LS-SVM （least squares support vector machines） are a class of kemel machines emphasizing on primal-dual aspects in a constrained optimization framework. LS-SVMs aim at extending methodologies typical of classical su...LS-SVM （least squares support vector machines） are a class of kemel machines emphasizing on primal-dual aspects in a constrained optimization framework. LS-SVMs aim at extending methodologies typical of classical support vector machines for problems beyond classification and regression. This paper describes a methodology that was developed for the prediction of the critical flashover voltage of polluted insulators by using a LS-SVM. The methodology uses as input variables characteristics of the insulator such as diameter, height, creepage distance, form factor and equivalent salt deposit density. The estimation offlashover performance of polluted insulators is based on field experience and laboratory tests are invaluable as they significantly reduce the time and labour involved in insulators design and selection. The majority of the variables to be predicted are dependent upon several independent variables. The results from this work are useful to predict the contamination severity, critical flashover voltage as a function of contamination severity, arc length, and especially to predict the flashover voltage. The validity of the approach was examined by testing several insulators with different geometries. Moreover, the performance of the proposed approach with other intelligence method based on ANN （artificial neural networks） is compared. It can be concluded that the LS-SVM approach has better generalization ability that assist the measurement and monitoring of contamination severity, flashover voltage and leakage current.展开更多
OBJECTIVE: To evaluate the effect of Huadananshen mistura in clinical treatment of Chinese patients with insomnia. METHODS: In this randomized, double-blind, placebo-controlled, multi-center study, 244 patients with i...OBJECTIVE: To evaluate the effect of Huadananshen mistura in clinical treatment of Chinese patients with insomnia. METHODS: In this randomized, double-blind, placebo-controlled, multi-center study, 244 patients with insomnia were randomly assigned to a placebo group, a low-dose (10 mL/day), or a high-dose (20 mL/day) mistura group. Efficacy was assessed by using the sleep dysfunction rating scale (SDRS) and Clinical Global Impression-Improvement (CGI-I) scores. Safety and tolerability assessments included emergent adverse events, laboratory tests, and electrocardiograms. RESULTS: Total SDRS scores decreased in all three groups, and there were significant differences between the placebo group and the lowand high-dose mistura groups (P=0.000). CGI-I ratings in the lowand high-dose mistura groups were sig-nificantly better than that of the placebo group (P= 0.000). Incidences of rebound insomnia were similar in all three groups (placebo group: 6.94% , low-dose mistura group: 12.99% , and high-dose mistura group: 10.96% ; P=0.475). The efficacy of Huadananshen mistura in the lowor high-dose group was significantly better than that of the placebo group (P=0.000), but with no significant difference found between the lowand high-dose mistura groups (P=0.887). The rates of adverse events were similar in the three groups (placebo 2.44% , low-dose mistura 0%, and high-dose mistura 5%; P=0.088). CONCLUSION: Huadananshen mistura is an effective and generally well-tolerated hypnotic medicine for the treatment of Chinese patients with insomnia.展开更多
文摘LS-SVM （least squares support vector machines） are a class of kemel machines emphasizing on primal-dual aspects in a constrained optimization framework. LS-SVMs aim at extending methodologies typical of classical support vector machines for problems beyond classification and regression. This paper describes a methodology that was developed for the prediction of the critical flashover voltage of polluted insulators by using a LS-SVM. The methodology uses as input variables characteristics of the insulator such as diameter, height, creepage distance, form factor and equivalent salt deposit density. The estimation offlashover performance of polluted insulators is based on field experience and laboratory tests are invaluable as they significantly reduce the time and labour involved in insulators design and selection. The majority of the variables to be predicted are dependent upon several independent variables. The results from this work are useful to predict the contamination severity, critical flashover voltage as a function of contamination severity, arc length, and especially to predict the flashover voltage. The validity of the approach was examined by testing several insulators with different geometries. Moreover, the performance of the proposed approach with other intelligence method based on ANN （artificial neural networks） is compared. It can be concluded that the LS-SVM approach has better generalization ability that assist the measurement and monitoring of contamination severity, flashover voltage and leakage current.
基金Supported by the Grants from National Major Project for IND(2012ZX09303-003)Shanghai Health Talent Professional Project(XBR2011049)
文摘OBJECTIVE: To evaluate the effect of Huadananshen mistura in clinical treatment of Chinese patients with insomnia. METHODS: In this randomized, double-blind, placebo-controlled, multi-center study, 244 patients with insomnia were randomly assigned to a placebo group, a low-dose (10 mL/day), or a high-dose (20 mL/day) mistura group. Efficacy was assessed by using the sleep dysfunction rating scale (SDRS) and Clinical Global Impression-Improvement (CGI-I) scores. Safety and tolerability assessments included emergent adverse events, laboratory tests, and electrocardiograms. RESULTS: Total SDRS scores decreased in all three groups, and there were significant differences between the placebo group and the lowand high-dose mistura groups (P=0.000). CGI-I ratings in the lowand high-dose mistura groups were sig-nificantly better than that of the placebo group (P= 0.000). Incidences of rebound insomnia were similar in all three groups (placebo group: 6.94% , low-dose mistura group: 12.99% , and high-dose mistura group: 10.96% ; P=0.475). The efficacy of Huadananshen mistura in the lowor high-dose group was significantly better than that of the placebo group (P=0.000), but with no significant difference found between the lowand high-dose mistura groups (P=0.887). The rates of adverse events were similar in the three groups (placebo 2.44% , low-dose mistura 0%, and high-dose mistura 5%; P=0.088). CONCLUSION: Huadananshen mistura is an effective and generally well-tolerated hypnotic medicine for the treatment of Chinese patients with insomnia.
