UV nano embossing for polymer nano structures with non-transparent mold insert

In recent years, UV nano embossing (or imprinting) process has been widely used for mass replication of nano structures. Most of the UV embossing machines use a UV transparent mold insert (e.g. quartz or glass). However, when a master of nano structures of interest could be realized only in a UV non-transparent mold material, it would be desirable to have a UV embossing machine which could be operated with such a UV non-transparent mold insert. In this regard, we have designed and manufactured a new UV embossing system in such a way that UV non-transparent (e.g., metal or ceramic) mold inserts can also be used as the master for the mass replication of nano structures. For the new UV embossing system, we fabricate several metal mold inserts: a nickel electroformed mold insert having grating nano structures and two AAO (anodic aluminum oxide) mold inserts having dimple nano structures and high-aspect-ratio nanopores. Finally, corresponding nano structures are successfully replicated via the UV nano embossing machine developed in this study.     

基于注意力机制和集成学习的网页黑名单判别方法

搜索引擎作为互联网主要应用之一,能够根据用户需求从互联网资源中检索并返回有效信息。然而,得到的返回列表往往包含广告和失效网页等噪声信息,而这些信息会干扰用户的检索与查询。针对复杂的网页结构特征和丰富的语义信息,提出了一种基于注意力机制和集成学习的网页黑名单判别方法,并采用本方法构建了一种基于集成学习和注意力机制的卷积神经网络（EACNN）模型来过滤无用的网页。首先,根据网页上不同种类的HTML标签数据,构建多个基于注意力机制的卷积神经网络（CNN）基学习器;然后,采用基于网页结构特征的集成学习方法对不同基学习器的输出结果执行不同的权重计算,从而实现EACNN的构建;最后,将EACNN的输出结果作为网页内容分析结果,从而实现网页黑名单的判别。所提方法通过注意力机制来关注网页语义信息,并通过集成学习的方式引入网页结构特征。实验结果表明,与支持向量机（SVM）、K近邻（KNN）、CNN、长短期记忆（LSTM）网络、GRU、结合注意力机制的卷积神经网络（ACNN）等基线模型相比,所提模型在所构建的面向地理信息领域的判别数据集上具有最高的准确率（0.97）、召回率（0.95）和F₁分值（0.96）,验证了EACNN在网页黑名单判别工作中的优势。     

A simple GPU-based approach for 3D Voronoi diagram construction and visualization

In this paper we propose a simple GPU-based approach for discrete incremental approximation of 3D Voronoi diagram. By constructing region maps via GPU. Nearest sites, space clustering, and shortest distance query can be quickly answered by looking up the region map. In addition, we propose another representation of the 3D Voronoi diagram for visualization.     

计算机输入设备的频谱检测与分析

利用频谱分析仪对计算机输入设备工作时发射的辐射信号进行测试,获取输入设备辐射信号的频谱数据并进行相应的频谱特性分析。找出其泄漏的主要频段和特点,为输入设备的防护提供依据。     

基于外观的复合属性学习的细粒度识别

由于语义可理解性及共享性,视觉属性作为刻画对象的中间特征表示在众多领域得到了广泛应用。视觉属性学习中,大量的人工成本用于属性定义和标注,因此难以避免地引入了主观偏见,属性表示的类别判别性难以保证,尤其面临对判别性要求较高的细粒度识别任务时更为明显。复合属性符合人类认知规律以及对象复杂多模分布的事实,从刻画对象的分布入手,以较低廉的代价建立兼具一定描述能力及较好判别能力的特征表示,以应对细粒度识别任务对判别特征和判别模型的较高要求。在细粒度识别代表性公开数据集CUB上验证了所提方法的有效性。在细粒度识别任务中,复合属性表现出比人工定义的属性以及类别判别属性更优的性能。     

大型联合循环机组余热锅炉选型比较

分析了大型燃气—蒸汽联合循环机组余热锅炉补燃与不补燃的应用条件及各自特点,给出了几种蒸汽轮机循环系统的布置方案,并分析了蒸汽循环系统的选择方法,对余热锅炉型式进行了分析比较。     

基于贝杰龙算法的±500kV直流输电线路耐雷性能研究

为保证电力系统稳定运行,研究了输电线路反击耐雷性能,提出采用贝杰龙算法等值模型对线路杆塔进行等值,利用VB编程计算求解杆塔的雷电过电压,判断绝缘子串是否发生闪络,评估其耐雷水平.以内蒙古东部地区±500 kV伊穆直流线路为例,对比了VB编程计算结果与EMTP电磁暂态仿真结果,误差在允许值范围内,验证了该方法的准确性.     

向无源网络供电的VSC-HVDC系统控制策略

在同步旋转坐标系下,利用电压源型高压直流输电(voltage source converter based high voltage DC,VSC-HVDC)的暂态数学模型,提出了一种向无源网络供电的VSC-HVDC系统新型控制策略。基于非线性系统反馈线性化控制的逆系统方法,推导了VSC-HVDC的逆系统模型,构造了伪线性系统,实现了对VSC-HVDC系统有功功率和无功功率的解耦。采用极点配置方法对该伪线性系统进行了综合,设计了控制器,并对反馈线性化中重要的隐动态问题进行了讨论,保证了控制系统的稳定性。仿真结果表明,该控制器具有较好的动态性能。     

HFC网络MAC协议的三叉树冲突化解算法分析

对HFC网络中普遍采用的三叉树冲突化解算法进行分析，介绍树冲突化解算法的两种栈管理模式：FIFO(先进先出)模式和LIFO(后进先出)模式，并举例说明FIFO和LIFPO的冲突化解过程。     

Ionic Modulation of Interfacial Magnetism in Light Metal/Ferromagnetic Insulator Layered Nanostructures

Ferromagnetic insulator thin film nanostructures are becoming the key component of the state‐of‐the‐art spintronic devices, for instance, yttrium iron garnet (YIG) with low damping, high Curie temperature, and high resistivity is explored into many spin–orbit interactions related spintronic devices. Voltage modulation of YIG, with great practical/theoretical significance, thus can be widely applied in various YIG‐based spintronics effects. Nevertheless, to manipulate ferromagnetism of YIG through electric field (E‐field), instead of current, in an energy efficient manner is essentially challenging. Here, a YIG/Cu/Pt layered nanostructure with a weak spin–orbit coupling interaction is fabricated, and then the interfacial magnetism of the Cu and YIG is modified via ionic liquid gating method significantly. A record‐high E‐field‐induced ferromagnetic resonance field shift of 1400 Oe is achieved in YIG (17 nm)/Cu (5 nm)/Pt (3 nm)/ionic liquid/Au capacitor layered nanostructures with a small voltage bias of 4.5 V. The giant magnetoelectric tunability comes from voltage‐induced extra ferromagnetic ordering in Cu layer, confirmed by the first‐principle calculation. This E‐field modulation of interfacial magnetism between light metal and magnetic isolator may open a door toward compact, high‐performance, and energy‐efficient spintronic devices.