971 resultados para Power Sensitivity Model


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Multi-core and many-core platforms are becoming increasingly heterogeneous and asymmetric. This significantly increases the porting and tuning effort required for parallel codes, which in turn often leads to a growing gap between peak machine power and actual application performance. In this work a first step toward the automated optimization of high level skeleton-based parallel code is discussed. The paper presents an abstract annotation model for skeleton programs aimed at formally describing suitable mapping of parallel activities on a high-level platform representation. The derived mapping and scheduling strategies are used to generate optimized run-time code. © 2013 Springer-Verlag Berlin Heidelberg.

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This work presents the application of reduced rank regression to the field of systems biology. A computational approach is used to investigate the mechanisms of the janus-associated kinases/signal transducers and transcription factors (JAK/STAT) and mitogen activated protein kinases (MAPK) signal transduction pathways in hepatic cells stimulated by interleukin-6. The results obtained identify the contribution of individual reactions to the dynamics of the model. These findings are compared to previously available results from sensitivity analysis of the model which focused on the parameters involved and their effect. This application of reduced rank regression allows for an understanding of the individual reaction terms involved in the modelled signal transduction pathways and has the benefit of being computationally inexpensive. The obtained results complement existing findings and also confirm the importance of several protein complexes in the MAPK pathway which hints at benefits that can be achieved by further refining the model.

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This paper argues that the structured dependency thesis must be extended to incorporate political power. It outlines a political framework of analysis with which to identify who gains and who loses from social policy. I argue that public policy for older people is a product not only of social structures but also of political decision-making. The Schneider and Ingram (1993) ‘ target populations’ model is used to investigate how the social construction of groups as dependent equates with lower levels of influence on policy making. In United Kingdom and European research, older people are identified as politically quiescent, but conversely in the United States seniors are viewed as one of the most influential and cohesive interest groups in the political culture. Why are American seniors perceived as politically powerful, while older people in Europe are viewed as dependent and politically weak? This paper applies the ‘target populations’ model to senior policy in the Republic of Ireland to investigate how theoretical work in the United States may be used to identify the significance of senior power in policy development. I conclude that research must recognise the connections between power, politics and social constructions to investigate how state policies can influence the likelihood that seniors will resist structured dependency using political means.

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The European Union has set a target of 20% for the share of renewable energy sources in gross final energy consumption in 2020. These renewable energy targets are priority objectives for the Europe 2020 strategy for inclusive growth. In line with the European Union renewable energy policies, the Northern Ireland Executive has a target to deliver 40% renewable electricity by 2020. Currently, Northern Ireland imports 98% of the energy it uses in the form of fossil fuels. Locally produced energy and electricity is needed to ensure sustainable development. The aim of this research is to develop part of a strategy for the mechanical power take-off system for a flap type wave energy converter. Aquamarine Power Ltd’s Oyster flap was the device used for simulation and testing purposes. In this paper the state-of-the-art of wave energy converters is reviewed and a 40th scale test model was developed and built.

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Approximately 20 per cent of quasi-stellar objects (QSOs) exhibit broad, blue-shifted absorption lines in their ultraviolet spectra. Such features provide clear evidence for significant outflows from these systems, most likely in the form of accretion disc winds. These winds may represent the ‘quasar’ mode of feedback that is often invoked in galaxy formation/evolution models, and they are also key to unification scenarios for active galactic nuclei (AGN) and QSOs. To test these ideas, we construct a simple benchmark model of an equatorial, biconical accretion disc wind in a QSO and use a Monte Carlo ionization/radiative transfer code to calculate the ultraviolet spectra as a function of viewing angle. We find that for plausible outflow parameters, sightlines looking directly into the wind cone do produce broad, blue-shifted absorption features in the transitions typically seen in broad absorption line (BAL) QSOs. However, our benchmark model is intrinsically X-ray weak in order to prevent overionization of the outflow, and the wind does not yet produce collisionally excited line emission at the level observed in non-BAL QSOs. As a first step towards addressing these shortcomings, we discuss the sensitivity of our results to changes in the assumed X-ray luminosity and mass-loss rate, Ṁwind. In the context of our adopted geometry, Ṁwind ∼ Ṁacc is required in order to produce significant BAL features. The kinetic luminosity and momentum carried by such outflows would be sufficient to provide significant feedback.

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The power output from a wave energy converter is typically predicted using experimental and/or numerical modelling techniques. In order to yield meaningful results the relevant characteristics of the device, together with those of the wave climate must be modelled with sufficient accuracy.

The wave climate is commonly described using a scatter table of sea states defined according to parameters related to wave height and period. These sea states are traditionally modelled with the spectral distribution of energy defined according to some empirical formulation. Since the response of most wave energy converters vary at different frequencies of excitation, their performance in a particular sea state may be expected to depend on the choice of spectral shape employed rather than simply the spectral parameters. Estimates of energy production may therefore be affected if the spectral distribution of wave energy at the deployment site is not well modelled. Furthermore, validation of the model may be affected by differences between the observed full scale spectral energy distribution and the spectrum used to model it.

This paper investigates the sensitivity of the performance of a bottom hinged flap type wave energy converter to the spectral energy distribution of the incident waves. This is investigated experimentally using a 1:20 scale model of Aquamarine Power’s Oyster wave energy converter, a bottom hinged flap type device situated at the European Marine Energy Centre (EMEC) in approximately 13m water depth. The performance of the model is tested in sea states defined according to the same wave height and period parameters but adhering to different spectral energy distributions.

The results of these tests show that power capture is reduced with increasing spectral bandwidth. This result is explored with consideration of the spectral response of the device in irregular wave conditions. The implications of this result are discussed in the context of validation of the model against particular prototype data sets and estimation of annual energy production.

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This paper investigates the construction of linear-in-the-parameters (LITP) models for multi-output regression problems. Most existing stepwise forward algorithms choose the regressor terms one by one, each time maximizing the model error reduction ratio. The drawback is that such procedures cannot guarantee a sparse model, especially under highly noisy learning conditions. The main objective of this paper is to improve the sparsity and generalization capability of a model for multi-output regression problems, while reducing the computational complexity. This is achieved by proposing a novel multi-output two-stage locally regularized model construction (MTLRMC) method using the extreme learning machine (ELM). In this new algorithm, the nonlinear parameters in each term, such as the width of the Gaussian function and the power of a polynomial term, are firstly determined by the ELM. An initial multi-output LITP model is then generated according to the termination criteria in the first stage. The significance of each selected regressor is checked and the insignificant ones are replaced at the second stage. The proposed method can produce an optimized compact model by using the regularized parameters. Further, to reduce the computational complexity, a proper regression context is used to allow fast implementation of the proposed method. Simulation results confirm the effectiveness of the proposed technique. © 2013 Elsevier B.V.

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Foucault identified the roots of governmentality in religious beliefs and religious history with its genealogical core the equivalent of pastoral power, the art of governing people by relying on a dualistic logic; individualization and totalization. This technology of power arose and matured within the Roman Catholic Church and provided a model for many states in the achievement and exercise of power. Informed by the work of Foucault on pastoral power the present work examines the genealogical core of governmentality in the context of the Roman Catholic Church at a time of great crisis in the 15th century when the Roman Catholic Church was undergoing reform instituted by Pope Eugenius IV (1431-1447). The contributions of accounting to pastoral power are shown in this study to have been pivotal in restoring the Church’s standing and influence. Accounting was one of the technologies that allowed the bishops to control both the diocese as a whole and each priest, to subjugate the priests to the bishops’ authority and, thereby, to govern the diocese through a never-ending extraction of truth.

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Universities are in a current state of transition, whereby they are expected to develop a wide range of relationships with stakeholders in order to enhance regional innovation systems. However, despite external environmental pressures commonly regarded as one of the main drivers of business model evolution, there is a lack of studies that explore business model innovation as a result of multiple stakeholder influences. Accordingly, the aim of this paper is to examine the changing university business model within a region of the United Kingdom, using a stakeholder perspective that will aid theoretical development and refinement in both the business model and stakeholder fields. This examination is aided by consideration of the university business model as an activity system. Repeat interviews, combined with stakeholder theory, have been used to show how the changing university business model–stakeholder relationship has progressed through different stakeholder stages with resultant changes in content, structure and governance. Furthermore, conflicting objectives between each of the stakeholder groups (i.e. academics, industry liaison staff, technology transfer office staff and government support agency representatives) have led to the university business model evolving not as a process of co-creation but rather in a series of transitions whereby multiple stakeholders are continually shaping the university business model through strategies that are dependent upon their salience. Finally, this paper contributes to the development and refinement of business model innovation research, in that the use of stakeholder constructs can illustrate the impact of multiple stakeholders' power and influence on business model innovation.

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This study presents a model based on partial least squares (PLS) regression for dynamic line rating (DLR). The model has been verified using data from field measurements, lab tests and outdoor experiments. Outdoor experimentation has been conducted both to verify the model predicted DLR and also to provide training data not available from field measurements, mainly heavily loaded conditions. The proposed model, unlike the direct measurement based DLR techniques, enables prediction of line rating for periods ahead of time whenever a reliable weather forecast is available. The PLS approach yields a very simple statistical model that accurately captures the physical performance of the conductor within a given environment without requiring a predetermination of parameters as required by many physical modelling techniques. Accuracy of the PLS model has been tested by predicting the conductor temperature for measurement sets other than those used for training. Being a linear model, it is straightforward to estimate the conductor ampacity for a set of predicted weather parameters. The PLS estimated ampacity has proven its accuracy through an outdoor experiment on a piece of the line conductor in real weather conditions.

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This paper is concerned with the voltage and reactive power issues surrounding the connection of Distributed Generation (DG) on the low-voltage (LV) distribution network. The presented system-wide voltage control algorithm consists of three stages. Firstly available reactive power reserves are utilized. Then, if required, DG active power output is curtailed. Finally, curtailment of non-critical site demand is considered. The control methodology is tested on a variant of the 13-bus IEEE Node Radial Distribution Test Feeder. The presented control algorithm demonstrated that the distribution system operator (DSO) can maintain voltage levels within a desired statutory range by dispatching reactive power from DG or network devices. The practical application of the control strategy is discussed.

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Although pumped hydro storage is seen as a strategic key asset by grid operators, financing it is complicated in new liberalised markets. It could be argued that the optimum generation portfolio is now determined by the economic viability of generators based on a short to medium term return on investment. This has meant that capital intensive projects such as pumped hydro storage are less attractive for wholesale electricity companies because the payback periods are too long. In tandem a significant amount of wind power has entered the generation mix, which has resulted in operating and planning integration issues due to wind's inherent uncertain, varying spatial and temporal nature. These integration issues can be overcome using fast acting gas peaking plant or energy storage. Most analysis of wind power integration using storage to date has used stochastic optimisation for power system balancing or arbitrage modelling to examine techno-economic viability. In this research a deterministic dynamic programming long term generation expansion model is employed to optimise the generation mix, total system costs and total carbon dioxide emissions, and unlike other studies calculates reserve to firm wind power. The key finding of this study is that the incentive to build capital-intensive pumped hydro storage to firm wind power is limited unless exogenous market costs come very strongly into play. Furthermore it was demonstrated that reserve increases with increasing wind power showing the importance of ancillary services in future power systems. © 2014 Elsevier Ltd. All rights reserved.

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Using device-to-device communications as an underlay for cellular communications will provide an exciting opportunity to increase network capacity as well as improving spectral efficiency. The unique geometry of device-to-device links, where user equipment is often held or carried at low elevation and in close proximity to the human body, will mean that they are particularly susceptible to shadowing events caused not only by the local environment but also by the user's body. In this paper, the shadowed κ - μ fading model is proposed, which is capable of characterizing shadowed fading in wireless communication channels. In this model, the statistics of the received signal are manifested by the clustering of multipath components. Within each of these clusters, a dominant signal component with arbitrary power may exist. The resultant dominant signal component, which is formed by the phasor addition of these leading contributions, is assumed to follow a Nakagami- m distribution. The probability density function, moments, and the moment-generating function are also derived. The new model is then applied to device-to-device links operating at 868 MHz in an outdoor urban environment. It was found that shadowing of the resultant dominant component can vary significantly depending upon the position of the user equipment relative to the body and the link geometry. Overall, the shadowed κ - μ fading model is shown to provide a good fit to the field data as well as providing a useful insight into the characteristics of the received signal.

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Understanding how invasive species spread is of particular concern in the current era of globalisation and rapid environmental change. The occurrence of super-diffusive movements within the context of Lévy flights has been discussed with respect to particle physics, human movements, microzooplankton, disease spread in global epidemiology and animal foraging behaviour. Super-diffusive movements provide a theoretical explanation for the rapid spread of organisms and disease, but their applicability to empirical data on the historic spread of organisms has rarely been tested. This study focuses on the role of long-distance dispersal in the invasion dynamics of aquatic invasive species across three contrasting areas and spatial scales: open ocean (north-east Atlantic), enclosed sea (Mediterranean) and an island environment (Ireland). Study species included five freshwater plant species, Azolla filiculoides, Elodea canadensis, Lagarosiphon major, Elodea nuttallii and Lemna minuta; and ten species of marine algae, Asparagopsis armata, Antithamnionella elegans, Antithamnionella ternifolia, Codium fragile, Colpomenia peregrina, Caulerpa taxifolia, Dasysiphonia sp., Sargassum muticum, Undaria pinnatifida and Womersleyella setacea. A simulation model is constructed to show the validity of using historical data to reconstruct dispersal kernels. Lévy movement patterns similar to those previously observed in humans and wild animals are evident in the re-constructed dispersal pattern of invasive aquatic species. Such patterns may be widespread among invasive species and could be exacerbated by further development of trade networks, human travel and environmental change. These findings have implications for our ability to predict and manage future invasions, and improve our understanding of the potential for spread of organisms including infectious diseases, plant pests and genetically modified organisms.

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Low-power processors and accelerators that were originally designed for the embedded systems market are emerging as building blocks for servers. Power capping has been actively explored as a technique to reduce the energy footprint of high-performance processors. The opportunities and limitations of power capping on the new low-power processor and accelerator ecosystem are less understood. This paper presents an efficient power capping and management infrastructure for heterogeneous SoCs based on hybrid ARM/FPGA designs. The infrastructure coordinates dynamic voltage and frequency scaling with task allocation on a customised Linux system for the Xilinx Zynq SoC. We present a compiler-assisted power model to guide voltage and frequency scaling, in conjunction with workload allocation between the ARM cores and the FPGA, under given power caps. The model achieves less than 5% estimation bias to mean power consumption. In an FFT case study, the proposed power capping schemes achieve on average 97.5% of the performance of the optimal execution and match the optimal execution in 87.5% of the cases, while always meeting power constraints.