1,721,021 research outputs found
Asistencia de la SEMh a la presentación del informe "Mujeres e Innovación 2023"
No full textEl día 06 marzo tuvo lugar en la Fundación Ortega Marañón la presentación del informe 'Mujeres e Innovación 2024', una publicación bienal realizada desde 2020 por el Observatorio Mujeres, Ciencia e Innovación del
Ministerio de Ciencia, Innovación y Universidades (MICIN) en colaboración con la Fundación Española para la Ciencia y la Tecnología (FECYT). A este evento, la Sociedad Española de Malas Hierbas acudió como invitada. Este informe analiza la situación y evolución de la (des)igualdad de género en el ámbito de la innovación, con especial atención a las brechas de género y a los retos a los que ASISTENCIA DE LA SEMh A LA PRESENTACIÓN DEL INFORME “MUJERES E INNOVACIÓN 2023” (por Ana de Castro)
deben responder las políticas de igualdad en la I+D+I. Esta ocasión incluye, por primera vez, opiniones de mujeres recabadas a través de encuestas anónimas, de grupos de discusión y de entrevistas en profundidad grabadas, donde se destaca que la gran mayoría de ellas comenzaron en la innovación y siguen en ésta para producir un impacto positivo en su entorno, siendo la financiación una las principales dificultades que encuentran a la hora de innovar.El informe, su resumen ejecutivo y la serie pueden consultarse en Mujeres e
Innovación (ciencia.gob.es) o visualizar el video del evento en
https://www.youtube.com/watch?v=3zUVEne0vRkPeer reviewe
Jornada de transferencia sobre tecnologías,digitales para la eficiencia del riego y aplicaciones en Agricultura de Precisión (AP)
No full textPara más información, visitad el video de las Jornadas de Transferencia en:
https://www.youtube.com/watch?v=LUhNuUOruacEl pasado día 25 de abril se celebró en la finca experimental vitivinícola El Socorro (Colmenar de Oreja, Madrid), la Jornada de Transferencia sobre “Tecnologías Digitales para la Eficiencia del Riego y Aplicaciones en Agricultura de Precisión” en la que se abordó el uso de herramientas tecnológicas aplicadas al manejo de la viña en el contexto de la Agricultura de Precisión (AP), concretamente al riego, suelo, malas hierbas y aplicación de fitosanitarios, desde el punto de vista científico, técnico y empresarial. Esta jornada se
enmarca en el proyecto europeo DATI del programa PRIMA, orientado al desarrollo y validación de nuevas soluciones tecnológicas para mejorar la eficiencia del riego en cultivos de la cuenca mediterránea. Ha sido organizado por el grupo de investigación Tech4Agro del Instituto de Ciencias Agrarias (ICA-CSIC) y el grupo Agricultura Sostenible y Ecología de Suelos (ASES) del Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), en colaboración con el Instituto Madrileño de Investigación y Desarrollo Rural, Agrario y Alimentario (IMIDRA).Peer reviewe
DRONEWEED: DRONE imagery dataset for early-season WEED classification
No full text[Description of methods used for collection/generation of data] Data were acquired through an RGB camera mounted on a UAV at an altitude of 11m.Identification of weed species at the early stages of growth is critical for precision agriculture. Accurate detection and classification to species level allows targeted control measures to be taken, significantly reducing pesticide use. This dataset consists of RGB images, captured with a Sony ILCE-6300L camera mounted on an unmanned aerial vehicle (UAV) at 11 meters altitude. The dataset covers several agricultural fields in Spain, focusing on two summer crops: corn and tomato. It is designed to improve the accuracy of early season weed detection by including images from two phenological stages. Specifically, the dataset contains 31,002 labeled images from the early growth stage - maize with four leaves unfolded (BBCH14) and tomato with the first flower bud visible (BBCH501) - as well as 36,556 images from a later growth stage - maize with seven leaves unfolded (BBCH17) and tomato with the ninth flower bud visible (BBCH509). In maize, weed species include Atriplex patula, Chenopodium album, Convolvulus arvensis, Datura ferox, Lolium rigidum, Salsola kali and Sorghum halepense. In tomato, weed species include Cyperus rotundus, Portulaca oleracea and Solanum nigrum. The images, stored in JPG format, were labeled by partitioning orthomosaics, with each image corresponding to a specific plant species. This dataset is ideal for developing advanced deep learning models, such as CNN and ViT, for early detection and classification of weed species in corn and tomato crops using UAV imagery. By providing this dataset, we aim to advance UAV-based weed detection and mapping technologies, contributing to precision agriculture with more efficient and accurate tools that promote sustainable and profitable agricultural practices.This work was supported by the Spanish Research State Agency (AEI) through the Project PID2020-113229RB-C41/AEI/10.13039/501100011033. The lead author, G.A. Mesías-Ruiz has been a beneficiary of a FPI fellowship by the Spanish Ministry of Education and Professional Training (PRE2018-083227).Peer reviewe
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Unmanned Aerial Vehicle Imagery for Early Stage Weed Classification and Detection in Maize and Tomato Crops
No full text[Description of methods used for collection/generation of data] Data were acquired through an RGB camera mounted on a UAV at an altitude of 11m. From the images obtained by the UAV, geomatic products were systematically generated for the creation of orthomosaics. This task was performed by incorporating information extracted from the RGB channels using Agisoft PhotoScan software (Agisoft LLC, St. Louis, MO). The resulting orthomosaics were subdivided into smaller sections. To identify and label weed species, malherbology experts carried out the task manually. This involved drawing bounding boxes around each plant and annotating various visible objects present in each divided image. This process was executed using the graphical tool labelImg open source software. The final result consists of a collection of individual images, each corresponding to a specific label, i.e., to each plant of each identified species.The dataset, titled 'Unmanned Aerial Vehicle Imagery for Early Stage Weed Classification and Detection in Maize and Tomato Crops,' comprises RGB images captured from an unmanned aerial vehicle flying at an altitude of 11 meters. These images were taken during the early growing season of two summer crops: Maize (BBCH14) at the CSIC experimental farm La Poveda in Arganda del Rey, Madrid, Spain, and Tomato (BBCH501) in commercial plots located in Santa Amalia, Badajoz, Spain. The dataset includes 33,467 labels representing weeds (Atriplex patula, Chenopodium album, Convolvulus arvensis, Cyperus rotundus, Lolium rigidum, Portulaca oleracea, Salsola kali, Solanum nigrum) and crops (maize, tomato). All images are saved in *.jpg format and have been labeled using partitions extracted from an orthomosaic. The final result consists of a collection of individual images, each corresponding to a specific label, i.e., to each plant of each identified species.This work was supported by the Spanish Research State Agency (AEI) through the Project PID2020-113229RB-C41/AEI/10.13039/501100011033. The lead author, G.A. Mesías-Ruiz has been a beneficiary of a FPI fellowship by the Spanish Ministry of Education and Professional Training (PRE2018-083227).Peer reviewe
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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