Alfred Russel Wallace Notes 10: The Impact of A.R. Wallace\u27s Sarawak Law Paper Resurrected

Six assertions that relate to the impact of Wallace’s Sarawak Law paper1 on the development of evolution theory have been proposed and analyzed by John van Wyhe.2 He concluded that they were all erroneous. The analysis presented a valid criticism of some casual and over-confident pronouncements with respect to interpretations of history. More significantly, it is a misguided attempt to expose “original historical meanings,” and thereby dismiss all other interpretations as necessarily incorrect. A re-analysis reveals that, contrary to van Wyhe’s analysis, much of the conventional wisdom is plausibly correct, and it remains the case that “the past is a foreign country,” but it is not another planet

Systematic treatment of failures using multilayer perceptrons

This paper discusses the empirical evaluation of improving generalization performance of neural networks by systematic treatment of training and test failures. As a result of systematic treatment of failures, multilayer perceptron (MLP) discriminants were developed as discrimination techniques. The experiments presented in this paper illustrate the application of discrimination techniques using MLP discriminants to neural networks trained to solve supervised learning task such as the Launch Interceptor Condition 1 problem. The MLP discriminants were constructed from the training and test patterns. The first discriminant is known as the hard-to-learn and easy-to-learn discriminant whilst the second one is known as hard-to-compute and easy-to-compute discriminant. Further treatments were also applied to hard-tolearn (or hard-to-compute) patterns prior to training (or testing). The experimental results reveal that directed splitting or using MLP discriminant is an important strategy in improving generalization of the networks

Improving generalization of neural network using length as discriminant

This paper discusses the empirical evaluation of improving generalization performance of neural networks by systematic treatment of training and test failures. As a result of systematic treatment of failures, a discrimination technique using LENGTH was developed. The experiments presented in this paper illustrate the application of discrimination technique using LENGTH to neural networks trained to solve supervised learning tasks such as the Launch Interceptor Condition 1 problem. The discriminant LENGTH is used to discriminate between the predicted "hard-to-learn" and predicted "easy-to-learn" patterns before these patterns are fed into the networks. The experimental results reveal that the utilization of LENGTH as discriminant has improved the average generalization of the networks increased

Discussion on \u27A.R. Wallace in the Light of Historical Method\u27 by John van Whye

The recent article by historian John van Wyhe purports to identify seventeen ‘myths’ concerning the life and work of naturalist Alfred Russel Wallace. Here we briefly describe what we feel is wrong with them, and refer to published literature that extend these arguments. Our objections do not extend to the ‘historical method’ van Wyhe adopts, but instead to the way he has ignored the criticisms of peers to the extent of not even acknowledging their scholarly articles

A scoping review to catalogue tinnitus problems in children

© 2019 The Authors Background: The reported prevalence of tinnitus in children is similar to that in adults. However, unlike adults, there is relatively little understanding of the tinnitus-related problems children experience. Knowledge of the problems experienced by adults has led to the development of numerous clinical questionnaires used by health professionals in assessment and treatment practices; to date no child-specific questionnaire measure of tinnitus has been developed. To support development of a questionnaire measure of tinnitus in children, the aim of this scoping review was to catalogue the peer-reviewed and grey scientific literature according to 1) the methods used to identify problems experienced by children with tinnitus, 2) tinnitus-related problems observed in or reported by children, and 3) research recommendations suggested by investigators with regards to tinnitus in children. Methods: A scoping review was conducted following an established methodological framework. Records were included where a tinnitus-related problem was reported in a child 18 years or younger, and tinnitus was reported as the primary complaint. Tinnitus problems were extracted and categorised into problem themes. Results: Thirty-five records met the inclusion criteria for this review. Methods used to identify tinnitus-related problems in children, and the number and range of problems reported, varied across the records. Symptom impact was summarised according to six problem themes; Physical health, Cognitive health, Hearing and listening, Emotional health, Quality of life, and Feeling different/isolated. Identified research recommendations highlighted a demand for more standardised approaches. Conclusions: The findings evidence the detrimental impact tinnitus can have on a child's quality of life and emotional wellbeing. The current British Society of Audiology Tinnitus in Children Practice Guidance recommends management practices to address the most broadly reported problems identified in this review; sleep difficulties, emotional difficulties, and concentration and hearing problems at school. Given the finding of this review, we suggest problems relating to the impact of tinnitus on quality of life and feelings of isolation are also important problem domains to consider when managing a child who has tinnitus. Current variability in the approach to identifying children's tinnitus problems underlines the importance of developing a standardised and dedicated measure of tinnitus in children

Getting on to a PhD

Over the last decade, there has been a 25% rise in the number of students applying for doctoral-level study across the UK (Universities UK, 2017). Prior to committing to a PhD, applicants must make an informed decision as to whether working towards a PhD is valuable for them in terms of personal and professional development. By answering some of the most frequent questions asked by PhD applicants, this article aims to de-mystify common myths associated with doctoral-level study

Computing with confidence: a Bayesian approach

Bayes’ rule is introduced as a coherent strategy for multiple recomputations of classifier system output, and thus as a basis for assessing the uncertainty associated with a particular system results --- i.e. a basis for confidence in the accuracy of each computed result. We use a Markov-Chain Monte Carlo method for efficient selection of recomputations to approximate the computationally intractable elements of the Bayesian approach. The estimate of the confidence to be placed in any classification result provides a sound basis for rejection of some classification results. We present uncertainty envelopes as one way to derive these confidence estimates from the population of recomputed results. We show that a coarse SURE or UNSURE confidence rating based on a threshold of agreed classifications works well, not only pinpointing those results that are reliable but also in indicating input data problems, such as corrupted or incomplete data, or application of an inadequate classifier model

Representing classifier confidence in the safety critical domain: an illustration from mortality prediction in trauma cases

Copyright © 2007 Springer Verlag. The final publication is available at link.springer.comThis work proposes a novel approach to assessing confidence measures for software classification systems in demanding applications such as those in the safety critical domain. Our focus is the Bayesian framework for developing a model-averaged probabilistic classifier implemented using Markov chain Monte Carlo (MCMC) and where appropriate its reversible jump variant (RJ-MCMC). Within this context we suggest a new technique, building on the reject region idea, to identify areas in feature space that are associated with "unsure" classification predictions. We term such areas "uncertainty envelopes" and they are defined in terms of the full characteristics of the posterior predictive density in different regions of the feature space. We argue this is more informative than use of a traditional reject region which considers only point estimates of predictive probabilities. Results from the method we propose are illustrated on synthetic data and also usefully applied to real life safety critical systems involving medical trauma data

A Bayesian methodology for estimating uncertainty of decisions in safety-critical systems

Published as chapter in Frontiers in Artificial Intelligence and Applications. Volume 149, IOS Press Book, 2006. Integrated Intelligent Systems for Engineering Design. Edited by Xuan F. Zha, R.J. Howlett. ISBN 978-1-58603-675-1, pp. 82-96. This version deposited in arxiv.orghttp://arxiv.org/abs/1012.0322Uncertainty of decisions in safety-critical engineering applications can be estimated on the basis of the Bayesian Markov Chain Monte Carlo (MCMC) technique of averaging over decision models. The use of decision tree (DT) models assists experts to interpret causal relations and find factors of the uncertainty. Bayesian averaging also allows experts to estimate the uncertainty accurately when a priori information on the favored structure of DTs is available. Then an expert can select a single DT model, typically the Maximum a Posteriori model, for interpretation purposes. Unfortunately, a priori information on favored structure of DTs is not always available. For this reason, we suggest a new prior on DTs for the Bayesian MCMC technique. We also suggest a new procedure of selecting a single DT and describe an application scenario. In our experiments on the Short-Term Conflict Alert data our technique outperforms the existing Bayesian techniques in predictive accuracy of the selected single DTs.Supported by a grant from the EPSRC under the Critical Systems Program, grant GR/R24357/0