A Learning Evaluation for an Immersive Virtual Laboratory for Technical Training applied into a Welding Workshop

ABSTRACT This study aims to explore the results of welding virtual training performance, designed using a learning model based on cognitive and usability techniques, applying an immersive concept focused on person attention. Moreover, it also intended to demonstrate that exits a moderating effect of performance improvement when the user experience is taken as a feed-back for the student. The results can provide important information to increase the operator performance during the training of welding complex machines to reduce accidents and waste of test material. Keywords: Immersion, Training, Usability, Virtual Reality, Weldin

Modeling and predicting pointing errors in two dimensions

Recently, Wobbrock et al. (2008) derived a predictive model of pointing accuracy to complement Fitts ’ law’s predictive model of pointing speed. However, their model was based on one-dimensional (1-D) horizontal movement, while applications of such a model require two dimensions (2-D). In this paper, the pointing error model is investigated for 2-D pointing in a study of 21 participants performing a time-matching task on the ISO 9241-9 ring-of-circles layout. Results show that the pointing error model holds well in 2-D. If univariate endpoint deviation (SDx) is used, regressing on N=72 observed vs. predicted error rate points yields R 2 =.953. If bivariate endpoint deviation (SDx,y) is used, regression yields R 2 =.936. For both univariate and bivariate models, the magnitudes of observed and predicted error rates are comparable. Author Keywords: Pointing error model, Fitts ’ law, metronome, movement time, error prediction, error rates

Modeling of Stimulus-Response Secondary Tasks with Different Modalities while Driving in a Computational Cognitive Architecture

This paper introduces a computational human performance model based upon the queueing network cognitive architecture to predict driver’s eye glances and workload for four stimulus-response secondary tasks (i.e., auditorymanual, auditory-speech, visual-manual, and visual-speech types) while driving. The model was evaluated with the empirical data from 24 subjects, and the percentage of eyes-off-road time and driver workload generated by the model were similar to the human subject data. Future studies aim to extend the types of voice announcements/commands to enable Human-Machine-Interface (HMI) evaluations with a wider range of usability test for in-vehicle infotainment system developments

A laser obstacle detection and avoidance system for manned and unmanned aircraft applications

This paper presents the key design features, the numerical simulations and the experimental ground/flight test activities performed to verify the functionalities of an obstacle detection and avoidance system suitable for various classes of manned and unmanned aircraft. The Laser Obstacle Avoidance and Monitoring (LOAM) system is proposed as one of the key non-cooperative sensors adopted for avoiding obstacles/intruders in the context of a future Sense-and-Avoid (SAA) capability. After a brief description of the system architecture and of the main data processing algorithms, avoidance trajectory generation and performance estimation models are described. A simulation of the avoidance trajectory generation algorithm is performed in a realistic scenario. Additionally, a brief overview of ground and flight test activities performed on various platforms and their main results is also presented. Some of the key aspects of the LOAM Human Machine Interface and Interaction (HMI2) design are also outlined. The demonstrated detection and avoidance performances and the robust trajectory generation algorithm ensure a safe avoidance of all classes of obstacles (i.e. ground and aerial) in all weather conditions and flight phases