El grupo ha surgido en base a los investigadores de la Coordinación I y IV, I+D+i, de la Dirección de Investigación y Desarrollo Tecnológico DIDT, de la Unidad Ejecutora 002 – INICTEL-UNI.
Controlar la interacción onda-material a través de nuevas técnicas para diversas aplicaciones bajo diferentes regímenes espectrales.
El grupo ha logrado conseguir fondos externos durante los últimos años con contratos de equipamiento científico y proyectos de investigación aplicada con agencias como INNOVATE Peru, FONDECYT, PennState-PUCP-UNI, etc. En todas las lineas de investigación se tienen colaboraciones muy activas con universidades e instituciones a nivel internacional como: PennState University (US), Universidade Estadual de Campinas (BR), Oklahoma University (US), Columbia University (US), Universidad Politécnica de Valencia (ESP), etc. Cuenta además con una sólida red de colaboración con otras universidades del país, que permiten realizar actividades de fabricación y caracterización de los prototipos.
– Diseño de Antenas.
– Estudios de compatibilidad electromagnética
1. Collaborative research on design and realization of Tunable Metasurfaces for TeraHertz Applications. PennState University-UNI-PUCP Seed Fund, 2017.
2.Estudio de perfiles en el subsuelo mediante métodos de inversión y modelado electromagnético utilizando un geo radar de VHF aplicado a la zona arqueológica de Caral, INICTEL-UNI-The Oklahoma University-Zona Arqueologicade Caral, P. Investigacion Aplicada FONDECYT.
3.-Implementación de un medidor de porcentaje de absorción especifica de 30 hasta 6000MHz , INICTEL-UNI-UCH, P. Equipamiento Científico,INNOVATE PERU.
4.-Análisis de la contribución de las metasuperficies a la mejora del ancho de banda y ganancia de antenas para satélites pequeños , INICTEL-APSCO-CONIDA. Instituto de Investigación de la Facultad de Ingeniería Eléctrica y Electronica IIFIEE-UNI.
Articulos:
Mark Clemente-Arenas,Julio Urbina, Akhlesh Lakhtakia, Metasurfaces with thermal hysteresis, the International Conference on Electromagnetics in Advanced Applications (ICEAA 2018). Cartagena-Colombia, 10-14 set. 2018.
Ygnacio-Espinoza, D. Peñaloza-Aponte, J. Alvarez-Montoya, A. Quispe-Mesco and Mark Clemente-Arenas, Quasi-transparent andcircularly polarized patch antenna using Metamaterial Integrated to a solar cell for S-band CubeSat applications, the International Conference on Electromagnetics in Advanced Applications (ICEAA 2018). Cartagena-Colombia, 10-14 set. 2018.
Marco Antonio Pumallica Paro, Jorge Luis Arizaca Cusicuna and Mark Clemente Arenas, Optimizing Cutoff Frequency in an Antipodal Vivaldi Antenna for GPR applications trough a novel balun, Electronics, Electrical Engineering and Computing (INTERCON), 2018 IEEE XXV International Conference on.
Dennis Noel Arizaca Cusicuna, Jorge Luis Arizaca Cusicuna and Mark Donny Clemente Arenas, High Gain 4×4 Rectangular Patch Antenna Array at 28GHz for Future 5G Applications, Electronics, Electrical Engineering and Computing (INTERCON), 2018 IEEE XXV International Conference on.
Diego Peñaloza-Aponte, Mark Clemente-Arenas, Directivity Enhancement to Antipodal Vivaldi Antenna with Slot Edges Using Zero-Index Metamaterial for S-Band SAR Application, 12th European Conference on Antennas and Propagation (EUCAP 2018). Londres, Reino Unido, 9-14 Abril. 2018.
Diego Peñaloza-Aponte, Juan Alvarez-Montoya, Mark Clemente-Arenas , GPR vivaldi antenna with DGS for archeological prospection, Electronics, Electrical Engineering and Computing (INTERCON), 2017 IEEE XXIV International Conference on. Avalaible on DOI: 10.1109/INTERCON.2017.8079704.
CloudPeru
The CloudPeru dataset consists of 476,422 image patches labeled as ‘clouds’ or ‘non-clouds’, from which 207,963 are clouds and 268,459 non-clouds. These images were extracted from 15 different PERUSAT-1 scenes which were previously corrected to obtain surface reflectance products. Each image patch is size normalized to 27×27 pixels and has four channels: Red (0.63-0.7 μm), green (0.53-0.59 μm), blue (0.45-0.50 μm) and NIR (0.752-0.885 μm). The spatial resolution is 2.8 m per pixel. We split 95% of the data to create the training set, 2.5% to the validation set and 2.5% to the test set.
The dataset is encoded as an “.hdf5” file, which can be read from Matlab or from Python using the “h5py” library. It can be downloaded from here:
ShadowPeru
The ShadowPeru dataset consists of 400 image patches extracted from 20 different PERUSAT-1 scenes of variable area and from different geographies. Each image patch has a correspondent shadow mask, which was manually annotated. These scenes were were previously corrected to obtain surface reflectance products. The patches are size normalized to 256×256 pixels and have four channels: Red (0.63-0.7 μm), green (0.53-0.59 μm), blue (0.45-0.50 μm) and NIR (0.752-0.885 μm). The spatial resolution is 2.8 m per pixel. We split 90% of the data to create the training set, 5% to the validation set and 5% to the test set.
The dataset is encoded as an “.hdf5” file, which can be read from Matlab or from Python using the “h5py” library. It can be downloaded from here:
WoodSpeciesPeru
The WoodSpeciesPeru dataset consist of 46,000 image patches of seven wood species, which are labeled with indexes ranging from 0 to 6 that correspond to species Ceiba pentandra, Cariniana domestica, Swietenia macrophylla King, Ormosia coccinea, Aspidosperma macrocarpon, Dipteryx micrantha and Cedrelinga cateniformis, respectively. These images were extracted from 115 different samples of the transverse, radial and tangential sections of the wood acquired with a digital microscope CISNO.
Each image patch has a size of 128×128 pixels and a scale of 0.5mm per 100pixels. We split 70% of the data to create the training set, 15% for the validation set and 15% for the test set.
The dataset is encoded as an “.hdf5” file, wich can be read from matlab or from Python using “h5py” library. It can be downloaded from here:
Download WoodSpeciesPeru dataset
El III Taller Regional: “Tecnología para Mitigar los Efectos de Desastres Naturales”
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