In recent years,deep convolution neural network has exhibited excellent performance in computer vision and has a far-reaching impact.Traditional plant taxonomic identification requires high expertise,which is time-con...In recent years,deep convolution neural network has exhibited excellent performance in computer vision and has a far-reaching impact.Traditional plant taxonomic identification requires high expertise,which is time-consuming.Most nature reserves have problems such as incomplete species surveys,inaccurate taxonomic identification,and untimely updating of status data.Simple and accurate recognition of plant images can be achieved by applying convolutional neural network technology to explore the best network model.Taking 24 typical desert plant species that are widely distributed in the nature reserves in Xinjiang Uygur Autonomous Region of China as the research objects,this study established an image database and select the optimal network model for the image recognition of desert plant species to provide decision support for fine management in the nature reserves in Xinjiang,such as species investigation and monitoring,by using deep learning.Since desert plant species were not included in the public dataset,the images used in this study were mainly obtained through field shooting and downloaded from the Plant Photo Bank of China(PPBC).After the sorting process and statistical analysis,a total of 2331 plant images were finally collected(2071 images from field collection and 260 images from the PPBC),including 24 plant species belonging to 14 families and 22 genera.A large number of numerical experiments were also carried out to compare a series of 37 convolutional neural network models with good performance,from different perspectives,to find the optimal network model that is most suitable for the image recognition of desert plant species in Xinjiang.The results revealed 24 models with a recognition Accuracy,of greater than 70.000%.Among which,Residual Network X_8GF(RegNetX_8GF)performs the best,with Accuracy,Precision,Recall,and F1(which refers to the harmonic mean of the Precision and Recall values)values of 78.33%,77.65%,69.55%,and 71.26%,respectively.Considering the demand factors of hardware equipment and inference time,Mobile NetworkV2 achieves the best balance among the Accuracy,the number of parameters and the number of floating-point operations.The number of parameters for Mobile Network V2(MobileNetV2)is 1/16 of RegNetX_8GF,and the number of floating-point operations is 1/24.Our findings can facilitate efficient decision-making for the management of species survey,cataloging,inspection,and monitoring in the nature reserves in Xinjiang,providing a scientific basis for the protection and utilization of natural plant resources.展开更多
As the era of large-scale highway maintenance arrives,the maintenance strategies have transitioned to a holistic approach that prioritizes safety,economic feasibility,and environmental sustainability.This research int...As the era of large-scale highway maintenance arrives,the maintenance strategies have transitioned to a holistic approach that prioritizes safety,economic feasibility,and environmental sustainability.This research introduces a multi-objective optimization model for highway maintenance that incorporates the interplay of decision-maker preferences across three key objectives:Highway safety performance,maintenance engineering cost,and carbon emissions.This study employs a large-sample data analysis on a subset of the Lianhuo Highway network,which includes 2,842 pavement sections.This approach mitigates the impact of outliers,ensuring a substantial data buffer that fortifies the model’s capacity for generalization and bolsters its robustness.The findings reveal a Pareto-optimal relationship among the three scrutinized variables.A particularly noteworthy observation is the M-shaped trajectory of carbon emissions,which initially rise,then decline,and ultimately rebound,contingent upon the selected maintenance strategy.Furthermore,an examination of the relationship between maintenance costs and safety performance discloses a trend of diminishing marginal returns,illustrating that the incremental gains in safety performance attenuate as maintenance investment escalates.展开更多
Artificial stock market simulation based on agent is an important means to study financial market.Based on the assumption that the investors are composed of a main fund,small trend and contrarian investors characteriz...Artificial stock market simulation based on agent is an important means to study financial market.Based on the assumption that the investors are composed of a main fund,small trend and contrarian investors characterized by four parameters,we simulate and research a kind of financial phenomenon with the characteristics of pyramid schemes.Our simulation results and theoretical analysis reveal the relationships between the rate of return of the main fund and the proportion of the trend investors in all small investors,the small investors'parameters of taking profit and stopping loss,the order size of the main fund and the strategies adopted by the main fund.Our work is helpful to explain the financial phenomenon with the characteristics of pyramid schemes in financial markets,design trading rules for regulators and develop trading strategies for investors.展开更多
In this paper, an application mode and method of knowledge management in remanufacturing engineering management is established based on Nonaka's SECI model. The relationships between knowledge transfer,knowledge s...In this paper, an application mode and method of knowledge management in remanufacturing engineering management is established based on Nonaka's SECI model. The relationships between knowledge transfer,knowledge sharing and remanufacturing engineering management are highlighted. It is noticeable that a great deal of knowledge transfer and sharing activities, which can improve the performance of remanufacturing engineering management constantly, are involved in remanufacturing engineering.展开更多
This paper presents a review of the challenges to engineering management in the Big Data Era as well as the Big Data applications. First, it outlines the definitions of big data, data science and intelligent knowledge...This paper presents a review of the challenges to engineering management in the Big Data Era as well as the Big Data applications. First, it outlines the definitions of big data, data science and intelligent knowledge and the history of big data. Second, the paper reviews the academic activities about big data in China. Then, it elaborates a number of challenging big data problems, including transforming semi-structured and non-structured data into"structured format" and explores the relationship of data heterogeneity, knowledge heterogeneity and decision heterogeneity. Furthermore, the paper reports various real-life applications of big data, such as financial and petroleum engineering and internet business.展开更多
As the first individualization-information processing equipment put into practical service worldwide,Automated Fingerprint Identification System(AFIS)has always been regarded as the first choice in individualization o...As the first individualization-information processing equipment put into practical service worldwide,Automated Fingerprint Identification System(AFIS)has always been regarded as the first choice in individualization of criminal suspects or those who died in mass disasters.By integrating data within the existing regional large-scale AFIS database,many countries are constructing an ultra large state-of-the-art AFIS(or Imperial Scale AFIS)system.Therefore,it is very important to develop a series of ten-print data quality controlling process for this system of this type,which would insure a substantial matching efficiency,as the pouring data come into this imperial scale being.As the image quality of ten-print data is closely relevant to AFIS matching proficiency,a lot of police departments have allocated huge amount of human and financial resources over this issue by carrying out manual verification works for years.Unfortunately,quality control method above is always proved to be inadequate because it is an astronomical task involved,in which it has always been problematic and less affiant for potential errors.Hence,we will implement quality control in the above procedure with supplementary-acquisition effect caused by the delay of feedback instructions sent from the human verification teams.In this article,a series of fingerprint image quality supervising techniques has been put forward,which makes it possible for computer programs to supervise the ten-print image quality in real-time and more accurate manner as substitute for traditional manual verifications.Besides its prominent advantages in the human and financial expenditures,it has also been proved to obviously improve the image quality of the AFIS ten-print database,which leads up to a dramatic improvement in the AFIS-matching accuracy as well.展开更多
Literature shows that both market data and financial media impact stock prices;however,using only one kind of data may lead to information bias.Therefore,this study uses market data and news to investigate their joint...Literature shows that both market data and financial media impact stock prices;however,using only one kind of data may lead to information bias.Therefore,this study uses market data and news to investigate their joint impact on stock price trends.However,combining these two types of information is difficult because of their completely different characteristics.This study develops a hybrid model called MVL-SVM for stock price trend prediction by integrating multi-view learning with a support vector machine(SVM).It works by simply inputting heterogeneous multi-view data simultaneously,which may reduce information loss.Compared with the ARIMA and classic SVM models based on single-and multi-view data,our hybrid model shows statistically significant advantages.In the robustness test,our model outperforms the others by at least 10%accuracy when the sliding windows of news and market data are set to 1–5 days,which confirms our model’s effectiveness.Finally,trading strategies based on single stock and investment portfolios are constructed separately,and the simulations show that MVL-SVM has better profitability and risk control performance than the benchmarks.展开更多
Web search query data are obtained to reflect social spots and serve as novel economic indicators. When faced with high-dimensional query data, selecting keywords that have plausible predictive ability and can reduce ...Web search query data are obtained to reflect social spots and serve as novel economic indicators. When faced with high-dimensional query data, selecting keywords that have plausible predictive ability and can reduce dimensionality is critical. This paper presents a new integrative method that combines Hurst Exponent （HE） and Time Difference Correlation （TDC） analysis to select keywords with powerful predictive ability. The method is called the HE-TDC screening method and requires keywords with predictive ability to satisfy two characteristics, namely, high correlation and fluctuation memorability similar to the predicting target series. An empirical study is employed to predict the volume of tourism visitors in the Jiuzhai Valley scenic area. The study shows that keywords selected using HE-TDC method produce a model with better robustness and predictive ability.展开更多
The developable surface is an important surface in computer aided design, geometric modeling and industrial manufactory. It is often given in the standard parametric form, but it can also be in the implicit form which...The developable surface is an important surface in computer aided design, geometric modeling and industrial manufactory. It is often given in the standard parametric form, but it can also be in the implicit form which is commonly used in algebraic geometry. Not all algebraic developable surfaces have rational parametrizations. In this paper, the authors focus on the rational developable surfaces. For a given algebraic surface, the authors first determine whether it is developable by geometric inspection, and then give a rational proper parametrization in the affrmative case. For a rational parametric surface, the authors also determine the developability and give a proper reparametrization for the developable surface.展开更多
The increasing importance of technology foresight has simultaneously raised the significance of methods that determine crucial areas and technologies.However,qualitative and quantitative methods have shortcomings.The ...The increasing importance of technology foresight has simultaneously raised the significance of methods that determine crucial areas and technologies.However,qualitative and quantitative methods have shortcomings.The former involve high costs and many limitations,while the latter lack expert experience.Intelligent knowledge management emphasizes human–machine integration,which combines the advantages of expert experience and data mining.Thus,we proposed a new technology foresight method based on intelligent knowledge management.This method constructs a technological online platform to increase the number of participating experts.A secondary mining is performed on the results of patent analysis and bibliometrics.Thus,forward-looking,innovative,and disruptive areas and relevant experts must be discovered through the following comprehensive process:Topic acquisition→topic delivery→topic monitoring→topic guidance→topic reclamation→topic sorting→topic evolution→topic conforming→expert recommendation.展开更多
In recent years,China has witnessed the rapid development in housing finance,and there have emerged constantly real estate finance innovations;however,there exists no relevant index for measuring the innovations of Ch...In recent years,China has witnessed the rapid development in housing finance,and there have emerged constantly real estate finance innovations;however,there exists no relevant index for measuring the innovations of China's real estate finance.Based on the perspectives of the governments,enterprises and the public,this paper constructs the"innovation index of real estate finance"on a quarterly basis from 2009 to 2019,with the method of empowerment which combines the subjective method(analytic hierarchy process)and the objective one(range coefficient method).It clearly and concretely depicts the innovations in housing finance and the related temporal-spatial characteristics in China since the outbreak of the financial crisis in 2008.The index covers 30 provinces,autonomous regions and municipalities directly under the central government,and analyzes its temporal and spatial characteristics.The findings show that there exist a strong spatial autocorrelation and a big regional difference in innovations.展开更多
Price differentiation or discrimination strategy has been regarded as the best choice for firms with online and offline channels, however, recent years often witnessed the practices of the uniform pricing strategy. Th...Price differentiation or discrimination strategy has been regarded as the best choice for firms with online and offline channels, however, recent years often witnessed the practices of the uniform pricing strategy. This paper aims to address the question whether the uniform pricing strategy may be better for the manufacturer, when the uniform pricing strategy has a positive impact on increasing the ciistomer demand and reducing the operations cost. The research shows that the uniform pricing strategy can be bet ter than the price differentiation strategy when the cost saving and demand increasing are large enough or the consumers' acceptance of online channel lies in a certain interval. Moreover, the manufac tu rers or brand owners need a tradeoff bet ween the benefit from online channel and the negative impact from the offline channel when they implement the price differentiation strategy. Finally, the authors obtain some managerial insights and implications based on the numerical analyses, which are in line with the phenomena in practice.展开更多
There are various types of pyramid schemes that have inflicted or are inflicting losses on many people in the world.We propose a pyramid scheme model which has the principal characters of many pyramid schemes that hav...There are various types of pyramid schemes that have inflicted or are inflicting losses on many people in the world.We propose a pyramid scheme model which has the principal characters of many pyramid schemes that have appeared in recent years: promising high returns, rewarding the participants for recruiting the next generation of participants, and the organizer takes all of the money away when they find that the money from the new participants is not enough to pay the previous participants interest and rewards.We assume that the pyramid scheme is carried out in the tree network, Erd?s–Réney(ER) random network, Strogatz–Watts(SW) small-world network, or Barabasi–Albert(BA) scale-free network.We then give the analytical results of the generations that the pyramid scheme can last in these cases.We also use our model to analyze a pyramid scheme in the real world and we find that the connections between participants in the pyramid scheme may constitute a SW small-world network.展开更多
In this paper, we develop an extended model for the project portfolio selection problem over a planning horizon with multiple time periods. The model incorporates the factors of project divisibility and interdependenc...In this paper, we develop an extended model for the project portfolio selection problem over a planning horizon with multiple time periods. The model incorporates the factors of project divisibility and interdependency at the same time for real-life applications. The project divisibility is considered as a strategy, not an unfortunate event as in the literature, in choosing the best execution schedule for the projects, and the classical concept of＂project interdependencies＂ among fully executed projects is then extended to the portions of executed projects. Additional constraints of reinvestment consideration, setup cost, cardinality restriction, precedence relationship and scheduling are also included in the model. For efficient computations, an equivalent mixed integer linear programming representation of the proposed model is derived. Numerical examples under four scenarios are presented to highlight the characteristics of the proposed model. In particular, the positive effects of project divisibility are shown for the first time.展开更多
This paper focuses on overall and sub-process supply chain efficiency evaluation using a network slacks-based measure model and an undesirable directional distance model. Based on a case analysis of a leading Chinese ...This paper focuses on overall and sub-process supply chain efficiency evaluation using a network slacks-based measure model and an undesirable directional distance model. Based on a case analysis of a leading Chinese B2 C firm W, a two-stage supply chain structure covering procurementstock and inventory-sale management is constructed. The research shows overall supply chain inefficiency is attributable to procurement-stock conversion inefficiency. From a view of operations model,the third-party platform model is more efficient than a "shop in shop" self-operated model. However,the self-operated mode performs better in product categories such as computer & Office & digital, food& drink and healthy products due to these products' delivery characteristics and consumers' shopping habits. In the logistics selection, most e-retail players are inclined to choose the hybrid model of 3 PL and self-operated logistics with the product category extension from vertical model to all-category model. These findings may help managers improve supplier-buyer relationship and strengthen supply chain management. This research offers a new explanation regarding the failure of e-retail supply chain.展开更多
The distance-based regression model has many applications in analysis of multivariate response regression in various ?elds, such as ecology, genomics, genetics, human microbiomics, and neuroimaging. It yields a pseudo...The distance-based regression model has many applications in analysis of multivariate response regression in various ?elds, such as ecology, genomics, genetics, human microbiomics, and neuroimaging. It yields a pseudo F test statistic that assesses the relation between the distance(dissimilarity) of the subjects and the predictors of interest. Despite its popularity in recent decades, the statistical properties of the pseudo F test statistic have not been revealed to our knowledge. This study derives the asymptotic properties of the pseudo F test statistic using spectral decomposition under the matrix normal assumption, when the utilized dissimilarity measure is the Euclidean or Mahalanobis distance. The pseudo F test statistic with the Euclidean distance has the same distribution as the quotient of two Chi-squared-type mixtures. The denominator and numerator of the quotient are approximated using a random variable of the form ξχ_d^2+ η, and the approximate error bound is given. The pseudo F test statistic with the Mahalanobis distance follows an F distribution.In simulation studies, the approximated distribution well matched the "exact" distribution obtained by the permutation procedure. The obtained distribution was further validated on H1N1 in?uenza data, aging human brain data, and embryonic imprint data.展开更多
Stochastic gradient descent(SGD) is one of the most common optimization algorithms used in pattern recognition and machine learning.This algorithm and its variants are the preferred algorithm while optimizing paramete...Stochastic gradient descent(SGD) is one of the most common optimization algorithms used in pattern recognition and machine learning.This algorithm and its variants are the preferred algorithm while optimizing parameters of deep neural network for their advantages of low storage space requirement and fast computation speed.Previous studies on convergence of these algorithms were based on some traditional assumptions in optimization problems.However,the deep neural network has its unique properties.Some assumptions are inappropriate in the actual optimization process of this kind of model.In this paper,we modify the assumptions to make them more consistent with the actual optimization process of deep neural network.Based on new assumptions,we studied the convergence and convergence rate of SGD and its two common variant algorithms.In addition,we carried out numerical experiments with LeNet-5,a common network framework,on the data set MNIST to verify the rationality of our assumptions.展开更多
Reduction of carbon dioxide(CO2)emissions is one of the biggest challenges for global sustainable development,in which economic growth characterized by industrialization plays a formidable role.We innovatively adopted...Reduction of carbon dioxide(CO2)emissions is one of the biggest challenges for global sustainable development,in which economic growth characterized by industrialization plays a formidable role.We innovatively adopted the input and output(I-O)table of 41 countries released by World I-O Database to determine the industrial structure change and analyze its impact on CO2 emission evolution by developing a cross-country panel model.The empirical results show that industrial structure change has a significantly negative effect on CO2 emissions;to be specific,0.1 unit increase in the linkage of manufacturing sector and service sector will lead to a decrease of 0.94 metric tons per capita CO2 emissions,indicating that upgrading industrial structure contributes to carbon mitigation and sustainable development.Further,urbanization,technology and trade openness have significantly negative impact on CO2 emissions,while economy growth and energy use take positive impacts.In particular,a 1%increase in per capita income will contribute to an increase of 8.6 metric tons per capita CO2 emissions.However,the effect of industrial structure on environment degradation is moderated by technology level.These findings fill the gaps of previous literature and provide valuable references for effective policies to mitigate CO2 emissions and achieve sustainable development.展开更多
Since China began reforming and opening up its economy,and especially since the launch of development projects in western China,province A has attracted an increasing amount of investment,which is the main driving for...Since China began reforming and opening up its economy,and especially since the launch of development projects in western China,province A has attracted an increasing amount of investment,which is the main driving force for provincial economic growth.Hence,this study uses a state space model to examine how government investment has affected economic growth in province A in western China,and explains whether there is a crowding-in effect or a crowding-out effect of local government investment on private investment.The findings indicate that both government and private investments have a positive,stimulating influence on economic growth in province A,with the latter being more impactful than the former.Productive and non-productive investments have different effects on province A’s economic growth.From the perspective of the trajectory of government investment elasticity,the elasticity of government and private investments in province A presents a very large spatio-temporal change.That is,from 1994 to 2009,government investment in province A had a crowding-in effect on private investment,but from 2010 to 2017,a crowding-out effect was observed.展开更多
China’s grain science and technology policies have played an important role in the development of China’s food industry.This paper aims to examine the effects of China’s grain science and technology policies on foo...China’s grain science and technology policies have played an important role in the development of China’s food industry.This paper aims to examine the effects of China’s grain science and technology policies on food security.It quantitatively assesses China’s food security by analyzing the main contents and development trends of China’s food science technology policies through the text metrology method,and then investigates the effects of grain science and technology policies on food security by employing a provincial dynamic panel model.The results show that food security in China is all-round developed,and that the release frequency and cumulative effect of grain science and technology policies play a significant role in promoting food security.Powerful grain science and technology policies can effectively guarantee China’s food security.展开更多
基金supported by the West Light Foundation of the Chinese Academy of Sciences(2019-XBQNXZ-A-007)the National Natural Science Foundation of China(12071458,71731009).
文摘In recent years,deep convolution neural network has exhibited excellent performance in computer vision and has a far-reaching impact.Traditional plant taxonomic identification requires high expertise,which is time-consuming.Most nature reserves have problems such as incomplete species surveys,inaccurate taxonomic identification,and untimely updating of status data.Simple and accurate recognition of plant images can be achieved by applying convolutional neural network technology to explore the best network model.Taking 24 typical desert plant species that are widely distributed in the nature reserves in Xinjiang Uygur Autonomous Region of China as the research objects,this study established an image database and select the optimal network model for the image recognition of desert plant species to provide decision support for fine management in the nature reserves in Xinjiang,such as species investigation and monitoring,by using deep learning.Since desert plant species were not included in the public dataset,the images used in this study were mainly obtained through field shooting and downloaded from the Plant Photo Bank of China(PPBC).After the sorting process and statistical analysis,a total of 2331 plant images were finally collected(2071 images from field collection and 260 images from the PPBC),including 24 plant species belonging to 14 families and 22 genera.A large number of numerical experiments were also carried out to compare a series of 37 convolutional neural network models with good performance,from different perspectives,to find the optimal network model that is most suitable for the image recognition of desert plant species in Xinjiang.The results revealed 24 models with a recognition Accuracy,of greater than 70.000%.Among which,Residual Network X_8GF(RegNetX_8GF)performs the best,with Accuracy,Precision,Recall,and F1(which refers to the harmonic mean of the Precision and Recall values)values of 78.33%,77.65%,69.55%,and 71.26%,respectively.Considering the demand factors of hardware equipment and inference time,Mobile NetworkV2 achieves the best balance among the Accuracy,the number of parameters and the number of floating-point operations.The number of parameters for Mobile Network V2(MobileNetV2)is 1/16 of RegNetX_8GF,and the number of floating-point operations is 1/24.Our findings can facilitate efficient decision-making for the management of species survey,cataloging,inspection,and monitoring in the nature reserves in Xinjiang,providing a scientific basis for the protection and utilization of natural plant resources.
基金Supported by the National Natural Science Foundation of China(72471223,72231010)。
文摘As the era of large-scale highway maintenance arrives,the maintenance strategies have transitioned to a holistic approach that prioritizes safety,economic feasibility,and environmental sustainability.This research introduces a multi-objective optimization model for highway maintenance that incorporates the interplay of decision-maker preferences across three key objectives:Highway safety performance,maintenance engineering cost,and carbon emissions.This study employs a large-sample data analysis on a subset of the Lianhuo Highway network,which includes 2,842 pavement sections.This approach mitigates the impact of outliers,ensuring a substantial data buffer that fortifies the model’s capacity for generalization and bolsters its robustness.The findings reveal a Pareto-optimal relationship among the three scrutinized variables.A particularly noteworthy observation is the M-shaped trajectory of carbon emissions,which initially rise,then decline,and ultimately rebound,contingent upon the selected maintenance strategy.Furthermore,an examination of the relationship between maintenance costs and safety performance discloses a trend of diminishing marginal returns,illustrating that the incremental gains in safety performance attenuate as maintenance investment escalates.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.71932008 and 91546201).
文摘Artificial stock market simulation based on agent is an important means to study financial market.Based on the assumption that the investors are composed of a main fund,small trend and contrarian investors characterized by four parameters,we simulate and research a kind of financial phenomenon with the characteristics of pyramid schemes.Our simulation results and theoretical analysis reveal the relationships between the rate of return of the main fund and the proportion of the trend investors in all small investors,the small investors'parameters of taking profit and stopping loss,the order size of the main fund and the strategies adopted by the main fund.Our work is helpful to explain the financial phenomenon with the characteristics of pyramid schemes in financial markets,design trading rules for regulators and develop trading strategies for investors.
基金supported by National Natural Science Foundation of China (Grant No. 71471169 and Grant No. 71071151)
文摘In this paper, an application mode and method of knowledge management in remanufacturing engineering management is established based on Nonaka's SECI model. The relationships between knowledge transfer,knowledge sharing and remanufacturing engineering management are highlighted. It is noticeable that a great deal of knowledge transfer and sharing activities, which can improve the performance of remanufacturing engineering management constantly, are involved in remanufacturing engineering.
基金supported by the key research grant"Innovative Research on Management Decision Making under Big Data Environment"(Grant No.71331005)"Non-structured Data Analysis Methods and Key Technologies for Management Decision Making"(Grant No.71501175)the key international collaboration grant"Business Intelligence Methods Based on Optimization Data Mining with Applications of Financial and Banking Management"(Grant No.71110107026)from the National Natural Science Foundation of China
文摘This paper presents a review of the challenges to engineering management in the Big Data Era as well as the Big Data applications. First, it outlines the definitions of big data, data science and intelligent knowledge and the history of big data. Second, the paper reviews the academic activities about big data in China. Then, it elaborates a number of challenging big data problems, including transforming semi-structured and non-structured data into"structured format" and explores the relationship of data heterogeneity, knowledge heterogeneity and decision heterogeneity. Furthermore, the paper reports various real-life applications of big data, such as financial and petroleum engineering and internet business.
基金The authors gratefully acknowledge the support of the Swiss National Science Foundation(through grant No.IZ32Z0_l68366)the University of Lausanne,and the support of the Collaborative Innovation Center of Judicial Civilization,China.And the authors also gratefully acknowledge the support of Liaoning Provincial Police Key Scientific Research Proj ect(through grant No.2016LNKJJH01)China Ministry of Public Safety Key Scientific Research Project(through grant No.2016JSYJAO1).
文摘As the first individualization-information processing equipment put into practical service worldwide,Automated Fingerprint Identification System(AFIS)has always been regarded as the first choice in individualization of criminal suspects or those who died in mass disasters.By integrating data within the existing regional large-scale AFIS database,many countries are constructing an ultra large state-of-the-art AFIS(or Imperial Scale AFIS)system.Therefore,it is very important to develop a series of ten-print data quality controlling process for this system of this type,which would insure a substantial matching efficiency,as the pouring data come into this imperial scale being.As the image quality of ten-print data is closely relevant to AFIS matching proficiency,a lot of police departments have allocated huge amount of human and financial resources over this issue by carrying out manual verification works for years.Unfortunately,quality control method above is always proved to be inadequate because it is an astronomical task involved,in which it has always been problematic and less affiant for potential errors.Hence,we will implement quality control in the above procedure with supplementary-acquisition effect caused by the delay of feedback instructions sent from the human verification teams.In this article,a series of fingerprint image quality supervising techniques has been put forward,which makes it possible for computer programs to supervise the ten-print image quality in real-time and more accurate manner as substitute for traditional manual verifications.Besides its prominent advantages in the human and financial expenditures,it has also been proved to obviously improve the image quality of the AFIS ten-print database,which leads up to a dramatic improvement in the AFIS-matching accuracy as well.
基金partly supported by National Natural Science Foundation of China(No.71771204,72231010)the Fundamental Research Funds for the Central Universities(No.E0E48946X2).
文摘Literature shows that both market data and financial media impact stock prices;however,using only one kind of data may lead to information bias.Therefore,this study uses market data and news to investigate their joint impact on stock price trends.However,combining these two types of information is difficult because of their completely different characteristics.This study develops a hybrid model called MVL-SVM for stock price trend prediction by integrating multi-view learning with a support vector machine(SVM).It works by simply inputting heterogeneous multi-view data simultaneously,which may reduce information loss.Compared with the ARIMA and classic SVM models based on single-and multi-view data,our hybrid model shows statistically significant advantages.In the robustness test,our model outperforms the others by at least 10%accuracy when the sliding windows of news and market data are set to 1–5 days,which confirms our model’s effectiveness.Finally,trading strategies based on single stock and investment portfolios are constructed separately,and the simulations show that MVL-SVM has better profitability and risk control performance than the benchmarks.
文摘Web search query data are obtained to reflect social spots and serve as novel economic indicators. When faced with high-dimensional query data, selecting keywords that have plausible predictive ability and can reduce dimensionality is critical. This paper presents a new integrative method that combines Hurst Exponent （HE） and Time Difference Correlation （TDC） analysis to select keywords with powerful predictive ability. The method is called the HE-TDC screening method and requires keywords with predictive ability to satisfy two characteristics, namely, high correlation and fluctuation memorability similar to the predicting target series. An empirical study is employed to predict the volume of tourism visitors in the Jiuzhai Valley scenic area. The study shows that keywords selected using HE-TDC method produce a model with better robustness and predictive ability.
基金supported by Beijing Nova Program under Grant No.Z121104002512065The author PerezDíaz S is a member of the Research Group ASYNACS(Ref.CCEE2011/R34)
文摘The developable surface is an important surface in computer aided design, geometric modeling and industrial manufactory. It is often given in the standard parametric form, but it can also be in the implicit form which is commonly used in algebraic geometry. Not all algebraic developable surfaces have rational parametrizations. In this paper, the authors focus on the rational developable surfaces. For a given algebraic surface, the authors first determine whether it is developable by geometric inspection, and then give a rational proper parametrization in the affrmative case. For a rational parametric surface, the authors also determine the developability and give a proper reparametrization for the developable surface.
基金The work is supported by the National Natural Science Foundation of China(Grant Nos.71471169,91546201 and 71071151).
文摘The increasing importance of technology foresight has simultaneously raised the significance of methods that determine crucial areas and technologies.However,qualitative and quantitative methods have shortcomings.The former involve high costs and many limitations,while the latter lack expert experience.Intelligent knowledge management emphasizes human–machine integration,which combines the advantages of expert experience and data mining.Thus,we proposed a new technology foresight method based on intelligent knowledge management.This method constructs a technological online platform to increase the number of participating experts.A secondary mining is performed on the results of patent analysis and bibliometrics.Thus,forward-looking,innovative,and disruptive areas and relevant experts must be discovered through the following comprehensive process:Topic acquisition→topic delivery→topic monitoring→topic guidance→topic reclamation→topic sorting→topic evolution→topic conforming→expert recommendation.
基金Supported by the National Science Foundation of China (71850014,71974108)Research on the Scientific and Technological Support Measures to Ensure Financial Security (2020-ZW10-A-022)R&D Program of China Construction Second Engineering Bureau Ltd (2021ZX190001)。
文摘In recent years,China has witnessed the rapid development in housing finance,and there have emerged constantly real estate finance innovations;however,there exists no relevant index for measuring the innovations of China's real estate finance.Based on the perspectives of the governments,enterprises and the public,this paper constructs the"innovation index of real estate finance"on a quarterly basis from 2009 to 2019,with the method of empowerment which combines the subjective method(analytic hierarchy process)and the objective one(range coefficient method).It clearly and concretely depicts the innovations in housing finance and the related temporal-spatial characteristics in China since the outbreak of the financial crisis in 2008.The index covers 30 provinces,autonomous regions and municipalities directly under the central government,and analyzes its temporal and spatial characteristics.The findings show that there exist a strong spatial autocorrelation and a big regional difference in innovations.
基金partially supported by the National Natural Science Foundation of China under Grant Nos.71390331,71461009,71761015,71202114Science and Technology Project of Jiangxi Provincial Education Department under Grant No.GJJ160436
文摘Price differentiation or discrimination strategy has been regarded as the best choice for firms with online and offline channels, however, recent years often witnessed the practices of the uniform pricing strategy. This paper aims to address the question whether the uniform pricing strategy may be better for the manufacturer, when the uniform pricing strategy has a positive impact on increasing the ciistomer demand and reducing the operations cost. The research shows that the uniform pricing strategy can be bet ter than the price differentiation strategy when the cost saving and demand increasing are large enough or the consumers' acceptance of online channel lies in a certain interval. Moreover, the manufac tu rers or brand owners need a tradeoff bet ween the benefit from online channel and the negative impact from the offline channel when they implement the price differentiation strategy. Finally, the authors obtain some managerial insights and implications based on the numerical analyses, which are in line with the phenomena in practice.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.71771204 and 91546201)
文摘There are various types of pyramid schemes that have inflicted or are inflicting losses on many people in the world.We propose a pyramid scheme model which has the principal characters of many pyramid schemes that have appeared in recent years: promising high returns, rewarding the participants for recruiting the next generation of participants, and the organizer takes all of the money away when they find that the money from the new participants is not enough to pay the previous participants interest and rewards.We assume that the pyramid scheme is carried out in the tree network, Erd?s–Réney(ER) random network, Strogatz–Watts(SW) small-world network, or Barabasi–Albert(BA) scale-free network.We then give the analytical results of the generations that the pyramid scheme can last in these cases.We also use our model to analyze a pyramid scheme in the real world and we find that the connections between participants in the pyramid scheme may constitute a SW small-world network.
文摘In this paper, we develop an extended model for the project portfolio selection problem over a planning horizon with multiple time periods. The model incorporates the factors of project divisibility and interdependency at the same time for real-life applications. The project divisibility is considered as a strategy, not an unfortunate event as in the literature, in choosing the best execution schedule for the projects, and the classical concept of＂project interdependencies＂ among fully executed projects is then extended to the portions of executed projects. Additional constraints of reinvestment consideration, setup cost, cardinality restriction, precedence relationship and scheduling are also included in the model. For efficient computations, an equivalent mixed integer linear programming representation of the proposed model is derived. Numerical examples under four scenarios are presented to highlight the characteristics of the proposed model. In particular, the positive effects of project divisibility are shown for the first time.
基金supported by the National Nature Science Foundation of China under Grant Nos.71390330,70921061,71202114 and 71331005the Hong Kong CERG Research Fund Polyu 5515/10HShandong Independent Innovation and Achievement Transformation Special Fund of China(2014ZZCX03302)
文摘This paper focuses on overall and sub-process supply chain efficiency evaluation using a network slacks-based measure model and an undesirable directional distance model. Based on a case analysis of a leading Chinese B2 C firm W, a two-stage supply chain structure covering procurementstock and inventory-sale management is constructed. The research shows overall supply chain inefficiency is attributable to procurement-stock conversion inefficiency. From a view of operations model,the third-party platform model is more efficient than a "shop in shop" self-operated model. However,the self-operated mode performs better in product categories such as computer & Office & digital, food& drink and healthy products due to these products' delivery characteristics and consumers' shopping habits. In the logistics selection, most e-retail players are inclined to choose the hybrid model of 3 PL and self-operated logistics with the product category extension from vertical model to all-category model. These findings may help managers improve supplier-buyer relationship and strengthen supply chain management. This research offers a new explanation regarding the failure of e-retail supply chain.
基金supported by National Natural Science Foundation of China (Grant No. 11722113)
文摘The distance-based regression model has many applications in analysis of multivariate response regression in various ?elds, such as ecology, genomics, genetics, human microbiomics, and neuroimaging. It yields a pseudo F test statistic that assesses the relation between the distance(dissimilarity) of the subjects and the predictors of interest. Despite its popularity in recent decades, the statistical properties of the pseudo F test statistic have not been revealed to our knowledge. This study derives the asymptotic properties of the pseudo F test statistic using spectral decomposition under the matrix normal assumption, when the utilized dissimilarity measure is the Euclidean or Mahalanobis distance. The pseudo F test statistic with the Euclidean distance has the same distribution as the quotient of two Chi-squared-type mixtures. The denominator and numerator of the quotient are approximated using a random variable of the form ξχ_d^2+ η, and the approximate error bound is given. The pseudo F test statistic with the Mahalanobis distance follows an F distribution.In simulation studies, the approximated distribution well matched the "exact" distribution obtained by the permutation procedure. The obtained distribution was further validated on H1N1 in?uenza data, aging human brain data, and embryonic imprint data.
基金supported by the National Natural Science Foundation of China(Nos.11731013,U19B2040,11991022)by the Leading Project of the Chinese Academy of Sciences(Nos.XDA27010102,XDA27010302)。
文摘Stochastic gradient descent(SGD) is one of the most common optimization algorithms used in pattern recognition and machine learning.This algorithm and its variants are the preferred algorithm while optimizing parameters of deep neural network for their advantages of low storage space requirement and fast computation speed.Previous studies on convergence of these algorithms were based on some traditional assumptions in optimization problems.However,the deep neural network has its unique properties.Some assumptions are inappropriate in the actual optimization process of this kind of model.In this paper,we modify the assumptions to make them more consistent with the actual optimization process of deep neural network.Based on new assumptions,we studied the convergence and convergence rate of SGD and its two common variant algorithms.In addition,we carried out numerical experiments with LeNet-5,a common network framework,on the data set MNIST to verify the rationality of our assumptions.
基金Supported by the National Natural Science Foundation of China(71403260,71573244,71532013).
文摘Reduction of carbon dioxide(CO2)emissions is one of the biggest challenges for global sustainable development,in which economic growth characterized by industrialization plays a formidable role.We innovatively adopted the input and output(I-O)table of 41 countries released by World I-O Database to determine the industrial structure change and analyze its impact on CO2 emission evolution by developing a cross-country panel model.The empirical results show that industrial structure change has a significantly negative effect on CO2 emissions;to be specific,0.1 unit increase in the linkage of manufacturing sector and service sector will lead to a decrease of 0.94 metric tons per capita CO2 emissions,indicating that upgrading industrial structure contributes to carbon mitigation and sustainable development.Further,urbanization,technology and trade openness have significantly negative impact on CO2 emissions,while economy growth and energy use take positive impacts.In particular,a 1%increase in per capita income will contribute to an increase of 8.6 metric tons per capita CO2 emissions.However,the effect of industrial structure on environment degradation is moderated by technology level.These findings fill the gaps of previous literature and provide valuable references for effective policies to mitigate CO2 emissions and achieve sustainable development.
基金Supported by the National Natural Science Foundation of China(12071458,71731009)。
文摘Since China began reforming and opening up its economy,and especially since the launch of development projects in western China,province A has attracted an increasing amount of investment,which is the main driving force for provincial economic growth.Hence,this study uses a state space model to examine how government investment has affected economic growth in province A in western China,and explains whether there is a crowding-in effect or a crowding-out effect of local government investment on private investment.The findings indicate that both government and private investments have a positive,stimulating influence on economic growth in province A,with the latter being more impactful than the former.Productive and non-productive investments have different effects on province A’s economic growth.From the perspective of the trajectory of government investment elasticity,the elasticity of government and private investments in province A presents a very large spatio-temporal change.That is,from 1994 to 2009,government investment in province A had a crowding-in effect on private investment,but from 2010 to 2017,a crowding-out effect was observed.
基金Supported by Chinese Academy of Sciences(KJZD-EW-G20)the National Natural Science Foundation of China(71974180)
文摘China’s grain science and technology policies have played an important role in the development of China’s food industry.This paper aims to examine the effects of China’s grain science and technology policies on food security.It quantitatively assesses China’s food security by analyzing the main contents and development trends of China’s food science technology policies through the text metrology method,and then investigates the effects of grain science and technology policies on food security by employing a provincial dynamic panel model.The results show that food security in China is all-round developed,and that the release frequency and cumulative effect of grain science and technology policies play a significant role in promoting food security.Powerful grain science and technology policies can effectively guarantee China’s food security.
