101 resultados para 2447: modelling and forecasting


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Computer Aided Control Engineering involves three parallel streams: Simulation and modelling, Control system design (off-line), and Controller implementation. In industry the bottleneck problem has always been modelling, and this remains the case - that is where control (and other) engineers put most of their technical effort. Although great advances in software tools have been made, the cost of modelling remains very high - too high for some sectors. Object-oriented modelling, enabling truly re-usable models, seems to be the key enabling technology here. Software tools to support control systems design have two aspects to them: aiding and managing the work-flow in particular projects (whether of a single engineer or of a team), and provision of numerical algorithms to support control-theoretic and systems-theoretic analysis and design. The numerical problems associated with linear systems have been largely overcome, so that most problems can be tackled routinely without difficulty - though problems remain with (some) systems of extremely large dimensions. Recent emphasis on control of hybrid and/or constrained systems is leading to the emerging importance of geometric algorithms (ellipsoidal approximation, polytope projection, etc). Constantly increasing computational power is leading to renewed interest in design by optimisation, an example of which is MPC. The explosion of embedded control systems has highlighted the importance of autocode generation, directly from modelling/simulation products to target processors. This is the 'new kid on the block', and again much of the focus of commercial tools is on this part of the control engineer's job. Here the control engineer can no longer ignore computer science (at least, for the time being). © 2006 IEEE.

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Computer Aided Control Engineering involves three parallel streams: Simulation and modelling, Control system design (off-line), and Controller implementation. In industry the bottleneck problem has always been modelling, and this remains the case - that is where control (and other) engineers put most of their technical effort. Although great advances in software tools have been made, the cost of modelling remains very high - too high for some sectors. Object-oriented modelling, enabling truly re-usable models, seems to be the key enabling technology here. Software tools to support control systems design have two aspects to them: aiding and managing the work-flow in particular projects (whether of a single engineer or of a team), and provision of numerical algorithms to support control-theoretic and systems-theoretic analysis and design. The numerical problems associated with linear systems have been largely overcome, so that most problems can be tackled routinely without difficulty - though problems remain with (some) systems of extremely large dimensions. Recent emphasis on control of hybrid and/or constrained systems is leading to the emerging importance of geometric algorithms (ellipsoidal approximation, polytope projection, etc). Constantly increasing computational power is leading to renewed interest in design by optimisation, an example of which is MPC. The explosion of embedded control systems has highlighted the importance of autocode generation, directly from modelling/simulation products to target processors. This is the 'new kid on the block', and again much of the focus of commercial tools is on this part of the control engineer's job. Here the control engineer can no longer ignore computer science (at least, for the time being). ©2006 IEEE.

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This paper proposes a Bayesian method for polyphonic music description. The method first divides an input audio signal into a series of sections called snapshots, and then estimates parameters such as fundamental frequencies and amplitudes of the notes contained in each snapshot. The parameter estimation process is based on a frequency domain modelling and Gibbs sampling. Experimental results obtained from audio signals of test note patterns are encouraging; the accuracy is better than 80% for the estimation of fundamental frequencies in terms of semitones and instrument names when the number of simultaneous notes is two.

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Chapter 20 Clustering User Data for User Modelling in the GUIDE Multi-modal Set- top Box PM Langdon and P. Biswas 20.1 ... It utilises advanced user modelling and simulation in conjunction with a single layer interface that permits a ...

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The universal exhaust gas oxygen (UEGO) sensor is a well-established device which was developed for the measurement of relative air fuel ratio in internal combustion engines. There is, however, little information available which allows for the prediction of the UEGO's behaviour when exposed to arbitrary gas mixtures, pressures and temperatures. Here we present a steady-state model for the sensor, based on a solution of the Stefan-Maxwell equation, and which includes a momentum balance. The response of the sensor is dominated by a diffusion barrier, which controls the rate of diffusion of gas species between the exhaust and a cavity. Determination of the diffusion barrier characteristics, especially the mean pore size, porosity and tortuosity, is essential for the purposes of modelling, and a measurement technique based on identification of the sensor pressure giving zero temperature sensitivity is shown to be a convenient method of achieving this. The model, suitably calibrated, is shown to make good predictions of sensor behaviour for large variations of pressure, temperature and gas composition. © 2012 IOP Publishing Ltd.

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Only very few constructed facilities today have a complete record of as-built information. Despite the growing use of Building Information Modelling and the improvement in as-built records, several more years will be required before guidelines that require as-built data modelling will be implemented for the majority of constructed facilities, and this will still not address the stock of existing buildings. A technical solution for scanning buildings and compiling Building Information Models is needed. However, this is a multidisciplinary problem, requiring expertise in scanning, computer vision and videogrammetry, machine learning, and parametric object modelling. This paper outlines the technical approach proposed by a consortium of researchers that has gathered to tackle the ambitious goal of automating as-built modelling as far as possible. The top level framework of the proposed solution is presented, and each process, input and output is explained, along with the steps needed to validate them. Preliminary experiments on the earlier stages (i.e. processes) of the framework proposed are conducted and results are shown; the work toward implementation of the remainder is ongoing.

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Within strategic technology management and innovation, often stakeholders extrapolate past industry dynamics, trends and patterns into the future. One frequently used concept is that of 'lifecycles' - an analogy of a sequence of stages encountered by living organisms. Lifecycle terms - such as technology, product, industry - are frequently used interchangeably and without clear definition. Within the interdisciplinary context of technology management and forecasting, this juxtaposition of dynamics can create confusion rather than simplification. This paper explores some of the dynamics typically associated with technology-based industries, illustrated with data from the early US automotive industry. A wide range of dimensions are seen to have potential to influence the path of industry development, and technology roadmapping architecture is used to present a simplified visualisation of some of these. Stakeholders need to consider the units of analysis, causality and synchronicity of relevant different dynamics, rather than isolated lifecycles. Some graphical curves represent simple aggregation of components; other dynamics have significant impact, but incur time lags, rather than being superimposed. To optimise alignment of the important dimensions within any technology development, and for future strategy decisions, understanding these interactions is critical. © 2012 Elsevier Inc.

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A novel smoke sensor was used to measure the smoke response to the fuel rack on a diesel engine. The conventional modelling methods used for engine control were investigated. The synchronization technique and Recursive Least Square method were applied to engine modelling and two models for controller design were derived.

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The design, 3D FEM modelling and measurement results of a novel high temperature, low power SOI CMOS MEMS thermal conductivity gas sensor are presented here. The sensor consists of a circular membrane with an embedded tungsten micro-heater. The high sensing capability is based on the temperature sensitivity of the resistive heating element. The sensor was fabricated at a commercial foundry using a 1 μm process and measures only 1×1 mm 2. The circular membrane has a 600 μm diameter while the heating element has a 320 μm diameter. Measurement results show that for a constant power consumption of 75 mW the heater temperature was 562.4°C in air, 565.9°C in N2, 592.5°C for 1 % H2 in Ar and 599.5°C in Ar. © 2013 IEEE.

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Design, FEM modelling and characterization of a novel dual mode thermal conductivity and infrared absorption sensor using SOI CMOS technology is reported. The dual mode sensing capability is based on the temperature sensitivity and wideband infrared radiation emission of the resistive heating element. The sensor was fabricated at a commercial foundry using a 1 μm process and measures only 1×1 mm2. Infrared detectors usually use thermopiles in addition to a separate IR source. A single highly responsive dual mode source and sensing element targeting not only low molecular mass gases but also greenhouse gases, while consuming 40 mW power at 700°C in synthetic air, thus makes this sensor particularly viable for battery powered handheld devices. © 2013 IEEE.