951 resultados para Robust Performance
Resumo:
Dedicated short range communications (DSRC) has been regarded as one of the most promising technologies to provide robust communications for large scale vehicle networks. It is designed to support both road safety and commercial applications. Road safety applications will require reliable and timely wireless communications. However, as the medium access control (MAC) layer of DSRC is based on the IEEE 802.11 distributed coordination function (DCF), it is well known that the random channel access based MAC cannot provide guaranteed quality of services (QoS). It is very important to understand the quantitative performance of DSRC, in order to make better decisions on its adoption, control, adaptation, and improvement. In this paper, we propose an analytic model to evaluate the DSRC-based inter-vehicle communication. We investigate the impacts of the channel access parameters associated with the different services including arbitration inter-frame space (AIFS) and contention window (CW). Based on the proposed model, we analyze the successful message delivery ratio and channel service delay for broadcast messages. The proposed analytical model can provide a convenient tool to evaluate the inter-vehicle safety applications and analyze the suitability of DSRC for road safety applications.
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We demonstrate that the transmission of 40 Gbits/s return-to-zero differential phase-shift keying (RZ-DPSK) signals is robust to lumped dispersion mapping on a typical installed terrestrial single-mode fiber/dispersion compensating fiber (SMF-DCF) link and will withstand, in this case, propagation through over 800 km of SMF with zero in-line group-velocity dispersion compensation while maintaining similar performance to configurations with periodic mapping. We establish that upgrading similar point-to-point links, which have lumped dispersion maps, are compatible with 40 Gbits/s RZ-DPSK and that economic benefits can be realized when implementing lumped dispersion mapping in new 40 Gbits/s RZ-DPSK terrestrial links, while incurring a relatively low performance penalty. (c) 2008 Optical Society of America.
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This paper analyses the relationship between production subsidies and firms’ export performance using a very comprehensive and recent firm-level database and controlling for the endogeneity of subsidies. It documents robust evidence that production subsidies stimulate export activity at the intensive margin, although this effect is conditional on firm characteristics. In particular, the positive relationship between subsidies and the intensive margin of exports is strongest among profit-making firms, firms in capital-intensive industries, and those located in non-coastal regions. Compared to firm characteristics, the extent of heterogeneity across ownership structure (SOEs, collectives, and privately owned firms) proves to be relatively less important.
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Using a unique firm level data, this paper analyses the role of political connections in the post-entry performance of private start-up companies in China. It documents robust evidence that political affiliation enhances firms' survival and growth prospects. But interestingly politically neutral start-ups enjoy faster productivity improvements conditional on survival. In addition, the benefits of political connections are largely confined to firms associated with local or top level governments, and they are more pronounced in capital-intensive industries. We conclude that the close association between the state and a segment of the business community is leading to sub-optimal resource allocation in the economy by interfering with the process of market selection.
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We use enterprise survey data to analyse and contrast the determinants of enterprise performance in China and Russia. We find that in China, enterprise growth and efficiency is associated with rapid increases in factor inputs, and with ownership to a lesser extent, but not greatly correlated with industry-specific or institutional factors. However, in Russia, enterprise growth is not associated with improvements in factor quantity (except for labor) or quality. The main determinants of company performance are instead demand and institutional factors at a regional level. The findings are robust across a variety of specifications.
Resumo:
- We conduct a Meta-analysis of 54 papers that study the relationship between multinationality and firm performance. The aim is to understand if any systematic relationships exist between the characteristics of each study and the reported results of linear and curvilinear regressions to examine the multinationality-performance relationship. - Our main finding, robust to different specifications and to different weights for each observation, is that when analysis is based on non-US data, the reported return to multinationality is higher. However, this relationship for non-US firms is usually U-shaped rather than inverted U-shaped. This indicates that US firms face lower returns to internationalization than other firms but are less likely to incur losses in the early stages of internationalization. - The findings also highlight the differences that are reported when comparing regression and non-regression based techniques. Our results suggest that in this area regression based analysis is more reliable than say ANOVA or other related approaches. - Other characteristics that influence the estimated rate of return and its shape across different studies are: the measure of multinationality used; size distribution of the sample; and the use of market-based indicators to measure firm performance. Finally, we find no evidence of publication bias.
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This paper proposes an integrative framework for the conduct of a more thorough and robust analysis regarding the linkage between Human Resource Management (HRM) and business performance. In order to provide the required basis for the proposed framework, initially, the core aspects of the main HRM models predicting business performance are analysed. The framework proposes both the principle of mediation (i.e. HRM outcomes mediate the relationship between organisational strategies and business performance) and the perspective of simultaneity of decision-making by firms with regard to the consideration of business strategies and HRM policies. In order to empirically test this framework the methodological approach of 'structural equation models' is employed. The empirical research is based on a sample of 178 organisations operating in the Greek manufacturing sector. The paper concludes that both the mediation principle and the simultaneity perspective are supported, emphasising further the positive role of HRM outcomes towards organisational performance.
Resumo:
This study examines the selectivity and timing performance of 218 UK investment trusts over the period July 1981 to June 2009. We estimate the Treynor and Mazuy (1966) and Henriksson and Merton (1981) models augmented with the size, value, and momentum factors, either under the OLS method adjusted with the Newey-West procedure or under the GARCH(1,1)-in-mean method following the specification of Glosten et al. (1993; hereafter GJR-GARCH-M). We find that the OLS method provides little evidence in favour of the selectivity and timing ability, consistent with previous studies. Interestingly, the GJR-GARCH-M method reverses this result, showing some relatively strong evidence on favourable selectivity ability, particularly for international funds, as well as favourable timing ability, particularly for domestic funds. We conclude that the GJR-GARCH-M method performs better in evaluating fund performance compared with the OLS method and the non-parametric approach, as it essentially accounts for the time-varying characteristics of factor loadings and hence obtains more reliable results, in particular, when the high frequency data, such as the daily returns, are used in the analysis. Our results are robust to various in-sample and out-of-sample tests and have valuable implications for practitioners in making their asset allocation decisions across different fund styles. © 2012 Elsevier B.V.
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A Eulerian-Eulerian CFD model was used to investigate the fast pyrolysis of biomass in a downer reactor equipped with a novel gas-solid separation mechanism. The highly endothermic pyrolysis reaction was assumed to be entirely driven by an inert solid heat carrier (sand). A one-step global pyrolysis reaction, along with the equations describing the biomass drying and heat transfer, was implemented in the hydrodynamic model presented in part I of this study (Fuel Processing Technology, V126, 366-382). The predictions of the gas-solid separation efficiency, temperature distribution, residence time and the pyrolysis product yield are presented and discussed. For the operating conditions considered, the devolatilisation efficiency was found to be above 60% and the yield composition in mass fraction was 56.85% bio-oil, 37.87% bio-char and 5.28% non-condensable gas (NCG). This has been found to agree reasonably well with recent relevant published experimental data. The novel gas-solid separation mechanism allowed achieving greater than 99.9% separation efficiency and < 2 s pyrolysis gas residence time. The model has been found to be robust and fast in terms of computational time, thus has the great potential to aid in future design and optimisation of the biomass fast pyrolysis process.
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This study investigates whether the completion of an optional sandwich work placement enhances student performance in final year examinations. Using Propensity Score Matching, our analysis departs from the literature by controlling for self-selection. Previous studies may have overestimated the impact of sandwich work placements on performance because it might be the case that high-calibre students choose to go on placement. Our results, utilising a large student data set, indicate that self-selection is present, but the effects of a placement on student performance still have an impact. This robust finding is found to be of a remarkably similar magnitude across two UK universities.
Resumo:
Data fluctuation in multiple measurements of Laser Induced Breakdown Spectroscopy (LIBS) greatly affects the accuracy of quantitative analysis. A new LIBS quantitative analysis method based on the Robust Least Squares Support Vector Machine (RLS-SVM) regression model is proposed. The usual way to enhance the analysis accuracy is to improve the quality and consistency of the emission signal, such as by averaging the spectral signals or spectrum standardization over a number of laser shots. The proposed method focuses more on how to enhance the robustness of the quantitative analysis regression model. The proposed RLS-SVM regression model originates from the Weighted Least Squares Support Vector Machine (WLS-SVM) but has an improved segmented weighting function and residual error calculation according to the statistical distribution of measured spectral data. Through the improved segmented weighting function, the information on the spectral data in the normal distribution will be retained in the regression model while the information on the outliers will be restrained or removed. Copper elemental concentration analysis experiments of 16 certified standard brass samples were carried out. The average value of relative standard deviation obtained from the RLS-SVM model was 3.06% and the root mean square error was 1.537%. The experimental results showed that the proposed method achieved better prediction accuracy and better modeling robustness compared with the quantitative analysis methods based on Partial Least Squares (PLS) regression, standard Support Vector Machine (SVM) and WLS-SVM. It was also demonstrated that the improved weighting function had better comprehensive performance in model robustness and convergence speed, compared with the four known weighting functions.
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Five axis machine tools are increasing and becoming more popular as customers demand more complex machined parts. In high value manufacturing, the importance of machine tools in producing high accuracy products is essential. High accuracy manufacturing requires producing parts in a repeatable manner and precision in compliance to the defined design specifications. The performance of the machine tools is often affected by geometrical errors due to a variety of causes including incorrect tool offsets, errors in the centres of rotation and thermal growth. As a consequence, it can be difficult to produce highly accurate parts consistently. It is, therefore, essential to ensure that machine tools are verified in terms of their geometric and positioning accuracy. When machine tools are verified in terms of their accuracy, the resulting numerical values of positional accuracy and process capability can be used to define design for verification rules and algorithms so that machined parts can be easily produced without scrap and little or no after process measurement. In this paper the benefits of machine tool verification are listed and a case study is used to demonstrate the implementation of robust machine tool performance measurement and diagnostics using a ballbar system.
Resumo:
One of the major drawbacks for mobile nodes in wireless networks is power management. Our goal is to evaluate the performance power control scheme to be used to reduce network congestion, improve quality of service and collision avoidance in vehicular network and road safety application. Some of the importance of power control (PC) are improving spatial reuse, and increasing network capacity in mobile wireless communications. In this simulation we have evaluated the performance of existing rate algorithms compared with context Aware Rate selection algorithm (ACARS) and also seen the performance of ACARS and how it can be applied to road safety, improve network control and power management. Result shows that ACARS is able to minimize the total transmit power in the presence of propagation processes and mobility of vehicles, by adapting to the fast varying channels conditions with the Path loss exponent values that was used for that environment which is shown in the network simulation parameter. Our results have shown that ACARS is a very robust algorithm which performs very well with the effect of propagation processes that is prone to every transmitted signal in mobile networks. © 2013 IEEE.
Resumo:
Based on a robust analysis of the existing literature on performance appraisal (PA), this paper makes a case for an integrated framework of effectiveness of performance appraisal (EPA). To achieve this, it draws on the expanded view of measurement criteria of EPA, i.e. purposefulness, fairness and accuracy, and identifies their relationships with ratee reactions. The analysis reveals that the expanded view of purposefulness includes more theoretical anchors for the purposes of PA and relates to various aspects of human resource functions, e.g. feedback and goal orientation. The expansion in the PA fairness criterion suggests certain newly established nomological networks, which were ignored in the past, e.g. the relationship between distributive fairness and organization-referenced outcomes. Further, refinements in PA accuracy reveal a more comprehensive categorization of rating biases. Coherence among measurement criteria has resulted in a ratee reactions-based integrated framework, which should be useful for both researchers and practitioners.
Resumo:
Undergraduates rated scripts describing the performance of different instructors in the following order: two positive or negative scripts followed by an average script; or two average scripts followed by a positive or a negative script. Context effects were assessed by comparing ratings of the target stimulus in the context and in the context-free control conditions. Several individual difference variables were measured as possible moderators of this phenomenon. Results indicated robust contrast effects mediated by beliefs in the variability of human nature in the extreme context conditions. In the positive context condition, high scorers in Variability were not affected by context, whereas medium or low scorers in Variability exhibited contrast effects. In the negative context condition, high scorers in Variability exhibited a more extreme contrast effect than medium or low scorers in Variability. In the average context conditions, contrast was observed only when the target was positive.