Now showing items 21-34 of 34

    • Mobile Application with Augmented Reality to Improve Learning in Science and Technology 

      Gamboa-Ramos, Miriam; Gómez-Noa, Ricardo; Iparraguirre-Villanueva, Orlando; Cabanillas-Carbonell, Michael; Herrera Salazar, José Luis (Science and Information Organization, 2021)
      Acceso abierto
      Education has taken a big turn due to the current health situation, and as a result the use of technology has become a great ally of education, achieving important benefits. Augmented reality is being used by teachers and ...
    • Optimization of a Photovoltaic Station for Charging Electric Vehicles 

      Beltozar Clemente, Saul; Herrera Escandon, Winy Livet; Iparraguirre-Villanueva, Orlando; Zapata-Paulini, Joselyn; Cabanillas-Carbonell, Michael (Springer Link, 2023)
      Acceso restringido
      The constant struggle to reduce greenhouse gas emissions caused by internal combustion vehicles makes electromobility a latent alternative solution. The main difficulty in its implementation is the scarce or non-existent ...
    • Predicting customer abandonment in recurrent neural networks using short-term memory 

      Beltozar-Clemente, Saul; Iparraguirre-Villanueva, Orlando; Pucuhuayla-Revatta, Félix; Zapata-Paulini, Joselyn; Cabanillas-Carbonell, Michael (Elsevier, 2023)
      Acceso abierto
      Customer retention, a critical business priority, has become a growing concern, especially in the telecommunications industry. This study addresses the need to anticipate and understand customer churn through the application ...
    • Predicting Election Results with Machine Learning—A Review 

      Argandoña-Mamani, Alexander; Ormeño-Alarcón, Terry; Iparraguirre-Villanueva, Orlando; Paulino-Moreno, Cleoge; Cabanillas-Carbonell, Michael (Springer Link, 2023)
      Acceso restringido
      Election results are a topic that never stops being talked about and even more so that social platforms are the perfect medium where polarization to a political party is established. That is why many academics have seen ...
    • Predicting Obesity in Nutritional Patients using Decision Tree Modeling 

      Iparraguirre-Villanueva, Orlando; Mirano-Portilla, Luis; Gamarra-Mendoza, Manuel; Robles-Espiritu, Wilmer (The Science and Information Organization, 2023)
      Acceso abierto
      Obesity has become a widespread problem that affects not only physical well-being but also mental health. To address this problem and provide solutions, Machine Learning (ML) technology tools are being applied. Studies are ...
    • Predictive Model with Machine Learning for Academic Performance 

      Cecenardo-Galiano, Carlos; Sumaran-Pedraza, Carolina; Obregon-Palomino, Luz; Iparraguirre-Villanueva, Orlando; Cabanillas-Carbonell, Michael (Springer Link, 2023)
      Acceso restringido
      Academic achievement (AP) in recent years has shown minimal progress with a difference of 0.05%, according to the report made by the Program for International Student Assessment (PISA). For this reason, the objective of ...
    • Productivity of incident management with conversational bots-a review 

      Iparraguirre-Villanueva, Orlando; Obregon-Palomino, Luz; Pujay-Iglesias, Wilson; Sierra-Liñan, Fernando; Cabanillas-Carbonell, Michael (IAES International Journal of Artificial Intelligence (IJ-AI), 2023)
      Acceso abierto
      The use of conversational agents (bots) in information systems managed by company’s increases productivity in the development of activities focused on processes such as customer service, healthcare, and presentation. The ...
    • Remote Heart Rate Monitoring Device Using the Internet of Things 

      Iparraguirre-Villanueva, Orlando; Surcco-Jacinto, Enrique; Balvin-Chávez, Melanie (International Journal of Online and Biomedical Engineering (iJOE), 2023)
      Acceso abierto
      Cardiovascular diseases are the leading cause of death worldwide. Therefore, this study aims to develop a mobile application utilizing the Internet of Things (IoT) to monitor patients’ heart rate. The study employed a ...
    • Search and classify topics in a corpus of text using the latent dirichlet allocation model 

      Iparraguirre-Villanueva, Orlando; Sierra-Liñan, Fernando; Herrera Salazar, Jose Luis; Beltozar-Clemente, Saul; Pucuhuayla-Revatta, Félix; Zapata-Paulini, Joselyn; Cabanillas-Carbonell, Michael (Indonesian Journal of Electrical Engineering and Computer Science, 2023)
      Acceso abierto
      This work aims at discovering topics in a text corpus and classifying the most relevant terms for each of the discovered topics. The process was performed in four steps: first, document extraction and data processing; ...
    • Sentiment Analysis of Tweets using Unsupervised Learning Techniques and the K-Means Algorithm 

      Iparraguirre-Villanueva, Orlando; Guevara-Ponce, Victor; Sierra-Liñan, Fernando; Beltozar-Clemente, Saul; Cabanillas-Carbonell, Michael (SAI The Science and Information Organization, 2022)
      Acceso abierto
      Abstract: Today, web content such as images, text, speeches, and videos are user-generated, and social networks have become increasingly popular as a means for people to share their ideas and opinions. One of the most ...
    • Técnicas y algoritmos para predecir el resultado de los partidos de fútbol utilizando la minería de datos, una revisión de la literatura 

      Araujo-Ahon, Antonio; Cardenas-Mayta, Brayan; Iparraguirre-Villanueva, Orlando; Zapata-Paulini, Joselyn; Cabanillas-Carbonell, Michael (Revista lbérica de Sistemas e Tecnologias de Informação, 2023)
      Acceso abierto
      El resultado de un deporte se ha convertido en una necesidad para los competidores, así como para los fanáticos que siguen a sus equipos favoritos. Sin embargo, la predicción de los resultados de un partido de fútbol (PSMR) ...
    • Text prediction recurrent neural networks using long shortterm memory-dropout 

      Iparraguirre-Villanueva, Orlando; Guevara-Ponce, Victor; Ruiz-Alvarado, Daniel; Beltozar-Clemente, Saul; Sierra-Liñan, Fernando; Zapata-Paulini, Joselyn; Cabanillas-Carbonell, Michael (Indonesian Journal of Electrical Engineering and Computer Science, 2023)
      Acceso abierto
      Unit short-term memory (LSTM) is a type of recurrent neural network (RNN) whose sequence-based models are being used in text generation and/or prediction tasks, question answering, and classification systems due to their ...
    • The Public Health Contribution of Sentiment Analysis of Monkeypox Tweets to Detect Polarities Using the CNN-LSTM Model 

      Iparraguirre-Villanueva, Orlando; Alvarez-Risco, Aldo; Herrera Salazar, Jose Luis; Beltozar-Clemente, Saul; Zapata-Paulini, Joselyn; Yáñez, Jaime A.; Cabanillas-Carbonell, Michael (MDPI, 2023)
      Acceso abierto
      Monkeypox is a rare disease caused by the monkeypox virus. This disease was considered eradicated in 1980 and was believed to affect rodents and not humans. However, recent years have seen a massive outbreak of monkeypox ...
    • Virtual Reality as a Tool in the Treatment of Claustrophobia - A Review 

      Iparraguirre-Villanueva, Orlando; Perez-Benito, Carlos; Cabanillas-Carbonell, Michael (Seventh Sense Research Group®, 2023)
      Acceso abierto
      Within the context of psychology, virtual reality (VR) is presented as a technological tool to address and treat the symptoms of claustrophobia. Claustrophobia is distinguished by a fear of small or enclosed environments, ...