A line follower robot implementation using Lego's Mindstorms Kit and Q-Learning

VICTOR RICARDO CRUZ ALVAREZ ENRIQUE HIDALGO PEÑA HECTOR GABRIEL ACOSTA MESA (2012, [Artículo])

Un problema común al trabajar con robots móviles es que la fase de programación puede ser un proceso largo, costoso y difícil para los programadores. Los Algoritmos de Aprendizaje por Refuerzo ofrecen uno de los marcos de trabajo más generales en el ámbito de aprendizaje de máquina. Este trabajo presenta un enfoque usando el algoritmo de Q-Learning en un robot Lego para que aprenda "por sí mismo" a seguir una línea negra dibujada en una superficie blanca. El entorno de programación utilizado en este trabajo es Matlab.

INGENIERÍA Y TECNOLOGÍA Algoritmos de aprendizaje reforzado Q-learning (Algoritmo de aprendizaje reforzado) Lego Mindstorms (Robótica) Matlab Reinforcement learning algorithms Q-Learning (Reinforcement learning algorithm) Lego Mindstorms (Robotics) Matlab

Situated learning through local stories: positioning socio-ecological concerns, knowledge and practices in school

Rosa Guadalupe Mendoza Zuany Juan Carlos A. Sandoval Rivera Paula Martínez Bautista (2023, [Artículo, Artículo])

The article analyzes the importance of the local stories, which contain concerns, knowledge and practices to look after the socio-ecological environment, to trigger situated and pertinent teaching and learning processes in primary education in rural and indigenous contexts in Veracruz, Mexico. In particular, it focuses on the stories about care in the framework of a deep socio-ecological crisis in two Nahua communities of the Huasteca region. Interview-conversations were carried out with community actors in the two communities in which 32 stories emerged. The analysis allowed the identification of socio-ecological concerns of the community, characteristics of the stories that show their potential in the learning processes, as well as types of knowledge and practices that are rarely considered in the classroom, which are capable of being linked to curricular content, in order to contribute to reflection and action on the socio-ecological crisis of the communities.

aprendizaje narración de historias medio ambiente ambiente socio-cultural escuela rural CIENCIAS SOCIALES; HUMANIDADES Y CIENCIAS DE LA CONDUCTA CIENCIAS SOCIALES HUMANIDADES Y CIENCIAS DE LA CONDUCTA Learning story telling environment socio-cultural environment rural school

COVID-19 and family participation in school activities.: Teaching experiences around the Learn at Home program

Evangelina Cervantes Holguín Pavel Roel Gutiérrez Sandoval (2022, [Artículo, Artículo])

The article analyzes, from the qualitative method, the participation of families and teaching staff of the first cycle of primary education in the state of Chihuahua (Mexico) to carry out the various activities of the Learn at Home program implemented in March 2020 as a response to the resulting health confinement by COVID-19. It is concluded that the participation of families in school emergency situations implies improving the relationship between teachers, families, and the community in the implementation processes of educational programs with greater support to organize study times, take advantage of the different cultural capitals and promote family co-responsibility.

Aprendizaje Educación a distancia Enseñanza primaria Epidemia Familia COVID-19 Chihuahua HUMANIDADES Y CIENCIAS DE LA CONDUCTA HUMANIDADES Y CIENCIAS DE LA CONDUCTA Family Elementary education Epidemics Distance education Learning

Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics

Xu Wang Sandesh Kumar Shrestha Philomin Juliana Suchismita Mondal Francisco Pinto Govindan Velu Leonardo Abdiel Crespo Herrera JULIO HUERTA_ESPINO Ravi Singh Jesse Poland (2023, [Artículo])

New Crop Varieties Plant Breeding Programs Yield Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA LEARNING GRAIN YIELDS WHEAT BREEDING FOOD SECURITY

Distance learning for farmers: Experience during the pandemic

Andrea Gardeazabal (2023, [Documento de trabajo])

In response to the COVID-19 pandemic's disruption of farmer training—a crucial component for enhancing the resilience and livelihoods of smallholder farmers—CIMMYT innovated educational solutions to sustain capacity building in agri-food systems. Addressing the challenges of limited mobile device access, poor internet connectivity, and digital illiteracy, CIMMYT implemented two pilot projects in Mexico. These projects facilitated distance learning for adult farmers in rural areas, employing both internet-based and non-internet methods. The non-internet approach utilized traditional media like print, while the internet-based approach leveraged WhatsApp for educational content delivery. Building on these experiences, CIMMYT expanded its offerings by creating micro -courses delivered through WhatsApp, hosted on the Co-LAB's new Learning Network platform, specifically targeting farmers. This paper delves into the various strategies, methods, and techniques adopted, documenting the learning outcomes, results, and key conclusions drawn from these innovative training initiatives.

Distance Learning Digital Inclusion Innovative Training CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DISTANCE EDUCATION CAPACITY DEVELOPMENT METHODS COMMUNICATION TECHNOLOGY

Síncrono / asíncrono. Convergencia y alternancia en la enseñanza futura del diseño

Francisco Gerardo Toledo Ramirez (2023, [Capítulo de libro])

La cuarentena sanitaria de los últimos dos años (COVID-19) obligó a “rediseñar”, “digitalizar” o “virtualizar” nuestros cursos y estilos de enseñanza en tiempo récord para “adaptarlas” al “formato virtual a distancia” (online). La profusión de comillas en las líneas anteriores tiene la intención de señalar el carácter incierto o erróneo que ciertos términos-fetiche adquirieron en el proceso. Es importante desmitificar esas figuras de la expresión que se elevaron casi al nivel de pseudo-epistemes (presuntamente novedosas) para la enseñanza del Diseño. Ese tema lo abordo con mayor amplitud en una nueva investigación, recientemente registrada en la UAM. En este texto esbozo (en forma algo lúdica) pero seria y breve a la vez, la conveniencia de tal desmitificación y avanzo en el delineamiento de un modelo de la alternancia y convergencia de recursos pedagógico-didácticos síncronos y asíncronos, mediante la tecnología-red digital, como un elemento estratégico para la educación futura en Diseño.

The health quarantine of the last 2 years (COVID-19) forced us to “redesign”, “digitize” or “virtualize” our courses and teaching styles in record time to “adapt” them to the “virtual format” “at a distance” (online). The profusion of quotation marks in the previous lines is intended to indicate the uncertain or erroneous character that certain fetish-terms acquired in the process. It is important to demystify those figures of expression that have risen almost to the level of pseudo-epistemes (presumably novel) for teaching design. I address this topic more fully in a new investigation, recently registered at the UAM. In this text I outline (in a somewhat playful way) but serious and brief at the same time, the convenience of such “demystification” and I advance in the outline of a model of alternation and convergence of synchronous and asynchronous pedagogical-didactic resources, through technology. -digital network, as a strategic element for future design education.

Síncrono, asíncrono, virtualidad, presencialidad, diseño, remoto. Synchronous, asynchronous, virtuality, face-to-face, design, remote. Design--Study and teaching, Higher. Distance education. Blended learning. Universidad Autónoma Metropolitana. Unidad Azcapotzalco. División de Ciencias y Artes para el Diseño. Artes gráficas. Educación a Distancia. Aprendizaje combinado. NK1170 HUMANIDADES Y CIENCIAS DE LA CONDUCTA CIENCIAS DE LAS ARTES Y LAS LETRAS

Multi-trait, multi-environment deep learning modeling for genomic-enabled prediction of plant traits

Osval Antonio Montesinos-Lopez Jose Crossa Francisco Javier Martin Vallejo (2018, [Artículo])

Deep Learning Genomic Prediction Bayesian Modeling Shared Data Resources CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BAYESIAN THEORY RESOURCES DATA BREEDING PROGRAMMES

Multi-environment genomic prediction of plant traits using deep learners with dense architecture

Osval Antonio Montesinos-Lopez Jose Crossa (2018, [Artículo])

Shared Data Resources Deep Learning Genomic Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ACCURACY GENOMICS NEURAL NETWORKS FORECASTING DATA MARKER-ASSISTED SELECTION

High-throughput plot-level quantitative phenotyping using convolutional neural networks on very high-resolution satellite images

Francisco Pinto Matthew Paul Reynolds Robert Furbank (2024, [Artículo])

Deep Learning Object-Based Image Analysis Optical Imagery CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURE IMAGE ANALYSIS PLANT BREEDING REMOTE SENSING MACHINE LEARNING

Statistical machine-learning methods for genomic prediction using the SKM library

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

Sparse Kernel Methods R package Statistical Machine Learning Genomic Selection CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MARKER-ASSISTED SELECTION MACHINE LEARNING GENOMICS METHODS