Abstract
This article presents European-based contributions for wireless power transmission (WPT), related to applications ranging from future Internet of Things (IoT) and fifth-generation (5G) systems to high-power electric vehicle charging. The contributors are all members of a European consortium on WPT, COST Action IC1301. WPT is the driving technology that will enable the next stage in the current consumer electronics revolution, including batteryless sensors, passive RF identification (RFID), passive wireless sensors, the IoT, and machine-to-machine solutions. The article discusses the latest developments in research by some of the members of this group.

Abstract
Mars and the Moon are envisaged as major destinations of future space exploration missions in the upcoming decades. Imaging LIDARs are seen as a key enabling technology in the support of autonomous guidance, navigation and control operations, as they can provide very accurate, wide range, high-resolution distance measurements as required for the exploration missions. Imaging LIDARs can be used at critical stages of these exploration missions, such as descent and selection of safe landing sites, rendezvous and docking manoeuvres, or robotic surface navigation and exploration. Despite these devices have been commercially available and used for long in diverse metrology and ranging applications, their size, mass and power consumption are still far from being suitable and attractive for space exploratory missions. Here, we describe a compact Single-Pixel Imaging LIDAR System that is based on a compressive sensing technique. The application of the compressive codes to a DMD array enables compression of the spatial information, while the collection of timing histograms correlated to the pulsed laser source ensures image reconstruction at the ranged distances. Single-pixel cameras have been compared with raster scanning and array based counterparts in terms of noise performance, and proved to be superior. Since a single photodetector is used, a better SNR and higher reliability is expected in contrast with systems using large format photodetector arrays. Furthermore, the event of failure of one or more micromirror elements in the DMD does not prevent full reconstruction of the images. This brings additional robustness to the proposed 3D imaging LIDAR. The prototype that was implemented has three modes of operation. Range Finder: Outputs the average distance between the system and the area of the target under illumination; Attitude Meter: Provides the slope of the target surface based on distance measurements in three areas of the target; 3D Imager: Produces 3D ranged images of the target surface. The implemented prototype demonstrated a frame rate of 30 mHz for 16x16 pixels images, a transversal (xy) resolution of 2 cm at 10 m for images with 64x64 pixels and the range (z) resolution proved to be better than 1 cm. The experimental results obtained for the "3D imaging" mode of operation demonstrated that it was possible to reconstruct spherical smooth surfaces. The proposed solution demonstrates a great potential for: Miniaturization; increase spatial resolution without using large format detector arrays; eliminate the need for scanning mechanisms; implementing simple and robust configurations. © 2014 SPIE.

Abstract
Innovation is a driver of economic growth, wealth and prosperity. On the other hand, corruption emerges as a worldwide problem responsible for sapping resources, inequality, human suffering and poverty. This study hypothesizes that national culture, measured using Hofstede 's six cultural dimensions, have an impact on corruption and innovation, and that highly corrupt nations are less innovative. Data were obtained from Hofstede's, Transparency International, and Global Innovation websites for the year 2012. The findings support the claim that most national culture aspects have an impact on corruption, although their impact on innovation is less measurable. Corruption was found to have a strong and negative effect on innovation. Our results draw attention to the usefulness of Hofstede's six-dimension framework in research and the need for further analysis on how corruption influences innovation through mechanisms other than national culture.

Abstract
The problem of selecting learning algorithms has been studied by the meta-learning community for more than two decades. One of the most important task for the success of a meta-learning system is gathering data about the learning process. This data is used to induce a (meta) model able to map characteristics extracted from different data sets to the performance of learning algorithms on these data sets. These systems are built under the assumption that the data are generated by a stationary distribution, i.e., a learning algorithm will perform similarly for new data from the same problem. However, many applications generate data whose characteristics can change over time. Therefore, a suitable bias at a given time may become inappropriate at another time. Although meta-learning has been used to continuously select a learning algorithm in data streams, data characterization has received less attention in this context. In this study, we provide a set of guidelines to support the proposal of characteristics able to describe non-stationary data over time. This guidance considers both the order of arrival of the examples and the type of variables involved in the base-level learning. In addition, we analyze the influence of characteristics regarding their dependence on data morphology. Experimental results using real data streams showed the effectiveness of the proposed data characterization general scheme to support algorithm selection by meta-learning systems. Moreover, the dependent metafeatures provided crucial information for the success of some meta-models.

Abstract
A simple and inexpensive POS for application to light airborne platforms was developed, and a modified Kalman Filtering was designed to integrate GNSS/IMU/Image data, which uses the relative orientation information to improve the accuracy of the exterior orientation parameters. The precise relative orientation of conjugate images was obtained using a SIFT/SFM matching algorithm. The relative exterior orientations were transformed from the camera frame to the navigation frame before they were used as external update information of the Kalman Filter. Combining all the relative orientation information retrieved from images, the Kalman Filter can give an improved output for the exterior orientation parameters. Airborne result from the tests of one straight strip shows that the heading accuracy of a GNSS/MEMS-IMU was improved from 0.26 degrees to 0.10 degrees, and the result from one closed strip shows that heading accuracy was improved from 1.11 degrees to 0.85 degrees and roll accuracy from 0.54 degrees to 0.43 degrees.

Abstract
In this work it is presented a system to help the users to maintain an active lifestyle. Our main objective is to evaluate the current mobile technologies for the development of systems to monitor the users' health and to promote a healthy lifestyle. It was developed a full system, including: an application for smartwatch; an application for smartphone; a back-end with a webservice in PHP. The application provides the functionalities to acquire the user's: heart rate; location, based on the GPS position; the number of steps; the position's elevation; etc. The back-end is used to register the data acquired and processed by the applications. The design was user centric and the development methodology was based on the agile paradigm, for which are described three development iterations.