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  • Rural Digital Europe
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  • Open Access English
    Authors: 
    Angie Higuchi; Daniel Coq-Huelva; Cristian Vasco; Rafaela Alfalla-Luque; Rocío Maehara;
    Publisher: Sociedade Brasileira de Economia e Sociologia Rural
    Country: Spain

    Abstract The growth of small-scale Peruvian farmers is highly dependent on cocoa factor productivity. Agricultural extension programs can help to improve farm productivity using available resources. Thus, the objective of this study is to estimate the productivity of Peruvian cocoa farming and identify if frequent technical assistance impacts on farmers’ technical efficiency. The data came from a survey of 379 cocoa farmers in Tocache, San Martin (177 producers who sell through intermediaries and 202 who are cooperative members), conducted between January and June 2015. This article is supported by the interaction of two associated techniques: the production function and the technical efficiency technique based on stochastic frontier analysis (SFA). The key findings were that the estimated coefficients for labor, capital, land and fertilizer were positive to cocoa production. Our outcomes also show there is a (marginally) significant relationship between technical assistance and technical efficiency (p-value<10%). There is also a positive relationship between efficiency and other socioeconomic characteristics of being a male, having experience in cocoa cultivation and practicing non-diversification in other crops. Policymakers could consider these results to improve farm management systems and, therefore, the competitiveness of the cocoa plantations in the Peruvian Amazonia. Resumen El crecimiento de los pequeños agricultores depende en gran medida de la productividad del cacao. Los programas de extensión agrícola pueden ayudar a mejorar dicha productividad utilizando los recursos disponibles. Por tanto, el objetivo de este estudio es estimar la productividad del cacao peruano e identificar si la frecuencia de asistencia técnica afecta la eficiencia técnica de los agricultores. Los datos provienen de una encuesta a 379 productores de cacao en Tocache, San Martín, realizada entre enero y junio de 2015. Este artículo se sustenta en la interacción de dos técnicas: la función de producción y la eficiencia técnica basada en el análisis de frontera estocástica. Los hallazgos clave fueron que los coeficientes estimados de trabajo, capital, tierras y fertilizantes fueron positivos para la producción. Asimismo, se muestra la existencia de una relación entre la frecuencia de asistencia técnica y la eficiencia técnica (p-valor<10%). También existe una relación positiva entre la eficiencia y otras características socioeconómicas al ser hombre, tener experiencia en el cacao y no practicar la diversificación en otros cultivos. Los formuladores de políticas públicas podrían considerar estos resultados para mejorar los sistemas de manejo agrarios y, por tanto, la competitividad de los cacaoteros en la Amazonía peruana.

  • Open Access English
    Authors: 
    Jana Bürger; Filip Küzmič; Urban Šilc; Florian Jansen; Erwin Bergmeier; Milan Chytrý; Alicia Cirujeda; Silvia Fogliatto; Guillaume Fried; Denise F. Dostatny; +16 more
    Countries: Spain, United Kingdom, Lithuania, United Kingdom, Lithuania

    Questions Two scientific disciplines, vegetation science and weed science, study arable weed vegetation, which has seen a strong diversity decrease in Europe over the last decades. We compared two collections of plot-based vegetation records originating from these two disciplines. The aim was to check the suitability of the collections for joint analysis and for addressing research questions from the opposing domains. We asked: are these collections complementary? If so, how can they be used for joint analysis? Location Europe. Methods We compared 13 311 phytosociological relevés and 13 328 records from weed science, concerning both data collection properties and the recorded species richness. To deal with bias in the data, we also analysed different subsets (i.e., crops, geographical regions, organic vs conventional fields, center vs edge plots). Results Records from vegetation science have an average species number of 19.0 ± 10.4. Metadata on survey methodology or agronomic practices are rare in this collection. Records from weed science have an average species number of 8.5 ± 6.4. They are accompanied by extensive methodological information. Vegetation science records and the weed science records taken at field edges or from organic fields have similar species numbers. The collections cover different parts of Europe but the results are consistent in six geographical subsets and the overall data set. The difference in species numbers may be caused by differences in methodology between the disciplines, i.e., plot positioning within fields, plot sizes, or survey timing. Conclusion This comparison of arable weed data that were originally sampled with a different purpose represents a new effort in connecting research between vegetation scientists and weed scientists. Both collections show different aspects of weed vegetation, which means the joint use of the data is valuable as it can contribute to a more complete picture of weed species diversity in European arable landscapes. Published

  • Open Access
    Authors: 
    Marc Vila; Víctor Casamayor; Schahram Dustdar; Ernest Teniente;
    Publisher: Elsevier BV
    Country: Spain

    There are billions of devices worldwide deployed, connected, and communicating to other systems. Sensors and actuators, which can be stationary or movable devices. These Edge devices are considered part of the Internet of Things (IoT) devices, which can be referred to as a tier of the Computing Continuum paradigm. There are two main concerns at stake in the success of this ecosystem. The interoperability between devices and systems is the first. Mainly, because most of them communicate uniquely and differently from each other, leading to heterogeneous data. The second issue is the lack of decision-making capacity to conduct actuations, such as communicating through different computing tiers based on latency constraints due to a certain measured factor. In this article, we propose an ontology to improve device interoperability in the IoT. In addition, we also explain how to ease data communication between Computing Continuum devices, providing tools to enhance data management and decision-making. A use case is also presented, using the automotive industry, where quickness in maneuver determination is key to avoid accidents. It is exemplified using two Raspberry Pi devices, connected using different networks and choosing the appropriate one depending on context-aware conditions. This work is partially funded by: Industrial Doctorates (2019 DI 001) from Generalitat de Catalunya. The SUDOQU project (PID2021-127181OB-I00) from MCIN/AEI. FEDER “Una manera de hacer Europa”; and project 2017-SGR-1749 from Generalitat de Catalunya. Also with the support of inLab FIB at UPC and Worldsensing. Peer Reviewed

  • Open Access Spanish; Castilian
    Authors: 
    Berrogui Morrás, Diego; Hernández Aldaz, Marta; Idoate Zapata, Marta; Zhan, Junjie;
    Publisher: Grup per a la Innovació i la Logística Docent en l'Arquitectura (GILDA)
    Country: Spain

    The challenges presented by digitization in the world of architecture have increased in recent decades due to the advance of new software. The present study seeks to be an instrument for the management of the adaptation or initiation in these new tools. We wanted to expose the current situation in architectural firms based on their own experiences and opinions. The methodology used has been, the realization of surveys to architecture studios from all over Spain about their knowledge of digitization and their vision of this, trying to find answers that interest both schools of architecture, as students and, therefore, future architects. These answers reflect the existing situation and future desires, so they can be used either way, as an aid to design the professional profile of students, as well as to think over on the role of digital tools in the future of the profession. Los retos que presenta la digitalización en el mundo de la arquitectura se han visto incrementados en las últimas décadas debido al avance de los nuevos softwares. El presente estudio busca ser un instrumento para la gestión de la adaptación o iniciación en estas nuevas herramientas. Hemos querido exponer el panorama actual en los estudios de arquitectura en base a sus propias experiencias y opiniones. La metodología empleada ha sido la realización de encuestas a estudios de toda España acerca de su nivel de digitalización y su visión de esta, intentando encontrar respuestas que interesan tanto a Escuelas de Arquitectura, como a alumnos y, por tanto, futuros arquitectos. Estas respuestas reflejan la situación existente y los deseos futuros, por lo que pueden servir tanto como ayuda para diseñar el perfil profesional de los alumnos como para reflexionar sobre el papel de las herramientas digitales en el futuro de la profesión. Peer Reviewed

  • Closed Access English
    Authors: 
    Cañete Cano-Coloma, Alberto;
    Publisher: Universitat Politècnica de València
    Country: Spain

    [ES] Muchos enfoques de Learning from Demonstration (LfD) presentados en los últimos años son métodos probabilísticos para transferir habilidades humanas a los robots. Uno de los enfoques de LfD que se ha desarrollado recientemente es Kernelized Movement Primitives (KMP), un método que utiliza un tratamiento basado en kernel para minimizar la pérdida de información en el aprendizaje de imitación. Este método es capaz de preservar las propiedades de las demostraciones humanas, así como adaptar las trayectorias a situaciones imprevistas en la evitación de obstáculos, mediante la modificación de la configuración de los puntos intermedios pertenecientes a la ruta de referencia. Sin embargo, la definición de estos puntos para modificar una trayectoria es actualmente manual, lo que puede ser un reto para un operador en términos de optimización y consumo de tiempo, lo que lleva a la necesidad de encontrar automáticamente los puntos. Un algoritmo que puede abordar este inconveniente y ha atraído la atención como un tratamiento para problemas de optimización no lineal de alta dimensión es la optimización de enjambre de partículas (PSO). En este trabajo final de máster, se ha propuesto un método de optimización restringida que combina KMP con una extensión 4D del PSO tradicional para lograr una generación restringida que evite obstáculos imprevistos en diferentes tareas, mejorando el posicionamiento y el tiempo de inserción de los puntos intermedios. En esta tesis, PSO se utiliza para mejorar la selección de puntos y pasar la información al KMP para la generación de rutas con el fin de evitar colisiones con obstáculos imprevisibles en el momento de la demostración. Los resultados mostraron que el uso del método de peso de inercia Simulated Annealing y la distancia de Fréchet es el mejor enfoque para encontrar una solución óptima en pocas iteraciones mientras se preserva la forma de la ruta de referencia. Esta integración de KMP con PSO se prueba en dos escenarios reales, donde un 7 DOF Franka está diseñado para realizar tareas de entrega y pick and place. La tesis concluye con una discusión de las trayectorias adaptadas y una presentación de posibles trabajos futuros. [EN] Many Learning from Demonstration (LfD) approaches presented in recent years are probabilistic methods to transfer human skills to robots. One of the LfD approaches that has been recently developed is Kernelized Movement Primitives (KMP), a method that uses a kernel-based treatment to minimize the information loss in imitation learning. This method is able to preserve the properties of human demonstrations, as well as adapt trajectories to unseen situations in obstacle avoidance, by modifying the configuration of via points belonging to the reference path. However, the definition of these points to modify a trajectory is currently manual, which can be challenging for an operator in terms of optimization and time consumption, leading to the necessity of automatically finding the points. An algorithm that can address this inconvenience and has attracted attention as a treatment for high-dimensional nonlinear optimization problems is Particle Swarm Optimization (PSO). In this master thesis, a constrained optimization method has been proposed that combines KMP with a 4D extension of the traditional PSO to achieve a constrained generation that avoids unpredicted obstacles in different tasks, by enhancing the positioning and time insertion of the via points. In this thesis, PSO is used to improve the selection of points and pass the information to the KMP for the path generation in order to prevent collisions with unseen obstacles at the demonstration time. Results shew that using the Simulated Annealing inertia weight method and Fréchet distance is the best approach to find an optimal solution in few iterations while preserving the shape of the reference path. This integration of KMP with PSO is tested in two real scenarios, where a 7 DOF Franka is designed to perform handover and pick and place tasks. The thesis concludes with a discussion of the adapted trajectories and a presentation of possible future work.

  • Open Access
    Authors: 
    Vadell Guiral, Enric; Pemán García, Jesús; Verkerk, Pieter Johannes; Erdozain, Matilde; Miguel Magaña, Sergio de;
    Publisher: Elsevier BV
    Country: Spain
    Project: EC | SUPERB (101036849), EC | GenTree (676876)

    Because forests provide a myriad of essential services to society, sustainable forest management that considers and promotes the multifunctional role of forests is of key importance. Understanding how forests have been and are being managed is essential to learn how current forest landscapes have been shaped and how management could be improved to better address all societal needs. Spain makes for an interesting case study due to its dramatic expansion in forest cover over the last 150 years following ambitious national reforestation and afforestation initiatives, as well as for its diversity of forest ecosystems and management approaches. However, a national-level assessment of such a development is currently missing. Therefore, our objective was to document and analyse the development of forest management practices in Spain since the mid-20th century. We developed narratives to describe the trends in 11 indicators of forest management decision-making and practices. Results show that while some decisions have evolved towards promoting multifunctionality (e.g., soil cultivation), others have intensified to maximize production at the expense of other ecosystem services (e.g., naturalness of tree species) and others have not changed much during the past 80 years (e.g., type of regeneration). The analysis also showed that some of the indicators have been conditioned by technological innovations (e.g., machine operation) and by the development of certain policies and legislation (e.g., the application of chemical agents). Based on these trends, we identified the main challenges that forest management in general, and in Spain in particular, may face as well as some decisions that may have to be reconsidered (cutting regime, tree maturity, naturalness of tree species) if the country wants to transition towards alternative silvicultural approaches that promote multifunctionality. In addition, a transition towards mixed-species, uneven-aged forests alongside with genetic improvement of tree species would also facilitate rising to one of the main challenges that forest management faces: to develop a climate-smart forestry that contributes to the mitigation of and adaptation to global change. SdM benfitted from a Serra-Húnter Fellowship provided by the Government of Catalonia. PJV contributed to this research as part of the GenTree project, which has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 676876. ME and SdM also contributed to this research as part of the SUPERB project, which has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 101036849.

  • Open Access
    Authors: 
    González-Gómez, L.; Intrigliolo, Diego S.; Rubio-Asensio, José S.; Buesa, Ignacio; Ramírez-Cuesta, Juan M.;
    Publisher: Elsevier BV
    Country: Spain

    Current water scarcity scenario has led to the implementation of sustainable agricultural practices intended to improve water use efficiency. The present work evaluates during three agricultural campaigns (2018-2020) the response of a young almond orchard to two management practices in terms by combining remote sensing indexes (Normalized Difference Vegetation Index, NDVI; and Soil Adjusted Vegetation Indexes, SAVI) and physiological/ morphological measurement (stem water potential, Ψstem; trunk perimeter and canopy diameter). The management practices included (I) sustained deficit irrigation and (II) soil management. Severe deficit irrigation resulted in lower vegetation indexes (VI) values, Ψstem and tree dimensions (13 %, 23 % and 14 % lower, respectively) than those obtained for full irrigation strategy; whereas moderate deficit irrigation did not affect any of the parameters analysed. The presence of vegetation cover in the inter-row resulted in a VIs increase (19-42 %) and in lower tree dimensions (reductions of 7-8 % for trunk perimeter and 0.34-0.37 m for canopy diameter) when compared to bare soil treatment, but did not have any influence on Ψstem. The present study proves the suitability of remote sensing and physiological measurements for assessing almond response to the different management practices.

  • Open Access English
    Authors: 
    Miguel Angel Lopez-Carmona;
    Publisher: Elsevier
    Country: Spain

    Behavioral modification using active instructions is a promising interventional method to optimize crowd evacuations. However, existing research efforts have been more focused on eliciting general principles of optimal behavior than providing explicit mechanisms to dynamically induce the desired behaviors, which could be claimed as a significant knowledge gap in crowd evacuation optimization. In particular, we propose using dynamic distancekeeping instructions to regulate pedestrian flows and improve safety and evacuation time. We investigate the viability of using Model Predictive Control (MPC) techniques to develop a behavioral controller that obtains the optimal distance-keeping instructions to modulate the pedestrian density at bottlenecks. System Identification is proposed as a general methodology to model crowd dynamics and build prediction models. Thus, for a testbed evacuation scenario and input?output data generated from designed microscopic simulations, we estimate a linear AutoRegressive eXogenous model (ARX), which is used as the prediction model in the MPC controller. A microscopic simulation framework is used to validate the proposal that embeds the designed MPC controller, tuned and refined in closed-loop using the ARX model as the Plant model. As a significant contribution, the proposed combination of MPC control and System Identification to model crowd dynamics appears ideally suited to develop realistic and practical control systems for controlling crowd motion. The flexibility of MPC control technology to impose constraints on control variables and include different disturbance models in the prediction model has confirmed its suitability in the design of behavioral controllers in crowd evacuations. We found that an adequate selection of output disturbance models in the predictor is critical in the type of responses given by the controller. Interestingly, it is expected that this proposal can be extended to different evacuation scenarios, control variables, control systems, and multiple-input multiple-output control structures. Ministerio de Economía y Competitividad

  • Open Access English
    Authors: 
    Qin Xin; Mamoun Alazab; Vicente García Díaz; Carlos Enrique Montenegro-Marin; Rubén González Crespo;
    Country: Spain

    Sustainable energy management is an inexpensive approach for improved energy use. However, the research used does not focus on cutting-edge technology possibilities in an Internet of things (IoT). This paper includes the needs for today’s distributed generation, households, and industries in proposing smart resource management deep learning model. A deep learning architecture of power management (DLA-PM) is presented in this article. It predicts future power consumption for a short period and provides effective communication between power distributors and customers. To keep power consumption and supply constant, mobile devices are linked to a universal IoT cloud server connected to the intelligent grids in the proposed design. An effective brief forecast decision-making method is followed by various preprocessing strategies to deal with electrical data. It conducts extensive tests with RMSE reduced by 0.08 for both residential and business data sources. Significant strengths include refined device-based, real-time energy administration via a shared cloud-based server data monitoring system, optimized selection of standardization technology, a new energy prediction framework, a learning process with decreased time, and lower error rates. In the proposed architecture, mobile devices link to a universal IoT cloud server communicating with the corresponding intelligent grids such that the power consumption and supply phenomena continually continue. It utilizes many preprocessing strategies to cope with the diversity of electrical data, follows an effective short prediction decision-making method, and executes it using resources. For residential and business data sources, it runs comprehensive trials with RMSE lowered by 0.08.

  • Restricted
    Authors: 
    Nadal, Ana; Rodríguez-Labajos, Beatriz; Cuerva Contreras, Eva; Josa Garcia-Tornel, Alejandro; Rieradevall Pons, Joan;
    Publisher: Elsevier BV
    Country: Spain

    This study examines urbanization patterns linked to social housing units and the way in which such patterns influence the practice of urban agriculture (UA) in Mexico. Due to the transformations that take place over time in Mexican social-housing units, impervious surfaces tend to increase at the expense of greenspace and UA possibilities. The research aims to identify the negative impact of social housing transformations on UA and suggest a policy framework for sustainable housing development in Mexico. The empirical analysis distinguishes four social housing typologies within two emblematic neighborhoods in the city of Merida, Mexico: Las Magnolias and Ampliación Tixcacal-Opichén. A survey of 157 housing units combines quantitative metrics and qualitative descriptors to unveil the detrimental impact of development on UA. The results show that UA takes place within the building lots and around the housing units, rather than in public urban areas. 60% of the sampled units practiced UA, with traditional backyard gardens being the most common modality. The research findings point to a systematic expansion of impervious surfaces, limitation of both cultivation choices and crop variety, and major restrictions on UA practices. Social housing represents the bulk of residential developments in Mexico (42.7% out of 35.5 million housing units). Left unregulated, the types of social housing transformations that have been empirically verified in this study endanger the availability of green space as the primary resource for UA. This research sheds light on critical policy changes and formulations that are required to enhance UA practices and to establish greener cities and more sustainable housing development. Peer Reviewed