António Cunha

Usability Test of 3Dconnexion 3D Mice Versus Keyboard+Mouse in Second Life Undertaken by People with Motor Disabilities due to Medullary Lesions

Abstract The use of keyboard and mouse combinations to navigate 3D environments of virtual worlds requires the coordination of both hands in order for the 2D degrees of motion of the mice to transform into the variety of motions available in a 3D space. Such coordination may pose a challenge to people with motor disabilities. 3D controllers known as “3D mice” are presented by manufacturers as significant interface alternatives. To establish the feasibility of such claims, we have conducted a usability test of two 3D mice marketed by 3Dconnexion, in parallel with a keyboard+mouse test. The 10 participants had motor disabilities due to medullary lesions on vertebrae C5-D11, and performed 13 different tasks in the Second Life virtual world: 5 participants used 3D mice, 5 used keyboard+mouse. We have concluded that 2-3 of the 5 most challenging tasks in the keyboard+mouse combination become less challenging using 3D mice. Participants’ feedback was more positive regarding 3D mice, but with significant differences between mice. Contrary to our initial expectations, the least stable mouse, Space Navigator, originated the best feedback.

Planning of a usability test for 3D controllers in Second Life / OpenSimulator virtual worlds

3D interface devices are being announced as rendering virtual world navigation easier. We have prepared a usability testing framework for two such devices, SpaceNavigator and SpacePilot PRO, manufactured by 3Dconnexion. The paper summarizes the underlying concepts of usability testing and links them to the requirements of a virtual world 3D interface context. We detail the metrics to be employed and the reasoning behind their selection, and the planning which yielded the actual framework to be used for conducting the 3D interface usability tests in the Second Life virtual world.

Intelligent Monitoring of Public Transport Systems - Data Consistency Analysis -

Abstract A major transport company working in a urban environment, in Portugal, has been developing an automatic vehicle location (AVL) system, based on a telemetric system to assist the optimisation of vehicle use, time-tabling and scheduling. The data is used in real time and stored on disk for later statistical analysis. Several factors can corrupt data during acquisition and transmission, and make it impossible to automatically extract useful information. A pre-processing stage is needed to extract inconsistent data. The paper describes a strategy, based on simulation, to pre-process the data in order to analyse data consistency and classify the messages as correct or incorrect.

Machine learning classification methods in hyperspectral data processing for agricultural applications

In agricultural applications hyperspectral imaging is used in cases where differences in spectral reflectance of the examined objects are small. However, the large amount of data generated by hyperspectral sensors requires advance processing methods. Machine learning approaches may play an important role in this task. They are known for decades, but they need high volume of data to compute accurate results. Until recently, the availability of hyperspectral data was a big drawback. It was first used in satellites, later in manned aircrafts and data availability from those platforms was limited because of logistics complexity and high price. Nowadays, hyperspectral sensors are available for unmanned aerial vehicles, which enabled to reach a high volume of data, thus overcoming these issues. This way, the aim of this paper is to present the status of the usage of machine learning approaches in the hyperspectral data processing, with a focus on agriculture applications. Nevertheless, there are not many studies available applying machine learning approach to hyperspectral data for agricultural applications. This apparent limitation was in fact the inspiration for making this survey. Preliminary results using UAV-based data are presented, showing the suitability of machine learning techniques in remote sensed data.

Reassuring the Elderly Regarding the Use of Mobile Devices for Mobility

People facing threats of mobility loss have their self-confidence shaken and tend to reduce their physical activity. As is well-known, the decreased physical activity, particularly for the elderly, is one of the factors that contribute to accelerating the deterioration of their health with consequent loss of autonomy and quality of life. Today, GPS-based technologies available on mobile devices offer many solutions to help guide users around much of the world. However, there are several known factors that act as barriers to the use of these technologies, such as user unfamiliarity with these devices, the complexity of geographical information and the difficulty of typing the origin and destination locations. In this paper we propose a solution for mobile devices that seeks to promote user confidence in daily mobility, especially among the elderly. We present the main system functionalities and the interface design.

Endoscopy — Brief historical survey, developments and therapeutics

Rapid increase of elder population and the appearance of more diseases needs the creation of new medical devices, as minimal invasive as possible. Nowadays, the endoscopic capsule allows good image and much less stress and pain to the patient than traditional endoscopic catheters. The endoscopy to become as developed as today had many improvements. We present on this paper a brief survey of the historical background of equipment developments, some of the most commonly used endoscopic procedures, their drawbacks and virtues.