基于CiteSpace的资源型产业研究知识图谱分析

资源型产业发展为推进国家经济增长和工业化进程提供了重要保障。为深入了解资源型产业的研究情况，以CNKI数据库为数据源，搜集2000—2020年关于资源型产业的核心及以上期刊论文，利用CiteSpace软件从发文作者与研究机构分布、关键词共现网络和时区图谱等方面，绘制知识图谱，进行可视化分析。研究发现：资源型产业领域的研究成果愈加丰富，但研究群体间联系合作较少，且现有的合作研究主要集中在所处地域资源富集和具有学科优势的研究机构及学者；资源型产业领域的研究热点可概括为产业发展、资源型城市、产业集群、产业结构、产业链和产业集聚等方面；针对资源型产业领域未来可从资源型产业相关理论研究、创新发展模式和可持续发展等方面深入展开。     

金属增材制造技术研究热点聚类分析

为深入分析金属增材制造技术分类和发展状况,采集中国期刊全文数据库(CNKI)收录的核心期刊上的768篇科技文献,借助文献分析可视化软件CiteSpace,对关键词聚类进行了全景式描绘,构建金属增材制造技术知识图谱,揭示该技术研究分类以及演化趋势。     

结合预训练模型和语言知识库的文本匹配方法

针对文本匹配任务,该文提出一种大规模预训练模型融合外部语言知识库的方法。该方法在大规模预训练模型的基础上,通过生成基于WordNet的同义—反义词汇知识学习任务和词组—搭配知识学习任务引入外部语言学知识。进而,与MT-DNN多任务学习模型进行联合训练,以进一步提高模型性能。最后利用文本匹配标注数据进行微调。在MRPC和QQP两个公开数据集的实验结果显示,该方法可以在大规模预训练模型和微调的框架基础上,通过引入外部语言知识进行联合训练有效提升文本匹配性能。     

Q值正演模拟约束下的零偏移距VSP资料Q值估算

随着油气勘探目的层逐步走向深部,球面扩散、透射损失、环境噪声等使得VSP资料的初至子波发生改变,导致常规的Q值估算方法质量难以得到保证。为此,利用塔里木盆地托甫台地区TP327井零偏移距VSP资料,综合考虑透射损失和球面扩散的影响,提出一种Q值正演模拟约束下的零偏移距VSP资料Q值估算方法。该方法通过研究区的纵波速度、横波速度和密度建立层状地质模型,利用射线追踪的方法,用大地吸收介质模型的Q值正演模拟结果,对频谱比法和经验公式估算的初始Q值进行修正,使得Q值正演模拟结果与实际地震波的衰减记录在频谱特征上吻合,从而得到更为精确的Q模型。TP327井Q值估算结果表明,该方法与李庆忠经验公式得到的结果在浅层比较接近,但在中层和深层,两者差异较大;Q值正演模拟结果约束的子波与实际VSP资料子波的频谱比较吻合,证实用Q值正演模拟约束得到的层间Q值更为可靠。利用Q值正演模拟约束方法得到的Q模型对研究区地震资料进行反Q滤波能显著提高地震资料分辨率,有助于提高碳酸盐岩地层中缝洞的识别精度。     

Airborne bacterial assemblage in a zero carbon building: A case study

Currently, there is little information pertaining to the airborne bacterial communities of green buildings. In this case study, the air bacterial community of a zero carbon building (ZCB) in Hong Kong was characterized by targeting the bacterial 16S rRNA gene. Bacteria associated with the outdoor environment dominated the indoor airborne bacterial assemblage, with a modest contribution from bacteria associated with human skin. Differences in overall community diversity, membership, and composition associated with short (day‐to‐day) and long‐term temporal properties were detected, which may have been driven by specific environmental genera and taxa. Furthermore, time‐decay relationships in community membership (based on unweighted UniFrac distances) and composition (based on weighted UniFrac distances) differed depending on the season and sampling location. A Bayesian source‐tracking approach further supported the importance of adjacent outdoor air bacterial assemblage in sourcing the ZCB indoor bioaerosol. Despite the unique building attributes, the ZCB microbial assemblage detected and its temporal characteristics were not dissimilar to that of conventional built environments investigated previously. Future controlled experiments and microbial assemblage investigations of other ZCBs will undoubtedly uncover additional knowledge related to how airborne bacteria in green buildings may be influenced by their distinctive architectural attributes.     

纳米零价铁材料对放射性核素的 去除及机理研究进展

随着人类社会的发展，放射性铀矿的开采和使用越来越多，环境面临着越来越严重的放射性污染问题。从生物和环境的角度来看，有效地清除环境中的放射性核素是核能利用过程中最重要的问题之一。纳米零价铁（nanoscale zero valent iron, nZVI）具有较大的比表面积和较高的活性位点，能显著提高放射性污染物的修复效率。本综述的目的是展示nZVI基材料对放射性核素的高效去除能力和环境修复作用。简介了常用的nZVI基材料（表面改性或多孔材料支撑的nZVI材料）及其对放射性核素的去除效果和相互作用机制（如吸附和氧化还原）。最后，对nZVI材料的应用和挑战给出个人见解。本综述有助于为高效去除放射性核素的nZVI材料的设计指明方向，为放射性核素的高效处理处置提供新材料。     

考虑关节角加速度约束的仿人机器人偏摆力矩控制方法

针对仿人机器人步行过程中存在的机器人关节角加速度约束影响控制性能的问题，提出一种考虑关节角加速度约束的仿人机器人偏摆力矩控制方法.该方法充分考虑了双臂在摆动过程中对偏摆力矩的影响，根据力矩平衡条件得到需要抵消的偏摆力矩的大小与方向，将偏摆力矩的控制问题转化为带约束条件的二次规划问题，并设计了一种在线变步长迭代算法计算得到优化后的双臂摆动轨迹.实验表明，该方法能有效抵消机器人步行中产生的偏摆力矩，避免控制过程中的"削峰"现象，有效提高机器人的步行稳定性.     

Ontology-based approach for the provision of simulation knowledge acquired by Data and Text Mining processes

Numerical simulation techniques such as Finite Element Analyses are essential in today's engineering design practices. However, comprehensive knowledge is required for the setup of reliable simulations to verify strength and further product properties. Due to limited capacities, design-accompanying simulations are performed too rarely by experienced simulation engineers. Therefore, product models are not sufficiently verified or the simulations lead to wrong design decisions, if they are applied by less experienced users. This results in belated redesigns of already detailed product models and to highly cost- and time-intensive iterations in product development.Thus, in order to support less experienced simulation users in setting up reliable Finite Element Analyses, a novel ontology-based approach is presented. The knowledge management tools developed on the basis of this approach allow an automated acquisition and target-oriented provision of necessary simulation knowledge. This knowledge is acquired from existing simulation models and text-based documentations from previous product developments by Text and Data Mining. By offering support to less experienced simulation users, the presented approach may finally lead to a more efficient and extensive application of reliable FEA in product development.     

Condition based maintenance of the two-beam laser welding in high volume manufacturing of piezoelectric pressure sensor

Two-beam laser welding (TBLW) is an advanced process for precise, low distortion joining of cylindrical miniature parts. The process is composed of a laser source, optics and various actuators, which form a sophisticated system for control and maintenance in high volume manufacturing. A well-established method for identifying welding defects and ensuring welding quality is the monitoring of plasma light emission in TBLW. Although such monitoring systems can detect a change in process status, they are not able to diagnose the nature of the fault. The main challenge in this research was to extend the use of quality-based monitoring systems to measure additional deterioration-related parameters and to estimate system deterioration from them by using expert knowledge.This paper shows a novel condition-based maintenance (CBM) for the TBLW system, which performs condition identification using online monitoring of plasma light emission in combination with offline inspection of the seam macrographs. A combination of quality parameters derived from seam macrographs of defective parts is used to identify process deterioration, such as contamination of the optics, misalignment of the optomechanical system, or reduced laser power. The information obtained is used to make predefined process adjustments based on expert domain knowledge. The implementation of the developed CBM in high volume manufacturing of piezoelectric pressure sensors resulted in more predictable TBLW by reducing system failures as well as shorter diagnosis times.