995 resultados para Exclusion Processes


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Though web services offer unique opportunities for the design of new business processes, the assessment of the potential impact of Web services on existing business information systems is often reduced to technical aspects. This paper proposes a four-phase methodology which facilitates the evaluation of the potential use of Web services on business information systems both from a technical and from a strategic viewpoint. It is based on business process models, which are used to frame the adoption and deployment of Web services and to assess their impact on existing business processes. The application of this methodology is described using a procurement scenario.

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Given that what students learn is so strongly related to how they learn, the modes of delivery and assessment that we as teachers provide them with have a major impact on their ability to learn. As this paper shows, good learning environments are constructed from a range of modes that respond to student learning styles and seek to align activities and learning outcomes with assessment tasks, to better accommodate a diversity of student learning styles and backgrounds. This paper uses a number of models of learning to critique and analyse the traditional practices of assessment in an architectural design class, and then proposes and reports on an alternative pattern of assessment. It discusses the issues of accommodating a group of first-year architecture students at Queensland University of Technology in 2009. These students arrived with diverse prior learning backgrounds, the group being evenly split between those with drawing capabilities and those without. They also had a variety of learning style preferences. The experiment in alternative assessment patterns presented here shows that what has traditionally been considered a diverse and difficult cohort of students can benefit from the assessment of a range of task types at different stages in the learning cycle.

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The purpose of this study is to contribute to the cross-disciplinary body of literature of identity and organisational culture. This study empirically investigated the Hatch and Schultz (2002) Organisational Identity Dynamics (OID) model to look at linkages between identity, image, and organisational culture. This study used processes defined in the OID model as a theoretical frame by which to understand the relationships between actual and espoused identity manifestations across visual identity, corporate identity, and organisational identity. The linking processes of impressing, mirroring, reflecting, and expressing were discussed at three unique levels in the organisation. The overarching research question of How does the organisational identity dynamics process manifest itself in practice at different levels within an organisation? was used as a means of providing empirical understanding to the previously theoretical OID model. Case study analysis was utilised to provide exploratory data across the organisational groups of: Level A - Senior Marketing and Corporate Communications Management, Level B - Marketing and Corporate Communications Staff, and Level C - Non-Marketing Managers and Employees. Data was collected via 15 in-depth interviews with documentary analysis used as a supporting mechanism to provide triangulation in analysis. Data was analysed against the impressing, mirroring, reflecting, and expressing constructs with specific criteria developed from literature to provide a detailed analysis of each process. Conclusions revealed marked differences in the ways in which OID processes occurred across different levels with implications for the ways in which VI, CI, and OI interact to develop holistic identity across organisational levels. Implications for theory detail the need to understand and utilise cultural understanding in identity programs as well as the value in developing identity communications which represent an actual rather than an espoused position.

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This paper describes the findings derived from an exploratory case study into the business processes at a leading Australian insurance provider. The business processes are frequently subjected to changes and deviations due to contextual events such as weather, financial conditions and others. In this study, we examine how context impacts business processes and how resulting business process changes are enacted. From our analysis, we suggest a methodological framework to guide organisations in the complex challenge of linking changing contextual factors with internal process design.

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This study investigated personal and social processes of adjustment at different stages of illness for individuals with brain tumour. A purposive sample of 18 participants with mixed tumour types (9 benign and 9 malignant) and 15 family caregivers was recruited from a neurosurgical practice and a brain tumour support service. In-depth semi-structured interviews focused on participants’ perceptions of their adjustment, including personal appraisals, coping and social support since their brain tumour diagnosis. Interview transcripts were analysed thematically using open, axial and selective coding techniques. The primary theme that emerged from the analysis entailed “key sense making appraisals”, which was closely related to the following secondary themes: (1) Interactions with those in the healthcare system, (2) reactions and support from the personal support network, and (3) a diversity of coping efforts. Adjustment to brain tumour involved a series of appraisals about the illness that were influenced by interactions with those in the healthcare system, reactions and support from people in their support network, and personal coping efforts. Overall, the findings indicate that adjustment to brain tumour is highly individualistic; however, some common personal and social processes are evident in how people make sense of and adapt to the illness over time. A preliminary framework of adjustment based on the present findings and its clinical relevance are discussed. In particular, it is important for health professionals to seek to understand and support individuals’ sense-making processes following diagnosis of brain tumour.

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Ocean processes are dynamic and complex events that occur on multiple different spatial and temporal scales. To obtain a synoptic view of such events, ocean scientists focus on the collection of long-term time series data sets. Generally, these time series measurements are continually provided in real or near-real time by fixed sensors, e.g., buoys and moorings. In recent years, an increase in the utilization of mobile sensor platforms, e.g., Autonomous Underwater Vehicles, has been seen to enable dynamic acquisition of time series data sets. However, these mobile assets are not utilized to their full capabilities, generally only performing repeated transects or user-defined patrolling loops. Here, we provide an extension to repeated patrolling of a designated area. Our algorithms provide the ability to adapt a standard mission to increase information gain in areas of greater scientific interest. By implementing a velocity control optimization along the predefined path, we are able to increase or decrease spatiotemporal sampling resolution to satisfy the sampling requirements necessary to properly resolve an oceanic phenomenon. We present a path planning algorithm that defines a sampling path, which is optimized for repeatability. This is followed by the derivation of a velocity controller that defines how the vehicle traverses the given path. The application of these tools is motivated by an ongoing research effort to understand the oceanic region off the coast of Los Angeles, California. The computed paths are implemented with the computed velocities onto autonomous vehicles for data collection during sea trials. Results from this data collection are presented and compared for analysis of the proposed technique.

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Path planning and trajectory design for autonomous underwater vehicles (AUVs) is of great importance to the oceanographic research community because automated data collection is becoming more prevalent. Intelligent planning is required to maneuver a vehicle to high-valued locations to perform data collection. In this paper, we present algorithms that determine paths for AUVs to track evolving features of interest in the ocean by considering the output of predictive ocean models. While traversing the computed path, the vehicle provides near-real-time, in situ measurements back to the model, with the intent to increase the skill of future predictions in the local region. The results presented here extend prelim- inary developments of the path planning portion of an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. This extension is the incorporation of multiple vehicles to track the centroid and the boundary of the extent of a feature of interest. Similar algorithms to those presented here are under development to consider additional locations for multiple types of features. The primary focus here is on algorithm development utilizing model predictions to assist in solving the motion planning problem of steering an AUV to high-valued locations, with respect to the data desired. We discuss the design technique to generate the paths, present simulation results and provide experimental data from field deployments for tracking dynamic features by use of an AUV in the Southern California coastal ocean.

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Children often have difficulties in learning spatial representations. This study investigated the effect of four different instructional formats on learning outcomes and strategies used when dealing with spatial tasks such as assembly procedures. It was hypothesised that instructional material that imposed least extraneous cognitive load would facilitate enhanced learning. Forty secondary students were presented with four types of instruction; orthographic drawing, isometric drawing, physical model and, isometric and physical model together. The findings provide evidence to suggest that working from physical models caused least extraneous cognitive load compared to the isometric and orthographic groups. The model group took less time, had more correctly completed models, required fewer extra looks, spent less time studying the instruction and made fewer errors. Problem decomposition, forward working and attending to information in the foreground of the graphical representation strategies were analysed.

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Manufacturing organisations spend more on Business Process Improvement initiatives to make them more competitive in growing global market. This paper presents a Rapid Improvement Workshop (RIW) framework which companies can used to identify the critical factors regulating the diffusion of business process improvement in their company. The framework can then be used address how process improvement can be efficiently implemented. We use the results from case studies at Caterpillar India. The paper identifies the critical factors that contribute to the successful implementation of process improvement programs in manufacturing organisations. We further identify certain technological and cultural barriers to the implementation of process improvement programs and how Indian manufacturing companies can overcome these barriers to attain competitive advantage in the global markets.

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In the exclusion-process literature, mean-field models are often derived by assuming that the occupancy status of lattice sites is independent. Although this assumption is questionable, it is the foundation of many mean-field models. In this work we develop methods to relax the independence assumption for a range of discrete exclusion process-based mechanisms motivated by applications from cell biology. Previous investigations that focussed on relaxing the independence assumption have been limited to studying initially-uniform populations and ignored any spatial variations. By ignoring spatial variations these previous studies were greatly simplified due to translational invariance of the lattice. These previous corrected mean-field models could not be applied to many important problems in cell biology such as invasion waves of cells that are characterised by moving fronts. Here we propose generalised methods that relax the independence assumption for spatially inhomogeneous problems, leading to corrected mean-field descriptions of a range of exclusion process-based models that incorporate (i) unbiased motility, (ii) biased motility, and (iii) unbiased motility with agent birth and death processes. The corrected mean-field models derived here are applicable to spatially variable processes including invasion wave type problems. We show that there can be large deviations between simulation data and traditional mean-field models based on invoking the independence assumption. Furthermore, we show that the corrected mean-field models give an improved match to the simulation data in all cases considered.

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Competitive markets are increasingly driving new initiatives for shorter cycle times resulting in increased overlapping of project phases. This, in turn, necessitates improving the interfaces between the different phases to be overlapped (integrated), thus allowing transfer of processes, information and knowledge from one individual or team to another. This transfer between phases, within and between projects, is one of the basic challenges to the philosophy of project management. To make the process transfer more transparent with minimal loss of momentum and project knowledge, this paper draws upon Total Quality Management (TQM) and Business Process Re-engineering (BPR) philosophies to develop a Best Practice Model for managing project phase integration. The paper presents the rationale behind the model development and outlines its two key parts; (1) Strategic Framework and (2) Implementation Plan. Key components of both the Strategic Framework and the Implementation Plan are presented and discussed.

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Although transport related social exclusion has been identified through zonal accessibility measures in the recent past, the debate has shifted from zonal to individual level measures. One way to identify disadvantaged individuals is to measure their size of participation in society (activity spaces). After reviewing existing literature, this paper has found two approaches to measure the activity spaces. One approach is based on the time-geographic potential path area (PPA) concept. The size of the PPA has largely been used as an indicator to the size of potential activity spaces and consequently individual accessibility. The limitations of the PPA concept have been identified in this paper and it is argued cannot be applied as a measure of social exclusion. The other approach is based on individuals’ actual travel activity participation called actual activity spaces. The size of actual activity spaces possesses a good potential measure of social exclusion. However, the indicators to measure the size of actual activity spaces are multidimensional representing the different aspects of social exclusion. The development of a unified approach has therefore been found to be important. This paper has developed a participation index (PI) using the different dimensions of actual activity spaces encountered. A framework has also been developed to operationalise the concept in GIS. The framework, on the one hand, will visualize individuals’ actual travel behaviour in real geographic space; on the other hand, it will calculate the size of their participation in society.

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We examine the impact of individual-specific information processing strategies (IPSs) on the inclusion/exclusion of attributes on the parameter estimates and behavioural outputs of models of discrete choice. Current practice assumes that individuals employ a homogenous IPS with regards to how they process attributes of stated choice (SC) experiments. We show how information collected exogenous of the SC experiment on whether respondents either ignored or considered each attribute may be used in the estimation process, and how such information provides outputs that are IPS segment specific. We contend that accounting the inclusion/exclusion of attributes will result in behaviourally richer population parameter estimates.

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Real-world business processes rely on the availability of scarce, shared resources, both human and non-human. Current workflow management systems support allocation of individual human resources to tasks but lack support for the full range of resource types used in practice, and the inevitable constraints on their availability and applicability. Based on past experience with resource-intensive workflow applications, we derive generic requirements for a workflow system which can use its knowledge of resource capabilities and availability to help create feasible task schedules. We then define the necessary architecture for implementing such a system and demonstrate its practicality through a proof-of-concept implementation. This work is presented in the context of a real-life surgical care process observed in a number of German hospitals.