Discrete event model-based simulation for train movement on a single-line railway

The aim of this paper is to present a discrete event model-based approach to simulate train movement with the con- sidered energy-saving factor. We conduct extensive case studies to show the dynamic characteristics of the traffic flow and demonstrate the effectiveness of the proposed approach. The simulation results indicate that the proposed discrete event model-based simulation approach is suitable for characterizing the movements of a group of trains on a single railway line with less iterations and CPU time. Additionally, some other qualitative and quantitative characteristics are investigated. In particular, because of the cumulative influence from the previous trains, the following trains should be accelerated or braked frequently to control the headway distance, leading to more energy consumption.

A discrete-event model to simulate the effect of truck bunching due to payload variance on cycle time, hauled mine materials and fuel consumption

Data collected from truck payload management systems at various surface mines shows that the payload variance is significant and must be considered in analysing the mine productivity,energy consumption,greenhouse gas emissions and associated cost.Payload variance causes significant differences in gross vehicle weights.Heavily loaded trucks travel slower up ramps than lightly loaded trucks.Faster trucks are slowed by the presence of slower trucks,resulting in‘bunching’,production losses and increasing fuel consumptions.This paper simulates the truck bunching phenomena in large surface mines to improve truck and shovel systems’efficiency and minimise fuel consumption.The study concentrated on completing a practical simulation model based on a discrete event method which is most commonly used in this field of research in other industries.The simulation model has been validated by a dataset collected from a large surface mine in Arizona state,USA.The results have shown that there is a good agreement between the actual and estimated values of investigated parameters.

EVENT联合思政教学模式在提升护理实习生人文关怀能力中的应用研究

目的探讨EVENT联合思政教学模式在提升护理实习生人文关怀能力中的应用效果。方法随机抽取2022年7月至2023年7月在甲状腺疝小儿外科进行实习的护生为研究对象,对照组采用常规教学模式,实验组在对照组的基础上采用EVENT联合思政教学模式。比较两组理论成绩、自主学习能力、工作投入度及人文关怀能力。结果教学后,实验组理论成绩、自主学习能力、工作投入度及人文关怀能力均高于对照组(P<0.05)。结论EVENT联合思政教学模式能提升护理实习生理论成绩、自主学习能力、工作投入度及人文关怀能力,值得在教学中推广应用。

基于改进Event模型的交叉航路碰撞风险分析

随着空中交通流量不断增加,降低因流量增大而引起的空中交通碰撞风险至关重要,以此来保障航空运行安全,提高空域利用率。采用改进Event模型对同高度层交叉航路碰撞风险进行评估,将更符合航空器运行特点的拼接四棱锥碰撞盒代替原长方体碰撞盒,建立碰撞风险模型。通过计算改进前后碰撞盒面积之比,得到改进的交叉航路碰撞风险公式,其中,侧向重叠概率的计算中采用广义帕累托分布表示其侧向导航误差。最后将空客A320及波音737客机作为实例对所建模型进行验证,结果表明,改进后的拼接四棱锥碰撞盒面积为原长方体碰撞盒面积的54%,碰撞风险较改进前模型大大减少。模型所得风险值满足安全目标水平,结果精度更高,能更好地评估交叉航路碰撞风险。

Efficient Deviation Detection Between a Process Model and Event Logs

Business processes described by formal or semi-formal models are realized via information systems.Event logs generated from these systems are probably not consistent with the existing models due to insufficient design of the information system or the system upgrade.By comparing an existing process model with event logs,we can detect inconsistencies called deviations,verify and extend the business process model,and accordingly improve the business process.In this paper,some abnormal activities in business processes are formally defined based on Petri nets.An efficient approach to detect deviations between the process model and event logs is proposed.Then,business process models are revised when abnormal activities exist.A clinical process in a healthcare information system is used as a case study to illustrate our work.Experimental results show the effectiveness and efficiency of the proposed approach.

Catalytic Cracking of Cycloparaffins Admixed with Olefins:1. Single-Event Microkinetic(SEMK) Modeling

Single-event microkinetic(SEMK) model of the catalytic cracking of methylcyclohexane admixed with 1-octene over REUSY zeolites at 693 K—753 K in the absence of coke formation is enhanced. To keep consistency with the wellknown carbenium ion chemistry, hydride transfer forming and consuming allylic carbenium ions in the aromatization of cycloparaffins are further investigated and differentiated. The reversibility of endocyclic β-scission and cyclization reactions is refined by accounting explicitly for the reacting olefins and resulting cycloparaffins in the corresponding thermodynamics. 24 activation energies for the reactions involved in the cracking of cycloparaffins are obtained by the regression of 15 sets of experimental data upon taking the resulting 37 main cracking products, i. e., responses into account. The enhanced SEMK model can adequately describe the catalytic behavior of 37 main products with conversion and temperature.

Sensitivities of Numerical Model Forecasts of Extreme Cyclone Events

A global forecast model is used to examine various sensitivities of numerical predictions of three extreme winter storms that occurred near the eastern continental margin of North America: the Ohio Valley blizzard of January 1978, the New England blizzard of February 1978, and the Mid-Atlantic cyclone of February 1979. While medium-resolution simulations capture much of the intensification, the forecasts of the precise timing and intensity levels suffer from various degrees of error. The coastal cyclones show a 5-10 hPa dependence on the western North Atlantic sea surface temperature, which is varied within a range (± 2.5℃) compatible with interannual fluctuations. The associated vertical velocities and precipitation rates show proportionately stronger dependences on the ocean temperature perturbations. The Ohio Valley blizzard, which intensified along a track 700-800 km from the coast, shows little sensitivity to ocean temperature. The effect of a shift of - 10?latitude in the position of the snow boundary is negligible in each case. The forecasts depend strongly on the model resolution, and the coarse-resolution forecasts are consistently inferior to the medium-resolution forecasts. Studies of the corresponding sensitivities of extreme cyclonic events over eastern Asia are encouraged in order to identify characteristics that are common to numerical forecasts for the two regions.

Research on Event Handling Models of Java

A new event-handling paradigm and its application model are proposed. The working mechanism and principle of event listener model is given in detail. Finally, the launching event mechanisms, the choosing event handling models and the dispatching mechanism are illustrated.

Event-driven process execution model for process virtual machine

Current orchestration and choreography process engines only serve with dedicate process languages.To solve these problems,an Event-driven Process Execution Model(EPEM) was developed.Formalization and mapping principles of the model were presented to guarantee the correctness and efficiency for process transformation.As a case study,the EPEM descriptions of Web Services Business Process Execution Language(WS-BPEL) were represented and a Process Virtual Machine(PVM)-OncePVM was implemented in compliance with the EPEM.

Uncovering offline event similarity of online friends by constructing null models

The emergence of Event-based Social Network(EBSN) data that contain both social and event information has cleared the way to study the social interactive relationship between the virtual interactions and physical interactions. In existing studies, it is not really clear which factors affect event similarity between online friends and the influence degree of each factor. In this study, a multi-layer network based on the Plancast service data is constructed. The the user’s events belongingness is shuffled by constructing two null models to detect offline event similarity between online friends. The results indicate that there is a strong correlation between online social proximity and offline event similarity. The micro-scale structures at multi-levels of the Plancast online social network are also maintained by constructing 0 k–3 k null models to study how the micro-scale characteristics of online networks affect the similarity of offline events. It is found that the assortativity pattern is a significant micro-scale characteristic to maintain offline event similarity. Finally, we study how structural diversity of online friends affects the offline event similarity. We find that the subgraph structure of common friends has no positive impact on event similarity while the number of common friends plays a key role, which is different from other studies. In addition, we discuss the randomness of different null models, which can measure the degree of information availability in privacy protection. Our study not only uncovers the factors that affect offline event similarity between friends but also presents a framework for understanding the pattern of human mobility.

Cyclic Reconfigurable Flow Shop under Different Configurations Modeling and Optimization Based on Timed Event Graph

Based on the idea that modules are independent of machines, different combinations of modules and machines result in different configurations and the system performances differ under different configurations, a kind of cyclic reconfigurable flow shops are proposed for the new manufacturing paradigm-reconfigurable manufacturing system. The cyclic reconfigurable flow shop is modeled as a timed event graph. The optimal configuration is defined as the one under which the cyclic reconfigurable flow shop functions with the minimum cycle time and the minimum number of pallets. The optimal configuration, the minimum cycle time and the minimum number of pallets can be obtained in two steps.

基于改进结构的航空器Event模型碰撞风险分析

为了提高航路容量,科学缩小航空器间隔标准,通过将经典Event模型碰撞盒改进为圆柱体与三棱锥拼接模型,提出了针对航空器在航路飞行阶段对于碰撞风险计算更为精确的改进Event模型。分别从垂向、纵向两个方面入手改进航路碰撞风险公式,并以航路飞行阶段的塞斯纳172,B737-800为算例进行分析。结果表明:改进的Event模型对于小型固定翼飞机的碰撞风险计算结果约为经典Event模型的8.47%,约为椭球体Event模型的33.92%,约为两圆锥体拼接Event模型的50.5%。对于中型客机的碰撞风险计算结果约为经典Event模型的9.36%,约为椭球体Event模型的47.75%,约为两圆锥体拼接Event模型的70.93%。结果表明,论文所提出的改进Event模型有效降低了风险计算冗余,并且相较于以往球体、椭球体、拼接圆锥、拼接棱锥等改进Event模型,精度更高。

Threshold autoregression models for forecasting El Nino events

-In this paper, monthly mean SST data in a large area are used. After the spacial average of the data is carried out and the secular monthly means are substracted, a time series (Jan. 1951-Dec. 1985) of SST anomalies of the cold tongue water area in the eastern tropical Pacific Ocean is obtained. On the basis of the time series, an autoregression model, a self-exciting threshold autoregression model and an open loop autoregression model are developed respectively. The interannual variations are simulated by means of those models. The simulation results show that all the three models have made very good hindcasting for the nine El Nino events since 1951. In order to test the reliability of the open loop threshold model, extrapolated forecast was made for the period of Jan. 1986-Feb. 1987. It can be seen from the forecasting that the model could forecast well the beginning and strengthening stages of the recent El Nino event (1986-1987). Correlation coefficients of the estimations to observations are respectively 0. 84, 0. 88 and 0. 89. It is obvious that all the models work well and the open loop threshold one is the best. So the open loop threshold autoregression model is a useful tool for monitoring the SSTinterannual variation of the cold tongue water area in the Eastern Equatorial Pacific Ocean and for estimating the El Nino strength.

UML到Event-B的系统化转换方法

在面向对象的软件开发中,UML已经成为事实上的建模标准。然而,UML虽然直观容易理解和应用,却存在着不精确的语义,而且UML是一种半形式化的建模语言,无法进行形式化的验证。Event-B是一种基于大量数学谓词逻辑的形式化方法,虽然精确却难以理解和应用。因此,如何结合UML图和Event-B方法的优点是研究的重点,以往的方法都是基于UML零散图到Event-B的转换,缺乏系统的转换方法。系统性的转换方法可以实现UML中的元素与Event-B中的元素相对应统一。一般的软件系统是中型系统,中型系统采用用例图、类图、状态图和顺序图这四种图就可以很好地表达清楚,有了上述的四种图,软件生命周期的需求获取、分析、设计、详细设计就可以完全表达清楚。文章中分别给出了这四种图到Event-B的转换方法,并将该系统的转换方法应用到对安全性和可靠性要求较高的电梯控制系统中。基于该实例的研究,验证了UML到Event-B系统性转换方法的可行性和有效性。UML到Event-B的系统转换方法不仅有利于UML的精确化和软件从业人员的使用,而且增强了形式化方法的可理解性,有利于形式化方法的推广和应用。

Rainfall-runoff modeling for storm events in a coastal forest catchmen t using neural networks

The process of transformation of rainfall into runoff over a catchment is very complex and highly nonlinear and exhibits both tempor al and spatial variabilities. In this article, a rainfall-runoff model using th e artificial neural networks (ANN) is proposed for simula ting the runoff in storm events. The study uses the data from a coa stal forest catchment located in Seto Inland Sea, Japan. This article studies the accuracy of the short-term rainfall forecast obta ined by ANN time-series analysis techniques and using antecedent rainfa ll depths and stream flow as the input information. The verification results from the proposed model indicate that the approach of ANN rai nfall-runoff model presented in this paper shows a reasonable agreement in rainfall-runoff modeling with high accuracy.

Qualitative analysis for state/event fault trees using formal model checking

A state/event fault tree(SEFT)is a modeling technique for describing the causal chains of events leading to failure in software-controlled complex systems.Such systems are ubiquitous in all areas of everyday life,and safety and reliability analyses are increasingly required for these systems.SEFTs combine elements from the traditional fault tree with elements from state-based techniques.In the context of the real-time safety-critical systems,SEFTs do not describe the time properties and important timedependent system behaviors that can lead to system failures.Further,SEFTs lack the precise semantics required for formally modeling time behaviors.In this paper,we present a qualitative analysis method for SEFTs based on transformation from SEFT to timed automata(TA),and use the model checker UPPAAL to verify system requirements’properties.The combination of SEFT and TA is an important step towards an integrated design and verification process for real-time safety-critical systems.Finally,we present a case study of a powerboat autopilot system to confirm our method is viable and valid after achieving the verification goal step by step.

Quasi-periodic events on structured earthquake models

There has been much interest in studying quasi-periodic events on earthquake models.Here we investigate quasiperiodic events in the avalanche time series on structured earthquake models by the analysis of the autocorrelation function and the fast Fourier transform.For random spatial earthquake models, quasi-periodic events are robust and we obtain a simple rule for a period that is proportional to the choice of unit time and the dissipation of the system.Moreover, computer simulations validate this rule for two-dimensional lattice models and cycle graphs, but our simulation results also show that small-world models, scale-free models, and random rule graphs do not have periodic phenomena.Although the periodicity of avalanche does not depend on the criticality of the system or the average degree of the system or the size of the system,there is evidence that it depends on the time series of the average force of the system.

A Study on the Evolution of Mechanism of Infectious Disease Analysis Model of Event Using Micro-Blog Platform

After the occurrence of unexpected group events of network, the relevant opinion information will spread rapidly through micro-blog, and the negative public opinion information will aggravate the unexpected the group events to upgrade and expand the scope of harm. It is difficult to deal. So public opinion control is very important. In this paper, we establish an influence model for spreading of public opinion based on SIR model. Through the political analysis, this paper finds that the network group events will subside, but the influence scope, time and ability of event cannot be ignored. As a result of this study, the corresponding strategies are put forward in this paper.

气候变化与碳中和

工业化以来化石燃料的广泛使用使大气中的二氧化碳浓度急剧升高,造成全球气候变暖、极端天气气候事件频发。为有效应对和减缓气候变化,国际社会通过《巴黎协定》设定了2℃和1.5℃温控目标,由此提出了碳中和的概念。文章介绍了全球变暖的基本事实、人类碳排放对工业化以来全球变暖的作用,归纳了关于未来气候变化的主要结果,阐释了1.5/2℃温升阈值与碳中和的关系,概述了国际社会为有效应对全球变暖而在减少碳排放方面的努力。

Test of newly developed conceptual hydrological model for simulation of rain-on-snow events in forested watershed

A conceptual hydrological model that links the Xin＇anjiang hydrological model and a physically based snow energy and mass balance model, described as the XINSNOBAL model, was developed in this study for simulating rain-on-snow events that commonly occur in the Pacific Northwest of the United States. The resultant model was applied to the Lookout Creek Watershed in the H. J. Andrews Experimental Forest in the western Cascade Mountains of Oregon, and its ability to simulate streamflow was evaluated. The simulation was conducted at 24-hour and one-hour time scales for the period of 1996 to 2005. The results indicated that runoffand peak discharge could be underestimated if snowpack accumulation and snowmelt under rain-on-snow conditions were not taken into account. The average deterministic coefficient of the hourly model in streamflow simulation in the calibration stage was 0.837, which was significantly improved over the value of 0.762 when the Xin＇anjiang model was used alone. Good simulation performance of the XINSNOBAL model in the WS 10 catchment, using the calibrated parameter of the Lookout Creek Watershed for proxy-basin testing, demonstrates that transplanting model parameters between similar watersheds can orovide a useful tool for discharge forecastin~, in un^au^ed basins.