The maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are ...The maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are common-used parameter estimation methods for maximum entropy distribution. In this study, we propose to use the particle swarm optimization method as a new parameter estimation method for the maximum entropy distribution, which has the advantage to avoid deviation introduced by simplifications made in other methods. We conducted a case study to fit the hindcasted thickness of the sea ice in the Liaodong Bay of Bohai Sea using these three parameter-estimation methods for the maximum entropy distribution. All methods implemented in this study pass the K-S tests at 0.05 significant level. In terms of the average sum of deviation squares, the empirical curve fitting method provides the best fit for the original data, while the method of moment provides the worst. Among all three methods, the particle swarm optimization method predicts the largest thickness of the sea ice for a same return period. As a result, we recommend using the particle swarm optimization method for the maximum entropy distribution for offshore structures mainly influenced by the sea ice in winter, but using the empirical curve fitting method to reduce the cost in the design of temporary and economic buildings.展开更多
The purpose of the study was to explore the factors mediating college students' radicalization. A sample of 1,116 students was drawn from four different Jordanian universities. The construct validity of the scale was...The purpose of the study was to explore the factors mediating college students' radicalization. A sample of 1,116 students was drawn from four different Jordanian universities. The construct validity of the scale was estimated by calculating the correlation between the radicalization items and the negative emotion items. A positive significant relationship was found (0.12, a = 0.000), a sign of validity of the scale. The scale reliability was also strong and was estimated at 0.90 using Cronbach Alpha. Factor analysis produced five factors explaining 45% of the total variance of radicalization. The first factor labeled "political radicalization" explained 18.5% of the variance, the second factor "religious radicalization" explained 12.7%, the third factor "violent radicalization" explained 6.4% of the variance, the fourth "group radicalization" accounted for 4%, and the fifth factor "social radicalization" only accounted for 3% of the total variance. Significant differences in student radicalization were found according to the geographical region of the university (North, Center and South), F = 14, a = 0.000. However, no significant differences were found in radicalization as it relates to gender, and type of college (i.e., Humanities vs. Pure Sciences).展开更多
基金supported by the National Natural Science Foundation of China (Nos. 51279186, 51479183, 51509227)the Shandong Province Natural Science Foundation, China (No. ZR2014EEQ030)the Fundamental Research Funds for the Central Universities (No. 201413003)
文摘The maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are common-used parameter estimation methods for maximum entropy distribution. In this study, we propose to use the particle swarm optimization method as a new parameter estimation method for the maximum entropy distribution, which has the advantage to avoid deviation introduced by simplifications made in other methods. We conducted a case study to fit the hindcasted thickness of the sea ice in the Liaodong Bay of Bohai Sea using these three parameter-estimation methods for the maximum entropy distribution. All methods implemented in this study pass the K-S tests at 0.05 significant level. In terms of the average sum of deviation squares, the empirical curve fitting method provides the best fit for the original data, while the method of moment provides the worst. Among all three methods, the particle swarm optimization method predicts the largest thickness of the sea ice for a same return period. As a result, we recommend using the particle swarm optimization method for the maximum entropy distribution for offshore structures mainly influenced by the sea ice in winter, but using the empirical curve fitting method to reduce the cost in the design of temporary and economic buildings.
文摘The purpose of the study was to explore the factors mediating college students' radicalization. A sample of 1,116 students was drawn from four different Jordanian universities. The construct validity of the scale was estimated by calculating the correlation between the radicalization items and the negative emotion items. A positive significant relationship was found (0.12, a = 0.000), a sign of validity of the scale. The scale reliability was also strong and was estimated at 0.90 using Cronbach Alpha. Factor analysis produced five factors explaining 45% of the total variance of radicalization. The first factor labeled "political radicalization" explained 18.5% of the variance, the second factor "religious radicalization" explained 12.7%, the third factor "violent radicalization" explained 6.4% of the variance, the fourth "group radicalization" accounted for 4%, and the fifth factor "social radicalization" only accounted for 3% of the total variance. Significant differences in student radicalization were found according to the geographical region of the university (North, Center and South), F = 14, a = 0.000. However, no significant differences were found in radicalization as it relates to gender, and type of college (i.e., Humanities vs. Pure Sciences).