Data aggregation from various web sources is very significant for web data analysis domain. In ad- dition, the recognition of coherence micro cluster is one of the most interesting issues in the field of data aggregat...Data aggregation from various web sources is very significant for web data analysis domain. In ad- dition, the recognition of coherence micro cluster is one of the most interesting issues in the field of data aggregation. Until now, many algorithms have been proposed to work on this issue. However, the deficiency of these solutions is that they cannot recognize the micro-cluster data stream accurately. A semantic-based coherent micro-cluster recognition algorithm for hybrid web data stream is nronosed.Firstly, an objective function is proposed to recognize the coherence micro-cluster and then the coher- ence micro-cluster recognition algorithm for hybrid web data stream based on semantic is raised. Fi-展开更多
Measurements of zero-degree breakup fragment energy distribution fromthe Coulomb-Explosions of 1.50965 MeV HD+ ion inicro-cluster beam are reported.Mean value of the internuclear separation of HD+ is found to be 0.125...Measurements of zero-degree breakup fragment energy distribution fromthe Coulomb-Explosions of 1.50965 MeV HD+ ion inicro-cluster beam are reported.Mean value of the internuclear separation of HD+ is found to be 0.12510.003 urn. Aset of high-resolution experimental arrangement and improvement of the Van-de-Graaffaccelerator are described briefly.展开更多
Objectives:In order to improve the prediction accuracy of forced-air pre-cooling for blueberries,a mathematical model of forced-air pre-cooling for blueberries based on the micro-cluster method was established.Materia...Objectives:In order to improve the prediction accuracy of forced-air pre-cooling for blueberries,a mathematical model of forced-air pre-cooling for blueberries based on the micro-cluster method was established.Materials and Methods:In order to determine the optimal micro-cluster model parameters suitable for forced air pre-cooling of blueberries,three factors controlling the micro-cluster geometry parameters were evaluated by 7/8 pre-cooling time,uniformity,and convective heat transfer coeffcient.Results:It was found that the optimal values of the number of micro-clusters(n3),the distance between individual units within a micro-cluster(a)and the distance between micro-clusters(c)were 3,0.75,and 0.2,respectively.Under these optimal values,the temperature error of the micro-cluster method remained below 1°C,achieving highly accurate temperature predictions during the blueberry pre-cooling process.The results showed that the micro-cluster method effectively solved the challenges of complex confguration,long simulation time,and low accuracy compared to the porous medium and equivalent sphere methods.Conclusion:Based on the above analysis,it can be concluded that the micro-cluster method provids a theoretical basis for optimizing forced-air pre-cooling processes and making informed control decisions.展开更多
为提高硬脆材料微结构的加工效率和精度,需要预测微磨具的不确定性磨损。基于微磨具在位视觉磨损检测和聚类分析,提出基于遗传算法的反向神经网络(genetic algorithm back propagation,GA-BP)模型。选取微磨具磨头截面面积损失量为指标...为提高硬脆材料微结构的加工效率和精度,需要预测微磨具的不确定性磨损。基于微磨具在位视觉磨损检测和聚类分析,提出基于遗传算法的反向神经网络(genetic algorithm back propagation,GA-BP)模型。选取微磨具磨头截面面积损失量为指标,以表征微磨具不确定性磨损特征。利用K-均值聚类算法划分微磨具磨损状态阶段。最后构建以主轴转速、进给率、微槽深度、磨削长度和微磨具初始截面面积为输入层神经元,以磨头截面面积损失量预测值为输出层的GA-BP神经网络模型。设计不同工艺参数条件下的单晶硅微槽微细磨削实验,基于自搭建的机器视觉系统在位测量微磨具的磨头截面面积磨损量。将实验测得的微磨具磨损量作为训练数据,与传统高斯过程回归预测模型对比,验证GA-BP神经网络模型的有效性和准确性。结果表明,GA-BP神经网络模型能够实现不同工艺参数和不同磨削长度下的微磨具磨损预测,比传统高斯过程回归预测模型具有更高预测精度,平均误差精度达到5%,可以实现微磨具磨损阶段状态预测。展开更多
基金Supported by the National High Technology Research and Development Programme of China(No.2011AA120300,2011AA120302)the National Key Technology Support Program of China(No.2013BAH66F02)
文摘Data aggregation from various web sources is very significant for web data analysis domain. In ad- dition, the recognition of coherence micro cluster is one of the most interesting issues in the field of data aggregation. Until now, many algorithms have been proposed to work on this issue. However, the deficiency of these solutions is that they cannot recognize the micro-cluster data stream accurately. A semantic-based coherent micro-cluster recognition algorithm for hybrid web data stream is nronosed.Firstly, an objective function is proposed to recognize the coherence micro-cluster and then the coher- ence micro-cluster recognition algorithm for hybrid web data stream based on semantic is raised. Fi-
文摘Measurements of zero-degree breakup fragment energy distribution fromthe Coulomb-Explosions of 1.50965 MeV HD+ ion inicro-cluster beam are reported.Mean value of the internuclear separation of HD+ is found to be 0.12510.003 urn. Aset of high-resolution experimental arrangement and improvement of the Van-de-Graaffaccelerator are described briefly.
基金supported by the Natural Science Foundation of Shandong Province,China(No.ZR2021QC186)the China Postdoctoral Science Foundation(No.2023M743923).
文摘Objectives:In order to improve the prediction accuracy of forced-air pre-cooling for blueberries,a mathematical model of forced-air pre-cooling for blueberries based on the micro-cluster method was established.Materials and Methods:In order to determine the optimal micro-cluster model parameters suitable for forced air pre-cooling of blueberries,three factors controlling the micro-cluster geometry parameters were evaluated by 7/8 pre-cooling time,uniformity,and convective heat transfer coeffcient.Results:It was found that the optimal values of the number of micro-clusters(n3),the distance between individual units within a micro-cluster(a)and the distance between micro-clusters(c)were 3,0.75,and 0.2,respectively.Under these optimal values,the temperature error of the micro-cluster method remained below 1°C,achieving highly accurate temperature predictions during the blueberry pre-cooling process.The results showed that the micro-cluster method effectively solved the challenges of complex confguration,long simulation time,and low accuracy compared to the porous medium and equivalent sphere methods.Conclusion:Based on the above analysis,it can be concluded that the micro-cluster method provids a theoretical basis for optimizing forced-air pre-cooling processes and making informed control decisions.
文摘为提高硬脆材料微结构的加工效率和精度,需要预测微磨具的不确定性磨损。基于微磨具在位视觉磨损检测和聚类分析,提出基于遗传算法的反向神经网络(genetic algorithm back propagation,GA-BP)模型。选取微磨具磨头截面面积损失量为指标,以表征微磨具不确定性磨损特征。利用K-均值聚类算法划分微磨具磨损状态阶段。最后构建以主轴转速、进给率、微槽深度、磨削长度和微磨具初始截面面积为输入层神经元,以磨头截面面积损失量预测值为输出层的GA-BP神经网络模型。设计不同工艺参数条件下的单晶硅微槽微细磨削实验,基于自搭建的机器视觉系统在位测量微磨具的磨头截面面积磨损量。将实验测得的微磨具磨损量作为训练数据,与传统高斯过程回归预测模型对比,验证GA-BP神经网络模型的有效性和准确性。结果表明,GA-BP神经网络模型能够实现不同工艺参数和不同磨削长度下的微磨具磨损预测,比传统高斯过程回归预测模型具有更高预测精度,平均误差精度达到5%,可以实现微磨具磨损阶段状态预测。
