User-transformer relations are significant to electric power marketing,power supply safety,and line loss calculations.To get accurate user-transformer relations,this paper proposes an identification method for user-tr...User-transformer relations are significant to electric power marketing,power supply safety,and line loss calculations.To get accurate user-transformer relations,this paper proposes an identification method for user-transformer relations based on improved quantum particle swarm optimization(QPSO)and Fuzzy C-Means Clustering.The main idea is:as energymeters at different transformer areas exhibit different zero-crossing shift features,we classify the zero-crossing shift data from energy meters through Fuzzy C-Means Clustering and compare it with that at the transformer end to identify user-transformer relations.The proposed method contributes in three main ways.First,based on the fuzzy C-means clustering algorithm(FCM),the quantum particle swarm optimization(PSO)is introduced to optimize the FCM clustering center and kernel parameters.The optimized FCM algorithm can improve clustering accuracy and efficiency.Since easily falls into a local optimum,an improved PSO optimization algorithm(IQPSO)is proposed.Secondly,considering that traditional FCM cannot solve the linear inseparability problem,this article uses a FCM(KFCM)that introduces kernel functions.Combinedwith the IQPSOoptimization algorithm used in the previous step,the IQPSO-KFCM algorithm is proposed.Simulation experiments verify the superiority of the proposed method.Finally,the proposed method is applied to transformer detection.The proposed method determines the class members of transformers and meters in the actual transformer area,and obtains results consistent with actual user-transformer relations.This fully shows that the proposed method has practical application value.展开更多
To identify the member of the caspase family proteases involved in γ radiation induced apoptosis in HL 60 cells, using degenerated oligonucleotide primers encoding the highly conserved peptides, which were present...To identify the member of the caspase family proteases involved in γ radiation induced apoptosis in HL 60 cells, using degenerated oligonucleotide primers encoding the highly conserved peptides, which were present in all known caspases, RT PCR was performed on poly (A) RNA from the γ radiation induced apoptotic HL 60 cells. Then, cloned and sequenced to identify the amplified DNA fragments. The results showed that the amplified DNA fragments were identified with a part of caspase 3 cDNA. It indicated that caspase 3 was involved in γ radiation induced apoptosis in HL 60 cells and may be the pivotal element of radiation induced apoptosis.展开更多
We identified a gibberellin-induced gene frag-ment in rice elongation by using differentialdisplay(DD)of mRNA.The rice seedlingscarried the eui(elongated)gene,named Zhen-chang A,were used,which were sensitive toGAand ...We identified a gibberellin-induced gene frag-ment in rice elongation by using differentialdisplay(DD)of mRNA.The rice seedlingscarried the eui(elongated)gene,named Zhen-chang A,were used,which were sensitive toGAand elongated rapidly after application of展开更多
基金supported by the National Natural Science Foundation of China(61671208).
文摘User-transformer relations are significant to electric power marketing,power supply safety,and line loss calculations.To get accurate user-transformer relations,this paper proposes an identification method for user-transformer relations based on improved quantum particle swarm optimization(QPSO)and Fuzzy C-Means Clustering.The main idea is:as energymeters at different transformer areas exhibit different zero-crossing shift features,we classify the zero-crossing shift data from energy meters through Fuzzy C-Means Clustering and compare it with that at the transformer end to identify user-transformer relations.The proposed method contributes in three main ways.First,based on the fuzzy C-means clustering algorithm(FCM),the quantum particle swarm optimization(PSO)is introduced to optimize the FCM clustering center and kernel parameters.The optimized FCM algorithm can improve clustering accuracy and efficiency.Since easily falls into a local optimum,an improved PSO optimization algorithm(IQPSO)is proposed.Secondly,considering that traditional FCM cannot solve the linear inseparability problem,this article uses a FCM(KFCM)that introduces kernel functions.Combinedwith the IQPSOoptimization algorithm used in the previous step,the IQPSO-KFCM algorithm is proposed.Simulation experiments verify the superiority of the proposed method.Finally,the proposed method is applied to transformer detection.The proposed method determines the class members of transformers and meters in the actual transformer area,and obtains results consistent with actual user-transformer relations.This fully shows that the proposed method has practical application value.
文摘To identify the member of the caspase family proteases involved in γ radiation induced apoptosis in HL 60 cells, using degenerated oligonucleotide primers encoding the highly conserved peptides, which were present in all known caspases, RT PCR was performed on poly (A) RNA from the γ radiation induced apoptotic HL 60 cells. Then, cloned and sequenced to identify the amplified DNA fragments. The results showed that the amplified DNA fragments were identified with a part of caspase 3 cDNA. It indicated that caspase 3 was involved in γ radiation induced apoptosis in HL 60 cells and may be the pivotal element of radiation induced apoptosis.
文摘We identified a gibberellin-induced gene frag-ment in rice elongation by using differentialdisplay(DD)of mRNA.The rice seedlingscarried the eui(elongated)gene,named Zhen-chang A,were used,which were sensitive toGAand elongated rapidly after application of
