The Deep Packet Inspection(DPI)method is a popular method that can accurately identify the flow data and its corresponding application.Currently,the DPI method is widely used in common network management systems.Howev...The Deep Packet Inspection(DPI)method is a popular method that can accurately identify the flow data and its corresponding application.Currently,the DPI method is widely used in common network management systems.However,the major limitation of DPI systems is that their signature library is mainly extracted manually,which makes it hard to efficiently obtain the signature of new applications.Hence,in this paper,we propose an automatic signature extraction mechanism using Principal Component Analysis(PCA)technology,which is able to extract the signature automatically.In the proposed method,the signatures are expressed in the form of serial consistent sequences constructed by principal components instead of normally separated substrings in the original data extracted from the traditional methods.Extensive experiments based on numerous sets of data have been carried out to evaluate the performance of the proposed scheme,and the results prove that the newly proposed method can achieve good performance in terms of accuracy and efficiency.展开更多
In this paper we discuss how to measure the component importance for a system in its signature representation. The definition is given in terms of compensator transform and it can be considered as a new formalization ...In this paper we discuss how to measure the component importance for a system in its signature representation. The definition is given in terms of compensator transform and it can be considered as a new formalization of the ideas presented by Bergman [1] in the context of system signature.展开更多
The Varzaghan district at the northwestern margin of the Urumieh–Dokhtar magmatic arc, is considered a promising area for the exploration of porphyry Cu deposits in Iran. In this study we identified mono-and multi-el...The Varzaghan district at the northwestern margin of the Urumieh–Dokhtar magmatic arc, is considered a promising area for the exploration of porphyry Cu deposits in Iran. In this study we identified mono-and multi-element geochemical anomalies associated with Cu–Au–Mo–Bi mineralization in the central parts of the Varzaghan district by applying the concentration–area fractal method. After mono-element geochemical investigations, principal component analysis was applied to ten selected elements in order to acquire a multi-element geochemical signature based on the mineralization-related component. Quantitative comparisons of the obtained fractal-based populations were carried out in accordance with known Cu occurrences using Student's t-values. Then,significant mono-and multi-element geochemical layers were separately combined with related geologic and structural layers to generate prospectivity models, using the fuzzy GAMMA approach. For quantitative evaluation of the effectiveness of different geochemical signatures in final prospectivity models, a prediction-area plot was adapted. The results show that the multi-element geochemical signature of principal component one(PC1) is more effective than mono-element layers in delimiting exploration targets related to porphyry Cu deposits.展开更多
目的:观察舌下免疫治疗(SLIT)疗效与尘螨组分sIgE和sIgG4水平变化的相关性。方法:回顾性分析2018年4月~2021年10月就诊于某院过敏反应科并行SLIT的过敏性鼻炎患儿(n=37),根据治疗1年后症状和药物综合评分(CSMS)分为控制稳定组(n=25)和...目的:观察舌下免疫治疗(SLIT)疗效与尘螨组分sIgE和sIgG4水平变化的相关性。方法:回顾性分析2018年4月~2021年10月就诊于某院过敏反应科并行SLIT的过敏性鼻炎患儿(n=37),根据治疗1年后症状和药物综合评分(CSMS)分为控制稳定组(n=25)和控制不稳定组(n=12),比较两组患儿9种重要尘螨致敏蛋白组分(Derp1/Derf1、Derp2/Derf2、Derp5、Derp7、Derp10、Derp21和Derp23)sIgE和sIgG4的水平变化。结果:Derp1/Derf1和Derp2/Derf2为主要致敏蛋白组分,其治疗前sIgE阳性率为86.5%~94.6%,其中Der p 2的sIgE浓度高于Derp1(P<0.0001)、Derp5(P<0.001)、Derp7(P<0.001)、Derp10(P<0.001)、Derp21(P<0.01);Derf2的sIgE浓度高于Derf1(P<0.0001)、Derp5(P<0.0001)、Derp7(P<0.0001)、Der p 10(P<0.0001)、Der p 21(P<0.0001)和Der p 23(P<0.01)。治疗前Der f 2的sIgG4浓度高于其他组分(P<0.0001),控制不稳定组中Der f 1的sIgG4阳性率(33.3%)高于控制稳定组(4.0%,P<0.05),且控制不稳定组中Derf1和Derp10的sIgG4浓度高于控制稳定组(P<0.05)。治疗1年后,控制稳定组患儿Der f 1和Der p 2的sIgG4水平高于治疗前(P<0.05)。结论:尘螨致敏过敏性鼻炎患儿应用SLIT治疗后,Der f 1和Der p 2的sIgG4浓度升高明显,提示SLIT疗效较好,为临床评估SLIT疗效提供了线索。展开更多
This paper considers machine-component cell formation problem of cellular manufacturing system. Since this problem comes under combinatorial category, development of a meta-heuristic is a must. In this paper, a hybrid...This paper considers machine-component cell formation problem of cellular manufacturing system. Since this problem comes under combinatorial category, development of a meta-heuristic is a must. In this paper, a hybrid genetic algorithm is presented. Normally, in genetic algorithm, the initial population is generated by random assignment of genes in each of the chromosomes. In this paper, the initial population is created using ideal seed heuristic. The proposed algorithm is compared with four other algorithms using 28 problems from literature. Through a completed factorial experiment, it is observed that the proposed algorithm outperforms the other algorithms in terms of grouping efficiency as well as grouping efficacy.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.61003282Beijing Higher Education Young Elite Teacher Project+3 种基金China Next Generation Internet(CNGI)Project"Research and Trial on Evolving Next Generation Network Intelligence Capability Enhancement(NICE)"the National Basic Research Program(973 Program)under Grant No.2009CB320-505the National Science and Technology Major Project"Research about Architecture of Mobile Internet"under Grant No.2011ZX03-002-001-01the National High Technology Research and Development Program(863 Program)under Grant No.2011AA010704
文摘The Deep Packet Inspection(DPI)method is a popular method that can accurately identify the flow data and its corresponding application.Currently,the DPI method is widely used in common network management systems.However,the major limitation of DPI systems is that their signature library is mainly extracted manually,which makes it hard to efficiently obtain the signature of new applications.Hence,in this paper,we propose an automatic signature extraction mechanism using Principal Component Analysis(PCA)technology,which is able to extract the signature automatically.In the proposed method,the signatures are expressed in the form of serial consistent sequences constructed by principal components instead of normally separated substrings in the original data extracted from the traditional methods.Extensive experiments based on numerous sets of data have been carried out to evaluate the performance of the proposed scheme,and the results prove that the newly proposed method can achieve good performance in terms of accuracy and efficiency.
文摘In this paper we discuss how to measure the component importance for a system in its signature representation. The definition is given in terms of compensator transform and it can be considered as a new formalization of the ideas presented by Bergman [1] in the context of system signature.
文摘The Varzaghan district at the northwestern margin of the Urumieh–Dokhtar magmatic arc, is considered a promising area for the exploration of porphyry Cu deposits in Iran. In this study we identified mono-and multi-element geochemical anomalies associated with Cu–Au–Mo–Bi mineralization in the central parts of the Varzaghan district by applying the concentration–area fractal method. After mono-element geochemical investigations, principal component analysis was applied to ten selected elements in order to acquire a multi-element geochemical signature based on the mineralization-related component. Quantitative comparisons of the obtained fractal-based populations were carried out in accordance with known Cu occurrences using Student's t-values. Then,significant mono-and multi-element geochemical layers were separately combined with related geologic and structural layers to generate prospectivity models, using the fuzzy GAMMA approach. For quantitative evaluation of the effectiveness of different geochemical signatures in final prospectivity models, a prediction-area plot was adapted. The results show that the multi-element geochemical signature of principal component one(PC1) is more effective than mono-element layers in delimiting exploration targets related to porphyry Cu deposits.
文摘目的:观察舌下免疫治疗(SLIT)疗效与尘螨组分sIgE和sIgG4水平变化的相关性。方法:回顾性分析2018年4月~2021年10月就诊于某院过敏反应科并行SLIT的过敏性鼻炎患儿(n=37),根据治疗1年后症状和药物综合评分(CSMS)分为控制稳定组(n=25)和控制不稳定组(n=12),比较两组患儿9种重要尘螨致敏蛋白组分(Derp1/Derf1、Derp2/Derf2、Derp5、Derp7、Derp10、Derp21和Derp23)sIgE和sIgG4的水平变化。结果:Derp1/Derf1和Derp2/Derf2为主要致敏蛋白组分,其治疗前sIgE阳性率为86.5%~94.6%,其中Der p 2的sIgE浓度高于Derp1(P<0.0001)、Derp5(P<0.001)、Derp7(P<0.001)、Derp10(P<0.001)、Derp21(P<0.01);Derf2的sIgE浓度高于Derf1(P<0.0001)、Derp5(P<0.0001)、Derp7(P<0.0001)、Der p 10(P<0.0001)、Der p 21(P<0.0001)和Der p 23(P<0.01)。治疗前Der f 2的sIgG4浓度高于其他组分(P<0.0001),控制不稳定组中Der f 1的sIgG4阳性率(33.3%)高于控制稳定组(4.0%,P<0.05),且控制不稳定组中Derf1和Derp10的sIgG4浓度高于控制稳定组(P<0.05)。治疗1年后,控制稳定组患儿Der f 1和Der p 2的sIgG4水平高于治疗前(P<0.05)。结论:尘螨致敏过敏性鼻炎患儿应用SLIT治疗后,Der f 1和Der p 2的sIgG4浓度升高明显,提示SLIT疗效较好,为临床评估SLIT疗效提供了线索。
文摘This paper considers machine-component cell formation problem of cellular manufacturing system. Since this problem comes under combinatorial category, development of a meta-heuristic is a must. In this paper, a hybrid genetic algorithm is presented. Normally, in genetic algorithm, the initial population is generated by random assignment of genes in each of the chromosomes. In this paper, the initial population is created using ideal seed heuristic. The proposed algorithm is compared with four other algorithms using 28 problems from literature. Through a completed factorial experiment, it is observed that the proposed algorithm outperforms the other algorithms in terms of grouping efficiency as well as grouping efficacy.
