Abstract. Business workflow assembles together a collection of tasks or activities in order to accomplish a business objective. Management of business workflows is facing many significant challenges, including in particular design, making changes, interoperations, etc. A key step in addressing these challenges is to develop techniques for mapping logical workflow specifications into executable workflow systems. In this paper we introduce a new artifact-centric workflow model called Artifact Conceptual Flow (ArtiFlow) and show that automated translation from ArtiFlow to BPEL is achievable. We also discuss technical issues in the translation.

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Since December 2019, a novel coronavirus (COVID-19) has spread all over the world, causing unpredictable economic losses and public fear. Although vaccines against this virus have been developed and administered for months, many countries still suffer from secondary COVID-19 infections, including the United Kingdom, France, and Malaysia. Observations of COVID-19 infections in the United Kingdom and France and their governance measures showed a certain number of similarities. A further investigation of these countries’ COVID-19 transmission patterns suggested that when a turning point appeared, the values of their stringency indices per population density (PSI) were nearly proportional to their absolute infection rate (AIR). To justify our assumptions, we developed a mathematical model named VSHR to predict the COVID-19 turning point for Malaysia. VSHR was first trained on 30-day infection records prior to the United Kingdom, Germany, France, and Belgium’s known turning points. It was then transferred to Malaysian COVID-19 data to predict this nation’s turning point. Given the estimated AIR parameter values in 5 days, we were now able to locate the turning point’s appearance on June 2nd, 2021. VSHR offered two improvements: (1) gathered countries into groups based on their SI patterns and (2) generated a model to identify the turning point for a target country within 5 days with 90% CI. Our research on COVID-19’s turning point for a country is beneficial for governments and clinical systems against future COVID-19 infections.

Dynamic substitution of conversational services during the execution of service orchestrations is a challenging issue in Service-Oriented Architecture. For a conversational service and its candidate substitute service, there may exist mismatches at interface level as well as protocol level. To make the service substitution consistent, it is essential to implement adaptation to overcome both types of mismatches. In this paper, we present an automatic approach to generate adaptation contract for conversational service substitution. Our approach is based on graph planning technique, which enables us to retrieve a solution in polynomial time. Experiments show that the proposed approach is potentially applicable for on-the-fly service substitution.

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