26 resultados para Uncertainty of forecasts

em Aston University Research Archive


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The uncertainty of measurements must be quantified and considered in order to prove conformance with specifications and make other meaningful comparisons based on measurements. While there is a consistent methodology for the evaluation and expression of uncertainty within the metrology community industry frequently uses the alternative Measurement Systems Analysis methodology. This paper sets out to clarify the differences between uncertainty evaluation and MSA and presents a novel hybrid methodology for industrial measurement which enables a correct evaluation of measurement uncertainty while utilising the practical tools of MSA. In particular the use of Gage R&R ANOVA and Attribute Gage studies within a wider uncertainty evaluation framework is described. This enables in-line measurement data to be used to establish repeatability and reproducibility, without time consuming repeatability studies being carried out, while maintaining a complete consideration of all sources of uncertainty and therefore enabling conformance to be proven with a stated level of confidence. Such a rigorous approach to product verification will become increasingly important in the era of the Light Controlled Factory with metrology acting as the driving force to achieve the right first time and highly automated manufacture of high value large scale products such as aircraft, spacecraft and renewable power generation structures.

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People manage a spectrum of identities in cyber domains. Profiling individuals and assigning them to distinct groups or classes have potential applications in targeted services, online fraud detection, extensive social sorting, and cyber-security. This paper presents the Uncertainty of Identity Toolset, a framework for the identification and profiling of users from their social media accounts and e-mail addresses. More specifically, in this paper we discuss the design and implementation of two tools of the framework. The Twitter Geographic Profiler tool builds a map of the ethno-cultural communities of a person's friends on Twitter social media service. The E-mail Address Profiler tool identifies the probable identities of individuals from their e-mail addresses and maps their geographical distribution across the UK. To this end, this paper presents a framework for profiling the digital traces of individuals.

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This paper shows how the angular uncertainties can be determined for a rotary-laser automatic theodolite of the type used in (indoor-GPS) iGPS networks. Initially, the fundamental physics of the rotating head device is used to propagate uncertainties using Monte Carlo simulation. This theoretical element of the study shows how the angular uncertainty is affected by internal parameters, the actual values of which are estimated. Experiments are then carried out to determine the actual uncertainty in the azimuth angle. Results are presented that show that uncertainty decreases with sampling duration. Other significant findings are that uncertainty is relatively constant throughout the working volume and that the uncertainty value is not dependent on the size of the reference angle. © 2009 IMechE.

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Purpose: This paper aims to describe an investigation into how company performance can be improved by integrating internal and external customers and technology. The approach was developed, implemented and evaluated in the operations of the building components industry. The research was carried out in the precast concrete division of a Singapore company. Design/methodology/ approach: For the purpose of undertaking the investigation an exploratory case study approach was used. This was divided into conceptual and action research stages. The action research was also used to implement the changes in the company. Questionnaire surveys were carried out among company employees and external customers to assess the effect of these changes. Results of the investigation were derived using content and statistical analysis. Triangulation between three sources was used for validating the data. Findings: The exploratory case study strategy resulted in rich research data, which provided evidence of the changes taking place and integration happening, leading to improved performance. The action research approach proved a powerful tool where the uncertainty of outcomes makes it near impossible to make accurate forecasts. Another output of the research was the development of an "integrated customer orientation" (ICO) model. Research limitations/implications: The research in this paper used a single site action research investigation so should be interpreted within the specific company and industry context. There are implications for theory and practice in a number of areas of production and marketing as well as contributions to understanding about productivity improvement and organisational development. The investigation also fulfils the dual objectives of action research by contributing to both knowledge and practice. Originality/value: The paper describes a unique approach towards improving productivity, quality and service through the use of action research to implement changes, as well as providing the research evidence to evaluate both the process of implementation and results achieved. © Emerald Group Publishing Limited.

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Dynamically adaptive systems (DASs) are intended to monitor the execution environment and then dynamically adapt their behavior in response to changing environmental conditions. The uncertainty of the execution environment is a major motivation for dynamic adaptation; it is impossible to know at development time all of the possible combinations of environmental conditions that will be encountered. To date, the work performed in requirements engineering for a DAS includes requirements monitoring and reasoning about the correctness of adaptations, where the DAS requirements are assumed to exist. This paper introduces a goal-based modeling approach to develop the requirements for a DAS, while explicitly factoring uncertainty into the process and resulting requirements. We introduce a variation of threat modeling to identify sources of uncertainty and demonstrate how the RELAX specification language can be used to specify more flexible requirements within a goal model to handle the uncertainty. © 2009 Springer Berlin Heidelberg.

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This paper details a method of estimating the uncertainty of dimensional measurement for a three-dimensional coordinate measurement machine. An experimental procedure was developed to compare three-dimensional coordinate measurements with calibrated reference points. The reference standard used to calibrate these reference points was a fringe counting interferometer with a multilateration-like technique employed to establish three-dimensional coordinates. This is an extension of the established technique of comparing measured lengths with calibrated lengths. Specifically a distributed coordinate measurement device was tested which consisted of a network of Rotary-Laser Automatic Theodolites (R-LATs), this system is known commercially as indoor GPS (iGPS). The method was found to be practical and was used to estimate that the uncertainty of measurement for the basic iGPS system is approximately 1 mm at a 95% confidence level throughout a measurement volume of approximately 10 m × 10 m × 1.5 m. © 2010 IOP Publishing Ltd.

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The automatic interpolation of environmental monitoring network data such as air quality or radiation levels in real-time setting poses a number of practical and theoretical questions. Among the problems found are (i) dealing and communicating uncertainty of predictions, (ii) automatic (hyper)parameter estimation, (iii) monitoring network heterogeneity, (iv) dealing with outlying extremes, and (v) quality control. In this paper we discuss these issues, in light of the spatial interpolation comparison exercise held in 2004.

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This thesis involves the secondary data of 1806 innovative manufacturing firms derived from the database of 2nd Taiwanese Innovation Survey. Three topics are researched. The first topic investigates the innovation value chain (IVC) in Taiwanese manufacturing firms. Previous IVC studies are all done in developed countries such as UK, Ireland, Northern Ireland and Switzerland, and it leaves the gap of those non-developed countries. The result shows the overall knowledge sourcing pattern of Taiwanese manufacturing firms presenting a complementary relationship which is consistent to the previous IVC studies. The main innovation input is still derived from internal R&D which suggests more utilisation of external knowledge may boost innovation outcome. Product innovation does enhance firm growth while process innovation reduces a firm’s productivity. The second topic uses the lens of IVC to investigate the difference of the innovation process from knowledge linkages to value added between high-tech and low- tech sectors. The findings indicate (1) there are significant differences in the IVC between high- and low-tech sectors, however these are defined; (2) how you define ‘sector’ matters i.e. the nature of the high-tech and low-tech differences varies depending on whether the technology definition is carried out at the industry or firm level; and (3) the high uncertainty of innovation cause the difficulty to predict firm performance especially for those firms with high intensity of innovation. The third topic investigates the innovation-exporting relationship and explores the determinants of export performance. Product innovation enhances export performance once a firm enters international markets while process innovation affects negatively on a firm’s likelihood of being an exporter. Furthermore, IP protection is found to affect directly export performance positively.

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To fully utilize second-life batteries on the grid system, a hybrid battery scheme needs to be considered for several reasons: the uncertainty over using a single source supply chain for second-life batteries, the differences in evolving battery chemistry and battery configuration by different suppliers to strive for greater power levels, and the uncertainty of degradation within a second-life battery. Therefore, these hybrid battery systems could have widely different module voltage, capacity, and initial state of charge and state of health. In order to suitably integrate and control these widely different batteries, a suitable multimodular converter topology and an associated control structure are required. This paper addresses these issues proposing a modular boost-multilevel buck converter based topology to integrate these hybrid second-life batteries to a grid-tie inverter. Thereafter, a suitable module-based distributed control architecture is introduced to independently utilize each converter module according to its characteristics. The proposed converter and control architecture are found to be flexible enough to integrate widely different batteries to an inverter dc link. Modeling, analysis, and experimental validation are performed on a single-phase modular hybrid battery energy storage system prototype to understand the operation of the control strategy with different hybrid battery configurations.

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Synchronous reluctance motors (SynRMs) are gaining in popularity in industrial drives due to their permanent magnet-free, competitive performance, and robust features. This paper studies the power losses in a 90-kW converter-fed SynRM drive by a calorimetric method in comparison of the traditional input-output method. After the converter and the motor were measured simultaneously in separate chambers, the converter was installed inside the large-size chamber next to the motor and the total drive system losses were obtained using one chamber. The uncertainty of both measurement methods is analyzed and discussed.

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This paper considers the global synchronisation of a stochastic version of coupled map lattices networks through an innovative stochastic adaptive linear quadratic pinning control methodology. In a stochastic network, each state receives only noisy measurement of its neighbours' states. For such networks we derive a generalised Riccati solution that quantifies and incorporates uncertainty of the forward dynamics and inverse controller in the derivation of the stochastic optimal control law. The generalised Riccati solution is derived using the Lyapunov approach. A probabilistic approximation type algorithm is employed to estimate the conditional distributions of the state and inverse controller from historical data and quantifying model uncertainties. The theoretical derivation is complemented by its validation on a set of representative examples.

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Thermal effects in uncontrolled factory environments are often the largest source of uncertainty in large volume dimensional metrology. As the standard temperature for metrology of 20°C cannot be achieved practically or economically in many manufacturing facilities, the characterisation and modelling of temperature offers a solution for improving the uncertainty of dimensional measurement and quantifying thermal variability in large assemblies. Technologies that currently exist for temperature measurement in the range of 0-50°C have been presented alongside discussion of these temperature measurement technologies' usefulness for monitoring temperatures in a manufacturing context. Particular aspects of production where the technology could play a role are highlighted as well as practical considerations for deployment. Contact sensors such as platinum resistance thermometers can produce accuracy closest to the desired accuracy given the most challenging measurement conditions calculated to be ∼0.02°C. Non-contact solutions would be most practical in the light controlled factory (LCF) and semi-invasive appear least useful but all technologies can play some role during the initial development of thermal variability models.

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In dimensional metrology, often the largest source of uncertainty of measurement is thermal variation. Dimensional measurements are currently scaled linearly, using ambient temperature measurements and coefficients of thermal expansion, to ideal metrology conditions at 20˚C. This scaling is particularly difficult to implement with confidence in large volumes as the temperature is unlikely to be uniform, resulting in thermal gradients. A number of well-established computational methods are used in the design phase of product development for the prediction of thermal and gravitational effects, which could be used to a greater extent in metrology. This paper outlines the theory of how physical measurements of dimension and temperature can be combined more comprehensively throughout the product lifecycle, from design through to the manufacturing phase. The Hybrid Metrology concept is also introduced: an approach to metrology, which promises to improve product and equipment integrity in future manufacturing environments. The Hybrid Metrology System combines various state of the art physical dimensional and temperature measurement techniques with established computational methods to better predict thermal and gravitational effects.

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This paper details work carried out to verify the dimensional measurement performance of the Indoor GPS (iGPS) system; a network of Rotary-Laser Automatic Theodolites (R-LATs). Initially tests were carried out to determine the angular uncertainties on an individual R-LAT transmitter-receiver pair. A method is presented of determining the uncertainty of dimensional measurement for a three dimensional coordinate measurement machine. An experimental procedure was developed to compare three dimensional coordinate measurements with calibrated reference points. The reference standard used to calibrate these reference points was a fringe counting interferometer with the multilateration technique employed to establish three dimensional coordinates. This is an extension of the established technique of comparing measured lengths with calibrated lengths. The method was found to be practical and able to establish that the expanded uncertainty of the basic iGPS system was approximately 1 mm at a 95% confidence level. Further tests carried out on a highly optimized version of the iGPS system have shown that the coordinate uncertainty can be reduced to 0.25 mm at a 95% confidence level.

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We have proposed a similarity matching method (SMM) to obtain the change of Brillouin frequency shift (BFS), in which the change of BFS can be determined from the frequency difference between detecting spectrum and selected reference spectrum by comparing their similarity. We have also compared three similarity measures in the simulation, which has shown that the correlation coefficient is more accurate to determine the change of BFS. Compared with the other methods of determining the change of BFS, the SMM is more suitable for complex Brillouin spectrum profiles. More precise result and much faster processing speed have been verified in our simulation and experiments. The experimental results have shown that the measurement uncertainty of the BFS has been improved to 0.72 MHz by using the SMM, which is almost one-third of that by using the curve fitting method, and the speed of deriving the BFS change by the SMM is 120 times faster than that by the curve fitting method.