4 resultados para tasking

em Aston University Research Archive


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This paper reveals how activity fragmentation and multi-tasking become tools of consumer anti-choice in the online grocery sector: facilitated by new technology practices that positively encourage anti-choice. This is demonstrated through five long-term ethnographic case studies of households in the Portsmouth area of England. All the respondents made some form of conscious effort to minimize the amount of time they spent in ‘big box’ grocery stores. They spend more time at home in planning, searching, socializing online, cumulating and fulfilling internet orders than if they had visited a store: something that all could easily do. The findings suggest the need for constant innovation by internet grocers if they are to remain in tune with dynamic consumer lifestyles and advances in technology. Examples of upcoming technologies requiring retailers to re-think their internet strategies are discussed in view of the possibilities offered by activity fragmentation and multi-tasking.

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The paper considers gender identities in higher education. It examines how people involved in university life engage in (re)creating gender identities and in (re)producing gender-related expectations (and stereotypes) of managerial behaviour. The process of construction of feminine identities is explored through the discourses of academics from a UK university (mainly women who hold managerial positions). The paper reports findings from a series of in-depth interviews with women managers (dean, associate deans and heads of departments) and with university academics (men and women) from a Business School, part of a large British new university. The school was of special interest because women held the majority of senior managerial posts. It appears that the process of construction of femininities is mainly developed around four (stereo-)typical aspects generally associated with feminine management practices (multi-tasking, supporting and nurturing, people and communication skills, and team-work).

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When visual sensor networks are composed of cameras which can adjust the zoom factor of their own lens, one must determine the optimal zoom levels for the cameras, for a given task. This gives rise to an important trade-off between the overlap of the different cameras’ fields of view, providing redundancy, and image quality. In an object tracking task, having multiple cameras observe the same area allows for quicker recovery, when a camera fails. In contrast having narrow zooms allow for a higher pixel count on regions of interest, leading to increased tracking confidence. In this paper we propose an approach for the self-organisation of redundancy in a distributed visual sensor network, based on decentralised multi-objective online learning using only local information to approximate the global state. We explore the impact of different zoom levels on these trade-offs, when tasking omnidirectional cameras, having perfect 360-degree view, with keeping track of a varying number of moving objects. We further show how employing decentralised reinforcement learning enables zoom configurations to be achieved dynamically at runtime according to an operator’s preference for maximising either the proportion of objects tracked, confidence associated with tracking, or redundancy in expectation of camera failure. We show that explicitly taking account of the level of overlap, even based only on local knowledge, improves resilience when cameras fail. Our results illustrate the trade-off between maintaining high confidence and object coverage, and maintaining redundancy, in anticipation of future failure. Our approach provides a fully tunable decentralised method for the self-organisation of redundancy in a changing environment, according to an operator’s preferences.