Evidence-based practice and information literacy

Evidence-based Practice (EBP) has recently emerged as a topic of discussion amongst professionals within the library and information services (LIS) industry. Simply stated, EBP is the process of using formal research skills and methods to assist in decision making and establishing best practice. The emerging interest in EBP within the library context serves to remind the library profession that research skills and methods can help ensure that the library industry remains current and relevant in changing times. The LIS sector faces ongoing challenges in terms of the expectation that financial and human resources will be managed efficiently, particularly if library budgets are reduced and accountability to the principal stakeholders is increased. Library managers are charged with the responsibility to deliver relevant and cost effective services, in an environment characterised by rapidly changing models of information provision, information access and user behaviours. Consequently they are called upon not only to justify the services they provide, or plan to introduce, but also to measure the effectiveness of these services and to evaluate the impact on the communities they serve. The imperative for innovation in and enhancements to library practice is accompanied by the need for a strong understanding of the processes of review, measurement, assessment and evaluation. In 2001 the Centre for Information Research was commissioned by the Chartered Institute of Library and Information Professionals (CILIP) in the UK to conduct an examination into the research landscape for library and information science. The examination concluded that research is “important for the LIS [library and information science] domain in a number of ways” (McNicol & Nankivell, 2001, p.77). At the professional level, research can inform practice, assist in the future planning of the profession, raise the profile of the discipline, and indeed the reputation and standing of the library and information service itself. At the personal level, research can “broaden horizons and offer individuals development opportunities” (McNicol & Nankivell, 2001, p.77). The study recommended that “research should be promoted as a valuable professional activity for practitioners to engage in” (McNicol & Nankivell, 2001, p.82). This chapter will consider the role of EBP within the library profession. A brief review of key literature in the area is provided. The review considers issues of definition and terminology, highlights the importance of research in professional practice and outlines the research approaches that underpin EBP. The chapter concludes with a consideration of the specific application of EBP within the dynamic and evolving field of information literacy (IL).

Towards authorisation models for secure information sharing : a survey and research agenda

This article presents a survey of authorisation models and considers their ‘fitness-for-purpose’ in facilitating information sharing. Network-supported information sharing is an important technical capability that underpins collaboration in support of dynamic and unpredictable activities such as emergency response, national security, infrastructure protection, supply chain integration and emerging business models based on the concept of a ‘virtual organisation’. The article argues that present authorisation models are inflexible and poorly scalable in such dynamic environments due to their assumption that the future needs of the system can be predicted, which in turn justifies the use of persistent authorisation policies. The article outlines the motivation and requirement for a new flexible authorisation model that addresses the needs of information sharing. It proposes that a flexible and scalable authorisation model must allow an explicit specification of the objectives of the system and access decisions must be made based on a late trade-off analysis between these explicit objectives. A research agenda for the proposed Objective-based Access Control concept is presented.

Structural and fire behaviour of a new light gauge steel wall system

Fire design is an essential element of the overall design procedure of structural steel members and systems. Conventionally the fire rating of load-bearing stud wall systems made of light gauge steel frames (LSF) is based on approximate prescriptive methods developed on the basis of limited fire tests. This design is limited to standard wall configurations used by the industry. Increased fire rating is provided simply by adding more plasterboards to the stud walls. This is not an acceptable situation as it not only inhibits innovation and structural and cost efficiencies but also casts doubt over the fire safety of these light gauge steel stud wall systems. Hence a detailed fire research study into the performance and effectiveness of a recently developed innovative composite panel wall system was undertaken at Queensland University of Technology using both full scale fire tests and numerical studies. Experimental results of LSF walls using the new composite panels under axial compression load have shown the improvement in fire performance and fire resistance rating. Numerical analyses are currently being undertaken using the finite element program ABAQUS. Measured temperature profiles of the studs are used in the numerical models and the results are used to calibrate against full scale test results. The validated model will be used in a detailed parametric study with an aim to develop suitable design rules within the current cold-formed steel structures and fire design standards. This paper will present the results of experimental and numerical investigations into the structural and fire behaviour of light gauge steel stud walls protected by the new composite panel. It will demonstrate the improvements provided by the new composite panel system in comparison to traditional wall systems.

Efficient and accurate retrieval of business process models through indexing

Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective than developing them from scratch. As process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. Experiments are conducted to demonstrate that our proposal achieves a significant reduction in query evaluation time.

Bayesian hybrid algorithms and models : implementation and associated issues

This thesis addresses computational challenges arising from Bayesian analysis of complex real-world problems. Many of the models and algorithms designed for such analysis are ‘hybrid’ in nature, in that they are a composition of components for which their individual properties may be easily described but the performance of the model or algorithm as a whole is less well understood. The aim of this research project is to after a better understanding of the performance of hybrid models and algorithms. The goal of this thesis is to analyse the computational aspects of hybrid models and hybrid algorithms in the Bayesian context. The first objective of the research focuses on computational aspects of hybrid models, notably a continuous finite mixture of t-distributions. In the mixture model, an inference of interest is the number of components, as this may relate to both the quality of model fit to data and the computational workload. The analysis of t-mixtures using Markov chain Monte Carlo (MCMC) is described and the model is compared to the Normal case based on the goodness of fit. Through simulation studies, it is demonstrated that the t-mixture model can be more flexible and more parsimonious in terms of number of components, particularly for skewed and heavytailed data. The study also reveals important computational issues associated with the use of t-mixtures, which have not been adequately considered in the literature. The second objective of the research focuses on computational aspects of hybrid algorithms for Bayesian analysis. Two approaches will be considered: a formal comparison of the performance of a range of hybrid algorithms and a theoretical investigation of the performance of one of these algorithms in high dimensions. For the first approach, the delayed rejection algorithm, the pinball sampler, the Metropolis adjusted Langevin algorithm, and the hybrid version of the population Monte Carlo (PMC) algorithm are selected as a set of examples of hybrid algorithms. Statistical literature shows how statistical efficiency is often the only criteria for an efficient algorithm. In this thesis the algorithms are also considered and compared from a more practical perspective. This extends to the study of how individual algorithms contribute to the overall efficiency of hybrid algorithms, and highlights weaknesses that may be introduced by the combination process of these components in a single algorithm. The second approach to considering computational aspects of hybrid algorithms involves an investigation of the performance of the PMC in high dimensions. It is well known that as a model becomes more complex, computation may become increasingly difficult in real time. In particular the importance sampling based algorithms, including the PMC, are known to be unstable in high dimensions. This thesis examines the PMC algorithm in a simplified setting, a single step of the general sampling, and explores a fundamental problem that occurs in applying importance sampling to a high-dimensional problem. The precision of the computed estimate from the simplified setting is measured by the asymptotic variance of the estimate under conditions on the importance function. Additionally, the exponential growth of the asymptotic variance with the dimension is demonstrated and we illustrates that the optimal covariance matrix for the importance function can be estimated in a special case.

Typical accuracy and quality control of a process for creating CT-Based virtual bone models

A pragmatic method for assessing the accuracy and precision of a given processing pipeline required for converting computed tomography (CT) image data of bones into representative three dimensional (3D) models of bone shapes is proposed. The method is based on coprocessing a control object with known geometry which enables the assessment of the quality of resulting 3D models. At three stages of the conversion process, distance measurements were obtained and statistically evaluated. For this study, 31 CT datasets were processed. The final 3D model of the control object contained an average deviation from reference values of −1.07±0.52 mm standard deviation (SD) for edge distances and −0.647±0.43 mm SD for parallel side distances of the control object. Coprocessing a reference object enables the assessment of the accuracy and precision of a given processing pipeline for creating CTbased 3D bone models and is suitable for detecting most systematic or human errors when processing a CT-scan. Typical errors have about the same size as the scan resolution.

Physiological investigation of periosteum structure and its application in periosteum tissue engineering

Although many different materials, techniques and methods, including artificial or engineered bone substitutes, have been used to repair various bone defects, the restoration of critical-sized bone defects caused by trauma, surgery or congenital malformation is still a great challenge to orthopedic surgeons. One important fact that has been neglected in the pursuit of resolutions for large bone defect healing is that most physiological bone defect healing needs the periosteum and stripping off the periosteum may result in non-union or non-healed bone defects. Periosteum plays very important roles not only in bone development but also in bone defect healing. The purpose of this project was to construct a functional periosteum in vitro using a single stem cell source and then test its ability to aid the repair of critical-sized bone defect in animal models. This project was designed with three separate but closely-linked parts which in the end led to four independent papers. The first part of this study investigated the structural and cellular features in periostea from diaphyseal and metaphyseal bone surfaces in rats of different ages or with osteoporosis. Histological and immunohistological methods were used in this part of the study. Results revealed that the structure and cell populations in periosteum are both age-related and site-specific. The diaphyseal periosteum showed age-related degeneration, whereas the metaphyseal periosteum is more destructive in older aged rats. The periosteum from osteoporotic bones differs from normal bones both in terms of structure and cell populations. This is especially evident in the cambial layer of the metaphyseal area. Bone resorption appears to be more active in the periosteum from osteoporotic bones, whereas bone formation activity is comparable between the osteoporotic and normal bone. The dysregulation of bone resorption and formation in the periosteum may also be the effect of the interaction between various neural pathways and the cell populations residing within it. One of the most important aspects in periosteum engineering is how to introduce new blood vessels into the engineered periosteum to help form vascularized bone tissues in bone defect areas. The second part of this study was designed to investigate the possibility of differentiating bone marrow stromal cells (BMSCs) into the endothelial cells and using them to construct vascularized periosteum. The endothelial cell differentiation of BMSCs was induced in pro-angiogenic media under both normoxia and CoCl2 (hypoxia-mimicking agent)-induced hypoxia conditions. The VEGF/PEDF expression pattern, endothelial cell specific marker expression, in vitro and in vivo vascularization ability of BMSCs cultured in different situations were assessed. Results revealed that BMSCs most likely cannot be differentiated into endothelial cells through the application of pro-angiogenic growth factors or by culturing under CoCl2-induced hypoxic conditions. However, they may be involved in angiogenesis as regulators under both normoxia and hypoxia conditions. Two major angiogenesis-related growth factors, VEGF (pro-angiogenic) and PEDF (anti-angiogenic) were found to have altered their expressions in accordance with the extracellular environment. BMSCs treated with the hypoxia-mimicking agent CoCl2 expressed more VEGF and less PEDF and enhanced the vascularization of subcutaneous implants in vivo. Based on the findings of the second part, the CoCl2 pre-treated BMSCs were used to construct periosteum, and the in vivo vascularization and osteogenesis of the constructed periosteum were assessed in the third part of this project. The findings of the third part revealed that BMSCs pre-treated with CoCl2 could enhance both ectopic and orthotopic osteogenesis of BMSCs-derived osteoblasts and vascularization at the early osteogenic stage, and the endothelial cells (HUVECs), which were used as positive control, were only capable of promoting osteogenesis after four-weeks. The subcutaneous area of the mouse is most likely inappropriate for assessing new bone formation on collagen scaffolds. This study demonstrated the potential application of CoCl2 pre-treated BMSCs in the tissue engineering not only for periosteum but also bone or other vascularized tissues. In summary, the structure and cell populations in periosteum are age-related, site-specific and closely linked with bone health status. BMSCs as a stem cell source for periosteum engineering are not endothelial cell progenitors but regulators, and CoCl2-treated BMSCs expressed more VEGF and less PEDF. These CoCl2-treated BMSCs enhanced both vascularization and osteogenesis in constructed periosteum transplanted in vivo.

Validation of FHWA crash models for rural intersections - Lessons learned

A national-level safety analysis tool is needed to complement existing analytical tools for assessment of the safety impacts of roadway design alternatives. FHWA has sponsored the development of the Interactive Highway Safety Design Model (IHSDM), which is roadway design and redesign software that estimates the safety effects of alternative designs. Considering the importance of IHSDM in shaping the future of safety-related transportation investment decisions, FHWA justifiably sponsored research with the sole intent of independently validating some of the statistical models and algorithms in IHSDM. Statistical model validation aims to accomplish many important tasks, including (a) assessment of the logical defensibility of proposed models, (b) assessment of the transferability of models over future time periods and across different geographic locations, and (c) identification of areas in which future model improvements should be made. These three activities are reported for five proposed types of rural intersection crash prediction models. The internal validation of the model revealed that the crash models potentially suffer from omitted variables that affect safety, site selection and countermeasure selection bias, poorly measured and surrogate variables, and misspecification of model functional forms. The external validation indicated the inability of models to perform on par with model estimation performance. Recommendations for improving the state of the practice from this research include the systematic conduct of carefully designed before-and-after studies, improvements in data standardization and collection practices, and the development of analytical methods to combine the results of before-and-after studies with cross-sectional studies in a meaningful and useful way.

Modeling crash outcome probabilities at rural intersections: Application of hierarchical binomial logistic models

It is important to examine the nature of the relationships between roadway, environmental, and traffic factors and motor vehicle crashes, with the aim to improve the collective understanding of causal mechanisms involved in crashes and to better predict their occurrence. Statistical models of motor vehicle crashes are one path of inquiry often used to gain these initial insights. Recent efforts have focused on the estimation of negative binomial and Poisson regression models (and related deviants) due to their relatively good fit to crash data. Of course analysts constantly seek methods that offer greater consistency with the data generating mechanism (motor vehicle crashes in this case), provide better statistical fit, and provide insight into data structure that was previously unavailable. One such opportunity exists with some types of crash data, in particular crash-level data that are collected across roadway segments, intersections, etc. It is argued in this paper that some crash data possess hierarchical structure that has not routinely been exploited. This paper describes the application of binomial multilevel models of crash types using 548 motor vehicle crashes collected from 91 two-lane rural intersections in the state of Georgia. Crash prediction models are estimated for angle, rear-end, and sideswipe (both same direction and opposite direction) crashes. The contributions of the paper are the realization of hierarchical data structure and the application of a theoretically appealing and suitable analysis approach for multilevel data, yielding insights into intersection-related crashes by crash type.

Derivation of motor vehicle tailpipe particle emission factors suitable for modelling urban fleet emissions and air quality assessments

Background, aim, and scope Urban motor vehicle fleets are a major source of particulate matter pollution, especially of ultrafine particles (diameters < 0.1 µm), and exposure to particulate matter has known serious health effects. A considerable body of literature is available on vehicle particle emission factors derived using a wide range of different measurement methods for different particle sizes, conducted in different parts of the world. Therefore the choice as to which are the most suitable particle emission factors to use in transport modelling and health impact assessments presented as a very difficult task. The aim of this study was to derive a comprehensive set of tailpipe particle emission factors for different vehicle and road type combinations, covering the full size range of particles emitted, which are suitable for modelling urban fleet emissions. Materials and methods A large body of data available in the international literature on particle emission factors for motor vehicles derived from measurement studies was compiled and subjected to advanced statistical analysis, to determine the most suitable emission factors to use in modelling urban fleet emissions. Results This analysis resulted in the development of five statistical models which explained 86%, 93%, 87%, 65% and 47% of the variation in published emission factors for particle number, particle volume, PM1, PM2.5 and PM10 respectively. A sixth model for total particle mass was proposed but no significant explanatory variables were identified in the analysis. From the outputs of these statistical models, the most suitable particle emission factors were selected. This selection was based on examination of the statistical robustness of the statistical model outputs, including consideration of conservative average particle emission factors with the lowest standard errors, narrowest 95% confidence intervals and largest sample sizes, and the explanatory model variables, which were Vehicle Type (all particle metrics), Instrumentation (particle number and PM2.5), Road Type (PM10) and Size Range Measured and Speed Limit on the Road (particle volume). Discussion A multiplicity of factors need to be considered in determining emission factors that are suitable for modelling motor vehicle emissions, and this study derived a set of average emission factors suitable for quantifying motor vehicle tailpipe particle emissions in developed countries. Conclusions The comprehensive set of tailpipe particle emission factors presented in this study for different vehicle and road type combinations enable the full size range of particles generated by fleets to be quantified, including ultrafine particles (measured in terms of particle number). These emission factors have particular application for regions which may have a lack of funding to undertake measurements, or insufficient measurement data upon which to derive emission factors for their region. Recommendations and perspectives In urban areas motor vehicles continue to be a major source of particulate matter pollution and of ultrafine particles. It is critical that in order to manage this major pollution source methods are available to quantify the full size range of particles emitted for traffic modelling and health impact assessments.

GVS : A flexible, low-end, 3D visualisation framework for enhancing conceptual groundwater models for community, management and simulations

In this paper we discuss an advanced, 3D groundwater visualisation and animation system that allows scientists, government agencies and community groups to better understand the groundwater processes that effect community planning and decision-making. The system is unique in that it has been designed to optimise community engagement. Although it incorporates a powerful visualisation engine, this open-source system can be freely distributed and boasts a simple user interface allowing individuals to run and investigate the models on their own PCs and gain intimate knowledge of the groundwater systems. The initial version of the Groundwater Visualisation System (GVS v1.0), was developed from a coastal delta setting (Bundaberg, QLD), and then applied to a basalt catchment area (Obi Obi Creek, Maleny, QLD). Several major enhancements have been developed to produce higher quality visualisations, including display of more types of data, support for larger models and improved user interaction. The graphics and animation capabilities have also been enhanced, notably the display of boreholes, depth logs and time-series water level surfaces. The GVS software remains under continual development and improvement

Clone Detection in Repositories of Business Process Models

Business process model repositories capture precious knowledge about an organization or a business domain. In many cases, these repositories contain hundreds or even thousands of models and they represent several man-years of effort. Over time, process model repositories tend to accumulate duplicate fragments, as new process models are created by copying and merging fragments from other models. This calls for methods to detect duplicate fragments in process models that can be refactored as separate subprocesses in order to increase readability and maintainability. This paper presents an indexing structure to support the fast detection of clones in large process model repositories. Experiments show that the algorithm scales to repositories with hundreds of models. The experimental results also show that a significant number of non-trivial clones can be found in process model repositories taken from industrial practice.

Strengthening and formally verifying privacy in identity management systems

In a digital world, users’ Personally Identifiable Information (PII) is normally managed with a system called an Identity Management System (IMS). There are many types of IMSs. There are situations when two or more IMSs need to communicate with each other (such as when a service provider needs to obtain some identity information about a user from a trusted identity provider). There could be interoperability issues when communicating parties use different types of IMS. To facilitate interoperability between different IMSs, an Identity Meta System (IMetS) is normally used. An IMetS can, at least theoretically, join various types of IMSs to make them interoperable and give users the illusion that they are interacting with just one IMS. However, due to the complexity of an IMS, attempting to join various types of IMSs is a technically challenging task, let alone assessing how well an IMetS manages to integrate these IMSs. The first contribution of this thesis is the development of a generic IMS model called the Layered Identity Infrastructure Model (LIIM). Using this model, we develop a set of properties that an ideal IMetS should provide. This idealized form is then used as a benchmark to evaluate existing IMetSs. Different types of IMS provide varying levels of privacy protection support. Unfortunately, as observed by Jøsang et al (2007), there is insufficient privacy protection in many of the existing IMSs. In this thesis, we study and extend a type of privacy enhancing technology known as an Anonymous Credential System (ACS). In particular, we extend the ACS which is built on the cryptographic primitives proposed by Camenisch, Lysyanskaya, and Shoup. We call this system the Camenisch, Lysyanskaya, Shoup - Anonymous Credential System (CLS-ACS). The goal of CLS-ACS is to let users be as anonymous as possible. Unfortunately, CLS-ACS has problems, including (1) the concentration of power to a single entity - known as the Anonymity Revocation Manager (ARM) - who, if malicious, can trivially reveal a user’s PII (resulting in an illegal revocation of the user’s anonymity), and (2) poor performance due to the resource-intensive cryptographic operations required. The second and third contributions of this thesis are the proposal of two protocols that reduce the trust dependencies on the ARM during users’ anonymity revocation. Both protocols distribute trust from the ARM to a set of n referees (n > 1), resulting in a significant reduction of the probability of an anonymity revocation being performed illegally. The first protocol, called the User Centric Anonymity Revocation Protocol (UCARP), allows a user’s anonymity to be revoked in a user-centric manner (that is, the user is aware that his/her anonymity is about to be revoked). The second protocol, called the Anonymity Revocation Protocol with Re-encryption (ARPR), allows a user’s anonymity to be revoked by a service provider in an accountable manner (that is, there is a clear mechanism to determine which entity who can eventually learn - and possibly misuse - the identity of the user). The fourth contribution of this thesis is the proposal of a protocol called the Private Information Escrow bound to Multiple Conditions Protocol (PIEMCP). This protocol is designed to address the performance issue of CLS-ACS by applying the CLS-ACS in a federated single sign-on (FSSO) environment. Our analysis shows that PIEMCP can both reduce the amount of expensive modular exponentiation operations required and lower the risk of illegal revocation of users’ anonymity. Finally, the protocols proposed in this thesis are complex and need to be formally evaluated to ensure that their required security properties are satisfied. In this thesis, we use Coloured Petri nets (CPNs) and its corresponding state space analysis techniques. All of the protocols proposed in this thesis have been formally modeled and verified using these formal techniques. Therefore, the fifth contribution of this thesis is a demonstration of the applicability of CPN and its corresponding analysis techniques in modeling and verifying privacy enhancing protocols. To our knowledge, this is the first time that CPN has been comprehensively applied to model and verify privacy enhancing protocols. From our experience, we also propose several CPN modeling approaches, including complex cryptographic primitives (such as zero-knowledge proof protocol) modeling, attack parameterization, and others. The proposed approaches can be applied to other security protocols, not just privacy enhancing protocols.

Years 2 to 6 students' ability to generalise : models, representations and theory for teaching and learning

Over the last three years, in our Early Algebra Thinking Project, we have been studying Years 3 to 5 students’ ability to generalise in a variety of situations, namely, compensation principles in computation, the balance principle in equivalence and equations, change and inverse change rules with function machines, and pattern rules with growing patterns. In these studies, we have attempted to involve a variety of models and representations and to build students’ abilities to switch between them (in line with the theories of Dreyfus, 1991, and Duval, 1999). The results have shown the negative effect of closure on generalisation in symbolic representations, the predominance of single variance generalisation over covariant generalisation in tabular representations, and the reduced ability to readily identify commonalities and relationships in enactive and iconic representations. This chapter uses the results to explore the interrelation between generalisation and verbal and visual comprehension of context. The studies evidence the importance of understanding and communicating aspects of representational forms which allowed commonalities to be seen across or between representations. Finally the chapter explores the implications of the studies for a theory that describes a growth in integration of models and representations that leads to generalisation.

Seeing the Wood for the Trees: A Critical Evaluation of Methods to Estimate the Parameters of Stochastic Differential Equations

Maximum-likelihood estimates of the parameters of stochastic differential equations are consistent and asymptotically efficient, but unfortunately difficult to obtain if a closed-form expression for the transitional probability density function of the process is not available. As a result, a large number of competing estimation procedures have been proposed. This article provides a critical evaluation of the various estimation techniques. Special attention is given to the ease of implementation and comparative performance of the procedures when estimating the parameters of the Cox–Ingersoll–Ross and Ornstein–Uhlenbeck equations respectively.