858 resultados para data pre-processing


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Although live VM migration has been intensively studied, the problem of live migration of multiple interdependent VMs has hardly been investigated. The most important problem in the live migration of multiple interdependent VMs is how to schedule VM migrations as the schedule will directly affect the total migration time and the total downtime of those VMs. Aiming at minimizing both the total migration time and the total downtime simultaneously, this paper presents a Strength Pareto Evolutionary Algorithm 2 (SPEA2) for the multi-VM migration scheduling problem. The SPEA2 has been evaluated by experiments, and the experimental results show that the SPEA2 can generate a set of VM migration schedules with a shorter total migration time and a shorter total downtime than an existing genetic algorithm, namely Random Key Genetic Algorithm (RKGA). This paper also studies the scalability of the SPEA2.

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The space and positioning of Indigenous knowledges (IK) within Australian curricula and pedagogy are often contentious, informed by the broader Australian socio-cultural, political and economic landscape. Against changing educational policy, historically based on the myth of terra nullius, we discuss the shifting priorities for embedding Indigenous knowledges in educational practice in university and school curricula and pedagogy. In this chapter, we argue that personal and professional commitment to social justice is an important starting point for embedding Indigenous knowledges in the Australian school curricula and pedagogy. Developing teacher knowledge around embedding IK is required to enable teachers’ preparedness to navigate a contested historical/colonising space in curriculum decision-making, teaching and learning. We draw one mpirical data from a recent research project on supporting pre-service teachers as future curriculum leaders; the project was funded by the Office of Learning and Teaching (OLT). This project aimed to support future curriculum leaders to develop their knowledge of embedding IK at one Australian university. We propose supporting the embedding of IK in situ with pre-service teachers and their supervising teachers on practicum in real, sustained and affirming ways that shifts the recognition of IK from personal commitment to social justice in education, to one that values Indigenous knowledges as content to educate (Connell, 1993). We argue that sustained engagement with and appreciation of IKhas the potential to decolonise Australian curricula, shift policy directions and enhance race relations between Indigenous and non-Indigenous Australians .

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As technological capabilities for capturing, aggregating, and processing large quantities of data continue to improve, the question becomes how to effectively utilise these resources. Whenever automatic methods fail, it is necessary to rely on human background knowledge, intuition, and deliberation. This creates demand for data exploration interfaces that support the analytical process, allowing users to absorb and derive knowledge from data. Such interfaces have historically been designed for experts. However, existing research has shown promise in involving a broader range of users that act as citizen scientists, placing high demands in terms of usability. Visualisation is one of the most effective analytical tools for humans to process abstract information. Our research focuses on the development of interfaces to support collaborative, community-led inquiry into data, which we refer to as Participatory Data Analytics. The development of data exploration interfaces to support independent investigations by local communities around topics of their interest presents a unique set of challenges, which we discuss in this paper. We present our preliminary work towards suitable high-level abstractions and interaction concepts to allow users to construct and tailor visualisations to their own needs.

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In this paper, the results of the time dispersion parameters obtained from a set of channel measurements conducted in various environments that are typical of multiuser Infostation application scenarios are presented. The measurement procedure takes into account the practical scenarios typical of the positions and movements of the users in the particular Infostation network. To provide one with the knowledge of how much data can be downloaded by users over a given time and mobile speed, data transfer analysis for multiband orthogonal frequency division multiplexing (MB-OFDM) is presented. As expected, the rough estimate of simultaneous data transfer in a multiuser Infostation scenario indicates dependency of the percentage of download on the data size, number and speed of the users, and the elapse time.

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This work explored the applicability of electrocoagulation (EC) using aluminium electrodes for the removal of contaminants which can scale and foul reverse osmosis membranes from a coal seam (CS) water sample, predominantly comprising sodium chloride, and sodium bicarbonate. In general, the removal efficiency of species responsible for scaling and fouling was enhanced by increasing the applied current density/voltage and contact times (30–60 s) in the EC chamber. High removal efficiencies of species potentially responsible for scale formation in reverse osmosis units such as calcium (100%), magnesium (87.9%), strontium (99.3%), barium (100%) and silicates (98.3%) were achieved. Boron was more difficult to eliminate (13.3%) and this was postulated to be due to the elevated solution pH. Similarly, fluoride removal from solution (44%) was also inhibited by the presence of hydroxide ions in the pH range 9–10. Analysis of produced flocs suggested the dominant presence of relatively amorphous boehmite (AlOOH), albeit the formation of Al(OH)3 was not ruled out as the drying process employed may have converted aluminium hydroxide to aluminium oxyhydroxide species. Evidence for adsorption of contaminants on floc surface sites was determined from FTIR studies. The quantity of aluminium released during the electrocoagulation process was higher than the Faradaic amount which suggested that the high salt concentrations in the coal seam water had chemically reacted with the aluminium electrodes.

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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.

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BACKGROUND Many koala populations around Australia are in serious decline, with a substantial component of this decline in some Southeast Queensland populations attributed to the impact of Chlamydia. A Chlamydia vaccine for koalas is in development and has shown promise in early trials. This study contributes to implementation preparedness by simulating vaccination strategies designed to reverse population decline and by identifying which age and sex category it would be most effective to target. METHODS We used field data to inform the development and parameterisation of an individual-based stochastic simulation model of a koala population endemic with Chlamydia. The model took into account transmission, morbidity and mortality caused by Chlamydia infections. We calibrated the model to characteristics of typical Southeast Queensland koala populations. As there is uncertainty about the effectiveness of the vaccine in real-world settings, a variety of potential vaccine efficacies, half-lives and dosing schedules were simulated. RESULTS Assuming other threats remain constant, it is expected that current population declines could be reversed in around 5-6 years if female koalas aged 1-2 years are targeted, average vaccine protective efficacy is 75%, and vaccine coverage is around 10% per year. At lower vaccine efficacies the immunological effects of boosting become important: at 45% vaccine efficacy population decline is predicted to reverse in 6 years under optimistic boosting assumptions but in 9 years under pessimistic boosting assumptions. Terminating a successful vaccination programme at 5 years would lead to a rise in Chlamydia prevalence towards pre-vaccination levels. CONCLUSION For a range of vaccine efficacy levels it is projected that population decline due to endemic Chlamydia can be reversed under realistic dosing schedules, potentially in just 5 years. However, a vaccination programme might need to continue indefinitely in order to maintain Chlamydia prevalence at a sufficiently low level for population growth to continue.

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In vitro pre-vascularization is one of the main vascularization strategies in the tissue engineering field. Culturing cells within a tissue-engineered construct (TEC) prior to implantation provides researchers with a greater degree of control over the fate of the cells. However, balancing the diverse range of different cell culture parameters in vitro is seldom easy and in most cases, especially in highly vascularized tissues, more than one cell type will reside within the cell culture system. Culturing multiple cell types in the same construct presents its own unique challenges and pitfalls. The following review examines endothelial-driven vascularization and evaluates the direct and indirect role other cell types have in vessel and capillary formation. The article then analyses the different parameters researchers can modulate in a co-culture system in order to design optimal tissue-engineered constructs to match desired clinical applications.

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This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.

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Frog species have been declining worldwide at unprecedented rates in the past decades. There are many reasons for this decline including pollution, habitat loss, and invasive species [1]. To preserve, protect, and restore frog biodiversity, it is important to monitor and assess frog species. In this paper, a novel method using image processing techniques for analyzing Australian frog vocalisations is proposed. An FFT is applied to audio data to produce a spectrogram. Then, acoustic events are detected and isolated into corresponding segments through image processing techniques applied to the spectrogram. For each segment, spectral peak tracks are extracted with selected seeds and a region growing technique is utilised to obtain the contour of each frog vocalisation. Based on spectral peak tracks and the contour of each frog vocalisation, six feature sets are extracted. Principal component analysis reduces each feature set down to six principal components which are tested for classification performance with a k-nearest neighbor classifier. This experiment tests the proposed method of classification on fourteen frog species which are geographically well distributed throughout Queensland, Australia. The experimental results show that the best average classification accuracy for the fourteen frog species can be up to 87%.

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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%).

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This paper explores the changing employment expectations that frame the early professional work experiences of young planners in Australia. In particular, it considers the rising popularity of pre-graduation professional work experience as a precursor to formal entry into the workforce as a practising planner. This shift is being driven in part by employer expectations that graduates will already have ‘real world’ and relevant work experience. However, an equally significant driver appears to be a growing desire for early career and graduate planners to find ways to distinguish themselves from their peers in an increasingly tight labour market. Using data from an ongoing research project into the formative work experiences of young people this paper describes the three main types of pre-graduation professional work experience undertaken by young planners. It highlights the potential challenges and benefits of pre-graduation work experience from a legal, social and ethical perspective as well as from the perspective of young planners themselves. The paper concludes by reflecting on the role of the planning profession – employers, peak bodies and planning educators – in managing the tensions between producing ‘work ready’ graduates and safeguarding the employment conditions of early career planning professionals.

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Aerosol black carbon (BC) mass concentrations ([BC]), measured continuously during a multi-platform field experiment, Integrated Campaign for Aerosols gases and Radiation Budget (ICARB, March-May 2006), from a network of eight observatories spread over geographically distinct environments of India, (which included five mainland stations, one highland station, and two island stations (one each ill Arabian Sea and Bay of Bengal)) are examined for their spatio-temporal characteristics. During the period of study, [BC] showed large variations across the country, with values ranging from 27 mu g m(3) over industrial/urban locations to as low as 0.065 mu g m(-3) over the Arabian Sea. For all mainland stations, [BC] remained high compared to highland as well as island stations. Among the island stations, Port Blair (PBR) had higher concentration of BC, compared to Minicoy (MCY), implying more absorbing nature of Bay of Bengal aerosols than Arabian Sea. The highland station Nainital (NTL), in the central Himalayas, showed low values of [BC], comparable or even lower than that of the island station PBR, indicating the prevalence of cleaner environment over there. An examination of the changes in the mean temporal features, as the season advances from winter (December-February) to pre-monsoon (March-May), revealed that: (a) Diurnal variations were pronounced over all the mainland stations, with all afternoon low and a nighttime high: (b) At the islands, the diurnal variations, though resembled those over the mainlands, were less pronounced; and (c) In contrast to this, highland station showed an opposite pattern with an afternoon high and a late night or early morning low. The diurnal variations at all stations are mainly caused by the dynamics of local Atmospheric Boundary Layer (ABL), At the entire mainland as well as island stations (except HYD and DEL), [BC] showed a decreasing trend from January to May, This is attributed to the increased convective mixing and to the resulting enhanced vertical dispersal of species in the ABL. In addition, large short-period modulations were observed at DEL and HYD, which appeared to be episodic, An examination of this in the light of the MODIS-derived fire count data over India along with the back-trajectory analysis revealed that advection of BC from extensive forest fires and biomass-burning regions upwind were largely responsible for this episodic enhancement in BC at HYD and DEL.

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The hot deformation behavior of hot isostatically pressed (HIPd) P/M IN-100 superalloy has been studied in the temperature range 1000-1200 degrees C and strain rate range 0.0003-10 s(-1) using hot compression testing. A processing map has been developed on the basis of these data and using the principles of dynamic materials modelling. The map exhibited three domains: one at 1050 degrees C and 0.01 s(-1), with a peak efficiency of power dissipation of approximate to 32%, the second at 1150 degrees C and 10 s(-1), with a peak efficiency of approximate to 36% and the third at 1200 degrees C and 0.1 s(-1), with a similar efficiency. On the basis of optical and electron microscopic observations, the first domain was interpreted to represent dynamic recovery of the gamma phase, the second domain represents dynamic recrystallization (DRX) of gamma in the presence of softer gamma', while the third domain represents DRX of the gamma phase only. The gamma' phase is stable upto 1150 degrees C, gets deformed below this temperature and the chunky gamma' accumulates dislocations, which at larger strains cause cracking of this phase. At temperatures lower than 1080 degrees C and strain rates higher than 0.1 s(-1), the material exhibits flow instability, manifested in the form of adiabatic shear bands. The material may be subjected to mechanical processing without cracking or instabilities at 1200 degrees C and 0.1 s(-1), which are the conditions for DRX of the gamma phase.

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Power dissipation maps have been generated in the temperature range of 900 degrees C to 1150 degrees C and strain rate range of 10(-3) to 10 s(-1) for a cast aluminide alloy Ti-24Al-20Nb using dynamic material model. The results define two distinct regimes of temperature and strain rate in which efficiency of power dissipation is maximum. The first region, centered around 975 degrees C/0.1 s(-1), is shown to correspond to dynamic recrystallization of the alpha(2) phase and the second, centered around 1150 degrees C/0.001 s(-1), corresponds to dynamic recovery and superplastic deformation of the beta phase. Thermal activation analysis using the power law creep equation yielded apparent activation energies of 854 and 627 kJ/mol for the first and second regimes, respectively. Reanalyzing the data by alternate methods yielded activation energies in the range of 170 to 220 kJ/mol and 220 to 270 kJ/mol for the first and second regimes, respectively. Cross slip was shown to constitute the activation barrier in both cases. Two distinct regimes of processing instability-one at high strain rates and the other at the low strain rates in the lower temperature regions-have been identified, within which shear bands are formed.