Anabel Fraga

Prof. Anabel Fraga

Prof
orcid

Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 July 2011 in Information and Software Technology
Verified
Journal Article
Closed access
KRKarina Robles
Karina Robles
AFAnabel Fraga
Anabel Fraga
JORGE LUIS MORATO LARAJORGE LUIS MORATO LARA
JORGE LUIS MORATO LARA
JLJuan Llorens
Juan Llorens

18 February 2015 in Science and Engineering Ethics
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Journal Article
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GGGonzalo Génova
Gonzalo Génova
Hernan AstudilloHernan Astudillo
Hernan Astudillo
AFAnabel Fraga
Anabel Fraga

21 July 2007 in Science and Engineering Ethics
Verified
Journal Article
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GGGonzalo Génova
Gonzalo Génova
MGM. Rosario González
M. Rosario González
AFAnabel Fraga
Anabel Fraga

1 April 2020 in Applied Sciences
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Journal Article
Open access
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VMValentín Moreno
Valentín Moreno
GGGonzalo Génova
Gonzalo Génova
MAManuela Alejandres
Manuela Alejandres
AFAnabel Fraga
Anabel Fraga
Our purpose in this research is to develop a method to automatically and efficiently classify web images as Unified Modeling Language (UML) static diagrams, and to produce a computer tool that implements this function. The tool receives a bitmap file (in different formats) as an input and communicates whether the image corresponds to a diagram. For pragmatic reasons, we restricted ourselves to the simplest kinds of diagrams that are more useful for automated software reuse: computer-edited 2D representations of static diagrams. The tool does not require that the images are explicitly or implicitly tagged as UML diagrams. The tool extracts graphical characteristics from each image (such as grayscale histogram, color histogram and elementary geometric forms) and uses a combination of rules to classify it. The rules are obtained with machine learning techniques (rule induction) from a sample of 19,000 web images manually classified by experts. In this work, we do not consider the textual contents of the images. Our tool reaches nearly 95% of agreement with manually classified instances, improving the effectiveness of related research works. Moreover, using a training dataset 15 times bigger, the time required to process each image and extract its graphical features (0.680 s) is seven times lower.

8 September 2023 in Sustainability
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RGRaúl Pastor García
Raúl Pastor García
AFAnabel Fraga
Anabel Fraga
LLLuis López-Cozar
Luis López-Cozar
The decarbonization of cities is a priority for the European Union (EU). Fossil fuel and gas supplies need to be replaced with local renewable energy sources with a relevant increase in efficiency within 20 years in order to cap environmental, social, and economic negative impacts, and this cannot do significant harm. In this context, smart city development frameworks focused on mitigation, adaptation, and measurement not only collaborate in providing governance for sustainability but also facilitate the materialization of such sustainability along lifecycle engineering processes for decarbonization solutions. To achieve these goals, we must face the interoperability challenge and make information accessible for engineering and sustainability governance systematically. A starting point is to validate the models, data, and harmonized metadata. In this paper, the authors provide results that validate the utility of a conceptual model for interoperable smart and sustainable urban energy systems (ISSUESs). The validation is carried out for an urban energy system with a high potential for decarbonizing southern European smart cities and integrating several commercial solar technologies using academic bibliography and natural language processing (NLP) techniques.

6 June 2018 in Information Systems Frontiers
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Journal Article
Closed access
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AFAnabel Fraga
Anabel Fraga
JLJuan Llorens
Juan Llorens
GGGonzalo Génova
Gonzalo Génova