Artículos Publicados

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https://hdl.handle.net/20.500.14195/1347

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Browsing Artículos Publicados by Author "Aquino Cruz, Mario"

Now showing 1 - 5 of 5
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    An IoT Solution to Detect Overheated Idler Rollers in Belt Conveyors
    (International Journal of Advanced Computer Science and Applications, 2026-03-12) Ibarra-Cabrera, Manuel J.; Guevara Rios, Jaime; Vargas Ovalle, Dennis; Aquino Cruz, Mario; Calderon Vilca, Hugo D.; Ochoa, Sergio F.
    It is common knowledge that mechanical systems need oversight and maintenance procedures. There are numerous prevalent operation monitoring techniques, and in the era of IoT and predictive maintenance, it is possible to find multiple solutions to supervise these systems. This article describes the design and implementation of a low-cost system, which use an IoT approach to detect overheated idlers in conveyors belt in mining facilities. The system involves the use of temperature sensors, coordinately with heat map image sensors. The users (i.e., mining operators) can monitor overheated idlers in the whole conveyor belt, making on-demand queries using Telegram or a website, and also receiving autonomous warnings. Prototypes of this system were installed on a conveyor belt at a construction materials manufacturing company, and also in a copper mining company, both located in Apurimac, Peru. The usability and usefulness of the system were evaluated by 20 experts in maintenance and operation of conveyor belts, who filled the questionnaire proposed by TAM (Technology Acceptance Model). The results show that 91% of them consider the system useful for detecting the overheating of idlers in a conveyor belt, and 93% of them considers the solution as easy to use.
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    Aplicación móvil para el intercambio de libros en la Escuela Académico Profesional de Ingeniería Informática y Sistemas
    (Universidad Nacional Micaela Bastidas de Apurímac, 2020-12-12) Montalvo Navarro, Edwin Ramiro; Aquino Cruz, Mario
    El costo de adquisición de libros originales durante la formación académica universitaria en la región de Apurímac - Perú es muy elevado, los libros hacen más accesible la información académica de calidad dentro de Escuela Académico Profesional de Ingeniería Informática y Sistemas (EAPIIS) de la Universidad Nacional Micaela de Apurímac. Los alumnos que logran adquirir con mucho esfuerzo un nuevo libro, el cual es abandonado después de cursar un semestre académico y se crea la necesidad de adquirir nuevos libros para cursar el siguiente semestre académico, el presente trabajo de investigación describe los resultados de una aplicación móvil implementada para incrementar el intercambio de libros usados entre los alumnos de la EAPIIS y la reutilización de libros. Los resultados de la aplicación de la investigación evidenciaron: En base a los resultados obtenidos de un promedio de 12 préstamos realizados antes de utilizar la aplicación, después de utilizar la aplicación para el intercambio de libros usados el promedio fue de 16.5 logrando un incremento del 72.72%.
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    ApuEmo: Emotion Classification in Spanish Through a Hybrid Model With Transformer and Recurrent Layer
    (IEEE Access, 2026-03-12) Mamani Coaquira, Yonatan; Ibarra Cabrera, Manuel J.; Aquino Cruz, Mario; Mollocondo Flores, Wilson J.
    Emotion classification in social networks is a crucial task, driven by the increasing need to analyze the opinions and feelings expressed across various platforms such as Facebook, YouTube, Instagram, and X. This work presents a novel hybrid approach for emotion classification in Spanish-language texts, integrating the pre-trained SaBERT embedding with recurrent neural networks and attention mechanisms. A rigorous evaluation using the TASS 2020 dataset from the Workshop on Semantic Analysis for Task 2: Emotion Detection, alongside a collection of Spanish comments sourced from Facebook related to the Apurimac region in Peru, was conducted. The results show that the proposed model outperforms representative state-of-the-art models, such as ELiRF-UPV and UMUTeam, achieving a maximum F1-Macro value of 0.49. Moreover, complementary lexical and emotional analyses allowed for validating the model’s behaviour in regional contexts, revealing an emotional distribution consistent with the cultural and linguistic content of the Apurimac region in Peru.
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    Evaluation of Convolutional Neural Network Architectures for Detecting Drowsiness in Drivers
    (Universidad Nacional Micaela Bastidas de Apurímac, 2025-09-09) Hurtado Delgado, Bryan; Oscco Guillen, Marycielo Xiomara; Aquino Cruz, Mario
    Drowsiness in drivers is a condition that can manifest itself at any time, representing a constant challenge for road safety, especially in a context where artificial intelligence technologies are increasingly present in driver assistance systems. This paper presents a comparative evaluation of convolutional neural network (CNN) architectures for drowsiness detection, focusing on the identification of signals such as eye state and yawning. The research was of an applied type with a descriptive level, comparing the performance of LeNet, DenseNet121, InceptionV3 and MobileNet under challenging conditions, such as lighting and motion variations. A non-experimental design was used, with two datasets: a public dataset from Kaggle that included images classified into two categories (yawn and no yawn) and another created specifically for this study, which included images classified into three main categories (eyes open, eyes closed and undetected). The results indicated that, although all architectures performed well in controlled conditions, MobileNet stood out as the most accurate and consistent in challenging scenarios. DenseNet121 also showed good performance, while LeNet was effective in eye-state detection. This study provided a comprehensive assessment of the capabilities and limitations of CNNs for applications in drowsiness monitoring systems, and suggested future directions for improving accuracy in more challenging environments.
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    Telemonitoring and decision support system for covid-19 patients in the hospitalization area
    (Universidad Nacional Micaela Bastidas de Apurímac, 2020-03-20) Céspedes Ramos, Jhon Wildert; Osco Andrade, Franz Junior; Aquino Cruz, Mario
    The coronavirus pandemic was identified as a new beta-corona-RNA virus that has now been called severe acute respiratory syndrome coronavirus 2 (SARS - CoV - 2), due to its similarity to SARS - CoV1. The World Health Organization (WHO) has declared the coronavirus disease 2019 (COVID - 19) as a pandemic due to the alarming levels of spread, severity and inaction, currently there are more than 5.2 million infections in the world, In Peru there are more than 115 thousand infected, this disease has had a strong impact on the health team: numerous infections were registered in health personnel, mainly in those who provide functions in the first line of care for suspected or confirmed cases. In this way, when there are high rates of contagion within the health team, health systems lose the ability to provide an appropriate response, reducing the resilience of the health system. In Peru there are more than a thousand infected doctors, one of the reasons is the constant interaction with infected and suspected patients, also the scarce personal protective equipment, and the late delivery to health personnel (PPE), for everything before aforementioned, a proposal is made for a telemonitoring and decision support system for covid-19 patients in the hospitalization area.