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    Robotic Process Mining
    Dumas, M ; Rosa, ML ; Leno, V ; Polyvyanyy, A ; Maggi, FM ; van der Aalst, WMP ; Carmona, J (Springer, Cham, 2022-06-27)
    User interaction logs allow us to analyze the execution of tasks in a business process at a finer level of granularity than event logs extracted from enterprise systems. The fine-grained nature of user interaction logs open up a number of use cases. For example, by analyzing such logs, we can identify best practices for executing a given task in a process, or we can elicit differences in performance between workers or between teams. Furthermore, user interaction logs allow us to discover repetitive and automatable routines that occur during the execution of one or more tasks in a process. Along this line, this chapter introduces a family of techniques, called Robotic Process Mining (RPM), which allow us to discover repetitive routines that can be automated using robotic process automation technology. The chapter presents a structured landscape of concepts and techniques for RPM, including techniques for user interaction log preprocessing, techniques for discovering frequent routines, notions of routine automatability, as well as techniques for synthesizing executable routine specifications for robotic process automation.
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    Children in the Roman Farming Economy: Evidence, Problems and Possibilities
    Lewit, T ; Van Limbergen, D ; Hoffelinck, A ; Taelman, D (Palgrave Macmillan, 2022)
    Children’s roles within Roman farming have been little explored, despite a flood of recent work on many aspects of childhood in Roman society. Children were an important economic cohort, however, and would have made up a large group within the potential labour force of any farm. Close examination of textual and visual sources suggests that children played specific economic roles. Further, ethnographic studies on children’s farm work in the Mediterranean and beyond in more recent times reveal considerable correspondence with ancient practices. The allocation of certain categories of tasks to children appears highly consistent across time and geographic location. By combining these groups of evidence, we can consider the extent to which children’s labour would have contributed to the Roman farming economy. Children’s work should not be seen as insignificant or marginal: rather, it played an essential part, as in later times, within the economics of farm work.
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    Australian Family Property Law Current Issues and Challenges
    Fehlberg, B ; Sarmas, L ; Choudhry, S ; Herring, J (CAMBRIDGE UNIV PRESS, 2019-01-01)
    There are several reasons why it seems important to focus on Australian family property law now. In May 2017, the Australian Federal Attorney General announced a major review of the family law system, to be undertaken by the Australian Law Reform Commission. The inquiry's widely cast terms of final report is due by 31 March 2019.
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    Data and Process Resonance: Identifier Soundness for Models of Information Systems
    van der Werf, JMEM ; Rivkin, A ; Polyvyanyy, A ; Montali, M (Springer International Publishing, 2022-01-01)
    A model of an information system describes its processes and how these processes manipulate data objects. Object-aware extensions of Petri nets focus on modeling the life-cycle of objects and their interactions. In this paper, we focus on Petri nets with identifiers, where identifiers are used to refer to objects. These objects should “behave” well in the system from inception to termination. We formalize this intuition in the notion of identifier soundness, and show that although this property is undecidable in general, useful subclasses exist that guarantee identifier soundness by construction.
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    Bootstrapping Generalization of Process Models Discovered from Event Data
    Polyvyanyy, A ; Moffat, A ; García-Bañuelos, L (Springer International Publishing, 2022-01-01)
    Process mining extracts value from the traces recorded in the event logs of IT-systems, with process discovery the task of inferring a process model for a log emitted by some unknown system. Generalization is one of the quality criteria applied to process models to quantify how well the model describes future executions of the system. Generalization is also perhaps the least understood of those criteria, with that lack primarily a consequence of it measuring properties over the entire future behavior of the system when the only available sample of behavior is that provided by the log. In this paper, we apply a bootstrap approach from computational statistics, allowing us to define an estimator of the model’s generalization based on the log it was discovered from. We show that standard process mining assumptions lead to a consistent estimator that makes fewer errors as the quality of the log increases. Experiments confirm the ability of the approach to support industry-scale data-driven systems engineering.
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    Process Querying: Methods, Techniques, and Applications
    Polyvyanyy, A ; Polyvyanyy, A (Springer International Publishing, 2022)
    Process querying studies concepts and methods from fields like Big data, process modeling and analysis, business process intelligence, and process analytics and applies them to retrieve and manipulate real-world and designed processes. This chapter reviews state-of-the-art methods for process querying, summarizes techniques used to implement process querying methods, discusses typical applications of process querying, and identifies research gaps and suggests directions for future research in process querying.
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    Process Query Language
    Polyvyanyy, A (Springer International Publishing, 2022)
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    Introduction to Process Querying
    Polyvyanyy, A (Springer International Publishing, 2022)
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    Making and Marketing Porcelain in Eighteenth-Century London
    Martin, M ; Garrioch, D (Brill, 2022)
    This volume moves away from the model of knowledge 'transfer' and, drawing on new understandings of artisan work, considers the links between artisan creativity and mobility.
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    Early Detection and Classification of Patient-Ventilator Asynchrony Using Machine Learning
    Gao, E ; Ristanoski, G ; Aickelin, U ; Berlowitz, D ; Howard, M (Springer International Publishing, 2022-01-01)