一种装备反应时间测量装置设计与应用

为了对激光信号探测器输出的TTL信号和其他设备输出的差分信号时间间隔进行测量,设计了一种以AT89S2051单片机为主控制器,以CPLD复杂可编程逻辑器件EPM7128S为辅助控制器的反应时间测量装置。利用CPLD编程实现方便灵活的特点,简化电路设计,降低了成本。装置设置两路TTL信号输入接口、两路差分信号输入接口和两路脉冲信号输出接口,可按实际使用需要对反应时间起始与截止信号输入通道进行选择和设置,将测量结果显示输出。经检测和使用证明,装置操作简便、测量准确、运行稳定,能满足有关时间参数的测量使用,可向有关时间参数测量应用拓展。     

Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.     

Approximate cutting pattern optimization of frame-supported and pneumatic membrane structures

International Journal of Mechanics and Materials in Design - A simple iterative method is presented for cutting pattern optimization of frame-supported and pneumatic membrane structures for...     

Within-class multimodal classification

Multimedia Tools and Applications - In many real-world classification problems there exist multiple subclasses (or clusters) within a class; in other words, the underlying data distribution is...     

Creating the brain and interacting with the brain: an integrated approach to understanding the brain

In the past two decades, brain science and robotics have made gigantic advances in their own fields, and their interactions have generated several interdisciplinary research fields. First, in the ‘understanding the brain by creating the brain’ approach, computational neuroscience models have been applied to many robotics problems. Second, such brain-motivated fields as cognitive robotics and developmental robotics have emerged as interdisciplinary areas among robotics, neuroscience and cognitive science with special emphasis on humanoid robots. Third, in brain–machine interface research, a brain and a robot are mutually connected within a closed loop. In this paper, we review the theoretical backgrounds of these three interdisciplinary fields and their recent progress. Then, we introduce recent efforts to reintegrate these research fields into a coherent perspective and propose a new direction that integrates brain science and robotics where the decoding of information from the brain, robot control based on the decoded information and multimodal feedback to the brain from the robot are carried out in real time and in a closed loop.     

一种基于Spark的不确定数据集频繁模式挖掘算法

如何在海量不确定数据集中提高频繁模式挖掘性能是目前研究的热点.传统算法大多是以期望、概率或者权重等单一指标为数据项集支持度，在大数据背景下，同时考虑概率和权重支持度的算法难以兼顾其执行效率.为此，本文提出一种基于Spark的不确定数据集频繁模式挖掘算法（UWEFP），首先，为了同时兼顾数据项的概率和权重，计算一项集的最大概率权重值并进行剪枝；然后，为了减少对数据集的多次扫描，结合Spark框架的优点，设计了一种具有FP-tree特征的新颖的UWEFP-tree结构进行模式树的构建及挖掘；最后在Spark环境下，以UCI数据集进行实验验证.实验结果表明本文的方法在保证挖掘结果的同时，提高了效率.     

某工业厂房主体结构安全性评定探讨

结构的安全性是结构防止破坏倒塌的能力,是结构工程重要的质量指标.老工业基地中的厂房主体结构安全性评价,对于厂房加固改造起到了关键性作用.文中通过对某工业厂房主体结构大量现场勘验、隐患排查及检测数据,结合结构验算,从承载能力、损伤等几方面对该老旧工业厂房的安全性进行了评价与分析,并详细介绍了检测鉴定的流程,为以后类似的老旧工业厂房的检测鉴定提供参考.