基于DSP的多元数据同步采集与存储系统的设计与实现

从硬件和软件两个角度出发,介绍基于DSP的多元数据同步采集与存储系统的组成、工作模式以及功能的测试。系统主要由上位机和数字采集与存储单元组成,其中数字采集与存储单元的硬件部分包括电源模块,值班电路模块,数据采集模块,数据存储模块,时钟同步模块。系统采用DSP作为中央处理芯片,利用经过同步后的秒脉冲作为触发信号,实现同步数据采集。以CF卡作为存储介质,实现数据自容式存储。软件部分实现自检、同步、数据采集存储功能。经过测试,系统工作稳定,功能正常,同步精度在100ns以内。     

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...     

除尘器新型褶式滤筒的结构优化及系列化设计

以新型褶式滤筒为研究对象,选取滤筒褶数N_2、褶夹角θ、褶高h、过滤风速v为影响因子,除尘器压力损失为响应值,基于响应曲面法分析影响因子对压力损失的影响,建立滤筒除尘器压力损失的预测模型并得到滤筒褶皱结构最优参数。以滤筒内径D、筒体高度D_1为标准尺寸,依据相关国家标准设计滤筒筒体部分;以锥体高度D_2、锥体上圆直径D_3为系列尺寸,利用尺寸变化法设计锥体部分;通过Access软件建立滤筒产品数据库。结果表明:当θ=5.2°,N_2=50,v=0.01 m/s,h=0.035 m时,除尘器压力损失最低;当D_1=1 000 mm,D=320 mm时,D_2和D_3最佳值分别为600,130 mm,故采用D_2/D_1=0.6,D_3/D=0.4的比值设计相应滤筒锥体系列。     

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.