Forested catchments in southeast Australia play an important role in supplying water to major cities. Over the past decades, vegetation cover in this area has been affected by major bushfires that in return influence water yield. This study tests methods for forecasting water yield after bushfire, in a forested catchment in southeast Australia. Precipitation and remotely sensed Normalized Diffe...

The regulation of the narK gene in Escherichia coli was studied by constructing narK-lacZ gene and operon fusions and analyzing their expression in various mutant strains in response to changes in cell growth conditions. Expression of narK-lacZ was induced 110-fold by a shift to anaerobic growth and a further 8-fold by the presence of nitrate. The fnr gene product mediates this anaerobic respon...

The NarX and NarQ sensor-histidine kinases control phosphorylation of the NarL and NarP response regulators in response to the respiratory oxidants nitrate and nitrite. Target operon transcription is activated by the Fnr protein in response to anaerobiosis, and it is further activated and/or repressed by the phospho-NarL and phospho-NarP proteins, which bind to heptamer DNA sequences. The locat...

Modelling the respiratory system of intensive care patients can enable individualized mechanical ventilation therapy and reduce ventilator induced lung injuries. However, spontaneous breathing (SB) efforts result in asynchronous pressure waveforms that mask underlying respiratory mechanics. In this study, a nonlinear auto-regressive (NARX) model was identified using a modified Gauss-Newton (GN)...

The prediction of solar radiation has a significant role in several fields such as photovoltaic (PV) power production and micro grid management. interest is increasing nowadays so efficient can greatly improve the performance these different applications. This paper presents novel approach which combines two models, Auto Regressive Moving Average (ARMA) Nonlinear with eXogenous input (NARX). ch...

This paper presents a new algorithm for identification of NARX Hammerstein systems using support vector machines (SVMs) to model the static nonlinear elements. The SVM is fitted by minimizing an ε-insensitive, L-1 cost function which is robust in the presence of outliers. Another advantage of this algorithm is that the value of the uncertainty level epsilon can be specified by the user which gi...

The quantification of wave loading on offshore structures and components is a crucial element in the assessment their useful remaining life. In many applications well-known Morison's equation employed to estimate forcing from waves with assumed particle velocities accelerations. This paper develops grey-box modelling approach improve predictions force structural members. A model intends exploit...

The northern Gulf of Mexico coast is affected by the North Atlantic hurricane season, which causes storm surge disasters every year and brings serious economic losses to southern USA; therefore, it necessary make an accurate advance prediction level. In this paper, a model with simple structure, fast computation speed, results has been constructed based on nonlinear auto-regressive exogenous (N...

This paper compares the performance of Nonlinear Autoregressive Exogenous (NARX) Neural Network and Support Vector Machine (SVM) regression model to predict Air Pollutant Index (API) in Malaysia. Two models namely NARX SVM were developed using API air quality time series data from three monitoring stations: Pasir Gudang, TTDI Jaya Larkin. Hourly parameters collected year 2016 2018 utilized prod...