VPN技术在防震减灾中的应用

简要介绍VPN技术的应用、原理与搭建,并介绍了两个应用实例。显示了VPN技术在防震减灾工作中有广阔的应用前景。     

0515台风"卡努"影响浙江的强风分析

本文对0515台风“卡努”登陆浙江后,强度减弱为强热带风暴,对影响浙江沿海海面及沿海地区的外围风速远强于近风暴中心风速进行了分析,分析结果表明:副热带高压的加强、对流层中下层急流的动量下传、高空较强的下沉气流和台风外围气压梯度力迅猛增大的共同作用,是造成本次风暴外围风速远强于近风暴中心风速的重要原因。     

机载激光点云中高压电塔自动识别方法

提出了一种基于格网特征的机载激光点云高压电塔自动识别方法。首先对机载激光点云数据进行滤波去噪处理;然后对点云数据进行规则格网化特征分析获得高压电塔粗识别区域;最后对粗识别区域进行外接邻域网格线性特征悬空点集检测以确定电塔识别结果,并以分层切片法分析获取电塔平面中心坐标。采用大型无人机实际线路巡检获取的机载点云数据对本文算法进行验证,试验结果表明本算法可实现高压电塔的快速自动识别,对无人机电力巡检智能诊断具有一定的促进作用。     

应用Hydrolight模式研究含油水体辐射传输特性的关键技术

辐射传输模式Hydrolight在国际水色遥感研究领域已被广泛用于解决水体光学的各种问题,也是进行石油类污染水体辐射传输特性研究的有效模型。结合Hydrolight模式的机理、应用现状及含油水体的特点,提出了将该模式应用于光学特性复杂的石油污染水体辐射传输特性研究时需要解决的关键技术,包括测定石油污染水体吸收系数和散射系数、建立石油污染吸收和散射特性随波长和深度变化的参数化模型、确定油物质的吸附后悬浮颗粒物体散射函数模型等方面。依据2018年8月和2016年8月分别在辽宁大连港和辽宁盘锦辽河油田等区域测定的含油水体数据,讨论了这些关键技术的解决方案。     

基于无人船的水质监测及控制系统设计

针对执行水质监测任务过程中固定浮标监测站单点监测存在局限性、船载观测人员取样耗时耗力等问题,本文设计了一种搭载多点、分层自动采水取样装置的智能无人船水质监测系统,可实现目标水域的多点、分层连续水质数据测量及取样。该智能无人船具备基于快速随机树(Rapid Random Tree)算法的自主避障和快速路径规划功能,解决了现有无人船技术存在的多障碍自主路径规划难等问题。同时,本设计结合了ARM9控制芯片、M5310无线传输模块,通过可视化的显示界面和远程WEB访问的功能,大大提升了科研人员及时处理特殊情况便捷性。通过实验测试及比对分析,证明本设计具有智能高效、稳定可靠等优点,能够满足职能部门对于水质监测工作的需要。     

基于数据传输特性的卫星广播通道参数优化方法与应用

中国气象局卫星广播系统（CMACast）是全球对地观测广播系统（GEONETCast）框架下三大对地广播系统之一,在世界气象组织信息系统（WIS）和综合卫星数据分发服务系统(IGDDS)框架下,承担亚太地区气象数据广播分发的职责。随着气象业务的发展,广播系统数据量由180 GB/天增长至460 GB/天,在广播带宽资源有限而广播数据种类和大小各异的情况下,系统管理员越来越难以通过经验对广播通道参数调整以保持广播系统播发效率,造成部分通道数据播发时效下降严重,不能满足业务时效要求。通过对不同气象数据传输特性的定量分析,获得各类数据的精细化数据传输样本,在此基础上对各类数据广播通道参数进行科学、定量的计算和优化,使数据播发时效明显提升,应用到实际广播业务中效果明显。     

Inheritance Pattern of Microsatellite Loci and Their Use for Kinship Analysis in the Japanese Scallop Patinopecten yessoensis

The inheritance mode of seven microsatellite markers was investigated in Patinopecten yessoensis larvae from four con-trolled crosses,and the feasibility of using these markers for kinship estimation was also examined. All the seven microsatellite loci were compatible with Mendelian inheritance. Neither sex-linked barriers to transmission nor major barriers to fertilization between gametes from the parents were evident. Two of the seven loci showed the presence of null alleles in two families,suggesting the...     

The ecology and phylogeny of cyanobacterial symbionts in sponges

Cyanobacteria have flexible photosynthetic apparatus that allows them to utilise light at very low levels, making them ideal symbionts for a wide range of organisms. Sponge associations with cyanobacteria are common in all areas of the world, but little is known about them. Recent research has revealed new cyanobacterial symbionts that may be host specific and two major clades, ' Candidatus Synechococcus spongiarum ' and Oscillatoria spongeliae , that occur in widely separated geographic locations in unrelated sponge hosts. These clades may represent a cluster of closely related symbiont species, or may be single species that are maintained by periods of horizontal transmission over large distances. Erroneous assumptions regarding the importance of cyanobacterial symbionts to the survival of individual sponges or species may arise from cyanosponges being deemed to be phototrophic or mixotrophic without studies of their photophysiology. This review brings together recent and past research on cyanobacterial associations with sponges, including their biogeography, phylogeny, host specificity, and ecology.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models: An Empirical Validation of ISWRidge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p 〈0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to cheek the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height （X1 ） and potential energy （X2 ） significantly impact （p 〈 0. 0001 ） the amplitude-based refleeted rate; the P-values for the deviance and Pearson are all 〉 0.05 （0.2839, 0.3438, respectively）. That is, the goodness-of-fit between ridge height （ X1 ） and potential energy （X2） can further predict parameters under the scenario of the best parsimonious model. Investigation of 6 predictive powers （ R2, Max-rescaled R^2, Sorners＇ D, Gamma, Tau-a, and c, respectively） indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models： An Empirical Validation of ISW-Ridge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p<0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to check the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height (X1) and potential energy (X2) significantly impact (p<0.0001) the amplitude-based reflected rate; the P-values for the deviance and Pearson are all >0.05 (0.2839, 0.3438, respectively). That is, the goodness-of-fit between ridge height (X1) and potential energy (X2) can further predict parameters under the scenario of the best parsimonious model.Investigation of 6 predictive powers (R2, Max-rescaled R2, Somers'D, Gamma, Tau-a, and c, respectively) indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.