Data mining for lifetime prediction of metallic components

The ability to accurately predict the lifetime of building components is crucial to optimizing building design, material selection and scheduling of required maintenance. This paper discusses a number of possible data mining methods that can be applied to do the lifetime prediction of metallic components and how different sources of service life information could be integrated to form the basis of the lifetime prediction model

Moderation as judgement practice: Reconciling system level accountability and local level practice

Internationally, recognition of the role of assessment to inform the learning process has received much attention in recent years. Assessment for learning, not just of learning is being supported by an increasing body of literature providing strategies that teachers and their students can incorporate to support the learning process (Assessment Reform Group, 2002; Broadfoot & Black, 2004; James, 2006). Concurrently there has been an increase internationally in systemic accountability requirements of schools in terms of student results. The convergence of these two movements has resulted in some education systems promoting standards-driven reform involving authentic assessment and a re-examination of the relationship between the teacher and the student in the learning process. In this context standards are intended to be used as the basis for judgements of student achievement; while the results from assessment tasks are meant to both inform the teaching/learning process, and to report and track student progress. In such system, the role and reliability of teacher judgement takes centre stage.

The user query based learning system for lifetime prediction of metallic components

Real-World Data Mining Applications generally do not end up with the creation of the models. The use of the model is the final purpose especially in prediction tasks. The problem arises when the model is built based on much more information than that the user can provide in using the model. As a result, the performance of model reduces drastically due to many missing attributes values. This paper develops a new learning system framework, called as User Query Based Learning System (UQBLS), for building data mining models best suitable for users use. We demonstrate its deployment in a real-world application of the lifetime prediction of metallic components in buildings

High-level concept annotation using ontology and probabilistic inference

Image annotation is a significant step towards semantic based image retrieval. Ontology is a popular approach for semantic representation and has been intensively studied for multimedia analysis. However, relations among concepts are seldom used to extract higher-level semantics. Moreover, the ontology inference is often crisp. This paper aims to enable sophisticated semantic querying of images, and thus contributes to 1) an ontology framework to contain both visual and contextual knowledge, and 2) a probabilistic inference approach to reason the high-level concepts based on different sources of information. The experiment on a natural scene database from LabelMe database shows encouraging results.

Mid-level concept learning with visual contextual ontologies and probabilistic inference for image annotation

To date, automatic recognition of semantic information such as salient objects and mid-level concepts from images is a challenging task. Since real-world objects tend to exist in a context within their environment, the computer vision researchers have increasingly incorporated contextual information for improving object recognition. In this paper, we present a method to build a visual contextual ontology from salient objects descriptions for image annotation. The ontologies include not only partOf/kindOf relations, but also spatial and co-occurrence relations. A two-step image annotation algorithm is also proposed based on ontology relations and probabilistic inference. Different from most of the existing work, we specially exploit how to combine representation of ontology, contextual knowledge and probabilistic inference. The experiments show that image annotation results are improved in the LabelMe dataset.

Multi-level order, friction and contradiction : the evolution of Australian film industry policy

Cultural policy studies have previously highlighted the importance of multiple logics, friction and contradiction in cultural policy. Recent developments in institutional theory provide a framework for analysing change in cultural policy which explores movement between these multiple and sometimes contradictory logics. This paper analyses the role of friction in the evolution of Australian film industry policy and in particular the tension between competing logics regarding nationalism, commercialism and the state. The paper is suggestive of the relevance of institutional theory as a framework for understanding cultural policy evolution.

EMI issues in high power and high level diode-clamped converters

Planar busbar is a good candidate to reduce interconnection inductance in high power inverters compared with cables. However, power switching components with fast switching combined with hard switched-converters produce high di/dt during turn off time and busbar stray inductance then becomes an important issue which creates overvoltage. It is necessary to keep the busbar stray inductance as low as possible to decrease overvoltage and Electromagnetic Interference (EMI) noise. In this paper, the effect of different transient current loops on busbar physical structure of the high-voltage high-level diode-clamped converters will be highlighted. Design considerations of proper planar busbar will also be presented to optimise the overall design of diode-clamped converters.

Self-commutated current source converter with multi-level current reinjection

The multi-level current reinjection concept described in literature is well-known to produce high quality AC current waveforms in high power and high voltage self-commutating current source converters. This paper proposes a novel reinjection circuitry which is capable of producing a 7-level reinjection current. It is shown that this reinjection current effectively increases the pulse number of the converter to 72. The use of PSCAD/EMTDC simulation validates the functionality of the proposed concept illustrating its effectiveness on both AC and DC sides of the converter.

AITPM Email Newsletter Volume 0905, June 2009 : President's Message

President’s Message Hello fellow AITPM members, Due to three colliding forces of nature I find myself writing this month’s message from home – today, I am still getting over a persistent virus that seemed to set in just after returning from Singapore a couple of weeks ago, which my diabetes won’t let me get away with too easily (no Kermit the Frog swine flu jokes please). Combine this with a very wet day in Brisbane – in fact the wettest for 20 years (how can we complain, except for flash flooding?). And in Queensland today is a state school teachers’ strike, so one half of our brood is over watching TV. Family snapshots aside, the biggest news for our industry of late is the $8.5 billion announced in the Federal Budget for transport infrastructure projects; many “shovel ready”, but some – and fortunate for our profession – desktop ready. This newsletter provides nationwide coverage on the transport infrastructure aspects of the Federal Budget. We’ll need a bit more time to carefully look at the ensuing State Budgets’ announcements. Regarding the federal budget announcements, I am pleased to see serious attention being paid to upgrading the M1 system – I hope to see a motorway standard facility connecting Adelaide to at least Rockhampton in my lifetime. But some other important roads are of course missing out in this particular budget. Various levels of commitment are being made to urban passenger rail – some project significant while others planning significant. Enhancement of suburban rail is important across the capitals and Australia’s medium sized cities such as the Gold Coast and Newcastle. Not much on road safety initiatives jumped out at me, but I believe it is implied in the large road projects and in some of the detail elsewhere. I do believe it’s about time a ‘Vision Zero’ style policy is adopted at the National level, since any death is unacceptable on the road, just as it is in any other workplace. So, overall some good news on building transport infrastructure to keep the economy purring during this recession, and strongly supporting it during future boom times. The other edge to the sword, of course, is that we tax payers will be paying a considerable amount for borrowings for these projects over a long period of time. I close again in reminding everyone again that AITPM’s flagship event, the 2009 AITPM National Conference, Traffic Beyond Tomorrow, is being held in Adelaide from 5 to 7 August. www.aitpm.com has all of the details about how to register, sponsor a booth, session, etc. Best regards all, Jon Bunker

Optimisation of performance in top level athletes : an action-based coping approach : a commentary

INTRODUCTION In their target article, Yuri Hanin and Muza Hanina outlined a novel multidisciplinary approach to performance optimisation for sport psychologists called the Identification-Control-Correction (ICC) programme. According to the authors, this empirically-verified, psycho-pedagogical strategy is designed to improve the quality of coaching and consistency of performance in highly skilled athletes and involves a number of steps including: (i) identifying and increasing self-awareness of ‘optimal’ and ‘non-optimal’ movement patterns for individual athletes; (ii) learning to deliberately control the process of task execution; and iii), correcting habitual and random errors and managing radical changes of movement patterns. Although no specific examples were provided, the ICC programme has apparently been successful in enhancing the performance of Olympic-level athletes. In this commentary, we address what we consider to be some important issues arising from the target article. We specifically focus attention on the contentious topic of optimization in neurobiological movement systems, the role of constraints in shaping emergent movement patterns and the functional role of movement variability in producing stable performance outcomes. In our view, the target article and, indeed, the proposed ICC programme, would benefit from a dynamical systems theoretical backdrop rather than the cognitive scientific approach that appears to be advocated. Although Hanin and Hanina made reference to, and attempted to integrate, constructs typically associated with dynamical systems theoretical accounts of motor control and learning (e.g., Bernstein’s problem, movement variability, etc.), these ideas required more detailed elaboration, which we provide in this commentary.

Virtual reality or virtually real : blended teaching and learning in a Master's level research methods class

This paper examines the enabling effect of using blended learning and synchronous internet mediated communication technologies to improve learning and develop a Sense of Community (SOC) in a group of post-graduate students consisting of a mix of on-campus and off-campus students. Both quantitative and qualitative data collected over a number of years supports the assertion that the blended learning environment enhanced both teaching and learning. The development of a SOC was pivotal to the success of the blended approach when working with geographically isolated groups within a single learning environment.

Interestingness Measures for Multi-Level Association Rules

Association rule mining is one technique that is widely used when querying databases, especially those that are transactional, in order to obtain useful associations or correlations among sets of items. Much work has been done focusing on efficiency, effectiveness and redundancy. There has also been a focusing on the quality of rules from single level datasets with many interestingness measures proposed. However, with multi-level datasets now being common there is a lack of interestingness measures developed for multi-level and cross-level rules. Single level measures do not take into account the hierarchy found in a multi-level dataset. This leaves the Support-Confidence approach,which does not consider the hierarchy anyway and has other drawbacks, as one of the few measures available. In this paper we propose two approaches which measure multi-level association rules to help evaluate their interestingness. These measures of diversity and peculiarity can be used to help identify those rules from multi-level datasets that are potentially useful.