129 resultados para Intangible assets. Dynamic capabilities. Performance of tourist destinations


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The high thermal storage capacity of phase change material (PCM) can reduce energy consumption in buildings through energy storage and release when combined with renewable energy sources, night cooling, etc. PCM boards can be used to absorb heat gains during daytime and release heat at night. In this paper, the thermal performance of an environmental chamber fitted with phase change material boards has been investigated. During a full-cycle experiment, i.e. charging–releasing cycle, the PCM boards on a wall can reduce the interior wall surface temperature during the charging process, whereas the PCM wall surface temperature is higher than that of the other walls during the heat releasing process. It is found that the heat flux density of the PCM wall in the melting zone is almost twice as large as that of ordinary wall. Also, the heat-insulation performance of a PCM wall is better than that of an ordinary wall during the charging process, while during the heat discharging process, the PCM wall releases more heat energy. The convective heat transfer coefficient of PCM wall surface calculated using equations for a normal wall material produces an underestimation of this coefficient. The high convective heat transfer coefficient for a PCM wall is due to the increased energy exchange between the wall and indoor air.

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Since the first PFI hospital was established in 1994, many debates centred on the value for money and risk transfer in PFIs. Little concern is shown with PFI hospitals’ performance in delivering healthcare. Exploratory research was carried out to compare PFI with non‐PFI hospital performance. Five performance indicators were analysed to compare differences between PFI and non‐PFI hospitals, namely the length of waiting, the length of stay, MRSA infection rate, C difficile infection rate and patient experience. Data was collected from various government bodies. The results show that only some indexes measuring patient experience emerge statistically significant. This leads to a conclusion that PFI hospitals may not perform better than non‐PFI hospitals but they are not worse than non‐PFI hospitals in the delivery of services. However, future research needs to pay attention to reliability and validity of data sets currently available to undertake comparison.

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Four hull-less barley samples were milled on a Buhler MLU 202 laboratory mill and individual and combined milling fractions were characterized. The best milling performance was obtained when the samples were conditioned to 14.3% moisture. Yields were 37-48% for straight-run flour, 47-56% for shorts, and 5-8% for bran. The beta-glucan contents of the straight-run white flours were 1.6-2.1%, of which approximate to49% was water-extractable. The arabinoxylan contents were 1.2-1.5%, of which approximate to17% was water-extractable. Shorts and bran fractions contained more beta-glucan (4.2-5.8% and 3.0-4.7%, respectively) and arabinoxylan (6.1-7.7% and 8.1-11.8%, respectively) than the white flours. For those fractions, beta-glucan extractability was high (58.5 and 52.3%, respectively), whereas arabinoxylan extractability was very low (approximate to6.5 and 2.0%, respectively). The straight-run white flours had low alpha-amylase, beta-glucanase, and endoxylanase activities. The highest alpha-amylase activity was found in the shorts fractions and the highest beta-glucanase and endoxylanase activities were generally found in the bran fractions. Endoxylanase inhibitor activities were low in the white flours and highest in the shorts fractions. High flavanoid, tocopherol, and tocotrienol contents were found in bran and shorts fractions.

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This paper describes a region-based algorithm for deriving a concise description of a first order optical flow field. The algorithm described achieves performance improvements over existing algorithms without compromising the accuracy of the flow field values calculated. These improvements are brought about by not computing the entire flow field between two consecutive images, but by considering only the flow vectors of a selected subset of the images. The algorithm is presented in the context of a project to balance a bipedal robot using visual information.

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The performance benefit when using Grid systems comes from different strategies, among which partitioning the applications into parallel tasks is the most important. However, in most cases the enhancement coming from partitioning is smoothed by the effect of the synchronization overhead, mainly due to the high variability of completion times of the different tasks, which, in turn, is due to the large heterogeneity of Grid nodes. For this reason, it is important to have models which capture the performance of such systems. In this paper we describe a queueing-network-based performance model able to accurately analyze Grid architectures, and we use the model to study a real parallel application executed in a Grid. The proposed model improves the classical modelling techniques and highlights the impact of resource heterogeneity and network latency on the application performance.

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The performance benefit when using grid systems comes from different strategies, among which partitioning the applications into parallel tasks is the most important. However, in most cases the enhancement coming from partitioning is smoothed by the effects of synchronization overheads, mainly due to the high variability in the execution times of the different tasks, which, in turn, is accentuated by the large heterogeneity of grid nodes. In this paper we design hierarchical, queuing network performance models able to accurately analyze grid architectures and applications. Thanks to the model results, we introduce a new allocation policy based on a combination between task partitioning and task replication. The models are used to study two real applications and to evaluate the performance benefits obtained with allocation policies based on task replication.

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The aim of this paper is to study the impact of channel state information on the design of cooperative transmission protocols. This is motivated by the fact that the performance gain achieved by cooperative diversity comes at the price of the extra bandwidth resource consumption. Several opportunistic relaying strategies are developed to fully utilize the different types of a priori channel information. The analytical and numerical results demonstrate that the use of such a priori information increases the spectral efficiency of cooperative diversity, especially at low signal-to-noise ratio.

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The next generation consumer level interactive services require reliable and constant communication for both mobile and static users. The Digital Video Broadcasting ( DVB) group has exploited the rapidly increasing satellite technology for the provision of interactive services and launched a standard called Digital Video Broadcast through Return Channel Satellite (DYB-RCS). DVB-RCS relies on DVB-Satellite (DVB-S) for the provision of forward channel. The Digital Signal processing (DSP) implemented in the satellite channel adapter block of these standards use powerful channel coding and modulation techniques. The investigation is concentrated towards the Forward Error Correction (FEC) of the satellite channel adapter block, which will help in determining, how the technology copes with the varying channel conditions and user requirements(1).

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We agree with Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] and Quian Quiroga et al. [Phys. Rev. E 67, 063902 (2003)] that mutual information (MI) is a useful measure of dependence for electroencephalogram (EEG) data, but we show that the improvement seen in the performance of MI on extracting dependence trends from EEG is more dependent on the type of MI estimator rather than any embedding technique used. In an independent study we conducted in search for an optimal MI estimator, and in particular for EEG applications, we examined the performance of a number of MI estimators on the data set used by Quian Quiroga et al. in their original study, where the performance of different dependence measures on real data was investigated [Phys. Rev. E 65, 041903 (2002)]. We show that for EEG applications the best performance among the investigated estimators is achieved by k-nearest neighbors, which supports the conjecture by Quian Quiroga et al. in Phys. Rev. E 67, 063902 (2003) that the nearest neighbor estimator is the most precise method for estimating MI.

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We agree with Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] and Quian Quiroga [Phys. Rev. E 67, 063902 (2003)] that mutual information (MI) is a useful measure of dependence for electroencephalogram (EEG) data, but we show that the improvement seen in the performance of MI on extracting dependence trends from EEG is more dependent on the type of MI estimator rather than any embedding technique used. In an independent study we conducted in search for an optimal MI estimator, and in particular for EEG applications, we examined the performance of a number of MI estimators on the data set used by Quian Quiroga in their original study, where the performance of different dependence measures on real data was investigated [Phys. Rev. E 65, 041903 (2002)]. We show that for EEG applications the best performance among the investigated estimators is achieved by k-nearest neighbors, which supports the conjecture by Quian Quiroga in Phys. Rev. E 67, 063902 (2003) that the nearest neighbor estimator is the most precise method for estimating MI.

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Agri-environment schemes (AESs) have been implemented across EU member states in an attempt to reconcile agricultural production methods with protection of the environment and maintenance of the countryside. To determine the extent to which such policy objectives are being fulfilled, participating countries are obliged to monitor and evaluate the environmental, agricultural and socio-economic impacts of their AESs. However, few evaluations measure precise environmental outcomes and critically, there are no agreed methodologies to evaluate the benefits of particular agri-environmental measures, or to track the environmental consequences of changing agricultural practices. In response to these issues, the Agri-Environmental Footprint project developed a common methodology for assessing the environmental impact of European AES. The Agri-Environmental Footprint Index (AFI) is a farm-level, adaptable methodology that aggregates measurements of agri-environmental indicators based on Multi-Criteria Analysis (MCA) techniques. The method was developed specifically to allow assessment of differences in the environmental performance of farms according to participation in agri-environment schemes. The AFI methodology is constructed so that high values represent good environmental performance. This paper explores the use of the AFI methodology in combination with Farm Business Survey data collected in England for the Farm Accountancy Data Network (FADN), to test whether its use could be extended for the routine surveillance of environmental performance of farming systems using established data sources. Overall, the aim was to measure the environmental impact of three different types of agriculture (arable, lowland livestock and upland livestock) in England and to identify differences in AFI due to participation in agri-environment schemes. However, because farm size, farmer age, level of education and region are also likely to influence the environmental performance of a holding, these factors were also considered. Application of the methodology revealed that only arable holdings participating in agri-environment schemes had a greater environmental performance, although responses differed between regions. Of the other explanatory variables explored, the key factors determining the environmental performance for lowland livestock holdings were farm size, farmer age and level of education. In contrast, the AFI value of upland livestock holdings differed only between regions. The paper demonstrates that the AFI methodology can be used readily with English FADN data and therefore has the potential to be applied more widely to similar data sources routinely collected across the EU-27 in a standardised manner.