Satellite image segmentation plays a crucial role in remote sensing,supporting applications such as environmental monitoring,land use analysis,and disaster management.However,traditional segmentation methods often rel...Satellite image segmentation plays a crucial role in remote sensing,supporting applications such as environmental monitoring,land use analysis,and disaster management.However,traditional segmentation methods often rely on large amounts of labeled data,which are costly and time-consuming to obtain,especially in largescale or dynamic environments.To address this challenge,we propose the Semi-Supervised Multi-View Picture Fuzzy Clustering(SS-MPFC)algorithm,which improves segmentation accuracy and robustness,particularly in complex and uncertain remote sensing scenarios.SS-MPFC unifies three paradigms:semi-supervised learning,multi-view clustering,and picture fuzzy set theory.This integration allows the model to effectively utilize a small number of labeled samples,fuse complementary information from multiple data views,and handle the ambiguity and uncertainty inherent in satellite imagery.We design a novel objective function that jointly incorporates picture fuzzy membership functions across multiple views of the data,and embeds pairwise semi-supervised constraints(must-link and cannot-link)directly into the clustering process to enhance segmentation accuracy.Experiments conducted on several benchmark satellite datasets demonstrate that SS-MPFC significantly outperforms existing state-of-the-art methods in segmentation accuracy,noise robustness,and semantic interpretability.On the Augsburg dataset,SS-MPFC achieves a Purity of 0.8158 and an Accuracy of 0.6860,highlighting its outstanding robustness and efficiency.These results demonstrate that SSMPFC offers a scalable and effective solution for real-world satellite-based monitoring systems,particularly in scenarios where rapid annotation is infeasible,such as wildfire tracking,agricultural monitoring,and dynamic urban mapping.展开更多
In distributed fusion,when one or more sensors are disturbed by faults,a common problem is that their local estimations are inconsistent with those of other fault-free sensors.Most of the existing fault-tolerant distr...In distributed fusion,when one or more sensors are disturbed by faults,a common problem is that their local estimations are inconsistent with those of other fault-free sensors.Most of the existing fault-tolerant distributed fusion algorithms,such as the Covariance Union(CU)and Faulttolerant Generalized Convex Combination(FGCC),are only used for the point estimation case where local estimates and their associated error covariances are provided.A treatment with focus on the fault-tolerant distributed fusions of arbitrary local Probability Density Functions(PDFs)is lacking.For this problem,we first propose Kullback–Leibler Divergence(KLD)and reversed KLD induced functional Fuzzy c-Means(FCM)clustering algorithms to soft cluster all local PDFs,respectively.On this basis,two fault-tolerant distributed fusion algorithms of arbitrary local PDFs are then developed.They select the representing PDF of the cluster with the largest sum of memberships as the fused PDF.Numerical examples verify the better fault tolerance of the developed two distributed fusion algorithms.展开更多
Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy cl...Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy clustering techniques,such as Fuzzy C-Means(FCM),face significant challenges in handling uncertainty and the dependencies between different views.To overcome these limitations,we introduce a new multi-view fuzzy clustering approach that integrates picture fuzzy sets with a dual-anchor graph method for multi-view data,aiming to enhance clustering accuracy and robustness,termed Multi-view Picture Fuzzy Clustering(MPFC).In particular,the picture fuzzy set theory extends the capability to represent uncertainty by modeling three membership levels:membership degrees,neutral degrees,and refusal degrees.This allows for a more flexible representation of uncertain and conflicting data than traditional fuzzy models.Meanwhile,dual-anchor graphs exploit the similarity relationships between data points and integrate information across views.This combination improves stability,scalability,and robustness when handling noisy and heterogeneous data.Experimental results on several benchmark datasets demonstrate significant improvements in clustering accuracy and efficiency,outperforming traditional methods.Specifically,the MPFC algorithm demonstrates outstanding clustering performance on a variety of datasets,attaining a Purity(PUR)score of 0.6440 and an Accuracy(ACC)score of 0.6213 for the 3 Sources dataset,underscoring its robustness and efficiency.The proposed approach significantly contributes to fields such as pattern recognition,multi-view relational data analysis,and large-scale clustering problems.Future work will focus on extending the method for semi-supervised multi-view clustering,aiming to enhance adaptability,scalability,and performance in real-world applications.展开更多
With the rapid development of the aviation industry,air travel has become one of the most important modes.Improving the service quality of civil aviation airports is crucial to their competitiveness.This study intends...With the rapid development of the aviation industry,air travel has become one of the most important modes.Improving the service quality of civil aviation airports is crucial to their competitiveness.This study intends to develop a scientific and rational evaluation methodology and framework for assessing service quality in civil aviation airports,thereby providing a theoretical foundation and practical guidance for enhancing service standards in the aviation industry.First,the study constructs a CRITIC-bidirectional grey possibility clustering model,which uses the CRITIC method to determine the weights of indicators and integrates the forward grey possibility clustering model and the inverse grey possibility clustering model to determine possibility functions from two perspectives.Second,a service quality evaluation index system for civil airports is constructed from four dimensions,and the weights of each index within the system are subsequently calculated.Finally,the constructed model is applied to evaluate the service quality of nine domestic civil airports.Based on the clustering results,targeted countermeasures and suggestions are proposed.Empirical results demonstrate that,compared to the traditional grey possibility clustering model,the proposed model balances the objectivity of indicator weighting,the objectivity of possibility function construction,and the simplicity of the computational process,thereby possessing significant theoretical and practical implications.展开更多
Existing multi-view deep subspace clustering methods aim to learn a unified representation from multi-view data,while the learned representation is difficult to maintain the underlying structure hidden in the origin s...Existing multi-view deep subspace clustering methods aim to learn a unified representation from multi-view data,while the learned representation is difficult to maintain the underlying structure hidden in the origin samples,especially the high-order neighbor relationship between samples.To overcome the above challenges,this paper proposes a novel multi-order neighborhood fusion based multi-view deep subspace clustering model.We creatively integrate the multi-order proximity graph structures of different views into the self-expressive layer by a multi-order neighborhood fusion module.By this design,the multi-order Laplacian matrix supervises the learning of the view-consistent self-representation affinity matrix;then,we can obtain an optimal global affinity matrix where each connected node belongs to one cluster.In addition,the discriminative constraint between views is designed to further improve the clustering performance.A range of experiments on six public datasets demonstrates that the method performs better than other advanced multi-view clustering methods.The code is available at https://github.com/songzuolong/MNF-MDSC(accessed on 25 December 2024).展开更多
The increasing prevalence of multi-view data has made multi-view clustering a crucial technique for discovering latent structures from heterogeneous representations.However,traditional fuzzy clustering algorithms show...The increasing prevalence of multi-view data has made multi-view clustering a crucial technique for discovering latent structures from heterogeneous representations.However,traditional fuzzy clustering algorithms show limitations with the inherent uncertainty and imprecision of such data,as they rely on a single-dimensional membership value.To overcome these limitations,we propose an auto-weighted multi-view neutrosophic fuzzy clustering(AW-MVNFC)algorithm.Our method leverages the neutrosophic framework,an extension of fuzzy sets,to explicitly model imprecision and ambiguity through three membership degrees.The core novelty of AWMVNFC lies in a hierarchical weighting strategy that adaptively learns the contributions of both individual data views and the importance of each feature within a view.Through a unified objective function,AW-MVNFC jointly optimizes the neutrosophic membership assignments,cluster centers,and the distributions of view and feature weights.Comprehensive experiments conducted on synthetic and real-world datasets demonstrate that our algorithm achieves more accurate and stable clustering than existing methods,demonstrating its effectiveness in handling the complexities of multi-view data.展开更多
Platinum-based(Pt)catalysts are notoriously susceptible to deactivation in industrial chemical processes due to carbon monoxide(CO)poisoning.Overcoming this poisoning deactivation of Pt-based catalysts while enhancing...Platinum-based(Pt)catalysts are notoriously susceptible to deactivation in industrial chemical processes due to carbon monoxide(CO)poisoning.Overcoming this poisoning deactivation of Pt-based catalysts while enhancing their catalytic activity,selectivity,and durability remains a major challenge.Herein,we propose a strategy to enhance the CO tolerance of Pt clusters(Pt_n)by introducing neighboring functionalized vip single atoms(such as Fe,Co,Ni,Cu,Sb,and Bi).Among them,antimony(Sb)single atoms(SAs)exhibit significant performance enhancement,achieving 99%CO selectivity and 33.6%CO_(2)conversion at 450℃,Experimental results and density functional theory(DFT)calculations indicate the optimization arises from the electronic interaction between neighboring functionalized Sb SAs and Pt clusters,leading to optimal 5d electron redistribution in Pt clusters compared to other functionalized vip single atoms.The redistribution of 5d electrons weaken both theσdonation andπbackdonation interactions,resulting in a weakened bond strength with CO and enhancing catalyst activity and selectivity.In situ environmental transmission electron microscopy(ETEM)further demonstrates the exception thermal stability of the catalyst,even under H_(2)at 700℃.Notably,the functionalized Sb SAs also improve CO tolerance in various heterogenous catalysts,including Co/CeO_(2),Ni/CeO_(2),Pt/Al_(2)O_(3),and Pt/CeO_(2)-C.This finding provides an effective approach to overcome the primary challenge of CO poisoning in Pt-based catalysts,making their broader applications in various industrial catalysts.展开更多
Modularity is the key to improving the cost-variety trade-off in product development. To achieve the functional independency and structural independency of modules, a method of clustering components to identify module...Modularity is the key to improving the cost-variety trade-off in product development. To achieve the functional independency and structural independency of modules, a method of clustering components to identify modules based on functional and structural analysis was presented. Two stages were included in the method. In the first stage the products’ function was analyzed to determine the primary level of modules. Then the objective function for modules identifying was formulated to achieve functional independency of modules. Finally the genetic algorithm was used to solve the combinatorial optimization problem in modules identifying to form the primary modules of products. In the second stage the cohesion degree of modules and the coupling degree between modules were analyzed. Based on this structural analysis the modular scheme was refined according to the thinking of structural independency. A case study on the gear reducer was conducted to illustrate the validity of the presented method.展开更多
The internal structures as well as adsorption and hopping energies of monomers, dimers, trimers, tetramers, pentamers and hexamers of water on Pd（111） have been studied by density functional theory （DFT） plane-wav...The internal structures as well as adsorption and hopping energies of monomers, dimers, trimers, tetramers, pentamers and hexamers of water on Pd（111） have been studied by density functional theory （DFT） plane-wave pseudopotential method which performs the firstprinciples quantum-mechanical calculations to explore the properties of crystals and surfaces in materials. Based on the calculations, we suppose that their absorption is via one water molecule for monomers, dimmers and trimers, but three water molecules for pentamers and hexamers. Moreover, there is one water molecule bonding with Pd atom by O atom in pentamers and hexamers, which explains why pentamers and hexamers are stable. The binding energies of polymers may be used to explain why the trimer comes close to two nearby monomers to form a stable pentamer instead of tetramer. And the difference of mobility of small water clusters is due to their different hopping energies.展开更多
In recent years, functional data has been widely used in finance, medicine, biology and other fields. The current clustering analysis can solve the problems in finite-dimensional space, but it is difficult to be direc...In recent years, functional data has been widely used in finance, medicine, biology and other fields. The current clustering analysis can solve the problems in finite-dimensional space, but it is difficult to be directly used for the clustering of functional data. In this paper, we propose a new unsupervised clustering algorithm based on adaptive weights. In the absence of initialization parameter, we use entropy-type penalty terms and fuzzy partition matrix to find the optimal number of clusters. At the same time, we introduce a measure based on adaptive weights to reflect the difference in information content between different clustering metrics. Simulation experiments show that the proposed algorithm has higher purity than some algorithms.展开更多
We study the geometries, stabilities, electronic and magnetic properties of （MgO）n （n=2-10） clusters doped with a single Mn atom using the density functional theory with the gener- alized gradient approximation. T...We study the geometries, stabilities, electronic and magnetic properties of （MgO）n （n=2-10） clusters doped with a single Mn atom using the density functional theory with the gener- alized gradient approximation. The optimized geometries show that the impurity Mn atom prefers to replace the Mg atom which has low coordination number in all the lowest-energy MnMgn-1On （n=2-10） structures. The stability analysis clearly represents that the average binding energies of the doped clusters are larger than those of the corresponding pure （MgO）n clusters. Maximum peaks of the second order energy differences are observed for MnMg~_1On clusters at n=6, 9, implying that these clusters exhibit higher stability than their neighboring clusters. In addition, all the Mn-doped Mg clusters exhibit high total magnetic moments with the exception of MnMgO2 which has 3.00μB. Their magnetic behavior is attributed to the impurity Mn atom, the charge transfer modes, and the size of MnMgn- 1On clusters.展开更多
The clustering evaluation can be used to scientifically classify the objects to be evaluated according to the information aggregation of various evaluation rules. In grey weighted clustering evaluation, the index clus...The clustering evaluation can be used to scientifically classify the objects to be evaluated according to the information aggregation of various evaluation rules. In grey weighted clustering evaluation, the index clustering rule relies on the construction of the whitenization weight function, while the existing construction method of the linear function lacks the construction mechanism analysis and validity explanation. A normative construction principle is put forward by analyzing the construction mechanism of the function. Through proving the normative principle of the function,the basic modal function(BMF) is proposed and characterized by different function forms. Then, a new type of the whitenization weight function and its grey clustering evaluation model algorithm are given by studying the mechanism and nature of the construction of different forms of the function. Finally, the comparative study for self-innovation capability of defense science and technology industry(DSTI) is taken as an example. The results show that the different construction ways of the function have an effect on the clustering result. The proposed construction mechanism can better explain the index clustering rules and evaluation effectiveness,which will perfect the theoretical system of grey clustering evaluation and be applied to practice effectively.展开更多
The growth pattern and electronic properties of TiGen^- （n=7-12） clusters were investigated using anion photoelectron spectroscopy and density functional theory calculations. For both anionic and neutral TiGen clust...The growth pattern and electronic properties of TiGen^- （n=7-12） clusters were investigated using anion photoelectron spectroscopy and density functional theory calculations. For both anionic and neutral TiGen clusters, a half-encapsulated boat-shaped structure appears at n=8, and the boat-shaped structure is gradually covered by the additional Ge atoms to form Gen cage at n=9-11. TiGe12^- cluster has a distorted hexagonal prism cage structure. According to the natural population analysis, the electron transfers from the Gen framework to the Ti atom for TiGen^-/0 clusters at n=8-12, implying that the electron transfer pattern is related to the structural evolution.展开更多
The geometries of MgnNi2（n = 1 6） clusters are studied by using the hybrid density functional theory （B3LYP） with LANL2DZ basis sets. For the ground-state structures of MgnNi2 clusters, the stabilities and the ele...The geometries of MgnNi2（n = 1 6） clusters are studied by using the hybrid density functional theory （B3LYP） with LANL2DZ basis sets. For the ground-state structures of MgnNi2 clusters, the stabilities and the electronic properties are investigated. The results show that the groundstate structures and symmetries of Mg clusters change greatly due to the Ni atoms. The average binding energies have a growing tendency while the energy gaps have a declining tendency. In addition, the ionization energies exhibit an odd-even oscillation feature. We also conclude that n = 3, 5 are the magic numbers of the MgnNi2 clusters. The Mg3Ni2 and Mg5Ni2 clusters are more stable than neighbouring clusters, and the MgaNi2 cluster exhibits a higher chemical activity.展开更多
Anion ion photoelectron spectroscopy and density functional theory （DFT） are used to investigate the electronic and structural properties of ScSin （n = 2 - 6） clusters and their neutrals. We find that the structur...Anion ion photoelectron spectroscopy and density functional theory （DFT） are used to investigate the electronic and structural properties of ScSin （n = 2 - 6） clusters and their neutrals. We find that the structures of ScSin^- are similar to those of Sin＋1^-. The most stable isomers of ScSin^- cluster anions and their neutrals are similar for n=-2, 3 and 5 but different for n=4 and 6, indicating that the charge effect on geometry is size dependent for small scandiumsilicon clusters. The low electron binding energy （EBE） tails observed in the spectra of ScSi4,6^- can be explained by the existence of less stable isomers. A comparison between ScSin and VSin clusters shows the effects of metal size and electron configuration on cluster geometries.展开更多
The electronic and physical properties of PtmPdn （m＋n≤5） metal clusters and their interactions with dioxygen have been studied by using hybrid density functional B3LYP method. The total energies, atomization energ...The electronic and physical properties of PtmPdn （m＋n≤5） metal clusters and their interactions with dioxygen have been studied by using hybrid density functional B3LYP method. The total energies, atomization energies, vibration frequencies, and charge distributions were reported. The Pt-Pt bridge site modified by Pd atoms was found to be the most active site for the dissociation of dioxygen, which was mainly due to the change of electronic structures of the Pt atoms in bimetallic Pt-Pd clusters.展开更多
Structural and electronic properties of bimetallic clusters AlnCom with n=1～7 and m=1～2 have been investigated using the B3LYP-DFT method.Structural optimization and frequency analysis were performed at the CEP-121G...Structural and electronic properties of bimetallic clusters AlnCom with n=1～7 and m=1～2 have been investigated using the B3LYP-DFT method.Structural optimization and frequency analysis were performed at the CEP-121G level.The charge-induced structural changes in these anions were discussed.In addition,the corresponding total energies,binding energies,adiabatic electron affinities and vertical electron affinity were also presented and discussed.Our predicted vertical ionization potentials are in reasonable agreement with the experimental ionization potentials.Among different AlnCom and AlnCom-anions （n=1～7,m=1～2）,Al4Co,Al6Co,Al4Co-,Al6Co-and Al4Co2-are predicted to be species with high stabilities.展开更多
Although many multi-view clustering(MVC) algorithms with acceptable performances have been presented, to the best of our knowledge, nearly all of them need to be fed with the correct number of clusters. In addition, t...Although many multi-view clustering(MVC) algorithms with acceptable performances have been presented, to the best of our knowledge, nearly all of them need to be fed with the correct number of clusters. In addition, these existing algorithms create only the hard and fuzzy partitions for multi-view objects,which are often located in highly-overlapping areas of multi-view feature space. The adoption of hard and fuzzy partition ignores the ambiguity and uncertainty in the assignment of objects, likely leading to performance degradation. To address these issues, we propose a novel sparse reconstructive multi-view evidential clustering algorithm(SRMVEC). Based on a sparse reconstructive procedure, SRMVEC learns a shared affinity matrix across views, and maps multi-view objects to a 2-dimensional humanreadable chart by calculating 2 newly defined mathematical metrics for each object. From this chart, users can detect the number of clusters and select several objects existing in the dataset as cluster centers. Then, SRMVEC derives a credal partition under the framework of evidence theory, improving the fault tolerance of clustering. Ablation studies show the benefits of adopting the sparse reconstructive procedure and evidence theory. Besides,SRMVEC delivers effectiveness on benchmark datasets by outperforming some state-of-the-art methods.展开更多
Rational design and synthesis of low-cost trifunctional electrocatalysts with improved stability and superior electrocatalytic activity for oxygen reduction reaction(ORR),oxygen evolution reaction(OER),and hydrogen ev...Rational design and synthesis of low-cost trifunctional electrocatalysts with improved stability and superior electrocatalytic activity for oxygen reduction reaction(ORR),oxygen evolution reaction(OER),and hydrogen evolution reaction(HER) are highly desirable but remain as the bottlenecks at the current state of technology.In this paper,the cobalt-iron(Co-Fe) composite supported on nitrogen-doped carbon nanotubes(CoFe composite/NCNTs) is synthesized.The intrinsic OER and HER catalytic activities of this CoFe composite/NCNTs composite are significantly improved with palladium(Pd) nanocluster decoration [Pd-coated(CoFe composite/NCNTs)].The as-prepared Pd-coated(CoFe composite/NCNTs) catalyst exhibits excellent trifunctional electrocatalytic activity and stability due to the interfacial coupling between Pd and(CoFe composite/NCNTs).This catalyst is successfully employed in the water electrolysis cell as both OER and HER electrode catalysts,flexible rechargeable Zn-air battery as the bifunctional ORR and OER electrode catalyst.The cell voltage of this catalyst-coated electrodes requires only 1.60 V to achieve 10 mA cm^(-2) current density for water electrolysis cell,which is comparable to and even better than that of Pt/C and Ir/C based cell.The primary Zn-air battery using this catalyst shows a constant high open-circuit voltage(OCV) of 1.47 V and a maximum power density of 261 mW cm^(-2) in the flooded mode configuration.Most importantly,a flexible Zn-air battery with this catalyst runs very smoothly without a change in voltage gap during flat,bending,and twisting positions.展开更多
Boron is an element that has ability to build strong and highly directional bonds with boron itself. As a result, boron atoms form diverse structural motifs, ultimately can yield distinct nano structures, such as plan...Boron is an element that has ability to build strong and highly directional bonds with boron itself. As a result, boron atoms form diverse structural motifs, ultimately can yield distinct nano structures, such as planar, quasi-planar, convex, cage, open-cage, tubular, spherical, ring, dome-like, shell, capsule, and so on, i.e., it can take almost any shape. Therefore, a deep understanding of the physical and chemical properties becomes important in boron cluster chemistry. Electronic and geometric structures, total and binding energies, harmonic frequencies, point symmetries, charge distributions, dipole moments, chemical bondings and the highest occupied molecular orbital-lowest unoccupied molecular orbital energy gaps of neutral Bn （n=13-20） clusters have been investigated by density functional theory （DFT）, B3LYP with 6-311＋＋G（d,p） basis set. Furthermore, the first and the second energy differences are used to obtain the most stable sizes. We have observed that almost all physical properties are size dependent, and double-ring tubular form of B20 has the highest binding energy per atom. The icosahedral structure with an inside atom is found as impossible as a stable structure for the size thirteen. This structure transforms to an open-cage form. The structural transition from two-dimensional to three-dimensional is found at the size of 20 and consistent with the literature. The calculated charges by the Mulliken analysis show that there is a symmetry pattern with respect to the x-z and y-z planes for the charge distributions. The unusual planar stability of the boron clusters may be explained by the delocalized π and σ bonding characteristic together with the existence of the multicentered bonding. The results have been compared to available studies in the literature.展开更多
基金funded by the Research Project:THTETN.05/24-25,VietnamAcademy of Science and Technology.
文摘Satellite image segmentation plays a crucial role in remote sensing,supporting applications such as environmental monitoring,land use analysis,and disaster management.However,traditional segmentation methods often rely on large amounts of labeled data,which are costly and time-consuming to obtain,especially in largescale or dynamic environments.To address this challenge,we propose the Semi-Supervised Multi-View Picture Fuzzy Clustering(SS-MPFC)algorithm,which improves segmentation accuracy and robustness,particularly in complex and uncertain remote sensing scenarios.SS-MPFC unifies three paradigms:semi-supervised learning,multi-view clustering,and picture fuzzy set theory.This integration allows the model to effectively utilize a small number of labeled samples,fuse complementary information from multiple data views,and handle the ambiguity and uncertainty inherent in satellite imagery.We design a novel objective function that jointly incorporates picture fuzzy membership functions across multiple views of the data,and embeds pairwise semi-supervised constraints(must-link and cannot-link)directly into the clustering process to enhance segmentation accuracy.Experiments conducted on several benchmark satellite datasets demonstrate that SS-MPFC significantly outperforms existing state-of-the-art methods in segmentation accuracy,noise robustness,and semantic interpretability.On the Augsburg dataset,SS-MPFC achieves a Purity of 0.8158 and an Accuracy of 0.6860,highlighting its outstanding robustness and efficiency.These results demonstrate that SSMPFC offers a scalable and effective solution for real-world satellite-based monitoring systems,particularly in scenarios where rapid annotation is infeasible,such as wildfire tracking,agricultural monitoring,and dynamic urban mapping.
基金supported in part by the Open Fund of Intelligent Control Laboratory,China(No.ICL-2023–0202)in part by National Key R&D Program of China(Nos.2021YFC2202600,2021YFC2202603)。
文摘In distributed fusion,when one or more sensors are disturbed by faults,a common problem is that their local estimations are inconsistent with those of other fault-free sensors.Most of the existing fault-tolerant distributed fusion algorithms,such as the Covariance Union(CU)and Faulttolerant Generalized Convex Combination(FGCC),are only used for the point estimation case where local estimates and their associated error covariances are provided.A treatment with focus on the fault-tolerant distributed fusions of arbitrary local Probability Density Functions(PDFs)is lacking.For this problem,we first propose Kullback–Leibler Divergence(KLD)and reversed KLD induced functional Fuzzy c-Means(FCM)clustering algorithms to soft cluster all local PDFs,respectively.On this basis,two fault-tolerant distributed fusion algorithms of arbitrary local PDFs are then developed.They select the representing PDF of the cluster with the largest sum of memberships as the fused PDF.Numerical examples verify the better fault tolerance of the developed two distributed fusion algorithms.
基金funded by the Research Project:THTETN.05/24-25,VietnamAcademy of Science and Technology.
文摘Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy clustering techniques,such as Fuzzy C-Means(FCM),face significant challenges in handling uncertainty and the dependencies between different views.To overcome these limitations,we introduce a new multi-view fuzzy clustering approach that integrates picture fuzzy sets with a dual-anchor graph method for multi-view data,aiming to enhance clustering accuracy and robustness,termed Multi-view Picture Fuzzy Clustering(MPFC).In particular,the picture fuzzy set theory extends the capability to represent uncertainty by modeling three membership levels:membership degrees,neutral degrees,and refusal degrees.This allows for a more flexible representation of uncertain and conflicting data than traditional fuzzy models.Meanwhile,dual-anchor graphs exploit the similarity relationships between data points and integrate information across views.This combination improves stability,scalability,and robustness when handling noisy and heterogeneous data.Experimental results on several benchmark datasets demonstrate significant improvements in clustering accuracy and efficiency,outperforming traditional methods.Specifically,the MPFC algorithm demonstrates outstanding clustering performance on a variety of datasets,attaining a Purity(PUR)score of 0.6440 and an Accuracy(ACC)score of 0.6213 for the 3 Sources dataset,underscoring its robustness and efficiency.The proposed approach significantly contributes to fields such as pattern recognition,multi-view relational data analysis,and large-scale clustering problems.Future work will focus on extending the method for semi-supervised multi-view clustering,aiming to enhance adaptability,scalability,and performance in real-world applications.
基金support supplied by the National Natural Science Foundation of China(Nos.72571136,72271120)the Ministry of Education of the People’s Republic of China Humanities and Social Science project(No.24YJA630087)。
文摘With the rapid development of the aviation industry,air travel has become one of the most important modes.Improving the service quality of civil aviation airports is crucial to their competitiveness.This study intends to develop a scientific and rational evaluation methodology and framework for assessing service quality in civil aviation airports,thereby providing a theoretical foundation and practical guidance for enhancing service standards in the aviation industry.First,the study constructs a CRITIC-bidirectional grey possibility clustering model,which uses the CRITIC method to determine the weights of indicators and integrates the forward grey possibility clustering model and the inverse grey possibility clustering model to determine possibility functions from two perspectives.Second,a service quality evaluation index system for civil airports is constructed from four dimensions,and the weights of each index within the system are subsequently calculated.Finally,the constructed model is applied to evaluate the service quality of nine domestic civil airports.Based on the clustering results,targeted countermeasures and suggestions are proposed.Empirical results demonstrate that,compared to the traditional grey possibility clustering model,the proposed model balances the objectivity of indicator weighting,the objectivity of possibility function construction,and the simplicity of the computational process,thereby possessing significant theoretical and practical implications.
基金supported by the National Key R&D Program of China(2023YFC3304600).
文摘Existing multi-view deep subspace clustering methods aim to learn a unified representation from multi-view data,while the learned representation is difficult to maintain the underlying structure hidden in the origin samples,especially the high-order neighbor relationship between samples.To overcome the above challenges,this paper proposes a novel multi-order neighborhood fusion based multi-view deep subspace clustering model.We creatively integrate the multi-order proximity graph structures of different views into the self-expressive layer by a multi-order neighborhood fusion module.By this design,the multi-order Laplacian matrix supervises the learning of the view-consistent self-representation affinity matrix;then,we can obtain an optimal global affinity matrix where each connected node belongs to one cluster.In addition,the discriminative constraint between views is designed to further improve the clustering performance.A range of experiments on six public datasets demonstrates that the method performs better than other advanced multi-view clustering methods.The code is available at https://github.com/songzuolong/MNF-MDSC(accessed on 25 December 2024).
文摘The increasing prevalence of multi-view data has made multi-view clustering a crucial technique for discovering latent structures from heterogeneous representations.However,traditional fuzzy clustering algorithms show limitations with the inherent uncertainty and imprecision of such data,as they rely on a single-dimensional membership value.To overcome these limitations,we propose an auto-weighted multi-view neutrosophic fuzzy clustering(AW-MVNFC)algorithm.Our method leverages the neutrosophic framework,an extension of fuzzy sets,to explicitly model imprecision and ambiguity through three membership degrees.The core novelty of AWMVNFC lies in a hierarchical weighting strategy that adaptively learns the contributions of both individual data views and the importance of each feature within a view.Through a unified objective function,AW-MVNFC jointly optimizes the neutrosophic membership assignments,cluster centers,and the distributions of view and feature weights.Comprehensive experiments conducted on synthetic and real-world datasets demonstrate that our algorithm achieves more accurate and stable clustering than existing methods,demonstrating its effectiveness in handling the complexities of multi-view data.
基金financially supported by the Shanghai RisingStar Program(No.23QA1403700)the National Natural Science Foundation of China(NSFC,Grant No.U2230102)+1 种基金the sponsored by National Key Research and Development Program of China(No.2021YFB3502200)the Shanghai Technical Service Center of Science and Engineering Computing,Shanghai University.
文摘Platinum-based(Pt)catalysts are notoriously susceptible to deactivation in industrial chemical processes due to carbon monoxide(CO)poisoning.Overcoming this poisoning deactivation of Pt-based catalysts while enhancing their catalytic activity,selectivity,and durability remains a major challenge.Herein,we propose a strategy to enhance the CO tolerance of Pt clusters(Pt_n)by introducing neighboring functionalized vip single atoms(such as Fe,Co,Ni,Cu,Sb,and Bi).Among them,antimony(Sb)single atoms(SAs)exhibit significant performance enhancement,achieving 99%CO selectivity and 33.6%CO_(2)conversion at 450℃,Experimental results and density functional theory(DFT)calculations indicate the optimization arises from the electronic interaction between neighboring functionalized Sb SAs and Pt clusters,leading to optimal 5d electron redistribution in Pt clusters compared to other functionalized vip single atoms.The redistribution of 5d electrons weaken both theσdonation andπbackdonation interactions,resulting in a weakened bond strength with CO and enhancing catalyst activity and selectivity.In situ environmental transmission electron microscopy(ETEM)further demonstrates the exception thermal stability of the catalyst,even under H_(2)at 700℃.Notably,the functionalized Sb SAs also improve CO tolerance in various heterogenous catalysts,including Co/CeO_(2),Ni/CeO_(2),Pt/Al_(2)O_(3),and Pt/CeO_(2)-C.This finding provides an effective approach to overcome the primary challenge of CO poisoning in Pt-based catalysts,making their broader applications in various industrial catalysts.
基金National Basic Research Programme of China (973 Program) (No. 2003CB317005)Key Project of Chinese Ministry of Educa-tion (No. 105065)
文摘Modularity is the key to improving the cost-variety trade-off in product development. To achieve the functional independency and structural independency of modules, a method of clustering components to identify modules based on functional and structural analysis was presented. Two stages were included in the method. In the first stage the products’ function was analyzed to determine the primary level of modules. Then the objective function for modules identifying was formulated to achieve functional independency of modules. Finally the genetic algorithm was used to solve the combinatorial optimization problem in modules identifying to form the primary modules of products. In the second stage the cohesion degree of modules and the coupling degree between modules were analyzed. Based on this structural analysis the modular scheme was refined according to the thinking of structural independency. A case study on the gear reducer was conducted to illustrate the validity of the presented method.
基金Supported by the Natural Science Foundation of Yunnan Province (No. 2004B0003M)
文摘The internal structures as well as adsorption and hopping energies of monomers, dimers, trimers, tetramers, pentamers and hexamers of water on Pd（111） have been studied by density functional theory （DFT） plane-wave pseudopotential method which performs the firstprinciples quantum-mechanical calculations to explore the properties of crystals and surfaces in materials. Based on the calculations, we suppose that their absorption is via one water molecule for monomers, dimmers and trimers, but three water molecules for pentamers and hexamers. Moreover, there is one water molecule bonding with Pd atom by O atom in pentamers and hexamers, which explains why pentamers and hexamers are stable. The binding energies of polymers may be used to explain why the trimer comes close to two nearby monomers to form a stable pentamer instead of tetramer. And the difference of mobility of small water clusters is due to their different hopping energies.
文摘In recent years, functional data has been widely used in finance, medicine, biology and other fields. The current clustering analysis can solve the problems in finite-dimensional space, but it is difficult to be directly used for the clustering of functional data. In this paper, we propose a new unsupervised clustering algorithm based on adaptive weights. In the absence of initialization parameter, we use entropy-type penalty terms and fuzzy partition matrix to find the optimal number of clusters. At the same time, we introduce a measure based on adaptive weights to reflect the difference in information content between different clustering metrics. Simulation experiments show that the proposed algorithm has higher purity than some algorithms.
文摘We study the geometries, stabilities, electronic and magnetic properties of （MgO）n （n=2-10） clusters doped with a single Mn atom using the density functional theory with the gener- alized gradient approximation. The optimized geometries show that the impurity Mn atom prefers to replace the Mg atom which has low coordination number in all the lowest-energy MnMgn-1On （n=2-10） structures. The stability analysis clearly represents that the average binding energies of the doped clusters are larger than those of the corresponding pure （MgO）n clusters. Maximum peaks of the second order energy differences are observed for MnMg~_1On clusters at n=6, 9, implying that these clusters exhibit higher stability than their neighboring clusters. In addition, all the Mn-doped Mg clusters exhibit high total magnetic moments with the exception of MnMgO2 which has 3.00μB. Their magnetic behavior is attributed to the impurity Mn atom, the charge transfer modes, and the size of MnMgn- 1On clusters.
基金supported by the National Natural Science Foundation of China(71671090)the Aeronautical Science Foundation of China(2016ZG52068)+1 种基金the Liberal Arts and Social Sciences Foundation of the Ministry of Education(MOE)in China(15YJCZH189)the Qinglan Project for Excellent Youth or Middle-aged Academic Leaders in Jiangsu Province
文摘The clustering evaluation can be used to scientifically classify the objects to be evaluated according to the information aggregation of various evaluation rules. In grey weighted clustering evaluation, the index clustering rule relies on the construction of the whitenization weight function, while the existing construction method of the linear function lacks the construction mechanism analysis and validity explanation. A normative construction principle is put forward by analyzing the construction mechanism of the function. Through proving the normative principle of the function,the basic modal function(BMF) is proposed and characterized by different function forms. Then, a new type of the whitenization weight function and its grey clustering evaluation model algorithm are given by studying the mechanism and nature of the construction of different forms of the function. Finally, the comparative study for self-innovation capability of defense science and technology industry(DSTI) is taken as an example. The results show that the different construction ways of the function have an effect on the clustering result. The proposed construction mechanism can better explain the index clustering rules and evaluation effectiveness,which will perfect the theoretical system of grey clustering evaluation and be applied to practice effectively.
基金Wei-jun Zheng acknowledges the Knowledge Innovation Program of the Chinese Academy of Sciences （No.KJCX2-EW-H01） and Hong-guang Xu acknowl- edges the National Natural Science Foundation of China （No.21103202） for financial support. The theoretical calculations were conducted on the ScGrid and Deep- Comp 7000 of the Supercomputing Center, Computer Network Information Center of the Chinese Academy of Sciences.
文摘The growth pattern and electronic properties of TiGen^- （n=7-12） clusters were investigated using anion photoelectron spectroscopy and density functional theory calculations. For both anionic and neutral TiGen clusters, a half-encapsulated boat-shaped structure appears at n=8, and the boat-shaped structure is gradually covered by the additional Ge atoms to form Gen cage at n=9-11. TiGe12^- cluster has a distorted hexagonal prism cage structure. According to the natural population analysis, the electron transfers from the Gen framework to the Ti atom for TiGen^-/0 clusters at n=8-12, implying that the electron transfer pattern is related to the structural evolution.
基金Project supported by the National Natural Science Foundation of China (Grant No. 10676022)
文摘The geometries of MgnNi2（n = 1 6） clusters are studied by using the hybrid density functional theory （B3LYP） with LANL2DZ basis sets. For the ground-state structures of MgnNi2 clusters, the stabilities and the electronic properties are investigated. The results show that the groundstate structures and symmetries of Mg clusters change greatly due to the Ni atoms. The average binding energies have a growing tendency while the energy gaps have a declining tendency. In addition, the ionization energies exhibit an odd-even oscillation feature. We also conclude that n = 3, 5 are the magic numbers of the MgnNi2 clusters. The Mg3Ni2 and Mg5Ni2 clusters are more stable than neighbouring clusters, and the MgaNi2 cluster exhibits a higher chemical activity.
基金supported by the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KJCX2-EW-01)the National Natural Science Foundation of China (Grant Nos. 20853001 and 10874007)
文摘Anion ion photoelectron spectroscopy and density functional theory （DFT） are used to investigate the electronic and structural properties of ScSin （n = 2 - 6） clusters and their neutrals. We find that the structures of ScSin^- are similar to those of Sin＋1^-. The most stable isomers of ScSin^- cluster anions and their neutrals are similar for n=-2, 3 and 5 but different for n=4 and 6, indicating that the charge effect on geometry is size dependent for small scandiumsilicon clusters. The low electron binding energy （EBE） tails observed in the spectra of ScSi4,6^- can be explained by the existence of less stable isomers. A comparison between ScSin and VSin clusters shows the effects of metal size and electron configuration on cluster geometries.
基金This work was partly supported by Innovation Foundation of the Chinese Academy of Sciences (K2003D2), National Natural Science Foundation of China (No. 20173060), Hi-tech Research and Development Program of China (2003AA517040) and Knowledge Innovation Program of the Chinese Academy of Sciences (KGCX2-SW-310)
文摘The electronic and physical properties of PtmPdn （m＋n≤5） metal clusters and their interactions with dioxygen have been studied by using hybrid density functional B3LYP method. The total energies, atomization energies, vibration frequencies, and charge distributions were reported. The Pt-Pt bridge site modified by Pd atoms was found to be the most active site for the dissociation of dioxygen, which was mainly due to the change of electronic structures of the Pt atoms in bimetallic Pt-Pd clusters.
基金supported by the National Natural Science Foundation of China (20603021)Youth Foundation of Shanxi Province (2007021009)
文摘Structural and electronic properties of bimetallic clusters AlnCom with n=1～7 and m=1～2 have been investigated using the B3LYP-DFT method.Structural optimization and frequency analysis were performed at the CEP-121G level.The charge-induced structural changes in these anions were discussed.In addition,the corresponding total energies,binding energies,adiabatic electron affinities and vertical electron affinity were also presented and discussed.Our predicted vertical ionization potentials are in reasonable agreement with the experimental ionization potentials.Among different AlnCom and AlnCom-anions （n=1～7,m=1～2）,Al4Co,Al6Co,Al4Co-,Al6Co-and Al4Co2-are predicted to be species with high stabilities.
基金supported in part by NUS startup grantthe National Natural Science Foundation of China (52076037)。
文摘Although many multi-view clustering(MVC) algorithms with acceptable performances have been presented, to the best of our knowledge, nearly all of them need to be fed with the correct number of clusters. In addition, these existing algorithms create only the hard and fuzzy partitions for multi-view objects,which are often located in highly-overlapping areas of multi-view feature space. The adoption of hard and fuzzy partition ignores the ambiguity and uncertainty in the assignment of objects, likely leading to performance degradation. To address these issues, we propose a novel sparse reconstructive multi-view evidential clustering algorithm(SRMVEC). Based on a sparse reconstructive procedure, SRMVEC learns a shared affinity matrix across views, and maps multi-view objects to a 2-dimensional humanreadable chart by calculating 2 newly defined mathematical metrics for each object. From this chart, users can detect the number of clusters and select several objects existing in the dataset as cluster centers. Then, SRMVEC derives a credal partition under the framework of evidence theory, improving the fault tolerance of clustering. Ablation studies show the benefits of adopting the sparse reconstructive procedure and evidence theory. Besides,SRMVEC delivers effectiveness on benchmark datasets by outperforming some state-of-the-art methods.
基金the support of the National Nature Science Foundation of China (21908124)Zhaoqing Xijiang Talent Program。
文摘Rational design and synthesis of low-cost trifunctional electrocatalysts with improved stability and superior electrocatalytic activity for oxygen reduction reaction(ORR),oxygen evolution reaction(OER),and hydrogen evolution reaction(HER) are highly desirable but remain as the bottlenecks at the current state of technology.In this paper,the cobalt-iron(Co-Fe) composite supported on nitrogen-doped carbon nanotubes(CoFe composite/NCNTs) is synthesized.The intrinsic OER and HER catalytic activities of this CoFe composite/NCNTs composite are significantly improved with palladium(Pd) nanocluster decoration [Pd-coated(CoFe composite/NCNTs)].The as-prepared Pd-coated(CoFe composite/NCNTs) catalyst exhibits excellent trifunctional electrocatalytic activity and stability due to the interfacial coupling between Pd and(CoFe composite/NCNTs).This catalyst is successfully employed in the water electrolysis cell as both OER and HER electrode catalysts,flexible rechargeable Zn-air battery as the bifunctional ORR and OER electrode catalyst.The cell voltage of this catalyst-coated electrodes requires only 1.60 V to achieve 10 mA cm^(-2) current density for water electrolysis cell,which is comparable to and even better than that of Pt/C and Ir/C based cell.The primary Zn-air battery using this catalyst shows a constant high open-circuit voltage(OCV) of 1.47 V and a maximum power density of 261 mW cm^(-2) in the flooded mode configuration.Most importantly,a flexible Zn-air battery with this catalyst runs very smoothly without a change in voltage gap during flat,bending,and twisting positions.
文摘Boron is an element that has ability to build strong and highly directional bonds with boron itself. As a result, boron atoms form diverse structural motifs, ultimately can yield distinct nano structures, such as planar, quasi-planar, convex, cage, open-cage, tubular, spherical, ring, dome-like, shell, capsule, and so on, i.e., it can take almost any shape. Therefore, a deep understanding of the physical and chemical properties becomes important in boron cluster chemistry. Electronic and geometric structures, total and binding energies, harmonic frequencies, point symmetries, charge distributions, dipole moments, chemical bondings and the highest occupied molecular orbital-lowest unoccupied molecular orbital energy gaps of neutral Bn （n=13-20） clusters have been investigated by density functional theory （DFT）, B3LYP with 6-311＋＋G（d,p） basis set. Furthermore, the first and the second energy differences are used to obtain the most stable sizes. We have observed that almost all physical properties are size dependent, and double-ring tubular form of B20 has the highest binding energy per atom. The icosahedral structure with an inside atom is found as impossible as a stable structure for the size thirteen. This structure transforms to an open-cage form. The structural transition from two-dimensional to three-dimensional is found at the size of 20 and consistent with the literature. The calculated charges by the Mulliken analysis show that there is a symmetry pattern with respect to the x-z and y-z planes for the charge distributions. The unusual planar stability of the boron clusters may be explained by the delocalized π and σ bonding characteristic together with the existence of the multicentered bonding. The results have been compared to available studies in the literature.
