A novel model of fuzzy clustering, i.e. an allied fuzzy c means （AFCM） model is proposed based on the combination of advantages of fuzzy c means （FCM） and possibilistic c means （PCM） clustering. PCM is sensitive...A novel model of fuzzy clustering, i.e. an allied fuzzy c means （AFCM） model is proposed based on the combination of advantages of fuzzy c means （FCM） and possibilistic c means （PCM） clustering. PCM is sensitive to initializations and often generates coincident clusters. AFCM overcomes this shortcoming and it is an ex tension of PCM. Membership and typicality values can be simultaneously produced in AFCM. Experimental re- suits show that noise data can be well processed, coincident clusters are avoided and clustering accuracy is better.展开更多
To improve the accuracy of text clustering, fuzzy c-means clustering based on topic concept sub-space （TCS2FCM） is introduced for classifying texts. Five evaluation functions are combined to extract key phrases. Con...To improve the accuracy of text clustering, fuzzy c-means clustering based on topic concept sub-space （TCS2FCM） is introduced for classifying texts. Five evaluation functions are combined to extract key phrases. Concept phrases, as well as the descriptions of final clusters, are presented using WordNet origin from key phrases. Initial centers and membership matrix are the most important factors affecting clustering performance. Orthogonal concept topic sub-spaces are built with the topic concept phrases representing topics of the texts and the initialization of centers and the membership matrix depend on the concept vectors in sub-spaces. The results show that, different from random initialization of traditional fuzzy c-means clustering, the initialization related to text content contributions can improve clustering precision.展开更多
In studying the XCAP-C-like protein in the root meristematic cells of Allium sativa L., the nuclei were isolated from the cells and the nuclear matrices prepared. A 165 kD polypeptide, which is equivalent to XCAP-C in...In studying the XCAP-C-like protein in the root meristematic cells of Allium sativa L., the nuclei were isolated from the cells and the nuclear matrices prepared. A 165 kD polypeptide, which is equivalent to XCAP-C in molecular weight, was demonstrated in the nuclei by SDS-PAGE, and was then proved to be an XCAP-C-like protein by Western blot using an anti-XCAP-C antiserum, but neither the polypeptide nor the XCAP-C-like protein was detected in die nuclear matrix. The nuclei, Chromosomes and chromosome scaffolds were observed to emanate strong, specific fluorescence after labeled with the anti-XCAP-C antiserum and an FITC-conjugated secondary antibody, indicating their containment of the XCAP-C-like protein. It was confirmed by viewing with immunoelectron microscopy that the gold particles representing the localization of the XCAP-C-like protein were found to be mainly distributed in the condensed chromatin regions of the nuclei and chromosomes.展开更多
A new species, Hedotettix nujiangensis Zheng sp. nov., is described. The chromosome complement of H. nujiangensis consists of 2n （♂） = 13. Sex determination is XO. All chromosomes are telocentric （T） and the sex ...A new species, Hedotettix nujiangensis Zheng sp. nov., is described. The chromosome complement of H. nujiangensis consists of 2n （♂） = 13. Sex determination is XO. All chromosomes are telocentric （T） and the sex chromosome is the fourth element in size. Type specimens are deposited at Southwest Forestry University.展开更多
To solve the traveling salesman problem with the characteristics of clustering,a novel hybrid algorithm,the ant colony algorithm combined with the C-means algorithm,is presented.In order to improve the speed of conver...To solve the traveling salesman problem with the characteristics of clustering,a novel hybrid algorithm,the ant colony algorithm combined with the C-means algorithm,is presented.In order to improve the speed of convergence,the traveling salesman problem(TSP)data is specially clustered by the C-means algorithm,then,the result is processed by the ant colony algorithm to solve the problem.The proposed algorithm treats the C-means algorithm as a new search operator and adopts a kind of local searching strategy—2-opt,so as to improve the searching performance.Given the cluster number,the algorithm can obtain the preferable solving result.Compared with the three other algorithms—the ant colony algorithm,the genetic algorithm and the simulated annealing algorithm,the proposed algorithm can make the results converge to the global optimum faster and it has higher accuracy.The algorithm can also be extended to solve other correlative clustering combination optimization problems.Experimental results indicate the validity of the proposed algorithm.展开更多
A fully integrated low power transmitter for an IEEE 802. llb transceiver system is implemented in SMIC 0.18μm technology. The direct-conversion transmitter includes two Chebyshev I low pass filters,two PGAs,a SSB mi...A fully integrated low power transmitter for an IEEE 802. llb transceiver system is implemented in SMIC 0.18μm technology. The direct-conversion transmitter includes two Chebyshev I low pass filters,two PGAs,a SSB mixer, and a PA driver. The transmitter provides a gain control of 32dB in 3dB steps. The maximum output power is - 3.4dBm and the EVM is 6. 8%. The power consumption of the transmitter is only 57.6mW with a 1.8V power supply. The chip area of the transmitter is 1.6mm × 1.6mm.展开更多
Partition-based clustering with weighted feature is developed in the framework of shadowed sets. The objects in the core and boundary regions, generated by shadowed sets-based clustering, have different impact on the ...Partition-based clustering with weighted feature is developed in the framework of shadowed sets. The objects in the core and boundary regions, generated by shadowed sets-based clustering, have different impact on the prototype of each cluster. By integrating feature weights, a formula for weight calculation is introduced to the clustering algorithm. The selection of weight exponent is crucial for good result and the weights are updated iteratively with each partition of clusters. The convergence of the weighted algorithms is given, and the feasible cluster validity indices of data mining application are utilized. Experimental results on both synthetic and real-life numerical data with different feature weights demonstrate that the weighted algorithm is better than the other unweighted algorithms.展开更多
Determining the relatively similar hydrological properties of the watersheds is very crucial in order to readily classify them for management practices such as flood and soil erosion control. This study aimed to ident...Determining the relatively similar hydrological properties of the watersheds is very crucial in order to readily classify them for management practices such as flood and soil erosion control. This study aimed to identify homogeneous hydrological watersheds using remote sensing data in western Iran. To achieve this goal, remote sensing indices including SAVI, LAI, NDMI, NDVI and snow cover, were extracted from MODIS data over the period 2000 to 2015. Then, a fuzzy method was used to clustering the watersheds based on the extracted indices. A fuzzy c-mean(FCM) algorithm enabled to classify 38 watersheds in three homogeneous groups.The optimal number of clusters was determined through evaluation of partition coefficient, partition entropy function and trial and error. The results indicated three homogeneous regions identified by the fuzzy c-mean clustering and remote sensing product which are consistent with the variations of topography and climate of the study area. Inherently,the grouped watersheds have similar hydrological properties and are likely to need similar management considerations and measures.展开更多
基金National Science foundation of China(10671126)Shanghai Higher Education Outstanding Young Professor(sdl07038)Doctor foundation of Shanghai University of Electric Power(F06028).
文摘A novel model of fuzzy clustering, i.e. an allied fuzzy c means （AFCM） model is proposed based on the combination of advantages of fuzzy c means （FCM） and possibilistic c means （PCM） clustering. PCM is sensitive to initializations and often generates coincident clusters. AFCM overcomes this shortcoming and it is an ex tension of PCM. Membership and typicality values can be simultaneously produced in AFCM. Experimental re- suits show that noise data can be well processed, coincident clusters are avoided and clustering accuracy is better.
基金The National Natural Science Foundation of China(No60672056)Open Fund of MOE-MS Key Laboratory of Multime-dia Computing and Communication(No06120809)
文摘To improve the accuracy of text clustering, fuzzy c-means clustering based on topic concept sub-space （TCS2FCM） is introduced for classifying texts. Five evaluation functions are combined to extract key phrases. Concept phrases, as well as the descriptions of final clusters, are presented using WordNet origin from key phrases. Initial centers and membership matrix are the most important factors affecting clustering performance. Orthogonal concept topic sub-spaces are built with the topic concept phrases representing topics of the texts and the initialization of centers and the membership matrix depend on the concept vectors in sub-spaces. The results show that, different from random initialization of traditional fuzzy c-means clustering, the initialization related to text content contributions can improve clustering precision.
文摘In studying the XCAP-C-like protein in the root meristematic cells of Allium sativa L., the nuclei were isolated from the cells and the nuclear matrices prepared. A 165 kD polypeptide, which is equivalent to XCAP-C in molecular weight, was demonstrated in the nuclei by SDS-PAGE, and was then proved to be an XCAP-C-like protein by Western blot using an anti-XCAP-C antiserum, but neither the polypeptide nor the XCAP-C-like protein was detected in die nuclear matrix. The nuclei, Chromosomes and chromosome scaffolds were observed to emanate strong, specific fluorescence after labeled with the anti-XCAP-C antiserum and an FITC-conjugated secondary antibody, indicating their containment of the XCAP-C-like protein. It was confirmed by viewing with immunoelectron microscopy that the gold particles representing the localization of the XCAP-C-like protein were found to be mainly distributed in the condensed chromatin regions of the nuclei and chromosomes.
基金supported by the National Natural Science Foundation of China (31060291)
文摘A new species, Hedotettix nujiangensis Zheng sp. nov., is described. The chromosome complement of H. nujiangensis consists of 2n （♂） = 13. Sex determination is XO. All chromosomes are telocentric （T） and the sex chromosome is the fourth element in size. Type specimens are deposited at Southwest Forestry University.
基金The National Key Technology R&D Program of China during the 11th Five-Year Plan Period(No.2006BAH02A06)
文摘To solve the traveling salesman problem with the characteristics of clustering,a novel hybrid algorithm,the ant colony algorithm combined with the C-means algorithm,is presented.In order to improve the speed of convergence,the traveling salesman problem(TSP)data is specially clustered by the C-means algorithm,then,the result is processed by the ant colony algorithm to solve the problem.The proposed algorithm treats the C-means algorithm as a new search operator and adopts a kind of local searching strategy—2-opt,so as to improve the searching performance.Given the cluster number,the algorithm can obtain the preferable solving result.Compared with the three other algorithms—the ant colony algorithm,the genetic algorithm and the simulated annealing algorithm,the proposed algorithm can make the results converge to the global optimum faster and it has higher accuracy.The algorithm can also be extended to solve other correlative clustering combination optimization problems.Experimental results indicate the validity of the proposed algorithm.
文摘A fully integrated low power transmitter for an IEEE 802. llb transceiver system is implemented in SMIC 0.18μm technology. The direct-conversion transmitter includes two Chebyshev I low pass filters,two PGAs,a SSB mixer, and a PA driver. The transmitter provides a gain control of 32dB in 3dB steps. The maximum output power is - 3.4dBm and the EVM is 6. 8%. The power consumption of the transmitter is only 57.6mW with a 1.8V power supply. The chip area of the transmitter is 1.6mm × 1.6mm.
基金Supported by the National Natural Science Foundation of China(61139002)~~
文摘Partition-based clustering with weighted feature is developed in the framework of shadowed sets. The objects in the core and boundary regions, generated by shadowed sets-based clustering, have different impact on the prototype of each cluster. By integrating feature weights, a formula for weight calculation is introduced to the clustering algorithm. The selection of weight exponent is crucial for good result and the weights are updated iteratively with each partition of clusters. The convergence of the weighted algorithms is given, and the feasible cluster validity indices of data mining application are utilized. Experimental results on both synthetic and real-life numerical data with different feature weights demonstrate that the weighted algorithm is better than the other unweighted algorithms.
文摘Determining the relatively similar hydrological properties of the watersheds is very crucial in order to readily classify them for management practices such as flood and soil erosion control. This study aimed to identify homogeneous hydrological watersheds using remote sensing data in western Iran. To achieve this goal, remote sensing indices including SAVI, LAI, NDMI, NDVI and snow cover, were extracted from MODIS data over the period 2000 to 2015. Then, a fuzzy method was used to clustering the watersheds based on the extracted indices. A fuzzy c-mean(FCM) algorithm enabled to classify 38 watersheds in three homogeneous groups.The optimal number of clusters was determined through evaluation of partition coefficient, partition entropy function and trial and error. The results indicated three homogeneous regions identified by the fuzzy c-mean clustering and remote sensing product which are consistent with the variations of topography and climate of the study area. Inherently,the grouped watersheds have similar hydrological properties and are likely to need similar management considerations and measures.
