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Dr. Iván García-Magariño
University of Zaragoza, Department of Computer Science and Engineering of Systems, Teruel , Spain

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0 Big Data
0 Internet of Things
0 wearable sensors
0 Datamining
0 Mobile applications for health and well-being

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Internet of Things
Agent-based simulation and multi-agent systems
Mobile applications for health and well-being
Big Data

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Research article
Published: 17 March 2021 in Wireless Communications and Mobile Computing
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The last decade has witnessed a steep growth in multimedia traffic due to real-time content delivery such as in online games and video conferencing. In some contexts, MANETs play a key role in the hyperconnectivity of everything in multimedia services. In this context, this work proposes a new scheduling approach based on context-aware mobile nodes for their connectivity. The contribution relies on reporting not only the locations of devices in the network but also their movement identified by sensors. In order to illustrate this approach, we have developed a novel agent-based simulator called MASEMUL for illustrating the proposed approach. The results show that a movement-aware scheduling strategy defined with the proposed approach has decreased the ratio of channel interruptions over another common strategy in mobile networks.

ACS Style

Moustafa M. Nasralla; Iván García-Magariño; Jaime Lloret. MASEMUL: A Simulation Tool for Movement-Aware MANET Scheduling Strategies for Multimedia Communications. Wireless Communications and Mobile Computing 2021, 2021, 1 -12.

AMA Style

Moustafa M. Nasralla, Iván García-Magariño, Jaime Lloret. MASEMUL: A Simulation Tool for Movement-Aware MANET Scheduling Strategies for Multimedia Communications. Wireless Communications and Mobile Computing. 2021; 2021 ():1-12.

Chicago/Turabian Style

Moustafa M. Nasralla; Iván García-Magariño; Jaime Lloret. 2021. "MASEMUL: A Simulation Tool for Movement-Aware MANET Scheduling Strategies for Multimedia Communications." Wireless Communications and Mobile Computing 2021, no. : 1-12.

Journal article
Published: 18 February 2021 in Sustainability
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The COVID-19 pandemic has changed people’s lives and the way in which certain services are provided. Such changes are not uncommon in healthcare services and they will have to adapt to the new situation by increasing the number of services remotely offered. Limited mobility has resulted in interruption of treatments that traditionally have been administered through face-to-face modalities, especially those related to cognitive impairments. In this telerehabilitation approach, both the patient and the specialist physician enter a virtual reality (VR) environment where they can interact in real time through avatars. A spaced retrieval (SR) task is implemented in the system to analyze cognitive performance. An experimental group (n = 20) performed the SR task in telerehabilitation mode, whereas a control group (n = 20) performed the SR task through a traditional face-to-face mode. The obtained results showed that it is possible to carry out cognitive rehabilitation processes through a telerehabilitation modality in conjunction with VR. The cost-effectiveness of the system will also contribute to making healthcare systems more efficient, overcoming both geographical and temporal limitations.

ACS Style

José Varela-Aldás; Jorge Buele; Pedro Ramos Lorente; Iván García-Magariño; Guillermo Palacios-Navarro. A Virtual Reality-Based Cognitive TeleRehabilitation System for Use in the COVID-19 Pandemic. Sustainability 2021, 13, 2183 .

AMA Style

José Varela-Aldás, Jorge Buele, Pedro Ramos Lorente, Iván García-Magariño, Guillermo Palacios-Navarro. A Virtual Reality-Based Cognitive TeleRehabilitation System for Use in the COVID-19 Pandemic. Sustainability. 2021; 13 (4):2183.

Chicago/Turabian Style

José Varela-Aldás; Jorge Buele; Pedro Ramos Lorente; Iván García-Magariño; Guillermo Palacios-Navarro. 2021. "A Virtual Reality-Based Cognitive TeleRehabilitation System for Use in the COVID-19 Pandemic." Sustainability 13, no. 4: 2183.

Journal article
Published: 23 November 2020 in Computers & Electrical Engineering
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In the last few years, several techniques and models are used for retrieving significant information from urban big data of smart cities. This research work aims at developing a data fusion-based traffic congestion control system in smart cities using a deep learning model. A hybrid model based on the convolution neural network (CNN) and long short term memory (LSTM) architectures are used for region-based traffic flow predictions in smart cities. CNN is used for the classification of spatial data while LSTM for temporal data. The experiments used the CityPulse Traffic and CityPulse Pollution datasets, and measured root mean square error (RMSE), time consumption and accuracy. A small RMSE value of 49 and highest accuracy of 92.3% compared to other baseline models depicts the applicability of the proposed model in the region-based traffic flow prediction problems in the smart cities.

ACS Style

Sulaiman Khan; Shah Nazir; Iván García-Magariño; Anwar Hussain. Deep learning-based urban big data fusion in smart cities: Towards traffic monitoring and flow-preserving fusion. Computers & Electrical Engineering 2020, 89, 106906 .

AMA Style

Sulaiman Khan, Shah Nazir, Iván García-Magariño, Anwar Hussain. Deep learning-based urban big data fusion in smart cities: Towards traffic monitoring and flow-preserving fusion. Computers & Electrical Engineering. 2020; 89 ():106906.

Chicago/Turabian Style

Sulaiman Khan; Shah Nazir; Iván García-Magariño; Anwar Hussain. 2020. "Deep learning-based urban big data fusion in smart cities: Towards traffic monitoring and flow-preserving fusion." Computers & Electrical Engineering 89, no. : 106906.

Journal article
Published: 17 November 2020 in Sensors
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Virtual Reality (VR) has had significant advances in rehabilitation, due to the gamification of cognitive activities that facilitate treatment. On the other hand, Immersive Virtual Reality (IVR) produces outstanding results due to the interactive features with the user. This work introduces a VR application for memory rehabilitation by walking through a maze and using the Oculus Go head-mounted display (HMD) technology. The mechanics of the game require memorizing geometric shapes while the player progresses in two modes, autonomous or manual, with two levels of difficulty depending on the number of elements to remember. The application is developed in the Unity 3D video game engine considering the optimization of computational resources to improve the performance in the processing and maintaining adequate benefits for the user, while the generated data is stored and sent to a remote server. The maze task was assessed with 29 subjects in a controlled environment. The obtained results show a significant correlation between participants’ response accuracy in both the maze task and a face–pair test. Thus, the proposed task is able to perform memory assessments.

ACS Style

José Varela-Aldás; Guillermo Palacios-Navarro; Rebecca Amariglio; Iván García-Magariño. Head-Mounted Display-Based Application for Cognitive Training. Sensors 2020, 20, 6552 .

AMA Style

José Varela-Aldás, Guillermo Palacios-Navarro, Rebecca Amariglio, Iván García-Magariño. Head-Mounted Display-Based Application for Cognitive Training. Sensors. 2020; 20 (22):6552.

Chicago/Turabian Style

José Varela-Aldás; Guillermo Palacios-Navarro; Rebecca Amariglio; Iván García-Magariño. 2020. "Head-Mounted Display-Based Application for Cognitive Training." Sensors 20, no. 22: 6552.

Research article
Published: 15 July 2020 in Journal of Healthcare Engineering
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The management of cancer patients’ symptoms in doctor consultations is a cornerstone in clinical care, this process being fundamental for the follow-up of the evolution of these. This article presents an application that allows collecting periodically and systematically the data of cancer patients and their visualization by the medical team. In this article, we made the analysis, design, implementation, and final evaluation by analyzing the correlation of this data collection with interaction patterns to determine how the user information can be enriched with information from the interaction patterns. We have followed an agile methodology based on the iterative and incremental development of successive prototypes with increased fidelity, where the requirements and solutions have evolved over time according to the need and assessments made. The comprehensive analysis of the patient’s condition allowed us to perform a first analysis of the correlation of the states of patients concerning mood, sleeping quality, and pain with the interaction patterns. A future goal of this project is to optimize the process of data collection and the analysis of information. Another future goal is to reduce the time dedicated to reporting the evolution of symptoms in face-to-face consultations and to help professionals in analyzing the patient’s evolution even in the period that has not been attended in person.

ACS Style

Javier Navarro-Alamán; Raquel Lacuesta; Iván García-Magariño; Jesús Gallardo; Elena Ibarz; Jaime Lloret. Close2U: An App for Monitoring Cancer Patients with Enriched Information from Interaction Patterns. Journal of Healthcare Engineering 2020, 2020, 1 -13.

AMA Style

Javier Navarro-Alamán, Raquel Lacuesta, Iván García-Magariño, Jesús Gallardo, Elena Ibarz, Jaime Lloret. Close2U: An App for Monitoring Cancer Patients with Enriched Information from Interaction Patterns. Journal of Healthcare Engineering. 2020; 2020 ():1-13.

Chicago/Turabian Style

Javier Navarro-Alamán; Raquel Lacuesta; Iván García-Magariño; Jesús Gallardo; Elena Ibarz; Jaime Lloret. 2020. "Close2U: An App for Monitoring Cancer Patients with Enriched Information from Interaction Patterns." Journal of Healthcare Engineering 2020, no. : 1-13.

Journal article
Published: 15 July 2020 in Sensors
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Multi-Agent Systems can support e-Healthcare applications for improving quality of life of citizens. In this direction, we propose a healthcare system architecture named smart healthcare city. First, we divide a given city into various zones and then we propose a zonal level three-layered system architecture. Further, for effectiveness we introduce a Multi-Agent System (MAS) in this three-layered architecture. Protecting sensitive health information of citizens is a major security concern. Group key agreement (GKA) is the corner stone for securely sharing the healthcare data among the healthcare stakeholders of the city. For establishing GKA, many efficient cryptosystems are available in the classical field. However, they are yet dependent on the supposition that some computational problems are infeasible. In light of quantum mechanics, a new field emerges to share a secret key among two or more members. The unbreakable and highly secure features of key agreement based on fundamental laws of physics allow us to propose a Quantum GKA (QGKA) technique based on renowned Quantum Diffie–Hellman (QDH). In this, a node acts as a Group Controller (GC) and forms 2-party groups with remaining nodes, establishing a QDH-style shared key per each two-party. It then joins these keys into a single group key by means of a XOR-operation, acting as a usual group node. Furthermore, we extend the QGKA to Dynamic QGKA (DQGKA) by adding join and leave protocol. Our protocol performance was compared with existing QGKA protocols in terms of Qubit efficiency (QE), unitary operation (UO), unitary operation efficiency (UOE), key consistency check (KCC), security against participants attack (SAP) and satisfactory results were obtained. The security analysis of the proposed technique is based on unconditional security of QDH. Moreover, it is secured against internal and external attack. In this way, e-healthcare Multi-Agent System can be robust against future quantum-based attacks.

ACS Style

Vankamamidi S. Naresh; Moustafa M. Nasralla; Sivaranjani Reddi; Iván García-Magariño. Quantum Diffie–Hellman Extended to Dynamic Quantum Group Key Agreement for e-Healthcare Multi-Agent Systems in Smart Cities. Sensors 2020, 20, 3940 .

AMA Style

Vankamamidi S. Naresh, Moustafa M. Nasralla, Sivaranjani Reddi, Iván García-Magariño. Quantum Diffie–Hellman Extended to Dynamic Quantum Group Key Agreement for e-Healthcare Multi-Agent Systems in Smart Cities. Sensors. 2020; 20 (14):3940.

Chicago/Turabian Style

Vankamamidi S. Naresh; Moustafa M. Nasralla; Sivaranjani Reddi; Iván García-Magariño. 2020. "Quantum Diffie–Hellman Extended to Dynamic Quantum Group Key Agreement for e-Healthcare Multi-Agent Systems in Smart Cities." Sensors 20, no. 14: 3940.

Conference paper
Published: 10 July 2020 in Communications in Computer and Information Science
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An immersive virtual reality application was developed as a serious game to support children on their decisions about food, the system was composed by the Gear VR (Viewer and controller), and a phone which contains the mobile application developed in Unity, providing the immersive environment, the platform was based on a path where the player has to go through it choosing between different sort of meals and also between different physical activities, the effect of balanced diet plus adequate physical activity seems reflected on the avatar previously chosen by the user, the app was tested on 12 children between 8 and 10 years old during one week, children participated on the study after receiving an informed consent, analyzing the tendencies of food choice on children before and after, a notorious positive effect could be seen on the users according to the avatar analyzed at the end of the round, besides a System usability ore was also applied to evaluate the degree of usability of the app, reaching a ore of 88.33% which rates the app as very usable, this results were even better than what was planned at the beginning of the experience.

ACS Style

Esteban M. Fuentes; José Varela-Aldás; Guillermo Palacios-Navarro; Iván García-Magariño. Immersive Virtual Reality App to Promote Healthy Eating in Children. Communications in Computer and Information Science 2020, 9 -15.

AMA Style

Esteban M. Fuentes, José Varela-Aldás, Guillermo Palacios-Navarro, Iván García-Magariño. Immersive Virtual Reality App to Promote Healthy Eating in Children. Communications in Computer and Information Science. 2020; ():9-15.

Chicago/Turabian Style

Esteban M. Fuentes; José Varela-Aldás; Guillermo Palacios-Navarro; Iván García-Magariño. 2020. "Immersive Virtual Reality App to Promote Healthy Eating in Children." Communications in Computer and Information Science , no. : 9-15.

Journal article
Published: 06 July 2020 in Electronics
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Real-time data management analytics involve capturing data in real-time and, at the same time, processing data in a light way to provide an effective real-time support. Real-time data management analytics are key for supporting decisions of business intelligence. The proposed approach covers all these phases by (a) monitoring online information from websites with Selenium-based software and incrementally conforming a database, and (b) incrementally updating summarized information to support real-time decisions. We have illustrated this approach for the investor–company field with the particular fields of Bitcoin cryptocurrency and Internet-of-Things (IoT) smart-meter sensors in smart cities. The results of 40 simulations on historic data showed that one of the proposed investor strategies achieved 7.96% of profits on average in less than two weeks. However, these simulations and other simulations of up to 69 days showed that the benefits were highly variable in these two sets of simulations (respective standard deviations were 24.6% and 19.2%).

ACS Style

Iván García-Magariño; Moustafa M. Nasralla; Shah Nazir. Real-Time Analysis of Online Sources for Supporting Business Intelligence Illustrated with Bitcoin Investments and IoT Smart-Meter Sensors in Smart Cities. Electronics 2020, 9, 1101 .

AMA Style

Iván García-Magariño, Moustafa M. Nasralla, Shah Nazir. Real-Time Analysis of Online Sources for Supporting Business Intelligence Illustrated with Bitcoin Investments and IoT Smart-Meter Sensors in Smart Cities. Electronics. 2020; 9 (7):1101.

Chicago/Turabian Style

Iván García-Magariño; Moustafa M. Nasralla; Shah Nazir. 2020. "Real-Time Analysis of Online Sources for Supporting Business Intelligence Illustrated with Bitcoin Investments and IoT Smart-Meter Sensors in Smart Cities." Electronics 9, no. 7: 1101.

Journal article
Published: 25 June 2020 in IEEE Access
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Internet of Things (IoT) is becoming highly supportive in innovative technological solutions for assisting impaired people. Some of these IoT solutions are still in a prototyping phase ignoring possible attacks and the corresponding security defenses. This article proposes a learning-based approach for defending against perception-layer attacks performed on specific sensor types in smart furniture for impaired people. This approach is based on the analysis of time series by means of dynamic time warping algorithm for calculating similarity and a novel detector for identifying anomalies. This approach has been illustrated by defending against simulated perception-layer magnetic attacks on a smart cupboard with door magnetic sensors. The results show the performance of the proposed approach for properly identifying these attacks. In particular, these results advocate an accuracy about 95.5% per day.

ACS Style

Moustafa M. Nasralla; Ivan Garcia-Magarino; Jaime Lloret. Defenses Against Perception-Layer Attacks on IoT Smart Furniture for Impaired People. IEEE Access 2020, 8, 119795 -119805.

AMA Style

Moustafa M. Nasralla, Ivan Garcia-Magarino, Jaime Lloret. Defenses Against Perception-Layer Attacks on IoT Smart Furniture for Impaired People. IEEE Access. 2020; 8 ():119795-119805.

Chicago/Turabian Style

Moustafa M. Nasralla; Ivan Garcia-Magarino; Jaime Lloret. 2020. "Defenses Against Perception-Layer Attacks on IoT Smart Furniture for Impaired People." IEEE Access 8, no. : 119795-119805.

Journal article
Published: 05 May 2020 in Journal of Biomedical Informatics
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An increasing number of cancer patients is treated and recover each year, and consequently there are survivors that require specialized and coordinated follow-up. The physical, social, working, psychological and emotional aspects of these survivors have to be characterized, investigated and treated by multidisciplinary and interdisciplinary teams. Nowadays, oncology community is focused on tracking records of interest in Patient-Reported Outcome (PROs) for patients of different cancer types. In the last years, several articles have proven that PROs are an effective method to improve the management of patient symptoms and, subsequently, clinical care. In this scenario, patient engagement is one of the most relevant aspects for PROs success. In this sense, one of the most promising strategies for increasing engagement is gamification, that is, the introduction of game elements in systems that are not games. Therefore, in this work we introduce a methodology for developing gamification apps for cancer survivors that aims at increasing engagement when collecting PROs data.

ACS Style

Javier Navarro-Alamán; Raquel Lacuesta; Iván Garcia-Magariño; Jesús Gallardo. A methodology for the design and development of gamified mobile apps for monitoring cancer survivors. Journal of Biomedical Informatics 2020, 106, 103439 .

AMA Style

Javier Navarro-Alamán, Raquel Lacuesta, Iván Garcia-Magariño, Jesús Gallardo. A methodology for the design and development of gamified mobile apps for monitoring cancer survivors. Journal of Biomedical Informatics. 2020; 106 ():103439.

Chicago/Turabian Style

Javier Navarro-Alamán; Raquel Lacuesta; Iván Garcia-Magariño; Jesús Gallardo. 2020. "A methodology for the design and development of gamified mobile apps for monitoring cancer survivors." Journal of Biomedical Informatics 106, no. : 103439.

Journal article
Published: 31 March 2020 in Sensors
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Wireless sensor network and industrial internet of things have been a growing area of research which is exploited in various fields such as smart home, smart industries, smart transportation, and so on. There is a need of a mechanism which can easily tackle the problems of nonlinear delay integro-differential equations for large-scale applications of Internet of Things. In this paper, Haar wavelet collocation technique is developed for the solution of nonlinear delay integro-differential equations for wireless sensor network and industrial Internet of Things. The method is applied to nonlinear delay Volterra, delay Fredholm and delay Volterra–Fredholm integro-differential equations which are based on the use of Haar wavelets. Some examples are given to show the computational efficiency of the proposed technique. The approximate solutions are compared with the exact solution. The maximum absolute and mean square roots errors for distant number of collocation points are also calculated. The results show that Haar method is efficient for solving these equations for industrial Internet of Things. The results are compared with existing methods from the literature. The results exhibit that the method is simple, precise and efficient.

ACS Style

Rohul Amin; Shah Nazir; Iván García-Magariño. A Collocation Method for Numerical Solution of Nonlinear Delay Integro-Differential Equations for Wireless Sensor Network and Internet of Things. Sensors 2020, 20, 1962 .

AMA Style

Rohul Amin, Shah Nazir, Iván García-Magariño. A Collocation Method for Numerical Solution of Nonlinear Delay Integro-Differential Equations for Wireless Sensor Network and Internet of Things. Sensors. 2020; 20 (7):1962.

Chicago/Turabian Style

Rohul Amin; Shah Nazir; Iván García-Magariño. 2020. "A Collocation Method for Numerical Solution of Nonlinear Delay Integro-Differential Equations for Wireless Sensor Network and Internet of Things." Sensors 20, no. 7: 1962.

Review article
Published: 14 November 2019 in Wireless Communications and Mobile Computing
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The impact of Internet of Things has been revolutionized in all fields of life, but its impact on the healthcare system has been significant due to its cutting edge transition. The role of Internet of Things becomes more dominant when it is supported by the features of mobile computing. The mobile computing extends the functionality of IoT in healthcare environment by bringing a massive support in the form of mobile health (m-health). In this research, a systematic literature review protocol is proposed to study how mobile computing assists IoT applications in healthcare, contributes to the current and future research work of IoT in the healthcare system, brings privacy and security in health IoT devices, and affects the IoT in the healthcare system. Furthermore, the intentions of the paper are to study the impacts of mobile computing on IoT in healthcare environment or smart hospitals in light of our systematic literature review protocol. The proposed study reports the papers that were included based on filtering process by title, abstract, and contents, and a total of 116 primary studies were included to support the proposed research. These papers were then analysed for research questions defined for the proposed study.

ACS Style

Shah Nazir; Yasir Ali; Naeem Ullah; Iván García-Magariño. Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review. Wireless Communications and Mobile Computing 2019, 2019, 1 -20.

AMA Style

Shah Nazir, Yasir Ali, Naeem Ullah, Iván García-Magariño. Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review. Wireless Communications and Mobile Computing. 2019; 2019 ():1-20.

Chicago/Turabian Style

Shah Nazir; Yasir Ali; Naeem Ullah; Iván García-Magariño. 2019. "Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review." Wireless Communications and Mobile Computing 2019, no. : 1-20.

Journal article
Published: 26 August 2019 in IEEE Access
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Internet of Things (IoT) widely use analysis of data with artificial intelligence (AI) techniques in order to learn from user actions, support decisions, track relevant aspects of the user, and notify certain events when appropriate. However, most AI techniques are based on mathematical models that are difficult to understand by the general public, so most people use AI-based technology as a black box that they eventually start to trust based on their personal experience. This article proposes to go a step forward in the use of AI in IoT, and proposes a novel approach within the Human-centric AI field for generating explanations about the knowledge learned by a neural network (in particular a multilayer perceptron) from IoT environments. More concretely, this work proposes two techniques based on the analysis of artificial neuron weights, and another technique aimed at explaining each estimation based on the analysis of training cases. This approach has been illustrated in the context of a smart IoT kitchen that detects the user depression based on the food used for each meal, using a simulator for this purpose. The results revealed that most auto-generated explanations made sense in this context (i.e. 97.0%), and the execution times were low (i.e. 1.5 ms or lower) even considering the common configurations varying independently the number of neurons per hidden layer (up to 20), the number of hidden layers (up to 20) and the number of training cases (up to 4,000).

ACS Style

Ivan Garcia-Magarino; Rajarajan Muttukrishnan; Jaime Lloret. Human-Centric AI for Trustworthy IoT Systems With Explainable Multilayer Perceptrons. IEEE Access 2019, 7, 125562 -125574.

AMA Style

Ivan Garcia-Magarino, Rajarajan Muttukrishnan, Jaime Lloret. Human-Centric AI for Trustworthy IoT Systems With Explainable Multilayer Perceptrons. IEEE Access. 2019; 7 (99):125562-125574.

Chicago/Turabian Style

Ivan Garcia-Magarino; Rajarajan Muttukrishnan; Jaime Lloret. 2019. "Human-Centric AI for Trustworthy IoT Systems With Explainable Multilayer Perceptrons." IEEE Access 7, no. 99: 125562-125574.

Conference paper
Published: 28 July 2019 in Advanced Data Mining and Applications
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ACS Style

José Varela-Aldás; Guillermo Palacios-Navarro; Iván García-Magariño; Esteban M. Fuentes. Effects of Immersive Virtual Reality on the Heart Rate of Athlete’s Warm-Up. Advanced Data Mining and Applications 2019, 175 -185.

AMA Style

José Varela-Aldás, Guillermo Palacios-Navarro, Iván García-Magariño, Esteban M. Fuentes. Effects of Immersive Virtual Reality on the Heart Rate of Athlete’s Warm-Up. Advanced Data Mining and Applications. 2019; ():175-185.

Chicago/Turabian Style

José Varela-Aldás; Guillermo Palacios-Navarro; Iván García-Magariño; Esteban M. Fuentes. 2019. "Effects of Immersive Virtual Reality on the Heart Rate of Athlete’s Warm-Up." Advanced Data Mining and Applications , no. : 175-185.

Journal article
Published: 26 July 2019 in Journal of Computational Science
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Some employees suffer from burnout, and most bosses ignore this problem. Job burnout may hinder employees’ quality of life, personal accomplishment and satisfaction with life in general. It can also influence negatively the profits of the business or the organization, as the literature reveals. Mindfulness-based interventions have proven to be useful for ameliorating some aspects of burnout. By the same token, some agent-based simulator (ABSs) have been useful for predicting the influence of mindfulness programs on meditators in different aspects such as their emotions and their heart rate variability. In this context, the current work presents a novel ABS application that simulates the effects of mindfulness-based interventions on the job burnout subscales known as emotional exhaustion, depersonalization, personal accomplishment, exhaustion in general, and disengagement from work. This application allows users to define mindfulness programs without needing any computer-science technical knowledge and simulates its influence on a group of practitioners with certain features. The simulator has been tested by simulating two mindfulness-based interventions of two scenarios reported in the literature. The ABS received input from the pre-intervention burnout measures, and performed 1,000 simulations for each scenario for avoiding bias from the nondeterministic behavior. The simulated outcomes referring to the post-intervention burnout measures were similar to the real ones. The mean differences, mean squared errors and mean absolute error were below 0.4% in the normalized values of all the burnout subscales reported in the two scenarios. The source code of this ABS is publicly available for guaranteeing reproducibility and allowing other researchers to extend it or reuse some of its components.

ACS Style

Iván García-Magariño; Inmaculada Plaza; Filippo Neri. ABS-MindBurnout: An agent-based simulator of the effects of mindfulness-based interventions on job burnout. Journal of Computational Science 2019, 36, 101012 .

AMA Style

Iván García-Magariño, Inmaculada Plaza, Filippo Neri. ABS-MindBurnout: An agent-based simulator of the effects of mindfulness-based interventions on job burnout. Journal of Computational Science. 2019; 36 ():101012.

Chicago/Turabian Style

Iván García-Magariño; Inmaculada Plaza; Filippo Neri. 2019. "ABS-MindBurnout: An agent-based simulator of the effects of mindfulness-based interventions on job burnout." Journal of Computational Science 36, no. : 101012.

Journal article
Published: 04 June 2019 in Sensors
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Sensor systems for the Internet of Things (IoT) make it possible to continuously monitor people, gathering information without any extra effort from them. Thus, the IoT can be very helpful in the context of early disease detection, which can improve peoples’ quality of life by applying the right treatment and measures at an early stage. This paper presents a new use of IoT sensor systems—we present a novel three-door smart cupboard that can measure the memory of a user, aiming at detecting potential memory losses. The smart cupboard has three sensors connected to a Raspberry Pi, whose aim is to detect which doors are opened. Inside of the Raspberry Pi, a Python script detects the openings of the doors, and classifies the events between attempts of finding something without success and the events of actually finding it, in order to measure the user’s memory concerning the objects’ locations (among the three compartments of the smart cupboard). The smart cupboard was assessed with 23 different users in a controlled environment. This smart cupboard was powered by an external battery. The memory assessments of the smart cupboard were compared with a validated test of memory assessment about face–name associations and a self-reported test about self-perceived memory. We found a significant correlation between the smart cupboard results and both memory measurement methods. Thus, we conclude that the proposed novel smart cupboard successfully measured memory.

ACS Style

Franks González-Landero; Iván García-Magariño; Rebecca Amariglio; Raquel Lacuesta. Smart Cupboard for Assessing Memory in Home Environment. Sensors 2019, 19, 2552 .

AMA Style

Franks González-Landero, Iván García-Magariño, Rebecca Amariglio, Raquel Lacuesta. Smart Cupboard for Assessing Memory in Home Environment. Sensors. 2019; 19 (11):2552.

Chicago/Turabian Style

Franks González-Landero; Iván García-Magariño; Rebecca Amariglio; Raquel Lacuesta. 2019. "Smart Cupboard for Assessing Memory in Home Environment." Sensors 19, no. 11: 2552.

Editorial
Published: 21 May 2019 in Mobile Information Systems
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ACS Style

Iván García-Magariño; Dilip Sarkar; Raquel Lacuesta. Wearable Technology and Mobile Applications for Healthcare. Mobile Information Systems 2019, 2019, 1 -2.

AMA Style

Iván García-Magariño, Dilip Sarkar, Raquel Lacuesta. Wearable Technology and Mobile Applications for Healthcare. Mobile Information Systems. 2019; 2019 ():1-2.

Chicago/Turabian Style

Iván García-Magariño; Dilip Sarkar; Raquel Lacuesta. 2019. "Wearable Technology and Mobile Applications for Healthcare." Mobile Information Systems 2019, no. : 1-2.

Journal article
Published: 01 May 2019 in Expert Systems with Applications
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ACS Style

Iván García-Magariño; Eva Cerezo; Inmaculada Plaza; Luca Chittaro. A mobile application to report and detect 3D body emotional poses. Expert Systems with Applications 2019, 122, 207 -216.

AMA Style

Iván García-Magariño, Eva Cerezo, Inmaculada Plaza, Luca Chittaro. A mobile application to report and detect 3D body emotional poses. Expert Systems with Applications. 2019; 122 ():207-216.

Chicago/Turabian Style

Iván García-Magariño; Eva Cerezo; Inmaculada Plaza; Luca Chittaro. 2019. "A mobile application to report and detect 3D body emotional poses." Expert Systems with Applications 122, no. : 207-216.

Journal article
Published: 11 April 2019 in IEEE Transactions on Learning Technologies
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Most novice teachers and even some experienced teachers can lack appropriate tools for designing teaching strategies that ensure the quality of education. The ability of working in teams is crucial in educating professionals. The literature proves that social relations influence the performance of teams. For instance, the team cohesion is directly related with its performance. In the current work, we have developed an agent-based tool for assisting teachers in simulating their teaching strategies to estimate their influence on the group sociometrics like cohesion, coherence of reciprocal relations, dissociation and density of relations. The experiments with nine scenarios in disciplines of computer science, electronic, psychology, business, tourism and renewal energies with 239 students and six teachers including experienced and novice ones show that its underlying agent-based framework can adapt to different disciplines obtaining similar outcomes to the real ones. We learned that the tool was especially reliable in predicting the density of relations and the cohesion, being the latter one probably the most relevant due to its known relation with academic performance. In addition, we also learned that it was difficult to assess the prediction quality of the dissociation in higher education, due to the usual low amounts or absence of reciprocal rejections in the students' groups in this educational stage. The presented agent-based tool is publicly distributed as open source for facilitating other researchers in following this research line.

ACS Style

Ivan Garcia-Magarino; Inmaculada Plaza; Raul Igual; Andres S. Lombas; Hana Jamali. An Agent-Based Simulator Applied to Teaching-Learning Process to Predict Sociometric Indices in Higher Education. IEEE Transactions on Learning Technologies 2019, 13, 246 -258.

AMA Style

Ivan Garcia-Magarino, Inmaculada Plaza, Raul Igual, Andres S. Lombas, Hana Jamali. An Agent-Based Simulator Applied to Teaching-Learning Process to Predict Sociometric Indices in Higher Education. IEEE Transactions on Learning Technologies. 2019; 13 (2):246-258.

Chicago/Turabian Style

Ivan Garcia-Magarino; Inmaculada Plaza; Raul Igual; Andres S. Lombas; Hana Jamali. 2019. "An Agent-Based Simulator Applied to Teaching-Learning Process to Predict Sociometric Indices in Higher Education." IEEE Transactions on Learning Technologies 13, no. 2: 246-258.

Original article
Published: 07 January 2019 in Neural Computing and Applications
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The opacity of real-estate market involves some challenges in their agent-based simulation. While some real-estate Web sites provide the prices of a great amount of houses publicly, the prices of the rest are not available. The estimation of these prices is necessary for simulating their evolution from a complete initial set of houses. Additionally, this estimation could also be useful for other purposes such as appraising houses, letting buyers know which are the best offered prices (i.e., the lowest ones compared to the appraisals) and recommending the buyers to set an initial price. This work proposes combining dimensionality reduction methods with machine learning techniques to obtain the estimated prices. In particular, this work analyzes the use of nonnegative factorization, recursive feature elimination and feature selection with a variance threshold, as dimensionality reduction methods. It compares the application of linear regression, support vector regression, the k-nearest neighbors and a multilayer perceptron neural network, as machine learning techniques. This work has applied a tenfold cross-validation for comparing the estimations and errors and assessing the improvement over a basic estimator commonly used in the beginning of simulations. The developed software and the used dataset are freely available from a data research repository for the sake of reproducibility and the support to other researchers.

ACS Style

Iván García-Magariño; Carlos Medrano; Jorge Delgado. Estimation of missing prices in real-estate market agent-based simulations with machine learning and dimensionality reduction methods. Neural Computing and Applications 2019, 32, 2665 -2682.

AMA Style

Iván García-Magariño, Carlos Medrano, Jorge Delgado. Estimation of missing prices in real-estate market agent-based simulations with machine learning and dimensionality reduction methods. Neural Computing and Applications. 2019; 32 (7):2665-2682.

Chicago/Turabian Style

Iván García-Magariño; Carlos Medrano; Jorge Delgado. 2019. "Estimation of missing prices in real-estate market agent-based simulations with machine learning and dimensionality reduction methods." Neural Computing and Applications 32, no. 7: 2665-2682.