The control theory of driving suggests that driver distraction can be analyzed as a breakdown of control at three levels. Common approach for analyzing distraction experimentally is to utilize capacity-based measures to assess distraction at the level of operational control. Three driving simulation experiments with 61 participants were organized to evaluate which kind of measures could be used to analyze drivers' tactical visual sampling models and the related effects of distraction while searching textual information on in-car display. The effects of two different text types were evaluated. The utilized capacity-based measures seemed to be insufficient for revealing participants' tactical behaviors or effects of text type. The measures of workload or performance did not indicate reliably the differences found between participants' visual sampling strategies or which text type is better for enabling safer task timing behaviors. Visual sampling measures did indicate effects of text type on participants' tactical abilities. Differences in participants' visual sampling strategies leading to different levels of systematicity in visual behaviors can explain the variances in visual sampling efficiency. Displays encouraging unsystematic glance allocation behaviors were found potentially the most distracting in relation to safe visual sampling of in-vehicle displays.

1 Institute for Pervasive Computing, Johannes Kepler University, Altenberger Strasse 69, 4040 Linz, Austria 2UCT Research & Design Department, University of Applied Sciences Vorarlberg, Hochschulstrase 1, 6850 Dornbirn, Austria 3Department of Broadcasting Telecommunications and Mass Media, Temple University, Room 203B Annenberg Hall, Main Campus, 1801 N. Broad Street, Philadelphia, PA 19122, USA 4Department for Artificial Intelligence and Interactive Multimedia, Harrow School of Computer Science, University of Westminster, London W1B 2UW, UK

If an interactive form in the worldwide web requires users to select multiple answers from a given list, this can be implemented in several ways. This paper discusses an empirical study with participants, where two interface elements for choosing multiple answers (checkboxes and list boxes) were compared. Results showed that participants chose the same amount of options in both conditions but were faster and more satisfied using checkboxes. The time differences disappeared after several trials, revealing a learning effect for the list box element. As a conclusion, it can be recommended that website developers and online researchers should use checkboxes instead of list boxes for their online forms and questionnaires to enhance usability and user satisfaction—at least for a smaller number of options.

Massively multiplayer online role-playing games (MMORPGs) have great potential as sites for research within the social and human-computer interaction. In the MMORPGs, a stability player taxonomy model is very important for game design. It helps to balance different types of players and improve business strategy of the game. The players in mobile MMORPGs are also connected with social networks; many studies only use the player's own attributes statistics or questionnaire survey method to predict player taxonomy, so lots of social network relations' information will be lost. In this paper, by analyzing the impacts of player's social network, commercial operating data from mobile MMORPGs is used to establish our player taxonomy model (SN model). From the model results, social network-related information in mobile MMORPGs will be considered as important factors to pose this optimized player taxonomy model. As experimental results showed, compared with another player taxonomy model (RA model), our proposed player taxonomy model can achieve good results: classification is more stable.

It is evident that a lot of accidents occur because of drowsiness or inattentiveness of the driver. The logical consequence is that we have to find methods to better analyze the driver. A lot of research has been spent on camera-based systems which focus on the driver's eye gaze or his head movement. But there are few systems that provide camera-free driver analyzing. This is the main goal of the work presented here which is structured in three phases, with the operational goal of having a working driver analyzer implemented in a car. The main question is: is it possible to make statements concerning the driver and his state by using vehicle data from the CAN Bus only? This paper describes the current state of driver analyzing, our overall system architecture, as well as future work. At the moment, we focus on detecting the driving style of a person.

We present the results of an experimental study towards modeling the reader's emotional state variations induced by the typographic elements in electronic documents. Based on the dimensional theory of emotions we investigate how typographic elements, like font style (bold, italics, bold-italics) and font (type, size, color and background color), affect the reader's emotional states, namely, Pleasure, Arousal, and Dominance (PAD). An experimental procedure was implemented conforming to International Affective Picture System guidelines and incorporating the Self-Assessment Manikin test. Thirty students participated in the experiment. The stimulus was a short paragraph of text for which any content, emotion, and/or domain dependent information was excluded. The Analysis of Variance revealed the dependency of (a) all the three emotional dimensions on font size and font/background color combinations and (b) the Pleasure dimension on font type and font style. We introduce a set of mapping rules showing how PAD vary on the discrete values of font style and font type elements. Moreover, we introduce a set of equations describing the PAD dimensions' dependency on font size. This novel model can contribute to the automated reader's emotional state extraction in order, for example, to enhance the acoustic rendition of the documents, utilizing text-to-speech synthesis.

In recent years, electronic services delivered via the World Wide Web have become increasingly important to governments. Substantial investments have been made to provide crucial services and information to citizens, businesses, and governmental institutions. This paper presents the development of a short questionnaire to measure user satisfaction with e-Governmental portals. After two validations of the instrument with federal e-Governmental portals in Switzerland, a final set of 15 items remained that were tested with 2498 participants. The final version showed high internal consistency (Cronbach's ) of .91, good item difficulties (.51 to .82), and discriminatory power coefficients (.49 to .81), as well as a moderate average homogeneity of .47. The survey was translated into five languages.

Stroop interference and facilitation effects were documented in the visual, auditory, olfactory, and gustatory modalities. This study extends the Stroop phenomena also for kinesthetic and haptic tasks. In a touch-enabled computer interface, participants touched and manipulated virtual objects (cylinders, cubes, and tiles), through a pen-like stylus, and identified their haptic qualities (weight, firmness, vibrations). Similarly, participants were stimulated with a mechanical force pushing their hands lightly towards a specific direction which they had to identify. While performing these identification tasks, participants were simultaneously presented with words or symbols that were congruent, neutral, or incongruent with the experienced kinesthetic/haptic sensations. Error rates and response times were affected in the following order: congruent < neutral < incongruent. As technologies advance into multisensory systems, engineers and designers can improve human-computer interactions by ensuring optimal congruence between all the inter- and intra-sensory elements in the display.

Interactive surfaces are only just beginning to break into the market, and they still do not offer the advanced functionality demonstrated with many lab prototypes. The path from a prototype system to a finished product for use in real-world scenarios is a long one, and many obstacles must be overcome. The design of an interactive multitouch table had to address issues like optical recognition, hardware design, and ergonomics. This paper describes in detail the construction of a large, robust multi-touch table called mrT. It will show how to solve major problems of the diffuse illumination technique and other challenges of constructing a large-screen, high-resolution, self-contained interactive multitouch surface that not only serves as a development system but can be deployed in the real-world. Additionally, to further motivate some of the design decisions, especially why the diffuse illumination technology was chosen, this paper will discuss related on-going research projects on the application side.

We deal with the topic of segmenting emotion-related (emotional/affective) episodes into adequate units for analysis and automatic processing/classification—a topic that has not been addressed adequately so far. We concentrate on speech and illustrate promising approaches by using a database with children's emotional speech. We argue in favour of the word as basic unit and map sequences of words on both syntactic and ‘‘emotionally consistent” chunks and report classification performances for an exhaustive modelling of our data by mapping word-based paralinguistic emotion labels onto three classes representing valence (positive, neutral, negative), and onto a fourth rest (garbage) class.