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Editorial

Gustavo Díaz — Wed, 27 Nov 2024 00:00:00 +0000

COMPETENCE ANALYSIS IN THE PROGRAMMING II COURSE (DATA STRUCTURES) IN THE NIGHT SHIFT OF THE FIEC, UNIVERSITY OF PANAMA: BACHELOR'S DEGREE IN COMPUTER SCIENCE APPLIED TO THE TEACHING AND IMPLEMENTATION OF TECHNOLOGIES, YEAR 2022

Carlos E. Chávez-González — Tue, 26 Nov 2024 00:00:00 +0000

The objective of this study is to analyze the ability to develop the programming II course (data structures) of the night shift of Facultad de Informática, Electrónica y comunicación (FIEC) of the University of Panama: The research will be very useful for the FIEC, the bachelor's degree in computer science applied to the teaching and implementation of technologies year 2022, considering the great importance it has for students and teachers who receive the course and dictate it respectively; therefore, it will be very useful for the FIEC, the bachelor's degree in computer science applied to the teaching and implementation of technologies, teachers, to have valuable information to design the most appropriate teaching strategies to dictate this subject.

The research that has been developed is of quantitative type, the population that was studied are the students of bachelor's degree in computer science applied to the teaching and implementation of technology, night group year 2022, carried out with a sample of 16 students. The survey was used as the main technique and the Google forms questionnaire was used as an instrument, which explains the difference between the skills and previous knowledge of the students with respect to the required competencies. To measure the degree of association between the variables, the percentage average was used.

A percentage of 25% was obtained as the mean statistical value, which leads to the conclusion that the students' skills and prior knowledge is low. That is, the predictive value for skills is very low, and that there would be other factors that are influencing the students' knowledge.

USE AND APPLICATION OF MACHINE LEARNING TO CREATE MODELS IN DECISION MAKING IN THE HEALTH AREA

Denis Cedeño — Tue, 26 Nov 2024 00:00:00 +0000

Artificial intelligence (AI) is the discipline that tries to replicate and develop intelligence and its implicit processes through computers. AI synthesizes and automates tasks that are intellectual in principle and is therefore potentially relevant to any field of human intellectual activity, currently encompassing a wide variety of subfields, such as natural language processing (NLP), machine learning (ML), robotics. With AI, data analysis projects are being carried out working with ML, however, these types of solutions are very scarce, especially in the medical area of ??our country. Using innovative technologies such as AI applied to areas as sensitive as health is increasing every day. The new models based on ML are currently being used more, however, in our countries there are few studies related to the subject. Therefore, this research aims to use various ML techniques and determine how these models can help us solve health problems.

Industry 4.0 in 5G era: Oportunities and Challenges in Home Automation through Internet of Things.

Tue, 26 Nov 2024 00:00:00 +0000

Current society is undergoing an unprecedented digital transformation that is changing our interaction with technology. The disruptive advancements of Industry 4.0, based on technologies from the fourth industrial revolution, have a significant impact on disciplines such as electrical engineering, business administration, computer science, technology, and software, among others. These advancements integrate physical, digital, and biological technologies such as artificial intelligence, robotics, data analysis, and the Internet of Things (IoT). The technology of 5G and IoT are closely related, enabling the integration of automated and monitored homes, along with the interconnection of devices through distributed sensors in various platforms and services with extensive data processing and storage capabilities. 5G, with its fast connection speed and low latency, is crucial for the full development of IoT and other technologies such as augmented reality, autonomous vehicles, and telemedicine. IoT emerges as an evolutionary complement to communication and computer science applied to objects, allowing interaction through the Internet. The implementation of smart homes begins with the installation of internet-connected devices such as sensors, thermostats, and smart appliances that can be interconnected to achieve automated processes and optimized energy consumption. However, along with the opportunities offered by home automation through IoT, challenges related to security also arise. It is essential to implement adequate security measures such as strong passwords, frequent updates, firewalls, and antivirus software to protect connected devices from potential external attacks and manipulations. Users must also be aware of the importance of maintaining security in their homes and take immediate action to mitigate risks in the event of threats.

DEVELOPMENT OF A MOBILE APPLICATION FOR THE DISSEMINATION OF SCIENTIFIC PRODUCTION IN SOCIAL NETWORKS

José Antonio Murillo Tuñón, Francisco Farnum — Tue, 26 Nov 2024 00:00:00 +0000

With the emergence of mobile technologies, such as touch screens and more compact electronic devices, it is possible to be connected to scientific information immediately, with accurate information. With the purpose of making visible the scientific production of the University of Panama, under the FAIR principle (Findability, Accessibility, Interoperability and Reusability); the “Journal's Tips By Up” Mobile App was developed in the open access language “Dart” of the Google platform, using Flutter as a framework for multiplatform applications. This App offers an interactive medium to the scientific articles published in the Portal of Journals of the University of Panama, and links to YouTube channels and other social networks of the University, disseminating interviews, videos, summary of congresses and others. Since its launching in the year 2022, it has contributed to improve the metrics of view and download of articles in the scientific journals of the Institution.

Considerations about IoT in the Building Design, Construction and Maintenance Management

Marjorie Gutiérrez de Gómez, Cristóbal Gómez Sevillano — Tue, 26 Nov 2024 00:00:00 +0000

Artificial intelligence (AI) generates controversy if it is applied in the exercise of liberal professions that were thought to be exclusive activities for humans, such as creating pictures or paintings, writing texts, or architectural design. However, the impact that these technologies have has been such that, if we do not update ourselves, we will lose execution capacity and therefore become obsolete. Wireless networks aim to provide data and information connectivity with high energy efficiency, low cost and support many connected devices as an evolution of the Internet of Things (IoT) both in the design and construction processes, as well as in the operation of the building, its maintenance and daily insertion into the life of smart cities. Here we will make a quick review of the (IoT) applications already available in our work area, with the intention of promoting and motivating their use in building intervention projects.

Semi-autonomous search and rescue robot architecture of Fast manufacturing

Yenikarina Salazar, Iván Armuelles — Tue, 26 Nov 2024 00:00:00 +0000

In this paper we propose the development of a rapidly manufactured search and rescue unmanned ground vehicle prototype capable of traveling on uneven terrain, debris, and inclined planes through a semi-autonomous system that can detect and evaluate the state of a victim who is in danger among the rubble of a collapsed structure.

The development of a rapidly manufactured unmanned ground vehicle must not only have maneuverability capabilities in difficult access. Also, obtain information about the physical environment to locate victims through sensors. Being able to identify the orientation of movement within the field, detect the presence of heat, perceive motion in confined spaces, determine the presence of toxic gases, such as high levels of carbon dioxide; communicate with a victim through a microphone and speaker, and be able to respond in case of finding a person alive. The mobile robot must carry out search and rescue missions and objectives similar to those completed by an industrialized robot.

Study of solar flares and their influence on electronic communication channels through the implementation of a monitoring system for the VLF frequency band

Angie M´árquez, Axel Márquez, Fermín Póvaz — Tue, 26 Nov 2024 00:00:00 +0000

This research work analyzes the non-incidence of solar flares on wireless communication systems operating in the microwave frequency band, specifically in the S band (2.4 GHz), such as WiFi networks. The study focuses on the influence of solar flares on the propagation of electromagnetic waves in the Very Low Frequency (VLF) band. A monitoring system was implemented that includes loop antennas, specialized VLF receivers, and microcontrollers to capture real-time data. This system allowed for the investigation of the relationship between solar events and the variability in VLF wave propagation, with relevant applications in submarine communications and navigation systems.The analysis covers the background of the problem, the research methodology, and the contribution to the knowledge of space weather. Additionally, the types of filters, reception systems, and antennas used are examined, highlighting their importance in accurately capturing data during solar events. The results of this research advance the understanding of the impacts of solar phenomena on electronic communications in the VLF band, providing valuable information to mitigate possible adverse effects.

Machine Learning Algorithms in the Prediction of University Academic Performance: a Systematic Review

Fabiola Montero, Nelson Montilla, Julio Arcia — Tue, 26 Nov 2024 00:00:00 +0000

In recent years, the growth of Machine Learning has had a significant impact across various fields, including education. In the educational sphere, Machine Learning techniques or algorithms have been applied for various purposes, such as predicting the academic performance of higher education students. This article focuses on reviewing publications that present the results obtained by employing Machine Learning algorithms to predict the academic performance of university students. A systematic review was conducted using academic databases such as Redalyc, Google Scholar, and Scielo, utilizing search filters and relevant keywords. Subsequently, the most relevant articles were selected for analysis. The purpose of this review article is to identify the most frequently used and effective Machine Learning algorithms for predicting the academic performance of university students, as well as to examine how they have been implemented in different universities, serving as a guide for future research involving the application of these algorithms with student data from the University of Panama. The results show that the most commonly used algorithms for this type of prediction are Decision Trees, K-Nearest Neighbors (KNN), Naive Bayes, Random Forest, and Support Vector Machines (SVM), as well as Artificial Neural Networks, which also stand out for their high accuracy. The use of these algorithms to predict academic performance in universities offers great potential to reduce dropout rates, improve academic outcomes, support pedagogical decisions, and optimize educational resources.

IoT and the Amazon sidewalk threat: protecting your home and privacy

Jenny Ríos — Tue, 26 Nov 2024 00:00:00 +0000

Amazon Sidewalk is a new feature that connects Amazon smart devices (like Echo and Ring) to each other and to neighbors' devices, creating a community internet network. While this can increase the connectivity and security of devices, it has also raised privacy concerns. Privacy advocates point out that Amazon collects data on network usage and that devices automatically opt into the service without explicit user consent. Additionally, there are potential security vulnerabilities that could be exploited by malicious actors. It is important to be aware of the risks and benefits of IoT before using devices like Amazon Sidewalk. Users should take steps to protect their privacy, such as using strong passwords, keeping devices updated, and being proactive with security settings.

USE OF A PROTOTYPE FOR THE GENERATION OF EOLIC ENERGY, AS AN ALTERNATIVE LEARNING METHOD OF LENZ AND FARADAY LAWS

Javier Fernández Pájaro, Denis Rubin Edwards — Tue, 26 Nov 2024 00:00:00 +0000

Nowadays there are several techniques used to generate electrical energy, based mainly on Lenz and Faraday laws related to the generation of electrical energy, for the reasons stated above this essay generates an alternative learning methodology, which allows the student to understand from their experiences the theoretical foundations related to the entire process of generation, storage and distribution of electrical energy, to achieve this purpose a prototype is built using the air force to generate electricity using magnets, a coil and an LED, which demonstrates the generation of electrical energy through the rotation of magnets and electromagnetic induction.