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

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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.
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.
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.
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.
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.
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.
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.
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.
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.
Efficient use of mobile devices for quantification of pressure injury images
(IOS Press, 2018-01-01) Garcia-Zapirain B; Sierra-Sosa D; Ortiz P D; Isaza-Monsalve M; Elmaghraby A; Garcia-Zapirain B; Sierra-Sosa D; Ortiz P D; Isaza-Monsalve M; Elmaghraby A; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
Pressure Injuries are chronic wounds that are formed due to the constriction of the soft tissues against bone prominences. In order to assess these injuries, the medical personnel carry out the evaluation and diagnosis using visual methods and manual measurements, which can be inaccurate and may generate discomfort in the patients. By using segmentation techniques, the Pressure Injuries can be extracted from an image and accurately parameterized, leading to a correct diagnosis. In general, these techniques are based on the solution of differential equations and the involved numerical methods are demanding in terms of computational resources. In previous work, we proposed a technique developed using toroidal parametric equations for image decomposition and segmentation without solving differential equations. In this paper, we present the development of a mobile application useful for the non-contact assessment of Pressure Injuries based on the toroidal decomposition from images. The usage of this technique allows us to achieve an accurate segmentation almost 8 times faster than Active Contours without Edges (ACWE) and Dynamic Contours methods.We describe the techniques and the implementation for Android devices using Python and Kivy. This application allows for the segmentation and parameterization of injuries, obtain relevant information for the diagnosis and tracking the evolution of patient's injuries. © 2018 - IOS Press and the authors.
Emotion Recognition from EEG and Facial Expressions: A Multimodal Approach
(Institute of Electrical and Electronics Engineers Inc., 2018-01-01) Chaparro V.; Gomez A.; Salgado A.; Quintero O.L.; Lopez N.; Villa L.F.; Chaparro V.; Gomez A.; Salgado A.; Quintero O.L.; Lopez N.; Villa L.F.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
The understanding of a psychological phenomena such as emotion is of paramount importance for psychologists, since it allows to recognize a pathology and to prescribe a due treatment for a patient. While approaching this problem, mathematicians and computational science engineers have proposed different unimodal techniques for emotion recognition from voice, electroencephalography, facial expression, and physiological data. It is also well known that identifying emotions is a multimodal process. The main goal in this work is to train a computer to do so. In this paper we will present our first approach to a multimodal emotion recognition via data fusion of Electroencephalography and facial expressions. The selected strategy was a feature-level fusion of both Electroencephalography and facial microexpressions, and the classification schemes used were a neural network model and a random forest classifier. Experimental set up was out with the balanced multimodal database MAHNOB-HCI. Results are promising compared to results from other authors with a 97% of accuracy. The feature-level fusion approach used in this work improves our unimodal techniques up to 12% per emotion. Therefore, we may conclude that our simple but effective approach improves the overall results of accuracy. © 2018 IEEE.
Emotional Networked maps from EEG signals
(Institute of Electrical and Electronics Engineers Inc., 2020-01-01) Gomez A.; Quintero O.L.; Lopez-Celani N.; Villa L.F.; Gomez A.; Quintero O.L.; Lopez-Celani N.; Villa L.F.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
The EEG has showed that contains relevant information about recognition of emotional states. It is important to analyze the EEG signals to understand the emotional states not only from a time series approach but also determining the importance of the generating process of these signals, the location of electrodes and the relationship between the EEG signals. From the EEG signals of each emotional state, a functional connectivity measurement was used to construct adjacency matrices: lagged phase synchronization (LPS), averaging adjacency matrices we built a prototype network for each emotion. Based on these networks, we extracted a set node features seeking to understand their behavior and the relationship between them. We found through the strength and degree, the group of representative electrodes for each emotional state, finding differences from intensity of measurement and the spatial location of these electrodes. In addition, analyzing the cluster coefficient, degree, and strength, we find differences between the networks from the spatial patterns associated with the electrodes with the highest coefficient. This analysis can also gain evidence from the connectivity elements shared between emotional states, allowing to cluster emotions and concluding about the relationship of emotions from EEG perspective. © 2020 IEEE.
Estimation of fundamental diagrams in large-scale traffic networks with scarce sensor measurements
(Institute of Electrical and Electronics Engineers Inc., 2018-01-01) Montoya O.L.Q.; Canudas-De-Wit C.; Montoya O.L.Q.; Canudas-De-Wit C.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
The macroscopic fundamental diagram (MFD) relates space-mean flow density and the speed of an entire network. We present a method for the estimation of a 'normalized' MFD with the goal to compute specific Fundamental Diagram in places where loop sensors data is no available. The methodology allows using some data from different points in the city and possibly combining several kinds of information. To this aim, we tackle at least three major concerns: the data dispersion, the sparsity of the data, and the role of the link (with data) within the network. To preserve the information we decided to treat it as two-dimensional signals (images), so we based our estimation algorithm on image analysis, preserving data veracity until the last steps (instead of first matching curves that induce a first approximation). Then we use image classification and filtering tools for merging of main features and scaling. Finally, just the Floating Car Data (FCD) is used to map back the general form to the specific road where sensors are missing. We obtained a representation of the street by means of its likelihood with other links within the same network. © 2018 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.
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.
HIPAE helicopter-borne in-situ pollution assessment experiment: Plataforma alternativa para la medición de contaminantes en capas verticales
(Institute of Electrical and Electronics Engineers Inc., 2019-01-01) Botero A.Y.; Florez J.; Duque J.F.; Rendon A.; Lopez-Restrepo S.; Pinel N.; Quintero O.L.; Oquinte1@eafit.edu.co; Rodriguez J.S.; Galvez J.; Lopera D.V.; Montilla E.; Marulanda J.I.; Isaza C.; Lainez M.L.A.; Zapata A.F.; Botero A.Y.; Florez J.; Duque J.F.; Rendon A.; Lopez-Restrepo S.; Pinel N.; Quintero O.L.; Oquinte1@eafit.edu.co; Rodriguez J.S.; Galvez J.; Lopera D.V.; Montilla E.; Marulanda J.I.; Isaza C.; Lainez M.L.A.; Zapata A.F.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
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.
Memories Webinar "A dark cloud rises in the sky: meet SIATA, a system for environmental management"
(Universidad EAFIT, 2024) Maria Eugenia Puerta-Yepes; Camilo García-Duque; Luz Jeannette Mejia-Chavarriaga; Daniel Ruiz-Carrascal; Universidad EAFIT
Memories of the conference in English. If a strong storm is approaching, as in the song of the Golden Binomial, or a ravine is rising, or if air pollutants represent a risk to your health, SIATA warns you. But Do you know how the Aburrá Valley Early Warning System - SIATA works? Within the framework of #COP16 we want to highlight the role of this system that generates, translates, transfers and disseminates alerts for environmental management and timely action by citizens throughout the Aburrá Valley. This project of the Metropolitan Area of the Aburrá Valley finds its strategic academic ally in the Directorate of Innovation and Technological Development of EAFIT, which puts at the service of citizens all the capacity for generating new knowledge, technological development and social innovation of our academic community.
Memories Webinar "A dark cloud rises in the sky: meet SIATA, a system for environmental management"
(Universidad EAFIT, 2024) Maria Eugenia Puerta-Yepes; Camilo García-Duque; Luz Jeannette Mejia-Chavarriaga; Daniel Ruiz-Carrascal; Universidad EAFIT
Memories of the conference in Spanish. If a strong storm is approaching, as in the song of the Golden Binomial, or a ravine is rising, or if air pollutants represent a risk to your health, SIATA warns you. But Do you know how the Aburrá Valley Early Warning System - SIATA works? Within the framework of #COP16 we want to highlight the role of this system that generates, translates, transfers and disseminates alerts for environmental management and timely action by citizens throughout the Aburrá Valley. This project of the Metropolitan Area of the Aburrá Valley finds its strategic academic ally in the Directorate of Innovation and Technological Development of EAFIT, which puts at the service of citizens all the capacity for generating new knowledge, technological development and social innovation of our academic community.
A Metaheuristic Approach for the Cumulative Capacitated Arc Routing Problem
(Springer Verlag, 2018-09-03) Rivera, Juan Carlos; Lenis, Sergio Andres; Rivera, Juan Carlos; Lenis, Sergio Andres; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
In this paper we propose a new variant of the capacitated arc routing problem (CARP). In this new problem the objective function becomes a cumulative objective computed as the traveled distance multiplied by the vehicle load. A metaheuristic approach is proposed which is based on the hybridization of three known procedures: GRASP, VND and Set covering model. The metaheuristic is tested with some benchmark instances from CARP. The results allow to evaluate the performance with the different metaheuristic components and to compare the solutions with the classical objective function. © 2018, Springer Nature Switzerland AG.

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