Object-oriented Petri nets (OPNs) is extended into stochastic object-oriented Petri nets (SOPNs) by associating the OPN of an object with stochastic transitions and introducing stochastic places. The stochastic transi...Object-oriented Petri nets (OPNs) is extended into stochastic object-oriented Petri nets (SOPNs) by associating the OPN of an object with stochastic transitions and introducing stochastic places. The stochastic transition of the SOPNs of a production resources can be used to model its reliability, while the SOPN of a production resource can describe its performance with reliability considered. The SOPN model of a case production system is built to illustrate the relationship between the system's performances and the failures of individual production resources.展开更多
Modern satellite propulsion systems are generally designed to fulfill multiphase-missions.Traditional reliability modelling methods have problems of inadequate depict capacity considering complex systems such as satel...Modern satellite propulsion systems are generally designed to fulfill multiphase-missions.Traditional reliability modelling methods have problems of inadequate depict capacity considering complex systems such as satellite propulsion system.An extended object-oriented Petri net(EOOPN)method was proposed to facilitate the reliability modelling of satellite propulsion system in the paper.The proposed method was specified for modelling of phased mission system,and it could be implemented by generating combination of Petri net(PN)principles and object-oriented(OO)programming.The effectiveness of the proposed method was demonstrated through the reliability modelling of a satellite propulsion system with EOOPN.The major advantage of the proposed method is that the dimension of net model can be reduced significantly,and phased mission system at system,phase,or component levels can be respectively depicted.Furthermore,the state-space explosion problem is solved by the proposed EOOPN model efficiently.展开更多
In the developing course of the information system, the modeling method of information system and model expressing problem are very important. This paper through discussing the facing object of Petri network, expatiat...In the developing course of the information system, the modeling method of information system and model expressing problem are very important. This paper through discussing the facing object of Petri network, expatiates the basic problem of how to set up the business procedure model on the basis of Petri network, and shows the expressing and storing methods of the model in computer way.展开更多
Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detecti...Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detection approaches, ranging from traditional heuristic algorithms to machine learning methods, are used to identify these defects. Ensemble learning methods have strengthened the detection of these defects. However, existing approaches do not simultaneously exploit the capabilities of extracting relevant features from pre-trained models and the performance of neural networks for the classification task. Therefore, our goal has been to design a model that combines a pre-trained model to extract relevant features from code excerpts through transfer learning and a bagging method with a base estimator, a dense neural network, for defect classification. To achieve this, we composed multiple samples of the same size with replacements from the imbalanced dataset MLCQ1. For all the samples, we used the CodeT5-small variant to extract features and trained a bagging method with the neural network Roberta Classification Head to classify defects based on these features. We then compared this model to RandomForest, one of the ensemble methods that yields good results. Our experiments showed that the number of base estimators to use for bagging depends on the defect to be detected. Next, we observed that it was not necessary to use a data balancing technique with our model when the imbalance rate was 23%. Finally, for blob detection, RandomForest had a median MCC value of 0.36 compared to 0.12 for our method. However, our method was predominant in Long Method detection with a median MCC value of 0.53 compared to 0.42 for RandomForest. These results suggest that the performance of ensemble methods in detecting structural development defects is dependent on specific defects.展开更多
Recently automotive nets are adopted to solve increasing problems in automotive electronic systems.Technologies of automotive local area network from CAN and LIN can solve the problems of the increasing of wire bunch ...Recently automotive nets are adopted to solve increasing problems in automotive electronic systems.Technologies of automotive local area network from CAN and LIN can solve the problems of the increasing of wire bunch weight and lack in module installation space.However,the multilayer automotive nets software becomes more and more complex,and the development expense is difficult to predict and to keep in check.In this paper,the modeling method of hierarchical automotive nets and the substitution operation based on object-oriented colored Petri net(OOCPN) are proposed.The OOCPN model which analyzes the software structure and validates the collision mechanism of CAN/LIN bus can speed the automobile system development.First,the subsystems are divided and modeled by object-oriented Petri net(OOPN).According to the sets of message sharing relations,the message ports among them are set and the communication gate transitions are defined.Second,the OOPN model is substituted step by step until the inner objects in the automotive body control modules(BCM) are indivisible and colored by colored Petri net(CPN).And the color subsets mark the node messages for the collision mechanism.Third,the OOCPN model of the automotive body CAN/LIN nets is assembled,which keeps the message sets and the system can be expanded.The proposed model is used to analyze features of information sharing among the objects,and it is also used to describe each subsystem real-time behavior of processing messages and implemental device controllers operating,and puts forward a reasonable software framework for the automotive body control subsystem.The research can help to design the communication model in the automotive body system effectively and provide a convenient and rapid way for developing the logical hierarchy software.展开更多
随着信息化与工业化的融合不断加深,工业控制系统中信息域与物理域交叉部分越来越多,传统信息系统的网络攻击会威胁工业控制系统网络。传统的工业控制系统安全评估方法只考虑功能安全的风险,而忽略了信息安全风险对功能安全的影响。文...随着信息化与工业化的融合不断加深,工业控制系统中信息域与物理域交叉部分越来越多,传统信息系统的网络攻击会威胁工业控制系统网络。传统的工业控制系统安全评估方法只考虑功能安全的风险,而忽略了信息安全风险对功能安全的影响。文中提出一种基于改进petri网的工业控制系统功能安全和信息安全一体化风险建模方法(Safety and Security Petri Net Risk Assessment,SSPN-RA),其中包括一体化风险识别、一体化风险分析、一体化风险评估3个步骤。所提方法首先识别并抽象化工业控制系统中的功能安全与信息安全数据,然后在风险分析过程中通过构造结合Kill Chain的petri网模型,分析出功能安全与信息安全中所存在的协同攻击路径,对petri网中功能安全与信息安全节点进行量化。同时,通过安全事件可能性以及其造成的各类损失计算出风险值,实现对工业控制系统的一体化风险评估。在开源的仿真化工工业控制系统下验证该方法的可行性,并与功能安全故障树分析和信息安全攻击树分析进行对比。实验结果表明,所提方法能够定量地得到工业控制系统的风险值,同时也解决了功能安全与信息安全单一领域分析无法识别的信息物理协同攻击和安全风险问题。展开更多
近年来室内燃气事故多发,而燃气用户风险意识淡薄、户内安全检查难度大。针对现行室内燃气安全管理技术多为静态主观评估的局限性,构建了基于模糊Petri网(Fuzzy Petri Net,FPN)的风险计算规则,提出了结合粒子群优化算法(Particles Swarm...近年来室内燃气事故多发,而燃气用户风险意识淡薄、户内安全检查难度大。针对现行室内燃气安全管理技术多为静态主观评估的局限性,构建了基于模糊Petri网(Fuzzy Petri Net,FPN)的风险计算规则,提出了结合粒子群优化算法(Particles Swarm Optimization,PSO)和FPN的室内燃气泄漏动态风险评估模型。首先,应用Petri网的直观图像描述和异步并发处理能力建立室内燃气泄漏事故风险演化的拓扑结构模型,借助FPN的模糊推理能力处理风险传播的不确定性;然后,根据燃气运维数据,融合PSO动态更新初始参数,提高风险评估的准确性。结果表明,基于PSO-FPN的室内风险评估方法可弱化燃气公司安检人员分析的主观不确定性,更为准确地量化风险因子演化过程,实现室内燃气泄漏风险的动态分析,有效支持户内燃气泄漏风险管控。展开更多
基金This project is supported by National Natural Science Foundation of China (No.50085003).
文摘Object-oriented Petri nets (OPNs) is extended into stochastic object-oriented Petri nets (SOPNs) by associating the OPN of an object with stochastic transitions and introducing stochastic places. The stochastic transition of the SOPNs of a production resources can be used to model its reliability, while the SOPN of a production resource can describe its performance with reliability considered. The SOPN model of a case production system is built to illustrate the relationship between the system's performances and the failures of individual production resources.
文摘Modern satellite propulsion systems are generally designed to fulfill multiphase-missions.Traditional reliability modelling methods have problems of inadequate depict capacity considering complex systems such as satellite propulsion system.An extended object-oriented Petri net(EOOPN)method was proposed to facilitate the reliability modelling of satellite propulsion system in the paper.The proposed method was specified for modelling of phased mission system,and it could be implemented by generating combination of Petri net(PN)principles and object-oriented(OO)programming.The effectiveness of the proposed method was demonstrated through the reliability modelling of a satellite propulsion system with EOOPN.The major advantage of the proposed method is that the dimension of net model can be reduced significantly,and phased mission system at system,phase,or component levels can be respectively depicted.Furthermore,the state-space explosion problem is solved by the proposed EOOPN model efficiently.
文摘In the developing course of the information system, the modeling method of information system and model expressing problem are very important. This paper through discussing the facing object of Petri network, expatiates the basic problem of how to set up the business procedure model on the basis of Petri network, and shows the expressing and storing methods of the model in computer way.
文摘Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detection approaches, ranging from traditional heuristic algorithms to machine learning methods, are used to identify these defects. Ensemble learning methods have strengthened the detection of these defects. However, existing approaches do not simultaneously exploit the capabilities of extracting relevant features from pre-trained models and the performance of neural networks for the classification task. Therefore, our goal has been to design a model that combines a pre-trained model to extract relevant features from code excerpts through transfer learning and a bagging method with a base estimator, a dense neural network, for defect classification. To achieve this, we composed multiple samples of the same size with replacements from the imbalanced dataset MLCQ1. For all the samples, we used the CodeT5-small variant to extract features and trained a bagging method with the neural network Roberta Classification Head to classify defects based on these features. We then compared this model to RandomForest, one of the ensemble methods that yields good results. Our experiments showed that the number of base estimators to use for bagging depends on the defect to be detected. Next, we observed that it was not necessary to use a data balancing technique with our model when the imbalance rate was 23%. Finally, for blob detection, RandomForest had a median MCC value of 0.36 compared to 0.12 for our method. However, our method was predominant in Long Method detection with a median MCC value of 0.53 compared to 0.42 for RandomForest. These results suggest that the performance of ensemble methods in detecting structural development defects is dependent on specific defects.
基金supported by National Natural Science Foundation of China (Grant No. 60873003)
文摘Recently automotive nets are adopted to solve increasing problems in automotive electronic systems.Technologies of automotive local area network from CAN and LIN can solve the problems of the increasing of wire bunch weight and lack in module installation space.However,the multilayer automotive nets software becomes more and more complex,and the development expense is difficult to predict and to keep in check.In this paper,the modeling method of hierarchical automotive nets and the substitution operation based on object-oriented colored Petri net(OOCPN) are proposed.The OOCPN model which analyzes the software structure and validates the collision mechanism of CAN/LIN bus can speed the automobile system development.First,the subsystems are divided and modeled by object-oriented Petri net(OOPN).According to the sets of message sharing relations,the message ports among them are set and the communication gate transitions are defined.Second,the OOPN model is substituted step by step until the inner objects in the automotive body control modules(BCM) are indivisible and colored by colored Petri net(CPN).And the color subsets mark the node messages for the collision mechanism.Third,the OOCPN model of the automotive body CAN/LIN nets is assembled,which keeps the message sets and the system can be expanded.The proposed model is used to analyze features of information sharing among the objects,and it is also used to describe each subsystem real-time behavior of processing messages and implemental device controllers operating,and puts forward a reasonable software framework for the automotive body control subsystem.The research can help to design the communication model in the automotive body system effectively and provide a convenient and rapid way for developing the logical hierarchy software.
文摘随着信息化与工业化的融合不断加深,工业控制系统中信息域与物理域交叉部分越来越多,传统信息系统的网络攻击会威胁工业控制系统网络。传统的工业控制系统安全评估方法只考虑功能安全的风险,而忽略了信息安全风险对功能安全的影响。文中提出一种基于改进petri网的工业控制系统功能安全和信息安全一体化风险建模方法(Safety and Security Petri Net Risk Assessment,SSPN-RA),其中包括一体化风险识别、一体化风险分析、一体化风险评估3个步骤。所提方法首先识别并抽象化工业控制系统中的功能安全与信息安全数据,然后在风险分析过程中通过构造结合Kill Chain的petri网模型,分析出功能安全与信息安全中所存在的协同攻击路径,对petri网中功能安全与信息安全节点进行量化。同时,通过安全事件可能性以及其造成的各类损失计算出风险值,实现对工业控制系统的一体化风险评估。在开源的仿真化工工业控制系统下验证该方法的可行性,并与功能安全故障树分析和信息安全攻击树分析进行对比。实验结果表明,所提方法能够定量地得到工业控制系统的风险值,同时也解决了功能安全与信息安全单一领域分析无法识别的信息物理协同攻击和安全风险问题。
文摘近年来室内燃气事故多发,而燃气用户风险意识淡薄、户内安全检查难度大。针对现行室内燃气安全管理技术多为静态主观评估的局限性,构建了基于模糊Petri网(Fuzzy Petri Net,FPN)的风险计算规则,提出了结合粒子群优化算法(Particles Swarm Optimization,PSO)和FPN的室内燃气泄漏动态风险评估模型。首先,应用Petri网的直观图像描述和异步并发处理能力建立室内燃气泄漏事故风险演化的拓扑结构模型,借助FPN的模糊推理能力处理风险传播的不确定性;然后,根据燃气运维数据,融合PSO动态更新初始参数,提高风险评估的准确性。结果表明,基于PSO-FPN的室内风险评估方法可弱化燃气公司安检人员分析的主观不确定性,更为准确地量化风险因子演化过程,实现室内燃气泄漏风险的动态分析,有效支持户内燃气泄漏风险管控。
