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1
artículo
Hiring processes are intended to recruit and retain ideal candidates; those who would generate competitive value in an organization. In an increasingly global context, the challenge is often costly, inefficient, and complex. Even though artificial intelligence already solves specific tasks with greater speed, precision, and efficiency in various fields, and in different companies, in the area of human resources the desirability of the use of data science continues to be debated. By reviewing cases and research, in which the integration of artificial intelligence applications in the selection processes was tested, measuring and socializing impacts, I contribute to the current discussion aimed at overcoming the mistrust that exists by default, and that is associated with the ethical challenges and risks t assumed to solve a human problem through technology. I conclude that it is possible t...
2
artículo
Hiring processes are intended to recruit and retain ideal candidates; those who would generate competitive value in an organization. In an increasingly global context, the challenge is often costly, inefficient, and complex. Even though artificial intelligence already solves specific tasks with greater speed, precision, and efficiency in various fields, and in different companies, in the area of human resources the desirability of the use of data science continues to be debated. By reviewing cases and research, in which the integration of artificial intelligence applications in the selection processes was tested, measuring and socializing impacts, I contribute to the current discussion aimed at overcoming the mistrust that exists by default, and that is associated with the ethical challenges and risks t assumed to solve a human problem through technology. I conclude that it is possible t...
3
artículo
Publicado 2022
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The objective of this research was to analyze the improvement in the data analysis and problem-solving competence of students of industrial and systems engineering (IIS) and mechatronics engineering (IMEC) through the use of this technology and its impact on the results of the undergraduate general examination (EGEL). A training course was held for teachers and students for the design of learning objects (LO), and a questionnaire on the use of AR and the improvement in learning was administered. AR is a technology that has begun to be introduced in different contexts and at different educational levels. The results obtained through the Wilcoxon test and the multiple correspondence analysis (MCA) showed that there were improvements in academic performance with the use of AR and an interest in this tool being used during the academic training process.
4
artículo
Publicado 2023
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Currently, continuous technological advancements are pervasive in society, enhancing various aspects of our lives, including entertainment, information, and communication. In this context, one of the primary domains that can benefit from these advancements is education. The constant technological developments must be applied to the educational system to keep pace with changes in our lifestyle. Augmented reality (AR) is an innovative technology that allows smartphones to combine the real environment with virtual objects. Through the device's accelerometer, gyroscope, and camera, AR places 3D models on the screen based on the user's movements, creating an interactive experience. This technology has the potential to improve the learning experience in schools, making teaching more dynamic and increasing student motivation and interest in subjects such as mathematics and sciences, among other...
5
tesis doctoral
Publicado 2024
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This dissertation investigates the potential improvement of volcanic eruption understanding and forecasting methods by using advanced data processing techniques to analyze large datasets at three target volcanoes (Piton de la Fournaise (PdlF) (France), Sabancaya, and Ubinas (Peru)). The central objective of this study is to search for possible empirical relationships between the pre-eruptive behavior of the accelerated increase in seismic activity using the Failure Forecast Method (FFM) and velocity variations measured by Coda Wave Interferometry (CWI), since both observations are reported to be independently associated with medium damage. The FFM is a deterministic method used to forecast volcanic eruptions using an empirical relationship of increased and accelerated evolution of an observable (e.g., volcano-seismic event rates). The event rates used with FFM in this study were generate...
6
tesis doctoral
Publicado 2024
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This dissertation investigates the potential improvement of volcanic eruption understanding and forecasting methods by using advanced data processing techniques to analyze large datasets at three target volcanoes (Piton de la Fournaise (PdlF) (France), Sabancaya, and Ubinas (Peru)). The central objective of this study is to search for possible empirical relationships between the pre-eruptive behavior of the accelerated increase in seismic activity using the Failure Forecast Method (FFM) and velocity variations measured by Coda Wave Interferometry (CWI), since both observations are reported to be independently associated with medium damage. The FFM is a deterministic method used to forecast volcanic eruptions using an empirical relationship of increased and accelerated evolution of an observable (e.g., volcano-seismic event rates). The event rates used with FFM in this study were generate...
7
artículo
Publicado 2024
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La rápida globalización y la creciente necesidad de comunicación interlingüística requieren corpus modernos y en tiempo real para ayudar a los estudiantes de idiomas. Los métodos tradicionales para crear dichos corpus, especialmente en español, son inadecuados debido a su incapacidad para procesar la gran cantidad de datos no estructurados disponibles en internet. En este estudio se exploran las metodologías de inteligencia artificial (IA) para la adquisición automática de documentos en español de la web, preprocesándolos y clasificándolos con el fin de construir un corpus vasto y flexible para el aprendizaje del español. La investigación aplica el rastreo web mediante el framework Scrapy para recopilar datos, que luego se limpian y clasifican utilizando modelos avanzados de procesamiento del lenguaje natural (PLN). En concreto, el estudio emplea el algoritmo BERT (Bidirec...
8
artículo
The COVID-19 pandemic has brought about significant changes in people’s lifestyles, with the educational sector being one of the most reliant on technology to facilitate the teaching and learning process. In this literature review, a search for articles related to the metaverse in education, published in 2022 and 2023, has been conducted across six databases: Scopus, EBSCO Host, ScienceDirect, Taylor & Francis Online, IEEE Xplore, and Springer. The PRISMA methodology was used to analyze and systematize the manuscripts found. The aim of this research was to examine how integrating the metaverse into education can enhance educational accessibility and equity by enabling students to utilize virtual learning resources and opportunities. In addition, they can engage in interactions with others to learn and create interactive content during the teaching and learning process. This requires a ...
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10
tesis de grado
Publicado 2024
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Las aplicaciones de la Inteligencia Artificial dentro de la industria de la construcción para la detección de trabajadores, equipos y herramientas requieren de una gran cantidad de datos variados para lograr un alto nivel de precisión (mean Average Precision-, mAP) y nivel de confianza en las detecciones y clasificaciones, y evitar los problemas de sobreentrenamientos, los cuales podrían perjudicar a los modelos de aprendizaje profundo. Sin embargo, los conjuntos de datos publicados en línea carecen de una variedad de imágenes que capturen los diferentes escenarios en una construcción, tales como las diversas actividades en obras, los cambios de estación, la variación en la iluminación en el transcurso del día, entre otros. Además, la creación de estos suele conllevar un proceso largo y monótono. Con el fin de abordar este problema, la presente investigación plantea el uso...
11
artículo
Publicado 2021
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Implementation of model-based fault diagnosis systems can be a difficult task due to the complex dynamics of most systems, an appealing alternative to avoiding modeling is to use machine learning-based techniques for which the implementation is more affordable nowadays. However, the latter approach often requires extensive data processing. In this paper, a hybrid approach using recent developments in neural ordinary differential equations is proposed. This approach enables us to combine a natural deep learning technique with an estimated model of the system, making the training simpler and more efficient. For evaluation of this methodology, a nonlinear benchmark system is used by simulation of faults in actuators, sensors, and process. Simulation results show that the proposed methodology requires less processing for the training in comparison with conventional machine learning approache...
12
artículo
Publicado 2021
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We want to thank the Image Processing Research Laboratory. (INTI-Lab) and the Universidad de Ciencias y Humanidades. (UCH) for their support in this research, the National Fund for. Scientific, Technological and Technological Innovation (FONDECYT), according to the research: ?SAMAYCOV: ?Desarrollo de un dispositivo electr?nico port?til a bajo costo para evaluar riesgo de neumon?a basado en sonido pulmonar anormal en pacientes con sospecha de COVID-19 en zonas vulnerables?. CONVENIO 054-2020-FONDECYT?; for the financing of this research and the Electronics Laboratory of the UCH for assigning us their facilities and being able to carry out the respective tests.
13
tesis de maestría
Publicado 2024
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Esta tesis abordó el desarrollo de recursos computacionales para la detección y clasificación de disfluencias de tartamudez en español, cubriendo desde la recolección y anotación de audios hasta la implementación de un modelo de aprendizaje automático y estrategias de aumento de datos. Se recolectaron audios en español de cinco participantes con tartamudez, conformes a los estándares del dataset SEP-28K y con apoyo de dos especialistas en tartamudez. Aunque la naturaleza controlada de las grabaciones limitó la diversidad de disfluencias observadas, estos audios proporcionaron una base sólida para el desarrollo del modelo. El modelo presentado se basó en el modelo DisfluencyNet. Este modelo fue pre entrenado utilizando wav2vec 2.0 XLSR53 aprovechando su robusta base de datos multilingüe. El modelo demostró su capacidad para identificar y clasificar disfluencias en español,...
14
tesis de grado
Publicado 2025
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El presente informe de tesis, tuvo como intención conocer la influencia del uso de redes neuronales y su efectividad en la detección de neumonía asociada al Covid – 19 en las radiografías de tórax. La investigación se divide en 3 etapas, la primera etapa es la adquisición de datos y generación de un dataset y el pre procesamiento de las imágenes, la segunda etapa consiste en el modelamiento de la arquitectura a implementar en cada red neuronal y el entrenamiento del modelo general de red neuronal convolucional y la última etapa se generan las pruebas y resultados del modelo particular. A partir de los resultados alcanzados se puede aseverar que: para una mejor evaluación se debe aplicar data augmentation en la identificación de neumonía asociada a Covid- 19 con una exactitud mayor que 0.93. Así también se verifica que el modelo ha sufrido de sobreajuste (overfitting) que...
15
tesis de grado
Publicado 2025
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Esta presente investigación tiene como objetivo aplicar técnicas de procesamiento de lenguaje natural (NLP) y fine tuning para generar resúmenes coherentes de notas de enfermería en centros de salud de Trujillo. La problemática se centra en la sobrecarga de trabajo del personal de enfermería y el tiempo que demanda la lectura y análisis de estas notas clínicas, las cuales son clave para la continuidad del cuidado del paciente. Para enfrentar este desafío, se recopilaron y preprocesaron notas de enfermería obtenidas de diferentes instituciones de salud, la cantidad de notas obtenidas ascendió a 41 ejemplares. El siguiente paso fue limpiar los datos obtenidos, digitalizarlos y aumentar los datos mediante diversas tecnicas de Data Augmentation, como Synonym Replacement, Back Translate, Paraphrasing with generative model y Contextual Word Embeddings Augmentation. Mediante estas t...
16
artículo
This study aimed to understand the repercussions of prison for female companions of imprisoned men. Twelve female companions of male prisoners participated in the study. Data were collected through a sociodemographic data questionnaire and a semi-structured interview, and submitted to Thematic Analysis. There was an important change in the women’s entire lives after the arrest of their partners, considering experiences directly related to prison, as well as repercussions on their lives in general, which went beyond direct contact with the prison context. It is considered necessary to highlight the processes to which these women are exposed, as well as to legitimize their experiences, intertwined in a process of significant increase in incarceration in Brazil.
17
artículo
This study aimed to understand the repercussions of prison for female companions of imprisoned men. Twelve female companions of male prisoners participated in the study. Data were collected through a sociodemographic data questionnaire and a semi-structured interview, and submitted to Thematic Analysis. There was an important change in the women’s entire lives after the arrest of their partners, considering experiences directly related to prison, as well as repercussions on their lives in general, which went beyond direct contact with the prison context. It is considered necessary to highlight the processes to which these women are exposed, as well as to legitimize their experiences, intertwined in a process of significant increase in incarceration in Brazil.
18
tesis de maestría
Publicado 2024
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Esta tesis abordó el desarrollo de recursos computacionales para la detección y clasificación de disfluencias de tartamudez en español, cubriendo desde la recolección y anotación de audios hasta la implementación de un modelo de aprendizaje automático y estrategias de aumento de datos. Se recolectaron audios en español de cinco participantes con tartamudez, conformes a los estándares del dataset SEP-28K y con apoyo de dos especialistas en tartamudez. Aunque la naturaleza controlada de las grabaciones limitó la diversidad de disfluencias observadas, estos audios proporcionaron una base sólida para el desarrollo del modelo. El modelo presentado se basó en el modelo DisfluencyNet. Este modelo fue pre entrenado utilizando wav2vec 2.0 XLSR53 aprovechando su robusta base de datos multilingüe. El modelo demostró su capacidad para identificar y clasificar disfluencias en español,...
19
artículo
Publicado 2025
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Pokémon Double Battles present a complex decision-making environment that has traditionally relied on manual data analysis. This paper introduces an automated system leveraging computer vision and deep learning to extract structured gameplay data from battle footage. Our approach integrates You Only Look Once (YOLO) for Pokémon sprite recognition along with Tesseract-based optical character recognition (OCR) for extracting move and status text. The study introduces a custom-built image dataset generated through the augmentation of publicly available Pokémon sprites, which is then used to train a YOLO model for sprite recognition. The system was tested across multiple controlled and real-world gameplay scenarios, achieving high accuracy in Pokémon recognition and action tracking. Additionally, a JSON-based gameplay notation system is proposed to structure battle sequences, thus improv...
20
tesis de grado
Publicado 2024
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This study aimed to compare the effectiveness of the YOLOv8n algorithm with different deep learning models in the task of automatic detection and counting of Colossoma macropomum postlarvae, a key process to improve aquaculture production and reduce mortality in this field. In order to evaluate the quality of the results, metrics such as accuracy, sensitivity, F1-Score and processing time were analyzed, comparing the performance of YOLOv8n with PP-PicoDet-det-L, Faster R-CNN and Grid R-CNN. The methodology employed included preprocessing and data augmentation techniques applied to a set of 71 images obtained from various mobile devices, which ensured greater representativeness and quality of the sample. The training of the algorithms was carried out in 12 epochs, using both a supercomputer and a workstation provided by IIAP. The results indicate that YOLOv8n exhibits superior performance...
