Conventional nonlinear Raman–Nath diffraction(NRND)spots exhibit a straight-line distribution when the pump laser enters the nonlinear dielectric grating at normal incidence or at oblique incidence.Here,we report on ...Conventional nonlinear Raman–Nath diffraction(NRND)spots exhibit a straight-line distribution when the pump laser enters the nonlinear dielectric grating at normal incidence or at oblique incidence.Here,we report on the first observation of the conical NRND phenomenon from a submicron-thick periodically poled lithium niobate thin film(PPLNTF)sample under a near-infrared femtosecond pulse laser excitation at various cone angles.All the multi-order second harmonic generation(SHG)diffraction signals present a novel evolution arc-shaped arrangement feature.展开更多
In educational practice,teachers often need to manually assemble an exercise collection as a class quiz or a homework assignment.A well-assembled exercise collection needs to have the proper difficulty index and discr...In educational practice,teachers often need to manually assemble an exercise collection as a class quiz or a homework assignment.A well-assembled exercise collection needs to have the proper difficulty index and discrimination index so that it can better develop students'abilities.In this paper,we propose an exercise collection auto-assembling framework,in which a teacher provides the target values of difficulty and discrimination indices and a qualified exercise collection is automatically assembled.The framework consists of two stages.At the answer prediction stage,a knowledge tracing model is utilized to predict the students'answers to unseen exercises based on their history interaction records.In addition,to better represent the exercises in the model,we propose exercise embeddings and design a pre-training approach.At the collection assembling stage,we propose a deep reinforcement learning model to assemble the required exercise collection effectively.Since the knowledge tracing model in the first stage has different confidences in the predicted answers,it is also taken into account in the objective.Experimental results show the effectiveness and efficiency of the proposed framework.展开更多
基金Science and Technology Project of Guangdong(2020B010190001)National Natural Science Foundation of China(12434016,11974119)+1 种基金Guangzhou Science and Technology Plan Project(2023A04J1309)National Funded Postdoctoral Researcher Program(GZB20240785)。
文摘Conventional nonlinear Raman–Nath diffraction(NRND)spots exhibit a straight-line distribution when the pump laser enters the nonlinear dielectric grating at normal incidence or at oblique incidence.Here,we report on the first observation of the conical NRND phenomenon from a submicron-thick periodically poled lithium niobate thin film(PPLNTF)sample under a near-infrared femtosecond pulse laser excitation at various cone angles.All the multi-order second harmonic generation(SHG)diffraction signals present a novel evolution arc-shaped arrangement feature.
基金This work was supported by the National Natural Science Foundation of China under Grant Nos.62072261 and 61925205,and Huawei and TAL education.
文摘In educational practice,teachers often need to manually assemble an exercise collection as a class quiz or a homework assignment.A well-assembled exercise collection needs to have the proper difficulty index and discrimination index so that it can better develop students'abilities.In this paper,we propose an exercise collection auto-assembling framework,in which a teacher provides the target values of difficulty and discrimination indices and a qualified exercise collection is automatically assembled.The framework consists of two stages.At the answer prediction stage,a knowledge tracing model is utilized to predict the students'answers to unseen exercises based on their history interaction records.In addition,to better represent the exercises in the model,we propose exercise embeddings and design a pre-training approach.At the collection assembling stage,we propose a deep reinforcement learning model to assemble the required exercise collection effectively.Since the knowledge tracing model in the first stage has different confidences in the predicted answers,it is also taken into account in the objective.Experimental results show the effectiveness and efficiency of the proposed framework.
