Abstract
Limited perception capabilities underwater shrink the envelope of effective localization techniques that can be applied in this environment. Long-term localization in six degrees of freedom can only be achieved by combining different sources of information. A multiple vehicle underwater localization solution, for localizing an underwater mining vehicle and its support vessel, is presented in this paper. The surface vessel carries a short baseline network, that interact with the inverted ultra-short baseline, carried by the underwater mining vehicle. A multiple antenna GNSS system provides data for localizing the surface vessel and to georeference the short baseline array. Localization of the mining vehicle results from a data fusion approach, that combines multiple sources of sensor information using the Extended Kalman Filter (EKF) framework. The developed solutions were applied in the context of the VAMOS! European project. Long-term real time position errors below 0.2 meters, for the underwater machine, and 0.02 meters, for the surface vessel, were accomplished in the field. All presented results are based on data acquired in a real scenario.

Abstract
The load balance aspect of the Container Loading Problem (CLP) has been handled in an simplified way in the literature. Either load balance has been treated as a soft constraint or the geometrical centre of the container has been assumed to be the ideal location for the centre of gravity of the cargo, or both, which does not meet regulatory directives and transportation legislation. In this paper, we treat load balance as a 'hard constraint and adopt vehicle specific diagrams that define the feasibility domain for the location of the centre of gravity of the cargo, according to the vehicle specific technical characteristics, thus fulfilling and complying with real-world regulations and legislation. We propose a multi-population biased random-key genetic algorithm (BRKGA), with a new fitness function that takes static stability and load balance into account. Extensive computational experiments were performed with different variants of the proposed approach. Also solutions taken from the literature were evaluated in terms of load balance. The computational results show that it is possible to obtain stable and load balanced solutions without compromising the performance in terms of container volume utilization, and demonstrate also the advantage in incorporating load balance in the packing generation algorithm.

Abstract
The ex-ante division of consumers into potential off-grid and grid-extension clusters represents a crucial input to electrification planning. This paper explores the application of image processing tools to distinguish grid-expansion from offgrid consumer clusters spatially, considering peak-load surfaces. Instead of point-based cluster analysis, the proposed model induces morphological pixel changes in the image through filtering and segmentation techniques. This way, load clusters can be isolated based on texture and coherence in an unprecedented way. Various single and sequential image processing techniques are compared, together with a rough grid expansion-ratio estimate for each case. Model outcomes are benchmarked against off-grid/on-grid clusters retrieved by using the Rural Electrification Model.

Abstract
Cyber-Physical Systems (CPS) are creating new market opportunities and business models for all kind of European Industries. CPS-based platforms are increasing in their size and target application areas in a steady manner. However, even if progress is made every day supported by continuous technological advancements, CPS application and deployment is still challenging. Many solutions have been made available or is currently under development in several research projects/initiatives. Typically, these solutions show no interoperability between each other and are tailored to a specific application context. Thus, there is an urgent need for a clear definition of what a CPS-populated system actually is. This will provide a common ground for designing and building interoperable CPS-populated systems. Interoperability represents one of the most challenging problems for such systems essentially due to their intrinsic characteristics: heterogeneity, distribution and networked. These must be addressed to allow the cooperation and collaboration between all the actors of the system. In this landscape, the MANTIS project is aimed to provide a reference model for interoperable and interconnected CPS-populated systems for maintenance-related ecosystems, which is the focus of this paper.

Abstract
The article refers to a new model of genetic algorithm. The method used has finality of optimize the filtering of artifacts in DICOM images in two-steps.The first step is constituted by filterings with BM4D, 3d median filter and ellipsoid filter. The second step is formed by the application of operators of simple mutations in the previously recovered image, for that was used: intensity change, gaussian filter and mean filter. As a result, a better performance filter was obtained and which provides an improvement in diagnosis, in diseases assessment and in decisions making by the professional.

Abstract
We study a model of a Cournot duopoly where firms invest in R&D to reduce their production costs. Depending on the parameters, we may find regions with one, two or three Nash equilibria of the investment. Here, we study the effect of the parameters in these regions, in particular, we study the effect of the possible market saturation, the maximum relative cost reduction and the product differentiation, giving special attention to regions with multiple Nash equilibria. We observed that, in general, the competitive region, where both firms invest, is reduced as we increase the possible market saturation and the differentiation of the products and is enlarged when we increase the maximum relative cost reduction. © 2018, Springer International Publishing AG, part of Springer Nature.