Person:
Saquicela Galarza, Víctor Hugo

Birth Date

1975-12-15

ORCID

0000-0002-2438-9220

Scopus Author ID

36624403800

Afiliación

Universidad de Cuenca, Cuenca, Ecuador
Universidad de Cuenca, Departamento de Ciencias de la Computación, Cuenca, Ecuador

País

Ecuador

Organizational Units

Organizational Unit

Facultad de Ingeniería

La Facultad de Ingeniería, a inicios de los años 60, mediante resolución del Honorable Consejo Universitario, se formalizó la Facultad de Ingeniería de la Universidad de Cuenca, conformada por las escuelas de Ingeniería Civil y Topografía. Esta nueva estructura permitió una mayor especialización y fortalecimiento en áreas clave para el desarrollo regional. Cuenta con programas académicos reconocidos internacionalmente, que promueven y lideran actividades de investigación. Aplica un modelo educativo centrado en el estudiante y con procesos de mejora continua. Establece como prioridad una educación integra, la formación humanística es parte del programa de estudios que complementa a la sólida preparación científico-técnica. Las actividades culturales pertenecen a un programa permanente y activo al interior de nuestras dependencias, a la par de proyectos que desde el alumnado y bajo la supervisión de docentes cumplen con servicios de apoyo a nivel local y regional; promoviendo así una vinculación estrecha con la comunidad.

Job Title

Profesor (T)

Last Name

Saquicela Galarza

First Name

Víctor Hugo

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Search Results

Now showing 1 - 10 of 42

Discovering research trends in the computer science area of Ecuador: an approach using semantic knowledge bases
(Institute of Electrical and Electronics Engineers Inc., 2019) Segarra Flores, Jose Luis; Ortiz Vivar, José Enrique; Gualan Saavedra, Ronald Marcelo; Saquicela Galarza, Víctor Hugo
We present a study of research trends for the area of Computer Sciences in Ecuador in recent years. This analysis was performed through a new method that leverages on semantic web technologies and external knowledge bases (i.e. DBpedia and UNESCO nomenclature) for identifying research topics within articles' metadata. This information takes into account the documents' publication date in order to construct time series which are analyzed and interpreted looking for trends. Concretely, we focused our study on the REDI (Semantic Repository of Ecuadorian Researchers) knowledge base which compiles most of the scholarly assets produced in Ecuador and more specifically on the Computer Science subset of publications. This study found that most of the research topics have shown an steady growth in the volume of publications over time, whereas the Semantic Web and E-Government research topics had a great impact initially and now have been slightly reducing its share in favor of new topics such as Information Integration, Machine Learning and Data Mining.
An Approach to Experiment Reproducibility Through MLOps and Semantic Web Technologies
(IEEE, 2023) Seaman Mora, Daniel Andres ; Palacio Baus, Kenneth Samuel; Saquicela Galarza, Víctor Hugo; Peñafiel Mora, David Marcelo; Seaman Mora, Daniel Andres
This article addresses the challenge of reproducing machine learning (ML) experiments by integrating processes based on MLOps and semantic technologies. The inherent complexity of experimentation in scientific research hinders reproducibility through conventional methods, which has led to the need to automate processes. In this work, a solution has been developed allowing the execution of ML experiments of other researchers and their reproducibility. The use of semantic technologies allows the complete description of the experiment, including the data and resources necessary for its execution. The approach proposed in this work contributes to the automation of the experimentation phases based on MLOps, demonstrating how it can be used to reproduce experiments and offer a solution to the complexity of experimentation in scientific research. The effectiveness of the solution proposed in this work is evaluated by means of a survey-based analysis carried out among researchers who currently use manual processes to perform machine learning experiments. The results indicate that manual processing is prone to errors and not scalable regarding the size and complexity of most experiments. Moreover, the solution proposed in this work, which combines MLOps-based processes and semantic technologies, has been well received by researchers and considered to significantly improve the efficiency, reproducibility, and scalability of machine learning experimentation.
Predicting ozone pollution in urban areas using machine learning and quantile regression models
(Springer International Publishing, 2021) Cueva, Fernando; Saquicela Galarza, Víctor Hugo; Sarmiento Vintimilla, Juan Carlos; Cabrera Mejia, Fanny Virginia; Sarmiento Jara, Juan Pablo; Sarmiento Jara, Juan Pablo
Ozone is the most harmful secondary pollutant in terms of negative effects on climate change and human health. Predicting ozone emission levels has therefore gained importance within the field of environmental management. This study, performed in the Andean city of Cuenca, Ecuador, compares the performance of two methodologies currently used for this task and based on machine learning and quantile regression techniques. These techniques were applied using cross-sectional data to predict the ozone concentration per city block during the year 2018. Our results reveal that ozone concentration is significantly influenced by nitrogen dioxide, sedimentary particles, sulfur dioxide, traffic, and spatial features. We use the mean square error, the coefficient of determination, and the quantile loss as evaluation metrics for the performance of the ozone prediction models, employing a cross-validation scheme with a fold. Our work shows that the random forest technique outperforms gradient boosting prediction, neural network, and quantile regression methods.
Generation of Microservice Names from Functional Requirements: An Automated Approach
(Springer Science and Business Media Deutschland GmbH, 2024) Granda Juca, María Fernanda; Saquicela Galarza, Víctor Hugo; Arias Barros, Jhoan Sebastian; Suquisupa Nacipucha, Pamela Aracely
In the context of the advancement of software architectures based on microservices and the relevance of requirements engineering in application development, the problem of manual creation and the need for expertise to define microservices, a human activity that requires a high level of knowledge and experience, arises. To address this challenge, a solution is proposed that consists of finding the ideal names for microservices. To automate the process of identifying microservice names, this proposal is based on the application of Natural Language Processing (NLP) techniques, graph analysis and community detection, including the use of artificial intelligence language models such as ChatGPT.
Towards an E-learning Platform Based on Interactive Visual Elements
(IEEE Computer Society, 2019) Medina Cartuche, Jose Luis; Espinoza Mejía, Jorge Mauricio; Saquicela Galarza, Víctor Hugo; Vega Zamora, Oswaldo Francisco
The traditional approach of e-learning platforms based on learning management systems has allowed education to be accessible to a broader group of people; however, their pedagogical model based on promoting a transmissive approach has caused learning outcomes do not achieve the success of their traditional counterpart. There is a disconnection between what happens in the physical classroom and what happens when students take an online class. The experience usually goes from interactive to static.In this work, we propose the design of an interactive e-learning platform that makes use of dynamic media such as videos, to improve the interactive experience of students. To this end, the main limitations of current systems are studied and different solutions are proposed to mitigate the problems. The main contributions of this work are, first, to establish a set of challenges that interactive e-learning platforms should support, and second, the description of the necessary processes to implement the platform.
Enriching Electronic Program Guides using semantic technologies and external resources
(INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC., 2014-09-15) Saquicela Galarza, Víctor Hugo; Alban Bermeo, Humberto Marcelo; Espinoza Mejía, Jorge Mauricio; Palacio Baus, Kenneth Samuel
Electronic Program Guides (EPGs) describe broadcast programming information provided by TV stations. However, users may obtain more information when these guides have been enriched. The main contribution of this work is to present an automation process for EPG's information enrichment through the use of semantic technologies and external resources. Among the several resources involved in the enrichment process, the following can be mentioned : ontologies, web services, semantic repositories and natural language processing techniques.
REDI: towards knowledge graph-powered scholarly information management and research networking
(2020) Ortiz Vivar, Jose Enrique; Segarra Flores, José Luis; Villazón Terrazas, Boris Marcelo; Saquicela Galarza, Víctor Hugo
Academic data management has become an increasingly challenging task as research evolves over time. Essential tasks such as information retrieval and research networking have turned into extremely difficult operations due to an ever-growing number of researchers and scientific articles. Numerous initiatives have emerged in the IT environments to address this issue, especially focused on web technologies. Although those approaches have individually provided solutions for diverse problems, they still can not offer integrated knowledge bases nor flexibility to exploit adequately this information. In this article, we present REDI, a Linked Data-powered framework for academic knowledge management and research networking, which introduces a new perspective of integration. REDI combines information from multiple sources into a consolidated knowledge base through state-of-the-art procedures and leverages semantic web standards to represent the information. Moreover, REDI takes advantage of such knowledge for data visualisation and analysis, which ultimately improves and simplifies many activities including research networking.
REDI: a linked data-powered research networking platform
(Springer, 2018) Sumba Toral, Francisco Xavier; Segarra Flores, José Luis; Villazón Terrazas, Boris Marcelo; Espinoza Mejía, Jorge Mauricio; Saquicela Galarza, Víctor Hugo; Sumba Toral, Francisco Xavier
Research networking is a difficult part of academics in spite of the multiple benefits that the Web has brought within this field in recent years. Even though scientific and business social networks provide a medium to discover peers worldwide, their usefulness meets its limits when real-world requirements come in. The broad audience of those tools and other bibliographic databases lead them to ignore cultural and geographical aspects such regional indexes, organizational structures, among others. On this poster, we introduce REDI, a Linked Data - powered research networking platform which combines both local (institutional/regional) and external (Web) scholarly sources in a consolidated knowledge base. Moreover, REDI leverages on its knowledge base to cluster authors within similar research areas easing networking and unveiling a variety of new information from data for multiple purposes.
Towards the Creation of a Semantic Repository of iStar-Based Context Models and the DHARMA Method [Hacia la Creación de un Repositorio Semántico de Modelos de Contexto Basados en i* y el método DHARMA]
(ASSOCIACAO IBERICA DE SISTEMAS E TECNOLOGIAS DE INFORMACAO, 2016-01-01) Abad Regalado, Karina Alexandra; Carvallo Vega, Juan Pablo; Espinoza Mejía, Jorge Mauricio; Saquicela Galarza, Víctor Hugo
A general process for the semantic annotation and enrichment of electronic program guides
(Springer Verlag, 2019) Gonzalez Toral, Hernan Santiago; Espinoza Mejía, Jorge Mauricio; Palacio Baus, Kenneth Samuel; Saquicela Galarza, Víctor Hugo
Electronic Program Guides (EPGs) are usual resources aimed to inform the audience about the programming being transmitted by TV stations and cable/satellite TV providers. However, they only provide basic metadata about the TV programs, while users may want to obtain additional information related to the content they are currently watching. This paper proposes a general process for the semantic annotation and subsequent enrichment of EPGs using external knowledge bases and natural language processing techniques with the aim to tackle the lack of immediate availability of related information about TV programs. Additionally, we define an evaluation approach based on a distributed representation of words that can enable TV content providers to verify the effectiveness of the system and perform an automatic execution of the enrichment process. We test our proposal using a real-world dataset and demonstrate its effectiveness by using different knowledge bases, word representation models and similarity measures. Results showed that DBpedia and Google Knowledge Graph knowledge bases return the most relevant content during the enrichment process, while word2vec and fasttext models with Words Mover’s Distance as similarity function can be combined to validate the effectiveness of the retrieval task.