Artículos y presentaciones en Congresos

URI permanente para esta colecciónhttps://digital.cic.gba.gob.ar/handle/11746/543

Examinar

Envíos recientes

Mostrando 1 - 20 de 318
  • Artículo
    Acceso Abierto
    Research Infrastructures in Citizen Science: State of Knowledge and Taxonomic Framework As a Pathway to Sustainability
    (2025) Soacha-Godoy, Karen; Prakash, Pranesh; Álvarez, Ana; Giraldo Tejada, Adriana; López-Borrull, Alexandre; Salvador, Xavier; Rodero, Carlos; Torres, Diego; Rodero, Iván; Ayure, Mabel; Piera, Jaume
    Citizen science platforms (CSPs) and citizen observatories (COs) are rapidly expanding research infrastructures (RIs) that support the growth of citizen science. These systems have boosted data collection capabilities and broadened participant engagement across spatial and demographic dimensions. Despite their essential role in advancing citizen science, the current state of knowledge of these infrastructures remains largely unexplored, affecting both theoretical understanding and practical implementation. The study discussed herein addresses this knowledge gap through a systematic review of 474 articles, with in-depth analysis of 72 publications spanning a 15-year period across multiple disciplinary domains. The methodological framework integrates bibliometric analysis with qualitative investigation, utilizing Web of Science and Scopus databases, supplemented by grey literature from Zenodo and Google Scholar. Findings indicate that research in this field has developed across three main waves: technological development and engagement, monitoring systems and openness, and frontiers technologies. This evolution reflects a progression in the CSP body of knowledge from technical documentation to complex socio-technological systems. Analysis of 450 articles identified 98 unique terms referring to CSPs, highlighting conceptual fragmentation. To clarify the landscape of overlapping, we propose a CSP purpose-based taxonomic framework comprising nine platform categories, contributing to a clearer understanding of the CSPs’ role in citizen science. Additionally, our systematic analysis reveals key research trajectories essential for strengthening CSPs and COs as sustainable infrastructures.
  • Artículo
    Acceso Abierto
    Ciencia Ciudadana en el arbolado urbano: integración interdisciplinaria, nuevos aportes
    (2025) Nazarre, Rosalina Amneris; Correa, Natalia; de Antueno, Lucía; Delpino, Juan Pablo; Fernández, Alejandro; Torres, Diego
    Este artículo es una extensión de un trabajo realizado en 2023 en donde se presentaron las actividades realizadas en el marco del proyecto de extensión de la Facultad de Informática de la Universidad Nacional de La Plata (UNLP) titulado “Ciencia Ciudadana en el censado del arbolado urbano". Aquí, de forma complementaria, se mencionan los nuevos aportes propuestos desde una mirada cualitativa e interdisciplinaria y los resultados obtenidos en la experiencia.
  • Artículo
    Acceso Abierto
    El uso de la Inteligencia Artificial (IA) y Procesamiento de Lenguaje Natural (PLN) para mejorar la transparencia del servicio de Justicia
    (2024) Giannini, Leandro; Martínez, Diego; Delle Ville, Juliana; Antonelli, Leandro; Grigera, Julián
    Se presentan en este trabajo los resultados de la segunda fase del proyecto de implementación de herramientas de inteligencia artificial y procesamiento de lenguaje natural en la producción de indicadores del funcionamiento de la Corte Suprema (CS). El proyecto, desarrollado en colaboración por integrantes del Instituto de Derecho Procesal y del Laboratorio de Investigación y Formación en Informática Avanzada, ambos de la Universidad Nacional de La Plata, busca promover la incorporación de herramientas de IA y PLN para favorecer prácticas de transparencia activa en la órbita del sistema de justicia.
  • Artículo
    Acceso Abierto
    Investigating STEM Students’ First-Time Experience with Smart Glasses
    (2022) Santana, Ronny; Rossi, Gustavo Héctor; Méndez, Gonzalo Gabriel; Rybarczyk, Yves; Vera, Francisco; Rodríguez, Andrés
    We study how STEM students experience the use of smart glasses for the first time. We evaluate the glasses’ usability, degree of technological acceptance, experience, and elicited emotional response. To this end, we resort to several quantitative instruments and semistructured interviews. We found that students greatly appreciate the potential and current support that smart glasses and AR provide as educational tools. We discuss our findings and identify opportunities for further research with these devices to support educational activities.
  • Artículo
    Acceso Abierto
    A co-training model based in learning transfer for the classification of research papers
    (2024) Cevallos-Culqui, Alex; Pons, Claudia Fabiana; Rodríguez, Gustavo
    A multitude of scholarly papers can be accessed online, and their continual growth poses challenges in categorization. In diverse academic fields, organizing these documents is important, as it assists institutions, journals, and scholars in structuring their content to improve the visibility of research. In this study, we propose a co-training model based on transfer learning to classify papers according to institutional research lines. We utilize co- training text processing techniques to enhance model learning through transformers, enabling the identification of trends and patterns in document texts. The model is structured with two views (titles and abstracts) for data preprocessing and training. Each input employs different document representation techniques that augment its training using BERT's pre-trained scheme. For evaluating the proposed model, a dataset comprising 898 institutional papers is compiled. These documents undergo classification prediction in five or eleven classes, and the model performance is compared with individually trained models from each view using the BART pre-trained scheme and combined models. The best precision level of 0,87 has been achieved, compared to BERT pre-trained model's metric of 0,78 (five classes). These findings suggest that co-training models can be a valuable approach to improve the predictive performance of text classification.
  • Artículo
    Acceso Abierto
    AGUTER a platform for Automated Generation of User Acceptance TEsts from Requirements Specifications
    (2021) Antonelli, Leandro; Camilleri, Guy; Torres, Diego; Zarate, Pascale
    This article proposes a strategy to make the testing step easier, generating User Acceptance Tests (UATs) in an automatic way from requirements artifacts. [Design/methodology/approach] This strategy is based on two modeling frameworks: Scenarios and Task/method paradigm. Scenarios is a requirement artifact used to describe business processes and requirements, and Task/Method paradigm is a modeling paradigm coming from the Arti-ficial Intelligence field. The proposed strategy is composed of four steps. In the first step, scenarios are described through a semantic wiki website. Then scenarios are automatically translated into a task/method model (step two). In the third step, the Task/method model obtained in step two is executed in order to produce and store all possible achievements of tasks and thus scenarios. The stored achievements are saved in a data structure called execution tree. Finally, from this execution tree (step four), the user acceptance tests are generated. [Findings] The feasibility of this strategy is shown through a case study coming from the agriculture production systems field. [Originality/value] Generally, test design approaches deal with a small number of variables describing one specific situation where a decision table or workflow is used to design tests. Our proposed approach can deal with many variables because we rely on scenarios that can be composed in order to obtain a tree with all the testing paths that can arise from their description.
  • Artículo
    Acceso Abierto
    Alfadatizando 2.0 applied to data visualization at high school level and for digital humanities: empowering digital citizens
    (2025) Lliteras, Alejandra Beatriz; Artopoulos, Alejandra; Ger, Julián; Boza, Gerónimo
    Given the great evolution and transformation of digital technologies and their penetration in different aspects of daily life, there is a need to provide equal possibilities and equal rights to access them, which implies training digi-tal citizens. On the other hand, digital technology and some methods of social sciences and computer science to visualize data, support what is known as digi-tal humanities. These add computational thinking and create new kinds of jobs, skills and specific knowledge. Currently there are several efforts to add their teaching at the higher level, however, there is little evidence of their presence at the high school level. With the aim of promoting the formation of digital citi-zens by considering aspects of computational thinking through data visualiza-tion in digital humanities, this paper first analyzes articles that consider the teaching of digital humanities in order to know the visualization methods ap-plied. A platform to make educational activities considering some of the sur-veyed methods is presented, a case study considering a curricular design is pro-posed and a proof of concepts from the above is performed. The results of the survey analysis show, on the one hand, the use of certain data visualization methods in the teaching of digital humanities at high school level, on the other hand, the feasibility of using the proposed platform for the defined case study and the viability to develop digital skills and computational thinking in students. This is considered a contribution to the empowerment of digital cit-izens from the high school level.
  • Artículo
    Acceso Abierto
    Rethinking Breath in VR: A Performative Approach to Enhance User Flow with Bio-sensing Wearable Interfaces
    (2025) Duarte, Yesica; Rodríguez, Andrés
    Asignificant number of Virtual Reality (VR) applications focus on mindfulness, using biosensor technologies (e.g., ECG) to provide real-time feedback on users’ physiological states. However, the measurement of data for the human body is complex. Commercial devices often lack precision, while medical-grade sensors require controlled environments, which can lead to disruptions and break immersion, affecting the flow of VR experiences. Thus, complicating the evaluation of mindfulness. Pinch To Awaken XR is a VR art game that utilizes wearable interfaces to measure breathing from a holistic perspective. Showcased as an Extended Reality (XR) performance, it uses first-person research methods by embodying both the researcher and performer, placing the body as the central source of inquiry. This case study reveals that integrating a performative approach can enhance the flow and engagement in mindfulness VR experiences, while also offering a novel approach for evaluating biosensing interfaces in HCI user studies, using a body-centered design.
  • Documento de conferencia
    Acceso Abierto
    Teaching digital humanities at high school level
    (2025) Lliteras, Alejandra Beatriz; Artopoulos, Alejandro Martín
    The incorporation of digital technology in educational environments was usually thought of from a didactic and/or pedagogical perspective. However, the digital transformation driven by smartphones, platforms and generative artificial intelligence showed that curricular and/or epistemological aspects had to be considered, such as the incorporation of programming and computational thinking in basic education. Within this line of research, it is particularly productive to inquire about the incorporation of digital humanities at the high school level. The objective of this work is to know through a first literature review, the implementation of educational experiences in the field of digital humanities at the high school level of articles from academic sources. In addition to present global and local initiatives of innovative aspects in digital education. The analysis addresses the description of the fields in which relevant cases of teaching experiences were found, the digital methods used as well as the emergence of new emerging curricular areas such as Digital Citizenship. The conclusions point out the areas of opportunity for the development of knowledge areas, topics, applications and didactic materials to continue the development of the teaching of humanistic or digital humanistic computational knowledge at the high school level.
  • Documento de conferencia
    Acceso Abierto
    Adversarial image generation using geneticalgorithms with black-box technique
    (2023) Pérez, Gabriela Alejandra; Pons, Claudia Fabiana
    Convolutional neural networks are a technique that has demon-strated great success in computer vision tasks, such as image classifica-tion and object detection. Like any machine learning model, they havelimitations and vulnerabilities that must be carefully considered for safeand effective use. One of the main limitations lies in their complexityand the difficulty of interpreting their internal workings, which can beexploited for malicious purposes. The goal of these attacks is to makedeliberate changes to the input data in order to deceive the model andcause it to make incorrect decisions. These attacks are known as adver-sarial attacks. This work focuses on the generation of adversarial im-ages using genetic algorithms for a convolutional neural network trainedon the MNIST dataset. Several strategies are employed, including tar-geted and untargeted attacks, as well as the presentation of interpretableand non-interpretable images that are unrecognizable to humans but aremisidentified and confidently classified by the network. The experimentdemonstrates the ability to generate adversarial images in a relativelyshort time, highlighting the vulnerability of neural networks and the easewith which they can be deceived. These results underscore the impor-tance of developing more secure and reliable artificial intelligence systemscapable of resisting such attacks
  • Artículo
    Acceso Abierto
    Semi-supervised learning models for documentclassification: A systematic review and meta-analysis
    (2023) Cevallos-Culqui, Alex; Pons, Claudia Fabiana; Rodríguez, Gustavo
    The proliferation of digital documents in the internet has given rise to the search for informationpatterns that allow for the categorization of organizational documents to generate knowledge in a institution.One of the Artificial Intelligence techniques for this purpose is text classification, which for its application useslabels (categorized documents) with supervised (with labels) or unsupervised (without labels) training models.Both traditional models with their advantages and disadvantages have been consolidated into semi-supervisedmodels to extract the best qualities of each one, however, the labeling process involves resources that need to beoptimized to improve the classification accuracy. An analysis of the types of semi-supervised models would showthe strengths of their training and how the structure of each of them affects the accuracy of their classification. Thepresent study proposes a structure of semi-supervised model in document classification, in order to analyze thequalities of each one in their categorization process, it through a systematic literature review (SLR) that analyzesthe performance of the studies to conduct a meta-analysis. Further, the study search strategy was defined by thePICOC method (Population, Intervention, Comparison, Outcome, Context), supported by two research questionsand delimited in a search chain that allowed the collection of 332 research studies. These papers were filteredusing the PRISMA method and the determination of exclusion criteria, in total 46 papers have been selected forthe present study.From this SLR, an organizational structure has been obtained for semi-supervised models anda scheme for the classification process. In addition, the advantages and disadvantages of different learning typeshave been analyzed, evaluating their classification performance in each type of learning through a meta-analysis.This has determined that the models that present the best levels of performance are active learning model (0.88)and ensemble learning model (0.84)
  • Artículo
    Acceso Abierto
    Rule Extraction in Trained Feedforward Deep Neural Networks: Integrating Cosine Similarity and Logic for Explainability
    (2024) Negro, Pablo Ariel; Pons, Claudia Fabiana
    Explainability is a key aspect of machine learning, necessary for ensuring transparency and trust in decision-making processes. As machine learning models become more complex, the integration of neural and symbolic approaches has emerged as a promising solution to the explainability problem. One effective solution involves using search techniques to extract rules from trained deep neural networks by examining weight and bias values and calculating their correlation with outputs. This article proposes incorporating cosine similarity in this process to narrow down the search space and identify the critical path connecting inputs to final results. Additionally, the integration of first-order logic (FOL) is suggested to provide a more comprehensive and interpretable understanding of the decision-making process. By leveraging cosine similarity and FOL, an innovative algorithm capable of extracting and explaining rule patterns learned by a feedforward trained neural network was developed and tested in two use cases, demonstrating its effectiveness in providing insights into model behavior.
  • Documento de conferencia
    Acceso Abierto
    Extracción de reglas de redes neuronales feedforward entrenadas con lógica de primer orden
    (2024) Negro, Pablo; Pons, Claudia Fabiana
    La necesidad de integración neural-simbólica se hace evidente a me-dida que se abordan problemas más complejos, y que van más allá de tareas de dominio limitadas como lo es la clasificación. Los métodos de búsqueda para la extracción de reglas de las redes neuronales funcionan enviando combinaciones de datos de entrada que activan un conjunto de neuronas. Ordenando adecuada-mente los pesos de entrada de una neurona, es posible acotar el espacio de bús-queda. Con base en esta observación, este trabajo tiene por objetivo presentar un método para extraer el patrón de reglas aprendido por una red neuronal entrenada feedforward, analizar sus propiedades y explicar estos patrones a través del uso de lógica de primer orden (FOL)
  • Artículo
    Acceso Abierto
    Evaluation of Transfer Learning Techniques in Neural Networks with Tiny-scale Training Data
    (2023) Pérez, Gabriela Alejandra; Jacinto, Milagros; Moschettoni, Martín; Pons, Claudia Fabiana
    This paper rigorously analyzes the process of building a deep neural network for image recognition and classification using Transfer Learning techniques. The biggest challenge is assuming that the training dataset is very small. The research is based on addressing a particular case study, the income of donations to the Food Bank of La Plata. The results obtained corroborate that the techniques analyzed are appropriate to solve tasks of detection and classification of images even in cases in which there is a very moderate number of samples.
  • Documento de conferencia
    Acceso Abierto
    A baseline underwater soundscape of an intensely human-exploited estuarine and the effects of vessel traffic sound
    (2024) Pons, Juan; Uibrig, Román; Molina, Juan; Pons, Claudia Fabiana
    In this article, we studied the anthropically impacted natural environmental sound in the port of Bahía Blanca, located in the southern province of Buenos Aires, Argentina. To acquire the acoustic signals, an omni-directional passive hydrophone was used. The acoustic signals were analyzed using scripts implemented in the R programming language. Temporal series without maritime traffic were used as a baseline to describe the soundscape in the harbour area by estimating its power spectral density (PSD). Subsequently, the acoustic environment was analyzed with the presence of two man-made acoustic sources: "boat" and "ship" in the vicinity. Finally, the calculated normal soundscape level in the harbour has a magnitude of 116.25 dB re 1 µPa.
  • Documento de conferencia
    Acceso Abierto
    Método_SCGE validando las cuatro etapas en un organismo gubernamental
    (2024) Castro, Marcelo; Pons, Claudia Fabiana; Rodríguez, Rocío Andrea
    En el presente trabajo se realiza la validación de las cuatro etapas correspondientes a la metodología para sistematizar y estandarizar los procesos de Gobierno Electrónico en la gestión pública, a través de servicios computacionales (metodo_SCGE). Esta metodología considera software, hardware y comunicaciones, el análisis de estos componentes permite generar un modelo integral basado en Servicios Computacionales para Gobierno Electrónico (SCGE). El artículo contiene una presentación de algunas metodologías existentes que se pueden aplicar a servicios computacionales, una breve descripción de metodo_SCGE, incluyendo componentes, características, etapas y actividades. Al final se presenta la validación de las cuatro etapas, sobre un servicio específico perteneciente a un organismo gubernamental.
  • Documento de conferencia
    Acceso Abierto
    Identification of biological properties in organismsusing Machine Learning techniques on wholegenome sequences
    (2023) Ferella, Nicolas; Pizio, Pablo
    The advance in technology and genome sequencing processes in the recentdecades have made large volumes of biological data available to researchers fromall over the world, which, due to the large scales, are difficult to analyze in theirentirety. Therefore, it is intuitive to think of Artificial Intelligence to work withsuch information.In order to reduce the existing gap between the researchers and the ArtificialIntelligence tools, a software was developed that allows the creation of a works-pace for biological organisms, the processing of its corresponding genomes, andthe creation and training of models of Machine Learning, everything using asimple (yet powerful) graphical interface.The trained models are then analyzed to find which patterns determine theresult of the property that is being investigated on the biological organism,finding in the process the genes with the greatest impact on the model’s predic-tions, allowing the researcher to subsequently analyze the desired genes in thelaboratory, saving time and resources in the process
  • Documento de conferencia
    Acceso Abierto
    El desafío de Scrum distribuido en diferentes locaciones
    (2023) Salazar, Joaquín; Grimaldi, Pablo; Pons, Claudia
    En las últimas décadas la tecnología ha avanzado rápidamente y con ella la forma de trabajo de todas las personas relacionadas con IT, hoy en día es totalmente normal que un equipo esté integrado por personas que están en diferentes ciudades del mundo, trabajando de manera remota o con diferentes husos horarios e idiomas. Al mismo tiempo, el uso de las metodologías ágiles; principalmente Scrum, ha tenido un gran crecimiento en su implementación. Por esta razón es oportuno poder realizar un análisis de todos los desafíos que implica usar Scrum de manera distribuida, brindando además un aporte de posibles soluciones y consejos para afrontarlos.
  • Documento de conferencia
    Acceso Abierto
    Validando la segunda etapa de metodo_SCGE en un organismo gubernamental
    (2023) Castro, Marcelo; Pons, Claudia Fabiana; Rodríguez, Rocío Andrea
    En el presente trabajo se realiza la validación de la segundaetapa correspondiente a la metodología para sistematizar y estandarizar los procesos de Gobierno Electrónico en la gestión pública, a través de servicios computacionales (metodo_SCGE). En esta metodología se consideran distintos aspectos tales como software, hardware y comunicaciones, el análisis de estos componentes permite generar un modelo integral basado en Servicios Computacionales de Gobierno Electrónico (SCGE). El artículo contieneuna presentación de algunas metodologías existentes que se pueden aplicar a servicios computacionales, una breve introducción al concepto de servicios computacionales en el ámbito de gobierno electrónico y una descripción de sus componentes. También se describen las etapas que componen la metodología desarrollada. Finalmente se presenta la validaciónde la segunda etapasobre un servicio específico perteneciente a un organismo gubernamental
  • Artículo
    Acceso Abierto
    Semiotics: An Approach to Model Security Scenarios for IoT-Based Agriculture Software
    (2024) Hurtado, Julio Ariel; Antonelli, Leandro; López, Santiago; Gómez, Adriana; Delle Ville, Juliana; Maltempo, Giuliana; Zambrano, Frey Giovanny; Solis, Andrés; Camacho, Marta Cecilia; Solinas, Miguel; Kaplan, Gladys; Muñoz, Freddy
    Agriculture is a vital human activity that contributes to sustainable development. A few decades ago, the agricultural sector adopted the Internet of Things (IoT), which has played a relevant role in precision and smart farming. The IoT developments in agriculture require that numerous connected devices work cooperatively. This increases the vulnerability of IoT devices, mainly because they lack the necessary built-in security because of their context and computational capacity. Other security threats to these devices are related to data storage and processing connected to edge or cloud servers. To ensure that IoT-based solutions meet functional and non-functional requirements, particularly those concerning security, software companies should adopt a security-focused approach to their software requirements specification. This paper proposes a method for specifying security scenarios, integrating requirements and architecture viewpoints into the context of IoT for agricultural solutions. The method comprises four steps: (i) describe scenarios for the intended software, (ii) describe scenarios with incorrect uses of the system, (iii) translate these scenarios into security scenarios using a set of rules, and (iv) improve the security scenarios. This paper also describes a prototype application that employs the proposed algorithm to strengthen the incorrect use scenario based on the correct use scenario. Then, the expert can complete the information for the analysis and subsequent derivation of the security scenario. In addition, this paper describes a preliminary validation of our approach. The results show that the proposed approach enables software engineers to define and analyze security scenarios in the IoT and agricultural contexts with good results. A survey administered to five security experts found that the proposed security scenario method is generally useful for specifying agricultural IoT solutions but needs improvement in different areas.