Reproducibility of digital evidence in forensic investigations

We present a three-component model of a digital investigation which comprises: determination of input-output layers, assignment of read and write operations associated with use of forensic tools, and time-stamping of read and write operations. This builds on work of several authors, culminating in the new model presented here which is generic, scalable and compatible with all functions in the system, and which is guaranteed to produce a high quality of reproducibility.

Prototyping real-time systems using Petri net and object-oriented models

The objective of the research for this thesis is to develop techniques in order to build an executable model of a real-time system. This model is to be used early in the development of the system not only to detect errors in the specification of the system but also to validate expectations of the developer as to the operation of the system. A graphical specification of a real-time system called the transformation schema was chosen to be used to build the model. Two executable models of a real-time system are described.

Some empirical evidence on offender time discount rates

The conventional wisdom is that offenders have very high discount rates not only with respect to income and fines but also with respect to time incarcerated. These rates are difficult to measure objectively and the usual approach is to ask subjects hypothetical questions and infer time preference from their answers. In this article, we propose estimating rates at which offenders discount time incarcerated by specifying their equilibrium plea, defined as the discount rate, which equates the time and expected time spent in jail following a guilty plea and a trial. Offenders are assumed to exhibit positive time preference and discount time spent in jail at a constant rate. Our choice of sample is interesting because the offenders are not on bail, punishment is not delayed and the offences are planned therefore conforming to Becker’s model of the decision to commit a crime. Contrary to the discussion in the literature, we do not find evidence of consistently high time discount rates, and therefore cannot unequivocally infer that the prison experience always results in low levels of specific deterrence.

Multifaceted role of nitric oxide in an in vitro mouse neuronal injury model: transcriptomic profiling defines the temporal recruitment of death signalling cascades

Nitric oxide is implicated in the pathogenesis of various neuropathologies characterized by oxidative stress. Although nitric oxide has been reported to be involved in the exacerbation of oxidative stress observed in several neuropathologies, existent data fail to provide a holistic description of how nitrergic pathobiology elicits neuronal injury. Here we provide a comprehensive description of mechanisms contributing to nitric oxide induced neuronal injury by global transcriptomic profiling. Microarray analyses were undertaken on RNA from murine primary cortical neurons treated with the nitric oxide generator DETA-NONOate (NOC-18, 0.5 mM) for 8–24 hrs. Biological pathway analysis focused upon 3672 gene probes which demonstrated at least a ±1.5-fold expression in a minimum of one out of three time-points and passed statistical analysis (one-way anova, P < 0.05). Numerous enriched processes potentially determining nitric oxide mediated neuronal injury were identified from the transcriptomic profile: cell death, developmental growth and survival, cell cycle, calcium ion homeostasis, endoplasmic reticulum stress, oxidative stress, mitochondrial homeostasis, ubiquitin-mediated proteolysis, and GSH and nitric oxide metabolism. Our detailed time-course study of nitric oxide induced neuronal injury allowed us to provide the first time a holistic description of the temporal sequence of cellular events contributing to nitrergic injury. These data form a foundation for the development of screening platforms and define targets for intervention in nitric oxide neuropathologies where nitric oxide mediated injury is causative.

Factors impacting on the effectiveness of computer-assisted courseware

The level of satisfaction of computer-assisted tutorial courseware that is used as part of the undergraduate property and construction course at the University of Melbourne. It is important to determine if the computer-assisted teaching model improves the learning experience for students. This research examines the levels of satisfaction with a courseware model for teaching construction cost planning. The conclusions suggest that the advantages of the use of the model must be identified and actively supported throughout the whole course. In addition, further development of computer-based courseware is pointless unless the problems associated with their use can be minimized.

Process drama and digital games as text and action in virtual worlds : developing new literacies in school

This article explores the intersections between drama and digital gaming and the educational possibilities for literacy of both. The article draws on a model for the educational uses of digital gaming and three case studies from the Australian Research Council funded three and a half year project, Literacy in the digital world of the twenty first century: Learning from computer games. This model theorises the scope of the possibilities for literacy outcomes from the usage of computer games. The article describes how the model works, and then applies the model to drama education, specifying some new ways of thinking about the literacy outcomes from drama education. Process drama is theorised as the creation of text-in-action.

Profiling national mandatory folic acid fortification policy around the world

Mandatory food fortification “occurs when governments legally oblige food producers to fortify particular foods or categories of foods with specified micronutrients” [1]. Because mandatory food fortification exposes everyone in the population who consumes the fortified food(s) to raised levels of the specified micronutrient, it is one of the most powerful policy instruments available to influence dietary intake and population health outcomes. Many national food regulatory authorities have established policy guidance on mandatory food fortification. From an international perspective, the Codex Alimentarius Commission (Codex) provides principles for the addition of essential nutrients to foods [2]. According to these Codex principles, mandatory food fortification with additional vitamins and minerals is recommended where there is proven public health and nutrition need (Note: these principles are under review at the time of writing).

Necessary and sufficient checkpoint selection for temporal verification of high-confidence cloud workflow systems

On-time completion is an important temporal QoS (Quality of Service) dimension and one of the fundamental requirements for high-confidence workflow systems. In recent years, a workflow temporal verification framework, which generally consists of temporal constraint setting, temporal checkpoint selection, temporal verification, and temporal violation handling, has been the major approach for the high temporal QoS assurance of workflow systems. Among them, effective temporal checkpoint selection, which aims to timely detect intermediate temporal violations along workflow execution plays a critical role. Therefore, temporal checkpoint selection has been a major topic and has attracted significant efforts. In this paper, we will present an overview of work-flow temporal checkpoint selection for temporal verification. Specifically, we will first introduce the throughput based and response-time based temporal consistency models for business and scientific cloud workflow systems, respectively. Then the corresponding benchmarking checkpoint selection strategies that satisfy the property of “necessity and sufficiency” are presented. We also provide experimental results to demonstrate the effectiveness of our checkpoint selection strategies, and finally points out some possible future issues in this research area.

A guide to clarifying evidence in Australian child forensic interviews

Purpose – Interviewing victims of child sex abuse requires considerable care in order to minimise error. Due to children’s heightened suggestibility any question asked of a child could potentially incite error that could undermine the witness’s credibility. A focus group was conducted in order to facilitate the development of guidance for interviewers around the circumstances in which it is necessary to ask children follow-up questions in an interview. The paper aims to discuss these issues.

Design/methodology/approach – Seven Crown prosecutors representing every Australian state and territory (with the exception of one small state) were issued with 25 hypothetical narrative accounts of child abuse and asked to indicate what information, if any, required follow-up in the child’s narrative. Their responses and rationale for requiring following up in some cases and not others were discussed.

Findings – Thematic analysis revealed three recommendations to guide questioning: whether the case involved identification or recognition evidence; the presence of contextual features that may influence the witness’s memory, or that should trigger a particular line of questioning; and whether the information can or should be sought at a later stage by the trial prosecutor, rather than by the interviewer. Practical implications – The recommendations are discussed within the context of their implications for interviewing, that is, how each recommendation could be implemented in practice.

Originality/value – The present study extends prior literature by elucidating principles to guide decision making across interview topic areas. The need for such guidance is highlighted by research suggesting that topics such as offender identity, offence time and place, and witnesses are a source of overzealous questioning in interviews.

Challenges in designing culturally-adaptive ICT-based learning environments

This paper argues that two of the major problems facing local courseware developers and educators in creating culturally-sensitive lCT-based learning environments are the difficulties of representing cultural artefacts in courseware and of having a model of 'culture' that can be implemented in lCT-based systems. A developing learning-object model is presented; one that can be adopted to address aspects of this problem by providing a systematic way to approach implementing and representing cultural artefacts in courseware. This also provides a basis for some aspects of computer-based cultural preservation initiatives. While this approach may have higher short term development costs, the potential long term cultural benefits to the society far outweigh short term considerations.

Asymmetric recognition of good and bad news at Malaysian capital market : a pre and crisis analysis

The aim of this paper is to analyze the asymmetric recognition of good and bad news on reported earnings of Malaysian-listed firms. The study uses both descriptive and regression analyses to ascertain whether there is a contemporaneous relationship between news (good and bad) and reported earnings. The analysis is based on a sample of 150 firms listed on the Bursa Malaysia Index over a period of 10 years, from 1990 to 2000. Two regression models were adopted based on Basu (1997) and Giner and Rees (2001). The first model aims to capture asymmetric recognition of good and bad news into reported earnings while the latter model is developed to capture both asymmetric recognition of information shock and permanent earnings effect on contemporaneous earnings. The evidence from this study reported the steady increase in earnings per share till 1997. However, a drastic decline was observed for the period 1997 to 1999 because of Asian financial crisis. The findings from the regression model one suggested that the asymmetric recognition of good news was more prominent during the good time compare to bad time and vice versa. The findings from model two also suggested that autoregressive effect of permanent effect was very prominent both for crisis and non crisis periods.

Virtual melawati : 3D GIS as a decision support tool for urban planning

Virtual Melawati is an environment for developing expertise in the application of 3D interactive visualization and GIS (Geographic Information System) to address problems of the built environment and to test the model as a decision support tool in the context of the local planning authorities in Malaysia. The visual approach enables the integration of highly complex spatial GIS information such as the evolution and transformation of the urban precinct as well as the impact of planned developments into the decision making process. The study will examine the techniques of data acquisition, data reconstruction from physical to digital, urban analysis and visualization in constructing an interactive 3D GIS model to support and assist the decision making process in urban design and planning. The outcomes of the study will deliver an experimental test bed for improving decision making processes in urban planning and design utilizing 3D modeling and GIS. The project will accelerate the uptake of digital and multimedia methods in local government, facilitate current planning and consultation processes between councils and stakeholders and improve the dissemination and management of spatial information about urban environments.

Joint learning and dictionary construction for pattern recognition

We propose a joint representation and classification framework that achieves the dual goal of finding the most discriminative sparse overcomplete encoding and optimal classifier parameters. Formulating an optimization problem that combines the objective function of the classification with the representation error of both labeled and unlabeled data, constrained by sparsity, we propose an algorithm that alternates between solving for subsets of parameters, whilst preserving the sparsity. The method is then evaluated over two important classification problems in computer vision: object categorization of natural images using the Caltech 101 database and face recognition using the Extended Yale B face database. The results show that the proposed method is competitive against other recently proposed sparse overcomplete counterparts and considerably outperforms many recently proposed face recognition techniques when the number training samples is small.

Hierarchical semi-markov conditional random fields for recursive sequential data

Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov chains to model complex hierarchical, nested Markov processes. It is parameterised in a discriminative framework and has polynomial time algorithms for learning and inference. Importantly, we develop efficient algorithms for learning and constrained inference in a partially-supervised setting, which is important issue in practice where labels can only be obtained sparsely. We demonstrate the HSCRF in two applications: (i) recognising human activities of daily living (ADLs) from indoor surveillance cameras, and (ii) noun-phrase chunking. We show that the HSCRF is capable of learning rich hierarchical models with reasonable accuracy in both fully and partially observed data cases.

e-Mental health for mood and anxiety disorders in general practice

Background Australia is a world leader in the development of internetdelivered programs for the prevention and management of mood and anxiety disorders. Despite a strong evidence base of time- and cost-effectiveness, as well as clinical efficacy, the uptake of these programs in general practice remains low. Objective To familiarise general practitioners (GPs) with the range of online programs in Australia that have demonstrated efficacy and are currently available for use by patients with mental health problems. Discussion E-mental health programs provide an efficacious and accessible form of mental healthcare and have the potential to fill the gap for those for whom such care is inaccessible, unaffordable or unacceptable. Clinicians can also use it in a stepped-care manner to augment existing healthcare services. There are a number of online resources currently available to Australians who have mood or anxiety disorders. These resources have strong evidence to support their effectiveness. Online portals facilitate access to these programs. Recently the Australian Federal Government has funded an education program (eMHPrac) for GPs and mental health professionals, to outline what is available, indicate situations where recommending such resources is appropriate, and suggest ways in which they can be incorporated into general practice.