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Abstract. The number of GPS trajectories recorded daily has been continuously growing in the recent years and new methods to analyse such big data are surfacing all the time. In this paper, we focus on destination prediction, which is useful in various applications like hazard detection and advertisement. We proposed a real-time method for destination prediction of moving users. It uses the current movement trajectory of the user together with historical and regional information to make an accurate prediction. The method is efficient because we can rapidly compute features with the help of spatial and non-spatial indexing methods. We tested the method with real trajectories collected by Mopsi users. The success rate of the method is up to 65 % depending on the length of the recorded trajectory so far, i.e. how long the user has been on move. To our knowledge, this is the first real-time system capable of such success.

Adolescents face difficult developmental tasks and multiple challenges and are exposed to very varied risk factors. In case the protection factors are not strong enough, they can generate many difficulties or emotional and behavioral disorders, especially due to the fragility and vulnerability of the adolescent's inner world during this period. This paper presents an analysis of the protection factors underlying the resilience of young offenders admitted in educational centers in Romania. The analysis is part of a broader research conducted in a doctoral thesis. The conclusions show us that the basic pillar of reeducating these young people relies in completing their studies at least at the level of primary school and the orientation towards learning a profession, so that those who blame material deprivation as the cause of delinquency have the possibility to earn a living through work.