Aperiodic Extended Surface Perturbations in the Ising Model

We study the influence of an aperiodic extended surface perturbation on the surface critical behaviour of the two-dimensional Ising model in the extreme anisotropic limit. The perturbation decays as a power of the distance from the free surface with an oscillating amplitude following some aperiodic sequence. The asymptotic density is 1/2 so that the mean ampltitude vanishes. The relevance of the perturbation is discussed by combining scaling arguments of Cordery and Burkhardt for the Hilhorst-van Leeuwen model and Luck for aperiodic perturbations. The relevance-irrelevance criterion involves the decay exponent of the perturbation, the wandering exponent which governs the fluctuation of the sequence and the bulk correlation length exponent. Analytical results are obtained for the surface magnetization which displays a rich variety of critical behaviours. The results are checked through a numerical finite-size-scaling study. They show that second-order effects must be taken into account in the discussion of the relevance-irrelevance criterion. The scaling behaviours of the first gap and the surface energy are also discussed.Comment: 13 pages, 13 figures, LaTeX2e, EPJ macro

Deliberate ignorance in project risk management

The management of project risk is considered a key discipline by most organisations involved in projects. Best practice project risk management processes are claimed to be self-evidently correct. However, project risk management involves a choice between which information is utilized and which is deemed to be irrelevant and hence excluded. Little research has been carried out to ascertain the manifestation of barriers to optimal project risk management such as 'irrelevance'; the deliberate inattention of risk actors to risk. This paper presents the results of a qualitative study of IT project managers, investigating their reasons for deeming certain known risks to be irrelevant. The results both confirm and expand on Smithson's [Smithson, M., 1989. Ignorance and Uncertainty. Springer-Verlag, New York] taxonomy of ignorance and uncertainty and in particular offer further context related insights into the phenomenon of 'irrelevance' in project risk management. We suggest that coping with 'irrelevance' requires defence mechanisms, the effective management of relevance as well as the setting of, and sticking to priorities. (C) 2009 Elsevier Ltd and IPMA. All rights reserved

A Distribution Separation Method Using Irrelevance Feedback Data for Information Retrieval

In many research and application areas, such as information retrieval and machine learning, we often encounter dealing with a probability distribution which is mixed by one distribution that is relevant to our task in hand and the other that is irrelevant and we want to get rid of. Thus, it is an essential problem to separate the irrelevant distribution from the mixture distribution. This paper is focused on the application in Information Retrieval, where relevance feedback is a widely used technique to build a refined query model based on a set of feedback documents. However, in practice, the relevance feedback set, even provided by users explicitly or implicitly, is often a mixture of relevant and irrelevant documents. Consequently, the resultant query model (typically a term distribution) is often a mixture rather than a true relevance term distribution, leading to a negative impact on the retrieval performance. To tackle this problem, we recently proposed a Distribution Separation Method (DSM), which aims to approximate the true relevance distribution by separating a seed irrelevance distribution from the mixture one. While it achieved a promising performance in an empirical evaluation with simulated explicit irrelevance feedback data, it has not been deployed in the scenario where one should automatically obtain the irrelevance feedback data. In this article, we propose a substantial extension of the basic DSM from two perspectives: developing a further regularization framework and deploying DSM in the automatic irrelevance feedback scenario. Specifically, in order to avoid the output distribution of DSM drifting away from the true relevance distribution when the quality of seed irrelevant distribution (as the input to DSM) is not guaranteed, we propose a DSM regularization framework to constrain the estimation for the relevance distribution. This regularization framework includes three algorithms, each corresponding to a regularization strategy incorporated in the objective function of DSM. In addition, we exploit DSM in automatic (i.e., pseudo) irrelevance feedback, by automatically detecting the seed irrelevant documents via three different document re-ranking methods. We have carried out extensive experiments based on various TREC data sets, in order to systematically evaluate the proposed methods. The experimental results demonstrate the effectiveness of our proposed approaches in comparison with various strong baselines

On the relevance of earnings components in valuation and forecasting

Pre-print also submitted to SSRN Archive. The final publication is available at Springer via http://dx.doi.org/ 10.1007/s11156-013-0347-yThis paper articulates the links between relevance of an earnings component in forecasting (abnormal) earnings and its relevance in valuation in a nonlinear framework. The analysis shows that forecasting relevance does not imply valuation relevance even though valuation irrelevance is implied by forecasting irrelevance. Firstly, I consider an accounting information system where earnings components "add up" to a fully informative earnings number. Secondly, I analyze two accounting systems where a "core" earnings component is the relevant earnings construct for valuation and the second earnings component is irrelevant but may be predictable and relevant in forecasting other accounting items. I find that dividend displacement effect on earnings and the dynamics of individual earnings components are critical in this analysis

The Continued Relevance of the Irrelevance-of-Motive Maxim

The irrelevance-of-motive maxim-the longstanding principle that a defendant\u27s motives are irrelevant to criminal liability-has come under attack. Critics of this maxim claim that motives, under any plausible conception of the term, are in fact relevant in the criminal law. According to these critics, the only way to defend the truth of the irrelevance-of-motive maxim is to render it true by definition, by defining motive as the subcategory of intentions that are irrelevant to criminal liability. This Note defends the irrelevance-of-motive maxim by applying a plausible conception of motive that conforms to the historical meaning of the term. With the proper definition in place, the irrelevance-of-motive maxim can be understood as stating a valid principle of criminal law, defied only by the advent of a certain kind of bias crime legislation