51 resultados para analysis of performance


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A significant challenge in the prediction of climate change impacts on ecosystems and biodiversity is quantifying the sources of uncertainty that emerge within and between different models. Statistical species niche models have grown in popularity, yet no single best technique has been identified reflecting differing performance in different situations. Our aim was to quantify uncertainties associated with the application of 2 complimentary modelling techniques. Generalised linear mixed models (GLMM) and generalised additive mixed models (GAMM) were used to model the realised niche of ombrotrophic Sphagnum species in British peatlands. These models were then used to predict changes in Sphagnum cover between 2020 and 2050 based on projections of climate change and atmospheric deposition of nitrogen and sulphur. Over 90% of the variation in the GLMM predictions was due to niche model parameter uncertainty, dropping to 14% for the GAMM. After having covaried out other factors, average variation in predicted values of Sphagnum cover across UK peatlands was the next largest source of variation (8% for the GLMM and 86% for the GAMM). The better performance of the GAMM needs to be weighed against its tendency to overfit the training data. While our niche models are only a first approximation, we used them to undertake a preliminary evaluation of the relative importance of climate change and nitrogen and sulphur deposition and the geographic locations of the largest expected changes in Sphagnum cover. Predicted changes in cover were all small (generally <1% in an average 4 m2 unit area) but also highly uncertain. Peatlands expected to be most affected by climate change in combination with atmospheric pollution were Dartmoor, Brecon Beacons and the western Lake District.

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Decision theory is the study of models of judgement involved in, and leading to, deliberate and (usually) rational choice. In real estate investment there are normative models for the allocation of assets. These asset allocation models suggest an optimum allocation between the respective asset classes based on the investors’ judgements of performance and risk. Real estate is selected, as other assets, on the basis of some criteria, e.g. commonly its marginal contribution to the production of a mean variance efficient multi asset portfolio, subject to the investor’s objectives and capital rationing constraints. However, decisions are made relative to current expectations and current business constraints. Whilst a decision maker may believe in the required optimum exposure levels as dictated by an asset allocation model, the final decision may/will be influenced by factors outside the parameters of the mathematical model. This paper discusses investors' perceptions and attitudes toward real estate and highlights the important difference between theoretical exposure levels and pragmatic business considerations. It develops a model to identify “soft” parameters in decision making which will influence the optimal allocation for that asset class. This “soft” information may relate to behavioural issues such as the tendency to mirror competitors; a desire to meet weight of money objectives; a desire to retain the status quo and many other non-financial considerations. The paper aims to establish the place of property in multi asset portfolios in the UK and examine the asset allocation process in practice, with a view to understanding the decision making process and to look at investors’ perceptions based on an historic analysis of market expectation; a comparison with historic data and an analysis of actual performance.

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European economic and political integration have been recognised as having implications for patterns of performance in national real estate and capital markets and have generated a wide body of research and commentary. In 1999, progress towards monetary integration within the European Union culminated in the introduction of a common currency and monetary policy. This paper investigates the effects of this ‘event’ on the behaviour of stock returns in European real estate companies. A range of statistical tests is applied to the performance of European property companies to test for changes in segmentation, co-movement and causality. The results suggest that, relative to the wider equity markets, the dispersion of performance is higher, correlations are lower, a common contemporaneous factor has much lower explanatory power whilst lead-lag relationships are stronger. Consequently, the evidence of transmission of monetary integration to real estate securities is less noticeable than to general securities. Less and slower integration is attributed to the relatively small size of the real estate securities market and the local and national nature of the majority of the companies’ portfolios.

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Following earlier work looking at overall career difficulties and low economic rewards faced by graduates in creative disciplines, the paper takes a closer look into the different career patterns and economic performance of “Bohemian” graduates across different creative disciplines. While it is widely acknowledged in the literature that careers in the creative field tend to be unstructured, often relying on part-time work and low wages, our knowledge of how these characteristics differ across the creative industries and occupational sectors is very limited. The paper explores the different trajectory and career patterns experienced by graduates in different creative disciplinary fields and their ability to enter creative occupations. Data from the Higher Education Statistical Agency (HESA) are presented, articulating a complex picture of the reality of finding a creative occupation for creative graduates. While students of some disciplines struggle to find full-time work in the creative economy, for others full-time occupation is the norm. Geography plays a crucial role also in offering graduates opportunities in creative occupations and higher salaries. The findings are contextualised in the New Labour cultural policy framework and conclusions are drawn on whether the creative industries policy construct has hidden a very problematic reality of winners and losers in the creative economy.

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To fully appreciate the environmental impact of a workplace the transport-related carbon dioxide (CO2) emissions resulting from its location should be considered in addition to the emissions that result from the occupation of the building itself. Since the first one was built in the early 1980s, business parks have become a significant workplace location for service-sector workers; a sector of the economy that grew rapidly at that time as the UK manufacturing output declined and the employment base shifted to retail services and de-regulated financial services. This paper examines the transport-related CO2 emissions associated with these workplace locations in comparison to town and city centre locations. Using 2001 Census Special Workplace Statistics which record people’s residence, usual workplace and mode of transport between them, distance travelled and mode of travel were calculated for a sample of city centre and out-of-town office locations. The results reveal the extent of the difference between transport-related CO2 emitted by commuters to out-of-town and city centre locations. The implications that these findings have for monitoring the environmental performance of workplaces are discussed.

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This paper aims to clarify the potential confusion about the application of attribution analysis to real estate portfolios. Its three primary objectives are: · To review, and as far as possible reconcile, the varying approaches to attribution analysis evident in the literature. · To give a clear statement of the purposes of attribution analysis, and its meaning for real-world property managers. · To show, using real portfolio data from IPD's UK performance measurement service, the practical implications of applying different attribution methods.

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Aircraft systems are highly nonlinear and time varying. High-performance aircraft at high angles of incidence experience undesired coupling of the lateral and longitudinal variables, resulting in departure from normal controlled � ight. The construction of a robust closed-loop control that extends the stable and decoupled � ight envelope as far as possible is pursued. For the study of these systems, nonlinear analysis methods are needed. Previously, bifurcation techniques have been used mainly to analyze open-loop nonlinear aircraft models and to investigate control effects on dynamic behavior. Linear feedback control designs constructed by eigenstructure assignment methods at a � xed � ight condition are investigated for a simple nonlinear aircraft model. Bifurcation analysis, in conjunction with linear control design methods, is shown to aid control law design for the nonlinear system.

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Automatic keyword or keyphrase extraction is concerned with assigning keyphrases to documents based on words from within the document. Previous studies have shown that in a significant number of cases author-supplied keywords are not appropriate for the document to which they are attached. This can either be because they represent what the author believes a paper is about not what it actually is, or because they include keyphrases which are more classificatory than explanatory e.g., “University of Poppleton” instead of “Knowledge Discovery in Databases”. Thus, there is a need for a system that can generate an appropriate and diverse range of keyphrases that reflect the document. This paper proposes two possible solutions that examine the synonyms of words and phrases in the document to find the underlying themes, and presents these as appropriate keyphrases. Using three different freely available thesauri, the work undertaken examines two different methods of producing keywords and compares the outcomes across multiple strands in the timeline. The primary method explores taking n-grams of the source document phrases, and examining the synonyms of these, while the secondary considers grouping outputs by their synonyms. The experiments undertaken show the primary method produces good results and that the secondary method produces both good results and potential for future work. In addition, the different qualities of the thesauri are examined and it is concluded that the more entries in a thesaurus, the better it is likely to perform. The age of the thesaurus or the size of each entry does not correlate to performance.

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Leptospira have a worldwide distribution and include important zoonotic pathogens yet diagnosis and differentiation still tend to rely on traditional bacteriological and serological approaches. In this study a 1.3 kb fragment of the rrs gene (16S rDNA) was sequenced from a panel of 22 control strains, representing serovars within the pathogenic species Leptospira interrogans, Leptospira borgpetersenii, and Leptospira kirschneri, to identify single nucleotide polymorphisms (SNPs). These were identified in the 5' variable region of the 16S sequence and a 181 bp PCR fragment encompassing this region was used for speciation by Denaturing High Performance Liquid Chromatography (D-HPLC). This method was applied to eleven additional species, representing pathogenic, non-pathogenic and intermediate species and was demonstrated to rapidly differentiate all but 2 of the non-pathogenic Leptospira species. The method was applied successfully to infected tissues from field samples proving its value for diagnosing leptospiral infections found in animals in the UK. Crown Copyright (C) 2010 Published by Elsevier Ltd. All rights reserved.

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The behavior of the ensemble Kalman filter (EnKF) is examined in the context of a model that exhibits a nonlinear chaotic (slow) vortical mode coupled to a linear (fast) gravity wave of a given amplitude and frequency. It is shown that accurate recovery of both modes is enhanced when covariances between fast and slow normal-mode variables (which reflect the slaving relations inherent in balanced dynamics) are modeled correctly. More ensemble members are needed to recover the fast, linear gravity wave than the slow, vortical motion. Although the EnKF tends to diverge in the analysis of the gravity wave, the filter divergence is stable and does not lead to a great loss of accuracy. Consequently, provided the ensemble is large enough and observations are made that reflect both time scales, the EnKF is able to recover both time scales more accurately than optimal interpolation (OI), which uses a static error covariance matrix. For OI it is also found to be problematic to observe the state at a frequency that is a subharmonic of the gravity wave frequency, a problem that is in part overcome by the EnKF.However, error in themodeled gravity wave parameters can be detrimental to the performance of the EnKF and remove its implied advantages, suggesting that a modified algorithm or a method for accounting for model error is needed.

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Construction professional services (CPSs), such as architecture, engineering, and consultancy, are not only high value-added profit centers in their own right but also have a knock-on effect on other businesses, such as construction and the export of materials and machinery. Arguably, competition in the international construction market has shifted to these knowledge-intensive CPS areas. Yet CPSs represent a research frontier that has received scant attention. This research aims to enrich the body of knowledge on CPSs by examining strengths, weaknesses, opportunities, and threats (SWOT) of Chinese CPSs (CCPSs) in the international context. It does so by triangulating theories with quantitative and qualitative data gleaned from yearbooks, annual reports, interviews, seminars, and interactions with managers in major CCPS companies. It is found that CCPSs present both strengths and weaknesses in talents, administration systems, and development strategies in dealing with the external opportunities and threats brought about by globalization and market evolution. Low price, which has helped the Chinese construction business to succeed in the international market, is also a major CCPS strength. An opportunity for CCPSs is the relatively strong delivery capability possessed by Chinese contractors; by partnering with them CCPSs can better establish themselves in the international arena. This is probably the first ever comprehensive study on the performance of CCPSs in the international marketplace. The research is conducted at an opportune time, particularly when the world is witnessing the burgeoning force of Chinese businesses in many areas including manufacturing, construction, and, potentially, professional services. It adds new insights to the knowledge body of CPSs and provides valuable references to other countries faced with the challenge of developing CPS business efficiently in the international market.

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Mobile-to-mobile (M-to-M) communications are expected to play a crucial role in future wireless systems and networks. In this paper, we consider M-to-M multiple-input multiple-output (MIMO) maximal ratio combining system and assess its performance in spatially correlated channels. The analysis assumes double-correlated Rayleigh-and-Lognormal fading channels and is performed in terms of average symbol error probability, outage probability, and ergodic capacity. To obtain the receive and transmit spatial correlation functions needed for the performance analysis, we used a three-dimensional (3D) M-to-M MIMO channel model, which takes into account the effects of fast fading and shadowing. The expressions for the considered metrics are derived as a function of the average signal-to-noise ratio per receive antenna in closed-form and are further approximated using the recursive adaptive Simpson quadrature method. Numerical results are provided to show the effects of system parameters, such as distance between antenna elements, maximum elevation angle of scatterers, orientation angle of antenna array in the x–y plane, angle between the x–y plane and the antenna array orientation, and degree of scattering in the x–y plane, on the system performance. Copyright © 2011 John Wiley & Sons, Ltd.

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In contrast to their bustling construction counterparts, Chinese construction professional services (CPS) such as architecture, engineering, and consultancy, seem still to be stagnant in the international market. CPS are not only high value-added profit centers in their own right, but also have a knock-on effect on subsequent businesses such as construction, and the export of materials and machinery. Arguably, competition in the international construction market has shifted to knowledge-intensive CPS. Yet,CPS represent a research area that has been paid scant attention. This research aims to add to the body of knowledge of CPS by examining strengths, weaknesses, opportunities, and threats (SWOT) of Chinese CPS (CCPS) in the international context. It does so by triangulating theories with quantitative and qualitative data gleaned from yearbooks, annual reports, interviews, seminars, and interactions with managers in major CCPS companies. It is found that CCPS present both strengths and weaknesses in talents, administration systems, and development strategies in dealing with the external opportunities and threats brought about by globalization and market evolvement. Low price, which has helped the Chinese construction business to succeed in the international market, is also a CCPS major strength. An opportunity for CCPS is the relatively strong delivery capability possessed by Chinese contractors. By partnering with them CCPS can better edge into the international arena. This is probably the first ever comprehensive study in investigating the performance of CCPS in the international market. The research is also timely, particularly when the world is witnessing the burgeoning force of Chinese businesses in many areas including manufacturing, construction, and potentially, professional services.

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In this paper we consider the structure of dynamically evolving networks modelling information and activity moving across a large set of vertices. We adopt the communicability concept that generalizes that of centrality which is defined for static networks. We define the primary network structure within the whole as comprising of the most influential vertices (both as senders and receivers of dynamically sequenced activity). We present a methodology based on successive vertex knockouts, up to a very small fraction of the whole primary network,that can characterize the nature of the primary network as being either relatively robust and lattice-like (with redundancies built in) or relatively fragile and tree-like (with sensitivities and few redundancies). We apply these ideas to the analysis of evolving networks derived from fMRI scans of resting human brains. We show that the estimation of performance parameters via the structure tests of the corresponding primary networks is subject to less variability than that observed across a very large population of such scans. Hence the differences within the population are significant.

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A number of urban land-surface models have been developed in recent years to satisfy the growing requirements for urban weather and climate interactions and prediction. These models vary considerably in their complexity and the processes that they represent. Although the models have been evaluated, the observational datasets have typically been of short duration and so are not suitable to assess the performance over the seasonal cycle. The First International Urban Land-Surface Model comparison used an observational dataset that spanned a period greater than a year, which enables an analysis over the seasonal cycle, whilst the variety of models that took part in the comparison allows the analysis to include a full range of model complexity. The results show that, in general, urban models do capture the seasonal cycle for each of the surface fluxes, but have larger errors in the summer months than in the winter. The net all-wave radiation has the smallest errors at all times of the year but with a negative bias. The latent heat flux and the net storage heat flux are also underestimated, whereas the sensible heat flux generally has a positive bias throughout the seasonal cycle. A representation of vegetation is a necessary, but not sufficient, condition for modelling the latent heat flux and associated sensible heat flux at all times of the year. Models that include a temporal variation in anthropogenic heat flux show some increased skill in the sensible heat flux at night during the winter, although their daytime values are consistently overestimated at all times of the year. Models that use the net all-wave radiation to determine the net storage heat flux have the best agreement with observed values of this flux during the daytime in summer, but perform worse during the winter months. The latter could result from a bias of summer periods in the observational datasets used to derive the relations with net all-wave radiation. Apart from these models, all of the other model categories considered in the analysis result in a mean net storage heat flux that is close to zero throughout the seasonal cycle, which is not seen in the observations. Models with a simple treatment of the physical processes generally perform at least as well as models with greater complexity.