浙江大学医学院附属妇产科医院超声科鲁红主任、周一敏医生于2011年通过英国胎儿医学基金会(Fetal Medicine Foundation;FMF)孕早期暨NT超声筛查资格理论课程培训及图像分析记录考核,获得美国FMF早孕超声筛查认证资格。浙江省产前...浙江大学医学院附属妇产科医院超声科鲁红主任、周一敏医生于2011年通过英国胎儿医学基金会(Fetal Medicine Foundation;FMF)孕早期暨NT超声筛查资格理论课程培训及图像分析记录考核,获得美国FMF早孕超声筛查认证资格。浙江省产前诊断中心超声组也因此成为获得该基金会认证的11—13+6孕周超声检查证书的中心,展开更多
<div style="text-align:justify;"> An in-fiber axial micro-strain sensor based on a Few Mode Fiber Bragg Grating (FM-FBG) is proposed and experimentally characterized. This FM-FBG is in inscribed in a m...<div style="text-align:justify;"> An in-fiber axial micro-strain sensor based on a Few Mode Fiber Bragg Grating (FM-FBG) is proposed and experimentally characterized. This FM-FBG is in inscribed in a multi-layer few-mode fiber (ML-FMF), and could acquire the change of the axial strain along fibers, which depends on the transmission dips. On account of the distinct dual-mode property, a good stability of this sensor is realized. The two transmission dips could have the different sensing behaviors. Both the propagation characteristics and operation principle of such a sensor are demonstrated in detail. High sensitivity of the FM-FBG, ~4 pm/με and ~4.5 pm/με within the range of 0 με - 1456 με, is experimentally achieved. FM-FBGs could be easily scattered along one fiber. So this sensor may have a great potential of being used in sensor networks. </div>展开更多
The medium for next-generation communication is considered as fiber for fast,secure communication and switching capability.Mode division and space division multiplexing provide an excellent switching capability with h...The medium for next-generation communication is considered as fiber for fast,secure communication and switching capability.Mode division and space division multiplexing provide an excellent switching capability with high data transmission rate.In this work,the authors have approached an inverse modeling technique using regression-based machine learning to design a weakly coupled few-mode fiber for facilitating mode division multiplexing.The technique is adapted to predict the accurate profile parameters for the proposed few-mode fiber to obtain the maximum number of modes.It is for a three-ring-core few-mode fiber for guiding five,ten,fifteen,and twenty modes.Three types of regression models namely ordinary least-square linear multi-output regression,k-nearest neighbors of multi-output regression,and ID3 algorithm-based decision trees for multi-output regression are used for predicting the multiple profile parameters.It is observed that the ID3-based decision tree for multioutput regression is the robust,highly-accurate machine learning model for fast modeling of FMFs.The proposed fiber claims to be an efficient candidate for the next-generation 5G and 6G backhaul networks using mode division multiplexing.展开更多
文摘浙江大学医学院附属妇产科医院超声科鲁红主任、周一敏医生于2011年通过英国胎儿医学基金会(Fetal Medicine Foundation;FMF)孕早期暨NT超声筛查资格理论课程培训及图像分析记录考核,获得美国FMF早孕超声筛查认证资格。浙江省产前诊断中心超声组也因此成为获得该基金会认证的11—13+6孕周超声检查证书的中心,
文摘<div style="text-align:justify;"> An in-fiber axial micro-strain sensor based on a Few Mode Fiber Bragg Grating (FM-FBG) is proposed and experimentally characterized. This FM-FBG is in inscribed in a multi-layer few-mode fiber (ML-FMF), and could acquire the change of the axial strain along fibers, which depends on the transmission dips. On account of the distinct dual-mode property, a good stability of this sensor is realized. The two transmission dips could have the different sensing behaviors. Both the propagation characteristics and operation principle of such a sensor are demonstrated in detail. High sensitivity of the FM-FBG, ~4 pm/με and ~4.5 pm/με within the range of 0 με - 1456 με, is experimentally achieved. FM-FBGs could be easily scattered along one fiber. So this sensor may have a great potential of being used in sensor networks. </div>
文摘The medium for next-generation communication is considered as fiber for fast,secure communication and switching capability.Mode division and space division multiplexing provide an excellent switching capability with high data transmission rate.In this work,the authors have approached an inverse modeling technique using regression-based machine learning to design a weakly coupled few-mode fiber for facilitating mode division multiplexing.The technique is adapted to predict the accurate profile parameters for the proposed few-mode fiber to obtain the maximum number of modes.It is for a three-ring-core few-mode fiber for guiding five,ten,fifteen,and twenty modes.Three types of regression models namely ordinary least-square linear multi-output regression,k-nearest neighbors of multi-output regression,and ID3 algorithm-based decision trees for multi-output regression are used for predicting the multiple profile parameters.It is observed that the ID3-based decision tree for multioutput regression is the robust,highly-accurate machine learning model for fast modeling of FMFs.The proposed fiber claims to be an efficient candidate for the next-generation 5G and 6G backhaul networks using mode division multiplexing.