An interactive multimedia learning environment for VLSI built with COSMOS

This paper presents Bigger Bits, an interactive multimedia learning environment that teaches students about VLSI within the context of computer electronics. The system was built with COSMOS (Content Oriented semantic Modelling Overlay Scheme), which is a modelling scheme that we developed for enabling the semantic content of multimedia to be used within interactive systems

A user perspective of quality of service in m-commerce

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2004 Springer VerlagIn an m-commerce setting, the underlying communication system will have to provide a Quality of Service (QoS) in the presence of two competing factors—network bandwidth and, as the pressure to add value to the business-to-consumer (B2C) shopping experience by integrating multimedia applications grows, increasing data sizes. In this paper, developments in the area of QoS-dependent multimedia perceptual quality are reviewed and are integrated with recent work focusing on QoS for e-commerce. Based on previously identified user perceptual tolerance to varying multimedia QoS, we show that enhancing the m-commerce B2C user experience with multimedia, far from being an idealised scenario, is in fact feasible if perceptual considerations are employed

COSMOS-7: Video-oriented MPEG-7 scheme for modelling and filtering of semantic content

MPEG-7 prescribes a format for semantic content models for multimedia to ensure interoperability across a multitude of platforms and application domains. However, the standard leaves it open as to how the models should be used and how their content should be filtered. Filtering is a technique used to retrieve only content relevant to user requirements, thereby reducing the necessary content-sifting effort of the user. This paper proposes an MPEG-7 scheme that can be deployed for semantic content modelling and filtering of digital video. The proposed scheme, COSMOS-7, produces rich and multi-faceted semantic content models and supports a content-based filtering approach that only analyses content relating directly to the preferred content requirements of the user

Dynamic selection of a video content adaptation strategy from a Pareto front

This article is available open access through the publisher’s website through the link below. Copyright @ 2008 The Authors.Genetic Algorithms may be used together with Pareto Optimality in the process of selection of a suitable video content adaptation strategy, the former to return best or fittest solutions that have evolved over many generations and the latter to evaluate and rank each generation's solutions against a set of objectives without the need to assign weights to each one. The outcome of this is a Pareto front of optimal strategies, all of which would satisfy the objectives. The distribution of optimal strategies on a Pareto front, however, suggests that there may be a ‘best-fit’ optimal strategy. This article refines the process of selection of an optimal strategy by taking into account this distribution alongside user preferences, video content characteristics and usage history. In order to make the refined process dynamic, it pursues its implementation using Self-Organising Neural Networks

Enriching MPEG-7 user models with content metadata

MPEG-7 is an XML-based standard that provides tools for creating rich and structured multimedia content metadata. However, only an extremely limited range of preferences can be specified for user models and multimedia content metadata created by other parts of the standard cannot be fully exploited. This results in a very incomplete mapping of user models to content models. We present an approach to address the problem by representing user models by means of existing MPEG-7 content description tools

M-commerce perceptual quality of service

Copyright @ 2003 CAiS

XML-based genetic rules for scene boundary detection in a parallel processing environment

Genetic programming is based on Darwinian evolutionary theory that suggests that the best solution for a problem can be evolved by methods of natural selection of the fittest organisms in a population. These principles are translated into genetic programming by populating the solution space with an initial number of computer programs that can possibly solve the problem and then evolving the programs by means of mutation, reproduction and crossover until a candidate solution can be found that is close to or is the optimal solution for the problem. The computer programs are not fully formed source code but rather a derivative that is represented as a parse tree. The initial solutions are randomly generated and set to a certain population size that the system can compute efficiently. Research has shown that better solutions can be obtained if 1) the population size is increased and 2) if multiple runs are performed of each experiment. If multiple runs are initiated on many machines the probability of finding an optimal solution are increased exponentially and computed more efficiently. With the proliferation of the web and high speed bandwidth connections genetic programming can take advantage of grid computing to both increase population size and increasing the number of runs by utilising machines connected to the web. Using XML-Schema as a global referencing mechanism for defining the parameters and syntax of the evolvable computer programs all machines can synchronise ad-hoc to the ever changing environment of the solution space. Another advantage of using XML is that rules are constructed that can be transformed by XSLT or DOM tree viewers so they can be understood by the GP programmer. This allows the programmer to experiment by manipulating rules to increase the fitness of a rule and evaluate the selection of parameters used to define a solution

MC2: A framework and service for MPEG-7 content-modelling communities

This article is available open access through the publisher’s website through the link below. Copyright @ The Author 2012.Harnessing the power of Web communities, the effort on creating metadata can be greatly reduced. Collaborative communities can create, update and maintain content models for multimedia resources more effectively than single users working alone. This paper presents MC2, a framework for MPEG-7 content-modelling communities. MC2 is based on the challenges to collaborative multimedia content modelling reported in the research literature and the results of an experiment undertaken to investigate user behaviour in collaborative content modelling. An MC2 service has also been implemented as a proof of concept for this framework, which is evaluated with a population of users and against the challenges.EPSR