332 resultados para Distributed parameters


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Distribution feeder voltage reinforcement by multiple site reactive power compensation systems has recently been reported by many researchers. However, voltage control by multiple DSTATCOMs across a distribution feeder may introduce control interactions and/or voltage instability. This paper addresses these control interaction issues and proposes a control scheme that alleviates interactions among controllers. The proposed control scheme also enhances proper sharing of reactive power among DSTATCOMs. A mathematical model of a distribution system with any number of DSTATCOMs is developed to investigate the performance of the control system. This mathematical model is used to conduct eigenvalue analysis to develop the criterion for controller design. The proposed control scheme is tested in time domain on a sample radial distribution feeder installed with multiple DSTATCOMs and test results are presented.

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Modelling an environmental process involves creating a model structure and parameterising the model with appropriate values to accurately represent the process. Determining accurate parameter values for environmental systems can be challenging. Existing methods for parameter estimation typically make assumptions regarding the form of the Likelihood, and will often ignore any uncertainty around estimated values. This can be problematic, however, particularly in complex problems where Likelihoods may be intractable. In this paper we demonstrate an Approximate Bayesian Computational method for the estimation of parameters of a stochastic CA. We use as an example a CA constructed to simulate a range expansion such as might occur after a biological invasion, making parameter estimates using only count data such as could be gathered from field observations. We demonstrate ABC is a highly useful method for parameter estimation, with accurate estimates of parameters that are important for the management of invasive species such as the intrinsic rate of increase and the point in a landscape where a species has invaded. We also show that the method is capable of estimating the probability of long distance dispersal, a characteristic of biological invasions that is very influential in determining spread rates but has until now proved difficult to estimate accurately.

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This paper presents a comprehensive study to find the most efficient bitrate requirement to deliver mobile video that optimizes bandwidth, while at the same time maintains good user viewing experience. In the study, forty participants were asked to choose the lowest quality video that would still provide for a comfortable and long-term viewing experience, knowing that higher video quality is more expensive and bandwidth intensive. This paper proposes the lowest pleasing bitrates and corresponding encoding parameters for five different content types: cartoon, movie, music, news and sports. It also explores how the lowest pleasing quality is influenced by content type, image resolution, bitrate, and user gender, prior viewing experience, and preference. In addition, it analyzes the trajectory of users’ progression while selecting the lowest pleasing quality. The findings reveal that the lowest bitrate requirement for a pleasing viewing experience is much higher than that of the lowest acceptable quality. Users’ criteria for the lowest pleasing video quality are related to the video’s content features, as well as its usage purpose and the user’s personal preferences. These findings can provide video providers guidance on what quality they should offer to please mobile users.

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This paper focuses on understanding distributed leadership and professional learning communities (PLCs). Through an Australian Government grant, the Teacher Education Done Differently (TEDD) project, data were analysed from 25 school executives about distributed leadership as a potential for influencing educational change through forums such as PLCs. Findings will be discussed in relation to: (1) Understanding the nature of a PLC, (2) Leadership within PLCs, (3) Advancing PLCs, and (4) PLCs as forums for capacity building a profession. A cyclic model for facilitating PLCs is presented, where information such as issues and problems are brought to the collective, discussed and analysed openly to provide further feedback. There are implications for leaders to up-skill staff on distributed leadership practices and further research required to determine which practices facilitate successful PLCs.

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Twin studies offer the opportunity to determine the relative contribution of genes versus environment in traits of interest. Here, we investigate the extent to which variance in brain structure is reduced in monozygous twins with identical genetic make-up. We investigate whether using twins as compared to a control population reduces variability in a number of common magnetic resonance (MR) structural measures, and we investigate the location of areas under major genetic influences. This is fundamental to understanding the benefit of using twins in studies where structure is the phenotype of interest. Twenty-three pairs of healthy MZ twins were compared to matched control pairs. Volume, T2 and diffusion MR imaging were performed as well as spectroscopy (MRS). Images were compared using (i) global measures of standard deviation and effect size, (ii) voxel-based analysis of similarity and (iii) intra-pair correlation. Global measures indicated a consistent increase in structural similarity in twins. The voxel-based and correlation analyses indicated a widespread pattern of increased similarity in twin pairs, particularly in frontal and temporal regions. The areas of increased similarity were most widespread for the diffusion trace and least widespread for T2. MRS showed consistent reduction in metabolite variation that was significant in the temporal lobe N-acetylaspartate (NAA). This study has shown the distribution and magnitude of reduced variability in brain volume, diffusion, T2 and metabolites in twins. The data suggest that evaluation of twins discordant for disease is indeed a valid way to attribute genetic or environmental influences to observed abnormalities in patients since evidence is provided for the underlying assumption of decreased variability in twins.

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Distributed generators (DGs) are defined as generators that are connected to a distribution network. The direction of the power flow and short-circuit current in a network could be changed compared with one without DGs. The conventional protective relay scheme does not meet the requirement in this emerging situation. As the number and capacity of DGs in the distribution network increase, the problem of coordinating protective relays becomes more challenging. Given this background, the protective relay coordination problem in distribution systems is investigated, with directional overcurrent relays taken as an example, and formulated as a mixed integer nonlinear programming problem. A mathematical model describing this problem is first developed, and the well-developed differential evolution algorithm is then used to solve it. Finally, a sample system is used to demonstrate the feasiblity and efficiency of the developed method.

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Some uncertainties such as the stochastic input/output power of a plug-in electric vehicle due to its stochastic charging and discharging schedule, that of a wind unit and that of a photovoltaic generation source, volatile fuel prices and future uncertain load growth, all together could lead to some risks in determining the optimal siting and sizing of distributed generators (DGs) in distributed systems. Given this background, under the chance constrained programming (CCP) framework, a new method is presented to handle these uncertainties in the optimal sitting and sizing problem of DGs. First, a mathematical model of CCP is developed with the minimization of DGs investment cost, operational cost and maintenance cost as well as the network loss cost as the objective, security limitations as constraints, the sitting and sizing of DGs as optimization variables. Then, a Monte Carolo simulation embedded genetic algorithm approach is developed to solve the developed CCP model. Finally, the IEEE 37-node test feeder is employed to verify the feasibility and effectiveness of the developed model and method. This work is supported by an Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) Project on Intelligent Grids Under the Energy Transformed Flagship, and Project from Jiangxi Power Company.

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Precise identification of the time when a change in a hospital outcome has occurred enables clinical experts to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for survival time of a clinical procedure in the presence of patient mix in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step change in the mean survival time of patients who underwent cardiac surgery. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. Markov Chain Monte Carlo is used to obtain posterior distributions of the change point parameters including location and magnitude of changes and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time CUSUM control charts for different magnitude scenarios. The proposed estimator shows a better performance where a longer follow-up period, censoring time, is applied. In comparison with the alternative built-in CUSUM estimator, more accurate and precise estimates are obtained by the Bayesian estimator. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered.

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This study investigated potential palaeoclimate proxies provided by rare earth element (REE) geochemistry in speleothems and in clay mineralogy of cave sediments. Speleothem and sediment samples were collected from a series of cave fill deposits that occurred with rich vertebrate fossil assemblages in and around Mount Etna National Park, Rockhampton (central coastal Queensland). The fossil deposits range from Plio- Pleistocene to Holocene in age (based on uranium/thorium dating) and appear to represent depositional environments ranging from enclosed rainforest to semi-arid grasslands. Therefore, the Mount Etna cave deposits offer the perfect opportunity to test new palaeoclimate tools as they include deposits that span a known significant climate shift on the basis of independent faunal data. The first section of this study investigates the REE distribution of the host limestone to provide baseline geochemistry for subsequent speleothem investigations. The Devonian Mount Etna Beds were found to be more complex than previous literature had documented. The studied limestone massif is overturned, highly recrystallised in parts and consists of numerous allochthonous blocks with different spatial orientations. Despite the complex geologic history of the Mount Etna Beds, Devonian seawater-like REE patterns were recovered in some parts of the limestone and baseline geochemistry was determined for the bulk limestone for comparison with speleothem REE patterns. The second part of the study focused on REE distribution in the karst system and the palaeoclimatic implications of such records. It was found that REEs have a high affinity for calcite surfaces and that REE distributions in speleothems vary between growth bands much more than along growth bands, thus providing a temporal record that may relate to environmental changes. The morphology of different speleothems (i.e., stalactites, stalagmites, and flowstones) has little bearing on REE distributions provided they are not contaminated with particulate fines. Thus, baseline knowledge developed in the study suggested that speleothems were basically comparable for assessing palaeoclimatically controlled variations in REE distributions. Speleothems from rainforest and semi-arid phases were compared and it was found that there are definable differences in REE distribution that can be attributed to climate. In particular during semiarid phases, total REE concentration decreased, LREE became more depleted, Y/Ho increased, La anomalies were more positive and Ce anomalies were more negative. This may reflect more soil development during rainforest phases and more organic particles and colloids, which are known to transport REEs, in karst waters. However, on a finer temporal scale (i.e. growth bands) within speleothems from the same climate regime, no difference was seen. It is suggested that this may be due to inadequate time for soil development changes on the time frames represented by differences in growth band density. The third part of the study was a reconnaissance investigation focused on mineralogy of clay cave sediments, illite/kaolinite ratios in particular, and the potential palaeoclimatic implications of such records. Although the sample distribution was not optimal, the preliminary results suggest that the illite/kaolinite ratio increased during cold and dry intervals, consistent with decreased chemical weathering during those times. The study provides a basic framework for future studies at differing latitudes to further constrain the parameters of the proxy. The identification of such a proxy recorded in cave sediment has broad implications as clay ratios could potentially provide a basic local climate proxy in the absence of fossil faunas and speleothem material. This study suggests that REEs distributed in speleothems may provide information about water throughput and soil formation, thus providing a potential palaeoclimate proxy. It highlights the importance of understanding the host limestone geochemistry and broadens the distribution and potential number of cave field sites as palaeoclimate information no longer relies solely on the presence of fossil faunas and or speleothems. However, additional research is required to better understand the temporal scales required for the proxies to be recognised.

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A distributed fuzzy system is a real-time fuzzy system in which the input, output and computation may be located on different networked computing nodes. The ability for a distributed software application, such as a distributed fuzzy system, to adapt to changes in the computing network at runtime can provide real-time performance improvement and fault-tolerance. This paper introduces an Adaptable Mobile Component Framework (AMCF) that provides a distributed dataflow-based platform with a fine-grained level of runtime reconfigurability. The execution location of small fragments (possibly as little as few machine-code instructions) of an AMCF application can be moved between different computing nodes at runtime. A case study is included that demonstrates the applicability of the AMCF to a distributed fuzzy system scenario involving multiple physical agents (such as autonomous robots). Using the AMCF, fuzzy systems can now be developed such that they can be distributed automatically across multiple computing nodes and are adaptable to runtime changes in the networked computing environment. This provides the opportunity to improve the performance of fuzzy systems deployed in scenarios where the computing environment is resource-constrained and volatile, such as multiple autonomous robots, smart environments and sensor networks.

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Colour is one of the most important parameters in sugar quality and its presence in raw sugar plays a key role in the marketing strategy of sugar industries worldwide. This study investigated the degradation of a mixture of colour precursors using the Fenton oxidation process. These colour precursors are caffeic acid, p–coumaric acid and ferulic acid, which are present in cane juice. Results showed that with a Fe(II) to H2O2 molar ratio of 1:15 in an aqueous system at 25 °C, 77% of the total phenolic acid content was removed at pH 4.72. However, in a synthetic juice solution which contained 13 mass % sucrose (35 °C, pH 5.4), only 60% of the total phenolic acid content was removed.

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The ability to detect unusual events in surviellance footage as they happen is a highly desireable feature for a surveillance system. However, this problem remains challenging in crowded scenes due to occlusions and the clustering of people. In this paper, we propose using the Distributed Behavior Model (DBM), which has been widely used in computer graphics, for video event detection. Our approach does not rely on object tracking, and is robust to camera movements. We use sparse coding for classification, and test our approach on various datasets. Our proposed approach outperforms a state-of-the-art work which uses the social force model and Latent Dirichlet Allocation.

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In this conceptual article, we extend earlier work on Open Innovation and Absorptive Capacity. We suggest that the literature on Absorptive Capacity does not place sufficient emphasis on distributed knowledge and learning or on the application of innovative knowledge. To accomplish physical transformations, organisations need specific Innovative Capacities that extend beyond knowledge management. Accessive Capacity is the ability to collect, sort and analyse knowledge from both internal and external sources. Adaptive Capacity is needed to ensure that new pieces of equipment are suitable for the organisation's own purposes even though they may have been originally developed for other uses. Integrative Capacity makes it possible for a new or modified piece of equipment to be fitted into an existing production process with a minimum of inessential and expensive adjustment elsewhere in the process. These Innovative Capacities are controlled and coordinated by Innovative Management Capacity, a higher-order dynamic capability.

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Changing sodium intake from 70-200 mmol/day elevates blood pressure in normotensive volunteers by 6/4 mmHg. Older people, people with reduced renal function on a low sodium diet and people with a family history of hypertension are more likely to show this effect. The rise in blood pressure was associated with a fall in plasma volume suggesting that plasma volume changes do not initiate hypertension. In normotensive individuals the most common abnormality in membrane sodium transport induced by an extra sodium load was an increased permeability of the red cell to sodium. Some normotensive individuals also had an increase in the level of a plasma inhibitor that inhibited Na-K ATPase. These individuals also appeared to have a rise in blood pressure. Sodium intake and blood pressure are related. The relationship differs in different people and is probably controlled by the genetically inherited capacity of systems involved in membrane sodium transport.