Abstract

Abstract
Safety-critical cooperative vehicle applications such as platooning, require extensive testing, however, the complexity and cost involved in this process, increasingly demands for realistic simulation tools to ease the validation of such technologies, helping to bridge the gap between development and real-word deployment. In this paper we propose a realistic co-simulation framework for cooperative vehicles, that integrates Gazebo, an advanced robotics simulator, with the OMNeT++ network simulator, over the Robot Operating System (ROS) framework, supporting the simulation of advanced cooperative applications such as platooning, in realistic scenarios.

Abstract
The Second International Workshop on Narrative Extraction from Texts (Text2Story'19 [http://text2story19.inesctec.pt/]) was held on the 14th of April 2019, in conjunction with the 41 st European Conference on Information Retrieval (ECIR 2019) in Cologne, Germany. The workshop provided a platform for researchers in IR, NLP, and design and visualization to come together and share the recent advances in extraction and formal representation of narratives. The workshop consisted of two invited talks, ten research paper presentations, and a poster and demo session. The proceedings of the workshop are available online at http://ceur-ws.org/Vol-2342/

Abstract
With the appearance of innovative virtual reality (VR) technologies, the need to create immersive content arose. Although there are already some non-immersive solutions to address immersive audio-visual content, there are no solutions that allow the creation of immersive multisensory content. This work proposes a novel architecture for a collaborative immersive tool that allows the creation of multisensory VR experiences in real-time, thus promoting the expeditious development, adoption, and use of immersive systems and enabling the building of custom-solutions that can be used in an intuitive manner to support organizations' business initiatives. To validate the presented proposal, two approaches for the authoring tools (Desktop interface and Immersive interface) were subjected to a set of tests and evaluations consisting of a usability study that demonstrated not only the participants' acceptance of the authoring tool but also the importance of using immersive interfaces for the creation of such VR experiences.

Abstract
Serious games are increasingly being used as innovative tool for developing entrepreneurial skills, such as strategic management, leadership, communication, negotiation or decision making. FLIGBY is a serious game that was initially developed with the objective of simulating the business management process and the application of Flow theory in a business context. However, most recently it has been suggested that serious games in general, and FLIGBY in particular, can be used in other contexts, namely in the development of entrepreneurial skills. In this sense, this study tries to verify if the competences developed and evaluated in FLIGBY on the Master Analytics Profiler (MAP) can be used to evaluate the entrepreneurial capacities of the students in the context of the course of entrepreneurship in a higher education institution. The findings indicate that the performance of these students in FLIGBY is very similar to the benchmark with only small oscillations. However, some asymmetries emerged considering the educational and professional experience, such that the students of the management course showed better business-oriented thinking and IT students revealed greater time-management skills. Finally, professional experience has proved to be relevant for making decisions about stress and for the completion of managerial tasks successfully.

Abstract
Soil moisture (SM) at three depths (15, 25, and 30 cm), derived from the optical trapezoidal model (OPTRAM), was used for multiyear, multisite monitoring of agricultural droughts over two agricultural crops (Maize and Soybean) in southern Mozambique. The OPTRAM was implemented using satellite data from Sentinel-2 and was validated against field SM assessed by gravimetric methods and by Watermark Sensors in sandy-soils with very low water holding capacity (0.13 cm(3)/cm(3)). The OPTRAM model estimated the SM at 15 and 25 cm yielding a R-2 >= 0.79 and RMSE <= 0.030 cm(3)/cm(3). The OPTRAM-derived SM was successfully used as input to compute and map the soil water deficit index, an indicator of agricultural drought. The results indicate that OPTRAM can provide useful information to improve water productivity in cropland under the specific conditions of Mozambique agricultural systems and for early warning systems development. (C) 2019 Society of Photo-Optical Instrumentation Engineers (SPIE)