21,360 research outputs found

    Supporting the reconciliation of models of object behaviour

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    This paper presents Reconciliation+, a method which identifies overlaps between models of software systems behaviour expressed as UML object interaction diagrams (i.e., sequence and/or collaboration diagrams), checks whether the overlapping elements of these models satisfy specific consistency rules and, in cases where they violate these rules, guides software designers in handling the detected inconsistencies. The method detects overlaps between object interaction diagrams by using a probabilistic message matching algorithm that has been developed for this purpose. The guidance to software designers on when to check for inconsistencies and how to deal with them is delivered by enacting a built-in process model that specifies the consistency rules that can be checked against overlapping models and different ways of handling violations of these rules. Reconciliation+ is supported by a toolkit. It has also been evaluated in a case study. This case study has produced positive results which are discussed in the paper

    Adaptive Process Management in Cyber-Physical Domains

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    The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time

    Data-driven Modeling and Coordination of Large Process Structures

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    In the engineering domain, the development of complex products (e.g., cars) necessitates the coordination of thousands of (sub-)processes. One of the biggest challenges for process management systems is to support the modeling, monitoring and maintenance of the many interdependencies between these sub-processes. The resulting process structures are large and can be characterized by a strong relationship with the assembly of the product; i.e., the sub-processes to be coordinated can be related to the different product components. So far, sub-process coordination has been mainly accomplished manually, resulting in high efforts and inconsistencies. IT support is required to utilize the information about the product and its structure for deriving, coordinating and maintaining such data-driven process structures. In this paper, we introduce the COREPRO framework for the data-driven modeling of large process structures. The approach reduces modeling efforts significantly and provides mechanisms for maintaining data-driven process structures

    A Process Modelling Framework Based on Point Interval Temporal Logic with an Application to Modelling Patient Flows

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    This thesis considers an application of a temporal theory to describe and model the patient journey in the hospital accident and emergency (A&E) department. The aim is to introduce a generic but dynamic method applied to any setting, including healthcare. Constructing a consistent process model can be instrumental in streamlining healthcare issues. Current process modelling techniques used in healthcare such as flowcharts, unified modelling language activity diagram (UML AD), and business process modelling notation (BPMN) are intuitive and imprecise. They cannot fully capture the complexities of the types of activities and the full extent of temporal constraints to an extent where one could reason about the flows. Formal approaches such as Petri have also been reviewed to investigate their applicability to the healthcare domain to model processes. Additionally, to schedule patient flows, current modelling standards do not offer any formal mechanism, so healthcare relies on critical path method (CPM) and program evaluation review technique (PERT), that also have limitations, i.e. finish-start barrier. It is imperative to specify the temporal constraints between the start and/or end of a process, e.g., the beginning of a process A precedes the start (or end) of a process B. However, these approaches failed to provide us with a mechanism for handling these temporal situations. If provided, a formal representation can assist in effective knowledge representation and quality enhancement concerning a process. Also, it would help in uncovering complexities of a system and assist in modelling it in a consistent way which is not possible with the existing modelling techniques. The above issues are addressed in this thesis by proposing a framework that would provide a knowledge base to model patient flows for accurate representation based on point interval temporal logic (PITL) that treats point and interval as primitives. These objects would constitute the knowledge base for the formal description of a system. With the aid of the inference mechanism of the temporal theory presented here, exhaustive temporal constraints derived from the proposed axiomatic system’ components serves as a knowledge base. The proposed methodological framework would adopt a model-theoretic approach in which a theory is developed and considered as a model while the corresponding instance is considered as its application. Using this approach would assist in identifying core components of the system and their precise operation representing a real-life domain deemed suitable to the process modelling issues specified in this thesis. Thus, I have evaluated the modelling standards for their most-used terminologies and constructs to identify their key components. It will also assist in the generalisation of the critical terms (of process modelling standards) based on their ontology. A set of generalised terms proposed would serve as an enumeration of the theory and subsume the core modelling elements of the process modelling standards. The catalogue presents a knowledge base for the business and healthcare domains, and its components are formally defined (semantics). Furthermore, a resolution theorem-proof is used to show the structural features of the theory (model) to establish it is sound and complete. After establishing that the theory is sound and complete, the next step is to provide the instantiation of the theory. This is achieved by mapping the core components of the theory to their corresponding instances. Additionally, a formal graphical tool termed as point graph (PG) is used to visualise the cases of the proposed axiomatic system. PG facilitates in modelling, and scheduling patient flows and enables analysing existing models for possible inaccuracies and inconsistencies supported by a reasoning mechanism based on PITL. Following that, a transformation is developed to map the core modelling components of the standards into the extended PG (PG*) based on the semantics presented by the axiomatic system. A real-life case (from the King’s College hospital accident and emergency (A&E) department’s trauma patient pathway) is considered to validate the framework. It is divided into three patient flows to depict the journey of a patient with significant trauma, arriving at A&E, undergoing a procedure and subsequently discharged. Their staff relied upon the UML-AD and BPMN to model the patient flows. An evaluation of their representation is presented to show the shortfalls of the modelling standards to model patient flows. The last step is to model these patient flows using the developed approach, which is supported by enhanced reasoning and scheduling

    A deliberative model for self-adaptation middleware using architectural dependency

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    A crucial prerequisite to externalized adaptation is an understanding of how components are interconnected, or more particularly how and why they depend on one another. Such dependencies can be used to provide an architectural model, which provides a reference point for externalized adaptation. In this paper, it is described how dependencies are used as a basis to systems' self-understanding and subsequent architectural reconfigurations. The approach is based on the combination of: instrumentation services, a dependency meta-model and a system controller. In particular, the latter uses self-healing repair rules (or conflict resolution strategies), based on extensible beliefs, desires and intention (EBDI) model, to reflect reconfiguration changes back to a target application under examination

    The influence of corporate social responsibility policy and initiatives on human resource management practices and experiences

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    The expectation that organisations will act in a socially responsible manner under the guise of Corporate Social Responsibility (CSR) is now one of the most significant contextual influences organisations face. This is particularly relevant to organisations located in industries that have the potential for significant environmental impact such as the cement industry. One often-acknowledged key element in CSR is the role of people in the successful implementation of CSR policy and practice. However, CSR research is rarely focused on the influence of people management in this process. This research has specifically brought back into focus the complexities, tensions and contradictions evident in the employment relationship via insights from the field of Human Resource Management (HRM) and the utilisation of the HR Causal Chain Model (Purcell et al., 2009) as a broad research framework. Using a single-case systematic combining approach (Dubois & Gadde, 2002, 2014) within a social constructionist perspective, this study aimed to address the question: How does Corporate Social Responsibility policy and initiatives influence Human Resource practices and stakeholder experiences? The case organisation used in this study was an Australian cement manufacturing plant, known for the purposes of this research as CementCo. The study utilised in-depth interviews, observation, analysis of secondary documentation, and thematic analysis to explore both the intended HR and CSR policies and practices of CementCo, and the processes involved in how these practices are enacted by line managers and experienced by employees in consideration of workplace culture and subcultures. The process-based approach provides significant insights into the HR and CSR implementation process and the ‘black box’ of HRM research. The findings demonstrate that while it is important to design and commit to strategically aligned and integrated HR and CSR strategies and policies, the dynamic and unpredictable process of implementation has a much larger impact on the success of these strategies than is recognised in contemporary CSR research. As such, one of the key contributions of this research is that within HRM and HRM-CSR research the implementation process should be considered, and it should be considered as a process that relies on the actions and attitudes of multiple stakeholders. The study has acknowledged and embraced the complexities, tensions and contradictions often neglected in mainstream HRM, and more broadly the organisation of work and people. It has explored the realities of organisational life, the perspectives and perceptions of those often forgotten in mainstream literature, and the processes of how work is organised and how people are managed. It has also contributed to the broadening of the field through the inclusion of more than just traditional HR functions, by exploring HR’s broader role in the organisation and its social responsibility. In doing so, this study has shifted the HR research approach to one that incorporates the broader realities, processes, experiences, and perceptions, and thus redefined what a HR thesis can look like

    Supporting adaptiveness of cyber-physical processes through action-based formalisms

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    Cyber Physical Processes (CPPs) refer to a new generation of business processes enacted in many application environments (e.g., emergency management, smart manufacturing, etc.), in which the presence of Internet-of-Things devices and embedded ICT systems (e.g., smartphones, sensors, actuators) strongly influences the coordination of the real-world entities (e.g., humans, robots, etc.) inhabitating such environments. A Process Management System (PMS) employed for executing CPPs is required to automatically adapt its running processes to anomalous situations and exogenous events by minimising any human intervention. In this paper, we tackle this issue by introducing an approach and an adaptive Cognitive PMS, called SmartPM, which combines process execution monitoring, unanticipated exception detection and automated resolution strategies leveraging on three well-established action-based formalisms developed for reasoning about actions in Artificial Intelligence (AI), including the situation calculus, IndiGolog and automated planning. Interestingly, the use of SmartPM does not require any expertise of the internal working of the AI tools involved in the system

    Alternative approaches for studying shared and distributed leadership

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    Scholars hold different perspectives about leadership which are not limited to a formally appointed leader. Of the abundance of terms used to describe this phenomenon, shared and distributed are the most prevalent. These terms are often used interchangeably, resulting in confusion in the way that shared and distributed leadership is conceptualized and investigated. This paper provides a historical development of this field, challenges existing conceptions and reveals inconsistencies and contradictions that are seldom acknowledged. Four distinct approaches to the study of shared and distributed leadership are identified in the literature, each embracing different ontological views and leadership epistemologies. Individually, the four approaches offer valuable - yet partial - understanding. Comparing and contrasting the assumptions and insights from the four approaches raises fundamental issues about how we think about leadership in terms of research, practice and development

    Collaboration and Coordination in Process-Centered Software Development Environments

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