Browsing by Subject "Performance evaluation"

Now showing 1 - 3 of 3
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    A self-adaptive deep learning-based system for anomaly detection in 5G networks
    (IEEE, 2018-02-07) Fernández Maimó, Lorenzo; Perales Gómez, Ángel Luis; García Clemente, Félix J.; Gil Pérez, Manuel; Martínez Pérez, Gregorio; Ingeniería y Tecnología de Computadores
    The upcoming fifth-generation (5G) mobile technology, which includes advanced communication features, is posing new challenges on cybersecurity defense systems. Although innovative approaches have evolved in the last few years, 5G will make existing intrusion detection and defense procedures become obsolete, in case they are not adapted accordingly. In this sense, this paper proposes a novel 5G-oriented cyberdefense architecture to identify cyberthreats in 5G mobile networks efficient and quickly enough. For this, our architecture uses deep learning techniques to analyze network traffic by extracting features from network flows. Moreover, our proposal allows adapting, automatically, the configuration of the cyberdefense architecture in order to manage traffic fluctuation, aiming both to optimize the computing resources needed in each particular moment and to fine tune the behavior and the performance of analysis and detection processes. Experiments using a well-known botnet data set depict how a neural network model reaches a sufficient classification accuracy in our anomaly detection system. Extended experiments using diverse deep learning solutions analyze and determine their suitability and performance for different network traffic loads. The experimental results show how our architecture can self-adapt the anomaly detection system based on the volume of network flows gathered from 5G subscribers' user equipments in real-time and optimizing the resource consumption.
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    Designing a sport performance evaluation model in Khouzestan Province, Iran, with Interpretive Structural Modeling
    (Murcia: Servicio de Publicaciones de la Universidad de Murcia, 2019) Mazarei, Ebrahim; Heydarinejad, Sedighe; Shafienia, Parvane; Zarra-Nezhad, Mansour
    Any sport organization intensively needs a performance evalua-tion system to ensure the desirability of its activities, particularly in dyna-mic and complicated environments. The objective of this study was to use interpretive structural modeling (ISM) to propose a performance evalua-tion model for the youth and sports offices in Khuzestan Province, Iran. This is a quantitative study of descriptive-analytical type. The statistical population consisted of 120 scientific and executive experts. 60 individuals were invited to participate, and finally, 30 individuals were selected as the final respondents by purposive sampling method. The data measurement tool was a researcher-made questionnaire. Its validity was confirmed by the experts. Descriptive and inferential statistics methods were used to analyze the data. MATLAB was employed to analyze the data concerning the in-terpretive structural model. The results showed that most of the strategies are in the linked area according to the analysis of the influence power and dependence (MICMAC Table). Moreover, the results of the strategy classi-fication indicated that the most essential strategies were: strategies of sport preparation scheme, legislation, structural obstacles elimination, creation of the province sport strategic council, and strategic management approach.
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    Evaluación del rendimiento en la enseñanza superior. Comparación de resultados entre alumnos procedentes de la LOGSE y del COU
    (Universidad de Murcia. Servicio de Publicaciones, 2002) Miguel Díaz, Mario de; Apodaca Urquijo, Pedro Miguel; Arias Blanco, José Miguel; Escudero Escorza, Tomás; Rodriguez Espinar, Sebastián; Vidal García, Javier
    In this paper, we analyze the performance of university students who have followed two different models of secondary education in Spain (COU and LOGSE). In order to do that, we have followed up a sample of cohorts from first year at university in 5 Spanish universities: Barcelona, Oviedo, País Vasco, Salamanca and Zaragoza. That means that we have analyzed data from almost 150.000 students along 2 to 6 years. We have used descriptive and comparative statistics, bivariate and multivariate, and also some meta-analysis. Our main conclusion is that there are no significant differences in the performance of students at university depending on the type of secondary education they have followed.