788 resultados para Markovian Arrival Process (MAP)


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This research contributes a fully-operational approach for managing business process risk in near real-time. The approach consists of a language for defining risks on top of process models, a technique to detect such risks as they eventuate during the execution of business processes, a recommender system for making risk-informed decisions, and a technique to automatically mitigate the detected risks when they are no longer tolerable. Through the incorporation of risk management elements in all stages of the lifecycle of business processes, this work contributes to the effective integration of the fields of Business Process Management and Risk Management.

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The purpose of this paper is to review existing knowledge management (KM) practices within the field of asset management, identify gaps, and propose a new approach to managing knowledge for asset management. Existing approaches to KM in the field of asset management are incomplete with the focus primarily on the application of data and information systems, for example the use of an asset register. It is contended these approaches provide access to explicit knowledge and overlook the importance of tacit knowledge acquisition, sharing and application. In doing so, current KM approaches within asset management tend to neglect the significance of relational factors; whereas studies in the knowledge management field have showed that relational modes such as social capital is imperative for ef-fective KM outcomes. In this paper, we argue that incorporating a relational ap-proach to KM is more likely to contribute to the exchange of ideas and the devel-opment of creative responses necessary to improve decision-making in asset management. This conceptual paper uses extant literature to explain knowledge management antecedents and explore its outcomes in the context of asset man-agement. KM is a component in the new Integrated Strategic Asset Management (ISAM) framework developed in conjunction with asset management industry as-sociations (AAMCoG, 2012) that improves asset management performance. In this paper we use Nahapiet and Ghoshal’s (1998) model to explain antecedents of relational approach to knowledge management. Further, we develop an argument that relational knowledge management is likely to contribute to the improvement of the ISAM framework components, such as Organisational Strategic Manage-ment, Service Planning and Delivery. The main contribution of the paper is a novel and robust approach to managing knowledge that leads to the improvement of asset management outcomes.

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Process modelling is an integral part of any process industry. Several sugar factory models have been developed over the years to simulate the unit operations. An enhanced and comprehensive milling process simulation model has been developed to analyse the performance of the milling train and to assess the impact of changes and advanced control options for improved operational efficiency. The developed model is incorporated in a proprietary software package ‘SysCAD’. As an example, the milling process model has been used to predict a significant loss of extraction by returning the cush from the juice screen before #3 mill instead of before #2 mill as is more commonly done. Further work is being undertaken to more accurately model extraction processes in a milling train, to examine extraction issues dynamically and to integrate the model into a whole factory model.

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Purpose – Context-awareness has emerged as an important principle in the design of flexible business processes. The goal of the research is to develop an approach to extend context-aware business process modeling toward location-awareness. The purpose of this paper is to identify and conceptualize location-dependencies in process modeling. Design/methodology/approach – This paper uses a pattern-based approach to identify location-dependency in process models. The authors design specifications for these patterns. The authors present illustrative examples and evaluate the identified patterns through a literature review of published process cases. Findings – This paper introduces location-awareness as a new perspective to extend context-awareness in BPM research, by introducing relevant location concepts such as location-awareness and location-dependencies. The authors identify five basic location-dependent control-flow patterns that can be captured in process models. And the authors identify location-dependencies in several existing case studies of business processes. Research limitations/implications – The authors focus exclusively on the control-flow perspective of process models. Further work needs to extend the research to address location-dependencies in process data or resources. Further empirical work is needed to explore determinants and consequences of the modeling of location-dependencies. Originality/value – As existing literature mostly focusses on the broad context of business process, location in process modeling still is treated as “second class citizen” in theory and in practice. This paper discusses the vital role of location-dependencies within business processes. The proposed five basic location-dependent control-flow patterns are novel and useful to explain location-dependency in business process models. They provide a conceptual basis for further exploration of location-awareness in the management of business processes.

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Empirical evidence shows that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication arises for example when the repository covers multiple variants of the same processes or due to copy-pasting. Previous work has addressed the problem of efficiently retrieving exact clones that can be refactored into shared subprocess models. This article studies the broader problem of approximate clone detection in process models. The article proposes techniques for detecting clusters of approximate clones based on two well-known clustering algorithms: DBSCAN and Hi- erarchical Agglomerative Clustering (HAC). The article also defines a measure of standardizability of an approximate clone cluster, meaning the potential benefit of replacing the approximate clones with a single standardized subprocess. Experiments show that both techniques, in conjunction with the proposed standardizability measure, accurately retrieve clusters of approximate clones that originate from copy-pasting followed by independent modifications to the copied fragments. Additional experiments show that both techniques produce clusters that match those produced by human subjects and that are perceived to be standardizable.

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In this chapter we describe a critical fairytales unit taught to 4.5 to 5.5 year olds in a context of intensifying pressure to raise literacy achievement. The unit was infused with lessons on reinterpreted fairytales followed by process drama activities built around a sophisticated picture book, Beware of the Bears (MacDonald, 2004). The latter entailed a text analytic approach to critical literacy derived from systemic functional linguistics (Halliday, 1978; Halliday & Matthiessen, 2004). This approach provides a way of analysing how words and discourse are used to represent the world in a particular way and shape reader relations with the author in a particular field (Janks, 2010).

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This paper describes a design framework intended to conceptually map the influence that game design has on the creative activity people engage in during gameplay. The framework builds on behavioral and verbal analysis of people playing puzzle games. The analysis was designed to better understand the extent to which gameplay activities within different games facilitate creative problem solving. We have used an expert review process to evaluate these games in terms of their game design elements and have taken a cognitive action approach to this process to investigate how particular elements produce the potential for creative activity. This paper proposes guidelines that build upon our understanding of the relationship between the creative processes that players undertake during a game and the components of the game that allow these processes to occur. These guidelines may be used in the game design process to better facilitate creative gameplay activity.

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Description of a patient's injuries is recorded in narrative text form by hospital emergency departments. For statistical reporting, this text data needs to be mapped to pre-defined codes. Existing research in this field uses the Naïve Bayes probabilistic method to build classifiers for mapping. In this paper, we focus on providing guidance on the selection of a classification method. We build a number of classifiers belonging to different classification families such as decision tree, probabilistic, neural networks, and instance-based, ensemble-based and kernel-based linear classifiers. An extensive pre-processing is carried out to ensure the quality of data and, in hence, the quality classification outcome. The records with a null entry in injury description are removed. The misspelling correction process is carried out by finding and replacing the misspelt word with a soundlike word. Meaningful phrases have been identified and kept, instead of removing the part of phrase as a stop word. The abbreviations appearing in many forms of entry are manually identified and only one form of abbreviations is used. Clustering is utilised to discriminate between non-frequent and frequent terms. This process reduced the number of text features dramatically from about 28,000 to 5000. The medical narrative text injury dataset, under consideration, is composed of many short documents. The data can be characterized as high-dimensional and sparse, i.e., few features are irrelevant but features are correlated with one another. Therefore, Matrix factorization techniques such as Singular Value Decomposition (SVD) and Non Negative Matrix Factorization (NNMF) have been used to map the processed feature space to a lower-dimensional feature space. Classifiers with these reduced feature space have been built. In experiments, a set of tests are conducted to reflect which classification method is best for the medical text classification. The Non Negative Matrix Factorization with Support Vector Machine method can achieve 93% precision which is higher than all the tested traditional classifiers. We also found that TF/IDF weighting which works well for long text classification is inferior to binary weighting in short document classification. Another finding is that the Top-n terms should be removed in consultation with medical experts, as it affects the classification performance.

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Process models describe someone’s understanding of processes. Processes can be described using unstructured, semi-formal or diagrammatic representation forms. These representations are used in a variety of task settings, ranging from understanding processes to executing or improving processes, with the implicit assumption that the chosen representation form will be appropriate for all task settings. We explore the validity of this assumption by examining empirically the preference for different process representation forms depending on the task setting and cognitive style of the user. Based on data collected from 120 business school students, we show that preferences for process representation formats vary dependent on application purpose and cognitive styles of the participants. However, users consistently prefer diagrams over other representation formats. Our research informs a broader research agenda on task-specific applications of process modeling. We offer several recommendations for further research in this area.

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To effectively manage the challenges being faced by construction organisations in a fast changing business environment, many organisations are attempting to integrate knowledge management (KM) into their business operations. KM activities interact with each other and form a process which receives input from its internal business environment and produces outputs that should be justified by its business performance. This paper aims to provide further understanding on the dynamic nature of the KM process. Through a combination of path analysis and system dynamic simulation, this study found that: 1) an improved business performance enables active KM activities and provide feedback and guidance for formulating learning-based policies; and 2) effective human resource recruitment policies can enlarge the pool of individual knowledge, which lead to a more conducive internal business environment, as well as a higher KM activity level. Consequently, the desired business performance level can be reached within a shorter time frame.

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In 2007 some of us were fortunate enough to be in Dundee for the Royal College of Nursing’s Annual International Nursing Research Conference. A highlight of that conference was an enactment of the process and context debate. The chair asked for volunteers and various members of the audience came forward giving the impression that they were nurses and that it was a chance selection. The audience accepted these individuals as their representatives and once they had gathered on stage we all expected the debate to begin. But the large number of researchers in the audience gave little thought to the selection and recruitment process they had just witnessed. Then the selected representatives stood up and sang A cappella. Suddenly the context was different and we questioned the process. The point was made: process or context, or both?