Multistep matched-field inversion for broad-band data from ASIAEX2001

This paper discusses the results of geoacoustic inversion carried out using explosive charge data from the Asian Seas International Acoustic Experiment (ASIAEX) East China Sea (ECS) Experiment. A multifrequency incoherent matched-field inversion processor and a genetic algorithm (GA) are used for the inversion. A multistep matched field inversion approach is presented, which makes use of the varying sensitivities of wave fields at various frequencies to reduce the inversion problem into a sequence of smaller inversions with fewer unknowns to estimate at each stage. Different parameters are estimated using data at different frequencies according to their sensitivities. Inversion results for different areas in the ECS region are summarized and compared with core data.     

Radio spectra of the low-luminosity active galactic nucleus NGC 266 at centimetre-to-submillimetre wavelengths

We report multi-frequency and multi-epoch radio continuum observations with multi-spatial resolution for the low-luminosity active galactic nucleus (LLAGN) NGC 266. In the centimetre regime, we find diffuse components with Very Large Array (VLA) observations, and a variable compact core with a rising spectrum with Very Long Baseline Array (VLBA) observations. Although the spectral index of the rising spectrum is consistent with the prediction of the simple advection-dominated accretion flow (ADAF) model, the observed radio power is slightly high compared with that of the model prediction. A spectral break at centimetre-to-millimetre wavelengths is inferred from the upper limits of flux densities from Nobeyama Millimetre Array (NMA) and James Clerk Maxwell Telescope (JCMT) data at millimetre and submillimetre wavelengths, respectively. More complicated considerations are required for the theoretical model to interpret such observed radio properties.     

A neural network approach to ship track-keeping control

This paper presents an on-line trained neural net work controller for ship track-keeping problems. Following a brief review of the ship track-keeping control development since the 1980's, an analysis of various existing backpropagation-based neural controllers is provided. We then propose a single-input multioutput (SIMO) neural control strategy for situations where the exact mathematical dynamics of the ship are not available. The aim of this study is to build an autonomous neural controller which uses rudder to regulate both the tracking error and heading error. During the whole control process, the proposed SIMO neural controller adapts itself on-line from a direct evaluation of the control accuracy, and hence the need for a “teacher” or an off-line training process can be removed. With a relatively modest amount of quantitative knowledge of the ship behavior, the design philosophy enables real time control of a nonlinear ship model under random wind disturbances and measurement noise. Three different track-keeping tasks have been simulated to demonstrate the effectiveness of the training method and the robust performance of the proposed neural control strategy     

Type II bursts of different subclasses associated to transients and mass ejection in the higher corona

The list of mass ejections published in Solar Geophysical Data during the period of Jan. 1981 to Oct. 1987 contains about 1300 Surges, Sprays and Type II bursts. The relationship between the mass ejection events and the shock front events is investigated by means of correlation of time and position. The result shows that type II bursts start as frequently after the mass ejections as prior to them.     

Identification of physical processes inherent in artificial neural network rainfall runoff models

The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd.     

Variations in the natural abundance of 15N in estuarine suspended particulate matter: A specific indicator of biological processing

In this study, the ¹⁴N:¹⁵N ratio of suspended particulate material collected from the Tamar river estuary, south-west England, is described. Three populations of particles, distinguishable by their ¹⁵N content, were observed. This investigation has shown that populations of estuarine particles are generated by biological transformations in situ and that the ¹⁵N content of estuarine particles does not merely reflect hydrodynamic mixing of the freshwater and seawater source particulate material.