显示器电磁木马是通过控制计算机屏幕电磁辐射达到窃取信息目的的一种新型木马。当前的主流防护思想是用软件防护代替较为成熟但造价昂贵的硬件防护机制,然而目前软防护思想大多侧重于理论方法的探索,在实现机制上相对比较复杂。针对显...显示器电磁木马是通过控制计算机屏幕电磁辐射达到窃取信息目的的一种新型木马。当前的主流防护思想是用软件防护代替较为成熟但造价昂贵的硬件防护机制,然而目前软防护思想大多侧重于理论方法的探索,在实现机制上相对比较复杂。针对显示器电磁木马的工作特点提出了Soft-TEMPEST防护机制,设计了显示器电磁木马的ADFA(API Detection and Frequency Analysis)检测方法。该方法通过API函数序列的周期性挖掘分析,结合对屏幕像素信息的傅里叶变换及频谱分析,达到检测出木马进程的目的。测试结果表明,该方法能够成功检测出多种显示器电磁木马,而且原理简单,方便投入使用。展开更多
In this context,two different approaches of soil liquefaction evaluation using a soft computing technique based on the worldwide standard penetration test(SPT) databases have been studied.Gene expression programming(G...In this context,two different approaches of soil liquefaction evaluation using a soft computing technique based on the worldwide standard penetration test(SPT) databases have been studied.Gene expression programming(GEP) as a gray-box modeling approach is used to develop different deterministic models in order to evaluate the occurrence of soil liquefaction in terms of liquefaction field performance indicator(LI) and factor of safety(FS) in logistic regression and classification concepts.The comparative plots illustrate that the classification concept-based models show a better performance than those based on logistic regression.In the probabilistic approach,a calibrated mapping function is developed in the context of Bayes’ theorem in order to capture the failure probabilities(PL) in the absence of the knowledge of parameter uncertainty.Consistent results obtained from the proposed probabilistic models,compared to the most well-known models,indicate the robustness of the methodology used in this study.The probability models provide a simple,but also efficient decision-making tool in engineering design to quantitatively assess the liquefaction triggering thresholds.展开更多
The shear stress distribution in circular channels was modeled in this study using gene expression programming(GEP). 173 sets of reliable data were collected under four flow conditions for use in the training and test...The shear stress distribution in circular channels was modeled in this study using gene expression programming(GEP). 173 sets of reliable data were collected under four flow conditions for use in the training and testing stages. The effect of input variables on GEP modeling was studied and 15 different GEP models with individual, binary, ternary, and quaternary input combinations were investigated. The sensitivity analysis results demonstrate that dimensionless parameter y/P, where y is the transverse coordinate, and P is the wetted perimeter, is the most influential parameter with regard to the shear stress distribution in circular channels. GEP model 10, with the parameter y/P and Reynolds number(Re) as inputs, outperformed the other GEP models, with a coefficient of determination of 0.7814 for the testing data set. An equation was derived from the best GEP model and its results were compared with an artificial neural network(ANN) model and an equation based on the Shannon entropy proposed by other researchers. The GEP model, with an average RMSE of 0.0301, exhibits superior performance over the Shannon entropy-based equation, with an average RMSE of 0.1049, and the ANN model, with an average RMSE of 0.2815 for all flow depths.展开更多
A single soft fault diagnosis method for analog circuit with tolerance based on particle swarm optimization （PSO） is proposed. The parameter deviation of circuit elements is defined as the element of particle. Node-...A single soft fault diagnosis method for analog circuit with tolerance based on particle swarm optimization （PSO） is proposed. The parameter deviation of circuit elements is defined as the element of particle. Node-voltage incremental equations based on the sensitivity analysis are built as constraints of a linear programming （LP） equation. Through inducing the penalty coefficient, the LP equation is set as the fitness function for the PSO program. After evaluating the best position of particles, the position of the optimal particle states whether the actual parameter is within tolerance range or not. Simulation result shows the effectiveness of the method.展开更多
智能软开关(soft normally open point, SNOP)凭借其灵活的功率调节能力逐渐应用于配电网中。但由于大量分布式电源(distributed generation, DG)接入,SNOP受到线路容量的限制,调节能力有限。为发挥其最大调节能力,文中提出适用于配电...智能软开关(soft normally open point, SNOP)凭借其灵活的功率调节能力逐渐应用于配电网中。但由于大量分布式电源(distributed generation, DG)接入,SNOP受到线路容量的限制,调节能力有限。为发挥其最大调节能力,文中提出适用于配电系统的SNOP对线路有功功率裕度调节灵敏度的定义,将其作为SNOP调节能力的评价指标,由此建立SNOP的选址优化模型。在此基础上,引入系统节点电压裕度以及线路功率裕度2个安全评价指标,构建以综合运行裕度最大为目标函数的配电网运行优化模型。将上述模型转化为二阶锥模型,通过MATLAB工具实现该问题的有效求解。最后,通过改进的IEEE 33节点算例对所提模型与求解方法进行验证,进一步表明了所提选址方法能够发挥SNOP的最大调节作用,优化控制策略可以实现配电网安全经济运行。展开更多
文摘显示器电磁木马是通过控制计算机屏幕电磁辐射达到窃取信息目的的一种新型木马。当前的主流防护思想是用软件防护代替较为成熟但造价昂贵的硬件防护机制,然而目前软防护思想大多侧重于理论方法的探索,在实现机制上相对比较复杂。针对显示器电磁木马的工作特点提出了Soft-TEMPEST防护机制,设计了显示器电磁木马的ADFA(API Detection and Frequency Analysis)检测方法。该方法通过API函数序列的周期性挖掘分析,结合对屏幕像素信息的傅里叶变换及频谱分析,达到检测出木马进程的目的。测试结果表明,该方法能够成功检测出多种显示器电磁木马,而且原理简单,方便投入使用。
文摘In this context,two different approaches of soil liquefaction evaluation using a soft computing technique based on the worldwide standard penetration test(SPT) databases have been studied.Gene expression programming(GEP) as a gray-box modeling approach is used to develop different deterministic models in order to evaluate the occurrence of soil liquefaction in terms of liquefaction field performance indicator(LI) and factor of safety(FS) in logistic regression and classification concepts.The comparative plots illustrate that the classification concept-based models show a better performance than those based on logistic regression.In the probabilistic approach,a calibrated mapping function is developed in the context of Bayes’ theorem in order to capture the failure probabilities(PL) in the absence of the knowledge of parameter uncertainty.Consistent results obtained from the proposed probabilistic models,compared to the most well-known models,indicate the robustness of the methodology used in this study.The probability models provide a simple,but also efficient decision-making tool in engineering design to quantitatively assess the liquefaction triggering thresholds.
文摘The shear stress distribution in circular channels was modeled in this study using gene expression programming(GEP). 173 sets of reliable data were collected under four flow conditions for use in the training and testing stages. The effect of input variables on GEP modeling was studied and 15 different GEP models with individual, binary, ternary, and quaternary input combinations were investigated. The sensitivity analysis results demonstrate that dimensionless parameter y/P, where y is the transverse coordinate, and P is the wetted perimeter, is the most influential parameter with regard to the shear stress distribution in circular channels. GEP model 10, with the parameter y/P and Reynolds number(Re) as inputs, outperformed the other GEP models, with a coefficient of determination of 0.7814 for the testing data set. An equation was derived from the best GEP model and its results were compared with an artificial neural network(ANN) model and an equation based on the Shannon entropy proposed by other researchers. The GEP model, with an average RMSE of 0.0301, exhibits superior performance over the Shannon entropy-based equation, with an average RMSE of 0.1049, and the ANN model, with an average RMSE of 0.2815 for all flow depths.
基金supported by the Program for New Century Excellent Talents in University under Grant No.NCET-05-0804partly supported by Chinese National Programs for High Technology Research and Development under Grant No.2006AA06Z222
文摘A single soft fault diagnosis method for analog circuit with tolerance based on particle swarm optimization （PSO） is proposed. The parameter deviation of circuit elements is defined as the element of particle. Node-voltage incremental equations based on the sensitivity analysis are built as constraints of a linear programming （LP） equation. Through inducing the penalty coefficient, the LP equation is set as the fitness function for the PSO program. After evaluating the best position of particles, the position of the optimal particle states whether the actual parameter is within tolerance range or not. Simulation result shows the effectiveness of the method.
文摘智能软开关(soft normally open point, SNOP)凭借其灵活的功率调节能力逐渐应用于配电网中。但由于大量分布式电源(distributed generation, DG)接入,SNOP受到线路容量的限制,调节能力有限。为发挥其最大调节能力,文中提出适用于配电系统的SNOP对线路有功功率裕度调节灵敏度的定义,将其作为SNOP调节能力的评价指标,由此建立SNOP的选址优化模型。在此基础上,引入系统节点电压裕度以及线路功率裕度2个安全评价指标,构建以综合运行裕度最大为目标函数的配电网运行优化模型。将上述模型转化为二阶锥模型,通过MATLAB工具实现该问题的有效求解。最后,通过改进的IEEE 33节点算例对所提模型与求解方法进行验证,进一步表明了所提选址方法能够发挥SNOP的最大调节作用,优化控制策略可以实现配电网安全经济运行。
