Logistical aspects of large telemedicine networks. 2: Measurement of network activity

We carried out a retrospective review of the videoconference activity records in a university-run hospital telemedicine studio. Usage records describing videoconferencing activity in the telemedicine studio were compared with the billing records provided by the telecommunications company. During a seven-month period there were 211 entries in the studio log: 108 calls made from the studio and 103 calls made from a far-end location. We found that 103 calls from a total of 195 calls reported by the telecommunications company were recorded in the usage log. The remaining 92 calls were not recorded, probably for one of several reasons, including: failed calls-a large number of unrecorded calls (57%) lasted for less than 2 min (median 1.6 min); origin of videoconference calls-calls may have been recorded incorrectly in the usage diary (i.e. as being initiated from the far end, when actually initiated from the studio); and human error. Our study showed that manual recording of videoconference activity may not accurately reflect the actual activity taking place. Those responsible for recording and analysing videoconference activity, particularly in large telemedicine networks, should do so with care.

Measuring globalisation: An evolutionary economic approach to tracking the evolution of international trade

Operationalising and measuring the concept of globalisation is important, as the extent to which the international economy is integrated has a direct impact on industrial dynamics, national trade policies and firm strategies. Using complex systems network analysis with longitudinal trade data from 1938 to 2003, this paper presents a new way to measure globalisation. It demonstrates that some important aspects of the international trade network have been remarkably stable over this period. However, several network measures have changed substantially over the same time frame. Taken together, these analyses provide a novel measure of globalisation.

Biodiversity conservation planning tools: Present status and challenges for the future

Species extinctions and the deterioration of other biodiversity features worldwide have led to the adoption of systematic conservation planning in many regions of the world. As a consequence, various software tools for conservation planning have been developed over the past twenty years. These, tools implement algorithms designed to identify conservation area networks for the representation and persistence of biodiversity features. Budgetary, ethical, and other sociopolitical constraints dictate that the prioritized sites represent biodiversity with minimum impact on human interests. Planning tools are typically also used to satisfy these criteria. This chapter reviews both the concepts and technical choices that underlie the development of these tools. Conservation planning problems can be formulated as optimization problems, and we evaluate the suitability of different algorithms for their solution. Finally, we also review some key issues associated with the use of these tools, such as computational efficiency, the effectiveness of taxa and abiotic parameters at choosing surrogates for biodiversity, the process of setting explicit targets of representation for biodiversity surrogates, and

Appropriate indicators for injury control?

Indicators are valuable tools used to measure progress towards a desired health outcome. Increased awareness of the public health burden due to injury has lead to a concomitant interest in monitoring the impact of national initiatives that aim to reduce the size of the burden. Several injury indicators have now been proposed. This study examines the ability of each of the suggested indicators to reflect the nature and extent of the burden of non-fatal injury. A criterion validity, population-based, prospective cohort study was conducted in Brisbane, a sub-tropical Metropolitan City on the eastern seaboard of Australia, over a 12-month period between 1 January and 31 December 1998. Neither the presence of a long bone fracture nor the need for hospitalisation for 4 or more days were sensitive or specific indicators for 'serious' or major injury as defined by the 'Gold Standard' Injury Severity Score (ISS). Subsequent analysis, using other public health outcome measures demonstrated that the major component of the illness burden of injury was in fact due to 'minor' not serious injury. However, the suggested indicators demonstrated low sensitivity and specificity for these outcomes as well. The results of the study support the need to include at least all hospitalisations in any population-based measure of injury and not attempt to simplify the indicator to a more convenient measure aimed at identifying just those cases of,serious' injury.

Multiparametric evaluation of dysphonic severity

In recent years, the multiparametric approach for evaluating perceptual rating of voice quality has been advocated. This study evaluates the accuracy of predicting perceived overall severity of voice quality with a minimal set of aerodynamic, voice range profile (phonetogram), and acoustic perturbation measures. One hundred and twelve dysphonic persons (93 women and 19 men) with laryngeal pathologies and 41 normal controls (35 women and six men) with normal voices participated in this study. Perceptual severity judgement was carried out by four listeners rating the G (overall grade) parameter of the GRBAS scale.(1) The minimal set of instrumental measures was selected based on the ability of the measure to discriminate between dysphonic and normal voices, and to attain at least a moderate correlation with perceived overall severity. Results indicated that perceived overall severity was best described by maximum phonation time of sustained /a/, peak intraoral pressure of the consonant-vowel /pi/ strings production, voice range profile area, and acoustic jitter. Direct-entry discriminant function analysis revealed that these four voice measures in combination correctly predicted 67.3% of perceived overall severity levels.

The tree cut and merge algorithm for estimation of network reliability

This article presents Monte Carlo techniques for estimating network reliability. For highly reliable networks, techniques based on graph evolution models provide very good performance. However, they are known to have significant simulation cost. An existing hybrid scheme (based on partitioning the time space) is available to speed up the simulations; however, there are difficulties with optimizing the important parameter associated with this scheme. To overcome these difficulties, a new hybrid scheme (based on partitioning the edge set) is proposed in this article. The proposed scheme shows orders of magnitude improvement of performance over the existing techniques in certain classes of network. It also provides reliability bounds with little overhead.

Applying network analysis to the conservation of habitat trees in urban environments: a case study from Brisbane, Australia

In Australia more than 300 vertebrates, including 43 insectivorous bat species, depend on hollows in habitat trees for shelter, with many species using a network of multiple trees as roosts, We used roost-switching data on white-striped freetail bats (Tadarida australis; Microchiroptera: Molossidae) to construct a network representation of day roosts in suburban Brisbane, Australia. Bats were caught from a communal roost tree with a roosting group of several hundred individuals and released with transmitters. Each roost used by the bats represented a node in the network, and the movements of bats between roosts formed the links between nodes. Despite differences in gender and reproductive stages, the bats exhibited the same behavior throughout three radiotelemetry periods and over 500 bat days of radio tracking: each roosted in separate roosts, switched roosts very infrequently, and associated with other bats only at the communal roost This network resembled a scale-free network in which the distribution of the number of links from each roost followed a power law. Despite being spread over a large geographic area (> 200 km(2)), each roost was connected to others by less than three links. One roost (the hub or communal roost) defined the architecture of the network because it had the most links. That the network showed scale-free properties has profound implications for the management of the habitat trees of this roosting group. Scale-free networks provide high tolerance against stochastic events such as random roost removals but are susceptible to the selective removal of hub nodes. Network analysis is a useful tool for understanding the structural organization of habitat tree usage and allows the informed judgment of the relative importance of individual trees and hence the derivation of appropriate management decisions, Conservation planners and managers should emphasize the differential importance of habitat trees and think of them as being analogous to vital service centers in human societies.

Visualization of learning in multilayer perceptron networks using principal component analysis

This paper is concerned with the use of scientific visualization methods for the analysis of feedforward neural networks (NNs). Inevitably, the kinds of data associated with the design and implementation of neural networks are of very high dimensionality, presenting a major challenge for visualization. A method is described using the well-known statistical technique of principal component analysis (PCA). This is found to be an effective and useful method of visualizing the learning trajectories of many learning algorithms such as back-propagation and can also be used to provide insight into the learning process and the nature of the error surface.

Segmenting the market of West Australian senior tourists using an artificial neural network

Measuring perceptions of customers can be a major problem for marketers of tourism and travel services. Much of the problem is to determine which attributes carry most weight in the purchasing decision. Older travellers weigh many travel features before making their travel decisions. This paper presents a descriptive analysis of neural network methodology and provides a research technique that assesses the weighting of different attributes and uses an unsupervised neural network model to describe a consumer-product relationship. The development of this rich class of models was inspired by the neural architecture of the human brain. These models mathematically emulate the neurophysical structure and decision making of the human brain, and, from a statistical perspective, are closely related to generalised linear models. Artificial neural networks or neural networks are, however, nonlinear and do not require the same restrictive assumptions about the relationship between the independent variables and dependent variables. Using neural networks is one way to determine what trade-offs older travellers make as they decide their travel plans. The sample of this study is from a syndicated data source of 200 valid cases from Western Australia. From senior groups, active learner, relaxed family body, careful participants and elementary vacation were identified and discussed. (C) 2003 Published by Elsevier Science Ltd.

A reduced load approximation accounting for link interactions in a loss network

This paper is concerned with evaluating the performance of loss networks. Accurate determination of loss network performance can assist in the design and dimen- sioning of telecommunications networks. However, exact determination can be difficult and generally cannot be done in reasonable time. For these reasons there is much interest in developing fast and accurate approximations. We develop a reduced load approximation that improves on the famous Erlang fixed point approximation (EFPA) in a variety of circumstances. We illustrate our results with reference to a range of networks for which the EFPA may be expected to perform badly.