In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the...In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements.展开更多
It is a challenging topic to develop an efficient algorithm for large scale classification problems in many applications of machine learning. In this paper, a hierarchical clustering and fixed-layer local learning (HC...It is a challenging topic to develop an efficient algorithm for large scale classification problems in many applications of machine learning. In this paper, a hierarchical clustering and fixed-layer local learning (HCFLL) based support vector machine(SVM) algorithm is proposed to deal with this problem. Firstly, HCFLL hierarchically clusters a given dataset into a modified clustering feature tree based on the ideas of unsupervised clustering and supervised clustering. Then it locally trains SVM on each labeled subtree at a fixed-layer of the tree. The experimental results show that compared with the existing popular algorithms such as core vector machine and decision-tree support vector machine, HCFLL can significantly improve the training and testing speeds with comparable testing accuracy.展开更多
To improve the diagnosis accuracy and self-adaptability of fatigue crack in ulterior place of the supporting shaft, time series and neural network are attempted to be applied in research on diag-nosing the fatigue cr...To improve the diagnosis accuracy and self-adaptability of fatigue crack in ulterior place of the supporting shaft, time series and neural network are attempted to be applied in research on diag-nosing the fatigue crack’s degree based on analyzing the vibration characteristics of the supporting shaft. By analyzing the characteristic parameter which is easy to be detected from the supporting shaft’s exterior, the time series model parameter which is hypersensitive to the situation of fatigue crack in ulterior place of the supporting shaft is the target input of neural network, and the fatigue crack’s degree value of supporting shaft is the output. The BP network model can be built and net-work can be trained after the structural parameters of network are selected. Furthermore, choosing the other two different group data can test the network. The test result will verify the validity of the BP network model. The result of experiment shows that the method of time series and neural network are effective to diagnose the occurrence and the development of the fatigue crack’s degree in ulterior place of the supporting shaft.展开更多
Background: Promoting breastfeeding support by public health nurses (PHN) requires first that the support which they currently provide to be assessed. However, there is no assessment tool for this purpose. The aim of ...Background: Promoting breastfeeding support by public health nurses (PHN) requires first that the support which they currently provide to be assessed. However, there is no assessment tool for this purpose. The aim of this study was therefore to develop a scale to assess breastfeeding support currently provided by PHN. Methods: We developed the Practice of Breastfeeding Support Scale (PBSS) for PHN based on the results of a previous study. The content validity of the PBSS was established through discussion with three other researchers. A pilot study was conducted to confirm face validity. To confirm reliability and validity, an anonymous, self-reported questionnaire was sent to PHN working in municipal offices. The statistical analyses included the Kaiser-Meyer-Olkin (KMO), Barlett’s Test of Sphericity, exploratory factor analysis (EFA), Cronbach’s alpha and correlation coefficient. Results: 768 PHN participated in this study. Cronbach’s alpha of PBSS was 0.85. The KMO measure was 0.892, and Bartlett’s Test of Sphericity was p Conclusion: The reliability and validity of PBSS were confirmed. These findings suggested that the PBSS has the potential to help promote breastfeeding support by PHN by clarifying their current breastfeeding support practices and related factors.展开更多
Reaction dynamics in gases at operating temperatures at the atomic level are the basis of heterogeneous gas-solid catalyst reactions and are crucial to the catalyst function.Supported noble metal nanocatalysts such as...Reaction dynamics in gases at operating temperatures at the atomic level are the basis of heterogeneous gas-solid catalyst reactions and are crucial to the catalyst function.Supported noble metal nanocatalysts such as platinum are of interest in fuel cells and as diesel oxidation catalysts for pollution control,and practical ruthenium nanocatalysts are explored for ammonia synthesis.Graphite and graphitic carbons are of interest as supports for the nanocatalysts.Despite considerable literature on the catalytic processes on graphite and graphitic supports,reaction dynamics of the nanocatalysts on the supports in different reactive gas environments and operating temperatures at the single atom level are not well understood.Here we present real time in-situ observations and analyses of reaction dynamics of Pt in oxidation,and practical Ru nanocatalysts in ammonia synthesis,on graphite and related supports under controlled reaction environments using a novel in-situ environmental(scanning) transmission electron microscope with single atom resolution.By recording snapshots of the reaction dynamics,the behaviour of the catalysts is imaged.The images reveal single metal atoms,clusters of a few atoms on the graphitic supports and the support function.These all play key roles in the mobility,sintering and growth of the catalysts.The experimental findings provide new structural insights into atomic scale reaction dynamics,morphology and stability of the nanocatalysts.展开更多
目的汉化老年人社会支持行为量表(The Social Support Behaviors scale,SSB),在中国老年人群中进行文化调适并检验其信效度。方法采用Brislin翻译模式进行量表的翻译、回译及文化调适。采用便利抽样方法选取548名老年人进行调查,以检验...目的汉化老年人社会支持行为量表(The Social Support Behaviors scale,SSB),在中国老年人群中进行文化调适并检验其信效度。方法采用Brislin翻译模式进行量表的翻译、回译及文化调适。采用便利抽样方法选取548名老年人进行调查,以检验中文版SSB量表的信效度。结果中文版SSB量表包括社会化、情感支持、建议或指导和实际援助4个维度,共31个条目。总量表的Cronbach′sα系数为0.927,各维度的Cronbach′sα系数分别为0.924、0.932、0.924和0.837;总量表的重测信度为0.782,各维度的重测信度分别为0.685、0.530、0.648、0.863。探索性因子分析提取4个因子,可解释的总变异为66.711%;验证性因子分析结果中χ^(2)/df=2.567,NFI=0.898,CFI=0.902,IFI=0.903,GFI=0.802,TLI=0.889,RMSEA=0.076,RMR=0.061;总量表的AVE值为0.628,各维度的AVE值区间为0.523~0.629;总量表的CR值为0.637,各维度的CR值区间为0.759~0.931;总量表得分与社会支持评价量表得分呈正相关(r=0.579,P<0.001)。结论中文版老年人社会支持行为量表具有良好的信效度,可作为我国老年人功能性社会支持的测量工具。展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No 60573065)the Natural Science Foundation of Shandong Province,China (Grant No Y2007G33)the Key Subject Research Foundation of Shandong Province,China(Grant No XTD0708)
文摘In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements.
基金National Natural Science Foundation of China ( No. 61070033 )Fundamental Research Funds for the Central Universities,China( No. 2012ZM0061)
文摘It is a challenging topic to develop an efficient algorithm for large scale classification problems in many applications of machine learning. In this paper, a hierarchical clustering and fixed-layer local learning (HCFLL) based support vector machine(SVM) algorithm is proposed to deal with this problem. Firstly, HCFLL hierarchically clusters a given dataset into a modified clustering feature tree based on the ideas of unsupervised clustering and supervised clustering. Then it locally trains SVM on each labeled subtree at a fixed-layer of the tree. The experimental results show that compared with the existing popular algorithms such as core vector machine and decision-tree support vector machine, HCFLL can significantly improve the training and testing speeds with comparable testing accuracy.
基金This project is supported by National Natural Science Fundation of China (No. 50675066)Provincial Key Technologies R&D of Hunan, China (No. 05FJ2001)China Postdoctoral Science Foundation (No. 2005038006).
文摘To improve the diagnosis accuracy and self-adaptability of fatigue crack in ulterior place of the supporting shaft, time series and neural network are attempted to be applied in research on diag-nosing the fatigue crack’s degree based on analyzing the vibration characteristics of the supporting shaft. By analyzing the characteristic parameter which is easy to be detected from the supporting shaft’s exterior, the time series model parameter which is hypersensitive to the situation of fatigue crack in ulterior place of the supporting shaft is the target input of neural network, and the fatigue crack’s degree value of supporting shaft is the output. The BP network model can be built and net-work can be trained after the structural parameters of network are selected. Furthermore, choosing the other two different group data can test the network. The test result will verify the validity of the BP network model. The result of experiment shows that the method of time series and neural network are effective to diagnose the occurrence and the development of the fatigue crack’s degree in ulterior place of the supporting shaft.
文摘Background: Promoting breastfeeding support by public health nurses (PHN) requires first that the support which they currently provide to be assessed. However, there is no assessment tool for this purpose. The aim of this study was therefore to develop a scale to assess breastfeeding support currently provided by PHN. Methods: We developed the Practice of Breastfeeding Support Scale (PBSS) for PHN based on the results of a previous study. The content validity of the PBSS was established through discussion with three other researchers. A pilot study was conducted to confirm face validity. To confirm reliability and validity, an anonymous, self-reported questionnaire was sent to PHN working in municipal offices. The statistical analyses included the Kaiser-Meyer-Olkin (KMO), Barlett’s Test of Sphericity, exploratory factor analysis (EFA), Cronbach’s alpha and correlation coefficient. Results: 768 PHN participated in this study. Cronbach’s alpha of PBSS was 0.85. The KMO measure was 0.892, and Bartlett’s Test of Sphericity was p Conclusion: The reliability and validity of PBSS were confirmed. These findings suggested that the PBSS has the potential to help promote breastfeeding support by PHN by clarifying their current breastfeeding support practices and related factors.
基金the Engineering and Physical Science Research Council(EPSRC),U.K.for the award of a research grant EP/J0118058/1 and postdoctoral research assistantships(PDRAs) to M.R.W.and R.W.M.from the grant。
文摘Reaction dynamics in gases at operating temperatures at the atomic level are the basis of heterogeneous gas-solid catalyst reactions and are crucial to the catalyst function.Supported noble metal nanocatalysts such as platinum are of interest in fuel cells and as diesel oxidation catalysts for pollution control,and practical ruthenium nanocatalysts are explored for ammonia synthesis.Graphite and graphitic carbons are of interest as supports for the nanocatalysts.Despite considerable literature on the catalytic processes on graphite and graphitic supports,reaction dynamics of the nanocatalysts on the supports in different reactive gas environments and operating temperatures at the single atom level are not well understood.Here we present real time in-situ observations and analyses of reaction dynamics of Pt in oxidation,and practical Ru nanocatalysts in ammonia synthesis,on graphite and related supports under controlled reaction environments using a novel in-situ environmental(scanning) transmission electron microscope with single atom resolution.By recording snapshots of the reaction dynamics,the behaviour of the catalysts is imaged.The images reveal single metal atoms,clusters of a few atoms on the graphitic supports and the support function.These all play key roles in the mobility,sintering and growth of the catalysts.The experimental findings provide new structural insights into atomic scale reaction dynamics,morphology and stability of the nanocatalysts.
文摘目的汉化老年人社会支持行为量表(The Social Support Behaviors scale,SSB),在中国老年人群中进行文化调适并检验其信效度。方法采用Brislin翻译模式进行量表的翻译、回译及文化调适。采用便利抽样方法选取548名老年人进行调查,以检验中文版SSB量表的信效度。结果中文版SSB量表包括社会化、情感支持、建议或指导和实际援助4个维度,共31个条目。总量表的Cronbach′sα系数为0.927,各维度的Cronbach′sα系数分别为0.924、0.932、0.924和0.837;总量表的重测信度为0.782,各维度的重测信度分别为0.685、0.530、0.648、0.863。探索性因子分析提取4个因子,可解释的总变异为66.711%;验证性因子分析结果中χ^(2)/df=2.567,NFI=0.898,CFI=0.902,IFI=0.903,GFI=0.802,TLI=0.889,RMSEA=0.076,RMR=0.061;总量表的AVE值为0.628,各维度的AVE值区间为0.523~0.629;总量表的CR值为0.637,各维度的CR值区间为0.759~0.931;总量表得分与社会支持评价量表得分呈正相关(r=0.579,P<0.001)。结论中文版老年人社会支持行为量表具有良好的信效度,可作为我国老年人功能性社会支持的测量工具。
