Recent advances on wheel-rail dynamic performance of curve negotiation are reviewed in this paper. There are four issues, the mechanism and calculation method of curve negotiation, the analysis and assessment of dynam...Recent advances on wheel-rail dynamic performance of curve negotiation are reviewed in this paper. There are four issues, the mechanism and calculation method of curve negotiation, the analysis and assessment of dynamic performance of vehicle, the effect of vehicle parameters on dynamic performance, and the influence of railway parameters on dynamic performance. The promising future development of wheel-rail coupled dynamics theory is analyzed in the research of curve negotiation. The framework and technique matching performance of wheel-rail dynamic interaction on the curved track are put forward for modem railways. In addition, the application of performance matching technique is introduced to the dynamic engineering, in which the wheel load is reduced obviously when the speed of train is raised to 200-250 km/h.展开更多
Modeling and matching texts is a critical issue in natural language processing(NLP) tasks. In order to improve the accuracy of text matching, multi-granularities capture matching features(MG-CMF) model was proposed. T...Modeling and matching texts is a critical issue in natural language processing(NLP) tasks. In order to improve the accuracy of text matching, multi-granularities capture matching features(MG-CMF) model was proposed. The proposed model used convolution operations to construct the representation of text under multiple granularities, used max-pooling operations to filter more reasonable text representations and built a matching matrix at different granularities. Then, the convolution neural network(CNN) was used to capture the matching information in each granularity. Finally, the captured matching features were input into the fully connected neural network to obtain the matching similarity. By making some experiments, the results indicate that the MG-CMF model not only gets multiple granularity representations of sentences but also can obtain matching information from multiple granularities of sentences better than the other text matching models.展开更多
The lost information caused by feature interaction is restored by using auxiliary faces (AF) and virtual links (VL). The delta volume of the interacted features represented by concave attachable connected graph (CACG)...The lost information caused by feature interaction is restored by using auxiliary faces (AF) and virtual links (VL). The delta volume of the interacted features represented by concave attachable connected graph (CACG) can be decomposed into several isolated features represented by complete concave adjacency graph (CCAG). We can recognize the feature’s sketchy type by using CCAG as a hint; the exact type of the feature can be attained by deleting the auxiliary faces from the isolated feature. United machining feature (UMF) is used to represent the features that can be machined in the same machining process. It is important to the rationalizing of the process plans and reduce the time costing in machining. An example is given to demonstrate the effectiveness of this method.展开更多
Protein complexes are the basic units of macro-molecular organizations and help us to understand the cell's mechanism.The development of the yeast two-hybrid,tandem affinity purification,and mass spectrometry high...Protein complexes are the basic units of macro-molecular organizations and help us to understand the cell's mechanism.The development of the yeast two-hybrid,tandem affinity purification,and mass spectrometry high-throughput proteomic techniques supplies a large amount of protein-protein interaction data,which make it possible to predict overlapping complexes through computational methods.Research shows that overlapping complexes can contribute to identifying essential proteins,which are necessary for the organism to survive and reproduce,and for life's activities.Scholars pay more attention to the evaluation of protein complexes.However,few of them focus on predicted overlaps.In this paper,an evaluation criterion called overlap maximum matching ratio(OMMR) is proposed to analyze the similarity between the identified overlaps and the benchmark overlap modules.Comparison of essential proteins and gene ontology(GO) analysis are also used to assess the quality of overlaps.We perform a comprehensive comparison of serveral overlapping complexes prediction approaches,using three yeast protein-protein interaction(PPI) networks.We focus on the analysis of overlaps identified by these algorithms.Experimental results indicate the important of overlaps and reveal the relationship between overlaps and identification of essential proteins.展开更多
基金support and motivation provided by National Basic Research Programof China(973 Program No.2013CB036206)National Natural Science Foundation of China(No.61134002)
文摘Recent advances on wheel-rail dynamic performance of curve negotiation are reviewed in this paper. There are four issues, the mechanism and calculation method of curve negotiation, the analysis and assessment of dynamic performance of vehicle, the effect of vehicle parameters on dynamic performance, and the influence of railway parameters on dynamic performance. The promising future development of wheel-rail coupled dynamics theory is analyzed in the research of curve negotiation. The framework and technique matching performance of wheel-rail dynamic interaction on the curved track are put forward for modem railways. In addition, the application of performance matching technique is introduced to the dynamic engineering, in which the wheel load is reduced obviously when the speed of train is raised to 200-250 km/h.
文摘Modeling and matching texts is a critical issue in natural language processing(NLP) tasks. In order to improve the accuracy of text matching, multi-granularities capture matching features(MG-CMF) model was proposed. The proposed model used convolution operations to construct the representation of text under multiple granularities, used max-pooling operations to filter more reasonable text representations and built a matching matrix at different granularities. Then, the convolution neural network(CNN) was used to capture the matching information in each granularity. Finally, the captured matching features were input into the fully connected neural network to obtain the matching similarity. By making some experiments, the results indicate that the MG-CMF model not only gets multiple granularity representations of sentences but also can obtain matching information from multiple granularities of sentences better than the other text matching models.
文摘The lost information caused by feature interaction is restored by using auxiliary faces (AF) and virtual links (VL). The delta volume of the interacted features represented by concave attachable connected graph (CACG) can be decomposed into several isolated features represented by complete concave adjacency graph (CCAG). We can recognize the feature’s sketchy type by using CCAG as a hint; the exact type of the feature can be attained by deleting the auxiliary faces from the isolated feature. United machining feature (UMF) is used to represent the features that can be machined in the same machining process. It is important to the rationalizing of the process plans and reduce the time costing in machining. An example is given to demonstrate the effectiveness of this method.
基金Project supported by the National Scientific Research Foundation of Hunan Province, China （Nos. 14C0096, 10C0408, and 10B010）, the Natural Science Foundation of Hunan Province, China （Nos. 13JJ4106 and 14J J3138）, and the Science and Technology Plan Project of Hunan Province, China （No. 2010FJ3044）
文摘Protein complexes are the basic units of macro-molecular organizations and help us to understand the cell's mechanism.The development of the yeast two-hybrid,tandem affinity purification,and mass spectrometry high-throughput proteomic techniques supplies a large amount of protein-protein interaction data,which make it possible to predict overlapping complexes through computational methods.Research shows that overlapping complexes can contribute to identifying essential proteins,which are necessary for the organism to survive and reproduce,and for life's activities.Scholars pay more attention to the evaluation of protein complexes.However,few of them focus on predicted overlaps.In this paper,an evaluation criterion called overlap maximum matching ratio(OMMR) is proposed to analyze the similarity between the identified overlaps and the benchmark overlap modules.Comparison of essential proteins and gene ontology(GO) analysis are also used to assess the quality of overlaps.We perform a comprehensive comparison of serveral overlapping complexes prediction approaches,using three yeast protein-protein interaction(PPI) networks.We focus on the analysis of overlaps identified by these algorithms.Experimental results indicate the important of overlaps and reveal the relationship between overlaps and identification of essential proteins.
