Advances in new technologies and the desire to achieve a sustainable and safe energy supply, enable communities to transition from conventional to renewable resources, such as geothermal energy. Perception and acceptance amongst different audiences have a high impact on the feasibility of energy projects, which is an important aspect to analyze. For this reason, this study focuses on describing the level of awareness and acceptance of deep geothermal energy within an educated segment of the population in five European and American countries (Canada, Colombia, Chile, Belgium, and France) at different stages of geothermal development. This study was conducted through an online survey, which was targeted to post-secondary students and professionals. Some of the most significant conclusions are: (1) there is a high degree of awareness of geothermal energy among the respondents in Chile and Canada, a medium level in Belgium and France, and a low one in Colombia; (2) there is a favorable acceptance of a geothermal project in each country, even when hydraulic stimulation is considered; (3) environmental aspects and community safety are the most important issues that must be addressed to support a pilot geothermal project.
In this paper we propose an algorithm to identify sets of the most frequently visited tourist sites. We do this by examining the trajectories followed by tourists and by considering their visits to these sites. We propose a second algorithm that recommends a specific order to visit these sites. To accomplish this task, we consider variables such as tourist preferences, departure and arrival locations, and time constraints. To validate our proposal, a prototype website application was developed, which experiments with real vehicle trajectories in Rio de Janeiro. Although more exhaustive experiments will be required to deal with different possible scenarios, preliminary results show the usefulness of our proposal for displaying sets of neighborhoods frequented by vehicles as they move about a city.Keywords: Tourism, routes, tourist recommender, heuristic algorithms, trajectories, frequent routes. RESUMENEn este artículo se propone un algoritmo para identificar los conjuntos de sitios turísticos más frecuentemente visitados. Para ello se examinan las trayectorias seguidas por turistas y se consideran sus visitas a los sitios turísticos. Se propone un segundo algoritmo que sugiere el orden en el que deben ser visitados los sitios identificados por el primer algoritmo. Para lograr esto se consideran variables como preferencias turísticas, lugar de partida y de llegada y restricciones de tiempo. La propuesta se validó mediante una aplicación web prototipo y se experimentó con trayectorias reales de vehículos en Río de Janeiro. Aunque se requieren experimentos más exhaustivos y se deben considerar otros escenarios, los resultados preliminares mostraron la utilidad de la propuesta al identificar conjuntos de barrios que son frecuentados por los vehiculos a medida que estos se desplazan por la ciudad.
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