82 resultados para Autoregressive Disturbances
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Wavelets introduce new classes of basis functions for time-frequency signal analysis and have properties particularly suited to the transient components and discontinuities evident in power system disturbances. Wavelet analysis involves representing signals in terms of simpler, fixed building blocks at different scales and positions. This paper examines the analysis and subsequent compression properties of the discrete wavelet and wavelet packet transforms and evaluates both transforms using an actual power system disturbance from a digital fault recorder. The paper presents comparative compression results using the wavelet and discrete cosine transforms and examines the application of wavelet compression in power monitoring to mitigate against data communications overheads.
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A sub-chronic administration of phencyclidine to the rat brings about enduring pathophysiological and cognitive changes that resemble some features of schizophrenia. The present study aimed to determine whether the behavioural consequence of this phencyclidine regime extends to a long-term disruption of social interaction that might provide a parallel with some negative symptoms of the disease. Rats were treated with phencyclidine (2mg/kg bi-daily for 1 week) or vehicle followed by a drug-free period. Social interaction was assessed 24h, 1 week, 3 weeks and 6 weeks post-treatment. A long-lasting disturbance of social behaviour was observed in the phencyclidine group, namely more contact and non-contact interaction with an unfamiliar target rat at all time points. Six weeks post-phencyclidine, analysis of brains showed a reduction in expression of parvalbumin immunoreactive neurons in the hippocampus with significant reductions localised to the CA1 and dentate gyrus regions. These results show that sub-chronic phencyclidine produces long-lasting disruptions in social interaction that, however, do not model the social withdrawal seen in patients with schizophrenia. These disturbances of social behaviour may be associated with concurrent pathophysiological brain changes.
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In this article, we extend the earlier work of Freeland and McCabe [Journal of time Series Analysis (2004) Vol. 25, pp. 701–722] and develop a general framework for maximum likelihood (ML) analysis of higher-order integer-valued autoregressive processes. Our exposition includes the case where the innovation sequence has a Poisson distribution and the thinning is binomial. A recursive representation of the transition probability of the model is proposed. Based on this transition probability, we derive expressions for the score function and the Fisher information matrix, which form the basis for ML estimation and inference. Similar to the results in Freeland and McCabe (2004), we show that the score function and the Fisher information matrix can be neatly represented as conditional expectations. Using the INAR(2) speci?cation with binomial thinning and Poisson innovations, we examine both the asymptotic e?ciency and ?nite sample properties of the ML estimator in relation to the widely used conditional least
squares (CLS) and Yule–Walker (YW) estimators. We conclude that, if the Poisson assumption can be justi?ed, there are substantial gains to be had from using ML especially when the thinning parameters are large.
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Corrigendum Vol. 30, Issue 2, 259, Article first published online: 15 MAR 2009 to correct the order of authors names: Bu R., K. Hadri, and B. McCabe.
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Radiocarbon dating is routinely used in paleoecology to build chronolo- gies of lake and peat sediments, aiming at inferring a model that would relate the sediment depth with its age. We present a new approach for chronology building (called “Bacon”) that has received enthusiastic attention by paleoecologists. Our methodology is based on controlling core accumulation rates using a gamma autoregressive semiparametric model with an arbitrary number of subdivisions along the sediment. Using prior knowledge about accumulation rates is crucial and informative priors are routinely used. Since many sediment cores are currently analyzed, using different data sets and prior distributions, a robust (adaptive) MCMC is very useful. We use the t-walk (Christen and Fox, 2010), a self adjusting, robust MCMC sampling algorithm, that works acceptably well in many situations. Outliers are also addressed using a recent approach that considers a Student-t model for radiocarbon data. Two examples are presented here, that of a peat core and a core from a lake, and our results are compared with other approaches.
Resumo:
An Automated Interpulse Duration Assessment system (AIDA) is described which permits detection of irregularities in cardiac rhythms in selected invertebrates. The sensitivity of AIDA was demonstrated by its ability to detect handling stress in mussels (Mytilus edulis) that was not evident when measuring heart rate alone. Changes in cardiac activity patterns of crabs (Carcinus maenas) held in the laboratory for up to 10 wk was also examined using the new technique. The frequency distribution of interpulse duration changed significantly as the nutritional state changed. Potential applications of the AIDA system are discussed.
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Background: Although sleep problems are commonly reported among dementia caregivers, the nature and frequency of caregiver sleep disruptions, and their relationship to health status, has received little empirical attention to date. Methods: The current study investigated the sleep situations of a sample of 60 spousal caregivers currently residing with a Alzheimer disease care recipient, including the frequency of nocturnal disruptions by the care recipient, and the reasons for these disruptions. In addition, exploratory correlations were computed between caregiver sleep variables and health outcomes. Results: Some 63% of spousal caregivers reported sleep disruptions due to the nocturnal behavior of the recipients of their care. Poorer caregiver sleep quality was associated with higher frequency of nocturnal disruptions by the care recipient, the care recipient needing to use the bathroom, and wandering, higher caregiver depressive symptoms, and higher levels of caregiver role burden. The frequency of nocturnal disruptions was associated with poorer mental health status and a greater number of depressive symptoms. Conclusions: Results suggest that nocturnal disruptions by the care recipient may have adverse health consequences for spousal caregivers, and that further study of the determinants of caregiver sleep quality and health outcomes are warranted. © 2007 International Psychogeriatric Association.
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The doubly-fed induction generator (DFIG) now represents the dominant technology in wind turbine design. One consequence of this is limited damping and inertial response during transient grid disturbances. A dasiadecoupledpsila strategy is therefore proposed to operate the DFIG grid-side converter (GSC) as a static synchronous compensator (STATCOM) during a fault, supporting the local voltage, while the DFIG operates as a fixed-speed induction generator (FSIG) providing an inertial response. The modeling aspects of the decoupled control strategy, the selection of protection control settings, the significance of the fault location and operation at sub- and super-synchronous speeds are analyzed in detail. In addition, a case study is developed to validate the proposed strategy under different wind penetrations levels. The simulations show that suitable configuration of the decoupled strategy can be deployed to improve system voltage stability and inertial response for a range of scenarios, especially at high wind penetration. The conclusions are placed in context of the practical limitations of the technology employed and the system conditions.
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Wavelet transforms provide basis functions for time-frequency analysis and have properties that are particularly useful for compression of analogue point on wave transient and disturbance power system signals. This paper evaluates the reduction properties of the wavelet transform using real power system data and discusses the application of the reduction method for information transfer in network communications.
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Managing gait disturbances in people with Parkinson’s disease is a pressing challenge, as symptoms can contribute to injury and morbidity through an increased risk of falls. While drug-based interventions have limited efficacy in alleviating gait impairments, certain non-pharmacological methods, such as cueing, can also induce transient improvements to gait. The approach adopted here is to use computationally-generated sounds to help guide and improve walking actions. The first method described uses recordings of force data taken from the steps of a healthy adult which in turn were used to synthesize realistic gravel-footstep sounds that represented different spatio-temporal parameters of gait, such as step duration and step length. The second method described involves a novel method of sonifying, in real time, the swing phase of gait using real-time motion-capture data to control a sound synthesis engine. Both approaches explore how simple but rich auditory representations of action based events can be used by people with Parkinson’s to guide and improve the quality of their walking, reducing the risk of falls and injury. Studies with Parkinson’s disease patients are reported which show positive results for both techniques in reducing step length variability. Potential future directions for how these sound approaches can be used to manage gait disturbances in Parkinson’s are also discussed.