Research and design of an expert diagnosis system for rail vehicle driven by data mechanism models

Purpose-The aim of this work is to research and design an expert diagnosis system for rail vehicle driven by data mechanism models.Design/methodology/approach-The expert diagnosis system utilizes statistical and deep learning methods to model the real-time status and historical data features of rail vehicle.Based on data mechanism models,it predicts the lifespan of key components,evaluates the health status of the vehicle and achieves intelligent monitoring and diagnosis of rail vehicle.Findings-The actual operation effect of this system shows that it has improved the intelligent level of the rail vehicle monitoring system,which helps operators to monitor the operation of vehicle online,predict potential risks and faults of vehicle and ensure the smooth and safe operation of vehicle.Originality/value-This system improves the efficiency of rail vehicle operation,scheduling and maintenance through intelligent monitoring and diagnosis of rail vehicle.

我国高校大数据治理能力成熟度模型的构建与实践——基于CMM与ISM融合研究的视角

构建科学有效的高校大数据治理评价模型,对激活大数据在教育数字化转型中的核心驱动作用,发挥高校在教育数字化转型中的引领示范作用具有重要意义。基于此,基于高校大数据治理的核心要素,通过融合解释结构模型(ISM)和能力成熟度模型(CMM)两种研究方法,以ISM的层次结构划分逻辑、核心要素在层次结构中的分布情况等量化手段,强化在CMM构建过程中,划分成熟度等级、确定关键过程域、明晰成熟度等级和关键过程域的对应关系等主要环节的科学性与合理性,构建出包括5个成熟度级别、21项关键过程域在内的我国高校大数据治理能力成熟度模型。同时,基于2022年浙江省高校信息化建设评估项目数据,采取分层抽样法抽取30所高校开展模型的实践应用,以期为高校大数据治理评价研究提供参考。

基于Design-Expert的电链锯锯齿结构参数优化

为提高电链锯的锯切效率,对电链锯锯齿的齿形结构参数进行研究,以单位锯切功为电链锯锯切效率的衡量指标,通过对电链锯锯切过程的仿真研究,得出不同结构锯齿的单位锯切功。以电链锯锯齿中的外形前角、侧刃楔角和顶刃楔角等结构参数作为影响因子,采用Box-Benhnken中心组合试验方法设计多因素正交试验,使用Design-expert软件进行数据分析得出最优齿形结构参数组合。研究结果表明,所选取的齿形结构参数对单位锯切功影响程度由大到小顺序依次为外形前角、侧刃楔角、顶刃楔角,并获得最优齿形结构参数组合,外形前角为10.92°、侧刃楔角为45.7°、顶刃楔角为45.41°。

Prediction System for Diagnosis and Detection of Coronavirus Disease-2019(COVID-19):A Fuzzy-Soft Expert System

In early December 2019,a new virus named“2019 novel coronavirus(2019-nCoV)”appeared in Wuhan,China.The disease quickly spread worldwide,resulting in the COVID-19 pandemic.In the currentwork,we will propose a novel fuzzy softmodal(i.e.,fuzzy-soft expert system)for early detection of COVID-19.Themain construction of the fuzzy-soft expert systemconsists of five portions.The exploratory study includes sixty patients(i.e.,fortymales and twenty females)with symptoms similar to COVID-19 in(Nanjing Chest Hospital,Department of Respiratory,China).The proposed fuzzy-soft expert systemdepended on five symptoms of COVID-19(i.e.,shortness of breath,sore throat,cough,fever,and age).We will use the algorithm proposed by Kong et al.to detect these patients who may suffer from COVID-19.In this way,the present system is beneficial to help the physician decide if there is any patient who has COVID-19 or not.Finally,we present the comparison between the present system and the fuzzy expert system.

Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-SpeedWire Rod Finishing Mills

The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise.As complex system-level equipment,it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring.To solve the above problems,an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper.First,based on its mechanical structure,time and frequency domain analysis are improved in fault feature extraction.The approach of combining virtual value,peak value with kurtosis value index,is adopted in time domain analysis.Speed adjustment and side frequency analysis are proposed in frequency domain analysis to obtain accurate component characteristic frequency and its corresponding sideband.Then,according to time and frequency domain characteristics,fault location based on expert experience is proposed to get an accurate fault result.Finally,the proposed method is implemented in the equipment intelligent diagnosis system.By taking an equipment fault on site,for example,the effectiveness of the proposed method is illustrated in the system.

Expert consensus on irrigation and intracanal medication in root canal therapy

Chemical cleaning and disinfection are crucial steps for eliminating infection in root canal treatment. However, irrigant selection or irrigation procedures are far from clear. The vapor lock effect in the apical region has yet to be solved, impeding irrigation efficacy and resulting in residual infections and compromised treatment outcomes.

Interpretation of Chinese Expert Consensus on the Diagnosis and Management Strategy of Patients with Statin Intolerance: A guiding file for helping to lipid management for Chinese population

It is well-known that elevated low-density lipoprotein cholesterol(LDL-C)is a causal risk factor for atheroscler-otic cardiovascular disease(ASCVD),statins are cornerstone drugs for the cause-based treatment of ASCVD,which has created a new era for ASCVD therapy.However,statin intolerance is not clinically uncommon,which there are several issues with confu-sion and misunderstandings.Hence,a file named Chinese Expert Consensus on the Diagnosis and Management Strategy of Pa-tients With Statin Intolerance,like a navigator,has recently been published written by a team of experts from the Cardiovascular Metabolic Medicine Professional Committee,Expert Committee of the National Center for Cardiovascular Diseases aiming to en-hance the standardized clinical application of statins and improve the prevention and clinical outcome.In this article,author briefly summarized the key points of above consensus in order to helping to comprehending the content of the consensus sugges-tions.

发动机缸体CMM精密测量的温度影响研究

缸体是发动机的核心零件之一,制造过程及产品的尺寸质量控制是重点工作。缸体尺寸精度要求高,需使用三坐标精密测量设备,温度是影响精密测量的重要因素,本文从两方面研究其具体影响:第一,高精度三坐标校准和日常标定对温度的敏感性高,温度波动直接影响标定数据,从而进一步影响工件测量结果,通过设计实验研究其具体影响;第二,充分的恒温过程是实现精密测量的前提,缸体加工过程中会安装托盘,不同材料的恒温特异性差异导致恒温过程复杂,研究如何提高恒温效率并保证结果准确,对实际生产具有重要意义。

Fully Completed Spherical Fuzzy Approach-Based Z Numbers(PHIModel)for Enhanced Group Expert Consensus

This study aims to establish an expert consensus and enhance the efficacy of decision-making processes by integrating Spherical Fuzzy Sets(SFSs)and Z-Numbers(SFZs).A novel group expert consensus technique,the PHImodel,is developed to address the inherent limitations of both SFSs and the traditional Delphi technique,particularly in uncertain,complex scenarios.In such contexts,the accuracy of expert knowledge and the confidence in their judgments are pivotal considerations.This study provides the fundamental operational principles and aggregation operators associated with SFSs and Z-numbers,encompassing weighted geometric and arithmetic operators alongside fully developed operators tailored for SFZs numbers.Subsequently,a case study and comparative analysis are conducted to illustrate the practicality and effectiveness of the proposed operators and methodologies.Integrating the PHI model with SFZs numbers represents a significant advancement in decision-making frameworks reliant on expert input.Further,this combination serves as a comprehensive tool for decision-makers,enabling them to achieve heightened levels of consensus while concurrently assessing the reliability of expert contributions.The case study results demonstrate the PHI model’s utility in resolving complex decision-making scenarios,showcasing its ability to improve consensus-building processes and enhance decision outcomes.Additionally,the comparative analysis highlights the superiority of the integrated approach over traditional methodologies,underscoring its potential to revolutionize decision-making practices in uncertain environments.

An innovative classification system for ranking the biological effects of marine aromatic hydrocarbons based on fish embryotoxicity

Petroleum hydrocarbon pollution is a global concern,particularly in coastal environments.Polycyclic aromatic hydrocarbons(PAHs) are regarded as the most toxic components of petroleum hydrocarbons.In this study,the biomonitoring and ranking effects of petroleum hydrocarbons and PAHs on the marine fish model Oryzias melastigma embryos were determined in the Jiulong River Estuary(JRE) and its adjacent waters in China.The results showed that the levels of petroleum hydrocarbons from almost all sites met the primary standard for marine seawater quality,and the concentrations of the 16 priority PAHs in the surface seawater were lower compared with those in other coastal areas worldwide.A new fish expert system based on the embryotoxicity of O.melastigma(OME-FES) was developed and applied in the field to evaluate the biological effects of petroleum hydrocarbons and PAHs.The selected physiological index and molecular indicators in OME-FES were appropriate biomarkers for indicating the harmful effects of petroleum hydrocarbons and PAHs.The outcome of OME-FES revealed that the biological effect levels of the sampling sites ranged from level Ⅰ(no stress) to level Ⅲ(medium stress),which is further corroborated by the findings of nested analysis of variance(ANOVA) models.Our results suggest that the OME-FES is an effective tool for evaluating and ranking the biological effects of marine petroleum hydrocarbons and PAHs.This method may also be applied to evaluate other marine pollutants based on its framework.

UAV maneuvering decision-making algorithm based on deep reinforcement learning under the guidance of expert experience

Autonomous umanned aerial vehicle(UAV) manipulation is necessary for the defense department to execute tactical missions given by commanders in the future unmanned battlefield. A large amount of research has been devoted to improving the autonomous decision-making ability of UAV in an interactive environment, where finding the optimal maneuvering decisionmaking policy became one of the key issues for enabling the intelligence of UAV. In this paper, we propose a maneuvering decision-making algorithm for autonomous air-delivery based on deep reinforcement learning under the guidance of expert experience. Specifically, we refine the guidance towards area and guidance towards specific point tasks for the air-delivery process based on the traditional air-to-surface fire control methods.Moreover, we construct the UAV maneuvering decision-making model based on Markov decision processes(MDPs). Specifically, we present a reward shaping method for the guidance towards area and guidance towards specific point tasks using potential-based function and expert-guided advice. The proposed algorithm could accelerate the convergence of the maneuvering decision-making policy and increase the stability of the policy in terms of the output during the later stage of training process. The effectiveness of the proposed maneuvering decision-making policy is illustrated by the curves of training parameters and extensive experimental results for testing the trained policy.

基于CMM模型智慧图书馆知识资源建设评估

文章基于成熟度模型(CMM)构建了智慧图书馆知识资源建设评价指标体系,结合69名智慧图书馆管理者和147名智慧图书馆馆员的调查数据,界定了指标权重,测算了指标平均值,并在此基础上测量了知识资源建设的成熟度值,指出智慧图书馆知识资源建设整体上处于发展阶段,主要弱项为知识资源重构。

British Law Expert:South China Sea Islands Are Chinese Territory

The History and Sovereignty of the South China Sea Islands clarifies the sovereignty over the South China Sea Islands with irrefutable facts.THE English edition of The History and Sovereignty of the South China Sea Islands was released by New Star Press under China International Communications Group at the 2024 Beijing International Book Fair on June 20.Prior to this,the Chinese version of the book,also published by New Star Press,had attracted wide attention from the international community.

Practice and Thinking of Agricultural Science and Technology Experts Serving the Grassroots to Promote Rural Revitalization

Provincial agricultural research institutes are local agricultural research institutions.They are familiar with local agricultural and ru-ral conditions,and have advantages in scientific and technological achievements,technical reserves and the construction of scientific and tech-nological talent support systems.In the process of promoting the implementation of the rural revitalization strategy,all the responsibilities and obligations of the agricultural research institute are to identify the focus of scientific and technological support and talent support in rural revital-ization,and break the bottleneck and constraints of rural revitalization.By sorting out the current situation of agricultural science and technolo-gy experts serving the grassroots in the problem of talent support for rural revitalization,this paper analyzed the existing problems and put for-ward countermeasures and recommendations.

A Health State Prediction Model Based on Belief Rule Base and LSTM for Complex Systems

In industrial production and engineering operations,the health state of complex systems is critical,and predicting it can ensure normal operation.Complex systems have many monitoring indicators,complex coupling structures,non-linear and time-varying characteristics,so it is a challenge to establish a reliable prediction model.The belief rule base(BRB)can fuse observed data and expert knowledge to establish a nonlinear relationship between input and output and has well modeling capabilities.Since each indicator of the complex system can reflect the health state to some extent,the BRB is built based on the causal relationship between system indicators and the health state to achieve the prediction.A health state prediction model based on BRB and long short term memory for complex systems is proposed in this paper.Firstly,the LSTMis introduced to predict the trend of the indicators in the system.Secondly,the Density Peak Clustering(DPC)algorithmis used todetermine referential values of indicators for BRB,which effectively offset the lack of expert knowledge.Then,the predicted values and expert knowledge are fused to construct BRB to predict the health state of the systems by inference.Finally,the effectiveness of the model is verified by a case study of a certain vehicle hydraulic pump.

基于P-CMM五级标准的医院人力资源模块过程域构建

有效的人力资源管理对于医院的成功和可持续发展至关重要。随着医疗行业的竞争日益激烈和变革的加速,医院越来越意识到需要建立高效的人力资源管理流程来应对挑战和促进组织成熟度的提升。在这一背景下,基于人力资源能力成熟度模型(people capability maturity model,P-CMM)的医院人力资源模块过程域构建成为了一种备受关注的方法。本文旨在探讨基于P-CMM五级标准的医院人力资源模块过程域构建的研究和实践。通过回顾国内外相关文献,总结目前的研究现状掌握P-CMM模型在人力资源管理中的应用实践、实施效益、挑战和局限性,以及成功的最佳实践和因素。同时,从P-CMM的初始级、管理级、定义级、可预测级、优化阶段构建医院人力资源模块过程域,从而为提高医院人力资源管理的成熟度和质量,推动医院的可持续发展提供参考。

基于Design-Expert的碱激发粉煤灰建筑外墙腻子配合比优化试验研究

为了拓展工业固体废弃物粉煤灰的回收利用途径,减少对环境造成的污染,增加其在筑材料中回收利用率。在建筑外墙腻子中加入碱性激发剂(Ca(OH)_(2)、Na_(2)SiO_(3))、粉煤灰,研究碱性激发剂的激发效果。同时通过Design-Expert设计试验,分析主要组分对腻子漆膜粘结强度、吸水量的影响。结果表明:加入碱性激发剂5%,粉煤灰32.5%时,吸水量减少14%,粘结强度增加43%。乳胶粉对吸水量、粘结强度的影响非常显著(P<0.0001),其次是粉煤灰的加入量。通过加入碱性激发剂、提高乳胶粉占比,粉煤灰掺量能达到32%~65%,原配比中水泥的掺量相对减少0%~16%。

基于ANSYS和Design-Expert的农用挖掘机斗杆机构优化设计

JKW-20山地农用挖掘机斗杆机构存在设计冗余,在保证安全可靠的前提下,为解决斗杆机构材料冗余问题,实现轻量化改进,建立了农用挖掘机挖掘装置斗杆机构耦合模型,通过ANSYS软件静力学仿真及拓扑优化,确定了斗杆机构拓扑优化新结构。由于拓扑优化结构不符合实际生产要求,基于优化结果设计斗杆变量,确定优化目标函数,利用Design-Expert进行斗杆机构尺寸优化求解。由优化结果对比可知:运用Design-Expert优化后的斗杆结构相对原结构具备更轻的质量和更大的强度,该方法不仅节约了JKW-20山地农用挖掘机的生产成本,还可为类似的机构设计提供优化思路。

Design and Development of Web-based Expert System for the Diagnosis of Disease and Pests of Fruits and Vegetables

According to the requirements of agricultural production and usem, taking diagnosis and decision-making of prevention for common diseases and pests in fruits and vegetables in southern China as the core, with communication and sharing as principle, adopted diagnosis, inquiries and guiding prevention of diseases and pests in fruits and vegetables as purpose, expert examination system of plant disease and pests in fruits and vegetables based on Web highly integrates the knowledge and prevention techniques of common diseases and pests for main fruit and vegetable in south China. In this system, the users can browse and inquiry the information about the fruit and vegetable diseases and pests, as well as their diagnosis and control. The implementation of the system plays an active role in promo- ting plant protection knowledge and guiding farms to scientifically control diseases and pests in fruits and vegetables

Variable universe fuzzy expert system for aluminum electrolysis

In aluminum electrolytic process, the variables affect the current efficiency and the stability of electrolysis cells. AIF3 addition and aluminum tapping volume are two important factors that affect economic benefits of aluminum electrolytic production. Fuzzy logic provides a suitable mechanism to describe the relationship between the process variables and the current efficiency. Fuzzy expert system based on Mamdani fuzzy inference process for aluminum electrolysis was adopted to adjust A1F3 addition and aluminum tapping volume. A novel variable universe approach was applied in the system to solve the problem that different electrolysis cells have different universes of variables. The system was applied to 300 kA aluminum electrolysis cells in a aluminum plant. Experimental results showed that the electrolyte temperature was kept stably between 945 and 955℃, the current efficiency reached 93.5%, and the DC power consumption was 13 000 kW.h per ton aluminum.