Fernando Auat Cheein

Harper Adams University

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Miguel Torres‐Torriti

Pontificia Universidad Católica de Chile

Ricardo Carelli

National University of San Juan

Teodiano Bastos-Filho

Universidade Federal do Espírito Santo

Juan Villacrés

University of California, Davis

Javier Guevara

Federico Santa María Technical University

Michelle Viscaíno

Federico Santa María Technical University

Eduard Gregorio

Universitat de Lleida

Joan R. Rosell-Polo

Universitat de Lleida

Oswaldo Menéndez

Universidad Católica del Norte

Andrés Fuentes

Federico Santa María Technical University

Cooperative Institutions

Federico Santa María Technical University

National University of San Juan

University of Chile

Pontificia Universidad Católica de Chile

Universidade Federal do Espírito Santo

National Polytechnic School

Universidad Técnica Federico Santa María

Consejo Nacional de Investigaciones Científicas y Técnicas

Universitat Politècnica de Catalunya

Universitat de Lleida

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Assessment of Triboelectric Nanogenerators for Electric Field Energy Harvesting

Sensors (2024)

Oswaldo Menéndez Juan Villacrés Alvaro Prado Juan Pablo Vásconez Fernando Auat Cheein

Electric-field energy harvesters (EFEHs) have emerged as a promising technology for harnessing the electric field surrounding energized environments. Current research indicates that EFEHs are closely associated with Tribo-Electric Nano-Generators (TENGs). However, the performance of TENGs in energized environments remains unclear. This work aims to evaluate the performance of TENGs in electric-field energy harvesting applications. For this purpose, TENGs of different sizes, operating in single-electrode mode were conceptualized, assembled, and experimentally tested. Each TENG was mounted on a 1.5 HP single-phase induction motor, operating at nominal parameters of 8 A, 230 V, and 50 Hz. In addition, the contact layer was mounted on a linear motor to control kinematic stimuli. The TENGs successfully induced electric fields and provided satisfactory performance to collect electrostatic charges in fairly variable electric fields. Experimental findings disclosed an approximate increase in energy collection ranging from 1.51% to 10.49% when utilizing TENGs compared to simple EFEHs. The observed correlation between power density and electric field highlights TENGs as a more efficient energy source in electrified environments compared to EFEHs, thereby contributing to the ongoing research objectives of the authors.

Mechanical energy

Electrostatic induction

Electric potential energy

10.3390/s24082507

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Retrieval of Vegetation Indices Related to Leaf Water Content from a Single Index: A Case Study of Eucalyptus globulus (Labill.) and Pinus radiata (D. Don.)

Plants (2021)

Juan Villacrés Andrés Fuentes Pedro Reszka Fernando Auat Cheein

The vegetation indices derived from spectral reflectance have served as an indicator of vegetation’s biophysical and biochemical parameters. Some of these indices are capable of characterizing more than one parameter at a time. This study examines the feasibility of retrieving several spectral vegetation indices from a single index under the assumption that all these indices are correlated with water content. The models used are based on a linear regression adjusted with least squares. The spectral signatures of Eucalyptus globulus and Pinus radiata, which constitute 97.5% of the forest plantation in Valparaiso region in Chile, have been used to test and validate the proposed approach. The linear models were fitted with an independent data set from which their performance was assessed. The results suggest that from the Leaf Water Index, other spectral indices can be recovered with a root mean square error up to 0.02, a bias of 1.12%, and a coefficient of determination of 0.77. The latter encourages using a sensor with discrete wavelengths instead of a continuum spectrum to estimate the forestry’s essential parameters.

Eucalyptus globulus

Pinus radiata

Radiata

Spectral index

10.3390/plants10040697

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Methodology for the Quantitative Risk Analysis of Wildfires in the Wildland-Urban Interface: Application to Electrical Infrastructure

Imprensa da Universidade de Coimbra eBooks (2022)

G. Severino Andrés Fuentes Alejandro Valdivia Fernando Auat Cheein Pedro Reszka

Wildfires have caused significant damage in Chile in the last decade, with electrical infrastructure being particularly vulnerable to extreme wildfire events. Therefore, the objective of this work is to estimate the risk of a wildfire damaging an electrical substation operated by the Chilean company Chilquinta DistribuciÃ³n SA, located in the Wildland-Urban Interface (WUI) of the city of Valparaiso, Chile. A Wildfire Quantitative Risk Analysis (WFQRA) framework is proposed for this purpose, where the quantification of risk results from the product between the probability of a wildfire reaching the WUI and its consequences. The former was determined with an event tree analysis, a tool in which the advance in time of the initiating event (ignition of a wildland fuel) was analyzed through a series of questions related to the area burned, wind direction and ranges of ambient temperature and wind speed, with answers of the type yes or no. This anaylsis gave 0.004 events/year as the probability of a wildfire reaching the WUI. On the other hand, the analysis of consequences requires determining the vulnerability of the object of study to a thermal insult, which is the quantitative relationship between the thermal exposure of the object to the fire and the damage experienced by it. This vulnerability was assessed by expressing it in terms of a probability of failure (ignition) for different doses of thermal radiation, i.e., a dose-response curve. Since these curves are typically of sigmoid shape, a novel probit equation was determined by analyzing experimental data of PMMA, a material that served as a proxy for the actual materials within the electrical substation. Thermal exposure of a target within the substation was calculated with an average fireline intensity (1832 kW/m) and flame length (3.98 m) obtained with FlamMap simulations of fire behavior in a simplified landscape representing the study area. With these results, the vulnerability model for PMMA developed in this work gave PMMA ignition probabilities of 0.029 and 0.269 for two wildfire scenarios considered in the substation. Finally, wildfire risk was estimated as 10-4 to 10-3 events/year, or equivalently, one event every 1,000 to 10,000 years. These results can be used as input to the decision-making process in Chilquinta and public institutions for taking mitigation measures to reduce wildfire risk in the WUI. Future work will be focused on refining this result.

Vulnerability

Wildland–urban interface

10.14195/978-989-26-2298-9_143

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A two-stage deep learning strategy for weed identification in grassfields

Computers and Electronics in Agriculture (2024)

Felipe Calderara-Cea Miguel Torres‐Torriti Fernando Auat Cheein José Delpiano

Identification

10.1016/j.compag.2024.109300

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Yield prediction of root crops in field using remote sensing: A comprehensive review

Computers and Electronics in Agriculture (2024)

Hanhui Jiang Liguo Jiang Leilei He Bryan Gilbert Murengami Xudong Jing

Root (linguistics)

10.1016/j.compag.2024.109600

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Ear imagery database

Figshare (2020)

Michelle Viscaíno Fernando Auat Cheein

Database of external and middle ear conditions:
Earwax plugMyringosclerosisChronic otitis mediaNormal ear
Total images: 880
Validated by ENT specialist

10.6084/m9.figshare.11886630

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Analyzing the Capabilities of Electric Field Energy Harvesting Using Natural Leaves

IEEE Access (2021)

Oswaldo Menéndez Juan Villacrés Robert Guamán-Rivera Fernando Auat Cheein

Electric field energy harvesters (EFEHs) are reliable and sustainable power sources that may be used to power wireless sensor nodes (WSNs) in urban Internet of Things (IoT) networks, replacing traditional batteries. However, the large-scale deployments begin to pose significant environmental concerns regarding fabrication material degradation and recycling. In this context, this work analyses the performance of the natural green leaves as a replacement for standard electrodes in EFEH developments. To this end, different 10×3 cm2 EFEHs were assembled with raw leaves from the following species Magnolia Obovata, Ravenala Madagascariensis, Acanthus Mollis, and Agapanthus Africanus. Each harvester was evaluated at different drying steps, concluding that natural leaves may collect electrostatic charges related to the urban electric field, which might power ultra-low-energy devices. Experimental results reveal that Agapanthus Africanus electrodes perform best, with an open-circuit voltage (VOC) of 111.88 V and a short-circuit current (ISC) of 229.09 nA. On the other hand, the VOC of Magnolia Obavata leaves achieved 76.76 V, and the ISC was 135.30 nA (the worst case). Although the performance for Ravenala Madagascariensis samples is less than Agapanthus Africanus ones, the size leaf is another critical parameter to design functional devices. Therefore, the experimental section also includes the conceptualization, design, and experimental testing of a functional EFEH prototype called Leaf-EFEH, which is assembled with Ravenala Madagascariensis leaves. Finally, numerous experiments have shown that the proposed Leaf-EFEH can power ultra-low-power devices.

10.1109/access.2021.3129717

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Citations (4)

Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions

World Journal of Gastroenterology (2021)

Michelle Viscaíno Javier Torres Bustos P. Gomis Muñoz Cecilia Auat Cheein Fernando Auat Cheein

Colorectal cancer (CRC) was the second-ranked worldwide type of cancer during 2020 due to the crude mortality rate of 12.0 per 100000 inhabitants.It can be prevented if glandular tissue (adenomatous polyps) is detected early.Colonoscopy has been strongly recommended as a screening test for both early cancer and adenomatous polyps.However, it has some limitations that include the high polyp miss rate for smaller (< 10 mm) or flat polyps, which are easily missed during visual inspection.Due to the rapid advancement of technology, artificial intelligence (AI) has been a thriving area in different fields, including medicine.Particularly, in gastroenterology AI software has been included in computer-aided systems for diagnosis and to improve the assertiveness of automatic polyp detection and its classification as a preventive method for CRC.This article provides an overview of recent research focusing on AI tools and their applications in the early detection of CRC and adenomatous polyps, as well as an insightful analysis of the main advantages and misconceptions in the field.

Adenomatous polyps

Polypectomy

10.3748/wjg.v27.i38.6399

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Citations (32)

3D Spectral Graph Wavelet Point Signatures in Pre-Processing Stage for Mobile Laser Scanning Point Cloud Registration in Unstructured Orchard Environments

IEEE Sensors Journal (2021)

Javier Guevara Jordi Gené-Mola Eduard Gregorio Fernando Auat Cheein

The use of three-dimensional registration techniques is an important component for sensor-based localization and mapping. Several approaches have been proposed to align three-dimensional data, obtaining meaningful results in structured scenarios. However, the increased use of high-frame-rate 3D sensors has lead to more challenging application scenarios where the performance of registration techniques may degrade significantly. In order to improve the accuracy of the procedure, different works have considered a representative subset of points while preserving application-dependent features for registration. In this work, we tackle such a problem, considering the use of a general feature-extraction operator in the spectral domain as a prior step to the registration. The proposed spectral strategies use three wavelet transforms that are evaluated along with four well-known registration techniques. The methodology was experimentally validated in a dense orchard environment. The results show that the probability of failure in registration can be reduced up to 12.04% for the evaluated approaches, leading to a significant increase in the localization accuracy. Those results validate the effectiveness and efficiency of the spectral-assisted registration algorithms in an agricultural setting and motivate their usage for a wider range of applications.

Image registration

10.1109/jsen.2021.3129340

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Diseño e Implementación de un Sistema de Localización y Mapeo Simultáneos (SLAM) para la Plataforma Robótica ROBOTINO

Revista Politécnica (2014)

Victor Patricio Díaz Narváez Francisco Yandún David Pozo Luis Morales Jorge Rosero

En el presente documento se presenta el desarrollo e implementacion en MATLAB de un algoritmo de SLAM para un robot movil comercial, operando en entornos estructurados estaticos, cuya localizacion esta dada por la odometria del robot y el modelo del mismo. Para la realizacion del mapeo se utiliza el sensor de rango laser Hokuyo URG-04LX; una vez obtenido el mapa se implementa un algoritmo capaz de detectar esquinas dentro del entorno, con el fin de que puedan ser utilizadas en futuras aplicaciones de SLAM donde sea necesario la inclusion de “landmarks” o caracteristicas de entorno. Para atenuar los errores en posicionamiento inherentes a la odometria propia del robot se implementa un Filtro Extendido de Kalman entre la odometria y el modelo omnidireccional del robot movil, en base a lo cual se obtienen mejores resultados para la localizacion. La deteccion de esquinas se realiza usando la Transformada de Hough, algoritmo mediante el cual se identifica lineas presentes en el mapa y posteriormente se halla esquinas como un cruce entre dos lineas. Se presentan los resultados como un analisis de los mapas obtenidos contrastados con los entornos reales, ademas del analisis de errores sobre la localizacion del robot. This paper presents the development and implementation of a Simultaneous Localization And Mapping (SLAM) algorithm for a commercial mobile robot, operating in structured and static environments. The location is given by the odometry of the robot and its model. To perform the mapping a sensor laser range Hokuyo URG - 04LX is used.Later, an algorithm capable of detecting corners in the environment is implemented, they can be used in future applications of SLAM where being necessary the inclusion of landmarks or characteristics of environment. To mitigate the position errors inherent to odometryof the robot is implemented an Extended Kalman Filter between the odometry and omnidirectional mobile robot model. This technique improves the results of localization. Corner's detection is performed using the Hough transform algorithm, which identifies lines on the map and subsequently corners like a cross between two lines. We present the results as an analysis of the obtained maps that include contrasts with the real environments. In addition,we analyze the location error of the robot.

10.33333/rp.v33i1.178

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Citations (2)