9 resultados para input method


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The complexity of sustainable development means that it is often difficult to evaluate and communicate the concept effectively. One standard method to reduce complexity and improve Communication, while maintaining scientific objectivity, is to use selected indicators. The aim of this paper is to describe and evaluate a process Of public participation in the selection of sustainable development indicators that utilised the Q-method for discourse analysis. The Q-method was Utilised to combine public opinion with technical expertise to create a list of technically robust indicators that would be relevant to the public, The method comprises statement collection, statement analysis, Q-sorts and Q-sort analysis. The results of the Q-method generated a list of statements for which a preliminary list of indicators was then developed by a team of experts from the fields of environmental science, sustainable development and Psychology. Subsequently members of the public evaluated the preliminary list of indicators, to select a final list of indicators that were both technically sound and incorporated the views of the public. The Utilisation of the Q-method in this process was evaluated using previously published criteria. The application of the Q-method in this context needs to be considered not only by the quality of the indicators developed, but also from the perspective of the benefit of the process to the participants. it was concluded that the Q-method provided an effective framework for public participation in the selection of indicators as it allowed the public to discuss Sustainable development in familiar language and in the context of their daily lives. By combining this information with expert input, a list of technically robust indicators that resonate with the public was developed. The results demonstrated that many citizens are not aware Of Sustainable development, and if it is to be successfully communicated to them, then indicators and policy need to be couched in terms familiar and relevant to citizen and communities. (C) 2009 Elsevier Ltd. All rights reserved.

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A significant part of the literature on input-output (IO) analysis is dedicated to the development and application of methodologies forecasting and updating technology coefficients and multipliers. Prominent among such techniques is the RAS method, while more information demanding econometric methods, as well as other less promising ones, have been proposed. However, there has been little interest expressed in the use of more modern and often more innovative methods, such as neural networks in IO analysis in general. This study constructs, proposes and applies a Backpropagation Neural Network (BPN) with the purpose of forecasting IO technology coefficients and subsequently multipliers. The RAS method is also applied on the same set of UK IO tables, and the discussion of results of both methods is accompanied by a comparative analysis. The results show that the BPN offers a valid alternative way of IO technology forecasting and many forecasts were more accurate using this method. Overall, however, the RAS method outperformed the BPN but the difference is rather small to be systematic and there are further ways to improve the performance of the BPN.

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A self-tuning filter is disclosed. The self-tuning filter includes a digital clocking signal and an input coupled to the digital clocking signal, whereby the input reads a value incident on the input when the digital clocking signal changes to a predetermined state. A clock-tunable filter is, furthermore, coupled to the digital clocking signal so that the frequency of the clock-tunable filter is adjusted in relation to a sampling frequency at which the digital clocking signal operates. The self-tuning filter may be applied to an input of a data acquisition unit and applied to an input having a variable sampling frequency. A method of controlling the frequency of a clock-tunable filter is also disclosed.

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Massively parallel networks of highly efficient, high performance Single Instruction Multiple Data (SIMD) processors have been shown to enable FPGA-based implementation of real-time signal processing applications with performance and
cost comparable to dedicated hardware architectures. This is achieved by exploiting simple datapath units with deep processing pipelines. However, these architectures are highly susceptible to pipeline bubbles resulting from data and control hazards; the only way to mitigate against these is manual interleaving of
application tasks on each datapath, since no suitable automated interleaving approach exists. In this paper we describe a new automated integrated mapping/scheduling approach to map algorithm tasks to processors and a new low-complexity list scheduling technique to generate the interleaved schedules. When applied to a spatial Fixed-Complexity Sphere Decoding (FSD) detector
for next-generation Multiple-Input Multiple-Output (MIMO) systems, the resulting schedules achieve real-time performance for IEEE 802.11n systems on a network of 16-way SIMD processors on FPGA, enable better performance/complexity balance than current approaches and produce results comparable to handcrafted implementations.

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Capillary-based systems for measuring the input impedance of musical wind instruments were first developed in the mid-20th century and remain in widespread use today. In this paper, the basic principles and assumptions underpinning the design of such systems are examined. Inexpensive modifications to a capillary-based impedance measurement set-up made possible due to advances in computing and data acquisition technology are discussed. The modified set-up is able to measure both impedance magnitude and impedance phase even though it only contains one microphone. In addition, a method of calibration is described that results in a significant improvement in accuracy when measuring high impedance objects on the modified capillary-based system. The method involves carrying out calibration measurements on two different objects whose impedances are well-known theoretically. The benefits of performing two calibration measurements (as opposed to the one calibration measurement that has been traditionally used) are demonstrated experimentally through input impedance measurements on two test objects and a Boosey and Hawkes oboe. © S. Hirzel Verlag · EAA.

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Plastic wastes, and particularly plastic bags and sachets, are a major concern for urban and rural environment in African countries. In the last years some actions have been started for the plastic recycling like the artisanal production of paving blocks with melted plastic bags and sand, albeit with differences in production processes. Nevertheless, the environmental and economic impact of such activities is still to be confirmed. The aim of this study is to propose a methodology for assessing and comparing the environmental and energetic performances of artisanal methods, and for defining the overall quality of the produced blocks. This methodology has been shaped through the analysis of
production processes operated by artisans/small enterprises in West Africa and through physic-mechanical tests on the blocks. A questionnaire which allows an insight into the process and on the product has been developed and tested over five processes. Results show that a high input energy level is observed through all the processes, while considerable savings of energy could be achieved. Moreover, tests results confirmed the importance of the utilised plastic concerning thermal dilatation, mechanical resistance at higher temperature and cooling-shrinkage effects. In conclusion, doubts remain about the technical and environmental effectiveness of the sampled experiences, durability of the products and sustainability of this approach. Nevertheless, being the collection and recycling of plastic wastes a potential income generation activity for marginalised social groups in urban environment, a process optimisation could improve the impact of blocks production. Alternative recycling activities should also be considered.

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An experimental investigation is carried out to verify the feasibility of using an instrumented vehicle to detect and monitor bridge dynamic parameters. The low-cost method consists of the use of a moving vehicle fitted with accelerometers on its axles. In the laboratory experiment, the vehicle–bridge interaction model consists of a scaled two-axle vehicle model crossing a simply supported steel beam. The bridge model also includes a scaled road surface profile. The effects of varying the vehicle model configuration and speed are investigated. A finite element beam model is calibrated using the experimental results, and a novel algorithm for the identification of global bridge stiffness is validated. Using measured vehicle accelerations as input to the algorithm, the beam stiffness is identified with a reasonable degree of accuracy.

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We have designed software that can â€â€™look’’ at recorded ultrasound sequences. We analyzed fifteen video sequences representing recorded ultrasound scans of nine fetuses. Our method requires a small amount of user labelled pixels for processing the first frame. These initialize GrowCut 1 , a background removal algorithm, which was used for separating the fetus from its surrounding environment (segmentation). For each subsequent frame, user input is no longer necessary as some of the pixels will inherit labels from the previously processed frame. This results in our software’s ability to track movement. Two sonographers rated the results of our computer’s â€vision’ on a scale from 1 (poor fit) to 10 (excellent fit). They assessed tracking accuracy for the entire video as well as segmentation accuracy (the ability to identify fetus from non-fetus) for every 100th processed frame. There was no appreciable deterioration in the software’s ability to track the fetus over time. I