Abstract
A laser scanner is a popular sensor widely used in industry and mobile robots applications that measures the distance to the sensor on a slice of the plan. This sensor can be used in mobile robots localization task. In this paper, a low cost laser scanner sensor is modelled so that it can be implemented in a simulation environment. The simulation reflects the laser model properties such as target colour dependences, noise, limits and time constraints. A correction of the laser scanner nonlinearities is proposed. The noise spectrum is also addressed.

Abstract
Infotainment applications in vehicles are currently supported both by the in-vehicle platform, as well as by user's smart devices, such as smartphones and tablets. More and more the user expects that there is a continuous service of applications inside or outside of the vehicle, provided in any of these devices (a simple but common example is hands-free mobile phone calls provided by the vehicle platform). With the increasing complexity of 'apps', it is necessary to support increasing levels of Quality of Service (QoS), with varying resource requirements. Users may want to start listening to music in the smartphone, or video in the tablet, being this application transparently 'moved' into the vehicle when it is started. This paper presents an adaptable offloading mechanism, following a service-oriented architecture pattern, which takes into account the QoS requirements of the applications being executed when making decisions.

Abstract

Abstract
New generations of turbines have lower repair and maintenance costs than the previous generation. This is justified by the development of new components and materials. As the power of newer turbines is usually substantially larger, it is possible to get an economy of scale and lower maintenance costs per kW of rated power. This is simply because it is not needed to service a large turbine more often than a small one. New methods of earlier detection of faults are needed. The use of all information from SCADA (Supervisory Control and Data Acquisition) system can be useful, but it is necessary to develop tools to deal with bigger amount of information. Neural networks can help and turn possible new maintenance and operation schemes.

Abstract
This study describes and evaluates an automated technique that exploits the potential of heterogeneous multi-core processor (HMP) systems when customised with respect to the number of cores and L1 cache memory sizes using a field programmable gate array fitted with LEON3 cores at its base. The authors evaluated the real energy consumption of the HMP system tuned for a set of 50 application codes using a data-mining tool for finding code similarities and selecting HMP configurations. The selected HMP system configuration requires a small cache configuration and consumes less energy when compared to a homogeneous system with the same number of cores and only with a very modest increase in execution time. © The Institution of Engineering and Technology 2015.

Abstract
A new methodology for fault detection on wearable medical devices is proposed. The main strategy relies on correctly classifying the captured physiological signals, in order to distinguish whether the actual cause is a wearer health abnormality or a system functional flaw. Data fusion techniques, namely fuzzy logic, are employed to process the captured data, like the electrocardiogram and blood pressure, to increase the trust levels with which diagnostics are made. Concerning the wearer condition, additional information is provided after classifying the set of signals into normal or abnormal (e.g. arrhythmia, chest angina, and stroke). As for the monitoring system, once an abnormal situation is detected in its operation or in the sensors, a set of tests is run to check if actually the wearer shows a degradation of his health condition or if the system is reporting erroneous values.