以沥青混合料试件为研究对象,探讨了原子力显微样本的制备方法.选取最大纵向起伏度和表面粗糙度两个指标对不同储存条件下的样本制备效果进行评定,提出采用低温冷冻措施保证AFM(atomic force microscope)样本平整度的制样方法;利用原子...以沥青混合料试件为研究对象,探讨了原子力显微样本的制备方法.选取最大纵向起伏度和表面粗糙度两个指标对不同储存条件下的样本制备效果进行评定,提出采用低温冷冻措施保证AFM(atomic force microscope)样本平整度的制样方法;利用原子力显微技术的力学性能量化模块AFMQNM(atomic force microscope-quantitative nano mechanical),选取沥青胶浆区域3个典型的观测区域,进行原子力显微测试及微尺度力学性能量化表征.研究结果表明,"冷冻保存、低温切割"的混合料试件样本制备方法能够满足AFM技术的观测要求;AFM-QNM技术可以在混合料试件中直接测试沥青(胶浆)和矿质集料的模量和黏附性质,可有效区分不同的材料组分.展开更多
A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a n...A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a newly configured product through soft computing technique instead of practical test experiments,which helps to evaluate whether or not the product variant can satisfy the customers' individual requirements.The PCA technique was used to reduce and orthogonalize the module parameters that affect the product performance.Then,these extracted features were used as new input variables in SVM model to mine knowledge from the limited existing product data.The performance values of a newly configured product can be predicted by means of the trained SVM models.This PCA-SVM method can ensure that the performance prediction is executed rapidly and accurately,even under the small sample conditions.The applicability of the proposed method was verified on a family of plate electrostatic precipitators.展开更多
the routing protocol for low-power and lossy networks(RPL) has been used in advanced metering infrastructure(AMI)which could provide two-way communication between smart meters and city utilities.To improve the network...the routing protocol for low-power and lossy networks(RPL) has been used in advanced metering infrastructure(AMI)which could provide two-way communication between smart meters and city utilities.To improve the network performance of AMI networks, this paper proposed an improved algorithm of RPL based on triangle module operator(IAR-TMO). IAR-TMO proposes membership functions of the following five typical routing metrics: end-to-end delay, number of hops, expected transmission count(ETX),node remaining energy, and child node count.Moreover, IAR-TMO uses triangle module operator to fuse membership functions of these routing metrics. Then, IAR-TMO selects preferred parents(the next hop) based on the triangle module operator. Theoretical analysis and simulation results show that IAR-TMO has a great improvement when compared with two recent representative algorithms: ETXOF(ETX Objective Function) and OF-FL(Objective Function based on Fuzzy Logic), in terms of network lifetime, average end-to-end delay,etc. Consequently, the network performances of AMI networks can be improved effectively.展开更多
文摘以沥青混合料试件为研究对象,探讨了原子力显微样本的制备方法.选取最大纵向起伏度和表面粗糙度两个指标对不同储存条件下的样本制备效果进行评定,提出采用低温冷冻措施保证AFM(atomic force microscope)样本平整度的制样方法;利用原子力显微技术的力学性能量化模块AFMQNM(atomic force microscope-quantitative nano mechanical),选取沥青胶浆区域3个典型的观测区域,进行原子力显微测试及微尺度力学性能量化表征.研究结果表明,"冷冻保存、低温切割"的混合料试件样本制备方法能够满足AFM技术的观测要求;AFM-QNM技术可以在混合料试件中直接测试沥青(胶浆)和矿质集料的模量和黏附性质,可有效区分不同的材料组分.
基金Project(9140A18010210KG01) supported by the Departmental Pre-Research Fund of China
文摘A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a newly configured product through soft computing technique instead of practical test experiments,which helps to evaluate whether or not the product variant can satisfy the customers' individual requirements.The PCA technique was used to reduce and orthogonalize the module parameters that affect the product performance.Then,these extracted features were used as new input variables in SVM model to mine knowledge from the limited existing product data.The performance values of a newly configured product can be predicted by means of the trained SVM models.This PCA-SVM method can ensure that the performance prediction is executed rapidly and accurately,even under the small sample conditions.The applicability of the proposed method was verified on a family of plate electrostatic precipitators.
基金supported by the Beijing Laboratory of Advanced Information Networks
文摘the routing protocol for low-power and lossy networks(RPL) has been used in advanced metering infrastructure(AMI)which could provide two-way communication between smart meters and city utilities.To improve the network performance of AMI networks, this paper proposed an improved algorithm of RPL based on triangle module operator(IAR-TMO). IAR-TMO proposes membership functions of the following five typical routing metrics: end-to-end delay, number of hops, expected transmission count(ETX),node remaining energy, and child node count.Moreover, IAR-TMO uses triangle module operator to fuse membership functions of these routing metrics. Then, IAR-TMO selects preferred parents(the next hop) based on the triangle module operator. Theoretical analysis and simulation results show that IAR-TMO has a great improvement when compared with two recent representative algorithms: ETXOF(ETX Objective Function) and OF-FL(Objective Function based on Fuzzy Logic), in terms of network lifetime, average end-to-end delay,etc. Consequently, the network performances of AMI networks can be improved effectively.
