Conference Agenda

During remote classes, teachers face the challenge of recognizing students' emotions, especially when their cameras are on. To address this problem, a facial detection and recognition system was developed that allowed measuring emotions in real time, providing data that can be statistically analyzed. The objective was to establish and classify the emotions expressed by students during remote classes, which allows detecting their real-time participation in the virtual environment. To obtain the best predictive model for detecting student participation in real time, different models were adjusted. Various reference data sets were used to measure the performance and accuracy of the proposed system. The results showed that the proposed system achieves accuracy on different reference sets and on the proposed data set itself. The real-time predictive classification model, modelFEC6.h5, outperforms the others with an accuracy of 94.62% for facial emotion classification in real-time virtual learning scenarios.

The digital transformation has driven the massive use of digital technologies, significantly increasing the digital carbon footprint and its environmental impact. The objective of this research was to determine the effect of the mobile application “Huella Cero” on awareness about HCD in young people. The SCRUM methodology was used to develop the mobile application. The research was of an applied type and pre-experimental design of pretest and posttest. We worked with a sample of 22 young people. The survey was used as a technique and the questionnaire validated by experts and with an acceptable Cronbach's alpha coefficient of 0.87 was used as an instrument. Finally, it was found that the “Zero Footprint” mobile application had a positive effect on raising awareness about HCD in young people.

Abstract– Spare parts inventories are characterized by a large volume of products with diverse characteristics and intermittent, highly variable demand, making it impossible to achieve effective planning using traditional methods. This paper proposes a framework based on classification, forecasting, simulation, and optimization techniques to determine the optimal inventory management policy for each product, thereby reducing associated costs. The study examines the current situation of a Peruvian company specializing in forklift sales and rentals, which faces this challenge, and details the procedures and mathematical modeling techniques applied at each stage to implement the proposed framework. In the classification stage, a new five-category classification system, called alpha-omega, is introduced. In the forecasting stage, Bayesian inference methods and probabilistic forecasting techniques are proposed. For the simulation stage, the Monte Carlo method is used to recreate various policy scenarios for each product. In the optimization stage, Bayesian optimization is applied to determine the optimal parameters for these policies to maximize utility. Finally, the framework’s implementation requirements and its potential economic benefits are assessed. The study concludes that the proposed framework can generate significant cost savings for the company; however, its successful implementation requires an organizational culture that fosters synergy among the involved departments.

Inflation is a macroeconomic phenomenon that affects a country's purchasing power and economic stability. In Ecuador, dollarization limits the use of traditional monetary policy tools, making it necessary to analyze other macroeconomic variables to understand inflation. This study aims to identify the critical macroeconomic variables explaining inflation in Ecuador through a data-driven approach, providing a useful reference framework for their incorporation into future econometric models and economic policy decision-making. A quantitative approach was employed, based on time series analysis, cointegration tests, and correlations, using data from the Central Bank of Ecuador and the National Institute of Statistics and Census. The results show that total liquidity, money supply, and the real exchange rate maintain a long-term relationship with inflation, while the reference lending rate and public spending influence it in the short term. Additionally, it was confirmed that inflation in Ecuador does not follow a clear trend but is highly influenced by these factors. It is concluded that economic policy should focus on regulating total liquidity and the real exchange rate to mitigate inflationary effects. The application of appropriate econometric models will enhance inflation forecasting and control in the context of dollarization.

Purpose: The emergence of the metaverse presents opportunities and disruptions for users and organizations. This article explores perspectives on the future of digital marketing, proposing a new marketing ecosystem. It discusses strategies that allow organizations to communicate with their customer base in previously unimaginable ways, transforming the concept of marketing into an innovative and groundbreaking field of action.

Design/Methodology/Approach: A hybrid system model is proposed for generating immersive virtual tours based on 360° VR videos for hotel environments, their surroundings, and tourist areas. The proposal for a metaverse environment includes designing user interface prototypes that utilize avatars, automating the segmentation of 360° videos using convolutional neural networks, and composing personalized tours based on user profiles through an inference engine employing Case-Based Reasoning (CBR).

Findings: Standalone functionality tests within the metaverse for the tour composition component, tailored to user profiles recommended by the CBR inference mechanism, proved successful.

Originality/Value: The application of these systems can contribute to reservation intent and brand image improvement, as immersive experiences can trigger effects on affective, attitudinal/behavioral, and cognitive dimensions.

The purpose of the study was to identify the relationship between Risk Management and Information Security in an Educational Community in the Andean Zone of Peru. In the methodological aspect, we have an applied study, non-experimental design, descriptive correlational, with the survey and validated and reliable questionnaires as tools to obtain data, applied to a sample of 69 collaborators and a census type sampling. The main findings were the level of Risk Management with 67.2% approval and the level of Information Security with 64.7% approval, according to the perception of the members of the educational community of interest. The data did not adjust to a normal distribution, in such sense the correlation statistic of Spearman's Rho was applied, concluding the existence of a low positive significant correlation (Rho=0, 315) between Risk Management and Computer Security in an Educational Community of the Andean Zone of Peru.

The objective is to identify the impact of artificial intelligence in business marketing, the main clusters, the AI tools that have been applied for the benefit of marketing, their implementation process, the strategies employed in the application and the main challenges of AI in marketing application. To this end, a systematic review was conducted following the PRISMA guidelines and the PICO question of the empirical studies found in the Scopus and Web of Science (WoS) databases. Subsequently, a bibliometric analysis was developed and a total of 35 scientific articles were identified in journals indexed between the years 2019 and 2024 that met the inclusion criteria and were ready to extract the information. It was identified that the application of AI in companies improved the quality of predictions about customer behavior, which helps to perform better segmentation and personalization of offers to the target audience, and to increase customer retention. It was concluded that there is a close connection between artificial intelligence, marketing and commerce, and emphasis was placed on emerging areas such as data mining, machine learning, ChatGPT-4, neural networks, BiLSTM, chatbots algorithms and virtual assistants, which are revolutionizing the field.