超声变幅杆解析法设计的可靠性研究

本文提出了用有限元法验证变幅杆解析法设计的可靠性，对三种类型的变幅杆先作解析法设计；然后利用有限元分析软件ANSYS进行模态分析，确定了变幅杆的固有频率，计算了固有频率与工作频率之间的相对误差，以此来评价解析法设计的可靠性；并分析了影响解析法设计可靠性的两个基本因素。     

一种高动态范围图像可视化算法*

提出的自适应HDR图像可视化算法中,输入图像被分解为基本层和细节层.该算法将整体明暗效果的显示看做整体问题,对表示亮度的基本层采用基于整体统计信息的直方图调整算法处理;可视细节信息的保持作为局部问题,算法采用自适应细节增强算法处理细节层.通过定义映射图对细节增强后的图像进行最终映射,将两方面结合起来得到最终结果.实验结果表明,该算法能对HDR图像进行较高视觉质量的显示.     

深冷处理提高镀锌钢板点焊电极寿命的机理

为了提高镀锌钢板点焊电极寿命，作者提出了镀锌钢板点焊电极的深冷处理方法。采用不同深冷处理工艺参数处理了点焊镀锌钢板的Cr—Zr—Cu合金电极，用这些电极进行了镀锌钢板点焊电极寿命试验并与未深冷处理的电极寿命进行了比较。用扫描电子显微镜对深冷处理电极进行了背散射及面扫描分析，用X射线衍射法观测了深冷处理前后的电极晶粒度，测试了电极在深冷处理前后的电阻率。通过对深冷电极微观结构的观测及电极性能的测试，探讨了深冷处理提高镀锌钢板点焊电极寿命的机理。研究结果表明，深冷处理提高了镀锌钢板点焊电极基体的致密性，改变了合金元素的分布，细化了电极材料的晶粒，提高了镀锌钢板点焊电极的导电、导热能力及电极抗压渍变形的能力，从而提高了镀锌钢板点焊电极的寿命。     

PET共聚阻燃改性研究进展

该文综述了近年来聚对苯二甲酸乙二醇酯(PET)以共聚改性方式制备高性能阻燃PET的最新研究进展,主要从磷系共聚阻燃、高温交联、高温重排、高温离子聚集和高温端基捕获链扩展5个方面对阻燃改性PET的阻燃机理和阻燃性能进行阐述,并总结了不同阻燃共聚改性方法的特点,对未来PET共聚阻燃的研究方向提出展望.     

结合Transformer的轻量化中文语音识别

近年来,深度神经网络模型在语音识别领域成为热门研究对象。然而,深层神经网络的构建依赖庞大的参数和计算开销,过大的模型体积也增加了其在边缘设备上部署的难度。针对上述问题,提出了基于Transformer的轻量化语音识别模型。首先使用深度可分离卷积获得音频特征信息;其次构建了双半步剩余权重前馈神经网络,即Macaron-Net结构,并引入低秩矩阵分解,实现了模型压缩;最后使用稀疏注意力机制,提升了模型的训练速度和解码速度。为了验证模型,在Aishell-1和aidatatang_200zh数据集上进行了测试。实验结果显示,所提模型与Open-Transformer相比,所提模型在字错误率上相对下降了19.8%,在实时率上相对下降了32.1%。     

无线可充能传感器网络的锚点算法与移动设备调度研究

由于传感器的电池容量和存储容量有限,导致无法持续对传感器进行能量补充并收集传感器生成的感测数据。针对该问题,研究了周期性能量补充和数据收集问题,提出了一种用于充能和数据收集的方法,包括基于网格的算法(GBA)、基于支配集的算法(DSBA)和基于圆相交的算法(CIBA)。通过这三种方法或两两相结合的方法找到锚点集合,通过移动设备调度算法调度最小数量的移动设备来访问生成的锚点。仿真结果验证了所提方法的有效性。与联合能量数据采集(JEDA)算法、最小覆盖圆(SEC)算法相比,所提CIBA需要的移动设备数量最少,总移动距离也最短,具有良好的综合性能。     

提升芯片智能化生产的器件失效分析

智能化自动化生产是现代化芯片生产的主要发展趋势之一,通过失效分析手段进行芯片良率提升并将失效数据模型补充至智能化生产的监测管理是自动化芯片代工的重要手段。本文以60 V沟槽功率器件为研究对象,通过完成芯片制造全流程后电性测试得到的良率数据,从失效检测的电性、剖面形貌出发,利用结构形貌结果反推工艺失效节点,并建立失效数据库。结果表明,采用热点分析及高倍电镜观察可快速排查芯片的器件失效的结构,并根据工艺流程迅速判断失效工艺步骤。     

Science and technology in the region: The output of regional science and technology, its strengths and its leading institutions

Summary We operationalize scientific output in a region by means of the number of articles (as in the SciSearch database) per year and technology output by means of the number of patent applications (as in the database of the European Patent Office) per priority year. All informetric analyses were done using the DIALOG online-system. The main research questions are the following: Which scientific and technological fields or topics are most influent within a region and which institutions or companies are mainly publishing articles or holding patents? Do the distributions of regional science and technology fields and of publishing institutions follow the well-known informetric function? Are there - as it is expected - only few fields and few institutions which dominate the region? Is there a connection between the economic power of a region and the regional publication and patent output? Examples studied in detail are seven German regions: Aachen, Düsseldorf, Hamburg, Köln (Cologne), Leipzig - Halle - Dessau, München (Munich), and Stuttgart. Three different indicators were used, science and technology attraction of a region (number of scientific articles and patents), science and technology intensity (articles and patents per 1,000 inhabitants), and science and technology density (articles and patents per 1 billion EURO gross value added). Top region concerning both attraction and intensity is Munich, concerning density it is Aachen.     

虚拟标准显色设备——跨网络色彩重现的新方案

随着网络的普及和多媒体应用的增长,彩色的传输和真实重现日益受到重视.虽然基于ICC的色彩管理提供了色彩复制与传递机制,但是这些技术仍存在增加系统开销、设备特性信息传递困难、不同色彩管理系统难以混合等问题.本文提出了"虚拟标准显色设备"的概念,较好地解决了跨网络、跨平台的色彩重现问题.实验结果证明了这种方法的有效性.     

Competitiveness analysis of automotive industry in Turkey using Bayesian networks

The purpose of this study is to analyze the relations between the factors that enable national competitive advantage and the establishment of competitive superiority in automotive industry through a comprehensive analytical model. Bayesian networks (BN) are used to investigate the associations of different factors in the automotive industry which lead to competitive advantage. The results of the study focus on building a road map for the automotive sector policy makers in their way to improve the competitiveness through scenario analysis. Using the probabilistic dependency structure of the Bayesian network all of the variables in the model can be estimated. Thus, with the proposed model the automotive industry can be analyzed as a whole system and not only in terms of single variables. Findings of the model indicate that technological developments in automotive industry can alter the nature of competition in this industry.