Evelio J. González

Implementing Motivational Features in Reactive Blended Learning: Application to an Introductory Control Engineering Course

This paper presents a significant advance in a reactive blended learning methodology applied to an introductory control engineering course. This proposal was based on the inclusion of a reactive element (a fuzzy-logic-based controller) designed to regulate the workload for each student according to his/her activity and performance. The contribution of this proposal stands on the inclusion of elements related to motivational factors in the students. Student motivation has been widely identified as a key factor for the academic success of every teaching-learning activity.

Use of Constructivism and Collaborative Teaching in an ILP Processors Course

Simulators are widely used to teach instruction level parallelism (ILP) topics. A simulator called SIMDE, which combines the superscalar and very long instruction word (VLIW) approaches to ILP processors in a single environment, has been developed. SIMDE has been validated and improved using feedback from students during two academic years. Although the simulator is a valuable tool in and of itself, this paper goes one step beyond by using SIMDE with an educational methodology based on constructivism and collaborative learning. This methodology has been applied in a computer architecture course that uses the Moodle platform as a framework for collaboration between students and teachers

A reactive blended learning proposal for an introductory control engineering course

As it happens in other fields of engineering, blended learning is widely used to teach process control topics. In this paper, the inclusion of a reactive element - a Fuzzy Logic based controller - is proposed for a blended learning approach in an introductory control engineering course. This controller has been designed in order to regulate the workload for each student, according to his activity and performance. The proposed course is based on a web tool called ControlWeb, which includes a complete vision of control topics and is used intensively along the course. The results of the evaluation of the methodology attest its efficiency in terms of learning degree and performance of the students.

A Neuro-Fuzzy System for Extracting Environment Features Based on Ultrasonic Sensors

In this paper, a method to extract features of the environment based on ultrasonic sensors is presented. A 3D model of a set of sonar systems and a workplace has been developed. The target of this approach is to extract in a short time, while the vehicle is moving, features of the environment. Particularly, the approach shown in this paper has been focused on determining walls and corners, which are very common environment features. In order to prove the viability of the devised approach, a 3D simulated environment has been built. A Neuro-Fuzzy strategy has been used in order to extract environment features from this simulated model. Several trials have been carried out, obtaining satisfactory results in this context. After that, some experimental tests have been conducted using a real vehicle with a set of sonar systems. The obtained results reveal the satisfactory generalization properties of the approach in this case.

An expert system for supervised classifier design: Application to Alzheimer diagnosis

The aim of this paper is to present a knowledge-based approach to supervised classifier design. For this purpose, an expert system has been built following the Common KADS methodology. Classifier design is seen as a general design problem and a modified version of the well-known Propose-Critique-Modify method is proposed as a suitable strategy to solve it. In this context, a number of heuristics are used to shrink the search in the space of possible designs. Although the system is evaluated on different datasets, special emphasis is put on a particular problem: Alzheimers diagnosis.

Fuzzy and MultiAgent Instructional Planner for an Intelligent Tutorial System

This article presents some aspects in our research into the design of a Fuzzy and MultiAgent Instructional Planner belonging to an Intelligent Tutoring System (ITS), which has been designed as a tool for the reinforcement of the addition operation. The authors propose the combined use of both fuzzy and MultiAgent Systems. The fuzzy logic methodology is used to model the students knowledge and the teaching strategy. Furthermore, the MultiAgent System implemented determines the learning objectives so as to provide the student with an efficient learning process. The fuzzy and MultiAgent Systems comprising the instructional planner were verified with the collaboration of experts in mathematics and in other areas of knowledge. The results obtained by the primary school children who used the ITS are also presented.

A control system proposal for engineering education

The goal of the work is to improve the teaching-learning process through the inclusion of prediction features in a control system proposal namely Reactive Blended Learning. To achieve this goal, a model of the student has been proposed, whose considered outputs are the performance and a participation index that measures the activity level of the student in the class. The controller is based on fuzzy logic and uses the predictions of the model to anticipate the students state. An important issue that has been taken into account is the limited time to identify the dynamics of the student learning before the course ends. This limitation has been treated through a three-stage process. It is important to remark that this work is not focused on obtaining a complete student model, but on getting useful information for the detection of trends in the teaching-learning process. Preliminary results on a real course are presented to attest the efficiency of the proposed control strategy.

RETRACTED: Hopf bifurcation stability in Hopfield neural networks

In this paper we consider a simple discrete Hopfield neural network model and analyze local stability using the associated characteristic model. In order to study the dynamic behavior of the quasi-periodic orbit, the Hopf bifurcation must be determined. For the case of two neurons, we find one necessary condition that yields the Hopf bifurcation. In addition, we determine the stability and direction of the Hopf bifurcation by applying normal form theory and the center manifold theorem. An example is given and a numerical simulation is performed to illustrate the results. We analyze the influence of bias weights on the stability of the quasi-periodic orbit and study the phase-locking phenomena for certain experimental results with Arnold Tongues in a particular weight configuration.

Brief paper: A neuro-fuzzy method applied to the motors of a stereovision system

In this paper, a new approach for steering a binocular head is presented. This approach is based on extracting the experts knowledge in order to improve the behaviour of the classical control strategies. This is carried out without inserting new elements in the system. Neuro-fuzzy techniques have been chosen in order to reach this target. As a result, a more friendly robotic system is achieved.

Teaching kinematics with interactive schematics and 3D models

In this paper, some computer applications for teaching forward and inverse kinematics in Robotics are presented. These applications, developed in Unity3D and Python, allow both teachers and students to create and manipulate 3D interactive representations of the studied robotic models. The use of these tools has been proved to help students improve their understanding of the geometric transformations and mathematical operations required to solve both forward and inverse kinematics exercises.