Active control comparisons: the ideal trial design

This report describes the concept for a clinical trial that uses carbamazepine as the gold-standard active control for a study of newly diagnosed patients. The authors describe an endpoint including efficacy and tolerability, and a stopping rule that uses a series of interim analyses in order to reach a conclusion as efficiently as possible without sacrificing reliability.

Robust neurofuzzy rule base knowledge extraction and estimation using subspace decomposition combined with regularization and D-optimality

A new robust neurofuzzy model construction algorithm has been introduced for the modeling of a priori unknown dynamical systems from observed finite data sets in the form of a set of fuzzy rules. Based on a Takagi-Sugeno (T-S) inference mechanism a one to one mapping between a fuzzy rule base and a model matrix feature subspace is established. This link enables rule based knowledge to be extracted from matrix subspace to enhance model transparency. In order to achieve maximized model robustness and sparsity, a new robust extended Gram-Schmidt (G-S) method has been introduced via two effective and complementary approaches of regularization and D-optimality experimental design. Model rule bases are decomposed into orthogonal subspaces, so as to enhance model transparency with the capability of interpreting the derived rule base energy level. A locally regularized orthogonal least squares algorithm, combined with a D-optimality used for subspace based rule selection, has been extended for fuzzy rule regularization and subspace based information extraction. By using a weighting for the D-optimality cost function, the entire model construction procedure becomes automatic. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.

Neurofuzzy design and model construction of nonlinear dynamical processes from data

A common problem in many data based modelling algorithms such as associative memory networks is the problem of the curse of dimensionality. In this paper, a new two-stage neurofuzzy system design and construction algorithm (NeuDeC) for nonlinear dynamical processes is introduced to effectively tackle this problem. A new simple preprocessing method is initially derived and applied to reduce the rule base, followed by a fine model detection process based on the reduced rule set by using forward orthogonal least squares model structure detection. In both stages, new A-optimality experimental design-based criteria we used. In the preprocessing stage, a lower bound of the A-optimality design criterion is derived and applied as a subset selection metric, but in the later stage, the A-optimality design criterion is incorporated into a new composite cost function that minimises model prediction error as well as penalises the model parameter variance. The utilisation of NeuDeC leads to unbiased model parameters with low parameter variance and the additional benefit of a parsimonious model structure. Numerical examples are included to demonstrate the effectiveness of this new modelling approach for high dimensional inputs.

A framework for graphic description in book design

This project is concerned with the way that illustrations, photographs, diagrams and graphs, and typographic elements interact to convey ideas on the book page. A framework for graphic description is proposed to elucidate this graphic language of ‘complex texts’. The model is built up from three main areas of study, with reference to a corpus of contemporary children’s science books. First, a historical survey puts the subjects for study in context. Then a multidisciplinary discussion of graphic communication provides a theoretical underpinning for the model; this leads to various proposals, such as the central importance of ratios and relationships among parts in creating meaning in graphic communication. Lastly a series of trials in description contribute to the structure of the model itself. At the heart of the framework is an organising principle that integrates descriptive models from fields of design, literary criticism, art history, and linguistics, among others, as well as novel categories designed specifically for book design. Broadly, design features are described in terms of elemental component parts (micro-level), larger groupings of these (macro-level), and finally in terms of overarching, ‘whole book’ qualities (meta-level). Various features of book design emerge at different levels; for instance, the presence of nested discursive structures, a form of graphic recursion in editorial design, is proposed at the macro-level. Across these three levels are the intersecting categories of ‘rule’ and ‘context’, offering different perspectives with which to describe graphic characteristics. Contextbased features are contingent on social and cultural environment, the reader’s previous knowledge, and the actual conditions of reading; rule-based features relate to the systematic or codified aspects of graphic language. The model aims to be a frame of reference for graphic description, of use in different forms of qualitative or quantitative research and as a heuristic tool in practice and teaching.