Removal of bird-contaminated wind profiler data based on neural networks

This paper presents the results of a study that relied on trainable neural network classifiers to identify and remove bird-contaminated data from wind measurements recorded by a 1290-MHz wind profiler. A wind profiler is a Doppler radar system measuring the three-dimensional wind field. Migrating birds crossing the radar beam can lead to erroneous wind observations. Bird removal was performed by training conventional feedforward neural networks (FFNNs) and quantum neural networks (QNNs) to identify and remove bird-contaminated data recorded by a 1290-MHz wind profiler. A series of experiments evaluated several sets of input features extracted from wind profiler data, various FFNNs and QNNs of different sizes, and criteria employed for identifying birds in wind profiler data.     

One-Dimensional Continuous-Time Quantum Walks

We survey the equations of continuous-time quantum walks on simple one-dimensional lattices, which include the finite and infinite lines and the finite cycle, and compare them with the classical continuous-time Markov chains. The focus of our expository article is on analyzing these processes using the Laplace transform on the stochastic recurrences. The resulting time evolution equations, classical vs. quantum, are strikingly similar in form, although dissimilar in behavior. We also provide comparisons with analyses performed using spectral methods. PACS: 03.67.Lx     

基于量子神经网络(QNN)的语音增强技术

将量子神经网络(QNN)应用于语音增强技术中,并与基于径向基函数神经(RBF)网络的语音增强技术进行比较.实验结果表明,基于QNN上的语音增强技术效果比基于人工神经网络(ANN)中的RBF网络的语音增强技术效果好,消噪能力强,有更好的鲁棒性.另外,该技术还能够改善语音质量.     

Fluid Flow,Heat Transfer and Inclusion Motion in a Four‐Strand Billet Continuous Casting Tundish

Inclusions in the steel in a four‐strand continuous casting tundish, billet and wire products are firstly investigated with industrial trials, and the fraction of inclusions removed in terms of total oxygen in the tundish is measured. Then the 3‐dimenional fluid flow, heat transfer and inclusion motion in the tundish are numerically simulated. The κ‐? two‐equation model is used to model turbulence. Inclusion motion and trajectories are calculated by considering drag force and buoyancy force, coupling the effect of turbulent fluctuation (Random Walk Model). The effect of strands‐blocking on the fluid flow, heat transfer and inclusion removal is studied. A new design of tundish is proposed focusing on removing more inclusions from the molten steel.     

基于随机游走的流形学习与可视化

现有的全局流形学习算法都敏感于邻域大小这一难以高效选取的参数,它们都采用了基于欧氏距离的邻域图创建方法,从而使邻域图容易产生“短路”边。本文提出了一种基于随机游走模型的全局 流形学习算法(Random walk-based isometric mapping,RW-ISOMAP)。和欧氏距离相比,由随机游走模型得到的通勤时间距离是由给定两点间的所有通路以概率为权组合而成的,不但鲁棒性更高,而且还能在一定程度上度量具有非线性几何结构的数据之间的相似性。因此采用通勤时间距离来创建邻域图的RW-ISOMAP算法将不再敏感于邻域大小参数,从而可以更容易地选取邻域大小参数,同时还具有更高的鲁棒性。最后的实验结果证实了该算法的有效性。     

基于3D角度编码的量子遗传算法

为了充分利用量子态在算法中的量子特性,提高算法的搜索效率,减少存储空间,提出了一种基于3D角度编码的量子遗传算法。该算法将量子位描述为3D球面坐标下的一对相位角,充分利用了量子的空间运动特性,并引入一种自适应旋转角大小和方向的确定方案,从而进一步简化了染色体的更新和变异过程,而且使算法的量子特性、存储性能、时间性能都得到很大的提高。仿真结果表明,其在算法优化效率和搜索能力上都优于简单遗传算法和普通量子遗传算法。     

基于概率超图的视频事件语义检测

视频事件类别的归属具有模糊性和不确定性,将超图的点边射入矩阵拓展成概率形式的软超图进行关联关系分析和语义分析,将会更有利于提高多事件检索检测的精准率和召回率。提出基于概率超图模型的视频事件语义检测算法（PHVESD）。 该方法首先将颜色、灰度共生矩阵、Tchebichef矩、局部二值模式（LBP）等四种底层视觉特征进行融合; 然后定义视频段的亲密度函数并利用亲密度的信息构建概率超图模型,其中每条超边对应一种事件语义;采用随机游走过程来预测视频段属于每条超边的概率;最后结合阈值采用条件概率模型对视频段进行事件语义分类。将该方法用于交通突发事件多语义检测中并与其他的识别算法相比较,实验结果表明,与基于超图模型的多标签随机游走算法（MLRW）相比,PHVESD的算法使多语义事件检测的准确率提高了10%,召回率提高了8%。     

A nano- and micro- integrated protein chip based on quantum dot probes and a microfluidic network

A novel nano- and micro-integrated protein chip (NMIPC) that can detect proteins with ultrahigh sensitivity has been fabricated. A microfluidic network (μFN) was used to construct the protein chips, which allowed facile patterning of proteins and subsequent biomolecular recognition. Aqueous phase-synthesized, water-soluble fluorescent CdTe/CdS core-shell quantum dots (aqQDs), having high quantum yield and high photostability, were used as the signaling probe. Importantly, it was found that aqQDs were compatible with microfluidic format assays, which afforded highly sensitive protein chips for cancer biomarker assays. Electronic Supplementary Material  Supplementary material is available for this article at and is accessible for authorized users.