The characteristics of coplanar waveguide (CPW) fed ring antennas (such as gain, efficiency and polarization purity) are degraded by the dielectric losses and excitation of surface waves on the substrates. To countera...The characteristics of coplanar waveguide (CPW) fed ring antennas (such as gain, efficiency and polarization purity) are degraded by the dielectric losses and excitation of surface waves on the substrates. To counteract such effects, we propose to remove some portions of the substrate in the vicinity of the metallic patches, which effectively eliminates the conditions for the generation of surface waves. The proposed technique is applied to a CPW-fed ring antenna and a prototype model is fabricated. The measurement data and the computer simulation results agree well and indicate the efficacy of the technique for the improvement of antenna gain and efficiency.展开更多
Shear stress distribution prediction in open channels is of utmost importance in hydraulic structural engineering as it directly affects the design of stable channels.In this study,at first,a series of experimental te...Shear stress distribution prediction in open channels is of utmost importance in hydraulic structural engineering as it directly affects the design of stable channels.In this study,at first,a series of experimental tests were conducted to assess the shear stress distribution in prismatic compound channels.The shear stress values around the whole wetted perimeter were measured in the compound channel with different floodplain widths also in different flow depths in subcritical and supercritical conditions.A set of,data mining and machine learning algorithms including Random Forest(RF),M5P,Random Committee,KStar and Additive Regression implemented on attained data to predict the shear stress distribution in the compound channel.Results indicated among these five models;RF method indicated the most precise results with the highest R2 value of 0.9.Finally,the most powerful data mining method which studied in this research compared with two well-known analytical models of Shiono and Knight method(SKM)and Shannon method to acquire the proposed model functioning in predicting the shear stress distribution.The results showed that the RF model has the best prediction performance compared to SKM and Shannon models.展开更多
文摘The characteristics of coplanar waveguide (CPW) fed ring antennas (such as gain, efficiency and polarization purity) are degraded by the dielectric losses and excitation of surface waves on the substrates. To counteract such effects, we propose to remove some portions of the substrate in the vicinity of the metallic patches, which effectively eliminates the conditions for the generation of surface waves. The proposed technique is applied to a CPW-fed ring antenna and a prototype model is fabricated. The measurement data and the computer simulation results agree well and indicate the efficacy of the technique for the improvement of antenna gain and efficiency.
文摘Shear stress distribution prediction in open channels is of utmost importance in hydraulic structural engineering as it directly affects the design of stable channels.In this study,at first,a series of experimental tests were conducted to assess the shear stress distribution in prismatic compound channels.The shear stress values around the whole wetted perimeter were measured in the compound channel with different floodplain widths also in different flow depths in subcritical and supercritical conditions.A set of,data mining and machine learning algorithms including Random Forest(RF),M5P,Random Committee,KStar and Additive Regression implemented on attained data to predict the shear stress distribution in the compound channel.Results indicated among these five models;RF method indicated the most precise results with the highest R2 value of 0.9.Finally,the most powerful data mining method which studied in this research compared with two well-known analytical models of Shiono and Knight method(SKM)and Shannon method to acquire the proposed model functioning in predicting the shear stress distribution.The results showed that the RF model has the best prediction performance compared to SKM and Shannon models.
