A data mining approach for fault diagnosis: An application of anomaly detection algorithm

Rolling-element bearing failures are the most frequent problems in rotating machinery, which can be catastrophic and cause major downtime. Hence, providing advance failure warning and precise fault detection in such components are pivotal and cost-effective. The vast majority of past research has focused on signal processing and spectral analysis for fault diagnostics in rotating components. In this study, a data mining approach using a machine learning technique called anomaly detection (AD) is presented. This method employs classification techniques to discriminate between defect examples. Two features, kurtosis and Non-Gaussianity Score (NGS), are extracted to develop anomaly detection algorithms. The performance of the developed algorithms was examined through real data from a test to failure bearing. Finally, the application of anomaly detection is compared with one of the popular methods called Support Vector Machine (SVM) to investigate the sensitivity and accuracy of this approach and its ability to detect the anomalies in early stages.

A CCG virtual system for big data application communication costs analysis

Network topology and routing are two important factors in determining the communication costs of big data applications at large scale. As for a given Cluster, Cloud, or Grid system, the network topology is fixed and static or dynamic routing protocols are preinstalled to direct the network traffic. Users cannot change them once the system is deployed. Hence, it is hard for application developers to identify the optimal network topology and routing algorithm for their applications with distinct communication patterns. In this study, we design a CCG virtual system (CCGVS), which first uses container-based virtualization to allow users to create a farm of lightweight virtual machines on a single host. Then, it uses software-defined networking (SDN) technique to control the network traffic among these virtual machines. Users can change the network topology and control the network traffic programmingly, thereby enabling application developers to evaluate their applications on the same system with different network topologies and routing algorithms. The preliminary experimental results through both synthetic big data programs and NPB benchmarks have shown that CCGVS can represent application performance variations caused by network topology and routing algorithm.

Electrochemical mechanism of eugenol at a Cu doped gold nanoparticles modified glassy carbon electrode and its analytical application in food samples

A simple one-step electrodeposition method was used to construct a glassy carbon electrode (GCE), which has been modified with Cu doped gold nanoparticles (GNPs), i.e. a Cu@AuNPs/GCE. This electrode was characterized with the use of scanning electron microscopy (SEM) and X-ray diffraction (XRD) techniques. The eugenol was electrocatalytically oxidized at the Cu@AuNPs/GCE. At this electrode, in comparison with the behavior at the GCE alone, the corresponding oxidation peak current was enhanced and the shift of the oxidation potentials to lower values was observed. Electrochemical behavior of eugenol at the Cu@AuNPs/GCE was investigated with the use of the cyclic voltammetry (CV) technique, and additionally, in order to confirm the electrochemical reaction mechanism for o-methoxy phenols, CVs for catechol, guaiacol and vanillin were investigated consecutively. Based on this work, an electrochemical reaction mechanism for o-methoxy phenols was suggested, and in addition, the above Cu@AuNPs/GCE was successfully employed for the analysis of eugenol in food samples.

Grant application: QUT Learning and Teaching scheme 2012 Cracking the Code - A checklist to complement CRAs for first year Justice students.

Widening participation brings with it increasing diversity, increased variation in the level of academic preparedness (Clarke, 2011; Nelson, Clarke, & Kift 2010). Cultural capital coupled with negotiating the academic culture creates an environment based on many assumptions about academic writing and university culture. Variations in staff and student expectations relating to the teaching and learning experience is captured in a range of national and institutional data (AUSSE, CEQ, LEX). Nationally, AUSSE data (2009) indicates that communication, writing, speaking and analytic skills, staff expectations are quite a bit higher than students. The research team noted a recognisable shift in the changing cohort of students and their understanding and engagement with feedback and CRAs, as well as variations in teaching staff and student expectations. The current reality of tutor and student roles is that: - Students self select when/how they access lectures and tutorials. - Shorter tutorial times result in reduced opportunity to develop rapport with students. - CRAs are not always used consistently by staff (different marking styles and levels of feedback). - Marking is not always undertaken by the student’s tutor/lecturer. - Student support services might be recommended to students once a poor grade has been given. Students can perceive this as remedial and a further sense of failure. - CRA sheet has a mark /grade attached to it. Stigma attached to low mark. Hard to focus on the CRA feedback with a poor mark etched next to it. - Limited opportunities for sessionals to access professional development to assist with engaging students and feedback. - FYE resources exist, however academic time is a factor in exploring and embedding these resources. Feedback is another area with differing expectations and understandings. Sadler (2009) contends that students are not equipped to decode the statements properly. For students to be able to apply feedback, they need to understand the meaning of the feedback statement. They also need to identify, the particular aspects of their work that need attention. The proposed Checklist/guide would be one page and submitted with each assessment piece thereby providing an interface to engage students and tutors in managing first year understandings and expectations around CRAs, feedback, and academic practice.

The first application of wastewater-based drug epidemiology in five South Korean cities

Illicit drug consumption in five cities in South Korea was estimated by analyzing 17 drug residues in untreated wastewater samples collected during the Christmas and New Year period of 2012-13. Only methamphetamine, amphetamine, and codeine were detected at concentrations of tens of nanograms per liter or even lower concentrations in more than 90% of the samples. Other illicit drug residues (including cocaine, methadone, and benzoylecgonine) that have been detected frequently in wastewater from other countries were not found in this study. Methamphetamine was found to be the most widely used illicit drug in South Korea, and the estimated average consumption rate was 22 mg d−1 (1000 people)−1. This rate is, for example, 2-5 times lower than the estimated average consumption rates in Hong Kong and other parts of China and 4-80 times lower than the estimated average consumption rates in cities in Western countries. It should be noted that the wastewater samples analyzed in this study were collected during a holiday season, when daily consumption of illicit drugs is often higher than on an average day. The methamphetamine usage rates were calculated for different cities in South Korea, and the usage rates in smaller cities was higher (2-4 times) than the average.

Impacts of tillage and application methods on atrazine and alachlor losses from upland fields: Research paper

The effects of tillage practises and the methods of chemical application on atrazine and alachlor losses through run-off were evaluated for five treatments: conservation (untilled) and surface (US), disk and surface, plow and surface, disk and preplant-incorporated, and plow and preplant-incorporated treatments. A rainfall simulator was used to create 63.5 mm h^-1 of rainfall for 60 min and 127 mm h^-1 for 15 min. Rainfall simulation occurred 24-36 h after chemical application. There was no significant difference in the run-off volume among the treatments but the untilled treatment significantly reduced erosion loss. The untilled treatments had the highest herbicide concentration and the disk treatments were higher than the plow treatments. The surface treatments showed a higher concentration than the incorporated treatments. The concentration of herbicides in the water decreased with time. Among the experimental sites, the one with sandy loam soil produced the greatest losses, both in terms of the run-off volume and herbicide loss. The US treatments had the highest loss and the herbicide incorporation treatments had smaller losses through run-off as the residue cover was effective in preventing herbicide losses. Incorporation might be a favorable method of herbicide application to reduce the herbicide losses by run-off.

Application of power electronics in improving power quality and supply efficiency of AC traction networks

Major advances in power electronics during recent years have prompted considerable interest within the traction community. The capability of new technologies to reduce the AC railway networks' effect on power quality and improve their supply efficiency is expected to significantly decrease the cost of electric rail supply systems. Of particular interest are Static Frequency Converter (SFC), Rail Power Conditioner (RPC), High Voltage Direct Current (HVDC) and Energy Storage Systems (ESS) solutions. Substantial impacts on future feasibility of railway electrification are anticipated. Aurizon, Australia's largest heavy haul railway operator, has recently commissioned the world's first 50Hz/50Hz SFC installation and is currently investigating SFC, RPC, HVDC and ESS solutions. This paper presents a summary of current and emerging technologies with a particular focus on the potential techno-economic benefits.

Application of image processing techniques for frog call classification

Frogs have received increasing attention due to their effectiveness for indicating the environment change. Therefore, it is important to monitor and assess frogs. With the development of sensor techniques, large volumes of audio data (including frog calls) have been collected and need to be analysed. After transforming the audio data into its spectrogram representation using short-time Fourier transform, the visual inspection of this representation motivates us to use image processing techniques for analysing audio data. Applying acoustic event detection (AED) method to spectrograms, acoustic events are firstly detected from which ridges are extracted. Three feature sets, Mel-frequency cepstral coefficients (MFCCs), AED feature set and ridge feature set, are then used for frog call classification with a support vector machine classifier. Fifteen frog species widely spread in Queensland, Australia, are selected to evaluate the proposed method. The experimental results show that ridge feature set can achieve an average classification accuracy of 74.73% which outperforms the MFCCs (38.99%) and AED feature set (67.78%).

Constructing a traditional Chinese medicine data warehouse application

The explosive growth in the development of Traditional Chinese Medicine (TCM) has resulted in the continued increase in clinical and research data. The lack of standardised terminology, flaws in data quality planning and management of TCM informatics are preventing clinical decision-making, drug discovery and education. This paper argues that the introduction of data warehousing technologies to enhance the effectiveness and durability in TCM is paramount. To showcase the role of data warehousing in the improvement of TCM, this paper presents a practical model for data warehousing with detailed explanation, which is based on the structured electronic records, for TCM clinical researches and medical knowledge discovery.

Generalised growth models for aquatic species with an application to blacklip abalone (Haliotis rubra)

This paper presents a maximum likelihood method for estimating growth parameters for an aquatic species that incorporates growth covariates, and takes into consideration multiple tag-recapture data. Individual variability in asymptotic length, age-at-tagging, and measurement error are also considered in the model structure. Using distribution theory, the log-likelihood function is derived under a generalised framework for the von Bertalanffy and Gompertz growth models. Due to the generality of the derivation, covariate effects can be included for both models with seasonality and tagging effects investigated. Method robustness is established via comparison with the Fabens, improved Fabens, James and a non-linear mixed-effects growth models, with the maximum likelihood method performing the best. The method is illustrated further with an application to blacklip abalone (Haliotis rubra) for which a strong growth-retarding tagging effect that persisted for several months was detected

Kallikrein-related peptidases in prostate cancer: From molecular function to clinical application

Prostate cancer is a leading contributor to male cancer-related deaths worldwide. Kallikrein-related peptidases (KLKs) are serine proteases that exhibit deregulated expression in prostate cancer, with KLK3, or prostate specific antigen (PSA), being the widely-employed clinical biomarker for prostate cancer. Other KLKs, such as KLK2, show promise as prostate cancer biomarkers and, additionally, their altered expression has been utilised for the design of KLK-targeted therapies. There is also a large body of in vitro and in vivo evidence supporting their role in cancer-related processes. Here, we review the literature on studies to date investigating the potential of other KLKs, in addition to PSA, as biomarkers and in therapeutic options, as well as their current known functional roles in cancer progression. Increased knowledge of these KLK-mediated functions, including degradation of the extracellular matrix, local invasion, cancer cell proliferation, interactions with fibroblasts, angiogenesis, migration, bone metastasis and tumour growth in vivo, may help define new roles as prognostic biomarkers and novel therapeutic targets for this cancer.

4th International Workshop on Theory and Application of Visualizations and Human-centric Aspects in Processes

This is the fourth TAProViz workshop being run at the 13th International Conference on Business Process Management (BPM). The intention this year is to consolidate on the results of the previous successful workshops by further developing this important topic, identifying the key research topics of interest to the BPM visualization community. Towards this goal, the workshop topics were extended to human computer interaction and related domains. Submitted papers were evaluated by at least three program committee members, in a double blind manner, on the basis of significance, originality, technical quality and exposition. Three full and one position papers were accepted for presentation at the workshop. In addition, we invited a keynote speaker, Jakob Pinggera, a postdoctoral researcher at the Business Process Management Research Cluster at the University of Innsbruck, Austria.

Impacts of sodic soil amelioration on deep drainage

Groundwater tables are rising beneath irrigated fields in some areas of the Lower Burdekin in North Queensland, Australia. The soils where this occurs are predominantly sodic clay soils with low hydraulic conductivities. Many of these soils have been treated by applying gypsum or by increasing the salinity of irrigation water by mixing saline groundwater with fresh river water. While the purpose of these treatments is to increase infiltration into the surface soils and improve productivity of the root zone, it is thought that the treatments may have altered the soil hydraulic properties well below the root zone leading to increased groundwater recharge and rising water tables. In this paper we discuss the use of column experiments and HYDRUS modelling, with major ion reaction and transport and soil water chemistry-dependent hydraulic conductivity, to assess the likely depth, magnitude and timing of the impacts of surface soil amelioration on soil hydraulic properties below the root zone and hence groundwater recharge. In the experiments, columns of sodic clays from the Lower Burdekin were leached for extended periods of time with either gypsum solutions or mixed cation salt solutions and change s in hydraulic conductivity were measured. Leaching with a gypsum solution for an extended time period, until the flow rate stabilised, resulted in an approximately twenty fold increase in the hydraulic conductivity when compared with a low salinity, mixed cation solution. HYDRUS modelling was used to high light the role of those factors which might influence the impacts of soil treatment, particularly at depth, including the large amounts of rain during the relatively short wet season and the presence of thick low permeability clay layers.

Impact of cool roof application on commercial buildings: A contribution to sustainable design in Australia

This study investigated the cool roof technology effects on annual energy saving of a large one-storey commercial building in Queensland, Australia. A computer model of the case study was developed using commercial software by using the appropriate geometrical and thermal building specifications. Field study data were used to validate the model. The model was then used to extend the investigation to other cities in various Australian climate zones. The results of this research show that significant energy savings can be obtained using cool roof technology, particularly in warm, sunny climates, and the thesis can contribute to provide a guideline for application of cool roof technology to single-storey commercial building throughout Australia.

Multi-Hypotheses Tracking using the Dempster–Shafer Theory, application to ambiguous road context

This paper presents a Multi-Hypotheses Tracking (MHT) approach that allows solving ambiguities that arise with previous methods of associating targets and tracks within a highly volatile vehicular environment. The previous approach based on the Dempster–Shafer Theory assumes that associations between tracks and targets are unique; this was shown to allow the formation of ghost tracks when there was too much ambiguity or conflict for the system to take a meaningful decision. The MHT algorithm described in this paper removes this uniqueness condition, allowing the system to include ambiguity and even to prevent making any decision if available data are poor. We provide a general introduction to the Dempster–Shafer Theory and present the previously used approach. Then, we explain our MHT mechanism and provide evidence of its increased performance in reducing the amount of ghost tracks and false positive processed by the tracking system.