Study on TSV isolation liners for a Via Last approach with the use in 3D-WLP for MEMS

This paper discusses approaches for the isolation of deep high aspect ratio through silicon vias (TSV) with respect to a Via Last approach for micro-electro-mechanical systems (MEMS). Selected TSV samples have depths in the range of 170…270 µm and a diameter of 50 µm. The investigations comprise the deposition of different layer stacks by means of subatmospheric and plasma enhanced chemical vapour deposition (PECVD) of tetraethyl orthosilicate; Si(OC₂H₅)₄ (TEOS). Moreover, an etch-back approach and the selective deposition on SiN were also included in the investigations. With respect to the Via Last approach, the contact opening at the TSV bottom by means of a specific spacer-etching method have been addressed within this paper. Step coverage values of up to 74 % were achieved for the best of those approaches. As an alternative to the SiO₂-isolation liners a polymer coating based on the CVD of Parylene F was investigated, which yields even higher step coverage in the range of 80 % at the lower TSV sidewall for a surface film thickness of about 1000 nm. Leakage current measurements were performed and values below 0.1 nA/cm² at 10 kV/cm were determined for the Parylene F films which represents a promising result for the aspired application to Via Last MEMS-TSV.     

牙颌点云数据的显著性特征提取

随着激光扫描测量技术的发展,其数据测量精度的逐渐增高使得获取的几何模型表面点云数据的细节信息越丰富,能更准确的反应物体几何表面特征,但如此海量的点云数据同时也带来对应的技术挑战,海量的点云数据在计算机文件存储、数据后期进一步处理以及软件可视化方面都不方便且效率低下.本文中的算法首先采用栅格法对点云进行空间划分及领域关系的建立,其次利用局部表面拟合的方法估算点云法向量,然后利用点云K领域法的向量求解坐标点的显著性值,最后根据显著性的值构建点云八叉树.该算法实现了对点云显著性特征的提取和对点云数据量的进一步简化,它不仅保留了对点云细节特征保持方面的优势,而且在时间效率上得到了提高.     

Efficient entanglement concentration of arbitrary unknown less-entangled three-atom W states via photonic Faraday rotation in cavity QED

We propose an efficient entanglement concentration protocol (ECP) for nonlocal three-atom systems in an arbitrary unknown less-entangled W state, resorting to the Faraday rotation of photonic polarization in cavity quantum electrodynamics and the systematic concentration method. In the first step of the present ECP, one party in quantum communication performs a parity-check measurement on her two atoms in two three-atom systems for dividing the composite six-atom systems into two groups. In the first group, the three parties will obtain some three-atom systems in a less-entangled state with two unknown coefficients. In the second group, they will obtain some less-entangled two-atom systems. In the second step of the ECP, the three parties can obtain a subset of three-atom systems in the standard maximally entangled W state by exploiting the above three-atom and two-atom systems. Moreover, the preserved systems in the failed instances can be used as the resource for the entanglement concentration in the next round. The total success probability of the ECP can therefore be largely increased by iterating the entanglement concentration process several rounds. The distinct feature of our ECP is that we can concentrate arbitrary unknown atomic entangled W states via photonic Faraday rotation, and thus it may be universal and useful for entanglement concentration in future quantum communication network.     

Neural-network-based fuzzy logic control of a 3D rigid pendulum

International Journal of Control, Automation and Systems - This paper concerns the attitude control problem of a 3D rigid pendulum based on dynamic T-S fuzzy neural model. A generalized 3D rigid...     

基于LDA主题模型的分布式信息检索集合选择方法

该文针对分布式信息检索时不同集合对最终检索结果贡献度有差异的现象,提出一种基于LDA主题模型的集合选择方法。该方法首先使用基于查询的采样方法获取各集合描述信息;其次,通过建立LDA主题模型计算查询与文档的主题相关度;再次,用基于关键词相关度与主题相关度相结合的方法估计查询与样本集中文档的综合相关度,进而估计查询与各集合的相关度;最后,选择相关度最高的M个集合进行检索。实验部分采用R_m、P@n和MAP作为评价指标,对集合选择方法的性能进行了验证。实验结果表明该方法能更准确的定位到包含相关文档多的集合,提高了检索结果的召回率和准确率。     

Landsat-8长条带影像正射校正

目的 Landsat-8传感器采用线阵推扫式成像,通过分景处理获得标准景产品。面对大范围遥感数据需求,长条带数据具有更高的应用价值。长条带数据的一般获取方法是通过拼接标准景正射产品的方式,该方法处理效率不高,并且当条带中某景由于云覆盖量较多无法生产正射产品时,将无法通过多景拼接的方式生成相应的长条带正射产品。针对此方法存在的问题,本文提出一种Landsat-8长条带影像的正射校正方法。方法 以长条带影像为整体,通过控制点匹配、长条带几何精校正和正射校正3个部分,直接生成长条带级别的正射校正产品。在长条带几何精校正过程中,提出了Landsat-8的基于轨道约束的长条带平差模型及控制点优化选取方法。结果 在15景的条带长度范围内,本文方法生成的长条带正射产品的几何精度在12 m以内,满足Landsat-8正射产品的精度要求,且处理效率相较于标准景拼接方式提升1倍左右;对于云覆盖较多的景,利用连续3景进行长条带正射校正,可以得到与标准景正射产品几何精度相当的长条带正射产品。结论 本文提出的长条带处理方法,在一定长度范围内,能够得到满足Landsat-8正射产品的精度要求的长条带正射产品,处理效率得到较大提高,且能够有效克服传统方法中云覆盖情形对长条带产品获取的限制。     

改进权值非局部均值超声图像去噪

目的 超声图像斑点噪声会影响诊断的准确性和可靠性。通过分析超声图像斑点噪声统计模型,结合非局部均值滤波算法,提出一种基于超声斑点噪声模型的改进权值非局部均值（NLM）滤波算法。方法 算法针对超声图像灰度信息对图像进行预处理,利用超声图像斑点噪声模型改进传统NLM算法的权值计算函数,基于图像特征确定最优采样间隔进行下采样,利用改进后的权值计算函数对图像进行NLM去噪处理。结果 分别采用人工合成与真实超声图像对本文算法性能进行测试,并与传统非局部均值滤波算法、非局部总变分（NLTV）等算法进行去噪效果比较,同时采用均方误差、峰值信噪比和平均结构相似性作为滤波算法性能的客观评价指标。本文算法能快速完成超声图像的去噪处理,峰值信噪比较其他算法可以提高0.2 dB以上,可以降低均方误差,提高平均结构相似性,缩短处理时间,并得到较好的图像质量和视觉效果。结论 根据超声图像斑点噪声模型对NLM算法的权值计算函数进行优化,使得NLM图像滤波算法能更好地适用于超声图像的去噪,基于超声斑点噪声模型的改进权值NLM算法相较于其他算法,滤波效果更佳,适合超声图像去噪。     

基于概率的无监督缺陷预测方法

软件缺陷预测能够提高软件开发和测试的效率,保障软件质量。无监督缺陷预测方法具有不需要标签数据的特点,从而能够快速应用于工程实践中。提出了基于概率的无监督缺陷预测方法—PCLA,将度量元值与阈值的差值映射为概率,使用概率评估类存在缺陷的可能性,然后再通过聚类和标记来完成缺陷预测,以解决现有无监督方法直接根据阈值判断时对阈值比较敏感而引起的信息丢失问题。将PCLA方法应用在NetGen和Relink两组数据集,共7个软件项目上,实验结果表明PCLA方法在查全率、查准率、F-measure上相对现有无监督方法分别平均提升4.1%、2.52%、3.14%。     

基于物联网的在线打印出版云平台设计

设计了一个基于物联网的在线打印出版云平台,技术上融合了物联网、大数据、云计算等相关技术,采用经典的LTMJ (Linux+Tomcat+MySQL+JDK)架构,建立数据持久层、业务逻辑层、接口控制层,为读者开发移动终端阅读APP,为作者、出版社和平台运营商开发办公OA,为打印终端开发接口.平台最大的特点是把碎片化的知识系统化,满足系统性阅读与学习的需要.