By using the method of density-matrix renormalization-group to solve the different spin spin correlation functions, the nearest-neighbouring entanglement （NNE） and the next-nearest-neighbouring entanglement （NNNE）...By using the method of density-matrix renormalization-group to solve the different spin spin correlation functions, the nearest-neighbouring entanglement （NNE） and the next-nearest-neighbouring entanglement （NNNE） of one-dimensional alternating Heisenberg XY spin chain are investigated in the presence of alternating the-nearestneighbouring interaction of exchange couplings, external magnetic fields and the next-nearest neighbouring interaction. For a dimerised ferromagnetic spin chain, the NNNE appears only above a critical dimerized interaction, meanwhile, the dimerized interaction a effects a quantum phase transition point and improves the NNNE to a large extent. We also study the effect of ferromagnetic or antiferromagnetic next-nearest neighbouring （NNN） interaction on the dynamics of NNE and NNNE. The ferromagnetic NNN interaction increases and shrinks the NNE below and above a critical frustrated interaction respectively, while the antiferromagnetic NNN interaction always reduces the NNE. The antiferromagnetic NNN interaction results in a large value of NNNE compared with the case where the NNN interaction is ferromagnetic.展开更多
The paper systematically deals with the background of regional isotopic compo-sitions in the lower and middle reaches of the Yangtze River and neighbouring areas. It isshown that the lead isotopic compositions of diff...The paper systematically deals with the background of regional isotopic compo-sitions in the lower and middle reaches of the Yangtze River and neighbouring areas. It isshown that the lead isotopic compositions of different geological formations and units are con-trolled by the primary mantle heterogeneity, dynamic process of crust-mantle interchange,abundances of uraninm, thorium and lead of various layers of the earth and timing. Studies onthe background of regional isotopic compositions may offer significant information forgeochemical regionalization, tracing of sources of ore-forming materials, and regionalprognosis of ore deposits.展开更多
VisuShrink, ModineighShrink and NeighShrink are efficient image denoising algorithms based on the discrete wavelet transform (DWT). These methods have disadvantage of using a suboptimal universal threshold and identic...VisuShrink, ModineighShrink and NeighShrink are efficient image denoising algorithms based on the discrete wavelet transform (DWT). These methods have disadvantage of using a suboptimal universal threshold and identical neighbouring window size in all wavelet subbands. In this paper, an improved method is proposed, that determines a threshold as well as neighbouring window size for every subband using its lengths. Our experimental results illustrate that the proposed approach is better than the existing ones, i.e., NeighShrink, ModineighShrink and VisuShrink in terms of peak signal-to-noise ratio (PSNR) i.e. visual quality of the image.展开更多
Forest health is currently assessed in Europe （ICP Forests monitoring program）. Crown defoliation and dieback, tree mortality, and pathogenic damage are the main aspects considered in tree health assessment. The wor...Forest health is currently assessed in Europe （ICP Forests monitoring program）. Crown defoliation and dieback, tree mortality, and pathogenic damage are the main aspects considered in tree health assessment. The worsening of environmental conditions （i.e., increase of temperature and drought events） may cause large-spatial scale tree mortality and forest decline. However, the role of stand features, including tree species assemblage and diversity as factors that modify environmental impacts, is poorly considered. The present contribution reanalyses the historical dataset of crown conditions in Italian forests from ] 997 to 2014 to identify ecological and structural factors that influence tree crown defoliation, highlighting in a special manner the role of tree diversity. The effects of tree diversity were explored using the entire data set through multivariate cluster analyses and on individual trees, analysing the influence of the neighbouring tree diversity and identity at the local （neighbour） level. Preliminary results suggest that each tree species shows a specific behaviour in relation to crown defoliation, and the distribution of crown defoliation across Italian forests reflects the distribution of the main forest types and their ecological equilibrium with the environment. The potentiality and the problems connected to the possible extension of this analysis at a more general level （European and North American） were discussed.展开更多
Under the guide of advanced theories of geosciences, new technology and methods of prospecting, integrating sedimentation, magmatic emplacement, metamorphism and deformation with mineralization by means of intersectio...Under the guide of advanced theories of geosciences, new technology and methods of prospecting, integrating sedimentation, magmatic emplacement, metamorphism and deformation with mineralization by means of intersectional subjects, the author has revealed that the geodynamic setting of formation of uranium deposits of granitic exocontact zone type in eastern Hunan and neighbouring areas has a specia1 stretching strike-slip structure, a special thermal rock series,a special texture and composition of the crust and mantle, elaborated the macroscopic and microscopic features of stretching decollement faults in the Mingyuefeng area, and summed up the metallogenic regularities of typical uranium deposits, factors for a genetic mode1 and the criteria for prospecting by synthetic information, on the basis of which he has made prognosis of concealed and blind uranium deposits.展开更多
The natural element method （NEM） is a newly- developed numerical method based on Voronoi diagram and Delaunay triangulation of scattered points, which adopts natural neighbour interpolation to construct trial functi...The natural element method （NEM） is a newly- developed numerical method based on Voronoi diagram and Delaunay triangulation of scattered points, which adopts natural neighbour interpolation to construct trial functions in the framework of Galerkin method. Owing to its distinctive advantages, the NEM is used widely in many problems of computational mechanics. Utilizing the NEM, this paper deals with numerical limit analysis of structures made up of perfectly rigid-plastic material. According to kinematic the- orem of plastic limit analysis, a mathematical programming natural element formulation is established for determining the upper bound multiplier of plane problems, and a direct iteration algorithm is proposed accordingly to solve it. In this algorithm, the plastic incompressibility condition is handled by two different treatments, and the nonlinearity and nons- moothness of the goal function are overcome by distinguishing the rigid zones from the plastic zones at each iteration. The procedure implementation of iterative process is quite simple and effective because each iteration is equivalent to solving an associated elastic problem. The obtained limit load multiplier is proved to monotonically converge to the upper bound of true solution. Several benchmark examples are investigated to validate the significant performance of the NEM in the application field of limit analysis.展开更多
Firefly algorithm(FA)is a recently-proposed swarm intelligence technique.It has shown good performance in solving various optimization problems.According to the standard firefly algorithm and most of its variants,a fi...Firefly algorithm(FA)is a recently-proposed swarm intelligence technique.It has shown good performance in solving various optimization problems.According to the standard firefly algorithm and most of its variants,a firefly migrates to every other brighter firefly in each iteration.However,this method leads to defects of oscillations of positions,which hampers the convergence to the optimum.To address these problems and enhance the performance of FA,we propose a new firefly algorithm,which is called the Best Neighbor Firefly Algorithm(BNFA).It employs the best neighbor guided strategy,where each firefly is attracted to the best firefly among some randomly chosen neighbors,thus reducing the firefly oscillations in every attraction-induced migration stage,while increasing the probability of the guidance a new better direction.Moreover,it selects neighbors randomly to prevent the firefly form being trapped into a local optimum.Extensive experiments are conducted to find out the optimal parameter settings.To verify the performance of BNFA,13 classical benchmark functions are tested.Results show that BNFA outperforms the standard FA and other recently proposed modified FAs.展开更多
This paper studies evolutionary mechanism of parameter selection in the construction of weight function for Nearest Neighbour Estimate in nonparametric regression. Construct an algorithm which adaptively evolves fine ...This paper studies evolutionary mechanism of parameter selection in the construction of weight function for Nearest Neighbour Estimate in nonparametric regression. Construct an algorithm which adaptively evolves fine weight and makes good prediction about unknown points. The numerical experiments indicate that this method is effective. It is a meaningful discussion about practicability of nonparametric regression and methodology of adaptive model-building.展开更多
Background:Species-specific genotypic features,local neighbourhood interactions and resource supply strongly influence the tree stature and growth rate.In mixed-species forests,diversity-mediated biomass allocation ha...Background:Species-specific genotypic features,local neighbourhood interactions and resource supply strongly influence the tree stature and growth rate.In mixed-species forests,diversity-mediated biomass allocation has been suggested to be a fundamental mechanism underlying the positive biodiversity-productivity relationships.Empirical evidence,however,is rare about the impact of local neighbourhood diversity on tree characteristics analysed at a very high level of detail.To address this issue we analysed these effects on the individual-tree crown architecture and tree productivity in a mature mixed forest in northern Germany.Methods:Our analysis considers multiple target tree species across a local neighbourhood species richness gradient ranging from 1 to 4.We applied terrestrial laser scanning to quantify a large number of individual mature trees(N=920)at very high accuracy.We evaluated two different neighbour inclusion approaches by analysing both a fixed radius selection procedure and a selection based on overlapping crowns.Results and conclusions:We show that local neighbourhood species diversity significantly increases crown dimension and wood volume of target trees.Moreover,we found a size-dependency of diversity effects on tree productivity(basal area and wood volume increment)with positive effects for large-sized trees(diameter at breast height(DBH)>40 cm)and negative effects for small-sized(DBH<40 cm)trees.In our analysis,the neighbour inclusion approach has a significant impact on the outcome.For scientific studies and the validation of growth models we recommend a neighbour selection by overlapping crowns,because this seems to be the relevant scale at which local neighbourhood interactions occur.Because local neighbourhood diversity promotes individual-tree productivity in mature European mixed-species forests,we conclude that a small-scale species mixture should be considered in management plans.展开更多
In this paper a new continuous variable called core-ratio is defined to describe the probability for a residue to be in a binding site, thereby replacing the previous binary description of the interface residue using ...In this paper a new continuous variable called core-ratio is defined to describe the probability for a residue to be in a binding site, thereby replacing the previous binary description of the interface residue using 0 and 1. So we can use the support vector machine regression method to fit the core-ratio value and predict the protein binding sites. We also design a new group of physical and chemical descriptors to characterize the binding sites. The new descriptors are more effective, with an averaging procedure used. Our test shows that much better prediction results can be obtained by the support vector regression （SVR） method than by the support vector classification method.展开更多
It is an important problem in chaos theory whether an observed irregular signal is deterministic chaotic or stochas- tic. We propose an efficient method for distinguishing deterministic chaotic from stochastic time se...It is an important problem in chaos theory whether an observed irregular signal is deterministic chaotic or stochas- tic. We propose an efficient method for distinguishing deterministic chaotic from stochastic time series for short scalar time series. We first investigate, with the increase of the embedding dimension, the changing trend of the distance between two points which stay close in phase space. And then, we obtain the differences between Gaussian white noise and deterministic chaotic time series underlying this method. Finally, numerical experiments are presented to testify the validity and robustness of the method. Simulation results indicate that our method can distinguish deterministic chaotic from stochastic time series effectively even when the data are short and contaminated.展开更多
Using a tight binding transfer matrix method, we calculate the complex band structure of armchair graphene nanoribbons. The real part of the complex band structure calculated by the transfer matrix method fits well wi...Using a tight binding transfer matrix method, we calculate the complex band structure of armchair graphene nanoribbons. The real part of the complex band structure calculated by the transfer matrix method fits well with the bulk band structure calculated by a Hermitian matrix. The complex band structure gives extra information on carrier＇s decay behaviour. The imaginary loop connects the conduction and valence band, and can profoundly affect the characteristics of nanoscale electronic device made with graphene nanoribbons. In this work, the complex band structure calculation includes not only the first nearest neighbour interaction, but also the effects of edge bond relaxation and the third nearest neighbour interaction. The band gap is classified into three classes. Due to the edge bond relaxation and the third nearest neighbour interaction term, it opens a band gap for N = 3M- 1. The band gap is almost unchanged for N =3M ＋ 1, but decreased for N = 3M. The maximum imaginary wave vector length provides additional information about the electrical characteristics of graphene nanoribbons, and is also classified into three classes.展开更多
The trained Gaussian mixture model is used to make skincolour segmentation for the input image sequences. The hand gesture region is extracted, and the relative normalization images are obtained by interpolation opera...The trained Gaussian mixture model is used to make skincolour segmentation for the input image sequences. The hand gesture region is extracted, and the relative normalization images are obtained by interpolation operation. To solve the proem of hand gesture recognition, Fuzzy-Rough based nearest neighbour（RNN） algorithm is applied for classification. For avoiding the costly compute, an improved nearest neighbour classification algorithm based on fuzzy-rough set theory （FRNNC） is proposed. The algorithm employs the represented cluster points instead of the whole training samples, and takes the hand gesture data＇s fuzziness and the roughness into account, so the campute spending is decreased and the recognition rate is increased. The 30 gestures in Chinese sign language alphabet are used for approving the effectiveness of the proposed algorithm. The recognition rate is 94.96%, which is better than that of KNN （K nearest neighbor）and Fuzzy- KNN （Fuzzy K nearest neighbor）.展开更多
This paper aimed to highlight the effects of conflict in Mongolia on trade policy and openness, by estimating the trade flows with neighbor countries （China and Russia）. Fourteen years＇ （2000-2013） data of Mongol...This paper aimed to highlight the effects of conflict in Mongolia on trade policy and openness, by estimating the trade flows with neighbor countries （China and Russia）. Fourteen years＇ （2000-2013） data of Mongolian imports and exports were collected and gone through principal component analysis （PCA） and empirical analysis for grouping various trades with China and Russia. The empirical analysis identified the determining factors of Mongolian trade flow and openness with China and Russia. Empirical analysis evidenced that Mongolian trade and openness policy raised bilateral trade between China and Russia, leaving a great influence on economic size. Two main questions represented as empirically tested by each sample country. How did Mongolian trade policy and openness influence trade flows between China and Russia and economic growth of Mongolia？ Did Mongolian trade policy and the bilateral trade with China and Russia increase on trade openness？ Finally, the study focused on the forecasts from 2016 to 2018 to examine Mongolian trade flows with China and Russia using ordinary least squares method and autoregressive-moving-average （ARMA） model. China-Mongolia-Russia trade flows will continue to dominate during the forecasted period. As shown by the structure of export and import, goods with China and Russia influenced the mutual trade amount. Moreover, China and Russia traded to continue with Mongolia for goods in long run. Trade policy and openness, the major contributor in Mongolian economy, are significantly playing roles in trade and economy.展开更多
This paper proposes a novel grading method of apples,in an automated grading device that uses convolutional neural networks to extract the size,color,texture,and roundness of an apple.The developed machine learning me...This paper proposes a novel grading method of apples,in an automated grading device that uses convolutional neural networks to extract the size,color,texture,and roundness of an apple.The developed machine learning method uses the ability of learning representative features by means of a convolutional neural network(CNN),to determine suitable features of apples for the grading process.This information is fed into a one-to-one classifier that uses a support vector machine(SVM),instead of the softmax output layer of the CNN.In this manner,Yantai apples with similar shapes and low discrimination are graded using four different approaches.The fusion model using both CNN and SVM classifiers is much more accurate than the simple k-nearest neighbor(KNN),SVM,and CNN model when used separately for grading,and the learning ability and the generalization ability of the model is correspondingly increased by the combined method.Grading tests are carried out using the automated grading device that is developed in the present work.It is verified that the actual effect of apple grading using the combined CNN-SVM model is fast and accurate,which greatly reduces the manpower and labor costs of manual grading,and has important commercial prospects.展开更多
This paper deals with a real-life application of epilepsy classification, where three phases of absence seizure, namely pre-seizure, seizure and seizure-free, are classified using real clinical data. Artificial neural...This paper deals with a real-life application of epilepsy classification, where three phases of absence seizure, namely pre-seizure, seizure and seizure-free, are classified using real clinical data. Artificial neural network （ANN） and support vector machines （SVMs） combined with su- pervised learning algorithms, and k-means clustering （k-MC） combined with unsupervised techniques are employed to classify the three seizure phases. Different techniques to combine binary SVMs, namely One Vs One （OvO）, One Vs All （OVA） and Binary Decision Tree （BDT）, are employed for multiclass classification. Comparisons are performed with two traditional classification methods, namely, k-Nearest Neighbour （k- NN） and Naive Bayes classifier. It is concluded that SVM-based classifiers outperform the traditional ones in terms of recognition accuracy and robustness property when the original clinical data is distorted with noise. Furthermore, SVM-based classifier with OvO provides the highest recognition accuracy, whereas ANN-based classifier overtakes by demonstrating maximum accuracy in the presence of noise.展开更多
Mossbauer absorption spectra in a natural chromite from Shanxi province of China were measured, covering a temperature range from 12 K to 800 K. Each spectrum at low temperature can be fitted to three doublets: the fi...Mossbauer absorption spectra in a natural chromite from Shanxi province of China were measured, covering a temperature range from 12 K to 800 K. Each spectrum at low temperature can be fitted to three doublets: the first two are attributed to tetrahedral T-site Fe ions and the third one to octahedral M-site Fe ions. Such assignment was confirmed by the detailed analyses of the temperature dependent centre shift and other parameters. As a main result, our data strongly supported the ordered distribution with Fe2+ in T-site and Fe3+ in M-site for chromite studied. No evidence for electron hopping processes was detected.展开更多
Fourier descriptors are used as features for 3-D aircraft classification and pose determination from a 2-D image recorded at an arbitrary viewing angle. By the feature ranking of Fourier descriptors, a classification ...Fourier descriptors are used as features for 3-D aircraft classification and pose determination from a 2-D image recorded at an arbitrary viewing angle. By the feature ranking of Fourier descriptors, a classification procedure based on the fast nearest neighbour rule is proposed to save the matching time of an unknown aircraft with a partial library search. The testing results of some typical examples indicate this method is generally applicable and efficient in 3-D aircraft recognition.展开更多
基金Project supported by the Key Higher Education Program of Hubei Province, China (Grant No Z20052201)Natural Science Foundation of Hubei Province, China (Grant No 2006ABA055)Postgraduate Program of Hubei Normal University of China(Grant No 2007D20)
文摘By using the method of density-matrix renormalization-group to solve the different spin spin correlation functions, the nearest-neighbouring entanglement （NNE） and the next-nearest-neighbouring entanglement （NNNE） of one-dimensional alternating Heisenberg XY spin chain are investigated in the presence of alternating the-nearestneighbouring interaction of exchange couplings, external magnetic fields and the next-nearest neighbouring interaction. For a dimerised ferromagnetic spin chain, the NNNE appears only above a critical dimerized interaction, meanwhile, the dimerized interaction a effects a quantum phase transition point and improves the NNNE to a large extent. We also study the effect of ferromagnetic or antiferromagnetic next-nearest neighbouring （NNN） interaction on the dynamics of NNE and NNNE. The ferromagnetic NNN interaction increases and shrinks the NNE below and above a critical frustrated interaction respectively, while the antiferromagnetic NNN interaction always reduces the NNE. The antiferromagnetic NNN interaction results in a large value of NNNE compared with the case where the NNN interaction is ferromagnetic.
基金This study was co-supported by the State Eighth Five-Year Plan Scientific Project(No.85-901-03-08D)and National Natural Science Foundation of China(No.49473187).
文摘The paper systematically deals with the background of regional isotopic compo-sitions in the lower and middle reaches of the Yangtze River and neighbouring areas. It isshown that the lead isotopic compositions of different geological formations and units are con-trolled by the primary mantle heterogeneity, dynamic process of crust-mantle interchange,abundances of uraninm, thorium and lead of various layers of the earth and timing. Studies onthe background of regional isotopic compositions may offer significant information forgeochemical regionalization, tracing of sources of ore-forming materials, and regionalprognosis of ore deposits.
文摘VisuShrink, ModineighShrink and NeighShrink are efficient image denoising algorithms based on the discrete wavelet transform (DWT). These methods have disadvantage of using a suboptimal universal threshold and identical neighbouring window size in all wavelet subbands. In this paper, an improved method is proposed, that determines a threshold as well as neighbouring window size for every subband using its lengths. Our experimental results illustrate that the proposed approach is better than the existing ones, i.e., NeighShrink, ModineighShrink and VisuShrink in terms of peak signal-to-noise ratio (PSNR) i.e. visual quality of the image.
基金funded and carried out within SMART4Action LIFE+project“Sustainable Monitoring and Reporting to Inform Forest and Environmental Awareness and Protection”LIFE13 ENV/IT/000813
文摘Forest health is currently assessed in Europe （ICP Forests monitoring program）. Crown defoliation and dieback, tree mortality, and pathogenic damage are the main aspects considered in tree health assessment. The worsening of environmental conditions （i.e., increase of temperature and drought events） may cause large-spatial scale tree mortality and forest decline. However, the role of stand features, including tree species assemblage and diversity as factors that modify environmental impacts, is poorly considered. The present contribution reanalyses the historical dataset of crown conditions in Italian forests from ] 997 to 2014 to identify ecological and structural factors that influence tree crown defoliation, highlighting in a special manner the role of tree diversity. The effects of tree diversity were explored using the entire data set through multivariate cluster analyses and on individual trees, analysing the influence of the neighbouring tree diversity and identity at the local （neighbour） level. Preliminary results suggest that each tree species shows a specific behaviour in relation to crown defoliation, and the distribution of crown defoliation across Italian forests reflects the distribution of the main forest types and their ecological equilibrium with the environment. The potentiality and the problems connected to the possible extension of this analysis at a more general level （European and North American） were discussed.
文摘Under the guide of advanced theories of geosciences, new technology and methods of prospecting, integrating sedimentation, magmatic emplacement, metamorphism and deformation with mineralization by means of intersectional subjects, the author has revealed that the geodynamic setting of formation of uranium deposits of granitic exocontact zone type in eastern Hunan and neighbouring areas has a specia1 stretching strike-slip structure, a special thermal rock series,a special texture and composition of the crust and mantle, elaborated the macroscopic and microscopic features of stretching decollement faults in the Mingyuefeng area, and summed up the metallogenic regularities of typical uranium deposits, factors for a genetic mode1 and the criteria for prospecting by synthetic information, on the basis of which he has made prognosis of concealed and blind uranium deposits.
基金supported by the National Foundation for Excellent Doctoral Thesis of China (200025)the Program for New Century Excellent Talents in University (NCET-04-0075)the National Natural Science Foundation of China (19902007)
文摘The natural element method （NEM） is a newly- developed numerical method based on Voronoi diagram and Delaunay triangulation of scattered points, which adopts natural neighbour interpolation to construct trial functions in the framework of Galerkin method. Owing to its distinctive advantages, the NEM is used widely in many problems of computational mechanics. Utilizing the NEM, this paper deals with numerical limit analysis of structures made up of perfectly rigid-plastic material. According to kinematic the- orem of plastic limit analysis, a mathematical programming natural element formulation is established for determining the upper bound multiplier of plane problems, and a direct iteration algorithm is proposed accordingly to solve it. In this algorithm, the plastic incompressibility condition is handled by two different treatments, and the nonlinearity and nons- moothness of the goal function are overcome by distinguishing the rigid zones from the plastic zones at each iteration. The procedure implementation of iterative process is quite simple and effective because each iteration is equivalent to solving an associated elastic problem. The obtained limit load multiplier is proved to monotonically converge to the upper bound of true solution. Several benchmark examples are investigated to validate the significant performance of the NEM in the application field of limit analysis.
基金Supported by the National Natural Science Foundation of China(61763019,61364025)the Science and Technology Foundation of Jiangxi Province,China(GJJ161076)
文摘Firefly algorithm(FA)is a recently-proposed swarm intelligence technique.It has shown good performance in solving various optimization problems.According to the standard firefly algorithm and most of its variants,a firefly migrates to every other brighter firefly in each iteration.However,this method leads to defects of oscillations of positions,which hampers the convergence to the optimum.To address these problems and enhance the performance of FA,we propose a new firefly algorithm,which is called the Best Neighbor Firefly Algorithm(BNFA).It employs the best neighbor guided strategy,where each firefly is attracted to the best firefly among some randomly chosen neighbors,thus reducing the firefly oscillations in every attraction-induced migration stage,while increasing the probability of the guidance a new better direction.Moreover,it selects neighbors randomly to prevent the firefly form being trapped into a local optimum.Extensive experiments are conducted to find out the optimal parameter settings.To verify the performance of BNFA,13 classical benchmark functions are tested.Results show that BNFA outperforms the standard FA and other recently proposed modified FAs.
文摘This paper studies evolutionary mechanism of parameter selection in the construction of weight function for Nearest Neighbour Estimate in nonparametric regression. Construct an algorithm which adaptively evolves fine weight and makes good prediction about unknown points. The numerical experiments indicate that this method is effective. It is a meaningful discussion about practicability of nonparametric regression and methodology of adaptive model-building.
基金LG was funded by the German Research Foundation(DFG 320926971)through the project“Analysis of diversity effects on above-groundproductivity in forests:advancing the mechanistic understanding of spatiotemporal dynamics in canopy space filling using mobile laser scanning”。
文摘Background:Species-specific genotypic features,local neighbourhood interactions and resource supply strongly influence the tree stature and growth rate.In mixed-species forests,diversity-mediated biomass allocation has been suggested to be a fundamental mechanism underlying the positive biodiversity-productivity relationships.Empirical evidence,however,is rare about the impact of local neighbourhood diversity on tree characteristics analysed at a very high level of detail.To address this issue we analysed these effects on the individual-tree crown architecture and tree productivity in a mature mixed forest in northern Germany.Methods:Our analysis considers multiple target tree species across a local neighbourhood species richness gradient ranging from 1 to 4.We applied terrestrial laser scanning to quantify a large number of individual mature trees(N=920)at very high accuracy.We evaluated two different neighbour inclusion approaches by analysing both a fixed radius selection procedure and a selection based on overlapping crowns.Results and conclusions:We show that local neighbourhood species diversity significantly increases crown dimension and wood volume of target trees.Moreover,we found a size-dependency of diversity effects on tree productivity(basal area and wood volume increment)with positive effects for large-sized trees(diameter at breast height(DBH)>40 cm)and negative effects for small-sized(DBH<40 cm)trees.In our analysis,the neighbour inclusion approach has a significant impact on the outcome.For scientific studies and the validation of growth models we recommend a neighbour selection by overlapping crowns,because this seems to be the relevant scale at which local neighbourhood interactions occur.Because local neighbourhood diversity promotes individual-tree productivity in mature European mixed-species forests,we conclude that a small-scale species mixture should be considered in management plans.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 10674172 and 10874229)
文摘In this paper a new continuous variable called core-ratio is defined to describe the probability for a residue to be in a binding site, thereby replacing the previous binary description of the interface residue using 0 and 1. So we can use the support vector machine regression method to fit the core-ratio value and predict the protein binding sites. We also design a new group of physical and chemical descriptors to characterize the binding sites. The new descriptors are more effective, with an averaging procedure used. Our test shows that much better prediction results can be obtained by the support vector regression （SVR） method than by the support vector classification method.
文摘It is an important problem in chaos theory whether an observed irregular signal is deterministic chaotic or stochas- tic. We propose an efficient method for distinguishing deterministic chaotic from stochastic time series for short scalar time series. We first investigate, with the increase of the embedding dimension, the changing trend of the distance between two points which stay close in phase space. And then, we obtain the differences between Gaussian white noise and deterministic chaotic time series underlying this method. Finally, numerical experiments are presented to testify the validity and robustness of the method. Simulation results indicate that our method can distinguish deterministic chaotic from stochastic time series effectively even when the data are short and contaminated.
基金Project supported by the Fundamental Research Funds for the Central Universities (Grant No. YWF-10-02-040)
文摘Using a tight binding transfer matrix method, we calculate the complex band structure of armchair graphene nanoribbons. The real part of the complex band structure calculated by the transfer matrix method fits well with the bulk band structure calculated by a Hermitian matrix. The complex band structure gives extra information on carrier＇s decay behaviour. The imaginary loop connects the conduction and valence band, and can profoundly affect the characteristics of nanoscale electronic device made with graphene nanoribbons. In this work, the complex band structure calculation includes not only the first nearest neighbour interaction, but also the effects of edge bond relaxation and the third nearest neighbour interaction. The band gap is classified into three classes. Due to the edge bond relaxation and the third nearest neighbour interaction term, it opens a band gap for N = 3M- 1. The band gap is almost unchanged for N =3M ＋ 1, but decreased for N = 3M. The maximum imaginary wave vector length provides additional information about the electrical characteristics of graphene nanoribbons, and is also classified into three classes.
文摘The trained Gaussian mixture model is used to make skincolour segmentation for the input image sequences. The hand gesture region is extracted, and the relative normalization images are obtained by interpolation operation. To solve the proem of hand gesture recognition, Fuzzy-Rough based nearest neighbour（RNN） algorithm is applied for classification. For avoiding the costly compute, an improved nearest neighbour classification algorithm based on fuzzy-rough set theory （FRNNC） is proposed. The algorithm employs the represented cluster points instead of the whole training samples, and takes the hand gesture data＇s fuzziness and the roughness into account, so the campute spending is decreased and the recognition rate is increased. The 30 gestures in Chinese sign language alphabet are used for approving the effectiveness of the proposed algorithm. The recognition rate is 94.96%, which is better than that of KNN （K nearest neighbor）and Fuzzy- KNN （Fuzzy K nearest neighbor）.
文摘This paper aimed to highlight the effects of conflict in Mongolia on trade policy and openness, by estimating the trade flows with neighbor countries （China and Russia）. Fourteen years＇ （2000-2013） data of Mongolian imports and exports were collected and gone through principal component analysis （PCA） and empirical analysis for grouping various trades with China and Russia. The empirical analysis identified the determining factors of Mongolian trade flow and openness with China and Russia. Empirical analysis evidenced that Mongolian trade and openness policy raised bilateral trade between China and Russia, leaving a great influence on economic size. Two main questions represented as empirically tested by each sample country. How did Mongolian trade policy and openness influence trade flows between China and Russia and economic growth of Mongolia？ Did Mongolian trade policy and the bilateral trade with China and Russia increase on trade openness？ Finally, the study focused on the forecasts from 2016 to 2018 to examine Mongolian trade flows with China and Russia using ordinary least squares method and autoregressive-moving-average （ARMA） model. China-Mongolia-Russia trade flows will continue to dominate during the forecasted period. As shown by the structure of export and import, goods with China and Russia influenced the mutual trade amount. Moreover, China and Russia traded to continue with Mongolia for goods in long run. Trade policy and openness, the major contributor in Mongolian economy, are significantly playing roles in trade and economy.
文摘This paper proposes a novel grading method of apples,in an automated grading device that uses convolutional neural networks to extract the size,color,texture,and roundness of an apple.The developed machine learning method uses the ability of learning representative features by means of a convolutional neural network(CNN),to determine suitable features of apples for the grading process.This information is fed into a one-to-one classifier that uses a support vector machine(SVM),instead of the softmax output layer of the CNN.In this manner,Yantai apples with similar shapes and low discrimination are graded using four different approaches.The fusion model using both CNN and SVM classifiers is much more accurate than the simple k-nearest neighbor(KNN),SVM,and CNN model when used separately for grading,and the learning ability and the generalization ability of the model is correspondingly increased by the combined method.Grading tests are carried out using the automated grading device that is developed in the present work.It is verified that the actual effect of apple grading using the combined CNN-SVM model is fast and accurate,which greatly reduces the manpower and labor costs of manual grading,and has important commercial prospects.
文摘This paper deals with a real-life application of epilepsy classification, where three phases of absence seizure, namely pre-seizure, seizure and seizure-free, are classified using real clinical data. Artificial neural network （ANN） and support vector machines （SVMs） combined with su- pervised learning algorithms, and k-means clustering （k-MC） combined with unsupervised techniques are employed to classify the three seizure phases. Different techniques to combine binary SVMs, namely One Vs One （OvO）, One Vs All （OVA） and Binary Decision Tree （BDT）, are employed for multiclass classification. Comparisons are performed with two traditional classification methods, namely, k-Nearest Neighbour （k- NN） and Naive Bayes classifier. It is concluded that SVM-based classifiers outperform the traditional ones in terms of recognition accuracy and robustness property when the original clinical data is distorted with noise. Furthermore, SVM-based classifier with OvO provides the highest recognition accuracy, whereas ANN-based classifier overtakes by demonstrating maximum accuracy in the presence of noise.
文摘Mossbauer absorption spectra in a natural chromite from Shanxi province of China were measured, covering a temperature range from 12 K to 800 K. Each spectrum at low temperature can be fitted to three doublets: the first two are attributed to tetrahedral T-site Fe ions and the third one to octahedral M-site Fe ions. Such assignment was confirmed by the detailed analyses of the temperature dependent centre shift and other parameters. As a main result, our data strongly supported the ordered distribution with Fe2+ in T-site and Fe3+ in M-site for chromite studied. No evidence for electron hopping processes was detected.
文摘Fourier descriptors are used as features for 3-D aircraft classification and pose determination from a 2-D image recorded at an arbitrary viewing angle. By the feature ranking of Fourier descriptors, a classification procedure based on the fast nearest neighbour rule is proposed to save the matching time of an unknown aircraft with a partial library search. The testing results of some typical examples indicate this method is generally applicable and efficient in 3-D aircraft recognition.
