16,269 research outputs found

    Private Rights versus Public Power: The Role of State Action in Alaska Constitutional Jurisprudence

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    Linear approximations of nonlinear systems can be obtained by fitting a linear model to data from a nonlinear system, for example, using the prediction-error method. In many situations, the type of linear model and the model orders are selected after estimating several models and evaluating them using various validation techniques. Two commonly used validation methods for linear models are spectral and residual analysis. Unfortunately, these methods will not always work if the true system is nonlinear. However, if the input can be viewed as if it has been generated by filtering white noise through a minimum phase filter, spectral and residual analysis can be used for validation of linear models of nonlinear systems. Furthermore, it can be shown that the input minimum phase property guarantees that a certain optimality result will hold. Here, the benefits of using minimum phase instead of non-minimum phase filters for input design will be shown both theoretically and in numerical experiments

    Application of the morphological alpha shape method to the extraction of topographical features from engineering surfaces

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    In contrast to the mean-line based filters, morphological filters are function oriented and more suitable for the functional prediction of component performance. This paper presents a novel morphological method based on the alpha shape for the extraction of topographical features from engineering surfaces. Compared to the traditional implementation of morphological filters, the alpha shape method is more efficient in performance for large structuring element. The resulting envelope follows the form of the surface all over such that the distortions caused the end effects are avoided. A series of measured surfaces from the automotive cylinder liner and the bioengineering femoral heads are analyzed using the morphological alpha shape method. The topographical features are successfully extracted, enabling further analysis to the components

    A Criterion for Comparing Measurement Results and Determining Conformity with Specifications

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    In this paper a new criterion for comparing measurement results and determining conformity with specifications is proposed, which essentially is a strategy of estimating the empirical relationships of objects. Comparing with traditional methods given in GUM: 2008 and ISO 14253-1, this criterion improves the resolution of comparison by reducing the sizes of the coverage intervals to be compared. Interval order (a binary relation) is used for comparing the coverage intervals of the measurand and represents the empirical relations. The systematic effects of measurement are classified into two types: monotonic and non-monotonic effects, so that, without correcting the monotonic effects, a biased measurand can be specified to represent the empirical relations. Thereby the uncertainty components arising from the monotonic effects can be removed from the combined uncertainty. A strategy is given for determining the relationships among measurement results and specification limits. An example is given to demonstrate the application of the criterion

    Relational Structure of Measurement with Application on Specification of Freeform Surface

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    A contradiction is shown in this paper that, for contact surface measurement, if a measured surface profile is exactly coincident with the USL (upper specification limit), the measured result may still be out of specification. To understand and avoid this contradiction, a relational construction of measurement is proposed bases on the representational measurement theory. By observing the connection between measurement and inverse problem, measurement is modeled as a mapping from the preordered set of measurands (objects to be measured) to the partially ordered set of measured values. Thereby, a desired property of the specifications limits is derived, and a correction of the USL of surface profile is proposed

    Identifying and Characterizing Micro-machining Signatures on Freeform Surfaces Using Morphological Methods

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    Freeform surfaces are replacing traditional surfaces and have significantly reduced volume and weight and highly improved performance in modern complex optic systems, bio-systems and other disciplines [1]. These high-precision freeform components are enabled by state-of-the-art micro-machining technologies, compromising mechanical methods (diamond turning and polishing etc.), physical methods (laser beam and ion beam machining), and chemical methods (lithography, electro-chemical machining etc.). However, a fundamental pre-requisite to achieve the potential growth to these high-added value freeform components is to measure and characterize these components with the required accuracy such that their manufacturing quality can be controlled. The surface topography is a fingerprint of all process stages of the manufacturing process. Thus identifying and evaluating these topographical features on freeform surfaces left by production techniques are critically important in that they could present an indication of the manufacturing quality and offer feedback to the process control

    A criterion for comparing measurement results and determining conformity with specifications

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    In this paper a new criterion for comparing measurement results and determining conformity with specifications is proposed, which essentially is a strategy of estimating the empirical relationships of objects. Comparing with traditional methods given in GUM:2008 and ISO 14253-1, this criterion improves the resolution of comparison by reducing the sizes of the coverage intervals to be compared. Interval order (a binary relation) is used for comparing the coverage intervals of the measurand and represents the empirical relations. The systematic effects of measurement are classified into two types: monotonic and non-monotonic effects, so that, without correcting the monotonic effects, a biased measurand can be specified to represent the empirical relations. Thereby the uncertainty components arising from the monotonic effects can be removed from the combined uncertainty. A strategy is given for determining the relationships among measurement results and specification limits. An example is given to demonstrate the application of the criterion

    An ANOVA method of evaluating the specification uncertainty in roughness measurement

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    The specifications of roughness used in industry are normally incomplete, and the incompleteness can induce a significant uncertainty, called specification uncertainty. It’s important to know the magnitude and effect of this uncertainty, but there are yet no standard methods of evaluating the specification uncertainty. In this paper, we propose an ANOVA method to estimate the specification uncertainty. In this method, ANOVA is used to separate specification uncertainty from measurement uncertainty, and the sampling method of GR&R (gauge repeatability and reproducibility) is applied. A case study is given to demonstrate how to use this method to evaluate the specification uncertainty of measuring roughness with PGI (Phase Grating Interferometer) when the filter type is not specified

    Asian and OECD international R&D spillovers

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    Previous studies have demonstrated an empirical relationship between accumulated R&D expenditures and total factor productivity (TFP), and have shown that the benefits of R&D can spill across countries through trade. This paper extends these analyses to a sample of 15 OECD countries and six Asian countries, Chinese Taipei, India, Indonesia, Korea, Singapore and Thailand. An empirical model is estimated which relates TFP to domestic and foreign R&D activity, TFP catch-up and business cycle variables. Model estimates show that TFP and domestic R&D capital are positively related, and that domestic R&D has a relatively large impact on TFP growth in the NICs and LICs. Country-specific international R&D spillover elasticities are of mixed sign, and no apparent pattern by country group is evident. While this result does not change the earlier qualitative conclusions, it suggests that estimates of sample average R&D spillover elasticities should be cautiously interpreted.R&D activity; Asian and OECD spillovers

    16S rRNA gene-based profiling of the human infant gut microbiota is strongly influenced by sample processing and PCR primer choice

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    Acknowledgements The authors acknowledge the assistance of Grietje Holtrop (RINH-BioSS) with the statistical analysis of the data and the Wellcome Trust Sanger Institute’s 454 pyrosequencing team for generating 16S rRNA gene data. AWW, PS and JP received core funding support from the Wellcome Trust [grant number 098051]. AWW, JCM, HJF and KPS are funded by the Scottish Government (SG-RESAS).Peer reviewedPublisher PD
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