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Arturo Mendez-Patino

Researcher at Instituto Tecnológico de Morelia

Publications -  7
Citations -  107

Arturo Mendez-Patino is an academic researcher from Instituto Tecnológico de Morelia. The author has contributed to research in topics: Smart grid & Transmission system. The author has an hindex of 2, co-authored 7 publications receiving 74 citations.

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Journal ArticleDOI

DSP-based arrhythmia classification using wavelet transform and probabilistic neural network

TL;DR: An arrhythmia classification method implemented on a Digital Signal Processing (DSP) platform intended for on-line, real-time ambulatory operation to classify eight heartbeat conditions is presented and suggests that the method and prototype presented may be suitable for being implemented on wearable sensing applications auxiliary for on theline,real-time diagnosis.
Journal ArticleDOI

Smart Grids en México: Situación actual, retos y propuesta de implementación

TL;DR: In this paper, a panorama general del estado que guardan las redes inteligentes in México, as well as the viabilidad de construir Micro Redes Eléctricas o Micro Grids (MGs), for proveer energía eléctrica a sectores de la sociedad no atendidos o para hacer más eficientes los servicios actuales.
Journal ArticleDOI

Impact of TCSC on Directionality of Traveling Waves to Locate Faults in Transmission Lines

TL;DR: An algorithm protection for power transmission lines, compensated with a Thyristor-Controlled Series Capacitor, capable of discriminating the directionality of traveling waves as well as detecting and locating eleven types of faults is presented.
Book ChapterDOI

Forecasting Electricity Consumption Using Weather Data in an Edge-Fog-Cloud Data Analytics Architecture

TL;DR: This work shows the implementation of a forecasting model considering weather data across the smart metering system infrastructure using and edge-fog-cloud architecture for data analytics.

Evaluation of Feedforward Artificial Neural Networks (ANN) to Adjust Soil Moisture Estimates Derived From Time Domain Reflectometry (TDR) Measurements Using Soil Temperature and Gravimetric Data

TL;DR: In this paper, the authors examined the performance of two feedforward Artificial Neural Networks (ANN) configurations, commonly used for data regression analysis, to adjust TDR soil moisture estimates using soil temperature and gravimetric data.