Objective:To investigate the efficacy of in-phase and quadrature(IQ)demodulation in electronic fetal heart rate monitoring(EFM)to reduce false reports of fetal heart rate(FHR)doubling or halving.Methods:This is a pros...Objective:To investigate the efficacy of in-phase and quadrature(IQ)demodulation in electronic fetal heart rate monitoring(EFM)to reduce false reports of fetal heart rate(FHR)doubling or halving.Methods:This is a prospective cohort study.A total of 263 full-term pregnant women who delivered at Peking University Shenzhen Hospital between August 2019 and July 2020 were prospectively enrolled in the study.FHR monitoring began when the cervix was dilated to 2-3 cm and continued until delivery.Raw fetal Doppler audio signals and internal and external cardiotocography curves from internal electrode monitoring,EFM with conventional demodulation(external),and EFM with IQ demodulation(external)were acquired to compare FHR doubling and halving time.In cohort 1,FHR was compared between IQ demodulation and conventional demodulation.In cohort 2,FHR was compared between IQ demodulation,conventional demodulation,and internal FHR monitoring.Count data were statistically analyzed using the Chi-squared test,and measurement data were statistically analyzed usingt-test for correlation coefficients,and Bland-Altman analysis for concordance ranges.Results:To compare IQ demodulation and conventional demodulation,225 pregnant women were monitored for a total of 835,870 seconds.The beat-to-beat interval of FHRs in raw fetal Doppler audio signals was used as the reference.The results showed a doubling time of 3401 seconds(0.407%,3401/835,870)and a halving time of 2918 seconds(0.349%,2918/835,870)with conventional demodulation,compared to 241 seconds(0.029%,241/835,870)and 589 seconds(0.070%,589/835,870),respectively,with IQ demodulation.IQ demodulation reduced FHR doubling by approximately 93%(3160/3401)and FHR halving by approximately 80%(2329/2918)compared to conventional demodulation(P<0.01).Conclusion:EFM with IQ demodulation significantly reduces false FHR doubling and halving,with an efficacy similar to that of internal FHR monitoring.展开更多
In this paper I examine the sensitivity of total UK Covid-19 deaths and the demand for intensive care and ward beds,to the timing and duration of suppression periods during a 500-day period.This is achieved via a SEIR...In this paper I examine the sensitivity of total UK Covid-19 deaths and the demand for intensive care and ward beds,to the timing and duration of suppression periods during a 500-day period.This is achieved via a SEIR model.Using an expected latent period of 4.5 days and infectious period of 3.8 days,R0 was first estimated as 3.18 using observed death rates under unmitigated spread and then under the effects of the total lockdown(R0-0.60)beginning 23 March.The case fatality rate given infection is taken as 1%.Parameter values for mean length of stay and conditional probability of death for ICU and non-ICU hospital admissions are guided by Ferguson et al.(2020).Under unmitigated spread the model predicts around 600,000 deaths in the UK.Starting with one exposed person at time zero and a suppression consistent with an R0 of 0.60 on day 72,the model predicts around 39,000 deaths for a first wave,but this reduces to around 11,000 if the intervention takes place one week earlier.If the initial suppression were in place until day 200 and then relaxed to an R0 of 1.5 between days 200 and 300,to be followed by a return to an R0 of 0.60,the model predicts around 43,000 deaths.This would increase to around 64,000 if the release from the first suppression takes place 20 days earlier.The results indicate the extreme sensitivity to timing and the consequences of even small delays to suppression and premature relaxation of such measures.展开更多
通过选取并提交专家标注最有信息量的样例,主动学习算法中可以有效地减轻标注大量未标注样例的负担.采样是主动学习算法中一个影响性能的关键因素.当前主流的采样算法往往考虑选取的样例尽可能平分版本空间.但这一方法假定版本空间中的...通过选取并提交专家标注最有信息量的样例,主动学习算法中可以有效地减轻标注大量未标注样例的负担.采样是主动学习算法中一个影响性能的关键因素.当前主流的采样算法往往考虑选取的样例尽可能平分版本空间.但这一方法假定版本空间中的每一假设都具有相同的概率成为目标函数,而这在真实世界问题中不可能满足.分析了平分版本策略的局限性.进而提出一种旨在尽可能最大限度减小版本空间的启发式采样算法MPWPS(the most possibly wrong-predicted sampling),该算法每次采样时选取当前分类器最有可能预测错误的样例,从而淘汰版本空间中多于半数的假设.这种方法使分类器在达到相同的分类正确率时,采样次数比当前主流的针对平分版本空间的主动学习算法采样次数更少.实验表明,在大多数数据集上,当达到相同的目标正确率时,MPWPS方法能够比传统的采样算法采样次数更少.展开更多
为了提高椭圆曲线标量乘法的效率,根据将求逆转换为乘法运算的思想,提出了在二进制域F2n上用仿射坐标直接计算7P的两种算法。两种算法分别通过引入公因子和除法多项式来计算7P,其运算量分别为2I+7S+14M和I+6S+20M,比Purohit等提出的算法...为了提高椭圆曲线标量乘法的效率,根据将求逆转换为乘法运算的思想,提出了在二进制域F2n上用仿射坐标直接计算7P的两种算法。两种算法分别通过引入公因子和除法多项式来计算7P,其运算量分别为2I+7S+14M和I+6S+20M,比Purohit等提出的算法(PUROHIT G N,RAWAT S A,KUMAR M.Elliptic curve point multiplication using MBNR and Point halving.International Journal of Advanced Networking and Applications,2012,3(5):1329-1337)分别节省了一次和两次求逆运算。同时还给出直接计算7kP的快速算法,该算法比重复计算k次7P更有效。最后结合半点运算和扩展多基表示形式将这些新算法应用到标量乘法中。实验结果表明,在美国国家标准技术研究所(NIST)推荐的椭圆曲线上,当预存储点的个数为2和5时,新算法比Purohit算法效率提高了30%和37%,比洪银芳等所提的算法(洪银芳,桂丰,丁勇.基于半点和多基表示的标量乘法扩展算法.计算机工程,2011,37(4):163-165)效率提高了9%和13%。新算法以增加少量的预计算存储为代价,能有效降低标量乘法的运算量。展开更多
基金Shenzhen Science and Technology Innovation Commission(JCYJ20180228162311024)。
文摘Objective:To investigate the efficacy of in-phase and quadrature(IQ)demodulation in electronic fetal heart rate monitoring(EFM)to reduce false reports of fetal heart rate(FHR)doubling or halving.Methods:This is a prospective cohort study.A total of 263 full-term pregnant women who delivered at Peking University Shenzhen Hospital between August 2019 and July 2020 were prospectively enrolled in the study.FHR monitoring began when the cervix was dilated to 2-3 cm and continued until delivery.Raw fetal Doppler audio signals and internal and external cardiotocography curves from internal electrode monitoring,EFM with conventional demodulation(external),and EFM with IQ demodulation(external)were acquired to compare FHR doubling and halving time.In cohort 1,FHR was compared between IQ demodulation and conventional demodulation.In cohort 2,FHR was compared between IQ demodulation,conventional demodulation,and internal FHR monitoring.Count data were statistically analyzed using the Chi-squared test,and measurement data were statistically analyzed usingt-test for correlation coefficients,and Bland-Altman analysis for concordance ranges.Results:To compare IQ demodulation and conventional demodulation,225 pregnant women were monitored for a total of 835,870 seconds.The beat-to-beat interval of FHRs in raw fetal Doppler audio signals was used as the reference.The results showed a doubling time of 3401 seconds(0.407%,3401/835,870)and a halving time of 2918 seconds(0.349%,2918/835,870)with conventional demodulation,compared to 241 seconds(0.029%,241/835,870)and 589 seconds(0.070%,589/835,870),respectively,with IQ demodulation.IQ demodulation reduced FHR doubling by approximately 93%(3160/3401)and FHR halving by approximately 80%(2329/2918)compared to conventional demodulation(P<0.01).Conclusion:EFM with IQ demodulation significantly reduces false FHR doubling and halving,with an efficacy similar to that of internal FHR monitoring.
文摘In this paper I examine the sensitivity of total UK Covid-19 deaths and the demand for intensive care and ward beds,to the timing and duration of suppression periods during a 500-day period.This is achieved via a SEIR model.Using an expected latent period of 4.5 days and infectious period of 3.8 days,R0 was first estimated as 3.18 using observed death rates under unmitigated spread and then under the effects of the total lockdown(R0-0.60)beginning 23 March.The case fatality rate given infection is taken as 1%.Parameter values for mean length of stay and conditional probability of death for ICU and non-ICU hospital admissions are guided by Ferguson et al.(2020).Under unmitigated spread the model predicts around 600,000 deaths in the UK.Starting with one exposed person at time zero and a suppression consistent with an R0 of 0.60 on day 72,the model predicts around 39,000 deaths for a first wave,but this reduces to around 11,000 if the intervention takes place one week earlier.If the initial suppression were in place until day 200 and then relaxed to an R0 of 1.5 between days 200 and 300,to be followed by a return to an R0 of 0.60,the model predicts around 43,000 deaths.This would increase to around 64,000 if the release from the first suppression takes place 20 days earlier.The results indicate the extreme sensitivity to timing and the consequences of even small delays to suppression and premature relaxation of such measures.
文摘通过选取并提交专家标注最有信息量的样例,主动学习算法中可以有效地减轻标注大量未标注样例的负担.采样是主动学习算法中一个影响性能的关键因素.当前主流的采样算法往往考虑选取的样例尽可能平分版本空间.但这一方法假定版本空间中的每一假设都具有相同的概率成为目标函数,而这在真实世界问题中不可能满足.分析了平分版本策略的局限性.进而提出一种旨在尽可能最大限度减小版本空间的启发式采样算法MPWPS(the most possibly wrong-predicted sampling),该算法每次采样时选取当前分类器最有可能预测错误的样例,从而淘汰版本空间中多于半数的假设.这种方法使分类器在达到相同的分类正确率时,采样次数比当前主流的针对平分版本空间的主动学习算法采样次数更少.实验表明,在大多数数据集上,当达到相同的目标正确率时,MPWPS方法能够比传统的采样算法采样次数更少.
文摘为了提高椭圆曲线标量乘法的效率,根据将求逆转换为乘法运算的思想,提出了在二进制域F2n上用仿射坐标直接计算7P的两种算法。两种算法分别通过引入公因子和除法多项式来计算7P,其运算量分别为2I+7S+14M和I+6S+20M,比Purohit等提出的算法(PUROHIT G N,RAWAT S A,KUMAR M.Elliptic curve point multiplication using MBNR and Point halving.International Journal of Advanced Networking and Applications,2012,3(5):1329-1337)分别节省了一次和两次求逆运算。同时还给出直接计算7kP的快速算法,该算法比重复计算k次7P更有效。最后结合半点运算和扩展多基表示形式将这些新算法应用到标量乘法中。实验结果表明,在美国国家标准技术研究所(NIST)推荐的椭圆曲线上,当预存储点的个数为2和5时,新算法比Purohit算法效率提高了30%和37%,比洪银芳等所提的算法(洪银芳,桂丰,丁勇.基于半点和多基表示的标量乘法扩展算法.计算机工程,2011,37(4):163-165)效率提高了9%和13%。新算法以增加少量的预计算存储为代价,能有效降低标量乘法的运算量。
