Restrictions in pub closing times and lockouts in Newcastle, Australia five years on.

In 2008 pub closing times were restricted from 5 am to 3:30 am in the central business district (CBD) of Newcastle, Australia. A previous study showed a one-third reduction in assaults in the 18 months following the restriction. We assessed whether the assault rate remained lower over the following 3.5 years and whether the introduction of a 'lockout' in nearby Hamilton was associated with a reduction in assaults there.

Evolutionary optimization: a big data perspective

Stochastic search techniques such as evolutionary algorithms (EA) are known to be better explorer of search space as compared to conventional techniques including deterministic methods. However, in the era of big data like most other search methods and learning algorithms, suitability of evolutionary algorithms is naturally questioned. Big data pose new computational challenges including very high dimensionality and sparseness of data. Evolutionary algorithms' superior exploration skills should make them promising candidates for handling optimization problems involving big data. High dimensional problems introduce added complexity to the search space. However, EAs need to be enhanced to ensure that majority of the potential winner solutions gets the chance to survive and mature. In this paper we present an evolutionary algorithm with enhanced ability to deal with the problems of high dimensionality and sparseness of data. In addition to an informed exploration of the solution space, this technique balances exploration and exploitation using a hierarchical multi-population approach. The proposed model uses informed genetic operators to introduce diversity by expanding the scope of search process at the expense of redundant less promising members of the population. Next phase of the algorithm attempts to deal with the problem of high dimensionality by ensuring broader and more exhaustive search and preventing premature death of potential solutions. To achieve this, in addition to the above exploration controlling mechanism, a multi-tier hierarchical architecture is employed, where, in separate layers, the less fit isolated individuals evolve in dynamic sub-populations that coexist alongside the original or main population. Evaluation of the proposed technique on well known benchmark problems ascertains its superior performance. The algorithm has also been successfully applied to a real world problem of financial portfolio management. Although the proposed method cannot be considered big data-ready, it is certainly a move in the right direction.

Five ways to hack and cheat with bring-your-own-device electronic examinations

Bring-your-own-device electronic examinations (BYOD e-exams) are a relatively new type of assessment where students sit an in-person exam under invigilated conditions with their own laptop. Special software restricts student access to prohibited computer functions and files, and provides access to any resources or software the examiner approves. In this study, the decades-old computer security principle that ‘software security depends on hardware security’ is applied to a range of BYOD e-exam tools. Five potential hacks are examined, four of which are confirmed to work against at least one BYOD e-exam tool. The consequences of these hacks are significant, ranging from removal of the exam paper from the venue through to receiving live assistance from an outside expert. Potential mitigation strategies are proposed; however, these are unlikely to completely protect the integrity of BYOD e-exams. Educational institutions are urged to balance the additional affordances of BYOD e-exams for examiners against the potential affordances for cheaters.

Obtain confidentiality or/and authenticity in Big Data by ID-based generalized signcryption

Recently, the Big Data paradigm has received considerable attention since it gives a great opportunity to mine knowledge from massive amounts of data. However, the new mined knowledge will be useless if data is fake, or sometimes the massive amounts of data cannot be collected due to the worry on the abuse of data. This situation asks for new security solutions. On the other hand, the biggest feature of Big Data is "massive", which requires that any security solution for Big Data should be "efficient". In this paper, we propose a new identity-based generalized signcryption scheme to solve the above problems. In particular, it has the following two properties to fit the efficiency requirement. (1) It can work as an encryption scheme, a signature scheme or a signcryption scheme as per need. (2) It does not have the heavy burden on the complicated certificate management as the traditional cryptographic schemes. Furthermore, our proposed scheme can be proven-secure in the standard model. © 2014 Elsevier Inc. All rights reserved.

The myths big media peddle to demand deregulation

This article argues that big media in Australia promote three myths about rural and regional news in Australia as part of their case to deregulate the industry. These myths are that geography no longer matters in local news; that big media are the only ones who can save regional news; and that people in regional Australia can access less news that their city counterparts.

Leaning too far? PISA, policy and Australia's ‘top five’ ambitions

 Australia has declared its ambition to be within the ‘top five’ in the Programme for International Student Assessment (PISA) by 2025. So serious is it about this ambition, that the Australian Government has incorporated it into the Australian Education Act, 2013. Given this focus on PISA results and rankings, we go beyond average scores to take a close look at Australia’s performance in PISA, examining rankings by different geographical units, by item content and by test completion. Based on this analysis and using data from interviews with measurement and policy experts, we show how uninformative and even misleading the ‘average performance scores’, on which the rankings are based, can be. We explore how a more nuanced understanding would point to quite different policy actions. After considering the PISA data and Australia’s ‘top five’ ambition closely, we argue that neither the rankings nor such ambitions should be given much credence.

Congestion pricing and active transport - evidence from five opportunities for natural experiment

Congestion pricing schemes have been implemented in cities worldwide as a means of addressing externalities associated with inefficient price signals in transport systems. Limited evidence exists however on the secondary impacts of these schemes, which may include both environmental and health benefits associated with a resultant reduction in motor vehicle usage. There is increasing recognition that transport behaviours may play a role as opportunistic population level targets to reduce physical inactivity. Yet limited evidence currently exists on the effectiveness of transport interventions, such as congestion pricing schemes, for improving physical activity levels.This study aims to examine the physical activity effects of congestion pricing, with the health benefits of physical activity well established. Congestion pricing schemes implemented internationally were considered as 'natural experiments' and evidence of modal shift from vehicle to active forms of transport or physical activity effect was reviewed. Twelve studies were included from a search of peer-reviewed and 'grey' literature, with overall evidence for a physical activity or modal shift effect considered weak. The quality of the available evidence was also considered to be low.This is not to say that congestion pricing schemes may not have important secondary physical activity related health benefits. Instead, this review highlights the paucity of evidence that has been collected from real-world implementation of congestion pricing schemes. Given the growing recognition of the importance of distal mediators and determinants of health and the need for an 'all-of-government' approach more and better quality evidence of effectiveness of transport interventions for a broad range of outcomes, including health, is required. Significant barriers to the collection of such evidence exist, with strategies for overcoming some of these barriers identified. Only with a better understanding of the full range of potential health impacts can transport policy be fully utilised as a tool for population health.

Corporate social responsibility programs of big food in Australia: a content analysis of industry documents

OBJECTIVE: To examine Corporate Social Responsibility (CSR) tactics by identifying the key characteristics of CSR strategies as described in the corporate documents of selected 'Big Food' companies. METHODS: A mixed methods content analysis was used to analyse the information contained on Australian Big Food company websites. Data sources included company CSR reports and web-based content that related to CSR initiatives employed in Australia. RESULTS: A total of 256 CSR activities were identified across six organisations. Of these, the majority related to the categories of environment (30.5%), responsibility to consumers (25.0%) or community (19.5%). CONCLUSIONS: Big Food companies appear to be using CSR activities to: 1) build brand image through initiatives associated with the environment and responsibility to consumers; 2) target parents and children through community activities; and 3) align themselves with respected organisations and events in an effort to transfer their positive image attributes to their own brands. IMPLICATIONS: Results highlight the type of CSR strategies Big Food companies are employing. These findings serve as a guide to mapping and monitoring CSR as a specific form of marketing.

Investor protection, firm informational problems, big N auditors, and cost of debt around the world

This paper examines the effects of investor protection, firm informational problems (proxied by firm size, firm age, and the number of analysts following), and Big N auditors on firms' cost of debt around the world. Using data from 1994 to 2006 and over 90,000 firm-year observations, we find that the cost of debt is lower when firms are audited by Big N auditors, especially in countries with strong investor protection. Second, we find that firms with more informational problems (i.e., higher information asymmetry problems) benefit more from Big N auditors in terms of lower cost of debt only in countries with stronger investor protection.

A secure cloud computing based framework for big data information management of smart grid

Smart grid is a technological innovation that improves efficiency, reliability, economics, and sustainability of electricity services. It plays a crucial role in modern energy infrastructure. The main challenges of smart grids, however, are how to manage different types of front-end intelligent devices such as power assets and smart meters efficiently; and how to process a huge amount of data received from these devices. Cloud computing, a technology that provides computational resources on demands, is a good candidate to address these challenges since it has several good properties such as energy saving, cost saving, agility, scalability, and flexibility. In this paper, we propose a secure cloud computing based framework for big data information management in smart grids, which we call 'Smart-Frame.' The main idea of our framework is to build a hierarchical structure of cloud computing centers to provide different types of computing services for information management and big data analysis. In addition to this structural framework, we present a security solution based on identity-based encryption, signature and proxy re-encryption to address critical security issues of the proposed framework.