Interpretation of association rules in multi-tier structures

Dealing with the large amount of data resulting from association rule mining is a big challenge. The essential issue is how to provide efficient methods for summarizing and representing meaningful discovered knowledge from databases. This paper presents a new approach called multi-tier granule mining to improve the performance of association rule mining. Rather than using patterns, it uses granules to represent knowledge that is implicitly contained in relational databases. This approach also uses multi-tier structures and association mappings to interpret association rules in terms of granules. Consequently, association rules can be quickly assessed and meaningless association rules can be justified according to these association mappings. The experimental results indicate that the proposed approach is promising

Renormalization group interpretation of the Born and Rytov approximations

In this paper the method of renormalization group (RG) [Phys. Rev. E 54, 376 (1996)] is related to the well-known approximations of Rytov and Born used in wave propagation in deterministic and random media. Certain problems in linear and nonlinear media are examined from the viewpoint of RG and compared with the literature on Born and Rytov approximations. It is found that the Rytov approximation forms a special case of the asymptotic expansion generated by the RG, and as such it gives a superior approximation to the exact solution compared with its Born counterpart. Analogous conclusions are reached for nonlinear equations with an intensity-dependent index of refraction where the RG recovers the exact solution. © 2008 Optical Society of America.

A regional interpretation of rules and good practice for greenhouse accounting : Northern Australian savanna systems

Land-use change, particularly clearing of forests for agriculture, has contributed significantly to the observed rise in atmospheric carbon dioxide concentration. Concern about the impacts on climate has led to efforts to monitor and curtail the rapid increase in concentrations of carbon dioxide and other greenhouse gases in the atmosphere. Internationally, much of the current focus is on the Kyoto Protocol to the United Nations Framework Convention on Climate Change (UNFCCC). Although electing to not ratify the Protocol, Australia, as a party to the UNFCCC, reports on national greenhouse gas emissions, trends in emissions and abatement measures. In this paper we review the complex accounting rules for human activities affecting greenhouse gas fluxes in the terrestrial biosphere and explore implications and potential opportunities for managing carbon in the savanna ecosystems of northern Australia. Savannas in Australia are managed for grazing as well as for cultural and environmental values against a background of extreme climate variability and disturbance, notably fire. Methane from livestock and non-CO2 emissions from burning are important components of the total greenhouse gas emissions associated with management of savannas. International developments in carbon accounting for the terrestrial biosphere bring a requirement for better attribution of change in carbon stocks and more detailed and spatially explicit data on such characteristics of savanna ecosystems as fire regimes, production and type of fuel for burning, drivers of woody encroachment, rates of woody regrowth, stocking rates and grazing impacts. The benefits of improved biophysical information and of understanding the impacts on ecosystem function of natural factors and management options will extend beyond greenhouse accounting to better land management for multiple objectives.

The importance of good data, analysis and interpretation for showing the economics of reducing healthcare-associated infection

To the Editor—In a recent review article in Infection Control and Hospital Epidemiology, Umscheid et al1 summarized published data on incidence rates of catheter-associated bloodstream infection (CABSI), catheter-associated urinary tract infection (CAUTI), surgical site infection (SSI), and ventilator- associated pneumonia (VAP); estimated how many cases are preventable; and calculated the savings in hospital costs and lives that would result from preventing all preventable cases. Providing these estimates to policy makers, political leaders, and health officials helps to galvanize their support for infection prevention programs. Our concern is that important limitations of the published studies on which Umscheid and colleagues built their findings are incompletely addressed in this review. More attention needs to be drawn to the techniques applied to generate these estimates...

A two-stage item recommendation method using probabilistic ranking with reconstructed tensor model

In a tag-based recommender system, the multi-dimensional item, tag> correlation should be modeled effectively for finding quality recommendations. Recently, few researchers have used tensor models in recommendation to represent and analyze latent relationships inherent in multi-dimensions data. A common approach is to build the tensor model, decompose it and, then, directly use the reconstructed tensor to generate the recommendation based on the maximum values of tensor elements. In order to improve the accuracy and scalability, we propose an implementation of the -mode block-striped (matrix) product for scalable tensor reconstruction and probabilistically ranking the candidate items generated from the reconstructed tensor. With testing on real-world datasets, we demonstrate that the proposed method outperforms the benchmarking methods in terms of recommendation accuracy and scalability.

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.

The Artful Interpretation of Science through Picture Books

Science picture books offer pleasurable and educational reading experiences. These texts open up opportunities for cross-curriculum teaching and learning and a means for developing students’ visual literacy skills, aesthetic appreciation, and higher level thinking skills. Picture books demonstrate how one mode or semiotic system (visual and verbal) mediates the other, often complementing, extending, and filling-in the gaps between words and images. Students’ meaning making is further extended when they can understand the subtleties and effects (and affects) of the visual elements of art and design, and the different styles of writing and language use.

Item reputation-aware recommender systems

Recommender systems provide personalized advice for customers online based on their own preferences, while reputation systems generate a community advice on the quality of items on the Web. Both systems use users’ ratings to generate their output. In this paper, we propose to combine reputation models with recommender systems to enhance the accuracy of recommendations. The main contributions include two methods for merging two ranked item lists which are generated based on recommendation scores and reputation scores, respectively, and a personalized reputation method to generate item reputations based on users’ interests. The proposed merging methods can be applicable to any recommendation methods and reputation methods, i.e., they are independent from generating recommendation scores and reputation scores. The experiments we conducted showed that the proposed methods could enhance the accuracy of existing recommender systems.

Reterritorializing multimodal design in the classroom through a socially mediated Indigenous heritage

National or International Significance Flows of cultural heritage in textual practices are vital to sustaining Indigenous communities - a national and international priority (Commonwealth of Australia, 2011). Indigenous heritage, whether passed on by oral tradition or ubiquitous social media, can be seen as a "conversation between the past and the future" (Fairclough, 2012, p. xv). Indigenous heritage involves appropriating memories within a cultural flow to pass on a spiritual legacy. This presentation reports ethnographic research of social media practices in a small independent Aboriginal school in Southeast Queensland, Australia that is resided over by the Yuggera elders and an Aboriginal principal. Quality of Research The purpose was to rupture existing notions of white literacies in schools, and to deterritorialize the uses of digital media by dominant cultures in the public sphere. Examples of learning experiences included the following: i. Integrating Indigenous language and knowledge into media text production; ii. Classroom visits from Indigenous elders; and iii. Publishing oral histories through digital scrapbooking. The program aligned with the Australian National Curriculum English (ACARA, 2014), which mandates the teaching of multimodal text creation. Data sources included a class set of digital scrapbooks collaboratively created in a preparatory-one primary classroom. The digital scrapbooks combined digitally encoded words, images of material artifacts, and digital music files. A key feature of the writing and digital design task was to retell and digitally display and archive a cultural narrative of significance to the Indigenous Australian community and its memories and material traces of the past for the future. Data analysis of the students' digital stories involved the application of key themes of negotiated, material, and digitally mediated forms of heritage practice. It drew on Australian Indigenous research by Keddie et al. (2013) to guard against the homogenizing of culture that can arise from a focus on a static view of culture. The interpretation of findings located Indigenous appropriation of social media within broader racialized politics that enables Indigenous literacy to be understood as a dynamic, negotiated, and transgenerational flows of practice. It demonstrates that Indigenous children's use of media production reflects "shifting and negotiated identities" in response to changing media environments that can function to sustain Indigenous cultural heritages (Appadurai, 1696, p. xv). Impact on practice, policy or theory The findings are important for teachers at a time when Aboriginal and Torres Strait Islander Histories and Cultures is a cross-curricular policy priority in the Australian Curriculum (ACARA, 2014). The findings show how curriculum policies can be applied to classroom practice in ways that are epistemologically consistent with Indigenous ways of knowing and being. Theoretically, it demonstrates how the children's experiences of culture are layered over time, as successive generations inherit, interweave, and hear others' cultural stories or maps. Practically, recommendations are provided for an approach to appropriating social media in schools that explicitly attends to the dynamic nature of Indigenous practices, negotiated through intercultural constructions and flows, and opening space for a critical anti-racist approach to multimodal text production. Timeliness The research is timely in the context of the accessibility and role of digital and multimodal forms of communication, including for Aboriginal and Torres Strait Islander communities.

A survey of radiographers' confidence and self-perceived accuracy in frontline image interpretation and their continuing educational preferences

Introduction The provision of a written comment on traumatic abnormalities of the musculoskeletal system detected by radiographers can assist referrers and may improve patient management, but the practice has not been widely adopted outside the United Kingdom. The purpose of this study was to investigate Australian radiographers’ perceptions of their readiness for practice in a radiographer commenting system and their educational preferences in relation to two different delivery formats of image interpretation education, intensive and non-intensive. Methods A cross-sectional web-based questionnaire was implemented between August and September 2012. Participants included radiographers with experience working in emergency settings at four Australian metropolitan hospitals. Conventional descriptive statistics, frequency histograms, and thematic analysis were undertaken. A Wilcoxon signed-rank test examined whether a difference in preference ratings between intensive and non-intensive education delivery was evident. Results The questionnaire was completed by 73 radiographers (68% response rate). Radiographers reported higher confidence and self-perceived accuracy to detect traumatic abnormalities than to describe traumatic abnormalities of the musculoskeletal system. Radiographers frequently reported high desirability ratings for both the intensive and the non-intensive education delivery, no difference in desirability ratings for these two formats was evident (z = 1.66,P = 0.11). Conclusions Some Australian radiographers perceive they are not ready to practise in a frontline radiographer commenting system. Overall, radiographers indicated mixed preferences for image interpretation education delivered via intensive and non-intensive formats. Further research, preferably randomised trials, investigating the effectiveness of intensive and non-intensive education formats of image interpretation education for radiographers is warranted.

How to plan and implement an environmental education program for a conservation area : lessons from Australia and Borneo

The Augo Wetland Forest Park, along with other conservation areas around the world, provides an opportunity for a personal connection with the natural world - an opportunity for creating ways to convince people to reverse the degradation of the planet. In this presentation I use the settings approach, as used by the World Health Organisation in health promotion, as a framework. The WHO’s 1986 Ottawa Charter states that "Health is created and lived by people within the settings of their everyday life; where they learn, work, play, and love." I argue that, similarly, a conservation area provides a setting for people to connect with environmental issues and can be the place where positive behaviours and actions for the environment are created and enacted. In a wired and virtual world, such settings may be the only opportunity some people, especially children, get to connect with the environment. An evidence-based, intentionally designed and implemented environmental education program enhances the opportunities for the personal connection and subsequent action. Planning and implementing an Environmental education program for a conservation area requires an understanding of the principles of three domains: • Environmental Communication • Environmental Education • Environmental Interpretation In this presentation I define these domains and demonstrate how they become interdependent within the context of a particular setting such as a conservation area. I outline the principles of each domain and demonstrate how they can be enacted with reference to environmental education program case studies from settings in Australia and Borneo. The first case study is based around a proposal for a planned residential community at Eden’s Crossing, in Brisbane’s high growth Western corridor. The setting featured a number of important natural and heritage conservation characteristics and the developer wanted to be pro-active in informing the market what this development aims to achieve in terms of innovative community and environmental objectives. By designing an education and interpretation program in line with best practice education and interpretation principles the developers would be assisted in their efforts to build community, preserve heritage, and facilitate environmentally sensitive lifestyles for the future residents of Eden’s Crossing. Above all, the strategy focused on advancing sustainability in a way that made the Eden’s Crossing greenfield development significantly greener. It did this by interacting with prospective purchasers, and building knowledge about sustainability with a view to shaping the future community of Eden’s Crossing in terms of attitudes and behaviours. The second case study is based around the development of the Rainforest Interpretation Centre (RIC), now renamed the Rainforest Discovery Centre, an environmental education facility managed by the Sabah Forestry Department (SFD) and located at the edge of the Kabili-Sepilok Forest Reserve in the East Malaysian state of Sabah (Borneo). This setting is of paramount importance for biodiversity conservation and research and a vital habitat for orang utan. As an Environmental Education Consultant I was tasked with developing an environmental education program for this setting as part of the SFD’s long- term strategy towards sustainable forest management. By employing the principles of Environmental Education and Environmental Interpretation I designed and implemented a program with three major components: • an environmental education component for visiting primary and secondary school groups. • an environmental education component for in-service and pre-service teachers and teacher educators. • a public awareness and environmental interpretation component which caters for the general public and tourists. From these modest beginnings the program has expanded and new facilities have been developed to meet the demands of visitors, teachers and students. The effectiveness of the program can be traced back to the grounding in the principles of best practice environmental education, communication and interpretation.

Refining user and item profiles based on multidimensional data for top-n item recommendation

In recommender systems based on multidimensional data, additional metadata provides algorithms with more information for better understanding the interaction between users and items. However, most of the profiling approaches in neighbourhood-based recommendation approaches for multidimensional data merely split or project the dimensional data and lack the consideration of latent interaction between the dimensions of the data. In this paper, we propose a novel user/item profiling approach for Collaborative Filtering (CF) item recommendation on multidimensional data. We further present incremental profiling method for updating the profiles. For item recommendation, we seek to delve into different types of relations in data to understand the interaction between users and items more fully, and propose three multidimensional CF recommendation approaches for top-N item recommendations based on the proposed user/item profiles. The proposed multidimensional CF approaches are capable of incorporating not only localized relations of user-user and/or item-item neighbourhoods but also latent interaction between all dimensions of the data. Experimental results show significant improvements in terms of recommendation accuracy.