In a composite-step approach, a step Sk is computed as the sum of two components Uk and hk. The normal component Vk, which is called the vertical step, aims to improve the linearized feasibility, while the tangential ...In a composite-step approach, a step Sk is computed as the sum of two components Uk and hk. The normal component Vk, which is called the vertical step, aims to improve the linearized feasibility, while the tangential component hk, which is also called horizontal step, concentrates on reducing a model of the merit functions. As a filter method, it reduces both the infeasibility and the objective function. This is the same property of these two methods. In this paper, one concerns the composite-step like filter approach. That is, a step is tangential component hk if the infeasibility is reduced. Or else, Sk is a composite step composed of normal component Uk, and tangential component hk.展开更多
In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken a...In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.展开更多
A temperature forecasting model was created firstly based on the Kalman filter method,and then used to predict the highest and lowest temperature in Nanchang station from October 27 to November 1,2017.Finally,accordin...A temperature forecasting model was created firstly based on the Kalman filter method,and then used to predict the highest and lowest temperature in Nanchang station from October 27 to November 1,2017.Finally,according to the empirical forecasting method,guidance forecasts were established for the northern,central,and southern parts of Nanchang City.After inspection,it was found that the temperature prediction model established based on the Kalman filter method in Nanchang station had good prediction performance,and especially in the 24-hour forecast,it had advantages over the European Center.The accuracy of low temperature forecast was better than that of high temperature forecast.展开更多
The sinusoid curve fit is widely applied in the evaluation of digitized measurement equipment, such as data acquisition system, digital storage oscilloscope, waveform recorder and A/D converter,etc. Because of the di...The sinusoid curve fit is widely applied in the evaluation of digitized measurement equipment, such as data acquisition system, digital storage oscilloscope, waveform recorder and A/D converter,etc. Because of the distortion and noise of sinusoid signal generator, the digitizing and the non linearity errors in measurement, it is impossible to avoid the distortion and the noise in sinusoid sampling series. The distortion and the noise limit the accuracy of curve fit results. Therefore, it is desirable to find a filter that can filter out both distortion and noise of the sinusoid sampling series, and in the meantime, the filter doesn′t influence the amplitude, the frequency, the phase and DC bias of fitting curve of the sine wave. And then, the uncertainty of fitting parameter can be reduced. This filter is designed and realized. Its realization in time domain is described and its transfer function in frequency domain is presented.展开更多
In this paper,we present a modeling of the soil-water characteristic curve for residual and sedimentary soils of Bom Brinquedo Hill’s,located in Antonina,Brazil.This mountain range region is characterized as a natura...In this paper,we present a modeling of the soil-water characteristic curve for residual and sedimentary soils of Bom Brinquedo Hill’s,located in Antonina,Brazil.This mountain range region is characterized as a natural disaster risk area,requiring continuous research related to the stability of the area.To obtain the soil-water characteristic curve,undisturbed samples of residual and sedimentary soil were collected,followed by suction testing using the filter paper method.Considering the bimodal characteristic presented by the soil,LABFIT software was employed for curve fitting using the generic formulation“Harris+C”.The results of the tests indicated that the phenomenon of hysteresis had a greater influence in situations with higher suction levels.When comparing the residual moisture values of the macropores between residual soil and sedimentary soil,the former exhibited the lower value.This suggests that the residual soil has a coarser grain size and larger pores,which facilitates the release of water retained in the soil’s macropores.展开更多
An optical emission spectroscopy(OES)method with a non-invasive measurement capability,without inducing disturbance to the discharge,represents an effective method for material monitoring.However,when the OES method i...An optical emission spectroscopy(OES)method with a non-invasive measurement capability,without inducing disturbance to the discharge,represents an effective method for material monitoring.However,when the OES method is employed to monitor the trace erosion product within the ceramic channel of a Hall thruster,it becomes challenging to distinguish between signal and noise.In this study,we propose a model filtering method based on the signal characteristics of the Hall thruster plume spectrometer.This method integrates the slit imaging and spectral resolution features of the spectrometer.Employing this method,we extract the spectral signals of the erosion product and working gas from the Hall thruster under different operating conditions.The results indicate that our new method performs comparably to the traditional method without model filtering when extracting atom signals from strong xenon working gas.However,for trace amounts of the erosion product,our approach significantly enhances the signal-to-noise ratio(SNR),enabling the identification of extremely weak spectral signals even under low mass flow rate and low-voltage conditions.We obtain boron atom concentration of 3.91×10^(-3) kg/m^(3) at a mass flow rate of 4×10^(-7) kg/s and voltage of 200 V while monitoring a wider range of thruster operating conditions.The new method proposed in this study is suitable for monitoring other low-concentration elements,making it valuable for materials processing,environmental monitoring and space propulsion applications.展开更多
Aiming at the problem that the traditional collaborative filtering recommendation algorithm does not fully consider the influence of correlation between projects on recommendation accuracy,this paper introduces projec...Aiming at the problem that the traditional collaborative filtering recommendation algorithm does not fully consider the influence of correlation between projects on recommendation accuracy,this paper introduces project attribute fuzzy matrix,measures the project relevance through fuzzy clustering method,and classifies all project attributes.Then,the weight of the project relevance is introduced in the user similarity calculation,so that the nearest neighbor search is more accurate.In the prediction scoring section,considering the change of user interest with time,it is proposed to use the time weighting function to improve the influence of the time effect of the evaluation,so that the newer evaluation information in the system has a relatively large weight.The experimental results show that the improved algorithm improves the recommendation accuracy and improves the recommendation quality.展开更多
In this paper we present a filter-trust-region algorithm for solving LC1 unconstrained optimization problems which uses the second Dini upper directional derivative. We establish the global convergence of the algorith...In this paper we present a filter-trust-region algorithm for solving LC1 unconstrained optimization problems which uses the second Dini upper directional derivative. We establish the global convergence of the algorithm under reasonable assumptions.展开更多
For Microwave Humidity and Temperature sounder(MWHTS) measurements over the ocean, a cloud filtering method is presented to filter out cloud-and precipitation-affected observations by analyzing the sensitivity of the ...For Microwave Humidity and Temperature sounder(MWHTS) measurements over the ocean, a cloud filtering method is presented to filter out cloud-and precipitation-affected observations by analyzing the sensitivity of the simulated brightness temperatures of MWHTS to cloud liquid water, and using the root mean square error(RMSE)between observation and simulation in clear sky as a reference standard. The atmospheric temperature and humidity profiles are retrieved using MWHTS measurements with and without filtering by multiple linear regression(MLR),artificial neural networks(ANN) and one-dimensional variational(1DVAR) retrieval methods, respectively, and the effects of the filtering method on the retrieval accuracies are analyzed. The numerical results show that the filtering method can improve the retrieval accuracies of the MLR and the 1DVAR retrieval methods, but have little influence on that of the ANN. In addition, the dependencies of the retrieval methods upon the testing samples of brightness temperature are studied, and the results show that the 1DVAR retrieval method has great stability due to that the testing samples have great impact on the retrieval accuracies of the MLR and the ANN, but have little impact on that of the 1DVAR.展开更多
Few study gives guidance to design weighting filters according to the frequency weighting factors,and the additional evaluation method of automotive ride comfort is not made good use of in some countries.Based on the ...Few study gives guidance to design weighting filters according to the frequency weighting factors,and the additional evaluation method of automotive ride comfort is not made good use of in some countries.Based on the regularities of the weighting factors,a method is proposed and the vertical and horizontal weighting filters are developed.The whole frequency range is divided several times into two parts with respective regularity.For each division,a parallel filter constituted by a low-and a high-pass filter with the same cutoff frequency and the quality factor is utilized to achieve section factors.The cascading of these parallel filters obtains entire factors.These filters own a high order.But,low order filters are preferred in some applications.The bilinear transformation method and the least P-norm optimal infinite impulse response（IIR） filter design method are employed to develop low order filters to approximate the weightings in the standard.In addition,with the window method,the linear phase finite impulse response（FIR） filter is designed to keep the signal from distorting and to obtain the staircase weighting.For the same case,the traditional method produces 0.330 7 m · s^–2 weighted root mean square（r.m.s.） acceleration and the filtering method gives 0.311 9 m · s^–2 r.m.s.The fourth order filter for approximation of vertical weighting obtains 0.313 9 m · s^–2 r.m.s.Crest factors of the acceleration signal weighted by the weighting filter and the fourth order filter are 3.002 7 and 3.011 1,respectively.This paper proposes several methods to design frequency weighting filters for automotive ride comfort evaluation,and these developed weighting filters are effective.展开更多
Conventional frequency domain method used in random noise attenuation singular value decomposition （SVD） filtering processing causes bending event damage. To mitigate this problem, we present a mixed Cadzow filterin...Conventional frequency domain method used in random noise attenuation singular value decomposition （SVD） filtering processing causes bending event damage. To mitigate this problem, we present a mixed Cadzow filtering method based on fractional Fourier transform to suppress random noise in 3D seismic data. First, the seismic data is transformed to the time-frequency plane via the fractional Fourier transform. Second, based on the Eigenimage filtering method and Cadzow filtering method, the mixed high-dimensional Hankel matrix is built; then, SVD is performed. Finally, random noise is eliminated effectively by reducing the rank of the matrix. The theoretical model and real applications of the mixed filtering method in a region of Sichuan show that our method can not only suppress noise effectively but also preserve the frequency and phase of effective signals quite well and significantly improve the signal-to-noise ratio of 3D post-stack seismic data.展开更多
How to deal with colored noises of GOCE （Gravity field and steady - state Ocean Circulation Explorer） satellite has been the key to data processing. This paper focused on colored noises of GOCE gradient data and the...How to deal with colored noises of GOCE （Gravity field and steady - state Ocean Circulation Explorer） satellite has been the key to data processing. This paper focused on colored noises of GOCE gradient data and the frequency spectrum analysis. According to the analysis results, gravity field model of the optima] degrees 90-240 is given, which is recovered by COCE gradient data. This paper presents an iterative Wiener filtering method based on the gravity gradient invariants. By this method a degree-220 model was calculated from GOCE SGG （Satellite Gravity Gradient） data. The degrees above 90 of ITG2010 were taken as the prior gravity field model, replacing the low degree gravity field model calculated by GOCE orbit data. GOCE gradient colored noises was processed by Wiener filtering. Finally by Wiener filtering iterative calculation, the gravity field model was restored by space-wise harmonic analysis method. The results show that the model＇s accuracy matched well with the ESA＇s （European Space Agency） results by using the same data,展开更多
This study aimed to investigate the toxicity of rare earth ion yttrium under the stress of leaching agent ammonium sulfate （NH4）2SO4. [Method] By using earthworms as indicator organisms of environmental pol ution, a...This study aimed to investigate the toxicity of rare earth ion yttrium under the stress of leaching agent ammonium sulfate （NH4）2SO4. [Method] By using earthworms as indicator organisms of environmental pol ution, acute toxic ef-fects of rare earth yttrium on earthworms under the stress of ammonium sulfate were investigated with filter paper contact method. [Result] Under single stress of rare earth yttrium, the semi-lethal concentration after 48 and 24 h was LC50=213.41 mg/L and LC50=322.63 mg/L, respectively. ② Under single stress of ammonium sul-fate, the semi-lethal concentration after 48 h and 24 h was LC50=13.89 g/L and LC50=15.05 g/L, respectively. ③ In combined treatment of low concentration （10 g/L） of ammonium sulfate and different doses of rare earth yttrium, the semi-lethal con-centration after 48 and 24 h was LC50=198.65 g/L and LC50=399.85 g/L, respective-ly; in combined treatment of middle concentration （14 g/L） of ammonium sulfate and different doses of rare earth yttrium, the semi-lethal concentration after 48 and 24 h was LC50=167.3 mg/L and LC50=256.73 mg/L, respectively; in combined treatment of high concentration （20 g/L） of ammonium sulfate and different doses of rare earth yttrium, the semi-lethal concentration after 48 h and 24 h was LC50=31.03 mg/L and LC50=127.65 mg/L, respectively. [Conclusion] Low concentration of ammonium sulfate could reduce the toxicity of rare earth yttrium to earthworms and produce certain antagonism against rare earth yttrium; middle concentration ammonium sulfate in-creased the toxicity of rare earth yttrium to earthworms and produced relatively sig-nificant synergistic effects; high concentration ammonium sulfate significantly in-creased the toxicity of rare earth yttrium to earthworms. Compared with ammonium sulfate, dead earthworms exposed to rare earth yttrium were more easily fractured, and living earthworms showed insensitive response to acupuncture.展开更多
This paper proposes a hybrid feature selection sequence comple-mented with filter and wrapper concepts to improve the accuracy of Machine Learning(ML)based supervised classifiers for classifying the survivability of b...This paper proposes a hybrid feature selection sequence comple-mented with filter and wrapper concepts to improve the accuracy of Machine Learning(ML)based supervised classifiers for classifying the survivability of breast cancer patients into classes,living and deceased using METABRIC and Surveillance,Epidemiology and End Results(SEER)datasets.The ML-based classifiers used in the analysis are:Multiple Logistic Regression,K-Nearest Neighbors,Decision Tree,Random Forest,Support Vector Machine and Multilayer Perceptron.The workflow of the proposed ML algorithm sequence comprises the following stages:data cleaning,data balancing,feature selection via a filter and wrapper sequence,cross validation-based training,testing and performance evaluation.The results obtained are compared in terms of the following classification metrics:Accuracy,Precision,F1 score,True Positive Rate,True Negative Rate,False Positive Rate,False Negative Rate,Area under the Receiver Operating Characteristics curve,Area under the Precision-Recall curve and Mathews Correlation Coefficient.The comparison shows that the proposed feature selection sequence produces better results from all supervised classifiers than all other feature selection sequences considered in the analysis.展开更多
[ Objective] To explore the effects of different proportion of bee pollen on the water holding capacity of pork in Duroc Landrace x Yorkshire growing-finishing pigs in order to determine the optimal proportion. [ Met...[ Objective] To explore the effects of different proportion of bee pollen on the water holding capacity of pork in Duroc Landrace x Yorkshire growing-finishing pigs in order to determine the optimal proportion. [ Method] A total of 80 Duroc x Landrace x Yorkshire growing-finishing pigs, weighing （10.0 ± 1.0） kg, were randomly divided into five groups. The experimental period was 120 d including the 5-day pre-feecling period. The corn-soybean meal was not replaced during the whole period. All pigs had free access to feed and water. The pigs were fasting for 24 h but not prohibited from feed before the beginning. Group I was the control group reared with the diet not supplemented bee pollen. The pigs in group II, III ,IV and V were reared with the diet supplemented bee pollen at the concentration of 1%, 3%, 5% and 7%, respectively. After slaughtering, eye muscle was used for determination of water holding capacity through fast filter paper method, drip loss method, cooking loss method and Na- pole yield determination method. [ Resultl With the increase of the proportion of bee pollen, the water holding capacity of pork was first good and then poor. The addition of bee pollen at the concentration of 5% significantly reduced the drip loss of pork and the water holding capacity which was detected by fast filter paper method, but the cooking loss and Napole yield were not significantly influenced. [ Condmion] The bee pollen can effectively improve the water holding capacity of pork in Duroc x Landrace x Yorkshire growing-finishing pigs, and the optimal proportion is 5%.展开更多
In this paper we present a filter-successive linearization method with trust region for solutions of nonlinear semidefinite programming. Such a method is based on the concept of filter for nonlinear programming introd...In this paper we present a filter-successive linearization method with trust region for solutions of nonlinear semidefinite programming. Such a method is based on the concept of filter for nonlinear programming introduced by Fletcher and Leyffer in 2002. We describe the new algorithm and prove its global convergence under weaker assumptions. Some numerical results are reported and show that the new method is potentially efficient.展开更多
Aiming to deficiency of the filter and wrapper feature selection methods, anew method based on composite method of filter and wrapper method is proposed. First the methodfilters original features to form a feature sub...Aiming to deficiency of the filter and wrapper feature selection methods, anew method based on composite method of filter and wrapper method is proposed. First the methodfilters original features to form a feature subset which can meet classification correctness rate,then applies wrapper feature selection method select optimal feature subset. A successful techniquefor solving optimization problems is given by genetic algorithm (GA). GA is applied to the problemof optimal feature selection. The composite method saves computing time several times of the wrappermethod with holding the classification accuracy in data simulation and experiment on bearing faultfeature selection. So this method possesses excellent optimization property, can save more selectiontime, and has the characteristics of high accuracy and high efficiency.展开更多
In order to choose the appropriate reference surface on the machined surface roughness of Si Cp/Al composites, the cutting experiments of Si Cp/Al composites were carried out, and the machined surface topography was m...In order to choose the appropriate reference surface on the machined surface roughness of Si Cp/Al composites, the cutting experiments of Si Cp/Al composites were carried out, and the machined surface topography was measured by OLS3000 Confocal laser scanning microscope. The 3D measured data of machined surface topography were analyzed by the area power spectrum density. The result shows that the texture of machined surface topography in milling of Si Cp/Al composites is almost isotropic. This is the reason that the values of Rq at different locations on the same machined surface are obviously different. Through the comparison of performance of different filtering methods, the robust least squares reference surface can be used to extract the surface roughness of SiC p/Al composites effectively.展开更多
Airframe maintenance is traditionally performed at scheduled maintenance stops.The decision to repair a fuselage panel is based on a fixed crack size threshold,which allows to ensure the aircraft safety until the next...Airframe maintenance is traditionally performed at scheduled maintenance stops.The decision to repair a fuselage panel is based on a fixed crack size threshold,which allows to ensure the aircraft safety until the next scheduled maintenance stop.With progress in sensor technology and data processing techniques,structural health monitoring（SHM） systems are increasingly being considered in the aviation industry.SHM systems track the aircraft health state continuously,leading to the possibility of planning maintenance based on an actual state of aircraft rather than on a fixed schedule.This paper builds upon a model-based prognostics framework that the authors developed in their previous work,which couples the Extended Kalman filter（EKF） with a firstorder perturbation（FOP） method.By using the information given by this prognostics method,a novel cost driven predictive maintenance（CDPM） policy is proposed,which ensures the aircraft safety while minimizing the maintenance cost.The proposed policy is formally derived based on the trade-off between probabilities of occurrence of scheduled and unscheduled maintenance.A numerical case study simulating the maintenance process of an entire fleet of aircrafts is implemented.Under the condition of assuring the same safety level,the CDPM is compared in terms of cost with two other maintenance policies：scheduled maintenance and threshold based SHM maintenance.The comparison results show CDPM could lead to significant cost savings.展开更多
Detection and tracking of multi-target with unknown and varying number is a challenging issue, especially under the condition of low signal-to-noise ratio(SNR). A modified multi-target track-before-detect(TBD) method ...Detection and tracking of multi-target with unknown and varying number is a challenging issue, especially under the condition of low signal-to-noise ratio(SNR). A modified multi-target track-before-detect(TBD) method was proposed to tackle this issue using a nonstandard point observation model. The method was developed from sequential Monte Carlo(SMC)-based probability hypothesis density(PHD) filter, and it was implemented by modifying the original calculation in update weights of the particles and by adopting an adaptive particle sampling strategy. To efficiently execute the SMC-PHD based TBD method, a fast implementation approach was also presented by partitioning the particles into multiple subsets according to their position coordinates in 2D resolution cells of the sensor. Simulation results show the effectiveness of the proposed method for time-varying multi-target tracking using raw observation data.展开更多
基金Supported partially by Chinese NNSF grants 19731010the knowledge innovation program of CAS.
文摘In a composite-step approach, a step Sk is computed as the sum of two components Uk and hk. The normal component Vk, which is called the vertical step, aims to improve the linearized feasibility, while the tangential component hk, which is also called horizontal step, concentrates on reducing a model of the merit functions. As a filter method, it reduces both the infeasibility and the objective function. This is the same property of these two methods. In this paper, one concerns the composite-step like filter approach. That is, a step is tangential component hk if the infeasibility is reduced. Or else, Sk is a composite step composed of normal component Uk, and tangential component hk.
基金This work is funded by the National Natural Science Foundation of China(Grant Nos.42377164 and 52079062)the National Science Fund for Distinguished Young Scholars of China(Grant No.52222905).
文摘In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.
文摘A temperature forecasting model was created firstly based on the Kalman filter method,and then used to predict the highest and lowest temperature in Nanchang station from October 27 to November 1,2017.Finally,according to the empirical forecasting method,guidance forecasts were established for the northern,central,and southern parts of Nanchang City.After inspection,it was found that the temperature prediction model established based on the Kalman filter method in Nanchang station had good prediction performance,and especially in the 24-hour forecast,it had advantages over the European Center.The accuracy of low temperature forecast was better than that of high temperature forecast.
文摘The sinusoid curve fit is widely applied in the evaluation of digitized measurement equipment, such as data acquisition system, digital storage oscilloscope, waveform recorder and A/D converter,etc. Because of the distortion and noise of sinusoid signal generator, the digitizing and the non linearity errors in measurement, it is impossible to avoid the distortion and the noise in sinusoid sampling series. The distortion and the noise limit the accuracy of curve fit results. Therefore, it is desirable to find a filter that can filter out both distortion and noise of the sinusoid sampling series, and in the meantime, the filter doesn′t influence the amplitude, the frequency, the phase and DC bias of fitting curve of the sine wave. And then, the uncertainty of fitting parameter can be reduced. This filter is designed and realized. Its realization in time domain is described and its transfer function in frequency domain is presented.
文摘In this paper,we present a modeling of the soil-water characteristic curve for residual and sedimentary soils of Bom Brinquedo Hill’s,located in Antonina,Brazil.This mountain range region is characterized as a natural disaster risk area,requiring continuous research related to the stability of the area.To obtain the soil-water characteristic curve,undisturbed samples of residual and sedimentary soil were collected,followed by suction testing using the filter paper method.Considering the bimodal characteristic presented by the soil,LABFIT software was employed for curve fitting using the generic formulation“Harris+C”.The results of the tests indicated that the phenomenon of hysteresis had a greater influence in situations with higher suction levels.When comparing the residual moisture values of the macropores between residual soil and sedimentary soil,the former exhibited the lower value.This suggests that the residual soil has a coarser grain size and larger pores,which facilitates the release of water retained in the soil’s macropores.
基金financially supported by National Natural Science Foundation of China(No.U22B2094)。
文摘An optical emission spectroscopy(OES)method with a non-invasive measurement capability,without inducing disturbance to the discharge,represents an effective method for material monitoring.However,when the OES method is employed to monitor the trace erosion product within the ceramic channel of a Hall thruster,it becomes challenging to distinguish between signal and noise.In this study,we propose a model filtering method based on the signal characteristics of the Hall thruster plume spectrometer.This method integrates the slit imaging and spectral resolution features of the spectrometer.Employing this method,we extract the spectral signals of the erosion product and working gas from the Hall thruster under different operating conditions.The results indicate that our new method performs comparably to the traditional method without model filtering when extracting atom signals from strong xenon working gas.However,for trace amounts of the erosion product,our approach significantly enhances the signal-to-noise ratio(SNR),enabling the identification of extremely weak spectral signals even under low mass flow rate and low-voltage conditions.We obtain boron atom concentration of 3.91×10^(-3) kg/m^(3) at a mass flow rate of 4×10^(-7) kg/s and voltage of 200 V while monitoring a wider range of thruster operating conditions.The new method proposed in this study is suitable for monitoring other low-concentration elements,making it valuable for materials processing,environmental monitoring and space propulsion applications.
基金supported by the National Natural Science Foundation of China(61772196,61472136)the Hunan Provincial Focus Social Science Fund(2016ZDB006)+2 种基金Hunan Provincial Social Science Achievement Review Committee results appraisal identification project(Xiang social assessment 2016JD05)Key Project of Hunan Provincial Social Science Achievement Review Committee(XSP 19ZD1005)the financial support provided by the Key Laboratory of Hunan Province for New Retail Virtual Reality Technology(2017TP1026).
文摘Aiming at the problem that the traditional collaborative filtering recommendation algorithm does not fully consider the influence of correlation between projects on recommendation accuracy,this paper introduces project attribute fuzzy matrix,measures the project relevance through fuzzy clustering method,and classifies all project attributes.Then,the weight of the project relevance is introduced in the user similarity calculation,so that the nearest neighbor search is more accurate.In the prediction scoring section,considering the change of user interest with time,it is proposed to use the time weighting function to improve the influence of the time effect of the evaluation,so that the newer evaluation information in the system has a relatively large weight.The experimental results show that the improved algorithm improves the recommendation accuracy and improves the recommendation quality.
基金Supported by CERG: CityU 101005 of the Government of Hong Kong SAR, Chinathe National Natural ScienceFoundation of China, the Specialized Research Fund of Doctoral Program of Higher Education of China (Grant No.20040319003)the Natural Science Fund of Jiangsu Province of China (Grant No. BK2006214)
文摘In this paper we present a filter-trust-region algorithm for solving LC1 unconstrained optimization problems which uses the second Dini upper directional derivative. We establish the global convergence of the algorithm under reasonable assumptions.
基金Key Fostering Project of National Space Science Center,Chinese Academy of Sciences(Y62112f37s)National 863 Project of China(2015AA8126027)
文摘For Microwave Humidity and Temperature sounder(MWHTS) measurements over the ocean, a cloud filtering method is presented to filter out cloud-and precipitation-affected observations by analyzing the sensitivity of the simulated brightness temperatures of MWHTS to cloud liquid water, and using the root mean square error(RMSE)between observation and simulation in clear sky as a reference standard. The atmospheric temperature and humidity profiles are retrieved using MWHTS measurements with and without filtering by multiple linear regression(MLR),artificial neural networks(ANN) and one-dimensional variational(1DVAR) retrieval methods, respectively, and the effects of the filtering method on the retrieval accuracies are analyzed. The numerical results show that the filtering method can improve the retrieval accuracies of the MLR and the 1DVAR retrieval methods, but have little influence on that of the ANN. In addition, the dependencies of the retrieval methods upon the testing samples of brightness temperature are studied, and the results show that the 1DVAR retrieval method has great stability due to that the testing samples have great impact on the retrieval accuracies of the MLR and the ANN, but have little impact on that of the 1DVAR.
文摘Few study gives guidance to design weighting filters according to the frequency weighting factors,and the additional evaluation method of automotive ride comfort is not made good use of in some countries.Based on the regularities of the weighting factors,a method is proposed and the vertical and horizontal weighting filters are developed.The whole frequency range is divided several times into two parts with respective regularity.For each division,a parallel filter constituted by a low-and a high-pass filter with the same cutoff frequency and the quality factor is utilized to achieve section factors.The cascading of these parallel filters obtains entire factors.These filters own a high order.But,low order filters are preferred in some applications.The bilinear transformation method and the least P-norm optimal infinite impulse response（IIR） filter design method are employed to develop low order filters to approximate the weightings in the standard.In addition,with the window method,the linear phase finite impulse response（FIR） filter is designed to keep the signal from distorting and to obtain the staircase weighting.For the same case,the traditional method produces 0.330 7 m · s^–2 weighted root mean square（r.m.s.） acceleration and the filtering method gives 0.311 9 m · s^–2 r.m.s.The fourth order filter for approximation of vertical weighting obtains 0.313 9 m · s^–2 r.m.s.Crest factors of the acceleration signal weighted by the weighting filter and the fourth order filter are 3.002 7 and 3.011 1,respectively.This paper proposes several methods to design frequency weighting filters for automotive ride comfort evaluation,and these developed weighting filters are effective.
基金sponsored by the major science and technology special topic of CNPC(No.2013E-38-08)
文摘Conventional frequency domain method used in random noise attenuation singular value decomposition （SVD） filtering processing causes bending event damage. To mitigate this problem, we present a mixed Cadzow filtering method based on fractional Fourier transform to suppress random noise in 3D seismic data. First, the seismic data is transformed to the time-frequency plane via the fractional Fourier transform. Second, based on the Eigenimage filtering method and Cadzow filtering method, the mixed high-dimensional Hankel matrix is built; then, SVD is performed. Finally, random noise is eliminated effectively by reducing the rank of the matrix. The theoretical model and real applications of the mixed filtering method in a region of Sichuan show that our method can not only suppress noise effectively but also preserve the frequency and phase of effective signals quite well and significantly improve the signal-to-noise ratio of 3D post-stack seismic data.
基金supported by the National Natural Science Foundation of China(41404020)
文摘How to deal with colored noises of GOCE （Gravity field and steady - state Ocean Circulation Explorer） satellite has been the key to data processing. This paper focused on colored noises of GOCE gradient data and the frequency spectrum analysis. According to the analysis results, gravity field model of the optima] degrees 90-240 is given, which is recovered by COCE gradient data. This paper presents an iterative Wiener filtering method based on the gravity gradient invariants. By this method a degree-220 model was calculated from GOCE SGG （Satellite Gravity Gradient） data. The degrees above 90 of ITG2010 were taken as the prior gravity field model, replacing the low degree gravity field model calculated by GOCE orbit data. GOCE gradient colored noises was processed by Wiener filtering. Finally by Wiener filtering iterative calculation, the gravity field model was restored by space-wise harmonic analysis method. The results show that the model＇s accuracy matched well with the ESA＇s （European Space Agency） results by using the same data,
基金Supported by National Natural Science Foundation of China(Grant No.21067003,51364015)National High-Tech Research and Development Program of China(GrantNo.2012BAC11B07)+1 种基金Natural Science Foundation of Jiangxi Province(Grant No.20114BAB203024)Science and Technology Project of the Education Department ofJiangxi Province~~
文摘This study aimed to investigate the toxicity of rare earth ion yttrium under the stress of leaching agent ammonium sulfate （NH4）2SO4. [Method] By using earthworms as indicator organisms of environmental pol ution, acute toxic ef-fects of rare earth yttrium on earthworms under the stress of ammonium sulfate were investigated with filter paper contact method. [Result] Under single stress of rare earth yttrium, the semi-lethal concentration after 48 and 24 h was LC50=213.41 mg/L and LC50=322.63 mg/L, respectively. ② Under single stress of ammonium sul-fate, the semi-lethal concentration after 48 h and 24 h was LC50=13.89 g/L and LC50=15.05 g/L, respectively. ③ In combined treatment of low concentration （10 g/L） of ammonium sulfate and different doses of rare earth yttrium, the semi-lethal con-centration after 48 and 24 h was LC50=198.65 g/L and LC50=399.85 g/L, respective-ly; in combined treatment of middle concentration （14 g/L） of ammonium sulfate and different doses of rare earth yttrium, the semi-lethal concentration after 48 and 24 h was LC50=167.3 mg/L and LC50=256.73 mg/L, respectively; in combined treatment of high concentration （20 g/L） of ammonium sulfate and different doses of rare earth yttrium, the semi-lethal concentration after 48 h and 24 h was LC50=31.03 mg/L and LC50=127.65 mg/L, respectively. [Conclusion] Low concentration of ammonium sulfate could reduce the toxicity of rare earth yttrium to earthworms and produce certain antagonism against rare earth yttrium; middle concentration ammonium sulfate in-creased the toxicity of rare earth yttrium to earthworms and produced relatively sig-nificant synergistic effects; high concentration ammonium sulfate significantly in-creased the toxicity of rare earth yttrium to earthworms. Compared with ammonium sulfate, dead earthworms exposed to rare earth yttrium were more easily fractured, and living earthworms showed insensitive response to acupuncture.
文摘This paper proposes a hybrid feature selection sequence comple-mented with filter and wrapper concepts to improve the accuracy of Machine Learning(ML)based supervised classifiers for classifying the survivability of breast cancer patients into classes,living and deceased using METABRIC and Surveillance,Epidemiology and End Results(SEER)datasets.The ML-based classifiers used in the analysis are:Multiple Logistic Regression,K-Nearest Neighbors,Decision Tree,Random Forest,Support Vector Machine and Multilayer Perceptron.The workflow of the proposed ML algorithm sequence comprises the following stages:data cleaning,data balancing,feature selection via a filter and wrapper sequence,cross validation-based training,testing and performance evaluation.The results obtained are compared in terms of the following classification metrics:Accuracy,Precision,F1 score,True Positive Rate,True Negative Rate,False Positive Rate,False Negative Rate,Area under the Receiver Operating Characteristics curve,Area under the Precision-Recall curve and Mathews Correlation Coefficient.The comparison shows that the proposed feature selection sequence produces better results from all supervised classifiers than all other feature selection sequences considered in the analysis.
文摘[ Objective] To explore the effects of different proportion of bee pollen on the water holding capacity of pork in Duroc Landrace x Yorkshire growing-finishing pigs in order to determine the optimal proportion. [ Method] A total of 80 Duroc x Landrace x Yorkshire growing-finishing pigs, weighing （10.0 ± 1.0） kg, were randomly divided into five groups. The experimental period was 120 d including the 5-day pre-feecling period. The corn-soybean meal was not replaced during the whole period. All pigs had free access to feed and water. The pigs were fasting for 24 h but not prohibited from feed before the beginning. Group I was the control group reared with the diet not supplemented bee pollen. The pigs in group II, III ,IV and V were reared with the diet supplemented bee pollen at the concentration of 1%, 3%, 5% and 7%, respectively. After slaughtering, eye muscle was used for determination of water holding capacity through fast filter paper method, drip loss method, cooking loss method and Na- pole yield determination method. [ Resultl With the increase of the proportion of bee pollen, the water holding capacity of pork was first good and then poor. The addition of bee pollen at the concentration of 5% significantly reduced the drip loss of pork and the water holding capacity which was detected by fast filter paper method, but the cooking loss and Napole yield were not significantly influenced. [ Condmion] The bee pollen can effectively improve the water holding capacity of pork in Duroc x Landrace x Yorkshire growing-finishing pigs, and the optimal proportion is 5%.
基金supported by National Natural Science Foundation of China (Grant No. 10871098)Science Foundation of Jiangsu Province (Grant No. BK2006214)
文摘In this paper we present a filter-successive linearization method with trust region for solutions of nonlinear semidefinite programming. Such a method is based on the concept of filter for nonlinear programming introduced by Fletcher and Leyffer in 2002. We describe the new algorithm and prove its global convergence under weaker assumptions. Some numerical results are reported and show that the new method is potentially efficient.
基金This project is supported by Scientific Research Foundation of National Defence of China (No.41319040202).
文摘Aiming to deficiency of the filter and wrapper feature selection methods, anew method based on composite method of filter and wrapper method is proposed. First the methodfilters original features to form a feature subset which can meet classification correctness rate,then applies wrapper feature selection method select optimal feature subset. A successful techniquefor solving optimization problems is given by genetic algorithm (GA). GA is applied to the problemof optimal feature selection. The composite method saves computing time several times of the wrappermethod with holding the classification accuracy in data simulation and experiment on bearing faultfeature selection. So this method possesses excellent optimization property, can save more selectiontime, and has the characteristics of high accuracy and high efficiency.
基金Projects(51305284,61203208) supported by the National Natural Science Foundation of China
文摘In order to choose the appropriate reference surface on the machined surface roughness of Si Cp/Al composites, the cutting experiments of Si Cp/Al composites were carried out, and the machined surface topography was measured by OLS3000 Confocal laser scanning microscope. The 3D measured data of machined surface topography were analyzed by the area power spectrum density. The result shows that the texture of machined surface topography in milling of Si Cp/Al composites is almost isotropic. This is the reason that the values of Rq at different locations on the same machined surface are obviously different. Through the comparison of performance of different filtering methods, the robust least squares reference surface can be used to extract the surface roughness of SiC p/Al composites effectively.
基金supported by UT-INSA Program(2013)the support of the China Scholarship Council(CSC)
文摘Airframe maintenance is traditionally performed at scheduled maintenance stops.The decision to repair a fuselage panel is based on a fixed crack size threshold,which allows to ensure the aircraft safety until the next scheduled maintenance stop.With progress in sensor technology and data processing techniques,structural health monitoring（SHM） systems are increasingly being considered in the aviation industry.SHM systems track the aircraft health state continuously,leading to the possibility of planning maintenance based on an actual state of aircraft rather than on a fixed schedule.This paper builds upon a model-based prognostics framework that the authors developed in their previous work,which couples the Extended Kalman filter（EKF） with a firstorder perturbation（FOP） method.By using the information given by this prognostics method,a novel cost driven predictive maintenance（CDPM） policy is proposed,which ensures the aircraft safety while minimizing the maintenance cost.The proposed policy is formally derived based on the trade-off between probabilities of occurrence of scheduled and unscheduled maintenance.A numerical case study simulating the maintenance process of an entire fleet of aircrafts is implemented.Under the condition of assuring the same safety level,the CDPM is compared in terms of cost with two other maintenance policies：scheduled maintenance and threshold based SHM maintenance.The comparison results show CDPM could lead to significant cost savings.
基金Projects(61002022,61471370)supported by the National Natural Science Foundation of China
文摘Detection and tracking of multi-target with unknown and varying number is a challenging issue, especially under the condition of low signal-to-noise ratio(SNR). A modified multi-target track-before-detect(TBD) method was proposed to tackle this issue using a nonstandard point observation model. The method was developed from sequential Monte Carlo(SMC)-based probability hypothesis density(PHD) filter, and it was implemented by modifying the original calculation in update weights of the particles and by adopting an adaptive particle sampling strategy. To efficiently execute the SMC-PHD based TBD method, a fast implementation approach was also presented by partitioning the particles into multiple subsets according to their position coordinates in 2D resolution cells of the sensor. Simulation results show the effectiveness of the proposed method for time-varying multi-target tracking using raw observation data.
