ID 原文 译文
24645 针对幅值强、频带宽、持续时间短等脉冲电场测量需求，本文提出一种基于电光聚合物缺陷光子晶体的全介质脉冲电场传感器。 As for the measurement requirements of the pulse electric field with high intensity, wide frequency band and short duration, an all-dielectric electric field sensor based on photonic crystal with electro-optic polymer defect was proposed in this paper.
24646 在周期性分布的光子晶体中引入电光聚合物作为缺陷层，外界电场的作用下，电光聚合物的折射率发生改变，这将会引起光子晶体的谐振频率偏移，监测谐振频率的变化即可实现被测电场测量。 The electro-optic polymer in the form of a defect layer was inserted in the periodic one-dimensional photonic crystal structure. The variations of refractive index of electro-optic polymer under the externally applied electric fields may induce the changes of the resonance wavelength of the defect mode. Accordingly, the applied electric field may be measured by monitoring the shift of the resonant wavelength.
24647 仿真结果表明，通过合理设计传感器的结构参数，结合波长-光强解调系统，基于电光聚合物缺陷光子晶体的电场传感器的电场分辨力可以达到约30V/m，最高可测量场强则可达到兆V/m量级。 It is theoretically shown that the minimal detectable electric field of 30V/m can be achieved and the maximum detectable field could reach up to the order of MV/m。
24648 为实现确知频率信号在强噪声环境下的有效提取，本文在零空间追踪(Null Space Pursuit, NSP)方法的基础上，通过增加已知频率的先验信息约束，提出了一种基于频率确知信号约束的微弱信号提取方法。 In order to realize the effective extraction of determined frequency signal under the strong noise environment, we propose a weak signal extraction method based on null space pursuit (NSP) and determined frequency signal constraint.
24649 该方法继承了零空间追踪方法的优良属性，通过将确定的频率作为先验信息约束，可以实现其微弱信号相位和幅度的有效提取，仿真实验证明最多可实现高达 30dB 信噪比的提升；特别适合相对低信噪比环境下（信噪比小于-5dB）的微弱信号提取。 The proposed approach inherits the excellent properties of NSP algorithm, by incorporating the determined frequency as prior information constraint, can extract the amplitude and phase of the weak signal effectively. The simulated experimental results show that, for the weak signal extraction, the proposed approach can improve signal to noise ratio (SNR) up to 30dB and especially suitable for low SNR environment extraction (i.e. SNR below -5dB).
24650 该方法提供了常规的微弱确知信号的检测/提取方法之外的一种新的选择。 In addition to the traditional methods, this approach provides an alternative way for the weak signal extraction or detection.
24651 随着工业物联网和人工智能技术的迅猛发展，各种复杂软件系统（Complex Software System, CSS）日趋盛行，成为最重要的软件系统开发范式之一，其固有的成长性构造和适应性演化性质要求 CSS必须能够实时感知和诊断自身的健康状态，确保其适应性演化过程中的质量。 With the rapid development of Industry Internet of Things and AI technology, various complex software systems (CSS) are becoming more and more popular, and becoming one of the most important software development paradigms. Its inherent growth construction and adaptive evolution require CSS to be able to perceive and diagnose its own health status in real time, so as to ensure the quality of its adaptive evolution.
24652 本文采用特征工程和存储库数据挖掘技术，对影响开源 CSS 健康状态的特征进行分析，建立了一个数据驱动的实时、客观地反映开源 CSS 健康状态的自感知模型，并进一步借鉴质量控制图的思想，定义了能够辅助开源 CSS故障诊断的自诊断模型。 The paper uses feature engineering and mining software repositories (MSR) technology to analyze the features that affect the health of open source CSS, and establishes adata driven perception model that can reflect the health status of open source CSS in real time and objectively. Furthermore, a self-diagnosis model that can assist open source CSS fault diagnosis is defined with reference to the quality control chart.
24653 最后，通过对比实验，证明了本文提出的模型因为全面综合了软件开发过程的绝大多数特征，能够更加全面和有效地评价软件的健康状态。 Finally, through the model comparison experiment, it is proved that our model can evaluate the health of software more comprehensively and effectively because it integrates most feature of software development process.
24654 提出基于词频处理的 Laplacian 图谱聚类算法，以解决短文本数据维数高、特征稀疏等问题。 A Laplacian graph clustering algorithm based on word frequency processing is presented, to solve the problems of high feature dimension and sparse feature in short text.