Renovación de destinos litorales maduros a partir del patrimonio cultural: Plan Costa Blanca Cultura

El destino turístico Costa Blanca se caracteriza por la existencia de una amplia oferta turística y por su situación privilegiada respecto a los mercados potenciales de demanda. En la actualidad, ambas características no son suficientes para garantizar la competitividad de este espacio; en un contexto turístico enormemente dinámico en el que la diversidad de elementos de atracción y la imagen del destino puede incidir en la decisión de viaje de los turistas. Por ello, ante la necesidad de acometer procesos de renovación del destino Costa Blanca que permitan garantizar la competitividad de la actividad en términos territoriales y económicos, se apuesta por el patrimonio cultural como uno de los argumentos que mayores posibilidades puede ofrecer desde el ámbito de la planificación del destino turístico para diseñar y ejecutar actuaciones encaminadas a la renovación del mismo. Así, la presente comunicación se basa en los principales resultados obtenidos en el Plan Costa Blanca Cultura, con el objetivo de analizar el grado de uso turístico del patrimonio cultural de la provincia de Alicante, para a partir de un diagnóstico previo, proponer estrategias y actuaciones encaminadas al diseño y gestión posterior de productos temáticos de naturaleza cultural. La metodología de trabajo se ha basado entre otras acciones, en la participación de los agentes turísticos y sociales, aspecto que ha llevado a la selección de las líneas de trabajo prioritarias basadas en temas que superarían la dicotomía entre litoral e interior otorgando al patrimonio un papel integrador del territorio, y a la propuesta de un modelo de gestión innovador en el destino Costa Blanca.

Distortion of self-image: risk factor for obesity in children and teenagers

Introduction: Self-image is important in the behaviour and lifestyle of children and adolescents. Analysing the self-image they have and the factors that might influence their distortion, can be used to prevent problems of obesity and anorexia. The main objective of present publication was to analyse the risk factors that may contribute to self-image distortion. Material and Methods: A descriptive survey study was conducted among 659 children and adolescents in two social classes (low and medium-high), measuring height and weight, calculating BMI percentile for age and gender. Body image and self-perception were registered. Results: The percentage of overweight-obesity is higher in scholars (41.8% boys, 28.7% girls) than in adolescents (30.1% and 22.2% respectively), with no difference between socioeconomic classes. The multinomial logistic regression analysis gives a risk of believing thinner higher (p=0.000) among boys OR=2.9(95%CI:1.43-3.37), school (p=0.000) OR=2.42(95%CI:1.56-3.76) and much lower (p=0.000) between normally nourished OR=0.08(95%CI:0.05-0.13), with no differences according to socioeconomic status. The risk of believing fatter is lower (p=0.000) between boys OR=0.28(95%CI:0.14-0.57), school(p=0.072) OR=0.54(95%CI:0.27-1.6), and much higher among underweight (p=0.000) OR=9x108(95% CI:4x108-19x108). Conclusions: Are risk factors of believing thinner: males, being in a group of schoolchildren and overweight-obesity. Conversely, are risk factors of believing fatter: females, teen and above all, be thin.

A Novel Prediction Method for Early Recognition of Global Human Behaviour in Image Sequences

Human behaviour recognition has been, and still remains, a challenging problem that involves different areas of computational intelligence. The automated understanding of people activities from video sequences is an open research topic in which the computer vision and pattern recognition areas have made big efforts. In this paper, the problem is studied from a prediction point of view. We propose a novel method able to early detect behaviour using a small portion of the input, in addition to the capabilities of it to predict behaviour from new inputs. Specifically, we propose a predictive method based on a simple representation of trajectories of a person in the scene which allows a high level understanding of the global human behaviour. The representation of the trajectory is used as a descriptor of the activity of the individual. The descriptors are used as a cue of a classification stage for pattern recognition purposes. Classifiers are trained using the trajectory representation of the complete sequence. However, partial sequences are processed to evaluate the early prediction capabilities having a specific observation time of the scene. The experiments have been carried out using the three different dataset of the CAVIAR database taken into account the behaviour of an individual. Additionally, different classic classifiers have been used for experimentation in order to evaluate the robustness of the proposal. Results confirm the high accuracy of the proposal on the early recognition of people behaviours.