“学习曲线”模式在涪陵页岩气田试气施工中的应用

涪陵页岩气公司在试气环节引入了"学习曲线"模式,建立了试气施工管理制度和工艺标准,强化监督与落实;加大了专业技能知识培训力度,实行试气施工人员持证上岗;精心做好试气施工谋划工作,确保试气施工不受因素影响;全面优化试气施工设计,及时调整试气现场管理;积极借鉴学习曲线图经验,对试气作业实行专业化分工;引进和研发先进设备和工艺,为试气作业提供有力保障。     

当前网络政治参与中存在的问题与对策

针对我国当前网络政治参与中存在着非法参与行为多、政务信息不公开致使公众政治参与缺乏信息基础、政府对公众网络政治参与的行为与观点缺乏回应等问题,本文提出了采取完善政治参与和网络政治参与的法治化机制,建立健全网络参政相关法规,保障公民网络参政议政权益,规范和打击非法政治参与行为;修改政府信息公开的法律法规,加大政府信息公开力度与规范网络监督机制;建立政府对公民网络政治参与的回应制度,以解决公民网络政治参与的相关问题,推动法治文明.     

Metallographic sample prepared by ion beam etching

Ion beam etching technique was used to reveal the metallograhpic microstructure and interface morphology of electroplating chromium coating, in particular, whose substrate surface layer was treated in advance by laser quenching. Chemical etchings were also conducted for comparison. The reveal microstructures were observed and analyzed by scanning electron microscopy. The results show that ion beam etching can reveal well the whole microstructures of composite coating-substrate materials.     

高线粗中轧机"浮动"检测结构设计及故障排除

为克服轧制中因机架锁紧功能降低而产生的机架沿轨座轴向移动的"浮动"现象,对其产生原因进行了分析,并通过改进锁紧装置结构及相关部件,使"浮动"故障得到预防和有效控制并及时排除。     

基于VC++6.0的3-DOF机器人鼠标移动轨迹示教控制系统

采用VC 6.0开发软件,设计了一个3-DOF机器人鼠标移动轨迹示教控制系统,在该控制系统中采用鼠标移动轨迹示教来替代传统按钮式示教盒示教,有效地克服了传统示教次数多、运动不稳定的缺点.适用于对精度要求不高的机器人进行有特定要求的点位控制.     

创新服务方式推行"三网"合一全面提升纳税服务信息化建设水平

江苏省盐城地税局全面实现12366纳税热线系统与"盐城地税"门户网站的互联互通.该局按照标准统一、效率优先的要求,建立统一的纳税服务平台,竭力为纳税人提供规范高效的纳税服务.一方面实现了信息共享.网站上所有的政策法规、热点问题及其他业务资料全部从12366热线系统业务库中快速读取.另一方面实现了功能整合.以12366热线为主体,将热线、网站、短信平台中的咨询建议等互动功能进行整合,提供多渠道咨询和一员化处理的服务.     

用Packet Tracer模拟软件提高《网络互联技术》实验教学效果

实验教学是高职计算机网络课程的重要组成部分,目前高职计算机网络实验课程开展困难,效果不明显。该文结合当前高职计算机网络课程实验教学的现状,谈一谈如何利用Packet Tracer模拟软件提高《网络互联技术》课程的实验教学效果。     

建筑美学

把建筑定义为美学带有主观随意性,局限性,除了形式美,建筑还具有实用,经济,技术等价值。本文分别从建筑的形式美,使用功能,先进技术、环境特色等方面具体阐述建筑美学,对大多数人关心的建筑美学做一个冷静而深入的思考,探究这样一种美从何而来。     

Residual Feature Attentional Fusion Network for Lightweight Chest CT Image Super-Resolution

The diagnosis of COVID-19 requires chest computed tomography (CT). High-resolution CT images can provide more diagnostic information to help doctors better diagnose the disease, so it is of clinical importance to study super-resolution (SR) algorithms applied to CT images to improve the resolution of CT images. However, most of the existing SR algorithms are studied based on natural images, which are not suitable for medical images; and most of these algorithms improve the reconstruction quality by increasing the network depth, which is not suitable for machines with limited resources. To alleviate these issues, we propose a residual feature attentional fusion network for lightweight chest CT image super-resolution (RFAFN). Specifically, we design a contextual feature extraction block (CFEB) that can extract CT image features more efficiently and accurately than ordinary residual blocks. In addition, we propose a feature-weighted cascading strategy (FWCS) based on attentional feature fusion blocks (AFFB) to utilize the high-frequency detail information extracted by CFEB as much as possible via selectively fusing adjacent level feature information. Finally, we suggest a global hierarchical feature fusion strategy (GHFFS), which can utilize the hierarchical features more effectively than dense concatenation by progressively aggregating the feature information at various levels. Numerous experiments show that our method performs better than most of the state-of-the-art (SOTA) methods on the COVID-19 chest CT dataset. In detail, the peak signal-to-noise ratio (PSNR) is 0.11 dB and 0.47 dB higher on CTtest1 and CTtest2 at SR compared to the suboptimal method, but the number of parameters and multi-adds are reduced by 22K and 0.43G, respectively. Our method can better recover chest CT image quality with fewer computational resources and effectively assist in COVID-19.