马尔可夫切换的汽车悬架系统的事件触发H∞滤波

针对具有马尔可夫切换信道的两自由度（2-DOF） 四分之一汽车悬架系统,研究了事件触发 H_∞ 滤波问题.首先,信道切换由马尔可夫链控制;其次,考虑到事件触发的通信方案,由于有限的网络带宽,产生信号量化和随机丢包问题;然后,采用马尔可夫线性跳变系统模型来表示整个滤波网络系统.利用Lyapunov泛函和线性矩阵不等式方法将事件触发 H_∞ 滤波问题转化为凸优化问题,从而设计了切换信道相关的滤波器,使得滤波误差系统在均方意义上是指数稳定的并达到期望的性能水平.最后,通过仿真实例验证了所提出的设计方法的有效性.     

顾及土地生态安全的环鄱阳湖城市群土地利用情景模拟

在国家大力推进新型城镇化和落实城市群空间规划的背景下,评价城市群土地生态安全水平,并以此为限制条件预测城市群未来土地利用格局,对城市群可持续发展具有重要意义。本文以环鄱阳湖城市群为研究对象,对城市群土地生态安全格局和变化进行分析,根据土地生态安全评价结果设置自然发展情景和生态保护情景,结合多分类Logistic回归和多标准评价方法(MCE),构建CA-Markov模型,预测2种情景下2030年土地利用格局并进行对比分析。研究结果表明:①2005、2010和2015年,环鄱阳湖城市群网格平均生态安全值分别为0.574、0.573和0.571,空间布局上呈现"中部低、东西高"的特征;②预测2030年,自然发展情景下新增城镇用地主要位于九江市、上饶市和南昌市,生态保护情景下限制城镇用地和其他建设用地向土地生态安全高值区扩展,使得城镇用地和其他建设用地扩展更加集中;③预测生态保护情景下,高生态安全区面积比自然发展情景下多39.39%且分布更加均匀,包括鄱阳湖周边区域、九江市中部以及新余市和吉安市,城市群生态安全得到有效保护。该研究可为环鄱阳湖城市群土地利用规划及生态保护提供参考。     

结合像元级与对象级的滨海湿地变化检测方法

滨海湿地是动态且脆弱的生态系统,遥感变化检测技术为滨海湿地动态变化监测提供了有效手段。为解决像元级变化检测对配准误差敏感及其椒盐现象严重,对象级变化检测受分割参数影响较大且过程繁琐等问题,本文提出了显著图引导的结合像元级与对象级变化检测方法。首先,提取湿地亮度、归一化差异植被指数、归一化差异水体指数三个特征,得到特征差异影像;其次,利用最大对称环绕显著性检测算法生成显著图,采用结合模糊C均值和马尔可夫随机场方法对显著区域进行分割得到初始像元级变化检测结果;最后,在面向对象分割的基础上,通过构建对象的不确定性指数自适应选择训练样本,采用随机森林分类器进行分类得到最终变化检测结果。利用江苏盐城滨海湿地资源三号影像进行实验,结果表明,结合像元级与对象级方法的湿地变化检测总体精度为93.51%,与像元级、对象级方法相比,虚检率分别降低了29.04%和22.78%。     

两种纯化方法获得脂肪酸的链长及碳同位素分布特征对比

饱和脂肪酸及其同位素组成是重建古环境和古气候的重要代用指标,目前存在多种提取及纯化流程。在全球变化研究中,基于不同原理的纯化流程得到的脂肪酸含量及其同位素组成是否一致,直接影响着该指标应用于不同区域重建结果的对比。本文用两种常见的脂肪酸纯化流程提取脂肪酸标准、现生植物和泥炭样品类脂物,通过对比发现:对脂肪酸标准两种流程都可以得到纯净的单体脂肪酸,而且回收率均较高(85%以上),都是较为可靠的脂肪酸纯化流程;然而对于天然样品,虽然高碳数脂肪酸(碳数>C₂₄)的回收率相近,流程1却能够获得相对较多的低碳数饱和脂肪酸,如泥炭样品中该流程获得的n-C₂₂脂肪酸是流程2的3倍;两种流程纯化狗尾草(Setaira viridis)和三叶草(Trifolium repens)得到n-C₁₆脂肪酸的δ¹³C不同,流程1分别为-21.1‰和-36.2‰;流程2分别为-23.3‰和-34.9‰,表明两个实验流程得到的低碳数脂肪酸的含量、脂肪酸链长分布模式以及碳同位素组成均存在明显的差异。实验结果显示,流程2分离纯化样品可得到几乎全部的游离态脂肪酸,而流程1可提纯样品中游离态和酯态存在的总脂肪酸。由于在沉积物中游离态脂肪酸和酯态脂肪酸可以相互转化,因此使用流程1分析样品中的总脂肪酸更为合适,也可以将类脂物皂化使酯态脂肪酸释放为游离态,然后使用流程2。     

基于最短路径分析的中间件设计与应用研究

最短路径分析的根本目的是研究、筹划一项网络工程应如何安排而使其运行效果最好,其在社会生活中应用广泛且研究意义重大。在软件开发方面,q-间件能够屏蔽底层多源异构系统环境和数据环境,提高模型复用率和软件开发效率,因此本文提出通过中间件方式实现最短路径分析算法与应用系统的集成,为实际应用提供新的思路。     

Farm Size and Land Use Pattern Changes in Postsocialist Poland∗

The postsocialist transition resulted in widespread structural change in Polish agriculture, but fine-scale assessments of how these changes affected farming and rural landscapes are scarce. This article examines changes in farm sizes and land use patterns after the breakdown of socialism in Poland using micro-census data and satellite images. Our study area is Pyrzyce County. The analysis indicates a polarization of the farm size distribution (e.g., medium-sized farms disappeared) as well as marked changes in land use patterns (e.g., increasing field sizes and field aggregation). Interviews with farmers and stakeholders suggest that this shift can be explained by decreasing competitiveness of medium-sized farms in the emerging new agricultural value chain, which forced farmers to increase and intensify production or to downsize their farms, especially when the preference was for other occupations.     

Sex Offender Residential Movement Patterns: A Markov Chain Analysis

This article introduces a new approach to the analysis of changes in sex offender residences over time. Using a Markov chain framework, we analyze residential movement patterns of registered sex offenders in Hamilton County, Ohio, over a three-year period (2005–2007). Results indicate a 46 percent reduction in offenders violating spatial restriction zone policy as compared to a counterfactual case where offenders move as a function of housing distributions. Strong legacy effects are also found as offenders previously in violation of restriction policies move into other restricted zones at a higher rate than offenders who were previously in compliance with the policy. Parcels that previously were home to registered offenders also continue to attract offenders in future periods. Although we find differences in the probabilities of attracting offenders for parcels outside and inside restricted zones that are consistent with offender restrictive policies, these differences are actually significantly smaller than what holds under the counterfactual. Parcels in restricted zones continue to attract offenders at a higher rate than expected, despite the policy restrictions.     

美国岛链封锁及其对我国海上安全的影响

新中国成立以来,美国及其盟国利用西太平洋岛链对中国采取封锁战略,严重威胁着中国在太平洋海上出海通道的安全。因此中国应从被动到积极应对,采取有效措施冲破岛链封锁,打通出海口,维护中国海上航线及其咽喉要道的安全:一是要把解决台湾问题作为核心关键;二是要把解决南海问题作为重要突破口;三是要把争夺钓鱼岛及其附属岛屿控制权和坚决反对日本利用冲之鸟礁来扩大专属经济区的错误做法作为支撑;四是要加强对岛链和出海通道的科学研究,同时要运用有关国际海洋法维护自身权利,并增强应急能力;五是要努力争取获得在印度洋的出海口;六是要加强各种层次和各种领域的国际合作;七是要不断提升中国海军近海防御和远海防卫作战能力。     

Comparison of the structure and accuracy of two land change models

This paper compares two land change models in terms of appropriateness for various applications and predictive power. Cellular Automata Markov (CA_Markov) and Geomod are the two models, which have similar options to allow for specification of the predicted quantity and location of land categories. The most important structural difference is that CA_Markov has the ability to predict any transition among any number of categories, while Geomod predicts only a one‐way transition from one category to one alternative category.

To assess the predictive power, each model is run several times to predict land change in central Massachusetts, USA. The models are calibrated with information from 1971 to 1985, and then the models predict the change from 1985 to 1999. The method to measure the predictive power: 1) separates the calibration process from the validation process, 2) assesses the accuracy at multiple resolutions, and 3) compares the predictive model vis‐à‐vis a null model that predicts pure persistence. Among 24 model runs, the predictive models are more accurate than the null model at resolutions coarser than two kilometres, but not at resolutions finer than one kilometre. The choice of the options account for more variation in accuracy of runs than the choice of the model per se. The most accurate model runs are those that did not use spatial contiguity explicitly. For this particular study area, the added complexity of CA_Markov is of no benefit.     

基于马尔科夫模型的新疆甘家湖湿地景观格局模拟与预测

以干旱、半干旱区生态脆弱的甘家湖湿地为研究对象,基于2000年和2008年第2期Land-sat TM/ETM为数据源,运用ARCGIS等地理信息系统分析软件,结合实地考察对研究区进行景观分类,确定转移概率矩阵,制作景观格局空间转移格局图,并将马尔科夫过程引入到湿地景观格局的预测和分析,对湿地各景观要素面积进行分析和动态预测。结果表明:①新疆甘家湖湿地功能正在逐步退化,表现于水域面积和沼泽地面积的减小,盐碱地面积不断扩大;②随着对湿地保护的加强,近些年来湿地环境有明显改善,基于马尔科夫模型的预测,在未来的近50年内,沙地面积趋于减少,由2008年的27.4%减少到2060的21.98%,草地面积趋于增加,由2008年的0.6%上升到2060年的1.33%,局部地区的湿地环境有所转好。