Methods for Optimal Work Instruction Delivery: Pictograms v Images

This paper focuses on quantifying the benefits of pictogram based instructions relative to static images for work instruction delivery. The assembly of a stiffened aircraft panel has been used as an exemplar for the work which seeks to address the challenge of identifying an instructional mode that can be location or language neutral while at the same time optimising assembly build times and maintaining build quality. Key performance parameters measured using a series of panel build experiments conducted by two separate groups were: overall build time, the number of subject references to instructional media, the number of build errors and the time taken to correct any mistakes. Overall build time for five builds for a group using pictogram instructions was about 20% lower than for the group using image based instructions. Also, the pictogram group made fewer errors. Although previous work identified that animated instructions result in optimal build times, the language neutrality of pictograms as well as the fact that they can be used without visualisation hardware mean that, on balance, they have broader applicability in terms of transferring assembly knowledge to the manufacturing environment.

Modeling continuous self-report measures of perceived emotion using generalized additive mixed models

Emotion research has long been dominated by the “standard method” of displaying posed or acted static images of facial expressions of emotion. While this method has been useful it is unable to investigate the dynamic nature of emotion expression. Although continuous self-report traces have enabled the measurement of dynamic expressions of emotion, a consensus has not been reached on the correct statistical techniques that permit inferences to be made with such measures. We propose Generalized Additive Models and Generalized Additive Mixed Models as techniques that can account for the dynamic nature of such continuous measures. These models allow us to hold constant shared components of responses that are due to perceived emotion across time, while enabling inference concerning linear differences between groups. The mixed model GAMM approach is preferred as it can account for autocorrelation in time series data and allows emotion decoding participants to be modelled as random effects. To increase confidence in linear differences we assess the methods that address interactions between categorical variables and dynamic changes over time. In addition we provide comments on the use of Generalized Additive Models to assess the effect size of shared perceived emotion and discuss sample sizes. Finally we address additional uses, the inference of feature detection, continuous variable interactions, and measurement of ambiguity.

Toward Unconstrained Ear Recognition From Two-Dimensional Images

Ear recognition, as a biometric, has several advantages. In particular, ears can be measured remotely and are also relatively static in size and structure for each individual. Unfortunately, at present, good recognition rates require controlled conditions. For commercial use, these systems need to be much more robust. In particular, ears have to be recognized from different angles ( poses), under different lighting conditions, and with different cameras. It must also be possible to distinguish ears from background clutter and identify them when partly occluded by hair, hats, or other objects. The purpose of this paper is to suggest how progress toward such robustness might be achieved through a technique that improves ear registration. The approach focuses on 2-D images, treating the ear as a planar surface that is registered to a gallery using a homography transform calculated from scale-invariant feature-transform feature matches. The feature matches reduce the gallery size and enable a precise ranking using a simple 2-D distance algorithm. Analysis on a range of data sets demonstrates the technique to be robust to background clutter, viewing angles up to +/- 13 degrees, and up to 18% occlusion. In addition, recognition remains accurate with masked ear images as small as 20 x 35 pixels.

The Violent Maintenance of the Portuguese Colonial Identity and the Search for a Postcolonial one: literary images of Portugal as a colonial and postcolonial nation

Through the examination of Camões's Os Lusíadas , Sena's Os Grão-Capitães and Saramago's A Jangada de Pedra , this article explores violence as a means of shaping Portuguese identity in different historical contexts, and how these works portray the continued recourse to violence as Portugal moves from colonizing to postcolonial nation.

Making Risk Visible. The role of images in the assessment of (cancer) genetic risk

Whilst analysis of 'risk' (in its many conceptual shapes) has loomed large in both medicine and social sciences over the past 25 years, detailed investigations as to how risk assessments are actually put together (in either lay or professional contexts) are few in number. The studies that are available usually focus on the use of words or everyday conversation in assembling risk. Talking about risk is, of course, important, but what tends to be ignored is the fact that risk can be and is often made visible. For example, it can be made visible through the use of tables, charts, diagrams and various kinds of sophisticated laboratory images. This paper concentrates on the role of such images in the context of a cancer genetics clinic and its associated laboratory. Precisely how these images are tied into the production of risk estimates, how professionals discuss and use such images in clinical work, and how professionals reference them to display facts about risk is the focus of the paper. The paper concludes by highlighting the significance of different kinds of visibility for an understanding of genetic abnormalities and how such differences might impact on the attempts of lay people to get to grips with risk.