Song [Song D 2004 Phys. Rev. A69034301] first proposed two key distribution schemes with the symmetry feature.We find that, in the schemes, the private channels which Alice and Bob publicly announce the initial Bell s...Song [Song D 2004 Phys. Rev. A69034301] first proposed two key distribution schemes with the symmetry feature.We find that, in the schemes, the private channels which Alice and Bob publicly announce the initial Bell state or the measurement result through are not needed in discovering keys, and Song’s encoding methods do not arrive at the optimization.Here, an optimized encoding method is given so that the efficiencies of Song’s schemes are improved by 7/3 times. Interestingly, this optimized encoding method can be extended to the key distribution scheme composed of generalized Bell states.展开更多
An encoding method has a direct effect on the quality and the representationof the discovered knowledge in data mining systems. Biological macromolecules are encoded by stringsof characters, called primary structures....An encoding method has a direct effect on the quality and the representationof the discovered knowledge in data mining systems. Biological macromolecules are encoded by stringsof characters, called primary structures. Knowing that data mining systems usually use relationaltables to encode data, we have then to re-encode these strings and transform them into relationaltables. In this paper, we do a comparative study of the existing static encoding methods, that arebased on the Biologist know-how, and our new dynamic encoding one, that is based on the constructionof Discriminant and Minimal Substrings (DMS). Different classification methods are used to do thisstudy. The experimental results show that our dynamic encoding method is more efficient than thestatic ones, to encode biological macromolecules within a data mining perspective.展开更多
This paPer addresses the issue of building a case-based preliminary design system by using Hopfield networks. one limitation of Hopfield networks is that it cannot be tralned, i.e. the weights between two neurons must...This paPer addresses the issue of building a case-based preliminary design system by using Hopfield networks. one limitation of Hopfield networks is that it cannot be tralned, i.e. the weights between two neurons must be set in advance. A pattern stored in Hopfield networks cannot be recalled if the pattern is not a local minimum.Two concepts are proposed to deal with this problem. They are the multiple training encoding method and the puppet encoding method. The multiple training encoding method, which guarantees to recall a single stored pattern under appropriate initial conditions of data, is theoretica-lly analyzed, and the minimal number of times for using a pattern for training to guarantee recalling of the pattern among a set of patterns is derived. The puppet encoding method is proved to be able to guarantee recalling of all stored patterns if attaching puppet data to the stored patterns is available.An integrated software PDS (Prelindnary Design System), which is developed from two aspects, is described. One is from a case-based expert system-CPDS (Case-based Prelindnary Design System), which is based on the algorithm of the Hopfield and developed for uncertain problems in PDS; the other is RPDS (Rule-based Preliminary Design System), which attacks logic or deduced problems in PDS. Based on the results of CPDS, RPDS can search for feasible solutioll in design model. CPDS is demonstrated to be useful in the domains of preliminary designs of cable-stayed bridges in this paper.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.11205115)the Program for Academic Leader Reserve Candidates in Tongling University(Grant No.2014tlxyxs30)the 2014-year Program for Excellent Youth Talents in University of Anhui Province,China
文摘Song [Song D 2004 Phys. Rev. A69034301] first proposed two key distribution schemes with the symmetry feature.We find that, in the schemes, the private channels which Alice and Bob publicly announce the initial Bell state or the measurement result through are not needed in discovering keys, and Song’s encoding methods do not arrive at the optimization.Here, an optimized encoding method is given so that the efficiencies of Song’s schemes are improved by 7/3 times. Interestingly, this optimized encoding method can be extended to the key distribution scheme composed of generalized Bell states.
文摘An encoding method has a direct effect on the quality and the representationof the discovered knowledge in data mining systems. Biological macromolecules are encoded by stringsof characters, called primary structures. Knowing that data mining systems usually use relationaltables to encode data, we have then to re-encode these strings and transform them into relationaltables. In this paper, we do a comparative study of the existing static encoding methods, that arebased on the Biologist know-how, and our new dynamic encoding one, that is based on the constructionof Discriminant and Minimal Substrings (DMS). Different classification methods are used to do thisstudy. The experimental results show that our dynamic encoding method is more efficient than thestatic ones, to encode biological macromolecules within a data mining perspective.
文摘This paPer addresses the issue of building a case-based preliminary design system by using Hopfield networks. one limitation of Hopfield networks is that it cannot be tralned, i.e. the weights between two neurons must be set in advance. A pattern stored in Hopfield networks cannot be recalled if the pattern is not a local minimum.Two concepts are proposed to deal with this problem. They are the multiple training encoding method and the puppet encoding method. The multiple training encoding method, which guarantees to recall a single stored pattern under appropriate initial conditions of data, is theoretica-lly analyzed, and the minimal number of times for using a pattern for training to guarantee recalling of the pattern among a set of patterns is derived. The puppet encoding method is proved to be able to guarantee recalling of all stored patterns if attaching puppet data to the stored patterns is available.An integrated software PDS (Prelindnary Design System), which is developed from two aspects, is described. One is from a case-based expert system-CPDS (Case-based Prelindnary Design System), which is based on the algorithm of the Hopfield and developed for uncertain problems in PDS; the other is RPDS (Rule-based Preliminary Design System), which attacks logic or deduced problems in PDS. Based on the results of CPDS, RPDS can search for feasible solutioll in design model. CPDS is demonstrated to be useful in the domains of preliminary designs of cable-stayed bridges in this paper.
