Information literacy : a theoretical framework for higher education

Information literacy has been a significant issue in the library community for many years. It is now being recognised as an important issue by the higher education community. This theoretical framework draws together important elements of the information literacy agenda specifically for tertiary educators and administrators. The frame-work examines three areas of primary concern: the possible outcomes of information literacy education (through outlining the characteristics of information literate people); the nature of information literacy education; and the potential role of stake-holders (including information services, faculty, staff developers and learning counsellors) in helping staff and students to be information literate. This theoretical framework forms part of the Griffith University Information Literacy Blueprint. The Blueprint was designed between June and August of 1994. The project, a quality initiative of the Division of Information Services, was led by Janice Rickards, University Librarian.

A framework for security analysis of key derivation functions

This paper presents a comprehensive formal security framework for key derivation functions (KDF). The major security goal for a KDF is to produce cryptographic keys from a private seed value where the derived cryptographic keys are indistinguishable from random binary strings. We form a framework of five security models for KDFs. This consists of four security models that we propose: Known Public Inputs Attack (KPM, KPS), Adaptive Chosen Context Information Attack (CCM) and Adaptive Chosen Public Inputs Attack(CPM); and another security model, previously defined by Krawczyk [6], which we refer to as Adaptive Chosen Context Information Attack(CCS). These security models are simulated using an indistinguisibility game. In addition we prove the relationships between these five security models and analyse KDFs using the framework (in the random oracle model).

A Critical Perspective of the Indonesian Institutional Framework for PPP Toll Roads

The development of toll roads in Indonesia started around 1978. Initially, the management and development of toll roads sat directly under the Government of Indonesia (GoI) being undertaken through PT JasaMarga, a state owned enterprise specifically established to provide toll roads. Due to the slow growth and low capability of toll roads to fulfil infrastructure needs in the first ten years of operation (only 2.688kms/year), GoI changed its strategy in 1989 to one of using private sector participation for roads delivery through a Public Private Partnership (PPP) scheme. In this latter period, PT JasaMarga had two roles, both as regulator on behalf of the private sector as well as being the operator. However, from 1989 to 2004 the growth rate of toll roads actually decreased further to 2.300kms/year. Facing this challenge of low growth rate of toll roads, in 2004GoI changed the toll road management system and the role of regulator was returned to the Government through the establishment of the Toll Road Regulatory Agency (BPJT). GoI also amended the institutional framework to strengthen the toll road management system. Despite the introduction of this new institutional framework, the growth of toll roads still showed insignificant change. This problem in toll road development has generated an urgent need for research into this issue. The aim of the research is to understand the performance of the new institutional framework in enhancing PPP procured toll road development. The methodology of the research was to undertake a questionnaire survey distributed to private sector respondents involved in toll road development. The results of this study show that there are several problems inherent in the institutional framework, but the most significant problem comes from the uncertainty of the function of the strategic executive body in the land expropriation process.

The evolution and biogeography of the austral horse fly tribe Scionini (Diptera: Tabanidae: Pangoniinae) inferred from multiple mitochondrial and nuclear genes

Phylogenetic relationships within the Tabanidae are largely unknown, despite their considerable medical and ecological importance. The first robust phylogenetic hypothesis for the horse fly tribe Scionini is provided, completing the systematic placement of all tribes in the subfamily Pangoniinae. The Scionini consists of seven mostly southern hemisphere genera distributed in Australia, New Guinea, New Zealand and South America. A 5757. bp alignment of 6 genes, including mitochondrial (COI and COII), ribosomal (28S) and nuclear (AATS and CAD regions 1, 3 and 4) genes, was analysed for 176 taxa using both Bayesian and maximum likelihood approaches. Results indicate the Scionini are strongly monophyletic, with the exclusion of the only northern hemisphere genus Goniops. The South American genera Fidena, Pityocera and Scione were strongly monophyletic, corresponding to current morphology-based classification schemes. The most widespread genus Scaptia was paraphyletic and formed nine strongly supported monophyletic clades, each corresponding to either the current subgenera or several previously synonymised genera that should be formally resurrected. Molecular results also reveal a newly recognised genus endemic to New Zealand, formerly placed within Scaptia. Divergence time estimation was employed to assess the global biogeographical patterns in the Pangoniinae. These analyses demonstrated that the Scionini are a typical Gondwanan group whose diversification was influenced by the fragmentation of that ancient land mass. Furthermore, results indicate that the Scionini most likely originated in Australia and subsequently radiated to New Zealand and South American by both long distance dispersal and vicariance. The phylogenetic framework of the Scionini provided herein will be valuable for taxonomic revisions of the Tabanidae.

Homeostatic epistemology : reliability, coherence and coordination in a Bayesian virtue epistemology

How do agents with limited cognitive capacities flourish in informationally impoverished or unexpected circumstances? Aristotle argued that human flourishing emerged from knowing about the world and our place within it. If he is right, then the virtuous processes that produce knowledge, best explain flourishing. Influenced by Aristotle, virtue epistemology defends an analysis of knowledge where beliefs are evaluated for their truth and the intellectual virtue or competences relied on in their creation. However, human flourishing may emerge from how degrees of ignorance are managed in an uncertain world. Perhaps decision-making in the shadow of knowledge best explains human wellbeing—a Bayesian approach? In this dissertation I argue that a hybrid of virtue and Bayesian epistemologies explains human flourishing—what I term homeostatic epistemology. Homeostatic epistemology supposes that an agent has a rational credence p when p is the product of reliable processes aligned with the norms of probability theory; whereas an agent knows that p when a rational credence p is the product of reliable processes such that: 1) p meets some relevant threshold for belief (such that the agent acts as though p were true and indeed p is true), 2) p coheres with a satisficing set of relevant beliefs and, 3) the relevant set of beliefs is coordinated appropriately to meet the integrated aims of the agent. Homeostatic epistemology recognizes that justificatory relationships between beliefs are constantly changing to combat uncertainties and to take advantage of predictable circumstances. Contrary to holism, justification is built up and broken down across limited sets like the anabolic and catabolic processes that maintain homeostasis in the cells, organs and systems of the body. It is the coordination of choristic sets of reliably produced beliefs that create the greatest flourishing given the limitations inherent in the situated agent.

Bayesian modelling of surveillance and proof of freedom : the mathematical, logical & psychological challenges

Keeping exotic plant pests out of our country relies on good border control or quarantine. However with increasing globalization and mobilization some things slip through. Then the back up systems become important. This can include an expensive form of surveillance that purposively targets particular pests. A much wider net is provided by general surveillance, which is assimilated into everyday activities, like farmers checking the health of their crops. In fact farmers and even home gardeners have provided a front line warning system for some pests (eg European wasp) that could otherwise have wreaked havoc. Mathematics is used to model how surveillance works in various situations. Within this virtual world we can play with various surveillance and management strategies to "see" how they would work, or how to make them work better. One of our greatest challenges is estimating some of the input parameters : because the pest hasn't been here before, it's hard to predict how well it might behave: establishing, spreading, and what types of symptoms it might express. So we rely on experts to help us with this. This talk will look at the mathematical, psychological and logical challenges of helping experts to quantify what they think. We show how the subjective Bayesian approach is useful for capturing expert uncertainty, ultimately providing a more complete picture of what they think... And what they don't!

Bayesian survival analysis using gene expression

This thesis developed and applied Bayesian models for the analysis of survival data. The gene expression was considered as explanatory variables within the Bayesian survival model which can be considered the new contribution in the analysis of such data. The censoring factor that is inherent of survival data has also been addressed in terms of its impact on the fitting of a finite mixture of Weibull distribution with and without covariates. To investigate this, simulation study were carried out under several censoring percentages. Censoring percentage as high as 80% is acceptable here as the work involved high dimensional data. Lastly the Bayesian model averaging approach was developed to incorporate model uncertainty in the prediction of survival.

A flexible Bayesian model for describing temporal variability of N2O emissions from an Australian pasture

Soil-based emissions of nitrous oxide (N2O), a well-known greenhouse gas, have been associated with changes in soil water-filled pore space (WFPS) and soil temperature in many previous studies. However, it is acknowledged that the environment-N2O relationship is complex and still relatively poorly unknown. In this article, we employed a Bayesian model selection approach (Reversible jump Markov chain Monte Carlo) to develop a data-informed model of the relationship between daily N2O emissions and daily WFPS and soil temperature measurements between March 2007 and February 2009 from a soil under pasture in Queensland, Australia, taking seasonal factors and time-lagged effects into account. The model indicates a very strong relationship between a hybrid seasonal structure and daily N2O emission, with the latter substantially increased in summer. Given the other variables in the model, daily soil WFPS, lagged by a week, had a negative influence on daily N2O; there was evidence of a nonlinear positive relationship between daily soil WFPS and daily N2O emission; and daily soil temperature tended to have a linear positive relationship with daily N2O emission when daily soil temperature was above a threshold of approximately 19°C. We suggest that this flexible Bayesian modeling approach could facilitate greater understanding of the shape of the covariate-N2O flux relation and detection of effect thresholds in the natural temporal variation of environmental variables on N2O emission.

A data mining framework for relevance feature discovery

This thesis is a study for automatic discovery of text features for describing user information needs. It presents an innovative data-mining approach that discovers useful knowledge from both relevance and non-relevance feedback information. The proposed approach can largely reduce noises in discovered patterns and significantly improve the performance of text mining systems. This study provides a promising method for the study of Data Mining and Web Intelligence.

A framework for cost-aware process management : cost reporting and cost prediction

Organisations are constantly seeking efficiency gains for their business processes in terms of time and cost. Management accounting enables detailed cost reporting of business operations for decision making purposes, although significant effort is required to gather accurate operational data. Process mining, on the other hand, may provide valuable insight into processes through analysis of events recorded in logs by IT systems, but its primary focus is not on cost implications. In this paper, a framework is proposed which aims to exploit the strengths of both fields in order to better support management decisions on cost control. This is achieved by automatically merging cost data with historical data from event logs for the purposes of monitoring, predicting, and reporting process-related costs. The on-demand generation of accurate, relevant and timely cost reports, in a style akin to reports in the area of management accounting, will also be illustrated. This is achieved through extending the open-source process mining framework ProM.

A framework to better understand emotional experiences with portable interactive devices : preliminary trial

Two longitudinal experiments were conducted exploring emotional experiences with PIDs over six months including media and medial Portable Interactive Devices (PIDs). Results identifying the impact of negative social and personal interactions on the overall emotional experience as well as different task categories (Features, Functional, Mediation and Auxiliary) and their corresponding emotional responses have previously been reported [2,3,4,5]. This paper builds on these findings and presents the Designing for Evolving Emotional Experience (DE3) framework promoting positive (and deals with negative) emotional experiences with PIDs including a set of principles to better understand emotional experiences. To validate the DE3 framework a preliminary trial was conducted with five practicing industrial designers. The trial required them to consider initial design concepts using the DE3 framework followed by a questionnaire asking about their use of the framework for concept development. The trial aimed to analyse the effectiveness, efficiency and usefulness of the framework in assisting in the development of initial concepts for PIDs taking into account emotional experiences. Common themes regarding the framework are outlined including the ease of use, the effectiveness in focusing on the personal and social contexts and positive ratings regarding its use. Overall the feedback from the preliminary trial was encouraging with responses suggesting that the framework was accessible, rated highly and most importantly permitted designers to consider emotional experiences during concept development. The paper concludes with a discussion regarding the future development of the DE3 framework and the potential implications to design theory and the design discipline.

An intuitive dashboard for Bayesian network inference

Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.

MODAM: A MODular Agent-based Modelling framework

Designing the smart grid requires combining varied models. As their number increases, so does the complexity of the software. Having a well thought architecture for the software then becomes crucial. This paper presents MODAM, a framework designed to combine agent-based models in a flexible and extensible manner, using well known software engineering design solutions (OSGi specification [1] and Eclipse plugins [2]). Details on how to build a modular agent-based model for the smart grid are given in this paper, illustrated by an example for a small network.

A methodology to develop an urban transport disadvantage framework : the case of Brisbane, Australia

Most individuals travel in order to participate in a network of activities which are important for attaining a good standard of living. Because such activities are commonly widely dispersed and not located locally, regular access to a vehicle is important to avoid exclusion. However, planning transport system provisions that can engage members of society in an acceptable degree of activity participation remains a great challenge. The main challenges in most cities of the world are due to significant population growth and rapid urbanisation which produces increased demand for transport. Keeping pace with these challenges in most urban areas is difficult due to the widening gap between supply and demand for transport systems which places the urban population at a transport disadvantage. The key element in mitigating the issue of urban transport disadvantage is to accurately identify the urban transport disadvantaged. Although wide-ranging variables and multi-dimensional methods have been used to identify this group, variables are commonly selected using ad-hoc techniques and unsound methods. This poses questions of whether the current variables used are accurately linked with urban transport disadvantage, and the effectiveness of the current policies. To fill these gaps, the research conducted for this thesis develops an operational urban transport disadvantage framework (UTDAF) based on key statistical urban transport disadvantage variables to accurately identify the urban transport disadvantaged. The thesis develops a methodology based on qualitative and quantitative statistical approaches to develop an urban transport disadvantage framework designed to accurately identify urban transport disadvantage. The reliability and the applicability of the methodology developed is the prime concern rather than the accuracy of the estimations. Relevant concepts that impact on urban transport disadvantage identification and measurement and a wide range of urban transport disadvantage variables were identified through a review of the existing literature. Based on the reviews, a conceptual urban transport disadvantage framework was developed based on the causal theory. Variables identified during the literature review were selected and consolidated based on the recommendations of international and local experts during the Delphi study. Following the literature review, the conceptual urban transport disadvantage framework was statistically assessed to identify key variables. Using the statistical outputs, the key variables were weighted and aggregated to form the UTDAF. Before the variable's weights were finalised, they were adjusted based on results of correlation analysis between elements forming the framework to improve the framework's accuracy. The UTDAF was then applied to three contextual conditions to determine the framework's effectiveness in identifying urban transport disadvantage. The development of the framework is likely to be a robust application measure for policy makers to justify infrastructure investments and to generate awareness about the issue of urban transport disadvantage.