CHURNs : freshness assurance for humans

We present CHURNs, a method for providing freshness and authentication assurances to human users. In computer-to-computer protocols, it has long been accepted that assurances of freshness such as random nonces are required to prevent replay attacks. Typically, no such assurance of freshness is presented to a human in a human-and-computer protocol. A Computer–HUman Recognisable Nonce (CHURN) is a computer-aided random sequence that the human has a measure of control over and input into. Our approach overcomes limitations such as ‘humans cannot do random’ and that humans will follow the easiest path. Our findings show that CHURNs are significantly more random than values produced by unaided humans; that humans may be used as a second source of randomness, and we give measurements as to how much randomness can be gained from humans using our approach; and that our CHURN-generator makes the user feel more in control, thus removing the need for complete trust in devices and underlying protocols. We give an example of how a CHURN may be used to provide assurances of freshness and authentication for humans in a widely used protocol.

A novel method of Fiber Bragg Grating (FBG) strain modulation and its application in FBG accelerometers

This thesis has systemically investigated the possibility of improving one type of optical fiber sensors by using a novel mechanism. Many parameters of the sensor have been improved, and one outcome of this innovation is that civil structures, such as bridges and high-rise buildings, may be operated more safely and used longer.

Real or imagined? A study exploring the existence of common method variance effects in road safety research

Common method variance (CMV) has received little attention within the field of road safety research despite a heavy reliance on self-report data. Two surveys were completed by 214 motorists over a two-month period, allowing associations between social desirability and key road safety variables and relationships between scales across the two survey waves to be examined. Social desirability was found to have a strong negative correlation with the Driver Behaviour Questionnaire (DBQ) sub-scales as well as age, but not with crashes and offences. Drivers who scored higher on the social desirability scale were also less likely to report aberrant driving behaviours as measured by the DBQ. Controlling for social desirability did not substantially alter the predictive relationship between the DBQ and the crash and offences variables. The strength of the correlations within and between the two waves were also compared with the results strongly suggesting that effects associated with CMV were present. Identification of CMV would be enhanced by the replication of this study with a larger sample size and comparing self-report data with official sources.

Q-RARA : a rapid and rigorous method for researching small, primary health care organisations

Understanding the organisational processes driving quality primary care is crucial to the maintaining and improving practice. Qualitative methods are increasingly popular in health services research, but this area is dominated by interview studies. Multiple qualitative methods are rarely used in a systematically integrated fashion. We developed a method to study small primary health care organizations using rapid appraisal and qualitative mixed methods: Q-RARA – Qualitative Rapid Appraisal, Rigorous Analysis

A rating aggregation method for generating product reputations

Many websites offer the opportunity for customers to rate items and then use customers' ratings to generate items reputation, which can be used later by other users for decision making purposes. The aggregated value of the ratings per item represents the reputation of this item. The accuracy of the reputation scores is important as it is used to rank items. Most of the aggregation methods didn't consider the frequency of distinct ratings and they didn't test how accurate their reputation scores over different datasets with different sparsity. In this work we propose a new aggregation method which can be described as a weighted average, where weights are generated using the normal distribution. The evaluation result shows that the proposed method outperforms state-of-the-art methods over different sparsity datasets.

Marx as a Critical Discourse Analyst : The Genesis of a Critical Method and its Relevance to the Critique of Global Capital (with Phil Graham)

In this paper we identify elements in Marx’s economic and political writings that are relevant to contemporary critical discourse analysis (CDA). We argue that Marx can be seen to be engaging in a form of discourse analysis. We identify the elements in Marx’s historical materialist method that support such a perspective, and exemplify these in longitudinal comparison of Marx’s texts.