63 resultados para Application efficiency


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Measuring variations in efficiency and its extension, eco-efficiency, during a restructuring period in different industries has always been a point of interest for regulators and policy makers. This paper assesses the impacts of restructuring of procurement in the Iranian power industry on the performance of power plants. We introduce a new slacks-based model for Malmquist-Luenberger (ML) Index measurement and apply it to the power plants to calculate the efficiency, eco-efficiency, and technological changes over the 8-year period (2003-2010) of restructuring in the power industry. The results reveal that although the restructuring had different effects on the individual power plants, the overall growth in the eco-efficiency of the sector was mainly due to advances in pure technology. We also assess the correlation between efficiency and eco-efficiency of the power plants, which indicates a close relationship between these two steps, thus lending support to the incorporation of environmental factors in efficiency analysis. © 2014 Elsevier Ltd.

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We demonstrate a simple method to experimentally evaluate nonlinear transmission performance of high order modulation formats using a low number of channels and channel-like ASE. We verify it's behaviour is consistent with the AWGN model of transmission.

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In this paper we study the self-organising behaviour of smart camera networks which use market-based handover of object tracking responsibilities to achieve an efficient allocation of objects to cameras. Specifically, we compare previously known homogeneous configurations, when all cameras use the same marketing strategy, with heterogeneous configurations, when each camera makes use of its own, possibly different marketing strategy. Our first contribution is to establish that such heterogeneity of marketing strategies can lead to system wide outcomes which are Pareto superior when compared to those possible in homogeneous configurations. However, since the particular configuration required to lead to Pareto efficiency in a given scenario will not be known in advance, our second contribution is to show how online learning of marketing strategies at the individual camera level can lead to high performing heterogeneous configurations from the system point of view, extending the Pareto front when compared to the homogeneous case. Our third contribution is to show that in many cases, the dynamic behaviour resulting from online learning leads to global outcomes which extend the Pareto front even when compared to static heterogeneous configurations. Our evaluation considers results obtained from an open source simulation package as well as data from a network of real cameras. © 2013 IEEE.

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We demonstrate a high-efficiency random lasing in a 850 m span of a phosphosilicate fiber. Random distributed feedback owing to the Rayleigh backscattering in the fiber enables narrowband generation with output power of up to 7.3 W at the Stokes wavelength λS = 1308 nm from 11 Wof the pump power at λP = 1115 nm. The laser demonstrates unique generation efficiency. Near the generation threshold, more than 2 W of output power is generated from only 0.5 W of pump power excess over the generation threshold. At high pump power, the quantum conversion efficiency defined as a ratio of generated and pump photons at the laser output exceeds 100%. Itis explained by the fact that every pump photon is converted into the Stokes photon far from the output fiber end, while the Stokes photons have lower attenuation than the pump photons. © 2014 Astro Ltd.

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We demonstrate a random fiber laser of ultimate efficiency. More than 2 Watts are generated from 0.5W of pump excess over the generation threshold. At higher power, an optical efficiency corresponds to the quantum limit.

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Data envelopment analysis (DEA) is the most widely used methods for measuring the efficiency and productivity of decision-making units (DMUs). The need for huge computer resources in terms of memory and CPU time in DEA is inevitable for a large-scale data set, especially with negative measures. In recent years, wide ranges of studies have been conducted in the area of artificial neural network and DEA combined methods. In this study, a supervised feed-forward neural network is proposed to evaluate the efficiency and productivity of large-scale data sets with negative values in contrast to the corresponding DEA method. Results indicate that the proposed network has some computational advantages over the corresponding DEA models; therefore, it can be considered as a useful tool for measuring the efficiency of DMUs with (large-scale) negative data.

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In a pilot project an optimized mobile latent heat storage based on a system available on the market has been tested at Fraunhofer Institute for Environmental, Safety and Energy Technology. Initially trials were conducted with the aim of optimizing the process of charging and discharging. A specifically constructed test rig at the incineration trials centre at the institute allowed charging and discharging procedures of the mobile latent heat storage with adjustable parameters. In addition an evaluation model was constructed to further optimize the heat exchanger systems. In conclusion the prototype of the mobile latent heat storage was tested in practical operation. The economic and technical feasibility of heat transportation was shown if not utilized waste heat is available. © 2014 The Authors.

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The influence of IT investment on hospital efficiency and quality are of great interest to healthcare executives as well as insurers. Few studies have examined how IT investments influence both efficiency and quality or whether there is an optimal IT investment level that influences both in the desired direction. Decision makers in healthcare wonder if there are tradeoffs between their pursuit of hospital operational efficiency and quality. Our study involving a 2-stage double bootstrap DEA analysis of 187 US hospitals over 2. years found direct effects of IT investment upon service quality and a moderating effect of quality upon operational efficiency. Further, our findings indicate a U-shaped relationship between IT investments and operational efficiency suggesting that IT investments have diminishing returns beyond a certain point.

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Internal quantum efficiency (IQE) of a blue high-brightness InGaN/GaN light-emitting diode (LED) was evaluated from the external quantum efficiency measured as a function of current at various temperatures ranged between 13 and 440 K. Processing the data with a novel evaluation procedure based on the ABC-model, we have determined the temperature-dependent IQE of the LED structure and light extraction efficiency of the LED chip. Separate evaluation of these parameters is helpful for further optimization of the heterostructure and chip designs. The data obtained enable making a guess on the temperature dependence of the radiative and Auger recombination coefficients, which may be important for identification of dominant mechanisms responsible for the efficiency droop in III-nitride LEDs. Thermal degradation of the LED performance in terms of the emission efficiency is also considered.

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A hybrid passive-active damping solution with improved system stability margin and enhanced dynamic performance is proposed for high power grid interactive converters. In grid connected active rectifier/inverter application, line side LCL filter improves the high frequency attenuation and makes the converter compatible with the stringent grid power quality regulations. Passive damping though offers a simple and reliable solution but it reduces overall converter efficiency. Active damping solutions do not increase the system losses but can guarantee the stable operation up to a certain speed of dynamic response which is limited by the maximum bandwidth of the current controller. This paper examines this limit and introduces a concept of hybrid passive-active damping solution with improved stability margin and high dynamic performance for line side LCL filter based active rectifier/inverter applications. A detailed design, analysis of the hybrid approach and trade-off between system losses and dynamic performance in grid connected applications are reported. Simulation and experimental results from a 10 kVA prototype demonstrate the effectiveness of the proposed solution. An analytical study on system stability and dynamic response with the variations of various controller and passive filter parameters is presented.

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Queuing is one of the very important criteria for assessing the performance and efficiency of any service industry, including healthcare. Data Envelopment Analysis (DEA) is one of the most widely-used techniques for performance measurement in healthcare. However, no queue management application has been reported in the health-related DEA literature. Most of the studies regarding patient flow systems had the objective of improving an already existing Appointment System. The current study presents a novel application of DEA for assessing the queuing process at an Outpatients’ department of a large public hospital in a developing country where appointment systems do not exist. The main aim of the current study is to demonstrate the usefulness of DEA modelling in the evaluation of a queue system. The patient flow pathway considered for this study consists of two stages; consultation with a doctor and pharmacy. The DEA results indicated that waiting times and other related queuing variables included need considerable minimisation at both stages.

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Performance analysis has become a vital part of the management practices in the banking industry. There are numerous applications using DEA models to estimate efficiency in banking, and most of them assume that inputs and outputs are known with absolute precision. Here, we propose new Fuzzy-DEA α-level models to assess underlying uncertainty. Further, bootstrap truncated regressions with fixed factors are used to measure the impact of each model on the efficiency scores and to identify the most relevant contextual variables on efficiency. The proposed models have been demonstrated using an application in Mozambican banks to handle the underlying uncertainty. Findings reveal that fuzziness is predominant over randomness in interpreting the results. In addition, fuzziness can be used by decision-makers to identify missing variables to help in interpreting the results. Price of labor, price of capital, and market-share were found to be the significant factors in measuring bank efficiency. Managerial implications are addressed.

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Data Envelopment Analysis (DEA) is a powerful analytical technique for measuring the relative efficiency of alternatives based on their inputs and outputs. The alternatives can be in the form of countries who attempt to enhance their productivity and environmental efficiencies concurrently. However, when desirable outputs such as productivity increases, undesirable outputs increase as well (e.g. carbon emissions), thus making the performance evaluation questionable. In addition, traditional environmental efficiency has been typically measured by crisp input and output (desirable and undesirable). However, the input and output data, such as CO2 emissions, in real-world evaluation problems are often imprecise or ambiguous. This paper proposes a DEA-based framework where the input and output data are characterized by symmetrical and asymmetrical fuzzy numbers. The proposed method allows the environmental evaluation to be assessed at different levels of certainty. The validity of the proposed model has been tested and its usefulness is illustrated using two numerical examples. An application of energy efficiency among 23 European Union (EU) member countries is further presented to show the applicability and efficacy of the proposed approach under asymmetric fuzzy numbers.

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The utilization of solar energy by photovoltaic (PV) systems have received much research and development (R&D) attention across the globe. In the past decades, a large number of PV array have been installed. Since the installed PV arrays often operate in harsh environments, non-uniform aging can occur and impact adversely on the performance of PV systems, especially in the middle and late periods of their service life. Due to the high cost of replacing aged PV modules by new modules, it is appealing to improve energy efficiency of aged PV systems. For this purpose, this paper presents a PV module reconfiguration strategy to achieve the maximum power generation from non-uniformly aged PV arrays without significant investment. The proposed reconfiguration strategy is based on the cell-unit structure of PV modules, the operating voltage limit of gird-connected converter, and the resulted bucket-effect of the maximum short circuit current. The objectives are to analyze all the potential reorganization options of the PV modules, find the maximum power point and express it in a proposition. This proposition is further developed into a novel implementable algorithm to calculate the maximum power generation and the corresponding reconfiguration of the PV modules. The immediate benefits from this reconfiguration are the increased total power output and maximum power point voltage information for global maximum power point tracking (MPPT). A PV array simulation model is used to illustrate the proposed method under three different cases. Furthermore, an experimental rig is built to verify the effectiveness of the proposed method. The proposed method will open an effective approach for condition-based maintenance of emerging aging PV arrays.

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This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array.