Intelligent multimedia communication for enhanced medical e-collaboration in back pain treatment

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2004 SAGE PublicationsRemote, multimedia-based, collaboration in back pain treatment is an option which only recently has come to the attention of clinicians and IT providers. The take-up of such applications will inevitably depend on their ability to produce an acceptable level of service over congested and unreliable public networks. However, although the problem of multimedia application-level performance is closely linked to both the user perspective of the experience as well as to the service provided by the underlying network, it is rarely studied from an integrated viewpoint. To alleviate this problem, we propose an intelligent mechanism that integrates user-related requirements with the more technical characterization of quality of service, obtaining a priority order of low-level quality of service parameters, which would ensure that user-centred quality of perception is maintained at an optimum level. We show how our framework is capable of suggesting appropriately tailored transmission protocols, by incorporating user requirements in the remote delivery of e-health solutions

Intelligent multimedia transmission for back pain treatment

Copyright @ 2002 EUNITERemote, multimedia-based, collaboration in back pain treatment is an option which only recently has come to the attention of clinicians and IT providers. The take up of such applications will inevitably depend on their ability to produce an acceptable level of service over congested and unreliable public networks However, although the problem of multimedia application-level performance is closely linked to both the user perspective of the experience as well as to the service provided by the underlying network, it is rarely studied from an integrated viewpoint. To alleviate this problem in the context of a multimedia application, a method is proposed in this paper for obtaining a priority order of low-level Quality of Service parameters, which would ensure that user-level Quality of Perception is maintained at an optimum level. Thus we present an approach that integrates technical concerns with user perceptual considerations for intelligent decision-making in the construction of tailor-made multimedia communication protocols. The proposed approach, based on multicriteria decision making, incorporates not only classical networking considerations, but, indeed, user preferences as well. Moreover, our approach also opens the possibility for such protocols to dynamically adapt based on a changing operating environment and user preferences

Intelligent protocol adaptation for enhanced medical e-collaboration

Copyright @ 2003 AAAIDistributed multimedia e-health applications have a set specific requirements which must be taken into account effective use is to be made of the limited resources provided by public telecommunication networks. Moreover, there an architectural gap between the provision of network-level Quality of Service (QoS) and user requirements of e-health applications. In this paper, we address the problem bridging this gap from a multi-attribute decision-making perspective in the context of a remote collaborative environment for back pain treatment. We propose intelligent mechanism that integrates user- related requirements with the more technical characterisation Quality of Service. We show how our framework is capable of suggesting appropriately tailored transmission protocols, by incorporating user requirements in the remote delivery e-health solutions

Evolving Connectionist Models to Capture Population Variability across Language Development: Modeling Children's Past Tense Formation

Children's acquisition of the English past tense has been widely studied as a testing ground for theories of language development, mostly because it comprises a set of quasi-regular mappings. English verbs are of two types: regular verbs, which form their past tense based on a productive rule, and irregular verbs, which form their past tenses through exceptions to that rule. Although many connectionist models exist for capturing language development, few consider individual differences. In this article, we explore the use of populations of artificial neural networks (ANNs) that evolve according to behavioral genetics principles in order to create computational models capable of capturing the population variability exhibited by children in acquiring English past tense verbs. Literature in the field of behavioral genetics views variability in children's learning in terms of genetic and environmental influences. In our model, the effects of genetic influences are simulated through variations in parameters controlling computational properties of ANNs, and the effects of environmental influences are simulated via a filter applied to the training set. This filter alters the quality of information available to the artificial learning system and creates a unique subsample of the training set for each simulated individual. Our approach uses a population of twins to disentangle genetic and environmental influences on past tense performance and to capture the wide range of variability exhibited by children as they learn English past tenses. We use a novel technique to create the population of ANN twins based on the biological processes of meiosis and fertilization. This approach allows modeling of both individual differences and development (within the lifespan of an individual) in a single framework. Finally, our approach permits the application of selection on developmental performance on the quasi-regular task across generations. Setting individual differences within an evolutionary framework is an important and novel contribution of our work. We present an experimental evaluation of this model, focusing on individual differences in performance. The experiments led to several novel findings, including: divergence of population attributes during selection to favor regular verbs, irregular verbs, or both; evidence of canalization, analogous to Waddington's developmental epigenetic landscape, once selection starts targeting a particular aspect of the task domain; and the limiting effect on the power of selection in the face of stochastic selection (roulette wheel), sexual reproduction, and a variable learning environment for each individual. Most notably, the heritability of traits showed an inverse relationship to optimization. Selected traits show lower heritability as the genetic variation of the population reduces. The simulations demonstrate the viability of linking concepts such as heritability of individual differences, cognitive development, and selection over generations within a single computational framework

On the Impact of Link Layer Retransmissions on TCP for Aeronautical Communications

In this article, we evaluate the impact of link layer retransmissions on the performance of TCP in the context of aeronautical communications.We present the architecture of aeronautical networks, which is manly driven by an important channel access delay, and the various retransmission strategies that can be implemented at both link and transport layers. We consider a worst case scenario to illustrate the benefits provided by the ARQ scheme at the link layer in terms of transmission delay.We evaluate the trade-off between allowing a fast data transmission and a low usage of satellite capacity by adjusting link layer parameters

Computational intelligence in adaptive educational hypermedia

In this paper neuro-fuzzy synergism is applied to implement content sequencing in adaptive hypermedia systems. The level of understanding of the learner is used to construct lessons adapted to the learner’s knowledge goals and level of expertise on the domain concepts s/he has already studied. The learner’s evaluation is based on defining appropriate fuzzy sets and relate learner’s response with appropriate knowledge and cognitive characterizations. A connectionist-based structure of the domain knowledge is adopted for representing knowledge and inferring the planning strategy for generating the hypermedia page from pieces of educational material. The fuzziness associated with the evaluation of the learner is handled well by the proposed connectionist architecture

Adaptive web-based learning: accommodating individual differences through system's adaptation

The idea of developing educational hypermedia systems for the Web is very challenging, and demands the synergy of computer science and instructional science. The paper builds on theories from instructional design and learning styles to develop a design rational and guidelines for adaptive web-based learning systems that use individual differences as a basis of system’s adaptation. Various examples are provided to illustrate how instructional manipulations with regards to content adaptation and presentation, and adaptive navigation support, as well as the overall degree of system adaptation, are guided by educational experiences geared towards individual differences

Development and convergence analysis of training algorithms with local learning rate adaptation

A new theorem for the development and convergence analysis of supervised training algorithms with an adaptive learning rate for each weight is presented. Based on this theoretical result, a strategy is proposed to automatically adapt the search direction, as well as the stepsize length along the resultant search direction. This strategy is applied to some well known local learning algorithms to investigate its effectiveness