Cation interdiffusion between thick film of YBa2Cu3O7-δ and ceramic substrate

Thick films of superconducting oxides, YBa₂Cu₃O_7-, were successfully made by conventional screen-printing technology on Al₂O₃, MgO, and ZrO₂ substrates. Interdiffusion between the superconductive film and substrate was investigated using analytical electron microscopy. The results indicate that MgO and ZrO₂ are superior to Al₂O₃ for substrate materials.     

Nonsmooth spatial frictional contact dynamics of multibody systems

Multibody System Dynamics - Computational prediction of 3D crutch-assisted walking patterns is a challenging problem that could be applied to study different biomechanical aspects of crutch walking...     

On the use of multibody dynamics techniques to simulate fluid dynamics and fluid–solid interaction problems

Multibody System Dynamics - A multibody dynamics-based solution to the fluid dynamics problem is compared herein to two established Lagrangian-based techniques used by the computational fluid...     

Mechanical analysis of double-layered circular graphene sheets as building material embedded in an elastic medium

Journal of Central South University - Possessing the unique and highly valuable properties, graphene sheets (GSs) have attracted increasing attention including that from the building engineer due...     

A novel spherical-ordered macroporous CuO nanocatalyst for the electrochemical reduction of carbon dioxide

Journal of Applied Electrochemistry - The electrocatalytic reduction of CO2 is a promising research direction in resource utilization and sustainable energy development. However, there is still a...     

20G高压锅炉管裂纹原因分析

对20G高压锅炉管产生裂纹的原因进行了分析，结果表明是冷拔工艺不当所致。     

基于逻辑回归模型的木片和树皮的图像识别

为了提高木片生物能的利用率,需要除去木片中的树皮杂质。识别木片和树皮的图像对于实现二者分离具有重要作用。提出一种基于逻辑回归模型来对木片和树皮进行图像识别的算法。算法流程包括计算各种可以描述木片和树皮纹理的参数,利用SAS统计分析出最佳参数,将最佳参数计算所得的样本数据用于SAS LOGISTIC过程得到预测方程,再将预测方程用于逻辑回归模型来实现木片和树皮的图像识别。通过实验可知,最佳参数为灰度方差,该图像识别算法的正确率能达到97.4%。     

Recover Fault Services via Complex Service-to-Node Mappings in Wireless Sensor Networks

With the motivation of seamlessly extending wireless sensor networks to the external environment, service-oriented architecture comes up as a promising solution. However, as sensor nodes are failure prone, this consequently renders the whole wireless sensor network to seriously faulty. When a particular node is faulty, the service on it should be migrated into those substitute sensor nodes that are in a normal status. Currently, two kinds of approaches exist to identify the substitute sensor nodes: the most common approach is to prepare redundancy nodes, though the involved tasks such as maintaining redundancy nodes, i.e., relocating the new node, lead to an extra burden on the wireless sensor networks. More recently, other approaches without using redundancy nodes are emerging, and they merely select the substitute nodes in a sensor node’s perspective i.e., migrating the service of faulty node to it’s nearest sensor node, though usually neglecting the requirements of the application level. Even a few work consider the need of the application level, they perform at packets granularity and don’t fit well at service granularity. In this paper, we aim to remove these limitations in the wireless sensor network with the service-oriented architecture. Instead of deploying redundancy nodes, the proposed mechanism replaces the faulty sensor node with consideration of the similarity on the application level, as well as on the sensor level. On the application level, we apply the Bloom Filter for its high efficiency and low space costs. While on the sensor level, we design an objective solution via the coefficient of a variation as an evaluation for choosing the substitute on the sensor level.