CorTexT platform

@article{Lundvall2022,

title = {China's catching-up in artificial intelligence seen as a co-evolution of corporate and national innovation systems},

author = {Bengt-Åke Lundvall and Cecilia Rikap},

url = {https://www.sciencedirect.com/science/article/pii/S0048733321001918},

doi = {https://doi.org/10.1016/j.respol.2021.104395},

issn = {0048-7333},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

journal = {Research Policy},

volume = {51},

number = {1},

pages = {104395},

abstract = {Inspired by Christopher Freeman's work on how radical technical change opens up for shifts in world leadership and on the role of innovation systems in this process, this paper explores China's emergence as a lead country in artificial intelligence as reflecting a co-evolution of Corporate and National Innovation Systems. Taking Freeman's (1987) work on Japan as our lead, we focus on the domestic interaction within and on the openness of China's national innovation system. To follow up on his prediction of the increasing importance of big companies as network leaders, we introduce the concept “corporate innovation system” with special attention to two Chinese tech giants: Alibaba and Tencent.},

keywords = {},

pubstate = {forthcoming},

tppubtype = {article}

}

@article{Jaramillo2021,

title = {Load modelling and non-intrusive load monitoring to integrate distributed energy resources in low and medium voltage networks},

author = {Andres F. Moreno Jaramillo and David M. Laverty and D. John Morrow and Jesús Martinez del Rincon}and Aoife M. Foley},

url = {https://www.sciencedirect.com/science/article/pii/S0960148121010612},

doi = {https://doi.org/10.1016/j.renene.2021.07.056},

issn = {0960-1481},

year  = {2021},

date = {2021-12-01},

urldate = {2021-12-01},

journal = {Renewable Energy},

volume = {179},

pages = {445-466},

abstract = {In many countries distributed energy resources (DER) (e.g. photovoltaics, batteries, wind turbines, electric vehicles, electric heat pumps, air-conditioning units and smart domestic appliances) are part of the ‘Green Deal’ to deliver a climate neutral society. Policy roadmaps, despite providing a framework and penetration targets for DER, often lack the network planning strategies needed to transition from passive to active distribution networks. Currently, DER's dynamic performance parameters and location identification techniques are not fully standardised. In fact, it can be very ad hoc. Standardised distributed load modelling and non-intrusive load monitoring (NILM) for equipment manufacturers, installers and network operators is critical to low and medium voltage network management in order to facilitate better balancing, flexibility and electricity trading across and within the power system for mass DER deployment. The aim of this paper is to fill this load modelling and NILM knowledge gap for DERto inform the ‘Green Deal’ transition and support standardisation. In the paper, existing load modelling techniques and NILM methodologies are critically examined to inform and guide research activity, equipment development and regulator thinking, as well as network operators. Seven key findings that need urgent attention are identified to support a smooth power system reconfiguration.},

keywords = {},

pubstate = {forthcoming},

tppubtype = {article}

}

@article{Penteado2021,

title = {Mapping the dynamics of medical informatics: a bibliometric analysis of the scientific field},

author = {Penteado, Bruno Elias and Fornazin, Marcelo and Castro, Leonardo and Freire, Sandro Luis},

doi = {10.29397/reciis.v15i4.2395},

issn = {1981-6278},

year  = {2021},

date = {2021-12-01},

urldate = {2021-12-01},

journal = {Revista Eletrônica de Comunicação},

abstract = {Digital health is an emerging topic in academic forums, public policies, and healthcare organizations. Assuming that digital health derives from previous medical informatics knowledge, this work presents findings from a bibliometric study on medical informatics technological and conceptual evolution in the last decades, emphasizing methodological aspects. We performed a bibliometric analysis in metadata from 100,000 papers indexed under the category 'medical informatics' in the Web of Science database between 1960 and 2020. Longitudinal analysis using software Bibliometrix and CorText were conducted in three axes: frequency of items, authors' countries, and keywords. Based on the methodological hypothesis guiding the study, the changes in keywords over time offer a proxy view on the conceptual and technological changes in the medical informatics research field. The results show that medical informatics consistently grew over the last six decades, expanding to several countries. Conceptual and technological changes that emerged from the keyword analysis supported the identification of well delimited periods related to general labels, such as: 'health informatics' and 'e-health'. The 'medical informatics' is recurring as a general label due to international scientific associations' adoption since the early 1970s. Moreover, in the last five years, we could identify the term 'digital health', which will probably be a major label in the next decade. The keyword analysis also showed the association between labels and technological changes, adding more evidence that these changes are related to concepts and technological applications.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Abdo2021,

title = {Domain-topic models with chained dimensions: Charting an emergent domain of a major oncology conference},

author = {Alexandre Hannud Abdo and Jean-Philippe Cointet and Pascale Bourret and Alberto Cambrosio},

url = {https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24606},

doi = {https://doi.org/10.1002/asi.24606},

year  = {2021},

date = {2021-11-24},

urldate = {2021-11-24},

journal = {Canadian Institutes of Health Research},

abstract = {This paper presents a contribution to the study of bibliographic corpora through science mapping. From a graph representation of documents and their textual dimension, stochastic block models can provide a simultaneous clustering of documents and words that we call a domain-topic model. Previous work investigated the resulting topics, or word clusters, while ours focuses on the study of the document clusters we call domains. To enable the description and interactive navigation of domains, we introduce measures and interfaces that consider the structure of the model to relate both types of clusters. We then present a procedure that extends the block model to cluster metadata attributes of documents, which we call a domain-chained model, noting that our measures and interfaces transpose to metadata clusters. We provide an example application to a corpus relevant to current science, technology and society (STS) research and an interesting case for our approach: the abstracts presented between 1995 and 2017 at the American Society of Clinical Oncology Annual Meeting, the major oncology research conference. Through a sequence of domain-topic and domain-chained models, we identify and describe a group of domains that have notably grown through the last decades and which we relate to the establishment of “oncopolicy” as a major concern in oncology.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}