基于语言特征自动获取的反问句识别方法

反问句是以疑问的形式表达强烈情感的修辞方式,对其有效识别可为自然语言处理中的情感分析任务提供技术支持。该文提出了一种基于语言特征自动获取的反问句识别方法。首先,利用标签注意机制,建立了一个数据驱动的特征抽取模型,用于获取与任务相关的词汇、句法结构、符号标记和话题等语言特征。其次,利用Bi-LSTM模型分别对句子和语言特征进行表示,两者的交互注意被用于获取句子的各个词和符号的注意力权重向量。该权重向量作用于句子的表示,用于构建一个强化语言特征的反问句识别模型。在中文微博数据集上的实验结果表明,提出的方法与之前的工作相比,反问句识别性能有显著提升。     

Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

Polynomial filtering for nonlinear stochastic systems with state‐ and disturbance‐dependent noises

This article is concerned with the polynomial filtering problem for a class of nonlinear stochastic systems governed by the Itô differential equation. The system under investigation involves polynomial nonlinearities, unknown‐but‐bounded disturbances, and state‐ and disturbance‐dependent noises ((x,d)‐dependent noises for short). By expanding the polynomial nonlinear functions in Taylor series around the state estimate, a new polynomial filter design method is developed with hope to reduce the conservatism of the existing results. In virtue of stochastic analysis and inequality technique, sufficient conditions in terms of parameter‐dependent linear matrix inequalities (PDLMIs) are derived to guarantee that the estimation error system is input‐to‐state stable in probability. Moreover, the desired polynomial matrix can be obtained by solving the PDLMIs via the sum‐of‐squares approach. The effectiveness and applicability of the proposed method are illustrated by two numerical examples with one concerning the permanent magnet synchronous motor.     

Stochastic stabilization and destabilization of nonlinear and time‐varying hybrid systems by noise

The aim of this article is to design a suitable strength function g(t,x,r(t)) such that the Wiener noise g(t,x(t),r(t))dw(t) either stabilizes or destabilizes a given nonlinear and time‐varying hybrid system . To this end, the basic properties, including the existence and uniqueness of the local and global solutions and the nonzero property of solutions of the nonlinear and time‐varying hybrid stochastic systems, are first investigated as the theoretical basis of the article. Second, two theorems and the corresponding corollaries on the stability and instability of the hybrid stochastic systems are established. Third, the design method for the noise strength g(t,x,r(t)) is then proposed based on the established theorems. We also point out that the Markov jump r(t) may have a stabilizing (respectively, destabilizing) effect when we design the noise strength g(t,x,r(t)) so that the introduced noise g(t,x(t),r(t))dw(t) stabilizes (respectively, destabilizes) the corresponding hybrid system. Finally, we illustrate our method using two examples. Compared with the existing literature, our method is suitable for a wider class of nonlinear and time‐varying systems with weaker conditions than quasi‐linear systems.     

α径迹法用于分辨高浓铀和Pu微粒的方法研究

擦拭样品微粒分析技术是核保障环境样品分析的一种主要手段，从大量灰尘颗粒中识别并定位含高浓铀（HEU）或含Pu微粒是微粒分析首先需要解决的问题。本文以HEU和Pu微粒为研究对象，建立了用于微粒α径迹测量的样品制备方法，采用CR-39固体径迹探测器为α径迹探测器，测量了不同蚀刻时间2种微粒产生的α径迹星的径迹参数。结果表明：可通过测量径迹短轴与曲率直径并作图来分辨HEU和Pu微粒，该方法对于蚀刻时间大于10 h的微粒径迹星，均能明显分辨，对于径迹非常密集的径迹星，也能准确分辨。     

Fault detection and identification for a class of continuous piecewise affine systems with unknown subsystems and partitions

This paper establishes a novel online fault detection and identification strategy for a class of continuous piecewise affine (PWA) systems, namely, bimodal and trimodal PWA systems. The main contributions with respect to the state‐of‐the‐art are the recursive nature of the proposed scheme and the consideration of parametric uncertainties in both partitions and in subsystems parameters. In order to handle this situation, we recast the continuous PWA into its max‐form representation and we exploit the recursive Newton‐Gauss algorithm on a suitable cost function to derive the adaptive laws to estimate online the unknown subsystem parameters, the partitions, and the loss in control authority for the PWA model. The effectiveness of the proposed methodology is verified via simulations applied to the benchmark example of a wheeled mobile robot.     

Isolation and identification of two major acylated anthocyanins from purple sweet potato (Ipomoea batatas L. cultivar Eshu No. 8) by UPLC‐QTOF‐MS/MS and NMR

In recent years, researches on the isolation and preparation of monomeric anthocyanins have intensified because of the requirements of quantitative and structure–bioactivity relationship analyses. However, simple and effective methods about the scale of monomeric anthocyanins from the natural purple sweet potato powder are rarely reported. In this study, high molecular weight acylated monomeric anthocyanins were isolated from purple sweet potato (Ipomoea batatas L. cultivar Eshu No. 8) via the combination of column chromatography and semi‐preparative HPLC technology and identified mainly by ultra‐high‐performance liquid chromatography quadrupole time‐of‐flight tandem mass spectrometry/mass spectrometry (UPLC‐QTOF‐MS/MS) and ¹H and ¹³C nuclear magnetic resonance (NMR). Two major acylated anthocyanins were unambiguously determined as peonidin 3‐O‐(6‐O‐(E)‐caffeoyl‐(2‐O‐(6‐O‐p‐hydroxybenzoyl)‐β‐D‐glucopyranosyl)‐β‐D‐glucopyranoside)‐5‐O‐(β‐D‐glucopyranoside) and peonidin 3‐O‐(6‐O‐(E)‐caffeoyl‐(2‐O‐(6‐O‐(E)‐feruloyl)‐β‐D‐ glucopyranosyl)‐β‐D‐glucopyranoside)‐5‐O‐(β‐D‐glucopyranoside). The results of this study may help promote the purification of high molecular weight acylated anthocyanins from purple sweet potato as well as from other plant materials in nature.     

基于机器视觉的机车齿轮毂全自动双轴拧紧机的设计和应用

设计了基于机器视觉的机车齿轮毂全自动双轴拧紧机,根据拧紧工艺和扭矩控制原理实现对螺栓拧紧力矩的控制;通过丝杠变径机构,实现不同规格齿轮毂螺栓拧紧;利用机器视觉实现螺栓位置的识别以及初始位置的确定;讨论了自动拧紧机控制系统的硬件组成和软件系统配置,并介绍了防错、防漏功能的设计流程。螺栓自动拧紧机可提高装配精度和操作效率,降低工人的劳动强度。     

风速时间序列混沌判定方法比较研究

混沌识别是对非线性时间序列进行混沌预测的前提。针对时间序列风速确定性与随机性相结合的复杂非线性特征,研究了不同的混沌识别方法,并对风速时间序列进行混沌特征识别。应用随机噪声、周期运动及经典混沌系统的时间序列对所选方法进行可靠性验证。对美国国家风能研究中心M2测风塔实测时间序列风速数据进行非线性混沌特征识别。结果表明:风速时间序列具有明显的混沌特征;各风速时间序列表现出不同程度的混沌特征;各混沌识别方法对风速时间序列混沌特征的表达形式不同,互为补充,相互验证。     

Structural optimization with an automatic mode identification method for tracking the local vibration mode

Traditional optimization methods, which take a specific order of modal frequency as the design constraint, could fail to obtain the desired solution because of modal substitution. An improved optimization model with continuous sizing variables is established to solve this problem, in which the minimum weight and a given local modal frequency are considered as the objective and the constraint. To capture accurately the expected mode of vibration, a local mode identification technique is proposed based on the strain energy ratio between the local area and the whole structure. With that scheme, an optimization system is developed, in which the local mode can be effectively identified and the constraint can be updated with it in the iteration process. Two numerical examples, of a reinforced plate and a satellite structure, are applied to illustrate the effectiveness and efficacy of the proposed method.