The validity of correlation analysis between finite element model（FEM） and modal test data is strongly affected by three factors, i.e., quality of excitation and measurement points in modal test,FEM reduction method...The validity of correlation analysis between finite element model（FEM） and modal test data is strongly affected by three factors, i.e., quality of excitation and measurement points in modal test,FEM reduction methods, and correlation check techniques. A new criterion based on modified mode participation（MMP） for choosing the best excitation point is presented. Comparison between this new criterion and mode participation（MP） criterion is made by using Case 1 with a simple printed circuit board（PCB）. The result indicates that this new criterion produces better results. In Case 2, 35 measurement points are selected to perform modal test and correlation analysis while 9 selected in Case 3.System equivalent reduction expansion process（SEREP）, modal assurance criteria（MAC）, coordinate modal assurance criteria（CoMAC）, pseudo orthogonality check（POC） and coordinate orthogonality check（CORTHOG） are used to show the error introduced by modal test in Cases 2 and 3. Case 2 shows that additional errors which cannot be identified by using CoMAC can be found by using CORTHOG.In both Cases 2 and 3, Guyan reduction, improved reduced system（IRS） method, SEREP and Hybrid reduction are compared for accuracy and robustness. The results suggest that the quality of the reduction process is problem dependent. However, the IRS method is an improvement over the Guyan reduction, and the Hybrid reduction is an improvement over the SEREP reduction.展开更多
Combined Reliability distribution with correlation analysis,a new method has been proposed to make Reliability distribution where considering the elements about structure correlation and failure correlation of subsyst...Combined Reliability distribution with correlation analysis,a new method has been proposed to make Reliability distribution where considering the elements about structure correlation and failure correlation of subsystems.Firstly,we make a sequence for subsystems by means of TOPSIS which comprehends the considerations of Reliability allocation,and introducing a Copula connecting function to set up a distribution model based on structure correlation,failure correlation and target correlation,and then acquiring reliability target area of all subsystems by Matlab.In this method,not only the traditional distribution considerations are concerned,but also correlation influences are involved,to achieve supplementing information and optimizing distribution.展开更多
According to the data from Henan Statistical Yearbook from 2002 to 2008, from production capital, production conditions, labour inputs and financial support, this paper selects 11 variables influencing comprehensive p...According to the data from Henan Statistical Yearbook from 2002 to 2008, from production capital, production conditions, labour inputs and financial support, this paper selects 11 variables influencing comprehensive productivity of agriculture in Henan Province. Through calculation and analysis of grey correlation of variables and comprehensive productivity of agriculture, this paper determines the impact of different variables on comprehensive productivity of agriculture. The results show that the agricultural capital has become the most important factor influencing comprehensive productivity of agriculture in Henan Province, while the impact of production conditions, labour inputs and financial support on comprehensive productivity of agriculture in Henan Province diminishes in turn. Corresponding countermeasures and suggestions are put forward to promote the sustainable development of comprehensive productivity of agriculture in Henan Province as follows: strengthen agricultural financial system building, and ensure agricultural production expenditure; scientifically arrange allocation of agricultural resources, and improve agricultural production conditions; carry out training of agricultural skills, and elevate the quality of agricultural labour forces; increase financial expenditure for agricultural production, and optimize financial expenditure structure.展开更多
The difficulties associated with performing direct compression strength tests on rocks lead to the development of indirect test methods for the rock strength assessment. Indirect test methods are simple, more economic...The difficulties associated with performing direct compression strength tests on rocks lead to the development of indirect test methods for the rock strength assessment. Indirect test methods are simple, more economical, less time-consuming, and easily adaptable to the field. The main aim of this study was to derive correlations between direct and indirect test methods for basalt and rhyolite rock types from Carlin trend deposits in Nevada. In the destructive methods, point load index, block punch index, and splitting tensile strength tests are performed. In the non-destructive methods, Schmidt hammer and ultrasonic pulse velocity tests are performed. Correlations between the direct and indirect compression strength tests are developed using linear and nonlinear regression analysis methods. The results show that the splitting tensile strength has the best correlation with the uniaxial compression strength.Furthermore, the Poisson's ratio has no correlation with any of the direct and indirect test results.展开更多
In order to measure the flow velocity of carbon particle suspension perpendicular to the receiving axis of ultrasound transducer, the standard deviation of photoacoustic Doppler frequency spectrum is used to estimate ...In order to measure the flow velocity of carbon particle suspension perpendicular to the receiving axis of ultrasound transducer, the standard deviation of photoacoustic Doppler frequency spectrum is used to estimate the bandwidth broadening, and the spectrum standard deviation is calculated by an auto-correlation method. A 532 nm pulsed laser with the repetition rate of 20 Hz is used as a pumping source to generate photoacoustic signal. The photoacoustic signals are detected using a focused PZT ultrasound transducer with the central frequency of 10 MHz. The suspension of carbon particles is driven by a syringe pump. The complex photoacoustic signal is calculated by Hilbert transformation from time domain signal before auto-correlation. The standard deviation of the Doppler bandwidth broadening is calculated by averaging the auto-correlation results of several individual A scans. The feasibility of the proposed method is demonstrated by measuring the spectrum standard deviation of the transversal carbon particle flow from 5.0 mm/s to 8.4 mrn/s. The experimental results show that the auto-correlation result is approximately linearly distributed within the measuring range.展开更多
An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variat...An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system（ANFIS）model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules： the astronomical tide module caused by celestial bodies’ movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system（FIS） structure,three approaches which include grid partition（GP）, fuzzy c-means（FCM） and sub-clustering（SC） are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability.展开更多
Based on the analysis of the grain supply and demand gap’s current situation in China, this paper establishes an indicator system for the influence factors of grain supply and demand gap. Then this paper calculates t...Based on the analysis of the grain supply and demand gap’s current situation in China, this paper establishes an indicator system for the influence factors of grain supply and demand gap. Then this paper calculates the correlation degree between the main grain varieties’ supply and demand gap and its influence factors. The results show that sown area and unit yield have the greatest impact on wheat supply and demand gap;per capita disposable income and unit yield have the greatest impact on corn supply and demand gap;per capita disposable income and agricultural mechanization level have the greatest impact on the supply and demand gap of soybean and rice. From the analysis results, we can obtain the difference between the factors affecting the grain supply and demand gap, and provide a certain theoretical basis and new ideas for the balance of grain supply and demand in China.展开更多
In most of real operational conditions only response data are measurable while the actual excitations are unknown, so modal parameter must be extracted only from responses. This paper gives a theoretical formulation f...In most of real operational conditions only response data are measurable while the actual excitations are unknown, so modal parameter must be extracted only from responses. This paper gives a theoretical formulation for the cross-correlation functions and cross-power spectra between the outputs under the assumption of white-noise excitation. It widens the field of modal analysis under ambient excitation because many classical methods by impulse response functions or frequency response functions can be used easily for modal analysis under unknown excitation. The Polyreference Complex Exponential method and Eigensystem Realization Algorithm using cross-correlation functions in time domain and Orthogonal Polynomial method using cross-power spectra in frequency domain are applied to a steel frame to extract modal parameters under operational conditions. The modal properties of the steel frame from these three methods are compared with those from frequency response functions analysis. The results show that the modal analysis method using cross-correlation functions or cross-power spectra presented in this paper can extract modal parameters efficiently under unknown excitation.展开更多
Smart growth has been gaining increasing attention among academia and practitioners as a new technology-based solution to meet the city disease challenges.In the research,we mainly accomplish two tasks.One builds an e...Smart growth has been gaining increasing attention among academia and practitioners as a new technology-based solution to meet the city disease challenges.In the research,we mainly accomplish two tasks.One builds an evaluation system to measure the smart growth of a city.And the other develops a growth plan.Firstly,coordination coefficient(C value) model is applied to measure the smart degree.To begin with,we divide the indicators into four aspects which involve five parameters.Then,entropy method is used to calculate the weight of every parameter.After normalizing data of indicators,we set up a smart growth indicator evaluation system.Aiming to assessing the detailed performances,we rank the eight cities according to the score of C value which corresponds to our normal cognition.Secondly,based on Salvo combat model and dynamic trend analysis model,We draw up a 20-year growth plan with a period of 5 years for the two cities we choose.The Salvo model is adopted to describe the dynamic process.Dynamic trend analysis model is introduced to gain the optimum solution and the optimal point in every stage.In addition,compared with the point of every stage,we can obtain the proportion of investment in different stages.Thirdly,to evaluate the sensitivity of our model with the OFAT Method,we adjust the parameters k_1,k_2 and O_(ij) approximately.It comes out that the change of k_1,k_2 and O_(ij) has an impact on the C value.But the sensitivity of k_1,k_2 is higher.Lastly,we analyze the influence caused by population growth.To a certain extent,it can be concluded that the plan we made can alleviate the negative impact of population growth through the analysis of the chart.展开更多
After the breakout of COVID-19,many entity industries have to shut down.The rapid decline of money transaction caused by the shutdown of the entity industries has shocked the financial service industry while the incre...After the breakout of COVID-19,many entity industries have to shut down.The rapid decline of money transaction caused by the shutdown of the entity industries has shocked the financial service industry while the increase in digital transactions also offers them opportunities.Facing both challenges and opportunities,financial services firms should change their target and compensation policy during the pandemic to survive.After analysing three major firms in this industry by using SOAR method,we conclude four keys for financial services firms to survive in COVID-19.展开更多
MBA education has become the fastest growing segment of education in China in recent years and a segment that can now be considered indispensible.However,how best to teach it has long been a source of debate.One of th...MBA education has become the fastest growing segment of education in China in recent years and a segment that can now be considered indispensible.However,how best to teach it has long been a source of debate.One of the key issues is how to match student traits with teaching methods.While engaged as teachers of marketing management,the authors collected data by questionnaire,carried out empirical research and data comparison,and undertook contingency analysis.It was found that different personal traits in students lead to different attitudes towards teaching methods.A student’s major in college,gender,and sector of employment has little influence on attitudes towards teaching methods,while age,the most sensitive factor,plays the biggest role,followed by job and class.Therefore,these factors should be taken into consideration when arranging classes,developing the curriculum,and planning teaching methods.展开更多
Distributed fiber-optic sensing has become an indispensable tool for large-scale structural and environmentalmonitoring, where spectral interrogation of backscattering light enables high-precision quantitative measure...Distributed fiber-optic sensing has become an indispensable tool for large-scale structural and environmentalmonitoring, where spectral interrogation of backscattering light enables high-precision quantitative measurement ofexternal perturbations. Conventional spectral analysis methods, typically based on frequency-domain serialinterrogation or time-to-frequency mapping, face inherent trade-offs between measurement speed, dynamic strainmeasurement range, and system complexity. Here, we present a distributed frequency comb enabled spectrumcorrelationreflectometry as a universal spectral analysis framework that leverages optical frequency comb for parallelmulti-frequency interrogation, which is experimentally demonstrated in a phase-sensitive optical time-domainreflectometry (φ-OTDR) system. This method eliminates the need for large frequency scans, achieving more thantenfold improvement in measurement speed over the state-of-the-art spectral analysis methods. Compared to existingphase-demodulated φ-OTDR systems, this method enables vibration amplitude monitoring with a dynamic strainmeasurement range expanded by more than an order of magnitude, while intrinsically circumventing phaseunwrapping issues and interference fading. This work establishes a new paradigm for distributed spectral analysis,providing a flexible and robust platform for a wide range of sensing technologies, including Rayleigh and Brillouinbasedschemes, which may have significant impact for geophysics, seismology, civil engineering, and other fields.展开更多
Accurate prediction of shield tunneling-induced settlement is a complex problem that requires consideration of many influential parameters.Recent studies reveal that machine learning(ML)algorithms can predict the sett...Accurate prediction of shield tunneling-induced settlement is a complex problem that requires consideration of many influential parameters.Recent studies reveal that machine learning(ML)algorithms can predict the settlement caused by tunneling.However,well-performing ML models are usually less interpretable.Irrelevant input features decrease the performance and interpretability of an ML model.Nonetheless,feature selection,a critical step in the ML pipeline,is usually ignored in most studies that focused on predicting tunneling-induced settlement.This study applies four techniques,i.e.Pearson correlation method,sequential forward selection(SFS),sequential backward selection(SBS)and Boruta algorithm,to investigate the effect of feature selection on the model’s performance when predicting the tunneling-induced maximum surface settlement(S_(max)).The data set used in this study was compiled from two metro tunnel projects excavated in Hangzhou,China using earth pressure balance(EPB)shields and consists of 14 input features and a single output(i.e.S_(max)).The ML model that is trained on features selected from the Boruta algorithm demonstrates the best performance in both the training and testing phases.The relevant features chosen from the Boruta algorithm further indicate that tunneling-induced settlement is affected by parameters related to tunnel geometry,geological conditions and shield operation.The recently proposed Shapley additive explanations(SHAP)method explores how the input features contribute to the output of a complex ML model.It is observed that the larger settlements are induced during shield tunneling in silty clay.Moreover,the SHAP analysis reveals that the low magnitudes of face pressure at the top of the shield increase the model’s output。展开更多
基金supported by Science and Technology on Reliability and Environmental Engineering Laboratory,Beihang University
文摘The validity of correlation analysis between finite element model（FEM） and modal test data is strongly affected by three factors, i.e., quality of excitation and measurement points in modal test,FEM reduction methods, and correlation check techniques. A new criterion based on modified mode participation（MMP） for choosing the best excitation point is presented. Comparison between this new criterion and mode participation（MP） criterion is made by using Case 1 with a simple printed circuit board（PCB）. The result indicates that this new criterion produces better results. In Case 2, 35 measurement points are selected to perform modal test and correlation analysis while 9 selected in Case 3.System equivalent reduction expansion process（SEREP）, modal assurance criteria（MAC）, coordinate modal assurance criteria（CoMAC）, pseudo orthogonality check（POC） and coordinate orthogonality check（CORTHOG） are used to show the error introduced by modal test in Cases 2 and 3. Case 2 shows that additional errors which cannot be identified by using CoMAC can be found by using CORTHOG.In both Cases 2 and 3, Guyan reduction, improved reduced system（IRS） method, SEREP and Hybrid reduction are compared for accuracy and robustness. The results suggest that the quality of the reduction process is problem dependent. However, the IRS method is an improvement over the Guyan reduction, and the Hybrid reduction is an improvement over the SEREP reduction.
基金Sponsored by the National Natural Science Foundation of China(Grant No.51175222,51275205)
文摘Combined Reliability distribution with correlation analysis,a new method has been proposed to make Reliability distribution where considering the elements about structure correlation and failure correlation of subsystems.Firstly,we make a sequence for subsystems by means of TOPSIS which comprehends the considerations of Reliability allocation,and introducing a Copula connecting function to set up a distribution model based on structure correlation,failure correlation and target correlation,and then acquiring reliability target area of all subsystems by Matlab.In this method,not only the traditional distribution considerations are concerned,but also correlation influences are involved,to achieve supplementing information and optimizing distribution.
文摘According to the data from Henan Statistical Yearbook from 2002 to 2008, from production capital, production conditions, labour inputs and financial support, this paper selects 11 variables influencing comprehensive productivity of agriculture in Henan Province. Through calculation and analysis of grey correlation of variables and comprehensive productivity of agriculture, this paper determines the impact of different variables on comprehensive productivity of agriculture. The results show that the agricultural capital has become the most important factor influencing comprehensive productivity of agriculture in Henan Province, while the impact of production conditions, labour inputs and financial support on comprehensive productivity of agriculture in Henan Province diminishes in turn. Corresponding countermeasures and suggestions are put forward to promote the sustainable development of comprehensive productivity of agriculture in Henan Province as follows: strengthen agricultural financial system building, and ensure agricultural production expenditure; scientifically arrange allocation of agricultural resources, and improve agricultural production conditions; carry out training of agricultural skills, and elevate the quality of agricultural labour forces; increase financial expenditure for agricultural production, and optimize financial expenditure structure.
基金CDC/NIOSH for their partial funding of this work
文摘The difficulties associated with performing direct compression strength tests on rocks lead to the development of indirect test methods for the rock strength assessment. Indirect test methods are simple, more economical, less time-consuming, and easily adaptable to the field. The main aim of this study was to derive correlations between direct and indirect test methods for basalt and rhyolite rock types from Carlin trend deposits in Nevada. In the destructive methods, point load index, block punch index, and splitting tensile strength tests are performed. In the non-destructive methods, Schmidt hammer and ultrasonic pulse velocity tests are performed. Correlations between the direct and indirect compression strength tests are developed using linear and nonlinear regression analysis methods. The results show that the splitting tensile strength has the best correlation with the uniaxial compression strength.Furthermore, the Poisson's ratio has no correlation with any of the direct and indirect test results.
基金supported by the Joint Funds of the National Natural Science Foundation of China(No.U1204612)the Natural Science Foundation of He’nan Educational Committee(No.13A416180)
文摘In order to measure the flow velocity of carbon particle suspension perpendicular to the receiving axis of ultrasound transducer, the standard deviation of photoacoustic Doppler frequency spectrum is used to estimate the bandwidth broadening, and the spectrum standard deviation is calculated by an auto-correlation method. A 532 nm pulsed laser with the repetition rate of 20 Hz is used as a pumping source to generate photoacoustic signal. The photoacoustic signals are detected using a focused PZT ultrasound transducer with the central frequency of 10 MHz. The suspension of carbon particles is driven by a syringe pump. The complex photoacoustic signal is calculated by Hilbert transformation from time domain signal before auto-correlation. The standard deviation of the Doppler bandwidth broadening is calculated by averaging the auto-correlation results of several individual A scans. The feasibility of the proposed method is demonstrated by measuring the spectrum standard deviation of the transversal carbon particle flow from 5.0 mm/s to 8.4 mrn/s. The experimental results show that the auto-correlation result is approximately linearly distributed within the measuring range.
基金The National Natural Science Foundation of China under contract No.51379002the Fundamental Research Funds for the Central Universities of China under contract Nos 3132016322 and 3132016314the Applied Basic Research Project Fund of the Chinese Ministry of Transport of China under contract No.2014329225010
文摘An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system（ANFIS）model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules： the astronomical tide module caused by celestial bodies’ movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system（FIS） structure,three approaches which include grid partition（GP）, fuzzy c-means（FCM） and sub-clustering（SC） are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability.
文摘Based on the analysis of the grain supply and demand gap’s current situation in China, this paper establishes an indicator system for the influence factors of grain supply and demand gap. Then this paper calculates the correlation degree between the main grain varieties’ supply and demand gap and its influence factors. The results show that sown area and unit yield have the greatest impact on wheat supply and demand gap;per capita disposable income and unit yield have the greatest impact on corn supply and demand gap;per capita disposable income and agricultural mechanization level have the greatest impact on the supply and demand gap of soybean and rice. From the analysis results, we can obtain the difference between the factors affecting the grain supply and demand gap, and provide a certain theoretical basis and new ideas for the balance of grain supply and demand in China.
基金Item of the 9-th F ive Plan of the Aeronautical Industrial Corporation
文摘In most of real operational conditions only response data are measurable while the actual excitations are unknown, so modal parameter must be extracted only from responses. This paper gives a theoretical formulation for the cross-correlation functions and cross-power spectra between the outputs under the assumption of white-noise excitation. It widens the field of modal analysis under ambient excitation because many classical methods by impulse response functions or frequency response functions can be used easily for modal analysis under unknown excitation. The Polyreference Complex Exponential method and Eigensystem Realization Algorithm using cross-correlation functions in time domain and Orthogonal Polynomial method using cross-power spectra in frequency domain are applied to a steel frame to extract modal parameters under operational conditions. The modal properties of the steel frame from these three methods are compared with those from frequency response functions analysis. The results show that the modal analysis method using cross-correlation functions or cross-power spectra presented in this paper can extract modal parameters efficiently under unknown excitation.
文摘Smart growth has been gaining increasing attention among academia and practitioners as a new technology-based solution to meet the city disease challenges.In the research,we mainly accomplish two tasks.One builds an evaluation system to measure the smart growth of a city.And the other develops a growth plan.Firstly,coordination coefficient(C value) model is applied to measure the smart degree.To begin with,we divide the indicators into four aspects which involve five parameters.Then,entropy method is used to calculate the weight of every parameter.After normalizing data of indicators,we set up a smart growth indicator evaluation system.Aiming to assessing the detailed performances,we rank the eight cities according to the score of C value which corresponds to our normal cognition.Secondly,based on Salvo combat model and dynamic trend analysis model,We draw up a 20-year growth plan with a period of 5 years for the two cities we choose.The Salvo model is adopted to describe the dynamic process.Dynamic trend analysis model is introduced to gain the optimum solution and the optimal point in every stage.In addition,compared with the point of every stage,we can obtain the proportion of investment in different stages.Thirdly,to evaluate the sensitivity of our model with the OFAT Method,we adjust the parameters k_1,k_2 and O_(ij) approximately.It comes out that the change of k_1,k_2 and O_(ij) has an impact on the C value.But the sensitivity of k_1,k_2 is higher.Lastly,we analyze the influence caused by population growth.To a certain extent,it can be concluded that the plan we made can alleviate the negative impact of population growth through the analysis of the chart.
文摘After the breakout of COVID-19,many entity industries have to shut down.The rapid decline of money transaction caused by the shutdown of the entity industries has shocked the financial service industry while the increase in digital transactions also offers them opportunities.Facing both challenges and opportunities,financial services firms should change their target and compensation policy during the pandemic to survive.After analysing three major firms in this industry by using SOAR method,we conclude four keys for financial services firms to survive in COVID-19.
基金The study was supported by China Universrly of Geosciences(Beijing)Discipline Construction Project(2013−2014 annual support No.12)China University of Geosciences(Beijing)Teaching Research and Teaching Reform Project(JGYB-2012.16).
文摘MBA education has become the fastest growing segment of education in China in recent years and a segment that can now be considered indispensible.However,how best to teach it has long been a source of debate.One of the key issues is how to match student traits with teaching methods.While engaged as teachers of marketing management,the authors collected data by questionnaire,carried out empirical research and data comparison,and undertook contingency analysis.It was found that different personal traits in students lead to different attitudes towards teaching methods.A student’s major in college,gender,and sector of employment has little influence on attitudes towards teaching methods,while age,the most sensitive factor,plays the biggest role,followed by job and class.Therefore,these factors should be taken into consideration when arranging classes,developing the curriculum,and planning teaching methods.
基金supported by the National Key R&D Program of China(2023YFB2906303)Major Program(JD)of Hubei Province(2023BAA013)+1 种基金the National Natural Science Foundation of China(62105111,62225110)the Chilean National Agency for Research and Development(Fondecyt Regular 1241085,Fondequip EQM220113 and Basal AFB240002).
文摘Distributed fiber-optic sensing has become an indispensable tool for large-scale structural and environmentalmonitoring, where spectral interrogation of backscattering light enables high-precision quantitative measurement ofexternal perturbations. Conventional spectral analysis methods, typically based on frequency-domain serialinterrogation or time-to-frequency mapping, face inherent trade-offs between measurement speed, dynamic strainmeasurement range, and system complexity. Here, we present a distributed frequency comb enabled spectrumcorrelationreflectometry as a universal spectral analysis framework that leverages optical frequency comb for parallelmulti-frequency interrogation, which is experimentally demonstrated in a phase-sensitive optical time-domainreflectometry (φ-OTDR) system. This method eliminates the need for large frequency scans, achieving more thantenfold improvement in measurement speed over the state-of-the-art spectral analysis methods. Compared to existingphase-demodulated φ-OTDR systems, this method enables vibration amplitude monitoring with a dynamic strainmeasurement range expanded by more than an order of magnitude, while intrinsically circumventing phaseunwrapping issues and interference fading. This work establishes a new paradigm for distributed spectral analysis,providing a flexible and robust platform for a wide range of sensing technologies, including Rayleigh and Brillouinbasedschemes, which may have significant impact for geophysics, seismology, civil engineering, and other fields.
基金support provided by The Science and Technology Development Fund,Macao SAR,China(File Nos.0057/2020/AGJ and SKL-IOTSC-2021-2023)Science and Technology Program of Guangdong Province,China(Grant No.2021A0505080009).
文摘Accurate prediction of shield tunneling-induced settlement is a complex problem that requires consideration of many influential parameters.Recent studies reveal that machine learning(ML)algorithms can predict the settlement caused by tunneling.However,well-performing ML models are usually less interpretable.Irrelevant input features decrease the performance and interpretability of an ML model.Nonetheless,feature selection,a critical step in the ML pipeline,is usually ignored in most studies that focused on predicting tunneling-induced settlement.This study applies four techniques,i.e.Pearson correlation method,sequential forward selection(SFS),sequential backward selection(SBS)and Boruta algorithm,to investigate the effect of feature selection on the model’s performance when predicting the tunneling-induced maximum surface settlement(S_(max)).The data set used in this study was compiled from two metro tunnel projects excavated in Hangzhou,China using earth pressure balance(EPB)shields and consists of 14 input features and a single output(i.e.S_(max)).The ML model that is trained on features selected from the Boruta algorithm demonstrates the best performance in both the training and testing phases.The relevant features chosen from the Boruta algorithm further indicate that tunneling-induced settlement is affected by parameters related to tunnel geometry,geological conditions and shield operation.The recently proposed Shapley additive explanations(SHAP)method explores how the input features contribute to the output of a complex ML model.It is observed that the larger settlements are induced during shield tunneling in silty clay.Moreover,the SHAP analysis reveals that the low magnitudes of face pressure at the top of the shield increase the model’s output。
