Phase-matching quantum key distribution is a promising scheme for remote quantum key distribution,breaking through the traditional linear key-rate bound.In practical applications,finite data size can cause significant...Phase-matching quantum key distribution is a promising scheme for remote quantum key distribution,breaking through the traditional linear key-rate bound.In practical applications,finite data size can cause significant system performance to deteriorate when data size is below 1010.In this work,an improved statistical fluctuation analysis method is applied for the first time to two decoy-states phase-matching quantum key distribution,offering a new insight and potential solutions for improving the key generation rate and the maximum transmission distance while maintaining security.Moreover,we also compare the influence of the proposed improved statistical fluctuation analysis method on system performance with those of the Gaussian approximation and Chernoff-Hoeffding boundary methods on system performance.The simulation results show that the proposed scheme significantly improves the key generation rate and maximum transmission distance in comparison with the Chernoff-Hoeffding approach,and approach the results obtained when the Gaussian approximation is employed.At the same time,the proposed scheme retains the same security level as the Chernoff-Hoeffding method,and is even more secure than the Gaussian approximation.展开更多
目的探讨新生儿溶血病(HDN)的类型、抗体分布与输(换)血治疗的血液配型方案及疗效的关系。方法收集本院新生儿科2016年1月—2019年12月共350例住院HDN临床资料,包括年龄、性别、体重、胎次,回顾性统计患儿的溶血类型、血型抗体分布与治...目的探讨新生儿溶血病(HDN)的类型、抗体分布与输(换)血治疗的血液配型方案及疗效的关系。方法收集本院新生儿科2016年1月—2019年12月共350例住院HDN临床资料,包括年龄、性别、体重、胎次,回顾性统计患儿的溶血类型、血型抗体分布与治疗转归,分析其中输(换)血病例的血液配型方案,并以输血前后患儿血红蛋白(Hb)的变化评估其输血效果,以换血前后患儿的胆红素(Bil)和血红蛋白(Hb)的变化评估其换血效果。结果本组新生儿溶血病例中,ABO-HDN占94%(329/350),换血率为0.91%(3/329);Rh-HDN占5.43%(19/350),换血率为42.1%(8/19);ABO+MNSs-HDN占0.29%(1/350);Rh+Kidd-HDN占0.29%(1/350)。按照推荐方案输(换)血,11名输血患儿的输血次数1—2(1.82±0.40)次、(47.55±6.86)mL/次、输血量40—10(86.4±21.09)mL,输血前后Hb(g/L)分别为85.00±21.66 vs 125.09±12.96(P<0.05);12名换血患儿的换血次数1—2(1.17±0.39)次、(516.59±123.64)mL/次、换血量300—1403(602.69±279.05)mL;换血前后TBil(μmol/L)分别为327.22±97.40 vs 206.26±62.92(P<0.05),IBil(μmol/L)分别为295.66±110.98 vs 187.99±62.61(P<0.05),DBil(μmol/L)分别为37.23±31.83 vs 18.24±12.46(P>0.05);Hb(g/L)分别为105.64±44.94 vs 143.00±22.09(P<0.05)。结论HDN虽然以ABO血型系统最多见,但输(换)血疗法主要应用于Rh HDN,换血后Bil降低、Hb提升效果更明显。展开更多
针对传统模式匹配检测技术存在的计算量大、检测率低误、报警率高等问题,提出了一种基于协议分析的智能匹配检测方法。该检测方法充分利用TCP/IP(Transmission Control Protocol/Internet Protocol)技术的高度规则性检测攻击的存在,明...针对传统模式匹配检测技术存在的计算量大、检测率低误、报警率高等问题,提出了一种基于协议分析的智能匹配检测方法。该检测方法充分利用TCP/IP(Transmission Control Protocol/Internet Protocol)技术的高度规则性检测攻击的存在,明显减少了匹配检测的计算量。设计并实现了基于动态分析的自动排序规则库。实验结果表明,该智能匹配方案能使模式匹配的时间缩短20%,从而提高了入侵检测的效率。展开更多
文摘Phase-matching quantum key distribution is a promising scheme for remote quantum key distribution,breaking through the traditional linear key-rate bound.In practical applications,finite data size can cause significant system performance to deteriorate when data size is below 1010.In this work,an improved statistical fluctuation analysis method is applied for the first time to two decoy-states phase-matching quantum key distribution,offering a new insight and potential solutions for improving the key generation rate and the maximum transmission distance while maintaining security.Moreover,we also compare the influence of the proposed improved statistical fluctuation analysis method on system performance with those of the Gaussian approximation and Chernoff-Hoeffding boundary methods on system performance.The simulation results show that the proposed scheme significantly improves the key generation rate and maximum transmission distance in comparison with the Chernoff-Hoeffding approach,and approach the results obtained when the Gaussian approximation is employed.At the same time,the proposed scheme retains the same security level as the Chernoff-Hoeffding method,and is even more secure than the Gaussian approximation.
文摘目的探讨新生儿溶血病(HDN)的类型、抗体分布与输(换)血治疗的血液配型方案及疗效的关系。方法收集本院新生儿科2016年1月—2019年12月共350例住院HDN临床资料,包括年龄、性别、体重、胎次,回顾性统计患儿的溶血类型、血型抗体分布与治疗转归,分析其中输(换)血病例的血液配型方案,并以输血前后患儿血红蛋白(Hb)的变化评估其输血效果,以换血前后患儿的胆红素(Bil)和血红蛋白(Hb)的变化评估其换血效果。结果本组新生儿溶血病例中,ABO-HDN占94%(329/350),换血率为0.91%(3/329);Rh-HDN占5.43%(19/350),换血率为42.1%(8/19);ABO+MNSs-HDN占0.29%(1/350);Rh+Kidd-HDN占0.29%(1/350)。按照推荐方案输(换)血,11名输血患儿的输血次数1—2(1.82±0.40)次、(47.55±6.86)mL/次、输血量40—10(86.4±21.09)mL,输血前后Hb(g/L)分别为85.00±21.66 vs 125.09±12.96(P<0.05);12名换血患儿的换血次数1—2(1.17±0.39)次、(516.59±123.64)mL/次、换血量300—1403(602.69±279.05)mL;换血前后TBil(μmol/L)分别为327.22±97.40 vs 206.26±62.92(P<0.05),IBil(μmol/L)分别为295.66±110.98 vs 187.99±62.61(P<0.05),DBil(μmol/L)分别为37.23±31.83 vs 18.24±12.46(P>0.05);Hb(g/L)分别为105.64±44.94 vs 143.00±22.09(P<0.05)。结论HDN虽然以ABO血型系统最多见,但输(换)血疗法主要应用于Rh HDN,换血后Bil降低、Hb提升效果更明显。
文摘针对传统模式匹配检测技术存在的计算量大、检测率低误、报警率高等问题,提出了一种基于协议分析的智能匹配检测方法。该检测方法充分利用TCP/IP(Transmission Control Protocol/Internet Protocol)技术的高度规则性检测攻击的存在,明显减少了匹配检测的计算量。设计并实现了基于动态分析的自动排序规则库。实验结果表明,该智能匹配方案能使模式匹配的时间缩短20%,从而提高了入侵检测的效率。
