Customer information system data pre-processing with feature selection techniques for non-technical losses prediction in an electricity market

Non-technical losses (NTL) identification and prediction are important tasks for many utilities. Data from customer information system (CIS) can be used for NTL analysis. However, in order to accurately and efficiently perform NTL analysis, the original data from CIS need to be pre-processed before any detailed NTL analysis can be carried out. In this paper, we propose a feature selection based method for CIS data pre-processing in order to extract the most relevant information for further analysis such as clustering and classifications. By removing irrelevant and redundant features, feature selection is an essential step in data mining process in finding optimal subset of features to improve the quality of result by giving faster time processing, higher accuracy and simpler results with fewer features. Detailed feature selection analysis is presented in the paper. Both time-domain and load shape data are compared based on the accuracy, consistency and statistical dependencies between features.

Mutation analysis to verify feature matrices for isolating errors in simulation models

Software simulation models are computer programs that need to be verified and debugged like any other software. In previous work, a method for error isolation in simulation models has been proposed. The method relies on a set of feature matrices that can be used to determine which part of the model implementation is responsible for deviations in the output of the model. Currrently these feature matrices have to be generated by hand from the model implementation, which is a tedious and error-prone task. In this paper, a method based on mutation analysis, as well as prototype tool support for the verification of the manually generated feature matrices is presented. The application of the method and tool to a model for wastewater treatment shows that the feature matrices can be verified effectively using a minimal number of mutants.

Critical feature analysis of a radiotherapy machine

The software implementation of the emergency shutdown feature in a major radiotherapy system was analyzed, using a directed form of code review based on module dependences. Dependences between modules are labelled by particular assumptions; this allows one to trace through the code, and identify those fragments responsible for critical features. An `assumption tree' is constructed in parallel, showing the assumptions which each module makes about others. The root of the assumption tree is the critical feature of interest, and its leaves represent assumptions which, if not valid, might cause the critical feature to fail. The analysis revealed some unexpected assumptions that motivated improvements to the code.

Introduction: special issue on key debates in advertising

Research on advertising has been conducted mainly from within disciplines such as marketing and reception studies. Within translation studies, research has focused more on comparative analysis of language pairs for intersystemic differences, and more recently on intercultural differences in product appeal and cultural values. Advertising as text type was most comprehensively used and developed within Western cultures, then 'exported' to other cultures. Initially the assumption was that the message could be translated and the product would sell on the basis of Western value-based market research, although this is now clearly shown not to be the case, as contributors to this volume all demonstrate through empirical studies. The introduction to this volume offers a comprehensive survey of work done in the field, both within and outside translation studies, outlines the use of semiotics as a suitable framework for research, and summarizes the key issues relating to the global vs. local debate

Evaluating the effectiveness of Bayesian feature selection

A practical Bayesian approach for inference in neural network models has been available for ten years, and yet it is not used frequently in medical applications. In this chapter we show how both regularisation and feature selection can bring significant benefits in diagnostic tasks through two case studies: heart arrhythmia classification based on ECG data and the prognosis of lupus. In the first of these, the number of variables was reduced by two thirds without significantly affecting performance, while in the second, only the Bayesian models had an acceptable accuracy. In both tasks, neural networks outperformed other pattern recognition approaches.

Data visualization with simultaneous feature selection

Data visualization algorithms and feature selection techniques are both widely used in bioinformatics but as distinct analytical approaches. Until now there has been no method of measuring feature saliency while training a data visualization model. We derive a generative topographic mapping (GTM) based data visualization approach which estimates feature saliency simultaneously with the training of the visualization model. The approach not only provides a better projection by modeling irrelevant features with a separate noise model but also gives feature saliency values which help the user to assess the significance of each feature. We compare the quality of projection obtained using the new approach with the projections from traditional GTM and self-organizing maps (SOM) algorithms. The results obtained on a synthetic and a real-life chemoinformatics dataset demonstrate that the proposed approach successfully identifies feature significance and provides coherent (compact) projections. © 2006 IEEE.

Its in her eyes? A barometer for EU accession through female perceptions of role portrayals in advertising:a cross-cultural study of Ukraine and Turkey?

This article examines female response to gender role portrayals in advertising for Ukraine and Turkey. Being both new potential EU candidates, we argue that gender stereotype could also be used as a \u2018barometer\u2019 of progress and closure towards a more generally accepted EU behaviour against women. While their history remains different, both from a political and society values point of views, constraints are currently being faced that require convergence or justification of practices and understanding. Principal components analysis is employed over 290 questionnaires to identify the underlying dimensions. Results indicate overall similarities in perceptions, fragmentation within groups, but seem to provide divergence regarding thresholds.

Personal uses and perceived social and economic effects of advertising in Bulgaria and Romania

Purpose - The objective of this paper is to uncover the underlying dimensions of, and examine the similarities and differences in, personal uses of advertising, perceived socio-economic effects of advertising, and consumer beliefs and attitudes toward advertising in Bulgaria and Romania. Moreover, it aims to identify the relative importance of the predictors of attitudes toward advertising in the two countries. Design/methodology/approach - The paper draws upon findings of previous research and theoretical developments by Bauer and Greyser, Sandage and Leckenby, and Pollay and Mittal. The study uses a stratified random sample of 947 face-to-face interviews with adult respondents from major urban areas in Bulgaria (507) and Romania (440). Variables are measured on multi-item scales as a typical application of the reflective indicator model. Findings - Results show that there are significant differences between Romanian and Bulgarian respondents in terms of their attitudes toward advertising. Romanians are more positive about advertising as an institution than the instruments of advertising. Romanians seem to accept the role of advertising in a free market economy, but have less confidence in advertising claims and techniques. Bulgarian respondents seem more sceptical toward advertising in general and are less enthusiastic about embracing the role of advertising as an institution. Moreover, Bulgarians are highly negative towards the instruments advertising uses to convey its messages to consumers. Research limitations/implications - The research findings reflect the views of urban dwellers and may not be generalisable to the wider population of the two countries. Interviewer bias was reduced by eliminating verbal or non-verbal cues to the respondents, and by the use of stratified random sampling. Practical implications - The paper suggests that the regulatory role of codes of advertising practice and industry regulating bodies should be enhanced, and their ability to protect consumers enforced. Marketing campaigns should be more inclusive to involve diverse social groups and reflect generally-accepted social norms. Originality/value - This study reveals that, while general attitudes toward advertising may be similar, attitudes toward the institution and instruments of advertising may differ even in countries with geographic proximity and low cultural distance. © Emerald Group Publishing Limited.