Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

This study allows the implementation of techniques to manage failures, evaluate wear and parameterize the obsolescence of industrial equipment to reduce uncertainty and guarantee the guided monitoring of the natural work team to provide reliability in the life cycle, reduce breakdowns and replacements, and promote asset management compliance, associate mechanical integrity and alloy formulation. According to the analysis of results, the conceptualizations of studies in tribology and engineering are strengthened, in addition to establishing improvements so as not to lead to wrong diagnoses and bad decisions. It is concluded that the study allows to guarantee greater usefulness and productive and economic efficiency in industrial operations in the fulfillment of work orders, in addition to implementing routine procedures with the formulated tools, both quantitative and qualitative, that permit forecasting improvements in the remaining life of machines and production systems with a view to sustainability.

Human mobility to Ecuador has been a topic of increasing diffusion in the current situation, due to the post-pandemic conditions that the country is going through. For this reason, this article examines the information concerning the citizens who have received a visa from the Ministerio de Relaciones Exteriores y Movilidad Humana. Based on the available data, the analysis has focused on applicants from Colombia and Venezuela. Two machine learning models have been used in order to highlight and validate a possible relationship between the socioeconomic characteristics of citizens with respect to their migratory category; identifying whether variables such as age, gender, marital status, and nationality can influence the visa application with respect to the type of residence. According to the findings, single Colombian citizens, regardless of their age, opt for temporary residency, while divorced Colombians opt for permanent residency. For single Venezuelan citizens under 23 years of age, the majority have permanent residency; however, those older than 23 years of age opt for temporary residency.

The design of an algorithm that operates at the link level to synchronize the nodes that are part of a multi-hop linear topology is presented. The objective is that the nodes can transmit and receive frames in the same time interval and avoid the use of protocols at the network level to have end-to-end connectivity. To verify the effectiveness of the algorithm, a prototype network with a linear topology using the IEEE 802.15.4 protocol was implemented. The algorithm is executed in each node of the network. Therefore, the time interval in which the nodes must be active was calculated so that all nodes that are part of the multi-hop linear topology can transmit the monitoring data to the border node in the same time interval. The tests were performed in several scenarios in which one or several nodes transmit their data and it was verified that the nodes are activated simultaneously to operate in active mode. Based on the results, the algorithm performance was validated and provides a tool for the creation of applications associated with linear infrastructure monitoring.

The main objective of this project is the development of an Interactive Voice Response (IVR) system for the notification of operational data regarding process variables at the Boquerón Plant, Petróleos de Venezuela S.A. (PDVSA), Monagas State. The IVR system that is in connection with the historical module of the Supervisory Control and Data Acquisition System (SCADA) Guardian of ALBA (GALBA) provides the user who requires it, the updated information in real-time of any of the process variables used in the plant. The study was of feasible project modality corresponding to field research and descriptive level, due to the fact that it seeks to solve a particular need. Four phases of the Capital Investment Project Guide (GGPIC) were used. The IVR system developed allows the acquisition of operational information from the Boquerón Plant (oil and gas production reports, oil and gas production trends) from any place and at any time, by any means the user prefers, either by email, SMS, or directly by voice, providing greater reliability of data for senior management executives, which allows speeding up the identification of failures and the decision-making process, and helps to maintain the continuity of operations at the Boquerón Plant.

Massive Open Online Courses (MOOCs) have become a disruptive technology that has aimed to democratize access to education. These are courses that are offered openly, generally on a MOOC platform such as Open edX. These are courses that are offered openly, generally on a MOOC platform such as Open edX, and are taken by hundreds of thousands of students autonomously (without the presence or guidance of a teacher). When a MOOC is closed to a smaller number of students and is used privately and integrated into the academic curriculum, it is known as a Small Private Online Course (SPOC). SPOCs, unlike MOOCs, require the presence and guidance of a teacher while students take the course. However, the Open edX platform lacks visualizations to assist students and teachers in making decisions during the course. In other words, follow-up and monitoring is scarce and limited. For this reason, the present work proposes to develop a component called XBlock that implements, on the one hand, visualizations for students in order to account for their learning process; and, on the other hand, visualizations for teachers so that they can monitor, follow up and give feedback to students in a SPOC. To achieve this, the methodology adapted from LATUX was used for the planning, design and implementation of an XBlock and also for the evaluation of the visualization of the dashboard. As a result of the evaluation, it was found that about 80% of the students perceive the developed XBlock as a positive stimulus to redirect student behavior. In addition, it contributes as a support for teachers when designing teaching strategies that allow them to monitor and provide better feedback to students so that they can successfully complete the course.

This research presents the data analysis of electrical energy billed to regulated clients in the metropolitan region of Chile during 2015-2021 to establish the characteristics of the data structure and the relationship between the variables. It also aims to predict the classes of new records, and to identify underlying patterns in the data. This study uses descriptive statistical analysis, and the K-Means and K-NN machine learning algorithms. For this study period, it was established that the average unit energy consumption for residential customers was 453 kWh, and 10,315 kWh for non-residential customers. Likewise, there is a dependency between the number of clients and the electricity billed, as well as between the commune and the distribution company. On the other hand, the K-Means algorithm suggests a model that groups the data according to the type of customer and the type of electricity distribution company that supplies regulated customers. The application of the K-NN algorithm resulted in a model to predict the type of client of the new records, with an accuracy of 99.73%.

The bibliographic review is a fundamental phase in a research project, and it must guarantee that the most relevant information in the field of study is obtained. Our main objective was to know the works related to the Internet of medical things, from now on (IoMT).  We analyzed a total of 535 articles searched in Association for Computing Machinery in Adelante ACM, Web of Science and Scopus the search domain was IoMT, we established 3 parameters, (problematic, artifact and artifact evaluation), this according to the Research of Design Science in Adelante DSR, is a research approach for the construction of artifacts to provide a useful solution to a problem in each domain. The equation (Internet of things AND mesh) resulted in 535, (Internet of things AND medicine) a total of 417 and finally (Internet of medical things AND mesh) with 8, this means that there is a lot to investigate in this research domain. The advantages identified in this type of topology is to carry messages from one node to another by different paths, there can be absolutely no interruption in communications, each server has its own communica-tions with all other servers. Health and IT issues have been drastically influenced by the large data from IoMT devic-es. In this paper, we conducted a review of the scientific literature and mapped research trends on the IoMT paradigm in the health domain. Finally, this paper expands on the liter-ature, and the findings of this study can serve as a basis for future studies.

This article presents the practical implementation of a frequency control technique (virtual inertia) in an energy storage system based on supercapacitors (ESS-SC). The design of this proposal provides frequency support to a real isolated microgrid that integrates renewable generation sources (solar photovoltaic, 15 kWp), conventional synchronous generation (diesel thermal, 44 kVA), and energy storage systems (ESS-SC, 30 kW). The base case is a hybrid solar-diesel microgrid (typical situation of insular systems) operating in normal conditions. Frequency support tasks' effectiveness provided by the SAE-SC checks out, and the resilience of the microgrid are evaluated in terms of this variable. The experimental results show that the implementation of the proposal allows reducing the frequency fluctuations of the microgrid by 30%, representing a significant improvement in the quality of the electricity supply. The experiments were carried out in the Microgrid Laboratory of the Centro Científico, Tecnológico y de Investigación Balzay (CCTI-B) of the Universidad de Cuenca.

The use of chatbots in a variety of businesses is becoming more and more recurrent due to the scalability of customer service and the generation of automatic purchase processes. This project develops a chatbot system called Chatty that uses NLP to receive customer orders through an instant messaging application for the Snap eats delivery platform. The implementation of the chatbot achieved a significant percentage increase in the number of orders during the period in which it was measured. In addition to receiving positive ratings from users regarding ease of use. Using NLP in a chatbot for communication with customers is unusual due to the complexity and lack of control over the conversation; however, by applying a defined data flow, such complexity is reduced since the user is addressed without the need to use predetermined forms, creating a more fluid interaction. The NLP engine used for this project is GPT-3, which is a very powerful language generator model created by the company OpenAI.

Nowadays, the different cyber-attacks have forced organizations to find different equipment to protect them; however, the attack patterns are not the same in all organizations since their core work is not identical. Therefore, this paper proposes an analysis of the most recurrent attack patterns in university environments based on a comparison of the functionalities and results obtained by three types of Intrusion Detection Systems (IDS): two of them using free software and the third one using licensed software, as well as to carry out attacks on them in a controlled environment. This article contains the following sections: introduction, methodology, results, discussion, and conclusions. With the comparative analysis, it is expected to obtain statistics about the most critical attack patterns faced by this type of environment. Finally, guidelines are issued for the most optimal configurations to mitigate such attack patterns.