Restoring force correction based on online discrete tangent stiffness estimation method for real-time hybrid simulation

In real-time hybrid simulation（RTHS）, it is difficult if not impossible to completely erase the error in restoring force due to actuator response delay using existing displacement-based compensation methods. This paper proposes a new force correction method based on online discrete tangent stiffness estimation（online DTSE） to provide accurate online estimation of the instantaneous stiffness of the physical substructure. Following the discrete curve parameter recognition theory, the online DTSE method estimates the instantaneous stiffness mainly through adaptively building a fuzzy segment with the latest measurements, constructing several strict bounding lines of the segment and calculating the slope of the strict bounding lines, which significantly improves the calculation efficiency and accuracy for the instantaneous stiffness estimation. The results of both computational simulation and real-time hybrid simulation show that：（1） the online DTSE method has high calculation efficiency, of which the relatively short computation time will not interrupt RTHS; and（2） the online DTSE method provides better estimation for the instantaneous stiffness, compared with other existing estimation methods. Due to the quick and accurate estimation of instantaneous stiffness, the online DTSE method therefore provides a promising technique to correct restoring forces in RTHS.

Direct immune-SCIR public-opinion propagation model based on real-time online users

Current public-opinion propagation research usually focused on closed network topologies without considering the fluctuation of the number of network users or the impact of social factors on propagation. Thus, it remains difficult to accurately describe the public-opinion propagation rules of social networks. In order to study the rules of public opinion spread on dynamic social networks, by analyzing the activity of social-network users and the regulatory role of relevant departments in the spread of public opinion, concepts of additional user and offline rates are introduced, and the direct immune-susceptible, contacted, infected, and refractory (DI-SCIR) public-opinion propagation model based on real-time online users is established. The interventional force of relevant departments, credibility of real information, and time of intervention are considered, and a public-opinion propagation control strategy based on direct immunity is proposed. The equilibrium point and the basic reproduction number of the model are theoretically analyzed to obtain boundary conditions for public-opinion propagation. Simulation results show that the new model can accurately reflect the propagation rules of public opinion. When the basic reproduction number is less than 1, public opinion will eventually disappear in the network. Social factors can significantly influence the time and scope of public opinion spread on social networks. By controlling social factors, relevant departments can analyze the rules of public opinion spread on social networks to suppress the propagate of negative public opinion and provide a powerful tool to ensure security and stability of society.

A Non-Contact Original-State Online Real-Time Monitoring Method for Complex Liquids in Industrial Processes

Failures are very common during the online real-time monitoring of large quantities of complex liquids in industrial processes, and can result in excessive resource consumption and pollution. In this study, we introduce a monitoring method capable of non-contact original-state online real-time monitoring for strongly coated, high-salinity, and multi-component liquids. The principle of the method is to establish the relationship among the concentration of the target substance in the liquid （C）, the color space coor- dinates of the target substance at different concentrations （L＊, a＊, b＊）, and the maximum absorption wave- length （λmax）; subsequently, the optimum wavelength λT of the liquid is determined by a high-precision scanning-type monitoring system that is used to detect the instantaneous concentration of the target substance in the flowing liquid. Unlike traditional monitoring methods and existing online monitoring methods, the proposed method does not require any pretreatment of the samples （i.e., filtration, dilution, oxidation/reduction, addition of chromogenic agent, constant volume, etc.）, and it is capable of original- state online real-time monitoring. This method is employed at a large electrolytic manganese plant to monitor the Fe3. concentration in the colloidal process of the plant＇s aging liquid （where the concentra- tions of Fe3＋, Mn2＋, and （NH4）2SO4 are 0.5-18 mg.L 1, 35-39 g.L 1, and 90-110 g.L 1, respectively）. The relative error of this monitoring method compared with an off-line laboratory monitoring is less than 2%.

Online pharmaceutical process analysis of Chinese medicine using a miniature mass spectrometer: Extraction of active ingredients as an example

The automation of traditional Chinese medicine(TCM)pharmaceuticals has driven the development of process analysis from offline to online.Most of common online process analytical technologies are based on spectroscopy,making the identification and quantification of specific ingredients still a challenge.Herein,we developed a quality control(QC)system for monitoring TCM pharmaceuticals based on paper spray ionization miniature mass spectrometry(mini-MS).It enabled real-time online qualitative and quantitative detection of target ingredients in herbal extracts using mini-MS without chromatographic separation for the first time.Dynamic changes of alkaloids in Aconiti Lateralis Radix Praeparata(Fuzi)during decoction were used as examples,and the scientific principle of Fuzi compatibility was also investigated.Finally,the system was verified to work stably at the hourly level for pilot-scale extraction.This mini-MS based online analytical system is expected to be further developed for QC applications in a wider range of pharmaceutical processes.

Big Data Stream Analytics for Near Real-Time Sentiment Analysis

In the era of big data, huge volumes of data are generated from online social networks, sensor networks, mobile devices, and organizations’ enterprise systems. This phenomenon provides organizations with unprecedented opportunities to tap into big data to mine valuable business intelligence. However, traditional business analytics methods may not be able to cope with the flood of big data. The main contribution of this paper is the illustration of the development of a novel big data stream analytics framework named BDSASA that leverages a probabilistic language model to analyze the consumer sentiments embedded in hundreds of millions of online consumer reviews. In particular, an inference model is embedded into the classical language modeling framework to enhance the prediction of consumer sentiments. The practical implication of our research work is that organizations can apply our big data stream analytics framework to analyze consumers’ product preferences, and hence develop more effective marketing and production strategies.

VisQAC: Visual Analytics for Online Q&A Communities

Online question and answer(Q&A)communities,which allow users to exchange knowledge by asking and answering questions,have become increasingly popular.As a result of user active participation,these communities store overwhelming volumes of information.However,existing related methods are unable to meet community operators’needs for analyzing multi-dimensional Q&A sequences and understanding user behavior.In this paper,collaborating with domain experts in online community,we present a system,VisQAC,which explores the patterns of Q&A sequence and user behavior.In the system,a novel visual design is proposed,which is combined with flexible mapping measures for analyzing critical characteristics of sequence data.Moreover,a timeline visualization method is designed to visualize data with categorical attributes and its correlation can be displayed flexibly by choosing time mode and time granularity.The usefulness and effectiveness of the system are demonstrated with several case studies of VisQAC with community operators based on the Zhihu dataset.Our evaluation shows that VisQAC is beneficial to the understanding of Q&A sequence and associated user behavior.

面向Online Judge提交日志的用户编程行为可视分析

在线判题系统(Online Judge.OJ)提交日志,即用户通过在线评测系统提交程序代码产生的提交记录,包括用户、代码及提交状态等相关信息,反映了用户的在线编程行为.现有的OJ系统通常提供给用户题目列表信息以及用户的实时排名信息,但未对用户的在线编程行为从时序、题目类型、错误类型等维度给出相关可视化信息,从而造成用户不能及时评估自己编程的强项与弱项.为进一步帮助OJ用户及时评估自身编程能力及提高学习效率,基于用户在基本算法、数据结构、搜索、图论、动态规划、数学等解题能力的多维度量化分析,构建用户的编程能力雷达图,实现对用户的编程能力多维可视化;根据模型设计并实现了面向OJ提交日志的个体用户与群体用户编程行为的多维度可视化;最后通过对北京大学在线评测系统的提交日志进行实例分析,实现了个体用户多维度编程能力的实时评估及系统群体用户编程行为的可视分析,同时为编程题目的协同过滤与推荐提供支持.

Multi-Dimensional Customer Data Analysis in Online Auctions

In this paper, we designed a customer-centered data warehouse system with five subjects： listing, bidding, transaction, accounts, and customer contact based on the business process of online auction companies. For each subject, we analyzed its fact indexes and dimensions. Then take transaction subject as example, analyzed the data warehouse model in detail, and got the multi-dimensional analysis structure of transaction subject. At last, using data mining to do customer segmentation, we divided customers into four types： impulse customer, prudent customer, potential customer, and ordinary customer. By the result of multi-dimensional customer data analysis, online auction companies can do more target marketing and increase customer loyalty.

网络隐私权视域下的众筹平台隐私政策评价

对不同类型众筹平台的隐私政策进行科学评价,据此改善平台对用户网络隐私权的保障措施具有积极意义。文章基于国内外相关政策构建众筹平台隐私政策评价体系,利用层次分析-熵值定权法对指标进行赋权,并选取主流众筹平台开展实证研究。研究结果显示:我国众筹平台的用户网络隐私权保障情况整体不容乐观,个体差异巨大、保障水平参差不齐,对安全请求权和隐私利用权的保障效果优于对隐私知情权和隐私控制权的保障,需从规范隐私监管机制、建立分类隐私保护措施和优化隐私保护政策等层面进行优化。

线上线下混合式教学模式在卫生分析化学实验教学中的应用

目的 探讨线上线下混合式教学模式在卫生分析化学实验教学中的应用效果。方法 选取2022年9—12月贵州医科大学2021级卫生检验与检疫专业本科生52名作为教学对象,分为2组,对照组20名学生应用传统教学法;试验组32名学生应用线上线下混合式教学模式,分别对2组学生的实验成绩进行比较,同时对学生教学效果进行满意度问卷调查。结果 对照组技能考试成绩为72.50(65.25,78.00)分,试验组成绩为81.50(72.00,85.00)分,试验组学生实验技能成绩高于对照组,差异有统计学意义(P <0.05);在高分数分数段(≥80分)试验组高于对照组,差异有统计学意义(P <0.001)。结论 在卫生分析化学实验授课中,应用线上线下混合式教学,结合技能考试的教学方式可有效提高学生实验成绩,提高学生实践操作能力,学生对线上线下混合式教学模式评价较高,取得了较好的教学效果。

分析化学的专业差别化教学设计与实践

通过从分析化学课程特点、专业差别化教学现状,进而从教学团队的建设、教学内容及教学形式的设计、过程性评价、缩减学时背景下的教学设计的实现等方面,探讨了分析化学专业差别化教学改革的设计与实践。分析化学专业差别化教学改革应注重“基础知识+专业氛围”及“线上线下混合式”教学,使学生们在课程学习流程导图的引导下,循序渐进地学习理论并巩固和拓展专业知识,建立学习自信及专业兴趣。对于相应的过程性评价,采用的评价模式能够促进学生达到自身的高标准、高水平即是实现了评价的目的。

基于层次分析-模糊综合评价的线上课程质量评价研究

随着“互联网+”时代的到来,纯线上教学和线上-线下混合式教学已成为高等教育教学模式发展的新趋势,也是近年高等教育教学改革研究的热点。为淘汰“水课”,国家大力打造线上“金课”,期望起到标杆和导向作用。如何对线上课程教学质量进行全面、科学的评价则直接关系着提升线上课程质量、甄别线上课程含金量以及更好地发挥金课的“标杆”作用。该文以学生为中心,突出学生评价主体地位,考虑目前我国主流慕课平台的发展现状以及线上课程教学特点和规律,采用AHP层次分析法构建一套较全面、合理的线上课程质量评价指标体系,同时结合模糊综合评价法对线上课程质量进行量化评估。其成果可为高校或者广大教师进行线上课程质量评价提供理论支撑和指导建议。

线上线下教学的有效衔接与融合探索

以药学专业分析化学课程为例,分析线上线下教学衔接过程中存在的问题、衔接要点,对理论部分及实验部分的教学衔接进行设计探索,以期实现线上线下教学的有效衔接,保证教学质量。

iDEAL-CIO: Instant Digital Express Advocated “Magic Lamp” for Cloud Intelligence Outlet

Instant Digital Express iDEAL-CIO The “Magic Lamp” for Cloud Intelligence Outlet, which has been recommended, combines innovations to satisfy modern users’ needs and efficiently sift through the ever-expanding amount of intelligent content stored in the cloud. One such innovation introduces a ground-breaking concept to remove superfluous and outdated sequential search patterns that overwhelm the user and computer in order to better serve the user in an eclectic & elastic and multidimensional approach to finding, grouping, assimilation, organizing, and delivering archival content. The cloud intelligence outlet (CIO) is presented in this article as the perfect magic lamp option for quick digital express advocacy. The grouping, indexing, folding, and targeting (GIFT) method of multidimensional online synthetic/analytical intelligent content (MOSAIC) for adaptive intelligence is the fundamental intelligent aggregation and automated process of the Magic Lamp. Three perspectives above this new ideal framework are available to observe: The Magic Lamp proposes contextual and multiple analytical tracks to improve cloud intelligence services conceptually. Technically speaking, MOSAIC combines domain-specific services for a wide range of international users, and through the usage of Cloud Intelligence Outlet, GIFT operationally activates grouping, indexing, folding, and targeting to promote decent experience and in-depth research on target for users’ wants. Because of this, iDEAL-CIO works in tandem with cloud extraction, digital transformation, and archival loading to provide improved service through the readily accessible cloud intelligence outlet.

异构体系结构下的混合负载数据库自适应并行技术

混合负载处理(HTAP)数据库通过统一的平台处理不同的工作负载,消除数据在不同平台之间迁移和开发运营的成本,实现对最新事务数据的实时分析。针对在保证系统新鲜度的同时最小化在线事务处理(OLTP)和在线分析处理(OLAP)在系统运行过程中的相互干扰的问题,提出一种中央处理器/图形处理器(CPU/GPU)异构体系结构下的混合负载数据库自适应并行技术。首先,构建异构体系结构下的混合负载数据库系统;其次,针对系统中的数据新鲜度问题,提出基于固定时间段的任务调度方法,以分离数据同步与分析查询;再次,提出一种多流并行分析处理策略,以提高系统分析处理性能;最后,针对高新鲜度的场景提出热数据优化方法,以提供全局最高新鲜度。基于CH-benCHmark基准进行测试和对比实验结果表明,与BatchDB相比,所提混合负载数据库事务性能下降率减小了50%。所提优化策略可以在提供可预测的新鲜度的情况下提供最高的分析处理性能,在少量性能损失的情况下提供最高的新鲜度。

Research on the Hotspots and Development of“Internet+Nursing Services”in China:A Bibliometric Analysis Based on CiteSpace

Objective:This study aims to explore the current research status,hotspots,and trends of the emerging nursing model of“Internet+nursing service”in China,and to provide theoretical references for further research and development.Methods:The literature related to“Internet+nursing service”was retrieved from the China National Knowledge Infrastructure(CNKI),Wanfang database,VIP database,and SinoMed.Subsequently,visual analysis was performed using the CiteSpace scientific knowledge mapping software.Results:A total of 1223 articles were included.The number of papers published in this field has been increasing yearly,and a core group of authors has been formed.Research institutions are mainly comprised of universities and hospitals and a high percentage of projects were funded provincially and municipally,while the least percentage of projects were funded nationally.The main research hotspots include the nurse standardized management for online appointments,the current application situation for the nursing model,and factors influencing its application amongst the elderly and also in women and children’s groups.Conclusion:Although the“Internet+nursing service”in China is still in its early stages,considerable progress has been made in relevant research.Future research should focus on identifying and omitting factors that hinder the industry’s growth,thereby establishing an effective long-term model of care.

在线学习行为评价框架:基于模糊层次分析法和模糊综合评价法

针对智慧教育场景下,在线学习评价的全面性和有效性所面临的不足,构建了一个基于模糊层次分析法(fuzzy analytic hierarchy process,FAHP)和模糊综合评价法(fuzzy synthetic evaluation method,FSEM)的在线学习行为指标评价框架.框架以CIPP(context,input,process,product)教育评价模型为指导,融合教育评价标签类目体系,确立了学习探索、编程实践、知识掌握、创新协作和沟通交互这5个维度,并细化为二级指标和三级指标,从而实现了评价的全面覆盖.通过FAHP-FSEM计算各级指标权重,并进行一致性检验,确保了评价的科学性和合理性.以水杉在线平台为案例,利用大规模多源的过程化学习数据,从多维度、多视角进行了综合评价,并通过可视化大屏呈现学生画像和学习行为特征.所提框架为个性化学习效果的提升和在线教育改革提供了有力数据支持,具有广泛的应用前景.

基于层次分析法的设备状态评估诊断技术

变压器在电力系统的电能传输过程中扮演着关键角色,其设备的状态诊断,是一项具有衍生结构的多级任务。为提高变压器状态诊断的可靠性,研究将萨蒂的层次分析法应用到变压器状态诊断中,提出了一种基于专家评估的决策诊断技术。介绍了层次分析法的关键性指标——连贯性指数(CI);建立了变压器状态诊断的数学模型;利用层次分析法,通过计算验证了所提方法诊断结果的可靠性。结果表明,该方法简单高效,适用于变压器技术状态的在线诊断。

基于线上线下混合式教学模式打造分析化学一流本科课程

网络的发展促进“网络+教学”相结合的线上线下混合式教学模式的兴起,积极探索适应时代发展的线上线下混合式教学模式是专业课教学改革的方向。分析化学是高等学校化学专业的一门专业基础课,信阳学院分析化学课程进行基于“雨课堂+慕课+QQ群+线下课堂教学”的线上线下混合式教学模式改革和探索,课题组从课程目标、课程内容、教学模式、课程考核等方面进行优化改革,积极打造分析化学一流本科课程建设。实践表明,改革后的课程教学能充分体现以学生为中心的教学理念,充分激发学生学习的积极性,培养学生发现问题和解决问题的能力,为线上线下混合式教学模式改革提供一条可借鉴的探索路径。

线上线下混合式教学在卫生分析化学实验教学中的应用研究

目的:探讨线上线下混合式教学模式在卫生分析化学实验教学中的应用效果。方法:选取贵州医科大学卫生检验与检疫专业本科生作为教学对象,分为两组。2018级、2019级作为试验组,应用线上线下混合式教学模式;2017级作为对照组,应用传统教学法。分别对两组学生的实验基本操作技能进行比较,同时对2018级教学效果进行满意度问卷调查。结果:试验组学生实验技能考核成绩明显高于对照组(P<0.05),且接受调查的学生对混合教学的需要率100%。结论:卫生分析化学实验授课中应用线上线下混合式教学模式能有效提高学生实验成绩,提高学生实践操作能力,学生对混合式教学方法评价较高,取得了较好的教学效果。