Mario Muñoz-Organero | Universidad Carlos III de Madrid (original) (raw)

Publications by Mario Muñoz-Organero

Journal of Systems and Software, 2022

Selenium WebDriver is a library that allows controlling web browsers (e.g., Chrome, Firefox, etc.... more Selenium WebDriver is a library that allows controlling web browsers (e.g., Chrome, Firefox, etc.) programmatically. It provides a cross-browser programming interface in several languages used primarily to implement end-to-end tests for web applications. JUnit is a popular unit testing framework for Java. Its latest version (i.e., JUnit 5) provides a programming and extension model called Jupiter. This paper presents Selenium-Jupiter, an open-source JUnit 5 extension for Selenium WebDriver. Selenium-Jupiter aims to ease the development of Selenium WebDriver tests thanks to an automated driver management process implemented in conjunction with the Jupiter parameter resolution mechanism. Moreover, Selenium-Jupiter provides seamless integration with Docker, allowing the use of different web browsers in Docker containers out of the box. This feature enables cross-browser testing, load testing, and troubleshooting (e.g., configurable session recordings). This paper presents an example case in which Selenium-Jupiter is used to evaluate the performance of video conferencing systems based on WebRTC. This example case shows that Selenium-Jupiter can build and maintain the required infrastructure for complex tests effortlessly.

EMPIRICAL SOFTWARE ENGINEERING, 2021

Selenium WebDriver is a framework used to control web browsers automatically. It provides a cross... more Selenium WebDriver is a framework used to control web browsers automatically. It provides a cross-browser Application Programming Interface (API) for different languages (e.g., Java, Python, or JavaScript) that allows automatic navigation, user impersonation, and verification of web applications. Internally, Selenium WebDriver makes use of the native automation support of each browser. Hence, a platform-dependent binary file (the so-called driver) must be placed between the Selenium WebDriver script and the browser to support this native communication. The management (i.e., download, setup, and maintenance) of these drivers is cumbersome for practitioners. This paper provides a complete methodology to automate this management process. Particularly, we present WebDriver-Manager, the reference tool implementing this methodology. WebDriverManager provides different execution methods: as a Java dependency, as a Command-Line Interface (CLI) tool, as a server, as a Docker container, and as a Java agent. To provide empirical validation of the proposed approach, we surveyed the Web-DriverManager users. The aim of this study is twofold. First, we assessed the extent to which WebDriverManager is adopted and used. Second, we evaluated the WebDriverManager API following Clarke's usability dimensions. A total of 148 participants worldwide completed this survey in 2020. The results show a remarkable assessment of the automation capabilities and API usability of Web-DriverManager by Java users, but a scarce adoption for other languages.

IEEE Access, 2019

Wearable sensors provide a user-friendly and non-intrusive mechanism to extract user-relateddata ... more Wearable sensors provide a user-friendly and non-intrusive mechanism to extract user-relateddata that paves the way to the development of personalized applications. Within
those applications, humanactivity
recognition (HAR) plays an important role in the characterization of the user
context. Outlierdetection
methods focus on finding anomalous data samples that are likely to have been generated by adifferent mechanism. This paper combines outlier detection and HAR by introducing a novel algorithmthat is able both to
detect information from secondary activities inside the main activity and to extract datasegments of a particular sub-activity from a different activity. Several machine learning algorithms havebeen previously
used in the area of HAR based on the analysis of the time sequences generated by wearablesensors. Deep recurrent neural networks (DRNNs) have proven to be optimally adapted to the sequentialcharacteristics of
wearable sensor data in previous studies. A DRNN-based algorithm is proposed in thispaper for outlier detection in HAR. The results are validated both for intra- and inter-subject cases and bothfor outlier
detection and sub-activity recognition using two different datasets. A first
dataset comprising 4 major activities (walking, running, climbing up, and down) from 15 users is used to train and validate the proposal. Intra-subject outlier detection is able to detect all major outliers in the walking activity in thisdataset, while inter-subject outlier detection only fails for one participant executing the activity in a peculiarway.
Sub-activity detection has been validated by finding out and extracting walking segments present inthe other three activities in this dataset. A second dataset using four different users, a different setting anddifferent
sensor devices is used to assess the generalization of results.

IEEE Sensors, 2019

Human Activity Recognition (HAR) provides the context for many user-centered personal recommender... more Human Activity Recognition (HAR) provides the context for many user-centered personal recommender systems in areas such as healthcare, sports, lifelong learning or home automation. Based on different types of sensors (either camera based, environmental sensors or wearable and mobile sensors) user related data provides the basis to extract movement related features from which the activity that the user is performing can be assessed. Among the different types of sensors, wearable sensors provide a user convenient, non-intrusive, always available alternative that has gained special attention for HAR. Wearable sensors will be a relevant part of the Internet of Things. This paper presents a novel mechanism to detect which particular activity a user is performing based on the data from a single tri-axial accelerometer. A Convolutional Neural Network is used in order to automatically extract the most relevant features to characterize acceleration patterns with interactivity discrimination capacity. The user anchored coordinate system generating the data from the accelerometer sensor is transformed into a georeferenced coordinate system in order to estimate the horizontal and vertical acceleration components. A sliding window with 50% overlap is used to extract 5 seconds of acceleration data from which a square horizontal-vertical acceleration image is computed. Both monochrome and colored images are generated either by adding the influence of the time evolution of the acceleration series or not in the generated image. The results for both p-fold cross-validation and leave on out approaches are presented using a public dataset. The results outperform by around 8% of those obtained by the authors of the dataset in the case of using a p-fold cross-validation.

IEEE Access, 2019

Recommender systems have been based on context and content, and now the technological challenge o... more Recommender systems have been based on context and content, and now the technological challenge of making personalized recommendations based on the user emotional state arises through physiological signals that are obtained from devices or sensors. This paper applies the deep learning approach using a deep convolutional neural network on a dataset of physiological signals (electrocardiogram and galvanic skin response), in this case, the AMIGOS dataset. The detection of emotions is done by correlating these physiological signals with the data of arousal and valence of this dataset, to classify the affective state of a person. In addition, an application for emotion recognition based on classic machine learning algorithms is proposed to extract the features of physiological signals in the domain of time, frequency, and non-linear. This application uses a convolutional neural network for the automatic feature extraction of the physiological signals, and through fully connected network layers, the emotion prediction is made. The experimental results on the AMIGOS dataset show that the method proposed in this paper achieves a better precision of the classification of the emotional states, in comparison with the originally obtained by the authors of this dataset.

COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2018

Automatic detection of traffic lights, street crossings and urban roundabouts combining outlier d... more Automatic detection of traffic lights, street crossings and urban roundabouts combining outlier detection and deep learning classification techniques based on GPS traces while driving.

Revista Iberoamericana De Tecnologías Del Aprendizaje, 2006

Audio Response Systems (ARS) are currently used as a mechanism to enhance face to face education ... more Audio Response Systems (ARS) are currently used as a mechanism to enhance face to face education in classrooms and the results are promising. These systems could also improve certain aspects in e-learning if designed appropriately. This paper presents a design and implementation of an ARS adapted to both face to face education and distance learning scenarios. We also show how

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013

ABSTRACT MOOCs have been a disruptive educational trend in the last months. Some MOOCs just repli... more ABSTRACT MOOCs have been a disruptive educational trend in the last months. Some MOOCs just replicate traditional teaching pedagogies, adding multimedia elements like video lectures. Others go beyond, trying to engage the massive number of participants by promoting discussions and relying on their contributions to the course. MOOC platforms usually provide some built-in social tools for this purpose, although instructors or participants may suggest others to foster discussions and crowdsourcing. This paper analyses the impact of two built-in (Q&A and forum) and three external social tools (Facebook, Twitter and MentorMob) in a MOOC on educational technologies. Most of the participants agreed on the importance of social tools to be in touch with their partners and share information related to the course, the forum being the one preferred. Furthermore, the lessons learned from the enactment of this MOOC employing social tools are summarized so that others may benefit from them.

Learning in the Synergy of Multiple Disciplines, Proceedings, 2009

Abstract. This paper presents a system that connects students with complementary profiles, so the... more Abstract. This paper presents a system that connects students with complementary profiles, so they can interchange knowledge and help each other. The profile of the students is built by a modified intelligent tutoring system. Every time the user profile is updated, a gateway updates the profile stored in the user's personal terminal using a web-service based communication mechanism. The terminals (eg mobile phones) are able to find and communicate between themselves using Bluetooth. When they find two complementary ...

2010 10th IEEE International Conference on Advanced Learning Technologies, 2010

Pedro J. Muñoz-Merino, Carlos Delgado Kloos, Mario Muñoz-Organero Department of Telematic Enginee... more Pedro J. Muñoz-Merino, Carlos Delgado Kloos, Mario Muñoz-Organero Department of Telematic Engineering Carlos III University of Madrid Leganés, Madrid, Spain {pedmume, cdk, munozm}@it.uc3m.es ... Martin Wolpers, Martin Friedrich Information Contextualization ...

Proceedings of the 6th International Conference on Semantic Systems - I-SEMANTICS '10, 2010

Abstract In this paper, we introduce a graph representation of the main elements of our defined R... more Abstract In this paper, we introduce a graph representation of the main elements of our defined RDF binding for contextualized attention metadata (CAM). In addition, we give a brief overview of two applications that we have implemented using the CAM semantic web format. The Zeitgeist and a" find similar users" applications illustrate our approach.

Lecture Notes in Computer Science, 2006

There is a strong consensus about the need for IPsec, although its use is not widespread for end-... more There is a strong consensus about the need for IPsec, although its use is not widespread for end-to-end communications. One of the main reasons for this is the difficulty for authenticating two end-hosts that do not share a secret or do not rely on a common Certification Authority. In this paper we propose a modification to IKE to use reverse DNS and DNSSEC (named DNSSEC-to-IKE) to provide end-to-end authentication to Internet hosts that do not share any secret, without requiring the deployment of a new infrastructure. We perform a comparative analysis in terms of requirements, provided security and performance with state-of-the-art IKE authentication methods and with a recent proposal for IPv6 based on CGA. We conclude that DNSSEC-to-IKE enables the use of IPsec in a broad range of scenarios in which it was not applicable, at the price of offering slightly less security and incurring in higher performance costs.

Proceedings of the 2012 IEEE Global Engineering Education Conference (EDUCON), 2012

Abstract In this paper, an overview is given about the research carried out in the area of mobile... more Abstract In this paper, an overview is given about the research carried out in the area of mobile teaching and learning by Universidad Carlos III de Madrid, a member of the eMadrid Excellence Network. Mobile learning is raising growing expectations and is considered by some authors the next disruptive revolution in education. Cognitive and pedagogical theories supporting this prospect are reviewed. How these theories can be translated into meaningful educational practices is analysed by exploring ways of usage of mobile ...

Advances in Intelligent Systems and Computing, 2013

2012 IEEE International Conference on Consumer Electronics (ICCE), 2012

There are lots of devices and services inside a home which have to be managed. OSGi platforms all... more There are lots of devices and services inside a home which have to be managed. OSGi platforms alleviate this management by installing some services on a gateway located at home. A service provider might manage those services as part of a package of services. In general, OSGi platforms are connected to centralized repositories facilitating the maintenance by service providers. However, when various service providers work on a given gateway the number of services and components installed in it increases. This sometimes leads to inconsistencies as duplicate components that might cause performance problems or service interruptions. This paper presents a system for analyzing and automatically optimizing the components deployed on a OSGi home gateway.

Proceedings of the 5th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, 2008

... Authors, Gustavo Ramírez-González, Universidad Carlos III de Madrid, Spain. Mario Muñoz-Organ... more ... Authors, Gustavo Ramírez-González, Universidad Carlos III de Madrid, Spain. Mario Muñoz-Organero, Universidad Carlos III de Madrid, Spain. ... Collaborative Colleagues: GustavoRamírez-González: colleagues. Mario Muñoz-Organero: colleagues. ...

IEEE Transactions on Intelligent Transportation Systems, 2000

ABSTRACT This paper implements and validates an expert system that, based on the detection or pre... more ABSTRACT This paper implements and validates an expert system that, based on the detection or previous knowledge of certain types of traffic signals, proposes a method to reduce fuel consumption by calculating optimal deceleration patterns, minimizing the use of braking. The expert system uses a mobile device's embedded camera to monitor the environment and to recognize certain types of static traffic signals that force or can force a vehicle to stop. The system uses an adaptation of the algorithm proposed by Viola and Jones for the recognition of faces in real time, adapted to the detection of traffic signals. Detected signals are also incorporated into a central database for future use. When the vehicle approaches an upcoming traffic signal, the algorithm estimates the distance required to stop the vehicle without using the brakes, taking into account the rolling resistance coefficient and the road slope angle. Appropriate advice and feedback are provided to the driver to release the accelerator pedal. The expert system is implemented on Android mobile devices and has been validated using a data set of 180 tests with five different models of vehicles and nine different drivers. The main contribution of this paper is the proposal of an assistant that uses information from the environment and from the vehicle to calculate optimal deceleration patterns when approaching traffic signals that force or may force the vehicle to stop. In addition, the proposed solution does not require the installation of infrastructure on the road, and it can be installed into any vehicle.

Applied Mathematics and Computation, 2013

a b s t r a c t This paper examined the spectral properties of quadruple symmetric real functions... more a b s t r a c t This paper examined the spectral properties of quadruple symmetric real functions. Theorem is formulated, under which the complex spectra of such symmetric functions are conjugated. The properties of the trigonometric functions are used in the proof of the theorem. Numerical results are presented for illustrating of the proven theorem. (P. Philipoff), aii2010@abv.bg (A. Ivanov), munozm@it.uc3m.es (M. Muñoz), galerida@abv.bg (G. Raikova), tatur@i-proc.com (M. Tatur), bolter@abv.bg (P. Michaylov).

The success or failure of e-learning courses depends not only on the design and quality of the le... more The success or failure of e-learning courses depends not only on the design and quality of the learning materials but on the ability to motivate students to study them. Motivational factors are of the uppermost importance in e-learning courses since the motivational impact of the student-teacher proximity obtained in faceto-face education is normally not achievable. This paper makes an analysis about how to make use of some of the tools available in e-learning systems to try to motivate students. The paper makes a general review of the available tools and takes a special interest in forums and assessments. The results are validated based on the experience obtained from the teaching of the subject "Internet Society". This subject is offered to the students of all the six public Universities in Madrid (Spain) using a Moodle based e-learning platform. The experience has studied the behaviour of 60 students and their reactions to several motivational stimuli based on forum participation and assessments.

Journal of Systems and Software, 2022

Selenium WebDriver is a library that allows controlling web browsers (e.g., Chrome, Firefox, etc.... more Selenium WebDriver is a library that allows controlling web browsers (e.g., Chrome, Firefox, etc.) programmatically. It provides a cross-browser programming interface in several languages used primarily to implement end-to-end tests for web applications. JUnit is a popular unit testing framework for Java. Its latest version (i.e., JUnit 5) provides a programming and extension model called Jupiter. This paper presents Selenium-Jupiter, an open-source JUnit 5 extension for Selenium WebDriver. Selenium-Jupiter aims to ease the development of Selenium WebDriver tests thanks to an automated driver management process implemented in conjunction with the Jupiter parameter resolution mechanism. Moreover, Selenium-Jupiter provides seamless integration with Docker, allowing the use of different web browsers in Docker containers out of the box. This feature enables cross-browser testing, load testing, and troubleshooting (e.g., configurable session recordings). This paper presents an example case in which Selenium-Jupiter is used to evaluate the performance of video conferencing systems based on WebRTC. This example case shows that Selenium-Jupiter can build and maintain the required infrastructure for complex tests effortlessly.

EMPIRICAL SOFTWARE ENGINEERING, 2021

Selenium WebDriver is a framework used to control web browsers automatically. It provides a cross... more Selenium WebDriver is a framework used to control web browsers automatically. It provides a cross-browser Application Programming Interface (API) for different languages (e.g., Java, Python, or JavaScript) that allows automatic navigation, user impersonation, and verification of web applications. Internally, Selenium WebDriver makes use of the native automation support of each browser. Hence, a platform-dependent binary file (the so-called driver) must be placed between the Selenium WebDriver script and the browser to support this native communication. The management (i.e., download, setup, and maintenance) of these drivers is cumbersome for practitioners. This paper provides a complete methodology to automate this management process. Particularly, we present WebDriver-Manager, the reference tool implementing this methodology. WebDriverManager provides different execution methods: as a Java dependency, as a Command-Line Interface (CLI) tool, as a server, as a Docker container, and as a Java agent. To provide empirical validation of the proposed approach, we surveyed the Web-DriverManager users. The aim of this study is twofold. First, we assessed the extent to which WebDriverManager is adopted and used. Second, we evaluated the WebDriverManager API following Clarke's usability dimensions. A total of 148 participants worldwide completed this survey in 2020. The results show a remarkable assessment of the automation capabilities and API usability of Web-DriverManager by Java users, but a scarce adoption for other languages.

IEEE Access, 2019

Wearable sensors provide a user-friendly and non-intrusive mechanism to extract user-relateddata ... more Wearable sensors provide a user-friendly and non-intrusive mechanism to extract user-relateddata that paves the way to the development of personalized applications. Within
those applications, humanactivity
recognition (HAR) plays an important role in the characterization of the user
context. Outlierdetection
methods focus on finding anomalous data samples that are likely to have been generated by adifferent mechanism. This paper combines outlier detection and HAR by introducing a novel algorithmthat is able both to
detect information from secondary activities inside the main activity and to extract datasegments of a particular sub-activity from a different activity. Several machine learning algorithms havebeen previously
used in the area of HAR based on the analysis of the time sequences generated by wearablesensors. Deep recurrent neural networks (DRNNs) have proven to be optimally adapted to the sequentialcharacteristics of
wearable sensor data in previous studies. A DRNN-based algorithm is proposed in thispaper for outlier detection in HAR. The results are validated both for intra- and inter-subject cases and bothfor outlier
detection and sub-activity recognition using two different datasets. A first
dataset comprising 4 major activities (walking, running, climbing up, and down) from 15 users is used to train and validate the proposal. Intra-subject outlier detection is able to detect all major outliers in the walking activity in thisdataset, while inter-subject outlier detection only fails for one participant executing the activity in a peculiarway.
Sub-activity detection has been validated by finding out and extracting walking segments present inthe other three activities in this dataset. A second dataset using four different users, a different setting anddifferent
sensor devices is used to assess the generalization of results.

IEEE Sensors, 2019

Human Activity Recognition (HAR) provides the context for many user-centered personal recommender... more Human Activity Recognition (HAR) provides the context for many user-centered personal recommender systems in areas such as healthcare, sports, lifelong learning or home automation. Based on different types of sensors (either camera based, environmental sensors or wearable and mobile sensors) user related data provides the basis to extract movement related features from which the activity that the user is performing can be assessed. Among the different types of sensors, wearable sensors provide a user convenient, non-intrusive, always available alternative that has gained special attention for HAR. Wearable sensors will be a relevant part of the Internet of Things. This paper presents a novel mechanism to detect which particular activity a user is performing based on the data from a single tri-axial accelerometer. A Convolutional Neural Network is used in order to automatically extract the most relevant features to characterize acceleration patterns with interactivity discrimination capacity. The user anchored coordinate system generating the data from the accelerometer sensor is transformed into a georeferenced coordinate system in order to estimate the horizontal and vertical acceleration components. A sliding window with 50% overlap is used to extract 5 seconds of acceleration data from which a square horizontal-vertical acceleration image is computed. Both monochrome and colored images are generated either by adding the influence of the time evolution of the acceleration series or not in the generated image. The results for both p-fold cross-validation and leave on out approaches are presented using a public dataset. The results outperform by around 8% of those obtained by the authors of the dataset in the case of using a p-fold cross-validation.

IEEE Access, 2019

Recommender systems have been based on context and content, and now the technological challenge o... more Recommender systems have been based on context and content, and now the technological challenge of making personalized recommendations based on the user emotional state arises through physiological signals that are obtained from devices or sensors. This paper applies the deep learning approach using a deep convolutional neural network on a dataset of physiological signals (electrocardiogram and galvanic skin response), in this case, the AMIGOS dataset. The detection of emotions is done by correlating these physiological signals with the data of arousal and valence of this dataset, to classify the affective state of a person. In addition, an application for emotion recognition based on classic machine learning algorithms is proposed to extract the features of physiological signals in the domain of time, frequency, and non-linear. This application uses a convolutional neural network for the automatic feature extraction of the physiological signals, and through fully connected network layers, the emotion prediction is made. The experimental results on the AMIGOS dataset show that the method proposed in this paper achieves a better precision of the classification of the emotional states, in comparison with the originally obtained by the authors of this dataset.

COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2018

Automatic detection of traffic lights, street crossings and urban roundabouts combining outlier d... more Automatic detection of traffic lights, street crossings and urban roundabouts combining outlier detection and deep learning classification techniques based on GPS traces while driving.

Revista Iberoamericana De Tecnologías Del Aprendizaje, 2006

Audio Response Systems (ARS) are currently used as a mechanism to enhance face to face education ... more Audio Response Systems (ARS) are currently used as a mechanism to enhance face to face education in classrooms and the results are promising. These systems could also improve certain aspects in e-learning if designed appropriately. This paper presents a design and implementation of an ARS adapted to both face to face education and distance learning scenarios. We also show how

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013

ABSTRACT MOOCs have been a disruptive educational trend in the last months. Some MOOCs just repli... more ABSTRACT MOOCs have been a disruptive educational trend in the last months. Some MOOCs just replicate traditional teaching pedagogies, adding multimedia elements like video lectures. Others go beyond, trying to engage the massive number of participants by promoting discussions and relying on their contributions to the course. MOOC platforms usually provide some built-in social tools for this purpose, although instructors or participants may suggest others to foster discussions and crowdsourcing. This paper analyses the impact of two built-in (Q&A and forum) and three external social tools (Facebook, Twitter and MentorMob) in a MOOC on educational technologies. Most of the participants agreed on the importance of social tools to be in touch with their partners and share information related to the course, the forum being the one preferred. Furthermore, the lessons learned from the enactment of this MOOC employing social tools are summarized so that others may benefit from them.

Learning in the Synergy of Multiple Disciplines, Proceedings, 2009

Abstract. This paper presents a system that connects students with complementary profiles, so the... more Abstract. This paper presents a system that connects students with complementary profiles, so they can interchange knowledge and help each other. The profile of the students is built by a modified intelligent tutoring system. Every time the user profile is updated, a gateway updates the profile stored in the user's personal terminal using a web-service based communication mechanism. The terminals (eg mobile phones) are able to find and communicate between themselves using Bluetooth. When they find two complementary ...

2010 10th IEEE International Conference on Advanced Learning Technologies, 2010

Pedro J. Muñoz-Merino, Carlos Delgado Kloos, Mario Muñoz-Organero Department of Telematic Enginee... more Pedro J. Muñoz-Merino, Carlos Delgado Kloos, Mario Muñoz-Organero Department of Telematic Engineering Carlos III University of Madrid Leganés, Madrid, Spain {pedmume, cdk, munozm}@it.uc3m.es ... Martin Wolpers, Martin Friedrich Information Contextualization ...

Proceedings of the 6th International Conference on Semantic Systems - I-SEMANTICS '10, 2010

Abstract In this paper, we introduce a graph representation of the main elements of our defined R... more Abstract In this paper, we introduce a graph representation of the main elements of our defined RDF binding for contextualized attention metadata (CAM). In addition, we give a brief overview of two applications that we have implemented using the CAM semantic web format. The Zeitgeist and a" find similar users" applications illustrate our approach.

Lecture Notes in Computer Science, 2006

There is a strong consensus about the need for IPsec, although its use is not widespread for end-... more There is a strong consensus about the need for IPsec, although its use is not widespread for end-to-end communications. One of the main reasons for this is the difficulty for authenticating two end-hosts that do not share a secret or do not rely on a common Certification Authority. In this paper we propose a modification to IKE to use reverse DNS and DNSSEC (named DNSSEC-to-IKE) to provide end-to-end authentication to Internet hosts that do not share any secret, without requiring the deployment of a new infrastructure. We perform a comparative analysis in terms of requirements, provided security and performance with state-of-the-art IKE authentication methods and with a recent proposal for IPv6 based on CGA. We conclude that DNSSEC-to-IKE enables the use of IPsec in a broad range of scenarios in which it was not applicable, at the price of offering slightly less security and incurring in higher performance costs.

Proceedings of the 2012 IEEE Global Engineering Education Conference (EDUCON), 2012

Abstract In this paper, an overview is given about the research carried out in the area of mobile... more Abstract In this paper, an overview is given about the research carried out in the area of mobile teaching and learning by Universidad Carlos III de Madrid, a member of the eMadrid Excellence Network. Mobile learning is raising growing expectations and is considered by some authors the next disruptive revolution in education. Cognitive and pedagogical theories supporting this prospect are reviewed. How these theories can be translated into meaningful educational practices is analysed by exploring ways of usage of mobile ...

Advances in Intelligent Systems and Computing, 2013

2012 IEEE International Conference on Consumer Electronics (ICCE), 2012

There are lots of devices and services inside a home which have to be managed. OSGi platforms all... more There are lots of devices and services inside a home which have to be managed. OSGi platforms alleviate this management by installing some services on a gateway located at home. A service provider might manage those services as part of a package of services. In general, OSGi platforms are connected to centralized repositories facilitating the maintenance by service providers. However, when various service providers work on a given gateway the number of services and components installed in it increases. This sometimes leads to inconsistencies as duplicate components that might cause performance problems or service interruptions. This paper presents a system for analyzing and automatically optimizing the components deployed on a OSGi home gateway.

Proceedings of the 5th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, 2008

... Authors, Gustavo Ramírez-González, Universidad Carlos III de Madrid, Spain. Mario Muñoz-Organ... more ... Authors, Gustavo Ramírez-González, Universidad Carlos III de Madrid, Spain. Mario Muñoz-Organero, Universidad Carlos III de Madrid, Spain. ... Collaborative Colleagues: GustavoRamírez-González: colleagues. Mario Muñoz-Organero: colleagues. ...

IEEE Transactions on Intelligent Transportation Systems, 2000

ABSTRACT This paper implements and validates an expert system that, based on the detection or pre... more ABSTRACT This paper implements and validates an expert system that, based on the detection or previous knowledge of certain types of traffic signals, proposes a method to reduce fuel consumption by calculating optimal deceleration patterns, minimizing the use of braking. The expert system uses a mobile device's embedded camera to monitor the environment and to recognize certain types of static traffic signals that force or can force a vehicle to stop. The system uses an adaptation of the algorithm proposed by Viola and Jones for the recognition of faces in real time, adapted to the detection of traffic signals. Detected signals are also incorporated into a central database for future use. When the vehicle approaches an upcoming traffic signal, the algorithm estimates the distance required to stop the vehicle without using the brakes, taking into account the rolling resistance coefficient and the road slope angle. Appropriate advice and feedback are provided to the driver to release the accelerator pedal. The expert system is implemented on Android mobile devices and has been validated using a data set of 180 tests with five different models of vehicles and nine different drivers. The main contribution of this paper is the proposal of an assistant that uses information from the environment and from the vehicle to calculate optimal deceleration patterns when approaching traffic signals that force or may force the vehicle to stop. In addition, the proposed solution does not require the installation of infrastructure on the road, and it can be installed into any vehicle.

Applied Mathematics and Computation, 2013

a b s t r a c t This paper examined the spectral properties of quadruple symmetric real functions... more a b s t r a c t This paper examined the spectral properties of quadruple symmetric real functions. Theorem is formulated, under which the complex spectra of such symmetric functions are conjugated. The properties of the trigonometric functions are used in the proof of the theorem. Numerical results are presented for illustrating of the proven theorem. (P. Philipoff), aii2010@abv.bg (A. Ivanov), munozm@it.uc3m.es (M. Muñoz), galerida@abv.bg (G. Raikova), tatur@i-proc.com (M. Tatur), bolter@abv.bg (P. Michaylov).

The success or failure of e-learning courses depends not only on the design and quality of the le... more The success or failure of e-learning courses depends not only on the design and quality of the learning materials but on the ability to motivate students to study them. Motivational factors are of the uppermost importance in e-learning courses since the motivational impact of the student-teacher proximity obtained in faceto-face education is normally not achievable. This paper makes an analysis about how to make use of some of the tools available in e-learning systems to try to motivate students. The paper makes a general review of the available tools and takes a special interest in forums and assessments. The results are validated based on the experience obtained from the teaching of the subject "Internet Society". This subject is offered to the students of all the six public Universities in Madrid (Spain) using a Moodle based e-learning platform. The experience has studied the behaviour of 60 students and their reactions to several motivational stimuli based on forum participation and assessments.

Journal of universal computer science, Mar 28, 2024

INTED proceedings, Mar 1, 2016

In this paper we present a dataset componsed of domain-specific sentiment lexicons in six languag... more In this paper we present a dataset componsed of domain-specific sentiment lexicons in six languages for two domains. We used existing collections of reviews from Trip Advisor, Amazon, the Stanford Network Analysis Project and the OpinRank Review Dataset. We use an RDF model based on the lemon and Marl formats to represent the lexicons. We describe the methodology that we applied to generate the domain-specific lexicons and we provide access information to our datasets.

El crecimiento del numero de vehiculos en circulacion ha experimentado un fuerte aumento en los u... more El crecimiento del numero de vehiculos en circulacion ha experimentado un fuerte aumento en los ultimos 20 anos. La generalizacion del uso del automovil ha tenido efectos muy positivos en la economia de los paises. Sin embargo, tambien ha provocado grandes problemas debido la contaminacion y a la cantidad de energia que consumen. Por otra parte, la mayoria de los vehiculos emplean hidrocarburos, que no se encuentran disponibles en todas las regiones, provocando dependencias energeticas entre paises. Ademas, su extraccion tiene un impacto muy grande en el medioambiente. Los vehiculos se han convertido en un problema importante para los gobiernos y los habitantes, que sufren enfermedades respiratorias provocadas por los gases que emiten. Ante estos inconvenientes, los gobiernos han desarrollado normativas para regular las emisiones de los vehiculos. Las conductores tambien han empezado a exigir vehiculos que consuman menos debido al aumento del precio del combustible, convirtiendose e...

En este informe se presenta el estado del arte sobre lo que concierne al aprendizaje móvil con us... more En este informe se presenta el estado del arte sobre lo que concierne al aprendizaje móvil con uso de tecnología, mobile Learning (mLearning). Las áreas abordadas en este estado del arte corresponden a movilidad y uso de dispositivos móviles, experiencias de mLearning, y ...

Lecture Notes in Computer Science, Dec 31, 2022

Mathematics, Sep 23, 2023

Advances in intelligent systems and computing, 2013

This paper implements and validates a system to save fuel based on the collaboration of drivers. ... more This paper implements and validates a system to save fuel based on the collaboration of drivers. The system gets the optimal speed pattern evaluating the driving of nearby drivers. A fuzzy logic system is used to assess drivers and the information about nearby vehicles is obtained through WIFI-Direct. Best driver sends the optimal speed pattern to the other vehicles and the mobile device notifies the user through a vibration pattern or speaker if the user should slow down or speed up.