OBJECTIVES AND METHODS armA is a novel plasmid-borne 16S rRNA methyltransferase that confers high-level resistance to 4,6-disubstituted deoxystreptamines. Recently, we have isolated from a high-level broad-spectrum aminoglycoside-resistant Escherichia coli animal isolate a plasmid, pMUR050, that bore the armA gene. In order to elucidate the genetic basis for the spread of armA, we have determin...

This research article aimed at modeling the variations in the dollar/cedi exchange rate. It examines the applicability of a range of ARCH/GARCH specifications for modeling volatility of the series. The variants considered include the ARMA, GARCH, IGARCH, EGARCH and M-GARCH specifications. The results show that the series was non stationary which resulted from the presence of a unit root in it. ...

Image restoration step is important in many image processing applications. In this work, we attempt to restore radiological images degraded during acquisition and processing. Details of the work, carried out to optimize a Neural Network (NN) for identifying an AutoRegressive Moving Average (ARMA) model used for nonlinearly degraded image restoration, are presented in this paper. The degraded im...

In the 2011 SAS® Global Forum, two weighted portmanteau tests were introduced for goodness-of-fit of an Autoregressive-Moving Average (ARMA) time series process. This result is summarized and extended for use as a diagnostic tool in detecting nonlinear and variance-changing processes such as the Generalized Autoregressive Conditional Heteroscedasticity process. The efficacy of the weighting sch...

In the previous paper (Pupeikis, 1998), the problem of recursive estimation of the state of linear dynamic systems, described by an autoregressive model (AR), in the presence of timevarying outliers in observations to be processed has been considered. An approach to the robust recursive state estimation has been obtained and proved by estimating the real chemical process (Box and Jenkins, 1970)...

There has been increased interest in time series data mining recently. In some cases, approaches of real-time segmenting time series are necessary in time series similarity search and data mining, and this is the focus of this paper. A real-time iterative algorithm that is based on time series prediction is proposed in this paper. Proposed algorithm consists of three modular steps. (1) Modeling...

Among 235 extended-spectrum beta-lactamase-producing Klebsiella pneumoniae (ESBL) isolates collected from a nationwide surveillance performed in Taiwan, 102 (43.4%) were resistant to amikacin. Ninety-two of these 102 (90.2%) isolates were carrying CTX-M-type beta-lactamases individually or concomitantly with SHV-type or CMY-2 beta-lactamases. The armA and rmtB alleles were individually detected...

We have derived some matrix equations for speedy computation of the conditional covariance kernel of a discrete-time process obtained from irregularly sampling an underlying continuous-time ARMA process. These results are applicable to both stationary and non-stationary ARMA processes. We have also demonstrated that these matrix results can be useful in shedding new insights on the covariance s...

introduction: accurate water demand modeling for the city is very important for forecasting and policies adoption related to water resources management. thus, for future requirements of water estimation, forecasting and modeling, it is important to utilize models with little errors. water has a special place among the basic human needs, because it not hampers human life. the importance of the i...

Abstract – Analysis of time series data can involve the inversion of large covariance matrices. For the class of ARMA (p, q) processes there are no exact explicit expressions for these inverses, except for the MA (1) process. In practice, the sample covariance matrix can be very large and inversion can be computationally time consuming and so approximate explicit expressions for the inverse are...