A framework for Australian Universities and public libraries supporting regional, rural and remote students
- Authors: Partridge, Helen , Power, Emma , Ostini, Jenny , Owen, Sue , Pizzani, Blanca
- Date: 2021
- Type: Text , Journal article
- Relation: Journal of the Australian Library and Information Association Vol. 70, no. 4 (2021), p. 391-404
- Full Text: false
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- Description: University students living in regional, rural and remote (RRR) communities of Australia face unique challenges including geographical isolation, lack of access to face-to-face support, and technological barriers. This paper outlines a project funded by the Australian Government’s Higher Education Participation and Partnerships Program that was undertaken by five universities with significant enrolments of students from low socio-economic backgrounds living in RRR communities. The project established a Framework for Australian Universities and Public Libraries Supporting Regional, Rural and Remote Students that provides a set of strategic recommendations that will guide the development of accessible, relevant and sustainable study and learning support to meet the needs of low socio-economic students living in RRR communities. This national project provided a unique opportunity for Australia’s universities and public libraries to work together in order to ‘future proof’ the education of students from low socio-economic backgrounds living in regional and remote communities. © 2021 Helen Partridge, Emma Power, Jenny Ostini, Sue Owen and Blanca Pizzani.
A framework for data privacy and security accountability in data breach communications
- Authors: Thomas, Louise , Gondal, Iqbal , Oseni, Taiwo , Firmin, Sally
- Date: 2022
- Type: Text , Journal article
- Relation: Computers and Security Vol. 116, no. (2022), p.
- Full Text: false
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- Description: Organisations need to take steps to protect the privacy and security of the personal information they hold. However, when data is breached, how do individuals know whether the organisation took reasonable steps to protect their data? When breached organisations notify affected individuals, this communication is likely to be one of the few windows into the incident from the outside and can become an important artefact for research. This desktop study aimed to consider the extent to which publicly available Australian data breach communications reflect data privacy and security best practices. This paper presents a brief review of literature and government guidance on data security and privacy best practices, along with the results of a qualitative content analysis of 33 publicly available Australian data breach communications. This analysis illustrated that there was little reflection of data privacy and security practices. Literature, government guidance and the content analysis were used to inform and develop a new voluntary framework for organisations. This consists of a series of evaluation questions divided into two broad categories: responsible data management and responsible portrayal of the breach. The framework has the potential to help organisations plan the inclusion of data privacy and security management aspects in their data breach communications. This could assist organisations to address their legal and ethical responsibility to account for their actions in managing privacy and security of the personal data they hold. © 2022
A framework for the design and development of physical employment tests and standards
- Authors: Payne, Warren , Harvey, Jack
- Date: 2010
- Type: Text , Journal article
- Relation: Ergonomics Vol. 53, no. 7 (2010), p. 858-871
- Full Text: false
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- Description: Because operational tasks in the uniformed services (military, police, fire and emergency services) are physically demanding and incur the risk of injury, employment policy in these services is usually competency based and predicated on objective physical employment standards (PESs) based on physical employment tests (PETs). In this paper, a comprehensive framework for the design of PETs and PESs is presented. Three broad approaches to physical employment testing are described and compared: generic predictive testing; task-related predictive testing; task simulation testing. Techniques for the selection of a set of tests with good coverage of job requirements, including job task analysis, physical demands analysis and correlation analysis, are discussed. Regarding individual PETs, theoretical considerations including measurability, discriminating power, reliability and validity, and practical considerations, including development of protocols, resource requirements, administrative issues and safety, are considered. With regard to the setting of PESs, criterion referencing and norm referencing are discussed. Statement of Relevance: This paper presents an integrated and coherent framework for the development of PESs and hence provides a much needed theoretically based but practically oriented guide for organisations seeking to establish valid and defensible PESs. © 2010 Taylor & Francis.
A framework for the etiology of running-related injuries
- Authors: Bertelsen, Michael , Hulme, Adam , Petersen, Jesper , Brund, Rene , Sørensen, Henrik , Finch, Caroline , Parner, Erik , Nielsen, Rasmus
- Date: 2017
- Type: Text , Journal article , Review
- Relation: Scandinavian Journal of Medicine and Science in Sports Vol. 27, no. 11 (2017), p. 1170-1180
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- Description: The etiology of running-related injury is important to consider as the effectiveness of a given running-related injury prevention intervention is dependent on whether etiologic factors are readily modifiable and consistent with a biologically plausible causal mechanism. Therefore, the purpose of the present article was to present an evidence-informed conceptual framework outlining the multifactorial nature of running-related injury etiology. In the framework, four mutually exclusive parts are presented: (a) Structure-specific capacity when entering a running session; (b) structure-specific cumulative load per running session; (c) reduction in the structure-specific capacity during a running session; and (d) exceeding the structure-specific capacity. The framework can then be used to inform the design of future running-related injury prevention studies, including the formation of research questions and hypotheses, as well as the monitoring of participation-related and non-participation-related exposures. In addition, future research applications should focus on addressing how changes in one or more exposures influence the risk of running-related injury. This necessitates the investigation of how different factors affect the structure-specific load and/or the load capacity, and the dose-response relationship between running participation and injury risk. Ultimately, this direction allows researchers to move beyond traditional risk factor identification to produce research findings that are not only reliably reported in terms of the observed cause-effect association, but also translatable in practice. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
A fully automated breast cancer recognition system using discrete-gradient based clustering and multi category feature selection
- Authors: Ghosh, Ranadhir , Ghosh, Moumita , Yearwood, John
- Date: 2005
- Type: Text , Journal article
- Relation: Journal of Advanced Computational Intelligence and Intelligent Informatics Vol. 9, no. 3 (2005), p. 244-256
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- Description: Advances in machine intelligence have provided a whole new window of opportunities in medical research. Building a fully automated computer aided diagnostic system for digital mammograms is just one of them. Given some success with semi-automated systems earlier, a fully automated CAD system is just another step forward. A proper combination of a feature selection model and a classifier for those areas of a mammogram marked by radiologists has been very successful. However a fully automated system with only two modules is a time consuming process as the suspicious areas in a mammogram can be quite small when compared to the whole image. Thus an additional clustering process can help in reducing the time complexity of the overall process. In this paper we propose a fast clustering process to identify suspicious areas. Another novelty of this paper is a multi-category feature selection approach. The choice of features to represent the patterns affects several aspects of pattern recognition problems such as accuracy, required learning time and the required number of samples. In this paper we propose a hybrid canonical based feature extraction technique as a combination of an evolutionary algorithm based classifier with a feed forward MLP model.
- Description: C1
- Description: 2003001358
A fully automated offline handwriting recognition system incorporating rule based neural network validated segmentation and hybrid neural network classifier
- Authors: Ghosh, Moumita , Ghosh, Ranadhir , Verma, Brijesh
- Date: 2004
- Type: Text , Journal article
- Relation: International Journal of Pattern Recognition and Artificial Intelligence Vol. 18, no. 7 (Nov 2004), p. 1267-1283
- Full Text: false
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- Description: In this paper we propose a fully automated offline handwriting recognition system that incorporates rule based segmentation, contour based feature extraction, neural network validation, a hybrid neural network classifier and a hamming neural network lexicon. The work is based on our earlier promising results in this area using heuristic segmentation and contour based feature extraction. The segmentation is done using many heuristic based set of rules in an iterative manner and finally followed by a neural network validation system. The extraction of feature is performed using both contour and structure based feature extraction algorithm. The classification is performed by a hybrid neural network that incorporates a hybrid combination of evolutionary algorithm and matrix based solution method. Finally a hamming neural network is used as a lexicon. A benchmark dataset from CEDAR has been used for training and testing- Author
- Description: C1
- Description: 2003000867
A fuzzy derivative approach to classification of outcomes from the ADRAC database
- Authors: Mammadov, Musa , Saunders, Gary , Yearwood, John
- Date: 2004
- Type: Text , Journal article
- Relation: International Transactions in Operational Research Vol. 11, no. 2 (2004), p. 169-180
- Full Text: false
- Reviewed:
- Description: The Australian Adverse Drug Reaction Advisory Committee (ADRAC) database has been collected and maintained by the Therapeutic Goods Administration. In this paper we study a part of his database (Card2) which contains records having just reactions from the Cardiovascular group. Drug-reaction relationships are presented by a vector of degrees which shows the degree of association of a drug with each class of reactions. In this work we examine these relationships in the classification of reaction outcomes. A modified version of the fuzzy derivative method (FDM2) is used for classification.
- Description: C1
- Description: 2003000895
A fuzzy logic approach to experience based
- Authors: Sun, Zhaohao , Finnie, Gavin
- Date: 2007
- Type: Text , Journal article
- Relation: International Journal of Intelligent Systems Vol. 22, no. 8 (2007), p. 867-889
- Full Text: false
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- Description: International Journal of Intelligent Systems archive Volume 22 Issue 8, August 2007 John Wiley & Sons, Inc. New York, NY, USA table of contents doi>10.1002/int.v22:8
A general stochastic clustering method for automatic cluster discovery
- Authors: Tan, Swee , Ting, Kaiming , Teng, Shyh
- Date: 2011
- Type: Text , Journal article
- Relation: Pattern Recognition Vol. 44, no. 10-11 (2011), p. 2786-2799
- Full Text: false
- Reviewed:
- Description: Finding clusters in data is a challenging problem. Given a dataset, we usually do not know the number of natural clusters hidden in the dataset. The problem is exacerbated when there is little or no additional information except the data itself. This paper proposes a general stochastic clustering method that is a simplification of nature-inspired ant-based clustering approach. It begins with a basic solution and then performs stochastic search to incrementally improve the solution until the underlying clusters emerge, resulting in automatic cluster discovery in datasets. This method differs from several recent methods in that it does not require users to input the number of clusters and it makes no explicit assumption about the underlying distribution of a dataset. Our experimental results show that the proposed method performs better than several existing methods in terms of clustering accuracy and efficiency in majority of the datasets used in this study. Our theoretical analysis shows that the proposed method has linear time and space complexities, and our empirical study shows that it can accurately and efficiently discover clusters in large datasets in which many existing methods fail to run.
A generalization of the Remez algorithm to a class of linear spline approximation problems with constraints on spline parameters
- Authors: Sukhorukova, Nadezda
- Date: 2008
- Type: Text , Journal article
- Relation: Optimization Methods and Software Vol. 23, no. 5 (2008), p. 793-810
- Full Text: false
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- Description: The classical Remez algorithm was developed for constructing the best polynomial approximations for continuous and discrete functions in an interval [a, b]. In this paper, the classical Remez algorithm is generalized to the problem of linear spline approximation with certain conditions on the spline parameters. Namely, the spline parameters have to be nonnegative and the values of the splines at one of the borders (or both borders) of the approximation intervals may be fixed. This type of constraint occurs in some practical applications, e.g. the problem of taxation tables restoration. The results of the numerical experiments with a Remez-like algorithm developed for this class of conditional optimization problems, are presented.
- Description: C1
A generalized subgradient method with piecewise linear subproblem
- Authors: Bagirov, Adil , Ganjehlou, Asef Nazari , Tor, Hakan , Ugon, Julien
- Date: 2010
- Type: Text , Journal article
- Relation: Dynamics of Continuous, Discrete and Impulsive Systems Series B: Applications and Algorithms Vol. 17, no. 5 (2010), p. 621-638
- Full Text: false
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- Description: In this paper, a new version of the quasisecant method for nonsmooth nonconvex optimization is developed. Quasisecants are overestimates to the objective function in some neighborhood of a given point. Subgradients are used to obtain quasisecants. We describe classes of nonsmooth functions where quasisecants can be computed explicitly. We show that a descent direction with suffcient decrease must satisfy a set of linear inequalities. In the proposed algorithm this set of linear inequalities is solved by applying the subgradient algorithm to minimize a piecewise linear function. We compare results of numerical experiments between the proposed algorithm and subgradient method. Copyright © 2010 Watam Press.
A generic ensemble approach to estimate multidimensional likelihood in Bayesian classifier learning
- Authors: Aryal, Sunil , Ting, Kaiming
- Date: 2016
- Type: Text , Journal article
- Relation: Computational Intelligence Vol. 32, no. 3 (2016), p. 458-479
- Full Text: false
- Reviewed:
- Description: In Bayesian classifier learning, estimating the joint probability distribution (,) or the likelihood (|) directly from training data is considered to be difficult, especially in large multidimensional data sets. To circumvent this difficulty, existing Bayesian classifiers such as Naive Bayes, BayesNet, and ADE have focused on estimating simplified surrogates of (,) from different forms of one‐dimensional likelihoods. Contrary to the perceived difficulty in multidimensional likelihood estimation, we present a simple generic ensemble approach to estimate multidimensional likelihood directly from data. The idea is to aggregate (|) estimated from a random subsample of data . This article presents two ways to estimate multidimensional likelihoods using the proposed generic approach and introduces two new Bayesian classifiers called and that estimate (|) using a nearest‐neighbor density estimation and a probability estimation through feature space partitioning, respectively. Unlike the existing Bayesian classifiers, ENNBayes and MassBayes have constant training time and space complexities and they scale better than existing Bayesian classifiers in very large data sets. Our empirical evaluation shows that ENNBayes and MassBayes yield better predictive accuracy than the existing Bayesian classifiers in benchmark data sets.
A geometric design model for the circolimacon positive displacement machine
- Authors: Sultan, Ibrahim
- Date: 2008
- Type: Text , Journal article
- Relation: Journal of Mechanical Design Vol. 130, no. 6 (Jun 2008), p. 8
- Full Text: false
- Reviewed:
- Description: A circolimacon positive displacement machine is driven by a lima on mechanism, but the profiles of its rotor and housing are circular arcs. As such, its design models are different from those of the lima on-to-lima on machines, whose profiles are cut to the limacon equations. For the benefit of the reader the paper starts with a brief background on the general geometric aspects of the limacon fluid processing technology. However the focus is then turned to the circolimacon machine, where its design parameters are introduced and geometric models are proposed to assist with the design process. Also, a computational inverse design model has been employed to work out a set of congruent geometric parameters to meet certain design requirements. Case studies are presented at the end of the paper to give the reader a numerical perspective on the design process of this class of positive displacement machines.
- Description: C1
A global optimization approach to classification
- Authors: Bagirov, Adil , Rubinov, Alex , Yearwood, John
- Date: 2002
- Type: Text , Journal article
- Relation: Optimization and Engineering Vol. 9, no. 7 (2002), p. 129-155
- Full Text: false
- Reviewed:
- Description: In this paper is presented an hybrid algorithm for finding the absolute extreme point of a multimodal scalar function of many variables. The algorithm is suitable when the objective function is expensive to compute, the computation can be affected by noise and/or partial derivatives cannot be calculated. The method used is a genetic modification of a previous algorithm based on the Prices method. All information about behavior of objective function collected on previous iterates are used to chose new evaluation points. The genetic part of the algorithm is very effective to escape from local attractors of the algorithm and assures convergence in probability to the global optimum. The proposed algorithm has been tested on a large set of multimodal test problems outperforming both the modified Prices algorithm and classical genetic approach.
- Description: C1
- Description: 2003000061
A global review of the invasive aquatic weed Cabomba caroliniana [A. Gray] (Carolina fanwort) : current and future management challenges, and research gaps
- Authors: Roberts, Jason , Florentine, Singarayer
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Weed Research Vol. 62, no. 1 (2022), p. 75-84
- Full Text: false
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- Description: Cabomba caroliniana [A. Gray] (Cabombaceae), also known as Carolina fanwort, is a native of South America which has now become a serious invasive threat to aquatic systems across the world. Its capacity to inundate a water column with active fragments and seeds makes the containment and management of C. caroliniana a challenging task and an ecological and economic necessity. Previous and current management efforts have been largely focussed on biological control, drawdown methods, herbicide application, manual removal, shading and the use of a concentrated urea solution. Although these methods have shown some success in reducing large infestations, they are generally considered to be unreliable when used alone since they are unable to contain or reduce the species in the long term with a single-use treatment protocol. It is feared that, without effective, improved and integrated management strategies, C. caroliniana will continue to invade aquatic ecosystems beyond its already wide current distribution, thus causing increased global economic and environmental damage. This review will therefore explore the biology and distribution of C. caroliniana and examine the current and previous attempts for its global management. It will also evaluate the most successful current treatments and clarify where research efforts are urgently needed for the improved long-term extirpation of this aquatic invader. © 2021 European Weed Research Society
A golden connection: Exploring the challenges of developing interpretation strategies for a Chinese heritage precinct on the central Victorian goldfields
- Authors: Frost, Warwick , Laing, Jennifer , Reeves, Keir , Wheeler, Fiona
- Date: 2012
- Type: Text , Journal article
- Relation: Historic Environment Vol. 24, no. 1 (2012), p. 35-40
- Full Text: false
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- Description: This article introduces and evaluates heritage tourism interpretation strategies for depicting the Chinese-Australian gold seeking experience across an urban tourism landscape in central Victoria, Australia. The city of Bendigo has its origins in the nineteenth century goldrushes and contains a variety of heritage sites, most notably those connected with the Chinese migration to the region in search of gold. These sites, including a temple, museum, cemetery, and kiln site, form arguably one of the most complete collections of Chinese goldrush heritage assets still in existence across the globe and have the potential to be marketed to visitors as a Chinese heritage precinct. They provide a direct familial and cultural nexus between southern China and Australia, yet also highlight a complex historical encounter that requires development of visitor interpretation to bring the stories to life and provide meaning and tourist appeal. This article, using a cultural landscape model, will evaluate the way in which key historical assets can be understood as heritage tourism attractions in the present day and the role of interpretation in that process, particularly focusing on the use of podcasts and promotional media films as interpretive tools. It will also consider how thematic interpretation, based on and acknowledging contested narratives, may add to the authenticity of the precinct for visitors and complement the built heritage. The findings suggest that while some of the Chinese heritage sites in Bendigo are successful tourism ventures or have strong tourist potential, overall the tourist experience is fragmented and would benefit from more integrated interpretation strategies that link the various sites across the precinct and the region.
A Grid-based neural network framework for multimodal biometrics
- Authors: Venkatraman, Sitalakshmi
- Date: 2010
- Type: Text , Journal article
- Relation: Proceedings of World Academy of Science, Engineering and Technology Vol. 72, no. (2010), p. 298-303
- Full Text: false
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- Description: Recent scientific investigations indicate that multimodal biometrics overcome the technical limitations of unimodal biometrics, making them ideally suited for everyday life applications that require a reliable authentication system. However, for a successful adoption of multimodal biometrics, such systems would require large heterogeneous datasets with complex multimodal fusion and privacy schemes spanning various distributed environments. From experimental investigations of current multimodal systems, this paper reports the various issues related to speed, error-recovery and privacy that impede the diffusion of such systems in real-life. This calls for a robust mechanism that caters to the desired real-time performance, robust fusion schemes, interoperability and adaptable privacy policies. The main objective of this paper is to present a framework that addresses the abovementioned issues by leveraging on the heterogeneous resource sharing capacities of Grid services and the efficient machine learning capabilities of artificial neural networks (ANN). Hence, this paper proposes a Grid-based neural network framework for adopting multimodal biometrics with the view of overcoming the barriers of performance, privacy and risk issues that are associated with shared heterogeneous multimodal data centres. The framework combines the concept of Grid services for reliable brokering and privacy policy management of shared biometric resources along with a momentum back propagation ANN (MBPANN) model of machine learning for efficient multimodal fusion and authentication schemes. Real-life applications would be able to adopt the proposed framework to cater to the varying business requirements and user privacies for a successful diffusion of multimodal biometrics in various day-to-day transactions.
A Grobner-Shirshov Algorithm for Applications in Internet Security
- Authors: Kelarev, Andrei , Yearwood, John , Watters, Paul , Wu, Xinwen , Ma, Liping , Abawajy, Jemal , Pan, L.
- Date: 2011
- Type: Text , Journal article
- Relation: Southeast Asian Bulletin of Mathematics Vol. 35, no. (2011), p. 807-820
- Full Text: false
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- Description: The design of multiple classication and clustering systems for the detection of malware is an important problem in internet security. Grobner-Shirshov bases have been used recently by Dazeley et al. [15] to develop an algorithm for constructions with certain restrictions on the sandwich-matrices. We develop a new Grobner-Shirshov algorithm which applies to a larger variety of constructions based on combinatorial Rees matrix semigroups without any restrictions on the sandwich-matrices.
A handshake and a smile: video-making, young people and mental health
- Authors: Speed, Lesley
- Date: 2010
- Type: Text , Journal article
- Relation: Screen Education Vol. 2010, no. 59 (2010), p. 52-57
- Full Text: false
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- Description: As digital technologies have enabled wider access to means of media production, community uses of digital media have proliferated. This article examines a recent community program that taught basic ideo-making skills to rural young people with mental illness. It aimed to assist the social integration of young people with mental illness and foster self-expression through video-making.
A health justice partnership for young people : strategies for program promotion to young people and youth workers
- Authors: Ollerenshaw, Alison , Camilleri, Margaret
- Date: 2023
- Type: Text , Journal article
- Relation: Australian Journal of Primary Health Vol. 29, no. 5 (2023), p. 422-427
- Full Text: false
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- Description: Health justice partnerships (HJP) are innovative models for delivering integrated health and legal services to people experiencing complex issues. An HJP was established in regional Victoria, Australia, for young people. Promoting the program to young people and workers was essential for program uptake. There is a dearth of published information about strategies that support program promotion for young people and workers. In this practice and innovation paper, three promotional strategies were employed: a dedicated program website, secondary consultations, and legal education and information sessions. Each strategy is examined, with information presented about why and how these strategies were implemented alongside this HJP. The strengths and limitations of each strategy are explored, with some strategies appearing to engage audiences with the program more than others. The insights about each of the strategies established for this program may inform other HJPs with their planning and implementation for increased program awareness. © 2023 The Author(s) (or their employer(s)).