To improve the efficiency of the attribute reduction, we present an attribute reduction algorithm based on background knowledge and information entropy by making use of background knowledge from research fields. Under...To improve the efficiency of the attribute reduction, we present an attribute reduction algorithm based on background knowledge and information entropy by making use of background knowledge from research fields. Under the condition of known background knowledge, the algorithm can not only greatly improve the efficiency of attribute reduction, but also avoid the defection of information entropy partial to attribute with much value. The experimental result verifies that the algorithm is effective. In the end, the algorithm produces better results when applied in the classification of the star spectra data.展开更多
The problem on the set-theoretical solutions to the quantum Yang-Baxter equation was presented byDrinfel'd as a main unsolved problem in quantum group theory. The set-theoretical solutions are a natural extensiono...The problem on the set-theoretical solutions to the quantum Yang-Baxter equation was presented byDrinfel'd as a main unsolved problem in quantum group theory. The set-theoretical solutions are a natural extensionof the usual (linear) solutions. In this paper, we not only give a further study on some known set-theoretical solutions(the Venkov's solutions), but also find a new kind of set-theoretical solutions which have a geometric interpretation.Moreover, the new solutions lead to the metahomomorphisms in group theory.展开更多
To solve the complicated feature extraction and long distance dependency problem in Word Segmentation Disambiguation （WSD）, this paper proposes to apply rough sets ill WSD based on the Maximum Entropy model. Firstly...To solve the complicated feature extraction and long distance dependency problem in Word Segmentation Disambiguation （WSD）, this paper proposes to apply rough sets ill WSD based on the Maximum Entropy model. Firstly, rough set theory is applied to extract the complicated features and long distance features, even frnm noise or inconsistent corpus. Secondly, these features are added into the Maximum Entropy model, and consequently, the feature weights can be assigned according to the performance of the whole disambiguation mnltel. Finally, tile semantic lexicou is adopted to build class-hased rough set teatures to overcome data spareness. The experiment indicated that our method performed better than previous models, which got top rank in WSD in 863 Evaluation in 2003. This system ranked first and second respcetively in MSR and PKU open test in the Second International Chinese Word Segmentation Bankeoff held in 2005.展开更多
In order to effectively analyse the multivariate time series data of complex process,a generic reconstruction technology based on reduction theory of rough sets was proposed,Firstly,the phase space of multivariate tim...In order to effectively analyse the multivariate time series data of complex process,a generic reconstruction technology based on reduction theory of rough sets was proposed,Firstly,the phase space of multivariate time series was originally reconstructed by a classical reconstruction technology.Then,the original decision-table of rough set theory was set up according to the embedding dimensions and time-delays of the original reconstruction phase space,and the rough set reduction was used to delete the redundant dimensions and irrelevant variables and to reconstruct the generic phase space,Finally,the input vectors for the prediction of multivariate time series were extracted according to generic reconstruction results to identify the parameters of prediction model.Verification results show that the developed reconstruction method leads to better generalization ability for the prediction model and it is feasible and worthwhile for application.展开更多
Vagueness of language has long been explored in the fields of philosophy and logic. Although Zadeh put forward fuzzy sets theory which was considered to be a decent quantitative instrument for the study of language va...Vagueness of language has long been explored in the fields of philosophy and logic. Although Zadeh put forward fuzzy sets theory which was considered to be a decent quantitative instrument for the study of language vagueness, the source of vagueness still remains a disputed issue. As the study of vagueness goes further, researchers attached more and more attention to the relation between language-cognition- reality, especially in the cognitive field. Thus we found that it would be more satisfied with the issue to construct a relation-model between five factors： reality, concept, human, language, and context. This model, which is different from the semantic triangle in explicating the factors, human and context, may help to explain the nature of vagueness and reclassify the language vagueness.展开更多
This study covers the problem that most products become less competitive especially in the decline stages of their life cycle as most companies do not put adequate emphasis on using networked manufacturing systems in ...This study covers the problem that most products become less competitive especially in the decline stages of their life cycle as most companies do not put adequate emphasis on using networked manufacturing systems in the entire life cycle of a single product. The study employed a non-experimental approach to collect data. The research paper relied on secondary data for further analysis. The secondary sources used in this paper have been referenced progressively in the entire paper. The paper found that most companies are often faced with the challenge of coping with quality management in a product life cycle. Also, it found that networked manufacturing systems have provided a new paradigm for real-time monitoring and control at various life stages. The paper is divided as following parts： section 1 is about the background and problem statement. Section 2 comes through literature review including theoretical ＆ empirical review. Section 3 explains the procedures and methods that were used in carrying out the study. It explains how data collection was carried out and how data analysis was performed. Section 4 is about the results the paper found. Section 5 is a discussion of the results presented.展开更多
Using the vector diffraction theory and the phenomenological model, this paper investigates the second harmonic tion （SHG） of a single centrosymmetric nanosphere excited by focused doughnut beams （DBs） with differ...Using the vector diffraction theory and the phenomenological model, this paper investigates the second harmonic tion （SHG） of a single centrosymmetric nanosphere excited by focused doughnut beams （DBs） with different topological charges. The results show that strong backward SHG （BSHG） appears when the particle is excited by focused DBs with topological charges of ±1. The backward second harmonic radiation can be caused by the depolarized effect of high numerical aperture （NA） objectives due to the strong longitudinal components.展开更多
The author reviews some recent developments in Chern-Simons theory on a hyperbolic 3-manifold M with complex gauge group G. The author focuses on the case of G = SL(N, C) and M being a knot complement: M = S^3\ K. The...The author reviews some recent developments in Chern-Simons theory on a hyperbolic 3-manifold M with complex gauge group G. The author focuses on the case of G = SL(N, C) and M being a knot complement: M = S^3\ K. The main result presented in this note is the cluster partition function, a computational tool that uses cluster algebra techniques to evaluate the Chern-Simons path integral for G = SL(N, C). He also reviews various applications and open questions regarding the cluster partition function and some of its relation with string theory.展开更多
A binary decision diagram(BDD) is a data structure that is used to represent a Boolean function.Converting fault tree into BDD can effectively simplify counting processes and improve the accuracy and effectiveness of ...A binary decision diagram(BDD) is a data structure that is used to represent a Boolean function.Converting fault tree into BDD can effectively simplify counting processes and improve the accuracy and effectiveness of the results. However, due to various types of uncertainties in reliability data, we cannot obtain precise failure probabilities. In order to accurately quantify the certainties and obtain much more reliable results, we use BDD method based on fuzzy set theory for reliability quantitative analysis. In this regard, we take W-axis feeding system of heavy-duty computer numerical control(CNC) machine as a project example and adopt fuzzy BDD quantitative analysis method to analyze its reliability. The analysis results(aided by computer calculation)illustrate the effectiveness of the method proposed in this paper.展开更多
基金Supported by the National Natural Science Foundation of China（No. 60573075）, the National High Technology Research and Development Program of China （No. 2003AA133060） and the Natural Science Foundation of Shanxi Province （No. 200601104）.
文摘To improve the efficiency of the attribute reduction, we present an attribute reduction algorithm based on background knowledge and information entropy by making use of background knowledge from research fields. Under the condition of known background knowledge, the algorithm can not only greatly improve the efficiency of attribute reduction, but also avoid the defection of information entropy partial to attribute with much value. The experimental result verifies that the algorithm is effective. In the end, the algorithm produces better results when applied in the classification of the star spectra data.
文摘The problem on the set-theoretical solutions to the quantum Yang-Baxter equation was presented byDrinfel'd as a main unsolved problem in quantum group theory. The set-theoretical solutions are a natural extensionof the usual (linear) solutions. In this paper, we not only give a further study on some known set-theoretical solutions(the Venkov's solutions), but also find a new kind of set-theoretical solutions which have a geometric interpretation.Moreover, the new solutions lead to the metahomomorphisms in group theory.
文摘To solve the complicated feature extraction and long distance dependency problem in Word Segmentation Disambiguation （WSD）, this paper proposes to apply rough sets ill WSD based on the Maximum Entropy model. Firstly, rough set theory is applied to extract the complicated features and long distance features, even frnm noise or inconsistent corpus. Secondly, these features are added into the Maximum Entropy model, and consequently, the feature weights can be assigned according to the performance of the whole disambiguation mnltel. Finally, tile semantic lexicou is adopted to build class-hased rough set teatures to overcome data spareness. The experiment indicated that our method performed better than previous models, which got top rank in WSD in 863 Evaluation in 2003. This system ranked first and second respcetively in MSR and PKU open test in the Second International Chinese Word Segmentation Bankeoff held in 2005.
基金Project(61025015) supported by the National Natural Science Funds for Distinguished Young Scholars of ChinaProject(21106036) supported by the National Natural Science Foundation of China+2 种基金Project(200805331103) supported by Research Fund for the Doctoral Program of Higher Education of ChinaProject(NCET-08-0576) supported by Program for New Century Excellent Talents in Universities of ChinaProject(11B038) supported by Scientific Research Fund for the Excellent Youth Scholars of Hunan Provincial Education Department,China
文摘In order to effectively analyse the multivariate time series data of complex process,a generic reconstruction technology based on reduction theory of rough sets was proposed,Firstly,the phase space of multivariate time series was originally reconstructed by a classical reconstruction technology.Then,the original decision-table of rough set theory was set up according to the embedding dimensions and time-delays of the original reconstruction phase space,and the rough set reduction was used to delete the redundant dimensions and irrelevant variables and to reconstruct the generic phase space,Finally,the input vectors for the prediction of multivariate time series were extracted according to generic reconstruction results to identify the parameters of prediction model.Verification results show that the developed reconstruction method leads to better generalization ability for the prediction model and it is feasible and worthwhile for application.
文摘Vagueness of language has long been explored in the fields of philosophy and logic. Although Zadeh put forward fuzzy sets theory which was considered to be a decent quantitative instrument for the study of language vagueness, the source of vagueness still remains a disputed issue. As the study of vagueness goes further, researchers attached more and more attention to the relation between language-cognition- reality, especially in the cognitive field. Thus we found that it would be more satisfied with the issue to construct a relation-model between five factors： reality, concept, human, language, and context. This model, which is different from the semantic triangle in explicating the factors, human and context, may help to explain the nature of vagueness and reclassify the language vagueness.
文摘This study covers the problem that most products become less competitive especially in the decline stages of their life cycle as most companies do not put adequate emphasis on using networked manufacturing systems in the entire life cycle of a single product. The study employed a non-experimental approach to collect data. The research paper relied on secondary data for further analysis. The secondary sources used in this paper have been referenced progressively in the entire paper. The paper found that most companies are often faced with the challenge of coping with quality management in a product life cycle. Also, it found that networked manufacturing systems have provided a new paradigm for real-time monitoring and control at various life stages. The paper is divided as following parts： section 1 is about the background and problem statement. Section 2 comes through literature review including theoretical ＆ empirical review. Section 3 explains the procedures and methods that were used in carrying out the study. It explains how data collection was carried out and how data analysis was performed. Section 4 is about the results the paper found. Section 5 is a discussion of the results presented.
基金supported by the National High Technology Research and Development Program of China (No.2011AA010205)the National Natural Science Foundation of China (Nos.10704043 and 61171027)+1 种基金the Key Program of the Applied Basic Research of Tianjin (No.10JCZDJC15200)the Specialized Research Fund for the Doctoral Program of Higher Education of China (No.20090031110033)
文摘Using the vector diffraction theory and the phenomenological model, this paper investigates the second harmonic tion （SHG） of a single centrosymmetric nanosphere excited by focused doughnut beams （DBs） with different topological charges. The results show that strong backward SHG （BSHG） appears when the particle is excited by focused DBs with topological charges of ±1. The backward second harmonic radiation can be caused by the depolarized effect of high numerical aperture （NA） objectives due to the strong longitudinal components.
基金supported by the U.S.Department of Energy(No.DE-SC0009988)
文摘The author reviews some recent developments in Chern-Simons theory on a hyperbolic 3-manifold M with complex gauge group G. The author focuses on the case of G = SL(N, C) and M being a knot complement: M = S^3\ K. The main result presented in this note is the cluster partition function, a computational tool that uses cluster algebra techniques to evaluate the Chern-Simons path integral for G = SL(N, C). He also reviews various applications and open questions regarding the cluster partition function and some of its relation with string theory.
基金the National Natural Science Foundation of China(No.51405065)
文摘A binary decision diagram(BDD) is a data structure that is used to represent a Boolean function.Converting fault tree into BDD can effectively simplify counting processes and improve the accuracy and effectiveness of the results. However, due to various types of uncertainties in reliability data, we cannot obtain precise failure probabilities. In order to accurately quantify the certainties and obtain much more reliable results, we use BDD method based on fuzzy set theory for reliability quantitative analysis. In this regard, we take W-axis feeding system of heavy-duty computer numerical control(CNC) machine as a project example and adopt fuzzy BDD quantitative analysis method to analyze its reliability. The analysis results(aided by computer calculation)illustrate the effectiveness of the method proposed in this paper.
