This page has only limited features, please log in for full access.

Unclaimed
Angélica González
University of Salamanca

Basic Info

Basic Info is private.

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Conference paper
Published: 31 July 2021 in Sustainable Smart Cities and Territories
Reads 0
Downloads 0

One of the main purposes of financial technology solutions is to reduce the infrastructure costs of financial institutions. Adopting the use of FinTech technologies implies, in addition to a reduction in costs derived from physical entities, an improvement in user satisfaction, greater flexibility in terms of data access on different devices and more transparency in financial management. As a result, this paper proposes a blockchain-based scalable platform for investment recommendations. The platform proposed in this research serves as a decision support tool. A use case is included showing the process from the initial product search to the final investment recommendation that concludes in the optimal portfolio.

ACS Style

Elena Hernández-Nieves; José A. García-Coria; Sara Rodríguez-González; Ana B. Gil-González. Distributed Decision Blockchain-Secured Support System to Enhance Stock Market Investment Process. Sustainable Smart Cities and Territories 2021, 48 -60.

AMA Style

Elena Hernández-Nieves, José A. García-Coria, Sara Rodríguez-González, Ana B. Gil-González. Distributed Decision Blockchain-Secured Support System to Enhance Stock Market Investment Process. Sustainable Smart Cities and Territories. 2021; ():48-60.

Chicago/Turabian Style

Elena Hernández-Nieves; José A. García-Coria; Sara Rodríguez-González; Ana B. Gil-González. 2021. "Distributed Decision Blockchain-Secured Support System to Enhance Stock Market Investment Process." Sustainable Smart Cities and Territories , no. : 48-60.

Journal article
Published: 07 July 2021 in Sensors
Reads 0
Downloads 0

It is estimated that we spend one-third of our lives at work. It is therefore vital to adapt traditional equipment and systems used in the working environment to the new technological paradigm so that the industry is connected and, at the same time, workers are as safe and protected as possible. Thanks to Smart Personal Protective Equipment (PPE) and wearable technologies, information about the workers and their environment can be extracted to reduce the rate of accidents and occupational illness, leading to a significant improvement. This article proposes an architecture that employs three pieces of PPE: a helmet, a bracelet and a belt, which process the collected information using artificial intelligence (AI) techniques through edge computing. The proposed system guarantees the workers’ safety and integrity through the early prediction and notification of anomalies detected in their environment. Models such as convolutional neural networks, long short-term memory, Gaussian Models were joined by interpreting the information with a graph, where different heuristics were used to weight the outputs as a whole, where finally a support vector machine weighted the votes of the models with an area under the curve of 0.81.

ACS Style

Sergio Márquez-Sánchez; Israel Campero-Jurado; Jorge Herrera-Santos; Sara Rodríguez; Juan Corchado. Intelligent Platform Based on Smart PPE for Safety in Workplaces. Sensors 2021, 21, 4652 .

AMA Style

Sergio Márquez-Sánchez, Israel Campero-Jurado, Jorge Herrera-Santos, Sara Rodríguez, Juan Corchado. Intelligent Platform Based on Smart PPE for Safety in Workplaces. Sensors. 2021; 21 (14):4652.

Chicago/Turabian Style

Sergio Márquez-Sánchez; Israel Campero-Jurado; Jorge Herrera-Santos; Sara Rodríguez; Juan Corchado. 2021. "Intelligent Platform Based on Smart PPE for Safety in Workplaces." Sensors 21, no. 14: 4652.

Journal article
Published: 08 June 2021 in Engineering Applications of Artificial Intelligence
Reads 0
Downloads 0

Following data ethics and respecting the clients’ privacy, the banking environment can use the client data that is available to them to offer personalized services to its clients. Intelligent recommender systems can support this attempt through specialized technological architectures. This article proposes the inclusion of CEBRA (CasE-Based Reasoning Application), a case-based reasoning system oriented to commercial banking, in a Fog Computing architecture coordinated by virtual agents. Throughout this article, the model of this architecture is presented and its life cycle is described, and improvements are proposed through the incorporation of several techniques in the retrieve and reuse phases, including the extraction of interests expressed by users on their social network profiles and collaborative filtering systems. A comprehensive case study has been carried out and a dataset of 60,000 cases has been generated to evaluate CEBRA. As a result, the Recommender System is presented, by including, the recommendation algorithm and a REST interface for its use. The recommendations are based on the user’s profile, previous ratings and/or additional knowledge such as the user’s contextual information. The proposal takes advantage of contextual information to support the promotion of banking and financial products, improving user satisfaction.

ACS Style

Elena Hernández-Nieves; Guillermo Hernández; Ana B. Gil-González; Sara Rodríguez-González; Juan M. Corchado. CEBRA: A CasE-Based Reasoning Application to recommend banking products. Engineering Applications of Artificial Intelligence 2021, 104, 104327 .

AMA Style

Elena Hernández-Nieves, Guillermo Hernández, Ana B. Gil-González, Sara Rodríguez-González, Juan M. Corchado. CEBRA: A CasE-Based Reasoning Application to recommend banking products. Engineering Applications of Artificial Intelligence. 2021; 104 ():104327.

Chicago/Turabian Style

Elena Hernández-Nieves; Guillermo Hernández; Ana B. Gil-González; Sara Rodríguez-González; Juan M. Corchado. 2021. "CEBRA: A CasE-Based Reasoning Application to recommend banking products." Engineering Applications of Artificial Intelligence 104, no. : 104327.

Journal article
Published: 12 May 2021 in Sensors
Reads 0
Downloads 0

Wearable technologies are becoming a profitable means of monitoring a person’s health state, such as heart rate and physical activity. The use of the smartwatch is becoming consolidated, not only as a novelty but also as a very useful tool for daily use. In addition, other devices, such as helmets or belts, are beneficial for monitoring workers and the early detection of any anomaly. They can provide valuable information, especially in work environments, where they help reduce the rate of accidents and occupational diseases, which makes them powerful Personal Protective Equipment (PPE). The constant monitoring of the worker’s health can be done in real-time, through temperature, falls, noise, impacts, or heart rate meters, activating an audible and vibrating alarm when an anomaly is detected. The gathered information is transmitted to a server in charge of collecting and processing it. In the first place, this paper provides an exhaustive review of the state of the art on works related to electronics for human activity behavior. After that, a smart multisensory bracelet, combined with other devices, developed a control platform that can improve operators’ security in the working environment. Artificial Intelligence and the Internet of Things (AIoT) bring together the information to improve safety on construction sites, power stations, power lines, etc. Real-time and historic data is used to monitor operators’ health and a hybrid system between Gaussian Mixture Model and Human Activity Classification. That is, our contribution is also founded on the use of two machine learning models, one based on unsupervised learning and the other one supervised. Where the GMM gave us a performance of 80%, 85%, 70%, and 80% for the 4 classes classified in real time, the LSTM obtained a result under the confusion matrix of 0.769, 0.892, and 0.921 for the carrying-displacing, falls, and walking-standing activities, respectively. This information was sent in real time through the platform that has been used to analyze and process the data in an alarm system.

ACS Style

Sergio Márquez-Sánchez; Israel Campero-Jurado; Daniel Robles-Camarillo; Sara Rodríguez; Juan Corchado-Rodríguez. BeSafe B2.0 Smart Multisensory Platform for Safety in Workplaces. Sensors 2021, 21, 3372 .

AMA Style

Sergio Márquez-Sánchez, Israel Campero-Jurado, Daniel Robles-Camarillo, Sara Rodríguez, Juan Corchado-Rodríguez. BeSafe B2.0 Smart Multisensory Platform for Safety in Workplaces. Sensors. 2021; 21 (10):3372.

Chicago/Turabian Style

Sergio Márquez-Sánchez; Israel Campero-Jurado; Daniel Robles-Camarillo; Sara Rodríguez; Juan Corchado-Rodríguez. 2021. "BeSafe B2.0 Smart Multisensory Platform for Safety in Workplaces." Sensors 21, no. 10: 3372.

Journal article
Published: 13 April 2021 in Sustainability
Reads 0
Downloads 0

Multi-agent systems integrate a great variety of artificial intelligence techniques from different fields, these systems have made it possible to create intelligent systems more efficiently. On the other hand, virtual reality applications are accepted as viable techniques in different areas such as visualization, simulation, design, and research. The combined use of these two technologies has led to the development of realistic and interactive applications. This work aims to do a Systematic Mapping Study (SMS) relying on the guidelines of Kitchenham and Petersen to analyze the state of the art of VR applications using multi-agent systems. Inclusion and exclusion criteria have been applied to identify relevant papers, 82 articles were selected and categorized according to the publication type, the research type, the asset type, and the purpose of the work. A complete review of the 82 selected articles was performed, based on the research questions that were established. This review made it possible to clarify the open lines of research that exist and to know where research in this field can be directed.

ACS Style

Alejandra Ospina-Bohórquez; Sara Rodríguez-González; Diego Vergara-Rodríguez. On the Synergy between Virtual Reality and Multi-Agent Systems. Sustainability 2021, 13, 4326 .

AMA Style

Alejandra Ospina-Bohórquez, Sara Rodríguez-González, Diego Vergara-Rodríguez. On the Synergy between Virtual Reality and Multi-Agent Systems. Sustainability. 2021; 13 (8):4326.

Chicago/Turabian Style

Alejandra Ospina-Bohórquez; Sara Rodríguez-González; Diego Vergara-Rodríguez. 2021. "On the Synergy between Virtual Reality and Multi-Agent Systems." Sustainability 13, no. 8: 4326.

Journal article
Published: 04 April 2021 in Electronics
Reads 0
Downloads 0

This article describes the development of a recommender system to obtain buy/sell signals from the results of technical analyses and of forecasts performed for companies operating in the Spanish continuous market. It has a modular design to facilitate the scalability of the model and the improvement of functionalities. The modules are: analysis and data mining, the forecasting system, the technical analysis module, the recommender system, and the visualization platform. The specification of each module is presented, as well as the dependencies and communication between them. Moreover, the proposal includes a visualization platform for high-level interaction between the user and the recommender system. This platform presents the conclusions that were abstracted from the resulting values.

ACS Style

Elena Hernández-Nieves; Javier Parra-Domínguez; Pablo Chamoso; Sara Rodríguez-González; Juan Corchado. A Data Mining and Analysis Platform for Investment Recommendations. Electronics 2021, 10, 859 .

AMA Style

Elena Hernández-Nieves, Javier Parra-Domínguez, Pablo Chamoso, Sara Rodríguez-González, Juan Corchado. A Data Mining and Analysis Platform for Investment Recommendations. Electronics. 2021; 10 (7):859.

Chicago/Turabian Style

Elena Hernández-Nieves; Javier Parra-Domínguez; Pablo Chamoso; Sara Rodríguez-González; Juan Corchado. 2021. "A Data Mining and Analysis Platform for Investment Recommendations." Electronics 10, no. 7: 859.

Journal article
Published: 01 January 2021 in Sensors
Reads 0
Downloads 0

This paper presents an efficient cyberphysical platform for the smart management of smart territories. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart cities is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study where the bike renting service of Paris—Vélib’ Métropole has been managed. This platform could enable smart territories to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the Internet, etc. The global intelligence of the platform could potentially coordinate its decision-making processes with intelligent nodes installed in the edge, which would use the most advanced data processing techniques.

ACS Style

Juan Corchado; Pablo Chamoso; Guillermo Hernández; Agustín Roman Gutierrez; Alberto Camacho; Alfonso González-Briones; Francisco Pinto-Santos; Enrique Goyenechea; David Garcia-Retuerta; María Alonso-Miguel; Beatriz Hernandez; Diego Villaverde; Manuel Sanchez-Verdejo; Pablo Plaza-Martínez; Manuel López-Pérez; Sergio Manzano-García; Ricardo Alonso; Roberto Casado-Vara; Javier Tejedor; Fernando de la Prieta; Sara Rodríguez-González; Javier Parra-Domínguez; Mohd Mohamad; Saber Trabelsi; Enrique Díaz-Plaza; Jose Garcia-Coria; Tan Yigitcanlar; Paulo Novais; Sigeru Omatu. Deepint.net: A Rapid Deployment Platform for Smart Territories. Sensors 2021, 21, 236 .

AMA Style

Juan Corchado, Pablo Chamoso, Guillermo Hernández, Agustín Roman Gutierrez, Alberto Camacho, Alfonso González-Briones, Francisco Pinto-Santos, Enrique Goyenechea, David Garcia-Retuerta, María Alonso-Miguel, Beatriz Hernandez, Diego Villaverde, Manuel Sanchez-Verdejo, Pablo Plaza-Martínez, Manuel López-Pérez, Sergio Manzano-García, Ricardo Alonso, Roberto Casado-Vara, Javier Tejedor, Fernando de la Prieta, Sara Rodríguez-González, Javier Parra-Domínguez, Mohd Mohamad, Saber Trabelsi, Enrique Díaz-Plaza, Jose Garcia-Coria, Tan Yigitcanlar, Paulo Novais, Sigeru Omatu. Deepint.net: A Rapid Deployment Platform for Smart Territories. Sensors. 2021; 21 (1):236.

Chicago/Turabian Style

Juan Corchado; Pablo Chamoso; Guillermo Hernández; Agustín Roman Gutierrez; Alberto Camacho; Alfonso González-Briones; Francisco Pinto-Santos; Enrique Goyenechea; David Garcia-Retuerta; María Alonso-Miguel; Beatriz Hernandez; Diego Villaverde; Manuel Sanchez-Verdejo; Pablo Plaza-Martínez; Manuel López-Pérez; Sergio Manzano-García; Ricardo Alonso; Roberto Casado-Vara; Javier Tejedor; Fernando de la Prieta; Sara Rodríguez-González; Javier Parra-Domínguez; Mohd Mohamad; Saber Trabelsi; Enrique Díaz-Plaza; Jose Garcia-Coria; Tan Yigitcanlar; Paulo Novais; Sigeru Omatu. 2021. "Deepint.net: A Rapid Deployment Platform for Smart Territories." Sensors 21, no. 1: 236.

Conference paper
Published: 04 November 2020 in Transactions on Petri Nets and Other Models of Concurrency XV
Reads 0
Downloads 0

After the paradigm shift produced by Web 2.0, the volume of opinion on the Internet has increased exponentially. The expansion of social media, whose textual content is somewhat subjective and comes loaded with opinions and assessments, can be very useful for recommending a product or brand. This information is an interesting challenge from the perspective of natural language processing, but is also an aspect of deep interest and great value not only as a marketing strategy for companies and political campaigns, but also as an indicator measuring consumer satisfaction with a product or service. In this paper, we present an opinion mining system that uses text mining techniques and natural language processing to automatically obtain useful knowledge about opinions, preferences and user trends. We studied improvements in the quality of opinion classification by using a voting system to choose the best classification of each tweet, base on of the absolute majority of the votes of the algorithms considered. In addition we developed a visualization tool that automatically combines these algorithms to assist end-user decision making. The opinion mining tool makes it possible to analyze and visualize data published on Twitter, to understand the sentiment analysis of users in relation to a product or service, by identifying the positive or negative sentiment expressed in Twitter messages.

ACS Style

Pâmella A. Aquino; Vivian F. López; María N. Moreno; María D. Muñoz; Sara Rodríguez. Opinion Mining System for Twitter Sentiment Analysis. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 465 -476.

AMA Style

Pâmella A. Aquino, Vivian F. López, María N. Moreno, María D. Muñoz, Sara Rodríguez. Opinion Mining System for Twitter Sentiment Analysis. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():465-476.

Chicago/Turabian Style

Pâmella A. Aquino; Vivian F. López; María N. Moreno; María D. Muñoz; Sara Rodríguez. 2020. "Opinion Mining System for Twitter Sentiment Analysis." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 465-476.

Journal article
Published: 01 November 2020 in Sensors
Reads 0
Downloads 0

Information and communication technologies (ICTs) have contributed to advances in Occupational Health and Safety, improving the security of workers. The use of Personal Protective Equipment (PPE) based on ICTs reduces the risk of accidents in the workplace, thanks to the capacity of the equipment to make decisions on the basis of environmental factors. Paradigms such as the Industrial Internet of Things (IIoT) and Artificial Intelligence (AI) make it possible to generate PPE models feasibly and create devices with more advanced characteristics such as monitoring, sensing the environment and risk detection between others. The working environment is monitored continuously by these models and they notify the employees and their supervisors of any anomalies and threats. This paper presents a smart helmet prototype that monitors the conditions in the workers’ environment and performs a near real-time evaluation of risks. The data collected by sensors is sent to an AI-driven platform for analysis. The training dataset consisted of 11,755 samples and 12 different scenarios. As part of this research, a comparative study of the state-of-the-art models of supervised learning is carried out. Moreover, the use of a Deep Convolutional Neural Network (ConvNet/CNN) is proposed for the detection of possible occupational risks. The data are processed to make them suitable for the CNN and the results are compared against a Static Neural Network (NN), Naive Bayes Classifier (NB) and Support Vector Machine (SVM), where the CNN had an accuracy of 92.05% in cross-validation.

ACS Style

Israel Campero-Jurado; Sergio Márquez-Sánchez; Juan Quintanar-Gómez; Sara Rodríguez; Juan Corchado. Smart Helmet 5.0 for Industrial Internet of Things Using Artificial Intelligence. Sensors 2020, 20, 6241 .

AMA Style

Israel Campero-Jurado, Sergio Márquez-Sánchez, Juan Quintanar-Gómez, Sara Rodríguez, Juan Corchado. Smart Helmet 5.0 for Industrial Internet of Things Using Artificial Intelligence. Sensors. 2020; 20 (21):6241.

Chicago/Turabian Style

Israel Campero-Jurado; Sergio Márquez-Sánchez; Juan Quintanar-Gómez; Sara Rodríguez; Juan Corchado. 2020. "Smart Helmet 5.0 for Industrial Internet of Things Using Artificial Intelligence." Sensors 20, no. 21: 6241.

Conference paper
Published: 10 September 2020 in Advances in Intelligent Systems and Computing
Reads 0
Downloads 0

Detection of video duplicates is an active field of research, motivated by the protection of intellectual property, the fight against piracy or the tracing of the origin of reused video segments. In this work, a method for the detection of duplicate videos is proposed and implemented, making use of deep learning methods and techniques typical of the field of information recovery. This method has been evaluated with a data set usually used in the field, with which high average accuracies, above 85%, have been obtained. The effect of the different layers of the convolutional neural network used by the algorithm, the aggregation mechanisms that can be used on them, and the influence of the recovery model have been studied, finding a set of parameters that optimize the overall accuracy of the system.

ACS Style

Guillermo Hernández; Sara Rodríguez; Angélica González; Juan Manuel Corchado; Javier Prieto. Video Analysis System Using Deep Learning Algorithms. Advances in Intelligent Systems and Computing 2020, 186 -199.

AMA Style

Guillermo Hernández, Sara Rodríguez, Angélica González, Juan Manuel Corchado, Javier Prieto. Video Analysis System Using Deep Learning Algorithms. Advances in Intelligent Systems and Computing. 2020; ():186-199.

Chicago/Turabian Style

Guillermo Hernández; Sara Rodríguez; Angélica González; Juan Manuel Corchado; Javier Prieto. 2020. "Video Analysis System Using Deep Learning Algorithms." Advances in Intelligent Systems and Computing , no. : 186-199.

Conference paper
Published: 15 July 2020 in Advances in Intelligent Systems and Computing
Reads 0
Downloads 0

Every company needs an organizational structure that allows it to organize and manage all its departments. For decades the most popular system of organization has been the vertical organizational model, but nowadays, thanks to the irruption of new technologies and the study of new work methodologies, other models such as the horizontal or the circular are very important. Transaction costs and the adoption of responsibilities in each of the organizational models are two key pieces in establishing the organizational model of the company. Depending on the priorities established by the entrepreneur, one organizational model or another will be chosen.

ACS Style

Javier Parra-Domínguez; Jorge A. Gonzalez; María E. Pérez-Pons; Juan Manuel Corchado; Sara Rodríguez-González. Transaction Costs and the Influence of New Technologies on Organizational Models. Advances in Intelligent Systems and Computing 2020, 144 -150.

AMA Style

Javier Parra-Domínguez, Jorge A. Gonzalez, María E. Pérez-Pons, Juan Manuel Corchado, Sara Rodríguez-González. Transaction Costs and the Influence of New Technologies on Organizational Models. Advances in Intelligent Systems and Computing. 2020; ():144-150.

Chicago/Turabian Style

Javier Parra-Domínguez; Jorge A. Gonzalez; María E. Pérez-Pons; Juan Manuel Corchado; Sara Rodríguez-González. 2020. "Transaction Costs and the Influence of New Technologies on Organizational Models." Advances in Intelligent Systems and Computing , no. : 144-150.

Conference paper
Published: 06 July 2020 in Communications in Computer and Information Science
Reads 0
Downloads 0

The industrial sector is the key driver of the society’s economic and social development. However, it is necessary for workers in this sector to have knowledge of and comply with the safety standards of the industry, designed to ensure their safety at work. Companies take different measures to reduce the rate of accidents; they use Internet of Things and Industry 4.0 technologies to detect and give notifications of anomalies detected in the work environment. This article proposes the design of an architecture using Personal Protective Equipment (PPE), where the collected information is processed by Artificial Intelligence (AI) techniques through Edge Computing and the implementation of Multi Agent System and ROS technology. The proposed system is to be embedded in the PPE worn by workers, guaranteeing their safety and integrity through the prediction and notification of anomalies detected in their environment with no need for internet give that in some cases there is internet connection is not possible.

ACS Style

Sergio Márquez Sánchez; Francisco Lecumberri; Vishwani Sati; Ashish Arora; Niloufar Shoeibi; Sara Rodríguez; Juan M. Corchado Rodríguez. Edge Computing Driven Smart Personal Protective System Deployed on NVIDIA Jetson and Integrated with ROS. Communications in Computer and Information Science 2020, 385 -393.

AMA Style

Sergio Márquez Sánchez, Francisco Lecumberri, Vishwani Sati, Ashish Arora, Niloufar Shoeibi, Sara Rodríguez, Juan M. Corchado Rodríguez. Edge Computing Driven Smart Personal Protective System Deployed on NVIDIA Jetson and Integrated with ROS. Communications in Computer and Information Science. 2020; ():385-393.

Chicago/Turabian Style

Sergio Márquez Sánchez; Francisco Lecumberri; Vishwani Sati; Ashish Arora; Niloufar Shoeibi; Sara Rodríguez; Juan M. Corchado Rodríguez. 2020. "Edge Computing Driven Smart Personal Protective System Deployed on NVIDIA Jetson and Integrated with ROS." Communications in Computer and Information Science , no. : 385-393.

Journal article
Published: 25 June 2020 in Applied Sciences
Reads 0
Downloads 0

The cloud computing paradigm has the ability to adapt to new technologies and provide consistent cloud services. These features have led to the widespread use of the paradigm, making it necessary for the underlying computer infrastructure to cope with the increased demand and the high number of end users. Platforms often use classical mathematical models for this purpose, helping assign computational resources to the services provided to the final user. Although this kind of model is valid and widespread, it can be refined through intelligent techniques. Therefore, this research presents a novel system consisting of a multi-agent system, which integrates a case-based reasoning system. The resulting system dynamically allocates resources within a cloud computing platform. This approach, which is distributed and scalable, can learn from previous experiences and produce better results in each resource allocation. A model of the system has been implemented and tested on a real cloud platform with successful results.

ACS Style

Fernando De La Prieta; Sara Rodríguez-González; Pablo Chamoso; Yves Demazeau; Juan Manuel Corchado. An Intelligent Approach to Allocating Resources within an Agent-Based Cloud Computing Platform. Applied Sciences 2020, 10, 4361 .

AMA Style

Fernando De La Prieta, Sara Rodríguez-González, Pablo Chamoso, Yves Demazeau, Juan Manuel Corchado. An Intelligent Approach to Allocating Resources within an Agent-Based Cloud Computing Platform. Applied Sciences. 2020; 10 (12):4361.

Chicago/Turabian Style

Fernando De La Prieta; Sara Rodríguez-González; Pablo Chamoso; Yves Demazeau; Juan Manuel Corchado. 2020. "An Intelligent Approach to Allocating Resources within an Agent-Based Cloud Computing Platform." Applied Sciences 10, no. 12: 4361.

Journal article
Published: 08 May 2020 in Neurocomputing
Reads 0
Downloads 0

In recent years, cities and especially urban mobility have undergone remarkable changes. Significant advances in technology have been translated into new mobility services for both goods and people. One evident change has been the transformation of traditional vehicle fleets into more open fleets, in the sense that their members can proactively decide whether or not they are part of a certain fleet and whether or not they perform certain services. Fleets of this type make the decision-making process to be highly distributed, and rule out some of the typically centralized decisions. The management and control of this type of open fleets is severely more complex and, for this reason, the availability of simulation tools that allow for their analysis can be very useful. In accordance with this, the main contribution of this work is the development of an agent-based simulation tool specifically designed for the simulation of new urban mobility models. In this way, the tool can simulate any type of fleet in different urban scenarios, including a solution of the Last Mile Delivery problem, which is also included as a proof of concept in this paper.

ACS Style

J. Palanca; A. Terrasa; S. Rodriguez; C. Carrascosa; V. Julian. An agent-based simulation framework for the study of urban delivery. Neurocomputing 2020, 423, 679 -688.

AMA Style

J. Palanca, A. Terrasa, S. Rodriguez, C. Carrascosa, V. Julian. An agent-based simulation framework for the study of urban delivery. Neurocomputing. 2020; 423 ():679-688.

Chicago/Turabian Style

J. Palanca; A. Terrasa; S. Rodriguez; C. Carrascosa; V. Julian. 2020. "An agent-based simulation framework for the study of urban delivery." Neurocomputing 423, no. : 679-688.

Journal article
Published: 03 February 2020 in International Journal of Medical Informatics
Reads 0
Downloads 0

The examination of the fundus allows to evaluate retinal the microcirculation in vivo. We assess the reliability and validity of ALTAIR software, and to evaluate its clinical relevance by the association of thickness, area and length of the retinal vessels with other measures of vascular structure and function, target organ damage and cardiovascular risk. Cross-sectional study involving a total of 250 subjects aged 62 ± 9 years, 51 % males. In a random subsample of 60 subjects (118 retinographies), we estimated the intraobserver, interobserver and interdevice intraclass correlation coefficients (ICC) of the measurements of retinal vascular thickness, area and length in 3 concentric circles. Concurrent validity was assessed with all 250 subjects (495 retinographies), analysing the relationship to age, blood pressure, target organ damage, vascular structure and function, and cardiovascular risk. Of the sample, 69 % were diagnosed with hypertension and 17 % with diabetes. Intraobserver ICC ranged from 0.640 for venous length to 0.906 for arterial area. Interobserver ICC ranged from 0.809 for arterial length to 0.916 for venous area, and interdevice ICC for arteriovenous ratio (AVR) was 0.887, thickness of arteries 0.590 and vein thickness 0.677. We found a moderate correlation between retinal vascular parameters and vascular structure and function, and target organ damage. In multiple linear regression analysis, the association with blood pressure, albumin/creatinine ratio, carotid intima-media thickness and cardiovascular risk is maintained. The ALTAIR tool has been useful for analysing the thickness, area and length of retinal vessels, with adequate reliability and a concomitant association of retinal vessel measurements with other cardiovascular parameters and cardiovascular risk. Therefore, in addition to thickness, the area and length of retinal vessels could also play a role in the prediction of cardiovascular risk.

ACS Style

Jose A. Maderuelo-Fernandez; Angel Garcia- Garciaa; Pablo Chamosob; Jose I.Recio-Rodríguezac; Sara Rodríguez- Gonzálezb; Maria C.Patino-Alonsoad; Emiliano Rodriguez- Sanchezae; Juan M. Corchado-Rodríguez; Manuel A.Gómez-Marcosae; Luis Garcia- Ortizaf. Automatic image analyser to assess retinal vessel calibre (ALTAIR). A new tool to evaluate the thickness, area and length of the vessels of the retina. International Journal of Medical Informatics 2020, 136, 104090 .

AMA Style

Jose A. Maderuelo-Fernandez, Angel Garcia- Garciaa, Pablo Chamosob, Jose I.Recio-Rodríguezac, Sara Rodríguez- Gonzálezb, Maria C.Patino-Alonsoad, Emiliano Rodriguez- Sanchezae, Juan M. Corchado-Rodríguez, Manuel A.Gómez-Marcosae, Luis Garcia- Ortizaf. Automatic image analyser to assess retinal vessel calibre (ALTAIR). A new tool to evaluate the thickness, area and length of the vessels of the retina. International Journal of Medical Informatics. 2020; 136 ():104090.

Chicago/Turabian Style

Jose A. Maderuelo-Fernandez; Angel Garcia- Garciaa; Pablo Chamosob; Jose I.Recio-Rodríguezac; Sara Rodríguez- Gonzálezb; Maria C.Patino-Alonsoad; Emiliano Rodriguez- Sanchezae; Juan M. Corchado-Rodríguez; Manuel A.Gómez-Marcosae; Luis Garcia- Ortizaf. 2020. "Automatic image analyser to assess retinal vessel calibre (ALTAIR). A new tool to evaluate the thickness, area and length of the vessels of the retina." International Journal of Medical Informatics 136, no. : 104090.

Review
Published: 28 December 2019 in Electronics
Reads 0
Downloads 0

Context: Smart Energy is a disruptive concept that has led to the emergence of new energy policies, technology projects, and business models. The development of those models is driven by world capitals, companies, and universities. Their purpose is to make the electric power system more efficient through distributed energy generation/storage, smart meter installation, or reduction of consumption/implementation costs. This work approaches Smart Energy as a paradigm that is concerned with systemic strategies involving the implementation of innovative technological developments in energy systems. However, many of the challenges encountered under this paradigm are yet to be overcome, such as the effective integration of solutions within Smart Energy systems. Edge Computing is included in this new technology group. Objective: To investigate developments that involve the use of Edge Computing and that provide solutions to Smart Energy problems. The research work will be developed using the methodology of systematic mapping of literature, following the guidelines established by Kitchenham and Petersen that facilitate the identification of studies published on the subject. Results: Inclusion and exclusion criteria have been applied to identify the relevant articles. We selected 80 papers that were classified according to the type of publication (journal, conferences, or book chapter), type of research (conceptual, experience, or validation), type of activity (implement, validate, analyze) and asset (architecture, framework, method, or models). Conclusion: A complete review has been conducted of the 80 articles that were closely related to the questions posed in this research. To reach the goal of building Edge Computing architectures for Smart Energy environments, several lines of research have been defined. In the future, such architectures will overcome current problems, becoming highly energy-efficient, cost-effective, and capacitated to process and respond in real-time.

ACS Style

Inés Sittón-Candanedo; Ricardo S. Alonso; Óscar García; Ana B. Gil; Sara Rodríguez-González. A Review on Edge Computing in Smart Energy by means of a Systematic Mapping Study. Electronics 2019, 9, 48 .

AMA Style

Inés Sittón-Candanedo, Ricardo S. Alonso, Óscar García, Ana B. Gil, Sara Rodríguez-González. A Review on Edge Computing in Smart Energy by means of a Systematic Mapping Study. Electronics. 2019; 9 (1):48.

Chicago/Turabian Style

Inés Sittón-Candanedo; Ricardo S. Alonso; Óscar García; Ana B. Gil; Sara Rodríguez-González. 2019. "A Review on Edge Computing in Smart Energy by means of a Systematic Mapping Study." Electronics 9, no. 1: 48.

Journal article
Published: 17 October 2019 in Applied Sciences
Reads 0
Downloads 0

The education sector is a major generator, consumer, and depositary of educational content. Thanks to technological advances, today’s educators and learners have ubiquitous and on-demand access to information. Technology has made it possible for us to communicate and share information effortlessly from anywhere in the world. However, the availability of vast amounts of heterogeneous educational content will not be useful unless we search, retrieve and integrate it, creating interoperable educational environments. The current challenges to integrating educational content arise from its distribution over several repositories. This research proposes AIREH (architecture for intelligent retrieval of educational content from heterogeneous environments), for the retrieval of digital content through agent-based virtual organizations. This flexible architecture facilitates the search for and integration of heterogeneous content through an information retrieval model that involves both case-based reasoning and federated search. Moreover, AIREH is based on an adaptive organization model for distributed planning, thanks to which, it manages open systems flexibly, dynamically, and effectively. The conducted case study gives very promising results and demonstrates the advantages of using agent-based virtual organizations in the retrieval of labeled digital content. The proposed model is flexible, customizable, comprehensive and efficient.

ACS Style

Ana B. Gil; Fernando De La Prieta; Sara Rodríguez; Juan M. Corchado. Smart System for the Retrieval of Digital Educational Content. Applied Sciences 2019, 9, 4400 .

AMA Style

Ana B. Gil, Fernando De La Prieta, Sara Rodríguez, Juan M. Corchado. Smart System for the Retrieval of Digital Educational Content. Applied Sciences. 2019; 9 (20):4400.

Chicago/Turabian Style

Ana B. Gil; Fernando De La Prieta; Sara Rodríguez; Juan M. Corchado. 2019. "Smart System for the Retrieval of Digital Educational Content." Applied Sciences 9, no. 20: 4400.

Journal article
Published: 27 August 2019 in Expert Systems with Applications
Reads 0
Downloads 0

In this article, a novel Fog Computing solution is proposed, developed in the area of fintech. It integrates predictive systems in the process of delivery of personalized customer services for the recommendation of the products of a banking entity. The motivation behind this research is to improve aspects of customer support services, especially, achieve greater security, increased transparency and agility of processes as well as reduce entity management costs. The presented architecture includes fog nodes where data are processed by light intelligent agents allowing for the implementation of contextual recommendation systems together with the configuration of a Case Based Reasoning in the Cloud layer to improve the efficiency of the whole system over the time. The recommendation system is the cornerstone of architecture operating on banking products, such as mortgages, loans, retirement plans, etc., and it is developed by a hybrid method of recommendation: collaborative filtering combined with content-based filtering. The article analyzes the presented architecture while performing a verification and simulation of the data in the context of commercial banking. For this purpose, it shows the use of the proposed system of recommendations that represent the different communication channels as well as the possible devices. The proposed architecture offers the opportunity to improve the customer service in the bank’s physical channels and at the same time generate technological support to improve the resolution capacity of office managers, allowing employees to adopt a more versatile and flexible role. It also allows the evolution of the banking services model in offices while the processes that support it to follow a one-stop shop approach.

ACS Style

Elena Hernández-Nieves; Guillermo Hernández; Ana-Belén Gil-González; Sara Rodríguez-González; Juan M. Corchado. Fog computing architecture for personalized recommendation of banking products. Expert Systems with Applications 2019, 140, 112900 .

AMA Style

Elena Hernández-Nieves, Guillermo Hernández, Ana-Belén Gil-González, Sara Rodríguez-González, Juan M. Corchado. Fog computing architecture for personalized recommendation of banking products. Expert Systems with Applications. 2019; 140 ():112900.

Chicago/Turabian Style

Elena Hernández-Nieves; Guillermo Hernández; Ana-Belén Gil-González; Sara Rodríguez-González; Juan M. Corchado. 2019. "Fog computing architecture for personalized recommendation of banking products." Expert Systems with Applications 140, no. : 112900.

Journal article
Published: 31 July 2019 in Sensors
Reads 0
Downloads 0

The Internet of Things (IoT) has become one of the most widely research paradigms, having received much attention from the research community in the last few years. IoT is the paradigm that creates an internet-connected world, where all the everyday objects capture data from our environment and adapt it to our needs. However, the implementation of IoT is a challenging task and all the implementation scenarios require the use of different technologies and the emergence of new ones, such as Edge Computing (EC). EC allows for more secure and efficient data processing in real time, achieving better performance and results. Energy efficiency is one of the most interesting IoT scenarios. In this scenario sensors, actuators and smart devices interact to generate a large volume of data associated with energy consumption. This work proposes the use of an Edge-IoT platform and a Social Computing framework to build a system aimed to smart energy efficiency in a public building scenario. The system has been evaluated in a public building and the results make evident the notable benefits that come from applying Edge Computing to both energy efficiency scenarios and the framework itself. Those benefits included reduced data transfer from the IoT-Edge to the Cloud and reduced Cloud, computing and network resource costs.

ACS Style

Inés Sittón-Candanedo; Ricardo S. Alonso; Óscar García; Lilia Muñoz; Sara Rodríguez-González. Edge Computing, IoT and Social Computing in Smart Energy Scenarios. Sensors 2019, 19, 3353 .

AMA Style

Inés Sittón-Candanedo, Ricardo S. Alonso, Óscar García, Lilia Muñoz, Sara Rodríguez-González. Edge Computing, IoT and Social Computing in Smart Energy Scenarios. Sensors. 2019; 19 (15):3353.

Chicago/Turabian Style

Inés Sittón-Candanedo; Ricardo S. Alonso; Óscar García; Lilia Muñoz; Sara Rodríguez-González. 2019. "Edge Computing, IoT and Social Computing in Smart Energy Scenarios." Sensors 19, no. 15: 3353.

Journal article
Published: 17 July 2019 in Processes
Reads 0
Downloads 0

The difficulty in precisely detecting and locating an ear within an image is the first step to tackle in an ear-based biometric recognition system, a challenge which increases in difficulty when working with variable photographic conditions. This is in part due to the irregular shapes of human ears, but also because of variable lighting conditions and the ever changing profile shape of an ear’s projection when photographed. An ear detection system involving multiple convolutional neural networks and a detection grouping algorithm is proposed to identify the presence and location of an ear in a given input image. The proposed method matches the performance of other methods when analyzed against clean and purpose-shot photographs, reaching an accuracy of upwards of 98%, but clearly outperforms them with a rate of over 86% when the system is subjected to non-cooperative natural images where the subject appears in challenging orientations and photographic conditions.

ACS Style

William Raveane; Pedro Luis Galdámez; María Angélica González Arrieta. Ear Detection and Localization with Convolutional Neural Networks in Natural Images and Videos. Processes 2019, 7, 457 .

AMA Style

William Raveane, Pedro Luis Galdámez, María Angélica González Arrieta. Ear Detection and Localization with Convolutional Neural Networks in Natural Images and Videos. Processes. 2019; 7 (7):457.

Chicago/Turabian Style

William Raveane; Pedro Luis Galdámez; María Angélica González Arrieta. 2019. "Ear Detection and Localization with Convolutional Neural Networks in Natural Images and Videos." Processes 7, no. 7: 457.