In this work we propose novel markers for identifying at-risk gamblers based on the concept of sustainability. The first hypothesis here verified is that problematic gamblers oscillate between intervals of increasing wager size followed by rapid drops, probably because they exceed their economic sustainability limits. Due to the non-periodic nature of these fluctuations, the proposed marker detects a certain occurring feature, such as a rapid drop in wager size, over a wide range of fluctuation periods, drop sizes and shapes. The second marker, counting the number of games the gambler is involved in, aims at predicting possible consequences of an exceeding amount of time dedicated to gambling, that ultimately causes social and relational breakdowns. In the experimental phase we demonstrate how the adoption of these markers allows for identifying larger segments of high- and medium-risk gamblers with respect to previous research on actual betting behaviours

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Effective encoding and indexing of audiovisual documents are two key aspects for enhancing the multimedia user experience. In this paper we propose the embedding of low-level content descriptors into a scalable video coding bit-stream by jointly optimizing encoding and indexing performance. This approach provides a new type of bit-stream where part of the information is used for both content encoding and content description, allowing the so called ”Midstream Content Access”. To support this concept, a novel technique based on the appropriate combination of Vector Quantization and Scalable Video Coding has been developed and evaluated. More specifically, the key-pictures of each video GOP are encoded at a first draft level by using an optimal visual-codebook, while the residual errors are encoded using a conventional approach. The same visual-codebook is also used to encode all the key pictures of a video shot, which boundaries are dynamically estimated. In this way, the visual-codebook is freely available as an efficient visual descriptor of the considered video shot. Moreover, since a new visual-codebook is introduced every time a new shot is detected, also an implicit temporal segmentation is provided

With the increasing popularity of repositories of personal images, the problem of effective encoding and retrieval of similar image collections has become very important. In this paper we propose an efficient method for the joint scalable encoding of image-data and visual-descriptors, applied to collections of similar images. From the generated compressed bit stream, it is possible to extract and decode the visual information at different granularity levels, enabling the so called "Midstream Content Access". The proposed approach is based on the appropriate combination of Vector Quantization (VQ) and JPEG2000 image coding. Specifically, the images are encoded at a first draft level using an optimal visual-codebook, while the residual errors are encoded using a JPEG2000 approach. In this way, the codebook of the VQ is freely available as an efficient visual descriptor of the considered image collection. This scalable representation supports fast browsing and retrieval of image collections providing also a coding efficiency comparable with those of standard image coding methods.