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Isaías García-Rodríguez
SECOMUCI Research Group, Escuela de Ingenierías Industrial e Informática, Universidad de León, Campus de Vegazana s/n, C.P. 24071 León, Spain

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Journal article
Published: 08 July 2021 in Biomedical Signal Processing and Control
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In this work, a sentiment analysis method that is capable of accepting audio of any length, without being fixed a priori, is proposed. Mel spectrogram and Mel Frequency Cepstral Coefficients are used as audio description methods and a Fully Convolutional Neural Network architecture is proposed as a classifier. The results have been validated using three well known datasets: EMODB, RAVDESS and TESS. The results obtained were promising, outperforming the state-of–the-art methods. Also, thanks to the fact that the proposed method admits audios of any size, it allows a sentiment analysis to be made in near real time, which is very interesting for a wide range of fields such as call centers, medical consultations or financial brokers.

ACS Style

María Teresa García-Ordás; Héctor Alaiz-Moretón; José Alberto Benítez-Andrades; Isaías García-Rodríguez; Oscar García-Olalla; Carmen Benavides. Sentiment analysis in non-fixed length audios using a Fully Convolutional Neural Network. Biomedical Signal Processing and Control 2021, 69, 102946 .

AMA Style

María Teresa García-Ordás, Héctor Alaiz-Moretón, José Alberto Benítez-Andrades, Isaías García-Rodríguez, Oscar García-Olalla, Carmen Benavides. Sentiment analysis in non-fixed length audios using a Fully Convolutional Neural Network. Biomedical Signal Processing and Control. 2021; 69 ():102946.

Chicago/Turabian Style

María Teresa García-Ordás; Héctor Alaiz-Moretón; José Alberto Benítez-Andrades; Isaías García-Rodríguez; Oscar García-Olalla; Carmen Benavides. 2021. "Sentiment analysis in non-fixed length audios using a Fully Convolutional Neural Network." Biomedical Signal Processing and Control 69, no. : 102946.

Article
Published: 19 April 2021 in The Journal of Supercomputing
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The increasing number of connected devices and the complexity of Internet of Things (IoT) ecosystems are demanding new architectures for managing and securing these networked environments. Intrusion Detection Systems (IDS) are security solutions that help to detect and mitigate the threats that IoT systems face, but there is a need for new IDS strategies and architectures. This paper describes a development environment that allows the programming and debugging of distributed, rule-based multi-agent IDS solutions. The proposed solution consists in the integration of a rule engine into the agent, the use of a specialized, wrapping agent class with a graphical user interface for programming and debugging purposes, and a mechanism for the incremental composition of behaviors. A comparative study and an example IDS are used to test and show the suitability and validity of the approach. The JADE multi-agent middleware has been used for the practical implementations.

ACS Style

Francisco José Aguayo-Canela; Héctor Alaiz-Moretón; María Teresa García-Ordás; José Alberto Benítez-Andrades; Carmen Benavides; Isaías García-Rodríguez. Enriched multi-agent middleware for building rule-based distributed security solutions for IoT environments. The Journal of Supercomputing 2021, 1 -23.

AMA Style

Francisco José Aguayo-Canela, Héctor Alaiz-Moretón, María Teresa García-Ordás, José Alberto Benítez-Andrades, Carmen Benavides, Isaías García-Rodríguez. Enriched multi-agent middleware for building rule-based distributed security solutions for IoT environments. The Journal of Supercomputing. 2021; ():1-23.

Chicago/Turabian Style

Francisco José Aguayo-Canela; Héctor Alaiz-Moretón; María Teresa García-Ordás; José Alberto Benítez-Andrades; Carmen Benavides; Isaías García-Rodríguez. 2021. "Enriched multi-agent middleware for building rule-based distributed security solutions for IoT environments." The Journal of Supercomputing , no. : 1-23.

Article
Published: 25 March 2021 in Cluster Computing
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The spread of the Internet of Things (IoT) is demanding new, powerful architectures for handling the huge amounts of data produced by the IoT devices. In many scenarios, many existing isolated solutions applied to IoT devices use a set of rules to detect, report and mitigate malware activities or threats. This paper describes a development environment that allows the programming and debugging of such rule-based multi-agent solutions. The solution consists of the integration of a rule engine into the agent, the use of a specialized, wrapping agent class with a graphical user interface for programming and testing purposes, and a mechanism for the incremental composition of behaviors. Finally, a set of examples and a comparative study were accomplished to test the suitability and validity of the approach. The JADE multi-agent middleware has been used for the practical implementation of the approach.

ACS Style

Francisco José Aguayo-Canela; Héctor Alaiz-Moretón; María Teresa García-Ordás; José Alberto Benítez-Andrades; Carmen Benavides; Paulo Novais; Isaías García-Rodríguez. Middleware-based multi-agent development environment for building and testing distributed intelligent systems. Cluster Computing 2021, 1 -13.

AMA Style

Francisco José Aguayo-Canela, Héctor Alaiz-Moretón, María Teresa García-Ordás, José Alberto Benítez-Andrades, Carmen Benavides, Paulo Novais, Isaías García-Rodríguez. Middleware-based multi-agent development environment for building and testing distributed intelligent systems. Cluster Computing. 2021; ():1-13.

Chicago/Turabian Style

Francisco José Aguayo-Canela; Héctor Alaiz-Moretón; María Teresa García-Ordás; José Alberto Benítez-Andrades; Carmen Benavides; Paulo Novais; Isaías García-Rodríguez. 2021. "Middleware-based multi-agent development environment for building and testing distributed intelligent systems." Cluster Computing , no. : 1-13.

Journal article
Published: 24 March 2021 in International Journal of Environmental Research and Public Health
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Background: Cannabis is an illegal psychoactive substance that’s use is widespread among adolescents. During adolescence, many changes can cause stress. In this phase, the group of friends becomes increasingly important, being a situation of vulnerability for the beginning of cannabis use, either as an escape mechanism or due to peer’s influence. Therefore, the purpose of this study is to describe and analyze the structure of the consumption and friendship network, the intention to use cannabis, and the stress in a secondary school class. Methods: An online platform with validated self-reported questionnaires were used for data collection. Results: The sample consisted of adolescents (n = 20) aged 14–16 from a third-year class of compulsory secondary education in Ponferrada (León, Spain). Significant differences were obtained concerning consumption intention and the different network metrics in both the friendship and consumption networks. Subsequently, the representation of these networks was carried out. Conclusions: Social Network Analysis is a very useful tool that provides a picture of the context in which adolescents are located. In the consumption network, there are central actors who have not yet consumed cannabis; this is a crucial moment to implement prevention strategies.

ACS Style

María Martínez-Fernández; Cristina Liébana-Presa; Elena Fernández-Martínez; Lisa Gomes; Isaías García-Rodríguez. Friendship and Consumption Networks in Adolescents and Their Relationship to Stress and Cannabis Use Intention. International Journal of Environmental Research and Public Health 2021, 18, 3335 .

AMA Style

María Martínez-Fernández, Cristina Liébana-Presa, Elena Fernández-Martínez, Lisa Gomes, Isaías García-Rodríguez. Friendship and Consumption Networks in Adolescents and Their Relationship to Stress and Cannabis Use Intention. International Journal of Environmental Research and Public Health. 2021; 18 (7):3335.

Chicago/Turabian Style

María Martínez-Fernández; Cristina Liébana-Presa; Elena Fernández-Martínez; Lisa Gomes; Isaías García-Rodríguez. 2021. "Friendship and Consumption Networks in Adolescents and Their Relationship to Stress and Cannabis Use Intention." International Journal of Environmental Research and Public Health 18, no. 7: 3335.

Journal article
Published: 15 February 2021 in Computer Methods and Programs in Biomedicine
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Background and objective: Diabetes is a chronic pathology which is affecting more and more people over the years. It gives rise to a large number of deaths each year. Furthermore, many people living with the disease do not realize the seriousness of their health status early enough. Late diagnosis brings about numerous health problems and a large number of deaths each year so the development of methods for the early diagnosis of this pathology is essential. Methods: In this paper, a pipeline based on deep learning techniques is proposed to predict diabetic people. It includes data augmentation using a variational autoencoder (VAE), feature augmentation using an sparse autoencoder (SAE) and a convolutional neural network for classification. Pima Indians Diabetes Database, which takes into account information on the patients such as the number of pregnancies, glucose or insulin level, blood pressure or age, has been evaluated. Results: A 92.31% of accuracy was obtained when CNN classifier is trained jointly the SAE for featuring augmentation over a well balanced dataset. This means an increment of 3.17% of accuracy with respect the state-of-the-art. Conclusions: Using a full deep learning pipeline for data preprocessing and classification has demonstrate to be very promising in the diabetes detection field outperforming the state-of-the-art proposals.

ACS Style

María Teresa García-Ordás; Carmen Benavides; José Alberto Benítez-Andrades; Héctor Alaiz-Moretón; Isaías García-Rodríguez. Diabetes detection using deep learning techniques with oversampling and feature augmentation. Computer Methods and Programs in Biomedicine 2021, 202, 105968 .

AMA Style

María Teresa García-Ordás, Carmen Benavides, José Alberto Benítez-Andrades, Héctor Alaiz-Moretón, Isaías García-Rodríguez. Diabetes detection using deep learning techniques with oversampling and feature augmentation. Computer Methods and Programs in Biomedicine. 2021; 202 ():105968.

Chicago/Turabian Style

María Teresa García-Ordás; Carmen Benavides; José Alberto Benítez-Andrades; Héctor Alaiz-Moretón; Isaías García-Rodríguez. 2021. "Diabetes detection using deep learning techniques with oversampling and feature augmentation." Computer Methods and Programs in Biomedicine 202, no. : 105968.

Journal article
Published: 20 July 2020 in Healthcare
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University students establish networks that impact on their behavior. Social Network Analysis (SNA) allows us to analyze the reticular structures formed and find patterns of interaction between university students. The main objective of this study was to observe the impact of interdisciplinary collaborative work between nursing and computer engineering students on the collaboration and friendship networks, emotions and performance of the participants. It is a quasi-experimental descriptive study with pre- and post-intervention measurements. The contact networks analyzed showed an increase in density in the post-intervention period. The most central people in the network corresponded with those who considered positive emotions most in their academic environment, while the less central people coincided with those who highlighted negative emotions. Academic performance was only significantly associated in the collaboration network, between this and OutdegreeN. This study shows the impact of interdisciplinary activities on teaching methodologies and the repercussions of emotions on curricular activity.

ACS Style

Pilar Marqués-Sánchez; Isaías García-Rodríguez; José Benítez-Andrades; Iván Fulgueiras-Carril; Patricia Fernández-Sierra; Elena Fernández-Martínez. Networks and Emotions in Cooperative Work: A Quasi-Experimental Study in University Nursing and Computer Engineering Students. Healthcare 2020, 8, 220 .

AMA Style

Pilar Marqués-Sánchez, Isaías García-Rodríguez, José Benítez-Andrades, Iván Fulgueiras-Carril, Patricia Fernández-Sierra, Elena Fernández-Martínez. Networks and Emotions in Cooperative Work: A Quasi-Experimental Study in University Nursing and Computer Engineering Students. Healthcare. 2020; 8 (3):220.

Chicago/Turabian Style

Pilar Marqués-Sánchez; Isaías García-Rodríguez; José Benítez-Andrades; Iván Fulgueiras-Carril; Patricia Fernández-Sierra; Elena Fernández-Martínez. 2020. "Networks and Emotions in Cooperative Work: A Quasi-Experimental Study in University Nursing and Computer Engineering Students." Healthcare 8, no. 3: 220.

Journal article
Published: 01 July 2020 in Information Sciences
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The use of social network theory and methods of analysis have been applied to different domains in recent years, including public health. The complete procedure for carrying out a social network analysis (SNA) is a time-consuming task that entails a series of steps in which the expert in social network analysis could make mistakes. This research presents a multi-domain knowledge model capable of automatically gathering data and carrying out different social network analyses in different domains, without errors and obtaining the same conclusions that an expert in SNA would obtain. The model is represented in an ontology called OntoSNAQA, which is made up of classes, properties and rules representing the domains of People, Questionnaires and Social Network Analysis. Besides the ontology itself, different rules are represented by SWRL and SPARQL queries. A Knowledge Based System was created using OntoSNAQA and applied to a real case study in order to show the advantages of the approach. Finally, the results of an SNA analysis obtained through the model were compared to those obtained from some of the most widely used SNA applications: UCINET, Pajek, Cytoscape and Gephi, to test and confirm the validity of the model.

ACS Style

José Alberto Benítez-Andrades; Isaías García-Rodríguez; Carmen Benavides; Héctor Alaiz-Moretón; José Emilio Labra Gayo. An ontology-based multi-domain model in social network analysis: Experimental validation and case study. Information Sciences 2020, 540, 390 -413.

AMA Style

José Alberto Benítez-Andrades, Isaías García-Rodríguez, Carmen Benavides, Héctor Alaiz-Moretón, José Emilio Labra Gayo. An ontology-based multi-domain model in social network analysis: Experimental validation and case study. Information Sciences. 2020; 540 ():390-413.

Chicago/Turabian Style

José Alberto Benítez-Andrades; Isaías García-Rodríguez; Carmen Benavides; Héctor Alaiz-Moretón; José Emilio Labra Gayo. 2020. "An ontology-based multi-domain model in social network analysis: Experimental validation and case study." Information Sciences 540, no. : 390-413.

Journal article
Published: 01 May 2020 in Future Generation Computer Systems
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ACS Style

José Alberto Benítez-Andrades; Isaías García-Rodríguez; Carmen Benavides; Héctor Alaiz-Moretón; Alejandro Rodríguez-González. Social network analysis for personalized characterization and risk assessment of alcohol use disorders in adolescents using semantic technologies. Future Generation Computer Systems 2020, 106, 154 -170.

AMA Style

José Alberto Benítez-Andrades, Isaías García-Rodríguez, Carmen Benavides, Héctor Alaiz-Moretón, Alejandro Rodríguez-González. Social network analysis for personalized characterization and risk assessment of alcohol use disorders in adolescents using semantic technologies. Future Generation Computer Systems. 2020; 106 ():154-170.

Chicago/Turabian Style

José Alberto Benítez-Andrades; Isaías García-Rodríguez; Carmen Benavides; Héctor Alaiz-Moretón; Alejandro Rodríguez-González. 2020. "Social network analysis for personalized characterization and risk assessment of alcohol use disorders in adolescents using semantic technologies." Future Generation Computer Systems 106, no. : 154-170.

Journal article
Published: 04 March 2020 in Sensors
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This study shows the feasibility of an eHealth solution for tackling eating habits and physical activity in the adolescent population. The participants were children from 11 to 15 years old. An intervention was carried out on 139 students in the intervention group and 91 students in the control group, in two schools during 14 weeks. The intervention group had access to the web through a user account and a password. They were able to create friendship relationships, post comments, give likes and interact with other users, as well as receive notifications and information about nutrition and physical activity on a daily basis and get (virtual) rewards for improving their habits. The control group did not have access to any of these features. The homogeneity of the samples in terms of gender, age, body mass index and initial health-related habits was demonstrated. Pre- and post-measurements were collected through self-reports on the application website. After applying multivariate analysis of variance, a significant alteration in the age-adjusted body mass index percentile was observed in the intervention group versus the control group, as well as in the PAQ-A score and the KIDMED score. It can be concluded that eHealth interventions can help to obtain healthy habits. More research is needed to examine the effectiveness in achieving adherence to these new habits.

ACS Style

José Alberto Benítez-Andrades; Natalia Arias; María Teresa García-Ordás; Marta Martínez-Martínez; Isaías García-Rodríguez. Feasibility of Social-Network-Based eHealth Intervention on the Improvement of Healthy Habits among Children. Sensors 2020, 20, 1404 .

AMA Style

José Alberto Benítez-Andrades, Natalia Arias, María Teresa García-Ordás, Marta Martínez-Martínez, Isaías García-Rodríguez. Feasibility of Social-Network-Based eHealth Intervention on the Improvement of Healthy Habits among Children. Sensors. 2020; 20 (5):1404.

Chicago/Turabian Style

José Alberto Benítez-Andrades; Natalia Arias; María Teresa García-Ordás; Marta Martínez-Martínez; Isaías García-Rodríguez. 2020. "Feasibility of Social-Network-Based eHealth Intervention on the Improvement of Healthy Habits among Children." Sensors 20, no. 5: 1404.

Journal article
Published: 22 February 2020 in Sensors
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The aim of this paper was the detection of pathologies through respiratory sounds. The ICBHI (International Conference on Biomedical and Health Informatics) Benchmark was used. This dataset is composed of 920 sounds of which 810 are of chronic diseases, 75 of non-chronic diseases and only 35 of healthy individuals. As more than 88% of the samples of the dataset are from the same class (Chronic), the use of a Variational Convolutional Autoencoder was proposed to generate new labeled data and other well known oversampling techniques after determining that the dataset classes are unbalanced. Once the preprocessing step was carried out, a Convolutional Neural Network (CNN) was used to classify the respiratory sounds into healthy, chronic, and non-chronic disease. In addition, we carried out a more challenging classification trying to distinguish between the different types of pathologies or healthy: URTI, COPD, Bronchiectasis, Pneumonia, and Bronchiolitis. We achieved results up to 0.993 F-Score in the three-label classification and 0.990 F-Score in the more challenging six-class classification.

ACS Style

María Teresa García-Ordás; José Alberto Benítez-Andrades; Isaías García-Rodríguez; Carmen Benavides; Héctor Alaiz-Moretón. Detecting Respiratory Pathologies Using Convolutional Neural Networks and Variational Autoencoders for Unbalancing Data. Sensors 2020, 20, 1214 .

AMA Style

María Teresa García-Ordás, José Alberto Benítez-Andrades, Isaías García-Rodríguez, Carmen Benavides, Héctor Alaiz-Moretón. Detecting Respiratory Pathologies Using Convolutional Neural Networks and Variational Autoencoders for Unbalancing Data. Sensors. 2020; 20 (4):1214.

Chicago/Turabian Style

María Teresa García-Ordás; José Alberto Benítez-Andrades; Isaías García-Rodríguez; Carmen Benavides; Héctor Alaiz-Moretón. 2020. "Detecting Respiratory Pathologies Using Convolutional Neural Networks and Variational Autoencoders for Unbalancing Data." Sensors 20, no. 4: 1214.

Journal article
Published: 11 November 2019 in Sustainability
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: This study proposed a collaborative methodology among university students in different grades in order to find sustainable strategies that are an added value for students, teachers, and society. In daily professional practice, different professionals must develop skills to collaborate and understand each other. For that reality to be sustainable, we believe that experiences must begin in the context of higher education. Social network analysis offers a new perspective on optimizing relationships between university students. The main goal of this study was to analyze students’ behavior in their networks following an educational intervention and the association with academic performance, resilience and engagement. This was a descriptive quasi-experimental study with pre–post measures of a cooperative interdisciplinary intervention. Participants comprised 50 nursing and computer engineering students. We measured help, friendship, and negative network centrality, engagement, resilience, and academic performance. No significant differences were observed between pre–post-intervention centrality measures in the negative network. However, the help and friendship networks presented statistically significant differences between inDegreeN, OutDegreeN and EigenvectorN on the one hand, and resilience and engagement—but not academic performance—on the other. Academic performance was solely associated with the team to which participants belonged. Cooperative interdisciplinary learning increased the number of ties and levels of prestige and influence among classmates. Further research is required in order to determine the influence of engagement and resilience on academic performance and the role of negative networks in network formation in education. This study provides important information for proposals on sustainable assessments in the field of higher education.

ACS Style

Pilar Marqués-Sánchez; Isaías García-Rodríguez; José Alberto Benítez-Andrades; Mari Carmen Portillo; Javier Pérez-Paniagua; María Mercedes Reguera-García. A Cooperative Interdisciplinary Task Intervention with Undergraduate Nursing and Computer Engineering Students. Sustainability 2019, 11, 6325 .

AMA Style

Pilar Marqués-Sánchez, Isaías García-Rodríguez, José Alberto Benítez-Andrades, Mari Carmen Portillo, Javier Pérez-Paniagua, María Mercedes Reguera-García. A Cooperative Interdisciplinary Task Intervention with Undergraduate Nursing and Computer Engineering Students. Sustainability. 2019; 11 (22):6325.

Chicago/Turabian Style

Pilar Marqués-Sánchez; Isaías García-Rodríguez; José Alberto Benítez-Andrades; Mari Carmen Portillo; Javier Pérez-Paniagua; María Mercedes Reguera-García. 2019. "A Cooperative Interdisciplinary Task Intervention with Undergraduate Nursing and Computer Engineering Students." Sustainability 11, no. 22: 6325.

Conference paper
Published: 26 June 2019 in 5th International Conference on Higher Education Advances (HEAd'19)
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Currently there is a trend towards facilitating multidisciplinary research and collaborations between different faculties and/or multi-university collaboration. In order to achieve standardization, we believe that this culture should begin with the teaching-learning processes. This research has investigated collaborative work between nursing students and computer engineering students. To analyze the group response, an analysis of the contacts was carried out through Social Network Analisys, pre- and post-intervention. The student networks analyzed were friendship, collaboration and negative networks. The results show that the intervention had a positive impact on networks among students, creating greater cohesiveness due to the resources they shared. The research adds useful evidence for proposing innovative and multidisciplinary strategies in terms of networks.

ACS Style

José Alberto Benítez-Andrades; Isaías García; Carmen Benavides; Javier Pérez-Paniagua; Pilar Marqués-Sánchez; Mercedes Reguera. Networks that Cross the Boundaries of the Classroom: A Quasi-Experimental Study of University Students. 5th International Conference on Higher Education Advances (HEAd'19) 2019, 1 .

AMA Style

José Alberto Benítez-Andrades, Isaías García, Carmen Benavides, Javier Pérez-Paniagua, Pilar Marqués-Sánchez, Mercedes Reguera. Networks that Cross the Boundaries of the Classroom: A Quasi-Experimental Study of University Students. 5th International Conference on Higher Education Advances (HEAd'19). 2019; ():1.

Chicago/Turabian Style

José Alberto Benítez-Andrades; Isaías García; Carmen Benavides; Javier Pérez-Paniagua; Pilar Marqués-Sánchez; Mercedes Reguera. 2019. "Networks that Cross the Boundaries of the Classroom: A Quasi-Experimental Study of University Students." 5th International Conference on Higher Education Advances (HEAd'19) , no. : 1.

Conference paper
Published: 01 June 2019 in 2019 14th Iberian Conference on Information Systems and Technologies (CISTI)
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ACS Style

Hugo Sanjurjo-González; Hector Alaiz-Moreton; Noelia Ramon; Belen Labrador; Isaias Garcia. Developing an Open Writing Aid for Non-Native Speakers of English: An Ontology-Based Approach. 2019 14th Iberian Conference on Information Systems and Technologies (CISTI) 2019, 1 .

AMA Style

Hugo Sanjurjo-González, Hector Alaiz-Moreton, Noelia Ramon, Belen Labrador, Isaias Garcia. Developing an Open Writing Aid for Non-Native Speakers of English: An Ontology-Based Approach. 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). 2019; ():1.

Chicago/Turabian Style

Hugo Sanjurjo-González; Hector Alaiz-Moreton; Noelia Ramon; Belen Labrador; Isaias Garcia. 2019. "Developing an Open Writing Aid for Non-Native Speakers of English: An Ontology-Based Approach." 2019 14th Iberian Conference on Information Systems and Technologies (CISTI) , no. : 1.

Research article
Published: 07 April 2019 in Complexity
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The large number of sensors and actuators that make up the Internet of Things obliges these systems to use diverse technologies and protocols. This means that IoT networks are more heterogeneous than traditional networks. This gives rise to new challenges in cybersecurity to protect these systems and devices which are characterized by being connected continuously to the Internet. Intrusion detection systems (IDS) are used to protect IoT systems from the various anomalies and attacks at the network level. Intrusion Detection Systems (IDS) can be improved through machine learning techniques. Our work focuses on creating classification models that can feed an IDS using a dataset containing frames under attacks of an IoT system that uses the MQTT protocol. We have addressed two types of method for classifying the attacks, ensemble methods and deep learning models, more specifically recurrent networks with very satisfactory results.

ACS Style

Hector Alaiz-Moreton; Jose Aveleira-Mata; Jorge Ondicol-Garcia; Angel Luis Muñoz-Castañeda; Isaías García; Carmen Benavides. Multiclass Classification Procedure for Detecting Attacks on MQTT-IoT Protocol. Complexity 2019, 2019, 1 -11.

AMA Style

Hector Alaiz-Moreton, Jose Aveleira-Mata, Jorge Ondicol-Garcia, Angel Luis Muñoz-Castañeda, Isaías García, Carmen Benavides. Multiclass Classification Procedure for Detecting Attacks on MQTT-IoT Protocol. Complexity. 2019; 2019 ():1-11.

Chicago/Turabian Style

Hector Alaiz-Moreton; Jose Aveleira-Mata; Jorge Ondicol-Garcia; Angel Luis Muñoz-Castañeda; Isaías García; Carmen Benavides. 2019. "Multiclass Classification Procedure for Detecting Attacks on MQTT-IoT Protocol." Complexity 2019, no. : 1-11.

Conference paper
Published: 30 March 2019 in Advances in Intelligent Systems and Computing
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Production rules have been traditionally considered a good knowledge representation formalism for creating expert systems, and also as a good mechanism for building intelligence within software agents due to the flexibility of their declarative knowledge representation. But the use of rules and rule engines for implementing behaviors inside agents in the context of a multiagent environment has a number of challenges if one wants to adhere and preserve the defining characteristics of agency and support the kind of communication and collaboration mechanisms needed by multiagent systems. This paper describes a framework, and its implementation, for the integration of production rules reasoning mechanisms inside software agents in the context of a multiagent platform, preserving the defining characteristics of agency and accomplishing the well-established FIPA standards for agent interaction. The implementation has been accomplished by using either CLIPS or Jess as the rule engine, but it can be extended to other formalisms. JADE was chosen as the multiagent platform for developing and testing the solution. The proposed framework includes the uncoupled integration of the rule inference engine into the agent and the adherence to FIPA specifications about using protocols and communication processes. The resulting framework can be used to adapt legacy expert systems whose functionality can be divided to be performed by separate agents or to build new, distributed intelligent systems exploiting the capacities of a multiagent platform at different levels. To show the validity of the approach, a functional test environment was built and is available for downloading.

ACS Style

Francisco J. Aguayo-Canela; Héctor Alaiz-Moretón; Isaías García-Rodríguez; Carmen Benavides-Cuéllar; José Alberto Benítez-Andrades; Paulo Novais. A FIPA-Compliant Framework for Integrating Rule Engines into Software Agents for Supporting Communication and Collaboration in a Multiagent Platform. Advances in Intelligent Systems and Computing 2019, 124 -133.

AMA Style

Francisco J. Aguayo-Canela, Héctor Alaiz-Moretón, Isaías García-Rodríguez, Carmen Benavides-Cuéllar, José Alberto Benítez-Andrades, Paulo Novais. A FIPA-Compliant Framework for Integrating Rule Engines into Software Agents for Supporting Communication and Collaboration in a Multiagent Platform. Advances in Intelligent Systems and Computing. 2019; ():124-133.

Chicago/Turabian Style

Francisco J. Aguayo-Canela; Héctor Alaiz-Moretón; Isaías García-Rodríguez; Carmen Benavides-Cuéllar; José Alberto Benítez-Andrades; Paulo Novais. 2019. "A FIPA-Compliant Framework for Integrating Rule Engines into Software Agents for Supporting Communication and Collaboration in a Multiagent Platform." Advances in Intelligent Systems and Computing , no. : 124-133.

Journal article
Published: 01 January 2019 in Dementia and Geriatric Cognitive Disorders
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Different studies have proven the effectiveness of cognitive stimulation (CS) for people with mild to moderate dementia, but further research is needed to gain insight into how CS interventions should be designed and developed. The objective of this study was to gather and analyze data about the development of a series of CS sessions with Alzheimer's disease (AD) patients, to gain insight into how different individuals engage to different CS activities. 24 AD patients with mild to moderate dementia (GDS = 4 and 5) participated in the study. Twelve different sessions were held with a different stimulation exercise each. Information about the achievement and engagement for each of the exercises were recorded for each patient. A significant correlation was found between the global engagement and the GDS level, and between engagement and gender (and also with educational level) for one of the exercises. These results may be useful for designing CS sessions depending on the composition of the group. For example, five exercises got very different engagement results when comparing patients with GDS = 4 and GDS = 5; if the session group consists of patients with both GDS levels, these kinds of exercises should be avoided to gain homogeneity in the engagement and prevent discouragement. The type and characteristics of CS exercises have an impact on the engagement level of AD patients with mild to moderate dementia. Further studies are necessary to better understand which characteristics of the exercises affect the engagement of the patient according to their particularities. This kind of study may help the design of CS sessions and improve the results obtained.

ACS Style

Silvia Tato-Colín; Luis Alberto Hurtado-Aznar; Isaías García-Rodríguez; Carmen Benavides-Cuéllar; Leticia Sánchez Valdeón. Improving Engagement of Mild to Moderate Dementia Alzheimer’s Disease Patients Using Evidence-Based Visual Cognitive Stimulation Exercises. Dementia and Geriatric Cognitive Disorders 2019, 48, 143 -153.

AMA Style

Silvia Tato-Colín, Luis Alberto Hurtado-Aznar, Isaías García-Rodríguez, Carmen Benavides-Cuéllar, Leticia Sánchez Valdeón. Improving Engagement of Mild to Moderate Dementia Alzheimer’s Disease Patients Using Evidence-Based Visual Cognitive Stimulation Exercises. Dementia and Geriatric Cognitive Disorders. 2019; 48 (3-4):143-153.

Chicago/Turabian Style

Silvia Tato-Colín; Luis Alberto Hurtado-Aznar; Isaías García-Rodríguez; Carmen Benavides-Cuéllar; Leticia Sánchez Valdeón. 2019. "Improving Engagement of Mild to Moderate Dementia Alzheimer’s Disease Patients Using Evidence-Based Visual Cognitive Stimulation Exercises." Dementia and Geriatric Cognitive Disorders 48, no. 3-4: 143-153.

Journal article
Published: 31 October 2018 in International Journal of Environmental Research and Public Health
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Social Network Analysis (SNA) is a set of techniques developed in the field of social and behavioral sciences research, in order to characterize and study the social relationships that are established among a set of individuals. When building a social network for performing an SNA analysis, an initial process of data gathering is achieved in order to extract the characteristics of the individuals and their relationships. This is usually done by completing a questionnaire containing different types of questions that will be later used to obtain the SNA measures needed to perform the study. There are, then, a great number of different possible network-generating questions and also many possibilities for mapping the responses to the corresponding characteristics and relationships. Many variations may be introduced into these questions (the way they are posed, the weights given to each of the responses, etc.) that may have an effect on the resulting networks. All these different variations are difficult to achieve manually, because the process is time-consuming and error-prone. The tool described in this paper uses semantic knowledge representation techniques in order to facilitate this kind of sensitivity studies. The base of the tool is a conceptual structure, called “ontology” that is able to represent the different concepts and their definitions. The tool is compared to other similar ones, and the advantages of the approach are highlighted, giving some particular examples from an ongoing SNA study about alcohol consumption habits in adolescents.

ACS Style

José Alberto Benítez-Andrades; Alejandro Rodríguez-González; Carmen Benavides; Leticia Sánchez-Valdeón; Isaías García. A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies. International Journal of Environmental Research and Public Health 2018, 15, 2420 .

AMA Style

José Alberto Benítez-Andrades, Alejandro Rodríguez-González, Carmen Benavides, Leticia Sánchez-Valdeón, Isaías García. A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies. International Journal of Environmental Research and Public Health. 2018; 15 (11):2420.

Chicago/Turabian Style

José Alberto Benítez-Andrades; Alejandro Rodríguez-González; Carmen Benavides; Leticia Sánchez-Valdeón; Isaías García. 2018. "A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies." International Journal of Environmental Research and Public Health 15, no. 11: 2420.

Journal article
Published: 30 October 2018 in Data & Knowledge Engineering
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Different approaches have been used in order to represent and build control engineering concepts for the computer. Software applications for these fields are becoming more and more demanding each day, and new representation schemas are continuously being developed. This paper describes a study of the use of knowledge models represented in ontologies for building Computer Aided Control Systems Design (CACSD) tools. The use of this approach allows the construction of formal conceptual structures that can be stated independently of any software application and be used in many different ones. In order to show the advantages of this approach, an ontology and an application have been built for the domain of design of lead/lag controllers with the root locus method, presenting the results and benefits found.

ACS Style

Carmen Benavides; Isaías García; Héctor Alaiz; Luis Quesada. An ontology-based approach to knowledge representation for Computer-Aided Control System Design. Data & Knowledge Engineering 2018, 118, 1 .

AMA Style

Carmen Benavides, Isaías García, Héctor Alaiz, Luis Quesada. An ontology-based approach to knowledge representation for Computer-Aided Control System Design. Data & Knowledge Engineering. 2018; 118 ():1.

Chicago/Turabian Style

Carmen Benavides; Isaías García; Héctor Alaiz; Luis Quesada. 2018. "An ontology-based approach to knowledge representation for Computer-Aided Control System Design." Data & Knowledge Engineering 118, no. : 1.

Journal article
Published: 21 August 2018 in International Journal of Environmental Research and Public Health
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In adolescence, friends are important due to their influence on the acquisition of habits such as alcohol consumption. However, there is a lack of studies that describe the structural context of adolescents, which would be useful to implement prevention strategies. Therefore, our research question was how adolescent friendship networks influence alcohol consumption. Our goal was to determine the structural profile of adolescent at-risk alcohol users and their relational context in the classroom. We designed a descriptive cross-sectional study based on social network analysis to analyze structural patterns. We recruited 195 students. Social-network and alcohol-consumption variables were analyzed using the UCINET and STATA programs. Some 86.67% of participants had consumed alcohol at some time in their lives and the prevalence of at-risk alcohol use was higher in females (50.48% vs. 49.52%; OR: 1.84; CI 95%: 0.99–3.43%; p = 0.036). The lower the intensity of friendship, the more contacts adolescent at-risk alcohol users had within the network, and the easier it was for them to access their peers. Consequently, we conclude that the structure of a class is a key factor that merits further research.

ACS Style

Enedina Quiroga; Arrate Pinto-Carral; Isaías García; Antonio J. Molina; Tania Fernández-Villa; Vicente Martín. The Influence of Adolescents’ Social Networks on Alcohol Consumption: A Descriptive Study of Spanish Adolescents Using Social Network Analysis. International Journal of Environmental Research and Public Health 2018, 15, 1795 .

AMA Style

Enedina Quiroga, Arrate Pinto-Carral, Isaías García, Antonio J. Molina, Tania Fernández-Villa, Vicente Martín. The Influence of Adolescents’ Social Networks on Alcohol Consumption: A Descriptive Study of Spanish Adolescents Using Social Network Analysis. International Journal of Environmental Research and Public Health. 2018; 15 (9):1795.

Chicago/Turabian Style

Enedina Quiroga; Arrate Pinto-Carral; Isaías García; Antonio J. Molina; Tania Fernández-Villa; Vicente Martín. 2018. "The Influence of Adolescents’ Social Networks on Alcohol Consumption: A Descriptive Study of Spanish Adolescents Using Social Network Analysis." International Journal of Environmental Research and Public Health 15, no. 9: 1795.

Journal article
Published: 08 December 2017 in International Journal of Environmental Research and Public Health
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Adolescence is a transitional period during which a number of changes occur. Social relationships established during this period influence adolescent behaviour and affect academic performance or alcohol consumption habits, among other issues. Teachers are very important actors in observing and guiding the evolution of their students, and should therefore have the appropriate knowledge and tools to gain insight into the complex social relationships that exist in their classes. The use of social network analysis (SNA) techniques may be helpful in order to study and monitor the evolution of these social networks. This study tries to understand how teachers perceive SNA metrics from an intuitive point of view. Using this information, useful tools could be created that allow teachers to use SNA techniques to improve their understanding of student relationships. A number of interviews with different teachers were held in secondary schools in Spain, allowing SNA concepts to be related to the everyday terms used by the teachers to characterize their students. Results from the study have an impact on questionnaire design for gathering data from students in order to perform an SNA analysis and on the design of software applications that can help teachers to understand the results of this analysis.

ACS Style

Enedina Quiroga; Isaías García; José Alberto Benítez-Andrades; Carmen Benavides; Vicente Martín; Enedina Quiroga Sanchez. A Qualitative Study of Secondary School Teachers’ Perception of Social Network Analysis Metrics in the Context of Alcohol Consumption among Adolescents. International Journal of Environmental Research and Public Health 2017, 14, 1531 .

AMA Style

Enedina Quiroga, Isaías García, José Alberto Benítez-Andrades, Carmen Benavides, Vicente Martín, Enedina Quiroga Sanchez. A Qualitative Study of Secondary School Teachers’ Perception of Social Network Analysis Metrics in the Context of Alcohol Consumption among Adolescents. International Journal of Environmental Research and Public Health. 2017; 14 (12):1531.

Chicago/Turabian Style

Enedina Quiroga; Isaías García; José Alberto Benítez-Andrades; Carmen Benavides; Vicente Martín; Enedina Quiroga Sanchez. 2017. "A Qualitative Study of Secondary School Teachers’ Perception of Social Network Analysis Metrics in the Context of Alcohol Consumption among Adolescents." International Journal of Environmental Research and Public Health 14, no. 12: 1531.