South China Sea(SCS) was investigated by analyzing a 30-year(1976–2005) numerically simulated daily wave height and wind speed data. The monthly variation of these parameters shows that wave height and wind speed have minimum values of 0.54 m and 4.15 ms^(-1), respectively in May and peak values of 2.04 m and 8.12 ms^(-1), respectively in December. Statistical analysis of the daily wave height and wind speed and the subsequent characterization of the annual, seasonal and monthly mean sea state based on these parameters were also done. Results showed that, in general, the slight sea state prevails in the SCS and has nearly the highest occurrence in all seasons and months. The moderate sea condition prevails in the winter months of December and January while the smooth(wavelets) sea state prevails in May. Furthermore, spatial variation of sea states showed that calm and smooth sea conditions have high occurrences(25%–80%) in the southern SCS. The slight sea condition shows the largest occurrence(25%–55%) over most parts of the SCS. High occurrences(8%–17%) of the rough and very rough seas distribute over some regions in the central SCS. Sea states from high to phenomenal conditions show rare occurrence(<12%) in the northern SCS. The calm(glassy) sea condition shows no occurrence in the SCS.

Low Complexity SOVA for Turbo Codes

Recently, trimming Soft-output Viterbi algorithm(T-SOVA) has been proposed to reduce the complexity of SOVA for Turbo codes. In its fi rst stage, a dynamic algorithm, lazy Viterbi algorithm, is used to indicate the minimal metric differences which brings obstacle on hardware implementation. This paper proposes a Viterbi algorithm(VA) based T-SOVA to facilitate hardware implementation. In the first stage of our scheme, a modified VA with regular structure is used to fi nd the maximum likelihood(ML) path and calculate the metric differences. Further, local sorting is introduced to trim the metric differences, which reduces the complexity of trimming operation. Simulation results and complexity analysis show that VA based T-SOVA performs as well as lazy VA based T-SOVA and is easier to be applied to hardware implementation.