Different Intelligent Approaches for Modeling the Style of Car Driving

Authors: Jose Aguilar, Kristell Aguilar, Danilo Chávez, Jorge Cordero and Eduard Puerto

Abstract:
In this paper, we propose a hierarchical pattern of the style of driving, which is composed of three levels, one to recognize the emotional state, other to recognize the state of the driver, and finally, the last one corresponds to the style of driving. Each level is defined by different types of descriptors, which are perceived in different multi-modal ways (sound, vision, etc.). Additionally, we analyze three techniques to recognize the style of driving, using our hierarchical pattern, one based on fuzzy logic, another based on chronicles (a temporal logic paradigm), and another based on an algorithm that models the functioning of the human neocortex, exploiting the idea of recursivity and learning in the recognition process. We compare the techniques considering the dynamic context where a car driver operates.

Keywords: Hierarchical Patterns, Fuzzy Logic, Chronicles, Dynamic Pattern Recognition, Style of Driving

Link: http://www.scitepress.org/DigitalLibrary/PublicationsDetail.aspx?ID=pKH2LWLdplY%3d&t=1

Towards a Fuzzy Cognitive Map for Opinion Mining

Authors: Jose Aguilar, Oswaldo Téran, Hebert Sánchez, José Gutiérrez de Meza, Jorge Cordero, and Danilo Chávez

Abstract:
In this paper, we propose a Fuzzy Cognitive Map (FCM) to opinion mining, with special attention to media influence on public opinion. Particularly, in this paper, we describe the FCM, the concepts and relationships among them. Our opinion mining model is based on a multilevel FCM, to distribute the concepts according to the aspects that describe the elements conforming public opinion, which are: social, technological and biological. We carry out preliminary tests, and the results are very encouraging.

Keywords: Fuzzy Cognitive Maps, Opinion Mining, Opinion Conformation, Media Manipulation

Link: http://www.sciencedirect.com/science/article/pii/S1877050917309432

Learning analytics tasks as services in smart classrooms

Authors: Jose Aguilar, Manuel Sánchez, Jorge Cordero, Priscila Valdiviezo-Díaz, Luis Barba-Guamán and Luis Chamba-Eras

Abstract:
A smart classroom integrates the different components in a traditional classroom, by using different technologies as artificial intelligence, ubiquitous, and cloud paradigms, among others, in order to improve the learning process. On the other hand, the learning analytics tasks are a set of tools that can be used to collect and analyze the data accumulated in a smart classroom. In this paper, we propose the definition of the learning analytics tasks as services, which can be invoked by the components of a smart classroom. We describe how to combine the cloud and multi-agent paradigms in a smart classroom, in order to provide academic services to the intelligent and non-intelligent agents in the smart classroom, to adapt and respond to the teaching and learning requirements of students. Additionally, we define a set of learning analytics tasks as services, which defines a knowledge feedback loop for the smart classroom, in order to improve the learning process in it, and we explain how they can be invoked and consumed by the agents in a smart classroom.

Keywords: Learning analytics as service, Smart classroom, Cloud computing, Ambient intelligences

Link: http://link.springer.com/article/10.1007%2Fs10209-017-0525-0
Other link: Learning analytics tasks as services in smart classrooms

Cite this article as:

Aguilar, J., Sánchez, M., Cordero, J. et al.

Univ Access Inf Soc (2017).

doi:10.1007/s10209-017-0525-0

A Dynamic Recognition Approach of Emotional States for Car Drivers

Authors: Jose Aguilar, Danilo Chavez, and Jorge Cordero

Abstract:
In this paper, we propose a recognition model of emotional state using multi-modal perception, a temporal logic paradigm (in particular, we use chronicles), and dynamical patterns. In this way, our recognition approach is based on chronicles to model the patterns, a definition of the emotions as dynamic patterns, and the idea that they are perceived in a multi-modal way (sound, vision, etc.). In this paper, we present these elements of our approach, and give one example of an application for the recognition of the emotions of the driver of a vehicle.

Keywords: Recognition of emotions, Chronicles, Dynamic patterns recognition

Link: http://link.springer.com/chapter/10.1007/978-3-319-48024-4_13

DOI: 10.1007/978-3-319-48024-4_13

A general framework for learning analytic in a smart classroom

Authors: Jose Aguilar, Priscila Valdiviezo, Jorge Cordero, Guido Riofrio, and Eduardo Encalada

Abstract. In this paper, we propose the utilization of the “Learning Analytics” paradigm in a Smart Classroom, a classroom that integrates artificial intelligence technology on the educational process. Learning Analytics can extract knowledge from the Smart Classroom platform, to better understand students and his/her learning processes. In this way, a Smart Classroom can understand and optimize
the learning process and the teaching environments proposed. The smart classroom can adapt its components to improve students’ performance, among other aspects. Particularly, this paper proposes a framework about how the Learning Analytics paradigm can be used in a Smart Classroom, in order to provide knowledge about the activities taking place within it. The framework is defined like a closed cycle of Learning Analytics tasks, which generate metrics used like feedback to optimize the pedagogical model proposed by the smart Classroom. The metrics evaluate the learning process and pedagogical practice provided by the smart Classroom. So, our main contribution is about how the Learning Analytics paradigm can be used in a Smart Classroom in order to improve the students’
performance.

Keywords: Learning analytics, Smart classroom,  Ambient intelligence, Data mining

Link: http://link.springer.com/chapter/10.1007/978-3-319-48024-4_17

DOI: 10.1007/978-3-319-48024-4_17