Distributed multimedia quality: the user perspective

Distributed multimedia supports a symbiotic infotainment duality, i.e. the ability to transfer information to the user, yet also provide the user with a level of satisfaction. As multimedia is ultimately produced for the education and / or enjoyment of viewers, the user’s-perspective concerning the presentation quality is surely of equal importance as objective Quality of Service (QoS) technical parameters, to defining distributed multimedia quality. In order to extensively measure the user-perspective of multimedia video quality, we introduce an extended model of distributed multimedia quality that segregates quality into three discrete levels: the network-level, the media-level and content-level, using two distinct quality perspectives: the user-perspective and the technical-perspective. Since experimental questionnaires do not provide continuous monitoring of user attention, eye tracking was used in our study in order to provide a better understanding of the role that the human element plays in the reception, analysis and synthesis of multimedia data. Results showed that video content adaptation, results in disparity in user video eye-paths when: i) no single / obvious point of focus exists; or ii) when the point of attention changes dramatically. Accordingly, appropriate technical- and user-perspective parameter adaptation is implemented, for all quality abstractions of our model, i.e. network-level (via simulated delay and jitter), media-level (via a technical- and user-perspective manipulated region-of-interest attentive display) and content-level (via display-type and video clip-type). Our work has shown that user perception of distributed multimedia quality cannot be achieved by means of purely technical-perspective QoS parameter adaptation.

The causal surface and its effect on distribution transparency in a distributed virtual environment

One goal in the development of distributed virtual environments (DVEs) is to create a system such that users are unaware of the distribution-the distribution should be transparent. The paper begins by discussing the general issues in DVEs that might make this possible, and a system that allows some level of distribution transparency is described. The system described suffers from effects of inconsistency, which in turn cause undesirable visual effects. The causal surface is introduced as a solution that removes these visual effects. The paper then introduces two determining factors of distribution transparency relating to user perception and performance. With regard to these factors, two hypotheses are stated relating to the causal surface. A user-trial on forty-five subjects is used to validate the hypotheses. A discussion of the results of the trial concludes that the causal surface solution does significantly improve the distribution transparency in a DVE.

Causal volumes in distributed virtual reality

Research to date has tended to concentrate on bandwidth considerations to increase scalability in distributed interactive simulation and virtual reality systems. This paper proposes that the major concern for latency in user interaction is that of the fundamental limit of communication rate due to the speed of light. Causal volumes and surfaces are introduced as a model of the limitations of causality caused by this fundamental delay. The concept of virtual world critical speed is introduced, which can be determined from the causal surface. The implications of the critical speed are discussed, and relativistic dynamics are used to constrain the object speed, in the same way speeds are bounded in the real world.

Maximising concurrency and scalability in a consistent, causal, distributed virtual reality system, whilst minimising the effect of network delays

The development of large scale virtual reality and simulation systems have been mostly driven by the DIS and HLA standards community. A number of issues are coming to light about the applicability of these standards, in their present state, to the support of general multi-user VR systems. This paper pinpoints four issues that must be readdressed before large scale virtual reality systems become accessible to a larger commercial and public domain: a reduction in the effects of network delays; scalable causal event delivery; update control; and scalable reliable communication. Each of these issues is tackled through a common theme of combining wall clock and causal time-related entity behaviour, knowledge of network delays and prediction of entity behaviour, that together overcome many of the effects of network delay.

Distortion in Distributed Virtual Environments

This paper proposes a solution to the problems associated with network latency within distributed virtual environments. It begins by discussing the advantages and disadvantages of synchronous and asynchronous distributed models, in the areas of user and object representation and user-to-user interaction. By introducing a hybrid solution, which utilises the concept of a causal surface, the advantages of both synchronous and asynchronous models are combined. Object distortion is a characteristic feature of the hybrid system, and this is proposed as a solution which facilitates dynamic real-time user collaboration. The final section covers implementation details, with reference to a prototype system available from the Internet.

Maximising concurrency and scalability in a consistent, causal, distributed virtual reality system, whilst minimising the effect of network delays

The development of large scale virtual reality and simulation systems have been mostly driven by the DIS and HLA standards community. A number of issues are coming to light about the applicability of these standards, in their present state, to the support of general multi-user VR systems. This paper pinpoints four issues that must be readdressed before large scale virtual reality systems become accessible to a larger commercial and public domain: a reduction in the effects of network delays; scalable causal event delivery; update control; and scalable reliable communication. Each of these issues is tackled through a common theme of combining wall clock and causal time-related entity behaviour, knowledge of network delays and prediction of entity behaviour, that together overcome many of the effects of network delays.

A Real-time, Predictive Architecture for Distributed Virtual Reality

User interaction within a virtual environment may take various forms: a teleconferencing application will require users to speak to each other (Geak, 1993), with computer supported co-operative working; an Engineer may wish to pass an object to another user for examination; in a battle field simulation (McDonough, 1992), users might exchange fire. In all cases it is necessary for the actions of one user to be presented to the others sufficiently quickly to allow realistic interaction. In this paper we take a fresh look at the approach of virtual reality operating systems by tackling the underlying issues of creating real-time multi-user environments.

Dietary intakes and food sources of phytoestrogens in the European Prospective Investigation into Cancer and Nutrition (EPIC) 24-hour dietary recall cohort

BACKGROUND/OBJECTIVES: Phytoestrogens are estradiol-like natural compounds found in plants that have been associated with protective effects against chronic diseases, including some cancers, cardiovascular diseases and osteoporosis. The purpose of this study was to estimate the dietary intake of phytoestrogens, identify their food sources and their association with lifestyle factors in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. SUBJECTS/METHODS: Single 24-hour dietary recalls were collected from 36 037 individuals from 10 European countries, aged 35–74 years using a standardized computerized interview programe (EPIC-Soft). An ad hoc food composition database on phytoestrogens (isoflavones, lignans, coumestans, enterolignans and equol) was compiled using data from available databases, in order to obtain and describe phytoestrogen intakes and their food sources across 27 redefined EPIC centres. RESULTS: Mean total phytoestrogen intake was the highest in the UK health-conscious group (24.9 mg/day in men and 21.1 mg/day in women) whereas lowest in Greece (1.3 mg/day) in men and Spain-Granada (1.0 mg/day) in women. Northern European countries had higher intakes than southern countries. The main phytoestrogen contributors were isoflavones in both UK centres and lignans in the other EPIC cohorts. Age, body mass index, educational level, smoking status and physical activity were related to increased intakes of lignans, enterolignans and equol, but not to total phytoestrogen, isoflavone or coumestan intakes. In the UK cohorts, the major food sources of phytoestrogens were soy products. In the other EPIC cohorts the dietary sources were more distributed, among fruits, vegetables, soy products, cereal products, non-alcoholic and alcoholic beverages. CONCLUSIONS: There was a high variability in the dietary intake of total and phytoestrogen subclasses and their food sources across European regions.

The Climate-G testbed: towards large scale distributed data management for climate change

Climate-G is a large scale distributed testbed devoted to climate change research. It is an unfunded effort started in 2008 and involving a wide community both in Europe and US. The testbed is an interdisciplinary effort involving partners from several institutions and joining expertise in the field of climate change and computational science. Its main goal is to allow scientists carrying out geographical and cross-institutional data discovery, access, analysis, visualization and sharing of climate data. It represents an attempt to address, in a real environment, challenging data and metadata management issues. This paper presents a complete overview about the Climate-G testbed highlighting the most important results that have been achieved since the beginning of this project.

P-Prism: a computationally efficient approach to scaling up classification rule induction

Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unseen data. Alternative algorithms have been developed such as the Prism algorithm. Prism constructs modular rules which produce qualitatively better rules than rules induced by TDIDT. However, along with the increasing size of databases, many existing rule learning algorithms have proved to be computational expensive on large datasets. To tackle the problem of scalability, parallel classification rule induction algorithms have been introduced. As TDIDT is the most popular classifier, even though there are strongly competitive alternative algorithms, most parallel approaches to inducing classification rules are based on TDIDT. In this paper we describe work on a distributed classifier that induces classification rules in a parallel manner based on Prism.

Grid computing solutions for distributed repositories of protein folding and unfolding simulations

The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data and a data warehouse. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular we look at two aspects, first how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories --- this is an important and challenging aspect of P-found because the data volumes involved are too large to be centralised. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling new scientific discoveries.