18 resultados para Modal Assurance Criterion

em Aston University Research Archive


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Relationships between clustering, description length, and regularisation are pointed out, motivating the introduction of a cost function with a description length interpretation and the unusual and useful property of having its minimum approximated by the densest mode of a distribution. A simple inverse kinematics example is used to demonstrate that this property can be used to select and learn one branch of a multi-valued mapping. This property is also used to develop a method for setting regularisation parameters according to the scale on which structure is exhibited in the training data. The regularisation technique is demonstrated on two real data sets, a classification problem and a regression problem.

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Online model order complexity estimation remains one of the key problems in neural network research. The problem is further exacerbated in situations where the underlying system generator is non-stationary. In this paper, we introduce a novelty criterion for resource allocating networks (RANs) which is capable of being applied to both stationary and slowly varying non-stationary problems. The deficiencies of existing novelty criteria are discussed and the relative performances are demonstrated on two real-world problems : electricity load forecasting and exchange rate prediction.

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In this paper, a co-operative distributed process mining system (CDPMS) is developed to streamline the workflow along the supply chain in order to offer shorter delivery times, more flexibility and higher customer satisfaction with learning ability. The proposed system is equipped with the ‘distributed process mining’ feature which is used to discover the hidden relationships among each working decision in distributed manner. This method incorporates the concept of data mining and knowledge refinement into decision making process for ensuring ‘doing the right things’ within the workflow. An example of implementation is given, based on the case of slider manufacturer.

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Conventional feed forward Neural Networks have used the sum-of-squares cost function for training. A new cost function is presented here with a description length interpretation based on Rissanen's Minimum Description Length principle. It is a heuristic that has a rough interpretation as the number of data points fit by the model. Not concerned with finding optimal descriptions, the cost function prefers to form minimum descriptions in a naive way for computational convenience. The cost function is called the Naive Description Length cost function. Finding minimum description models will be shown to be closely related to the identification of clusters in the data. As a consequence the minimum of this cost function approximates the most probable mode of the data rather than the sum-of-squares cost function that approximates the mean. The new cost function is shown to provide information about the structure of the data. This is done by inspecting the dependence of the error to the amount of regularisation. This structure provides a method of selecting regularisation parameters as an alternative or supplement to Bayesian methods. The new cost function is tested on a number of multi-valued problems such as a simple inverse kinematics problem. It is also tested on a number of classification and regression problems. The mode-seeking property of this cost function is shown to improve prediction in time series problems. Description length principles are used in a similar fashion to derive a regulariser to control network complexity.

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Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.

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The work constitutes a study of the strength of mild steel fillet welds subject to static loading, and the behaviour of flange welded beam-column connections under combined bending and shear. Tests are conducted on short welds in the as-welded and stress relieved conditions, and also on full-size beam-column connections. It is shown that welds under compression have a lower strength than when under tension. Failure of the fillet weld is initiated at the weld root, the important factor controlling the initiation being weld ductility. The greater the residual stress, the lower the weld ductility and ultimate strength. Thermal stress relieving increases strength by as much as 30%. Weld failure plane is rarely at the throat and varies from 0° to 45° depending upon loading condition. Failure plane average stresses are related by a circular function which is expressed in terms of externally applied forces at limit state. The tension weld of a flange-welded beam-column connection always fails before the compression weld. The shear load sharing between the welds is a complex function of elastic compression of the web, elastic/plastic deformation of the flanges, load/deformation characteristics, and the type of load application. Bearing forces between the compression flange and column face produce low level bearing stresses and frictional forces which make a negligible contribution to shear load resistance. Three modes of connection failure are possible; 'end mode', 'bending mode' and 'shear mode', with a sudden change taking place between the two latter.

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Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.

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We report what we believe to be the first experimental study of inter-modal cross-gain modulation and associated transient effects as different spatial modes and wavelength channels are added and dropped within a two-mode amplifier for SDM transmission.

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We report what we believe to be the first experimental study of inter-modal cross-gain modulation and associated transient effects as different spatial modes and wavelength channels are added and dropped within a two-mode amplifier for SDM transmission.

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Spatial objects may not only be perceived visually but also by touch. We report recent experiments investigating to what extent prior object knowledge acquired in either the haptic or visual sensory modality transfers to a subsequent visual learning task. Results indicate that even mental object representations learnt in one sensory modality may attain a multi-modal quality. These findings seem incompatible with picture-based reasoning schemas but leave open the possibility of modality-specific reasoning mechanisms.

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Background: There is evidence showing that men and women differ with regard to the processing of emotional information. However, the mechanisms behind these differences are not fully understood. Method: The sample comprised of 275 (167 female) right-handed, healthy participants, recruited from the community. We employed a customized affective priming task, which consisted of three subtests, differing in the modality of the prime (face, written word, and sound). The targets were always written words of either positive or negative valence. The priming effect was measured as reaction time facilitation in conditions where both prime and target were emotional (of the same positive or negative valence) compared with conditions where the emotional targets were preceded by neutral primes. Results: The priming effect was observed across all three modalities, with an interaction of gender by valence: the priming effect in the emotionally negative condition in male participants was stronger compared with females. This was accounted for by the differential priming effect within the female group where priming was significantly smaller in the emotionally negative conditions compared with the positive conditions. The male participants revealed a comparable priming effect across both the emotionally negative and positive conditions. Conclusion: Reduced priming in negative conditions in women may reflect interference processes due to greater sensitivity to negative valence of stimuli. This in turn could underlie the gender-related differences in susceptibility to emotional disorders.

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An optical in-fiber modal interferometer-based volume strain sensor for earthquake prediction is proposed and experimentally demonstrated. The sensing element is formed by wrapping a multimode-singlemode-multimode fiber structure onto a polyurethane hollow column. Due to the modal interference between the excited guided modes in the fiber, strong interference pattern could be observed in the transmission spectrum. Theoretical analysis verifies that the resonant wavelength shifts as a result of the volume strain variation caused by the column deformation with square root relationship. Sensitivity > 3.93 pm/με within the volume strain ranging from 0 to 1300 με is also experimentally demonstrated. By taking the response of bidirectional change of volume strain and the sluggish character of the employed sensing material into consideration, the sensing system presents good repeatability and stability. © 2001-2012 IEEE.

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In this paper, we investigate the impact of inter-modal four-wave mixing on mode- and wavelength-division-multiplexing systems. A set of coupled nonlinear Schrödinger equations, including linear mode coupling, is derived allowing to isolate the inter-modal four-wave mixing terms. The efficiency of inter-modal four-wave mixing between degenerate LP modes is found to be significantly higher than the intra-modal four-wave mixing efficiency. However, it is shown that the inter-modal four-wave mixing efficiency between degenerate modes is significantly reduced by the linear mode coupling.