The increasing literature addressing international mobility of researchers has repeatedly pointed out the lack of empirical data compiled over the last two decades, jeopardizing progress in the understanding of the characteristics and impacts of such human flows. This paper makes a contribution to the field by exploring the extent to which information obtained from researchers' electronic curriculum vitae (CV) may be used to study temporary geographical mobility. We exploit a new type of data set-a comprehensive database of electronic CVs-developing a broad set of cross-discipline mobility indicators to assess the dimensions and characteristics of international research visits among a population of over 10,000 researchers. The sample population is made up of PhD holders working in the regional research system of Andalusia, Spain. Information regarding their international research visits over the last four decades is downloaded from CVs contained in the electronic scientific information system of the region. We assess mobility rates and the characteristics of the temporary mobile population. The analysis of visiting patterns shows significant differences in mobility profiles in terms of frequency, duration and destination of visits, across disciplines, career stages and time periods. The study also shows how different definitions of international mobility lead to substantial variations in cross-discipline mobility rates.
Abstract:The aim of this paper is to determine pillars for fostering nautical tourism based on the beliefs and attitudes that professionals in the sector have towards the particularities and difficulties that the market is going through. To achieve these goals, in-depth interviews structured around 37 questions were carried out with agents of associations and nautical firms, public institutions, and the Chamber of Commerce. The qualitative analysis program NVIVO 11 was used to analyze the content of the gathered data. The findings reveal that the main difficulties are related to normative issues and taxation, illegal supply, and a lack of definition of the nautical tourist profile. This absence of definition causes a vagueness when estimating the total number of nautical tourists that visit a destination. Thus, this affects evaluation of the economic, social, and environmental impact of nautical tourism.
Objectives The quantitative analysis of the medal shares (MSs) in recent Winter Olympic history by sport and country will identify the relevant socioeconomic factors that are likely to derive policy issues. Methods Econometric modeling and concentration indices are used to predict and assess MSs by sport and country. The development of a mathematical routine to convert MSs to counts and the proposal of a modified Herfindahl index has added robustness to the analysis. Results The deviations of the predictions for Vancouver (2010) 〈http://www.vancouver2010.com/〉 from the observed values pinpoint significant factor differences among the sports. Medal concentrations are different by sport in the number of countries and their names. Conclusions Tradition and geography are primary factors affecting the medal‐winning process. Concerning feasible policies for newcomers, nationalization of athletes, development of talent identification systems, and fostering the participation in sports without a “monopolistic” winner could become short ‐ and long‐run successful paths.
The lack of trustworthy sensors makes development of Advanced Driver Assistance System (ADAS) applications a tough task. It is necessary to develop intelligent systems by combining reliable sensors and real-time algorithms to send the proper, accurate messages to the drivers. In this article, an application to detect and predict the movement of pedestrians in order to prevent an imminent collision has been developed and tested under real conditions. The proposed application, first, accurately measures the position of obstacles using a two-sensor hybrid fusion approach: a stereo camera vision system and a laser scanner. Second, it correctly identifies pedestrians using intelligent algorithms based on polylines and pattern recognition related to leg positions (laser subsystem) and dense disparity maps and u-v disparity (vision subsystem). Third, it uses statistical validation gates and confidence regions to track the pedestrian within the detection zones of the sensors and predict their position in the upcoming frames. The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle.
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