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.

Comparisons of Maximum Likelihood Estimates and Bayesian Estimates for the Discretized Discovery Process Model

A Bayesian approach using Markov chain Monte Carlo algorithms has been developed to analyze Smith’s discretized version of the discovery process model. It avoids the problems involved in the maximum likelihood method by effectively making use of the information from the prior distribution and that from the discovery sequence according to posterior probabilities. All statistical inferences about the parameters of the model and total resources can be quantified by drawing samples directly from the joint posterior distribution. In addition, statistical errors of the samples can be easily assessed and the convergence properties can be monitored during the sampling. Because the information contained in a discovery sequence is not enough to estimate all parameters, especially the number of fields, geologically justified prior information is crucial to the estimation. The Bayesian approach allows the analyst to specify his subjective estimates of the required parameters and his degree of uncertainty about the estimates in a clearly identified fashion throughout the analysis. As an example, this approach is applied to the same data of the North Sea on which Smith demonstrated his maximum likelihood method. For this case, the Bayesian approach has really improved the overly pessimistic results and downward bias of the maximum likelihood procedure.

Modeling and Simulation of Textile Supply Chain through Colored Petri Nets

The purpose of this paper is to describe the business process modeling and simulation of a textile supply chain using Colored Petri nets. Our model takes into account both the source process and delivery logistics that exist between any two members of supply chain;moreover, we model other activities performed by the company such as manufacturing clothing. The model has been built to acquire a better understanding about the behavior of a textile company in the fulfillment of requests from costumers. The model has been built using CPN Tools. This model was built with modules for activities of the supply chain textile, e.g. receiving orders of customers, determination of production plan, procurement raw material, transportation of raw material, production and delivering products to customers. This modularized model offers some advantages to represent complex supply chains according to their structure and requirements. Thus, we can add modules easily depending on the necessary activities.

Numerical Modelling of the Powder Metallurgical Manufacturing Chain of High Strength Sintered Gears

This paper presents a digital model for the powder metallurgical(PM)production chain of high-performance sintered gears based on an integrated computational materials engineering(ICME)platform.Discrete and finite element methods(DEM and FEM)were combined to describe the macroscopic material response to the thermomechanical loads and process conditions during the entire production process.The microstructural evolution during the sintering process was predicted on the meso-scale using a Monte-Carlo Model.The effective elastic properties were determined by a homogenization method based on modelling a representative volume element(RVE).The results were subsequently used for the FE modelling of the heat treatment process.Through the development of multi-scale models,it was possible obtain characteristics of the microstructural features.The predicted hardness and residual stress distributions allowed the calculation of the tooth root load bearing capacity of the heat-treated sintered gears.

Option Pricing and Hedging under a Markov Switching Lévy Process Model

In this paper, we consider a Markov switching Lévy process model in which the underlying risky assets are driven by the stochastic exponential of Markov switching Lévy process and then apply the model to option pricing and hedging. In this model, the market interest rate, the volatility of the underlying risky assets and the N-state compensator,depend on unobservable states of the economy which are modeled by a continuous-time Hidden Markov process. We use the MEMM(minimal entropy martingale measure) as the equivalent martingale measure. The option price using this model is obtained by the Fourier transform method. We obtain a closed-form solution for the hedge ratio by applying the local risk minimizing hedging.

A Stochastic SIVS Epidemic Model Based on Birth and Death Process

A new stochastic epidemic model, that is, a general continuous time birth and death chain model, is formulated based on a deterministic model including vaccination. We use continuous time Markov chain to construct the birth and death process. Through the Kolmogorov forward equation and the theory of moment generating function, the corresponding population expectations are studied. The theoretical result of the stochastic model and deterministic version is also given. Finally, numerical simulations are carried out to substantiate the theoretical results of random walk.

Modeling the Dynamics of the Random Demand Inventory Management System

At any given time, a product stock manager is expected to carry out activities to check his or her holdings in general and to monitor the condition of the stock in particular. He should monitor the level or quantity available of a given product, of any item. On the basis of the observation made in relation to the movements of previous periods, he may decide to order or not a certain quantity of products. This paper discusses the applicability of discrete-time Markov chains in making relevant decisions for the management of a stock of COTRA-Honey products. A Markov chain model based on the transition matrix and equilibrium probabilities was developed to help managers predict the likely state of the stock in order to anticipate procurement decisions in the short, medium or long term. The objective of any manager is to ensure efficient management by limiting overstocking, minimising the risk of stock-outs as much as possible and maximising profits. The determined Markov chain model allows the manager to predict whether or not to order for the period following the current period, and if so, how much.

基于AHP法的化工企业数字化供应链成熟度研究

人工智能、大数据等新兴技术推动着全球数字经济的发展,越来越多的制造业企业走上数字化转型的道路。数字化供应链将成为制造业企业发展的必然趋势,也是其数字化转型的关键。根据以往的研究成果,文章从企业战略管理、数字化技术应用、数字化供应链业务流程和组织文化四个维度建立化工企业数字化供应链成熟度评估指标模型,通过层次分析法,得出各指标评分。并以A公司为例进行实证分析,验证模型的科学性,得出成熟度等级,为相关企业数字化供应链的发展提供帮助。

“任务链+研学支架”教学模式的建构——新工科视角下“遥感数字图像处理”课教学改革

目前,传统教学在内容的系统性、认知活动高阶性、价值引领实效性、促学效果等方面存在着较严重的问题,为此,“遥感数字图像处理”课程基于新工科教学理念,以遥感技术的综合应用情境重构课程体系,开启“任务链+研学支架”教学模式,加强培养学生遥感应用能力和创新能力,以遥感技术服务社会需求为育人路径。新模式的构建,实现了应用与研学互动、研学与研教并举、育人与育才同构的效果,对同类型新工科课程具有借鉴意义。

我国医保谈判药品“双通道”管理政策执行困境及推进策略

目的为我国医保谈判药品“双通道”管理政策的顺利实施落地提供参考。方法基于史密斯政策执行过程模型,从实施细则与监管体系、药品遴选、药品配备和质量控制、医保基金运行状况和信息化能力4个方面对医保谈判药品“双通道”政策的执行困境进行分析,并提出相应推进策略。结果与结论我国医保谈判药品“双通道”政策可能存在政策实施细则和全流程监管体系不够明确,部分医保谈判药品纳入“双通道”管理的适宜性和可操作性有待斟酌,药品配备和质量控制方面存在难点,各地医保基金管理和运行状况存在差异以及信息化能力不足等执行困境。对此,本研究认为可通过完善“双通道”政策实施细则、提高“双通道”药品目录合理性、建立“双通道”药店动态退出机制、推行专业化配送服务、完善电子处方流转平台等措施来推动“双通道”政策的实施落地。

高等院校教师人才流动的Markov-chain预测模型

介绍并解析随机过程理论中的马尔科夫过程与马尔科夫链;针对高等院校教师人才流动变化过程,利用马尔科夫过程分析方法建立描述人员流动变化趋势的Markov-chain预测模型,详细阐述了模型的算法步骤.以某所高等院校教师人才流动的状态转移数据作为算例,运用新建立的预测模型,对该院校教师人才的流动趋势做出了预测分析.最后,将教师进修状态纳入分析范围,进行了教师职业生涯和职务发展趋势预测的深入分析.应用模型对实际算例的求解结果表明:Markov-chain预测模型及算法,叙述简洁、运算方便,为高等院校教师人才流动,乃至其他行业人才流动的预测提供了一种新的、有效的思路和方法.

基于Petri网的区块链农产品溯源系统建模与优化

构建一款基于Petri网的区块链农产品溯源系统模型.分析农产品溯源系统流程,建立基于Petri网的区块链农产品溯源系统模型.采用PIPE软件和PM4PY对Petri网模型的可靠性进行验证.验证结果表明,优化后的模型具有安全性、有界性、稳定性.

基于博弈论组合赋权-云模型的生鲜农产品冷链物流服务水平评价

为合理科学地评价生鲜农产品冷链物流服务水平,提出一种基于博弈论组合赋权-云模型的生鲜农产品冷链物流服务水平评价模型。首先,建立一套生鲜农产品冷链物流服务水平评价指标体系;其次,运用博弈论组合赋权法修正层次分析法和熵权法确定的各评价指标权重;最后,运用正向云发生器和逆向云发生器计算出云模型数字特征和综合云,并运用贴近度进行评价结果判定。选择某城市H生鲜农产品冷链物流企业为研究对象,研究结果表明,H生鲜农产品冷链物流企业的物流服务水平为较高等级,模型稳定程度高、雾化程度低,具有较好的可行性和可靠性。

MULTI-DIMENSIONAL MARKOV CHAIN–BASED ANALYSIS OF CONFLICT PROBABILITY FOR SPECTRUM RESOURCE SHARING

In this paper, we consider the optimal problem of channels sharing with het-erogeneous traffic （real-time service and non-real-time service） to reduce the data conflict probability of users. Moreover, a multi-dimensional Markov chain model is developed to analyze the performance of the proposed scheme. Meanwhile, performance metrics are derived. Numerical results show that the proposed scheme can effectively reduce the forced termination probability, blocking probability and spectrum utilization.

Research on Model of Virtual Organization and Its Practice

This paper discusses an organizational model to be used for both conventional and virtual organizations. The model deals with variable relationships within an organization and provides a framework for overall organizational design that may include relationship among different design variables and external relationship with environment. Based on the researches of virtual organization, this paper also illustrates the new model of organization in the real world such as Beijing 2008 Olympic games and Dongfeng Automobile group.

数字节点链驱动的孪生工序动态模型构建

针对机加工三维工序模型重建过程繁琐、效率低等问题,提出了数字化的孪生工序动态模型生成方法;阐述了设计制造层次化数据信息数字化表达模型,构建了以加工特征为核心的信息集成的工艺孪生语义模型;将语义信息集成于工序节点中,通过分析节点间关联原则和属性机制,完成了以特征序列为加工主线的数字化工序节点链生成;通过数字空间三维特征工序谱模型及相关的构建算法,建立了基于数字节点链的具有拓扑结构的孪生工序动态模型;以典型箱体为例验证所提方法的可行性,该方法实现了三维模型的快速构建和语义信息的管理应用。

“稻谷—大米”价值链价格联系、价格形成及主要影响因素研究

构建“稻谷—大米”价值链,对“稻谷—大米”价值链上价格形成过程进行描述性统计分析,采用Johansen检验、格兰杰因果检验方法及VEC模型方法,对价值链上主要环节价格联系及其主要影响因素进行实证研究。研究表明,稻谷收购市场和大米零售市场存在长期均衡状态,稻谷收购市场和稻谷国内期货市场存在长期均衡状态,但短期价格传导效率较低;“稻谷—大米”价值链上产生的价格增值主要集中在大米零售、大米加工和农户稻谷出售环节;所谓“稻强米弱”造成大米加工企业普遍经营不善的说法不能得到必要证据支持;过于强调国有粮库“顺价销售”出库大米不利于实现以粮食自产为基础的粮食安全目标。最后提出继续实施稻谷最低收购价格政策和以实现粮食自产为基础的粮食安全目标等政策建议。

中断风险下汽车企业供应链弹性影响因素研究

受疫情、新的地缘政治冲突、半导体芯片持续短缺的影响,全球经济环境变得越来越复杂,汽车企业不断遭受着供应链中断风险,提高供应链弹性变得至关重要。针对中断下的汽车企业供应链弹性,文中筛选出13个影响因素(指标),利用解释结构模型(ISM)和交叉影响矩阵相乘法(MICMAC)对各影响因素相互关系进行分析,采用网络分析法(ANP)量化各指标的权重,识别出关键指标,为汽车企业增强供应链弹性、协调全球供应链运作提供理论指导。

Petri网在STM32主函数程序编写方法中的应用

利用Petri网对主函数程序编写方法建模,以图形化描述计算机编程中的逻辑关系,验证主函数程序逻辑的正确性与可行性.

计及源荷随机性的连锁故障高维模型及风险评估

针对传统事故链模型无法适应新能源的随机性,提出基于随机潮流和层次分析法的高维事故链模型。首先,建立新能源及充电站的概率模型,并采用半不变量法和Cornish-Fisher级数确定电网内的随机潮流;其次,基于层次分析法从有功越限、电压越限及非正常气候3个维度构建高维事故链模型,并依据综合风险值推测事故链初始环节集和中间环节的演化;然后,基于本文所提模型开展连锁故障风险评估工作;最后,以改进的IEEE39节点算例进行仿真验证,仿真结果表明所提模型能较好地适应新能源的随机性并能统筹多个影响因素。