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.

Hierarchical Bayesian Calibration and On-line Updating Method for Influence Coefficient of Automatic Dynamic Balancing Machine

Measurement error of unbalance＇s vibration response plays a crucial role in calibration and on-line updating of influence coefficient（IC）. Focusing on the two problems that the moment estimator of data used in calibration process cannot fulfill the accuracy requirement under small sample and the disturbance of measurement error cannot be effectively suppressed in updating process, an IC calibration and on-line updating method based on hierarchical Bayesian method for automatic dynamic balancing machine was proposed. During calibration process, for the repeatedly-measured data obtained from experiments with different trial weights, according to the fact that measurement error of each sensor had the same statistical characteristics, the joint posterior distribution model for the true values of the vibration response under all trial weights and measurement error was established. During the updating process, information obtained from calibration was regarded as prior information, which was utilized to update the posterior distribution of IC combined with the real-time reference information to implement online updating. Moreover, Gibbs sampling method of Markov Chain Monte Carlo（MCMC） was adopted to obtain the maximum posterior estimation of parameters to be estimated. On the independent developed dynamic balancing testbed, prediction was carried out for multiple groups of data through the proposed method and the traditional method respectively, the result indicated that estimator of influence coefficient obtained through the proposed method had higher accuracy; the proposed updating method more effectively guaranteed the measurement accuracy during the whole producing process, and meantime more reasonably compromised between the sensitivity of IC change and suppression of randomness of vibration response.

Selection and Research for Online Registration System’s Database System

Based on the Online Registration System (ORS) characteristics and key technology analysis, this paper points out that that a good performance and high stability of the ORS lies in the choice of the system database. Database clustering technology which has merits such as concurrent processing, easy expansion, and high security is proposed to achieve database subsystem of ORS, and the design of the database cluster system framework is available in this paper. Finally, we also explore the database load balancing of the cluster system, heterogeneous database replication technology.

利益主体视角下在线教育著作权风险防范研究

伴随信息技术的飞速发展,在线教育突破了以往传统教学模式的时空限制,实现了教育资源的共享,近年来逐渐成为教育刚需。但随着在线教育规模的迅速扩张,围绕着优质在线教育课程展开的著作权利益之争也日益激烈,打破了传统线下教学模式下以教师与学生为二元主体而构建的既有著作权利益平衡机制。作为在线教育中的相关利益主体,课程著作权人、运营服务平台、学习用户各自均可能面临课程归属不明、课程传播违法、课程使用侵权等著作权风险。为扫清在线教育长效发展的制度羁绊,各利益主体应采取签订著作权共享协议、建立“AI加人工”核查机制、获取正版授权等相应措施,方能使在线教育模式下知识产品创造者、传播者、使用者三者间的利益实现新的平衡。

网络著作权强保护下的用户合法权益保护

网络著作权保护呈现强保护特征,主要表现为网络著作权执法力度的加强,不仅通过技术保护措施和信息披露制度为著作权人层层“加码”,还通过通知—屏蔽制度、内容审核补救措施多元化、算法执行推动网络服务提供者著作权保护责任不断加重。网络著作权的过度保护也存在着一些风险隐患,网络用户的合法权益面临侵害之虞,合理使用权利、言论自由权利、隐私权和个人数据保护权都受到不同程度的侵害和忽视。侵权情形的出现多数情况下与网络服务提供者有关,因此有必要对网络服务提供者的行为进行规制。应在公平平衡原则基础上,完善相关法律,推进技术进步,以维护著作权人、网络服务提供者和网络用户、社会公众之间的利益平衡。

高校思政课线上线下教学资源配置平衡原则和方法研究

线上教学资源和线下教学资源作为不同的资源空间,合理运用,能够调动教师的教学活力,提升学生的学习实效。思政课的线上线下教学资源各有优点和特点,教师需要在教学中把握线上线下教学资源配置的平衡原则和方法,使线上线下教学资源内容精炼得当,衔接科学。

Online Induction of Probabilistic Real-Time Automata

The probabilistic real-time automaton （PRTA） is a representation of dynamic processes arising in the sciences and industry. Currently, the induction of automata is divided into two steps： the creation of the prefix tree acceptor （PTA） and the merge procedure based on clustering of the states. These two steps can be very time intensive when a PRTA is to be induced for massive or even unbounded datasets. The latter one can be efficiently processed, as there exist scalable online clustering algorithms. However, the creation of the PTA still can be very time consuming. To overcome this problem, we propose a genuine online PRTA induction approach that incorporates new instances by first collapsing them and then using a maximum frequent pattern based clustering. The approach is tested against a predefined synthetic automaton and real world datasets, for which the approach is scalable and stable. Moreover, we present a broad evaluation on a real world disease group dataset that shows the applicability of such a model to the analysis of medical processes.

全球视野下的在线高等教育均衡发展

在高等教育迈向普及化的阶段,发展中国家不管是基于高端人才培养的国家需求,还是基于时代发展趋势的社会需求,或是基于职业个性发展的个人需求,都亟须发展高等教育。在线教育作为“互联网+”教育的产物,能有效促进其均衡发展。作为一个新事物,在线高等教育均衡发展面临诸多挑战:政策障碍是学分认证、知识产权与政策落实的问题;语言障碍增加交流协作、知识构建与国际竞争的难度;技术障碍加剧物理鸿沟、技能鸿沟与环境鸿沟的扩大;文化障碍导致互动偏好、角色认知与写作习惯的差异。为此,基于互联网教育传播系统,针对文化、技术、语言和政策障碍,提出在线高等教育均衡发展模型,通过共享高质量交流、资源、师资和大学,来消弭教育鸿沟、降低教育成本、提升教育水平以及实现教育公平,并提出发展本土特色、协同教学模式、横纵齐头并进与保障学分质量的建议以应对在线高等教育均衡发展面临的挑战。

基于战略地图制定互联网医院在线问诊绩效管理方案

目的线上线下融合是互联网医院运营的重点方向,如何科学制订绩效管理方案提升医联网医院整体运营效率是公立医院面临的主要挑战。方法收集2022年1—12月广西医科大学互联网医院平台数据,包括互联网医院线上总咨询量,总回复数、线上转化率和线下转化率等,并基于考核目标重新构建绩效考核方案,统计医务人员绩效指标。结果本院2022年线上总咨询量为296414人次,总回复数为246800人次。线上总问诊人次47416人次,线上问诊接诊40052人次。线上回复订单数排名前5的科室分别是妇科门诊、儿科门诊、消化内科门诊、内分泌科门诊、产科门诊;慢性病开方总数为91人次,已审核通过处方84人次。患者平均候诊时长约10 h。绩效考核年度最佳服务医生平均每月线下转诊率波动在31.70%~71.76%,平均咨询接诊率为87.08%~99.27%。结论实施绩效管理后部分科室医生积极性有所提高,线下转化率有所提升,但线上转换仍有不足,未来应考虑线上处方纳入绩效管理方案。

网购专利产品侵权诉讼地域管辖排除收货地规则研究——以格力与奥克斯等专利侵权纠纷管辖权异议案为例

网购新业态的层出不穷为专利侵权纠纷带来新的挑战,由于侵权行为地的不确定性,互联网专利侵权案件难以确定地域管辖。在司法实践中,不同的法院针对网络购物收货地法院是否具有管辖权的问题,呈现出截然不同的裁判立场。最高人民法院在格力与奥克斯等专利侵权纠纷管辖权异议案中确立了网购专利产品侵权诉讼地域管辖排除收货地的裁判规则,为类似案件的裁判提供了指引规则。通过对185份管辖权异议裁定书的分析发现,法院肯定或否定网络购物收货地法院管辖权的裁判逻辑都围绕信息网络侵权行为、侵权行为地的认定等要素展开。应当明确的是,互联网专利侵权管辖规范遵循的首要原则是管辖的确定性,同时要兼顾专利权的地域性。在司法审判中,首先应明晰《民诉法司法解释》第20条和第25条都不是网购专利产品收货地法院获得管辖权的依据。其次,网购收货的环节是专利产品脱离销售方实际控制行为的独立过程,因而网购收货地不能被解释为专利侵权行为实施地,亦不是侵犯专利权直接产生的结果地。该规则存在例外情形,在某些情形下将最密切联系原则内化于侵权行为地的解释,可以把网购收货地作为专利侵权管辖特别冲突规范。值得注意的是,在现行法律规定中,网络著作权侵权地域管辖的连接点包括信息来源地,可以直接适用《民诉法司法解释》第25条,但是不能对该条作扩大解释进而认为涵盖网络商标和专利侵权行为。最后,该规则的适用应当考虑与其他知识产权单行法的融合,应明确专利侵权诉讼中侵权结果发生地的具体内涵,以保持各知识产权单行法法律规则形式上的统一性,而在涉外专利侵权地域管辖规则的融合上,将网购收货地作为管辖连接点是较为经济性的管辖选择。

一种锂电池在线监测系统设计

针对锂电池自身的化学特性原因,导致单体电压出现不一致性的现象,提出一种锂电池在线监测系统,系统硬件由单片机、检测器、报警器组成,采用LTC8602芯片、ACS712芯片、DHT11传感器分别获取准确的电压值、电流值、温度值,实现了对锂电池的电量以及过充、欠充和温度异常等情况的检测。利用LM2596S-ADJ芯片、SS8050三极管对电池进行充放电时的电压均衡保护。实验结果证明,锂电池在线检测系统能够为充分利用电池、延长电池的使用寿命提供保障,使电池能够安全运行。

烧结主风机在线动平衡实践

离心式风机是烧结工序产线中的关键设备,由于其长期在含尘烟气中运行,经常因叶片磨损、结垢等原因造成振动超限,影响风机的正常运转,危害烧结生产运行。从动平衡的理论和概念入手,介绍了风机非解体在线动平衡修复的基本原理。以实践经验为主,通过实例系统地介绍了现场动平衡技术和实施过程中需注意的主要问题。通过在运行状态下的动平衡修复,使风机能够继续维持平稳运行。由于该技术不需要解体设备,具备修复及时性和维修费用低等优点,具有较高的推广应用价值。

算法推荐背景下网络服务提供者的侵权认定——全国首例算法推荐案评析

全国首例算法推荐案的争议焦点是字节公司是否因利用算法推荐技术与侵权用户构成共同侵权。算法推荐服务平台“注意义务”适用的困境主要有二:其一,算法推荐服务平台和算法推荐技术之间存在“责任鸿沟”;其二,算法推荐服务平台和个人权利之间存在“利益失衡”。根据算法推荐服务平台的运作模式以及技术的运作原理分析其预防侵权和救济权利的能力,是判断能否为主体施加“更高的注意义务”的第一步。注意义务的设定要考究算法推荐服务平台的专业信息管理能力、在算法推荐运行中的干预与控制能力和其收到适格“通知后”及时制止侵权行为能力。面对传统注意义务的适用困境,还应通过对类似的司法案例进行类型化分析和总结,从主体行为和客体信息内容类型两方面重构合理注意义务的框架。

基于随机平衡采样的不确定大数据流在线分类算法

不确定大数据流具有动态性和不平衡性特点,导致分类结果不精准,为此提出基于随机平衡采样的不确定大数据流在线分类算法。根据Spark框架大数据筛选结构,过滤筛选不确定大数据,释放不满足条件的大数据。应用Hoeffding算法计算实际值与观测值之差,判断差值与属性差值之间的关系,确定最佳分类属性。随机设定最小类别与最大类别数目,对非平衡样本抽样,避免因样本规模过大而造成的样本损失。建立在线分类器,逐级筛选不确定大数据。通过计算不确定信息增益,获取归类最大可能性类别,实现大数据流的在线分类。由实验结果可知,该算法对数据集W1、W2、W3分类的准确率最低值分别达到90%、94%、83%,具有精准分类效果。

A balanced decomposition approach to real-time visualization of large vector maps in CyberGIS

With the dramatic development of spatial data in- frastructure, CyberGIS has become significant for geospatial data sharing. Due to the large number of concurrent users and large volume of vector data, CyberGIS faces a great chal- lenge in how to improve performance. The real-time visual- ization of vector maps is the most common function in Cyber- GIS applications, and it is time-consuming especially when the data volume becomes large. So, how to improve the effi- ciency of visualization of large vector maps is still a signif- icant research direction for GIScience scientists. In this re- search, we review the existing three optimization strategies, and determine that the third category strategy （i.e., parallel optimization） is appropriate for the real-time visualization of large vector maps. One of the key issues of parallel optimiza- tion is how to decompose the real-time visualization tasks into balanced sub tasks while taking into consideration the spatial heterogeneous characteristics. We put forward some rules that the decomposition should conform to, and design a real-time visualization framework for large vector maps. We focus on a balanced decomposition approach that can assure efficiency and effectiveness. Considering the spatial hetero- geneous characteristic of vector data, we use a ＂horizontal grid, vertical multistage＂ approach to construct a spatial point distribution information grid. The load balancer analyzes the spatial characteristics of the map requests and decomposes the real-time viewshed into multiple balanced sub viewsheds.Then, all the sub viewsheds are distributed to multiple server nodes to be executed in parallel, so as to improve the real- time visualization efficiency of large vector maps. A group of experiments have been conducted by us. The analysis results demonstrate that the approach proposed in this research has the ability of balanced decomposition, and it is efficient and effective for all geometry types of vector data.

铁路变配电所蓄电池智能在线监护装置研究与应用

蓄电池组是铁路变配电所直流电源的重要组成部分。运行经验表明,因电源点多、分布分散、人员不足且运维自动化程度较低等因素限制,各站点蓄电池普遍存在维护不及时、不到位等现象,给直流系统的可靠运行造成了极大安全隐患。本文基于铁路变配电所直流电源蓄电池运维现状分析,设计了一种基于DC/DC双向变换电路的蓄电池智能在线监护装置,在不改变原直流电源系统接线方式及运行参数的基础上,实现蓄电池健康状态监测、自动在线核容、主动均衡及脉冲去硫等功能。该技术的应用,可进一步提高站用直流电源蓄电池组精细化运维和可视化管理水平,有效延长蓄电池使用寿命,对降低蓄电池运维成本、提高铁路安全运行水平具有显著意义。

一种机械式在线平衡头的设计与实验研究

由不平衡量引起的过大振动对旋转机械是有害的,因而需要用动平衡的方法来消除不平衡量。为了能实现在线动平衡,介绍一种机械式的平衡头。平衡头由9只圆盘构成,通过结构设计,9只盘可以形成四个独立的腔体,将小钢珠从外部定子中传送到4个腔体之一中,就能产生期望的不平衡校正量。详细介绍了平衡头的结构和工作原理,分析了工作过程和控制方案,描述了实验装置,最后通过实验验证了方案的有效性。

注液式高速切削主轴动平衡装置设计及其性能研究

为有效抑制高速切削主轴的不平衡振动,提出了适用于该类主轴的注液式在线动平衡装置,并讨论了该装置的工作原理及平衡终端的结构特性。为了实现喷液量的精密控制,通过控制液压系统喷射管道的直径、液体压力等参数,使平衡液体处于层流运动状态。通过分析平衡终端内、外圈径向位移与转速的关系,验证了该装置在高速旋转下的安全性。在研究该装置的平衡能力及精度的基础上,通过合理设计液体容腔,实现了喷液量与平衡配重间的线性关联。此外,还提出了考虑初次试重预估的迭代矢量反馈平衡控制策略,从而满足了该装置用于高速平衡时的特殊需求。高速主轴动平衡实验的结果表明,在20 700r/min时,通过平衡操作可使主轴不平衡振动的幅值下降约78.8%,从而验证了该平衡装置及其平衡控制策略的有效性。