96 resultados para land evaluate system


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Purpose – To evaluate the control strategy for a hybrid natural ventilation wind catchers and air-conditioning system and to assess the contribution of wind catchers to indoor air environments and energy savings if any. Design/methodology/approach – Most of the modeling techniques for assessing wind catchers performance are theoretical. Post-occupancy evaluation studies of buildings will provide an insight into the operation of these building components and help to inform facilities managers. A case study for POE was presented in this paper. Findings – The monitoring of the summer and winter month operations showed that the indoor air quality parameters were kept within the design target range. The design control strategy failed to record data regarding the operation, opening time and position of wind catchers system. Though the implemented control strategy was working effectively in monitoring the operation of mechanical ventilation systems, i.e. AHU, did not integrate the wind catchers with the mechanical ventilation system. Research limitations/implications – Owing to short-falls in the control strategy implemented in this project, it was found difficult to quantify and verify the contribution of the wind catchers to the internal conditions and, hence, energy savings. Practical implications – Controlling the operation of the wind catchers via the AHU will lead to isolation of the wind catchers in the event of malfunctioning of the AHU. Wind catchers will contribute to the ventilation of space, particularly in the summer months. Originality/value – This paper demonstrates the value of POE as indispensable tool for FM professionals. It further provides insight into the application of natural ventilation systems in building for healthier indoor environments at lower energy cost. The design of the control strategy for natural ventilation and air-conditioning should be considered at the design stage involving the FM personnel.

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Physiological parameters measured by an embedded body sensor system were demonstrated to respond to changes of the air temperature in an office environment. The thermal parameters were monitored with the use of a wireless sensor system that made possible to turn any existing room into a field laboratory. Two human subjects were monitored over daily activities and at various steady-state thermal conditions when the air temperature of the room was altered from 22-23°C to 25-28°C. The subjects indicated their thermal feeling on questionnaires. The measured skin temperature was distributed close to the calculated mean skin temperature corresponding to the given activity level. The variation of Galvanic Skin Response (GSR) reflected the evaporative heat loss through the body surfaces and indicated whether sweating occurred on the subjects. Further investigations are needed to fully evaluate the influence of thermal and other factors on the output given by the investigated body sensor system.

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Uncertainty contributes a major part in the accuracy of a decision-making process while its inconsistency is always difficult to be solved by existing decision-making tools. Entropy has been proved to be useful to evaluate the inconsistency of uncertainty among different respondents. The study demonstrates an entropy-based financial decision support system called e-FDSS. This integrated system provides decision support to evaluate attributes (funding options and multiple risks) available in projects. Fuzzy logic theory is included in the system to deal with the qualitative aspect of these options and risks. An adaptive genetic algorithm (AGA) is also employed to solve the decision algorithm in the system in order to provide optimal and consistent rates to these attributes. Seven simplified and parallel projects from a Hong Kong construction small and medium enterprise (SME) were assessed to evaluate the system. The result shows that the system calculates risk adjusted discount rates (RADR) of projects in an objective way. These rates discount project cash flow impartially. Inconsistency of uncertainty is also successfully evaluated by the use of the entropy method. Finally, the system identifies the favourable funding options that are managed by a scheme called SME Loan Guarantee Scheme (SGS). Based on these results, resource allocation could then be optimized and the best time to start a new project could also be identified throughout the overall project life cycle.

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Objective: To evaluate the effect of robot-mediated therapy on arm dysfunction post stroke. Design: A series of single-case studies using a randomized multiple baseline design with ABC or ACB order. Subjects (n = 20) had a baseline length of 8, 9 or 10 data points. They continued measurement during the B - robot-mediated therapy and C - sling suspension phases. Setting: Physiotherapy department, teaching hospital. Subjects: Twenty subjects with varying degrees of motor and sensory deficit completed the study. Subjects attended three times a week, with each phase lasting three weeks. Interventions: In the robot-mediated therapy phase they practised three functional exercises with haptic and visual feedback from the system. In the sling suspension phase they practised three single-plane exercises. Each treatment phase was three weeks long. Main measures: The range of active shoulder flexion, the Fugl-Meyer motor assessment and the Motor Assessment Scale were measured at each visit. Results: Each subject had a varied response to the measurement and intervention phases. The rate of recovery was greater during the robot-mediated therapy phase than in the baseline phase for the majority of subjects. The rate of recovery during the robot-mediated therapy phase was also greater than that during the sling suspension phase for most subjects. Conclusion: The positive treatment effect for both groups suggests that robot-mediated therapy can have a treatment effect greater than the same duration of non-functional exercises. Further studies investigating the optimal duration of treatment in the form of a randomized controlled trial are warranted.

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Background: This study was carried out as part of a European Union funded project (PharmDIS-e+), to develop and evaluate software aimed at assisting physicians with drug dosing. A drug that causes particular problems with drug dosing in primary care is digoxin because of its narrow therapeutic range and low therapeutic index. Objectives: To determine (i) accuracy of the PharmDIS-e+ software for predicting serum digoxin levels in patients who are taking this drug regularly; (ii) whether there are statistically significant differences between predicted digoxin levels and those measured by a laboratory and (iii) whether there are differences between doses prescribed by general practitioners and those suggested by the program. Methods: We needed 45 patients to have 95% Power to reject the null hypothesis that the mean serum digoxin concentration was within 10% of the mean predicted digoxin concentration. Patients were recruited from two general practices and had been taking digoxin for at least 4 months. Exclusion criteria were dementia, low adherence to digoxin and use of other medications known to interact to a clinically important extent with digoxin. Results: Forty-five patients were recruited. There was a correlation of 0·65 between measured and predicted digoxin concentrations (P < 0·001). The mean difference was 0·12 μg/L (SD 0·26; 95% CI 0·04, 0·19, P = 0·005). Forty-seven per cent of the patients were prescribed the same dose as recommended by the software, 44% were prescribed a higher dose and 9% a lower dose than recommended. Conclusion: PharmDIS-e+ software was able to predict serum digoxin levels with acceptable accuracy in most patients.

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The lithic record from the Solent River and its tributaries is re-examined in the light of recent interpretations about the changing demography of Britain during the Lower and early Middle Palaeolithic. Existing models of the terrace stratigraphies in the Solent and its tributary areas are reviewed and the corresponding archaeological record (specifically handaxes) for each terrace is assessed to provide models for the relative changes in human occupation through time. The Bournemouth area is studied in detail to examine the effects of quarrying and urbanisation on collection history and on the biases it introduces to the record. In addition, the effects of reworking of artefacts from higher into lower terraces are assessed, and shown to be a significant problem. Although there is very little absolute dating available for the Solent area, a cautious interpretation of the results from these analyses would suggest a pre-Marine Isotope Stage (MIS) 12 date for the first appearance of humans, a peak in population between MIS 12 and 10, and a decline in population during MIS 9 and 8. Owing to poor contextual data and small sample sizes, it is not clear when Levallois technology was introduced. This record is compared and contrasted to that from the Thames Valley. It is suggested that changes in the palaeogeography of Britain, in particular land connections to the continent, might have contributed to differences in the archaeological records from the Solent and Thames regions.

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Airborne LIght Detection And Ranging (LIDAR) provides accurate height information for objects on the earth, which makes LIDAR become more and more popular in terrain and land surveying. In particular, LIDAR data offer vital and significant features for land-cover classification which is an important task in many application domains. In this paper, an unsupervised approach based on an improved fuzzy Markov random field (FMRF) model is developed, by which the LIDAR data, its co-registered images acquired by optical sensors, i.e. aerial color image and near infrared image, and other derived features are fused effectively to improve the ability of the LIDAR system for the accurate land-cover classification. In the proposed FMRF model-based approach, the spatial contextual information is applied by modeling the image as a Markov random field (MRF), with which the fuzzy logic is introduced simultaneously to reduce the errors caused by the hard classification. Moreover, a Lagrange-Multiplier (LM) algorithm is employed to calculate a maximum A posteriori (MAP) estimate for the classification. The experimental results have proved that fusing the height data and optical images is particularly suited for the land-cover classification. The proposed approach works very well for the classification from airborne LIDAR data fused with its coregistered optical images and the average accuracy is improved to 88.9%.

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The method of entropy has been useful in evaluating inconsistency on human judgments. This paper illustrates an entropy-based decision support system called e-FDSS to the solution of multicriterion risk and decision analysis in projects of construction small and medium enterprises (SMEs). It is optimized and solved by fuzzy logic, entropy, and genetic algorithms. A case study demonstrated the use of entropy in e-FDSS on analyzing multiple risk criteria in the predevelopment stage of SME projects. Survey data studying the degree of impact of selected project risk criteria on different projects were input into the system in order to evaluate the preidentified project risks in an impartial environment. Without taking into account the amount of uncertainty embedded in the evaluation process; the results showed that all decision vectors are indeed full of bias and the deviations of decisions are finally quantified providing a more objective decision and risk assessment profile to the stakeholders of projects in order to search and screen the most profitable projects.

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This paper will present a conceptual framework for the examination of land redevelopment based on a complex systems/networks approach. As Alvin Toffler insightfully noted, modern scientific enquiry has become exceptionally good at splitting problems into pieces but has forgotten how to put the pieces back together. Twenty-five years after his remarks, governments and corporations faced with the requirements of sustainability are struggling to promote an ‘integrated’ or ‘holistic’ approach to tackling problems. Despite the talk, both practice and research provide few platforms that allow for ‘joined up’ thinking and action. With socio-economic phenomena, such as land redevelopment, promising prospects open up when we assume that their constituents can make up complex systems whose emergent properties are more than the sum of the parts and whose behaviour is inherently difficult to predict. A review of previous research shows that it has mainly focused on idealised, ‘mechanical’ views of property development processes that fail to recognise in full the relationships between actors, the structures created and their emergent qualities. When reality failed to live up to the expectations of these theoretical constructs then somebody had to be blamed for it: planners, developers, politicians. However, from a ‘synthetic’ point of view the agents and networks involved in property development can be seen as constituents of structures that perform complex processes. These structures interact, forming new more complex structures and networks. Redevelopment then can be conceptualised as a process of transformation: a complex system, a ‘dissipative’ structure involving developers, planners, landowners, state agencies etc., unlocks the potential of previously used sites, transforms space towards a higher order of complexity and ‘consumes’ but also ‘creates’ different forms of capital in the process. Analysis of network relations point toward the ‘dualism’ of structure and agency in these processes of system transformation and change. Insights from actor network theory can be conjoined with notions of complexity and chaos to build an understanding of the ways in which actors actively seek to shape these structures and systems, whilst at the same time are recursively shaped by them in their strategies and actions. This approach transcends the blame game and allows for inter-disciplinary inputs to be placed within a broader explanatory framework that does away with many past dichotomies. Better understanding of the interactions between actors and the emergent qualities of the networks they form can improve our comprehension of the complex socio-spatial phenomena that redevelopment comprises. The insights that this framework provides when applied in UK institutional investment into redevelopment are considered to be significant.

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Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface‐subsurface interactions due to fine‐scale topography and vegetation; improved representation of land‐atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

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The initial condition effect on climate prediction skill over a 2-year hindcast time-scale has been assessed from ensemble HadCM3 climate model runs using anomaly initialization over the period 1990–2001, and making comparisons with runs without initialization (equivalent to climatological conditions), and to anomaly persistence. It is shown that the assimilation improves the prediction skill in the first year globally, and in a number of limited areas out into the second year. Skill in hindcasting surface air temperature anomalies is most marked over ocean areas, and is coincident with areas of high sea surface temperature and ocean heat content skill. Skill improvement over land areas is much more limited but is still detectable in some cases. We found little difference in the skill of hindcasts using three different sets of ocean initial conditions, and we obtained the best results by combining these to form a grand ensemble hindcast set. Results are also compared with the idealized predictability studies of Collins (Clim. Dynam. 2002; 19: 671–692), which used the same model. The maximum lead time for which initialization gives enhanced skill over runs without initialization varies in different regions but is very similar to lead times found in the idealized studies, therefore strongly supporting the process representation in the model as well as its use for operational predictions. The limited 12-year period of the study, however, means that the regional details of model skill should probably be further assessed under a wider range of observational conditions.

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The increasing demand for ecosystem services, in conjunction with climate change, is expected to signif- icantly alter terrestrial ecosystems. In order to evaluate the sustainability of land and water resources, there is a need for a better understanding of the relationships between crop production, land surface characteristics and the energy and water cycles. These relationships are analysed using the Joint UK Land Environment Simulator (JULES). JULES includes the full hydrological cycle and vegetation effects on the energy, water, and carbon fluxes. However, this model currently only simulates land surface processes in natural ecosystems. An adapted version of JULES for agricultural ecosystems, called JULES-SUCROS has therefore been developed. In addition to overall model improvements, JULES-SUCROS includes a dynamic crop growth structure that fully fits within and builds upon the biogeochemical modelling framework for natural vegetation. Specific agro-ecosystem features such as the development of yield-bearing organs and the phenological cycle from sowing till harvest have been included in the model. This paper describes the structure of JULES-SUCROS and evaluates the fluxes simulated with this model against FLUXNET measurements at 6 European sites. We show that JULES-SUCROS significantly improves the correlation between simulated and observed fluxes over cropland and captures well the spatial and temporal vari- ability of the growth conditions in Europe. Simulations with JULES-SUCROS highlight the importance of vegetation structure and phenology, and the impact they have on land–atmosphere interactions.

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In 2003 the European Commission started using Impact Assessment (IA) as the main empirical basis for its major policy proposals. The aim was to systematically assess ex ante the economic, social and environmental impacts of EU policy proposals. In parallel, research proliferated in search for theoretical grounds for IAs and in an attempt to evaluate empirically the performance of the first sets of IAs produced by the European Commission. This paper combines conceptual and evaluative studies carried out in the first five years of EU IAs. It concludes that the great discrepancy between rationale and practice calls for a different theoretical focus and a higher emphasis on evaluating empirically crucial risk economics aspects of IAs, such as the value of statistical life, price of carbon, the integration of macroeconomic modelling and scenario analysis.

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Firms are faced with a wider set of choices when they identify a need for new office space. They can build or purchase accommodation, lease space for long or short periods with or without the inclusion of services, or they can use “instant office” solutions provided by serviced office operators. But how do they evaluate these alternatives and are they able to make rational choices? The research found that the shortening of business horizons lead to the desire for more office space on short-term contracts often with the inclusion of at least some facilities management and business support services. The need for greater flexibility, particularly in financial terms, was highlighted as an important criteria when selecting new office accommodation. The current office portfolios held were perceived not to meet these requirements. However, there was often a lack of good quality data available within occupiers which could be used to help them analyse the range of choices in the market. Additionally, there were other organisational constraints to making decisions about inclusive real estate products. These included fragmentation of decisions-making, internal politics and the lack of assessment of business risk alongside real estate risk. Overall therefore, corporate occupiers themselves act as an interial force to the development of new and innovative real estate products.