In this paper, we propose astochastic Petri net model P-timed Workflow (WPTSPN) to specify, verify, and analyze a business process (BP) of a Flexible Manufacturing System (FMS). After formalizing the semantics of our ...In this paper, we propose astochastic Petri net model P-timed Workflow (WPTSPN) to specify, verify, and analyze a business process (BP) of a Flexible Manufacturing System (FMS). After formalizing the semantics of our model, we illustrate how to verifysome of its properties (reachability, safety, boundedness, liveness, correctness, alive tokens, and security) in the P-Timed context. Next, we validate the relevance of the proposed model with MATLAB simulation through a specific FMS case study. Finally, we use a generalized truncated density function to predict the duration of a token’s sojourn (residence) in a timed place with respect to the sequence states of the global FMS workflow.展开更多
文摘目的:探讨胎盘生长因子(placental growth factor,PLGF)、可溶性fms样酪氨酸激酶-1(soluble fms-like tyrosine kinase-1,SFLT-1)和糖基化纤连蛋白(glycosylated fibronectin,GLYFN)检测对子痫前期的预测价值。方法:选择在无锡市妇幼保健院就诊的188例孕妇,分154例正常孕妇(对照组)和34例子痫前期患者(子痫组),应用免疫荧光法分别检测其在孕16~18周血清中PLGF、SFLT-1和GLYFN的浓度,比较子痫前期组和对照组各标志物的水平,并使用受试者操作特征曲线(receiver operating characteristic,ROC)对3种标志物的预测价值进行效能评估。结果:在妊娠中期,子痫前期组血清PLGF浓度低于对照组,SFLT-1及GLYFN浓度均高于对照组,3种标志物的差异均有统计学意义(3指标P=0.000)。95%置信区间的ROC曲线下面积(areas under the ROC curve,AUC)为,PLGF为0.941(0.907~0.974),SFLT-1为0.881(0.800~0.962),GLYFN为0.951(0.918~0.985),联合指标SFLT-1和GLYFN、3项指标联合检测在ROC曲线下面积(areas under the ROC curve,AUC)分别为0.968、0.986。结论:PLGF、SFLT-1、GLYFN 3种标志物水平在对照组和子痫前期组均存在明显差异,对子痫前期的发病具有一定的预测价值,SFLT-1联合PLGF、SFLT-1联合GLYFN、3项指标联合检测对子痫前期的预测价值高于任一单项指标。
文摘In this paper, we propose astochastic Petri net model P-timed Workflow (WPTSPN) to specify, verify, and analyze a business process (BP) of a Flexible Manufacturing System (FMS). After formalizing the semantics of our model, we illustrate how to verifysome of its properties (reachability, safety, boundedness, liveness, correctness, alive tokens, and security) in the P-Timed context. Next, we validate the relevance of the proposed model with MATLAB simulation through a specific FMS case study. Finally, we use a generalized truncated density function to predict the duration of a token’s sojourn (residence) in a timed place with respect to the sequence states of the global FMS workflow.
