Effect of spacing of reinforcement on the behaviour of partially grouted masonry shear walls

Partially Grouted Reinforced Masonry (PGRM) shear walls perform well in places where the cyclonic wind pressure dominates the design. Their out-of-plane flexural performance is better understood than their inplane shear behaviour; in particular, it is not clear whether the PGRM shear walls act as unreinforced masonry (URM) walls embedded with discrete reinforced grouted cores or as integral systems of reinforced masonry (RM) with wider spacing of reinforcement. With a view to understanding the inplane response of PGRM shear walls, ten full scale single leaf, clay block walls were constructed and tested under monotonic and cyclic inplane loading cases. It has been shown that where the spacing of the vertical reinforcement is less than 2000mm, the walls behave as an integral system of RM; for spacing greater than 2000mm, the walls behave similar to URM with no significant benefit from the reinforced cores based on the displacement ductility and stiffness degradation factors derived from the complete lateral load – lateral displacement curves.

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.

Test and evaluation system for multi-protocol sampled value protection schemes

Proposed transmission smart grids will use a digital platform for the automation of substations operating at voltage levels of 110 kV and above. The IEC 61850 series of standards, released in parts over the last ten years, provide a specification for substation communications networks and systems. These standards, along with IEEE Std 1588-2008 Precision Time Protocol version 2 (PTPv2) for precision timing, are recommended by the both IEC Smart Grid Strategy Group and the NIST Framework and Roadmap for Smart Grid Interoperability Standards for substation automation. IEC 61850-8-1 and IEC 61850-9-2 provide an inter-operable solution to support multi-vendor digital process bus solutions, allowing for the removal of potentially lethal voltages and damaging currents from substation control rooms, a reduction in the amount of cabling required in substations, and facilitates the adoption of non-conventional instrument transformers (NCITs). IEC 61850, PTPv2 and Ethernet are three complementary protocol families that together define the future of sampled value digital process connections for smart substation automation. This paper describes a specific test and evaluation system that uses real time simulation, protection relays, PTPv2 time clocks and artificial network impairment that is being used to investigate technical impediments to the adoption of SV process bus systems by transmission utilities. Knowing the limits of a digital process bus, especially when sampled values and NCITs are included, will enable utilities to make informed decisions regarding the adoption of this technology.

A biologically inspired object spectral-texture descriptor and its application to vegetation classification in power-line corridors

The use of appropriate features to represent an output class or object is critical for all classification problems. In this paper, we propose a biologically inspired object descriptor to represent the spectral-texture patterns of image-objects. The proposed feature descriptor is generated from the pulse spectral frequencies (PSF) of a pulse coupled neural network (PCNN), which is invariant to rotation, translation and small scale changes. The proposed method is first evaluated in a rotation and scale invariant texture classification using USC-SIPI texture database. It is further evaluated in an application of vegetation species classification in power line corridor monitoring using airborne multi-spectral aerial imagery. The results from the two experiments demonstrate that the PSF feature is effective to represent spectral-texture patterns of objects and it shows better results than classic color histogram and texture features.

Addressing sustainable living using a collaborative approach and multi-disciplinary techniques

In order to achieve meaningful reductions in individual ecological footprints, individuals must dramatically alter their day to day behaviours. Effective interventions will need to be evidence based and there is a necessity for the rapid transfer or communication of information from the point of research, into policy and practice. A number of health disciplines, including psychology and public health, share a common mission to promote health and well-being and it is becoming clear that the most practical pathway to achieving this mission is through interdisciplinary collaboration. This paper argues that an interdisciplinary collaborative approach will facilitate research that results in the rapid transfer of findings into policy and practice. The application of this approach is described in relation to the Green Living project which explored the psycho-social predictors of environmentally friendly behaviour. Following a qualitative pilot study, and in consultation with an expert panel comprising academics, industry professionals and government representatives, a self-administered mail survey was distributed to a random sample of 3000 residents of Brisbane and Moreton Bay (Queensland, Australia). The Green Living survey explored specific beliefs which included attitudes, norms, perceived control, intention and behaviour, as well as a number of other constructs such as environmental concern and altruism. This research has two beneficial outcomes. First, it will inform a practical model for predicting sustainable living behaviours and a number of local councils have already expressed an interest in making use of the results as part of their ongoing community engagement programs. Second, it provides an example of how a collaborative interdisciplinary project can provide a more comprehensive approach to research than can be accomplished by a single disciplinary project.

Discovery & effective use of quality association rules in multi-level datasets

In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.

Remote monitoring of outdoor performance of low scale dye sensitized solar cells for nanosensors nodes

This is the first outdoor test of small-scale dye sensitized solar cells (DSC) powering a standalone nanosensor node. A solar cell test station (SCTS) has been developed using standard DSC to power a gas nanosensor, a radio transmitter, and the control electronics (CE) for battery charging. The station is remotely monitored through wired (Ethernet cable) or wireless connection (radio transmitter) in order to evaluate in real time the performance of the solar cells powering a nanosensor and a transmitter under different weather conditions. We analyze trends of energy conversion efficiency after 60 days of operation. The 408 cm2 active surface module produces enough energy to power a gas nanosensor and a radio transmitter during the day and part of the night. Also, by using a variable programmable load we keep the system working on the maximum power point (MPP) quantifying the total energy generated and stored in a battery. Although this technology is at an early stage of development, these experiments provide useful data for future outdoor applications such as nanosensor network nodes.

Ontology-based specific and exhaustive user profiles for constraint information fusion for multi-agents

Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment.

Teaching new dogs old tricks. How the move to 24/7 interactive, integrated multimedia, multi-platform news and feature delivery is not really changing the skills employers demand of graduates

The journalism revolution is upon us. In a world where we are constantly being told that everyone can be a publisher and challenges are emerging from bloggers, Twitterers and podcasters, journalism educators are inevitably reassessing what skills we now need to teach to keep our graduates ahead of the game. QUT this year tackled that question head-on as a curriculum review and program restructure resulted in a greater emphasis on online journalism. The author spent a week in the online newsrooms of each of two of the major players – ABC online news and thecouriermail.com to watch, listen and interview some of the key players. This, in addition to interviews with industry leaders from Fairfax and news.com, lead to the conclusion that while there are some new skills involved in new media much of what the industry is demanding is in fact good old fashioned journalism. Themes of good spelling, grammar, accuracy and writing skills and a nose for news recurred when industry players were asked what it was that they would like to see in new graduates. While speed was cited as one of the big attributes needed in online journalism, the conclusion of many of the players was that the skills of a good down-table sub or a journalist working for wire service were not unlike those most used in online newsrooms.

Damage detection in truss bridges using vibration based multi-criteria approach

This paper uses dynamic computer simulation techniques to develop and apply a multi-criteria procedure using non-destructive vibration-based parameters for damage assessment in truss bridges. In addition to changes in natural frequencies, this procedure incorporates two parameters, namely the modal flexibility and the modal strain energy. Using the numerically simulated modal data obtained through finite element analysis of the healthy and damaged bridge models, algorithms based on modal flexibility and modal strain energy changes before and after damage are obtained and used as the indices for the assessment of structural health state. The application of the two proposed parameters to truss-type structures is limited in the literature. The proposed multi-criteria based damage assessment procedure is therefore developed and applied to truss bridges. The application of the approach is demonstrated through numerical simulation studies of a single-span simply supported truss bridge with eight damage scenarios corresponding to different types of deck and truss damage. Results show that the proposed multi-criteria method is effective in damage assessment in this type of bridge superstructure.

Researching employment relations : a self-reflexive analysis of a multi-method, school-based project

Drawing on primary data and adjunct material, this article adopts a critical self-reflexive approach to a three-year, Australian Research Council-funded projectthat explored themes around 'employment citizenship'for high school students in Queensland. The article addresses three overlapping areas that reflect some of the central dilemmas and challenges arising through the project- consent in the context of research ethics, questionnaire administration in schools, and focus group research practice. It contributes to the broader methodological literature addressing research with young people by canvassing pragmatic suggestions for future school-based research, and research addressing adolescent employment.

Stakeholder engagement by governance networks

Public awareness of large infrastructure projects, many of which are delivered through networked arrangements is high for several reasons. These projects often involve significant public investment; they may involve multiple and conflicting stakeholders and can potentially have significant environmental impacts (Lim and Yang, 2008). To produce positive outcomes from infrastructure delivery it is imperative that stakeholder “buy in” be obtained particularly about decisions relating to the scale and location of infrastructure. Given the likelihood that stakeholders will have different levels of interest and investment in project outcomes, failure to manage this dynamic could potentially jeopardise project delivery by delaying or halting the construction of essential infrastructure. Consequently, stakeholder engagement has come to constitute a critical activity in infrastructure development delivered through networks. This paper draws on stakeholder theory and governance network theory and provides insights into how three multi-level networks within the Roads Alliance in Queensland engage with stakeholders in the delivery of road infrastructure. New knowledge about stakeholders has been obtained by testing a model of Stakeholder Salience and Engagement which combines and extends the stakeholder identification and salience theory and the ladder of stakeholder management and engagement. By applying this model, the broad research question: “How do governance networks engage with stakeholders?” has been addressed. A multiple embedded case study design was selected as the overall approach to explore, describe, explain and evaluate how stakeholder engagement occurred in three governance networks delivering road infrastructure in Queensland. The outcomes of this research contribute to and extend stakeholder theory by showing how stakeholder salience impacts on decisions about the types of engagement processes implemented. Governance network theory is extended by showing how governance networks interact with stakeholders. From a practical perspective this research provides governance networks with an indication of how to more effectively undertake engagement with different types of stakeholders.

Remote monitoring of outdoor performance of low scale dye sensitized solar cells for nanosensors nodes

This is the first outdoor test of small-scale dye sensitized solar cells (DSC) powering a stand-alone nanosensor node. A solar cell test station (SCTS) has been developed using standard DSC to power a gas nanosensor, a radio transmitter, and the control electronics (CE) for battery charging. The station is remotely monitored through wired (Ethernet cable) or wireless connection (radio transmitter) in order to evaluate in real time the performance of the solar cells and devices under different weather conditions. The 408 cm2 active surface module produces enough energy to power a gas nanosensor and a radio transmitter during the day and part of the night. Also, by using a programmable load we keep the system working on the maximum power point (MPP) quantifying the total energy generated and stored in a battery. These experiments provide useful data for future outdoor applications such as nanosensor networks.