Examinando por Autor "Gomez, Javier"

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Forecasting and assessing consequences of aviation safety occurrences
(Elsevier, 2019-01) Rios Insua, David; Alfaro, Cesar; Gomez, Javier; Hernandez-Coronado, Pablo; Bernal, Francisco
Aviation safety is essential for the healthy growth and sustainability of the global economy. The implementation of Safety Management Systems to support safe service delivery has become one of the most important goals within the airline industry over the last years. However, in most cases the involved organisations use unsophisticated methods based on risk matrices for the development of such systems. In this paper, we present models to forecast and assess the consequences of aviation safety occurrences as part of a framework for aviation safety risk management at state level.
Forecasting aviation safety occurrences
(John Wiley & Sons Ltd., 2022-06-17) Flores, Bruno; Rios Insua, David; Alfaro, Cesar; Gomez, Javier
We present a general framework for aviation safety occurrence forecasting. This is a major component of a methodology for aviation safety risk management at national level. It covers novel models as well as novel combinations of earlier models. Having good quality occurrence and severity forecasting models is paramount to properly manage risks, maintain the confidence of its users and preserve the status of aviation as a safe transportation mode. The problem is involved due to the presence of complex effects like seasonality, trends, or stress that impact the rates of various occurrences and the uncertainty about future number of operations.
Framework for scoring the scientific reputation of researchers
(Springer, 2024) Martín de Diego, Isaac; Prieto, Juan Carlos; Fernández-Isabel, Alberto; Gomez, Javier; Alfaro, César
In the scientific community, there is no single, objective, and precise metric for ranking the work of researchers based on their scientific merit. Most existing metrics are based on the number of publications associated with an author along with the number of citations received by those publications. However, there is no standard metric officially used to evaluate the researchers’ careers. In this paper, the Framework for Reputation Estimation of Scientific Authors (FRESA) to address this issue is depicted. It is a system able to estimate the reputation of a researcher focusing on the achieved publications. It calculates two indexes making use of the relevance and the novelty concepts in the scientific domain. The system can depict the scientific trajectories of the researchers through the proposed indexes to illustrate their evolution over time. FRESA uses web information sources and applies similarity measures, text mining techniques, and clustering algorithms to also rank and group the researchers. The presented work is experimental, rendering promising results.
Toward Accelerated Training of Parallel Support Vector Machines Based on Voronoi Diagrams
(MDPI, 2021-11-29) Alfaro, Cesar; Gomez, Javier; M. Moguerza, Javier; Castillo, Javier; Martinez, Jose I.
Typical applications of wireless sensor networks (WSN), such as in Industry 4.0 and smart cities, involves acquiring and processing large amounts of data in federated systems. Important challenges arise for machine learning algorithms in this scenario, such as reducing energy consumption and minimizing data exchange between devices in different zones. This paper introduces a novel method for accelerated training of parallel Support Vector Machines (pSVMs), based on ensembles, tailored to these kinds of problems. To achieve this, the training set is split into several Voronoi regions. These regions are small enough to permit faster parallel training of SVMs, reducing computational payload. Results from experiments comparing the proposed method with a single SVM and a standard ensemble of SVMs demonstrate that this approach can provide comparable performance while limiting the number of regions required to solve classification tasks. These advantages facilitate the development of energy-efficient policies in WSN.