494,503 research outputs found

    Discovering Hierarchical Process Models: an Approach Based on Events Clustering

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    Process mining is a field of computer science that deals with discovery and analysis of process models based on automatically generated event logs. Currently, many companies use this technology for optimization and improving their processes. However, a discovered process model may be too detailed, sophisticated and difficult for experts to understand. In this paper, we consider the problem of discovering a hierarchical business process model from a low-level event log, i.e., the problem of automatic synthesis of more readable and understandable process models based on information stored in event logs of information systems. Discovery of better structured and more readable process models is intensively studied in the frame of process mining research from different perspectives. In this paper, we present an algorithm for discovering hierarchical process models represented as two-level workflow nets. The algorithm is based on predefined event ilustering so that the cluster defines a sub-process corresponding to a high-level transition at the top level of the net. Unlike existing solutions, our algorithm does not impose restrictions on the process control flow and allows for concurrency and iteration

    Hardware synthesis from high-level scenario specifications

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    PhD ThesisThe behaviour of many systems can be partitioned into scenarios. These facilitate engineersā€™ understanding of the specifications, and can be composed into efficient implementations via a form of high-level synthesis. In this work, we focus on highly concurrent systems, whose scenarios are typically described using concurrency models such as partial orders, Petri nets and data-flow structures. In this thesis, we study different aspects of hardware synthesis from high-level scenario specifications. We propose new formal models to simplify the specification of concurrent systems, and algorithms for hardware synthesis and verification of the scenario-based models of such systems. We also propose solutions for mapping scenariobased systems on silicon and evaluate their efficiency. Our experiments show that the proposed approaches improve the design of concurrent systems. The new formalisms can break down complex specifications into significantly simpler scenarios automatically, and can be used to fully model the dataflow of operations of reconfigurable event-driven systems. The proposed heuristics for mapping the scenarios of a system to a digital circuit supports encoding constraints, unlike existing methods, and can cope with specifications comprising hundreds of scenarios at the cost of only 5% of area overhead compared to exact algorithms. These experiments are driven by three case studies: (1) hardware synthesis of control architectures, e.g. microprocessor control units; (2) acceleration of the ordinal pattern encoding, i.e. an algorithm for detecting repetitive patterns within data streams; (3) and acceleration of computational drug discovery, i.e. computation of shortest paths in large protein-interaction networks. Our findings are employed to design two prototypes, which have a practical value for the considered case studies. The ordinal pattern encoding accelerator is asynchronous, highly resilient to unstable voltage supply, and designed to perform a range of computations via runtime reconfiguration. The drug discovery accelerator is synchronous, and up to three orders of magnitude faster than conventional software implementations

    Concurrent Design of Embedded Control Software

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    Embedded software design for mechatronic systems is becoming an increasingly time-consuming and error-prone task. In order to cope with the heterogeneity and complexity, a systematic model-driven design approach is needed, where several parts of the system can be designed concurrently. There is however a trade-off between concurrency efficiency and integration efficiency. In this paper, we present a case study on the development of the embedded control software for a real-world mechatronic system in order to evaluate how we can integrate concurrent and largely independent designed embedded system software parts in an efficient way. The case study was executed using our embedded control system design methodology which employs a concurrent systematic model-based design approach that ensures a concurrent design process, while it still allows a fast integration phase by using automatic code synthesis. The result was a predictable concurrently designed embedded software realization with a short integration time

    Realizing live sequence charts in SystemVerilog.

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    The design of an embedded control system starts with an investigation of properties and behaviors of the process evolving within its environment, and an analysis of the requirement for its safety performance. In early stages, system requirements are often specified as scenarios of behavior using sequence charts for different use cases. This specification must be precise, intuitive and expressive enough to capture different aspects of embedded control systems. As a rather rich and useful extension to the classical message sequence charts, live sequence charts (LSC), which provide a rich collection of constructs for specifying both possible and mandatory behaviors, are very suitable for designing an embedded control system. However, it is not a trivial task to realize a high-level design model in executable program codes effectively and correctly. This paper tackles the challenging task by providing a mapping algorithm to automatically synthesize SystemVerilog programs from given LSC specifications
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