Environmentally sensitive grain-size component (ESGSC) extracted from grain-size data of a sediment core B2, which were retrieved from mud area southwest off Cheju Island (MACI), East China Sea (ECS), can be used to i...Environmentally sensitive grain-size component (ESGSC) extracted from grain-size data of a sediment core B2, which were retrieved from mud area southwest off Cheju Island (MACI), East China Sea (ECS), can be used to indicate the variations of East Asia Winter Monsoon (EAWM), with high (low) content/mean-size of ESGCS denote to strong (weak) EAWM. Combined with AMS14C datings core B2 provides a continuous high-resolution record of EAWM changes over the past 2300 years, with an average resolution of 13 years. The results show that the variations of EAWM are con-sistent with temperature changes inferred from historical documents in eastern China over the past 2300 years, from which four climate stages may be identified. In stages before 1900 aBP (50 AD) and 1450―780 aBP (50―1170 AD) the EAWM were comparatively weak, corresponding to warm climate periods in eastern China, respectively. And in stages of 1900―1450 aBP (50―500 AD) and 780―219 aBP (1170―1731 AD) the EAWM were strongly developed, which correspond well to climate changes of two cold periods in eastern China. It is also shown from this study that the stage at 780―219 aBP (1170―1731 AD) was the coldest climate period during the last 2300 years and could be, therefore, related to the Little Ice Age (LIA). Climatic fluctuations appeared obviously in all the four stages, and two climate events of abrupt changes from warm to cold occurred at around 1900 aBP (50 AD) and 780 aBP (1170 AD), of which the latter is probably related to globe-scale changes of atmospheric circulation at that time.展开更多
The kernel principal component analysis （KPCA） method employs the first several kernel principal components （KPCs）, which indicate the most variance information of normal observations for process monitoring, but m...The kernel principal component analysis （KPCA） method employs the first several kernel principal components （KPCs）, which indicate the most variance information of normal observations for process monitoring, but may not reflect the fault information. In this study, sensitive kernel principal component analysis （SKPCA） is proposed to improve process monitoring performance, i.e., to deal with the discordance of T2 statistic and squared prediction error SVE statistic and reduce missed detection rates. T2 statistic can be used to measure the variation di rectly along each KPC and analyze the detection performance as well as capture the most useful information in a process. With the calculation of the change rate of T2 statistic along each KPC, SKPCA selects the sensitive kernel principal components for process monitoring. A simulated simple system and Tennessee Eastman process are employed to demonstrate the efficiency of SKPCA on online monitoring. The results indicate that the monitoring performance is improved significantly.展开更多
The expansion planning and operation of all three sectors, generation, transmission and distribution, of power system essentially require load forecasting. Weather conditions have significant impacts on forecasted loa...The expansion planning and operation of all three sectors, generation, transmission and distribution, of power system essentially require load forecasting. Weather conditions have significant impacts on forecasted load, especially short-term and mid-term. A momentous portion of the electrical energy is consumed, especially in cold or hot countries, to mitigate the impact of weather on the daily life of human society. Usually, weather dependent component of load is identified by fitting appropriate non-linear curve to the scatter plot of weather-load model. This technique some times shows lower correlation with weather variables. This paper proposes a new methodology to identify the weather sensitive component of electrical load using empirical mode decomposition (EMD) technique. The proposed methodology is applied to the daily peak load of Dhaka zone of Bangladesh Power System (BPS) of the year 2012. A detailed numerical process to evaluate the weather sensitive portion of the load is also presented. The proposed methodology is validated through statistical error evaluation process. Finally the salient features of the results are discussed.展开更多
The effects of soil solid components on soil sensitivity to acid deposition by sequential extraction method were studied. A multiple regression equation of soil sensitivity was set up on the basis of stepwise regressi...The effects of soil solid components on soil sensitivity to acid deposition by sequential extraction method were studied. A multiple regression equation of soil sensitivity was set up on the basis of stepwise regression analysis. The results showed that organic matter expressed dual effects that were decided by soil original pH value and exchangeable cation composition on acid buffering reactions. The hydrolysis of activated oxides was a very important proton buffering reaction when in low pH situation. The crystalline oxides also played a role in the buffering reactions, but the role was restricted by the rate of activation of oxides. Meanwhile, the results by stepwise analysis showed that factors that had significant effect on soil acid buffering capacity were content of montmorillite, soil original pH value, Al 0, Mn 0 and CEC in decreasing order. Finally, sixteen soils were classified into four types of sensitive with single index cluster and multiple fuzzy cluster analysis respectively.展开更多
Sediment cores were collected from the subaqueous delta of the Changjiang Estuary. Sediment grain-size profiles and their fractal dimensions were analyzed, to elucidate responses to long-term sedimentary processes. In...Sediment cores were collected from the subaqueous delta of the Changjiang Estuary. Sediment grain-size profiles and their fractal dimensions were analyzed, to elucidate responses to long-term sedimentary processes. In addition, the environmental sensitive populations of grain size have been extracted. The sediment cores can be divided into two parts, according to the sedimentary structures present. The upper part （0-12 cm） is interpreted as being the active layer, which is influenced frequently by changes in the short-term hydrodynamic environment. The lower part extends from a depth of 12 cm, to the bottom of the core. The pattern of fluctuation is linked to sediment grain size. Moreover, two grain-size sensitive populations can be identified. The fine sensitive population is 6.0-7.2 μm, which is a similar grain size to the suspended sediment from up-river. The coarse sensitive population varies from 40.7 to 57.5 μm, revealing complex changes. Thus, the riverine inputs from the Changjiang River may be an important source, which contributes to seasonal fluctuations of grain-size distribution, over the area. The sediments, with grain-sizes ranging from 0.9 to 20.3 μm, are characterised by self-similar in the fractal non-scale region. The fraetal dimension is eonsistant with the grain-size parameter varatioins, which could be used as a replacement index to reveal and reconstruct the sedimentary environmental evolution.展开更多
Conventional process monitoring method based on fast independent component analysis(Fast ICA) cannot take the ubiquitous measurement noises into account and may exhibit degraded monitoring performance under the advers...Conventional process monitoring method based on fast independent component analysis(Fast ICA) cannot take the ubiquitous measurement noises into account and may exhibit degraded monitoring performance under the adverse effects of the measurement noises. In this paper, a new process monitoring approach based on noisy time structure ICA(Noisy TSICA) is proposed to solve such problem. A Noisy TSICA algorithm which can consider the measurement noises explicitly is firstly developed to estimate the mixing matrix and extract the independent components(ICs). Subsequently, a monitoring statistic is built to detect process faults on the basis of the recursive kurtosis estimations of the dominant ICs. Lastly, a contribution plot for the monitoring statistic is constructed to identify the fault variables based on the sensitivity analysis. Simulation studies on the continuous stirred tank reactor system demonstrate that the proposed Noisy TSICA-based monitoring method outperforms the conventional Fast ICA-based monitoring method.展开更多
Principal component analysis(PCA)has been already employed for fault detection of air conditioning systems.The sliding window,which is composed of some parameters satisfying with thermal load balance,can select the ta...Principal component analysis(PCA)has been already employed for fault detection of air conditioning systems.The sliding window,which is composed of some parameters satisfying with thermal load balance,can select the target historical fault-free reference data as the template which is similar to the current snapshot data.The size of sliding window is usually given according to empirical values,while the influence of different sizes of sliding windows on fault detection of an air conditioning system is not further studied.The air conditioning system is a dynamic response process,and the operating parameters change with the change of the load,while the response of the controller is delayed.In a variable air volume(VAV)air conditioning system controlled by the total air volume method,in order to ensure sufficient response time,30 data points are selected first,and then their multiples are selected.Three different sizes of sliding windows with 30,60 and 90 data points are applied to compare the fault detection effect in this paper.The results show that if the size of the sliding window is 60 data points,the average fault-free detection ratio is 80.17%in fault-free testing days,and the average fault detection ratio is 88.47%in faulty testing days.展开更多
A process of preparing ZnO voltage sensitive ceramics doped with some oxides by coprecipitation was described in the paper. The thermal properties of ZnO nanometer powders and the current voltage characteristics of ...A process of preparing ZnO voltage sensitive ceramics doped with some oxides by coprecipitation was described in the paper. The thermal properties of ZnO nanometer powders and the current voltage characteristics of the ceramics have been investigated. The results showed that the six additive ZnO powders with hexagonal system were homogeneous grain size distribution in microstructure, the optimal reaction pH is 6.90±0.05, the temperature for calcining and sintering was at about 500 ℃ and 1100 ℃, respectively. The powders were also examined by SEM, IR and XRD etc, and the effect of doping La 2O 3 on the electrical properties of ZnO varistor was investigated too.展开更多
Objective: To introduce a method to calculate cardiovascular age, a new, accurate and much simpler index for assessing cardiovascular autonomic regulatory function, based on statistical analysis of heart rate and bloo...Objective: To introduce a method to calculate cardiovascular age, a new, accurate and much simpler index for assessing cardiovascular autonomic regulatory function, based on statistical analysis of heart rate and blood pressure variability (HRV and BPV) and baroreflex sensitivity (BRS) data. Methods: Firstly, HRV and BPV of 89 healthy aviation personnel were analyzed by the conventional autoregressive (AR) spectral analysis and their spontaneous BRS was obtained by the sequence method. Secondly, principal component analysis was conducted over original and derived indices of HRV, BPV and BRS data and the relevant principal components, PCi orig and PCi deri (i=1, 2, 3,...) were obtained. Finally, the equation for calculating cardiovascular age was obtained by multiple regression with the chronological age being assigned as the dependent variable and the principal components significantly related to age as the regressors. Results: The first four principal components of original indices accounted for over 90% of total variance of the indices, so did the first three principal components of derived indices. So, these seven principal components could reflect the information of cardiovascular autonomic regulation which was embodied in the 17 indices of HRV, BPV and BRS exactly with a minimal loss of information. Of the seven principal components, PC2 orig , PC4 orig and PC2 deri were negatively correlated with the chronological age ( P <0 05), whereas the PC3 orig was positively correlated with the chronological age ( P <0 01). The cardiovascular age thus calculated from the regression equation was significantly correlated with the chronological age among the 89 aviation personnel ( r =0.73, P <0 01). Conclusion: The cardiovascular age calculated based on a multi variate analysis of HRV, BPV and BRS could be regarded as a comprehensive indicator reflecting the age dependency of autonomic regulation of cardiovascular system in healthy aviation personnel.展开更多
Since most of the available component-based software reliability models consume high computational cost and suffer from the evaluating complexity for the software system with complex structures,a component-based back-...Since most of the available component-based software reliability models consume high computational cost and suffer from the evaluating complexity for the software system with complex structures,a component-based back-propagation reliability model(CBPRM)with low complexity for the complex software system reliability evaluation is presented in this paper.The proposed model is based on the artificial neural networks and the component reliability sensitivity analyses.These analyses are performed dynamically and assigned to the neurons to optimize the reliability evaluation.CBPRM has a linear increasing complexity and outperforms the state-based and the path-based reliability models.Another advantage of CBPRM over others is its robustness.CBPRM depends on the component reliabilities and the correlative sensitivities,which are independent from the software system structure.Based on the theory analysis and experiment results,it shows that the complexity of CBPRM is evidently lower than the contrast models and the reliability evaluating accuracy is acceptable when the software system structure is complex.展开更多
Total Knee Replacement(TKR)is the increasing trend now a day,in revision surgery which is associated with aseptic loosening,which is a challenging research for the TKR component.The selection of optimal material loose...Total Knee Replacement(TKR)is the increasing trend now a day,in revision surgery which is associated with aseptic loosening,which is a challenging research for the TKR component.The selection of optimal material loosening can be controlled at some limits.This paper is going to consider the best material selected among a number of alternative materials for the femoral component(FC)by using Graph Theory.Here GTMA process used for optimization of material and a systematic technique introduced through sensitivity analysis to find out the more reliable result.Obtained ranking suggests the use of optimized material over the other existing material.By following GTMA Co_Cr-alloys(wrought-Co-Ni-Cr-Mo)and Co_Cr-alloys(cast-able-Co-Cr-Mo)are on the 1st and 2nd position respectively.展开更多
The sensitivity of aerosol radiative properties (i.e., scattering coefficient, extinction coefficient, single scatter albedo, and asymmetry factor) and radiation transmission to aerosol composition, size distributions...The sensitivity of aerosol radiative properties (i.e., scattering coefficient, extinction coefficient, single scatter albedo, and asymmetry factor) and radiation transmission to aerosol composition, size distributions, and relative humidity (RH) is examined in this paper. Mie calculations and radiation calculations using a tropospheric visible radiation model are performed. The aerosol systems considered include inorganic and organic ions (e.g., Cl-, Br-, , , Na+, , K+, Ca2+, Mg2+, HCOO-, CH3COO-, CH3CH2COO-, CH3COCOO-, OOCCOO2-, MSA1-), and (2) water-insoluble inorganic and organic compounds e.g., (black carbon, n-alkanes, SiO2, Al2O3, Fe2O3 and other organic compounds). The partial molar refraction method and the volume-average method are used to calculate the real and imaginary parts of refractive index of real aerosols, respectively. The sensitivity simulations show that extinction coefficient increases by 70% when RH varies from 0 to 80%. Both extinction coefficient and asymmetry factor increase by ~48% when real part varies from 1.40 to 1.65. Scattering coefficient and single scattering albedo decrease by 18% and 24%, respectively, when the imaginary part varies from –0.005 to –0.1. Scattering and extinction coefficients increase by factors of 118 and 123, respectively, when the geometric mean radius varies from 0.05 to 0.3 ?m. Scattering and extinction coefficients and asymmetry factor increase by factors of 389, 334, and 5.4, respectively, when geometric standard deviation varies from 1.2 to 3.0. The sensitivity simulations using a tropospheric visible radiation model show that the radiation transmission is very sensitive to the change in geometric mean radius and standard deviation;other factors are insignificant.展开更多
Malware detection has become mission sensitive as its threats spread from computer systems to Internet of things systems.Modern malware variants are generally equipped with sophisticated packers,which allow them bypas...Malware detection has become mission sensitive as its threats spread from computer systems to Internet of things systems.Modern malware variants are generally equipped with sophisticated packers,which allow them bypass modern machine learning based detection systems.To detect packed malware variants,unpacking techniques and dynamic malware analysis are the two choices.However,unpacking techniques cannot always be useful since there exist some packers such as private packers which are hard to unpack.Although dynamic malware analysis can obtain the running behaviours of executables,the unpacking behaviours of packers add noisy information to the real behaviours of executables,which has a bad affect on accuracy.To overcome these challenges,in this paper,we propose a new method which first extracts a series of system calls which is sensitive to malicious behaviours,then use principal component analysis to extract features of these sensitive system calls,and finally adopt multi-layers neural networks to classify the features of malware variants and legitimate ones.Theoretical analysis and real-life experimental results show that our packed malware variants detection technique is comparable with the the state-of-art methods in terms of accuracy.Our approach can achieve more than 95.6\%of detection accuracy and 0.048 s of classification time cost.展开更多
The gradient descent(GD)method is used to fit the measured data(i.e.,the laser grain-size distribution of the sediments)with a sum of four weighted lognormal functions.The method is calibrated by a series of ideal num...The gradient descent(GD)method is used to fit the measured data(i.e.,the laser grain-size distribution of the sediments)with a sum of four weighted lognormal functions.The method is calibrated by a series of ideal numerical experiments.The numerical results indicate that the GD method not only is easy to operate but also could effectively optimize the parameters of the fitting function with the error decreasing steadily.The method is applied to numerical partitioning of laser grain-size components of a series of Garzêloess samples and three bottom sedimentary samples of submarine turbidity currents modeled in an open channel laboratory flume.The overall fitting results are satisfactory.As a new approach of data fitting,the GD method could also be adapted to solve other optimization problems.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.90211022 and 40206007)the Innovation Program of the Chinese Academy of Sciences(Grant No.KZCX3-SW-220).
文摘Environmentally sensitive grain-size component (ESGSC) extracted from grain-size data of a sediment core B2, which were retrieved from mud area southwest off Cheju Island (MACI), East China Sea (ECS), can be used to indicate the variations of East Asia Winter Monsoon (EAWM), with high (low) content/mean-size of ESGCS denote to strong (weak) EAWM. Combined with AMS14C datings core B2 provides a continuous high-resolution record of EAWM changes over the past 2300 years, with an average resolution of 13 years. The results show that the variations of EAWM are con-sistent with temperature changes inferred from historical documents in eastern China over the past 2300 years, from which four climate stages may be identified. In stages before 1900 aBP (50 AD) and 1450―780 aBP (50―1170 AD) the EAWM were comparatively weak, corresponding to warm climate periods in eastern China, respectively. And in stages of 1900―1450 aBP (50―500 AD) and 780―219 aBP (1170―1731 AD) the EAWM were strongly developed, which correspond well to climate changes of two cold periods in eastern China. It is also shown from this study that the stage at 780―219 aBP (1170―1731 AD) was the coldest climate period during the last 2300 years and could be, therefore, related to the Little Ice Age (LIA). Climatic fluctuations appeared obviously in all the four stages, and two climate events of abrupt changes from warm to cold occurred at around 1900 aBP (50 AD) and 780 aBP (1170 AD), of which the latter is probably related to globe-scale changes of atmospheric circulation at that time.
基金Supported by the 973 project of China （2013CB733600）, the National Natural Science Foundation （21176073）, the Doctoral Fund of Ministry of Education （20090074110005）, the New Century Excellent Talents in University （NCET-09-0346）, ＂Shu Guang＂ project （09SG29） and the Fundamental Research Funds for the Central Universities.
文摘The kernel principal component analysis （KPCA） method employs the first several kernel principal components （KPCs）, which indicate the most variance information of normal observations for process monitoring, but may not reflect the fault information. In this study, sensitive kernel principal component analysis （SKPCA） is proposed to improve process monitoring performance, i.e., to deal with the discordance of T2 statistic and squared prediction error SVE statistic and reduce missed detection rates. T2 statistic can be used to measure the variation di rectly along each KPC and analyze the detection performance as well as capture the most useful information in a process. With the calculation of the change rate of T2 statistic along each KPC, SKPCA selects the sensitive kernel principal components for process monitoring. A simulated simple system and Tennessee Eastman process are employed to demonstrate the efficiency of SKPCA on online monitoring. The results indicate that the monitoring performance is improved significantly.
文摘The expansion planning and operation of all three sectors, generation, transmission and distribution, of power system essentially require load forecasting. Weather conditions have significant impacts on forecasted load, especially short-term and mid-term. A momentous portion of the electrical energy is consumed, especially in cold or hot countries, to mitigate the impact of weather on the daily life of human society. Usually, weather dependent component of load is identified by fitting appropriate non-linear curve to the scatter plot of weather-load model. This technique some times shows lower correlation with weather variables. This paper proposes a new methodology to identify the weather sensitive component of electrical load using empirical mode decomposition (EMD) technique. The proposed methodology is applied to the daily peak load of Dhaka zone of Bangladesh Power System (BPS) of the year 2012. A detailed numerical process to evaluate the weather sensitive portion of the load is also presented. The proposed methodology is validated through statistical error evaluation process. Finally the salient features of the results are discussed.
文摘The effects of soil solid components on soil sensitivity to acid deposition by sequential extraction method were studied. A multiple regression equation of soil sensitivity was set up on the basis of stepwise regression analysis. The results showed that organic matter expressed dual effects that were decided by soil original pH value and exchangeable cation composition on acid buffering reactions. The hydrolysis of activated oxides was a very important proton buffering reaction when in low pH situation. The crystalline oxides also played a role in the buffering reactions, but the role was restricted by the rate of activation of oxides. Meanwhile, the results by stepwise analysis showed that factors that had significant effect on soil acid buffering capacity were content of montmorillite, soil original pH value, Al 0, Mn 0 and CEC in decreasing order. Finally, sixteen soils were classified into four types of sensitive with single index cluster and multiple fuzzy cluster analysis respectively.
基金The National Basic Research Program of China under contract No 2002CB412401the National Natural Science Foundation of China under contract Nos 40876043 & 40106009+1 种基金the Jiangsu Natural Science Foundation under contract NoBK2006131the NCET Program under contract NoNCET-06-0446
文摘Sediment cores were collected from the subaqueous delta of the Changjiang Estuary. Sediment grain-size profiles and their fractal dimensions were analyzed, to elucidate responses to long-term sedimentary processes. In addition, the environmental sensitive populations of grain size have been extracted. The sediment cores can be divided into two parts, according to the sedimentary structures present. The upper part （0-12 cm） is interpreted as being the active layer, which is influenced frequently by changes in the short-term hydrodynamic environment. The lower part extends from a depth of 12 cm, to the bottom of the core. The pattern of fluctuation is linked to sediment grain size. Moreover, two grain-size sensitive populations can be identified. The fine sensitive population is 6.0-7.2 μm, which is a similar grain size to the suspended sediment from up-river. The coarse sensitive population varies from 40.7 to 57.5 μm, revealing complex changes. Thus, the riverine inputs from the Changjiang River may be an important source, which contributes to seasonal fluctuations of grain-size distribution, over the area. The sediments, with grain-sizes ranging from 0.9 to 20.3 μm, are characterised by self-similar in the fractal non-scale region. The fraetal dimension is eonsistant with the grain-size parameter varatioins, which could be used as a replacement index to reveal and reconstruct the sedimentary environmental evolution.
基金Supported by the National Natural Science Foundation of China(61273160)the Natural Science Foundation of Shandong Province(ZR2011FM014)+1 种基金the Fundamental Research Funds for the Central Universities(12CX06071A)the Postgraduate Innovation Funds of China University of Petroleum(CX2013060)
文摘Conventional process monitoring method based on fast independent component analysis(Fast ICA) cannot take the ubiquitous measurement noises into account and may exhibit degraded monitoring performance under the adverse effects of the measurement noises. In this paper, a new process monitoring approach based on noisy time structure ICA(Noisy TSICA) is proposed to solve such problem. A Noisy TSICA algorithm which can consider the measurement noises explicitly is firstly developed to estimate the mixing matrix and extract the independent components(ICs). Subsequently, a monitoring statistic is built to detect process faults on the basis of the recursive kurtosis estimations of the dominant ICs. Lastly, a contribution plot for the monitoring statistic is constructed to identify the fault variables based on the sensitivity analysis. Simulation studies on the continuous stirred tank reactor system demonstrate that the proposed Noisy TSICA-based monitoring method outperforms the conventional Fast ICA-based monitoring method.
基金Fundamental Research Funds for the Central Universities of Ministry of Education of China。
文摘Principal component analysis(PCA)has been already employed for fault detection of air conditioning systems.The sliding window,which is composed of some parameters satisfying with thermal load balance,can select the target historical fault-free reference data as the template which is similar to the current snapshot data.The size of sliding window is usually given according to empirical values,while the influence of different sizes of sliding windows on fault detection of an air conditioning system is not further studied.The air conditioning system is a dynamic response process,and the operating parameters change with the change of the load,while the response of the controller is delayed.In a variable air volume(VAV)air conditioning system controlled by the total air volume method,in order to ensure sufficient response time,30 data points are selected first,and then their multiples are selected.Three different sizes of sliding windows with 30,60 and 90 data points are applied to compare the fault detection effect in this paper.The results show that if the size of the sliding window is 60 data points,the average fault-free detection ratio is 80.17%in fault-free testing days,and the average fault detection ratio is 88.47%in faulty testing days.
文摘A process of preparing ZnO voltage sensitive ceramics doped with some oxides by coprecipitation was described in the paper. The thermal properties of ZnO nanometer powders and the current voltage characteristics of the ceramics have been investigated. The results showed that the six additive ZnO powders with hexagonal system were homogeneous grain size distribution in microstructure, the optimal reaction pH is 6.90±0.05, the temperature for calcining and sintering was at about 500 ℃ and 1100 ℃, respectively. The powders were also examined by SEM, IR and XRD etc, and the effect of doping La 2O 3 on the electrical properties of ZnO varistor was investigated too.
文摘Objective: To introduce a method to calculate cardiovascular age, a new, accurate and much simpler index for assessing cardiovascular autonomic regulatory function, based on statistical analysis of heart rate and blood pressure variability (HRV and BPV) and baroreflex sensitivity (BRS) data. Methods: Firstly, HRV and BPV of 89 healthy aviation personnel were analyzed by the conventional autoregressive (AR) spectral analysis and their spontaneous BRS was obtained by the sequence method. Secondly, principal component analysis was conducted over original and derived indices of HRV, BPV and BRS data and the relevant principal components, PCi orig and PCi deri (i=1, 2, 3,...) were obtained. Finally, the equation for calculating cardiovascular age was obtained by multiple regression with the chronological age being assigned as the dependent variable and the principal components significantly related to age as the regressors. Results: The first four principal components of original indices accounted for over 90% of total variance of the indices, so did the first three principal components of derived indices. So, these seven principal components could reflect the information of cardiovascular autonomic regulation which was embodied in the 17 indices of HRV, BPV and BRS exactly with a minimal loss of information. Of the seven principal components, PC2 orig , PC4 orig and PC2 deri were negatively correlated with the chronological age ( P <0 05), whereas the PC3 orig was positively correlated with the chronological age ( P <0 01). The cardiovascular age thus calculated from the regression equation was significantly correlated with the chronological age among the 89 aviation personnel ( r =0.73, P <0 01). Conclusion: The cardiovascular age calculated based on a multi variate analysis of HRV, BPV and BRS could be regarded as a comprehensive indicator reflecting the age dependency of autonomic regulation of cardiovascular system in healthy aviation personnel.
基金Supported by the National Natural Science Foundation of China(No.60973118,60873075)
文摘Since most of the available component-based software reliability models consume high computational cost and suffer from the evaluating complexity for the software system with complex structures,a component-based back-propagation reliability model(CBPRM)with low complexity for the complex software system reliability evaluation is presented in this paper.The proposed model is based on the artificial neural networks and the component reliability sensitivity analyses.These analyses are performed dynamically and assigned to the neurons to optimize the reliability evaluation.CBPRM has a linear increasing complexity and outperforms the state-based and the path-based reliability models.Another advantage of CBPRM over others is its robustness.CBPRM depends on the component reliabilities and the correlative sensitivities,which are independent from the software system structure.Based on the theory analysis and experiment results,it shows that the complexity of CBPRM is evidently lower than the contrast models and the reliability evaluating accuracy is acceptable when the software system structure is complex.
文摘Total Knee Replacement(TKR)is the increasing trend now a day,in revision surgery which is associated with aseptic loosening,which is a challenging research for the TKR component.The selection of optimal material loosening can be controlled at some limits.This paper is going to consider the best material selected among a number of alternative materials for the femoral component(FC)by using Graph Theory.Here GTMA process used for optimization of material and a systematic technique introduced through sensitivity analysis to find out the more reliable result.Obtained ranking suggests the use of optimized material over the other existing material.By following GTMA Co_Cr-alloys(wrought-Co-Ni-Cr-Mo)and Co_Cr-alloys(cast-able-Co-Cr-Mo)are on the 1st and 2nd position respectively.
文摘The sensitivity of aerosol radiative properties (i.e., scattering coefficient, extinction coefficient, single scatter albedo, and asymmetry factor) and radiation transmission to aerosol composition, size distributions, and relative humidity (RH) is examined in this paper. Mie calculations and radiation calculations using a tropospheric visible radiation model are performed. The aerosol systems considered include inorganic and organic ions (e.g., Cl-, Br-, , , Na+, , K+, Ca2+, Mg2+, HCOO-, CH3COO-, CH3CH2COO-, CH3COCOO-, OOCCOO2-, MSA1-), and (2) water-insoluble inorganic and organic compounds e.g., (black carbon, n-alkanes, SiO2, Al2O3, Fe2O3 and other organic compounds). The partial molar refraction method and the volume-average method are used to calculate the real and imaginary parts of refractive index of real aerosols, respectively. The sensitivity simulations show that extinction coefficient increases by 70% when RH varies from 0 to 80%. Both extinction coefficient and asymmetry factor increase by ~48% when real part varies from 1.40 to 1.65. Scattering coefficient and single scattering albedo decrease by 18% and 24%, respectively, when the imaginary part varies from –0.005 to –0.1. Scattering and extinction coefficients increase by factors of 118 and 123, respectively, when the geometric mean radius varies from 0.05 to 0.3 ?m. Scattering and extinction coefficients and asymmetry factor increase by factors of 389, 334, and 5.4, respectively, when geometric standard deviation varies from 1.2 to 3.0. The sensitivity simulations using a tropospheric visible radiation model show that the radiation transmission is very sensitive to the change in geometric mean radius and standard deviation;other factors are insignificant.
基金National Science foundation of China under Grant No.61772191,No.61472131.
文摘Malware detection has become mission sensitive as its threats spread from computer systems to Internet of things systems.Modern malware variants are generally equipped with sophisticated packers,which allow them bypass modern machine learning based detection systems.To detect packed malware variants,unpacking techniques and dynamic malware analysis are the two choices.However,unpacking techniques cannot always be useful since there exist some packers such as private packers which are hard to unpack.Although dynamic malware analysis can obtain the running behaviours of executables,the unpacking behaviours of packers add noisy information to the real behaviours of executables,which has a bad affect on accuracy.To overcome these challenges,in this paper,we propose a new method which first extracts a series of system calls which is sensitive to malicious behaviours,then use principal component analysis to extract features of these sensitive system calls,and finally adopt multi-layers neural networks to classify the features of malware variants and legitimate ones.Theoretical analysis and real-life experimental results show that our packed malware variants detection technique is comparable with the the state-of-art methods in terms of accuracy.Our approach can achieve more than 95.6\%of detection accuracy and 0.048 s of classification time cost.
基金supported by the National Natural Science Foundation of China(Grant Nos.41072176,41371496)the National Science and Technology Supporting Program of China(Grant No.2013BAK05B04)the Fundamental Research Funds for the Central Universities(Grant No.201261006)
文摘The gradient descent(GD)method is used to fit the measured data(i.e.,the laser grain-size distribution of the sediments)with a sum of four weighted lognormal functions.The method is calibrated by a series of ideal numerical experiments.The numerical results indicate that the GD method not only is easy to operate but also could effectively optimize the parameters of the fitting function with the error decreasing steadily.The method is applied to numerical partitioning of laser grain-size components of a series of Garzêloess samples and three bottom sedimentary samples of submarine turbidity currents modeled in an open channel laboratory flume.The overall fitting results are satisfactory.As a new approach of data fitting,the GD method could also be adapted to solve other optimization problems.
