757 resultados para Work stability


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This paper focuses on the super/sub-synchronous operation of the doubly fed induction generator (DFIG) system. The impact of a damping controller on the different modes of operation for the DFIG based wind generation system is investigated. The co-ordinated tuning of the damping controller to enhance the damping of the oscillatory modes using bacteria foraging (BF) technique is presented. The results from eigenvalue analysis are presented to elucidate the effectiveness of the tuned damping controller in the DFIG system. The robustness issue of the damping controller is also investigated

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The numerical solution of stochastic differential equations (SDEs) has been focused recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the "best" choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy.

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Stochastic differential equations (SDEs) arise fi om physical systems where the parameters describing the system can only be estimated or are subject to noise. There has been much work done recently on developing numerical methods for solving SDEs. This paper will focus on stability issues and variable stepsize implementation techniques for numerically solving SDEs effectively. (C) 2000 Elsevier Science B.V. All rights reserved.

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Background: The 30-item USDI is a self-report measure that assesses depressive symptoms among university students. It consists of three correlated three factors: Lethargy, Cognitive-Emotional and Academic motivation. The current research used confirmatory factor analysis to asses construct validity and determine whether the original factor structure would be replicated in a different sample. Psychometric properties were also examined. Method: Participants were 1148 students (mean age 22.84 years, SD = 6.85) across all faculties from a large Australian metropolitan university. Students completed a questionnaire comprising of the USDI, the Depression Anxiety Stress Scale (DASS) and Life Satisfaction Scale (LSS). Results: The three correlated factor model was shown to be an acceptable fit to the data, indicating sound construct validity. Internal consistency of the scale was also demonstrated to be sound, with high Cronbach Alpha values. Temporal stability of the scale was also shown to be strong through test-retest analysis. Finally, concurrent and discriminant validity was examined with correlations between the USDI and DASS subscales as well as the LSS, with sound results contributing to further support the construct validity of the scale. Cut-off points were also developed to aid total score interpretation. Limitations: Response rates are unclear. In addition, the representativeness of the sample could be improved potentially through targeted recruitment (i.e. reviewing the online sample statistics during data collection, examining the representativeness trends and addressing particular faculties within the university that were underrepresented). Conclusions: The USDI provides a valid and reliable method of assessing depressive symptoms found among university students.

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The umbrella of Australian research higher degree (RHD) offerings has broadened from the traditional MPhil/PhD programmes to include a range of professional masters and doctoral degrees. This article reports on the experiences of three PhD students, engaged in an informally managed industry partnered research programme, described in this article as the work integrated research higher degree (WIRHD). Their learning process shares the attributes from both the traditional PhD programme and professional doctorates. However, because of the blended nature of the learning contexts, candidates engaged in the WIRHD programme must address a wider range of issues than those following the traditional RHD pathway. An exploratory case study approach was adopted with the view to develop an integrative framework to explain the various contexts that influence the learning experience of WIRHD candidates, as well as a structured approach to guide this contemporary form of industry partnered WIRHD process.

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Catalytic decomposition is a very attractive way to convert tar components into H2, CO and other useful chemicals. The performance of Fe3Ni8/PG (palygorskite, PG) reduced in hydrogen at different temperatures for the catalytic decomposition of benzene has been assessed. Benzene was used as the model biomass tar. The effects of calcination atmosphere, temperatures and benzene concentration on catalytic cracking of benzene were measured. The results of XRD (X-Ray Diffraction), TEM (Transmission Electron Microscope), TPR (Temperature Program Reduction), TPSR (Temperature Program Surface Reduction), TC (Total Carbon), the reactivity component and reaction mechanism over Fe3Ni8/PG for catalytic cracking of benzene are discussed. The results showed particles of awaruite (Fe, Ni) about 2–30 nm were found on the surface of palygorskite by TEM when the calcination temperature was 600 °C. Particles with size smaller than 30 nm were obtained on all prepared Fe3Ni8/PG catalysts as shown by XRD. The nanoparticles proved to be the reactive component for catalytic cracking of benzene and the increase of active particle size caused the decrease in the reactivity of Fe3Ni8/PG. Fe3Ni8/PG annealed in hydrogen at 600 °C was proved to have the best reactivity in experiments (45% hydrogen yield). High concentration benzene (448 g/m3) accelerated the formation of carbon deposition. However, iron oxide decreases carbon deposition and increases the stability of catalyst for catalytic cracking of benzene. The application of Fe3Ni8/PG catalysts was proved a very effective catalyst for the catalytic cracking of benzene.

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The drawdown of reservoirs can significantly affect the stability of upstream slopes of earth dams. This is due to the removal of the balancing hydraulic forces acting on the dams and the undrained condition within the upstream slope soils. In such scenarios, the stability of the slopes can be influenced by a range of factors including drawdown rates, slope inclination and soil properties. This paper investigates the effects of drawdown rate, saturated hydraulic conductivity and unsaturated shear strength of dam materials on the stability of the upstream slope of an earth dam. In this study, the analysis of pore-water pressure changes within the upstream slope during reservoir drawdown was coupled with the slope stability analysis using the general limit equilibrium method. The results of the analysis suggested that a decrease in the reservoir water level caused the stability of the upstream slope to decrease. The dam embankment constructed with highly permeable soil was found to be more stable during drawdown scenarios, compared to others. Further, lower drawdown rates resulted in a higher safety factor for the upstream slope. Also, the safety factor of the slope calculated using saturated shear strength properties of the dam materials was slightly higher than that calculated using unsaturated shear strength properties. In general, for all the scenarios analysed, the lowest safety factor was found to be at the reservoir water level of about 2/3 of drawdown regime.

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As a novel sensitive element and due to its advantages of immunity to electrical interference, distributed measurement, etc., fiber Bragg grating (FBG) has been researched widely. To realize the substitution of high accurate electronic temperature sensors, high sensitive FBG temperature sensors can be made by taking advantage of its characters of being sensitive to both temperature and strain. Although there are reports about high sensitive FBG temperature sensors, however, few about their stability have been done. We manufactured a high sensitive FBG temperature sensor, and put it together with an average FBG temperature sensor and an electronic crystal temperature sensor into a stainless steel container filled by water to observe the room temperature change. By comparing their results in two weeks, we have found out that: although the high sensitive FBG temperature sensor is in much better agreement with the electronic crystal sensor than the average FBG sensor is, it has occurred some small drifts. Because the drifts appeared in the process of further pulling the FBG, it might be a result of the slip of the FBG fixing points. This contributes some good experiences to the application of FBG in high accuracy temperature measurement.

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Compared to conventional metal-foil strain gauges, nanocomposite piezoresistive strain sensors have demonstrated high strain sensitivity and have been attracting increasing attention in recent years. To fulfil their ultimate success, the performance of vapor growth carbon fiber (VGCF)/epoxy nanocomposite strain sensors subjected to static cyclic loads was evaluated in this work. A strain-equivalent quantity (resistance change ratio) in cantilever beams with intentionally induced notches in bending was evaluated using the conventional metal-foil strain gauges and the VGCF/epoxy nanocomposite sensors. Compared to the metal-foil strain gauges, the nanocomposite sensors are much more sensitive to even slight structural damage. Therefore, it was confirmed that the signal stability, reproducibility, and durability of these nanocomposite sensors are very promising, leading to the present endeavor to apply them for static structural health monitoring.

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This report, prepared by QUT Social Work and Human Services, in collaboration with key sector stakeholders, identifies the current and potentially expanded uses of Simulated Learning Environments (SLE) as part of the Health Workforce Australia (HWA) National Project. An expert Reference Group guided the project, facilitated the data collection, and provided feedback and support on the findings and broad recommendations.

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Cuba’s higher education scholarship program has received little attention in the literature on education and development. In this chapter, I discuss themes that emerge from my interviews with graduates from English-speaking Caribbean countries who studied in Cuba, as well as Cuban educators, on the nature of their academic programs and their subsequent careers. This facilitates exploration of a number of questions, including the following: 1. How, in the perceptions of scholarship students and graduates, have they experienced the philosophy of combing study, practical work, and research in the tertiary education curriculum in Cuban universities? 2. What impact does studying in Cuba appear to have on graduates after they return to their home countries? 3. How does the experience of the graduates throw light on the relationship between tertiary education and national development?

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Background Predicting protein subnuclear localization is a challenging problem. Some previous works based on non-sequence information including Gene Ontology annotations and kernel fusion have respective limitations. The aim of this work is twofold: one is to propose a novel individual feature extraction method; another is to develop an ensemble method to improve prediction performance using comprehensive information represented in the form of high dimensional feature vector obtained by 11 feature extraction methods. Methodology/Principal Findings A novel two-stage multiclass support vector machine is proposed to predict protein subnuclear localizations. It only considers those feature extraction methods based on amino acid classifications and physicochemical properties. In order to speed up our system, an automatic search method for the kernel parameter is used. The prediction performance of our method is evaluated on four datasets: Lei dataset, multi-localization dataset, SNL9 dataset and a new independent dataset. The overall accuracy of prediction for 6 localizations on Lei dataset is 75.2% and that for 9 localizations on SNL9 dataset is 72.1% in the leave-one-out cross validation, 71.7% for the multi-localization dataset and 69.8% for the new independent dataset, respectively. Comparisons with those existing methods show that our method performs better for both single-localization and multi-localization proteins and achieves more balanced sensitivities and specificities on large-size and small-size subcellular localizations. The overall accuracy improvements are 4.0% and 4.7% for single-localization proteins and 6.5% for multi-localization proteins. The reliability and stability of our classification model are further confirmed by permutation analysis. Conclusions It can be concluded that our method is effective and valuable for predicting protein subnuclear localizations. A web server has been designed to implement the proposed method. It is freely available at http://bioinformatics.awowshop.com/snlpr​ed_page.php.

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Henmilite is a triclinic mineral with the crystal structure consisting of isolated B(OH)4 tetrahedra, planar Cu(OH)4 groups and Ca(OH)3 polyhedra. The structure can also be viewed as having dimers of Ca polyhedra connected to each other through 2B(OH) tetrahedra to form chains parallel to the C axis. The structure of the mineral has been assessed by the combination of Raman and infrared spectra. Raman bands at 902, 922, 951, and 984 cm−1 and infrared bands at 912, 955 and 998 cm−1 are assigned to stretching vibrations of tetragonal boron. The Raman band at 758 cm−1 is assigned to the symmetric stretching mode of tetrahedral boron. The series of bands in the 400–600 cm−1 region are due to the out-of-plane bending modes of tetrahedral boron. Two very sharp Raman bands are observed at 3559 and 3609 cm−1. Two infrared bands are found at 3558 and 3607 cm−1. These bands are assigned to the OH stretching vibrations of the OH units in henmilite. A series of Raman bands are observed at 3195, 3269, 3328, 3396, 3424 and 3501 cm−1 are assigned to water stretching modes. Infrared spectroscopy also identified water and OH units in the henmilite structure. It is proposed that water is involved in the structure of henmilite. Hydrogen bond distances based upon the OH stretching vibrations using a Libowitzky equation were calculated. The number and variation of water hydrogen bond distances are important for the stability off the mineral.

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Sedimentary palygorskite (SP) and hydrothermal palygorskite (HP) were characterized by XRF, TG/DSC, andXRD. The total iron and dissociative iron in palygorskite were detected using spectrophotometry. The results showed that about 3.57 wt% of Fe2O3 was detected in SP in contrast with 0.4 wt% in HP. SP was a Fe-substituted palygorskite, and HP was an Al-rich palygorskite. The occurrence of Fe substitution in SP resulted in two mass loss steps of coordinated water and resulted in a larger d spacing. The SP showed greater thermal stability than the HP. It was proposed the change of (200) diffraction peak and (240) diffraction peak reflect changes of tetrahedral and octahedral structures in palygorskite.

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The optimum parameters for synthesis of zeolite NaA based on metakaolin were investigated according to results of cation exchange capacity and static water adsorption of all synthesis products and selected X-ray diffraction (XRD). Magnetic zeolite NaA was synthesized by adding Fe3O4 in the precursor of zeolite. Zeolite NaA and magnetic zeolite NaA were characterized with scanning electron microscopy (SEM) and XRD. Magnetic zeolite NaA with different Fe3O4 loadings was prepared and used for removal of heavy metals (Cu2+, Pb2+). The results show the optimum parameters for synthesis zeolite NaA are SiO2/Al2O3 = 2.3, Na2O/SiO2 = 1.4, H2O/Na2O = 50, crystallization time 8 h, crystallization temperature 95 �C. The addition of Fe3O4 makes the NaA zeolite with good magnetic susceptibility and good magnetic stability regardless of the Fe3O4 loading, confirming the considerable separation efficiency. Additionally, Fe3O4 loading had a little effect on removal of heavy metal by magnetic zeolite, however, the adsorption capacity still reaches 2.3 mmol g�1 for Cu2+, Pb2+ with a removal efficiency of over 95% in spite of 4.7% Fe3O4 loading. This indicates magnetic zeolite can be used to remove metal heavy at least Cu2+, Pb2+ from water with metallic contaminants and can be separated easily after a magnetic process.