Underwater quantum communication plays a crucial role in ensuring secure data transmission and extensible quantum networks in underwater environments.However,the implementation of such applications encounters challeng...Underwater quantum communication plays a crucial role in ensuring secure data transmission and extensible quantum networks in underwater environments.However,the implementation of such applications encounters challenges due to the light attenuation caused by the complicated natural seawater.This paper focuses on employing a model based on seawater chlorophyll-a concentration to characterize the absorption and scattering of light through quantum channels.We propose a multi-scattering random channel model,which demonstrates characteristics of the excess noise in different propagation directions of communication links.Furthermore,we consider the fidelity of a continuous-variable quantum teleportation through seawater channel.To enhance transmission performance,non-Gaussian operations have been conducted.Numerical simulations show that incorporating non-Gaussian operations enables the protocol to achieve higher fidelity transmission or lower fidelity fading rates over longer transmission distances.展开更多
为提高监管部门对污染源排放单位监测数据的真实性、有效性以及客观性,提出一种融合Benford律和限制值模型的企业污染排放监测数据造假行为的风险评估方法。首先结合Benford律建立多层级数据是否造假的检测结构并以此生成非造假正样本...为提高监管部门对污染源排放单位监测数据的真实性、有效性以及客观性,提出一种融合Benford律和限制值模型的企业污染排放监测数据造假行为的风险评估方法。首先结合Benford律建立多层级数据是否造假的检测结构并以此生成非造假正样本数据集;其次,针对环境监测数据人为造假行为提出限制值造假模型(Limit Value Fake Model,LVFM),实现造假负样本数据集的生成;最后将扩充后的数据集输入多分类学习器进行预测识别。仿真结果表明,LVFM模型具有较好的造假隐蔽性;同时合成造假数据与真实造假数据基本相似度达到81%,即具有一定数据造假能力;综合多分类器预测对正负样本识别结果分析,随机森林(Random Forests,RF)获得了81.35%的准确率和71.33%的F1值,研究结果可为辅助生态安全监督以及决策的智慧管理提供参考。展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.61871407)the Natural Science Foundation of Hunan Province,China(Grant No.2021JJ30878)the Key Research and Development Program of Hunan Province,China(Grant Nos.2020GK4063 and 2022GK2016)。
文摘Underwater quantum communication plays a crucial role in ensuring secure data transmission and extensible quantum networks in underwater environments.However,the implementation of such applications encounters challenges due to the light attenuation caused by the complicated natural seawater.This paper focuses on employing a model based on seawater chlorophyll-a concentration to characterize the absorption and scattering of light through quantum channels.We propose a multi-scattering random channel model,which demonstrates characteristics of the excess noise in different propagation directions of communication links.Furthermore,we consider the fidelity of a continuous-variable quantum teleportation through seawater channel.To enhance transmission performance,non-Gaussian operations have been conducted.Numerical simulations show that incorporating non-Gaussian operations enables the protocol to achieve higher fidelity transmission or lower fidelity fading rates over longer transmission distances.
文摘为提高监管部门对污染源排放单位监测数据的真实性、有效性以及客观性,提出一种融合Benford律和限制值模型的企业污染排放监测数据造假行为的风险评估方法。首先结合Benford律建立多层级数据是否造假的检测结构并以此生成非造假正样本数据集;其次,针对环境监测数据人为造假行为提出限制值造假模型(Limit Value Fake Model,LVFM),实现造假负样本数据集的生成;最后将扩充后的数据集输入多分类学习器进行预测识别。仿真结果表明,LVFM模型具有较好的造假隐蔽性;同时合成造假数据与真实造假数据基本相似度达到81%,即具有一定数据造假能力;综合多分类器预测对正负样本识别结果分析,随机森林(Random Forests,RF)获得了81.35%的准确率和71.33%的F1值,研究结果可为辅助生态安全监督以及决策的智慧管理提供参考。
