204 resultados para Market segmentation


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Invited panel speaker at a Jean Monnet Chair funded research workshop organised by the Europa Institute, School of Law, University of Edinburgh (9 December 2011), http://www.pol.ed.ac.uk/research_themes/index/jean_monnet_centre_of_excellence/principles_of_market_access_workshop

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Over the last decade there has been a rapid global increase in wind power stimulated by energy and climate policies. However, as wind power is inherently variable and stochastic over a range of time scales, additional system balancing is required to ensure system reliability and stability. This paper reviews the technical, policy and market challenges to achieving ambitious wind power penetration targets in Ireland’s All-Island Grid and examines a number of measures proposed to address these challenges. Current government policy in Ireland is to address these challenges with additional grid reinforcement, interconnection and open-cycle gas plant. More recently smart grid combined with demand side management and electric vehicles have also been presented as options to mitigate the variability of wind power. In addition, the transmission system operators have developed wind farm specific grid codes requiring improved turbine controls and wind power forecasting techniques.

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We report the largest market basket survey of arsenic (As) in U.S. rice to date. Our findings show differences in transitional-metal levels between polished and unpolished rice and geographical variation in As and selenium (Se) between rice processed in California and the South Central U.S. The mean and median As grain levels for the South Central U.S. were 0.30 and 0.27 µg As g-1, respectively, for 107 samples. Levels for California were 41% lower than the South Central U.S., with a mean of 0.17 µg As g-1 and a median of 0.16 µg As g-1 for 27 samples. The mean and median Se grain levels for the South Central U.S. were 0.19 µg Se g-1. Californian rice levels were lower, averaging only 0.08 and 0.06 µg Se g-1 for mean and median values, respectively. The difference between the two regions was found to be significant for As and Se (General Linear Model (GLM):? As p < 0.001; Se p < 0.001). No statistically significant differences were observed in As or Se levels between polished and unpolished rice (GLM:? As p = 0.213; Se p = 0.113). No significant differences in grain levels of manganese (Mn), cobalt (Co), copper (Cu), or zinc (Zn) were observed between California and the South Central U.S. Modeling arsenic intake for the U.S. population based on this survey shows that for certain groups (namely Hispanics, Asians, sufferers of Celiac disease, and infants) dietary exposure to inorganic As from elevated levels in rice potentially exceeds the maximum intake of As from drinking water (based on consumption of 1 L of 0.01 mg L-1 In. As) and Californian state exposure limits. Further studies on the transformation of As in soil, grain As bioavailability in the human gastrointestinal tract, and grain elemental speciation trends are critical.

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The Irish government set a target in 2008 that 10% of all vehicles in the transport fleet be powered by electricity by 2020. Similar electric vehicle targets have been introduced in other countries. In this study the effects of 213,561 electric vehicles on the operation of the single wholesale electricity market for the Republic of Ireland and Northern Ireland is investigated. A model of Ireland’s electricity market in 2020 is developed using the power systems market model called PLEXOS for power systems. The amount of CO2 emissions associated with charging the EVs and the impacts with respect to Ireland’s target for renewable energy in transport is also quantified. A single generation portfolio and two different charging scenarios, arising from a peak and off-peak charging profile are considered. Results from the study confirm that offpeak charging is more beneficial than peak charging and that charging EVs will contribute 1.45% energy supply to the 10% renewable energy in transport target. The net CO2 reductions are 147 and 210 kt CO2 respectively.

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This article shows how both employers and the state have influenced macro-level processes and structures concerning the content and transposition of the European Union (EU) Employee Information and Consultation (I&C) Directive. It argues that the processes of regulation occupied by employers reinforce a voluntarism which marginalizes rather than shares decision-making power with workers. The contribution advances the conceptual lens of ‘regulatory space’ by building on Lukes’ multiple faces of power to better understand how employment regulation is determined across transnational, national and enterprise levels. The research proposes an integrated analytical framework on which ‘occupancy’ of regulatory space can be evaluated in comparative national contexts.

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In this paper, we propose a multi-camera application capable of processing high resolution images and extracting features based on colors patterns over graphic processing units (GPU). The goal is to work in real time under the uncontrolled environment of a sport event like a football match. Since football players are composed for diverse and complex color patterns, a Gaussian Mixture Models (GMM) is applied as segmentation paradigm, in order to analyze sport live images and video. Optimization techniques have also been applied over the C++ implementation using profiling tools focused on high performance. Time consuming tasks were implemented over NVIDIA's CUDA platform, and later restructured and enhanced, speeding up the whole process significantly. Our resulting code is around 4-11 times faster on a low cost GPU than a highly optimized C++ version on a central processing unit (CPU) over the same data. Real time has been obtained processing until 64 frames per second. An important conclusion derived from our study is the scalability of the application to the number of cores on the GPU. © 2011 Springer-Verlag.

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In recent years, gradient vector flow (GVF) based algorithms have been successfully used to segment a variety of 2-D and 3-D imagery. However, due to the compromise of internal and external energy forces within the resulting partial differential equations, these methods may lead to biased segmentation results. In this paper, we propose MSGVF, a mean shift based GVF segmentation algorithm that can successfully locate the correct borders. MSGVF is developed so that when the contour reaches equilibrium, the various forces resulting from the different energy terms are balanced. In addition, the smoothness constraint of image pixels is kept so that over- or under-segmentation can be reduced. Experimental results on publicly accessible datasets of dermoscopic and optic disc images demonstrate that the proposed method effectively detects the borders of the objects of interest.

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We model how student choices to rush a fraternity, and fraternity admission choices, interact with signals firms receive about student productivities to determine labor-market outcomes. The fraternity and students value wages and fraternity socializing values. We provide sufficient conditions under which, in equilibrium, most members have intermediate abilities: weak students apply, but are rejected unless they have high socializing values, while most able students do not apply to avoid taint from association with weaker members.