Quantum key distribution(QKD)is recognized as an unconditionally secure method of communication encryption,relying solely on the principles of quantum mechanics.A key performance metric for QKD systems is secure key r...Quantum key distribution(QKD)is recognized as an unconditionally secure method of communication encryption,relying solely on the principles of quantum mechanics.A key performance metric for QKD systems is secure key rate(SKR),which is a critical factor for real-world applications.Herein,we report a practical QKD system,equipped with compact gated InGaAs/InP single-photon detectors(SPDs),that can generate a high SKR of 15.2 Mb/s with a channel loss of 2 dB.This exceptional performance stems from the ultra-low afterpulsing probability of the SPDs,which significantly reduces the bit error rate in the QKD system.The typical quantum bit error rate is 1.3%.The results validate the feasibility of an integrated,practical QKD system and offer a reliable solution for the future development of real-world QKD networks.展开更多
"教师与学生提升制度"(The System for Teacher and Student Advancement,TAPTM)是美国全国优秀教学协会的一项核心改革方案。分析该制度的影响、成功的四大核心要素以及具体的实施程序,将为我国构建科学的教师评价体系提供..."教师与学生提升制度"(The System for Teacher and Student Advancement,TAPTM)是美国全国优秀教学协会的一项核心改革方案。分析该制度的影响、成功的四大核心要素以及具体的实施程序,将为我国构建科学的教师评价体系提供借鉴意见。展开更多
TAP?,the System for Teacher and Student Advancement,is a reform model introduced by the Milken Family Foundation in America in 1999,from which has been proved that teachers and students are benefit a lot.By analyzing ...TAP?,the System for Teacher and Student Advancement,is a reform model introduced by the Milken Family Foundation in America in 1999,from which has been proved that teachers and students are benefit a lot.By analyzing the implementation of the four elements of TAP?,this paper aims to find out the effectiveness of this system,and come up some feasible suggestions for the improvement of the teaching profession.展开更多
Classic non-local means (CNLM) algorithm uses the inherent self-similarity in images for noise removal. The denoised pixel value is estimated through the weighted average of all the pixels in its non-local neighborhoo...Classic non-local means (CNLM) algorithm uses the inherent self-similarity in images for noise removal. The denoised pixel value is estimated through the weighted average of all the pixels in its non-local neighborhood. In the CNLM algorithm, the differences between the pixel value and the distance of the pixel to the center are both taken into consideration to calculate the weighting coefficients. However, the Gaussian kernel cannot reflect the information of edge and structure due to its isotropy, and it has poor performance in flat regions. In this paper, an improved non-local means algorithm based on local edge direction is presented for image denoising. In edge and structure regions, the steering kernel regression (SKR) coefficients are used to calculate the weights, and in flat regions the average kernel is used. Experiments show that the proposed algorithm can effectively protect edge and structure while removing noises better when compared with the CNLM algorithm.展开更多
基金supported by the Innovation Program for Quantum Science and Technology(Grant No.2024ZD0302500)the National Natural Science Foundation of China(Grant No.62250710162)the Beijing Natural Science Foundation(Grant No.Z230005)。
文摘Quantum key distribution(QKD)is recognized as an unconditionally secure method of communication encryption,relying solely on the principles of quantum mechanics.A key performance metric for QKD systems is secure key rate(SKR),which is a critical factor for real-world applications.Herein,we report a practical QKD system,equipped with compact gated InGaAs/InP single-photon detectors(SPDs),that can generate a high SKR of 15.2 Mb/s with a channel loss of 2 dB.This exceptional performance stems from the ultra-low afterpulsing probability of the SPDs,which significantly reduces the bit error rate in the QKD system.The typical quantum bit error rate is 1.3%.The results validate the feasibility of an integrated,practical QKD system and offer a reliable solution for the future development of real-world QKD networks.
文摘TAP?,the System for Teacher and Student Advancement,is a reform model introduced by the Milken Family Foundation in America in 1999,from which has been proved that teachers and students are benefit a lot.By analyzing the implementation of the four elements of TAP?,this paper aims to find out the effectiveness of this system,and come up some feasible suggestions for the improvement of the teaching profession.
基金National Key Research and Development Program of China(No.2016YFC0101601)Fund for Shanxi“1331 Project”Key Innovative Research Team+1 种基金Shanxi Province Science Foundation for Youths(No.201601D021080)Universities Science and Technology Innovation Project of Shanxi Province(No.2017107)
文摘Classic non-local means (CNLM) algorithm uses the inherent self-similarity in images for noise removal. The denoised pixel value is estimated through the weighted average of all the pixels in its non-local neighborhood. In the CNLM algorithm, the differences between the pixel value and the distance of the pixel to the center are both taken into consideration to calculate the weighting coefficients. However, the Gaussian kernel cannot reflect the information of edge and structure due to its isotropy, and it has poor performance in flat regions. In this paper, an improved non-local means algorithm based on local edge direction is presented for image denoising. In edge and structure regions, the steering kernel regression (SKR) coefficients are used to calculate the weights, and in flat regions the average kernel is used. Experiments show that the proposed algorithm can effectively protect edge and structure while removing noises better when compared with the CNLM algorithm.
