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Mixed-Integer Linear Programming Models for One-Commodity Pickup and Delivery Traveling Salesman Problems
(Springer Verlag, 2019-01-01) Palacio J.D.; Rivera J.C.; Palacio J.D.; Rivera J.C.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
This article addresses two different pickup and delivery routing problems. In the first one, called the one-commodity pickup and delivery traveling salesman problem, a known amount of a single product is supplied or demanded by a set of two different types of locations (pickup or delivery nodes). Therefore, a capacitated vehicle must visit each location once at a minimum cost. We also deal with the relaxed case where locations can be visited several times. In the last problem, the pickup or delivery operation can be split into several smaller pickups or deliveries, and also locations can be used as temporal storage points with the aim of reducing the cost of the route. To solve these problems, we present two mixed-integer linear programming models and we solve them via commercial solver. We analyze how several visits to a single location may improve solution quality and we also show that our simple strategy has a good performance for instances with up to 60 locations. © 2019, Springer Nature Switzerland AG.
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
Meteorological Risk Early Warning System for Air Operations
(Institute of Electrical and Electronics Engineers Inc., 2019-01-01) Florez Zuluaga J.A.; David Ortega Pabon J.; Vargas Bonilla J.F.; Quintero Montova O.L.; Florez Zuluaga J.A.; David Ortega Pabon J.; Vargas Bonilla J.F.; Quintero Montova O.L.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
Today, airspace control has the challenge of merging information from independent and heterogeneous systems in order to minimize air safety risks and facilitate the decision-making process. One of the main risks for air operations is meteorology because convective formations like Torre cumulus or cumulonimbus could generate several dangerous phenomena such as icing, wind gusts, and thunderstorms, among others, that can affect the air operation safety. Based on previous works that allow the automatic identification of convective phenomena through the fusion of multispectral satellite images and other sources as winds and Meteorological Aerodrome Report (METAR), and establishing a common georeferenced coordinates system like WGS-84, for all sources, it can generate a system that could calculate early alerts about hazardous weather conditions in the aircrafts proximality for air traffic control system. For this, a meteorological analysis system can generate information about convective clouds calculating area, heights, temperatures, risk level and position of the meteorological formation. Parallelly the convective cloud is surrounded by optimal elliptical forms centered on the convective formation, generating a meteorological object. On the other hand, there is a system responsible for monitoring the information of the surveillance sensors. This system fused the air traffic sensors available like primary and secondary radar signals and ADS-B sensors in a unique WGS-84 coordinates system. Finally, in a georeferenced raster-Type graphing system or in a Geographic Information System (GIS), the meteorological and surveillance information is correlated projecting the track routes generates by air traffic system and traces generated by meteorological objects in order to establish times and high-risk areas, early. With this information, the Air Traffic Controller (ATC) system users, could minimize risk areas and reorganize the air traffic flow. This methodology then, would contribute to the decision-making process of ATC, facilitating the air flow reorganization and minimizing meteorological risks. For the development of this project a cooperative experimental methodology by subsystems was used. It was based on an operational knowledge and normal operating procedures of the Colombian Air Force, integrated with radar tracking technologies that implement decision trees. These alerts allow the air traffic controller to assess the risk and in accordance with the evaluation, if necessary, reorganize the air traffic flow for a specific area before the aircraft enter areas of bad weather mitigating the risks. © 2019 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.
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.
Standardized Approaches for Assessing Metagenomic Contig Binning Performance from Barnes-Hut t-Stochastic Neighbor Embeddings
(SPRINGER, 2020-01-01) Ceballos J.; Ariza-Jiménez L.; Pinel N.; Ceballos J.; Ariza-Jiménez L.; Pinel N.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
The performance of unsupervised methods for metagenomic binning is often assessed using simulated microbial communities. The lack of well-characterized evaluation protocols and approaches to community construction cognizant of biological realities impedes the rigorous assessment and standardization of the binning process. This work attempted to standardize performance evaluation using benchmark communities constructed according to the genome similarity metric Average Amino Acid identity. This approach allowed us to extend and deepen our previous research on the unsupervised binning of metagenomic sequence fragments based on low-dimensional embeddings of pentamer frequency profiles. Experimental results evidenced our method’s potential for the binning of metagenomic contigs to become an alternative to state-of-the-art methods such as MetaCluster 3.0. © 2020, Springer Nature Switzerland AG.
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.
A Mixed-Integer Linear Programming Model for a Selective Vehicle Routing Problem
(Springer Verlag, 2018-01-01) Posada A.; Rivera J.C.; Palacio J.D.; Posada A.; Rivera J.C.; Palacio J.D.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
In this paper, we propose a new vehicle routing problem variant. The new problem is a type of selective vehicle routing model in which it is not necessary to visit all nodes, but to visit enough nodes in such a way that all clusters are visited and from which it is possible to cover all nodes. Here, a mixed-integer linear programming formulation (MILP) is proposed in order to model the problem. The MILP is tested by using adapted instances from the generalized vehicle routing problem (GVRP). The model is also tested on small size GVRP instances as a special case of our proposed model. The results allow to evaluate the impact of clusters configuration in solver efficacy. © 2018, Springer Nature Switzerland AG.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.

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