“After the isolation caused by the pandemic, the entertainment sector has been forced to change the way it markets its products and services, and users have been adapting to the change. The objective of this research article is to provide added value and innovation to the advertising promotions of movies in the premiere, through the development of a mobile application based on augmented reality to improve customers’ shopping experience. For which the Agile Mobile-D Methodology was used for the development of the application and the results were studied using 5 indicators: Time to choose a movie, where an improvement of 38.26% was obtained compared to the Pre-Test; regarding the indicator time to acquire information about the movie, an improvement of 81.33% was obtained. 33%; concerning the third indicator, time to initiate the purchase, an improvement of 88% was obtained; concerning ...

The post-pandemic period brought with it new challenges for both businesses and private health centers, many of which were affected by the loss of customers. In the case of dental centers, many were affected by the distrust of customers, since activities performed in the oral cavity exposed them to the contagion of Covid-19. This research work proposes the implementation of a mobile application with Augmented Reality (AR) as a strategy for digital marketing immersion, with the aim of achieving a dynamic approach to the services provided in the dental center to customers, this is through the use of this technology in conjunction with social networks, contributing to the improvement of the business and building trust with customers. The application was developed under the Mobile-D methodology with a layered system development architecture, having as indicators the time of elaboration of th...

Decent work and economic growth are fundamental elements for the sustainable development of a society, with Sustainable Development Goal 8 (SDG8) being one of the key objectives of the United Nations’ 2030 Agenda. The 5G network has great potential to contribute significantly to the achievement of SDG8, offering faster and more reliable connectivity, which opens up new possibilities for innovation, operational efficiency, and job creation. The present study aimed to investigate the role of 5G technologies concerning decent work and economic growth (SDG8). As part of the method, 265 articles extracted from main databases such as Scopus, IEEExplore, and ScienceDirect were analyzed using the PRISMA methodology, resulting in 74 relevant articles after applying the inclusion and exclusion criteria. As a result, a greater contribution to the use of the 5G network was identified in sectors su...

The university-level mathematics teaching adopted by many professors is still a traditional classroom, and many students’ perception of mathematics is that it is a complicated subject. The operationality of the flipped classroom proposal implemented at a university has a poten tial that can be used to change the perception that university students and teachers have towards the mathematics course, as well as to change the methodology of many teachers on how they teach their courses in the classroom. This research is the result of the implementa tion of the flipped classroom methodology in the basic mathematics course that is part of the professional careers of the engineering faculty of a Peruvian university. The aim of this study was to analyze the impact of applying the flipped classroom on academic results and atti tudes towards mathematics, with an experimental group of 227 students...

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 of Deep Learning models. The central focus of the research was the development and evaluation of a short-term memory model (LSTM) specifically designed to predict customer leakage. The choice of LSTM as the mainstay of the research is based on its proven ability to model long-term dependencies in sequences, its resilience to recurrent challenges in neural networks, and its success in various sequence prediction tasks. The model implementation, configured sequentially with Keras, comprised of an initial LSTM layer of 64 units, followed by a 20% removal layer to mitigate overfitting. The second LSTM layer, with 32 units, was supplemented with another elimination layer....

En el presente trabajo de investigación se investigó la influencia del módulo en el aprendizaje de ecuaciones e inecuaciones lineales en los alumnos del segundo grado de educación secundaria del Colegio Estatal Politécnico Regional del Centro – El Tambo. El objetivo general fue determinar la influencia que produce el módulo en el aprendizaje de ecuaciones e inecuaciones lineales en los alumnos del segundo grado de educación secundaria del Colegio Estatal Politécnico Regional del Centro – El Tambo. La hipótesis planteada ha sido: el módulo influye positivamente en el aprendizaje de ecuaciones e inecuaciones lineales en los alumnos del segundo grado de educación secundaria del Colegio Estatal Politécnico Regional del Centro – El Tambo La investigación realizada corresponde al tipo de investigación tecnológica – aplicada. El método empleado es el experimental con la ...

“It is important to preserve our cultural identity through the preservation of our mother tongue, contributing to its dissemination. Augmented reality (AR) is a great ally of education that provides efficiency, and productivity and increases the interest of students in their academic activities. An AR application was developed for learning Quechua in preschool children, thus improving their learning, satisfaction, and preference compared to traditional teaching. Previously, learning styles were identified for better coverage of the application; the design thinking methodology was applied for the development of the application, then the respective tests were conducted where it was obtained that the children's performance improved by 28.3% more compared to traditional teaching, with an average satisfaction of 89% of the classrooms, and 81% of students' preference. It was concluded that t...

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 popular social media for expressing their feelings towards events that occur is Twitter. The main objective of this study is to classify and analyze the content of the affiliates of the Pension and Funds Administration (AFP) published on Twitter. This study incorporates machine learning techniques for data mining, cleaning, tokenization, exploratory analysis, classification, and sentiment analysis. To apply the study and examine the data, Twitter was used with the hashtag #afp, followed by descriptive and exploratory analysis, including metrics of the tweets. Finally, a content analysis was carried out, including word frequency calculation, lemmatization, and classification of words ...

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 popular social media for expressing their feelings towards events that occur is Twitter. The main objective of this study is to classify and analyze the content of the affiliates of the Pension and Funds Administration (AFP) published on Twitter. This study incorporates machine learning techniques for data mining, cleaning, tokenization, exploratory analysis, classification, and sentiment analysis. To apply the study and examine the data, Twitter was used with the hashtag #afp, followed by descriptive and exploratory analysis, including metrics of the tweets. Finally, a content analysis was carried out, including word frequency calculation, lemmatization, and classification of words ...

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 popular social media for expressing their feelings towards events that occur is Twitter. The main objective of this study is to classify and analyze the content of the affiliates of the Pension and Funds Administration (AFP) published on Twitter. This study incorporates machine learning techniques for data mining, cleaning, tokenization, exploratory analysis, classification, and sentiment analysis. To apply the study and examine the data, Twitter was used with the hashtag #afp, followed by descriptive and exploratory analysis, including metrics of the tweets. Finally, a content analysis was carried out, including word frequency calculation, lemmatization, and classification...

“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 ability to learn long-term dependencies. The present research integrates the LSTM network and dropout technique to generate a text from a corpus as input, a model is developed to find the best way to extract the words from the context. For training the model, the poem ““La Ciudad y los perros““ which is composed of 128,600 words is used as input data. The poem was divided into two data sets, 38.88% for training and the remaining 61.12% for testing the model. The proposed model was tested in two variants: word importance and context. The results were evaluated in terms of the semantic proximity of the generated text to the given context.“

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 ability to learn long-term dependencies. The present research integrates the LSTM network and dropout technique to generate a text from a corpus as input, a model is developed to find the best way to extract the words from the context. For training the model, the poem "La Ciudad y los perros" which is composed of 128,600 words is used as input data. The poem was divided into two data sets, 38.88% for training and the remaining 61.12% for testing the model. The proposed model was tested in two variants: word importance and context. The results were evaluated in terms of the semantic proximity of the generated text to the given context.

“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 in humans, setting off worldwide alerts from health agencies. As of September 2022, the number of confirmed cases in Peru had reached 1964. Although most monkeypox patients have been discharged, we cannot neglect the monitoring of the population with respect to the monkeypox virus. Lately, the population has started to express their feelings and opinions through social media, specifically Twitter, as it is the most used social medium and is an ideal space to gather what people think about the monkeypox virus. The information imparted through this medium can be in different formats, such as text, videos, images, audio, etc. The objective of this work is to analyze the ...

“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 in humans, setting off worldwide alerts from health agencies. As of September 2022, the number of confirmed cases in Peru had reached 1964. Although most monkeypox patients have been discharged, we cannot neglect the monitoring of the population with respect to the monkeypox virus. Lately, the population has started to express their feelings and opinions through social media, specifically Twitter, as it is the most used social medium and is an ideal space to gather what people think about the monkeypox virus. The information imparted through this medium can be in different formats, such as text, videos, images, audio, etc. The objective of this work is to analyze the ...

“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; second, labeling and training of the data; third, labeling of the unseen data; and fourth, evaluation of the model performance. For processing, a total of 10,322 ““curriculum““ documents related to data science were collected from the web during 2018-2022. The latent dirichlet allocation (LDA) model was used for the analysis and structure of the subjects. After processing, 12 themes were generated, which allowed ranking the most relevant terms to identify the skills of each of the candidates. This work concludes that candidates interested in data science must have skills in the following topics: first, they must be technical, they must have mastery of structured ...

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; second, labeling and training of the data; third, labeling of the unseen data; and fourth, evaluation of the model performance. For processing, a total of 10,322 "curriculum" documents related to data science were collected from the web during 2018-2022. The latent dirichlet allocation (LDA) model was used for the analysis and structure of the subjects. After processing, 12 themes were generated, which allowed ranking the most relevant terms to identify the skills of each of the candidates. This work concludes that candidates interested in data science must have skills in the following topics: first, they must be technical, they must have mastery of structured query languag...

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; second, labeling and training of the data; third, labeling of the unseen data; and fourth, evaluation of the model performance. For processing, a total of 10,322 "curriculum" documents related to data science were collected from the web during 2018-2022. The latent dirichlet allocation (LDA) model was used for the analysis and structure of the subjects. After processing, 12 themes were generated, which allowed ranking the most relevant terms to identify the skills of each of the candidates. This work concludes that candidates interested in data science must have skills in the following topics: first, they must be technical, they must have mastery of structured query languag...

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 in humans, setting off worldwide alerts from health agencies. As of September 2022, the number of confirmed cases in Peru had reached 1964. Although most monkeypox patients have been discharged, we cannot neglect the monitoring of the population with respect to the monkeypox virus. Lately, the population has started to express their feelings and opinions through social media, specifically Twitter, as it is the most used social medium and is an ideal space to gather what people think about the monkeypox virus. The information imparted through this medium can be in different formats, such as text, videos, images, audio, etc. The objective of this work is to analyze the pos...