This page has only limited features, please log in for full access.

Unclaimed
Manuel Utrilla Manso
Department of Signal Theory and Communications, Polytechnic School, University of Alcalá, 28871 Alcalá de Henares, Spain

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 09 August 2021 in Applied Sciences
Reads 0
Downloads 0

Acoustic analysis of materials is a common non-destructive technique, but most efforts are focused on the ultrasonic range. In the audible range, such studies are generally devoted to audio engineering applications. Ultrasonic sound has evident advantages, but also severe limitations, like penetration depth and the use of coupling gels. We propose a biomimetic approach in the audible range to overcome some of these limitations. A total of 364 samples of water and fructose solutions with 28 concentrations between 0 g/L and 9 g/L have been analyzed inside an anechoic chamber using audible sound configurations. The spectral information from the scattered sound is used to identify and discriminate the concentration with the help of an improved grouping genetic algorithm that extracts a set of frequencies as a classifier. The fitness function of the optimization algorithm implements an extreme learning machine. The classifier obtained with this new technique is composed only by nine frequencies in the (3–15) kHz range. The results have been obtained over 20,000 independent random iterations, achieving an average classification accuracy of 98.65% for concentrations with a difference of ±0.01 g/L.

ACS Style

Pilar García Díaz; Manuel Utrilla Manso; Jesús Alpuente Hermosilla; Juan Martínez Rojas. Study of the Optimal Waveforms for Non-Destructive Spectral Analysis of Aqueous Solutions by Means of Audible Sound and Optimization Algorithms. Applied Sciences 2021, 11, 7301 .

AMA Style

Pilar García Díaz, Manuel Utrilla Manso, Jesús Alpuente Hermosilla, Juan Martínez Rojas. Study of the Optimal Waveforms for Non-Destructive Spectral Analysis of Aqueous Solutions by Means of Audible Sound and Optimization Algorithms. Applied Sciences. 2021; 11 (16):7301.

Chicago/Turabian Style

Pilar García Díaz; Manuel Utrilla Manso; Jesús Alpuente Hermosilla; Juan Martínez Rojas. 2021. "Study of the Optimal Waveforms for Non-Destructive Spectral Analysis of Aqueous Solutions by Means of Audible Sound and Optimization Algorithms." Applied Sciences 11, no. 16: 7301.

Journal article
Published: 16 August 2018 in Sensors
Reads 0
Downloads 0

A new haptic sensor that is based on vibration produced by mechanical excitation from a clock coupled to a resonant cavity is presented. This sensor is intended to determine the chemical composition of liquid mixtures in a completely non-destructive method. In this case, a set of 23 samples of water, ethanol, and fructose mixtures has been used to simulate different kinds of alcoholic beverage. The spectral information from the vibrational absorption bands of liquid samples is analyzed by a Grouping Genetic Algorithm. An Extreme Learning Machine implements the fitness function that is able to classify the mixtures according to the concentration of ethanol and fructose. The 23 samples range from 0%–13% by volume of ethanol and from 0–3 g/L of fructose, all of them with different concentration. The new technique achieves an average classification accuracy of 96%.

ACS Style

Pilar García Díaz; Juan Antonio Martínez Rojas; Manuel Utrilla Manso; Leticia Monasterio Expósito. Analysis of Water, Ethanol, and Fructose Mixtures Using Nondestructive Resonant Spectroscopy of Mechanical Vibrations and a Grouping Genetic Algorithm. Sensors 2018, 18, 2695 .

AMA Style

Pilar García Díaz, Juan Antonio Martínez Rojas, Manuel Utrilla Manso, Leticia Monasterio Expósito. Analysis of Water, Ethanol, and Fructose Mixtures Using Nondestructive Resonant Spectroscopy of Mechanical Vibrations and a Grouping Genetic Algorithm. Sensors. 2018; 18 (8):2695.

Chicago/Turabian Style

Pilar García Díaz; Juan Antonio Martínez Rojas; Manuel Utrilla Manso; Leticia Monasterio Expósito. 2018. "Analysis of Water, Ethanol, and Fructose Mixtures Using Nondestructive Resonant Spectroscopy of Mechanical Vibrations and a Grouping Genetic Algorithm." Sensors 18, no. 8: 2695.

Journal article
Published: 01 June 2007 in Pattern Recognition and Image Analysis
Reads 0
Downloads 0

In this paper different methods applied to the Automatic Target Recognition problem are studied. A database of High Range Resolution radar profiles of six kinds of aircrafts is used to study the performance of four classification methods: k-Nearest Neighbor method, Multilayer Perceptrons, Radial Basis Function Networks, and Support Vector Machines. Results obtained with these classifiers show a high correlation between two of the classes of targets that cause the majority of errors. We propose to split the task into two subtasks. A first one in which the classes of correlated targets are grouped in a single class, and a second one to distinguish between them. Different classifiers are studied to be applied to each subtask. Results demonstrate that Radial Basis Function Networks are very good classifiers for the main subtask, while Support Vector Machines are the best classification method, among the studied, to distinguish between the correlated targets.

ACS Style

Roberto Gil-Pita; P. Jarabo-Amores; Manuel Rosa-Zurera; F. Lopez-Ferreras; M. Utrilla-Manso. Divide and conquer approach to improve performance on ATR systems. Pattern Recognition and Image Analysis 2007, 17, 284 -291.

AMA Style

Roberto Gil-Pita, P. Jarabo-Amores, Manuel Rosa-Zurera, F. Lopez-Ferreras, M. Utrilla-Manso. Divide and conquer approach to improve performance on ATR systems. Pattern Recognition and Image Analysis. 2007; 17 (2):284-291.

Chicago/Turabian Style

Roberto Gil-Pita; P. Jarabo-Amores; Manuel Rosa-Zurera; F. Lopez-Ferreras; M. Utrilla-Manso. 2007. "Divide and conquer approach to improve performance on ATR systems." Pattern Recognition and Image Analysis 17, no. 2: 284-291.

Conference paper
Published: 01 January 2005 in Computer Vision
Reads 0
Downloads 0

The work presented in this paper suggests a Traffic Sign Recognition (TSR) system whose core is based on a Multilayer Perceptron (MLP). A pre-processing of the traffic sign image (blob) is applied before the core. This operation is made to reduce the redundancy contained in the blob, to reduce the computational cost of the core and to improve its performance. For comparison purposes, the performance of the a statistical method like the k-Nearest Neighbour (k-NN) is included. The number of hidden neurons of the MLP is studied to obtain the value that minimizes the total classification error rate. Once obtained the best network size, the results of the experiments with this parameter show that the MLP achieves a total error probability of 3.85%, which is almost the half of the best obtained with the k-NN.

ACS Style

R. Vicen-Bueno; R. Gil-Pita; M. Rosa-Zurera; M. Utrilla-Manso; F. Lopez-Ferreras. Multilayer Perceptrons Applied to Traffic Sign Recognition Tasks. Computer Vision 2005, 865 -872.

AMA Style

R. Vicen-Bueno, R. Gil-Pita, M. Rosa-Zurera, M. Utrilla-Manso, F. Lopez-Ferreras. Multilayer Perceptrons Applied to Traffic Sign Recognition Tasks. Computer Vision. 2005; ():865-872.

Chicago/Turabian Style

R. Vicen-Bueno; R. Gil-Pita; M. Rosa-Zurera; M. Utrilla-Manso; F. Lopez-Ferreras. 2005. "Multilayer Perceptrons Applied to Traffic Sign Recognition Tasks." Computer Vision , no. : 865-872.

Conference paper
Published: 01 January 2005 in Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics
Reads 0
Downloads 0
ACS Style

M. Utrilla-Manso; R. Jimenez-Martinez; R. Mallol-Poyato; J. Sánchez-Golmayo; F. Lopez-Ferreras. A COMPUTER ORIENTED ALGORITHM FOR ANALYZING LIMIT CYCLES IN DISCRETE CONTROL SYSTEMS. Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics 2005, 155 -160.

AMA Style

M. Utrilla-Manso, R. Jimenez-Martinez, R. Mallol-Poyato, J. Sánchez-Golmayo, F. Lopez-Ferreras. A COMPUTER ORIENTED ALGORITHM FOR ANALYZING LIMIT CYCLES IN DISCRETE CONTROL SYSTEMS. Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics. 2005; ():155-160.

Chicago/Turabian Style

M. Utrilla-Manso; R. Jimenez-Martinez; R. Mallol-Poyato; J. Sánchez-Golmayo; F. Lopez-Ferreras. 2005. "A COMPUTER ORIENTED ALGORITHM FOR ANALYZING LIMIT CYCLES IN DISCRETE CONTROL SYSTEMS." Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics , no. : 155-160.