Risk assessment of high-speed railway CTC system based on improved game theory and cloud model

Purpose-In order to solve the problem of inaccurate calculation of index weights,subjectivity and uncertainty of index assessment in the risk assessment process,this study aims to propose a scientific and reasonable centralized traffic control(CTC)system risk assessment method.Design/methodologylapproach-First,system-theoretic process analysis(STPA)is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis.Then,to enhance the accuracy of weight calculation,the fuzzy analytical hierarchy process(FAHP),fuzzy decision-making trial and evaluation laboratory(FDEMATEL)and entropy weight method are employed to calculate the subjective weight,relative weight and objective weight of each index.These three types of weights are combined using game theory to obtain the combined weight for each index.To reduce subjectivity and uncertainty in the assessment process,the backward cloud generator method is utilized to obtain the numerical character(NC)of the cloud model for each index.The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system.This cloud model is used to obtain the CTC system's comprehensive risk assessment.The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud.Finally,this process yields the risk assessment results for the CTC system.Findings-The cloud model can handle the subjectivity and fuzziness in the risk assessment process well.The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/value-This study provides a cloud model-based method for risk assessment of CTC systems,which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment,achieving effective risk assessment of CTC systems.It can provide a reference and theoretical basis for risk management of the CTC system.

Research on Modelling Digital Paper-cut Preservation

This paper studies the model of the digital preservation of paper-cut after analyzing the state-of-the-art of the preservation of intangible cultural heritage at home and abroad, focusing on paper-cutting in Hebei, China in a comprehensive approach of sociology, anthropology, folk art, folklore, communication, computer, and information science. Models, methods, and solutions for the preservation and retention of national and folk cultural heritage are proposed. A virtual multimedia interactive system framework of the digital preservation of national and folk cultural heritage is constructed. The standards of paper-cut digitization are studied. The main content of the paper involves： regulated data collection and recording of the scattered Chinese folk paper-cut works in Hebei; digitization, optimization, compression, classification, icon and pattern extraction, vectorization, and work analysis of the first-hand material. This paper also investigates the demonstration, dissemination, database construction, and retrieval of the classified material, icons, and patterns; the demonstration of the reconstruction and application of icon and pattern database; the design and development of an immersive virtual gaming platform of the multi-media scenes and production process of folk paper-cut.

Call for papers of the special issue on Animal Models and Infectious Diseases

Primates and animal models are major areas of coverage for Zoological Research （ZR）. Over the past few years, ZR has released a series of special issues/topics addressing various aspects of these areas, e.g., ge- netics, immunology, and physiology neuroscience. A special issue for 2017 focusing on ＂Animal Models of Infectious Diseases＂ is under preparation and, so far, includes original research articles and reviews on filo- viruses and coxsackievirus involving guinea pigs, mice, and other species. Further to this, ZR would like to extend a very warm invitation to all peer researchers in the field to submit outstanding work to the journal on this special issue.

Stress Relaxation of a Paper Sheet under Cyclic Load: An Experimental and Theoretical Model

Mechanical experiments have been performed to study the dynamic stress relaxation of a paper sheet material mainly used in food packaging industry. The material was cyclically tensile-loaded with a strain range between 2.4% and 4%. The time period for each cycle was 400 seconds. It was found that stress will decrease when the number of cycles increases in the case of upper load and vice versa in the case of lower load. At the same time, the stress to strain curves followed the same pattern as the one from the previous cycle. The stress relaxation behavior of each cycle has been analyzed and the dynamic relaxation modulus was derived. An improved model is proposed to describe the dynamic relaxation behavior of the paper sheet. This model shows a very good fit to the experimental results and trends of prediction are observed. Furthermore, the physical description of this model and the variation by the cycles is discussed.

A MECHANICAL MODEL FOR THE DRY BASIS WEIGHT PLANT OF PAPER MAKING PROCESS

Of the two methods of getting the mathematical model of a given system,modeling and i-dentification,the first is of the advantage of“knowing it in the detailed inside”.In this paper,after the common technological process of paper making is approached,a simplified physicalimitation and the mathematical model are presented.The resulted model by means of modelingis of the same form with that through,identification by K.J.Astrom in 1970.The course ofmodel deriving is described in detail,from which one can see clearly how the minor factors ofthe dynamics are omitted and what may be included in the unmodeled dynamics.At the sametime,the limit to its usage is also given.

基于主题模型的论文标准化影响力指标研究——一个新的论文标准化影响力指标GTNI

当前学界关于论文的标准化评价指标多从学科角度分类,忽视论文主题的多样性且每一主题概率不同等问题。文章在CNCI(Category Normalized Citation Impact,学科规范化影响力)指标基础上,结合主题模型、引文分析等方法提出构建可横向比较的普适性指标GTNI(General Topic Normalized Citation Impact,基于主题模型的论文标准化影响力),以提高学术论文评价的科学性。GTNI是对论文每一主题被引进行标准化并综合而获得的指标。通过理论分析、指标构建、实证研究和对比检验,表明GTNI指标在论文影响力评价方面具有较好的效果,且具有应用前景。

现代测绘技术在古建烫样数字化项目中的应用

烫样是研究清代皇家建筑的珍贵文物,为配合文物信息数字化工作的开展,针对烫样数据的采集和处理方法进行了深入研究。在综合考虑多种数据采集方法的特点及烫样数字化记录的难点后,选择使用手持式三维扫描仪与多视角三维重建技术相结合的方式来进行烫样的基础数据采集,并通过实践总结出了一套完整的数据采集和处理工作流程。与此同时,针对成果可能的应用方式做了些许尝试,且为数据的后期维护与进一步利用拟定了数据管理系统的建设方案。

“双碳”背景下林纸绿色供应链利益分配优化模型及应用研究

在“双碳”发展背景下,考虑核心竞争能力、主观投入水平、客观贡献程度、生态绩效贡献度、风险承担强度等影响因素,构建优化夏普利值法模型,应用算例并结果分析,从研究结果可知,在林纸绿色供应链发展及利益分配过程中,首先要认识到影响因素对林纸绿色供应链的发展及利益分配的重要性。其次,要始终将绿色化贯穿林纸绿色供应链整个发展过程,充分体现林纸绿色供应链发展与“双碳”发展的目标一致性。

高校纸本图书使用者的本科生用户画像构建

以高校纸本图书使用者的本科生用户为研究对象,构建高校纸本图书的用户画像,可以更加深入地识别用户、更加有效地提升纸本图书的资源建设和服务质量,进而提升用户体验,促进学生系统、深刻阅读。选取层级标签方法来构建用户画像,在现有RFM模型的基础上,构建LRFM模型,识别出具有共同特征的用户群体,最终完成用户画像的构建。基于真实数据,对该文构建的用户画像模型进行实证,验证模型是有效的。

基于Stacking模型的学术论文多标签分类系统构建

学术论文高质量多标签自动分类是推动学术研究发展的关键程序之一。本研究利用Stacking模型将随机森林、支持向量机、极限树、极端梯度提升和神经网络五个分类器融合为一个异质集成分类器,并利用基于问题转换思想的多二分类模型将该分类器应用于学术论文多标签分类。根据学术论文的特点,依次实现了与之配套的论文特征提取模块、TF-IDF加权模块、数据预处理模块,最终构建成一个面向学术论文的多标签分类系统。仿真实验验证了本研究构建的学术论文多标签分类系统在处理学术论文多标签分类问题时,较传统的单模型分类器或同质集成模型分类器在泛化能力、稳定性与准确率方面都有一定程度的提升。图9。参考文献21。

以改进机器视觉算法构建纸张图像识别模型

为保障纸张生产加工质量,精准获取与识别纸张缺陷,以改进机器视觉算法构建了纸张图像识别模型。首先以由线阵CCD相机与双光源等构成的图像采集装备采集纸张缺陷图像,其次以改进机器视觉方法对纸张缺陷图像进行预处理分析,然后将预处理后图案以可变形卷积神经网络输入进行训练,以此检测识别纸张所存在的缺陷类型。实验测试结果表明,基于改进机器视觉算法的纸张图像识别模型可高效且精准识别缺陷,准确率高达98.4%,拥有较高识别度,可广泛推广以投入实际运用。

ARCS动机模型混合学习造纸英语听力App设计与开发

ARCS动机模型是1987年美国学者研究并提出的。信息技术的迅速发展,促使该动机模型在多媒体产品开发、课件设计及教育App领域得以广泛应用,并以此来调动学习者的积极性。依托ARCS动机模型对造纸英语听力App进行设计的主要目的是提升学习者对时间的利用率和学习满意度。基于此,针对用户对造纸英语听力App的学习需求,与现有技术相结合,对当前只限于“速记”“跟读”的学习英语听力App进行创新,提供新的研发思路与方向。

基于古籍保护的纸质文献VR系统转化模型构建研究

纸质古籍文献的数字化、虚拟化转化是当前我国古籍保护工作的重点方向之一。基于此,基于B/S架构搭建了一种纸质古籍文献向VR系统转化的模型,该模型包含三个核心层和一个辅助层,详细分析了该模型的关键业务逻辑包括古籍的图像采集和预处理、阅读信息定位、阅读信息提取等,并对该系统的工作情况进行测试。结果表明:在搭建的测试环境下,该转化系统对古籍纸质文献文字的采集准确率可达96.4%,系统综合延迟低于1.6ms,是一种较为理想的纸质古籍文献VR转化模型。

基于二元相关退化的动车组车载变压器油纸绝缘剩余寿命预测

针对动车组车载变压器油纸绝缘剩余寿命预测中单性能退化指标难以全面反映油纸绝缘退化过程的问题,考虑车载变压器油纸绝缘退化的个体差异性及两性能指标间的相关关系,提出了基于Copula函数的两性能指标相关退化的油纸绝缘剩余寿命预测方法:采用具有随机效应的维纳过程建立油纸绝缘的两性能指标相关退化模型,基于赤池信息准则(Akaike Information Criterion, AIC)选择拟合效果更优的Copula函数来描述两性能指标间的相关关系,采用最大似然估计法估计初始时刻的模型参数,基于序列贝叶斯更新方法在线更新退化模型中的漂移系数,以实现油纸绝缘剩余寿命的在线预测。最后以加速热老化试验下油纸绝缘的聚合度和抗拉强度的退化数据进行实例验证。结果表明,两性能指标相关退化模型比单性能指标退化模型的剩余寿命预测值与实际值之间的平均绝对误差更小,预测的准确性更高,且随着模型参数不断更新,剩余寿命的预测值与实际值间的绝对误差在不断减小,预测结果的准确性在不断提升。

基于Kano-FAST的瓦楞纸激光印刷设备设计研究

目的推动印刷行业朝更高效的方向迈进,提高印刷设备的易操作性和视觉识别性。方法将Kano和FAST(Function Analysis System Technique)模型引入瓦楞纸激光打印设备设计的前期应用需求分析中,通过问卷的方法获取用户的基本要求,并划分为几个子类型,进而建立Kano的二维功能属性模型。采用FAST法建立功能树,辅助使用Kano模型,从而更精准地分析用户需求,并更好地根据其需求进行优化设计。结果综合运用设计原理,针对性地挖掘瓦楞纸激光印刷设备在造型识别性、操作易用性、生产安全性上存在的问题,进而输出更优解。结论该设计方法的引入有助于为同类型的印刷设备设计提供参考,并引起更多相关厂家的重视,推动印刷行业向更积极的方向发展。

福建省造纸工业碳排放的灰色关联度、Tapio脱钩分析及情景预测

随着中国2030年前“碳达峰”目标的临近,福建省高能耗、高排放的造纸工业面临严峻的碳减排压力。本研究运用灰色关联度模型,计算总资产、总资产产值率、能源强度和能源结构与CO_(2)排放之间的关联度,通过Tapio脱钩模型,确定造纸工业产出与CO_(2)排放的脱钩状态,利用STIRPAT模型,预测4种情景下CO_(2)排放量,评估福建省造纸工业2030年前实现“碳达峰”目标的潜力。结果表明:(1)福建省造纸工业的总资产、总资产产值率、能源强度和能源结构与CO_(2)排放量关联度相近,且关联性较高;(2) 2007—2021年,福建省造纸工业产出与碳排放呈现6种脱钩状态,在研究期内的大多数年份表现为强脱钩与弱脱钩状态;总资产和能源结构对碳排放起到主要的拉动作用,能源强度是碳排放脱钩的主要驱动力;(3)预测期内(2022—2030年)基准情景与快速发展情景下CO_(2)排放量快速上升,低碳发展情景下CO_(2)排放量增长率相对较低,强低碳发展情景下CO_(2)排放量呈现非常缓慢的上升趋势。最后对降低福建省造纸工业碳排放,促进造纸工业可持续发展提出建议。

造纸机能耗优化模型设计及其计算机部署

为降低造纸机干燥部在运行过程中的能量消耗,节约造纸企业的生产成本,采集造纸机干燥部运行状态数据并通过调整异常值、滤波分析等手段对数据进行预处理。在此基础上,对预处理数据进行单变量分析,进而提取出与目标变量相关的特征变量,并采用随机森林法建立造纸机能耗优化模型。为验证造纸机能耗优化模型的实用性,为该模型建立了一套基于数据库和服务器技术的干燥部能耗优化系统,展示了该系统的客户端操作界面设计效果。根据系统显示的分析结果可知,造纸机能耗优化模型能够有效降低造纸企业的吨纸消耗成本。

基于特征点配准的真伪卷烟商标纸鉴别

为提高真伪卷烟商标纸鉴别的准确性和效率,降低鉴别的经验要求和主观性,提出一种基于特征点配准的真伪卷烟商标纸鉴别方法。使用一致的标准扫描采集卷烟样品图像,基于尺度不变特征转换算法提取图像特征点,通过特征匹配和基于单应性变换的图像配准获取判别预测变量。采用逻辑回归、梯度提升分类决策树算法构建二元分类模型对图像样本进行训练和评估。在64个卷烟规格、2 918个样本数据集上进行实验,该方法准确率高于95%。通过对比实验验证了该方法的稳定性和有效性。

造纸机干燥部排风系统节能优化设计研究

为实现针对造纸机干燥部排风系统的节能优化,降低造纸企业的生产经营成本,收集了某造纸企业提供的干燥部信息管理系统数据并建立了服务于排风系统节能优化的弹性网络模型。通过该模型对干燥部排风系统内各个排风机的排风温湿度进行预测,发现弹性网络模型对排风机排风温湿度的预测效果显著优于支持向量回归模型。因此,基于弹性网络的节能优化模型应用于110 g/m^(2)红杉纸、90 g/m^(2)挂面箱板纸、120 g/m^(2)挂面箱板纸等3条产品线的排风系统参数调节工作中。根据生产应用结果发现,3条纸张产品生产线经过参数调节后的吨绝干纸干燥成本依次下降了0.72%、0.68%、1.07%,体现出了较为理想的节能优化效果。

基于YOLOv8的女西裤板型弊病检测与修正

在服装定制成衣试穿环节,由于人体体型多样性,经常出现服装试穿不合身的情况。为协助改衣师快速准确找到板型问题及修改方案,以女西裤为例,收集常见的女西裤弊病图像(前裆堆量明显、前裆猫须明显、后片夹裆和后片大腿根堆斜褶明显)作为数据集,并采用深度学习算法中的YOLOv8模型进行实验。研究表明:模型测试阶段,精确度、召回率、平均精度均值(I_(ou)=50%)均达到98%以上,同时结合弊病修正实验验证了弊病修正建议的合理性,实现了女西裤板型弊病的智能检测与修正。