Moya-Albor, Ernesto
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Moya-Albor, Ernesto
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Moya Albor, Ernesto
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emoya
Moya-Albor, E.
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55523223700
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J-1891-2019

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Development of an Electric Powered Assisted Cycle with a Heart Rate Sensor Control System

2023 , García Cedillo, Roberto , Martínez López, Diego , Martínez Quintana, Eduardo , Pérez Guerra, Andrea , Sánchez Henkel Moreno, Juan Pablo , Vega Hernández, José Manuel , Moya-Albor, Ernesto , Ponce, Hiram , Brieva, Jorge

In this paper, we present the development of an intelligent bicycle which will be able to help the user achieve a more efficient exercise routine via the control of a DC motor. This project was developed in several stages, from the approach of the system's functions to the components that would conform to it in order to achieve a detailed concept that can meet the requirements correctly. The sector of the population that motivated the realization of this project and to whom it is mainly directed are all those who cycle in Mexico City and find their routines inefficient. Through the use of this bicycle, which has a heart rate measurement system, it is possible to monitor it to regulate the intensity of the exercise. It will be made possible by incorporating a motor that is activated as soon as it detects an elevated heart rate, which may mean that the user requires assistance or has to stop the exercise altogether. The results provide evidence that assisting the user does indeed help reduce overexertion. © 2023 IEEE.

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Design of a Soft Gripper Hand for a Quadruped Robot

2023 , Benavente González, Javier , Poza, José , Robles, Jacobo , Ponce, Hiram , Brieva, Jorge , Moya-Albor, Ernesto

This work aims to solve a current balancing problem for a quadruped robot by proposing a soft gripper. The main problem for the project is the lack of modules to make a quadruped robot walk through tough environments, which is designed to help in accidents to look for people and maintenance in factories. Viable solutions for the main body were found with a look alike chameleon robot. With that premise, the goal for the chameleon robot is to have a capable of moving through difficult surfaces and to have enough movement so to get better results in the displacement. To fulfill this requirement, the proposed key idea presented here is to design a gripper capable of helping the main body to achieve difficult places being as safe as possible. Furthermore, the gripper is an actual module for the main robot, and should be easy to substitute and build, in case it is needed in other situations. Because of that, the gripper is designed with the help of soft robotics. Experimental results in lab show the effectiveness of the soft gripper. We anticipate this system will help the robot to use the force effectively through each step. © 2023 IEEE.

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A Computer Vision Approach to Terminus Movement Analysis of Viedma Glacier

2023 , Moya-Albor, Ernesto , Schwartzman, Armin , Brieva, Jorge , Pardo, Mauricio , Ponce, Hiram , Chávez-Domínguez, Rodrigo

In this paper, an automatic segmentation approach of the Viedma glacier terminus is proposed. The method uses multi-spectral images from the Landsat-5 satellite to determine the area of the glacier through computer vision techniques. The area of the glacier is estimated, and a linear model is fitted, obtaining a correlation of 0.968 between the measured area and a fit linear regression model. On the other hand, a bio-inspired optical flow estimation approach is used to calculate and visualize the displacement of the glacier through time. In addition, an analysis is performed between the temperature variation in the Southern Cone and the decrease of the glacier in the function of time. A linear trend (r2=0.95) shows that the analyzed area of the glacier has decreased by about 1.9% annually in the observation season. It reveals an inverse relationship between the change in the size of the glacier and global warming, showing that if the same conditions remain, the glacier's zone analyzed in this work would be close to its disappearance in around 70 years, the time lapse in which a global temperature increase of 1.24 oC would be reached. © 2023 IEEE.

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Towards the Distributed Wound Treatment Optimization Method for Training CNN Models: Analysis on the MNIST Dataset

2023 , Ponce, Hiram , Moya-Albor, Ernesto , Brieva, Jorge

Convolutional neural network (CNN) is a prominent algorithm in Deep Learning methods. CNN architectures have been used successfully to solve various problems in image processing, for example, segmentation, classification, and enhancement task. However, automatic search for suitable architectures and training parameters remain an open area of research, where metaheuristic algorithms have been used to fine-tuning the hyperparameters and learning parameters. This work presents a bio-inspired distributed strategy based on Wound Treatment optimization (WTO) for training the learning parameters of a LenNet CNN model fast and accurate. The proposed method was evaluated over the popular benchmark dataset MNIST for handwritten digit recognition. Experimental results showed an improvement of 36.87% in training time using the distributed WTO method compared to the baseline with a single learning agent, and the accuracy increases 4.69% more using the proposed method in contrast with the baseline. As this is a preliminary study towards the distributed WTO method for training CNN models, we anticipate this approach can be used in robotics, multi-agent systems, federated learning, complex optimization problems, and many others, where an optimization task is required to be solved fast and accurate. © 2023 IEEE.

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Modular IoT-based Automated Hydroponic System

2021 , Aranda, Manlio , Savage, Alejandra , San Roman, José Luis , Noguera, Luis , Ponce, Hiram , Brieva, Jorge , Moya-Albor, Ernesto

The growth of population and the rapid urbanization have demanded overproduction of food while reducing the water supply, increasing energy consumption, limiting the land, and augmenting the cost of food transportation. Moreover, overproduction comes with food waste and a negative impact on the ecosystem. As an alternative, urban farming has been proposed to mitigate this problem. It includes cultivating in rooftops and residential indoors. In this regard, this work proposes the development of an automatic modular and vertical hydroponic system capable to regulate the water flow, the artificial lights, and the pH of the water. The hydroponic system is made of modules which means the user can upgrade the system depending on the needs like higher production or space reconfiguration. Also, the hydroponic system implements Internet-of-Things to monitor and operate it remotely. A first prototype is presented, and the experimental results validate its potential applicability. © 2021 IEEE.

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A perceptive watermarking approach applied to COVID-19 imaging data

2020 , Gomez-Coronel, Sandra L. , Moya-Albor, Ernesto , Brieva, Jorge , Ponce, Hiram

This work presents a watermarking algorithm applied to medical images of COVID-19 patients. The principal objective is to protect the information of the patient using an imperceptible watermarking and to preserve its diagnose. Our technique is based on a perceptive approach to insert the watermark by decomposing the medical image using the Hermite transform. We use as watermark two image logos, including text strings to demonstrate that the watermark can contain relevant information of the patient. Some metrics were applied to evaluate the performance of the algorithm. Finally, we present some results about robustness with some attacks applied to watermark images. © 2020 SPIE

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Bio-inspired Optical Flow-based Autonomous Obstacle Avoidance Control

2019 , Moya-Albor, Ernesto , Gomez-Coronel, Sandra L. , Ponce, Hiram , Brieva, Jorge , Chávez Domínguez, Rodrigo , Guadarrama-Muñoz, Alexis E.

In this paper, we propose a new methodology for autonomous obstacle avoidance control using a bio-inspired optical flow estimation. The main difference with other methods is that we use an image model inspired by the human vision system to define the constraints in the optical flow formulation which includes a Hermite transform (HT) and a perceptive mask. We use a physical robot platform to test the control algorithm, where due to the structure of the chassis a forward, reverse and turn movements were defined. The robot has a RBG camera to capture images of the path and then calculate optical flow estimation. To define velocity and direction robot response we propose a fuzzy controller. Finally, we made some experiments to demonstrate the performance of control navigation, and how responds algorithm using HT and a perceptive mask. © 2019 IEEE.

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Distance Estimation Using a Bio-Inspired Optical Flow Strategy Applied to Neuro-Robotics

2018 , Ponce, Hiram , Brieva, Jorge , Moya-Albor, Ernesto

Movement detection and characterization of a 3D scene are relevant tasks in vision systems and particularly in robotic applications controlled by visual features. One of the challenges to characterize a 3D scene in navigation systems is the depth estimation. In contrast to classical approaches using visual based stereo systems, we propose a monocular distance estimation system using convolutional neural networks (CNN) and a bio-inspired optical flow approach as part of a neuro-robotic system. We train the CNN using optical flow visual features guided by ultrasonic sensor-based measures in a 3D scenario. The datasets used are available in: http://sites.google.com/up.edu.mx/robotflow/. Experimental results confirm that a monocular camera can be applie for controlling the robot navigation and obstacle avoidance.

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Vision-Based Autonomous Navigation with Evolutionary Learning

2020 , Moya-Albor, Ernesto , Ponce, Hiram , Brieva, Jorge , Coronel, Sandra L. , Chávez Domínguez, Rodrigo

In this paper, we propose a vision-based autonomous robotics navigation system, it uses a bio-inspired optical flow approach using the Hermite transform and a fuzzy logic controller, the input membership functions were tuned applying a distributed evolutionary learning based on social wound treatment inspired in the Megaponera analis ant. The proposed method was implemented in a virtual robotics system using the V-REP software and in communication con MATLAB. The results show that the optimization of the input fuzzy membership functions improves the navigation behavior against an empirical tuning of them. © 2020, Springer Nature Switzerland AG.

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Optical Flow-Hermite and Fuzzy Q-Learning Based Robotic Navigation Approach

2021 , Moya-Albor, Ernesto , Brieva, Jorge , Ponce, Hiram , Gomez-Coronel, Sandra L.

The present paper presents a bio-inspired optical flow approach to autonomous robotics navigation. It uses a Fuzzy Q-Learning (FQL) method to take decisions in an unknown environment through a reinforcement signal. The proposed method was implemented in a virtual robotics system using the V-REP software and in communication con MATLAB. The preliminary results show that the robot was able to navigate successfully in unknown environments. © 2021 IEEE.

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