This paper proposes the integration of multi-sensorial stimuli and multi-modal interaction components into a sports multimedia asset under two dimensions: immersion and interaction. The first dimension comprises a binaural audio system and a set of sensory effects synchronized with the audiovisual content, whereas the second explores interaction through the insertion of interactive 3D objects into the main screen and on-demand presentation of additional information in a second touchscreen. We present an end-to-end solution integrating these components into a hybrid (internet-broadcast) television system using current 3DTV standards. Results from an experimental study analyzing the perceived quality of these stimuli and their influence in the Quality of Experience are presented. General Terms: Multimedia Information SystemsAdditional Key Words and Phrases: multi-sensorial multi-modal media, immersive media, interactive media, hybrid-based 3DTV, binaural audio, sensory effects, interactive 3D objects integrated into the video scene, second screen, quality of experience. ACM Reference Format:Francisco Pedro Luque, Iris Galloso, Carlos Alberto Martín, Claudio Feijoo and Guillermo Cisneros. 2014. Integration of multisensorial stimuli and multi-modal interaction in a hybrid 3DTV system.
European countries are facing increasing pressures on their water resources despite stringent regulations and systematic efforts on environmental protection. In this context, research and innovation play a strategic role reinforcing the efficiency of water policies. The present study provides a multilevel assessment of research and innovation practices in the field of water resource management in southern European countries and regions (more specifically; Cyprus, Albania, Poitou-Charentes in France, Andalusia in Spain and the North of Portugal). The analysis was based on a strategic framework aimed at gaining an insight of the current constraints, as well as of the existing and future technological solutions for a better water resource management. The triple helix model proved to be a useful analytical framework for assessing the efforts of different groups towards a common goal. The analysis proved the existence of a significant evolution in the use of technological tools to assist decision-making processes in integrated river basin management in all regions. Nevertheless, the absence of formal channels for knowledge and data exchange between researchers and water resource managers complicates the formers involvement in the decision-making process regarding water allocation. Both researchers and consultants emphasize the low availability of data, together with the need to advance on water resource economics as relevant constraints in the field. The SWOT analysis showed similar concerns among the participating regions and provided a battery of effective projects that resulted in the preparation of a Joint Action Plan.
The definition of pedestrian behavior when crossing the street and facing potential collision situations is crucial for the design of new Autonomous Emergency Braking systems (AEB) in commercial vehicles. To this end, this article proposes the generation of classification models through the deployment of machine learning techniques that can predict whether there will be a collision depending on the type of reaction, the lane where it occurs, the visual acuity the level of attention, and consider the most relevant factors that determine the cognitive and movement characteristics of pedestrians. Thereby, the inclusion of this type of model in the decision-making algorithm of the AEB system allows for modulating its response. For this purpose, relevant information on pedestrian behavior is obtained through experiments made in an ad-hoc, Virtual Reality (VR) environment, using a portable backpack system in three urban scenarios with different characteristics. Database generation, feature selection, and k-fold cross-validation generate the inputs to the supervised learning models. A subsequent analysis of the accuracy, optimization, error measurement, variable importance, and classification capability is conducted. The tree-based models provide more balanced results for the performance metrics (with higher accuracy for the single decision tree case) and are more easily interpretable and adaptable to the algorithm. From them it is deduced the high importance of the reaction type and the relative position where it occurs, coinciding with the high significance of these factors in the analyzed collisions.
Uncertainty in thematic maps has been tested mainly in maps with discrete or fuzzy classifications based on spectral data. However, many ecosystem maps in tropical countries consist of discrete polygons containing information on various ecosystem properties such as vegetation cover, soil, climate, geomorphology and biodiversity. The combination of these properties into one class leads to error. We propose a probability-based sampling design with two domains, multiple stages, and stratification with selection of primary sampling units (PSUs) proportional to the richness of strata present. Validation is undertaken through field visits and fine resolution remote sensing data. A pilot site in the center of the Colombian Andes was chosen to validate a government official ecosystem map. Twenty primary sampling units (PSUs) of 10 × 15 km were selected, and the final numbers of final sampling units (FSUs) were 76 for the terrestrial domain and 46 for the aquatic domain. Our results showed a confidence level of 95%, with the accuracy in the terrestrial domain varying between 51.8% and 64.3% and in the aquatic domain varying between 75% and 92%. Governments need to account for uncertainty since they rely on the quality of these maps to make decisions and guide policies.
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