The use of dynamic programming(DP)algorithms to learn Bayesian network structures is limited by their high space complexity and difficulty in learning the structure of large-scale networks.Therefore,this study propose...The use of dynamic programming(DP)algorithms to learn Bayesian network structures is limited by their high space complexity and difficulty in learning the structure of large-scale networks.Therefore,this study proposes a DP algorithm based on node block sequence constraints.The proposed algorithm constrains the traversal process of the parent graph by using the M-sequence matrix to considerably reduce the time consumption and space complexity by pruning the traversal process of the order graph using the node block sequence.Experimental results show that compared with existing DP algorithms,the proposed algorithm can obtain learning results more efficiently with less than 1%loss of accuracy,and can be used for learning larger-scale networks.展开更多
The 5’-end of the mitochondrial control region sequences of three flatfishes (Pleuronectiformes: Pleuronectidae) were amplified and sequenced. These sequences were compared with those of other three Pleuronectids spe...The 5’-end of the mitochondrial control region sequences of three flatfishes (Pleuronectiformes: Pleuronectidae) were amplified and sequenced. These sequences were compared with those of other three Pleuronectids species retrieved from GenBank. A phylogenetic tree was constructed based on the partial control region sequences. The results of phyloge- netic analysis are consistent with those of conventional systematics. Compared to previous studies, the structure of the 5’-end of mitochondrial control region was analyzed. The terminal associated sequence motif and its complementary motif were i- dentified at the 5’-end of the sequences. A conserved sequence block, named as CM5’d, was identified in the 5’-end of con- trol region sequences in all Pleuronectids. Another central conserved sequence block, named as CSB-F, was detected in the central conserved blocks.展开更多
Dealing with issues such as too simple image features and word noise inference in product image sentence anmotation, a product image sentence annotation model focusing on image feature learning and key words summariza...Dealing with issues such as too simple image features and word noise inference in product image sentence anmotation, a product image sentence annotation model focusing on image feature learning and key words summarization is described. Three kernel descriptors such as gradient, shape, and color are extracted, respectively. Feature late-fusion is executed in turn by the multiple kernel learning model to obtain more discriminant image features. Absolute rank and relative rank of the tag-rank model are used to boost the key words＇ weights. A new word integration algorithm named word sequence blocks building （WSBB） is designed to create N-gram word sequences. Sentences are generated according to the N-gram word sequences and predefined templates. Experimental results show that both the BLEU-1 scores and BLEU-2 scores of the sentences are superior to those of the state-of-art baselines.展开更多
Visible light positioning （VLP） is an emerging candidate for indoor positioning, which carl simultaneously meet the requirements for accuracy, cost, coverage area, and security. However, intercell interference causc...Visible light positioning （VLP） is an emerging candidate for indoor positioning, which carl simultaneously meet the requirements for accuracy, cost, coverage area, and security. However, intercell interference causcd by light intensity superposition linfits the application of VLP. In this Letter, we propose a united block sequence mapping （UBSM）-based VLP that utilizes superposition to integrate the multidimensional information from dense small cells into 2D information. The experimental result shows that UBSM-based VLP can achieve an accuracy of 1.5 cm with a 0.4 m row spacing and 0.35 m column spacing of LED lights.展开更多
基金Shaanxi Science Fund for Distinguished Young Scholars,Grant/Award Number:2024JC-JCQN-57Xi’an Science and Technology Plan Project,Grant/Award Number:2023JH-QCYJQ-0086+2 种基金Scientific Research Program Funded by Education Department of Shaanxi Provincial Government,Grant/Award Number:P23JP071Engineering Technology Research Center of Shaanxi Province for Intelligent Testing and Reliability Evaluation of Electronic Equipments,Grant/Award Number:2023-ZC-GCZX-00472022 Shaanxi University Youth Innovation Team Project。
文摘The use of dynamic programming(DP)algorithms to learn Bayesian network structures is limited by their high space complexity and difficulty in learning the structure of large-scale networks.Therefore,this study proposes a DP algorithm based on node block sequence constraints.The proposed algorithm constrains the traversal process of the parent graph by using the M-sequence matrix to considerably reduce the time consumption and space complexity by pruning the traversal process of the order graph using the node block sequence.Experimental results show that compared with existing DP algorithms,the proposed algorithm can obtain learning results more efficiently with less than 1%loss of accuracy,and can be used for learning larger-scale networks.
基金the Shandong Foundation of Sciences(No.Y2000D04) the National Key Basic Research Program from the Ministry of Science and Technology of China(No.G19990437).
文摘The 5’-end of the mitochondrial control region sequences of three flatfishes (Pleuronectiformes: Pleuronectidae) were amplified and sequenced. These sequences were compared with those of other three Pleuronectids species retrieved from GenBank. A phylogenetic tree was constructed based on the partial control region sequences. The results of phyloge- netic analysis are consistent with those of conventional systematics. Compared to previous studies, the structure of the 5’-end of mitochondrial control region was analyzed. The terminal associated sequence motif and its complementary motif were i- dentified at the 5’-end of the sequences. A conserved sequence block, named as CM5’d, was identified in the 5’-end of con- trol region sequences in all Pleuronectids. Another central conserved sequence block, named as CSB-F, was detected in the central conserved blocks.
基金The National Natural Science Foundation of China(No.61133012)the Humanity and Social Science Foundation of the Ministry of Education(No.12YJCZH274)+1 种基金the Humanity and Social Science Foundation of Jiangxi Province(No.XW1502,TQ1503)the Science and Technology Project of Jiangxi Science and Technology Department(No.20121BBG70050,20142BBG70011)
文摘Dealing with issues such as too simple image features and word noise inference in product image sentence anmotation, a product image sentence annotation model focusing on image feature learning and key words summarization is described. Three kernel descriptors such as gradient, shape, and color are extracted, respectively. Feature late-fusion is executed in turn by the multiple kernel learning model to obtain more discriminant image features. Absolute rank and relative rank of the tag-rank model are used to boost the key words＇ weights. A new word integration algorithm named word sequence blocks building （WSBB） is designed to create N-gram word sequences. Sentences are generated according to the N-gram word sequences and predefined templates. Experimental results show that both the BLEU-1 scores and BLEU-2 scores of the sentences are superior to those of the state-of-art baselines.
基金supported in part by the National 973Program of China(No.2013CB329205)the National Science Foundation of China(No.61401032)
文摘Visible light positioning （VLP） is an emerging candidate for indoor positioning, which carl simultaneously meet the requirements for accuracy, cost, coverage area, and security. However, intercell interference causcd by light intensity superposition linfits the application of VLP. In this Letter, we propose a united block sequence mapping （UBSM）-based VLP that utilizes superposition to integrate the multidimensional information from dense small cells into 2D information. The experimental result shows that UBSM-based VLP can achieve an accuracy of 1.5 cm with a 0.4 m row spacing and 0.35 m column spacing of LED lights.
