340 resultados para nuisance alarms


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The advancement of telemetry control for the water industry has increased the difficulty of 14 managing large volumes of nuisance alarms (i.e. alarms that do not require a response). The aim 15 of this study was to identify and reduce the number of nuisance alarms that occur for Northern 16 Ireland (NI) Water by carrying-out alarm duration analysis to determine the appropriate length of 17 persistence (an advanced alarm management tool) that could be applied. All data was extracted 18 from TelemWeb (NI Water’s telemetry monitoring system) and analysed in Excel. Over a 6 19 week period, an average of 40,000 alarms occurred per week. The alarm duration analysis, which 20 has never been implemented before by NI Water, found that an average of 57% of NI Water 21 alarms had a duration of <5 minutes. Applying 5 minute persistence; therefore, could prevent an 22 average 26,816 nuisance alarms per week. Most of these alarms were from wastewater assets.

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Aim: The aim of this survey was to assess registered nurse’s perceptions of alarm setting and management in an Australian Regional Critical Care Unit. Background: The setting and management of alarms within the critical care environment is one of the key responsibilities of the nurse in this area. However, with up to 99% of alarms potentially being false-positives it is easy for the nurse to become desensitised or fatigued by incessant alarms; in some cases up to 400 per patient per day. Inadvertently ignoring, silencing or disabling alarms can have deleterious implications for the patient and nurse. Method: A total population sample of 48 nursing staff from a 13 bedded ICU/HDU/CCU within regional Australia were asked to participate. A 10 item open-ended and multiple choice questionnaire was distributed to determine their perceptions and attitudes of alarm setting and management within this clinical area. Results: Two key themes were identified from the open-ended questions: attitudes towards inappropriate alarm settings and annoyance at delayed responses to alarms. A significant number of respondents (93%) agreed that alarm fatigue can result in alarm desensitisation and the disabling of alarms, whilst 81% suggested the key factors are those associated with false-positive alarms and inappropriately set alarms.

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Objective: We explore how accurately and quickly nurses can identify melodic medical equipment alarms when no mnemonics are used, when alarms may overlap, and when concurrent tasks are performed. Background: The international standard IEC 60601-1-8 (International Electrotechnical Commission, 2005) has proposed simple melodies to distinguish seven alarm sources. Previous studies with nonmedical participants reveal poor learning of melodic alarms and persistent confusions between some of them. The effects of domain expertise, concurrent tasks, and alarm overlaps are unknown. Method: Fourteen intensive care and general medical unit nurses learned the melodic alarms without mnemonics in two sessions on separate days. In the second half of Day 2 the nurses identified single alarms or pairs of alarms played in sequential, partially overlapping, or nearly completely overlapping configurations. For half the experimental blocks nurses performed a concurrent mental arithmetic task. Results: Nurses' learning was poor and was no better than the learning of nonnurses in a previous study. Nurses showed the previously noted confusions between alarms. Overlapping alarms were exceptionally difficult to identify. The concurrent task affected response time but not accuracy. Conclusion: Because of a failure of auditory stream segregation, the melodic alarms cannot be discriminated when they overlap. Directives to sequence the sounding of alarms in medical electrical equipment must be strictly adhered to, or the alarms must redesigned to support better auditory streaming. Application: Actual or potential uses of this research include the implementation of IEC 60601-1-8 alarms in medical electrical equipment.

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Melodic alarms proposed in the IEC 60601-1-8 standard for medical electrical equipment were tested for learnability and discriminability. Thirty-three non-anaesthetist participants learned the alarms over two sessions of practice, with or without mnemonics suggested in the standard. Fewer than 30% of participants could identify the alarms with 100% accuracy at the end of practice. Confusions persisted between pairs of alarms, especially if mnemonics were used during learning (p = 0.011). Participants responded faster (p < 0.00001) and more accurately (p = 0.002) to medium priority alarms than to high priority alarms, even though they rated the high priority alarms as sounding more urgent (p < 0.00001). Participants with at least 1 year of formal musical training identified the alarms more accurately (p = 0.0002) than musically untrained participants, and found the task easier overall (p < 0.00001). More intensive studies of the IEC 60601-1-8 alarms are needed for their effectiveness to be determined.

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Under Australian law, a tenant complaining of nuisance caused by another tenant traditionally had no recourse to the lessor unless the lessor actively participated in the nuisance. A recent Queensland Court of Appeal decision, Aussie Traveller Pty Ltd v Marklea Pty Ltd, has found that a lessor who fails to take steps to control a tenant's nuisance may be liable to other tenants for breach of the covenant of quiet enjoyment. This paper considers the recent decision in light of common law developments in Australia, England and the United States, including the American concept of constructive eviction.

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The Project will assess the impact of chemical applications and more targeted cleaning on nuisance fly control in feedlots. It will develop and evaluate new, biological agents for the control of nuisance flies and explore options for integration of these.

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Discusses, by reference to case law, whether damages for personal injury are recoverable under Rylands v Fletcher liability. Considers the issue by reference to a hypothetical scenario in which a claimant suffers personal injury as a result of a chemical leak from a factory for which the factory owner is not at fault. Considers claims based on diminution in amenity and for consequential loss.

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In May 2013, the Coalition Government introduced a Bill which if passed will streamline the tools available to tackle anti-social behaviour. One of their proposals is to replace the controversial anti-social behaviour order (ASBO) with what is termed an Injunction to Prevent Nuisance and Annoyance (IPNA). Although designed to tackle criminal and sub-criminal behaviour, this new intervention will be a purely civil order replacing the civil-criminal hybrid ASBO. This article explores some of the more troubling aspects of this part of the Bill including its expansive definition of anti-social behaviour, the avoidance of due process protections, the extensive restrictions that respondents may face and the likely impact of its use on young people. With legislation presently under Parliamentary scrutiny, this article calls for amendments to avoid the most problematic aspects of the ASBO being not just replicated but amplified.

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This thesis focuses on the application of optimal alarm systems to non linear time series models. The most common classes of models in the analysis of real-valued and integer-valued time series are described. The construction of optimal alarm systems is covered and its applications explored. Considering models with conditional heteroscedasticity, particular attention is given to the Fractionally Integrated Asymmetric Power ARCH, FIAPARCH(p; d; q) model and an optimal alarm system is implemented, following both classical and Bayesian methodologies. Taking into consideration the particular characteristics of the APARCH(p; q) representation for financial time series, the introduction of a possible counterpart for modelling time series of counts is proposed: the INteger-valued Asymmetric Power ARCH, INAPARCH(p; q). The probabilistic properties of the INAPARCH(1; 1) model are comprehensively studied, the conditional maximum likelihood (ML) estimation method is applied and the asymptotic properties of the conditional ML estimator are obtained. The final part of the work consists on the implementation of an optimal alarm system to the INAPARCH(1; 1) model. An application is presented to real data series.