针对在现场可编程门阵列(Field Programmable Gate Array,FPGA)上实现基于极化敏感阵列的多重信号分类(Multiple Signal Classification,MUSIC)算法进行二维波达方向(Direction of Arrival,DOA)和二维极化参数联合估计时,硬件资源占用...针对在现场可编程门阵列(Field Programmable Gate Array,FPGA)上实现基于极化敏感阵列的多重信号分类(Multiple Signal Classification,MUSIC)算法进行二维波达方向(Direction of Arrival,DOA)和二维极化参数联合估计时,硬件资源占用大、运行时间长的问题,提出了一种基于极化MUSIC算法的四维参数联合估计FPGA实现架构。该架构包括信号协方差矩阵计算模块、Jacobi旋转模块、噪声子空间提取模块、两级空间谱搜索模块和极化参数计算模块。Jacobi旋转模块被拆分为多个可复用模块,并采用查找表模块生成旋转矩阵。一级空间谱搜索模块通过二维DOA搜索初步确定信源的角度信息。二级空间谱搜索模块根据一级搜索的角度结果确定二级搜索区域各点的极化信息,并计算该区域的四维空间谱,区域内最小值对应的四维参数信息即为最终估计的信源方向角、俯仰角、极化辅助角和极化相位角。仿真结果表明,与传统极化MUSIC算法的四维搜索算法相比,该架构避免了大量四维空间谱计算,同时保证了四维参数估计的精度,显著减少了运行时间和硬件资源消耗。展开更多
Despite the widespread presence and frequent detection of polycyclic aromatic hydrocarbons(PAHs)in various aspects of life,there is limited research on their exposure levels in pregnant women and cumulative exposure f...Despite the widespread presence and frequent detection of polycyclic aromatic hydrocarbons(PAHs)in various aspects of life,there is limited research on their exposure levels in pregnant women and cumulative exposure from the living environment.This study included 1311 women in late pregnancy from the Zunyi birth cohort and measured the urinary concentrations of 10 hydroxylated PAH metabolites(OH-PAHs).Risk assessment was conducted based on the estimated daily intake to calculate the hazard quotient and hazard index(HI).A linear regression model was used to analyze the relationship between creatinine-adjusted OH-PAHs concentrations and living environment and lifestyle factors,while principal component analysis was applied to trace the sources of PAHs exposure.1-OHPYR was detected in all participants’urine,with naphthalene metabolites having the highest concentrations among creatinine-adjusted PAHs.OH-PAHs concentrations were associated with housing type,room number,cooking frequency,household size,exercise frequency,fuel type,distance from main road,and drinking water source.Pregnant women using traditional fuels and living in bungalows had higher health risks than those using clean energy and living in buildings.Those living within 100 m of a main road had higher HI than those farther away.Coal combustion was identified as the primary source of PAHs exposure.The study emphasizes the importance of reducing PAHs exposure,especially for pregnant women living in polluted environments.It recommends public health interventions such as improving indoor ventilation and providing clean energy to reduce related health risks.展开更多
Accurate time delay estimation of target echo signals is a critical component of underwater target localization.In active sonar systems,echo signal processing is vulnerable to the effects of reverberation and noise in...Accurate time delay estimation of target echo signals is a critical component of underwater target localization.In active sonar systems,echo signal processing is vulnerable to the effects of reverberation and noise in the maritime environment.This paper proposes a novel method for estimating target time delay using multi-bright spot echoes,assuming the target’s size and depth are known.Aiming to effectively enhance the extraction of geometric features from the target echoes and mitigate the impact of reverberation and noise,the proposed approach employs the fractional order Fourier transform-frequency sliced wavelet transform to extract multi-bright spot echoes.Using the highlighting model theory and the target size information,an observation matrix is constructed to represent multi-angle incident signals and obtain the theoretical scattered echo signals from different angles.Aiming to accurately estimate the target’s time delay,waveform similarity coefficients and mean square error values between the theoretical return signals and received signals are computed across various incident angles and time delays.Simulation results show that,compared to the conventional matched filter,the proposed algorithm reduces the relative error by 65.9%-91.5%at a signal-to noise ratio of-25 dB,and by 66.7%-88.9%at a signal-to-reverberation ratio of−10 dB.This algorithm provides a new approach for the precise localization of submerged targets in shallow water environments.展开更多
AIM:To build a functional generalized estimating equation(GEE)model to detect glaucomatous visual field progression and compare the performance of the proposed method with that of commonly employed algorithms.METHODS:...AIM:To build a functional generalized estimating equation(GEE)model to detect glaucomatous visual field progression and compare the performance of the proposed method with that of commonly employed algorithms.METHODS:Totally 716 eyes of 716 patients with primary open angle glaucoma(POAG)with at least 5 reliable 24-2 test results and 2y of follow-up were selected.The functional GEE model was used to detect perimetric progression in the training dataset(501 eyes).In the testing dataset(215 eyes),progression was evaluated the functional GEE model,mean deviation(MD)and visual field index(VFI)rates of change,Advanced Glaucoma Intervention Study(AGIS)and Collaborative Initial Glaucoma Treatment Study(CIGTS)scores,and pointwise linear regression(PLR).RESULTS:The proposed method showed the highest proportion of eyes detected as progression(54.4%),followed by the VFI rate(34.4%),PLR(23.3%),and MD rate(21.4%).The CIGTS and AGIS scores had a lower proportion of eyes detected as progression(7.9%and 5.1%,respectively).The time to detection of progression was significantly shorter for the proposed method than that of other algorithms(adjusted P≤0.019).The VFI rate displayed moderate pairwise agreement with the proposed method(k=0.47).CONCLUSION:The functional GEE model shows the highest proportion of eyes detected as perimetric progression and the shortest time to detect perimetric progression in patients with POAG.展开更多
文摘针对在现场可编程门阵列(Field Programmable Gate Array,FPGA)上实现基于极化敏感阵列的多重信号分类(Multiple Signal Classification,MUSIC)算法进行二维波达方向(Direction of Arrival,DOA)和二维极化参数联合估计时,硬件资源占用大、运行时间长的问题,提出了一种基于极化MUSIC算法的四维参数联合估计FPGA实现架构。该架构包括信号协方差矩阵计算模块、Jacobi旋转模块、噪声子空间提取模块、两级空间谱搜索模块和极化参数计算模块。Jacobi旋转模块被拆分为多个可复用模块,并采用查找表模块生成旋转矩阵。一级空间谱搜索模块通过二维DOA搜索初步确定信源的角度信息。二级空间谱搜索模块根据一级搜索的角度结果确定二级搜索区域各点的极化信息,并计算该区域的四维空间谱,区域内最小值对应的四维参数信息即为最终估计的信源方向角、俯仰角、极化辅助角和极化相位角。仿真结果表明,与传统极化MUSIC算法的四维搜索算法相比,该架构避免了大量四维空间谱计算,同时保证了四维参数估计的精度,显著减少了运行时间和硬件资源消耗。
基金supported by the National Key R&D Program of China(Nos.2018YFC1004300 and 2018YFC1004302)the Science&Technology Program of Guizhou Province(Nos.QKHHBZ[2020]3002,QKHPTRC-GCC[2022]039-1 and QKHPTRCCXTD[2022]014)the Scientific Research Program of Guizhou Provincial Department of Education(No.QJJ[2023]019).
文摘Despite the widespread presence and frequent detection of polycyclic aromatic hydrocarbons(PAHs)in various aspects of life,there is limited research on their exposure levels in pregnant women and cumulative exposure from the living environment.This study included 1311 women in late pregnancy from the Zunyi birth cohort and measured the urinary concentrations of 10 hydroxylated PAH metabolites(OH-PAHs).Risk assessment was conducted based on the estimated daily intake to calculate the hazard quotient and hazard index(HI).A linear regression model was used to analyze the relationship between creatinine-adjusted OH-PAHs concentrations and living environment and lifestyle factors,while principal component analysis was applied to trace the sources of PAHs exposure.1-OHPYR was detected in all participants’urine,with naphthalene metabolites having the highest concentrations among creatinine-adjusted PAHs.OH-PAHs concentrations were associated with housing type,room number,cooking frequency,household size,exercise frequency,fuel type,distance from main road,and drinking water source.Pregnant women using traditional fuels and living in bungalows had higher health risks than those using clean energy and living in buildings.Those living within 100 m of a main road had higher HI than those farther away.Coal combustion was identified as the primary source of PAHs exposure.The study emphasizes the importance of reducing PAHs exposure,especially for pregnant women living in polluted environments.It recommends public health interventions such as improving indoor ventilation and providing clean energy to reduce related health risks.
基金Supported by the State Key Laboratory of Acoustics and Marine Information Chinese Academy of Sciences(SKL A202507).
文摘Accurate time delay estimation of target echo signals is a critical component of underwater target localization.In active sonar systems,echo signal processing is vulnerable to the effects of reverberation and noise in the maritime environment.This paper proposes a novel method for estimating target time delay using multi-bright spot echoes,assuming the target’s size and depth are known.Aiming to effectively enhance the extraction of geometric features from the target echoes and mitigate the impact of reverberation and noise,the proposed approach employs the fractional order Fourier transform-frequency sliced wavelet transform to extract multi-bright spot echoes.Using the highlighting model theory and the target size information,an observation matrix is constructed to represent multi-angle incident signals and obtain the theoretical scattered echo signals from different angles.Aiming to accurately estimate the target’s time delay,waveform similarity coefficients and mean square error values between the theoretical return signals and received signals are computed across various incident angles and time delays.Simulation results show that,compared to the conventional matched filter,the proposed algorithm reduces the relative error by 65.9%-91.5%at a signal-to noise ratio of-25 dB,and by 66.7%-88.9%at a signal-to-reverberation ratio of−10 dB.This algorithm provides a new approach for the precise localization of submerged targets in shallow water environments.
基金Supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute(KHIDI),funded by the Ministry of Health&Welfare,Republic of Korea(No.HR20C0026)the National Research Foundation of Korea(NRF)(No.RS-2023-00247504)the Patient-Centered Clinical Research Coordinating Center,funded by the Ministry of Health&Welfare,Republic of Korea(No.HC19C0276).
文摘AIM:To build a functional generalized estimating equation(GEE)model to detect glaucomatous visual field progression and compare the performance of the proposed method with that of commonly employed algorithms.METHODS:Totally 716 eyes of 716 patients with primary open angle glaucoma(POAG)with at least 5 reliable 24-2 test results and 2y of follow-up were selected.The functional GEE model was used to detect perimetric progression in the training dataset(501 eyes).In the testing dataset(215 eyes),progression was evaluated the functional GEE model,mean deviation(MD)and visual field index(VFI)rates of change,Advanced Glaucoma Intervention Study(AGIS)and Collaborative Initial Glaucoma Treatment Study(CIGTS)scores,and pointwise linear regression(PLR).RESULTS:The proposed method showed the highest proportion of eyes detected as progression(54.4%),followed by the VFI rate(34.4%),PLR(23.3%),and MD rate(21.4%).The CIGTS and AGIS scores had a lower proportion of eyes detected as progression(7.9%and 5.1%,respectively).The time to detection of progression was significantly shorter for the proposed method than that of other algorithms(adjusted P≤0.019).The VFI rate displayed moderate pairwise agreement with the proposed method(k=0.47).CONCLUSION:The functional GEE model shows the highest proportion of eyes detected as perimetric progression and the shortest time to detect perimetric progression in patients with POAG.
