An extended approach to adjust inconsistent minority peer- and self-assessment scores of teamwork using assessor’s reliability

Teamwork is generally assessed either solely by academic staff or by both academic staff andstudents themselves confidentially as well as collaboratively. Peer- and self-assessments have beenused primarily to assess teamwork process and teacher assessment to assess teamwork product.Peer- and self-assessments are useful to elicit team members’ contribution towards teamwork and toconvert team mark into individual marks, provided the scores are reliable (the extent to which thescores are consistent). However, not all peer- and self-assessment scores are reliable. Anecdotal andliterature evidence suggest that there are several cases of inconsistencies in these scores. Individualcontribution scores given by teammates to an assessee (including himself/herself) can sometimesvary significantly due to both intentional and unintentional reasons. Simply using total individual ratingscores without considering an assessor’s reliability to estimate individual contribution factors cansometime results unfair grades and becomes hindrance to learning through teamwork.PURPOSEThis study proposes an extended approach to adjust inconsistent and/or distorted minority peer andself-assessment scores of teamwork using standard normal probability concept.APPROACHIn order to adjust inconsistent and/or distorted minority peer-and self-assessment scores of teamwork,an extended approach has been proposed. The approach uses the reliability of assessor’s scores ofan assessee using standard normal probability curve. The evaluation of the extended approach isconducted by comparing with the existing approaches using two case examples of peer- and selfassessmentof teamwork where minority team members’ scores are inconsistent.RESULTSThe evaluation of the extended approach shows that the proposed method is superior to the availableapproaches in order to adjust inconsistent peer- and self-assessment scores for special cases wherescores of minority team members are inconsistent. The extended approach helps both to automaticallydetect such scoring anomalies and to adjust the scores so that the fairer contributions to the teamworkwould be obtained and utilised.CONCLUSIONSThe extended approach is useful in that it helps both to automatically detect scoring anomalies and todevise the methods to adjust them. However, the approach does not address the issue of scoringinconsistencies by majority of team members as it uses average score as a basis for identifyinginconsistencies. Moreover, the approach needs to be implemented in the real teamwork environmentin order to identify the impacts of these scoring adjustments in teamwork process and teamworkproduct.

Distinguishing DDoS attacks from flash crowds using probability metrics

Both Flash crowds and DDoS (Distributed Denial-of-Service) attacks have very similar properties in terms of internet traffic, however Flash crowds are legitimate flows and DDoS attacks are illegitimate flows, and DDoS attacks have been a serious threat to internet security and stability. In this paper we propose a set of novel methods using probability metrics to distinguish DDoS attacks from Flash crowds effectively, and our simulations show that the proposed methods work well. In particular, these mathods can not only distinguish DDoS attacks from Flash crowds clearly, but also can distinguish the anomaly flow being DDoS attacks flow or being Flash crowd flow from Normal network flow effectively. Furthermore, we show our proposed hybrid probability metrics can greatly reduce both false positive and false negative rates in detection.

The cost-effectiveness of the Dose Adjustment for Normal Eating (DAFNE) structured education programme: an update using the Sheffield Type 1 Diabetes policy model

AIMS: 
To estimate the cost-effectiveness of training in flexible intensive insulin therapy [as provided in the Dose Adjustment for Normal Eating (DAFNE) structured education programme] compared with no training for adults with Type 1 diabetes mellitus in the UK using the Sheffield Type 1 Diabetes Policy Model.

METHODS: 
The Sheffield Type 1 Diabetes Policy Model was used to simulate the development of long-term microvascular and macrovascular diabetes-related complications and the occurrence of diabetes-related adverse events in 5000 adults with Type 1 diabetes. Total costs and quality-adjusted life years were estimated from a National Health Service perspective over a lifetime horizon, discounted at a rate of 3.5%. The treatment effectiveness of DAFNE was modelled as a reduction in HbA1c that affected the risk of developing long-term diabetes-related complications. Probabilistic and structural sensitivity analyses were conducted.

RESULTS:
DAFNE resulted in greater life expectancy and reduced incidence of some diabetes-related complications compared with no DAFNE. DAFNE was found to generate an average of 0.0294 additional quality-adjusted life years for an additional cost of £426 per patient, leading to an incremental cost-effectiveness ratio of £14 400 compared with no DAFNE. There was a 54% probability that DAFNE would be cost-effective at a willingness-to-pay threshold of £20 000 per quality-adjusted life year.

CONCLUSIONS: 
The results of this study suggest that DAFNE is a cost-effective structured education programme for people with Type 1 diabetes and support its provision by the National Health Service in the UK.

Modified CADF and CIPS panel unit root statistics with standard chi-squared and normal limiting distributions

In an influential paper Pesaran ('A simple panel unit root test in presence of cross-section dependence', Journal of Applied Econometrics, Vol. 22, pp. 265-312, 2007) proposes two unit root tests for panels with a common factor structure. These are the CADF and CIPS test statistics, which are amongst the most popular test statistics in the literature. One feature of these statistics is that their limiting distributions are highly non-standard, making for relatively complicated implementation. In this paper, we take this feature as our starting point to develop modified CADF and CIPS test statistics that support standard chi-squared and normal inference.