837 resultados para integrated-process model
Resumo:
This paper presents a technique for the automated removal of noise from process execution logs. Noise is the result of data quality issues such as logging errors and manifests itself in the form of infrequent process behavior. The proposed technique generates an abstract representation of an event log as an automaton capturing the direct follows relations between event labels. This automaton is then pruned from arcs with low relative frequency and used to remove from the log those events not fitting the automaton, which are identified as outliers. The technique has been extensively evaluated on top of various auto- mated process discovery algorithms using both artificial logs with different levels of noise, as well as a variety of real-life logs. The results show that the technique significantly improves the quality of the discovered process model along fitness, appropriateness and simplicity, without negative effects on generalization. Further, the technique scales well to large and complex logs.
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Existing techniques for automated discovery of process models from event logs gen- erally produce flat process models. Thus, they fail to exploit the notion of subprocess as well as error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of hierarchical BPMN models con- taining interrupting and non-interrupting boundary events and activity markers. The technique employs functional and inclusion dependency discovery techniques in order to elicit a process-subprocess hierarchy from the event log. Given this hierarchy and the projected logs associated to each node in the hierarchy, parent process and subprocess models are then discovered using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. By employing approximate dependency discovery tech- niques, it is possible to filter out noise in the event log arising for example from data entry errors or missing events. A validation with one synthetic and two real-life logs shows that process models derived by the proposed technique are more accurate and less complex than those derived with flat process discovery techniques. Meanwhile, a validation on a family of synthetically generated logs shows that the technique is resilient to varying levels of noise.
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The Source Monitoring Framework is a promising model of constructive memory, yet fails because it is connectionist and does not allow content tagging. The Dual-Process Signal Detection Model is an improvement because it reduces mnemic qualia to a single memory signal (or degree of belief), but still commits itself to non-discrete representation. By supposing that ‘tagging’ means the assignment of propositional attitudes to aggregates of anemic characteristics informed inductively, then a discrete model becomes plausible. A Bayesian model of source monitoring accounts for the continuous variation of inputs and assignment of prior probabilities to memory content. A modified version of the High-Threshold Dual-Process model is recommended to further source monitoring research.
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This paper demonstrates the integration and usage of Process Query Language (PQL), a special-purpose programming language for querying large collections of process models based on process model behavior, in the Apromore open-source process model repository. The resulting environment provides a unique user experience when carrying out process model querying tasks. The tool is useful for researchers and practitioners working with large process model collections, and specifically for those with an interest in model retrieval tasks as part of process compliance, process redesign and process standardization initiatives.
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In this paper we illustrate a set of features of the Apromore process model repository for analyzing business process variants. Two types of analysis are provided: one is static and based on differences on the process control flow, the other is dynamic and based on differences in the process behavior between the variants. These features combine techniques for the management of large process model collections with those for mining process knowledge from process execution logs. The tool demonstration will be useful for researchers and practitioners working on large process model collections and process execution logs, and specifically for those with an interest in understanding, managing and consolidating business process variants both within and across organizational boundaries.
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A model based on the cluster process representation of the self-exciting process model in White and Porter 2013 and Ruggeri and Soyer 2008is derived to allow for variation in the excitation effects for terrorist events in a self-exciting or cluster process model. The details of the model derivation and implementation are given and applied to data from the Global Terrorism Database from 2000–2012. Results are discussed in terms of practical interpretation along with implications for a theoretical model paralleling existing criminological theory.
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The air transport industry is a complex environment facing many challenges while coping with changing global imperatives. International airport passenger facilitation is a part of the socio-technical system where these challenges manifest, impacting businesses in terms of time, cost and quality. This research inductively develops an extensible configurable reference model by capturing and merging the cross-organisational facilitation process from five Australian airports. The reference model can be filtered according to the contextual needs of airport users to inform relevant and accurate business process design. The domain and methodological contributions constitute the first reported application of questionnaire-based configurability to airport processes.
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Analyzing and redesigning business processes is a complex task, which requires the collaboration of multiple actors. Current approaches focus on workshops where process stakeholders together with modeling experts create a graphical visualization of a process in a model. Within these workshops, stakeholders are mostly limited to verbal contributions, which are integrated into a process model by a modeling expert using traditional input devices. This limitation negatively affects the collaboration outcome and also the perception of the collaboration itself. In order to overcome this problem we created CubeBPM – a system that allows groups of actors to interact with process models through a touch based interface on a large interactive touch display wall. Using this system for collaborative modeling, we expect to provide a more effective collaboration environment thus improving modeling performance and collaboration.
Resumo:
Fluidised bed-heat pump drying technology offers distinctive advantages over the existing drying technology employed in the Australian food industry. However, as is the case with many other examples of innovations that have had clear relative advantages, the rates of adoption and diffusion of this technology have been very slow. "Why does this happen?" is the theme of this research study that has been undertaken with an objective to analyse a range of issues related to the market acceptance of technological innovations. The research methodology included the development of an integrated conceptual model based on an extensive review of literature in the areas of innovation diffusion, technology transfer and industrial marketing. Three major determinants associated with the market acceptance of innovations were identified as the characteristics of the innovation, adopter information processing capability and the influence of the innovation supplier on the adoption process. This was followed by a study involving more than 30 small and medium enterprises identified as potential adopters of fluidised bed-heat pump drying technology in the Australian food industry. The findings revealed that judgment was the key evaluation strategy employed by potential adopters in the particular industry sector. Further, it was evidenced that the innovations were evaluated against a predetermined criteria covering a range of aspects with emphasis on a selected set of attributes of the innovation. Implication of these findings on the commercialisation of fluidised bed-heat pump drying technology was established, and a series of recommendations was made to the innovation supplier (DPI/FT) enabling it to develop an effective commercialisation strategy.
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The article discusses a new decision support process for forestry pest management. Over the past few years, DSS have been introduced for forestry pest management, providing forest growers with advice in areas such as selecting the most suitable pesticide and relevant treatment. Most of the initiatives process knowledge from various domains for providing support for specific decision making problems. However, very few studies have identified the requirements of developing a combined process model in which all relevant practitioners can contribute and share knowledge for effective decision making; such an approach would need to include the decision makers’ perspective along with other relevant attributes such as the problem context and relevant policies. We outline a decision support process for forestry pest management, based on the design science research paradigm, in which a focus group technique has application to acquire both expert and practical knowledge in order to construct the DSS solution.
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Background Poor clinical handover has been associated with inaccurate clinical assessment and diagnosis, delays in diagnosis and test ordering, medication errors and decreased patient satisfaction in the acute care setting. Research on the handover process in the residential aged care sector is very limited. Purpose The aims of this study were to: (i) Develop an in-depth understanding of the handover process in aged care by mapping all the key activities and their information dynamics, (ii) Identify gaps in information exchange in the handover process and analyze implications for resident safety, (iii) Develop practical recommendations on how information communication technology (ICT) can improve the process and resident safety. Methods The study was undertaken at a large metropolitan facility in NSW with more than 300 residents and a staff including 55 registered nurses (RNs) and 146 assistants in nursing (AINs). A total of 3 focus groups, 12 interviews and 3 observation sessions were conducted over a period from July to October 2010. Process mapping was undertaken by translating the qualitative data via a five-category code book that was developed prior to the analysis. Results Three major sub-processes were identified and mapped. The three major stages are Handover process (HOP) I “Information gathering by RN”, HOP II “Preparation of preliminary handover sheet” and HOP III “Execution of handover meeting”. Inefficient processes were identified in relation to the handover including duplication of information, utilization of multiple communication modes and information sources, and lack of standardization. Conclusion By providing a robust process model of handover this study has made two critical contributions to research in aged care: (i) a means to identify important, possibly suboptimal practices; and (ii) valuable evidence to plan and improve ICT implementation in residential aged care. The mapping of this process enabled analysis of gaps in information flow and potential impacts on resident safety. In addition it offers the basis for further studies into a process that, despite its importance for securing resident safety and continuity of care, lacks research.
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This paper addresses the problem of discovering business process models from event logs. Existing approaches to this problem strike various tradeoffs between accuracy and understandability of the discovered models. With respect to the second criterion, empirical studies have shown that block-structured process models are generally more understandable and less error-prone than unstructured ones. Accordingly, several automated process discovery methods generate block-structured models by construction. These approaches however intertwine the concern of producing accurate models with that of ensuring their structuredness, sometimes sacrificing the former to ensure the latter. In this paper we propose an alternative approach that separates these two concerns. Instead of directly discovering a structured process model, we first apply a well-known heuristic technique that discovers more accurate but sometimes unstructured (and even unsound) process models, and then transform the resulting model into a structured one. An experimental evaluation shows that our “discover and structure” approach outperforms traditional “discover structured” approaches with respect to a range of accuracy and complexity measures.
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There has been a demand for uniform CAD standards in the construction industry ever since the large-scale introduction of computer aided design systems in the late 1980s. While some standards have been widely adopted without much formal effort, other standards have failed to gain support even though considerable resources have been allocated for the purpose. Establishing a standard concerning building information modeling has been one particularly active area of industry development and scientific interest within recent years. In this paper, four different standards are discussed as cases: the IGES and DXF/DWG standards for representing the graphics in 2D drawings, the ISO 13567 standard for the structuring of building information on layers, and the IFC standard for building product models. Based on a literature study combined with two qualitative interview studies with domain experts, a process model is proposed to describe and interpret the contrasting histories of past CAD standardisation processes.
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The term design in this paper particularly refers to the process (verb) and less-to the outcome or product. Design comprises a complex set of activities today involving both man and machine. Sustainability is a fundamental paradigm and carries significance in any process, natural or manmade, and its outcome. In simple terms, sustainability implies a state of sustainable living, viz, health and continuity, nurtured by diversity and evolution (innovations) in an ever-changing world. Design, in a similar line, has been comprehensively investigated and its current manifestations including design-aids (Computer Aided Design) have been evaluated in terms of sustainability. The paper investigates the rationale of sustainability to design as a whole - its purpose, its adoption in the natural world, its relevance to humankind and the technologies involved. Throughout its history, technology has been used to aid design. But in the current context of advanced algorithms and computational capacity, design no longer remains an exclusively animate faculty. Given this scenario, investigating sustainability in the light of advanced design aids such as CAD becomes pertinent. Considering that technology plays a part in design activities, the paper explores where technology must play a part and to what degree amongst the various activities that comprise design. The study includes an examination of the morphology of design and the development of a systems-thinking integrated forecasting model to evaluate the implications of CAD tools in design and sustainability. The results of the study along with a broad range of recommendations have been presented. (c) 2012 Elsevier Ltd. All rights reserved.
Resumo:
Arid and semiarid landscapes comprise nearly a third of the Earth's total land surface. These areas are coming under increasing land use pressures. Despite their low productivity these lands are not barren. Rather, they consist of fragile ecosystems vulnerable to anthropogenic disturbance.
The purpose of this thesis is threefold: (I) to develop and test a process model of wind-driven desertification, (II) to evaluate next-generation process-relevant remote monitoring strategies for use in arid and semiarid regions, and (III) to identify elements for effective management of the world's drylands.
In developing the process model of wind-driven desertification in arid and semiarid lands, field, remote sensing, and modeling observations from a degraded Mojave Desert shrubland are used. This model focuses on aeolian removal and transport of dust, sand, and litter as the primary mechanisms of degradation: killing plants by burial and abrasion, interrupting natural processes of nutrient accumulation, and allowing the loss of soil resources by abiotic transport. This model is tested in field sampling experiments at two sites and is extended by Fourier Transform and geostatistical analysis of high-resolution imagery from one site.
Next, the use of hyperspectral remote sensing data is evaluated as a substantive input to dryland remote monitoring strategies. In particular, the efficacy of spectral mixture analysis (SMA) in discriminating vegetation and soil types and detennining vegetation cover is investigated. The results indicate that hyperspectral data may be less useful than often thought in determining vegetation parameters. Its usefulness in determining soil parameters, however, may be leveraged by developing simple multispectral classification tools that can be used to monitor desertification.
Finally, the elements required for effective monitoring and management of arid and semiarid lands are discussed. Several large-scale multi-site field experiments are proposed to clarify the role of wind as a landscape and degradation process in dry lands. The role of remote sensing in monitoring the world's drylands is discussed in terms of optimal remote sensing platform characteristics and surface phenomena which may be monitored in order to identify areas at risk of desertification. A desertification indicator is proposed that unifies consideration of environmental and human variables.