Abstract
Deep Learning (DL) has been proven as a powerful recognition method as evidenced by its success in recent computer vision competitions. The most accurate results have been obtained by ensembles of DL models that pool their results. However, such ensembles are computationally costly, making them inapplicable to real-time applications. In this paper, we apply model compression techniques to the problem of semantic segmentation, which is one of the most challenging problems in computer vision. Our results suggest that compressed models can approach the accuracy of full ensembles on this task, combining the diverse strengths of networks of very different architectures, while maintaining real-time performance. (C) 2017 Published by Elsevier Inc.

Abstract
130In the majority of European countries, the evaluation of schools is at the heart of the educational system as a means to guarantee the quality of education. Every year, in most countries around the world, students perform national exams. Their results are analyzed by several stakeholders, including governmental agencies, the media, and researchers on educational issues. At present, advances in information and communication technology (ICT) and data analysis techniques allow schools to make use of massive amounts of data in their daily management. This chapter focuses in particular on the use of students’? data to benchmark schools. It illustrates the potential contribution of the information gathered and analyzed through data analytics to promote the continuous improvement of schools’? educational processes. © 2018 by Taylor & Francis Group, LLC.

Abstract

Abstract
Critical human-machine interfaces are present in many systems including avionics systems and medical devices. Use error is a concern in these systems both in terms of hardware panels and input devices, and the software that drives the interfaces. Guaranteeing safe usability, in terms of buttons, knobs and displays is now a key element in the overall safety of the system. New integrated development environments (IDEs) based on formal methods technologies have been developed by the research community to support the design and analysis of high-confidence human-machine interfaces. To date, little work has focused on the comparison of these particular types of formal IDEs. This paper compares and evaluates two state-of-the-art toolkits: CIRCUS, a model-based development and analysis tool based on Petri net extensions, and PVSio-web, a prototyping toolkit based on the PVS theorem proving system.

Abstract
This paper addresses a critical analysis of the impact of the wind ramp events with unforeseen magnitude in power systems at the very short term, modeling the response of the operational reserve against this type of phenomenon. A multi-objective approach is adopted, and the properties of the Pareto-optimal fronts are analyzed in cost versus risk, represented by a worst scenario of load curtailment. To complete this critical analysis, a study about the usage of the reserve in the event of wind power ramps is performed. A case study is used to compare the numerical results of the models based on stochastic programming and models that take a risk analysis view in the system with high level of wind power. Wind power uncertainty is represented by scenarios qualified by probabilities. The results show that the reliability reserve may not be adequate to accommodate unforeseen wind ramps and therefore the system may be at risk.

Abstract
The direct relationship between national cultural practice and entrepreneurship activities is analyzed in this chapter, based on the analysis of 44 countries. Datasets from 2012 and 2013 Global Entrepreneurship Monitor (GEM) report are used to characterize three types of entrepreneurship: Early-stage entrepreneurial activity (TEA); necessity-driven entrepreneurship (NDE) and opportunity-driven (ODE) entrepreneurship. Data sets on national cultural values are used to analyze five dimensions of Hofstede's work on cultural values (power distance, individualism/collectivism, masculinity/femininity, long/short term orientation, and uncertainty avoidance). For that, the authors use the Values Survey Module 2013, which has been adapted from Hofstede 's previous work from 2010 and 2008. The main conclusion is that the three types of entrepreneurship analyzed in this chapter are differently explained by the cultural and expanded models. If the country of origin and the type of economy are useful to explain TEA, they are of no added value to explain necessity-driven or opportunity-driven entrepreneurship.