Multi-level access control model for tree-like hierarchical organizations

An access control model is proposed based on the famous Bell-LaPadula （BLP） model.In the proposed model,hierarchical relationships among departments are built,a new concept named post is proposed,and assigning security tags to subjects and objects is greatly simplified.The interoperation among different departments is implemented through assigning multiple security tags to one post, and the more departments are closed on the organization tree,the more secret objects can be exchanged by the staff of the departments.The access control matrices of the department,post and staff are defined.By using the three access control matrices,a multi granularity and flexible discretionary access control policy is implemented.The outstanding merit of the BLP model is inherited,and the new model can guarantee that all the information flow is under control.Finally,our study shows that compared to the BLP model,the proposed model is more flexible.

Comparing of Aviation Network Structure of Mid-south,Northwest and Southwest of China Based on Hierarchical Index Model

In order to compare the aviation network of mid-south,northwest and southwest of China to reveal the structure similarity and difference for providing quantitative evidence to construct regional aviation network and improve its structure,hierarchical index model of regional aviation network was established through dividing the aviation network into layers to research its structure characters.Data matrixes were defined to record the basic state of regional aviation network.Index matrixes were constructed to describe the quantitative features of regional aviation network.On the basis of these indexes,several structure indexes of all layers of aviation network were calculated to show the structure features of aviation network,such as ratio of passenger volume within the region with across the region,share rate of passenger volume among layers,ratio of average number of airline for each airport,ratio of average passenger volume for each airline and ratio of airline rate.According to the statistical data,similar structure of share rate of passenger volume among layers and average passenger volume for each airline in their regional aviation network was found after calculating.But on the side of ratio of passenger volume within the region with across the region,ratio of average number of airlines for each airport and ratio of airline rate were different.

Study of a Comprehensive Assessment Method for Coal Mine Safety Based on a Hierarchical Grey Analysis

Coal mine safety is a complex system, which is controlled by a number of interrelated factors and is difficult to estimate. This paper proposes an index system of safety assessment based on correlated factors involved in coal mining and a comprehensive evaluation model that combines the advantages of the AHP and a grey clustering method to guarantee the accuracy and objectivity of weight coefficients. First, we confirmed the weight of every index using the AHP, then did a general safety assessment by means of a grey clustering method. This model analyses the status of mining safety both qualitatively and quantitatively. It keeps management and technical groups informed of the situation of the coal production line in real time, which aids in making correct decisions based on practical safety issues. A case study in the application of the model is presented. The results show that the method is applicable and realistic with regard to the core of a coal mine's safety management. Consequently, the safe production of a mine and the awareness of advanced safe production management is accelerated.

Research on Protecting Information Security Based on the Method of Hierarchical Classification in the Era of Big Data

Big data is becoming increasingly important because of the enormous information generation and storage in recent years.It has become a challenge to the data mining technique and management.Based on the characteristics of geometric explosion of information in the era of big data,this paper studies the possible approaches to balance the maximum value and privacy of information,and disposes the Nine-Cells information matrix,hierarchical classification.Furthermore,the paper uses the rough sets theory to proceed from the two dimensions of value and privacy,establishes information classification method,puts forward the countermeasures for information security.Taking spam messages for example,the massive spam messages can be classified,and then targeted hierarchical management strategy was put forward.This paper proposes personal Information index system,Information management platform and possible solutions to protect information security and utilize information value in the age of big data.

Local and regional flood frequency analysis based on hierarchical Bayesian model in Dongting Lake Basin,China

This study developed a hierarchical Bayesian(HB)model for local and regional flood frequency analysis in the Dongting Lake Basin,in China.The annual maximum daily flows from 15 streamflow-gauged sites in the study area were analyzed with the HB model.The generalized extreme value(GEV)distribution was selected as the extreme flood distribution,and the GEV distribution location and scale parameters were spatially modeled through a regression approach with the drainage area as a covariate.The Markov chain Monte Carlo(MCMC)method with Gibbs sampling was employed to calculate the posterior distribution in the HB model.The results showed that the proposed HB model provided satisfactory Bayesian credible intervals for flood quantiles,while the traditional delta method could not provide reliable uncertainty estimations for large flood quantiles,due to the fact that the lower confidence bounds tended to decrease as the return periods increased.Furthermore,the HB model for regional analysis allowed for a reduction in the value of some restrictive assumptions in the traditional index flood method,such as the homogeneity region assumption and the scale invariance assumption.The HB model can also provide an uncertainty band of flood quantile prediction at a poorly gauged or ungauged site,but the index flood method with L-moments does not demonstrate this uncertainty directly.Therefore,the HB model is an effective method of implementing the flexible local and regional frequency analysis scheme,and of quantifying the associated predictive uncertainty.

A Multilevel Secure Relation-Hierarchical Data Model for a Secure DBMS

A multilevel secure relation hierarchical data model for multilevel secure database is extended from the relation hierarchical data model in single level environment in this paper. Based on the model, an upper lower layer relationalintegrity is presented after we analyze and eliminate the covert channels caused by the database integrity.Two SQL statements are extended to process polyinstantiation in the multilevel secure environment.The system based on the multilevel secure relation hierarchical data model is capable of integratively storing and manipulating complicated objects ( e.g. , multilevel spatial data) and conventional data ( e.g. , integer, real number and character string) in multilevel secure database.

DESIGN OF EXACT REGENERATING HIERARCHICAL CODE FOR DISTRIBUTED STORAGE SYSTEM

Erasure code is widely used as the redundancy scheme in distributed storage system. When a storage node fails, the repair process often requires to transfer a large amount of data. Regenerating code and hierarchical code are two classes of codes proposed to reduce the repair bandwidth cost. Regenerating codes reduce the amount of data transferred by each helping node, while hierarchical codes reduce the number of nodes participating in the repair process. In this paper, we propose a "sub-code nesting framework" to combine them together. The resulting regenerating hierarchical code has low repair degree as hierarchical code and lower repair cost than hierarchical code. Our code can achieve exact regeneration of the failed node, and has the additional property of low updating complexity.

OBH-RSI:Object-Based Hierarchical Classification Using Remote Sensing Indices for Coastal Wetland

With the deterioration of the environment,it is imperative to protect coastal wetlands.Using multi-source remote sensing data and object-based hierarchical classification to classify coastal wetlands is an effective method.The object-based hierarchical classification using remote sensing indices(OBH-RSI)for coastal wetland is proposed to achieve fine classification of coastal wetland.First,the original categories are divided into four groups according to the category characteristics.Second,the training and test maps of each group are extracted according to the remote sensing indices.Third,four groups are passed through the classifier in order.Finally,the results of the four groups are combined to get the final classification result map.The experimental results demonstrate that the overall accuracy,average accuracy and kappa coefficient of the proposed strategy are over 94%using the Yellow River Delta dataset.

Structure Evolution of China Aviation Network Based on Hierarchical Model

The annual passenger volume of airport reflected its passenger transport scale and the role in aviation network.The airports in whole country were divided into three layers:first layer airports,second layer airports and third layer airports.The airlines from the first layer airports consisted the first layer aviation network.The airlines from the second layer airports consisted the second layer aviation network.The airlines from the third layer airports consisted the third layer aviation network.The structure and function of different layer aviation network had significant differences.These differences were shown in the number of airlines,average number of airlines of each airport,annual passenger volume of airport and average passenger volume of each airline.National aviation network hierarchical model was constructed to describe the whole country aviation network.The matrix was built to describe the airline number,annual passenger volume,average number of airlines,average passenger volume of each airport and airline rate of aviation network.The index of national aviation network structure was constructed to show the ratio of index between different aviation network layer to describe the aviation network structure.The structure index was built to illustrate the macrostructural features of national aviation network.The statistics data in year 1988,1994,2001,2008 and 2015 of China aviation network were analyzed and basic data matrixes,basic index matrixes and structure index matrixes were calculated.The trend of ratio of corresponding index between the first layer and the second layer showed the change of basic structure of China aviation network.At meantime,the tendency of ratio of corresponding index between the third layer and the second layer also showed the change of basic structure.The trend of network general structure index illustrated that the large scaled new airports and airlines construction had significant influence on the national aviation network structure.

Neighborhood Effects and Political Trust: A Multi-level Analysis of Chinese Rural-to-Urban Migrants’ Trust in County Government

Massive rural-to-urban migration in China is consequential for political trust: rural-to-urban migrants have been found to hold lower levels of trust in local government than their rural peers who choose to stay in the countryside (mean 4.92 and 6.34 out of 10, respectively, p < 0.001). This article explores why migrants have a certain level of political trust in their county-level government. Using data of rural-to-urban migrants from the China Family Panel Survey, this study performs a hierarchical linear modeling (HLM) to unpack the multi-level explanatory factors of rural-to-urban migrants’ political trust. Findings show that the individual-level socio-economic characteristics and perceptions of government performance (Level-1), the neighborhood-level characteristics-the physical and social status and environment of neighborhoods (Level-2), and the objective macroeconomic performance of county-level government (Level-3), work together to explain migrants’ trust levels. These results suggest that considering the effects of neighborhood-level factors on rural-to-urban migrants’ political trust merits policy and public management attention in rapidly urbanizing countries.

基于Donabedian理论的儿童肝移植全周期护理质量指标体系构建

目的初步构建儿童肝移植全周期护理质量指标体系,以期为护理质量监测及管理提供依据。方法以Donabedian“结构-过程-结果”三维质量评价模型为理论框架,采用文献分析、德尔菲法及层次分析法,构建儿童肝移植全周期护理质量指标体系的内容及指标权重。结果3轮函询问卷的有效回收率均为100%,专家权威系数分别为0.95、0.96、0.98,肯德尔和谐系数分别为0.165、0.209、0.220(P均<0.001)。最终构建的质量指标体系包括一级指标3项、二级指标15项、三级指标67项。结论初步构建儿童肝移植全周期护理质量指标体系,可为儿童肝移植护理质量评价提供参考依据。

锡林郭勒盟大型露天煤矿区地质环境时空演化评价

内蒙古锡林郭勒盟大型露天煤矿区经过20多年的开发,产生了一系列矿山地质环境问题,矿区地质环境在一定程度上遭到破坏,因此,开展大型露天煤矿区地质环境时空演化评价可为矿区生态地质环境修复提供参考。本文对锡林郭勒盟3个大型矿区进行地质环境时空演化评价。首先通过现场调查,明确了研究区主要的矿山地质环境问题,包括植被覆盖度下降、土地压占(排土场和工业场地)、地形地貌景观破坏(露天采坑)和含水层破坏等4类;其次利用遥感影像定量获取了2000—2020年之间的矿山地质环境问题信息,并建立了矿山地质环境评价指标体系;然后应用层次分析法确定了矿山地质环境评价指标的权重,并通过基于GIS的影响指数模型对矿山地质环境影响进行了评价和区划,探讨了矿山地质环境时空演化规律。研究结果表明:(1)3个大型矿区植被覆盖度下降区域的面积、排土场压占土地面积和露天采坑破坏地形地貌景观面积随时间不断增加;(2)大型矿区采矿对地质环境的影响划分为无影响区、轻微影响区、一般影响区、较强影响区和强烈影响区5个等级分区;(3)3个大型矿区地质环境时空演化规律基本相同,不同影响区的空间分布特征和面积随时间变化的规律不同。

省域视角下中国优势学科识别与分析——基于分级评价方法

优势学科是一个相对概念,比较视角可以是国家、省份、机构、学科等。目前评价学科水平主要以基本科学指标数据库(ESI)为依据,但ESI学科分类并不能较好地反映中国的学科发展情况,且ESI及其他一些引文分析法存在时滞性和缺乏省际横向比较的弊端。因此,从省域视角探索建立优势学科识别与分析方法体系,为加快建设具有中国特色的世界一流学科、促进各省份完善学科布局提供参考。以美国科学引文索引(SCI)收录论文为数据源,以SCI期刊分类与中国《研究生教育学科专业目录(2022年)》进行映射得到的77个学科作为依据,建立学科相对优势指数和发展潜力优势指数,并综合考虑省份学科规模和质量水平,利用分级评价的方式识别中国31个省份各自的优势学科和潜力学科。结果显示,中国31个省份的优势学科合计125个、潜力学科合计129个。这与各省份学科发展现状基本吻合,证明所提出方法的可行性。据此,各省份可进一步优化资源配置,强化现有优势,同时对亟需资助的潜力学科、弱势学科给予倾斜,构建合理的学科结构。

基于分区层次图的海量高维数据学习索引构建方法

学习索引是破解海量高维数据近似最近邻搜索问题的关键。然而,现有学习索引技术结果仅局限于单个分区中,且依赖于近邻图的构建。随着数据维度和规模的增长,索引难以对分区边界数据进行精确判断,并且构建时间复杂度增大,可扩展性难以保障。针对上述问题,提出了基于分区层次图的学习索引方法PBO-HNSW。该方法对分区边界数据进行重新分配,并行构建分布式图索引结构,从而有效应对近似最近邻搜索问题所面临的挑战。实验结果表明,该方法能够在百万级海量高维数据上实现毫秒级的索引构建。当召回率为0.93时,PBO-HNSW方法构建时间仅为基线方法的36.4%。

基于多时相Sentinel-2A影像的狼毒分布识别

狼毒(Stellera chamaejasme)是近年来青藏高原高寒草地的主要入侵毒杂草之一,及时高效的调查与监测可为狼毒综合防控与退化草地恢复提供重要的技术支持。本研究选取花期前与盛花期的Sentinel-2A多光谱影像,将Google Earth Engine平台去云、环境要素掩膜、特征优选和随机森林分类相结合,探讨区域尺度的狼毒遥感识别方法。结果表明,通过狼毒敏感指数计算,以及Spearman秩相关性分析与随机森林重要性排序相结合的二次降维,提取了7项狼毒分类特征并构建了4个特征组合方案。与单时相特征组合相比,多时相特征组合有效提高了狼毒识别精度,其中,基于随机森林模型的6个特征组合方案的分类总精度为84.62%,狼毒分类精度均大于80%,识别效果最佳。本研究显示,影像去云及掩膜预处理能够有效减少分类干扰信息,花期前与盛花期提取的多时相特征组合增强了狼毒群落与其他群落的影像光谱差异,在区域尺度狼毒遥感识别中具有较好的应用潜力。

大型企业自然灾害应急管理评估模型构建

根据自然灾害应急管理工作实际,基于鱼骨分析原理,构建了大型企业自然灾害应急管理评估指标体系,在此基础上,基于层次分析和模糊评价理论,建立了自然灾害应急管理评估模型。以某大型企业A为例,对自然灾害应急管理体系进行系统评估,梳理存在的问题与薄弱环节,提出加强和完善A企业自然灾害应急管理体系的对策和建议。研究成果可为大型或超大型企业自然灾害应急管理评估提供一定的理论和技术支撑。

基于多因子分级加权指数和法的雄安新区工程建设适宜性评价

【研究目的】河北雄安新区是一座即将建设的城市,为保障新区规划建设地质安全开展雄安新区工程建设适宜性评价。【研究方法】根据雄安新区地质条件,按照规划建设千年大计的要求,量身定制了工程建设适宜性评价指标体系,采用多因子分级加权指数和法对雄安新区工程建设适宜性进行了评价。【研究结果】结果显示:雄安新区工程建设适宜性较好,均为适宜区(925 km^(2))和较适宜区(845 km^(2)),较适宜区分布于研究区中南部和东北部,其他地区为适宜区,雄安新区部分地区存在一定程度的地面沉降、砂土液化、软土、水土污染和水土腐蚀性等环境地质问题。环境地质问题的存在直接影响了综合评价结果,但未在综合评定中直接排除建设的可行性。【结论】构建了雄安新区工程建设适宜性评价的全要素参数体系,并参规量化了评价因子,确定了较为合理的权重取值,形成了地质调查工作服务国土空间布局、工程建设、地下空间开发等为重点的地质调查评价方法体系,可为相关城市规划建设提供借鉴。

马尔可夫攻防模型下网络边缘态势监控仿真

马尔可夫攻防模型能够生成观测序列,通过对此序列的识别与预测,达到监控目的。由于网络的数据量大,各种攻击手段都对网络安全造成严重威胁。为了提高监控效果,提出一种基于马尔可夫攻防模型的网络边缘态势监控。通过设置采集平台,将马尔科夫攻防过程看作用户与攻击者的博奔过程,利用状态空间、状态概率分布、风险指数等七元组建立马尔可夫攻防模型;确定模型参数,采用模糊层次算法选取监控指标,设计模糊矩阵,获取指标权重,计算风险指数;确立监控平台整体架构,通过上述平台呈现风险指数,实现网络边缘态势监控。实验结果表明,所提方法的监控效果好,监控的平均绝对误差小,始终低于0.2,且对所有攻击类型均适用。

护理研究生科研伦理素养评价指标体系的构建

目的构建护理研究生科研伦理素养评价指标体系,为客观评价护理研究生的科研伦理素养提供工具。方法以素质冰山模型为理论基础,基于文献回顾和小组讨论拟订护理研究生科研伦理素养评价指标体系初稿,应用德尔菲法和层次分析法确定最终评价指标体系和权重。结果2轮函询专家积极系数分别为100%和85.0%,专家权威系数为0.900、0.921,肯德尔和谐系数为0.134、0.189(均P<0.05)。最终形成的护理研究生科研伦理素养评价指标体系,包括2个一级指标(外显科研伦理素养、内隐科研伦理素养)、5个二级指标(科研伦理知识、科研伦理技能、科研伦理能力、科研伦理态度、科研伦理价值观)、31个三级指标。结论构建的护理研究生科研伦理素养评价指标体系科学合理,可作为护理研究生科研伦理素养的评价工具。

有向图上基于层次树索引的最大cycle truss社区搜索

社区搜索旨在从信息网络中找出包含用户查询顶点的高内聚连通子图,cycle truss是一种基于cycle三角形的社区搜索模型,而现有的基于索引的cycle truss社区搜索方法存在索引空间大、搜索效率低、社区内聚性低的缺点。为了解决这一问题,提出一种基于层次树索引的最大cycle truss社区搜索方法。首先,提出了k-cycle truss分解算法,并引入了两个重要的概念:cycle三角连通与k-层次等价。基于k-层次等价设计了层次树索引TreeCIndex与表结构索引SuperTable,在此基础上,并基于这两个新的索引,提出了两个高效的cycle truss社区搜索算法。在4个真实数据集上与已有的基于TrussIndex与EquiTruss的社区搜索算法进行了比较,实验结果表明,TreeCIndex与SuperTable比TrussIndex与EquiTruss节省至少41.5%的空间,索引构建的时间节省8.2%至98.3%,且搜索最大cycle truss社区的效率分别高出了一个和两个数量级。