17 resultados para Small Area Estimation

em Aston University Research Archive


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This study has concentrated on the development of an impact simulation model for use at the sub-national level. The necessity for the development of this model was demonstrated by the growth of local economic initiatives during the 1970's, and the lack of monitoring and evaluation exercise to assess their success and cost-effectiveness. The first stage of research involved the confirmation that the potential for micro-economic and spatial initiatives existed. This was done by identifying the existence of involuntary structural unemployment. The second stage examined the range of employment policy options from the macroeconomic, micro-economic and spatial perspectives, and focused on the need for evaluation of those policies. The need for spatial impact evaluation exercise in respect of other exogenous shocks, and structural changes was also recognised. The final stage involved the investigation of current techniques of evaluation and their adaptation for the purpose in hand. This led to a recognition of a gap in the armoury of techniques. The employment-dependency model has been developed to fill that gap, providing a low-budget model, capable of implementation at the small area level and generating a vast array of industrially disaggregate data, in terms of employment, employment-income, profits, value-added and gross income, related to levels of United Kingdom final demand. Thus providing scope for a variety of impact simulation exercises.

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The aims of the project were twofold: 1) To investigate classification procedures for remotely sensed digital data, in order to develop modifications to existing algorithms and propose novel classification procedures; and 2) To investigate and develop algorithms for contextual enhancement of classified imagery in order to increase classification accuracy. The following classifiers were examined: box, decision tree, minimum distance, maximum likelihood. In addition to these the following algorithms were developed during the course of the research: deviant distance, look up table and an automated decision tree classifier using expert systems technology. Clustering techniques for unsupervised classification were also investigated. Contextual enhancements investigated were: mode filters, small area replacement and Wharton's CONAN algorithm. Additionally methods for noise and edge based declassification and contextual reclassification, non-probabilitic relaxation and relaxation based on Markov chain theory were developed. The advantages of per-field classifiers and Geographical Information Systems were investigated. The conclusions presented suggest suitable combinations of classifier and contextual enhancement, given user accuracy requirements and time constraints. These were then tested for validity using a different data set. A brief examination of the utility of the recommended contextual algorithms for reducing the effects of data noise was also carried out.

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We present results concerning the application of the Good-Turing (GT) estimation method to the frequentist n-tuple system. We show that the Good-Turing method can, to a certain extent rectify the Zero Frequency Problem by providing, within a formal framework, improved estimates of small tallies. We also show that it leads to better tuple system performance than Maximum Likelihood estimation (MLE). However, preliminary experimental results suggest that replacing zero tallies with an arbitrary constant close to zero before MLE yields better performance than that of GT system.

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Automatically generating maps of a measured variable of interest can be problematic. In this work we focus on the monitoring network context where observations are collected and reported by a network of sensors, and are then transformed into interpolated maps for use in decision making. Using traditional geostatistical methods, estimating the covariance structure of data collected in an emergency situation can be difficult. Variogram determination, whether by method-of-moment estimators or by maximum likelihood, is very sensitive to extreme values. Even when a monitoring network is in a routine mode of operation, sensors can sporadically malfunction and report extreme values. If this extreme data destabilises the model, causing the covariance structure of the observed data to be incorrectly estimated, the generated maps will be of little value, and the uncertainty estimates in particular will be misleading. Marchant and Lark [2007] propose a REML estimator for the covariance, which is shown to work on small data sets with a manual selection of the damping parameter in the robust likelihood. We show how this can be extended to allow treatment of large data sets together with an automated approach to all parameter estimation. The projected process kriging framework of Ingram et al. [2007] is extended to allow the use of robust likelihood functions, including the two component Gaussian and the Huber function. We show how our algorithm is further refined to reduce the computational complexity while at the same time minimising any loss of information. To show the benefits of this method, we use data collected from radiation monitoring networks across Europe. We compare our results to those obtained from traditional kriging methodologies and include comparisons with Box-Cox transformations of the data. We discuss the issue of whether to treat or ignore extreme values, making the distinction between the robust methods which ignore outliers and transformation methods which treat them as part of the (transformed) process. Using a case study, based on an extreme radiological events over a large area, we show how radiation data collected from monitoring networks can be analysed automatically and then used to generate reliable maps to inform decision making. We show the limitations of the methods and discuss potential extensions to remedy these.

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The superior properties of ferritic/martensitic steels in a radiation environment (low swelling, low activation under irradiation and good corrosion resistance) make them good candidates for structural parts in future reactors and spallation sources. While it cannot substitute for true reactor experiments, irradiation by charged particles from accelerators can reduce the number of reactor experiments and support fundamental research for a better understanding of radiation effects in materials. Based on the nature of low energy accelerator experiments, only a small volume of material can be uniformly irradiated. Micro and nanoscale post irradiation tests thus have to be performed. We show here that nanoindentation and micro-compression testing on T91 and HT-9 stainless steel before and after ion irradiation are useful methods to evaluate the radiation induced hardening.

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At detection threshold, sensitivity improves as the area of a test grating increases, but not when the test is placed on a pedestal and the task becomes contrast discrimination (G. E. Legge, & J. M. Foley, 1980). This study asks whether the abolition of area summation is specific to the situation where mask and test stimuli have the same spatial frequency and orientation ("within-channel" masking) or is more general, also occurring when mask and test stimuli are very different ("cross-channel" masking). Threshold versus contrast masking functions were measured where the test and mask were either both small (SS), both large (LL), or small and large, respectively (SL). For within-channel masking, facilitation and area summation were found at low mask contrasts, but the results for SS and LL converged at intermediate contrasts and above, replicating Legge and Foley (1980). For all three observers, less facilitation was found for SL than for SS. For cross-channel masking, area summation occurred across the entire masking function and results for SS and SL were identical. The results for the entire data set were well fit by an extended version of a contrast masking model (J. M. Foley, 1994) in which the weights of excitatory and suppressive surround terms were free parameters. I conclude that (i) there is no empirical abolition of area summation for cross-channel masking, (ii) within-channel area summation can be abolished empirically without being disabled in the model, (iii) observers are able to restrict the area of spatial integration, but not suppression, (iv) extending a cross-channel mask to the surround has no effect on contrast detection, and (v) there is a formal similarity between area summation and contrast adaptation. © 2004 ARVO.

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This thesis describes the geology, geochemistry and mineralogy of a Lower Proterozoic, metamorphosed volcanogenic Cu-Zn deposit, situated at the western end of the Flin Flon greenstone belt. Stratabound copper mineralisation occurs in silicified and chloritoid-bearing alteration assemblages within felsic tuffs and is mantled by thin (< 3m) high-grade sphalerite layers. Mineralisation is underlain by garnet-hornblende bearing Lower Iron Formation (LIF), and overlain by garnet-grunerite bearing Upper Iron Formation (UIF). Distinctive trace element trends, involving Ti and Zr, in mineralised and footwall felsic tuffs are interpreted to have formed by fractionation associated with a high-level magma chamber in a caldera-type environment. Discrimination diagrams for basaltic rocks are interpreted to indicate their formation in an environment similar to that of recent, primitive, tholeiitic island arcs. Microprobe studies of key mineral phases demonstrate large and small scale chemical variations in silicate phases related to primary lithological, rather than metamorphic, controls. LIF is characterised by alumino-ferro-tschermakite and relatively Mn-poor, Ca-rich garnets, whereas UIF contains manganoan grunerite and Mn-rich garnets. Metamorphic mineral reactions are considered and possible precursor assemblages identified for garnet-, and chloritoid-bearing rocks. Chloritoid-bearing rocks are interpreted as the metamorphosed equivalents of iron-rich feeder zones formed near the surface. The iron-formations are thought to represent iron-rich sediments formed on the sea floor formed from the venting of the ore fluids. Consideration of various mineral assemblages leads to an estimate for peak metamorphic conditions of 450-500oC and > 4Kb total pressure. Comparisons with other volcanogenic deposits indicate affinities with deposits of `Mattabi-type' from the Archean of Ontario. An extrapolation of the main conclusions of the thesis to adjacent areas points to the presence of a number of geologically similar localities with potential for mineralisation.

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In this paper new architectural approaches that improve the energy efficiency of a cellular radio access network (RAN) are investigated. The aim of the paper is to characterize both the energy consumption ratio (ECR) and the energy consumption gain (ECG) of a cellular RAN when the cell size is reduced for a given user density and service area. The paper affirms that reducing the cell size reduces the cell ECR as desired while increasing the capacity density but the overall RAN energy consumption remains unchanged. In order to trade the increase in capacity density with RAN energy consumption, without degrading the cell capacity provision, a sleep mode is introduced. In sleep mode, cells without active users are powered-off, thereby saving energy. By combining a sleep mode with a small-cell deployment architecture, the paper shows that the ECG can be increased by the factor n = (R/R) while the cell ECR continues to decrease with decreasing cell size.

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Considering its strong environmental impact, logistics plays a critical role in green supply chain management. It provides strategic links in the supply chain and is an essential function in the delivery of green products to the consumer. There is a general consensus on the fact that more environmentally sustainable companies may be achieved only if transport and logistics activities also become greener. To achieve this objective, buyer companies need to incorporate green considerations in the purchasing of transport and logistics services. This appears particularly challenging for small and medium sized enterprises (SMEs) because of their traditional lack of managerial, organisational and financial resources that often result in failure to adopt an environmental perspective. In the extant literature, green purchasing has received increased attention over the past decade and the strategic importance of introducing green aspects into purchasing practices has been recognised. However, little has been written in relation to purchasing green transport and logistics services. The aim of this paper is to explore practices in the buying of green transport and logistics services and to derive implications for small buyer companies. The paper analyses how general environmental company ambitions and environmental purchasing practices are reflected when green transport and logistics services are purchased in three different European countries (Italy, Ireland and Sweden) using a multiple case study research approach. The results of the paper indicate that while the case companies show a relatively high concern for green issues at corporate level, a lower importance is attributed to green issues at the purchasing function level. When green concerns in the purchasing of transport and logistics services are analysed the level of importance decreases further. Thus, a conflicting attitude is evident between the overall corporate level and the purchasing of transport and logistics services specifically. This suggests that there is potential for improvement especially in the area of green collaboration in buyer and supplier relationships.

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Enhancing the resilience of local communities to weather extremes has gained significant interest over the years, amidst the increased intensity and frequency of such events. The fact that such weather extremes are forecast to further increase in number and severity in future has added extra weight to the importance of the issue. As a local community consists of a number of community groups such as households, businesses and policy makers, the actions of different community groups in combination will determine the resilience of the community as a whole. An important role has to be played by Small and Medium-sized Enterprises (SMEs); which is an integral segment of a local community in the UK, in this regard. While it is recognised that they are vital to the economy of a country and determines the prosperity of communities, they are increasingly vulnerable to effects of extreme weather. This paper discusses some of the exploratory studies conducted in the UK on SMEs and their ability to cope with extreme weather events, specifically flooding. Although a reasonable level of awareness of the risk was observed among the SMEs, this has not always resulted in increased preparedness even if they are located in areas at risk of flooding. The attitude and the motivation to change differed widely between SMEs. The paper presents schemas by which the SMEs can identify their vulnerability better so that they can be populated among a community of SMEs, which can be taken forward to inform policy making in this area. Therefore the main contribution the paper makes to the body of knowledge in the area is a novel way to communicate to SMEs on improving resilience against extreme weather, which will inform some of the policy making initiatives in the UK.

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Purpose: Amidst the current economic climate, which places many constraints on expensive flood defence schemes, the policy makers tend to favour schemes that are sympathetic to the needs of small and medium-sized enterprises (SMEs) and which promote empowering local communities based on their individual local contexts. Research has shown that although several initiatives are in place to create behavioural change among SMEs in undertaking adaptation approaches against flooding, they often tend to delay their responses by means of a "wait and see" attitude. The paper aims to discuss these issues. Design/methodology/approach: This paper argues that unless there are conscious efforts in the policy-making community to undertake explicit measures to engage with SMEs in a collaborative way, the uptake of adaptation measures will not be achieved as intended. With the use of the "honest broker" approach the paper provides a conceptual way forward of how a sense of collaboration can be instigated in an engagement process between the policy makers and SMEs, so that the scientific knowledge is translated in an appropriately rational way, which best meets the expectations of the SMEs. Findings: The paper proposes a conceptual model for engaging SMEs that will potentially increase the uptake of flood adaptation measures by SMEs. This could be a useful model with which to kick start a collaborative engagement process that could escalate to wider participation in other areas to improve impact of policy initiatives. Originality/value: The paper lays the conceptual foundation for a new theoretical base in the area, which will encourage more empirical investigations that will potentially enhance the practicality of some of the existing policies. © Emerald Group Publishing Limited.

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The impact of ICT (information and communications technology) on the logistics service industry is reshaping its organisation and structure. Within this process, the nature of changes resulting from ICT dissemination in small 3PLs (third party logistics providers) is still unclear, although a large number of logistics service markets, especially in the EU context, are populated by a high number of small 3PLs. In addition, there is still a gap in the literature where the role of technological capability in small 3PLs is seriously underestimated. This gives rise to the need to develop investigation in this area. The paper presents the preliminary results of a case study analysis on ICT usage in a sample of 7 small Italian 3PLs. The results highlight some of the barriers to effective ICT implementation, as well as some of the critical success factors.

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ICT has triggered many changes in the logistics service industry. New technology is reshaping the organisation and structure of this industry as ICT impacts significantly on the operations of 3PLs. Within this process, while large 3PLs are gaining substantial benefits from technology usage, the nature of changes resulting from ICT usage in small 3PLs remains unclear. This is critical particularly for those markets populated by a high number of small 3PLs such as the Italian logistics industry. From the research point of view, there is still a gap in the literature where the role of technological capability in small 3PLs are seriously underestimated. This gives rise to the need to develop investigation in this area. This paper presents the preliminary results of a case study analysis on ICT usage in a sample of 7 small Italian 3PLs. The results highlight some of the barriers to effective ICT implementation, as well as some of the critical success factors.

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Information and communication technology (ICT) developments have strongly affected supply chain management (SCM) in recent years. ICT has had a great impact on all supply chain processes including planning, purchasing, production management, stock management, physical distribution and related integration management. Technology has become an important dimension of third party logistics (3PL) service supply as competitive advantage increasingly depends on the ability to create value for customers through the effective application of ICT. Within this process, while large 3PLs are gaining substantial benefits from technology usage and implementation, the magnitude of changes spurred by ICT dissemination in small logistics service providers remains unclear. This is reflected by the existing gap in literature where the role and competitive developing processes of small 3PLs are seriously underestimated. This gives rise to the need to develop research and investigation in this particular area. The objective of this paper is to narrow the knowledge gap in the field of ICT adoption in small 3PLs through an empirical investigation. It presents the results of a survey on a sample of small Italian 3PLs.

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Large-scale mechanical products, such as aircraft and rockets, consist of large numbers of small components, which introduce additional difficulty for assembly accuracy and error estimation. Planar surfaces as key product characteristics are usually utilised for positioning small components in the assembly process. This paper focuses on assembly accuracy analysis of small components with planar surfaces in large-scale volume products. To evaluate the accuracy of the assembly system, an error propagation model for measurement error and fixture error is proposed, based on the assumption that all errors are normally distributed. In this model, the general coordinate vector is adopted to represent the position of the components. The error transmission functions are simplified into a linear model, and the coordinates of the reference points are composed by theoretical value and random error. The installation of a Head-Up Display is taken as an example to analyse the assembly error of small components based on the propagation model. The result shows that the final coordination accuracy is mainly determined by measurement error of the planar surface in small components. To reduce the uncertainty of the plane measurement, an evaluation index of measurement strategy is presented. This index reflects the distribution of the sampling point set and can be calculated by an inertia moment matrix. Finally, a practical application is introduced for validating the evaluation index.