协同环境中共有资源的细粒度协作访问控制策略

在军事和商业领域中,由多个自治域形成的协作群体对共有资源(如客体、应用程序以及服务等)的访问问题越来越受到重视.协作中的基本事实是:尽管这些自治域有共同的目标,但同时有不同的自身利益.为了有效地保护共有资源,把“信任”的概念引入了协作访问控制中,并在基于量化权限的思想上,提出了细粒度的协作访问控制策略.在该策略里,权限的使用形式是元权限,也就是单位权限,它是访问共有客体权限的一个划分,可为多个域中不同用户所拥有.当访问共有资源时,参与者们所拥有的元权限的值之和以及人数必须达到规定的权限门限值和人数值,并且访问时间是所有参与者的共同许可访问时间段,这使得可以对协作资源进行有效地分布控制.另外,还引入了元权限的使用时间段约束.最后,证明了该细粒度协作访问控制策略关于协作系统的状态转换是保持安全的.

基于安全操作系统的电子证据获取与存储

基于实时取证的思想,提出了一种安全可取证操作系统(security forensics operating system,简称SeFOS)的概念和实现思路.提出了其总体结构,建立了该系统的取证行为模型,对其取证服务和取证机制进行了分析并作了有关形式化描述,阐述了证据数据的采集和安全保护方法,提出把取证机制置于内核,基于进程、系统调用、内核资源分配和网络数据等获取证据的方法,并通过模拟实验验证了SeFOS的可取证性.可取证操作系统的研究对于进一步研究可取证数据库管理系统(forensic database management system,简称FDBMS)和可取证网络系统(forensic network,简称FNetWork)具有重要意义.

长白山维管束植物多样性分布格局及其影响因子的研究

生物多样性的研究极其广泛，生物多样性的形成、维持机制和分布格局也一直是生物学和环境科学等研究的重要内容，植物作为生物总体中的重要组分，其种类组成、各个种的历史和现时分布及数量等历来是分析研究的重要对象。本文以中国长白山区为研究区域，通过植物多样性数据、地理及地形因子、能量因子、水分因子以及采集量和采集频度等其他因子资料，利用ArcGIS 9.2地理信息系统软件和SPSS等统计学软件，将长白山区按照行政区划分为74个小区，搜集各小区的环境因子数据，统计了各小区的生物多样性的数量，包括种子植物科、属、种，蕨类植物种丰富度状况及采集状况，对长白山区维管束植物分布格局与环境因子的关系进行了研究。 通过SPSS软件等统计学软件的分析，研究了中国长白山区植物多样性分布格局及其与环境因子的关系。研究结果表明，维管束植物的分布格局与年均温、年均降水、1月平均温度和温暖指数（WI）呈显著正相关（P<0.01），与经度、纬度和寒冷指数（CI）呈显著负相关（P<0.01），其中，影响植物分布格局的最主要的两个因子是年均降水量和1月温度（P<0.01, t测验），地理地形因子、热量因子和水分因子与植物多样性分布格局相关性非常显著。长白山区是人们已经开展了大量工作并基本完成了维管束植物普遍采集调查的区域，植物本底资料积累很好，有大量植物信息储存于植物标本之中。植物标本本身和标本为载体所记载的标本采集时间、地点、生境、该植物种在当地的丰富度等相关资料是生物多样性研究中丰富的原始数据源。 长白山区维管束植物包括150科729属1747种。其中蕨类植物22科44属100种，裸子植物5科11属33种，被子植物123科674属1614种。在此基础上，分析长白山区域植物标本采集状况，结果显示植物物种丰富度较高的地区有安图、桓仁、本溪县、凤城、抚松、鞍山市、清原、丹东市、尚志等，而丰富度较低的区域有双鸭山市、延寿、宾县、七台河、双阳、图们、木兰、通河等。长白山区维管植物多样性资源丰富，但各个区域的物种采集状况多寡不均，采集工作比较好的多集中在植物多样性资源保护较好的山区和自然保护区内。

基于双边滤波和双树复小波的图像去噪算法

中国科学院

Combined study of gamma p ->eta p and pi(-)p ->eta n in a chiral constituent quark approach

Within a chiral constituent quark model approach, η-meson production on the proton via electromagnetic and hadron probes is studied. With few parameters, the differential cross section and polarized beam asymmetry for γp → ηp and differential cross section for π − p → ηn processes are calculated and successfully compared with the data in the center-of-mass energy range from threshold up to 2 GeV. The five known resonances S11(1535), S11(1650), P13(1720),D13(1520), and F15(1680) are found to be dominant in the reaction mechanisms in both channels. Possible roles played by new resonances are also investigated; and in the photoproduction channel, significant contribution from S11 and D15 resonances, with masses around 1715 and 2090 MeV, respectively, are deduced. For the so-called missing resonances, no evidence is found within the investigated reactions. The helicity amplitudes and decay widths of N ∗ → πN, ηN are also presented and found to be consistent with the Particle Data Group values.

稠油污染土壤的臭氧预处理研究

采用蛭石模拟土壤,研究稠油污染土壤的臭氧预处理工艺。在臭氧浓度为50mg·L-1,气体流量为0.2m3·h-1的条件下,分析了臭氧通气时间、水土比、污染土壤陈化时间和污染浓度对土壤中石油烃去除率的影响。结果表明,模拟稠油污染土壤的最佳处理条件为臭氧通气30min,水土比为0∶1,此时总石油烃降解率为40.97%,其中芳烃降解率最高为90.18%,其次是饱和烃为61.81%。此外,臭氧预处理可以促使酯类等可溶性石油烃的生成,从而提高稠油的生物可利用率。因而,臭氧预处理能够降低后续处理的负荷,是一种可行的预处理方法。

Shallow gas in the muddy sediments of Eckernförde Bay, Germany

The seafloor of central Eckernförde Bay is characterised by soft muddy sediments that contain free methane gas. Bubbles of free gas cause acoustic turbidity which is observed with acoustic remote sensing systems. Repeated surveys with subbottom profiler and side scan sonar revealed an annual period both of depth of the acoustic turbidity and backscatter strength. The effects are delayed by 3–4 months relative to the atmospheric temperature cycle. In addition, prominent pockmarks, partly related to gas seepage, were detected with the acoustic systems. In a direct approach gas concentrations were measured from cores using the gas chromatography technique. From different tests it is concluded that subsampling of a core should start at its base and should be completed as soon as possible, at least within 35 min after core recovery. Comparison of methane concentrations of summer and winter cores revealed no significant seasonal variation. Thus, it is concluded that the temperature and pressure influences upon solubility control the depth variability of acoustic turbidity which is observed with acoustic remote sensing systems. The delay relative to the atmospheric temperature cycle is caused by slow heat transfer through the water column. The atmospheric temperature cycle as ‘exiting function’ for variable gas solubility offers an opportunity for modelling and predicting the depth of the acoustic turbidity. In practice, however, small-scale variations of, e.g., salinity, or gas concentration profile in the sediment impose limits to predictions. In addition, oceanographic influences as mixing in the water column, variable water inflow, etc. are further complications that reduce the reliability of predictions.