Examinando por Materia "algorithm"
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Ítem Adaptive LAMDA applied to identify and regulate a process with variable dead time(Institute of Electrical and Electronics Engineers Inc., 2020-01-01) Morales L.; Pozo D.; Aguilar J.; Rosales A.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las ComunicacionesIn this paper, an adaptive intelligent controller based on the fuzzy algorithm called LAMDA (Learning Algorithm for Multivariable Data Analysis) is presented in order to identify and regulate a process with variable dead time. The original algorithm has been used for supervised and unsupervised learning, whose main field of application is the identification of functional states of the systems. In this work a modification of LAMDA has been implemented which is capable of online learning using hybrid techniques. The proposal consists of two stages: training stage to learn about the unknown plant in order to establish initial parameters to the controller, and a second phase, called application, in which the control strategy is updated using online learning. The proposed method is tested in the control objective of regulation of a process with variable dead time, to analyze the viability of its utilization in these types of systems in which their dynamics are variable and unknown. © 2020 IEEE.Ítem Analytic approximation to the scattering of antiplane shear waves by free surfaces of arbitrary shape via superposition of incident, reflected and diffracted rays(OXFORD UNIV PRESS, 2013-03-01) Jaramillo, Juan; Gomez, Juan; Externo - Escuela - Ciencias; Vergara, Juan; Mecánica AplicadaThe scattering induced by surface topographies of arbitrary shapes, submitted to horizontally polarized shear waves (SH) is studied analytically. In particular, we propose an analysis technique based on a representation of the scattered field like the superposition of incident, reflected and diffracted rays. The diffraction contribution is the result of the interaction of the incident and reflectedwaves, with the geometric singularities present in the surface topography. This splitting of the solution into different terms, makes the difference between our method and alternative numerical/analytical approaches, where the complete field is described by a single term. The contribution from the incident and reflected fields is considered using standard techniques, while the diffracted field is obtained using the idea of a ray as was introduced by the geometrical theory of diffraction. Our final solution however, is an approximation in the sense that, surface-diffracted rays are neglected while we retain the contribution from corner-diffracted rays and its further diffraction. These surface rays are only present when the problem has smooth boundaries combined with shadow zones, which is far from being the typical scenario in far-field earthquake engineering. The proposed technique was tested in the study of a combined hill-canyon topography and the results were compared with those of a boundary element algorithm. After considering only secondary sources of diffraction, a difference of 0.09 per cent (with respect to the incident field amplitude) was observed. The proposed analysis technique can be used in the interpretation of numerical and experimental results and in the preliminary prediction of the response in complex topographies. © The Authors 2012. Published by Oxford University Press on behalf of The Royal Astronomical Society.Ítem A computationally efficient method for delineating irregularly shaped spatial clusters(Springer Berlin Heidelberg, 2011-12-01) Duque, Juan C.; Aldstadt, Jared; Velasquez, Ermilson; Franco, Jose L.; Betancourt, Alejandro; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)In this paper, we present an efficiency improvement for the algorithm called AMOEBA, A Multidirectional Optimum Ecotope-Based Algorithm, devised by Aldstadt and Getis (Geogr Anal 38(4):327-343, 2006). AMOEBA embeds a local spatial autocorrelation statistic in an iterative procedure in order to identify spatial clusters (ecotopes) of related spatial units. We provide an analysis of the computational complexity of the original AMOEBA and develop an alternative formulation that reduces computational time without losing optimality. Empirical evidence is provided using georeferenced socio-demographic data in Accra, Ghana. © 2010 Springer-Verlag.Ítem Drug dosage individualization based on a random-effects linear lodel(TAYLOR & FRANCIS INC, 2012-01-01) Diaz, Francisco J.; Cogollo, Myladis R.; Spina, Edoardo; Santoro, Vincenza; Rendon, Diego M.; de Leon, Jose; Universidad EAFIT. Escuela de Ciencias; Modelado MatemáticoThis article investigates drug dosage individualization when the patient population can be described with a random-effects linear model of a continuous pharmacokinetic or pharmacodynamic response. Specifically, we show through both decision-theoretic arguments and simulations that a published clinical algorithm may produce better individualized dosages than some traditional methods of therapeutic drug monitoring. Since empirical evidence suggests that the linear model may adequately describe drugs and patient populations, and linear models are easier to handle than the nonlinear models traditionally used in population pharmacokinetics, our results highlight the potential applicability of linear mixed models to dosage computations and personalized medicine. Copyright © Taylor & Francis Group, LLC.Ítem 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 MatemáticoPressure 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.Ítem Nuevas formas de la escucha: audífonos con sonido tridimensional(2020-12-01) Martinez Guerrero, Christian Alexander; Christian Alexander Martinez-Guerrero; Tarzan, Ali; Alunno, Marco; Bientinesi, Paolo; Vicerrectoría de Descubrimiento y CreaciónÍtem 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 MatemáticoThe 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.Ítem Shack-Hartmann centroid detection using the spiral phase transform(OSA - The Optical Society of America, 2012-01-01) Vargas, J.; Restrepo, R.; Estrada, J.C.; Sorzano, C.O.S.; Du, Y.-Z.; Carazo, J.M.; Universidad EAFIT. Departamento de Ciencias Básicas; Óptica AplicadaWe present a Shack-Hartmann (SH) centroid detection algorithm capable to measure in presence of strong noise, background illumination and spot modulating signals, which are typical limiting factors of traditional centroid detection algorithms. The proposed method is based on performing a normalization of the SH pattern using the spiral phase transform method and Fourier filtering. The spot centroids are then obtained using global thresholding and weighted average methods. We have tested the algorithm with simulations and experimental data obtaining satisfactory results. A complete MATLAB package that can reproduce all the results can be downloaded from [http://goo.gl/o2JhD]. © 2012 Optical Society of America.Ítem Shack-Hartmann spot dislocation map determination using an optical flow method(OPTICAL SOC AMER, 2014-01-27) Vargas, J.; Restrepo, R.; Belenguer, T.; Universidad EAFIT. Departamento de Ciencias Básicas; Óptica AplicadaWe present a robust, dense, and accurate Shack-Hartmann spot dislocation map determination method based on a regularized optical flow algorithm that does not require obtaining the spot centroids. The method is capable to measure in presence of strong noise, background illumination and spot modulating signals, which are typical limiting factors of traditional centroid detection algorithms. Moreover, the proposed approach is able to face cases where some of the reference beam spots have not a corresponding one in the distorted Hartmann diagram, and it can expand the dynamic range of the Shack-Hartmann sensor unwrapping the obtained dense dislocation maps. We have tested the algorithm with both simulations and experimental data obtaining satisfactory results. A complete MATLAB package that can reproduce all the results can be downloaded from [http://goo.gl/XbZVOr]. © 2014 Optical Society of America.Ítem A unified model framework for the multiattribute consistent periodic vehicle routing problem(Public Library of Science, 2020-01-01) Baldoquin M.G.; Martine J.A.; Diaz-Ramirez J.; Baldoquin M.G.; Martine J.A.; Diaz-Ramirez J.; Universidad EAFIT. Departamento de Ciencias; Matemáticas y AplicacionesModeling real-life transportation problems usually require the simultaneous incorporation of different variants of the classical vehicle routing problem (VRP). The periodic VRP (PVRP) is a classical extension in which routes are determined for a planning period of several days and each customer has an associated set of allowable visit schedules. This work proposes a unified model framework for PVRP that consists of multiple attributes or variants not previously addressed simultaneously, such as time-windows, time-dependence, and consistency-which guarantees the visits to customer by the same vehicle-, together with three objective functions that respond to the needs of practical problems. The numerical experimentation is focused on the effects of three factors: frequency, depot centrality, and the objective function on the performance of a general-purpose MILP solver, through the analysis of the achieved relative gaps. Results show higher sensitivity to the objective functions and to the problem sizes. © 2020 Baldoquin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Ítem Unsupervised fuzzy binning of metagenomic sequence fragments on three-dimensional Barnes-Hut t-Stochastic Neighbor Embeddings(Institute of Electrical and Electronics Engineers Inc., 2018-01-01) Ariza-Jimenez L.; Quintero O.L.; Pinel N.; Universidad EAFIT. Departamento de Ciencias; Ciencias Biológicas y Bioprocesos (CIBIOP)Shotgun metagenomic studies attempt to reconstruct population genome sequences from complex microbial communities. In some traditional genome demarcation approaches, high-dimensional sequence data are embedded into two-dimensional spaces and subsequently binned into candidate genomic populations. One such approach uses a combination of the Barnes-Hut approximation and the t -Stochastic Neighbor Embedding (BH-SNE) algorithm for dimensionality reduction of DNA sequence data pentamer profiles; and demarcation of groups based on Gaussian mixture models within humanimposed boundaries. We found that genome demarcation from three-dimensional BH-SNE embeddings consistently results in more accurate binnings than 2-D embeddings. We further addressed the lack of a priori population number information by developing an unsupervised binning approach based on the Subtractive and Fuzzy c-means (FCM) clustering algorithms combined with internal clustering validity indices. Lastly, we addressed the subject of shared membership of individual data objects in a mixed community by assigning a degree of membership to individual objects using the FCM algorithm, and discriminated between confidently binned and uncertain sequence data objects from the community for subsequent biological interpretation. The binning of metagenome sequence fragments according to thresholds in the degree of membership opens the door for the identification of horizontally transferred elements and other genomic regions of uncertain assignment in which biologically meaningful information resides. The reported approach improves the unsupervised genome demarcation of populations within complex communities, increases the confidence in the coherence of the binned elements, and enables the identification of evolutionary processes ignored in hard-binning approaches in shotgun metagenomic studies. © 2018 IEEE.Ítem Unsupervised fuzzy binning of metagenomic sequence fragments on three-dimensional Barnes-Hut t-Stochastic Neighbor Embeddings(Institute of Electrical and Electronics Engineers Inc., 2018-01-01) Ariza-Jimenez L.; Quintero O.L.; Pinel N.; Universidad EAFIT. Departamento de Ciencias; Biodiversidad, Evolución y ConservaciónShotgun metagenomic studies attempt to reconstruct population genome sequences from complex microbial communities. In some traditional genome demarcation approaches, high-dimensional sequence data are embedded into two-dimensional spaces and subsequently binned into candidate genomic populations. One such approach uses a combination of the Barnes-Hut approximation and the t -Stochastic Neighbor Embedding (BH-SNE) algorithm for dimensionality reduction of DNA sequence data pentamer profiles; and demarcation of groups based on Gaussian mixture models within humanimposed boundaries. We found that genome demarcation from three-dimensional BH-SNE embeddings consistently results in more accurate binnings than 2-D embeddings. We further addressed the lack of a priori population number information by developing an unsupervised binning approach based on the Subtractive and Fuzzy c-means (FCM) clustering algorithms combined with internal clustering validity indices. Lastly, we addressed the subject of shared membership of individual data objects in a mixed community by assigning a degree of membership to individual objects using the FCM algorithm, and discriminated between confidently binned and uncertain sequence data objects from the community for subsequent biological interpretation. The binning of metagenome sequence fragments according to thresholds in the degree of membership opens the door for the identification of horizontally transferred elements and other genomic regions of uncertain assignment in which biologically meaningful information resides. The reported approach improves the unsupervised genome demarcation of populations within complex communities, increases the confidence in the coherence of the binned elements, and enables the identification of evolutionary processes ignored in hard-binning approaches in shotgun metagenomic studies. © 2018 IEEE.Ítem Unsupervised fuzzy binning of metagenomic sequence fragments on three-dimensional Barnes-Hut t-Stochastic Neighbor Embeddings(Institute of Electrical and Electronics Engineers Inc., 2018-01-01) Ariza-Jimenez L.; Quintero O.L.; Pinel N.; Universidad EAFIT. Escuela de Ciencias; Modelado MatemáticoShotgun metagenomic studies attempt to reconstruct population genome sequences from complex microbial communities. In some traditional genome demarcation approaches, high-dimensional sequence data are embedded into two-dimensional spaces and subsequently binned into candidate genomic populations. One such approach uses a combination of the Barnes-Hut approximation and the t -Stochastic Neighbor Embedding (BH-SNE) algorithm for dimensionality reduction of DNA sequence data pentamer profiles; and demarcation of groups based on Gaussian mixture models within humanimposed boundaries. We found that genome demarcation from three-dimensional BH-SNE embeddings consistently results in more accurate binnings than 2-D embeddings. We further addressed the lack of a priori population number information by developing an unsupervised binning approach based on the Subtractive and Fuzzy c-means (FCM) clustering algorithms combined with internal clustering validity indices. Lastly, we addressed the subject of shared membership of individual data objects in a mixed community by assigning a degree of membership to individual objects using the FCM algorithm, and discriminated between confidently binned and uncertain sequence data objects from the community for subsequent biological interpretation. The binning of metagenome sequence fragments according to thresholds in the degree of membership opens the door for the identification of horizontally transferred elements and other genomic regions of uncertain assignment in which biologically meaningful information resides. The reported approach improves the unsupervised genome demarcation of populations within complex communities, increases the confidence in the coherence of the binned elements, and enables the identification of evolutionary processes ignored in hard-binning approaches in shotgun metagenomic studies. © 2018 IEEE.Ítem Upper limb posture estimation in robotic and virtual reality-based rehabilitation(HINDAWI PUBLISHING CORPORATION, 2014-07-08) Cortés C; Ardanza A; Molina-Rueda F; Cuesta-Gómez A; Unzueta L; Epelde G; Ruiz OE; De Mauro A; Florez J; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAENew motor rehabilitation therapies include virtual reality (VR) and robotic technologies. In limb rehabilitation, limb posture is required to (1) provide a limb realistic representation in VR games and (2) assess the patient improvement. When exoskeleton devices are used in the therapy, the measurements of their joint angles cannot be directly used to represent the posture of the patient limb, since the human and exoskeleton kinematic models differ. In response to this shortcoming, we propose a method to estimate the posture of the human limb attached to the exoskeleton. We use the exoskeleton joint angles measurements and the constraints of the exoskeleton on the limb to estimate the human limb joints angles. This paper presents (a) the mathematical formulation and solution to the problem, (b) the implementation of the proposed solution on a commercial exoskeleton system for the upper limb rehabilitation, (c) its integration into a rehabilitation VR game platform, and (d) the quantitative assessment of the method during elbow and wrist analytic training. Results show that this method properly estimates the limb posture to (i) animate avatars that represent the patient in VR games and (ii) obtain kinematic data for the patient assessment during elbow and wrist analytic rehabilitation. © 2014 Camilo Cortés et al.Ítem Vortex-enhanced coherent-illumination phase diversity for phase retrieval in coherent imaging systems(OSA - The Optical Society, 2016-04-15) Echeverri-Chacón, S.; Restrepo, R.; Cuartas-Vélez, C.; Uribe-Patarroyo, N.; Universidad EAFIT. Departamento de Ciencias Básicas; Óptica AplicadaWe propose a phase-retrieval method based on the numerical optimization of a new objective function using coherent phase-diversity images as inputs for the characterization of aberrations in coherent imaging systems. By employing a spatial light modulator to generate multiple-order spiral phase masks as diversities, we obtain an increase in the accuracy of the retrieved phase compared with similar state-of-the-art phase-retrieval techniques that use the same number of input images. We present simulations that show a consistent advantage of our technique, and experimental validation where our implementation is used to characterize a highly aberrated 4F optical system. (C) 2016 Optical Society of AmericaÍtem Y tú, ¿qué escuchas? Investigación EAFIT estudia el sonido en los audífonos(2020-12-01) Martinez Guerrero, Christian Alexander; Christian Alexander Martinez-Guerrero; Tarzan, Ali; Alunno, Marco; Bientinesi, Paolo; Estudios Musicales