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Examinando Producción Científica por Autor "Ocaña Zuñiga,Candy"
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Ítem Implementing the Sustainable Development Goals in University Higher Education: A Systematic Review(Universidad Nacional de Jaén, 2024-03-31) Quiñones Huatangari,Lenin; Huaccha Castillo,Annick Estefany; Ocaña Zuñiga,CandyThe role of higher education institutions in promoting sustainability is realised through scientific research and academic activities. It is therefore essential to explore strategies to assess and monitor the implementation of sustainable practices in these institutions. This study set out to examine the mainstreaming of the Sustainable Development Goals (SDGs) in higher education institutions. The methodology used was a systematic review of research articles in the Scopus database, conducted between 6 and 20 January 2023. The inclusion criteria covered global university experiences in implementing the SDGs. The review revealed that 28.56% of the publications included were from European universities, 24% from the Americas, 13% from Asia and a smaller number from Oceania (5%) and Africa (2%). The analysis identified indicators to assess adherence to the SDGs, such as number of publications, institutional affiliation, number of reports, disciplinary field, type of course, number of essays, subject area, student/classroom ratio and age of participants. The data collection instruments used were questionnaires, interviews, published articles and field notes. This systematic review details the concern of higher education institutions to measure the impact of their activities in relation to the SDG guidelines, as well as a critical and decision-oriented summary for institutions wishing to initiate the procesÍtem Noise estimation using an artificial neural network in the urban area of Jaen, Cajamarca(Universidad Nacional de Jaén, 2024-03-31) Quiñones Huatangari,Lenin; Ocaña Zuñiga,CandyJaen is a city in constant urban growth which generates an increase in vehicular traffic and active noise pollution. The research presents the development of an artificial neural network (ANN) to estimate the noise produced by vehicular traffic in the urban area of the city. Consequently, information was collected from two investigations coded as T1 and T2, for which a matrix of 10 variables was elaborated with 210 and 273 data respectively. Random random sampling was performed to divide the data matrix into 80% (training) and 20% (validation). Weka software and the multi-layer perceptron (MLP) training algorithm were used to model the ANN. An ANN for T1 with 6-19-1 architecture and an ANN for T2 with 6-15-1 architecture were obtained. The performance of the ANNs was evaluated using the correlation coefficient (R), coefficient of determination (R2) and root mean square error (RMSE). The results show that the MLP networks are able to estimate the sound pressure level with values of R=0.9927, R2=0.9854 and RMSE=0.7313 for T1, R=0.9989, R2=0.9978, and RMSE=0.1515 for T2.
