A systematic approach for improving the quality of official statistics: Case of Korean information and telecommunication industry

With the rapid growth of information and communication technology (ICT) in Korea, there was a need to improve the quality of official ICT statistics. In order to do this, various factors had to be considered, such as the quality of surveying, processing, and output as well as the reputation of the statistical agency. We used PLS estimation to determine how these factors might influence customer satisfaction. Furthermore, through a comparison of associated satisfaction indices, we provided feedback to the responsible statistics agency. It appears that our model can be used as a tool for improving the quality of official ICT statistics. © 2008 Elsevier B.V. All rights reserved.

Systematic misregistration and the statistical analysis of surface data.

Spatial normalisation is a key element of statistical parametric mapping and related techniques for analysing cohort statistics on voxel arrays and surfaces. The normalisation process involves aligning each individual specimen to a template using some sort of registration algorithm. Any misregistration will result in data being mapped onto the template at the wrong location. At best, this will introduce spatial imprecision into the subsequent statistical analysis. At worst, when the misregistration varies systematically with a covariate of interest, it may lead to false statistical inference. Since misregistration generally depends on the specimen's shape, we investigate here the effect of allowing for shape as a confound in the statistical analysis, with shape represented by the dominant modes of variation observed in the cohort. In a series of experiments on synthetic surface data, we demonstrate how allowing for shape can reveal true effects that were previously masked by systematic misregistration, and also guard against misinterpreting systematic misregistration as a true effect. We introduce some heuristics for disentangling misregistration effects from true effects, and demonstrate the approach's practical utility in a case study of the cortical bone distribution in 268 human femurs.

Does temporal discounting explain unhealthy behavior? A systematic review and reinforcement learning perspective.

The tendency to make unhealthy choices is hypothesized to be related to an individual's temporal discount rate, the theoretical rate at which they devalue delayed rewards. Furthermore, a particular form of temporal discounting, hyperbolic discounting, has been proposed to explain why unhealthy behavior can occur despite healthy intentions. We examine these two hypotheses in turn. We first systematically review studies which investigate whether discount rates can predict unhealthy behavior. These studies reveal that high discount rates for money (and in some instances food or drug rewards) are associated with several unhealthy behaviors and markers of health status, establishing discounting as a promising predictive measure. We secondly examine whether intention-incongruent unhealthy actions are consistent with hyperbolic discounting. We conclude that intention-incongruent actions are often triggered by environmental cues or changes in motivational state, whose effects are not parameterized by hyperbolic discounting. We propose a framework for understanding these state-based effects in terms of the interplay of two distinct reinforcement learning mechanisms: a "model-based" (or goal-directed) system and a "model-free" (or habitual) system. Under this framework, while discounting of delayed health may contribute to the initiation of unhealthy behavior, with repetition, many unhealthy behaviors become habitual; if health goals then change, habitual behavior can still arise in response to environmental cues. We propose that the burgeoning development of computational models of these processes will permit further identification of health decision-making phenotypes.

A systematic approach to materials information management for aerospace design

The materials information requirements of the aerospace sector are considered, specifically 'consolidation' (management of raw test data), 'analysis' (investigation of material trade-offs) and 'dissemination (secure distribution of data throughout an organization). An information architecture that satisfies the complex requirements of the aerospace materials industry is discussed and a case-study is presented. © 2003 by Granta Design Limited. Published by the American Institute of Aeronautics and Astronautics, Inc.