The complete discrimination system for polynomial method is applied to the long-short-wave interaction system to obtain the classifications of single traveling wave solutions. Compared with the solutions given by the ...The complete discrimination system for polynomial method is applied to the long-short-wave interaction system to obtain the classifications of single traveling wave solutions. Compared with the solutions given by the （G~/G）-expansion method, we gain some new solutions.展开更多
A ten-month field research study was meticulously conducted at Robert Moses State Park (RMSP) on the south shore of Long Island, NY. The objective was to determine if aerial phenomena of an unknown nature exist over a...A ten-month field research study was meticulously conducted at Robert Moses State Park (RMSP) on the south shore of Long Island, NY. The objective was to determine if aerial phenomena of an unknown nature exist over a coastal location and to characterize their properties and behaviors. Primary and secondary field observation methods were utilized in this data-centric study. Forensic engineering principles and methodologies guided the study. The challenges set forward were object detection, observation, and characterization, where multispectral electro-optical devices and radar were employed due to limited visual acuity and intermittent presentation of the phenomena. The primary means of detection utilized a 3 cm X-band radar operating in two scan geometries, the X- and Y-axis. Multispectral electro-optical devices were utilized as a secondary means of detection and identification. Data was emphasized using HF and LF detectors and spectrum analyzers incorporating EM, ultrasonic, magnetic, and RF field transducers to record spectral data in these domains. Data collection concentrated on characterizing VIS, NIR, SWIR, LWIR, UVA, UVB, UVC, and the higher energy spectral range of ionizing radiation (alpha, beta, gamma, and X-ray) recorded by Geiger-Müller counters as well as special purpose semiconductor diode sensors.展开更多
A detailed analysis of the dynamic frequency spectrum characteristics of gravity waves(GWs)during a local heavy rainfall event on 20–21 November 2016 in Foshan,China,is presented.The results of this analysis,which wa...A detailed analysis of the dynamic frequency spectrum characteristics of gravity waves(GWs)during a local heavy rainfall event on 20–21 November 2016 in Foshan,China,is presented.The results of this analysis,which was based on high-precision microbarograph data,indicate that GWs played a key role in generating the rainstorm.The GWs experienced two intermittent periods of amplitude enhancement and period widening.The largest amplitudes of the GWs were 80–160 Pa,with a corresponding period range of 140–270 min,which were approximately 4 h ahead of the rainstorm.The severe storms appeared to affect the GWs by augmenting the wave amplitudes with center amplitudes of approximately 80–100 Pa and periods ranging between 210 and 270 min;in particular,the amplitudes increased to approximately 10 Pa for GWs with shorter periods(less than 36 min).The pre-existing large-amplitude GWs may be precursors to severe storms;that is,these GWs occurred approximately 4 h earlier than the time radars and satellites identified convections.Thus,these results indicate that large-amplitude GWs constitute a possible mechanism for severe-storm warning.展开更多
We apply the （G＇/G）-expansion method to solve two systems of nonlinear differential equations and construct traveling wave solutions expressed in terms of hyperbolic functions, trigonometric functions, and rational...We apply the （G＇/G）-expansion method to solve two systems of nonlinear differential equations and construct traveling wave solutions expressed in terms of hyperbolic functions, trigonometric functions, and rational functions with arbitrary parameters. We highlight the power of the （G＇/G）-expansion method in providing generalized solitary wave solutions of different physical structures. It is shown that the （G＇/G）-expansion method is very effective and provides a powerful mathematical tool to solve nonlinear differential equation systems in mathematical physics.展开更多
目的直接动脉血压(arterial blood pressure,ABP)连续监测是侵入式的,传统袖带式的间接血压测量法无法实现连续监测。既往利用光学体积描记术(photoplethysmography,PPG)实现了连续无创血压监测,但其为收缩压和舒张压的离散值,而非ABP...目的直接动脉血压(arterial blood pressure,ABP)连续监测是侵入式的,传统袖带式的间接血压测量法无法实现连续监测。既往利用光学体积描记术(photoplethysmography,PPG)实现了连续无创血压监测,但其为收缩压和舒张压的离散值,而非ABP波的连续值,本研究期望基于卷积神经网络-长短期记忆神经网络(CNN-LSTM)利用PPG信号波重建ABP波信号,实现连续无创血压监测。方法构建CNN-LSTM混合神经网络模型,利用重症监护医学信息集(medical information mart for intensive care,MIMIC)中的PPG与ABP波同步记录信号数据,将PPG信号波经预处理降噪、归一化、滑窗分割后输入该模型,重建与之同步对应的ABP波信号。结果使用窗口长度312的CNN-LSTM神经网络时,重建ABP值与实际ABP值间误差最小,平均绝对误差(mean absolute error,MAE)和均方根误差(root mean square error,RMSE)分别为2.79 mmHg和4.24 mmHg,余弦相似度最大,重建ABP值与实际ABP值一致性和相关性情况良好,符合美国医疗器械促进协会(Association for the Advancement of Medical Instrumentation,AAMI)标准。结论CNN-LSTM混合神经网络可利用PPG信号波重建ABP波信号,实现连续无创血压监测。展开更多
We propose a systematic method to construct the Mel’nikov model of long–short wave interactions,which is a special case of the Kadomtsev–Petviashvili(KP)equation with self-consistent sources(KPSCS).We show details ...We propose a systematic method to construct the Mel’nikov model of long–short wave interactions,which is a special case of the Kadomtsev–Petviashvili(KP)equation with self-consistent sources(KPSCS).We show details how the Cauchy matrix approach applies to Mel’nikov’s model which is derived as a complex reduction of the KPSCS.As a new result wefind that in the dispersion relation of a 1-soliton there is an arbitrary time-dependent function that has previously not reported in the literature about the Mel’nikov model.This function brings time variant velocity for the long wave and also governs the short-wave packet.The variety of interactions of waves resulting from the time-freedom in the dispersion relation is illustrated.展开更多
本文以2019年1月1日至2021年12月31日舟山群岛南部外海观测点所涵盖的气象、海洋、地形等多种物理量数据为数据基础,使用长短时记忆(Long Short Term Memory,LSTM)神经网络搭建深度学习海浪预报模型,探讨输入输出序列比和输入要素数量...本文以2019年1月1日至2021年12月31日舟山群岛南部外海观测点所涵盖的气象、海洋、地形等多种物理量数据为数据基础,使用长短时记忆(Long Short Term Memory,LSTM)神经网络搭建深度学习海浪预报模型,探讨输入输出序列比和输入要素数量对模型预测性能的影响,在舟山海域实现波浪三要素,即有效波高、有效波周期、传播方向的短时预报,并用2022年台风“轩岚诺”和“梅花”期间的数据检验模型对极端海况的预测能力。研究结果表明,根据实测数据所训练的多要素海浪预报模型具有较好的预测准确度和稳定性,能较好地实现对极端海况的预测,当输入输出序列比为1∶1时模型准确度较高,预报时长为1 h的三要素模型对于日常海况中有效波高、有效波周期和波向的预测均方根误差(Root Mean Squared Error,RMSE)分别为0.116 m、0.569 s和24.583°,对于极端海况中有效波高的预测RMSE为0.191 m,输入要素数量的增加可进一步提升模型准确度,但在预测时长较长时也会增加训练成本。展开更多
基金Project supported by the Scientific Research Fund of Education Department of Heilongjiang Province of China (Grant No.12531475)
文摘The complete discrimination system for polynomial method is applied to the long-short-wave interaction system to obtain the classifications of single traveling wave solutions. Compared with the solutions given by the （G~/G）-expansion method, we gain some new solutions.
文摘A ten-month field research study was meticulously conducted at Robert Moses State Park (RMSP) on the south shore of Long Island, NY. The objective was to determine if aerial phenomena of an unknown nature exist over a coastal location and to characterize their properties and behaviors. Primary and secondary field observation methods were utilized in this data-centric study. Forensic engineering principles and methodologies guided the study. The challenges set forward were object detection, observation, and characterization, where multispectral electro-optical devices and radar were employed due to limited visual acuity and intermittent presentation of the phenomena. The primary means of detection utilized a 3 cm X-band radar operating in two scan geometries, the X- and Y-axis. Multispectral electro-optical devices were utilized as a secondary means of detection and identification. Data was emphasized using HF and LF detectors and spectrum analyzers incorporating EM, ultrasonic, magnetic, and RF field transducers to record spectral data in these domains. Data collection concentrated on characterizing VIS, NIR, SWIR, LWIR, UVA, UVB, UVC, and the higher energy spectral range of ionizing radiation (alpha, beta, gamma, and X-ray) recorded by Geiger-Müller counters as well as special purpose semiconductor diode sensors.
基金sponsored by the National Key R&D Program of China [Grant No.2018YFC1507900]the National Natural Science Foundation of China [Grant No.41530427]。
文摘A detailed analysis of the dynamic frequency spectrum characteristics of gravity waves(GWs)during a local heavy rainfall event on 20–21 November 2016 in Foshan,China,is presented.The results of this analysis,which was based on high-precision microbarograph data,indicate that GWs played a key role in generating the rainstorm.The GWs experienced two intermittent periods of amplitude enhancement and period widening.The largest amplitudes of the GWs were 80–160 Pa,with a corresponding period range of 140–270 min,which were approximately 4 h ahead of the rainstorm.The severe storms appeared to affect the GWs by augmenting the wave amplitudes with center amplitudes of approximately 80–100 Pa and periods ranging between 210 and 270 min;in particular,the amplitudes increased to approximately 10 Pa for GWs with shorter periods(less than 36 min).The pre-existing large-amplitude GWs may be precursors to severe storms;that is,these GWs occurred approximately 4 h earlier than the time radars and satellites identified convections.Thus,these results indicate that large-amplitude GWs constitute a possible mechanism for severe-storm warning.
基金Project supported by the Scientific Research Project of Eskisehir Osmangazi University, Turkey (Grant No. 201019031)
文摘We apply the （G＇/G）-expansion method to solve two systems of nonlinear differential equations and construct traveling wave solutions expressed in terms of hyperbolic functions, trigonometric functions, and rational functions with arbitrary parameters. We highlight the power of the （G＇/G）-expansion method in providing generalized solitary wave solutions of different physical structures. It is shown that the （G＇/G）-expansion method is very effective and provides a powerful mathematical tool to solve nonlinear differential equation systems in mathematical physics.
文摘目的直接动脉血压(arterial blood pressure,ABP)连续监测是侵入式的,传统袖带式的间接血压测量法无法实现连续监测。既往利用光学体积描记术(photoplethysmography,PPG)实现了连续无创血压监测,但其为收缩压和舒张压的离散值,而非ABP波的连续值,本研究期望基于卷积神经网络-长短期记忆神经网络(CNN-LSTM)利用PPG信号波重建ABP波信号,实现连续无创血压监测。方法构建CNN-LSTM混合神经网络模型,利用重症监护医学信息集(medical information mart for intensive care,MIMIC)中的PPG与ABP波同步记录信号数据,将PPG信号波经预处理降噪、归一化、滑窗分割后输入该模型,重建与之同步对应的ABP波信号。结果使用窗口长度312的CNN-LSTM神经网络时,重建ABP值与实际ABP值间误差最小,平均绝对误差(mean absolute error,MAE)和均方根误差(root mean square error,RMSE)分别为2.79 mmHg和4.24 mmHg,余弦相似度最大,重建ABP值与实际ABP值一致性和相关性情况良好,符合美国医疗器械促进协会(Association for the Advancement of Medical Instrumentation,AAMI)标准。结论CNN-LSTM混合神经网络可利用PPG信号波重建ABP波信号,实现连续无创血压监测。
基金supported by the NSF of China(Nos.11875040 and 11631007)。
文摘We propose a systematic method to construct the Mel’nikov model of long–short wave interactions,which is a special case of the Kadomtsev–Petviashvili(KP)equation with self-consistent sources(KPSCS).We show details how the Cauchy matrix approach applies to Mel’nikov’s model which is derived as a complex reduction of the KPSCS.As a new result wefind that in the dispersion relation of a 1-soliton there is an arbitrary time-dependent function that has previously not reported in the literature about the Mel’nikov model.This function brings time variant velocity for the long wave and also governs the short-wave packet.The variety of interactions of waves resulting from the time-freedom in the dispersion relation is illustrated.
文摘本文以2019年1月1日至2021年12月31日舟山群岛南部外海观测点所涵盖的气象、海洋、地形等多种物理量数据为数据基础,使用长短时记忆(Long Short Term Memory,LSTM)神经网络搭建深度学习海浪预报模型,探讨输入输出序列比和输入要素数量对模型预测性能的影响,在舟山海域实现波浪三要素,即有效波高、有效波周期、传播方向的短时预报,并用2022年台风“轩岚诺”和“梅花”期间的数据检验模型对极端海况的预测能力。研究结果表明,根据实测数据所训练的多要素海浪预报模型具有较好的预测准确度和稳定性,能较好地实现对极端海况的预测,当输入输出序列比为1∶1时模型准确度较高,预报时长为1 h的三要素模型对于日常海况中有效波高、有效波周期和波向的预测均方根误差(Root Mean Squared Error,RMSE)分别为0.116 m、0.569 s和24.583°,对于极端海况中有效波高的预测RMSE为0.191 m,输入要素数量的增加可进一步提升模型准确度,但在预测时长较长时也会增加训练成本。
