This article presents research on making schoolbook illustrations accessible for students with visual impairment. The MaskGen system was developed to interactively transpose illustrations of schoolbooks into tactile graphics. A methodology was designed to transpose the graphics and prepare them to be displayed on the STReSS 2 , a refreshable tactile device. We experimented different associations of tactile rendering and audio feedbacks to find a model that children with visual impairment could use. We experimented with three scientific graphics (diagram, bar-chart and map) with forty participants: twenty sighted adults, ten adults with visual impairment, and ten children with visual impairment. Results show that the participants with visual impairment liked the tactile graphics and could use them to explore illustrations and answer questions about their content.
Blends of bacterial poly(hydroxybutyrate) (PHB) with poly(hydroxyoctanoate) (PHO) were
prepared by co-dissolving the two polyesters in chloroform and casting the mixture. To probe the question
of blend miscibility, scanning electron microscopy (SEM) observations and differential scanning calorimetry
(DSC) spectra were collected for the blends and blend components as well. It has been observed that
PHB shows no miscibility at all with PHO, resulting in two-phase systems in which the nature of the
continuous phase is composition-dependent. Dynamic mechanical analysis and tensile properties of these
materials were also investigated. The morphology of the blend strongly influences the mechanical behavior.
The mechanical properties of these materials have been predicted from a model involving the percolation
concept. It takes both linear and nonlinear mechanical behaviors into account and allows for the effect
of the lack of adhesion between material domains and/or breakage of one of the component.
Practitioners in many fields of human-computer interaction are now using physiological data to measure different aspects of user experience. The dynamic nature of physiological data offers a continuous window to the users and allows a better understanding of their experience while interacting with a system. However, in order to be truly informative, physiological signals need to be closely linked to users' behaviors and interaction states. This paper presents an analysis method that provides a direct visual interpretation of users' physiological signals when interacting with an interface. The proposed physiological heatmap tool uses eyetracking data along with physiological signals to identify regions where users are experiencing different emotional and cognitive states with a higher frequency. The method was evaluated in an experiment with 44 participants. Results show that physiological heatmaps are able to identify emotionally significant regions within an interface better than standard gaze heatmaps. Applications of the method to different fields of HCI research are also discussed.
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