Nonlinear adaptive filtering using kernel‐based algorithms with dictionary adaptation

Nonlinear adaptive filtering has been extensively studied in the literature, using, for example, Volterra filters or neural networks. Recently, kernel methods have been offering an interesting alternative because they provide a simple extension of linear algorithms to the nonlinear case. The main drawback of online system identification with kernel methods is that the filter complexity increases with time, a limitation resulting from the representer theorem, which states that all past input vectors are required. To overcome this drawback, a particular subset of these input vectors (called dictionary) must be selected to ensure complexity control and good performance. Up to now, all authors considered that, after being introduced into the dictionary, elements stay unchanged even if, because of nonstationarity, they become useless to predict the system output. The objective of this paper is to present an adaptation scheme of dictionary elements, which are considered here as adjustable model parameters, by deriving a gradient‐based method under collinearity constraints. The main interest is to ensure a better tracking performance. To evaluate our approach, dictionary adaptation is introduced into three well‐known kernel‐based adaptive algorithms: kernel recursive least squares, kernel normalized least mean squares, and kernel affine projection. The performance is evaluated on nonlinear adaptive filtering of simulated and real data sets. As confirmed by experiments, our dictionary adaptation scheme allows either complexity reduction or a decrease of the instantaneous quadratic error, or both simultaneously. Copyright © 2015 John Wiley & Sons, Ltd.     

Effects of the ARCS-V-based motivational strategies on online learners' academic performance,motivation, volition,and course interest

This exploratory experimental study investigates the impact of motivational strategies based on the Attention, Relevance, Confidence, Satisfaction, and Volition (ARCS-V) model on online learners' academic performance, motivation, volition, and course interest. The research was conducted over an 11-week semester with 122 undergraduate online learners within two groups. One group received a traditional e-course, while the other group was offered the course with extra motivational strategies derived from the ARCS-V model. The results revealed that the group who used motivational strategies showed significantly higher gains in motivation, academic performance, and course interest scores. However, there were no significant differences between the groups regarding the volition. Furthermore, the motivation and interest variables were measured with Attention, Relevance, Confidence, and Satisfaction subscales of the ARCS-V model. In terms of interest variable, there was only a statistically significant difference on the Attention subscale. Regarding motivation variable, the results also showed a statistically significant difference on the attention, confidence, and satisfaction subsections of the ARCS-V model. The findings of the present study offer insights into ARCSV model-based research by examining the effects of the model as a valid and reliable framework for online learning environments. The implications and directions for future research are then discussed.     

上榆泉煤矿煤泥水多参数在线检测系统应用研究

针对上榆泉煤矿煤泥水性质参数人工检测周期长、误差大、滞后性严重的问题,采用多参数传感器和PLC,开发了煤泥水多参数在线检测系统。经过8 h稳定运行,平均结果显示该厂煤泥水参数为pH值为7.71、浓度9.45%、中值直径(D50)39.56μm、流量2 440 m3/h、水质硬度428.94 mg/L,与人工检测结果相一致。应用结果表明,该检测系统能够实现煤泥水多参数在线监测和数据分析功能,使煤泥水的处理更高效。     

瓦斯压力在线监测预警机制应用研究

为了能准确、有效、及时的预测预报井下煤矿瓦斯突出,根据高瓦斯煤层应力场与瓦斯场具有典型的耦合效应,且瓦斯压力场与地应力场的关系主要表现在瓦斯压力的变化上这一原理,并在平煤股份十矿己15-16煤层和己17煤层安装一套煤矿瓦斯突出灾害实时监测预警系统,利用该系统中的煤层瓦斯压力实时监测功能实时在线监测揭煤区域煤层瓦斯压力变化情况,结果表明：煤层瓦斯压力变化随着瓦斯抽放时间而降低,而随着瓦斯解吸量的增加升高；监控到的瓦斯突出煤层瓦斯压力的变化符合正常规律,开发的煤矿瓦斯突出灾害监测预警系统能够连续监测煤层瓦斯压力及其变化动态,为煤矿瓦斯突出灾害监测预警提供了技术基础和有效手段。     

我国建筑石料用灰岩采矿权成交价变化分析

砂石资源采矿权出让收益是地方财政收入的重要来源。近年来,砂石资源供应紧张价格大幅上涨的背景下,本文以典型的砂石资源建筑石料用灰岩为例,分析了全国及部分典型省份建筑石料用灰岩采矿权成交价的变化特征,主要结论是2011～2018年我国建筑石料用灰岩采矿权平均成交单价与砂石市场供应价格均呈上升趋势但前者涨幅远高于后者,并且采矿权成交单价的区间分布结构年度变化差异也较大,不同区域平均成交单价年度变化规律分异明显,贵州、甘肃两省采矿权成交单价相对较低且变化幅度相对较小,山西、吉林、湖北、广西4省采矿权成交单价相对较高且变化幅度相对较大。最后,从平抑砂石价格过快上涨、加强矿业权市场建设、促进砂石资源区域供需平衡、维护良好砂石市场价格秩序的角度提出了有关政策建议。     

电信专业学术英文写作模块化教学实践

学术英文写作是当今电子信息专业研究生必修的一门课程。然而传统的以教师为中心的灌输式教学已不能跟上网络迅猛发展的趋势,尤其是当疫情来临的特殊形势下。此外,现有的学术英文写作教学研究仅提供宏观的设计,缺乏具体的实际可操作性。为此,本文以引言写作逻辑为教学模块案例,探索了如何充分利用网络资源的优势,开展以学生为中心的课前课中课下有机融合的灵活的教学设计。所探索的引言写作技巧和详实的教学设计,为模块化网络教学提供一个切实可行的参考方案。     

基于同轴图像传感的激光焊接过程质量监测技术

针对激光焊接过程中由于参数不匹配、装配误差等原因造成的焊接过程不稳定等焊接缺陷，基于同轴图像传感技术，建立起一套激光焊接过程中的质量在线监测系统，对焊接过程中的熔池图像进行了采集分析及其熔池特征信息的提取. 结果表明，在激光功率为1 500 W的不等厚不锈钢薄板激光焊接试验条件下，焊接过程中的不稳定、下塌缺陷以及焊偏现象与熔池形状各特征信息变化具有一定的相关性. 结合BP神经网络算法对所提特征信息进行分类、识别，基于LabVIEW软件平台，可实现相应缺陷的自动化识别及报警功能.     

A review on ultrasonic spot welding of copper alloys

As a solid state joining process, ultrasonic spot welding has been proven to be a promising technique for joining copper alloys. However, challenges still remain in employing ultrasonic spot welding to join copper alloys. This article comprehensively reviews the current state of ultrasonic spot welding of copper alloys with a number of critical issues including materials flow, plastic deformation, temperature distribution, vibration, relative motion, vertical displacement, interface friction coefficient, online monitoring technique, coupled with the macrostructure and microstructure, the mechanical properties and electrical conductivity. In addition, the future trends in this field are provided.     

印尼BAYAH电厂一次风机故障原因分析与处理

本文针对印尼BAYAH电厂一次风机设备故障，详细的分析了故障产生的原因，介绍了三点法找转子动平衡和工装车削式在线修复电机滑环工法，阐述了两种工法的原理以及实施步骤。     

基于小波分析的谐波在线监测系统

针对传统谐波在线监测系统存的结果不准确，无法描述谐波动态变化特点，设计了基于小波分析的谐波在线监测系统。首先设计了谐波在线监测系统的硬件模块，然后谐波在线监测系统的软件模块，依据小波变换分析谐波信号特征，得到的谐波变化率，从而谐波在线监测系统的监测结果，最后采用具体实验进行了谐波在线监测系统性能的仿真实验，由实验结果可知，该系统的谐波监测精度高，可以有效检测各种谐波分量，保证电力系统稳定运行。