662 resultados para impulse matrix response


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A microgrid may be supplied from inertial (rotating type) and non-inertial (converter-interfaced) distributed generators (DGs). However the dynamic response of these two types of DGs is different. Inertial DGs have a slower response due to their governor characteristics while non inertial DGs have the ability to respond very quickly. The focus of this paper is to propose better controls using droop characteristics to improve the dynamic interaction between different DG types in an autonomous microgrid. The transient behavior of DGs in the microgrid is investigated during the DG synchronization and load changes. Power sharing strategies based on frequency and voltage droop are considered for DGs. Droop control strategies are proposed for DGs to improve the smooth synchronization and dynamic power sharing minimizing transient oscillations in the microgrid. Simulation studies are carried out on PSCAD for validation.

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This paper introduces the concept of workplace mobbing as a destructive organizational behaviour of psychological assaults perpetrated against the target causing them harm and loss of employment. The discussion is drawn from a three year Australian study of 212 self identified targets of workplace mobbing behaviours. The behaviours are typically covert with informal networks and friendship loyalties providing effective mechanisms for emotional abuse, including those arising from human resource management practices. This paper discusses the manipulation of informal sources of power, with the use of gossip, rumour, hearsay, and innuendo to discredit and demonise those targeted. The study explores some of the systemic reasons for these behaviours and identifies some of the contributing risk factors and suggests management practices that can minimise the harm caused.

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In an attempt to curb online copyright infringement, copyright owners are increasingly seeking to enlist the assistance of Internet Service Providers (‘ISPs’) to enforce copyright and impose sanctions on their users.1 Commonly termed ‘graduated response’ schemes, these measures generally require that the ISP take some action against users suspected of infringing copyright, ranging from issuing warnings, to collating allegations made against subscribers and reporting to copyright owners, to suspension and eventual termination of service.

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Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive semidefinite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space - classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semidefinite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -using the labeled part of the data one can learn an embedding also for the unlabeled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method for learning the 2-norm soft margin parameter in support vector machines, solving an important open problem.

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The aim of this work is to develop a Demand-Side-Response (DSR) model, which assists electricity end-users to be engaged in mitigating peak demands on the electricity network in Eastern and Southern Australia. The proposed innovative model will comprise a technical set-up of a programmable internet relay, a router, solid state switches in addition to the suitable software to control electricity demand at user's premises. The software on appropriate multimedia tool (CD Rom) will be curtailing/shifting electric loads to the most appropriate time of the day following the implemented economic model, which is designed to be maximizing financial benefits to electricity consumers. Additionally the model is targeting a national electrical load be spread-out evenly throughout the year in order to satisfy best economic performance for electricity generation, transmission and distribution. The model is applicable in region managed by the Australian Energy Management Operator (AEMO) covering states of Eastern-, Southern-Australia and Tasmania.

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The paper presents a demand side response scheme,which assists electricity consumers to proactively control own demands in such a way to deliberately avert congestion periods on the electrical network. The scheme allows shifting loads from peak to low demand periods in an attempt to flattening the national electricity requirement. The scheme can be concurrently used to accommodate the utilization of renewable energy sources,that might be available at user’s premises. In addition the scheme allows a full-capacity utilization of the available electrical infrastructure by organizing a wide-use of electric vehicles. The scheme is applicable in the Eastern and Southern States of Australia managed by the Australian Energy Market Operator. The results indicate the potential of the scheme to achieve energy savings and release capacity to accommodate renewable energy and electrical vehicle technologies.

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In this paper we examine the problem of prediction with expert advice in a setup where the learner is presented with a sequence of examples coming from different tasks. In order for the learner to be able to benefit from performing multiple tasks simultaneously, we make assumptions of task relatedness by constraining the comparator to use a lesser number of best experts than the number of tasks. We show how this corresponds naturally to learning under spectral or structural matrix constraints, and propose regularization techniques to enforce the constraints. The regularization techniques proposed here are interesting in their own right and multitask learning is just one application for the ideas. A theoretical analysis of one such regularizer is performed, and a regret bound that shows benefits of this setup is reported.

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Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive definite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space -- classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semi-definite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -- using the labelled part of the data one can learn an embedding also for the unlabelled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method to learn the 2-norm soft margin parameter in support vector machines, solving another important open problem. Finally, the novel approach presented in the paper is supported by positive empirical results.

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Intrinsically photosensitive retinal ganglion cells (ipRGCs) in the eye transmit the environmental light level, projecting to the suprachiasmatic nucleus (SCN) (Berson, Dunn & Takao, 2002; Hattar, Liao, Takao, Berson & Yau, 2002), the location of the circadian biological clock, and the olivary pretectal nucleus (OPN) of the pretectum, the start of the pupil reflex pathway (Hattar, Liao, Takao, Berson & Yau, 2002; Dacey, Liao, Peterson, Robinson, Smith, Pokorny, Yau & Gamlin, 2005). The SCN synchronizes the circadian rhythm, a cycle of biological processes coordinated to the solar day, and drives the sleep/wake cycle by controlling the release of melatonin from the pineal gland (Claustrat, Brun & Chazot, 2005). Encoded photic input from ipRGCs to the OPN also contributes to the pupil light reflex (PLR), the constriction and recovery of the pupil in response to light. IpRGCs control the post-illumination component of the PLR, the partial pupil constriction maintained for > 30 sec after a stimulus offset (Gamlin, McDougal, Pokorny, Smith, Yau & Dacey, 2007; Kankipati, Girkin & Gamlin, 2010; Markwell, Feigl & Zele, 2010). It is unknown if intrinsic ipRGC and cone-mediated inputs to ipRGCs show circadian variation in their photon-counting activity under constant illumination. If ipRGCs demonstrate circadian variation of the pupil response under constant illumination in vivo, when in vitro ipRGC activity does not (Weng, Wong & Berson, 2009), this would support central control of the ipRGC circadian activity. A preliminary experiment was conducted to determine the spectral sensitivity of the ipRGC post-illumination pupil response under the experimental conditions, confirming the successful isolation of the ipRGC response (Gamlin, et al., 2007) for the circadian experiment. In this main experiment, we demonstrate that ipRGC photon-counting activity has a circadian rhythm under constant experimental conditions, while direct rod and cone contributions to the PLR do not. Intrinsic ipRGC contributions to the post-illumination pupil response decreased 2:46 h prior to melatonin onset for our group model, with the peak ipRGC attenuation occurring 1:25 h after melatonin onset. Our results suggest a centrally controlled evening decrease in ipRGC activity, independent of environmental light, which is temporally synchronized (demonstrates a temporal phase-advanced relationship) to the SCN mediated release of melatonin. In the future the ipRGC post-illumination pupil response could be developed as a fast, non-invasive measure of circadian rhythm. This study establishes a basis for future investigation of cortical feedback mechanisms that modulate ipRGC activity.

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Understanding the complex mechanisms underlying bone remodeling is crucial to the development of novel therapeutics. Glycosaminoglycans (GAGs) localised to the extracellular matrix (ECM) of bone are thought to play a key role in mediating aspects of bone development. The influence of isolated GAGs was studied by utilising in vitro murine calvarial monolayer and organ culture model systems. Addition of GAG preparations extracted from the cell surface of human osteoblasts at high concentrations (5 microg/ml) resulted in decreased proliferation of cells and decreased suture width and number of bone lining cells in calvarial sections. When we investigated potential interactions between the growth factors fibroblast growth factor-2 (FGF2), bone morphogenic protein-2 (BMP2) and transforming growth factor-beta1 (TGFbeta1) and the isolated cell surface GAGs, differences between the two model systems emerged. The cell culture system demonstrated a potentiating role for the isolated GAGs in the inhibition of FGF2 and TGFbeta1 actions. In contrast, the organ culture system demonstrated an enhanced stimulation of TFGbeta1 effects. These results emphasise the role of the ECM in mediating the interactions between GAGs and growth factors during bone development and suggest the GAG preparations contain potent inhibitory or stimulatory components able to mediate growth factor activity.

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Extracellular matrix regulates many cellular processes likely to be important for development and regression of corpora lutea. Therefore, we identified the types and components of the extracellular matrix of the human corpus luteum at different stages of the menstrual cycle. Two different types of extracellular matrix were identified by electron microscopy; subendothelial basal laminas and an interstitial matrix located as aggregates at irregular intervals between the non-vascular cells. No basal laminas were associated with luteal cells. At all stages, collagen type IV α1 and laminins α5, β2 and γ1 were localized by immunohistochemistry to subendothelial basal laminas, and collagen type IV α1 and laminins α2, α5, β1 and β2 localized in the interstitial matrix. Laminin α4 and β1 chains occurred in the subendothelial basal lamina from mid-luteal stage to regression; at earlier stages, a punctate pattern of staining was observed. Therefore, human luteal subendothelial basal laminas potentially contain laminin 11 during early luteal development and, additionally, laminins 8, 9 and 10 at the mid-luteal phase. Laminin α1 and α3 chains were not detected in corpora lutea. Versican localized to the connective tissue extremities of the corpus luteum. Thus, during the formation of the human corpus luteum, remodelling of extracellular matrix does not result in basal laminas as present in the adrenal cortex or ovarian follicle. Instead, novel aggregates of interstitial matrix of collagen and laminin are deposited within the luteal parenchyma, and it remains to be seen whether this matrix is important for maintaining the luteal cell phenotype.