Algorithmic differentiation of linear mixed models with variance-covariance structures

Fernando Henrique Toledo Jose Crossa Juan Burgueño Keith Gardner Rosa Angela Pacheco Gil (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MATHEMATICAL MODELS ALGORITHMS LINEAR MODELS

Monitoreo e Instalación visual de señales a un motor eléctrico de inducción de instalación trifásica de forma jaula de ardilla, mediante la implementación de tecnología industria 4.0

Luis Ricardo Uribe Dávila (2023, [Tesis de maestría])

Vivimos la industria 4.0, misma que no es nueva, ya que sus orígenes se remontan a finales de la década de los 2000, en Alemania. Un pilar de la industria 4.0 es el análisis de datos, conocido como Big Data. El conocer los datos de un proceso, de un estudio, ayuda en gran medida a predecir el comportamiento que tendrá el proceso o la máquina a estudiar en un periodo a corto o mediano plazo. En el presente proyecto se analizan los datos arrojados por un motor eléctrico de corriente alterna, del tipo inducción, jaula de ardilla. El motor está diseñado para trabajar de manera continua, sin embargo, el uso que se le da, es meramente educativo; es decir, no sobre pasa las 15 horas por semana de uso. Mediante la toma de datos de las tres fases de corriente RMS o corriente de valor eficaz que posee el motor eléctrico que se realizará con el microcontrolador Arduino UNO, se analizarán los mismos mediante el software de cómputo numérico MATLAB, ordenando los datos, descartando valores que no aporten información relevante para lograr la predicción de datos. Por último, se llevará a conocer este proyecto a la carrera mecatrónica, área sistemas de manufactura flexible y área automatización, con el fin de que puedan observar de una mejor manera la aplicación y funcionamiento de uno de los pilares de la actual industria 4.0.

We live in industry 4.0, which is not new, since its origins date back to the late 2000s, in Germany. One pillar of industry 4.0 is data analysis, known as Big Data. Knowing the data of a process, of a study, helps greatly to predict the behavior that the process or machine will have to study in a short- or medium-term period. This project analyzes the data released by an electric motor of alternating current, of the type induction, squirrel cage. The engine is designed to work continuously, however, the use given to it is merely educational, that is; only not over spends 15 hours per week of use. By taking data from the three phases of RMS current or effective value current of the electric motor that will be made with the Arduino UNO micro controller, they will be analyzed using MATLAB numerical computing software, ordering the data, discarding values that do not provide relevant information to achieve data prediction. Finally, this project will be presented to the mechatronics career, flexible manufacturing systems area and automation area, so that they can observe in a better way the application and operation of one of the pillars of the current industry 4.0.

Mantenimiento predictivo Regresión lineal Industria 4.0 Big data Corriente RMS Predictive maintenance Linear regression Industry 4.0 Big data RMS Current INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS

Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy

Martin van Ittersum (2023, [Artículo])

Context: Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency. Objective: The aim of this study was to assess the performance of statistical and machine learning methods to explain and predict crop yield across thousands of farmers’ fields in contrasting farming systems worldwide. Methods: A large database of 10,940 field-year combinations from three countries in different stages of agricultural intensification was analyzed. Random effects models were used to partition crop yield variability and random forest models were used to explain and predict crop yield within a cross-validation scheme with data re-sampling over space and time. Results: Yield variability in relative terms was smallest for wheat and barley in the Netherlands and for wheat in Ethiopia, intermediate for rice in the Philippines, and greatest for maize in Ethiopia. Random forest models comprising a total of 87 variables explained a maximum of 65 % of cereal yield variability in the Netherlands and less than 45 % of cereal yield variability in Ethiopia and in the Philippines. Crop management related variables were important to explain and predict cereal yields in Ethiopia, while predictive (i.e., known before the growing season) climatic variables and explanatory (i.e., known during or after the growing season) climatic variables were most important to explain and predict cereal yield variability in the Philippines and in the Netherlands, respectively. Finally, model cross-validation for regions or years not seen during model training reduced the R2 considerably for most crop x country combinations, while for wheat in the Netherlands this was model dependent. Conclusion: Big data from farmers’ fields is useful to explain on-farm yield variability to some extent, but not to predict it across time and space. Significance: The results call for moderate expectations towards big data and machine learning in agronomic studies, particularly for smallholder farms in the tropics where model performance was poorest independently of the variables considered and the cross-validation scheme used.

Model Accuracy Model Precision Linear Mixed Models CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MACHINE LEARNING SUSTAINABLE INTENSIFICATION BIG DATA YIELDS MODELS AGRONOMY

Point placement of late vegetative stage nitrogen splits increase the productivity, N-use efficiency and profitability of tropical maize under decade long conservation agriculture

Hari Sankar Nayak C.M. Parihar Shankar Lal Jat ML JAT Ahmed Abdallah (2022, [Artículo])

Non-Linear Growth Model Nitrogen Remobilization Right Placement Precision Nitrogen Management CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GROWTH MODELS NITROGEN NUTRIENT MANAGEMENT

Response of African sorghum genotypes for drought tolerance under variable environments

Hussein Shimelis Baloua Nébié (2023, [Artículo])

Additive Main Effect and Multiplicative Interaction Best Linear Unbiased Estimates Drought Tolerance Indices CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ABIOTIC STRESS DROUGHT TOLERANCE SORGHUM GENOTYPES

Complex traits and candidate genes: estimation of genetic variance components across multiple genetic architectures

GIOVANNY COVARRUBIAS-PAZARAN Hans-Peter Piepho (2023, [Artículo])

Average Semivariance Linear Mixed Model Variance Component Estimation Polygenic Inheritance Oligogenic Inheritance Mendelian Inheritance CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MENDELISM GENETIC VARIANCE GENOME-WIDE ASSOCIATION STUDIES PHENOTYPES CHROMOSOME MAPPING

Enviromic prediction enables the characterization and mapping of Eucalyptus globulus Labill breeding zones

Germano Costa Neto Jose Crossa (2024, [Artículo])

Forest Tree Breeding Genomic Relationship Matrix Genomic Selection Best Linear Unbiased Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FOREST TREES BREEDING MARKER-ASSISTED SELECTION MYRTACEAE EUCALYPTUS GLOBULUS

Efficacy of plant breeding using genomic information

Osval Antonio Montesinos-Lopez Alison Bentley Carolina Saint Pierre Leonardo Abdiel Crespo Herrera Morten Lillemo Jose Crossa (2023, [Artículo])

Genomic Selection Genomic Prediction Genomic Best Linear Unbiased Predictor CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA PLANT BREEDING GENOMICS MARKER-ASSISTED SELECTION ENVIRONMENT

A novel method for genomic-enabled prediction of cultivars in new environments

Osval Antonio Montesinos-Lopez Brandon Alejandro Mosqueda González Jose Crossa (2023, [Artículo])

Genomic Best Linear Unbiased Prediction Gains in Accuracy Genomic Prediction Novel Methods CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOTYPE ENVIRONMENT INTERACTION METHODS ENVIRONMENT

Diseño de arreglos de antenas para entornos de 5G utilizando técnicas de simplificación en la red de alimentación

Design of antenna arrays for 5G environments using simplification techniques in the feeding network

ELIZVAN JUAREZ PACHECO (2023, [Tesis de doctorado])

En los últimos años, las redes de comunicaciones inalámbricas de quinta generación (5G) han tomado gran relevancia debido al crecimiento del número de usuarios móviles que se conectan a estas redes inalámbricas. Estas redes utilizan arreglos de antenas para generar haces de radiación directivos que pueden escanearse en una o múltiples direcciones en el espacio mediante el control de una red de alimentación. En una red de alimentación convencional cada elemento de antena se alimenta con un dispositivo amplificador y desfasador, lo que resulta en sistemas costosos y complejos de implementar. Por lo tanto, esta tesis de investigación propone nuevas técnicas de diseño que simplifican la red de alimentación al reducir el número de puertos de entrada y dispositivos desfasadores necesarios en el sistema de antenas. Las configuraciones propuestas consideran como requisitos de diseño el nivel de lóbulo lateral (SLL por sus siglas en inglés), rango de escaneo del haz principal y ancho de banda de operación adecuados para sistemas de 5G. Así, se introduce la técnica de bloques CORPS (Estructuras Periódicas de Radiación Coherente, en inglés) como una solución para simplificar la red de alimentación en arreglos lineales y planares. Esta técnica aprovecha la propiedad de interpolación de fase de las redes CORPS de una capa para generar los valores cofasales ideales necesarios para escanear el haz principal. Además, la aplicación de una excitación de amplitud de coseno alzado genera un haz de radiación con bajo SLL. Adicionalmente, se aplica la técnica de bloques CORPS en configuraciones con subarreglos para mejorar la reducción de desfasadores en comparación con la implementación individual de cada tecnología. Los resultados obtenidos mediante simulación electromagnética y mediciones experimentales validan los diferentes diseños propuestos. Todo esto contribuye al estado del arte al presentar diferentes diseños de arreglos de antenas que simplifican la red de alimentación manteniendo buenas características en el patrón de radiación en comparación con diseños tradicionales.

In recent years, fifth-generation wireless networks (5G) have become very relevant due to the exponential growth in the number of mobile users connecting to wireless networks. These networks employ antenna arrays to generate directional radiation beams that can be scanned in one or multiple directions in space by controlling a feeding network. In a conventional feeding network, each antenna element is fed with an amplifier and phase shifter device, which results in expensive and complex systems to implement. Therefore, this thesis proposes novel design techniques that simplify the feeding network by reducing the number of input ports and phase shifter devices required in the antenna system. The proposed configurations take into account requirements such as side lobe level (SLL), scanning range, and bandwidth appropriate for 5G systems. Thus, the CORPS (Coherent Radiation Periodic Structures) blocks technique is introduced as a solution to simplify the feeding network in linear and planar phased arrays. This technique takes advantage of the phase interpolation property of single-layer CORPS to generate the ideal cophasal values necessary for the main beam scanning. Furthermore, the application of a raised-cosine amplitude distribution generates a radiation beam with low SLL. Additionally, the CORPS blocks technique is applied in subarrays configurations to improve the phase shifters reduction compared to the individual implementation of each technology. The results obtained by electromagnetic simulation and experimental measurements validate the different proposed designs. This contributes to the state of the art by different designs of antenna arrays that simplify the feeding network while maintaining good radiation pattern characteristics when compared to traditional designs.

Arreglo de antenas, Red de alimentación, Quinta generación, Arreglo lineal, Arreglo planar Antenna array, Feeding network, Fifth Generation, Linear array, Planar array INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LAS TELECOMUNICACIONES ANTENAS ANTENAS