This paper intends to analyze the six types of English imperative sentences proposed by Chen (1984) from a perspective of causal-chain windowing. It comes to the conclusions that Talmy's causal-chain windowing app...This paper intends to analyze the six types of English imperative sentences proposed by Chen (1984) from a perspective of causal-chain windowing. It comes to the conclusions that Talmy's causal-chain windowing approach as well as the cognitive underpinnings of causal windowing and gapping is proved to be applicable in English imperative structures, and that generally speaking, the final portion of an imperative sentence is always windowed while the intermediate portions gapped.展开更多
The speed and quality of the image fusion always restrain each other.The real-time image fusion is one of the problems which needs to be studied and solved urgently.The windowing processing technology for the image fu...The speed and quality of the image fusion always restrain each other.The real-time image fusion is one of the problems which needs to be studied and solved urgently.The windowing processing technology for the image fusion proposed in this paper can solve this problem in a certain extent.The windowing rules were put forward and the applicable scope for the windowing fusion and the calculation method for the maximum windowing area were determined.And,the results of the windowing fusion were analyzed,verified and compared to confirm the feasibility of this technology.展开更多
This paper presents a Novel Windowing Algorithm for Electrocardiogram Feature Extraction and Pattern Recognition. The work presented here deals with a simple and efficient way of detecting ECG features that are P, Q, ...This paper presents a Novel Windowing Algorithm for Electrocardiogram Feature Extraction and Pattern Recognition. The work presented here deals with a simple and efficient way of detecting ECG features that are P, Q, R, S and T waves. Windowing method is used to select these waves. Windows are based on varying R-R intervals. It has been tested on ECG simulator data and also on different records of the MIT-BIH arrhythmia database, producing satisfactory results. ECG timing intervals are also required for monitoring the cardiac condition of patients. Hence after feature detections ECG timing intervals like the PR interval, QRS duration, the QT interval, the QT corrected interval and Vent Rate are efficiently calculated using proposed Formulae.展开更多
This paper revisits the characteristics of windowing techniques with various window functions involved,and successively investigates spectral leakage mitigation utilizing the Welch method.The discrete Fourier transfor...This paper revisits the characteristics of windowing techniques with various window functions involved,and successively investigates spectral leakage mitigation utilizing the Welch method.The discrete Fourier transform(DFT)is ubiquitous in digital signal processing(DSP)for the spectrum analysis and can be efciently realized by the fast Fourier transform(FFT).The sampling signal will result in distortion and thus may cause unpredictable spectral leakage in discrete spectrum when the DFT is employed.Windowing is implemented by multiplying the input signal with a window function and windowing amplitude modulates the input signal so that the spectral leakage is evened out.Therefore,windowing processing reduces the amplitude of the samples at the beginning and end of the window.In addition to selecting appropriate window functions,a pretreatment method,such as the Welch method,is effective to mitigate the spectral leakage.Due to the noise caused by imperfect,nite data,the noise reduction from Welch’s method is a desired treatment.The nonparametric Welch method is an improvement on the periodogram spectrum estimation method where the signal-to-noise ratio(SNR)is high and mitigates noise in the estimated power spectra in exchange for frequency resolution reduction.The periodogram technique based on Welch method is capable of providing good resolution if data length samples are appropriately selected.The design of nite impulse response(FIR)digital lter using the window technique is rstly addressed.The inuence of various window functions on the Fourier transform spectrum of the signals is discussed.Comparison on spectral resolution based on the traditional power spectrum estimation and various window-function-based Welch power spectrum estimations is presented.展开更多
Textual data streams have been extensively used in practical applications where consumers of online products have expressed their views regarding online products.Due to changes in data distribution,commonly referred t...Textual data streams have been extensively used in practical applications where consumers of online products have expressed their views regarding online products.Due to changes in data distribution,commonly referred to as concept drift,mining this data stream is a challenging problem for researchers.The majority of the existing drift detection techniques are based on classification errors,which have higher probabilities of false-positive or missed detections.To improve classification accuracy,there is a need to develop more intuitive detection techniques that can identify a great number of drifts in the data streams.This paper presents an adaptive unsupervised learning technique,an ensemble classifier based on drift detection for opinion mining and sentiment classification.To improve classification performance,this approach uses four different dissimilarity measures to determine the degree of concept drifts in the data stream.Whenever a drift is detected,the proposed method builds and adds a new classifier to the ensemble.To add a new classifier,the total number of classifiers in the ensemble is first checked if the limit is exceeded before the classifier with the least weight is removed from the ensemble.To this end,a weighting mechanism is used to calculate the weight of each classifier,which decides the contribution of each classifier in the final classification results.Several experiments were conducted on real-world datasets and the resultswere evaluated on the false positive rate,miss detection rate,and accuracy measures.The proposed method is also compared with the state-of-the-art methods,which include DDM,EDDM,and PageHinkley with support vector machine(SVM)and Naive Bayes classifiers that are frequently used in concept drift detection studies.In all cases,the results show the efficiency of our proposed method.展开更多
Cardiovascular diseases(CVDs)continue to present a leading cause ofmortalityworldwide,emphasizing the importance of early and accurate prediction.Electrocardiogram(ECG)signals,central to cardiac monitoring,have increa...Cardiovascular diseases(CVDs)continue to present a leading cause ofmortalityworldwide,emphasizing the importance of early and accurate prediction.Electrocardiogram(ECG)signals,central to cardiac monitoring,have increasingly been integratedwithDeep Learning(DL)for real-time prediction of CVDs.However,DL models are prone to performance degradation due to concept drift and to catastrophic forgetting.To address this issue,we propose a realtime CVDs prediction approach,referred to as ADWIN-GFR that combines Convolutional Neural Network(CNN)layers,for spatial feature extraction,with Gated Recurrent Units(GRU),for temporal modeling,alongside adaptive drift detection and mitigation mechanisms.The proposed approach integratesAdaptiveWindowing(ADWIN)for realtime concept drift detection,a fine-tuning strategy based on Generative Features Replay(GFR)to preserve previously acquired knowledge,and a dynamic replay buffer ensuring variance,diversity,and data distribution coverage.Extensive experiments conducted on the MIT-BIH arrhythmia dataset demonstrate that ADWIN-GFR outperforms standard fine-tuning techniques,achieving an average post-drift accuracy of 95.4%,amacro F1-score of 93.9%,and a remarkably low forgetting score of 0.9%.It also exhibits an average drift detection delay of 12 steps and achieves an adaptation gain of 17.2%.These findings underscore the potential of ADWIN-GFR for deployment in real-world cardiac monitoring systems,including wearable ECG devices and hospital-based patient monitoring platforms.展开更多
Ag-Cu-In-Ti low-temperature filler was used to braze the diamond and copper,and the effects of brazing temperature and soaking time on the microstructure and mechanical properties of the joints were investigated.In ad...Ag-Cu-In-Ti low-temperature filler was used to braze the diamond and copper,and the effects of brazing temperature and soaking time on the microstructure and mechanical properties of the joints were investigated.In addition,the joint formation mechanism was discussed,and the correlation between joint microstructure and mechanical performance was established.Results show that adding appropriate amount of In into the filler can significantly reduce the filler melting point and enhance the wettability of filler on diamond.When the brazing temperature is 750°C and the soaking time is 10 min,a uniformly dense braze seam with excellent metallurgical bonding can be obtained,and its average joint shear strength reaches 322 MPa.The lower brazing temperature can mitigate the risk of diamond graphitization and also reduce the residual stresses during joining.展开更多
针对现有任意反射面速度干涉仪(velocity interferometer system for any reflector,VISAR)装置中依靠人工准直光路的现状,同时为满足未来对远程自动化控制的需求,提出一种新的光路自动准直的方法。该方法通过互补金属氧化物半导体(comp...针对现有任意反射面速度干涉仪(velocity interferometer system for any reflector,VISAR)装置中依靠人工准直光路的现状,同时为满足未来对远程自动化控制的需求,提出一种新的光路自动准直的方法。该方法通过互补金属氧化物半导体(complementary metal oxide semiconductor,CMOS)间接测量并以光斑的像素偏差为系统输入,通过系数矩阵转换和离散模糊反馈控制方法快速消除误差。基于Windows的控制和自动化技术(the Windows control and automation technology,TwinCAT)中视觉和运动等模块,将各模块分别运行在不同的实时内核中,消除了视觉与运动控制模块间的通信环节,实现了快速实时的闭环控制。经过冲击波速度测量实验验证,该系统实现了远程“一键式”自动准直,可将准直时间缩短到2 s,准直精度为4.5μm,解决了现有装置人工调节效率不高的问题,提高了系统的精度和稳定性。展开更多
We present a windowing technique of waveform relaxation for dynamic systems. An effective estimation on window length is derived by an iterative error expression provided here. Relaxation processes can be speeded up i...We present a windowing technique of waveform relaxation for dynamic systems. An effective estimation on window length is derived by an iterative error expression provided here. Relaxation processes can be speeded up if one takes the windowing technique in advance. Numerical experiments are given to further illustrate the theoretical analysis.展开更多
The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-d...The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-dimension collision-free trajectory planning is the prerequisite to ensure airspace security.However,the timely information of surrounding situation is difficult to acquire by UAVs,which further brings security risks.As a mature technology leveraged in traditional civil aviation,the Automatic Dependent Surveillance-Broadcast(ADS-B)realizes continuous surveillance of the information of aircraft.Consequently,we leverage ADS-B for surveillance and information broadcasting,and divide the aerial airspace into multiple sub-airspaces to improve flight safety in UAV trajectory planning.In detail,we propose the secure Sub-airSpaces Planning(SSP)algorithm and Particle Swarm Optimization Rapidly-exploring Random Trees(PSO-RRT)algorithm for the UAV trajectory planning in law-altitude airspace.The performance of the proposed algorithm is verified by simulations and the results show that SSP reduces both the maximum number of UAVs in the sub-airspace and the length of the trajectory,and PSO-RRT reduces the cost of UAV trajectory in the sub-airspace.展开更多
文摘This paper intends to analyze the six types of English imperative sentences proposed by Chen (1984) from a perspective of causal-chain windowing. It comes to the conclusions that Talmy's causal-chain windowing approach as well as the cognitive underpinnings of causal windowing and gapping is proved to be applicable in English imperative structures, and that generally speaking, the final portion of an imperative sentence is always windowed while the intermediate portions gapped.
文摘The speed and quality of the image fusion always restrain each other.The real-time image fusion is one of the problems which needs to be studied and solved urgently.The windowing processing technology for the image fusion proposed in this paper can solve this problem in a certain extent.The windowing rules were put forward and the applicable scope for the windowing fusion and the calculation method for the maximum windowing area were determined.And,the results of the windowing fusion were analyzed,verified and compared to confirm the feasibility of this technology.
文摘This paper presents a Novel Windowing Algorithm for Electrocardiogram Feature Extraction and Pattern Recognition. The work presented here deals with a simple and efficient way of detecting ECG features that are P, Q, R, S and T waves. Windowing method is used to select these waves. Windows are based on varying R-R intervals. It has been tested on ECG simulator data and also on different records of the MIT-BIH arrhythmia database, producing satisfactory results. ECG timing intervals are also required for monitoring the cardiac condition of patients. Hence after feature detections ECG timing intervals like the PR interval, QRS duration, the QT interval, the QT corrected interval and Vent Rate are efficiently calculated using proposed Formulae.
基金supported by the Ministry of Science and Technology,Taiwan[Grant Numbers MOST 104-2221-E-019-026-MY2 and MOST 108-2221-E019-013].
文摘This paper revisits the characteristics of windowing techniques with various window functions involved,and successively investigates spectral leakage mitigation utilizing the Welch method.The discrete Fourier transform(DFT)is ubiquitous in digital signal processing(DSP)for the spectrum analysis and can be efciently realized by the fast Fourier transform(FFT).The sampling signal will result in distortion and thus may cause unpredictable spectral leakage in discrete spectrum when the DFT is employed.Windowing is implemented by multiplying the input signal with a window function and windowing amplitude modulates the input signal so that the spectral leakage is evened out.Therefore,windowing processing reduces the amplitude of the samples at the beginning and end of the window.In addition to selecting appropriate window functions,a pretreatment method,such as the Welch method,is effective to mitigate the spectral leakage.Due to the noise caused by imperfect,nite data,the noise reduction from Welch’s method is a desired treatment.The nonparametric Welch method is an improvement on the periodogram spectrum estimation method where the signal-to-noise ratio(SNR)is high and mitigates noise in the estimated power spectra in exchange for frequency resolution reduction.The periodogram technique based on Welch method is capable of providing good resolution if data length samples are appropriately selected.The design of nite impulse response(FIR)digital lter using the window technique is rstly addressed.The inuence of various window functions on the Fourier transform spectrum of the signals is discussed.Comparison on spectral resolution based on the traditional power spectrum estimation and various window-function-based Welch power spectrum estimations is presented.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Large Groups(Project under Grant Number(RGP.2/49/43)).
文摘Textual data streams have been extensively used in practical applications where consumers of online products have expressed their views regarding online products.Due to changes in data distribution,commonly referred to as concept drift,mining this data stream is a challenging problem for researchers.The majority of the existing drift detection techniques are based on classification errors,which have higher probabilities of false-positive or missed detections.To improve classification accuracy,there is a need to develop more intuitive detection techniques that can identify a great number of drifts in the data streams.This paper presents an adaptive unsupervised learning technique,an ensemble classifier based on drift detection for opinion mining and sentiment classification.To improve classification performance,this approach uses four different dissimilarity measures to determine the degree of concept drifts in the data stream.Whenever a drift is detected,the proposed method builds and adds a new classifier to the ensemble.To add a new classifier,the total number of classifiers in the ensemble is first checked if the limit is exceeded before the classifier with the least weight is removed from the ensemble.To this end,a weighting mechanism is used to calculate the weight of each classifier,which decides the contribution of each classifier in the final classification results.Several experiments were conducted on real-world datasets and the resultswere evaluated on the false positive rate,miss detection rate,and accuracy measures.The proposed method is also compared with the state-of-the-art methods,which include DDM,EDDM,and PageHinkley with support vector machine(SVM)and Naive Bayes classifiers that are frequently used in concept drift detection studies.In all cases,the results show the efficiency of our proposed method.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R196)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Cardiovascular diseases(CVDs)continue to present a leading cause ofmortalityworldwide,emphasizing the importance of early and accurate prediction.Electrocardiogram(ECG)signals,central to cardiac monitoring,have increasingly been integratedwithDeep Learning(DL)for real-time prediction of CVDs.However,DL models are prone to performance degradation due to concept drift and to catastrophic forgetting.To address this issue,we propose a realtime CVDs prediction approach,referred to as ADWIN-GFR that combines Convolutional Neural Network(CNN)layers,for spatial feature extraction,with Gated Recurrent Units(GRU),for temporal modeling,alongside adaptive drift detection and mitigation mechanisms.The proposed approach integratesAdaptiveWindowing(ADWIN)for realtime concept drift detection,a fine-tuning strategy based on Generative Features Replay(GFR)to preserve previously acquired knowledge,and a dynamic replay buffer ensuring variance,diversity,and data distribution coverage.Extensive experiments conducted on the MIT-BIH arrhythmia dataset demonstrate that ADWIN-GFR outperforms standard fine-tuning techniques,achieving an average post-drift accuracy of 95.4%,amacro F1-score of 93.9%,and a remarkably low forgetting score of 0.9%.It also exhibits an average drift detection delay of 12 steps and achieves an adaptation gain of 17.2%.These findings underscore the potential of ADWIN-GFR for deployment in real-world cardiac monitoring systems,including wearable ECG devices and hospital-based patient monitoring platforms.
基金National MCF Energy R&D Program(2019YFE03100400)。
文摘Ag-Cu-In-Ti low-temperature filler was used to braze the diamond and copper,and the effects of brazing temperature and soaking time on the microstructure and mechanical properties of the joints were investigated.In addition,the joint formation mechanism was discussed,and the correlation between joint microstructure and mechanical performance was established.Results show that adding appropriate amount of In into the filler can significantly reduce the filler melting point and enhance the wettability of filler on diamond.When the brazing temperature is 750°C and the soaking time is 10 min,a uniformly dense braze seam with excellent metallurgical bonding can be obtained,and its average joint shear strength reaches 322 MPa.The lower brazing temperature can mitigate the risk of diamond graphitization and also reduce the residual stresses during joining.
文摘针对现有任意反射面速度干涉仪(velocity interferometer system for any reflector,VISAR)装置中依靠人工准直光路的现状,同时为满足未来对远程自动化控制的需求,提出一种新的光路自动准直的方法。该方法通过互补金属氧化物半导体(complementary metal oxide semiconductor,CMOS)间接测量并以光斑的像素偏差为系统输入,通过系数矩阵转换和离散模糊反馈控制方法快速消除误差。基于Windows的控制和自动化技术(the Windows control and automation technology,TwinCAT)中视觉和运动等模块,将各模块分别运行在不同的实时内核中,消除了视觉与运动控制模块间的通信环节,实现了快速实时的闭环控制。经过冲击波速度测量实验验证,该系统实现了远程“一键式”自动准直,可将准直时间缩短到2 s,准直精度为4.5μm,解决了现有装置人工调节效率不高的问题,提高了系统的精度和稳定性。
基金Supported by the National Natural Science Foundation of China(No.60472003)the 863 Program of China(No.2001AA111042)
文摘We present a windowing technique of waveform relaxation for dynamic systems. An effective estimation on window length is derived by an iterative error expression provided here. Relaxation processes can be speeded up if one takes the windowing technique in advance. Numerical experiments are given to further illustrate the theoretical analysis.
基金supported by the National Key R&D Program of China(No.2022YFB3104502)the National Natural Science Foundation of China(No.62301251)+2 种基金the Natural Science Foundation of Jiangsu Province of China under Project(No.BK20220883)the open research fund of National Mobile Communications Research Laboratory,Southeast University,China(No.2024D04)the Young Elite Scientists Sponsorship Program by CAST(No.2023QNRC001).
文摘The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-dimension collision-free trajectory planning is the prerequisite to ensure airspace security.However,the timely information of surrounding situation is difficult to acquire by UAVs,which further brings security risks.As a mature technology leveraged in traditional civil aviation,the Automatic Dependent Surveillance-Broadcast(ADS-B)realizes continuous surveillance of the information of aircraft.Consequently,we leverage ADS-B for surveillance and information broadcasting,and divide the aerial airspace into multiple sub-airspaces to improve flight safety in UAV trajectory planning.In detail,we propose the secure Sub-airSpaces Planning(SSP)algorithm and Particle Swarm Optimization Rapidly-exploring Random Trees(PSO-RRT)algorithm for the UAV trajectory planning in law-altitude airspace.The performance of the proposed algorithm is verified by simulations and the results show that SSP reduces both the maximum number of UAVs in the sub-airspace and the length of the trajectory,and PSO-RRT reduces the cost of UAV trajectory in the sub-airspace.
