电力工程中的地质灾害危险性评估

我国幅员辽阔,地质环境条件多样且复杂,导致了地质灾害发育强烈,种类繁多、危害较大。地质灾害与工程建设活动密切相关,既相互作用,相互依存,又相互影响[1]。电力工程项目遍布全国,特别是输电线路大多为人烟稀少的山区分布,线路长,跨越的地质地貌区域复杂,存在的地质灾害多种多样,或多或少面临着各种地质灾害的严重威胁[2]。通过电力工程地质灾害危险性评估工作的现状及评估工作流程的介绍,进一步分析电力工程地质灾害的危险性评估工作中存在的问题并提出了相应的看法。     

基于水质指数法的城市河流水质综合评价研究

依据江门市泥海水水质2020年9月的5个断面的监测数据,以溶解氧（ＤＯ）、高锰酸盐指数（ＣＯＤＭｎ）、化学需氧量（ＣＯＤ）、氨氮（ＮＨ3－Ｎ）、总磷（ＴＰ）作为ＣＷＱＩ模型的5个主要变量对河道水质进行综合评价。分析结果表明:各监测点的ＣＯＤＭｎ和ＣＯＤ均满足Ⅳ类水质要求,ＴＰ基本满足Ⅳ类水质要求,ＤＯ污染较为严重,ＮＨ3－Ｎ污染最为严重。通过对泥海水的监测断面的水质时间空间分布趋势分析可知,5个水质参数变化规律在不同监测时间表现趋势差异较大,每个水质参数在不同监测断面中变化规律相差也较大。采用ＣＷＱＩ方法能够从定性和定量两个方面对监测结果进行综合分析,监测结果可为下一步实施改善型措施提供依据。     

No-reference stereoscopic image quality assessment using quaternion wavelet transform and heterogeneous ensemble learning

As the demand for high-quality stereo images has grown in recent years, stereoscopic image quality assessment (SIQA) has become an important research area in modern image processing technology.In this paper, we propose a no-reference stereoscopic image quality assessment (NR-SIQA) model using heterogeneous ensemble learning ‘quality-aware’ features from luminance image, chrominance image, disparity and cyclopean images via quaternion wavelet transform (QWT). Firstly, luminance image and chrominance image are generated by CIELAB color space as monocular perception, and the novel disparity and cyclopean images are utilized to complement with monocular information. Then, a number of ‘quality-aware’ features in the quaternion wavelet domain are discovered, including entropy, texture features, energy features, energy differences features and MSCN coefficients of high frequency sub-band. Finally, a heterogeneous ensemble model via support vector regression (SVR) & extreme learning machine (ELM) & random forest (RF) is proposed to predict quality score, and bootstrap sampling and rotated feature space are used to increase the diversity of data distribution. Comparing with the state-of-the-art NR-SIQA models, experimental results on four public databases prove the accuracy and robustness of the proposed model.     

Maximizing learning without sacrificing the fun: Stealth assessment,adaptivity and learning supports in educational games

In this study, we investigated the validity of a stealth assessment of physics understanding in an educational game, as well as the effectiveness of different game-level delivery methods and various in-game supports on learning. Using a game called Physics Playground, we randomly assigned 263 ninth- to eleventh-grade students into four groups: adaptive, linear, free choice and no-treatment control. Each condition had access to the same in-game learning supports during gameplay. Results showed that: (a) the stealth assessment estimates of physics understanding were valid—significantly correlating with the external physics test scores; (b) there was no significant effect of game-level delivery method on students' learning; and (c) physics animations were the most effective (among eight supports tested) in predicting both learning outcome and in-game performance (e.g. number of game levels solved). We included student enjoyment, gender and ethnicity in our analyses as moderators to further investigate the research questions.     

A Network Security Risk Assessment Method Based on a B_NAG Model

Computer networks face a variety of cyberattacks. Most network attacks are contagious and destructive, and these types of attacks can be harmful to society and computer network security. Security evaluation is an effective method to solve network security problems. For accurate assessment of the vulnerabilities of computer networks, this paper proposes a network security risk assessment method based on a Bayesian network attack graph (B_NAG) model. First, a new resource attack graph (RAG) and the algorithm E-Loop, which is applied to eliminate loops in the B_NAG, are proposed. Second, to distinguish the confusing relationships between nodes of the attack graph in the conversion process, a related algorithm is proposed to generate the B_NAG model. Finally, to analyze the reachability of paths in B_NAG, the measuring indexs such as node attack complexity and node state transition are defined, and an iterative algorithm for obtaining the probability of reaching the target node is presented. On this basis, the posterior probability of related nodes can be calculated. A simulation environment is set up to evaluate the effectiveness of the B_NAG model. The experimental results indicate that the B_NAG model is realistic and effective in evaluating vulnerabilities of computer networks and can accurately highlight the degree of vulnerability in a chaotic relationship.     

石油石化系统言息安全态势评估指标体系研究

文章阐述了石油石化系统信息安全态势评估指标体系的研究意义,提出了指标体系的研究思路,分析了指标体系的基本构成,说明了指标体系的总体框架,并对指标体系的数据获取和应用前景作了介绍。对于丰富和完善国家信息安全态势评估指标体系,是一个有意义的探索。     

基于SPOT-5多光谱影像的矿区塌塘水体提取方法研究

针对基于遥感影像的水体提取方法存在水体提取不完整和误提的现象,提出了一种基于SPOT-5多光谱影像的矿区塌塘水体提取方法。在利用波段合成增加一个可用波段的基础上对已有的水体提取方法进行适当的改进,并基于决策树分类器和改进后的方法进行矿区水体的四级提取,保证了水体提取的完整性,同时减少了误提率;最后利用实测数据对水体提取的精度进行了评定。试验结果表明,基于决策树分类器的水体提取方法具有较高的精度,能满足矿区实际应用的需要。     

一种基于网络安全风险评估的入侵检测方法

针对传统的入侵检测系统存在报警数量大、误报率高等缺陷,提出了一种基于网络安全风险评估的入侵检测方法,该方法基于入侵检测结果,引入抗体浓度随入侵强度动态变化这一人工免疫理论的最新研究成果进行网络安全风险的计算,然后根据当前网络面临的实时安全风险动态设置报警策略。实验结果表明,该方法能够实时、定量地计算主机和网络所面临的风险,并极大地降低报警数量和误报率。     

一种基于灰色关联分析的信息安全风险评估方法研究

随着信息化进程的快速发展,保障信息系统的安全性和降低信息系统潜在的风险,一直是国内外学者关注的焦点,而风险评估正是解决该问题的有效方法之一,但是在风险评估过程中存在评估指标难以量化、风险值难以界定等困难,因此文章提出了一种基于灰色关联分析的信息安全风险评估方法,该方法首先建立了信息系统的风险评估指标体系,其次将评估的信息系统与最优信息系统进行关联度分析,最后得出信息系统风险的准确度量。该方法可以使信息系统的评估过程简单化,标准化。     

分布式信息系统风险评估研究-以安徽烟草为例

对分布式信息系统所面临的主要风险进行识别和评估是构建灾备系统的首要任务。以安徽烟草分布式信息系统为例,首先分析了该信息系统在环境、管理、技术、设备等方面所存在的风险,然后以层次分析法为核心构造了评估决策模型,结合专家打分,计算出各类风险对安徽烟草信息系统的威胁程度并进行排序,从而识别出主要的风险源,为构建灾备体系提供依据。