14 resultados para mutual mistake

em Aston University Research Archive


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An unsupervised learning procedure based on maximizing the mutual information between the outputs of two networks receiving different but statistically dependent inputs is analyzed (Becker S. and Hinton G., Nature, 355 (1992) 161). By exploiting a formal analogy to supervised learning in parity machines, the theory of zero-temperature Gibbs learning for the unsupervised procedure is presented for the case that the networks are perceptrons and for the case of fully connected committees.

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Discusses the implications for the doctrine of common mistake of the Court of Appeal ruling in Great Peace Shipping Ltd v Tsavliris Salvage (International) Ltd on whether a contract for the hire of a ship was void on the ground of common mistake regarding the position of the ship. Reviews the origins of the doctrine of common mistake and the relationship between the doctrine and the implication of terms. Considers the determination of impossibility. Examines the role of equity in common mistake and remedial equitable intervention.

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Purpose – The purpose of this paper is to examine students’ perceptions of managerial mistakes and why (and why not) managers admit mistakes. Design/methodology/approach – This paper provides a reflective account of how students’ perceive management mistakes and deal with admitting “mea culpa” – “I am to blame”. Findings – The findings show a range of attitudes: they highlight the intermingling pressures associated with the cultural environment and mistakes; they identify media characteristics and its influences on mistakes and mea culpa; they highlight ceremonial processes and tasks that shape and influence the declaration of mea culpa; and they identify how the psychology and sociology of mistakes confronts and affects students. Taken together, the study highlights the varying degrees of wariness that is carried forward by the students from vicariously learning about management mistakes. Originality/value – This paper links up with recent discussions on retail failure and retail pedagogy. It is hoped that this paper will encourage more academics to address, and engage with, management mistakes creatively in their teaching.

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The focus of this paper is on the doctoral research training experienced by one of the authors and the ways in which the diverse linguistic and disciplinary perspectives of her two supervisors (co-authors of this paper) mediated the completion of her study. The doctoral candidate is a professional translator/interpreter and translation teacher. The paper describes why and how she identified her research area and then focused on the major research questions in collaboration with her two supervisors, who brought their differing perspectives from the field of linguistics to this translation research, even though they are not translators by profession or disciplinary background and do not speak Korean. In addition, the discussion considers the focus, purpose and theoretical orientation of the research itself (which addressed questions of readability in translated English-Korean texts through detailed analysis of a corpus and implications for professional translator training) as well as the supervisory and conceptual processes and practices involved. The authors contend that doctoral research of this kind can be seen as a mutual learning process and that inter-disciplinary research can make a contribution not only to the development of rigorous research in the field of translation studies but also to the other disciplinary fields involved.

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This is the first study to provide comprehensive analyses of the relative performance of both socially responsible investment (SRI) and Islamic mutual funds. The analysis proceeds in two stages. In the first, the performance of the two categories of funds is measured using partial frontier methods. In the second stage, we use quantile regression techniques.By combining two variants of the Free Disposal Hull (FDH) methods (order-m and order-?) in the first stage of analysis and quantile regression in the second stage, we provide detailed analyses of the impact of different covariates across methods and across different quantiles. In spite of the differences in the screening criteria and portfolio management of both types of funds, variation in the performance is only found for some of the quantiles of the conditional distribution of mutual fund performance. We established that for the most inefficient funds the superior performance of SRI funds is significant. In contrast, for the best mutual funds this evidence vanished and even Islamic funds perform better than SRI.These results show the benefits of performing the analysis using quantile regression.

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We investigate the behaviour of the mutual friction force in finite temperature quantum turbulence in 4He, paying particular attention to the role of quantized vortex reconnections. Through the use of the vortex filament model, we produce three experimentally relevant types of vortex tangles in steady-state conditions, and examine through statistical analysis, how local properties of the tangle influence the mutual friction force. Finally, by monitoring reconnection events, we present evidence to indicate that vortex reconnections are the dominant mechanism for producing areas of high curvature and velocity leading to regions of high mutual friction, particularly for homogeneous and isotropic vortex tangles.

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This is the first study to provide comprehensive analyses of the relative performance of both socially responsible investment (SRI) and Islamic mutual funds. The analysis proceeds in two stages. In the first, the performance of the two categories of funds is measured using partial frontier methods. In the second stage, we use quantile regression techniques. By combining two variants of the Free Disposal Hull (FDH) methods (order- m and order- α) in the first stage of analysis and quantile regression in the second stage, we provide detailed analyses of the impact of different covariates across methods and across different quantiles. In spite of the differences in the screening criteria and portfolio management of both types of funds, variation in the performance is only found for some of the quantiles of the conditional distribution of mutual fund performance. We established that for the most inefficient funds the superior performance of SRI funds is significant. In contrast, for the best mutual funds this evidence vanished and even Islamic funds perform better than SRI. These results show the benefits of performing the analysis using quantile regression. © 2013 Elsevier B.V.

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Efficiency in the mutual fund (MF), is one of the issues that has attracted many investors in countries with advanced financial market for many years. Due to the need for frequent study of MF's efficiency in short-term periods, investors need a method that not only has high accuracy, but also high speed. Data envelopment analysis (DEA) is proven to be one of the most widely used methods in the measurement of the efficiency and productivity of decision making units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper uses neural network back-ropagation DEA in measurement of mutual funds efficiency and shows the requirements, in the proposed method, for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of a large set of MFs. Copyright © 2014 Inderscience Enterprises Ltd.

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Legislation: Law of Property (Miscellaneous Provisions) Act 1989 (c.34) s.2 Case: Healey v Brown [2002] W.T.L.R. 849 (Ch D) Paper looks at the use of mutual wills in practice. An empirical survey of probate solicitors is carried out and the results analysed. Significantly most solicitors seem, unaware of the controversial ruling as regards mutual wills in Healey v Brown and the impact of S.2 Law of Property Miscellaneous Provisions Act 1989 where land is concerned. Unsuprisingly the survey demonstrates that mutual wills are not commonly used and tend to be avoided by practising solicitors.

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In this paper, we focus on the design of bivariate EDAs for discrete optimization problems and propose a new approach named HSMIEC. While the current EDAs require much time in the statistical learning process as the relationships among the variables are too complicated, we employ the Selfish gene theory (SG) in this approach, as well as a Mutual Information and Entropy based Cluster (MIEC) model is also set to optimize the probability distribution of the virtual population. This model uses a hybrid sampling method by considering both the clustering accuracy and clustering diversity and an incremental learning and resample scheme is also set to optimize the parameters of the correlations of the variables. Compared with several benchmark problems, our experimental results demonstrate that HSMIEC often performs better than some other EDAs, such as BMDA, COMIT, MIMIC and ECGA. © 2009 Elsevier B.V. All rights reserved.

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Using the path-integral technique we examine the mutual information for the communication channel modeled by the nonlinear Schrödinger equation with additive Gaussian noise. The nonlinear Schrödinger equation is one of the fundamental models in nonlinear physics, and it has a broad range of applications, including fiber optical communications - the backbone of the internet. At large signal-to-noise ratio we present the mutual information through the path-integral, which is convenient for the perturbative expansion in nonlinearity. In the limit of small noise and small nonlinearity we derive analytically the first nonzero nonlinear correction to the mutual information for the channel.

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Two new methodologies are introduced to improve inference in the evaluation of mutual fund performance against benchmarks. First, the benchmark models are estimated using panel methods with both fund and time effects. Second, the non-normality of individual mutual fund returns is accounted for by using panel bootstrap methods. We also augment the standard benchmark factors with fund-specific characteristics, such as fund size. Using a dataset of UK equity mutual fund returns, we find that fund size has a negative effect on the average fund manager’s benchmark-adjusted performance. Further, when we allow for time effects and the non-normality of fund returns, we find that there is no evidence that even the best performing fund managers can significantly out-perform the augmented benchmarks after fund management charges are taken into account.