Embedding defeasible logic into logic programming

Defeasible reasoning is a simple but efficient approach to nonmonotonic reasoning that has recently attracted considerable interest and that has found various applications. Defeasible logic and its variants are an important family of defeasible reasoning methods. So far no relationship has been established between defeasible logic and mainstream nonmonotonic reasoning approaches. In this paper we establish close links to known semantics of logic programs. In particular, we give a translation of a defeasible theory D into a meta-program P(D). We show that under a condition of decisiveness, the defeasible consequences of D correspond exactly to the sceptical conclusions of P(D) under the stable model semantics. Without decisiveness, the result holds only in one direction (all defeasible consequences of D are included in all stable models of P(D)). If we wish a complete embedding for the general case, we need to use the Kunen semantics of P(D), instead.

Supervised stationary cycling versus supervised treadmill walking for patients with intermittent claudication: Preliminary results

Introduction: Walking programmes are recommended as part of the initial treatment for intermittent claudication (IC). However, for many patients factors such as frailty, the severe leg discomfort associated with walking and safety concerns about exercising in public areas reduce compliance to such prescription. Thus, there is a need to identify a mode of exercise that provides the same benefits as regular walking while also offering convenience and comfort for these patients. The present study aims to provide evidence for the first time of the efficacy of a supervised cycle training programme compared with a conventional walking programme for the treatment of IC. Methods: Thus far 33 patients have been randomized to: a treadmill-training group (n = 12); a cycle-training group (n = 11); or a control group (n = 10). Training groups participated in three sessions of supervised training per week for a period of 6 weeks. Control patients received no experimental intervention. Maximal incremental treadmill testing was performed at baseline and after the 6 weeks of training. Measures included pain-free (PFWT) and maximal walking time (MWT), continuous heart rate and gas-analysis recording, and ankle-brachial index assessment. Results: In the treadmill trained group MWT increased significantly from 1016.7 523.7 to 1255.2 432.2 s (P < 0.05). MWT tended to increase with cycle training (848.72 333.18 to 939.54 350.35 s, P = 0.14), and remained unchanged in the control group (1555.1 683.23 to 1534.7 689.87 s). For PFWT, there was a non-significant increase in the treadmill-training group from 414.4 262.3 to 592.9 381.9 s, while both the cycle training and control groups displayed no significant change in this time (226.7 147.1 s to 192.3 56.8 and 499.4 503.7 s to 466.0 526.1 s, respectively). Conclusions: These preliminary results might suggest that, unlike treadmill walking, cycling has no clear effect on walking performance in patients with IC. Thus the current recommendations promoting walking based programmes appear appropriate. The present study was funded by the National Heart Foundation of Australia.

An empirical study of Hoelfding Racing for model selction in K-nearest neighbor classification

Racing algorithms have recently been proposed as a general-purpose method for performing model selection in machine teaming algorithms. In this paper, we present an empirical study of the Hoeffding racing algorithm for selecting the k parameter in a simple k-nearest neighbor classifier. Fifteen widely-used classification datasets from UCI are used and experiments conducted across different confidence levels for racing. The results reveal a significant amount of sensitivity of the k-nn classifier to its model parameter value. The Hoeffding racing algorithm also varies widely in its performance, in terms of the computational savings gained over an exhaustive evaluation. While in some cases the savings gained are quite small, the racing algorithm proved to be highly robust to the possibility of erroneously eliminating the optimal models. All results were strongly dependent on the datasets used.

Semi-supervised construction of general visualization hierarchies

We have recently developed a principled approach to interactive non-linear hierarchical visualization [8] based on the Generative Topographic Mapping (GTM). Hierarchical plots are needed when a single visualization plot is not sufficient (e.g. when dealing with large quantities of data). In this paper we extend our system by giving the user a choice of initializing the child plots of the current plot in either interactive, or automatic mode. In the interactive mode the user interactively selects ``regions of interest'' as in [8], whereas in the automatic mode an unsupervised minimum message length (MML)-driven construction of a mixture of GTMs is used. The latter is particularly useful when the plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. We illustrate our approach on a data set of 2300 18-dimensional points and mention extension of our system to accommodate discrete data types.

Semi-supervised learning of hierarchical latent trait models for data visualisation

An interactive hierarchical Generative Topographic Mapping (HGTM) ¸iteH_GTM has been developed to visualise complex data sets. In this paper, we build a more general visualisation system by extending the HGTM visualisation system in 3 directions: bf (1) We generalize HGTM to noise models from the exponential family of distributions. The basic building block is the Latent Trait Model (LTM) developed in ¸iteKaban_pami. bf (2) We give the user a choice of initializing the child plots of the current plot in either em interactive, or em automatic mode. In the interactive mode the user interactively selects ``regions of interest'' as in ¸iteH_GTM, whereas in the automatic mode an unsupervised minimum message length (MML)-driven construction of a mixture of LTMs is employed. bf (3) We derive general formulas for magnification factors in latent trait models. Magnification factors are a useful tool to improve our understanding of the visualisation plots, since they can highlight the boundaries between data clusters. The unsupervised construction is particularly useful when high-level plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. We illustrate our approach on a toy example and apply our system to three more complex real data sets.

Embedding e-portfolios for effective lifelong learning:a case study

Lifelong learning is a ‘keystone’ of educational policies (Faure, 1972) where the emphasis on learning shifts from teacher to learner. Higher Education (HE) institutions should be committed to developing lifelong learning, that is promoting learning that is flexible, diverse and relevant at different times, and in different places, and is pursued throughout life. Therefore the HE sector needs to develop effective strategies to encourage engagement in meaningful learning for diverse student populations. The use of e-portfolios, as a ‘purposeful aggregation of digital items’ (Sutherland & Powell, 2007), can meet the needs of the student community by encouraging reflection, the recording of experiences and achievements, and personal development planning (PDP). The use of e-portfolios also promotes inclusivity in learning as it provides students with the opportunity to articulate their aspirations and take the first steps along the pathway of lifelong learning. However, ensuring the uptake of opportunities within their learning is more complex than the students simply having access to the software. Therefore it is argued here that crucial to the effective uptake and engagement of the e-portfolio is embedding it purposefully within the curriculum. In order to investigate effective implementation of e-portfolios an explanatory case study on their use was carried out, initially focusing on 3 groups of students engaged in work-based learning and professional practice. The 3 groups had e-Portfolios embedded and assessed at different levels. Group 1 did not have the e-Portfolio embedded into their curriculum nor was the e-Portfolio assessed. Group 2 had the e-Portfolio embedded into the curriculum and formatively assessed. Group 3 also had the e-Portfolio embedded into the curriculum and were summatively assessed. Results suggest that the use of e-Portfolios needs to be integral to curriculum design in modules rather than used as an additional tool. In addition to this more user engagement was found in group 2 where the e-Portfolio was formatively assessed only. The implications of this case study are further discussed in terms of curriculum development.

Embodying and embedding children's sleep: some sociological comments and observations

This paper, drawing on our own research findings data, explores the embodiment and embedment of sleeping in children's everyday/night lives. Key themes here include children's attitudes and feelings toward the dormant body, the processes, routines and rituals associated with going to bed and going to sleep, issues associated with bedrooms and privacy, and finally the relationship between dormancy and domicile. This in turn provides the basis, in the remainder of the paper, for a further series of reflections on the mutually informing relations between the sociology of sleep and the sociology of childhood. Remaining questions and challenges involved in researching children's sleep are also considered. Sleep, it is concluded, is not simply a rich and fascinating sociological topic in its own right it also has the potential to shed valuable new light on a significant yet hitherto under-researched part of children's lives, contributing important new insights in doing so.

Vacuum spacetimes of embedding class two

Doubt is cast on the much quoted results of Yakupov that the torsion vector in embedding class two vacuum space-times is necessarily a gradient vector and that class 2 vacua of Petrov type III do not exist. The rst result is equivalent to the fact that the two second fundamental forms associated with the embedding necessarily commute and has been assumed in most later investigations of class 2 vacuum space-times. Yakupov stated the result without proof, but hinted that it followed purely algebraically from his identity: Rijkl Ckl = 0 where Cij is the commutator of the two second fundamental forms of the embedding.From Yakupov's identity, it is shown that the only class two vacua with non-zero commutator Cij must necessarily be of Petrov type III or N. Several examples are presented of non-commuting second fundamental forms that satisfy Yakupovs identity and the vacuum condition following from the Gauss equation; both Petrov type N and type III examples occur. Thus it appears unlikely that his results could follow purely algebraically. The results obtained so far do not constitute denite counter-examples to Yakupov's results as the non-commuting examples could turn out to be incompatible with the Codazzi and Ricci embedding equations. This question is currently being investigated.