3D velocity from 3D Doppler radial velocity

We present local least squares and regularization frameworks for computing 3D velocity (3D optical flow) from 3D radial velocity measured by a Doppler radar. We demonstrate the performance of our algorithms quantitatively on synthetic radial velocity data and qualitatively on real radial velocity data, obtained from the Doppler radar at Kurnell Radar station, Botany Bay, New South Wales, Australia. Radial velocity can be used to predict the future positions of storms in sequences of Doppler radar datasets.© 2005 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 15, 189–198, 2005     

A process-dependent real-time controller for sequencing batch reactor plants: results of full-scale operation.

This paper presents results of a research project, in which a process-dependent real-time control (RTC) strategy for a sequencing batch reactor plant was realised in full-scale. The cycle controller is based on NH4 analysers, NO3 probes, TSS probes and sludge level probes. With this new RTC strategy it was possible to increase the treatment capacity by 50%. By implementation of the new controller the TN, TP and NH4-N treatment efficiency could be improved significantly, too. The treatment efficiency concerning COD is comparable.     

Standby power system VRLA battery reserve life estimation scheme

This paper presents a valve-regulated lead acid (VRLA) battery reserve life estimation scheme. The scheme is adaptive in both type and frequency of involvement. The scheme is based on capacity trending with the support of a number of state-of-health (SOH) indicators. These SOH indicators include accumulated thermal stress, float voltage, and indicators acquired from the start-of-discharge (coup de fouet) region. An implementation test case is given, indicating that the scheme is capable of providing an accurate estimation of reserve life long before the end of life. Furthermore, the estimation accuracy improves as the end of battery life approaches.     

Novel tiO2 nanocatalysts for wastewater purification: tapping energy from the sun.

Water treatment using TiO2 semiconductor as a durable heterogeneous photocatalyst has been the focus of environmentalists in recent years. Currently, we developed an inexpensive and highly efficient approach for synthesizing nitrogen-doped TiO2 with lower band-gap energy that can respond to visible light. Doping on the molecular scale led to an enhanced nitrogen concentration of up to 21.8%. Reflectance measurements showed the synthesized N-doped TiO2 nanoparticles are catalytically active with the absorbance that extends into the visible region up to 600 nm. The water purification potential of this new class of compound was evaluated by studying the photodegradation of Acid Orange 7 (AO7) and E. coli. Experiments were conducted to compare the photocatalytic activities of N-doped TiO2 nanocatalysts and commercially available Degussa P25 power under identical solar light exposure. N-doped TiO2 demonstrated superior photocatalytic activities in both chemical compound degradation and bactericidal reactions. The result of this study shows the potential of applying new generations of catalyst for wastewater purification and disinfection.     

Modelling and simulation of KNbO3 ceramics dispersion

The dispersion of potassium niobate (KNbO₃) ceramics is analysed using the multiple-arc approach. This has revealed a high frequency arc that is unattainable by the Cole-Cole single arc analysis. The temperature dependence of the new arc is derived through the spread parameter of the relaxation distribution and interpreted in terms of the ferroelectric property of the KNbO₃ ceramics. It is shown that the overall dispersion behaviour of the ceramics is mainly due to the existence of two distinctly different polarisation mechanisms. The arc approach has also provided an effective tool for network simulation of dispersion whereby the ceramics are modelled by nine parallel R-C branches over the frequency range 10²-10⁵ Hz used     

Evaluation of image similarity by histogram intersection

Colour is the most widely used attribute in image retrieval and object recognition. A technique known as histogram intersection has been widely studied and is considered to be effective for color‐image indexing. The key issue of this algorithm is the selection of an appropriate color space and optimal quantization of the selected color space. The goal of this article is to measure the model performance in predicting human judgment in similarity measurement for various images, to explore the capability of the model with a wide set of color spaces, and to find the optimal quantization of the selected color spaces. Six color spaces and twelve quantization levels are involved in evaluating the performance of histogram intersection. The categorical judgment and rank order experiments were conducted to measure image similarity. The CIELAB color space was found to perform at least as good as or better than the other color spaces tested, and the ability to predict image similarity increased with the number of bins used in the histograms, for up to 512 bins (8 per channel). With more than 512 bins, further improvement was negligible for the image datasets used in this study. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 265–274, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20122     

Factors affecting cloud point analysis of palm oleins

Some of the factors affecting cloud point determination of palm oleins are described. These are the type of container used, method of stirring, rate of stirring and bath temperature. The repeatability and reproducibility standard deviations of the method are determined from collaborative trials. Recommendations for the test are made to reduce the large variations among laboratories.