Creativity, knowledge, engagement : keys to finding the right governance model for a regional community precinct

This paper investigates the Cooroy Mill community precinct (Sunshine Coast, Queensland), as a case study, seeking to understand the way local dynamics interplay and work with the community strengths to build a governance model of best fit. As we move to an age of ubiquitous computing and creative economies, the definition of public place and its governance take on new dimensions, which – while often utilizing models of the past – will need to acknowledge and change to the direction of the future. This paper considers a newly developed community precinct that has been built on three key principles: to foster creative expression with new media, to establish a knowledge economy in a regional area, and to subscribe to principles of community engagement. The study involved qualitative interviews with key stakeholders and a review of common practice models of governance along a spectrum from community control to state control. The paper concludes with a call for governance structures that are locally situated and tailored, inclusive, engaging, dynamic and flexible in order to build community capacity, encourage creativity, and build knowledge economies within emerging digital media cityscapes.

Impacts and opportunities : resident's view on sustainable development of tourism in regional Queensland, Australia

Tourism development is a priority for rural and regional areas of Australia. The challenge is how to develop the tourism industry in a sustainable manner. As part of a larger project investigating community perceptions of opportunities, strategies and challenges in regional sustainable development, this article explores participant's views and opinions of tourism development. Through purposive sampling, 28 local community leaders and residents in the Darling Downs region in Queensland, Australia, participated in four semi-structured focus groups. This paper focuses on two of these focus groups, where tourism was a critical issue. Participants were generally positive about the tourism industry and its impacts on their community, although they expressed several triple bottom line concerns about economic, environmental and scoial issues. Four key themes emerged: appropriate land use management, limited resources and ageing/insufficient infrastructure, preservaation of community heritage and lifestyle, and regional conflict. Residents supported sustainable tourism development and wanted to be more actively involved in decision-making, demanding greater transparency - and true engagement - from local government.

Regional changes in corneal thickness and shape with soft contact lenses

Purpose: To investigate the influence of soft contact lenses on regional variations in corneal thickness and shape while taking account of natural diurnal variations in these corneal parameters. Methods: Twelve young, healthy subjects wore 4 different types of soft contact lenses on 4 different days. The lenses were of two different materials (silicone hydrogel, hydrogel), designs (spherical, toric) and powers (–3.00, –7.00 D). Corneal thickness and topography measurements were taken before and after 8 hours of lens wear and on two days without lens wear, using the Pentacam HR system. Results: The hydrogel toric contact lens caused the greatest level of corneal thickening in the central (20.3 ± 10.0 microns) as well as peripheral cornea (24.1 ± 9.1 microns) (p < 0.001) with an obvious regional swelling of the cornea beneath the stabilizing zones. The anterior corneal surface generally showed slight flattening. All contact lenses resulted in central posterior corneal steepening and this was weakly correlated with central corneal swelling (p = 0.03) and peripheral corneal swelling (p = 0.01). Conclusions: There was an obvious regional corneal swelling apparent after wear of the hydrogel soft toric lenses, due to the location of the thicker stabilization zones of the toric lenses. However with the exception of the hydrogel toric lens, the magnitude of corneal swelling induced by the contact lenses over the 8 hours of wear was less than the natural diurnal thinning of the cornea over this same period.

Regional field measurement of soil moisture content with neutron probe

The neutron logging method has been widely used for field measurement of soil moisture content. This non-destructive method permitted the measurement of in-situ soil moisture content at various depths without the need for burying any sensor. Twenty-three sites located around regional Melbourne have been selected for long term monitoring of soil moisture content using neutron probe. Soil samples collected during the installation are used for site characterisation and neutron probe calibration purposes. A linear relationship is obtained between the corrected neutron probe reading and moisture content for both the individual and combined data from seven sites. It is observed that the liner relationship, developed using combined data, can be used for all sites with an average accuracy of about 80%. Monitoring of the variation of soil moisture content with depth in six months for two sites is presented in this paper.

Color and texture feature fusion using kernel PCA with application to object-based vegetation species classification

A good object representation or object descriptor is one of the key issues in object based image analysis. To effectively fuse color and texture as a unified descriptor at object level, this paper presents a novel method for feature fusion. Color histogram and the uniform local binary patterns are extracted from arbitrary-shaped image-objects, and kernel principal component analysis (kernel PCA) is employed to find nonlinear relationships of the extracted color and texture features. The maximum likelihood approach is used to estimate the intrinsic dimensionality, which is then used as a criterion for automatic selection of optimal feature set from the fused feature. The proposed method is evaluated using SVM as the benchmark classifier and is applied to object-based vegetation species classification using high spatial resolution aerial imagery. Experimental results demonstrate that great improvement can be achieved by using proposed feature fusion method.

A regional construction R&D evaluation system for China

Expenditure on R&D in the China construction industry has been relatively low in comparison with many developed countries for a number of years – a situation considered to be a major barrier to the industry’s competitiveness in general and unsatisfactory industry development of the 31 regions involved. A major problem with this is the lack of a sufficiently sophisticated method of objectively evaluating R&D activity in what are quite complex circumstances considering the size and regional differences that exist in this part of the world. A regional construction R&D evaluation system (RCRES) is presented aimed at rectifying the situation. This is based on 12 indicators drawn from the Chinese Government’s R&D Inventory of Resources in consultation with a small group of experts in the field, and further factor analysed into three groups. From this, the required evaluation is obtained by a simple formula. Examination of the results provides a ranking list of the R&D performance of each of the 31 regions, indicating a general disproportion between coastal and inland regions and highlighting regions receiving special emphasis or currently lacking in development. The understanding on this is vital for the future of China’s construction industry.

Sustainable urban and regional infrastructure development : technologies, applications and management

Sustainable Urban and Regional Infrastructure Development: Technologies, Applications and Management, bridges the gap in the current literature by addressing the overall problems present in society's major infrastructures, and the technologies that may be applied to overcome these problems. It focuses on ways in which energy intensive but 'invisible' (to the general public) facilities can become green or greener. The studies presented re lessons to be learnt from our neighbors and from our own backyard, and provide an excellent general overview of the issues facing us all.

Urban, regional, national and global knowledge capital [Guest editorial]

Purpose – The purpose of this paper is to introduce the JKM 2010 annual special issue on knowledge based development (KBD) with reference to the multi-level analysis characteristic of the field. ----- ----- Design/methodology/approach – A description of the knowledge management approach at ESOC (European Space Operations Centre of the European Space Agency) is provided first. At the core of this approach is the breakdown of knowledge in individual technical domains followed by coverage analysis and criticality assessment. Such a framework becomes the reference for best knowledge acquisition, transfer and storage locus identification and subsequent knowledge management practices and guidelines. ----- ----- Findings – KBD provides an integrated framework to account for multidisciplinary analyses and multilevel practices in knowledge capital generation, distribution and utilization. ----- ----- Originality/value – The collection of papers included in the annual special issue on KBD provides a representative, composite view of the research topics and applications concerns in the field. Involving a number of disciplines and levels of analysis, issues ranging from the technological gatekeeper to global knowledge flows show the interdependence of KBD concepts and tools.

Towards improvement of autonomous glider navigation accuracy through the use of regional ocean models

Autonomous underwater gliders are robust and widely-used ocean sampling platforms that are characterized by their endurance, and are one of the best approaches to gather subsurface data at the appropriate spatial resolution to advance our knowledge of the ocean environment. Gliders generally do not employ sophisticated sensors for underwater localization, but instead dead-reckon between set waypoints. Thus, these vehicles are subject to large positional errors between prescribed and actual surfacing locations. Here, we investigate the implementation of a large-scale, regional ocean model into the trajectory design for autonomous gliders to improve their navigational accuracy. We compute the dead-reckoning error for our Slocum gliders, and compare this to the average positional error recorded from multiple deployments conducted over the past year. We then compare trajectory plans computed on-board the vehicle during recent deployments to our prediction-based trajectory plans for 140 surfacing occurrences.

Trajectory design for autonomous underwater vehicles based on ocean model predictions for feature tracking

Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection. We consider the use of ocean model predictions to determine the locations to be visited by an AUV, which then provides near-real time, in situ measurements back to the model to increase the skill of future predictions. The motion planning problem of steering the vehicle between the computed waypoints is not considered here. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks. We design a sampling plan and present experimental results with AUV retasking in the Southern California Bight (SCB) off the coast of Los Angeles.

Preface : sustainable urban and regional infrastructure development : technologies, applications and management

The concept of ‘sustainability’ has been pushed to the forefront of policy-making and politics as the world wakes up to the impacts of climate change and the effects of the modern urban lifestyle. Climate change has emerged to be one of the biggest challenges faced by our planet today, threatening both built and natural systems with long term consequences which may be irreversible. While there is a vast literature in the market on sustainable cities and urban development, there is currently none that bring together the vital issues of urban and regional development, and the planning, management and implementation of sustainable infrastructure. Large scale infrastructure plays an important part in modern society by not only promoting economic growth, but also by acting as a key indicator for it. More importantly, it supplies municipal/local amenity and services: water, electricity, social and communication facilities, waste removal, transport of people and goods, as well as numerous other services. For the most part, infrastructure has been built by teams lead by engineers who are more concerned about functionality than the concept of sustainability. However, it has been widely stated that current practices and lifestyle cannot continue if we are to leave a healthy living planet to not only the next generation, but also to the generations beyond. Therefore, in order to be sustainable, there are drastic measures that need to be taken. Current single purpose and design infrastructures that are open looped are not sustainable; they are too resource intensive, consume too much energy and support the consumption of natural resources at a rate that will exhaust their supply. Because of this, it is vital that modern society, policy-makers, developers, engineers and planners become pioneers in introducing and incorporating sustainable features into urban and regional infrastructure.

A statistical framework for natural feature representation

This paper presents a robust stochastic framework for the incorporation of visual observations into conventional estimation, data fusion, navigation and control algorithms. The representation combines Isomap, a non-linear dimensionality reduction algorithm, with expectation maximization, a statistical learning scheme. The joint probability distribution of this representation is computed offline based on existing training data. The training phase of the algorithm results in a nonlinear and non-Gaussian likelihood model of natural features conditioned on the underlying visual states. This generative model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The instantiated likelihoods are expressed as a Gaussian mixture model and are conveniently integrated within existing non-linear filtering algorithms. Example applications based on real visual data from heterogenous, unstructured environments demonstrate the versatility of the generative models.

A stochastic model for natural feature representation

This paper presents a robust stochastic model for the incorporation of natural features within data fusion algorithms. The representation combines Isomap, a non-linear manifold learning algorithm, with Expectation Maximization, a statistical learning scheme. The representation is computed offline and results in a non-linear, non-Gaussian likelihood model relating visual observations such as color and texture to the underlying visual states. The likelihood model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The likelihoods are expressed as a Gaussian Mixture Model so as to permit convenient integration within existing nonlinear filtering algorithms. The resulting compactness of the representation is especially suitable to decentralized sensor networks. Real visual data consisting of natural imagery acquired from an Unmanned Aerial Vehicle is used to demonstrate the versatility of the feature representation.

Interpreting regional frequencies from synchronized phasor measurement in multi-area power systems

In this paper a new approach is proposed for interpreting of regional frequencies in multi machine power systems. The method uses generator aggregation and system reduction based on coherent generators in each area. The reduced system structure is able to be identified and a kalman estimator is designed for the reduced system to estimate the inter-area modes using the synchronized phasor measurement data. The proposed method is tested on a six machine, three area test system and the obtained results show the estimation of inter-area oscillations in the system with a high accuracy.