bluuebunny/crossref_metadata_2025 huggingface dataset:
DESAFIOS ÉTICOS E INOVAÇÕES PEDAGÓGICAS: A INTELIGÊNCIA ARTIFICIAL NA EDUCAÇÃO CONTEMPORÂNEA
Authors: Mattozo Elizangela , Cardozo Poliana Fabíula
Published: November 2024

Este estudo sobre o uso da Inteligência Artificial, doravante IA, na educação justifica-se pela crescente incorporação dessa tecnologia nas práticas pedagógicas e a necessidade de explorar seus impactos. O principal objetivo é mapear as tendências emergentes e os desafios éticos relacionados ao uso da IA, bem como investigar as inovações que essa tecnologia pode trazer, especialmente na personalização do ensino. A pesquisa adota uma abordagem qualitativa com base em revisão bibliográfica de 21 artigos recentes, publicados entre 2023 e 2024, coletados através da ferramenta ResearchRabbit.ai, a qual auxilia na descoberta e organização de redes de conhecimento acadêmico. A amostra inclui estudos que tratam do uso de IA em contextos educacionais, excluindo aqueles que se concentram apenas em aspectos técnicos. Os resultados revelam que os desafios éticos são amplamente discutidos nos artigos analisados, com foco em barreiras como a capacitação docente para lidar com novas tecnologias e as dificuldades de implementação. A palavra "desafio" foi frequentemente mencionada, refletindo a preocupação dos autores em relação à adaptação da IA ao ambiente educacional. Entre as inovações destacam-se a personalização do ensino e a gamificação como estratégias promissoras para melhorar o engajamento dos alunos. Espera-se com este estudo destacar que, embora a IA tenha grande potencial para transformar a educação, sua implementação deve ser acompanhada por políticas claras e contínua capacitação dos educadores. A participação ativa de professores, alunos e legisladores no debate sobre o uso da IA é fundamental para garantir que essa tecnologia seja um apoio, e não um substituto, nas interações humanas no processo educacional​.
ESTRATÉGIAS PARA A REDUÇÃO DA RECORRÊNCIA DE CÂNCER DE OVÁRIO EM PACIENTES DE ALTO RISCO: UMA ANÁLISE MULTIMODAL
Authors: Oliveira Ruy Sergio Sampaio Rezende de , Torres Uedson Aparecido de Oliveira , Cardoso Mayara , Aguinaga Eduarda Indio da Costa , Costa Costanza Ferraiuolo de Oliveira , Barreto Filho Luciano da Costa , Paiva Matheus Carvalho Souza , Lustosa Jennifer Mendes , Minamida Sthefany Akemi , Sevciuc Rafaela Cohn
Published: November 2024

O câncer de ovário é uma condição frequentemente associada a alta taxa de recorrência, especialmente em pacientes de alto risco. A presente análise multimodal visa avaliar estratégias terapêuticas para a redução da recorrência dessa neoplasia, com foco nas abordagens mais recentes e eficazes. Foram revisadas intervenções incluindo quimioterapia de manutenção, inibidores de PARP, imunoterapia, terapias direcionadas e intervenções cirúrgicas. A quimioterapia de manutenção demonstrou benefícios significativos na extensão da sobrevida livre de doença, embora sua eficácia seja influenciada pela resposta inicial e características moleculares do tumor. Inibidores de PARP, como olaparib e niraparib, mostraram-se eficazes especialmente em pacientes com mutações BRCA, oferecendo uma redução notável na taxa de recidiva. A imunoterapia e as terapias direcionadas apresentaram resultados variados, com a necessidade de maior pesquisa para determinar a eficácia em subgrupos específicos. Intervenções cirúrgicas, particularmente a citorredução completa, continuam a ser fundamentais no tratamento multimodal, melhorando significativamente os resultados quando combinadas com terapias adjuvantes. A integração dessas estratégias, ajustadas às características individuais dos pacientes, é crucial para otimizar o tratamento e prevenir a recorrência do câncer de ovário. Futuras pesquisas devem focar na personalização dos tratamentos e na avaliação de novas combinações terapêuticas para melhorar os desfechos clínicos.
Análisis de ingresos mediante la aplicación de métodos de suavización exponencial simple, caso Empresa Luis 1
Authors: Farinango Salazar Ronny Alexander , Torres Valarezo Rocío Jamileth
Published: November 2024

El propósito de esta investigación es determinar los ingresos proyectados basados en el volumen de ventas de la empresa Luis 1 S.A. en el cantón Portovelo, en el cual se ha utilizado la técnica de suavización exponencial simple. Para lograrlo, se ha empleado la metodología conocida como estudio de caso, pues es pertinente reconocer que este suceso es único, exclusivo y descriptivo. En este sentido, se ha empleado un enfoque mixto; es decir, cualitativo y cuantitativo que incluye dos entrevistas. Mientras que, en lo cuantitativo, se aplicó la fórmula matemática, que incluye variables como: dato real, dato pronosticado y constante de suavización alfa. Además, se utilizó el método de suavización exponencial simple (para predecir los ingresos por ventas), el cual fue descrito con antelación; empleando diferentes valores de alfa en los cálculos. Este paso fue fundamental, ya que permitió lograr un tercer objetivo específico: obtener pronósticos de ingresos para períodos determinados en la empresa Luis 1 S.A. Asimismo, es necesario indicar que se usó tres valores de constante de suavización: 0.1, 0.5 y 0.9; con la aplicación en la fórmula de suavización exponencial y estas constantes comparan los comportamientos reales frente a los pronosticados.  En última instancia, una de las conclusiones clave de este estudio de caso resalta la importancia de aplicar métodos de pronóstico en la administración. Estos métodos posibilitan comprender el comportamiento futuro de las variables y tomar decisiones acertadas para minimizar el riesgo y maximizar la utilidad.
Modelo conceptual para la reducción de riesgos en la gestión por competencias, en entidades comercializadoras de medicamentos cubanas
Authors: Nápoles Villa Ana Victoria , Marrero Fornaris Clara
Published: November 2024

Este artículo presenta la propuesta de un modelo conceptual para reducir los riesgos en la gestión por competencias de los procesos: selección evaluación del desempeño y formación, a partir de la necesidad, que demandan hoy las organizaciones, de incrementos dinámicos de productividad, calidad e innovación; meta que exige un mayor rendimiento de los recursos humanos, que requieren a su vez incrementar sus competencias a través de un desarrollo permanente. Para el despliegue de esta gestión, se requiere del diseño e implementación de instrumentos que se conviertan en recursos técnicos de vigilancia, que faciliten la identificación, evaluación, tratamiento, monitoreo, control y comunicación de los riesgos, con la finalidad de reducir, prever y controlar las consecuencias que provocan su ocurrencia en este sentido, así como explotar las oportunidades y los beneficios que emergen de la aplicación de estas alternativas, en la mejora  de la gestión de las personas. Para el diseño de este modelo conceptual se estudia la antecedencia teórica en la literatura especializada y se utilizan métodos científicos y empíricos, incluyendo técnicas y herramientas de la Ingeniería Industrial y otras especialidades afines, las cuales permiten identificar las dimensiones y variables que armonizan la gestión de los procesos de gestión de los recursos humanos con los riesgos, a través de la lógica de un conjunto de indicadores. Elementos que permiten modelar la reducción de los riesgos de la gestión por competencias en las entidades que comercializan medicamentos en Cuba.
Estudio de caso manejo de los despidos laborales producto de la pandemia COVID-19
Authors: Mocha Román Verónica Johana , Novillo Díaz Lenin Alexander , Peralta Feijoo Daniel Isaac
Published: November 2024

El presente informe de investigación aborda el manejo de los despidos laborales durante la pandemia COVID-19 en el sector privado del Cantón Machala. El contexto en el que se desarrolla el estudio es la crisis sanitaria generada por la pandemia y su impacto en los esfuerzos de reactivación económica del país. El objetivo principal del estudio es analizar las causas y consecuencias de los despidos laborales provocados por la pandemia en las empresas del Cantón Machala. Para lograrlo, se plantean objetivos específicos como identificar los despidos laborales, analizar las políticas públicas implementadas para su manejo y determinar las afectaciones directas e indirectas de los despidos laborales. La metodología utilizada en el estudio es de tipo descriptivo. Se recopilaron datos a través de encuestas y entrevistas realizadas a trabajadores y empleadores de empresas del sector privado en el Cantón Machala. Además, se llevó a cabo un análisis descriptivo de las categorías de la unidad de análisis para obtener información relevante y responder a los objetivos planteados. En cuanto a los resultados más relevantes, se concluye que es fundamental que las empresas adopten medidas de responsabilidad social empresarial para proteger a sus trabajadores durante la pandemia. También se recomienda que las políticas públicas sean más efectivas y brinden un mayor apoyo a las empresas para evitar los despidos laborales. Por último, se sugiere la realización de futuros estudios para profundizar en la situación laboral del país y proponer medidas más efectivas para proteger a los trabajadores en situaciones de crisis sanitaria.
Factores relacionados e implementación de estrategias para la disminución del ausentismo de citas programadas en la Clínica de Consulta Externa Odontológica Morelos del ISSEMYM
Authors: Ramírez López Israel , Álvarez Botello Julio , Chaparro Salinas Eva Martha
Published: November 2024

Existe una alta incidencia de ausentismo a citas programadas en la Clínica de Consulta Externa Odontológica Morelos (CCEOM) del ISSEMYM, viéndose comprometida la eficiencia en los servicios de consulta externa y especialidad. En esta investigación se efectuaron estrategias de cambio con el objetivo de reducir el ausentismo mediante la implementación de recordatorios de citas y estrategias para disminuir el ausentismo a citas programadas. Los recordatorios son una estrategia efectiva para disminuir el incumplimiento.
“Emprendedurismo”
Authors: Martínez Contreras María Teresa , Beltrán Enríquez José Antonio , Navas Maldonado Er
Published: November 2024

Desde hace ya algunos años es cada día más frecuente escuchar la palabra emprender, entendiéndola como la actitud que adopta una persona en busca de un sueño u objetivo, asumiendo riesgos buscando oportunidades de crecimiento que le provean una mejor calidad de vida, emprendiendo en proyectos en los que se tenga algún tipo de pasión, conocimiento, experiencia o habilidad, de ahí, que su principal motivación es el logro de un objetivo particular o bien obtener independencia económica. Actualmente existen estadísticas con base en estudios realizados por el INEGI que reportan que el 20% de los jóvenes universitarios de Arquitectura, tienen la intención de auto emplearse, montando su propio negocio, estadística dentro de la cual ya se encuentra el protagonista de la historia de emprendimiento que el día de hoy comparto, Ricardo, él es un joven arquitecto que ha decidido aventurarse en un área muy competida saliendo de su zona de confort y aprovechando las oportunidades y características personales y profesionales que posee para ir dejando huellas en lo que le apasiona “La construcción y diseño”.
Los beneficios de la Industria 4.0 en la industria automotriz de Baja California:
Authors: Ceseña Romero Paola Itzel , García Rivera Blanca Rosa , Olguín Tiznado Jesús Everardo
Published: November 2024

El objetivo de este estudio es generar información sobre el contraste entre la teoría y la práctica a través del análisis de un estudio de caso. Utilizando el método deductivo-inductivo, se realiza una entrevista a un experto en la industria automotriz para conocer los beneficios de la Industria 4.0 en el sector. Los resultados evidencian una falta de información sobre el concepto de Industria 4.0, pero demuestran conocimiento de sus derivados, como la manufactura aditiva y el uso de la nube. Las limitaciones incluyen que, dado que la entrevista es individual, el entrevistado puede sentirse cohibido, lo que podría afectar la fluidez de la conversación. La originalidad radica en que, aunque el concepto de Industria 4.0 es ampliamente utilizado en la investigación, no hay muchos estudios desde la teoría fundamentada.
Improvements in the land surface configuration to better simulate seasonal snow cover in the European Alps with the CNRM-AROME (cycle 46) convection-permitting regional climate model
Authors: Monteiro Diego , Caillaud Cécile , Lafaysse Matthieu , Napoly Adrien , Fructus Mathieu , Alias Antoinette , Morin Samuel
Published: November 2024

Abstract. Snow cover modeling remains a major challenge in climate and numerical weather prediction (NWP) models even in recent versions of high-resolution coupled surface–atmosphere (i.e., at kilometer scale) regional models. Evaluation of recent climate simulations, carried out as part of the WCRP-CORDEX Flagship Pilot Study on Convection (FPSCONV) with the CNRM-AROME convection-permitting regional climate model at 2.5 km horizontal resolution, has highlighted significant snow cover biases, severely limiting its potential in mountain regions. These biases, which are also found in AROME numerical weather prediction (NWP) model results, have multiple causes, involving atmospheric processes and their influence on input data to the land surface models in addition to deficiencies of the land surface model itself. Here we present improved configurations of the SURFEX-ISBA land surface model used in CNRM-AROME. We thoroughly evaluated these configurations on their ability to represent seasonal snow cover across the European Alps. Our evaluation was based on coupled simulations spanning the winters of 2018–2019 and 2019–2020, which were compared against remote sensing data and in situ observations. More specifically, the study tests the influence of various changes in the land surface configuration, such as the use of multi-layer soil and snow schemes, the division of the energy balance calculation by surface type within a grid cell (multiple patches), and new physiographic databases and parameter adjustments. Our findings indicate that using only more detailed individual components in the surface model did not improve the representation of snow cover due to limitations in the approach used to account for partial snow cover within a grid cell. These limitations are addressed in further configurations that highlight the importance, even at kilometer resolution, of taking into account the main subgrid surface heterogeneities and improving representations of interactions between fractional snow cover and vegetation. Ultimately, we introduce a land surface configuration, which substantially improves the representation of seasonal snow cover in the European Alps in coupled CNRM-AROME simulations. This holds promising potential for the use of such model configurations in climate simulations and numerical weather prediction both for AROME and other high-resolution climate models.
An Empirical Line approach for Agrowing Camera Aerial Images of inland waters based on exponential fit and in situ water measurements
Authors: Lucchetta Beatriz Cirino , Watanabe Fernanda Sayuri Yoshino , Bernardo Nariane Marselhe Ribeiro , Fialho Rafael de Campos , Imai Nilton Nobuhiro , Tommaselli Antonio Maria Garcia , Roncolato Gustavo Soares
Published: November 2024

Abstract. With the advancement of technology in the area of remote sensing, monitoring the Earth's surface using multispectral cameras attached to unmanned aerial vehicles (UAV) has become promising. However, in many Earth observation applications, it is needed to make compatible the spatial data of images captured by high spatial resolution multispectral sensors with the spectral response of targets on the Earth's surface. This relation is obtained through a radiometric calibration. The empirical line method is commonly used to calibrate the spectral bands of sensors. Thus, applications of this method using linear fit have retrieved negative values in water bodies. So that, attempting different adjustments, as well different reference targets, can solve this issue. In this study, the water quality of small bodies of water was analysed using a Agrowing multispectral camera, which derived negative values when applying linear fit. The aim of this study, therefore, was to fit a radiometric calibration based on empirical line method for Agrowing camera in inland water applications. Besides of standard reference targets, water samples also were attempted because showed a lower radiance response than the darkest (black) calibration target. Two empirical line methods were applied to convert the digital number (DN) from the Agrowing images into remote sensing reflectance (Rrs): linear and exponential. The exponential method showed to be more appropriate, with greater accuracy, unlike the linear method.
Thermal Infrared Image Georeferencing using an Ensemble of Land Cover Predictions
Authors: Madadikhaljan Mojgan , Schmitt Michael
Published: November 2024

Abstract. Precise georeferencing of remote sensing data is usually implemented in a post-processing fashion and is a crucial step for Earth observation applications such as change detection, natural hazard management, and ground target tracking. It is particularly important for small satellites intending to perform temperature monitoring and wildfire detection on a global scale wherein the precise location of fire is to be communicated. The cost-efficient navigating systems on board such satellites are often not capable of providing accurate geolocation information directly due to space and power limitations. Therefore, it is very important to have a globally applicable georeferencing refinement framework that is robust against illuminational and time-relevant scene changes. In this paper, we propose a georeferencing framework for thermal infrared images that consists of ensemble matching of deep learning-based land cover predictions to archival, well-georeferenced land cover maps. We verify the proposed framework on the georeferencing of single-band Landsat thermal imagery. Experimental results show the efficiency and practicality of the method with 72% of the test images geolocated within 1-pixel accuracy with no trajectory information available.
Comparing inpainting techniques for urban object restoration from orbital images
Authors: Nascimento Eduardo Soares , Ferreira Allan Alves Lopes , Cardim Guilherme Pina , Pina Pedro , da Silva Erivaldo Antonio
Published: November 2024

Abstract. Based on the comparison of three established inpainting techniques, namely Criminisi, Beltamio, and Galerne and Leclaire, our study aimed to identify the most effective method for road restoration after extraction and detection using a Mathematical Morphology operators combined with hybrid techniques of digital image processing in remote sensing images. While all techniques were evaluated based on both visual analysis and quantitative metrics, the Criminisi approach emerged as the better choice. Despite introducing some additional noise, this technique demonstrated superior performance in terms of Completeness and overall Quality, achieving approximately 95.23% and 94.56%, respectively. Its ability to accurately reconstruct linear geometries while effectively removing existing noise highlighted its suitability for road restoration tasks.
Assessing Land Use and Cover Changes arising from the 2022 water crisis in Southeast China: A comparative analysis of Remote Sensing Imagery classifications and Machine Learning algorithms
Authors: Nascimento Eduardo Soares , Watanabe Fernanda Sayuri Yoshino , Galo Maria de Lourdes Bueno Trindade , da Silva Erivaldo Antonio
Published: November 2024

Abstract. The water crisis in the southeast region of China in 2022, caused by one of the worst heatwaves on record, was characterized by severe shortages of water resources, leading to challenges for local communities, agriculture, and industry. To analyze changes in land use and land cover (LULC) in the Jialing River region, Chongqing, China, we compared Remote Sensing (RS) imagery classifications before and after the intense heat waves of 2022. We evaluated the performance of two machine learning algorithms, KDTree KNN and Random Forest (RF), in LULC classifications. The classifications were carried out based on the RS images from the OLI/Landsat 8 system, NDWI index, and SRTM data. The model performances were similar, the classification accuracy showed that the RF algorithm was superior to KDTree KNN. The RF LULC classification and area calculation corroborate with the visual analysis, reaffirming the superiority of RF, which shows a decrease in water surface area, unlike DKTree KNN.
Leaf Identification in High-Density LiDAR-RGB Data
Authors: Norberto Isabella Subtil , Faria Junior Clodoaldo Souza , Tommaselli Antonio Maria Garcia , Shimabukuro Milton Hirokazu , Martins-Neto Rorai Pereira , Imai Nilton Nobuhiro , da Silva Matheus Ferreira
Published: November 2024

Abstract. Leaf detection through automated segmentation of 3D data is becoming a crucial technique in many applications of digital agriculture. Some 3D segmentation techniques that can be mentioned are based on normal differences and median normalised vector growth. However, applying these approaches to high canopy density data remains challenging. In this study, we propose a processing flow for leaf detection in high canopy density LiDAR-RGB point clouds. First, a noise removal technique inspired by Moving Least Squares (MLS) was applied to the LiDAR point cloud, and a RGB colour was assigned to each point by combining computer vision and photogrammetric methods. Moreover, once the data were suitable for leaf detection, the branches were filtered using the Statistical Outlier Removal (SOR) filter based on an analysis of the statistical behaviour of the neighbourhood. Afterwards, an unsupervised DBSCAN (Density-Based Clustering Non-Parametric Algorithm) method was used to segment similar points. Finally, the points within each cluster were identified as leaf or non-leaf using the RGB values implemented by our method; ground points were filtered out using a maximum height threshold. As a result, the leaf, non-leaf, and ground point identifiers were correct in 98.9% of cases, with the branch filtering technique SOR proving effectiveness in removing branches with low information loss and without additional complex point densification steps in reconstruction. This SOR-based solution overcomes major challenges in semantic segmentation (leaves and branches) in high-density data and potentially contributes to precision agriculture.
Spatial and temporal variation of water reflectance in an Amazonian estuary: a case study around Tatuoca Island
Authors: Aviz Matheus Dias de , Martinez Jean-Michel , Polidori Laurent
Published: November 2024

Abstract. Studies of water color are related to its optically active components, including suspended sediments. The correlation of this parameter with reflectance data is well documented in the literature, to understand its concentrations and transport in the water body. The spatio-temporal variations of water color in an estuary are affected by various physical and hydrological components, which makes it complex to understand. In this study, we sought to understand the spatio-temporal variation of water color, for sampling purposes, in an estuary on the Amazon coast. To achieve our objectives, we applied geostatistical and statistical tools to test the spatio-temporal variability of water color, based on multisensor reflectance data, Landsat-8/9 and Sentinel-2 in the red band. The spatial variation showed distances of more than 48 m ±4.26 at high tide and 44 m ±7.62 at low tide. For the temporal variation, we found that the monthly variations are significant according to seasonality and have the same variation at different stages of the tide. Therefore, the color of the water in the Tatuoca Island region shows geostatistically and statistically significant spatio-temporal variation. The distances and temporal frequency of sampling should be adjusted according to the tides and seasonality to ensure that data is sampled in accordance with the variations in the environment.
Research on ecological and climate impacts of offshore wind farms based on remote sensing images
Authors: Tang Xinmin , Liu Ting , Zhang Tao , Zou Yunjia , Zhang Wei
Published: November 2024

Abstract. Offshore wind farm (OWF)’s impact on marine ecological environment has attracted widespread attention since its rapid development. The paper uses high-resolution satellite image data to extract the distribution of offshore wind farms (OWFs) in China based on deep learning method. Chlorophyll-a (CHL-a) concentration and sea surface temperature (SST) were used as indicators to analyze the impact of OWFs’ development. We can then draw the following conclusions: 1) From 2016 to 2022, the number of OWFs in China continues to increase, the growth rate reachs 28% in 2022. 2) The construction of OWFs presents a development trend from near sea to far sea and from shallow sea to deep sea. From 2016 to 2022, the new OWFs are mainly concentrated in sea areas with 5-50 meters water depth, accounting for 84.7 % of the total increase in OWFs. 3) The distribution density of OWFs is negatively correlated with CHL-a concentration and SST, the more OWFs, the greater the impact on CHL-a and SST. In one word, our work analyzed the development trend of OWFs in China and evaluated the impact of OWFs’ expansion on marine ecological environment and climate.
Multi-class Object Detection in Urban Scenes Based on Deep Learning
Authors: Wang Yunning , Liu Xianglei , Wang Runjie
Published: November 2024

Abstract. The rapid development of urbanization presents challenges and requirements for multi-class object detection in urban scenes. Accurately identifying buildings, vehicles, and trees in urban scenes can optimize urban planning, traffic management, monitoring environmental conditions, and promote the development of smart cities. Traditional target detection methods perform poorly in complex urban environments, while deep learning technology achieves accurate target recognition and positioning by automatically extracting high-level semantic features. In this study, we chose to use the YOLOv5s algorithm for multi-class target detection in urban scenes. YOLOv5s is a lightweight deep learning model with small storage space and efficient detection speed. In this paper, the Potsdam area data published by ISPRS is used to make the label data of buildings, vehicles and trees. The YOLOv5s algorithm is used to iteratively train the model. The results show that the mAP value detected by the YOLOv5s model can reach 82.83%. The experimental results show that the algorithm shows higher accuracy than SSD and Faster R-CNN in tree detection. Although it has a slight decline in building and vehicle detection, considering the factors such as detection accuracy, speed, and model size, the YOLOv5s algorithm has a better recognition and detection effect for the detection of multi-class targets in urban scenes.
A novel global multi-level terrain data tile production method
Authors: Wang Zhen , Huang Wei , Gao Chang , Wang Cong , Zhao Wenhao , Tang Dejin , Zheng Xinyan , Li Heng , Ding Lei , Han Zhengchang , Zhang Hongping
Published: November 2024

Abstract. Terrain services have increasingly wide applications in urban planning, 3D gaming animation, and other fields. Map websites typically provide terrain services to users in the form of terrain shaded relief tiles. Map tile technology offers a new solution for large-scale concurrent user access. Although terrain shaded relief tiles can effectively represent changes in terrain relief, users cannot adjust the visualized raster images for visualization schemes, making data analysis and applications more challenging. The emergence of Terrain-RGB technology has effectively addressed this limitation. However, currently, internet maps mostly provide multi-level map services to users in the form of web map tile service (WMTS). Terrain-RGB images produced by simple encoding tools may exhibit grid lines when rendered on tiles with a small grid spacing, affecting the usability of Terrain-RGB products. Therefore, this paper proposes a technical approach for producing global multi-level Terrain-RGB products using digital elevation model (DEM), focusing on addressing the issues of gridlines and splicing traces from different scenes DEM data, offering a new solution for map websites to release analyzable terrain services.
Dry mass grassland estimation using UAV ultra-wide RGB images
Authors: da Silva Rebeca Campos Emiliano , Tommaselli Antonio Maria Garcia , Imai Nilton Nobuhiro , Martins-Neto Rorai Pereira , da Silveira Daniel da Silva , Moro Edemar
Published: November 2024

Abstract. Dry mass is an important parameter to optimise grassland management. Traditionally, dry mass values are estimated manually by cutting, drying, and weighing vegetation samples. In large areas of cultivation, this becomes a time-consuming and costly activity. In recent years, many researchers have studied different sensors embedded in Unmanned Aerial Vehicles (UAV) to collect spatial data and estimate biomass using machine learning algorithms for forest and agricultural applications. However, there needs to be more research dealing with estimating production indices for pasture, especially in Brazil, as stated. This study evaluates the feasibility of using the GoPro wide-angle RGB camera on UAVs (Unmanned Aerial Vehicles) to estimate the dry mass of pastures. Different data analysis methods were compared, including the combination of vegetation indices (VIs) values and three-dimensional metrics (3D) extracted from the Canopy Height Model (CHM): all metrics (ALL), three VIs plus four 3D metrics (VI3 + CHM4) and only 3D metrics. Random Forest (RF) machine learning algorithm was used to estimate dry mass. The best results were obtained when merging all the variables from the two flight campaigns, with a coefficient of determination (R2) of 0.80 for the model and a Pearson Correlation Coefficient (PCC) of 0.85 for validation, with a Root Mean Square Error (RMSE%) of 20.5%. In summary, using RGB sensors embedded in UAVs is a promising technique for estimating farm grazing parameters.
Educación interprofesional entre Ingeniería Biomédica y Ciencias de la Salud
Authors: Rios Mariana , Perdiz Natalia P. , Aversano Florencia , Ulla Marina , Risk Marcelo R.
Published: November 2024

La educación interprofesional está relacionada con escenarios educativos donde profesionales o estudiantes de diferentes áreas de conocimiento aprenden con, de y acerca del otro para mejorar la calidad del cuidado en salud. En el presente trabajo describimos nuestras experiencias educativas, llevadas a cabo en la Universidad Hospital Italiano de Buenos Aires.
PELATIHAN APLIKASI SPEECHACE UNTUK MENINGKATKAN KEMAMPUAN BAHASA INGGRIS BAGI GURU
Authors: Riandini Dini , Marlita Reva , Romadoni Nova Salma , Subarkah Pungkas
Published: November 2024

English language skills must be improved, especially for educators or teachers. This is especially problematic for madrasah teachers who are not English graduates. For this reason, speechace application training is needed to improve English language skills for teachers of MI Muhammadiyah, Kedungwuluh, Patikraja, Banyumas. The purpose of the course is to provide knowledge and skills for teachers in optimizing information technology, especially the speechace application to support the improvement of English language skills and abilities in the school environment. The implementation method used is the Community Language Learning (CLL) method which consists of the preparation stage, implementation stage and evaluation stage. The results of this service during the training were active participant participation and the results obtained with the pre-test and post-test pre-test and post-test, then out of 21 participants, 95% of the participants This activity is expected to contribute to efforts to improve English language skills among teachers.
Comunicação interna como ferramenta de gestão de pessoas na XYZ Distribuições
Authors: Silva Andreza Carla da
Published: November 2024

O objetivo deste trabalho apresentar uma pesquisa na qual se faz a proposta de sugestões de melhorias na comunicação interna na empresa XYZ Distribuições. Utilizou-se uma abordagem qualitativa de estudo de caso. O artigo analisa como a XYZ vem crescendo e necessita de ferramentas eficazes para dissolver os problemas que notoriamente vêm aparecendo: funcionários desmotivados, fornecedores perdendo a confiança e clientes mostrando-se insatisfeitos. Foram examinados diferentes canais de comunicação como jornal interno, café da manhã, e-mails e reuniões quinzenais. Destacando suas vantagens e desvantagens. O artigo conclui com propostas de intervenção por estratégias de comunicação interna que promovam um ambiente mais colaborativo e eficaz, sugerindo a utilização de feedback constante e a adoção de tecnologias que facilitem a troca de informações.
Examining bias perpetuation in academic search engines: An algorithm audit of Google and Semantic Scholar
Authors: Kacperski Celina , Bielig Mona , Makhortykh Mykola , Sydorova Maryna , Ulloa Roberto
Published: November 2024

Researchers rely on academic Web search engines to find scientific sources, but search engine mechanisms may selectively present content that aligns with biases embedded in queries. This study examines whether confirmation biased queries prompted into Google Scholar and Semantic Scholar will yield results aligned with a query’s bias. Six queries (topics across health and technology domains such as ‘vaccines’, ‘Internet use’) were analyzed for disparities in search results. We confirm that biased queries (targeting ‘benefits’ or ‘risks’) affect search results in line with bias, with technology-related queries displaying more significant disparities. Overall, Semantic Scholar exhibited fewer disparities than Google Scholar. Topics rated as more polarizing did not consistently show more disparate results. Academic search results that perpetuate confirmation bias have strong implications for both researchers and citizens searching for evidence. More research is needed to explore how scientific inquiry and academic search engines interact.
Desigualdade social na educação pública no período da pandemia da covid-19: análise de produções da área da Educação
Authors: de Souza Ribeiro Camila , Alves da Silva Darcoleto Carina
Published: November 2024

Este texto, a partir do referencial teórico-metodológico materialista histórico-dialético, tem por objetivo explicitar dados de análise sobre como produções acadêmicas da área da Educação abordaram a desigualdade social e seus impactos na educação pública brasileira no período da pandemia da covid-19. Trata-se de uma pesquisa bibliográfica e documental, orientada pelo estado do conhecimento. O levantamento e a seleção de material foram realizados nas bases de dados do Portal de Periódicos e no Catálogo de Teses e Dissertações da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes), contemplando o período de 2020 ao início de 2022. A pesquisa analisou, no total, 34 artigos e dez dissertações de Mestrado. Para tratar da desigualdade social no Brasil, além de bibliografia que discute a temática, utilizaram-se documentos, entre eles, o relatório da Pesquisa Nacional por Amostra de Domicílios (PNAD) Contínua (2021). Os resultados indicam que as produções, ao discutirem a educação na pandemia, apontam reflexos da desigualdade social sobre ela, ainda que, no geral, não avancem na discussão sobre a relação entre os elementos que compõem essa desigualdade.
Model of Bilingual Mathematics Teaching at a Technical University
Authors: Snizhko Nataliia
Published: November 2024

The article highlights issues related to the implementation of bilingual education in Ukrainian technical universities. The study of this problem contributes to the training of engineering specialists who are able to carry out professional activities in the conditions of a foreign-language multicultural environment.
The model and levels of implementation of bilingual higher mathematics teaching/learning for students of engineering and technical specialties is considered. It is noted that the system of bilingual education should be integrated into the general model of the organization of training engineering personnel in a specific specialty. The formation of a certain level of students' foreign language communicative competence is considered as a criterion for the allocation of training stages. The following stages of bilingual mathematics teaching/learning in technical university are distinguished: preparatory, transitional, actual bilingual.
Each stage of bilingual teaching/learning is analyzed in detail from the following points: 1) direction of content (socio-cultural, mathematical, scientific), main unit of content (bilingual didactic element, bilingual subject-thematic module, discipline in a foreign language); 2) organizational forms and methods of training (integrated lectures and practical classes; conversation; project activity; information technologies; traditional, developing learning methods; elective course, special course or optional classes; text information activity; solving language tasks; methods of active learning; soft immersion; problem-based learning, independent work with educational and scientific literature); 3) the ratio of native and foreign languages (duplicative model, additive model, parity model and displacing model).
The designed model of bilingual mathematics teaching/learning ensures the formation of bilingual subject competence in mathematics and provides an interdisciplinary synthesis of subject, linguistic, general technical (engineering) and cultural components.
Vector for Improving the Internal System of Quality Assurance of education in General Secondary Education Institutions of Vinnytsia Region in the 2024/2025 Academic Year
Authors: Fedchyshena Maryna , Murakhovska-Kazmiruk Liudmyla
Published: November 2024

The article reveals the importance for the educational institution the internal system of the education quality ensuring development and functioning in order to overcome educational losses and provide quality educational services.
The authors analyzed the compounds of the functioning an effective internal system of the education quality ensuring in the areas: «Educational environment», «Pedagogical activity of teaching staff», «Students’ evaluation system», «Management processes of an educational institution». In this article substantiated self-assessment conducting of the educational and management processes of the institution. It is determined the necessary units of the functioning accessible, safe, high-quality education in the Vinnytsia region in today's circumstances there. This will allow the teaching staff of general secondary education institutions of Vinnitsa to form a vector of improvement of the internal system of ensuring the quality of education in 2024/2025.
Psychological and Pedagogical Support for Future Technology Teachers in the Educational-Scientific-Production Cluster
Authors: Holiiad Iryna , Rebryna Maryna
Published: November 2024

The article examines the importance of psychological and pedagogical support in the training process of future technology teachers, particularly in the context of modern educational challenges and the full-scale war. This support is aimed at developing emotional intelligence, stress resilience, preventing professional burnout, improving communication skills, and providing supervision. The research emphasizes the formation of teachers' professional identity, as well as their ability for self-analysis and self-reflection. Special attention is given to methods of coping with emotional stress during the war, including relaxation techniques, stress management, the use of positive thinking, and maintaining a work-life balance. The article is based on the experience of the Social and Psychological Center of the Lviv Educational-Scientific-Production Cluster, which focuses its efforts on supporting future teachers through supervision, training, and consultations.
The cluster integrates theoretical knowledge, scientific research, and practical training for specialists in the fields of vocational education and production. This model of teacher training is aimed at enhancing their qualifications, developing professional competencies, and adapting to the demands of the modern labor market.
The study explores the key stages of teacher training, which include foundational theoretical preparation, scientific research, practical internships at production enterprises, and further professional development. Special attention is paid to the implementation of innovative teaching approaches and the use of modern technologies that enable future teachers not only to master new teaching methodologies but also to integrate contemporary production processes into educational programs.
Methodical Principles of Using Mobile Applications in the Professional Training of Future Biology Teachers
Authors: Mironets Liudmyla , Yaroshenko Olga
Published: November 2024

The article explores the methodical principles of using mobile applications during the professional training of future biology teachers in higher educational institutions.
It is determined that the significance of using modern mobile learning tools is driven by the informatization of the educational process and the necessity to develop key information and digital competencies among future teachers. It is emphasized that forced distance learning requires new teaching methods and tools. It has been found that recently almost all students in general secondary education institutions possess and use mobile phones at a professional level. It is proven that smartphones or tablets can be effective learning tools for the educational process, provided that teachers are skilled in their application.
The possibilities of using mobile applications in the educational process of the professional training of future biology teachers are analyzed, revealing methodical approaches to their use: in lectures and laboratory sessions on the methodology of teaching biology, in completing independent work tasks, and in informal or non-formal education.
Creation of Stem-Centers Within Experimental Activities (Best Practices)
Authors: Boiko Svitlana
Published: November 2024

The article is devoted to the analysis of the organization of the creation of STEM centers as innovative educational environments aimed at the formation and development of STEM competencies and creative activity of education seekers, the development of innovative models of education and the professional improvement of pedagogical workers in the STEM direction.
It was found that the organization of the creation of STEM centers requires the provision of organizational, scientific-methodical, material and technical conditions and personnel support. It was determined that the organizational conditions include the development and adoption of the necessary regulatory documents that determine the principles of STEM-centers' activities. The scientific and methodological conditions provide for the development and adaptation of educational programs and educational and methodological materials, lesson plans and manuals focused on the integration of STEM disciplines.
Material and technical conditions provide for the availability of modern equipment, computer classes, laboratories, workshops, software and other technical means and resources. Staffing requires the involvement of qualified teachers, trainers, instructors, methodologists, specialists in STEM disciplines.
The study is aimed at studying the best practices of creating STEM centers within the framework of the implementation of an innovative educational project at the all-Ukrainian level on the topic "Organizational and scientific-methodical conditions for the creation of STEM centers" in 2022-2027.
The author of the article provided practical recommendations for organizing the creation of STEM centers, taking into account the results of the survey of basic educational institutions of the innovative educational project and the needs of modern education.
Virtual Digital Laboratory Vernier as a Tool of Implementing STEM-Education Principles in Physics Lessons
Authors: Shak Olena
Published: November 2024

The article highlights the results of the theoretical and methodological analysis of the issue of the use of the Vernier digital virtual laboratory as an innovative tool for implementing the principles of STEM education in physics lessons in high school. The purpose of this research paper is to justify the feasibility of integrating digital laboratories into the physics curriculum, which allows for its modernization through the integration of science, technology, engineering and mathematics. The study's methodological foundation is based on the active learning concept developed by D. Sokoloff, R. Thornton and P. Laws. According to it, the active nature of learning physics using the Vernier digital laboratory is ensured by the ability to conduct real, high-precision, and multiple measurements of various physical quantities, analyze the obtained data, visualize them as graphs or charts, and interactively adjust and generalize the results of the experiment.
The main advantages and disadvantages of using this innovative learning tool have been analyzed, and its compliance with safety, accessibility and adaptability requirements has been determined.
The content of implementing the scientific, technological, engineering and mathematical aspects of STEM education through the methodology of using the Vernier digital laboratory in physics lessons has been explored. An example of a tentative lesson plan for a physics class using the Vernier digital laboratory is provided.
Based on the conducted research and the practice of using the Vernier digital laboratory in middle school physics lessons, it has been concluded that it has significant and comprehensive educational potential as an innovative tool for implementing STEM education principles.
Formação de professores/as da/na educação infantil e relações étnico-raciais: um relato de experiência
Authors: Onofre Joelson Alves
Published: November 2024

O presente texto é um Relato de Experiência (RE) alusivo ao minicurso Formação de professores/as da/na educação infantil e relações étnico-raciais ministrado no II Seminário de Educação, Diversidade e Direitos Humanos. Objetiva apresentar reflexões relacionadas à formação de professores da educação infantil em interface com as questões étnico-raciais. O diálogo com os docentes dessa etapa da educação fez surgir várias problemáticas que permitem repensar a formação inicial e continuada no que tange às discussões relacionadas a uma educação infantil antirracista. Trata-se de um relato de abordagem qualitativa que teve como estratégia metodológica, dinâmicas, exposição dialogada, exibição de slides e debates. As questões surgidas possibilitaram aos professores repensar suas práticas pedagógicas, bem como reavaliar suas posturas e atitudes em relação ao racismo presente no campo educacional. O minicurso, enquanto proposta formativa, contribuiu para uma mudança de mentalidade e colaborou para o pensamento crítico-reflexivo no âmbito da educação para as relações raciais.