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https://hdl.handle.net/10784/27881

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Combining fuzzy and PID control for an unmanned helicopter
(IEEE Communications Society, 2005-01-01) Sanchez, E.N.; Becerra, H.M.; Velez, C.M.; Sanchez, E.N.; Becerra, H.M.; Velez, C.M.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
This paper reports the synthesis of a controller for the X-Cell mini-helicopter. It is developed on basis of the most realistic mathematical model actually availble ([1]). A combined control structure is proposed: Mamdani controllers keep set points for an altitude/attitude controller. These controllers are designed in the simplest rule base. Altitude/attitude controller is constituted for conventional SISO PID controllers for z-position and roll, pitch and yaw angles. This control scheme mimics the action of an expert pilot. The proposed scheme is tested via simulations; it presents a good performance for hover flight, and control position in slow speed. © 2005 IEEE.
Modeling, simulation and rapid prototyping of an unmanned mini-helicopter
(2006-01-01) Vélez, C.M.; Agudelo, A.; Alvarez, J.; Vélez, C.M.; Agudelo, A.; Alvarez, J.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
This paper presents a rapid software prototyping environment (RSPE) for the design, simulation, and real-time implementation of a control system for an autonomous mini-helicopter. The software prototyping environment consists of diverse modules, including a mini-helicopter simulation model, a navigation filter, different controllers, a ground control station, and linearization and parameter identification tools. The environment is intended to reduce development time and costs, giving the designer more time to focus on mathematical and algorithmic methods. A hardware-in-the-loop (HIL) simulation example is presented to study the use and advantages of the prototyping environment in control design and simulation. Copyright © 2006 by EAFIT University.
Avionics system for a mini-helicopter robot in a rapid software prototyping environment
(2010-01-01) Vélez S., C.M.; Hernández L., M.; Agudelo T., A.; Vélez S., C.M.; Hernández L., M.; Agudelo T., A.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
This paper describes the hardware and software of the avionics for a mini-helicopter robot called Colibrí, which provides the instrumentation, intelligence, and energy to the autonomous navigation. The paper describes the function of each electronic device in the navigation system and explains the tools for rapid software prototyping. This programming environment uses a high-level graphical language like Simulink® to design a test model, and from it automatically build the executable code in C, which runs in the QNX real-time operating system during each flight. Matlab® Real-Time Workshop is the tool that enables this efficient programming methodology. The tests in pilot assisted flights show that the environment makes easy the development of state estimators, finite state machines, controllers and other subsystems. © 2010 IEEE.
Parameter estimation of a predator-prey model using a genetic algorithm
(2010-01-01) Restrepo, J.G.; Sánchez, C.M.V.; Restrepo, J.G.; Sánchez, C.M.V.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
This paper presents the parameter estimation of a biological system with real data extracted from literature, and different model structures: Lotka-Volterra model (basic predator-prey model) and saturation predator-prey model. A third model is proposed and tested in simulation due to lack of appropriated real data; it includes inputs that excite the system and makes the estimation process more manageable. The model parameters were estimated using a genetic algorithm, which gives a combination of parameters used in simulation to compare outputs with real data and decide, using a cost function, which parameters are better. Comparing the models, the Lotka-Volterra model provides better adjustment but with unrealistic assumptions, while saturation model represents a system with real assumptions but the fit is not very high. ©2010 IEEE.
Comparison on the estimation of the biomass of a batch bioreactor through fuzzy systems, neural networks and adaptive neuro-fuzzy inference system
(2011-01-01) Muñoz, A.A.G.; Quintero, O.L.; Muñoz, A.A.G.; Quintero, O.L.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
The estimation of biomass production of d-endotoxins of the Bacillus thuringiensis (Bt) is a major problem in biotechnological processes, as bio-insecticides, which has been addressed with different methodologies such as extended Kalman filters (EKF), phenomenological observers, among others. This paper presents a comparison in the estimation of biomass concentration of d - endotoxins of the Bacillus thuringiensis (Bt), using Mamdani fuzzy inference systems (FIS), neural networks (NN) and adaptive neuro-fuzzy inference system (ANFIS) trained with differents clustering algorithms; and comparing the associated outcomes among these. © 2011 IEEE.
Evaluation of wavelet measures on automatic detection of emotion in noisy and telephony speech signals
(IEEE, 2014-01-01) Vasquez-Correa, J. C.; Garcia, N.; Vargas-Bonilla, J. F.; Orozco-Arroyave, J. R.; Arias-Londono, J. D.; Lucia Quintero M, O.; Vasquez-Correa, J. C.; Garcia, N.; Vargas-Bonilla, J. F.; Orozco-Arroyave, J. R.; Arias-Londono, J. D.; Lucia Quintero M, O.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
Detection of emotion in humans from speech signals is a recent research field. One of the scenarios where this field has been applied is in situations where the human integrity and security are at risk. In this paper we are propossing a set of features based on the Teager energy operator, and several entropy measures obtained from the decomposition signals from discrete wavelet transform to characterize different types of negative emotions such as anger, anxiety, disgust, and desperation. The features are measured in three different conditions: (1) the original speech signals, (2) the signals that are contaminated with noise, or are affected by the presence of a phone channel, and (3) the signals that are obtained after processing using an algorithm for Speech Enhancement based on Karhunen-Love Transform. According to the results, when the speech enhancement is applied, the detection of emotion in speech is increased in up to 22% compared to results obtained when the speech signal is highly contaminated with noise. © 2014 IEEE.
Adaptive architecture to support context-aware Collaborative Networked Virtual Surgical Simulators (CNVSS)
(SPRINGER, 2014-01-01) Diaz, C.; Trefftz, H.; Quintero, L.; Acosta, D.; Srivastava, S.; Diaz, C.; Trefftz, H.; Quintero, L.; Acosta, D.; Srivastava, S.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
Stand-alone and networked surgical virtual reality based simulators have been proposed as means to train surgical skills with or without a supervisor nearby the student or trainee. However, surgical skills teaching in medicine schools and hospitals is changing, requiring the development of new tools to focus on: (i) importance of mentors role, (ii) teamwork skills and (iii) remote training support. For these reasons a surgical simulator should not only allow the training involving a student and an instructor that are located remotely, but also the collaborative training session involving a group of several students adopting different medical roles during the training session. Collaborative Networked Virtual Surgical Simulators (CNVSS) allow collaborative training of surgical procedures where remotely located users with different surgical roles can take part in a training session. Several works have addressed the issues related to the development of CNVSS using various strategies. To the best of our knowledge no one has focused on handling heterogeneity in collaborative surgical virtual environments. Handling heterogeneity in this type of collaborative sessions is important because not all remotely located users have homogeneous Internet connections, nor the same interaction devices and displays, nor the same computational resources, among other factors. Additionally, if heterogeneity is not handled properly, it will have an adverse impact on the performance of each user during the collaborative session. In this paper we describe the development of an adaptive architecture with the purpose of implementing a context-aware model for collaborative virtual surgical simulation in order to handle the heterogeneity involved in the collaboration session. © 2014 Springer International Publishing.
Fuzzy Inference System for Modelling Failure Modes in a Ropeway for Massive Transportation
(ATLANTIS PRESS, 2015-01-01) Villa, Luisa F.; Quintero Montoya, O. L.; Castaneda, L.; Meja, G.; Villa, Luisa F.; Quintero Montoya, O. L.; Castaneda, L.; Meja, G.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
This work uses Fuzzy Inference Systems to model the failure modes of the Metrocable (ropeway massive transportation system in Medellin-Colombia) and to this aim, handle the concept of Condition Based Maintenance (CBM) for the automation of maintenance routine. Maintenance procedures in this massive transportation ropeway system have been designed from manufacturer and improved by expert knowledge trough years of operation, so they can be modeled by fuzzy models. The following work is part of the project ``Diagnostic system of the interface grip-cable of the Metrocable'', developed between the entities COLCIENCIAS, Metro de Medellin and Universidad EAFIT.
Recognition and regionalization of emotions in the arousal-valence plane
(Institute of Electrical and Electronics Engineers Inc., 2015-01-01) Bustamante, P.A.; Lopez Celani, N.M.; Perez, M.E.; Quintero Montoya, O.L.; Bustamante, P.A.; Lopez Celani, N.M.; Perez, M.E.; Quintero Montoya, O.L.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
The emotion recognition systems have become important for the diversity of its applications. Several methodologies have been proposed based on how emotions are reflected in biological systems, such as facial expressions, the activity of the nervous system or the prosody of voice. The detection of emotions by voice processing is an approach that involves a noninvasive procedure that produces results with an acceptable rate of detection. In this work an algorithm for features extraction was developed, that efficiently classify different emotional states. Thus, emotions that have not been trained can be associated with a trained emotion both belonging to the same region of the valence-arousal plane.
Measuring Quality Policy Deployment: A Fuzzy Logic Approach
(ATLANTIS PRESS, 2015-01-01) Cogollo-Florez, Juan; Cogollo-Florez, Myladis; Florez-Rendon, Andrea; Cogollo-Florez, Juan; Cogollo-Florez, Myladis; Florez-Rendon, Andrea; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
Global and balanced performance measurement in Quality Policy Deployment is a key element of quality management in public Higher Education Institutions (HEI's). This paper describes the design of a fuzzy linguistic model for measuring Quality Policy Deployment in a Colombian public HEI. The proposed model integrates Balanced Scorecard (BSC) principles with the theory of fuzzy sets for treatment of imprecision associated with quantifying of Quality Policy Deployment. The application of the model allowed to obtain a crisp Quality Policy Deployment Index incorporating imprecision and vagueness on these calculations through a fuzzy rule-based system.
Multiresolution analysis (discrete wavelet transform) through Daubechies family for emotion recognition in speech.
(IOP PUBLISHING LTD, 2016-01-01) Campo, D.; Quintero, O.L.; Bastidas, M.; Campo, D.; Quintero, O.L.; Bastidas, M.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
We propose a study of the mathematical properties of voice as an audio signal. This work includes signals in which the channel conditions are not ideal for emotion recognition. Multiresolution analysis- discrete wavelet transform - was performed through the use of Daubechies Wavelet Family (Db1-Haar, Db6, Db8, Db10) allowing the decomposition of the initial audio signal into sets of coefficients on which a set of features was extracted and analyzed statistically in order to differentiate emotional states. ANNs proved to be a system that allows an appropriate classification of such states. This study shows that the extracted features using wavelet decomposition are enough to analyze and extract emotional content in audio signals presenting a high accuracy rate in classification of emotional states without the need to use other kinds of classical frequency-time features. Accordingly, this paper seeks to characterize mathematically the six basic emotions in humans: boredom, disgust, happiness, anxiety, anger and sadness, also included the neutrality, for a total of seven states to identify.
A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies
(IOP PUBLISHING LTD, 2016-01-01) Ortiz, P.D.; Villa, L.F.; Salazar, C.; Quintero, O.L.; Ortiz, P.D.; Villa, L.F.; Salazar, C.; Quintero, O.L.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
A simple but efficient voice activity detector based on the Hilbert transform and a dynamic threshold is presented to be used on the pre-processing of audio signals. The algorithm to define the dynamic threshold is a modification of a convex combination found in literature. This scheme allows the detection of prosodic and silence segments on a speech in presence of non-ideal conditions like a spectral overlapped noise. The present work shows preliminary results over a database built with some political speech. The tests were performed adding artificial noise to natural noises over the audio signals, and some algorithms are compared. Results will be extrapolated to the field of adaptive filtering on monophonic signals and the analysis of speech pathologies on futures works.
Double Fourier analysis for Emotion Identification in Voiced Speech
(IOP PUBLISHING LTD, 2016-01-01) Sierra-Sosa, D.; Bastidas, M.; Ortiz, P.D.; Quintero, O.L.; Sierra-Sosa, D.; Bastidas, M.; Ortiz, P.D.; Quintero, O.L.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
We propose a novel analysis alternative, based on two Fourier Transforms for emotion recognition from speech. Fourier analysis allows for display and synthesizes different signals, in terms of power spectral density distributions. A spectrogram of the voice signal is obtained performing a short time Fourier Transform with Gaussian windows, this spectrogram portraits frequency related features, such as vocal tract resonances and quasi-periodic excitations during voiced sounds. Emotions induce such characteristics in speech, which become apparent in spectrogram time-frequency distributions. Later, the signal time-frequency representation from spectrogram is considered an image, and processed through a 2-dimensional Fourier Transform in order to perform the spatial Fourier analysis from it. Finally features related with emotions in voiced speech are extracted and presented.
An approach to emotion recognition in single-channel EEG signals: A mother child interaction
(IOP PUBLISHING LTD, 2016-01-01) Gómez, A.; Quintero, L.; López, N.; Castro, J.; Gómez, A.; Quintero, L.; López, N.; Castro, J.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
In this work, we perform a first approach to emotion recognition from EEG single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology. Single channel EEG signals are analyzed and processed using several window sizes by performing a statistical analysis over features in the time and frequency domains. Finally, a neural network obtained an average accuracy rate of 99% of classification in two emotional states such as happiness and sadness.
Design, construction and testing of a data transmission system for a mid-power rocket model
(IEEE Computer Society, 2017-01-01) Botero, A.Y.; Rodríguez, J.S.; Serna, J.G.; Gómez, A.; García, M.J.; Botero, A.Y.; Rodríguez, J.S.; Serna, J.G.; Gómez, A.; García, M.J.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
This paper presents the continuation of a previous work in the development of a communication module for a solid propellant mid-power rocket model named "Simple-1" mission. It considered the design, construction, and testing procedures related to the data transmission protocol and its data rate. The current phase considers the antenna's optimization, launching, and data analysis on-flight. In the actual optimization step, the antenna components were modified to increase the gain. A rocket model Estes Ventris Series Pro II® was used to carry in the payload section a communication module with several sensors in a CanSat form factor. The collected data was processed using an Arduino Mini micro-controller and transmitted using a radio module (Radiometrix) to a software defined radio (SDR) HackRF-based platform on the ground station. The printed circuit boards (PCBs) were designed and manufactured from commercial off the shelf (COTS) and assembled in a cylindrical rack structure similar to this small format satellite concept. The Simple-1 was tested with the help of a wind tunnel to validate the behavior of the antenna's subsystem and was proved in several launches using solid propellant motors reaching altitudes from 500-700 meters. Different experimental data such as altitude, position, atmospheric pressure, and vehicle temperature were successfully captured and analyzed. This demonstrates that it is possible to develop low cost near space activities, gradually installing capabilities in a teamwork. In this developing stage, the techniques to design and manufacture two layers PCB were appropriated by traditional circuit board etching methods. In addition, the SDR technology was studied and implemented for the telemetry architecture. The use of surface mounting devices (SMD) offers an alternative to reduce the volume of the module. In the future, it is expected to have more advances in the stability of the communication protocols, robust hardware manufacturing, and integration of electronic circuits in four-layer PCB, in order to contribute to the access to space in our region and local aerospace industry developments. © 2017 IEEE.
A Novel emotion recognition technique from voiced-speech
(IEEE, 2017-01-01) Uribe, Alejandro; Gomez, Alejandro; Bastidas, Manuela; Quintero, O. Lucia; Campo, Damian; Uribe, Alejandro; Gomez, Alejandro; Bastidas, Manuela; Quintero, O. Lucia; Campo, Damian; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
In the framework of the beginning of the investigation due to a work of an undergraduate student, the authors at Mathematical Modeling Research Group (GRIMMAT) propose the use of emotion recognition algorithms previously developed by them adapting it to the FAU Aibo emotion corpus which was the database used in the INTERSPEECH 2009 Emotion Challenge. Firstly, by resampling the audio signal and windowing process, the audio signal is segmented. Next, each segment is decomposed through the discrete wavelet transform, then the descriptive characteristics of the decomposed signal are extracted. Finally, a supervised classification scheme is used. This paper presents the main results and conclusions obtained.
Simple-1: Development stage of the data transmission system for a solid propellant mid-power rocket model
(IOP PUBLISHING LTD, 2017-01-01) Yarce A.; Sebastián Rodríguez J.; Galvez J.; Gómez A.; García M.J.; Yarce A.; Sebastián Rodríguez J.; Galvez J.; Gómez A.; García M.J.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
This paper presents the development stage of a communication module for a solid propellant mid-power rocket model. The communication module was named. Simple-1 and this work considers its design, construction and testing. A rocket model Estes Ventris Series Pro II® was modified to introduce, on the top of the payload, several sensors in a CanSat form factor. The Printed Circuit Board (PCB) was designed and fabricated from Commercial Off The Shelf (COTS) components and assembled in a cylindrical rack structure similar to this small format satellite concept. The sensors data was processed using one Arduino Mini and transmitted using a radio module to a Software Defined Radio (SDR) HackRF based platform on the ground station. The Simple-1 was tested using a drone in successive releases, reaching altitudes from 200 to 300 meters. Different kind of data, in terms of altitude, position, atmospheric pressure and vehicle temperature were successfully measured, making possible the progress to a next stage of launching and analysis. © Published under licence by IOP Publishing Ltd.
An approach to emotion recognition in single-channel EEG signals using stationarywavelet transform
(SPRINGER, 2017-01-01) Gómez, A.; Quintero, L.; López, N.; Castro, J.; Villa, L.; Mejía, G.; Gómez, A.; Quintero, L.; López, N.; Castro, J.; Villa, L.; Mejía, G.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
In this work, we perform an approach to emotion recognition from Electroencephalography (EEG) single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology. Single channel EEG signals are decomposed by several types of wavelets and each subsignal are processed using several window sizes by performing a statistical analysis. Finally, three types of classifiers were used, obtaining accuracy rate between 50% to 87% for the emotional states such as happiness, sadness and neutrality. © Springer Nature Singapore Pte Ltd. 2017.
Attenuation of reverse time migration artifacts using Laguerre-Gauss filtering
(European Association of Geoscientists and Engineers, EAGE, 2017-06-12) Paniagua, Juan Guillermo; Lucia Quintero M, O.; Paniagua, Juan Guillermo; Lucia Quintero M, O.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
Low-frequency artifacts appear in seismic images obtained by reverse time migration with the zero-lag crosscorrelation imaging condition due to the unwanted correlation of diving waves, head waves and backscattered waves. These artifacts can hide important details in the image and different methods have been proposed to attenuate or reduce them. The Laplacian filtering is the common post-processing technique to reduce the artifacts, but it increases the high-frequency noise in the image. Paniagua and Sierra-Sosa (2016) proposed the use of the Laguerre-Gauss spatial filtering (LGSF) to reduce the artifacts and enhance subsurface structures in the seismic image.\\ In this work, we describe the performance of the LGSF and demonstrate the good behavior of this postprocessing technique through synthetic examples. We used the original and different smoothed velocity models to show the capabilities of the LGSF and the results obtained in presence of small changes in the images. We demonstrate that despite the smoothed velocity models the LGSF preserves well the reflections with their true locations and significantly attenuates the low-frequency noise.
Short Research Advanced Project: Development of Strategies for Automatic Facial Feature Extraction and Emotion Recognition
(IEEE, 2017-10-18) Restrepo, David; Gomez, Alejandro; Restrepo, David; Gomez, Alejandro; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
Emotions are a fundamental part of the personal and social skills of the human being. The behavior, intelligence, reason and decision making process are some of the topic that can be influenced by the emotional state of a person. In this paper we develop a computational way for emotion recognition though images using the Cohn-Kanade database to train a pattern recognition neural network and Viola Jones object detector to extract the information of the facial expression. The resulting neural network showed an overall accuracy of 90.7% in recognizing between 6 basic emotions such a surprise, fear, happiness, sadness, disgust and anger.

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