Search results for "Autore"

Smart load prediction analysis for distributed power network of Holiday Cabins in Norwegian rural area

2020

Abstract The Norwegian rural distributed power network is mainly designed for Holiday Cabins with limited electrical loading capacity. Load prediction analysis, within such type of network, is necessary for effective operation and to manage the increasing demand of new appliances (e. g. electric vehicles and heat pumps). In this paper, load prediction of a distributed power network (i.e. a typical Norwegian rural area power network of 125 cottages with 478 kW peak demand) is carried out using regression analysis techniques for establishing autocorrelations and correlations among weather parameters and occurrence time in the period of 2014–2018. In this study, the regression analysis for loa…

Parametric and nonparametric methods to generate time-varying surrogate data.

2009

We present both nonparametric and parametric approaches to generating time-varying surrogate data. Nonparametric and parametric approaches are based on the use of the short-time Fourier transform and a time-varying autoregressive model, respectively. Time-varying surrogate data (TVSD) can be used to determine the statistical significance of the linear and nonlinear coherence function estimates. Two advantages of the TVSD are that it keeps one from having to make an arbitrary decision about the significance of the coherence value, and it properly takes into account statistical significance levels, which may change with time. Our simulation examples and experimental results on blood pressure …

Nonlinear effects of respiration on the crosstalk between cardiovascular and cerebrovascular control systems.

2016

Cardiovascular and cerebrovascular regulatory systems are vital control mechanisms responsible for guaranteeing homeostasis and are affected by respiration. This work proposes the investigation of cardiovascular and cerebrovascular control systems and the nonlinear influences of respiration on both regulations through joint symbolic analysis (JSA), conditioned or unconditioned on respiration. Interactions between cardiovascular and cerebrovascular regulatory systems were evaluated as well by performing correlation analysis between JSA indexes describing the two control systems. Heart period, systolic and mean arterial pressure, mean cerebral blood flow velocity and respiration were acquired…

Therapeutic Drug Monitoring of Kidney Transplant Recipients Using Profiled Support Vector Machines

2007

This paper proposes a twofold approach for therapeutic drug monitoring (TDM) of kidney recipients using support vector machines (SVMs), for both predicting and detecting Cyclosporine A (CyA) blood concentrations. The final goal is to build useful, robust, and ultimately understandable models for individualizing the dosage of CyA. We compare SVMs with several neural network models, such as the multilayer perceptron (MLP), the Elman recurrent network, finite/infinite impulse response networks, and neural network ARMAX approaches. In addition, we present a profile-dependent SVM (PD-SVM), which incorporates a priori knowledge in both tasks. Models are compared numerically, statistically, and in…

Sevoflurane Impairs Cerebral Blood Flow Autoregulation in Rats: Reversal by Nonselective Nitric Oxide Synthase Inhibition

2005

UNLABELLED In this study, we investigated the effects of 1.0 and 2.0 minimum alveolar anesthetic concentration (MAC) sevoflurane on cerebral blood flow (CBF) autoregulation before and after nonselective inhibition of nitric oxide (NO) synthase in rats. Rats were randomly assigned as follows: Group 1 (n = 8): 1.0 MAC sevoflurane; Groups 2 and 3 (n = 8 per group): 2.0 MAC sevoflurane. Assessment of autoregulation within a mean arterial blood pressure range of 140-60 mm Hg was performed by graded hemorrhage before and after administration of l-arginine methyl ester (l-NAME, 30 mg/kg IV, Groups 1 and 2) or during hypocapnia (Group 3). In 10 additional animals, brain tissue NO(2)(-) concentratio…

Ripensare la modernità cinematografica. Il ragazzo con la bicicletta di Jean-Pierre e Luc Dardenne

2014

Efficient Computation of Multiscale Entropy over Short Biomedical Time Series Based on Linear State-Space Models

2017

The most common approach to assess the dynamical complexity of a time series across multiple temporal scales makes use of the multiscale entropy (MSE) and refined MSE (RMSE) measures. In spite of their popularity, MSE and RMSE lack an analytical framework allowing their calculation for known dynamic processes and cannot be reliably computed over short time series. To overcome these limitations, we propose a method to assess RMSE for autoregressive (AR) stochastic processes. The method makes use of linear state-space (SS) models to provide the multiscale parametric representation of an AR process observed at different time scales and exploits the SS parameters to quantify analytically the co…

Multivariate autoregressive model with instantaneous effects to improve brain connectivity estimation

2009

Imputation Strategies for Missing Data in Environmental Time Series for An Unlucky Situation

2005

After a detailed review of the main specific solutions for treatment of missing data in environmental time series, this paper deals with the unlucky situation in which, in an hourly series, missing data immediately follow an absolutely anomalous period, for which we do not have any similar period to use for imputation. A tentative multivariate and multiple imputation is put forward and evaluated; it is based on the possibility, typical of environmental time series, to resort to correlations or physical laws that characterize relationships between air pollutants.

Assessing directional interactions among multiple physiological time series: The role of instantaneous causality

2012

This paper deals with the assessment of frequency domain causality in multivariate (MV) time series with significant instantaneous interactions. After providing different causality definitions, we introduce an extended MV autoregressive modeling approach whereby each definition is described in the time domain in terms of the model coefficients, and is quantified in the frequency domain by means of novel measures of directional connectivity. These measures are illustrated in a theoretical example showing how they reduce to known indexes when instantaneous causality is trivial, while they describe peculiar aspects of directional interaction in the presence of instantaneous causality. The appl…