16 resultados para selection methods

em Cambridge University Engineering Department Publications Database


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Designers who want to manufacture a hardenable steel component need to select both the steel and its heat treatment. This project aims to develop a selection methodology for steels and process routes as an aid to designers. Three studies were conducted: - production of software to calculate the "equivalent diameter" and "equivalent Jominy distance" for simple shapes of a steel component; - prediction of semi-empirical Jominy curves (as-cooled) using CCT diagrams and process modelling methods, which were validated by experiment on plain carbon steels; - investigation of tempering of Jominy bars to explore the potential for semi-empirical models for the hardness after tempering.

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Problem of DC link size in a stiff voltage-source inverter for electric drive is described in the paper. Advantages of advanced film capacitor technology over conventional one for DC link application are reviewed. Conventional DC link capacitor selection methods are questioned in view of advanced capacitor technology utilization in stiff voltage-source inverter. For capacitor selection maximum ripple rms current point is shown. DC link ripple current spectrum analysis under modern PWM techniques is presented. Some capacitor selection recommendations are given. The analysis has been aided greatly by computer modeling in PSpice. ©2005 IEEE.

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Computational models of visual cortex, and in particular those based on sparse coding, have enjoyed much recent attention. Despite this currency, the question of how sparse or how over-complete a sparse representation should be, has gone without principled answer. Here, we use Bayesian model-selection methods to address these questions for a sparse-coding model based on a Student-t prior. Having validated our methods on toy data, we find that natural images are indeed best modelled by extremely sparse distributions; although for the Student-t prior, the associated optimal basis size is only modestly over-complete.

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For increasing the usability of a medical device the usability engineering standards IEC 60601-1-6 and IEC 62366 suggest incorporating user information in the design and development process. However, practice shows that integrating user information and the related investigation of users, called user research, is difficult in the field of medical devices. In particular, identifying the most appropriate user research methods is a difficult process. This difficulty results from the complexity of the medical device industry, especially with respect to regulations and standards, the characteristics of this market and the broad range of potential user research methods available from various research disciplines. Against this background, this study aimed at guiding designers and engineers in selecting effective user research methods according to their stage in the design process. Two approaches are described which reduce the complexity of method selection by summarizing the high number of methods into homogenous method classes. These approaches are closely connected to the medical device industry characteristic design phases and therefore provide the possibility of selecting design-phase- specific user research methods. In the first approach potential user research methods are classified after their characteristics in the design process. The second approach suggests a method summarization according to their similarity in the data collection techniques and provides an additional linkage to design phase characteristics. Both approaches have been tested in practice and the results show that both approaches facilitate user research method selection. © 2009 Springer-Verlag.

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Background: There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. Aim. The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. Methods. This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data). Results: The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. Conclusions: A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection. © 2011 Jun et al.

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Almost all material selection problems require that a compromise be sought between some metric of performance and cost. Trade-off methods using utility functions allow optimal solutions to be found for two objective, but for three it is harder. This paper develops and demonstrates a method for dealing with three objectives.

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A novel materials-selection procedure has been developed and implemented in software. The procedure makes use of Materials Selection Charts: a new way of displaying material property data; and performance indices: combinations of material properties which govern performance. Optimization methods are employed for simultaneous selection of both material and shape.

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In most recent substructuring methods, a fundamental role is played by the coarse space. For some of these methods (e.g. BDDC and FETI-DP), its definition relies on a 'minimal' set of coarse nodes (sometimes called corners) which assures invertibility of local subdomain problems and also of the global coarse problem. This basic set is typically enhanced by enforcing continuity of functions at some generalized degrees of freedom, such as average values on edges or faces of subdomains. We revisit existing algorithms for selection of corners. The main contribution of this paper consists of proposing a new heuristic algorithm for this purpose. Considering faces as the basic building blocks of the interface, inherent parallelism, and better robustness with respect to disconnected subdomains are among features of the new technique. The advantages of the presented algorithm in comparison to some earlier approaches are demonstrated on three engineering problems of structural analysis solved by the BDDC method.

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Camera motion estimation is one of the most significant steps for structure-from-motion (SFM) with a monocular camera. The normalized 8-point, the 7-point, and the 5-point algorithms are normally adopted to perform the estimation, each of which has distinct performance characteristics. Given unique needs and challenges associated to civil infrastructure SFM scenarios, selection of the proper algorithm directly impacts the structure reconstruction results. In this paper, a comparison study of the aforementioned algorithms is conducted to identify the most suitable algorithm, in terms of accuracy and reliability, for reconstructing civil infrastructure. The free variables tested are baseline, depth, and motion. A concrete girder bridge was selected as the "test-bed" to reconstruct using an off-the-shelf camera capturing imagery from all possible positions that maximally the bridge's features and geometry. The feature points in the images were extracted and matched via the SURF descriptor. Finally, camera motions are estimated based on the corresponding image points by applying the aforementioned algorithms, and the results evaluated.

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Videogrammetry is an inexpensive and easy-to-use technology for spatial 3D scene recovery. When applied to large scale civil infrastructure scenes, only a small percentage of the collected video frames are required to achieve robust results. However, choosing the right frames requires careful consideration. Videotaping a built infrastructure scene results in large video files filled with blurry, noisy, or redundant frames. This is due to frame rate to camera speed ratios that are often higher than necessary; camera and lens imperfections and limitations that result in imaging noise; and occasional jerky motions of the camera that result in motion blur; all of which can significantly affect the performance of the videogrammetric pipeline. To tackle these issues, this paper proposes a novel method for automating the selection of an optimized number of informative, high quality frames. According to this method, as the first step, blurred frames are removed using the thresholds determined based on a minimum level of frame quality required to obtain robust results. Then, an optimum number of key frames are selected from the remaining frames using the selection criteria devised by the authors. Experimental results show that the proposed method outperforms existing methods in terms of improved 3D reconstruction results, while maintaining the optimum number of extracted frames needed to generate high quality 3D point clouds.© 2012 Elsevier Ltd. All rights reserved.