Abstract
An efficient algorithm for dynamically multiplexing MPEG2 encoded video sources is presented. Sources are grouped into classes regarding different combined levels of spatial detail and amount of movement. Simulations were performed using different associations of sources belonging to distinct classes, different bit rates and GOP structures. The implications associated to a real implementation are analyzed and a modular architecture is proposed. Simulation results are presented and discussed, showing that sequences with higher spatial detail and motion are those which exhibit the higher quality improvements. These results are almost not affected by the non alignment, at GOP level, between video sequences.

Abstract
The explosion of interest in consuming rich multimedia content resulted in a growing demand for technologies that enable seamless access over any network using any terminal without affecting the viewing experience. Scalable Video Coding (SVC) is considered to be one of the key technologies that will improve the accessibility to video resources through adapting them at network nodes or destination node at a negligible computational cost. State-of-the-art video coding technologies enable a comprehensive set of scalability options. However, the trade-off of having such enriched set of scalability options is the reduced compression efficiency and increased encoder/decoder complexity. This trade-off can be mitigated if the encoder has prior knowledge of the scalability options and levels that are actually needed at a given time. It is possible to achieve this goal in a closely monitored system, such as a Virtual Collaboration System (VCS), in which users and their usage environment are known. This paper proposes a framework to determine the scalability options and levels for encoding scalable video for a VCS. Simulation results highlight the benefits of the proposed framework.

Abstract
The MPEG experts are currently developing the MPEG-21 set of standards and this includes a framework and specifications for digital rights management (DRM), delivery of quality of services (QoS) over heterogeneous networks and terminals, packaging of multimedia content and other things essential for the infrastructural aspects of multimedia content distribution. Considerable research effort is being applied to these new developments and the capabilities of MPEG-21 technologies to address specific application areas are being investigated. One such application area is broadcasting, in particular the development of digital TV and its services. In more practical terms, digital TV addresses networking, events, channels, services, programs, signaling, encoding, bandwidth, conditional access, subscription, advertisements and interactivity. MPEG-21 provides an excellent framework of standards to be applied in digital TV applications. Within the scope of this research work we describe a new model based on MPEG-21 and its relevance to digital TV: the digital broadcast item model (DBIM). The goal of the DBIM is to elaborate the potential of MPEG-21 for digital TV applications. Within this paper we focus on a general description of the DBIM, quality of service (QoS) management and metadata filtering, digital rights management and also present use-cases and scenarios where the DBIM's role is explored in detail.

Abstract
Universities are continually pursuing ways to adapt their educational practices, looking to develop new learning culture that encourages creativity and active engagement. The adoption of augmented lecture podcast scenarios, based on a content-centric paradigm, looks a promising way to reach a new level of interactivity. This paper analyzes the main advantages provided by this innovative approach comparing it with the traditional podcasting developing model. Additionally, it proposes possible business models based on content distribution and augmentation, to enable wider exploitation of the approach within university environments. © 2012 Infonomics Society.

Abstract
This paper proposes a framework for a virtual classroom application based on a Virtual Collaboration System (VCS), which is being developed under the VISNET II Network of Excellence (NoE)(1), and discusses adaptation technologies that enable seamless access to classroom sessions while intellectual property and digital rights are managed. The proposed virtual classroom framework enables academic institutions to conduct their collaborative lecture series, to which registered students will be able to attend remotely and interactively over the Internet. Furthermore, the general public may also follow the classroom sessions under certain restrictions imposed by the participating institutions. In order to facilitate seamless access to a heterogeneous audience that is composed of users with various preferences and privileges accessing the classroom sessions over different network infrastructures and using terminal devices with diverse capabilities, context-aware content adaptation is required to meet constraints imposed by the usage context and enhance the quality of the user experience. Thus, this paper describes the concepts and functionalities of a context-aware content adaptation platform, that suits the requirements of such multimedia application scenarios. This platform is able to consume low-level contextual information to infer higher-level contexts, and thus decide the need for and type of adaptation operations to be performed upon the content. In this way, it is aimed to meet usage. constraints while also satisfying restrictions imposed by the Digital Rights Management (DRM) to govern the use of protected content.

Abstract
The use of formal probabilistic modelling together with advanced statistical inference in communications engineering, has the potential of providing a powerful workbench for deriving conclusions about the behaviour of systems and sources of data and therefore developing innovative and efficient control and management strategies of communication systems. Targeting the efficient dimensioning of systems and resources in order to make possible the provision of high quality and larger-choice services to the end-users, this paper proposes the use of a Bayesian framework in video broadband communications. In the context of the combined transmission of several good-quality video sources, such as a digital television broadcast service, using VBR video encoding algorithms and based on prior beliefs and statistical models, an intelligent multiplexer is capable of predicting the probable amount of free space and fill it with extra services or increase the quality of the transmitted channels.