Repositorio Nacional

This work was originated from the increasing interest in several industries to implement voice based virtual assistant solutions powered by the Natural Language Processing field of study. This work is focused on the automotive industry Human Machine Interface related products, specifically the Instrument Panel. Nowadays people are constantly using virtual assistants like Google Assistant, Alexa, Cortana or Siri on their electronic devices. Furthermore, 31% of cars have a built-in virtual assistant, for example Ford uses Alexa, Mercedes-Benz and Hyundai use Google Assistant, BMW and Nissan use Cortana, GM uses IBM Watson, Honda uses Hana and Toyota uses YUI. Apart from the proprietary solutions described earlier, there are also contemporary open-source generic solutions available on the market, such as Mycroft AI which stands out from other technologies due to ready to deploy, well documented, simple installation on a Linux PC or RPI SoC, and simple execution. This paper presents a way to use Mycroft AI as an alternative to add artificial intelligence-based voice assistance to applications in the automotive domain. The voice communication module presented here drives notifications related to three different entities: seat belt, fuel level and battery level, all of them are telltales present in any automotive Instrument Panel. Since the Mycroft AI design approach is based on Human Centered Design (HCD), the voice communication module presented here provides real user experience (UX) based design. As a conclusion, Mycroft AI demonstrates great potential as an alternative to add voice assistance to automotive industry Human Machine Interface related products. About future work, due to the fact that Mycroft AI is based on Python, there are many possibilities for connecting and expanding the voice communication module by using countless Python libraries in order to import and process any type of information, in any format or source, for example the information from communication technologies like CAN, LIN, Ethernet, MOST, GPS or any other device or technology in order to create comprehensive automotive solutions.

Este trabajo se originó del creciente interés por parte de diferentes industrias para implementar soluciones de asistente virtual basado en voz impulsadas por el campo de estudio del Procesamiento del Lenguaje Natural. Este trabajo está enfocado en los productos relacionados a la Interfaz Humano Máquina de la industria automotriz, específicamente el Panel de Instrumentos. Hoy en día las personas usan constantemente asistentes virtuales como Google Assistant, Alexa, Cortana o Siri en sus dispositivos electrónicos. Más aún, 31% de los autos tienen un asistente virtual integrado, por ejemplo, Ford usa Alexa, Mercedes-Benz y Hyundai usan Google Assistant, BMW y Nissan usan Cortana, GM usa IBM Watson, Honda usa Hana y Toyota usa YUI. Aparte de las soluciones de marca registrada descritas anteriormente, también hay soluciones genéricas de código abierto contemporáneas disponibles en el mercado, tales como Mycroft AI que se hace notar por sobre otras tecnologías por características como listo para usar, bien documentada, instalación simple en una PC Linux o RPI SoC, y una ejecución simple. Este artículo presenta una manera de usar Mycroft AI como una alternativa para agregar inteligencia artificial basada en asistencia de voz a aplicaciones en el dominio automotriz. El módulo de comunicación de voz presentado aquí maneja notificaciones relacionadas a tres diferentes entidades: cinturón de seguridad, nivel de gasolina y nivel de batería, todos ellos son indicadores virtuales presentes en cualquier Panel de Instrumentos Automotriz. Dado que el enfoque de diseño de Mycroft AI se basa en Diseño Centrado en el Human (HCD), el módulo de comunicación por voz presentado aquí provee un diseño basado en experiencia de usuario (UX) real. Como conclusión, Mycroft AI demuestra gran potencial como una alternativa para agregar asistencia de voz a los productos relacionados a Interfaz Humano Máquina de la industria automotriz. Acerca del trabajo a futuro, debido al hecho que Mycroft AI está basado en Python, existen muchas posibilidades para conectar y expandir el módulo de comunicación por voz a través del uso de innumerables bibliotecas de Python para importar y procesar cualquier tipo de información, en cualquier formato o fuente, por ejemplo la información proveniente de tecnologías de comunicación tales como CAN, LIN, Ethernet, MOST, GPS o cualquier otro dispositivo o tecnología para crear soluciones automotrices integrales.

Authorship acknowledgment. Ricardo Hernández Mejía: Conceptualization, Methodology, Software, Validation, Formal analysis, Research, Resources, Original draft, Visualization, Project administration. Francisco Javier Ibarra Villegas: Review and Editing, Supervision, Project Administration. Cain Pérez Wences: Review and Editing.

Acknowledgment. To Posgrado CIATEQ A.C. due to the institutional support and guidance received to conclude this work in a professional and successful way. To Continental Automotive Occidente due to the sponsorship provided to perform the master’s degree along with Posgrado CIATEQ A.C. which made possible this work. To Dr. Francisco Javier Ibarra Villegas due to their guidance and support on the process to shape and concrete this work.

Instrument panel Virtual assistant Voice communication module Mycroft AI Human centered design User experience Panel de instrumentos Asistente virtual Módulo de comunicación por voz Diseño centrado en el humano Experiencia de usuario INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS

Nitrogen use efficiency and genotype-by-environment interaction in durum wheat genotypes under varying nitrogen supply

Tesfaye Geleta Aga Bekele Abeyo (2024, [Artículo])

Straw Nitrogen Uptake Nitrogen Harvest Index CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA NITROGEN-USE EFFICIENCY STRAW GENOTYPE ENVIRONMENT INTERACTION HARD WHEAT

Commodity crops in biodiversity-rich production landscapes: Friends or foes? The example of cotton in the Mid Zambezi Valley, Zimbabwe

Frédéric Baudron Ken Giller (2022, [Artículo])

Land Sparing Land Sharing Human-Wildlife Conflicts CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BIODIVERSITY HOUSEHOLD SURVEYS LAND COVER LANDSCAPE MAMMALS CASH CROPS HUMAN-WILDLIFE RELATIONS LAND USE CHANGE

Review of Nationally Determined Contributions (NCD) of Vietnam from the perspective of food systems

Tek Sapkota (2023, [Documento de trabajo])

Over the past decades, Vietnam has significantly progressed and has transformed from being a food-insecure nation to one of the world’s leading exporters in food commodities, and from one of the world’s poorest countries to a low-middle-income country. The agriculture sector is dominated by rice and plays a vital role in food security, employment, and foreign exchange. Vietnam submitted its updated Nationally Determined Contributions (NDC) in 2022 based on the NDC 2020. There is a significant increase in greenhouse gas (GHG) emission reduction, towards the long-term goals identified in Vietnam’s National Climate Change Strategy to 2025, and efforts are being made to fulfil the commitments made at COP26. The Agriculture Sector is the second-largest contributor of GHG emissions in Vietnam, accounting for 89.75 MtCO2eq, which was about 31.6 percent of total emissions in 2014. Rice cultivation is the biggest source of emissions in the agriculture sector, accounting for 49.35% of emissions from agriculture. The total GHG removal from Land Use, Land Use Change and Forestry (LULUCF) in 2014 was -37.54 MtCO2eq, of which the largest part was from the forest land sub-sector (35.61 MtCO2eq), followed by removal from croplands (7.31 MtCO2eq) (MONRE 2019).

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE GREENHOUSE GAS EMISSIONS FOOD SYSTEMS LAND USE CHANGE AGRICULTURE POLICIES DATA ANALYSIS

Review of Nationally Determined Contributions (NCD) of Colombia from the perspective of food systems

Tek Sapkota (2023, [Documento de trabajo])

Food is a vital component of Colombia's economy. The impact of climate change on agriculture and food security in the country is severe. The effects have resulted in decreased production and in the productivity of agricultural soil. Desertification processes are accelerating and intensifying. Colombia's government formally submitted its Nationally Determined Contribution (NDC) on December 29, 2020. This paper examines Colombia's NDC from the standpoint of the food system.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE GREENHOUSE GAS EMISSIONS FOOD SYSTEMS LAND USE CHANGE AGRICULTURE POLICIES DATA ANALYSIS FOOD WASTES

Catching-up with genetic progress: Simulation of potential production for modern wheat cultivars in the Netherlands

João Vasco Silva Frits K. Van Evert Pytrik Reidsma (2023, [Artículo])

Context: Wheat crop growth models from all over the world have been calibrated on the Groot and Verberne (1991) data set, collected between 1982 and 1984 in the Netherlands, in at least 28 published studies to date including various recent ones. However, the recent use of this data set for calibration of potential yield is questionable as actual Dutch winter wheat yields increased by 3.1 Mg ha-1 over the period 1984 – 2015. A new comprehensive set of winter wheat experiments, suitable for crop model calibration, was conducted in Wageningen during the growing seasons of 2013–2014 and of 2014–2015. Objective: The present study aimed to quantify the change of winter wheat variety traits between 1984 and 2015 and to examine which of the identified traits explained the increase in wheat yield most. Methods: PCSE-LINTUL3 was calibrated on the Groot and Verberne data (1991) set. Next, it was evaluated on the 2013–2015 data set. The model was further recalibrated on the 2013–2015 data set. Parameter values of both calibrations were compared. Sensitivity analysis was used to assess to what extent climate change, elevated CO2, changes in sowing dates, and changes in cultivar traits could explain yield increases. Results: The estimated reference light use efficiency and the temperature sum from anthesis to maturity were higher in 2013–2015 than in 1982–1984. PCSE-LINTUL3, calibrated on the 1982–1984 data set, underestimated the yield potential of 2013–2015. Sensitivity analyses showed that about half of the simulated winter wheat yield increase between 1984 and 2015 in the Netherlands was explained by elevated CO2 and climate change. The remaining part was explained by the increased temperature sum from anthesis to maturity and, to a smaller extent, by changes in the reference light use efficiency. Changes in sowing dates, biomass partitioning fractions, thermal requirements for anthesis, and biomass reallocation did not explain the yield increase. Conclusion: Recalibration of PCSE-LINTUL3 was necessary to reproduce the high wheat yields currently obtained in the Netherlands. About half of the reported winter wheat yield increase was attributed to climate change and elevated CO2. The remaining part of the increase was attributed to changes in the temperature sum from anthesis to maturity and, to a lesser extent, the reference light use efficiency. Significance: This study systematically addressed to what extent changes in various cultivar traits, climate change, and elevated CO2 can explain the winter wheat yield increase observed in the Netherlands between 1984 and 2015.

Light Use Efficiency Potential Yield CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROP MODELLING LIGHT PHENOLOGY MAXIMUM SUSTAINABLE YIELD TRITICUM AESTIVUM WINTER WHEAT