951 resultados para Robust Performance


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La electrónica digital moderna presenta un desafío a los diseñadores de sistemas de potencia. El creciente alto rendimiento de microprocesadores, FPGAs y ASICs necesitan sistemas de alimentación que cumplan con requirimientos dinámicos y estáticos muy estrictos. Específicamente, estas alimentaciones son convertidores DC-DC de baja tensión y alta corriente que necesitan ser diseñados para tener un pequeño rizado de tensión y una pequeña desviación de tensión de salida bajo transitorios de carga de una alta pendiente. Además, dependiendo de la aplicación, se necesita cumplir con otros requerimientos tal y como proveer a la carga con ”Escalado dinámico de tensión”, donde el convertidor necesitar cambiar su tensión de salida tan rápidamente posible sin sobreoscilaciones, o ”Posicionado Adaptativo de la Tensión” donde la tensión de salida se reduce ligeramente cuanto más grande sea la potencia de salida. Por supuesto, desde el punto de vista de la industria, las figuras de mérito de estos convertidores son el coste, la eficiencia y el tamaño/peso. Idealmente, la industria necesita un convertidor que es más barato, más eficiente, más pequeño y que aún así cumpla con los requerimienos dinámicos de la aplicación. En este contexto, varios enfoques para mejorar la figuras de mérito de estos convertidores se han seguido por la industria y la academia tales como mejorar la topología del convertidor, mejorar la tecnología de semiconducores y mejorar el control. En efecto, el control es una parte fundamental en estas aplicaciones ya que un control muy rápido hace que sea más fácil que una determinada topología cumpla con los estrictos requerimientos dinámicos y, consecuentemente, le da al diseñador un margen de libertar más amplio para mejorar el coste, la eficiencia y/o el tamaño del sistema de potencia. En esta tesis, se investiga cómo diseñar e implementar controles muy rápidos para el convertidor tipo Buck. En esta tesis se demuestra que medir la tensión de salida es todo lo que se necesita para lograr una respuesta casi óptima y se propone una guía de diseño unificada para controles que sólo miden la tensión de salida Luego, para asegurar robustez en controles muy rápidos, se proponen un modelado y un análisis de estabilidad muy precisos de convertidores DC-DC que tienen en cuenta circuitería para sensado y elementos parásitos críticos. También, usando este modelado, se propone una algoritmo de optimización que tiene en cuenta las tolerancias de los componentes y sensados distorsionados. Us ando este algoritmo, se comparan controles muy rápidos del estado del arte y su capacidad para lograr una rápida respuesta dinámica se posiciona según el condensador de salida utilizado. Además, se propone una técnica para mejorar la respuesta dinámica de los controladores. Todas las propuestas se han corroborado por extensas simulaciones y prototipos experimentales. Con todo, esta tesis sirve como una metodología para ingenieros para diseñar e implementar controles rápidos y robustos de convertidores tipo Buck. ABSTRACT Modern digital electronics present a challenge to designers of power systems. The increasingly high-performance of microprocessors, FPGAs (Field Programmable Gate Array) and ASICs (Application-Specific Integrated Circuit) require power supplies to comply with very demanding static and dynamic requirements. Specifically, these power supplies are low-voltage/high-current DC-DC converters that need to be designed to exhibit low voltage ripple and low voltage deviation under high slew-rate load transients. Additionally, depending on the application, other requirements need to be met such as to provide to the load ”Dynamic Voltage Scaling” (DVS), where the converter needs to change the output voltage as fast as possible without underdamping, or ”Adaptive Voltage Positioning” (AVP) where the output voltage is slightly reduced the greater the output power. Of course, from the point of view of the industry, the figures of merit of these converters are the cost, efficiency and size/weight. Ideally, the industry needs a converter that is cheaper, more efficient, smaller and that can still meet the dynamic requirements of the application. In this context, several approaches to improve the figures of merit of these power supplies are followed in the industry and academia such as improving the topology of the converter, improving the semiconductor technology and improving the control. Indeed, the control is a fundamental part in these applications as a very fast control makes it easier for the topology to comply with the strict dynamic requirements and, consequently, gives the designer a larger margin of freedom to improve the cost, efficiency and/or size of the power supply. In this thesis, how to design and implement very fast controls for the Buck converter is investigated. This thesis proves that sensing the output voltage is all that is needed to achieve an almost time-optimal response and a unified design guideline for controls that only sense the output voltage is proposed. Then, in order to assure robustness in very fast controls, a very accurate modeling and stability analysis of DC-DC converters is proposed that takes into account sensing networks and critical parasitic elements. Also, using this modeling approach, an optimization algorithm that takes into account tolerances of components and distorted measurements is proposed. With the use of the algorithm, very fast analog controls of the state-of-the-art are compared and their capabilities to achieve a fast dynamic response are positioned de pending on the output capacitor. Additionally, a technique to improve the dynamic response of controllers is also proposed. All the proposals are corroborated by extensive simulations and experimental prototypes. Overall, this thesis serves as a methodology for engineers to design and implement fast and robust controls for Buck-type converters.

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Physician training has greatly benefitted from insights gained in understanding the manner in which experts search medical images for abnormalities. The aims of this study were to compare the search patterns of 30 fourth-year dental students and 15 certified oral and maxillofacial radiologists (OMRs) over panoramic images and to determine the most robust variables for future studies involving image visualization. Eye tracking was used to capture the eye movement patterns of both subject groups when examining 20 panoramic images classified as normal or abnormal. Abnormal images were further subclassified as having an obvious, intermediate, or subtle abnormality. The images were presented in random order to each participant, and data were collected on duration of the participants’ observations and total distance tracked, time to first eye fixation, and total duration and numbers of fixations on and off the area of interest (AOI). The results showed that the OMRs covered greater distances than the dental students (p<0.001) for normal images. For images of pathosis, the OMRs required less total time (p<0.001), made fewer eye fixations (p<0.01) with fewer saccades (p<0.001) than the students, and required less time before making the first fixation on the AOI (p<0.01). Furthermore, the OMRs covered less distance (p<0.001) than the dental students for obvious pathoses. For investigations of images of pathosis, time to first fixation is a robust parameter in predicting ability. For images with different levels of subtlety of pathoses, the number of fixations, total time spent, and numbers of revisits are important parameters to analyze when comparing observer groups with different levels of experience.

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The ability to innovate is generally accepted as a critical success factor to growth and future performance of firms. Yet, this acceptance obscures a comprehensive perspective on how firms can influence their innovation capacity and resulting performance. This paper proposes a '3P' construct of innovation measurement that simultaneously considers the Posture, Propensity and Performance related to a firm's innovation capabilities. We propose and provide empirical support showing that robust measurement of the performance implications of innovation requires the consideration of input, throughput and output factors simultaneously. Single or more limited indicators do not offer the degree of fine-tuning to a firm's innovation system that managers require. Thus, we propose the development, and future research into contingent variations, of a Composite Innovation Index (CII). We further demonstrate its use in comparing innovators and allowing managers to design a firm's innovation system.

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Physician training has greatly benefitted from insights gained in understanding the manner in which experts search medical images for abnormalities. The aims of this study were to compare the search patterns of 30 fourth-year dental students and 15 certified oral and maxillofacial radiologists (OMRs) over panoramic images and to determine the most robust variables for future studies involving image visualization. Eye tracking was used to capture the eye movement patterns of both subject groups when examining 20 panoramic images classified as normal or abnormal. Abnormal images were further subclassified as having an obvious, intermediate, or subtle abnormality. The images were presented in random order to each participant, and data were collected on duration of the participants’ observations and total distance tracked, time to first eye fixation, and total duration and numbers of fixations on and off the area of interest (AOI). The results showed that the OMRs covered greater distances than the dental students (p<0.001) for normal images. For images of pathosis, the OMRs required less total time (p<0.001), made fewer eye fixations (p<0.01) with fewer saccades (p<0.001) than the students, and required less time before making the first fixation on the AOI (p<0.01). Furthermore, the OMRs covered less distance (p<0.001) than the dental students for obvious pathoses. For investigations of images of pathosis, time to first fixation is a robust parameter in predicting ability. For images with different levels of subtlety of pathoses, the number of fixations, total time spent, and numbers of revisits are important parameters to analyze when comparing observer groups with different levels of experience.

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This paper addresses advanced control of a biological nutrient removal (BNR) activated sludge process. Based on a previously validated distributed parameter model of the BNR activated sludge process, we present robust multivariable controller designs for the process, involving loop shaping of plant model, robust stability and performance analyses. Results from three design case studies showed that a multivariable controller with stability margins of 0.163, 0.492 and 1.062 measured by the normalised coprime factor, multiplicative and additive uncertainties respectively give the best results for meeting performance robustness specifications. The controller robustly stabilises effluent nutrients in the presence of uncertainties with the behaviour of phosphorus accumulating organisms as well as to effectively attenuate major disturbances introduced as step changes. This study also shows that, performance of the multivariable robust controller is superior to multi-loops SISO PI controllers for regulating the BNR activated sludge process in terms of robust stability and performance and controlling the process using inlet feed flowrate is infeasible. (C) 2003 Elsevier Ltd. All rights reserved.

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Over the last decade, the international business literature has placed ever-greater emphasis on the role that learning and innovation play in determining multinational and multinational subsidiary performance. The present research seeks to understand the organizational paths leading to such desirable outcomes as greater learning, increased innovation and improved performance. Using a model tested with data collected through a survey of managers in subsidiaries of multinational firms, we find dual, independent paths to improved performance - one through networking and inter-unit learning and the other through subsidiary autonomy and innovation. A particular feature of these findings is that they can be shown to be robust after controlling for a wide range of environmental pressures and firm and industry factors. However, in the absence of environmental controls the dual path finding is rejected. These conflicting findings support the imperative to test models that include a diverse range of environmental pressures so that the true effects of organizational factors on learning, innovation and performance can be identified.

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High-performance liquid chromatography coupled by an electrospray ion source to a tandem mass spectrometer (HPLC-EST-MS/ MS) is the current analytical method of choice for quantitation of analytes in biological matrices. With HPLC-ESI-MS/MS having the characteristics of high selectivity, sensitivity, and throughput, this technology is being increasingly used in the clinical laboratory. An important issue to be addressed in method development, validation, and routine use of HPLC-ESI-MS/MS is matrix effects. Matrix effects are the alteration of ionization efficiency by the presence of coeluting substances. These effects are unseen in the chromatograrn but have deleterious impact on methods accuracy and sensitivity. The two common ways to assess matrix effects are either by the postextraction addition method or the postcolumn infusion method. To remove or minimize matrix effects, modification to the sample extraction methodology and improved chromatographic separation must be performed. These two parameters are linked together and form the basis of developing a successful and robust quantitative HPLC-EST-MS/MS method. Due to the heterogenous nature of the population being studied, the variability of a method must be assessed in samples taken from a variety of subjects. In this paper, the major aspects of matrix effects are discussed with an approach to address matrix effects during method validation proposed. (c) 2004 The Canadian Society of Clinical Chemists. All rights reserved.

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Semantic data models provide a map of the components of an information system. The characteristics of these models affect their usefulness for various tasks (e.g., information retrieval). The quality of information retrieval has obvious important consequences, both economic and otherwise. Traditionally, data base designers have produced parsimonious logical data models. In spite of their increased size, ontologically clearer conceptual models have been shown to facilitate better performance for both problem solving and information retrieval tasks in experimental settings. The experiments producing evidence of enhanced performance for ontologically clearer models have, however, used application domains of modest size. Data models in organizational settings are likely to be substantially larger than those used in these experiments. This research used an experiment to investigate whether the benefits of improved information retrieval performance associated with ontologically clearer models are robust as the size of the application domains increase. The experiment used an application domain of approximately twice the size as tested in prior experiments. The results indicate that, relative to the users of the parsimonious implementation, end users of the ontologically clearer implementation made significantly more semantic errors, took significantly more time to compose their queries, and were significantly less confident in the accuracy of their queries.

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One of critical challenges in automatic recognition of TV commercials is to generate a unique, robust and compact signature. Uniqueness indicates the ability to identify the similarity among the commercial video clips which may have slight content variation. Robustness means the ability to match commercial video clips containing the same content but probably with different digitalization/encoding, some noise data, and/or transmission and recording distortion. Efficiency is about the capability of effectively matching commercial video sequences with a low computation cost and storage overhead. In this paper, we present a binary signature based method, which meets all the three criteria above, by combining the techniques of ordinal and color measurements. Experimental results on a real large commercial video database show that our novel approach delivers a significantly better performance comparing to the existing methods.

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Most face recognition systems only work well under quite constrained environments. In particular, the illumination conditions, facial expressions and head pose must be tightly controlled for good recognition performance. In 2004, we proposed a new face recognition algorithm, Adaptive Principal Component Analysis (APCA) [4], which performs well against both lighting variation and expression change. But like other eigenface-derived face recognition algorithms, APCA only performs well with frontal face images. The work presented in this paper is an extension of our previous work to also accommodate variations in head pose. Following the approach of Cootes et al, we develop a face model and a rotation model which can be used to interpret facial features and synthesize realistic frontal face images when given a single novel face image. We use a Viola-Jones based face detector to detect the face in real-time and thus solve the initialization problem for our Active Appearance Model search. Experiments show that our approach can achieve good recognition rates on face images across a wide range of head poses. Indeed recognition rates are improved by up to a factor of 5 compared to standard PCA.

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We introduce a novel inversion-based neuro-controller for solving control problems involving uncertain nonlinear systems that could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. In this work a novel robust inverse control approach is obtained based on importance sampling from these distributions. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The performance of the new algorithm is illustrated through simulations with example systems.

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Ad hoc wireless sensor networks (WSNs) are formed from self-organising configurations of distributed, energy constrained, autonomous sensor nodes. The service lifetime of such sensor nodes depends on the power supply and the energy consumption, which is typically dominated by the communication subsystem. One of the key challenges in unlocking the potential of such data gathering sensor networks is conserving energy so as to maximize their post deployment active lifetime. This thesis described the research carried on the continual development of the novel energy efficient Optimised grids algorithm that increases the WSNs lifetime and improves on the QoS parameters yielding higher throughput, lower latency and jitter for next generation of WSNs. Based on the range and traffic relationship the novel Optimised grids algorithm provides a robust traffic dependent energy efficient grid size that minimises the cluster head energy consumption in each grid and balances the energy use throughout the network. Efficient spatial reusability allows the novel Optimised grids algorithm improves on network QoS parameters. The most important advantage of this model is that it can be applied to all one and two dimensional traffic scenarios where the traffic load may fluctuate due to sensor activities. During traffic fluctuations the novel Optimised grids algorithm can be used to re-optimise the wireless sensor network to bring further benefits in energy reduction and improvement in QoS parameters. As the idle energy becomes dominant at lower traffic loads, the new Sleep Optimised grids model incorporates the sleep energy and idle energy duty cycles that can be implemented to achieve further network lifetime gains in all wireless sensor network models. Another key advantage of the novel Optimised grids algorithm is that it can be implemented with existing energy saving protocols like GAF, LEACH, SMAC and TMAC to further enhance the network lifetimes and improve on QoS parameters. The novel Optimised grids algorithm does not interfere with these protocols, but creates an overlay to optimise the grids sizes and hence transmission range of wireless sensor nodes.

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In this paper we examine the relation between ownership structure and operating performance for European maritime firms. Using a sample of 266 firm-year observations, during the period 2002–2004, we provide evidence that operating performance is positively related with foreign held shares and investment corporation held shares, indicating better investor protection from managerial opportunism. We also find no relation between operating performance and employee held shares, suggesting no relation between employee commitment and firms’ economic performance. Furthermore, we find no relation between operating performance and government held shares, indicating that government may not adequately protect shareholders’ interests from managerial opportunism. Finally, we do find a positive relation between operating performance and portfolio held shares for code law maritime firms but not for common law maritime firms. Results are robust after adjusting for various firm and country risk characteristics. Overall, our results on the importance of the ownership structure are new to this setting and add to a large body of evidence linking ownership characteristics to corporate performance.

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This paper discusses the use of the non-parametric free disposal hull (FDH) and the parametric multi-level model (MLM) as alternative methods for measuring pupil and school attainment where hierarchical structured data are available. Using robust FDH estimates, we show how to decompose the overall inefficiency of a unit (a pupil) into a unit specific and a higher level (a school) component. By a sample of entry and exit attainments of 3017 girls in British ordinary single sex schools, we test the robustness of the non-parametric and parametric estimates. Finally, the paper uses the traditional MLM model in a best practice framework so that pupil and school efficiencies can be computed.

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This paper analyses the determinants of the export propensity of UK small and medium-sized enterprises (SMEs) based on the 2004 Annual Small Business Survey. Particular emphasis is placed upon the relationship between innovation activities (distinguishing product from process innovation) and export performance. In general the data suggest that some 17 per cent of firms within this group sell outside the UK. Businesses that export are also characterized by high levels of innovation activity (43 per cent of exporters innovate in products, 27 per cent innovate in process and 21 per cent innovate in both). When considering product and process innovation independently we find that both impact positively on the decision to export. However, once we consider the interdependence between both innovation activities, we find no robust evidence that process innovation increases the probability to export beyond product innovation.