Using evidence combination for transformer defect diagnosis

This paper describes a number of methods of evidence combination, and their applicability to the domain of transformer defect diagnosis. It explains how evidence combination fits into an on-line and implemented agent-based condition monitoring system, and the benefits of giving selected agents reflective abilities. Reflection has not previously been deployed in an industrial setting, and theoretical work has been in domains other than power engineering. This paper presents the results of implementing five different methods of evidence combination, showing that reflective techniques give greater accuracy than non-reflective

Coalition Against the Deportation of Irish Children: Evaluation of CADIC Achievements 2006-2007 (Final Report)

CADIC is widely considered to have been a very successful coalition by its members, funders and external parties. It mounted a high quality campaign that influenced government policy and provided effective support to a large number of vulnerable people. Its experience of coalition working highlights the following critical success factors that other NGOs entering a collaborative working model should consider carefully

Incentives and managerial experience in multi-taskteams: evidence from within a firm

This paper exploits a quasi-experimental setting to estimate the impact thata multi-dimensional group incentive scheme had on branch performance in a largedistribution firm. The scheme, which is based on the Balanced Scorecard, wasimplemented in all branches in one division, but not in another. Branches from thesecond division are used as a control group. Our results suggest that the balancedscorecard had some impact, but that it varied with branch characteristics, and inparticular, branches with more experienced managers were better able to respond tothe new incentives. This paper exploits a quasi-experimental setting to estimate the impact thata multi-dimensional group incentive scheme had on branch performance in a largedistribution firm. The scheme, which is based on the Balanced Scorecard, wasimplemented in all branches in one division, but not in another. Branches from thesecond division are used as a control group. Our results suggest that the balancedscorecard had some impact, but that it varied with branch characteristics, and inparticular, branches with more experienced managers were better able to respond tothe new incentives

Leading careers education information advice and guidance (CEIAG) in secondary schools

This report summarises the findings of a set of six case studies, undertaken during November 2010, which explored the effective leadership of careers education information advice and guidance (CEIAG) in a small sample of secondary schools in England. The findings indicate that effective CEIAG is an extremely important component of school provision as it impacts upon students’ aspirations, achievement and therefore potentially their life chances and social mobility. The report describes different curriculum models, with the integration of CEIAG across the curriculum as the preferred approach allied to a strong emphasis on partnership working. The leadership and management of CEIAG follow a distributed model with staff operating at a variety of levels to secure its development and implementation. There is significant evidence of this model combining the skills of both teaching and non-teaching staff. The importance of strategic vision, continuing professional development and monitoring and evaluation is highlighted as substantial. The report concludes with a set of key message for both school leaders and policymakers

Where Are My Intelligent Assistant's Mistakes? A Systematic Testing Approach

Intelligent assistants are handling increasingly critical tasks, but until now, end users have had no way to systematically assess where their assistants make mistakes. For some intelligent assistants, this is a serious problem: if the assistant is doing work that is important, such as assisting with qualitative research or monitoring an elderly parent’s safety, the user may pay a high cost for unnoticed mistakes. This paper addresses the problem with WYSIWYT/ML (What You See Is What You Test for Machine Learning), a human/computer partnership that enables end users to systematically test intelligent assistants. Our empirical evaluation shows that WYSIWYT/ML helped end users find assistants’ mistakes significantly more effectively than ad hoc testing. Not only did it allow users to assess an assistant’s work on an average of 117 predictions in only 10 minutes, it also scaled to a much larger data set, assessing an assistant’s work on 623 out of 1,448 predictions using only the users’ original 10 minutes’ testing effort

The evidence for automated grading in diabetic retinopathy screening

Peer reviewedPostprin