Analysis of the Reform of Ideological and Political Education in College English Curriculum from the Perspective of“Cultural Confidence”

With the rapid development of the education industry,higher requirements have been put forward for college English education and teaching,accelerating the pace of college English reform.Issues such as how to integrate knowledge transmission,language expression skill improvement,cultural element extraction,and ideological and political education,and present the role of curriculum education function have attracted attention.In the era of informatization,college students’thinking has undergone certain changes and gradually developed towards diversification.Therefore,universities should start from the perspective of cultural confidence,extract valuable ideological and political elements,and explore effective tourism ideological and political teaching methods.While helping college students enhance their cultural confidence,it is also beneficial for them to better inherit traditional Chinese culture.This article conducts an in-depth exploration of ideological and political education in college English courses from the perspective of“cultural confidence”and uses scientific and effective measures to solve the problems encountered,aiming to provide valuable guidelines for relevant researchers.

Maximum confidence measurements via probabilistic quantum cloning

Probabilistic quantum cloning（PQC） cannot copy a set of linearly dependent quantum states.In this paper,we show that if incorrect copies are allowed to be produced,linearly dependent quantum states may also be cloned by the PQC.By exploiting this kind of PQC to clone a special set of three linearly dependent quantum states,we derive the upper bound of the maximum confidence measure of a set.An explicit transformation of the maximum confidence measure is presented.

Confidence Level Based on Ridge Estimator in Process Measurement and Its Application

Ordinary least squares(OLS) algorithm is widely applied in process measurement, because the sensor model used to estimate unknown parameters can be approximated through multivariate linear model. However, with few or noisy data or multi-collinearity, unbiased OLS leads to large variance. Biased estimators, especially ridge estimator, have been introduced to improve OLS by trading bias for variance. Ridge estimator is feasible as an estimator with smaller variance. At the same confidence level, with additive noise as the normal random variable, the less variance one estimator has, the shorter the two-sided symmetric confidence interval is. However, this finding is limited to the unbiased estimator and few studies analyze and compare the confidence levels between ridge estimator and OLS. This paper derives the matrix of ridge parameters under necessary and sufficient conditions based on which ridge estimator is superior to OLS in terms of mean squares error matrix, rather than mean squares error.Then the confidence levels between ridge estimator and OLS are compared under the condition of OLS fixed symmetric confidence interval, rather than the criteria for evaluating the validity of different unbiased estimators. We conclude that the confidence level of ridge estimator can not be directly compared with that of OLS based on the criteria available for unbiased estimators, which is verified by a simulation and a laboratory scale experiment on a single parameter measurement.

Standardized Distance from the Mean to the Median as a Measure of Skewness

The normal distribution, which has a symmetric and middle-tailed profile, is one of the most important distributions in probability theory, parametric inference, and description of quantitative variables. However, there are many non-normal distributions and knowledge of a non-zero bias allows their identification and decision making regarding the use of techniques and corrections. Pearson’s skewness coefficient defined as the standardized signed distance from the arithmetic mean to the median is very simple to calculate and clear to interpret from the normal distribution model, making it an excellent measure to evaluate this assumption, complemented with the visual inspection by means of a histogram and a box-and-whisker plot. From its variant without tripling the numerator or Yule’s skewness coefficient, the objective of this methodological article is to facilitate the use of this latter measure, presenting how to obtain asymptotic and bootstrap confidence intervals for its interpretation. Not only are the formulas shown, but they are applied with an example using R program. A general rule of interpretation of ∓0.1 has been suggested, but this can only become relevant when contextualized in relation to sample size and a measure of skewness with a population or parametric value of zero. For this purpose, intervals with confidence levels of 90%, 95% and 99% were estimated with 10,000 draws at random with replacement from 57 normally distributed samples-population with different sample sizes. The article closes with suggestions for the use of this measure of skewness.

Confidence support vector domain description

To accelerate the training of support vector domain description （SVDD）, confidence support vector domain description （CSVDD） is proposed based on the observation that the description boundary is determined by a small subset of training data called support vectors. Namely, the number of training samples in the userdefined sphere is calculated and taken as the confidence measure, according to which the training samples are ranked in ascending order. Those former ranked ones are selected as the boundary targets for the SVDD training. Simulations on UCI data demonstrate the effectiveness and superiority of CSVDD： the number of training targets and the training time are reduced without any loss of accuracy.

A Bootstrapping Approach for Software Reliability Measurement Based on a Discretized NHPP Model

Discrete software reliability measurement has a proper characteristic for describing a software reliability growth process which depends on a unit of the software fault-detection period, such as the number of test runs, the number of executed test cases. This paper discusses discrete software reliability measurement based on a discretized nonhomogeneous Poisson process (NHPP) model. Especially, we use a bootstrapping method in our discrete software reliability measurement for discussing the statistical inference on parameters and software reliability assessment measures of our model. Finally we show numerical examples of interval estimations based on our bootstrapping method for the several software reliability assessment measures by using actual data.

Relative Irradiance Measurement and Bonding Configurations of Amorphous Fluorinated Carbon Films Deposited by Electron Cyclotron Resonance Plasma

a-C:F films are deposited by microwave electron cyclotron resonance (ECR)plasma chemical vapor deposition (CVD) using trifluoromethane (CHF3) and benzene (C6H6) as source gases at different microwave powers. The radicals in plasma originating from source gases dissociation are analyzed by relative irradiance measurement. The bonding configurations and binding state of a-C:F films are measured with Fourier-transformed infrared spectrometer (FTIR) and x-ray photoelectron spectroscopy (XPS). The results show that a-C:F films are mainly composed of CF radical at lower powers but of CF2 radical at higher powers. The deposition of films is related to the radicals generated in plasma and the main bonding configurations are dependent on the ratio of CF to CF2 radicals in films.

CMS实测地下矿采空区建模及稳定性分析研究

传统的采空区稳定性分析建立的数值分析模型,对空区的形状进行过多的简化,使得建立的空区模型过于简单,稳定性分析的结果可靠性较差。借助三维激光空区监测系统对地下矿山采空区进行三维扫描,精确的获取激光头到空区边界的距离。将全站仪测量的定位点坐标输入到CMSposprocess处理软件,将生成的数据输入到矿业工程软件3Dmine中建立起空区的实际赋存模型。研究用VC++编写出可以将3Dmine软件输出的块体质心点坐标直接导入有限差分软件FLAC3D中的应用程序,从而建立起空区力学模型,形成从实测模型到力学计算模型的新方法,大大提高了采空区稳定性分析的准确性和可靠性。结合石人沟铁矿空区稳定性分析工程实践,对石人沟铁矿-60 m水平南区空区进行静力计算,分析空区稳定性,获得了良好效果。

基于M-CM的建筑施工企业现场安全管理成熟度评价

为了有效提高建筑施工企业现场安全管理的效率,使企业能够明确自身现场安全管理的状况,保证安全管理的有序进行,借鉴项目管理成熟度模型（K-PMMM）和软件成熟度模型（CMM）,构建建筑施工企业现场安全管理成熟度评价指标体系。考虑指标之间的关联性和评价过程的模糊性、随机性,同时使调查问卷统计数据的信息量得到充分表达,分别运用测量模型确定评价指标的权重和云模型进行成熟度评价,构建基于测量-云模型（M-CM）的建筑施工企业现场安全管理成熟度评价模型,并利用MATLAB进行仿真分析。将模型应用到实际建筑工程项目中,结果表明,该工程项目的成熟度等级为可管理级,评价结果与现场实际情况相吻合。

基于未确知测度理论的矿井巷道安全风险评价分析

矿井巷道的安全性是保证矿山掘进与煤炭开采的重要保障之一,对其进行安全风险评价也是工程开展过程中不可或缺的关键环节。过往的评价方法往往更依赖于主观的定性分析,缺乏定量以及对各影响因素之间的主次关系考虑。基于此,从人、机、环、管4个方面出发,选取其中17个关键影响因素,运用未确知测度理论,科学建立了矿井巷道的安全评价体系;利用熵权法计算各影响因素的权重,再依据置信度识别准则对结果进行科学判定;最终对结果进行重要性排序,构建基于未确知测度理论的矿井巷道安全风险评价方法。结合工程实例分析结果表明,该评价方法客观全面,能够准确判别影响巷道安全状态的关键因素,与工程实际情况基本相符,证明该方法具有较高的准确性以及实际应用价值,可用于类似条件矿井巷道的综合安全评价。

大学生红色文化教育的意义、内容和路径研究

近年来,新时代的大学生红色文化教育已受到越来越多的关注与重视。开展红色教育是推进德育的重要举措,有利于实现大学生的全人素质的发展。红色文化在大学生教育中的应用,不仅能够丰富校园文化内涵,也能够促进大学生思想观念的进一步升华与变革。在这个信息快速发展和快节奏的时代,红色文化教育可以为大学生提供一个德育理念和实践的新视角。因此,大力加强新时代大学生红色文化教育,对于发展青年精神和智慧、增强中国大学生竞争力、营造和谐社会氛围,都具有重要意义。该文从新时代背景出发,结合红色文化教育的意义,对新时代大学生红色文化教育进行深入探析,讨论其内容,提出加强新时代大学生红色文化教育的策略。

基于CM的高分辨率遥感影像目标边缘提取

为了利用形态学思想进行彩色图像处理,将传统形态学扩展到彩色图像处理领域,并提出了一种利用彩色形态学进行高分辨率遥感影像目标边缘提取的方法。在RGB彩色空间中,利用矢量间距离和角度定义其相似性测度,以刻画与人类视觉感知相一致的彩色相似性。以上述相似性测度为准则,结合上确界、下确界构建彩色形态学的基本操作,包括膨胀、腐蚀、开、闭运算等。最后将提出的彩色形态学应用于高分辨率遥感影像处理及目标边缘提取,以验证其实用性和有效性。通过高分辨率遥感影像的仿真表明,其不仅对地物目标具有较好形变和平滑能力,而且能较好的提取遥感影像的目标边缘,为彩色形态学的应用奠定基础。

Bootstrap generated confidence interval for time averaged measure

In the simulation output analysis,there are some measures that should be calculated by time average concept such as the mean queue length.Especially,the confidence interval of those measures might be required for statistical analysis.In this situation,the traditional method that utilizes the central limit theorem(CLT)is inapplicable if the output data set has autocorrelation structure.The bootstrap is one of the most suitable methods which can reflect the autocorrelated phenomena in statistical analysis.Therefore,the confidence interval for a time averaged measure having autocorrelation structure can also be calculated by the bootstrap methods.This study introduces the method that constructs these confidence intervals applying the bootstraps.The bootstraps proposed are the threshold bootstrap(TB),the moving block bootstrap(MBB)and stationary bootstrap(SB).Finally,some numerical examples will be provided for verification.

基于美国FAERS数据库的达比加群酯不良反应信号挖掘研究

目的挖掘达比加群酯的药品不良反应(ADR)信号,为其临床使用安全性提供参考依据。方法基于美国食品药品监督管理局(FDA)不良事件报告系统(FAERS),联合报告比值比法(ROR)、比例报告比值法(PRR)、综合标准法(MHRA)和贝叶斯置信度递进神经网络法(BCPNN)对FAERS中2010年10月至2022年12月上报的达比加群酯ADR报告进行数据挖掘,分析相关ADR信号分布及信号强度,并深入分析不同部位出血相关ADR情况。结果共筛选出达比加群酯不良反应例次155881例,ADR信号783个,映射到27个系统器官,最多的系统器官为胃肠系统,排名前三的强信号分别为胃肠出血、脑血管意外和出血。药品说明书未收载的ADR包括有脑血管意外、跌倒、缺血性脑卒中、急性肾损伤、房颤等。同时得到出血相关ADR数31669例,以胃肠系统,神经系统、血管和淋巴系统等出血为主。结论达比加群酯在临床使用过程中应重点关注出血相关ADR,尤其是胃肠出血,同时应警惕说明书中未记录的ADR,并做好相关事件的应对措施。

改进的多标签深度森林算法研究

多标签深度森林(Multi-Label Deep Forest,MLDF)是一种基于深度森林的深度集成学习模型。为了限制模型的复杂度以及用户可以根据需求优化评价指标,多标签深度森林使用了两种算法:度量感知特征重用与度量感知层增长。前者重用前一层较好的特征,后者用于限制模型增长,然而度量感知特征重用算法使用当前层的输出取算术平均值来计算置信度,忽略了各个森林的精度差异造成的影响。因此,提出一种改进的度量感知特征重用算法,为每个森林在每个标签上赋予权重来计算置信度。实验结果表明,改进的算法在低维多标签数据集上有一定的提升。

基于改进未知测度的煤矿坚硬断层深孔爆破效果评价

煤矿井下坚硬断层深孔预裂爆破效果影响因素众多且具有不确定性,为了提高坚硬断层深孔预裂爆破效果评价的准确性,本文通过引入未知测度理论建立了从爆破质量、施工安全性及经济效益三个方面评价煤矿井下爆破效果的评价指标体系。将序关系分析法(G1法)确定的主观权重和熵权法(EW法)计算的客观权重耦合成综合权重改进权重计算模型,并采用置信度识别准则代替最大隶属度准则调整评级判定,并将该改进的评价模型运用到孙村煤矿深孔预裂爆破效果评价实践中,得出的爆破质量、施工安全性、经济效益对应的综合权重分别为0.503、0.274、0.223,置信度为0.856,对应该煤矿爆破效果等级为“好”,并从岩石裂隙发育程度、粉碎区范围和爆破振动三个方面给出了进一步提高爆破效果的建议。研究结果表明:该评价模型的结果与实际施工情况高度吻合,可为坚硬断层深孔预裂爆破效果评价提供新的参考。

影响燃气表计量结果的多种因素统计分析

本文旨在探究燃气表计量工作中的关键影响因素,包括检定人员、进气方式和工位,通过分析这些因素对计量结果的影响,提高燃气表的计量准确性和稳定性。首先,采用置信区间进行统计推断检定人员对检定结果的影响;然后,采用双样本T检验,比较左侧进气方式和右侧进气方式的合格率是否存在显著差异;最后,采用方差分析来分析工位对合格率的影响。结果表明,检定人员、进气方式、工位对燃气表计量结果造成的影响差异不显著。

基于阻抗测量的共模扼流圈高频建模

共模扼流圈是EMI滤波器的核心元件,它的高频特征极大地影响了EMI滤波器抑制传导EMI噪声的性能,有必要建立共模扼流圈的高频模型,以便更准确地评估和预测EMI滤波器的性能。本文提出了基于150kHz～30MHz频率范围内的阻抗测量实现的共模扼流圈高频建模方法,并通过一个实例给出了它的高频集总参数模型,该模型包括了共模电感、差模电感、寄生绕组电容和等效的损耗阻抗等参数。最后通过比较共模扼流圈插入损耗的测量结果和仿真结果,证实了本文所提出的共模扼流圈高频建模方法。

基于兴趣度含正负项目的关联规则挖掘方法

项目的引入使得挖掘出的频繁项集成倍增加,同时生成的关联规则数量更加庞大,引入兴趣度来约束从频繁项集中提取关联规则的数量。分析现有的兴趣度模型,从中选择了一种适合于含正负项目的关联规则挖掘的兴趣度方法,并且提出了置信度的一个性质,描述了含正负项目的频繁项集挖掘关联规则的算法,并对矛盾关联规则进行了分析。实验结果表明,该算法是有效和可行的。

关键词检测系统中基于音素网格的置信度计算

该文提出了一种基于音素网格的置信度计算方法。与传统的基于整个声学模型的置信度不同的是,这种方法在解码器生成的音素网格上计算关键词的置信度,从而具有更好的拒识能力。另外,针对两种置信度取值范围的不同,该文采用权重因子的方法综合利用两种置信度,取得了较好的效果。在自然对话的电话数据测试中,与传统的置信度计算方式相比,混和置信度的FOM(Figure Of Merit)值相对提高了17.0%。