Vayas Ortega, Germania
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Vayas Ortega, Germania
Main Affiliation
Ambato
Email
germaniavayas@uti.edu.ec
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Scopus Author ID
57194585958

Research Output
Now showing 1 - 10 of 14
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Differential Performance of Satellite Navigation in Urban and Rural Andes of Ecuador

2024 , David Rivas-Lalaleo , Víctor Bautista-Naranjo , Vayas Ortega, Germania , Tatiana Freire-Guachamín , Jefferson Pilicita-Veloso , Carlos Bran

This study assesses the effectiveness of Global Navigation Satellite Systems (GNSS) in Ecuador, a country situated on the equator, where unique challenges include elevated ionospheric activity and increased solar radiation. It focuses on the accuracy of major satellite navigation systems such as GPS, Glonass, and Galileo in various environments, from open fields to urban areas with dense building coverage. Using a satellite communication module and a data logger capturing information every second, the study provides a detailed comparison of these systems. The findings indicate that a combination of GPS and Glonass significantly enhances accuracy, reducing errors to less than 20 cm, which is crucial for high-precision applications in the equatorial region. This outcome is consistent with and expands the understanding of satellite navigation performance across different Andean landscapes, highlighting the need for tailored approaches in both urban and rural settings within the equatorial context. In summary, the research reaffirms the transformative role of geopositioning and GNSS in global navigation and emphasizes the potential for improving GNSS accuracy in the equatorial region. It contributes significantly to ongoing efforts to optimize geopositioning systems, ensuring their effectiveness in diverse geographical and environmental conditions, as exemplified in the Andean regions of Ecuador.

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Bibliometric study for CO2 measurement using IoT: Looking for the Latin American contributions

2022 , Páez-Carabajo J.-D. , Huerta M.-K. , Rivas-Lalaleo D. , Vayas Ortega, Germania , Clotet-Martinez R. , Castillo-Velazquez J.-I.

In recent years, the number of deaths due to environmental pollution has increased. The main air pollutants are carbon monoxide, carbon dioxide, and sulfur dioxide. These are produced by the consumption of fossil fuels in vehicles, industrial activity, and agricultural practices, among others. Various technologies have been used to detect carbon dioxide (CO2), including the Internet of Things (IoT). However, no studies have been carried out to visualize the impact of IoT on CO2 monitoring and which countries are focused on minimizing emissions. This work shows a bibliometric study for CO2 environmental sensing using IoT. SCOPUS was the selected database, and PRISMA was the methodology used. The first search returned 13.207 documents written between 2013 and 2022, after filtering selected keywords, selecting only English articles, and abstract review we selected finally 79 documents for the measurement of CO2 using IoT. The results of analyzing them, show that the Asian countries produces more than the western countries, where India and Indonesia are leading. Also is interesting to note that the USA and Latin America produced the same quantity of documents, where the four countries contributing to Latin America are Brazil, Mexico, Peru, and Ecuador. The main area of knowledge covered by the documents was Engineering with 25 percent followed by computer sciences, and 40 percent of documents were published by IEEE. Finally, the Latin American contributions to this field are outlined, verifying in detail the architectures for the proposed solutions with emphasis in sensors. © 2022 IEEE.

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A long-range, low-cost technique to measure water level variations over limnimeters on hydraulic weir using machine vision and IoT

2022 , Chiliquinga-Chiliquinga A. , Garcés-Llerena R. , Bautista-Naranjo V. , Vayas Ortega, Germania , Castillo-Velazquez J.-I. , Clotet R. , Huerta M. , Rivas-Lalaleo D.

It is neither practical nor economical to make continuous and direct measurements of the water flow in a stream, so indirect methods must be used to measure the water level and, based on a calibration curve, relate it to the corresponding flow rate. A hydraulic weir with a limnimeter fulfills this purpose, but its disadvantage is that it does not allow the automated registration of the water level and therefore new and more efficient technologies must be used to perform this measurement automatically and thus have a lower waste and optimization of the resource. This experiment develops an algorithm based on computer vision and the inclusion of the concepts of the Internet of Things, in order to measure and record the values of the water level in a hydraulic dam, also includes energy storage system, power supply, remote computer, devices with wireless communication and IoT platform that allow a measurement error of less than ± 2% to be obtained with respect to a visual measurement made by the operator. © 2022 IEEE.

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Boosting Accuracy and Reducing Time in Laser Shooting Practices: Video Processing Solutions for Impact Evaluation

2024 , David Rivas-Lalaleo , Víctor Bautista-Naranjo , Vayas Ortega, Germania , Erika Iza-Chango , Pamela Lema-Jumbo , Carlos Bran

This study explores the most effective method for impact measurement in laser shooting ranges, crucial for security training, accident prevention, and cost reduction. It utilizes video surveillance and image processing algorithms in Python to accurately determine laser impact locations. The research found that employing a single target per silhouette is most efficient, minimizing errors to ±1 impact and enabling heat map generation for feedback. The combination of video surveillance and image processing significantly enhances safety and reduces costs by providing real-time data. The findings advocate for the single target approach due to its precision and the comprehensive insights gained from heat maps, maintaining accuracy within a two-hit margin.

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Artificial Intelligence in Marketing: A Bibliometric Study

2024 , Suárez Pérez, Juan Carlos , Vayas Ortega, Germania

Nowadays, the use of artificial intelligence (AI) is revolutionizing and transforming businesses. In the field of marketing, it has enabled the optimization of strategies and campaigns, content personalization, more precise segmentation, and maximization of planning results, thanks to its ability to process and analyze data. The research aims to provide a bibliometric approach to current knowledge on AI in marketing. The methodology involved a bibliometric review by obtaining indexed research papers from the SCOPUS database, which were then analyzed using the VOSviewer application. The results identified that countries such as the United States, India, and China have the highest scientific production on the subject. Additionally, it was revealed that the most relevant knowledge areas are engineering, management and business, and accounting. In this context, it is concluded that it is crucial for companies worldwide to observe the advancements made by these countries to replicate strategies according to their needs. Considering that AI, thanks to the internet, is accessible for all types of businesses, they only need to identify opportunities and key areas to apply AI tools and train their personnel.

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Effect of the Real Wage on the Basic Family Basket in Ecuador

2024 , Vayas Ortega, Germania , Morales-Urrutia X. , Haro D.L. , Chancay D.

The effect of real wages on the basic family basket in Ecuador is a crucial issue in understanding households’ economic well-being. The real wage, which considers inflation and purchasing power, directly affects the ability of families to purchase essential goods and services. Analysis of this relationship provides insight into families’ challenges in meeting their basic needs and the potential implications for poverty and inequality in Ecuador. The study's objective is to analyze the purchasing power of the Ecuadorian population through data on real wages and basket costs from 2000 to 2021. The data analyzed comes from the Central Bank and INEC databases. The results indicate a sustained increase in the basic basket throughout the 2000–2021 period, which shows an increase in the prices of goods and services throughout the country. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

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Analysis of the Business Dimension in the Construction Sector in Ecuador: An Economic Approach

2024 , Vayas Ortega, Germania , Dayaneth Arroba-Naranjo , Ximena Morales-Urrutia , Diego Lara Haro

The objective of this research work is to study the business size of the construction sector in Ecuador through the application of a panel data econometric model. It seeks to identify the factors that influence the growth of this sector. The study population is construction companies active in Ecuador, according to the ISIC F classification, in the period 2018–2021. A methodology is used that includes a descriptive analysis to establish the behavior of the sector variables, as well as a correlational analysis to measure the significance of these variables in relation to growth. In addition, a panel data model that applies the assumption of fixed effects is used to verify Gibrat’s Law, which establishes that all companies have the same probability of growing regardless of their size. In conclusion, a significant relationship was found between sales and business size and growth in the construction sector in Ecuador. However, Gibrat’s Law is rejected in this case study.

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Organizational Commitment in Savings and Credit Cooperatives

2024 , Shaina Johanna Sisa , Espinoza Guano, Mónica , Vayas Ortega, Germania , Ximena Morales-Urrutia

With globalization and technological advancements, companies face changes that require a culture of continuous learning and adaptation. The changes effectively managing can determine an organization's success in a dynamic environment. Organizational Commitment (OC) is crucial as it measures employees' identification, belonging, and loyalty. In Ecuador, savings and credit unions and non-profit financial institutions decreased from 817 active entities in 2015 to 408 in 2023, functioning as an important source of employment. It is essential to determine the OC level and analyze its variables. Therefore, a bibliometric review was conducted to identify the scientific production on the subject, followed by a systematic review to substantiate and identify methods for measuring OC. The Meyer and Allen scale test was applied to 169 employees of a cooperative union. The data was processed using SPSS to perform a descriptive and correlational analysis with a non-experimental, cross-sectional design. The sample was evenly split between men and women, revealing connections between study dimensions and areas for improvement..

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Factors for the Creation of Technological Startups in Latin America

2024 , Vayas Ortega, Germania , Morales-Urrutia X. , Naranjo-Santamaría J.

The changes produced in recent years have made innovation and technology play an important role in the growth of technological start-ups. Likewise, public policies have been developed that contribute to the development and strengthening of this business sector. The aim of the study is to analyze the incidence of institutional factors, education and innovation, in the generation of technological startups. The data analyzed comes from the Global Entrepreneurship Monitor, the Pearson Correlation statistical technique was applied. The results suggest that there is a direct relationship between the factors analyzed. In conclusion, the growth of this type of companies is still incipient in Latin American countries, however, there is significant growth of these in the region. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

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Analysis of the Business Dimension in the Construction Sector in Ecuador: An Economic Approach

2024 , Vayas Ortega, Germania , Dayaneth Arroba-Naranjo , Ximena Morales-Urrutia , Diego Lara-Haro

The objective of this research work is to study the business size of the construction sector in Ecuador through the application of a panel data econometric model. It seeks to identify the factors that influence the growth of this sector. The study population is construction companies active in Ecuador, according to the ISIC F classification, in the period 2018–2021. A methodology is used that includes a descriptive analysis to establish the behavior of the sector variables, as well as a correlational analysis to measure the significance of these variables in relation to growth. In addition, a panel data model that applies the assumption of fixed effects is used to verify Gibrat’s Law, which establishes that all companies have the same probability of growing regardless of their size. In conclusion, a significant relationship was found between sales and business size and growth in the construction sector in Ecuador. However, Gibrat’s Law is rejected in this case study

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