Public policy in knowledge-based economies: Foundations and frameworks

Knowledge is a product of human social systems and, therefore, the foundations of the knowledge-based economy are social and cultural. Communication is central to knowledge creation and diffusion, and Public Policy in Knowledge-Based Economies highlights specific social and cultural conditions that can enhance the communication, use and creation of knowledge in a society.The purpose of this book is to illustrate how these social and cultural conditions are identified and analysed through new conceptual frameworks. Such frameworks are necessary to penetrate the surface features of knowledge-based economies - science and technology - and disclose what drives such economies.This book will provide policymakers, analysts and academics with the fundamental tools needed for the development of policy in this little understood and emerging area.

Knowledge and willingness to pay for the conservation of wildlife species: Experimental results evaluating Australian tropical species

The nature of an experiment involving 204 residents is outlined and the results are reported and analysed. Two consecutive surveys of the respondents provide data about their stated knowledge of 23 wildlife species present in tropical Australia, most of which exclusively occur there. In addition, these surveys provide data about the willingness of respondents to pay for the conservation of those species belonging to three taxa; reptiles, mammals, and birds. Thus it is possible to compare the respondents’ stated knowledge of the species with their willingness to pay for their conservation, and to draw relevant inferences from this. From the initial survey and these associations, interesting relationships can be observed between those variables (knowledge and willingness to pay). The second survey was completed after the respondents’ knowledge of the species was experimentally increased and became more balanced. This is shown to result in increased dispersion (greater discrimination) in willingness to contribute to conservation of the different species in the set of wildlife species considered. Both theoretical and policy conclusions are drawn from the results.

Knowledge of birds and willingness to pay for their conservation: An Australian case study

This case study concentrates on the extent of knowledge of members of the Australian public of Australia’s tropical bird species and their willingness to pay for their conservation. In order to place this issue in context, it first provides background information on the status of Australian bird species, focusing attention on species that occur in tropical Australia. Then, using survey results, this study considers the hypothesis that the public’s relative support for the conservation of different bird species depends on its comparative knowledge of their existence and status. Based on experimental results from a sample of residents of Brisbane, Queensland (Australia), it is found that their knowledge of bird species that occur exclusively in the Australian tropics (including tropical Queensland) is very poor compared to those that also occur in the Brisbane area and are relatively common. Experimental results indicate that when respondents in the sample had an option to allocate $1,000 between ten bird species listed in the survey, it resulted in a greater allocation of funds to the better known and more common species than when they were provided with balanced information about all the selected species. With balanced information the average allocation to bird species confined mostly to the Australian tropics, particularly those threatened or endangered, increased. The general consequences of this for policies for the conservation of birds are discussed.

Western Australian primary school teachers knowledge about childhood asthma and its management

A total of 164 primary school teachers from Perth, Western Australia anonymously completed a survey of their knowledge and attitudes about asthma. These teachers were active in assisting children with asthma management but most (91.5%) felt that they did not know enough about asthma. Attitudes toward children with asthma were positive; 97% agreed that such children should be encouraged to participate in sporting activities. Specific knowledge about asthma management and medications was, however, poor. This large sample of Western Australian teachers knew more than their European counterparts but asthma training is needed and should be targeted at improving knowledge of both regular and emergency treatments for asthma.

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

Capillary network models for transport in packed beds: Considerations of pore aspect ratio

The conventional analysis for the estimation of the tortuosity factor for transport in porous media is modified here to account for the effect of pore aspect ratio. Structural models of the porous medium are also constructed for calculating the aspect ratio as a function of porosity. Comparison of the model predictions with the extensive data of Currie (1960) for the effective diffusivity of hydrogen in packed beds shows good agreement with a network model of randomly oriented intersecting pores for porosities upto about 50 percent, which is the region of practical interest. The predictions based on this network model are also found to be in better agreement with the data of Currie than earlier expressions developed for unconsolidated and grainy media.

Young children, adolescents and alcohol - Part I: Exploring knowledge and awareness of alcohol and related issues

This article explores young children's and adolescents' views pertaining to: knowledge and awareness of alcohol and alcohol related issues; social situations in which. alcohol use is present; orientation to alcohol risk; perceived and actual alcohol use; social image and reputation; and short and long term health beliefs in relation to alcohol. Forty focus groups were conducted with 240 primary school students (118 males and 122 females) and 24 focus groups were conducted with 192 high school students (90 males and 102 females); the total being 64 focus groups comprising 432 school students. Participants ages ranged from five years three months to 16 years 10 months. The videotaped discussions revealed that approximately 75% of the primary school-aged children and almost all of the high school students reported that they had tasted alcohol. Parents were primarily responsible for providing the alcohol. Virtually all participants recognised and were able to correctly name a selection of alcoholic and non-alcoholic beverages, and levels of knowledge and awareness of the health and safety aspects of alcohol were relatively mixed. Presentation of bottles and cans was reported as being important in attracting young persons. These data suggest there is an urgent need for research addressed to the development of prevention/intervention education curriculum materials for use with primary school-aged children.

Modeling the fluid-flow-induced stress and collapse in a dendritic network

An analytical approach to the stress development in the coherent dendritic network during solidification is proposed. Under the assumption that stresses are developed in the network as a result of the friction resisting shrinkage-induced interdendritic fluid flow, the model predicts the stresses in the solid. The calculations reflect the expected effects of postponed dendrite coherency, slower solidification conditions, and variations of eutectic volume fraction and shrinkage. Comparing the calculated stresses to the measured shear strength of equiaxed mushy zones shows that it is possible for the stresses to exceed the strength, thereby resulting in reorientation or collapse of the dendritic network.

The knowledge gap: A perspective on trade, industry, technology and policy from pre-war Australian music technology manufacturing (1903-30)

Australia struggles to achieve economic competitiveness, prevent expansion of the trade deficit and develop value-added production despite applications of policy strategies from protectionism to trade liberalisation. This article argues that these problems were emerging at the turn of the century, and that an investigation of music technology manufacturing in the first two decades of this century reveals fundamental problems in the conduct of relevant policy analysis. Analysis has focused on the trade or technology gap which is only symptomatic of an underlying knowledge gap. The article calls for a knowledge policy approach which can allow protection without the negative effects of isolation from global markets and without having to resort to unworkable utopian free-trade dogma. A shift of focus from a 'goods traded' view to a knowledge transaction (or diffusion) perspective is advocated.

An object-oriented neural network approach to short-term traffic forecasting

This paper discusses an object-oriented neural network model that was developed for predicting short-term traffic conditions on a section of the Pacific Highway between Brisbane and the Gold Coast in Queensland, Australia. The feasibility of this approach is demonstrated through a time-lag recurrent network (TLRN) which was developed for predicting speed data up to 15 minutes into the future. The results obtained indicate that the TLRN is capable of predicting speed up to 5 minutes into the future with a high degree of accuracy (90-94%). Similar models, which were developed for predicting freeway travel times on the same facility, were successful in predicting travel times up to 15 minutes into the future with a similar degree of accuracy (93-95%). These results represent substantial improvements on conventional model performance and clearly demonstrate the feasibility of using the object-oriented approach for short-term traffic prediction. (C) 2001 Elsevier Science B.V. All rights reserved.

MHCWeb: Converting a WWW database into a knowledge-based collaborative environment

The World Wide Web (WWW) is useful for distributing scientific data. Most existing web data resources organize their information either in structured flat files or relational databases with basic retrieval capabilities. For databases with one or a few simple relations, these approaches are successful, but they can be cumbersome when there is a data model involving multiple relations between complex data. We believe that knowledge-based resources offer a solution in these cases. Knowledge bases have explicit declarations of the concepts in the domain, along with the relations between them. They are usually organized hierarchically, and provide a global data model with a controlled vocabulary, We have created the OWEB architecture for building online scientific data resources using knowledge bases. OWEB provides a shell for structuring data, providing secure and shared access, and creating computational modules for processing and displaying data. In this paper, we describe the translation of the online immunological database MHCPEP into an OWEB system called MHCWeb. This effort involved building a conceptual model for the data, creating a controlled terminology for the legal values for different types of data, and then translating the original data into the new structure. The 0 WEB environment allows for flexible access to the data by both users and computer programs.

Inter-subband redundancy prediction using neural network for video coding

High performance video codec is mandatory for multimedia applications such as video-on-demand and video conferencing. Recent research has proposed numerous video coding techniques to meet the requirement in bandwidth, delay, loss and Quality-of-Service (QoS). In this paper, we present our investigations on inter-subband self-similarity within the wavelet-decomposed video frames using neural networks, and study the performance of applying the spatial network model to all video frames over time. The goal of our proposed method is to restore the highest perceptual quality for video transmitted over a highly congested network. Our contributions in this paper are: (1) A new coding model with neural network based, inter-subband redundancy (ISR) prediction for video coding using wavelet (2) The performance of 1D and 2D ISR prediction, including multiple levels of wavelet decompositions. Our result shows a short-term quality enhancement may be obtained using both 1D and 2D ISR prediction.