Comparison of Different Classifiers and the Majority Voting Rule for the Detection of Plum Fruits in Garden Conditions.

Razieh Pourdarbani Sajad Sabzi Mario Hernández Hernández José Luis Hernández-Hernández Ginés García_Mateos Davood Kalantari José Miguel Molina Martínez (2019)

Color segmentation is one of the most thoroughly studied problems in agricultural applications of remote image capture systems, since it is the key step in several different tasks, such as crop harvesting, site specific spraying, and targeted disease control under natural light. This paper studies and compares five methods to segment plum fruit images under ambient conditions at 12 different light intensities, and an ensemble method combining them. In these methods, several color features in different color spaces are first extracted for each pixel, and then the most e

ective features are selected using a hybrid approach of artificial neural networks and the cultural algorithm (ANN-CA). The features selected among the 38 defined channels were the b* channel of L*a*b*, and the color purity index, C*, from L*C*h. Next, fruit/background segmentation is performed using five classifiers: artificial neural network-imperialist competitive algorithm (ANN-ICA); hybrid artificial neural network-harmony search (ANN-HS); support vector machines (SVM); k nearest neighbors (kNN); and linear discriminant analysis (LDA). In the ensemble method, the final class for each pixel is determined using the majority voting method. The experiments showed that the correct classification rate for the majority voting method excluding LDA was 98.59%, outperforming the results of the constituent methods.

Article

remote sensing in agriculture artificial neural network hybridization environmental conditions majority voting plum segmentation INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ALIMENTOS

Classification of Cucumber Leaves Based on Nitrogen Content Using the Hyperspectral Imaging Technique and Majority Voting.

Sajad Sabzi Razieh Pourdarbani Mohammad Hossein Rohban Alejandro Fuentes_Penna José Luis Hernández-Hernández Mario Hernández Hernández (2021)

Improper usage of nitrogen in cucumber cultivation causes nitrate accumulation in the fruit and results in food poisoning in humans; therefore, mandatory evaluation of food products becomes inevitable. Hyperspectral imaging has a very good ability to evaluate the quality of fruits and vegetables in a non-destructive manner. The goal of the present paper was to identify excess nitrogen in cucumber plants. To obtain a reliable result, the majority voting method was used, which takes into account the unanimity of five classifiers, namely, the hybrid artificial neural network¿imperialism competitive algorithm (ANN-ICA), the hybrid artificial neural network¿harmonic search (ANN-HS) algorithm, linear discrimination analysis (LDA), the radial basis function network (RBF), and the Knearest- neighborhood (KNN). The wavelengths of 723, 781, and 901 nm were determined as optimal wavelengths using the hybrid artificial neural network¿biogeography-based optimization (ANNBBO) algorithm, and the performance of classifiers was investigated using the optimal spectrum. The results of a t-test showed that there was no significant difference in the precision of the algorithm when using the optimal wavelengths and wavelengths of the whole range. The correct classification rate of the classifiers ANN-ICA, ANN-HS, LDA, RBF, and KNN were 96.14%, 96.11%, 95.73%, 64.03%, and 95.24%, respectively. The correct classification rate of majority voting (MV) was 95.55% for test data in 200 iterations, which indicates the system was successful in distinguishing nitrogen-rich leaves from leaves with a standard content of nitrogen.

Article

artificial neural network cucumber hyperspectral imaging majority voting nitrogen INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ALIMENTOS

Microbiological Analysis of the Air in a Popular Fish Processing and Marketing Area

Angélica Sinaí Quintanilla Martínez Lizet Aguirre Güitrón Luis Daniel Espinosa Chaurand MAYRA DIAZ RAMIREZ ALEJANDRO DE JESUS CORTES SANCHEZ (2022)

"Fish are marketed as a food and consumed worldwide. During the production of food, contamination by microorganisms is possible through the air, soil, water, surfaces, food handlers, etc. The air does not have a natural microbial composition, but it is a vehicle for the transmission of microorganisms of economic and health interest because they are associated with food spoilage and human diseases. The objective of this study was the microbiological analysis of the air in an area popular for the processing and marketing of fish products in the city of Tepic Nayarit. Using the passive or sedimentation method to collect microorganisms present in the air, the proportion of aerobic mesophile bacteria, coliform bacteria, fungi and yeast was determined at different locations in the fish processing and marketing area for four weeks. The results indicated that the aerobic mesophiles had the highest counts among all the microbial groups analyzed at the twelve different sampling points during the four weeks of the study; their numbers ranged from 2.44 to 2.95 log CFU/m3/h, followed by molds with counts from 1.44 to 2.75 log CFU/m3/h, yeasts with counts from 0.7 to 2.01 log CFU/m3/h and coliforms with counts that ranged from 0.7 to 1.68 log CFU/m3/h. We determined the proportion of the viable microbiological population present in the air at the different sampling points of the study area; several of these sampling points presented values above those recommended by various agencies around the world. Knowledge of the biological hazards transported through the air is important to establish and reduce the risk to the health of occupants and the contamination pathways of processed and marketed fishery products that may be associated with spoilage and foodborne diseases."

Article

food safety, food quality, air pollution, airborne biohazard, environmental monitoring INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ALIMENTOS HIGIENE DE LOS ALIMENTOS HIGIENE DE LOS ALIMENTOS

Impact of automation on enhancing energy quality in grid-connected photovoltaic systems

Virgilio Alfonso Murillo Rodríguez NOE VILLA VILLASEÑOR José Manuel Robles Solís OA Guirette-Barbosa (2023)

Rapid growth in the integration of new consumers into the electricity sector, particularly in the industrial sector, has necessitated better control of the electricity supply and of the users’ op-erating conditions to guarantee an adequate quality of service as well as the unregulated dis-turbances that have been generated in the electrical network that can cause significant failures, breakdowns and interruptions, causing considerable expenses and economic losses. This research examines the characteristics of electrical variations in equipment within a company in the industrial sector, analyzes the impact generated within the electrical system according to the need for operation in manufacturing systems, and proposes a new solution through automation of the regulation elements to maintain an optimal system quality and prevent damage and equipment failures while offering a cost-effective model. The proposed solution is evaluated through a reliable simulation in ETAP (Energy Systems Modeling, Analysis and Optimization) software, which emulates the interaction of control elements and simulates the design of electric flow equipment operation. The results demonstrate an improvement in system performance in the presence of disturbances when two automation schemes are applied as well as the exclusive operation of the capacitor bank, which improves the total system current fluctuations and improves the power factor from 85.83% to 93.42%. Such a scheme also improves the waveform in the main power system; another improvement result is when simultaneously operating the voltage and current filter together with the PV system, further improving the current fluctuations, improving the power factor from 85.83% to 94.81%, achieving better stability and improving the quality of the waveform in the main power grid.

This article belongs to Special Issue Advances and Optimization of Electric Energy System.

Article

Power quality Capacitor bank Voltage and current filter Photovoltaic system INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS

Modular ontology to support manufacturing SMEs toward industry 4.0

ZAIDA ANTONIETA MORA ALVAREZ OSCAR HERNANDEZ URIBE RAMON ALBERTO LUQUE MORALES LEONOR ADRIANA CARDENAS ROBLEDO (2023)

Industry 4.0 (I4.0) implementation is a hot topic among manufacturing organizations to reach smart factory status and integrate a fully connected ecosystem. Achieving such a transition presents notable challenges for Small and Medium Enterprises (SMEs) since they often face resource and skilled personnel limitations. This study developed a domain ontology to represent various stages of maturity toward I4.0 implementation. Ontology provides a tool for SMEs to self-assess in situations of machines, processes, and factories for the dimensions of control, integration, and intelligence. This study focused on the identification of classes and relationships according to I4.0 implementation situations in the context of a manufacturing setting, the reuse of ontologies related to the domain of observations to model situations, and the creation and validation of the ontology through the information obtained from the questionnaires applied to SMEs. Finally, the ontology delivers a tool to understand SMEs' current state concerning I4.0 implementation and plan based on informed decisions about the maturity state and the technology required to advance to the next stage in their manufacturing processes.

This study was partially supported by the grants CONAHCYT-CIATEQ CVU 899567 and 162867 and CONAHCYT SNI.

We express our gratitude to Teresa Novales Hernandez for the library support.

Article

Domain ontology Industry 4.0 SMEs Smart factory SPARQL Semantic web INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS

Diseño de un Algoritmo de Detección de Impulsos y Muescas de Voltaje en Corriente Alterna para Análisis de Calidad de la Energía

Roberto Moreno-Sanchez (2012)

El contexto en que se desarrolla este trabajo de tesis está relacionado con los métodos

de medición de calidad de la energía eléctrica, los que se pueden dividir en métodos

de cálculo en estado estable y transitorios. Los métodos de estimación de estado estable

requieren más de 1 ciclo de red para proporcionar mediciones válidas. Los métodos

de estimación para transitorios como las ondeletas, morfologías matemáticas, redes

neuronales, etc. son generalmente métodos complicados que requieren sintonización de

parámetros, cierta experiencia del usuario y un procesamiento digital complejo, lo que

los hace poco viables para medidores portátiles.

En este trabajo de tesis se presentan dos métodos en el dominio del tiempo para

la detección y aislamiento de anomalías transitorias con duración menor a medio ciclo

de red, específicamente para impulsos y muescas de voltaje, en corriente alterna. Estas

propuestas están diseñadas con operaciones básicas que no requieren sintonización de

parámetros ni de conocimiento previo de la anomalía, lo que los hace atractivos para

programarse en Analizadores de Calidad de la Energía Eléctrica Portátiles (ACEEP).

La principal contribución de los métodos propuestos es que, por su simpleza inherente,

pueden detectar anomalías transitorias con las mismas muestras que se requieren para

mediciones en estado estable, lo que los hace útiles para estudios prolongados que

requieran de 8 días o más, con lo que puede obtenerse de manera simultánea un panorama completo en estado estable y transitorio del monitoreo de la calidad de la energía eléctrica.

Los métodos propuestos sólo requieren dos muestras para obtener datos válidos

y lograr el aislamiento con respecto a perturbaciones en estado estable tales como

distorsión armónica, sags, swells e incluso ruido. Se realizó la validación con simulaciones y con señales reales de laboratorio.

Master thesis

INGENIERÍA Y TECNOLOGÍA

Modelos ARX para predecir la temperatura del aire de un invernadero: una metodología

ARX models for predicting greenhouse air temperature: a methodology

Irineo López-Cruz ABRAHAM ROJANO AGUILAR WALDO OJEDA BUSTAMANTE RAQUEL SALAZAR MORENO (2007)

Se presenta un procedimiento para obtener un modelo dinámico lineal de autoregresión con variables exógenas (ARX) para predecir el comportamiento de la temperatura del aire en el interior de un invernadero. Los ARX son modelos matemáticos dinámicos derivados de la teoría de Identificación de Sistemas. Las variables de entrada del modelo fueron temperatura del aire, radiación solar, velocidad del viento afectando el área de ventilación del invernadero y humedad relativa, cuantificadas en una estación meteorológica ubicada a 700 m de un invernadero en Chapingo, Estado de México.

A procedure is presented for obtaining a dynamic linear model of auto-regression with exogenous variables (ARX) for predicting the behaviour of the air temperature inside a greenhouse. The ARX are dynamic mathematical models derived from the theory of Systems Identification. The input variables of the model were air temperature, solar radiation, wind velocity affecting the ventilation area of the greenhouse and relative humidity, quantified in a meteorological station located 700 m from a greenhouse in Chapingo, State of México.

Article

Invernaderos Temperatura ambiental Modelos ARX INGENIERÍA Y TECNOLOGÍA

Recuperación integral de pérdidas de agua: guía técnica CNA-IMTA Sistemas de agua potable

VÍCTOR JAVIER BOURGUETT ORTÍZ José Manuel Rodríguez Varela (1996)

Se exponen algunas ideas, métodos y herramientas sobre diagnótico, eliminación y control de pérdidas y propone un enfoque que ayudará a mejorar la eficacia y eficiencia en la conservación del agua en ciudades y a decidir hasta que punto debe permitirse la recuperación de pérdidas en los sistemas hidráulicos urbanos, con bae en la elaboración de un proyecto integral de recuperación de pérdidas de agua.

Book

INGENIERÍA Y TECNOLOGÍA

Evaluación agrohidráulica de un sistema de drenaje subterráneo parcelario controlado

José Namuche CARLOS FUENTES RUIZ JOSE ANTONIO QUEVEDO TIZNADO Olga Xochitl Cisneros Estrada María Dolores Olvera Salgado (2019)

RD1904.1

El objetivo general del presente proyecto ha sido realizar la evaluación tanto agrohidráulica como económica y financiera de un sistema de drenaje subterráneo parcelario controlado, de una parcela localizada en el Ingenio Huixtla, perteneciente al Distrito de Temporal Tecnificado 018, Huixtla, Chiapas. Para alcanzar dicho objetivo, se han determinado los siguientes objetivos específicos: registrar y analizar los datos en un evento de drenaje; elaborar un modelo de simulación de drenaje agrícola; seleccionar muestras en transectos localizados tanto en una parcela sin drenaje o testigo como en la parcela con drenaje, para evaluar el impacto del sistema de drenaje conforme a la evolución del ciclo de cultivo; determinar el intervalo de tiempo en que es posible adelantar la fecha de siembra del cultivo, así como el abatimiento medio que se prevé obtener como producto del funcionamiento del sistema de drenaje; determinar parámetros econométricos: Relación Beneficio Costo (RBC), Tasa Interna de Retorno (TIR) y Valor Actual Neto (VAN); realizar un análisis comparativo de resultados tomando como testigos dos parcelas circundantes al predio donde se instale el sistema de drenaje parcelario subterráneo; divulgar los resultados y las prácticas de demostración en el módulo experimental, mediante eventos específicos para dar a conocer los trabajos; y elaborar el documento técnico final de resultados y conclusiones.

Working paper

Riego Drenaje subterráneo Evaluación INGENIERÍA Y TECNOLOGÍA

Caracterización de aguas residuales porcinas y su tratamiento por diferentes procesos en México

MARCO ANTONIO GARZON ZUÑIGA GERARDO RAMON BUELNA ACEDO (2014)

La mayoría de los sistemas de tratamiento de efluentes de granjas porcinas a escala real, presentan bajas eficiencias de remoción de contaminantes debido a que se han aplicado sistemas que no toman en cuenta la gran variación de concentración de contaminantes de los efluentes de diferentes procesos productivos (maternidad, destete, engorda y mezcla). Este trabajo presenta una investigación sobre la variación en la composición de 14 efluentes de granjas porcinas en México y la eficiencia de cinco diferentes procesos de tratamiento aplicados a escala real.

Article

Efluentes industriales Porcinos Digestión anaerobia Filtros biológicos INGENIERÍA Y TECNOLOGÍA