6 resultados para knowledge transfer framework
Resumo:
Here, we describe gene expression compositional assignment (GECA), a powerful, yet simple method based on compositional statistics that can validate the transfer of prior knowledge, such as gene lists, into independent data sets, platforms and technologies. Transcriptional profiling has been used to derive gene lists that stratify patients into prognostic molecular subgroups and assess biomarker performance in the pre-clinical setting. Archived public data sets are an invaluable resource for subsequent in silico validation, though their use can lead to data integration issues. We show that GECA can be used without the need for normalising expression levels between data sets and can outperform rank-based correlation methods. To validate GECA, we demonstrate its success in the cross-platform transfer of gene lists in different domains including: bladder cancer staging, tumour site of origin and mislabelled cell lines. We also show its effectiveness in transferring an epithelial ovarian cancer prognostic gene signature across technologies, from a microarray to a next-generation sequencing setting. In a final case study, we predict the tumour site of origin and histopathology of epithelial ovarian cancer cell lines. In particular, we identify and validate the commonly-used cell line OVCAR-5 as non-ovarian, being gastrointestinal in origin. GECA is available as an open-source R package.
Resumo:
Purpose – This paper aims to contribute towards understanding how safety knowledge can be elicited from railway experts for the purposes of supporting effective decision-making. Design/methodology/approach – A consortium of safety experts from across the British railway industry is formed. Collaborative modelling of the knowledge domain is used as an approach to the elicitation of safety knowledge from experts. From this, a series of knowledge models is derived to inform decision-making. This is achieved by using Bayesian networks as a knowledge modelling scheme, underpinning a Safety Prognosis tool to serve meaningful prognostics information and visualise such information to predict safety violations. Findings – Collaborative modelling of safety-critical knowledge is a valid approach to knowledge elicitation and its sharing across the railway industry. This approach overcomes some of the key limitations of existing approaches to knowledge elicitation. Such models become an effective tool for prediction of safety cases by using railway data. This is demonstrated using passenger–train interaction safety data. Practical implications – This study contributes to practice in two main directions: by documenting an effective approach to knowledge elicitation and knowledge sharing, while also helping the transport industry to understand safety. Social implications – By supporting the railway industry in their efforts to understand safety, this research has the potential to benefit railway passengers, staff and communities in general, which is a priority for the transport sector. Originality/value – This research applies a knowledge elicitation approach to understanding safety based on collaborative modelling, which is a novel approach in the context of transport.
Resumo:
Marketing and policy researchers seeking to increase the societal impact of their scholarship should engage directly with relevant stakeholders. For maximum societal effect, this engagement needs to occur both within the research process and throughout the complex process of knowledge transfer. A relational engagement approach to research impact is proposed as complementary and building upon traditional approaches. Traditional approaches to impact employ bibliometric measures and focus on the creation and use of journal articles by scholarly audiences, an important but incomplete part of the academic process. The authors suggest expanding the strategies and measures of impact to include process assessments for specific stakeholders across the entire course of impact: from the creation, awareness, and use of knowledge to societal impact. This relational engagement approach involves the co-creation of research with audiences beyond academia. The authors hope to begin a dialogue on the strategies researchers can make to increase the potential societal benefits of their research.
Resumo:
There has been private sector involvement in the delivery of public services in the Irish State since its foundation. This involvement was formalised in 1998 when Public Private Partnership (PPP) was officially introduced. Ireland is a latecomer to PPP and, prior to the credit crisis, was seen as a ‘rapid follower’ relying primarily on the UK PPP model in the procurement of infrastructure in transport, education, housing/urban regeneration and water/wastewater. PPP activity in Ireland stalled during the credit crisis, and some projects were cancelled, but it has taken off again recently with part of the Infrastructure and Capital Investment Plan 2016 – 2021 to be delivered through PPP showing continuing political commitment to PPP. Ireland’s interest in PPP cannot be explained by economic rationale alone, as PPP was initiated during a period of prosperity. We consider three alternative explanations: voluntary adoption – where the UK model was closely followed; coercive adoption – where PPP policy was forced upon Ireland; and institutional isomorphism – where institutional creation and change was promoted to aid public sector organisations in gaining institutional legitimacy. We find evidence of all three patterns, with coercive adoption becoming more relevant in recent years. Ireland’s rapid uptake of PPP differs from other European countries, mostly because when PPP was introduced in 1998, the Irish State was in an economic position where it could have directly procured necessary infrastructure. This paper therefore asks why PPP was adopted and how this adoption pattern has affected the sustainability of PPP in Ireland. This paper defines PPP; examines the background to the PPP approach adopted in Ireland; outlines the theoretical framework of the paper: transfer theory and institutional theory; discusses the methodology; reports on findings and gives conclusions.
Resumo:
In this paper, we investigate the secrecy performance of an energy harvesting relay system, where a legitimate source communicates with a legitimate destination via the assistance of multiple trusted relays. In the considered system, the source and relays deploy the time-switching-based radio frequency energy harvesting technique to harvest energy from a multi-antenna beacon. Different antenna selection and relay selection schemes are applied to enhance the security of the system. Specifically, two relay selection schemes based on the partial and full knowledge of channel state information, i.e., optimal relay selection and partial relay selection, and two antenna selection schemes for harvesting energy at source and relays, i.e., maximizing energy harvesting channel for the source and maximizing energy harvesting channel for the selected relay, are proposed. The exact and asymptotic expressions of secrecy outage probability in these schemes are derived. We demonstrate that applying relay selection approaches in the considered energy harvesting system can enhance the security performance. In particular, optimal relay selection scheme outperforms partial relay selection scheme and achieves full secrecy diversity order, regardless of energy harvesting scenarios.