Editorial : is it the time for railway industry to reinvent itself?

Editorial: is it the time for railway industry to reinvent itself? Railway infrastructure plays a critical role in urban development, mobility, and economic growth of society. This focus issue of the Electronic Journal of Structural Engineering is devoted to a special theme, “Advances in Rail Track Infrastructure and Practice - ARTRP”. It contains articles, which were rigorously peer reviewed and accepted from a list of invited manuscripts that demonstrate significant innovation in the area of the structural engineering aspects of the rail track infrastructure...

A tag-based personalized item recommendation system using tensor modeling and topic model approaches

This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment item, tag>, should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.

A new approach to spatial data interpolation using higher-order statistics

Interpolation techniques for spatial data have been applied frequently in various fields of geosciences. Although most conventional interpolation methods assume that it is sufficient to use first- and second-order statistics to characterize random fields, researchers have now realized that these methods cannot always provide reliable interpolation results, since geological and environmental phenomena tend to be very complex, presenting non-Gaussian distribution and/or non-linear inter-variable relationship. This paper proposes a new approach to the interpolation of spatial data, which can be applied with great flexibility. Suitable cross-variable higher-order spatial statistics are developed to measure the spatial relationship between the random variable at an unsampled location and those in its neighbourhood. Given the computed cross-variable higher-order spatial statistics, the conditional probability density function (CPDF) is approximated via polynomial expansions, which is then utilized to determine the interpolated value at the unsampled location as an expectation. In addition, the uncertainty associated with the interpolation is quantified by constructing prediction intervals of interpolated values. The proposed method is applied to a mineral deposit dataset, and the results demonstrate that it outperforms kriging methods in uncertainty quantification. The introduction of the cross-variable higher-order spatial statistics noticeably improves the quality of the interpolation since it enriches the information that can be extracted from the observed data, and this benefit is substantial when working with data that are sparse or have non-trivial dependence structures.

Delivering crushed paracetamol tablets using thickened fluids : does it alter the pharmacokinetics?

Dysphagia, often associated with conditions such as stroke, Parkinson’s disease, multiple sclerosis, and dementia, causes patients to have difficulty with swallowing food and/or liquids. These patients require their fluids to be thickened using gum-based thickening powders in order to facilitate safe swallowing. These thickened fluids are also used as a vehicle for delivery of crushed medicines. Our in vitro measurements suggest that thickened fluids can delay and reduce the dissolution of a number of medications. This study was conducted to assess the impact of the use of thickened fluids on the clinical pharmacokinetics of oral paracetamol. METHODS 20 Healthy volunteers were administered a single oral dose (1g) of paracetamol as either whole tablets, crushed with water, crushed with semi-solid jam, or crushed with thickened fluid according to a randomised, crossover design. Saliva samples were collected periodically over 8 hr and paracetamol concentration analysed by HPLC-UV. Non-compartmental pharmacokinetic analysis was conducted using Winnonlin®. RESULTS The mean peak concentration (Cmax) of paracetamol ranged between 5.62 – 8.00 μg/mL. Comparison between the crushed paracetamol with thickened water (Level 900) and other treatment options (whole, crushed with water, and crushed with jam) showed there was a significant difference in Cmax at 90% CI (p < 0.05). Also, whole tablet had a significant difference in Cmax between crushed with water and crushed with jam. There was no significant difference in AUC irrespective of the treatment. DISCUSSION The use of thickened water resulted in alteration in the absorption kinetics of paracetamol. Given this interaction, co-administration with thickened fluids may have important clinical implications for medications with a narrow therapeutic index.

Adaptive finite element analysis of elliptic problems based on bubble-type local mesh generation

A new mesh adaptivity algorithm that combines a posteriori error estimation with bubble-type local mesh generation (BLMG) strategy for elliptic differential equations is proposed. The size function used in the BLMG is defined on each vertex during the adaptive process based on the obtained error estimator. In order to avoid the excessive coarsening and refining in each iterative step, two factor thresholds are introduced in the size function. The advantages of the BLMG-based adaptive finite element method, compared with other known methods, are given as follows: the refining and coarsening are obtained fluently in the same framework; the local a posteriori error estimation is easy to implement through the adjacency list of the BLMG method; at all levels of refinement, the updated triangles remain very well shaped, even if the mesh size at any particular refinement level varies by several orders of magnitude. Several numerical examples with singularities for the elliptic problems, where the explicit error estimators are used, verify the efficiency of the algorithm. The analysis for the parameters introduced in the size function shows that the algorithm has good flexibility.

The 'gourmet' sausage factory: Keeping it human

Whilst tertiary institutions continue to invest heavily in the technological aspects of online Teaching & Learning (T&L), there does not appear to have been a commensurate investment in the “human” aspects of the use of the technology. Despite the broad recognition that teaching and learning materials need to be adapted for and to the onscreen medium, little attention appears to have been paid thus far to the actual people who are delivering it – who equally need to “adapt themselves” to that medium, in order to maximise the benefit of the technology by maximising the human communication skills of those using the online medium – as distinct from the technical skills required to drive and deliver the bits and bytes. The REdelivery Initiative was a direct response to that notion. This paper details – by way of a narrative of one of the workshop participants – that part of the process involving the professional development of academics specifically in and specifically for the digital, online, T&L context, in order to both illuminate and maximise the potential and opportunities afforded by the technology.

Regional avian species declines estimated from volunteer-collected long-term data using List Length Analysis

Long-term systematic population monitoring data sets are rare but are essential in identifying changes in species abundance. In contrast, community groups and natural history organizations have collected many species lists. These represent a large, untapped source of information on changes in abundance but are generally considered of little value. The major problem with using species lists to detect population changes is that the amount of effort used to obtain the list is often uncontrolled and usually unknown. It has been suggested that using the number of species on the list, the "list length," can be a measure of effort. This paper significantly extends the utility of Franklin's approach using Bayesian logistic regression. We demonstrate the value of List Length Analysis to model changes in species prevalence (i.e., the proportion of lists on which the species occurs) using bird lists collected by a local bird club over 40 years around Brisbane, southeast Queensland, Australia. We estimate the magnitude and certainty of change for 269 bird species and calculate the probabilities that there have been declines and increases of given magnitudes. List Length Analysis confirmed suspected species declines and increases. This method is an important complement to systematically designed intensive monitoring schemes and provides a means of utilizing data that may otherwise be deemed useless. The results of List Length Analysis can be used for targeting species of conservation concern for listing purposes or for more intensive monitoring. While Bayesian methods are not essential for List Length Analysis, they can offer more flexibility in interrogating the data and are able to provide a range of parameters that are easy to interpret and can facilitate conservation listing and prioritization. © 2010 by the Ecological Society of America.

Not just what they want, but why they want it: Traditional market research to deep customer insights

Purpose This paper explores advantages and disadvantages of both traditional market research and deep customer insight methods in order to lay the platform for revealing how a relationship between these two domains could be optimised during firm-based innovation. Design/methodology/approach The paper reports on an empirical research study conducted with thirteen Australian based firms engaged in a design-led approach to innovation. Firms were facilitated through a design-led approach where the process of gathering deep customer insights was isolated and investigated further in comparison to traditional market research methods. Findings Results show that deep customer insight methods are able to provide fresh, non-obvious ways of understanding customer needs, problems and behaviours that can become the foundation of new business opportunities. Findings concluded that deep customer insights methods provide the critical layer to understand why customers do and don’t engage with businesses. Revealing why was not accessible in traditional market research methods. Research limitations/implications The theoretical outcome of this study is a complementary methods matrix, providing guidance on appropriate implementation of research methods in accordance with a project’s timeline to optimise the complementation of traditional market research methods with design-led customer engagement methods. Practical implications Deep customer insight methods provide fresh, non-obvious ways of understanding customer needs, problems and behaviours that can become the foundation of new business opportunities. It is hoped that those in a position of data collection are encouraged to experiment and use deep customer insight methods to connect with their customers on a meaningful level and translate these insights into value. Originality/value This paper provides original value to a new understanding how design techniques can be applied to compliment and strengthen existing market research strategies. This is crucial in an era where business competition hinges on a subtle and often intimate understanding of customer needs and behaviours.

High order unconditionally stable difference schemes for the Riesz space-fractional telegraph equation

In this paper, a class of unconditionally stable difference schemes based on the Pad´e approximation is presented for the Riesz space-fractional telegraph equation. Firstly, we introduce a new variable to transform the original dfferential equation to an equivalent differential equation system. Then, we apply a second order fractional central difference scheme to discretise the Riesz space-fractional operator. Finally, we use (1, 1), (2, 2) and (3, 3) Pad´e approximations to give a fully discrete difference scheme for the resulting linear system of ordinary differential equations. Matrix analysis is used to show the unconditional stability of the proposed algorithms. Two examples with known exact solutions are chosen to assess the proposed difference schemes. Numerical results demonstrate that these schemes provide accurate and efficient methods for solving a space-fractional hyperbolic equation.

Generalized element load method for first- and second-order element solutions with element load effect

The finite element method in principle adaptively divides the continuous domain with complex geometry into discrete simple subdomain by using an approximate element function, and the continuous element loads are also converted into the nodal load by means of the traditional lumping and consistent load methods, which can standardise a plethora of element loads into a typical numerical procedure, but element load effect is restricted to the nodal solution. It in turn means the accurate continuous element solutions with the element load effects are merely restricted to element nodes discretely, and further limited to either displacement or force field depending on which type of approximate function is derived. On the other hand, the analytical stability functions can give the accurate continuous element solutions due to element loads. Unfortunately, the expressions of stability functions are very diverse and distinct when subjected to different element loads that deter the numerical routine for practical applications. To this end, this paper presents a displacement-based finite element function (generalised element load method) with a plethora of element load effects in the similar fashion that never be achieved by the stability function, as well as it can generate the continuous first- and second-order elastic displacement and force solutions along an element without loss of accuracy considerably as the analytical approach that never be achieved by neither the lumping nor consistent load methods. Hence, the salient and unique features of this paper (generalised element load method) embody its robustness, versatility and accuracy in continuous element solutions when subjected to the great diversity of transverse element loads.

Application of higher-order spectra for automated grading of diabetic maculopathy

Diabetic macular edema (DME) is one of the most common causes of visual loss among diabetes mellitus patients. Early detection and successive treatment may improve the visual acuity. DME is mainly graded into non-clinically significant macular edema (NCSME) and clinically significant macular edema according to the location of hard exudates in the macula region. DME can be identified by manual examination of fundus images. It is laborious and resource intensive. Hence, in this work, automated grading of DME is proposed using higher-order spectra (HOS) of Radon transform projections of the fundus images. We have used third-order cumulants and bispectrum magnitude, in this work, as features, and compared their performance. They can capture subtle changes in the fundus image. Spectral regression discriminant analysis (SRDA) reduces feature dimension, and minimum redundancy maximum relevance method is used to rank the significant SRDA components. Ranked features are fed to various supervised classifiers, viz. Naive Bayes, AdaBoost and support vector machine, to discriminate No DME, NCSME and clinically significant macular edema classes. The performance of our system is evaluated using the publicly available MESSIDOR dataset (300 images) and also verified with a local dataset (300 images). Our results show that HOS cumulants and bispectrum magnitude obtained an average accuracy of 95.56 and 94.39 % for MESSIDOR dataset and 95.93 and 93.33 % for local dataset, respectively.

How the energy sector could get it wrong with cloud computing

Cloud computing has significantly impacted a broad range of industries, but these technologies and services have been absorbed throughout the marketplace unevenly. Some industries have moved aggressively towards cloud computing, while others have moved much more slowly. For the most part, the energy sector has approached cloud computing in a measured and cautious way, with progress often in the form of private cloud solutions rather than public ones, or hybridized information technology systems that combine cloud and existing non-cloud architectures. By moving towards cloud computing in a very slow and tentative way, however, the energy industry may prevent itself from reaping the full benefit that a more complete migration to the public cloud has brought about in several other industries. This short communication is accordingly intended to offer a high-level overview of cloud computing, and to put forward the argument that the energy sector should make a more complete migration to the public cloud in order to unlock the major system-wide efficiencies that cloud computing can provide. Also, assets within the energy sector should be designed with as much modularity and flexibility as possible so that they are not locked out of cloud-friendly options in the future.

The Jean Chretien Pledge to Africa act: Patent law and humanitarian aid

This article evaluates the implementation of the WTO General Council Decision in 2003, which resolved that developed nations could export patented pharmaceutical drugs to member states in order to address public health issues - such as HIV/AIDS, tuberculosis, malaria and other epidemics. The Jean Chretien Pledge to Africa Act 2004 (Canada) provides authorisation for the export of pharmaceutical drugs from Canada to developing countries to address public health epidemics. The European Union has issued draft regulations governing the export of pharmaceutical drugs. A number of European countries - including Norway, the Netherlands, France, and Switzerland - are seeking to pass domestic legislation to give force to the WTO General Council Decision. Australia has shown little initiative in seeking to implement such international agreements dealing with access to essential medicines. It is argued that Australia should implement humanitarian legislation to embody the WTO General Council Decision, emulating models in Canada, Norway, and the European Union. Ideally, there should be no right of first refusal; the list of pharmaceutical drugs should be open-ended; and the eligible importing countries should not be limited to members of the WTO.

“Well it depends on what you’d call play”: Parent perspectives on play in Queensland’s Preparatory Year

In the context of recent education reform, Queensland’s Preparatory Year (Prep) is undergoing a period of significant change. The framing of Prep under a new national curriculum reflects a shift from its play-based roots to a formalised subject-based approach. This shift coincides with suggestions that parents may favour more formalised approaches to teaching and learning in the early years. This paper reports on two studies in which parents were interviewed about their views of play in Prep. Data were analysed thematically, with a focus on themes used by parents to talk about play. While parents broadly valued play, the findings suggest that parent participation greatly influenced their acceptance of play-based learning in the formal learning context of Prep. The findings raise implications for educators in fostering strong parent-teacher partnerships in order to facilitate improved parental understanding and support of play in early childhood programs.

Let's do it: A framework to investigate the affordances of experimental learning environments

BACKGROUND Experimental learning, traditionally conducted in on-campus laboratory venues, is the cornerstone of science and engineering education. In order to ensure that engineering graduates are exposed to ‘real-world’ situations and attain the necessary professional skill-sets, as mandated by course accreditation bodies such as Engineers Australia, face-to-face laboratory experimentation with real equipment has been an integral component of traditional engineering education. The online delivery of engineering coursework endeavours to mimic this with remote and simulated laboratory experimentation. To satisfy student and accreditation requirements, the common practice has been to offer equivalent remote and/or simulated laboratory experiments in lieu of the ones delivered, face-to face, on campus. The current implementations of both remote and simulated laboratories tend to be specified with a focus on technical characteristics, instead of pedagogical requirements. This work attempts to redress this situation by developing a framework for the investigation of the suitability of different experimental educational environments to deliver quality teaching and learning. PURPOSE For the tertiary education sector involved with technical or scientific training, a research framework capable of assessing the affordances of laboratory venues is an important aid during the planning, designing and evaluating stages of face-to-face and online (or cyber) environments that facilitate student experimentation. Providing quality experimental learning venues has been identified as one of the distance-education providers’ greatest challenges. DESIGN/METHOD The investigation draws on the expertise of staff at three Australian universities: Swinburne University of Technology (SUT), Curtin University (Curtin) and Queensland University of Technology (QUT). The aim was to analyse video recorded data, in order to identify the occurrences of kikan-shido (a Japanese term meaning ‘between desks instruction’ and over-the-shoulder learning and teaching (OTST/L) events, thereby ascertaining the pedagogical affordances in face-to-face laboratories. RESULTS These will be disseminated at a Master Class presentation at this conference. DISCUSSION Kikan-shido occurrences did reflect on the affordances of the venue. Unlike with other data collection methods, video recorded data and its analysis is repeatable. Participant bias is minimised or even eradicated and researcher bias tempered by enabling re-coding by others. CONCLUSIONS Framework facilitates the identification of experiential face-to-face learning venue affordances. Investigation will continue with on-line venues.