First full-scale trials of pebble matrix filtration

Protecting slow sand filters from high turbidity waters by pre-treatment using Pebble Matrix Filtration (PMF) has been studied in the laboratory at University College London followed by pilot field trials in Papua New Guinea and Serbia. Subsequently, the construction of two full-scale PMF units, one out of concrete (4.8m x4.8m x 3.0m high) and the other using pre-cast Ferro-cement panels (900mm x 1600mm x 20mm thick) with an effective diameter of 4.7m and 3m height, and the combined effective plan area of 40 m2 was completed to protect an existing Slow Sand Filter system at the National Water Supply Drainage Board (NWSDB) in Sri Lanka. Although the plant was completed in April 2008 due to some major repairs to address some leaks and other construction defects in both filters, monitoring was intermittent until November 2008. The results on the plant performance are presented here along with some of the construction problems encountered during the project.

Controlled automated discovery of collections of business process models

Automated process discovery techniques aim at extracting process models from information system logs. Existing techniques in this space are effective when applied to relatively small or regular logs, but generate spaghetti-like and sometimes inaccurate models when confronted to logs with high variability. In previous work, trace clustering has been applied in an attempt to reduce the size and complexity of automatically discovered process models. The idea is to split the log into clusters and to discover one model per cluster. This leads to a collection of process models – each one representing a variant of the business process – as opposed to an all-encompassing model. Still, models produced in this way may exhibit unacceptably high complexity and low fitness. In this setting, this paper presents a two-way divide-and-conquer process discovery technique, wherein the discovered process models are split on the one hand by variants and on the other hand hierarchically using subprocess extraction. Splitting is performed in a controlled manner in order to achieve user-defined complexity or fitness thresholds. Experiments on real-life logs show that the technique produces collections of models substantially smaller than those extracted by applying existing trace clustering techniques, while allowing the user to control the fitness of the resulting models.

Commissioning of a new commercial plastic scintillator system for radiotherapy

Introduction Since 1992 there have been several articles published on research on plastic scintillators for use in radiotherapy. Plastic scintillators are said to be tissue equivalent, temperature independent and dose rate independent [1]. Although their properties were found to be promising for measurements in megavoltage X-ray beams there were some technical difficulties with regards to its commercialisation. Standard Imaging has produced the first commercial system which is now available for use in a clinical setting. The Exradin W1 scintillator device uses a dual fibre system where one fibre is connected to the Plastic Scintillator and the other fibre only measures Cerenkov radiation [2]. This paper presents results obtained during commissioning of this dosimeter system. Methods All tests were performed on a Novalis Tx linear accelerator equipped with a 6 MV SRS photon beam and conventional 6 and 18 MV X-ray beams. The following measurements were performed in a Virtual Water phantom at a depth of dose maximum. Linearity: The dose delivered was varied between 0.2 and 3.0 Gy for the same field conditions. Dose rate dependence: For this test the repetition rate of the linac was varied between 100 and 1,000 MU/min. A nominal dose of 1.0 Gy was delivered for each rate. Reproducibility: A total of five irradiations for the same setup. Results The W1 detector gave a highly linear relationship between dose and the number of Monitor Units delivered for a 10 9 10 cm2 field size at a SSD of 100 cm. The linearity was within 1 % for the high dose end and about 2 % for the very low dose end. For the dose rate dependence, the dose measured as a function of repetition the rate (100–1,000 MU/min) gave a maximum deviation of 0.9 %. The reproducibility was found to be better than 0.5 %. Discussion and conclusions The results for this system look promising so far being a new dosimetry system available for clinical use. However, further investigation is needed to produce a full characterisation prior to use in megavoltage X-ray beams.

Impact and energy absorption of portable water-filled road safety barrier system fitted with foam

Portable water-filled barriers (PWFBs) are roadside appurtenances that are used to prevent errant vehicles from penetrating into temporary construction zones on roadways. A numerical model of the composite PWFB, consisting of a plastic shell, steel frame, water and foam was developed and validated against results from full scale experimental tests. This model can be extended to larger scale impact cases, specifically ones that include actual vehicle models. The cost-benefit of having a validated numerical model is significant and this allows the road barrier designer to conduct extensive tests via numerical simulations prior to standard impact tests Effects of foam cladding as additional energy absorption material in the PWFB was investigated. Different types of foam were treated and it was found that XPS foam was the most suitable foam type. Results from this study will aid PWFB designers in developing new generation of roadside structures which will provide enhanced road safety.

Z-source-inverter-based flexible distributed generation system solution for grid power quality improvement

Distributed generation (DG) systems are usually connected to the grid using power electronic converters. Power delivered from such DG sources depends on factors like energy availability and load demand. The converters used in power conversion do not operate with their full capacity all the time. The unused or remaining capacity of the converters could be used to provide some ancillary functions like harmonic and unbalance mitigation of the power distribution system. As some of these DG sources have wide operating ranges, they need special power converters for grid interfacing. Being a single-stage buck-boost inverter, recently proposed Z-source inverter (ZSI) is a good candidate for future DG systems. This paper presents a controller design for a ZSI-based DG system to improve power quality of distribution systems. The proposed control method is tested with simulation results obtained using Matlab/Simulink/PLECS and subsequently it is experimentally validated using a laboratory prototype.

Experimental evidences in bearing diagnostics for traction system of high speed trains

Rolling element bearings are the most critical components in the traction system of high speed trains. Monitoring their integrity is a fundamental operation in order to avoid catastrophic failures and to implement effective condition based maintenance strategies. Generally, diagnostics of rolling element bearings is usually performed by analyzing vibration signals measured by accelerometers placed in the proximity of the bearing under investigation. Several papers have been published on this subject in the last two decades, mainly devoted to the development and assessment of signal processing techniques for diagnostics. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in specific industrial applications, particularly in rail industry, remains scarcely investigated. This paper is aimed at filling this knowledge gap, by addressing the diagnostics of bearings taken from the service after a long term operation on the traction system of a high speed train. Moreover, in order to test the effectiveness of the diagnostic procedures in the environmental conditions peculiar to the rail application, a specific test-rig has been built, consisting of a complete full-scale train traction system, able to reproduce the effects of wheeltrack interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is proposed, in order to limit their number.

Impact of nitrification inhibitor (DMPP) on soil nitrous oxide emissions from an intensive broccoli production system in sub-tropical Australia

Vegetable cropping systems are often characterised by high inputs of nitrogen fertiliser. Elevated emissions of nitrous oxide (N2O) can be expected as a consequence. In order to mitigate N2O emissions from fertilised agricultural fields, the use of nitrification inhibitors, in combination with ammonium based fertilisers, has been promoted. However, no data is currently available on the use of nitrification inhibitors in sub-tropical vegetable systems. A field experiment was conducted to investigate the effect of the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) on N2O emissions and yield from broccoli production in sub-tropical Australia. Soil N2O fluxes were monitored continuously (3 h sampling frequency) with fully automated, pneumatically operated measuring chambers linked to a sampling control system and a gas chromatograph. Cumulative N2O emissions over the 5 month observation period amounted to 298 g-N/ha, 324 g-N/ha, 411 g-N/ha and 463 g-N/ha in the conventional fertiliser (CONV), the DMPP treatment (DMPP), the DMMP treatment with a 10% reduced fertiliser rate (DMPP-red) and the zero fertiliser (0N), respectively. The temporal variation of N2O fluxes showed only low emissions over the broccoli cropping phase, but significantly elevated emissions were observed in all treatments following broccoli residues being incorporated into the soil. Overall 70–90% of the total emissions occurred in this 5 weeks fallow phase. There was a significant inhibition effect of DMPP on N2O emissions and soil mineral N content over the broccoli cropping phase where the application of DMPP reduced N2O emissions by 75% compared to the standard practice. However, there was no statistical difference between the treatments during the fallow phase or when the whole season was considered. This study shows that DMPP has the potential to reduce N2O emissions from intensive vegetable systems, but also highlights the importance of post-harvest emissions from incorporated vegetable residues. N2O mitigation strategies in vegetable systems need to target these post-harvest emissions and a better evaluation of the effect of nitrification inhibitors over the fallow phase is needed.

A high cell count cascade full bridge converter for wide bandwidth ultrasonic transducer excitation

A nine level modular multilevel cascade converter (MMCC) based on four full bridge cells is shown driving a piezoelectric ultrasonic transducer at 71 and 39 kHz, in simulation and experimentally. The modular cells are small stackable PCBs, each with two fully integrated surface mount 22 V, 40 A MOSFET half-bridge converters, and include all control signal and power isolation. In this work, the bridges operate at 12 V and 384 kHz, to deliver a 96 Vpp 9 level waveform with an effective switching frequency of 3 MHz. A 9 pH air cored inductor forms a low pass filter in conjunction with the 3000 pF capacitance of the transducer load. Eight equally phase-displaced naturally sampled pulse width modulation (PWM) drive signals, along with the modulating sinusoid, are generated using phase accumulation techniques in a dedicated FPGA. Experimental time domain and FFT plots of the multilevel and transducer output waveforms are presented and discussed.

Decision support system for age-related macular degeneration using discrete wavelet transform

Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, k -nearest neighbor ( k -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.

Investigations of dielectric monitoring on an energised transformer oil–paper insulation system

Frequency domain spectroscopy (FDS) is being used to assess the insulation condition of oil–paper power transformers. However, it has to date only been implemented on de-energised transformers, which requires the transformers to be shut down for an extended period and may cause significant costs. To solve this issue, a newly improved monitoring method based on the FDS principle is proposed to implement the dielectric measurement on energised transformers. Moreover, a chirp waveform excitation and its novel processing method are introduced. Compared with the conventional FDS results, dielectric results from the energised insulation system have higher tanδ values because of the increased losses. To further understand the insulation ageing process, the effects of the geometric capacitance are removed from the measured imaginary admittance of the insulation system to enhance the ageing signature. The resulting imaginary admittance is then shown to correlate well with the central time constant in return voltage measurements results. The proposed methods address the issues on techniques used on energised transformers and provide a clue for on-line FDS diagnostic application.

Perception of prescription medicine sample packs among Australian professional, government, industry, and consumer organizations, based on automated textual analysis of one-on-one interviews

Background Prescription medicine samples provided by pharmaceutical companies are predominantly newer and more expensive products. The range of samples provided to practices may not represent the drugs that the doctors desire to have available. Few studies have used a qualitative design to explore the reasons behind sample use. Objective The aim of this study was to explore the opinions of a variety of Australian key informants about prescription medicine samples, using a qualitative methodology. Methods Twenty-three organizations involved in quality use of medicines in Australia were identified, based on the authors' previous knowledge. Each organization was invited to nominate 1 or 2 representatives to participate in semistructured interviews utilizing seeding questions. Each interview was recorded and transcribed verbatim. Leximancer v2.25 text analysis software (Leximancer Pty Ltd., Jindalee, Queensland, Australia) was used for textual analysis. The top 10 concepts from each analysis group were interrogated back to the original transcript text to determine the main emergent opinions. Results A total of 18 key interviewees representing 16 organizations participated. Samples, patient, doctor, and medicines were the major concepts among general opinions about samples. The concept drug became more frequent and the concept companies appeared when marketing issues were discussed. The Australian Pharmaceutical Benefits Scheme and cost were more prevalent in discussions about alternative sample distribution models, indicating interviewees were cognizant of budgetary implications. Key interviewee opinions added richness to the single-word concepts extracted by Leximancer. Conclusions Participants recognized that prescription medicine samples have an influence on quality use of medicines and play a role in the marketing of medicines. They also believed that alternative distribution systems for samples could provide benefits. The cost of a noncommercial system for distributing samples or starter packs was a concern. These data will be used to design further research investigating alternative models for distribution of samples.

Experimental investigations of improved dielectric condition monitoring methods on transformer oil-paper insulation system

Frequency Domain Spectroscopy (FDS) is successfully being used to assess the insulation condition of oil filled power transformers. However, it has to date only been implemented on de-energized transformers, which requires the transformers to be shut down for an extended period which can result in significant costs. To solve this issue, a method of implementing FDS under energized condition is proposed here. A chirp excitation waveform is used to replace the conventional sinusoidal waveform to reduce the measurement time in this method. Investigation of the dielectric response under the influence of a high voltage stress at power frequency is reported based on experimental results. To further understand the insulation ageing process, the geometric capacitance effect is removed to enhance the detection of the ageing signature. This enhancement enables the imaginary part of admittance to be used as a new indicator to assess the ageing status of the insulation.

Pollen image classification using the classifynder system: Algorithm comparison and a case study on New Zealand honey

We describe an investigation into how Massey University’s Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University’s pollen reference collection (2,890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set.We additionally work through a real world case study where we assess the ability of the system to determine the pollen make-up of samples of New Zealand honey. In addition to the Classifynder’s native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples.

A comparison of classification algorithms within the Classifynder pollen imaging system

We describe an investigation into how Massey University's Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University's pollen reference collection (2890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set. In addition to the Classifynder's native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples. © 2013 AIP Publishing LLC.

Visual control for automated aircraft collision avoidance systems

This thesis presents a new vision-based decision and control strategy for automated aircraft collision avoidance that can be realistically applied to the See and Avoid problem. The effectiveness of the control strategy positions the research as a major contribution toward realising the simultaneous operation of manned and unmanned aircraft within civilian airspace. Key developments include novel classical and visual predictive control frameworks, and a performance evaluation technique aligned with existing aviation practise and applicable to autonomous systems. The overall approach is demonstrated through experimental results on a small multirotor unmanned aircraft, and through high fidelity probabilistic simulation studies.