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Recently, cross-department business processes are becoming more and more complex. Different kinds of coordination patterns exist among different departments, which make modeling and analysis work more difficult. To our best knowledge, there is no formal method to give systematic modeling and verification for the cross-department processes when considering different kinds of coordination patterns among different departments. This paper proposes such a method based on Petri nets. The WF-net model extended with resource and message factors, RM_WF_Net for short, is first introduced. Then, the formal model of tasks is proposed and its coordination relations are given. Next, RM_WF_Net modeling for intradepartment processes is investigated and cross-department coordination patterns, including message interaction pattern, resource interaction pattern, task collaboration pattern, procedure abstract, service outsourcing pattern, and process activation pattern, are formally defined. The soundness of the RM_WF_Net is verified based on the reachability graph. A running case of the cross-department medical diagnosis business process is given to validate our proposed method. [ABSTRACT FROM AUTHOR]

Petri nets are suitable for modeling and analysis of business processes. However, the lack of data concepts often makes Petri-net-based models excessively large and difficult to analyze especially when process logic is sensitive to changes of process attribute values. Emergency treatment processes are a typical example of this situation. To solve the aforementioned problems, this paper proposes a new hierarchical Petri net model for modeling and verification of emergency treatment processes. The hierarchical Petri net model includes three separate but closely related models, i.e., a business process logic net, a business process semantic net, and a set of case models. Business process logic nets are used to model the task dependencies disregarding semantic information. Business process semantic nets introduce data concepts to business process logic nets to model semantic information such as process attributes or conditions of sequence flows. Case models are used to model the practical routes of specific business instances. Based on the three models, a formal verification algorithm of an emergency treatment process is presented. Finally, the hierarchical modeling and verification methods are validated by an emergency treatment process of highways under snow/ice weather conditions. [ABSTRACT FROM AUTHOR]

Coupled behaviors refer to the activities of one to many actors who are associated with each other in terms of certain relationships. With increasing network and community-based events and applications, such as group-based crime and social network interactions, behavior coupling contributes to the causes of eventual business problems. Effective approaches for analyzing coupled behaviors are not available, since existing methods mainly focus on individual behavior analysis. This paper discusses the problem of Coupled Behavior Analysis (CBA) and its challenges. A Coupled Hidden Markov Model (CHMM)-based approach is illustrated to model and detect abnormal group-based trading behaviors. The CHMM models cater for: 1) multiple behaviors from a group of people, 2) behavioral properties, 3) interactions among behaviors, customers, and behavioral properties, and 4) significant changes between coupled behaviors. We demonstrate and evaluate the models on order-book-level stock tick data from a major Asian exchange and demonstrate that the proposed CHMMs outperforms HMM-only for modeling a single sequence or combining multiple single sequences, without considering coupling relationships to detect anomalies. Finally, we discuss interaction relationships and modes between coupled behaviors, which are worthy of substantial study. [ABSTRACT FROM AUTHOR]