997 resultados para Asif Ali Zardari


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Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Antropologia, Poder e Identidade

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Beaver only had been found in Portugal in a Chalcolithic locality, the Vila Nova de S. Pedro castrum. It has now been idenrified in the Upper Paleolithic (Solurrean) from Gruta do Caldeirão, near Tomar. The species has been found recently at «Gruta do Almonda»; 4 teeth were collected in bed C, older than a Solutrean sequence (see Anexo for details). The species seems to have been rare, as it was also the case with portuguese miocene Castoridae Enroxenomys minutus and Chalicomys jaegeri. If account is taken of the presence in the Middle Ages until Castille of words meaning beaver (related to the popular latin Fiber/Biber), it is obvious that these animals still existed then. Such nouns were largely predominant over the rather erudite larin (greek derived) words as Castor, -óris and derived ones, as it could be expected. This allowed us to recognize that veiro should be the corresponding word with Fiber affinities in archaic portuguese. It was previously supposed to mean only expensive furs then imported into Portugal. Indeed it was also a zoonym. Anyway, beaver should be scarce by XIIIth century since it is not included in the quite detailed price list imposed by the «Lei da Almotaçaria» from December 26, 1253 (see Quadro II). Toponyms in veiro and derived words (fig. 2; Quadro III) (plural, feminines, diminutives, inhabited places) give a restrictive view of the Middle Age distribution. Some of them are certainly older than Portugal itself (first half of XIIth century); others existed by the XIVth century but were probably older. Some rare toponyms seem to be derived from rhe erudite latin Castor, -óris. Nothing suggests that these words were still in use as zoonyms during the Middle Ages. All toponyms are located in regions near rivers and other freshwaters ecologically suitable for beavers, so wecan approximately retrace irs former, Middle Age distribution in Portugal (fig. 2; Quadro III). Most of them are located in the Center-West and Northwest of Portugal, with a suitable c1imate (rainfall in general over 800 milimeters per year); the only sure geographical exception is Veiros, in Alto Alentejo province, in a region with comparable precipitations and less dry climare conditions than most of the territories South of the Tagus. There are less and less of these toponyms towards the South and the inner part of the country, and they are enrirely lacking in ali drier regions from Trás-os-Montes, Beira, Alentejo beyond Tagus' basin, and in Algarve. Nothing suggests beavers lived there, No pose-medieval toponym is known, nor any reference after middle XVth century. No such locality was at, or close by to, any frontier. Hence the hypothesis of veiro (e: al.) as meaning but points where expensive furs(supposedly known as veiros in general but without clearly saying from what animal they were obtained from) is to be discarded. During the Middle Ages, beaver distribution concerned all the main river basins from Minho to Tagus ones. Quice racefied in the XIIIth, the beavers may have disappeared from Portugal during the XVth century. Ecological requirements restricted their former distribution. Vulnerability to natural causes (i.e., severe drought) and to human pressure may have accounted heavily for this species extinction. Last (1446) reference for Portugal known to us suggests the species was by then almost extinct.

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Energy consumption is one of the major issues for modern embedded systems. Early, power saving approaches mainly focused on dynamic power dissipation, while neglecting the static (leakage) energy consumption. However, technology improvements resulted in a case where static power dissipation increasingly dominates. Addressing this issue, hardware vendors have equipped modern processors with several sleep states. We propose a set of leakage-aware energy management approaches that reduce the energy consumption of embedded real-time systems while respecting the real-time constraints. Our algorithms are based on the race-to-halt strategy that tends to run the system at top speed with an aim to create long idle intervals, which are used to deploy a sleep state. The effectiveness of our algorithms is illustrated with an extensive set of simulations that show an improvement of up to 8% reduction in energy consumption over existing work at high utilization. The complexity of our algorithms is smaller when compared to state-of-the-art algorithms. We also eliminate assumptions made in the related work that restrict the practical application of the respective algorithms. Moreover, a novel study about the relation between the use of sleep intervals and the number of pre-emptions is also presented utilizing a large set of simulation results, where our algorithms reduce the experienced number of pre-emptions in all cases. Our results show that sleep states in general can save up to 30% of the overall number of pre-emptions when compared to the sleep-agnostic earliest-deadline-first algorithm.

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The deregulation of electricity markets has diversified the range of financial transaction modes between independent system operator (ISO), generation companies (GENCO) and load-serving entities (LSE) as the main interacting players of a day-ahead market (DAM). LSEs sell electricity to end-users and retail customers. The LSE that owns distributed generation (DG) or energy storage units can supply part of its serving loads when the nodal price of electricity rises. This opportunity stimulates them to have storage or generation facilities at the buses with higher locational marginal prices (LMP). The short-term advantage of this model is reducing the risk of financial losses for LSEs in DAMs and its long-term benefit for the LSEs and the whole system is market power mitigation by virtually increasing the price elasticity of demand. This model also enables the LSEs to manage the financial risks with a stochastic programming framework.

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In competitive electricity markets it is necessary for a profit-seeking load-serving entity (LSE) to optimally adjust the financial incentives offering the end users that buy electricity at regulated rates to reduce the consumption during high market prices. The LSE in this model manages the demand response (DR) by offering financial incentives to retail customers, in order to maximize its expected profit and reduce the risk of market power experience. The stochastic formulation is implemented into a test system where a number of loads are supplied through LSEs.

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Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand.

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The forthcoming smart grids are comprised of integrated microgrids operating in grid-connected and isolated mode with local generation, storage and demand response (DR) programs. The proposed model is based on three successive complementary steps for power transaction in the market environment. The first step is characterized as a microgrid’s internal market; the second concerns negotiations between distinct interconnected microgrids; and finally, the third refers to the actual electricity market. The proposed approach is modeled and tested using a MAS framework directed to the study of the smart grids environment, including the simulation of electricity markets. This is achieved through the integration of the proposed approach with the MASGriP (Multi-Agent Smart Grid Platform) system.

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Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Doutor em Antropologia.

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Heterogeneous multicore platforms are becoming an interesting alternative for embedded computing systems with limited power supply as they can execute specific tasks in an efficient manner. Nonetheless, one of the main challenges of such platforms consists of optimising the energy consumption in the presence of temporal constraints. This paper addresses the problem of task-to-core allocation onto heterogeneous multicore platforms such that the overall energy consumption of the system is minimised. To this end, we propose a two-phase approach that considers both dynamic and leakage energy consumption: (i) the first phase allocates tasks to the cores such that the dynamic energy consumption is reduced; (ii) the second phase refines the allocation performed in the first phase in order to achieve better sleep states by trading off the dynamic energy consumption with the reduction in leakage energy consumption. This hybrid approach considers core frequency set-points, tasks energy consumption and sleep states of the cores to reduce the energy consumption of the system. Major value has been placed on a realistic power model which increases the practical relevance of the proposed approach. Finally, extensive simulations have been carried out to demonstrate the effectiveness of the proposed algorithm. In the best-case, savings up to 18% of energy are reached over the first fit algorithm, which has shown, in previous works, to perform better than other bin-packing heuristics for the target heterogeneous multicore platform.

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An ever increasing need for extra functionality in a single embedded system demands for extra Input/Output (I/O) devices, which are usually connected externally and are expensive in terms of energy consumption. To reduce their energy consumption, these devices are equipped with power saving mechanisms. While I/O device scheduling for real-time (RT) systems with such power saving features has been studied in the past, the use of energy resources by these scheduling algorithms may be improved. Technology enhancements in the semiconductor industry have allowed the hardware vendors to reduce the device transition and energy overheads. The decrease in overhead of sleep transitions has opened new opportunities to further reduce the device energy consumption. In this research effort, we propose an intra-task device scheduling algorithm for real-time systems that wakes up a device on demand and reduces its active time while ensuring system schedulability. This intra-task device scheduling algorithm is extended for devices with multiple sleep states to further minimise the overall device energy consumption of the system. The proposed algorithms have less complexity when compared to the conservative inter-task device scheduling algorithms. The system model used relaxes some of the assumptions commonly made in the state-of-the-art that restrict their practical relevance. Apart from the aforementioned advantages, the proposed algorithms are shown to demonstrate the substantial energy savings.

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Coarse Grained Reconfigurable Architectures (CGRAs) are emerging as enabling platforms to meet the high performance demanded by modern applications (e.g. 4G, CDMA, etc.). Recently proposed CGRAs offer time-multiplexing and dynamic applications parallelism to enhance device utilization and reduce energy consumption at the cost of additional memory (up to 50% area of the overall platform). To reduce the memory overheads, novel CGRAs employ either statistical compression, intermediate compact representation, or multicasting. Each compaction technique has different properties (i.e. compression ratio, decompression time and decompression energy) and is best suited for a particular class of applications. However, existing research only deals with these methods separately. Moreover, they only analyze the compaction ratio and do not evaluate the associated energy overheads. To tackle these issues, we propose a polymorphic compression architecture that interleaves these techniques in a unique platform. The proposed architecture allows each application to take advantage of a separate compression/decompression hierarchy (consisting of various types and implementations of hardware/software decoders) tailored to its needs. Simulation results, using different applications (FFT, Matrix multiplication, and WLAN), reveal that the choice of compression hierarchy has a significant impact on compression ratio (up to 52%), decompression energy (up to 4 orders of magnitude), and configuration time (from 33 n to 1.5 s) for the tested applications. Synthesis results reveal that introducing adaptivity incurs negligible additional overheads (1%) compared to the overall platform area.

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Work in Progress Session, 21st IEEE Real-Time and Embedded Techonology and Applications Symposium (RTAS 2015). 13 to 16, Apr, 2015, pp 27-28. Seattle, U.S.A..

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23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2015). 4 to 6, Mar, 2015. Turku, Finland.

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Poster presented in Work in Progress Session, The 28th GI/ITG International Conference on Architecture of Computing Systems (ARCS 2015). 24 to 27, Mar, 2015. Porto, Portugal.