Doing pedagogical research in engineering

This is a book

Nursing research for a multi-ethnic society

Summary points • Conducting research that appropriately and sensitively pays attention to ethnicity presents an important challenge to nursing researchers and demands particular competencies. • Nursing research must recognise the multifaceted nature of ethnicity and the varied ways in which health-related experiences and outcomes may be associated with ethnicity. • Ethnic identities are complex and fluid so that using fixed ethnic categories in research requires careful consideration. • Describing and explaining differences between ethnic 'groups' demands careful attention to sampling, data generation and analysis so that partial or misleading interpretations are avoided. • Researchers should be alert to the potential for research on minority ethnic groups to do more harm than good and should seek to ensure that their research focus and approach is informed by the experiences and priorities of these groups

Centrally Banked Cryptocurrencies

Current cryptocurrencies, starting with Bitcoin, build a decentralized blockchain-based transaction ledger, maintained through proofs-of-work that also generate a monetary supply. Such decentralization has benefits, such as independence from national political control, but also significant limitations in terms of scalability and computational cost. We introduce RSCoin, a cryptocurrency framework in which central banks maintain complete control over the monetary supply, but rely on a distributed set of authorities, or mintettes, to prevent double-spending. While monetary policy is centralized, RSCoin still provides strong transparency and auditability guarantees. We demonstrate, both theoretically and experimentally, the benefits of a modest degree of centralization, such as the elimination of wasteful hashing and a scalable system for avoiding double-spending attacks.Comment: 15 pages, 4 figures, 2 tables in Proceedings of NDSS 201

Tracing Transactions Across Cryptocurrency Ledgers

One of the defining features of a cryptocurrency is that its ledger, containing all transactions that have evertaken place, is globally visible. As one consequenceof this degree of transparency, a long line of recent re-search has demonstrated that even in cryptocurrenciesthat are specifically designed to improve anonymity it is often possible to track money as it changes hands,and in some cases to de-anonymize users entirely. With the recent proliferation of alternative cryptocurrencies, however, it becomes relevant to ask not only whether ornot money can be traced as it moves within the ledgerof a single cryptocurrency, but if it can in fact be tracedas it moves across ledgers. This is especially pertinent given the rise in popularity of automated trading platforms such as ShapeShift, which make it effortless to carry out such cross-currency trades. In this paper, weuse data scraped from ShapeShift over a thirteen-monthperiod and the data from eight different blockchains to explore this question. Beyond developing new heuristics and creating new types of links across cryptocurrency ledgers, we also identify various patterns of cross-currency trades and of the general usage of these platforms, with the ultimate goal of understanding whetherthey serve a criminal or a profit-driven agenda.Comment: 14 pages, 13 tables, 6 figure

Human-automation collaboration in manufacturing: identifying key implementation factors

Human-automation collaboration refers to the concept of human operators and intelligent automation working together interactively within the same workspace without conventional physical separation. This concept has commanded significant attention in manufacturing because of the potential applications, such as the installation of large sub-assemblies. However, the key human factors relevant to human-automation collaboration have not yet been fully investigated. To maximise effective implementation and reduce development costs for future projects these factors need to be examined. In this paper, a collection of human factors likely to influence human-automation collaboration are identified from current literature. To test the validity of these and explore further factors associated with implementation success, different types of production processes in terms of stage of maturity are being explored via industrial case studies from the project’s stakeholders. Data was collected through a series of semi-structured interviews with shop floor operators, engineers, system designers and management personnel

Your new colleague is a robot. Is that ok?

Human robot collaboration is a concept under development that will be applied within manufacturing environments in the near future to increase efficiency and quality. While there have been significant advances in technology to enable this progress there is still little known about the wider human factors issues of employing such systems in High Value Manufacturing environments. This paper sets out our current understanding of key organisational and individual factors which need to be explored

‘Ecstasy’ and the use of sleep medications in a general community sample: a four-year follow-up

Aims: Animal models show that a single dose of MDMA (‘ecstasy’) can result in long-term disruption of sleep. We evaluated the relationship between ecstasy consumption and the use of sleep medications in humans after controlling for key factors. Design: The Personality and Total Health Through Life project uses a longitudinal cohort with follow-up every four years. This study reports data from waves two and three. Setting: Participants were recruited from the electoral roll in the Australian Capital Territory and Queanbeyan, New South Wales, Australia. Participants: Participants were aged 20-24 years at wave one (1999-2000). Measures: The study collected self-reported data on ecstasy, meth/amphetamine, cannabis, alcohol, tobacco and use of sleeping medications (pharmaceutical or other substances). Depression was categorised with the Brief Patient Health Questionnaire (BPHQ). Other psychosocial measures included lifetime traumas. We used generalised estimating equations to model outcomes. Results: Ecstasy data were available from 2128 people at wave two and 1977 at wave three: sleeping medication use was reported by 227 (10.7%) respondents at wave two and 239 (12.1%) at wave three. Increased odds ratios (OR) for sleeping medication use was found for those with depression (OR=1.88, (95% confidence interval (CI) 1.39, 2.53), women (OR=1.44, 95% CI 1.13, 1.84), and increased by 19% for each lifetime trauma. Ecstasy use was not a significant predictor, but >monthly versus never meth/amphetamine use increased the odds (OR=3.03, 95% CI 1.30, 7.03). Conclusion: The use of ecstasy was not associated with the use of sleeping medications controlling for other risk factors.The PATH study was supported by an NHMRC Program Grant 179805 and NHMRC Project Grant 157125. The sponsors had no role in the design, conduct or reporting of the research. None of the authors have connections (direct or indirect) with the tobacco, alcohol, pharmaceutical or gaming industries or any body substantially funded by one of these organisations

The development of a Human Factors Readiness Level tool for implementing industrial human-robot collaboration

The concept of industrial human-robot collaboration (HRC) is becoming increasingly attractive as a means for enhancing manufacturing productivity and product. However, due to traditional preventive health and safety standards, there have been few operational examples of true HRC, so it has not been possible to explore the organisational human factors that need to be considered by manufacturing organisations to realise the benefits of industrial HRC until recently. Charalambous, Fletcher and Webb (2015) made the first attempt to identify the key organisational human factors for the successful implementation of industrial HRC through an industrial exploratory case study. This work enabled (i) development of a theoretical framework of key organisational human factors relevant to industrial HRC and (ii) identification of these factors as enablers or barriers. Although identifying the key organisational human factors (HF) was an important step, it presented a crucial question: when should practitioners involved in HRC design and implementation consider these factors? New industrial processes are typically designed and implemented using a maturity or readiness evaluation system, but these do not incorporate of or link to any formal considerations of HF. The aim of this paper is to expand on the previous findings and link the key human factors in the theoretical framework directly to a recognised industrial maturity readiness level system to develop a new Human Factors Readiness Level (HFRL) tool for system design practitioners to optimise successful implementation of industrial HRC