疫情下电磁场理论课程的网络教学

本文主要总结了新冠疫情期间作者的电磁场理论课程在线教学经验。对比分析了录播和直播的优缺点后,选择录播教学方式。基于超星网络教学平台,展示了录播网络教学的具体措施,包括网上答疑和学习效果检查以及在线批改作业等。给出了网络教学可以为线下教学继续使用的方法和手段,为疫情结束后的正常教学提供了新的网络教学补充措施。     

折臂式随车起重机转台的拓扑优化设计

为了使折臂式随车起重机转台在最大应力不超过材料许用应力的前提下实现轻量化设计的目的,通过ADAMS软件仿真确定其极限工况,对转台进行静力学分析及拓扑优化。通过拓扑优化得到了理想的材料分布。基于优化结果调整转台结构,并对改进后的转台进行静力学分析。结果表明,优化后的转台能够满足实际的使用需求。同时,转台质量降低了12%,证明了优化设计的有效性和可行性,并为折臂式随车起重机的相关设计提供了一定的借鉴。     

喷淋液滴在空气环境下的运动特性

本文以喷淋液滴在空气环境下运动特性为工程背景，建立单个液滴在常温、常压空气环境中的动量方程，分析液滴沉降特性、追赶特性及运动轨迹行为。计算结果表明，不同喷淋液滴初始条件下，短时间内存在重力大于曳力和重力小于曳力两种情况，但最终减速液滴均会达到受力平衡状态；液滴离开喷淋头后，垂向位移均迅速增大，液滴粒径越大、初始速度越大，垂向位移增长的速率也越大，达到相同位移的用时越短；液滴尺寸、初始速度相差越大，液滴追赶所用的时间越短，追赶位移越小，液滴尺寸、初始速度越接近，液滴追赶所用的时间越长，追赶位移越大；液滴初始速度越大、初始直径越大、喷射角度越大，横向速度消失越慢，达到的横向位移越大，喷射液滴覆盖的面积也越大。计算结果有助于优化工程实际中喷淋系统的设计与布置。     

Nonlinear dynamic behaviors and control based on simulation of high-purity heat integrated air separation column

In this paper, the dynamic behaviors on the basis of simulation for high-purity heat integrated air separation column (HIASC) are studied. A nonlinear generic model control (GMC) scheme is proposed based on the nonlinear behavior analyses of a HIASC process, and an adaptive generic model control (AGMC) scheme is further presented to correct the model parameters online. Related internal model control (IMC) scheme and multi-loop PID (M-PID) scheme are also developed as the comparative base. The comparative researches are carried out among these linear and nonlinear control schemes in detail. The simulation research results show that the proposed AGMC schemes present advantages in both servo control and regulatory control for the high-purity HIASC.     

FibVID: Comprehensive fake news diffusion dataset during the COVID-19 period

As the SARS-CoV-2 (COVID-19) pandemic has run rampant worldwide, the dissemination of misinformation has sown confusion on a global scale. Thus, understanding the propagation of fake news and implementing countermeasures has become exceedingly important to the well-being of society. To assist this cause, we produce a valuable dataset called FibVID (Fake news information-broadcasting dataset of COVID-19), which addresses COVID-19 and non-COVID news from three key angles. First, we provide truth and falsehood (T/F) indicators of news items, as labeled and validated by several fact-checking platforms (e.g., Snopes and Politifact). Second, we collect spurious-claim-related tweets and retweets from Twitter, one of the world’s largest social networks. Third, we provide basic user information, including the terms and characteristics of “heavy fake news” user to present a better understanding of T/F claims in consideration of COVID-19. FibVID provides several significant contributions. It helps to uncover propagation patterns of news items and themes related to identifying their authenticity. It further helps catalog and identify the traits of users who engage in fake news diffusion. We also provide suggestions for future applications of FibVID with a few exploratory analyses to examine the effectiveness of the approaches used.     

Model checking temporal knowledge and commitments in multi-agent systems using reduction

Though modeling and verifying Multi-Agent Systems (MASs) have long been under study, there are still challenges when many different aspects need to be considered simultaneously. In fact, various frameworks have been carried out for modeling and verifying MASs with respect to knowledge and social commitments independently. However, considering them under the same framework still needs further investigation, particularly from the verification perspective. In this article, we present a new technique for model checking the logic of knowledge and commitments (CTLKC⁺). The proposed technique is fully-automatic and reduction-based in which we transform the problem of model checking CTLKC⁺ into the problem of model checking an existing logic of action called ARCTL. Concretely, we construct a set of transformation rules to formally reduce the CTLKC⁺ model into an ARCTL model and CTLKC⁺ formulae into ARCTL formulae to get benefit from the extended version of NuSMV symbolic model checker of ARCTL. Compared to a recent approach that reduces the problem of model checking CTLKC⁺ to another logic of action called GCTL¹, our technique has better scalability and efficiency. We also analyze the complexity of the proposed model checking technique. The results of this analysis reveal that the complexity of our reduction-based procedure is PSPACE-complete for local concurrent programs with respect to the size of these programs and the length of the formula being checked. From the time perspective, we prove that the complexity of the proposed approach is P-complete with regard to the size of the model and length of the formula, which makes it efficient. Finally, we implement our model checking approach on top of extended NuSMV and report verification results for the verification of the NetBill protocol, taken from business domain, against some desirable properties. The obtained results show the effectiveness of our model checking approach when the system scales up.     

Model repair — aligning process models to reality

Process mining techniques relate observed behavior (i.e., event logs) to modeled behavior (e.g., a BPMN model or a Petri net). Process models can be discovered from event logs and conformance checking techniques can be used to detect and diagnose differences between observed and modeled behavior. Existing process mining techniques can only uncover these differences, but the actual repair of the model is left to the user and is not supported. In this paper we investigate the problem of repairing a process model w.r.t. a log such that the resulting model can replay the log (i.e., conforms to it) and is as similar as possible to the original model. To solve the problem, we use an existing conformance checker that aligns the runs of the given process model to the traces in the log. Based on this information, we decompose the log into several sublogs of non-fitting subtraces. For each sublog, either a loop is discovered that can replay the sublog or a subprocess is derived that is then added to the original model at the appropriate location. The approach is implemented in the process mining toolkit ProM and has been validated on logs and models from several Dutch municipalities.     

Revisiting the Parallel Strategy for DOACROSS Loops

Journal of Computer Science and Technology - DOACROSS loops are significant parts in many important scientific and engineering applications, which are generally exploited pipeline/wave-front...     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.     

煤矿冲击地压与冒顶复合灾害研究

随着煤矿向深部发展,矿井动力灾害既表现出冲击地压的部分特征,又表现出冒顶的部分特征。2种典型的灾害打破以往冒顶与冲击地压的发生具有一种互为逆向性的认知规律,在深部高应力煤巷,特别是留顶煤巷道中出现了相互诱导、复合发生的新灾害类型。在总结山东、山西和新疆矿区典型巷道冲击致顶板(顶煤)动力灾害特征的基础上,提出了深部巷道冲击地压与冒顶复合灾害的概念、机理与分类,指出复合灾害机理关键点在于揭示巷道整体系统和破碎区子系统的稳定原理及其2者间的相互影响。建立了巷道发生复合灾害的力学模型,根据扰动响应失稳判据,提出并得到了巷道发生复合灾害的临界应力Pcr、临界软化区半径ρ_cr和最大容许采扰应力增量σ_max,厘清了灾害发生的主控因素,分析了煤岩冲击倾向指数K、支护强度ps、巷道半径ρ₀、煤岩强度σ_c等对灾害发生的影响规律,同时阐明了围岩塑性软化、破碎深度随地应力增加的发育规律。研究结果表明,破碎发育巷道的动力失稳主体为弹性区、软化区与破碎区构成的不稳定系统,垮落主体为破碎区;稳定的破碎区提升了巷道冲击启动临界值,使其启动难度增大,但破碎区的发育又易引起顶煤垮落;巷道稳定支护是解决复合灾害的关键,科学合理支护既能有效调控围岩破碎防冒,又能提升冲击启动临界值。通过理论研究,揭示了巷道冲击地压与冒顶复合灾害的发生机理,阐明了巷道软化与破碎区及其稳控支护对深部破碎发育巷道动力灾害防治的重要性。