This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi...This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi analytical solutions of temperature increment and displacement of multi-layered composite structures are obtained by using the Laplace transform method,upon which the effects of thermal resistance coefficient,partition coefficient,thermal conductivity ratio and heat capacity ratio on the responses are studied.The results show that the generalized imperfect thermal contact model can realistically describe the imperfect thermal contact problem.Accordingly,it may degenerate into other thermal contact models by adjusting the thermal resistance coefficient and partition coefficient.展开更多
Stab-resistant textiles play a critical role in personal protection,necessitating a deeper understanding of how structural and layering factors influence their performance.The current study experimentally examines the...Stab-resistant textiles play a critical role in personal protection,necessitating a deeper understanding of how structural and layering factors influence their performance.The current study experimentally examines the effects of textile structure,layering,and ply orientation on the stab resistance of multi-layer textiles.Three 3D warp interlock(3DWI)structures({f1},{f2},{f3})and a 2D woven fabric({f4}),all made of high-performance p-aramid yarns,were engineered and manufactured.Multi-layer specimens were prepared and subjected to drop-weight stabbing tests following HOSBD standards.Stabbing performance metrics,including Depth of Trauma(DoT),Depth of Penetration(DoP),and trauma deformation(Ymax,Xmax),were investigated and analyzed.Statistical analyses(Two-and One-Way ANOVA)indicated that fabric type and layer number significantly impacted DoP(P<0.05),while ply orientation significantly affected DoP(P<0.05)but not DoT(P>0.05).Further detailed analysis revealed that 2D woven fabrics exhibited greater trauma deformation than 3D WIF structures.Increasing the number of layers reduced both DoP and DoT across all fabric structures,with f3 demonstrating the best performance in multi-layer configurations.Aligned ply orientations also enhanced stab resistance,underscoring the importance of alignment in dissipating impact energy.展开更多
Considering that real communication signals corrupted by noise are generally nonstationary, and timefrequency distributions are especially suitable for the analysis of nonstationary signals, time-frequency distributio...Considering that real communication signals corrupted by noise are generally nonstationary, and timefrequency distributions are especially suitable for the analysis of nonstationary signals, time-frequency distributions are introduced for the modulation classification of communication signals： The extracted time-frequency features have good classification information, and they are insensitive to signal to noise ratio （SNR） variation. According to good classification by the correct rate of a neural network classifier, a multilayer perceptron （MLP） classifier with better generalization, as well as, addition of time-frequency features set for classifying six different modulation types has been proposed. Computer simulations show that the MLP classifier outperforms the decision-theoretic classifier at low SNRs, and the classification experiments for real MPSK signals verify engineering significance of the MLP classifier.展开更多
To improve the performance of multiple classifier system, a knowledge discovery based dynamic weighted voting （KD-DWV） is proposed based on knowledge discovery. In the method, all base classifiers may be allowed to ...To improve the performance of multiple classifier system, a knowledge discovery based dynamic weighted voting （KD-DWV） is proposed based on knowledge discovery. In the method, all base classifiers may be allowed to operate in different measurement/feature spaces to make the most of diverse classification information. The weights assigned to each output of a base classifier are estimated by the separability of training sample sets in relevant feature space. For this purpose, some decision tables （DTs） are established in terms of the diverse feature sets. And then the uncertainty measures of the separability are induced, in the form of mass functions in Dempster-Shafer theory （DST）, from each DTs based on generalized rough set model. From the mass functions, all the weights are calculated by a modified heuristic fusion function and assigned dynamically to each classifier varying with its output. The comparison experiment is performed on the hyperspectral remote sensing images. And the experimental results show that the performance of the classification can be improved by using the proposed method compared with the plurality voting （PV）.展开更多
Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with ...Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with the nearest neighbor classifier (NNC) is proposed. The principal component analysis (PCA) is used to reduce the dimension and extract features. Then one-against-all stratedy is used to train the SVM classifiers. At the testing stage, we propose an al-展开更多
Three different kinds of PELE(the penetrator with lateral efficiency) were launched by ballistic artillery to impact the multi-layer spaced metal target plates.The lmpact velocities of the projectiles were measured by...Three different kinds of PELE(the penetrator with lateral efficiency) were launched by ballistic artillery to impact the multi-layer spaced metal target plates.The lmpact velocities of the projectiles were measured by the velocity measuring system.The damage degree and process of each laye r of target plate impacted by the three kinds of projectiles were analyzed.The experimental results show that all the three kinds of projectiles have the effect of expanding holes on the multi-layer spaced metal target plates.For the normal structure PELE(without layered) with tungsten alloy jacket and the radial layered PELE with tungsten alloy jacket,the diameters of holes on the seco nd layer of plates are 3.36 times and 3.76 times of the diameter of the projectile,re spectively.For radial layered PELE with W/Zr-based amorphous composite jacket,due to the large number of tungsten wires dispersed after the impact,the diameter of the holes on the four-layer spaced plates can reach 2.4 times,3.04 times,5.36 times and 2.68 times of the diameter of the projectile.Besides,the normal structure PELE with tungsten alloy jacket and the radial layered PELE whit tungsten alloy jacket formed a large number of fragments impact marks on the third target plate.Although the number of fragments penetrating the third target plate is not as large as that of the normal structure PELE,the area of dispersion of fragments impact craters on the third target plate is larger by the radial layered PELE.The radial layered PELE with W/Zr-based amorphous composite jacket released a lot of heat energy due to the impact of the matrix material,and formed a large area of ablation marks on the last three target plates.展开更多
High intensity focused ultrasound(HIFU)therapy is an effective method in clinical treatment of tumors,in order to explore the bio-heat conduction mechanism of in multi-layer media by concave spherical transducer,tempe...High intensity focused ultrasound(HIFU)therapy is an effective method in clinical treatment of tumors,in order to explore the bio-heat conduction mechanism of in multi-layer media by concave spherical transducer,temperature field induced by this kind of transducer in multi-layer media will be simulated through solving Pennes equation with finite difference method,and the influence of initial sound pressure,absorption coefficient,and thickness of different layers of biological tissue as well as thermal conductivity parameter on sound focus and temperature distribution will be analyzed,respectively.The results show that the temperature in focus area increases faster while the initial sound pressure and thermal conductivity increase.The absorption coefficient is smaller,the ultrasound intensity in the focus area is bigger,and the size of the focus area is increasing.When the thicknesses of different layers of tissue change,the focus position changes slightly,but the sound intensity of the focus area will change obviously.The temperature in focus area will rise quickly before reaching a threshold,and then the temperature will keep in the threshold range.展开更多
Asphalt mixture pavement reheating is one of the important steps in hot in-place recycling(HIR).To improve the heating speed of asphalt pavement in HIR,based on the numerical analysis model of asphalt mixture heating ...Asphalt mixture pavement reheating is one of the important steps in hot in-place recycling(HIR).To improve the heating speed of asphalt pavement in HIR,based on the numerical analysis model of asphalt mixture heating process,a new multi-layer low-temperature heating method(MLHM)was proposed.Considering input heat flux,the thermal capacity and thermal resistance of asphalt mixture,the heat transfer model was established based on energy conservation law.By heating the asphalt mixture in layers,it changes the situation that the heat energy can only be input from the upper surface of the asphalt mixture pavement.Through the simulation of the heating method of asphalt mixture in the existing technology,the result shows that the existing heating methods lead to serious aging or charring of the asphalt mixture.By MLHM,the upper and the bottom of the asphalt mixture are heated at the same time,and the heating temperature is lower than other heat methods,which not only reduces the heating thickness and increases the heating area of the asphalt mixture pavement,but also improves the heating speed,saves the energy resource and ensures the heating quality.Especially,by MLHM,the heating uniformity is better and speed is faster.展开更多
Support vector classifier （SVC） has the superior advantages for small sample learning problems with high dimensions, with especially better generalization ability. However there is some redundancy among the high dim...Support vector classifier （SVC） has the superior advantages for small sample learning problems with high dimensions, with especially better generalization ability. However there is some redundancy among the high dimensions of the original samples and the main features of the samples may be picked up first to improve the performance of SVC. A principal component analysis （PCA） is employed to reduce the feature dimensions of the original samples and the pre-selected main features efficiently, and an SVC is constructed in the selected feature space to improve the learning speed and identification rate of SVC. Furthermore, a heuristic genetic algorithm-based automatic model selection is proposed to determine the hyperparameters of SVC to evaluate the performance of the learning machines. Experiments performed on the Heart and Adult benchmark data sets demonstrate that the proposed PCA-based SVC not only reduces the test time drastically, but also improves the identify rates effectively.展开更多
In this work,the reflux classifier with closely spaced inclined channels is used as the pre-concentration facility to improve the separation efficiency before the shaking table separation.Three operating parameters of...In this work,the reflux classifier with closely spaced inclined channels is used as the pre-concentration facility to improve the separation efficiency before the shaking table separation.Three operating parameters of reflux classifier(RC)to pre-concentrate fine(0.023−0.15 mm)tailings of antimony oxide were optimized by response surface methodology(RSM)using a three-level Box-Behnken design(BBD).The parameters studied for the optimization were feeding speed,underflow,and ascending water speed.Second-order response functions were produced for the Sb grade and recovery rate of the concentrate.Taking advantage of the quadratic programming,when the factors of feeding,underflow and ascending water are respectively 225,30 and 133 cm^3/min,a better result can be achieved for the concentrate grade of 2.31% and recovery rate of 83.17%.At the same time,70.48% of the tailings with the grade of 0.20% were discarded out of the feeding.The results indicated that the reflux classifier has a good performance in dealing with fine tailings of antimony oxide.Moreover,second-order polynomial equations,ANOVA,and three-dimensional surface plots were developed to evaluate the effects of each parameter on Sb grade and recovery rate of the concentrate.展开更多
Automatic modulation classification is the process of identification of the modulation type of a signal in a general environment. This paper proposes a new method to evaluate the tracking performance of large margin c...Automatic modulation classification is the process of identification of the modulation type of a signal in a general environment. This paper proposes a new method to evaluate the tracking performance of large margin classifier against signal-tonoise ratio （SNR）, and classifies all forms of primary user＇s signals in a cognitive radio environment. For achieving this objective, two structures of a large margin are developed in additive white Gaussian noise （AWGN） channels with priori unknown SNR. A combination of higher order statistics and instantaneous characteristics is selected as effective features. Simulation results show that the classification rates of the proposed structures are well robust against environmental SNR changes.展开更多
This paper considers the problem of target and jamming recognition for the pulse Doppler radar fuze(PDRF).To solve the problem,the matched filter outputs of the PDRF under the action of target and jamming are analyzed...This paper considers the problem of target and jamming recognition for the pulse Doppler radar fuze(PDRF).To solve the problem,the matched filter outputs of the PDRF under the action of target and jamming are analyzed.Then,the frequency entropy and peak-to-peak ratio are extracted from the matched filter output of the PDRF,and the time-frequency joint feature is constructed.Based on the time-frequency joint feature,the naive Bayesian classifier(NBC)with minimal risk is established for target and jamming recognition.To improve the adaptability of the proposed method in complex environments,an online update process that adaptively modifies the classifier in the duration of the work of the PDRF is proposed.The experiments show that the PDRF can maintain high recognition accuracy when the signal-to-noise ratio(SNR)decreases and the jamming-to-signal ratio(JSR)increases.Moreover,the applicable analysis shows that he ONBCMR method has low computational complexity and can fully meet the real-time requirements of PDRF.展开更多
Under the scenario of dense targets in clutter, a multi-layer optimal data correlation algorithm is proposed. This algorithm eliminates a large number of false location points from the assignment process by rough corr...Under the scenario of dense targets in clutter, a multi-layer optimal data correlation algorithm is proposed. This algorithm eliminates a large number of false location points from the assignment process by rough correlations before we calculate the correlation cost, so it avoids the operations for the target state estimate and the calculation of the correlation cost for the false correlation sets. In the meantime, with the elimination of these points in the rough correlation, the disturbance from the false correlations in the assignment process is decreased, so the data correlation accuracy is improved correspondingly. Complexity analyses of the new multi-layer optimal algorithm and the traditional optimal assignment algorithm are given. Simulation results show that the new algorithm is feasible and effective.展开更多
Sentiment analysis is the computational study of how opinions, attitudes, emotions, and perspectives are expressed in language, and has been the important task of natural language processing. Sentiment analysis is hig...Sentiment analysis is the computational study of how opinions, attitudes, emotions, and perspectives are expressed in language, and has been the important task of natural language processing. Sentiment analysis is highly valuable for both research and practical applications. The focuses were put on the difficulties in the construction of sentiment classifiers which normally need tremendous labeled domain training data, and a novel unsupervised framework was proposed to make use of the Chinese idiom resources to develop a general sentiment classifier. Furthermore, the domain adaption of general sentiment classifier was improved by taking the general classifier as the base of a self-training procedure to get a domain self-training sentiment classifier. To validate the effect of the unsupervised framework, several experiments were carried out on publicly available Chinese online reviews dataset. The experiments show that the proposed framework is effective and achieves encouraging results. Specifically, the general classifier outperforms two baselines(a Na?ve 50% baseline and a cross-domain classifier), and the bootstrapping self-training classifier approximates the upper bound domain-specific classifier with the lowest accuracy of 81.5%, but the performance is more stable and the framework needs no labeled training dataset.展开更多
Considering the fact that in some complex cases,plate anchors are buried in multi-layered geotechnical materials,the ultimate dynamic analysis was performed to investigate the uplift capacity and failure mechanism of ...Considering the fact that in some complex cases,plate anchors are buried in multi-layered geotechnical materials,the ultimate dynamic analysis was performed to investigate the uplift capacity and failure mechanism of shallow strips and circular plate anchors in multi-layered soils.The nonlinear strength criterion and non-associated flow rule of geotechnical materials were introduced to investigate the influence of nonuniformity on the pullout performance and failure mechanism of shallow plate anchors.The expressions of the detaching curves or surfaces were obtained to reflect the failure mechanism,which can be used to figure out the ultimate uplift capacity and failure range.The results are generally in agreement with the numerical simulations and previous research.The effects of various parameters on the ultimate uplift capacity and failure mechanism of plate anchors in multi-layered soils were investigated,and it is found that the ultimate uplift capacity and failure range of shallow anchors increase with the increase of initial cohesion and dilatancy coefficient,but decrease with the unit weight,axial tensile stress and nonlinear coefficient.展开更多
This article investigates the characteristics of shock wave overpressure generated by multi-layer composite charge under different detonation modes.Combining dimensional analysis and the explosion mechanism of the cha...This article investigates the characteristics of shock wave overpressure generated by multi-layer composite charge under different detonation modes.Combining dimensional analysis and the explosion mechanism of the charge,a peak overpressure prediction model for the composite charge under singlepoint detonation and simultaneous detonation was established.The effects of the charge structure and initiation method on the overpressure field characteristics were investigated in AUTODYN simulation.The accuracy of the prediction model and the reliability of the numerical simulation method were subsequently verified in a series of static explosion experiments.The results reveal that the mass of the inner charge was the key factor determining the peak overpressure of the composite charge under single-point detonation.The peak overpressure in the radial direction improved apparently with an increase in the aspect ratio of the charge.The overpressure curves in the axial direction exhibited a multi-peak phenomenon,and the secondary peak overpressure even exceeded the primary peak at distances of 30D and 40D(where D is the charge diameter).The difference in peak overpressure among azimuth angles of 0-90°gradually decreased with an increase in the propagation distance of the shock wave.The coupled effect of the detonation energy of the inner and outer charge under simultaneous detonation improved the overpressure in both radial and axial directions.The difference in peak overpressure obtained from model prediction and experimental measurements was less than 16.4%.展开更多
基金Projects(42477162,52108347,52178371,52168046,52178321,52308383)supported by the National Natural Science Foundation of ChinaProjects(2023C03143,2022C01099,2024C01219,2022C03151)supported by the Zhejiang Key Research and Development Plan,China+6 种基金Project(LQ22E080010)supported by the Exploring Youth Project of Zhejiang Natural Science Foundation,ChinaProject(LR21E080005)supported by the Outstanding Youth Project of Natural Science Foundation of Zhejiang Province,ChinaProject(2022M712964)supported by the Postdoctoral Science Foundation of ChinaProject(2023AFB008)supported by the Natural Science Foundation of Hubei Province for Youth,ChinaProject(202203)supported by Engineering Research Centre of Rock-Soil Drilling&Excavation and Protection,Ministry of Education,ChinaProject(202305-2)supported by the Science and Technology Project of Zhejiang Provincial Communication Department,ChinaProject(2021K256)supported by the Construction Research Founds of Department of Housing and Urban-Rural Development of Zhejiang Province,China。
文摘This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi analytical solutions of temperature increment and displacement of multi-layered composite structures are obtained by using the Laplace transform method,upon which the effects of thermal resistance coefficient,partition coefficient,thermal conductivity ratio and heat capacity ratio on the responses are studied.The results show that the generalized imperfect thermal contact model can realistically describe the imperfect thermal contact problem.Accordingly,it may degenerate into other thermal contact models by adjusting the thermal resistance coefficient and partition coefficient.
文摘Stab-resistant textiles play a critical role in personal protection,necessitating a deeper understanding of how structural and layering factors influence their performance.The current study experimentally examines the effects of textile structure,layering,and ply orientation on the stab resistance of multi-layer textiles.Three 3D warp interlock(3DWI)structures({f1},{f2},{f3})and a 2D woven fabric({f4}),all made of high-performance p-aramid yarns,were engineered and manufactured.Multi-layer specimens were prepared and subjected to drop-weight stabbing tests following HOSBD standards.Stabbing performance metrics,including Depth of Trauma(DoT),Depth of Penetration(DoP),and trauma deformation(Ymax,Xmax),were investigated and analyzed.Statistical analyses(Two-and One-Way ANOVA)indicated that fabric type and layer number significantly impacted DoP(P<0.05),while ply orientation significantly affected DoP(P<0.05)but not DoT(P>0.05).Further detailed analysis revealed that 2D woven fabrics exhibited greater trauma deformation than 3D WIF structures.Increasing the number of layers reduced both DoP and DoT across all fabric structures,with f3 demonstrating the best performance in multi-layer configurations.Aligned ply orientations also enhanced stab resistance,underscoring the importance of alignment in dissipating impact energy.
文摘Considering that real communication signals corrupted by noise are generally nonstationary, and timefrequency distributions are especially suitable for the analysis of nonstationary signals, time-frequency distributions are introduced for the modulation classification of communication signals： The extracted time-frequency features have good classification information, and they are insensitive to signal to noise ratio （SNR） variation. According to good classification by the correct rate of a neural network classifier, a multilayer perceptron （MLP） classifier with better generalization, as well as, addition of time-frequency features set for classifying six different modulation types has been proposed. Computer simulations show that the MLP classifier outperforms the decision-theoretic classifier at low SNRs, and the classification experiments for real MPSK signals verify engineering significance of the MLP classifier.
基金This project was supported by the National Basic Research Programof China (2001CB309403)
文摘To improve the performance of multiple classifier system, a knowledge discovery based dynamic weighted voting （KD-DWV） is proposed based on knowledge discovery. In the method, all base classifiers may be allowed to operate in different measurement/feature spaces to make the most of diverse classification information. The weights assigned to each output of a base classifier are estimated by the separability of training sample sets in relevant feature space. For this purpose, some decision tables （DTs） are established in terms of the diverse feature sets. And then the uncertainty measures of the separability are induced, in the form of mass functions in Dempster-Shafer theory （DST）, from each DTs based on generalized rough set model. From the mass functions, all the weights are calculated by a modified heuristic fusion function and assigned dynamically to each classifier varying with its output. The comparison experiment is performed on the hyperspectral remote sensing images. And the experimental results show that the performance of the classification can be improved by using the proposed method compared with the plurality voting （PV）.
基金This project was supported by Shanghai Shu Guang Project.
文摘Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with the nearest neighbor classifier (NNC) is proposed. The principal component analysis (PCA) is used to reduce the dimension and extract features. Then one-against-all stratedy is used to train the SVM classifiers. At the testing stage, we propose an al-
基金supported by National Natural Science Foundation of China(Grant No.11802141)Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX18_0465)。
文摘Three different kinds of PELE(the penetrator with lateral efficiency) were launched by ballistic artillery to impact the multi-layer spaced metal target plates.The lmpact velocities of the projectiles were measured by the velocity measuring system.The damage degree and process of each laye r of target plate impacted by the three kinds of projectiles were analyzed.The experimental results show that all the three kinds of projectiles have the effect of expanding holes on the multi-layer spaced metal target plates.For the normal structure PELE(without layered) with tungsten alloy jacket and the radial layered PELE with tungsten alloy jacket,the diameters of holes on the seco nd layer of plates are 3.36 times and 3.76 times of the diameter of the projectile,re spectively.For radial layered PELE with W/Zr-based amorphous composite jacket,due to the large number of tungsten wires dispersed after the impact,the diameter of the holes on the four-layer spaced plates can reach 2.4 times,3.04 times,5.36 times and 2.68 times of the diameter of the projectile.Besides,the normal structure PELE with tungsten alloy jacket and the radial layered PELE whit tungsten alloy jacket formed a large number of fragments impact marks on the third target plate.Although the number of fragments penetrating the third target plate is not as large as that of the normal structure PELE,the area of dispersion of fragments impact craters on the third target plate is larger by the radial layered PELE.The radial layered PELE with W/Zr-based amorphous composite jacket released a lot of heat energy due to the impact of the matrix material,and formed a large area of ablation marks on the last three target plates.
基金Project(11174077)supported by the National Natural Science Foundation of ChinaProject(11JJ3079)supported by the Hunan Provincial Natural Science Foundation of ChinaProjects(12C0237,11C0844)supported by the Science Research Program of Education Department of Hunan Province,China
文摘High intensity focused ultrasound(HIFU)therapy is an effective method in clinical treatment of tumors,in order to explore the bio-heat conduction mechanism of in multi-layer media by concave spherical transducer,temperature field induced by this kind of transducer in multi-layer media will be simulated through solving Pennes equation with finite difference method,and the influence of initial sound pressure,absorption coefficient,and thickness of different layers of biological tissue as well as thermal conductivity parameter on sound focus and temperature distribution will be analyzed,respectively.The results show that the temperature in focus area increases faster while the initial sound pressure and thermal conductivity increase.The absorption coefficient is smaller,the ultrasound intensity in the focus area is bigger,and the size of the focus area is increasing.When the thicknesses of different layers of tissue change,the focus position changes slightly,but the sound intensity of the focus area will change obviously.The temperature in focus area will rise quickly before reaching a threshold,and then the temperature will keep in the threshold range.
基金Project(2017JM5077)supported by the Natural Science Basic Research Plan in Shaanxi Province,ChinaProjects(300102259109,300102259306)supported by the Fundamental Research Funds for the Central Universities,China。
文摘Asphalt mixture pavement reheating is one of the important steps in hot in-place recycling(HIR).To improve the heating speed of asphalt pavement in HIR,based on the numerical analysis model of asphalt mixture heating process,a new multi-layer low-temperature heating method(MLHM)was proposed.Considering input heat flux,the thermal capacity and thermal resistance of asphalt mixture,the heat transfer model was established based on energy conservation law.By heating the asphalt mixture in layers,it changes the situation that the heat energy can only be input from the upper surface of the asphalt mixture pavement.Through the simulation of the heating method of asphalt mixture in the existing technology,the result shows that the existing heating methods lead to serious aging or charring of the asphalt mixture.By MLHM,the upper and the bottom of the asphalt mixture are heated at the same time,and the heating temperature is lower than other heat methods,which not only reduces the heating thickness and increases the heating area of the asphalt mixture pavement,but also improves the heating speed,saves the energy resource and ensures the heating quality.Especially,by MLHM,the heating uniformity is better and speed is faster.
基金the National Natural Science of China (50675167)a Foundation for the Author of National Excellent Doctoral Dissertation of China(200535)
文摘Support vector classifier （SVC） has the superior advantages for small sample learning problems with high dimensions, with especially better generalization ability. However there is some redundancy among the high dimensions of the original samples and the main features of the samples may be picked up first to improve the performance of SVC. A principal component analysis （PCA） is employed to reduce the feature dimensions of the original samples and the pre-selected main features efficiently, and an SVC is constructed in the selected feature space to improve the learning speed and identification rate of SVC. Furthermore, a heuristic genetic algorithm-based automatic model selection is proposed to determine the hyperparameters of SVC to evaluate the performance of the learning machines. Experiments performed on the Heart and Adult benchmark data sets demonstrate that the proposed PCA-based SVC not only reduces the test time drastically, but also improves the identify rates effectively.
基金Project(2015SK20792)supported by Key Province Key Technology Research and Development Program of the Ministry of Science and Technology of Hunan,ChinaProjects(2019zzts703,2020zzts740,2020zzts202)supported by the Fundamental Research Funds for the Central Universities of ChinaProject(2020P4FZG03A)supported by State Key Laboratory of Vanadium and Titanium Resources Comprehensive Utilization,China。
文摘In this work,the reflux classifier with closely spaced inclined channels is used as the pre-concentration facility to improve the separation efficiency before the shaking table separation.Three operating parameters of reflux classifier(RC)to pre-concentrate fine(0.023−0.15 mm)tailings of antimony oxide were optimized by response surface methodology(RSM)using a three-level Box-Behnken design(BBD).The parameters studied for the optimization were feeding speed,underflow,and ascending water speed.Second-order response functions were produced for the Sb grade and recovery rate of the concentrate.Taking advantage of the quadratic programming,when the factors of feeding,underflow and ascending water are respectively 225,30 and 133 cm^3/min,a better result can be achieved for the concentrate grade of 2.31% and recovery rate of 83.17%.At the same time,70.48% of the tailings with the grade of 0.20% were discarded out of the feeding.The results indicated that the reflux classifier has a good performance in dealing with fine tailings of antimony oxide.Moreover,second-order polynomial equations,ANOVA,and three-dimensional surface plots were developed to evaluate the effects of each parameter on Sb grade and recovery rate of the concentrate.
文摘Automatic modulation classification is the process of identification of the modulation type of a signal in a general environment. This paper proposes a new method to evaluate the tracking performance of large margin classifier against signal-tonoise ratio （SNR）, and classifies all forms of primary user＇s signals in a cognitive radio environment. For achieving this objective, two structures of a large margin are developed in additive white Gaussian noise （AWGN） channels with priori unknown SNR. A combination of higher order statistics and instantaneous characteristics is selected as effective features. Simulation results show that the classification rates of the proposed structures are well robust against environmental SNR changes.
基金supported by the National Natural Science Foundation of China(Grant No.61973037 and No.61673066).
文摘This paper considers the problem of target and jamming recognition for the pulse Doppler radar fuze(PDRF).To solve the problem,the matched filter outputs of the PDRF under the action of target and jamming are analyzed.Then,the frequency entropy and peak-to-peak ratio are extracted from the matched filter output of the PDRF,and the time-frequency joint feature is constructed.Based on the time-frequency joint feature,the naive Bayesian classifier(NBC)with minimal risk is established for target and jamming recognition.To improve the adaptability of the proposed method in complex environments,an online update process that adaptively modifies the classifier in the duration of the work of the PDRF is proposed.The experiments show that the PDRF can maintain high recognition accuracy when the signal-to-noise ratio(SNR)decreases and the jamming-to-signal ratio(JSR)increases.Moreover,the applicable analysis shows that he ONBCMR method has low computational complexity and can fully meet the real-time requirements of PDRF.
基金This project was supported by the National Natural Science Foundation of China (60672139, 60672140)the Excellent Ph.D. Paper Author Foundation of China (200237)the Natural Science Foundation of Shandong (2005ZX01).
文摘Under the scenario of dense targets in clutter, a multi-layer optimal data correlation algorithm is proposed. This algorithm eliminates a large number of false location points from the assignment process by rough correlations before we calculate the correlation cost, so it avoids the operations for the target state estimate and the calculation of the correlation cost for the false correlation sets. In the meantime, with the elimination of these points in the rough correlation, the disturbance from the false correlations in the assignment process is decreased, so the data correlation accuracy is improved correspondingly. Complexity analyses of the new multi-layer optimal algorithm and the traditional optimal assignment algorithm are given. Simulation results show that the new algorithm is feasible and effective.
基金Projects(61170156,60933005)supported by the National Natural Science Foundation of China
文摘Sentiment analysis is the computational study of how opinions, attitudes, emotions, and perspectives are expressed in language, and has been the important task of natural language processing. Sentiment analysis is highly valuable for both research and practical applications. The focuses were put on the difficulties in the construction of sentiment classifiers which normally need tremendous labeled domain training data, and a novel unsupervised framework was proposed to make use of the Chinese idiom resources to develop a general sentiment classifier. Furthermore, the domain adaption of general sentiment classifier was improved by taking the general classifier as the base of a self-training procedure to get a domain self-training sentiment classifier. To validate the effect of the unsupervised framework, several experiments were carried out on publicly available Chinese online reviews dataset. The experiments show that the proposed framework is effective and achieves encouraging results. Specifically, the general classifier outperforms two baselines(a Na?ve 50% baseline and a cross-domain classifier), and the bootstrapping self-training classifier approximates the upper bound domain-specific classifier with the lowest accuracy of 81.5%, but the performance is more stable and the framework needs no labeled training dataset.
基金Project(51874202) supported by the National Natural Science Foundation of ChinaProject(2017JQ0003) supported by the Sichuan Youth Fund,China。
文摘Considering the fact that in some complex cases,plate anchors are buried in multi-layered geotechnical materials,the ultimate dynamic analysis was performed to investigate the uplift capacity and failure mechanism of shallow strips and circular plate anchors in multi-layered soils.The nonlinear strength criterion and non-associated flow rule of geotechnical materials were introduced to investigate the influence of nonuniformity on the pullout performance and failure mechanism of shallow plate anchors.The expressions of the detaching curves or surfaces were obtained to reflect the failure mechanism,which can be used to figure out the ultimate uplift capacity and failure range.The results are generally in agreement with the numerical simulations and previous research.The effects of various parameters on the ultimate uplift capacity and failure mechanism of plate anchors in multi-layered soils were investigated,and it is found that the ultimate uplift capacity and failure range of shallow anchors increase with the increase of initial cohesion and dilatancy coefficient,but decrease with the unit weight,axial tensile stress and nonlinear coefficient.
基金funded by the National Natural Science Foundation of China(Grant No.11972018,No.12002336)China Postdoctoral Science Foundation(Grant No.2021M701710)。
文摘This article investigates the characteristics of shock wave overpressure generated by multi-layer composite charge under different detonation modes.Combining dimensional analysis and the explosion mechanism of the charge,a peak overpressure prediction model for the composite charge under singlepoint detonation and simultaneous detonation was established.The effects of the charge structure and initiation method on the overpressure field characteristics were investigated in AUTODYN simulation.The accuracy of the prediction model and the reliability of the numerical simulation method were subsequently verified in a series of static explosion experiments.The results reveal that the mass of the inner charge was the key factor determining the peak overpressure of the composite charge under single-point detonation.The peak overpressure in the radial direction improved apparently with an increase in the aspect ratio of the charge.The overpressure curves in the axial direction exhibited a multi-peak phenomenon,and the secondary peak overpressure even exceeded the primary peak at distances of 30D and 40D(where D is the charge diameter).The difference in peak overpressure among azimuth angles of 0-90°gradually decreased with an increase in the propagation distance of the shock wave.The coupled effect of the detonation energy of the inner and outer charge under simultaneous detonation improved the overpressure in both radial and axial directions.The difference in peak overpressure obtained from model prediction and experimental measurements was less than 16.4%.
基金Supported by Gansu Province Natural Science Foundation（3ZS061-A25-045）, and the“Qing Lan”Talent Engineering Funds of Lanazhou Jiaotong University（QL-06-19A）
