Beam noise characteristics

Beam-noise spectrum levels were measured with high-resolution horizontal arrays of 22 to 100 wavelengths long at frequencies between 50 and 320 Hz in the Mediterranean Sea. Results indicate that the low-frequency noise field has two major components one of which is due to the dynamic and temporally variable distant shipping. Beam noise level differences of 10 to 20 dB were observed between the resolved distant shipping and the uncorrelated background noise. The measured distributions of beam-noise-intensity fluctuations were found to be non-Gaussian. The beam-noise-intensity distribution was found to depend on aperture length, frequency, bandwidth, integration time, and steering angle. The shapes of the beam-noise-intensity cumulative distribution functions were variable and qualitatively described by nonhomogeneous compound Poisson process as shown with a simulation of the shipping-induced noise field. Temporal characteristics of beam-noise-intensity fluctuations were found to have noise level fades at 30% probability below the median noise level with durations of 1 h for observations over 10 h.     

Counterpropagation fuzzy–neural network for streamflow reconstruction

This study combines neural networks and fuzzy arithmetic to present a counterpropagation fuzzy–neural network (CFNN) for streamflow reconstruction. The CFNN has a rule‐based control, a modified self‐organizing counterpropagation network, and a fuzzy control predictor. It can generate rules automatically by increasing the training data to improve the accuracy of streamflow reconstruction. The CFNN establishes the input and output relationship of a watershed without set‐up parameters. The parameters are estimated systematically by the approach converging to an optimal solution. One sequence of data generated by the Monte Carlo method is used to demonstrate the accuracy of the CFNN. The streamflow data of the Da‐chia River, in central Taiwan, is also used to evaluate the performances of the CFNN. The results indicate the reliability and accuracy of the CFNN for streamflow reconstruction. Copyright © 2001 John Wiley & Sons, Ltd.     

A two‐step‐ahead recurrent neural network for stream‐flow forecasting

In many engineering problems, such as flood warning systems, accurate multistep‐ahead prediction is critically important. The main purpose of this study was to derive an algorithm for two‐step‐ahead forecasting based on a real‐time recurrent learning (RTRL) neural network that has been demonstrated as best suited for real‐time application in various problems. To evaluate the properties of the developed two‐step‐ahead RTRL algorithm, we first compared its predictive ability with least‐square estimated autoregressive moving average with exogenous inputs (ARMAX) models on several synthetic time‐series. Our results demonstrate that the developed two‐step‐ahead RTRL network has efficient ability to learn and has comparable accuracy for time‐series prediction as the refitted ARMAX models. We then investigated the two‐step‐ahead RTRL network by using the rainfall–runoff data of the Da‐Chia River in Taiwan. The results show that the developed algorithm can be successfully applied with high accuracy for two‐step‐ahead real‐time stream‐flow forecasting. Copyright © 2003 John Wiley & Sons, Ltd.     

A spatio-temporal climate-based model of early dengue fever warning in southern Taiwan

Dengue Fever (DF) has been identified by the World Health organization (WHO) as one of the most serious vector-borne infectious diseases in tropical and sub-tropical areas. During 2007, in particular, there were over 2,000 DF cases in Taiwan, which was the highest number of cases in the recorded history of Taiwan epidemics. Most DF studies have focused mainly on temporal DF patterns and its close association with climatic covariates, whereas they have understated spatial DF patterns (spatial dependence and clustering) and composite space–time effects. The present study proposes a spatio-temporal DF prediction approach based on stochastic Bayesian Maximum Entropy (BME) analysis. Core and site-specific knowledge bases are considered, including climate and health datasets under conditions of uncertainty, space–time dependence functions, and a Poisson regression model of climatic variables contributing to DF occurrences in southern Taiwan during 2007. The results show that the DF outbreaks in the study area are highly influenced by climatic conditions. Furthermore, the analysis can provide the required “one-week-ahead” outbreak warnings based on spatio-temporal predictions of DF distributions. Therefore, the proposed approach can provide the Taiwan Disease Control Agency with a valuable tool to timely identify, control, and even efficiently prevent DF spreading across space–time.     

The approach to collapse of molecular clouds

The dense molecular cloud cores that form stars, like other self-gravitating objects, undergo bulk oscillations. Just at the point of gravitational instability, their fundamental oscillation mode has zero frequency. We study, using perturbation theory, the evolution of a spherical cloud that possesses such a frozen mode. We find that the cloud undergoes a prolonged epoch of subsonic, accelerating contraction. This slow contraction occurs whether the cloud is initially inflated or compressed by the oscillation. The subsonic motion described here could underlie the spectral infall signature observed in many starless dense cores.     

DESIGN AND IMPLEMENTATION OF DYNAMIC SYMBOLS IN DYNAMIC GIS

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The nature of straight-chain aliphatic structures in green river kerogen

Previous studies of the Green River kerogen only provide apparently contradictory conclusions about the size of the straight-chain aliphatic structures as well as the manner in which these structures form part of the kerogen matrix.The present investigation is an attempt to resolve this contradiction. A mild stepwise oxidation procedure was followed so that extensive degradation of kerogen-derived intermediates could be prevented. Products isolated from each oxidation step were analyzed by conventional GLC techniques, GC-MS, and proton-NMR measurements in order to ascertain the significance of the straight-chain aliphatic structures present in the Green River kerogen.The following results were obtained: (a) Green River kerogen contains a substantial portion (ca 2–4 carbons out of every 10) of straight-chain aliphatic structures which are longer than C₄, (b) the kerogen matrix forms a three-dimensional network of non-straight-chain clusters interconnected by long polymethylene cross-links, (c) the ‘core’, in comparison with the ‘periphery’ of the kerogen matrix, contains a greater proportion of straight-chain and branched aliphatic structures which are attached to the kerogen matrix at one terminus, (d) some of the straight-chain structures may exist as physically entrapped components in the kerogen matrix.     

NIST RM 8301 Boron Isotopes in Marine Carbonate (Simulated Coral and Foraminifera Solutions): Inter‐laboratory δ11B and Trace Element Ratio Value Assignment

The boron isotopic ratio of ¹¹B/¹⁰B (δ¹¹B_SRM951) and trace element composition of marine carbonates are key proxies for understanding carbon cycling (pH) and palaeoceanographic change. However, method validation and comparability of results between laboratories requires carbonate reference materials. Here, we report results of an inter‐laboratory comparison study to both assign δ¹¹B_SRM951 and trace element compositions to new synthetic marine carbonate reference materials (RMs), NIST RM 8301 (Coral) and NIST RM 8301 (Foram) and to assess the variance of data among laboratories. Non‐certified reference values and expanded 95% uncertainties for δ¹¹B_SRM951 in NIST RM 8301 (Coral) (+24.17‰ ± 0.18‰) and NIST RM 8301 (Foram) (+14.51‰ ± 0.17‰) solutions were assigned by consensus approach using inter‐laboratory data. Differences reported among laboratories were considerably smaller than some previous inter‐laboratory comparisons, yet discrepancies could still lead to large differences in calculated seawater pH. Similarly, variability in reported trace element information among laboratories (e.g., Mg/Ca ± 5% RSD) was often greater than within a single laboratory (e.g., Mg/Ca < 2%). Such differences potentially alter proxy‐reconstructed seawater temperature by more than 2 °C. These now well‐characterised solutions are useful reference materials to help the palaeoceanographic community build a comprehensive view of past ocean changes.     

Seismic structural control using a novel high‐performance active mass driver system

To resolve difficulties encountered by current technology in structural control against earthquakes, this study proposes a novel high‐performance active mass driver (HP‐AMD) system. Based on an active mass driver system, the device is integrated with a mechanical pulley system for stroke amplification to enhance simultaneously efficiency and save power. Meanwhile, an instantaneous optimal direct output feedback control algorithm is derived alongside the hardware development. Numerical simulation is performed using a five‐storey steel frame as the object structure under the 1940 El Centro earthquake. To gain further insight into the HP‐AMD system, the effects of stroke amplification as well as damper weight on system performance are explored. Analysis results demonstrate that the proposed HP‐AMD system is a promising means to improving current active structural control techniques. Copyright © 2000 John Wiley & Sons, Ltd.