Ship motion attitude is influenced by dynamic marine conditions,presenting significant challenges in developing effective prediction networks.Contemporary prediction networks demonstrate limitations in hidden feature ...Ship motion attitude is influenced by dynamic marine conditions,presenting significant challenges in developing effective prediction networks.Contemporary prediction networks demonstrate limitations in hidden feature extraction,long-term dependency maintenance,and frequency characteristic incorporation.This paper presents an enhanced model integrating the informer network with a Time Convolutional Network(TCN)and a Frequency-Enhanced Channel Attention Mechanism(FECAM).The model employs a TCN for multi-feature extraction and applies Dimension-Segment-Wise(DSW)embedding for comprehensive multi-dimensional sequence analysis.Furthermore,it incorporates discrete cosine transform within the FECAM module for thorough data frequency analysis.The model integrates these components with the informer model for multivariate prediction.This approach maintains the informer model's capabilities in long-term multivariate prediction while enhancing feature extraction and local frequency information capture from ship motion attitude data,thus improving long-term multivariate prediction accuracy.Experimental results indicate that the proposed model outperforms traditional ship motion attitude prediction methods in forecasting future motion,reducing attitude prediction errors,and improving prediction accuracy.展开更多
In order to enhance the image information from multi-sensor and to improve the abilities of the information analysis and the feature extraction, this letter proposed a new fusion approach in pixel level by means of th...In order to enhance the image information from multi-sensor and to improve the abilities of the information analysis and the feature extraction, this letter proposed a new fusion approach in pixel level by means of the Wavelet Packet Transform (WPT). The WPT is able to decompose an image into low frequency band and high frequency band in higher scale. It offers a more precise method for image analysis than Wavelet Transform (WT). Firstly, the proposed approach employs HIS (Hue, Intensity, Saturation) transform to obtain the intensity component of CBERS (China-Brazil Earth Resource Satellite) multi-spectral image. Then WPT transform is employed to decompose the intensity component and SPOT (Systeme Pour I'Observation de la Therre ) image into low frequency band and high frequency band in three levels. Next, two high frequency coefficients and low frequency coefficients of the images are combined by linear weighting strategies. Finally, the fused image is obtained with inverse WPT and inverse HIS. The results show the new approach can fuse details of input image successfully, and thereby can obtain a more satisfactory result than that of HM (Histogram Matched)-based fusion algorithm and WT-based fusion approach.展开更多
As a major global exchange, the Stock Exchange of Hong Kong （SEHK） only requires semi-annual reporting whereas other major exchanges including the ones in Chinese mainland require quarterly reporting. We argue again...As a major global exchange, the Stock Exchange of Hong Kong （SEHK） only requires semi-annual reporting whereas other major exchanges including the ones in Chinese mainland require quarterly reporting. We argue against the traditional view that higher reporting frequency is necessarily more beneficial. The decision on reporting frequency depends on how the information is being processed by the recipient traders and the results are not obvious. Using a sample of Chinese companies dual- listed in both China A share market and SEHK （AH shares） as the experimental group and mainland＇s companies listed on SEHK （H shares） only as the control group, we apply the difference-in-difference （DID） method to investigate the impacts of reporting frequency on stock information quality. The results suggest that after China A share market require quarterly financial reporting for all listed companies in 2002, the information asymmetry of the H tranche of AH stocks increases. Different from prior studies, the results suggest a negative association between stock information quality and financial reporting frequency. We argue that the increased information asymmetry in the H tranche is caused by the noise spilled over from the A tranche. We conduct multivariable GARCH tests and find evidence supporting this conjecture.展开更多
Digital data of precursors is noted for its high accuracy. Therefore, it is important to extract the high frequency information from the low ones in the digital data of precursors and to discriminate between the trend...Digital data of precursors is noted for its high accuracy. Therefore, it is important to extract the high frequency information from the low ones in the digital data of precursors and to discriminate between the trend anomalies and the short-term anomalies. This paper presents a method to separate the high frequency information from the low ones by using the wavelet transform to analyze the digital data of precursors, and illustrates with examples the train of thoughts of discriminating the short-term anomalies from trend anomalies by using the wavelet transform, thus provide a new effective approach for extracting the short-term and trend anomalies from the digital data of precursors.展开更多
Fourier ptychographic microscopy(FPM)is a pivotal computational imaging technique that achieves phase and amplitude reconstruction with high resolution and a wide field of view,using low numerical aperture objectives ...Fourier ptychographic microscopy(FPM)is a pivotal computational imaging technique that achieves phase and amplitude reconstruction with high resolution and a wide field of view,using low numerical aperture objectives and LED array illumination.Despite its unique strengths,FPM remains fundamentally limited in retrieving low spatial frequency phase information due to the absence of phase encoding in all on-axis and slightly off-axis(bright-field)illumination angles.To overcome this,we present a hybrid approach that combines FPM with the transport of intensity equation(TIE),enabling robust phase retrieval across a wide spatial frequency range without compromising system simplicity.Our method extends standard FPM acquisitions with a single addi-tional on-axis defocused image,from which low-frequency phase components are reconstructed via the TIE method,employing large defocus distance to suppress low-frequency artifacts and enhance robustness to intensity noise.High-frequency phase details are recovered through FPM processing.To additionally compensate for defocus-induced magnification variations caused by spherical wavefront illumination,we employ an affine transform-based correction scheme upon image registration.Notably,by restoring the missing low-frequency content,our hybrid method allows for more reliable quantitative phase recovery than standard FPM.We vali-dated our method using a quantitative phase test target for benchmarking accuracy and biological cheek cells,mouse neurons,and mouse brain tissue slice samples to demonstrate applicability for in vitro bioimaging.Experimental results confirm substantial improvements in phase reconstruction fidelity across spatial frequencies,establishing this hybrid FPM+TIE framework as a practical and high-performance solution for quantitative phase imaging in biomedical and optical metrology applications.展开更多
文摘Ship motion attitude is influenced by dynamic marine conditions,presenting significant challenges in developing effective prediction networks.Contemporary prediction networks demonstrate limitations in hidden feature extraction,long-term dependency maintenance,and frequency characteristic incorporation.This paper presents an enhanced model integrating the informer network with a Time Convolutional Network(TCN)and a Frequency-Enhanced Channel Attention Mechanism(FECAM).The model employs a TCN for multi-feature extraction and applies Dimension-Segment-Wise(DSW)embedding for comprehensive multi-dimensional sequence analysis.Furthermore,it incorporates discrete cosine transform within the FECAM module for thorough data frequency analysis.The model integrates these components with the informer model for multivariate prediction.This approach maintains the informer model's capabilities in long-term multivariate prediction while enhancing feature extraction and local frequency information capture from ship motion attitude data,thus improving long-term multivariate prediction accuracy.Experimental results indicate that the proposed model outperforms traditional ship motion attitude prediction methods in forecasting future motion,reducing attitude prediction errors,and improving prediction accuracy.
文摘In order to enhance the image information from multi-sensor and to improve the abilities of the information analysis and the feature extraction, this letter proposed a new fusion approach in pixel level by means of the Wavelet Packet Transform (WPT). The WPT is able to decompose an image into low frequency band and high frequency band in higher scale. It offers a more precise method for image analysis than Wavelet Transform (WT). Firstly, the proposed approach employs HIS (Hue, Intensity, Saturation) transform to obtain the intensity component of CBERS (China-Brazil Earth Resource Satellite) multi-spectral image. Then WPT transform is employed to decompose the intensity component and SPOT (Systeme Pour I'Observation de la Therre ) image into low frequency band and high frequency band in three levels. Next, two high frequency coefficients and low frequency coefficients of the images are combined by linear weighting strategies. Finally, the fused image is obtained with inverse WPT and inverse HIS. The results show the new approach can fuse details of input image successfully, and thereby can obtain a more satisfactory result than that of HM (Histogram Matched)-based fusion algorithm and WT-based fusion approach.
文摘As a major global exchange, the Stock Exchange of Hong Kong （SEHK） only requires semi-annual reporting whereas other major exchanges including the ones in Chinese mainland require quarterly reporting. We argue against the traditional view that higher reporting frequency is necessarily more beneficial. The decision on reporting frequency depends on how the information is being processed by the recipient traders and the results are not obvious. Using a sample of Chinese companies dual- listed in both China A share market and SEHK （AH shares） as the experimental group and mainland＇s companies listed on SEHK （H shares） only as the control group, we apply the difference-in-difference （DID） method to investigate the impacts of reporting frequency on stock information quality. The results suggest that after China A share market require quarterly financial reporting for all listed companies in 2002, the information asymmetry of the H tranche of AH stocks increases. Different from prior studies, the results suggest a negative association between stock information quality and financial reporting frequency. We argue that the increased information asymmetry in the H tranche is caused by the noise spilled over from the A tranche. We conduct multivariable GARCH tests and find evidence supporting this conjecture.
文摘Digital data of precursors is noted for its high accuracy. Therefore, it is important to extract the high frequency information from the low ones in the digital data of precursors and to discriminate between the trend anomalies and the short-term anomalies. This paper presents a method to separate the high frequency information from the low ones by using the wavelet transform to analyze the digital data of precursors, and illustrates with examples the train of thoughts of discriminating the short-term anomalies from trend anomalies by using the wavelet transform, thus provide a new effective approach for extracting the short-term and trend anomalies from the digital data of precursors.
基金Politechnika Warszawska(IDUB Young PW 504/04496/1143/45.010008)Narodowe Centrum Bada i Rozwoju Project No.(WPC3/2022/47/INTENCITY/2024 funded by the National Center for Research and Development as part of the 3rd competition for joint research projects as part of Polish-Chinese cooperation(2022))National Natural Science Foundation of China(62361136588).
文摘Fourier ptychographic microscopy(FPM)is a pivotal computational imaging technique that achieves phase and amplitude reconstruction with high resolution and a wide field of view,using low numerical aperture objectives and LED array illumination.Despite its unique strengths,FPM remains fundamentally limited in retrieving low spatial frequency phase information due to the absence of phase encoding in all on-axis and slightly off-axis(bright-field)illumination angles.To overcome this,we present a hybrid approach that combines FPM with the transport of intensity equation(TIE),enabling robust phase retrieval across a wide spatial frequency range without compromising system simplicity.Our method extends standard FPM acquisitions with a single addi-tional on-axis defocused image,from which low-frequency phase components are reconstructed via the TIE method,employing large defocus distance to suppress low-frequency artifacts and enhance robustness to intensity noise.High-frequency phase details are recovered through FPM processing.To additionally compensate for defocus-induced magnification variations caused by spherical wavefront illumination,we employ an affine transform-based correction scheme upon image registration.Notably,by restoring the missing low-frequency content,our hybrid method allows for more reliable quantitative phase recovery than standard FPM.We vali-dated our method using a quantitative phase test target for benchmarking accuracy and biological cheek cells,mouse neurons,and mouse brain tissue slice samples to demonstrate applicability for in vitro bioimaging.Experimental results confirm substantial improvements in phase reconstruction fidelity across spatial frequencies,establishing this hybrid FPM+TIE framework as a practical and high-performance solution for quantitative phase imaging in biomedical and optical metrology applications.
