By using the Mixture Model and radial velocity data from CfA redshift catalogue, we resolve the substructures of the Virgo cluster. Distances of three main subclusters are determined by the Tully-Fisher galaxies, they...By using the Mixture Model and radial velocity data from CfA redshift catalogue, we resolve the substructures of the Virgo cluster. Distances of three main subclusters are determined by the Tully-Fisher galaxies, they are 18.0±1.3Mpc, 25.0±2 3Mpc and 30.9±3.1Mpc respectively, which implicate that they are independent clusters, and the Virgo area has a significant depth in the line-of -sight direction.展开更多
The traditional grey incidence degree is mainly based on the distance analysis methods, which is measured by the displacement difference between corresponding points between sequences. When some data of sequences are ...The traditional grey incidence degree is mainly based on the distance analysis methods, which is measured by the displacement difference between corresponding points between sequences. When some data of sequences are missing (inconsistency in the length of the sequences), the only way is to delete the longer sequences or to fill the shorter sequences. Therefore, some uncertainty is introduced. To solve this problem, by introducing three-dimensional grey incidence degree (3D-GID), a novel GID based on the multidimensional dynamic time warping distance (MDDTW distance-GID) is proposed. On the basis of it, the corresponding grey incidence clustering (MDDTW distance-GIC) method is constructed. It not only has the simpler computation process, but also can be applied to the incidence comparison between uncertain multidimensional sequences directly. The experiment shows that MDDTW distance-GIC is more accurate when dealing with the uncertain sequences. Compared with the traditional GIC method, the precision of the MDDTW distance-GIC method has increased nearly 30%.展开更多
A leukocyte image fast scanning method based on max min distance clustering is proposed.Because of the lower proportion and uneven distribution of leukocytes in human peripheral blood,there will not be any leukocyte i...A leukocyte image fast scanning method based on max min distance clustering is proposed.Because of the lower proportion and uneven distribution of leukocytes in human peripheral blood,there will not be any leukocyte in lager quantity of the captured images if we directly scan the blood smear along an ordinary zigzag scanning routine with high power(100^(x))objective.Due to the larger field of view of low power(10^(x))objective,the captured low power blood smear images can be used to locate leukocytes.All of the located positions make up a specific routine,if we scan the blood smear along this routine with high power objective,there will be definitely leukocytes in almost all of the captured images.Considering the number of captured images is still large and some leukocytes may be redundantly captured twice or more,a leukocyte clustering method based on max-min distance clustering is developed to reduce the total number of captured images as well as the number of redundantly captured leukocytes.This method can improve the scanning eficiency obviously.The experimental results show that the proposed method can shorten scanning time from 8.0-14.0min to 2.54.0 min while extracting 110 nonredundant individual high power leukocyte images.展开更多
Seismic waveform clustering is a useful technique for lithologic identification and reservoir characterization.The current seismic waveform clustering algorithms are predominantly based on a fixed time window,which is...Seismic waveform clustering is a useful technique for lithologic identification and reservoir characterization.The current seismic waveform clustering algorithms are predominantly based on a fixed time window,which is applicable for layers of stable thickness.When a layer exhibits variable thickness in the seismic response,a fixed time window cannot provide comprehensive geologic information for the target interval.Therefore,we propose a novel approach for a waveform clustering workfl ow based on a variable time window to enable broader applications.The dynamic time warping(DTW)distance is fi rst introduced to effectively measure the similarities between seismic waveforms with various lengths.We develop a DTW distance-based clustering algorithm to extract centroids,and we then determine the class of all seismic traces according to the DTW distances from centroids.To greatly reduce the computational complexity in seismic data application,we propose a superpixel-based seismic data thinning approach.We further propose an integrated workfl ow that can be applied to practical seismic data by incorporating the DTW distance-based clustering and seismic data thinning algorithms.We evaluated the performance by applying the proposed workfl ow to synthetic seismograms and seismic survey data.Compared with the the traditional waveform clustering method,the synthetic seismogram results demonstrate the enhanced capability of the proposed workfl ow to detect boundaries of diff erent lithologies or lithologic associations with variable thickness.Results from a practical application show that the planar map of seismic waveform clustering obtained by the proposed workfl ow correlates well with the geological characteristics of wells in terms of reservoir thickness.展开更多
Most clustering algorithms need to describe the similarity of objects by a predefined distance function. Three distance functions which are widely used in two traditional clustering algorithms k-means and hierarchical...Most clustering algorithms need to describe the similarity of objects by a predefined distance function. Three distance functions which are widely used in two traditional clustering algorithms k-means and hierarchical clustering were investigated. Both theoretical analysis and detailed experimental results were given. It is shown that a distance function greatly affects clustering results and can be used to detect the outlier of a cluster by the comparison of such different results and give the shape information of clusters. In practice situation, it is suggested to use different distance function separately, compare the clustering results and pick out the 搒wing points? And such points may leak out more information for data analysts.展开更多
On the reasonable hypothesis that the internal motions of member stars of a cluster are random and isotropic, a method which can be used to estimate the velocity distance of the cluster and its uncertainty is develope...On the reasonable hypothesis that the internal motions of member stars of a cluster are random and isotropic, a method which can be used to estimate the velocity distance of the cluster and its uncertainty is developed. The velocity distance so determined is an absolute distance estimate, and is completely independent of the （widely used） luminosity distance, which is a relative distance estimate. Using the published high-accuracy observational data of radial velocities and proper motions of the stars in the open cluster M11 region, we have determined the distance of M 11 to be 1.89 ± 0.52 kpc. This is in quite good agreement with the published luminosity distances of the cluster. We briefly discuss the problems concerned, including the sources of errors in the method and its applicable range.展开更多
Facility location problems are concerned with the location of one or more facilities in a way that optimizes a certain objective such as minimizing transportation cost, providing equitable service to customers, captur...Facility location problems are concerned with the location of one or more facilities in a way that optimizes a certain objective such as minimizing transportation cost, providing equitable service to customers, capturing the largest market share, etc. Many facility location decisions involving distance objective functions on Spherical Surface have been approached using algorithmic, metaheuristic algorithms, branch-and-bound algorithm, approximation algorithms, simulation, heuristic techniques, and decomposition method. These approaches are most based on Euclidean distance or Great circle distance functions. However, if the location points are widely separated, the difference between driving distance, Euclidean distance and Great circle distance may be significant and this may lead to significant variations in the locations of the corresponding optimal source points. This paper presents a framework and algorithm to use driving distances on spherical surface and explores its use as a facility location decision tool and helps companies assess the optimal locations of facilities.展开更多
We test the distance-duality （DD） relation by combining the angular diameter distance DA provided by two galaxy cluster samples compiled by De Filippis et al. （the elliptical β model） and Bonamente et al. （the s...We test the distance-duality （DD） relation by combining the angular diameter distance DA provided by two galaxy cluster samples compiled by De Filippis et al. （the elliptical β model） and Bonamente et al. （the spherical β model）, and the luminosity distance DL from Constitution and Union2 type Ia supernova （SNe Ia） datasets. To obtain DL associated with the observed DA at the same redshift, we smooth the noise of the SNe Ia in a model-independent way, obtain the evolutionary curve of DL and, finally, test the DD relation. We find that the elliptical β model, when compared with the SNe Ia from the Constitution compilation, is only consistent with the DD relation at the 3σ confidence level （CL）, while the spherical β model is incompatible with the DD relation at the 3σ CL. For the Union2 compilation, the De Filippis and Bonamente samples are marginally compatible with the validity of the DD relation at the 1σ and 2σ CLs, respectively.展开更多
We propose a consistency test for some recent X-ray gas mass fraction （fgas） measurements in galaxy clusters, using the cosmic distance-duality relation, Ttneory = DL（1 ＋ Z）-2/DA, with luminosity distance （DL） ...We propose a consistency test for some recent X-ray gas mass fraction （fgas） measurements in galaxy clusters, using the cosmic distance-duality relation, Ttneory = DL（1 ＋ Z）-2/DA, with luminosity distance （DL） data from the Union2 compilation of type Ia supernovae. We set Z/theory = 1, instead of assigning any red- shift parameterizations to it, and constrain the cosmological information preferred by fga8 data along with supernova observations. We adopt a new binning method in the reduction of the Union2 data, in order to minimize the statistical errors. Four data sets of X-ray gas mass fraction, which are reported by Allen et al. （two samples）, LaRoque et al. and Ettori et al., are analyzed in detail in the context of two theoretical models of fgas. The results from the analysis of Alien et al.＇s samples demonstrate the feasibility of our method. It is found that the preferred cosmology by LaRoque et al.＇s sample is consistent with its reference cosmology within the 1σ confidence level. However, for Ettori et al.＇s fgas sample, the inconsistency can reach more than a 3σ confidence level and this dataset shows special preference to an ΩA = 0 cosmology.展开更多
In order to obtain clean members of the open cluster NGC 6819, the proper motions and radial velocities of 1691 stars are used to construct a three-dimensional （3D） velocity space. Based on the DBSCAN clustering alg...In order to obtain clean members of the open cluster NGC 6819, the proper motions and radial velocities of 1691 stars are used to construct a three-dimensional （3D） velocity space. Based on the DBSCAN clustering algorithm, 537 3D cluster members are obtained. From the 537 3D cluster members, the average radial velocity and absolute proper motion of the cluster are Vr = ＋2.30 ±0.04 km s-1 and （PMRA, PMDec） = （-2.5 ±0.5, -4.3 ± 0.5） mas yr-1, respectively. The proper motions, radial velocities, spatial positions and color-magnitude diagram of the 537 3D members indicate that our membership determination is effective. Among the 537 3D cluster members, 15 red clump giants can be easily identified by eye and are used as reliable standard candles for the distance estimate of the cluster. The distance modulus of the cluster is determined to be （m - M）0 -- 11.86 ± 0.05 mag （2355 ±54 pc）, which is quite consistent with published values. The uncertainty of our distance mod- ulus is dominated by the intrinsic dispersion in the luminosities of red clump giants （--0.04 mag）.展开更多
The validity of the cosmic distance-duality （DD） relation is investigated by using 91 measure- ments of the gas mass fraction of galaxy clusters recently reported by the Atacama Cosmology Telescope （ACT） and the l...The validity of the cosmic distance-duality （DD） relation is investigated by using 91 measure- ments of the gas mass fraction of galaxy clusters recently reported by the Atacama Cosmology Telescope （ACT） and the luminosity distance from the Union2.1 type Ia supernova （SNIa） sample independent of any cosmological models and the value of the Hubble constant. We consider four different approaches to derive the gas mass function and two different parameterizations of the DD relation, and find that they have very slight influences on the DD relation test and the relation is valid at the la confidence level. We also discuss the constraints on a andβ, which represent the effects of the shapes and colors of the light curves of SNIa, respectively. Our results on a and β are different from those obtained from the ACDM model and the galaxy cluster plus SNIa data.展开更多
文摘By using the Mixture Model and radial velocity data from CfA redshift catalogue, we resolve the substructures of the Virgo cluster. Distances of three main subclusters are determined by the Tully-Fisher galaxies, they are 18.0±1.3Mpc, 25.0±2 3Mpc and 30.9±3.1Mpc respectively, which implicate that they are independent clusters, and the Virgo area has a significant depth in the line-of -sight direction.
基金supported by the National Natural Science Foundation of China(6153302061309014)the Natural Science Foundation Project of CQ CSTC(cstc2017jcyj AX0408)
文摘The traditional grey incidence degree is mainly based on the distance analysis methods, which is measured by the displacement difference between corresponding points between sequences. When some data of sequences are missing (inconsistency in the length of the sequences), the only way is to delete the longer sequences or to fill the shorter sequences. Therefore, some uncertainty is introduced. To solve this problem, by introducing three-dimensional grey incidence degree (3D-GID), a novel GID based on the multidimensional dynamic time warping distance (MDDTW distance-GID) is proposed. On the basis of it, the corresponding grey incidence clustering (MDDTW distance-GIC) method is constructed. It not only has the simpler computation process, but also can be applied to the incidence comparison between uncertain multidimensional sequences directly. The experiment shows that MDDTW distance-GIC is more accurate when dealing with the uncertain sequences. Compared with the traditional GIC method, the precision of the MDDTW distance-GIC method has increased nearly 30%.
基金supported by the 863 National Plan Foundation of China under Grant No.2007AA01Z333 and Special Grand National Project of China under Grant No.2009ZX02204-008.
文摘A leukocyte image fast scanning method based on max min distance clustering is proposed.Because of the lower proportion and uneven distribution of leukocytes in human peripheral blood,there will not be any leukocyte in lager quantity of the captured images if we directly scan the blood smear along an ordinary zigzag scanning routine with high power(100^(x))objective.Due to the larger field of view of low power(10^(x))objective,the captured low power blood smear images can be used to locate leukocytes.All of the located positions make up a specific routine,if we scan the blood smear along this routine with high power objective,there will be definitely leukocytes in almost all of the captured images.Considering the number of captured images is still large and some leukocytes may be redundantly captured twice or more,a leukocyte clustering method based on max-min distance clustering is developed to reduce the total number of captured images as well as the number of redundantly captured leukocytes.This method can improve the scanning eficiency obviously.The experimental results show that the proposed method can shorten scanning time from 8.0-14.0min to 2.54.0 min while extracting 110 nonredundant individual high power leukocyte images.
基金supported by the National Science and Technology Major Project (No. 2017ZX05001-003)。
文摘Seismic waveform clustering is a useful technique for lithologic identification and reservoir characterization.The current seismic waveform clustering algorithms are predominantly based on a fixed time window,which is applicable for layers of stable thickness.When a layer exhibits variable thickness in the seismic response,a fixed time window cannot provide comprehensive geologic information for the target interval.Therefore,we propose a novel approach for a waveform clustering workfl ow based on a variable time window to enable broader applications.The dynamic time warping(DTW)distance is fi rst introduced to effectively measure the similarities between seismic waveforms with various lengths.We develop a DTW distance-based clustering algorithm to extract centroids,and we then determine the class of all seismic traces according to the DTW distances from centroids.To greatly reduce the computational complexity in seismic data application,we propose a superpixel-based seismic data thinning approach.We further propose an integrated workfl ow that can be applied to practical seismic data by incorporating the DTW distance-based clustering and seismic data thinning algorithms.We evaluated the performance by applying the proposed workfl ow to synthetic seismograms and seismic survey data.Compared with the the traditional waveform clustering method,the synthetic seismogram results demonstrate the enhanced capability of the proposed workfl ow to detect boundaries of diff erent lithologies or lithologic associations with variable thickness.Results from a practical application show that the planar map of seismic waveform clustering obtained by the proposed workfl ow correlates well with the geological characteristics of wells in terms of reservoir thickness.
文摘Most clustering algorithms need to describe the similarity of objects by a predefined distance function. Three distance functions which are widely used in two traditional clustering algorithms k-means and hierarchical clustering were investigated. Both theoretical analysis and detailed experimental results were given. It is shown that a distance function greatly affects clustering results and can be used to detect the outlier of a cluster by the comparison of such different results and give the shape information of clusters. In practice situation, it is suggested to use different distance function separately, compare the clustering results and pick out the 搒wing points? And such points may leak out more information for data analysts.
基金the National Natural Science Foundation of China.
文摘On the reasonable hypothesis that the internal motions of member stars of a cluster are random and isotropic, a method which can be used to estimate the velocity distance of the cluster and its uncertainty is developed. The velocity distance so determined is an absolute distance estimate, and is completely independent of the （widely used） luminosity distance, which is a relative distance estimate. Using the published high-accuracy observational data of radial velocities and proper motions of the stars in the open cluster M11 region, we have determined the distance of M 11 to be 1.89 ± 0.52 kpc. This is in quite good agreement with the published luminosity distances of the cluster. We briefly discuss the problems concerned, including the sources of errors in the method and its applicable range.
文摘Facility location problems are concerned with the location of one or more facilities in a way that optimizes a certain objective such as minimizing transportation cost, providing equitable service to customers, capturing the largest market share, etc. Many facility location decisions involving distance objective functions on Spherical Surface have been approached using algorithmic, metaheuristic algorithms, branch-and-bound algorithm, approximation algorithms, simulation, heuristic techniques, and decomposition method. These approaches are most based on Euclidean distance or Great circle distance functions. However, if the location points are widely separated, the difference between driving distance, Euclidean distance and Great circle distance may be significant and this may lead to significant variations in the locations of the corresponding optimal source points. This paper presents a framework and algorithm to use driving distances on spherical surface and explores its use as a facility location decision tool and helps companies assess the optimal locations of facilities.
基金Supported by the National Natural Science Foundation of China(Grants Nos. 10935013 and 11075083)the Zhejiang Provincial Natural Science Foundation of China under Grant No. Z6100077+3 种基金the FANEDD under Grant No. 200922the National Basic Research Program of China (Grant No. 2010CB832803)the NCET under Grant No. 09-0144the PCSIRT under Grant No. IRT0964
文摘We test the distance-duality （DD） relation by combining the angular diameter distance DA provided by two galaxy cluster samples compiled by De Filippis et al. （the elliptical β model） and Bonamente et al. （the spherical β model）, and the luminosity distance DL from Constitution and Union2 type Ia supernova （SNe Ia） datasets. To obtain DL associated with the observed DA at the same redshift, we smooth the noise of the SNe Ia in a model-independent way, obtain the evolutionary curve of DL and, finally, test the DD relation. We find that the elliptical β model, when compared with the SNe Ia from the Constitution compilation, is only consistent with the DD relation at the 3σ confidence level （CL）, while the spherical β model is incompatible with the DD relation at the 3σ CL. For the Union2 compilation, the De Filippis and Bonamente samples are marginally compatible with the validity of the DD relation at the 1σ and 2σ CLs, respectively.
基金supported by the National Basic Research Program of China (973 program Grant Nos. 2009CB824800 and 2012CB821804)+1 种基金the National Natural Science Foundation of China (Grant Nos. 11033002 and 11173006)the Fundamental Research Funds for the Central Universities
文摘We propose a consistency test for some recent X-ray gas mass fraction （fgas） measurements in galaxy clusters, using the cosmic distance-duality relation, Ttneory = DL（1 ＋ Z）-2/DA, with luminosity distance （DL） data from the Union2 compilation of type Ia supernovae. We set Z/theory = 1, instead of assigning any red- shift parameterizations to it, and constrain the cosmological information preferred by fga8 data along with supernova observations. We adopt a new binning method in the reduction of the Union2 data, in order to minimize the statistical errors. Four data sets of X-ray gas mass fraction, which are reported by Allen et al. （two samples）, LaRoque et al. and Ettori et al., are analyzed in detail in the context of two theoretical models of fgas. The results from the analysis of Alien et al.＇s samples demonstrate the feasibility of our method. It is found that the preferred cosmology by LaRoque et al.＇s sample is consistent with its reference cosmology within the 1σ confidence level. However, for Ettori et al.＇s fgas sample, the inconsistency can reach more than a 3σ confidence level and this dataset shows special preference to an ΩA = 0 cosmology.
基金supported by the National Natural Science Foundation of China(NSFCGrant No.11403004)+4 种基金the School Foundation of Changzhou University(ZMF1002121)support by the 973 Program(2014 CB845702)the Strategic Priority Research Program"The Emergence of Cosmological Structures"of the Chinese Academy of Sciences(CASgrant XDB09010100)the NSFC(Grant No.11373054)
文摘In order to obtain clean members of the open cluster NGC 6819, the proper motions and radial velocities of 1691 stars are used to construct a three-dimensional （3D） velocity space. Based on the DBSCAN clustering algorithm, 537 3D cluster members are obtained. From the 537 3D cluster members, the average radial velocity and absolute proper motion of the cluster are Vr = ＋2.30 ±0.04 km s-1 and （PMRA, PMDec） = （-2.5 ±0.5, -4.3 ± 0.5） mas yr-1, respectively. The proper motions, radial velocities, spatial positions and color-magnitude diagram of the 537 3D members indicate that our membership determination is effective. Among the 537 3D cluster members, 15 red clump giants can be easily identified by eye and are used as reliable standard candles for the distance estimate of the cluster. The distance modulus of the cluster is determined to be （m - M）0 -- 11.86 ± 0.05 mag （2355 ±54 pc）, which is quite consistent with published values. The uncertainty of our distance mod- ulus is dominated by the intrinsic dispersion in the luminosities of red clump giants （--0.04 mag）.
基金supported by the National Natural Science Foundation of China under Grant Nos.11175093, 11222545, 11435006 and 11375092by the Specialized Research Fund for the Doctoral Program of Higher Education under Grant No. 20124306110001
文摘The validity of the cosmic distance-duality （DD） relation is investigated by using 91 measure- ments of the gas mass fraction of galaxy clusters recently reported by the Atacama Cosmology Telescope （ACT） and the luminosity distance from the Union2.1 type Ia supernova （SNIa） sample independent of any cosmological models and the value of the Hubble constant. We consider four different approaches to derive the gas mass function and two different parameterizations of the DD relation, and find that they have very slight influences on the DD relation test and the relation is valid at the la confidence level. We also discuss the constraints on a andβ, which represent the effects of the shapes and colors of the light curves of SNIa, respectively. Our results on a and β are different from those obtained from the ACDM model and the galaxy cluster plus SNIa data.
文摘空间聚类是空间数据挖掘的重要手段之一。本文研究了一种基于质心点距离的Max-min distance空间聚类算法:通过加载园地图斑数据,计算其园地图斑质心,判断聚类中心之间的距离,并将符合条件的园地图斑进行聚类,最终将聚类结果可视化表达。本文的算法是利用Visual Studio 2017实验平台和ArcGIS Engine组件式开发环境,采用C#语言进行编写。实验结果表明:1)Max-mindistance聚类通过启发式的选择簇中心,克服了K-means选择簇中心过于邻近的缺点,能够适应嵩口镇等山区丘陵地区空间分布呈破碎的园地数据集分布,有效地实现园地的合理聚类;2)根据连片面积将园地空间聚类结果分为大中小三类,未来嵩口镇可以重点发展园地连片规模较大的村庄,形成规模化的青梅种植园。
