Dra. Gabriela Marín Raventós

Dra. Gabriela Marín Raventós

Labor: 
Investigador(a)
Unidad académica: 
Escuela de Ciencias de la Computación e Informática (ECCI)
Es estudiante: 
No

Formación académica

  • "Doctor of Philosophy" en Administración de Negocios, con énfasis en Sistemas de Información Gerencial, Graduate School of Business Administration, Texas A&M University, College Station, Texas, U.S.A., agosto 1993.
  • "Master of Science" en Ciencias de la Computación, Department of Computer Engineering and Science, Graduate School of Engineering, Case Western Reserve University, Cleveland, Ohio, U.S.A., agosto 1985.
  • Estudios de Maestría en Administración Pública, Programa Instituto Centroamericano de Administración Pública (ICAP) - Universidad de Costa Rica, San José, Costa Rica, de junio 1981 a abril 1982 (29 créditos).
  • Licenciatura en Ciencias de la Computación, Escuela de Matemáticas, Universidad de Costa Rica, San Pedro, Costa Rica, febrero 1981.
  • Bachillerato en Ciencias de la Computación, Escuela de Matemáticas, Universidad de Costa Rica, San Pedro, Costa Rica, agosto 1980.

Experiencia laboral

  • Directora, Centro de Investigación en Tecnologías de Información y Comunicación (CITIC), Universidad de Costa Rica,  21 de junio 2012 al 31 de julio 2017.
  • Decana del Sistema de Estudios de Posgrado, Universidad de Costa Rica, 30 junio 2008 al 29 junio 2012.
  • Vice-Decana del Sistema de Estudios de Posgrado, Universidad de Costa Rica, 14 de noviembre del 2007 al 29 de junio del 2008. 
  • Directora, Programa de Posgrado en Computación e Informática, Universidad de Costa Rica, 15 de mayo de 1998 al 30 de julio del 2009.
  • Representante, Area de Ingeniería ante el Cosejo del Sistema de Estudios de Posgradp, Universidad de Costa Rica, 2002-2004, 2004-2006, 2006-2008.
  • Profesora Catedrática, Escuela de Ciencia de la Computación e Informática, Universidad de Costa Rica, julio 1981- al presente.
  • Miembro, Comisión de Maestría, Telemática, 1998 hasta 2001.
  • Profesora y coordinadora, Programa de Diplomado en Computación Administrativa, Universidad de Costa Rica, desde 1987 hasta julio 1989.
  • Investigador I, Consejo Nacional de Rectores (CONARE), dese agosto 1980 a junio 1981.

Proyectos

Publicaciones

Typifying Data Required for the Development of Smart Agriculture Systems

Ago
2019

Descripción:

Smart agriculture is an active research field. Currently, many researchers are working on the construction of platforms directed to improve efficiency, crop processes, and data awareness. However, it is common that developers focus on data monitoring instead of the data relevance for decision making or the costs associated with the creation of monitoring platforms. In this paper, we present a classification of the data required by researchers on the construction of decision-support systems applied to smart agriculture processes. By using this classification, the user can define which data are relevant according to the characteristics of the problem that needs to be solved.We have applied the classification to data recollected in a study case conducted by the end of last year. Besides, we identify a list of agronomic and climatic variables commonly used in the construction of decision support systems. We apply the classification to this list of variables as an example for researchers. As a conclusion, this typification permits the researcher to identify data that has to be monitored and controlled, and data that does not have to be measured, the later based on the data characteristics and utility for the farmer.

Tipo de publicación: Conference Paper

Publicado en: 2019 IV Jornadas Costarricenses de Investigación en Computación e Informática (JoCICI)

Alzheimer’s Disease Early Detection Using a Low Cost Three-Dimensional Densenet-121 Architecture

Jun
2020

Descripción:

The objective of this work is to detect Alzheimer’s disease using Magnetic Resonance Imaging. For this, we use a three-dimensional densenet-121 architecture. With the use of only freely available tools, we obtain good results: a deep neural network showing metrics of 87% accuracy, 87% sensitivity (micro-average), 88% specificity (micro-average), and 92% AUROC (micro-average) for the task of classifying five different classes (disease stages). The use of tools available for free means that this work can be replicated in developing countries.

Tipo de publicación: Conference Paper

Publicado en: Lecture Notes in Computer Science

Effects of oral metaphors and allegories on programming problem solving

Mar
2018

Descripción:

Metaphors of ordinary concepts are intensively used in computer science for naming abstract concepts and for designing users interfaces. Metaphors are mappings from a source domain (e.g., a stream) to a target domain (e.g., a sequence of bytes). Typically computing phenomena are explained using incoherent discourses at the source domain, formed by metaphors taken from a diversity of origins. Nonetheless, versatility of metaphors allows for the creation of coherent discourses in the origin domain that map the target computing discourse, and we call them allegories. The limited number of existing studies about this topic has compared only textual allegories, visual allegories, and the traditional unconnected metaphors. Although their findings are heterogeneous, equal effectiveness is the most frequent empirical result between these three types of metaphors. Furthermore, we have not found any study about oral allegories, in spite of oral being the most used modality for metaphors in computer science education. This article experimentally compares the effects of oral allegories and oral metaphors on a complex problem‐solving task. As in previous studies, our results did not find any significant differences on support or detriment of oral allegories. Our results support new metaphor theories posing that the context significantly influences the metaphors’ efficacy, and encourages future research about the interaction between context and allegories.

Tipo de publicación: Journal Article

Publicado en: Computer Applications in Engineering Education

A Precise Layout Manager for Vector Graphics

Ago
2019

Descripción:

Automated layout is the use of software to determine the positions and sizes of visual elements that are part of an information presentation. As the amount of data that computers are able to process increases, automatic layout becomes more necessary. During the process of creating a program visualization, the authors needed a precise layout manager for scalable vector graphics that supported layers and animations. A literature review revealed the lack of a layout manager that satisfies these requirements. This paper reports the creation of a layout manager that uses floating-point arithmetic for precise and imperative arrangement of visual elements, that may be useful for other visual applications facing similar requirements.

Tipo de publicación: Conference Paper

Publicado en: 2019 IV Jornadas Costarricenses de Investigación en Computación e Informática (JoCICI)

Early Detection of Diseases in Precision Agriculture Processes Supported by Technology

Mar
2021

Descripción:

One of the biggest challenges for farmers is the prevention of disease appearance on crops. Governments around the world control border product entry to reduce the number of foreign diseases affecting local producers. Evenmore, it is also important to reduce the spread of crop diseases as quickly as possible and in early stages of propagation, to enable farmers to attack them on time, or to remove the affected plants. In this research, we propose the use of convolutional neural networks to detect diseases in horticultural crops. We compare the results of disease classification in images of plant leaves, in terms of performance, time execution, and classifier size. In the analysis, we implement two distinct classifiers, a densenet-161 pre-trained model and a custom created model. We concluded that for disease detection in tomato crops, our custom model has better execution time and size, and the classification performance is acceptable. Therefore, the custom model could be useful to use to create a solution that helps small farmers in rural areas in resource-limited mobile devices.

Tipo de publicación: Book Chapter

Publicado en: Advances in Sustainability Science and Technology

Online Judge Support for Programming Teaching

Jun
2021

Descripción:

Online programming judges are considered useful and sometimes indispensable tools to support competitive programming, professionals' recruiting, and programming education. In this last field, the scientific literature on these tools focuses on the learners' needs, but neglects the requirements of the professors, even though they are who mainly decide whether or not an educational tool is adopted in the courses they teach. This article collected 132 functional requirements for educative online judges, from the scientific literature and programming teachers with experience in the use of this type of tool. To know the degree of support, the requirements were grouped into 27 categories, and a requirements verification was performed with four available educative online judges reported in a recent systematic literature review. A low degree of satisfaction of requirements was found. This result encourages future research to create tools that better support teaching-learning processes and the requirements collected are a useful contribution as a starting point for such research.

Tipo de publicación: Conference Paper

Publicado en: 2020 XLVI Latin American Computing Conference (CLEI)

Common Causes and Effects of Technical Debt in Costa Rica: InsighTD Survey Replication

Oct
2021

Descripción:

Technical debt is a concept used to describe technical decisions that can benefit companies in the short term but can produce costs and software quality issues in the long term. Technical debt management can help enterprise profitability, sustainability, and the software industry's credibility. This paper presents a replication of the InsighTD survey (a globally distributed family of industrial surveys on causes and effects of TD), focusing on Costa Rica and comparing other regional countries. In total, 145 practitioners from the Costa Rican IT industry participated. Results show that the leading cause of technical debt is not technical (not only in Costa Rica but also in the region). On the other hand, the main effects reported are delivery delay and general dissatisfaction of the parties involved. A comparative study of InsighTD survey results in various countries is also included.

Tipo de publicación: Conference Paper

Publicado en: 2021 XLVII Latin American Computing Conference (CLEI)

When One Wireless Technology is Not Enough: A Network Architecture for Precision Agriculture Using LoRa, Wi-Fi, and LTE

Ene
2022

Descripción:

The world population will reach nearly 10 billion people by 2050, according to the United Nations. Therefore, more food to supply the world's demand will be required in the following years. Precision agriculture emerges as an option to satisfy the growing demand. In smart farming, wireless sensor networks (WSNs) are crucial in the deployment of sensors in crop fields. Precision agriculture includes crop monitoring and fertigation control. Monitoring and control have distinct network requirements. While monitoring stations deployment requires long-range networks, control stations have other requirements like low latency. For that reason, the use of a combination of WSN is necessary. In this paper, we present an option of network architecture for precision agriculture projects. The architecture includes the use of LoRa for monitoring stations and Wi-Fi/LTE for control stations. Currently, we are working on smart fertigation in greenhouses. For the architecture, we consider the typical requirements for smart farming projects, but also our project’s requirements.

Tipo de publicación: Conference Paper

Publicado en: Intelligent Sustainable Systems

Designing a Context-Aware Smart Notifications System for Precision Agriculture

Nov
2022

Descripción:

Smart farming solutions seek to help farmers in their daily activities. Their use has shown that it is beneficial for farmers to be aware of the distinct variables affecting the production. For this reason, having alerts and notifications in monitoring and control platforms is crucial. However, in some circumstances, farmers cannot attend to the messages delivered through traditional mechanisms, making it impossible for them to be informed at the right moment. In this paper, we present the design evaluation of an intelligent context-aware smart notifications system for precision agriculture. We consider using distinct notification mechanisms to improve the delivery of notifications to the farmers. We carry out an anticipated user experience evaluation to assess the system’s design and validate the use of the notification mechanisms in distinct scenarios. A total of 48 potential users from Spain and Costa Rica participated in the evaluation. The results show that our proposed system can be very helpful in supporting farmers to be aware of the state of crops. In addition, non-traditional notification mechanisms can potentially keep the farmers informed without affecting their daily activities. Costa Rican potential users value the system’s novelty more than Spanish users.

Tipo de publicación: Conference Paper

Publicado en: Proceedings of the International Conference on Ubiquitous Computing Ambient Intelligence (UCAmI 2022)

Social Network Analysis for Automatic Ranking of Political Stakeholders: a Case Study

Nov
2022

Descripción:

This article exposes the way in which the creation of a new method for calculating the popularity of stake holders in social networks can support political data analysis experts. The definition of a new formula for estimating popularity allowed us to have a new method that, together with other previously existing ones, allows us to build a multidimensional interpretation of reality. The construction of a method that would seem like a computational scientific curiosity has significant impacts for experts who carry out political analysis. The new ranking algorithm called BOPRank made it possible to identify political actors in a different way than known algorithms. While a wellknown algorithm showed popularity as a result of the work of campaign teams on social networks, the new algorithm reflected popularity obtained as a result of the reaction of the public on social networks.

Tipo de publicación: Conference Paper

Publicado en: 2022 XVLIII Latin American Computer Conference (CLEI)

Making Technical Debt Visible using Hybrid Sankey Diagrams: An Industrial Case Study

Nov
2022

Descripción:

Context: Technical debt (TD) is a challenge for companies who develop software on which their critical operations depend. To properly manage TD, it is necessary to make it visible to the different stakeholders involved to support informed decisions. Objective: To validate a TD visualization approach based on hybrid Sankey diagrams that makes the TD visible by showing (a) technical and business aspects, and (b) the flow of value and TD impacts. This approach regards visualizations as boundary objects. Method: We performed a multi-case study in a large multi-industry state-owned company. The objective was to validate the effectiveness of such visualizations and to explore their possible uses in TD management. We first used a retrospective case study on a TD decision-making scenario and, later, visualization usage scenarios using focus groups to evaluate its usefulness. Results: The results suggest that the proposed approach: (a) provides a structured process for systematic TD visualization to help the decision-making process; (b) enables the communication at knowledge boundaries between stakeholders to make informed decisions; (c) uses flow representations that are important for assessing the impact in multiple functional areas; and (d) enables documentation and reuse. Conclusion: The study results suggest that TD decision-making events can benefit from using our TD visualizations based on hybrid Sankey diagrams as boundary objects to portray the impact of TD in business, services, and technical aspects.

Tipo de publicación: Journal Article

Publicado en: International Journal of Software Engineering and Knowledge Engineering

Designing a Diagnosis Instrument to Determine e-Commerce Readiness for Micro and Small Enterprises in Rural Areas

May
2022

Descripción:

Electronic commerce, as a new way of commercialization, is not only a business decision, since not all companies, nor all consumers in a region, are technologically prepared to adopt electronic commerce. To implement this type of trade, companies should carry out a diagnostic study, both to know if the technological resources are available internally, and to determine if the potential clients are also ready and willing to use the channel.

From this perspective, this work seeks to design an instrument that allows diagnosing the e-Commerce readiness of micro and small businesses, and their potential consumers in rural areas. An iterative process to create the diagnosis instruments was used.  It involved iterations of design and evaluation stages. Academic experts with extensive experience in instrument design carried out the first evaluation; the second iteration was evaluated in a pilot field study where 6 companies and 10 consumers from similar regions participated. Finally, in a case study in the canton of Río Cuarto de Alajuela, 29 companies and 261 consumers from the region participated in this study. The diagnosis highlights that most of these companies express that they are not technologically prepared to implement e-commerce, while most of the participating consumers indicated that they do feel technologically prepared to use these platforms.

Tipo de publicación: Journal Article

Publicado en: CLEI Electronic Journal

Taxonomy of Malicious URL Detection Techniques

Feb
2024

Descripción:

Malicious URLs are often used by phishing campaigns, botnets and other attacks. Indeed, DNS traffic is necessary for the Internet to function correctly, which means that this data flow cannot be blocked. For these reasons, detecting malicious URLs is both important, challenging and still an open research problem. There are two types of techniques used to detect malicious URLs: rules-based and machine learning-based. The traditional, rules-based techniques rely on blacklists and heuristics. These techniques struggle to keep up with a rapidly changing array of malicious URLs. Therefore, machine learning-based techniques have emerged. Both detection techniques rely on URL characteristics such as length, number of vowels and others to classify them as legitimate or malicious. The main contribution of this paper is to propose a taxonomy of detection techniques and to point out which URL characteristics are used by each method. While surveys on the topic exist, a precise mapping between the detection methods and the characteristics is not available. We also compare these techniques, highlighting that machine learning-based techniques are more complex to implement but better at keeping up with rapidly incoming new malicious URLs. In contrast, rules-based techniques are simpler and easier to implement, but they struggle to update fast enough to identify new malicious URLs.

Tipo de publicación: Book Chapter

Publicado en: Information Technology and Systems

Usability assessment of a greenhouse context-aware alert system for small-scale farmers

Jun
2024

Descripción:

In the dynamic landscape of modern agriculture, integrating technology holds immense potential to enhance efficiency and productivity for small-scale farmers. This study presents a user-centric evaluation of an intelligent context-aware alert system, tailored for small-scale greenhouse farming. We employed standardized questionnaires, including the NASA Task Load Index and the User Experience Questionnaire, to assess the system's perceived utility, mental workload, and overall user experience. Our findings reveal the high perceived utility of the system among farmers. Farmers participating in the assessment indicated a strong intention to utilize the system for crop monitoring. Moreover, the system demonstrated a moderate mental workload, suggesting ease of use and potential acceptance by users. Our evaluation highlighted an excellent user experience, with scores ranging from very good to extremely good across all dimensions. Furthermore, user preferences for alert mechanisms underscored the importance of adaptable notifications, with voice and text alerts favored for comprehensive information dissemination. Light and voice alerts were preferred during manual tasks. This study highlights the significance of user-centered design in agricultural technology, offering insights to enhance the usability and the adoption of alert systems in small-scale farming environments. The positive reception of the system's utility and the moderate mental workload suggest that such technology can be readily adopted by farmers, thereby improving monitoring and management practices in greenhouse farming. The preference for adaptable alert mechanisms further emphasizes the need for flexible and context-sensitive solutions in agricultural technology.

Tipo de publicación: Journal Article

Publicado en: Frontiers in Computer Science

Scalable Technological Architecture Empowers Small-Scale Smart Farming Solutions

Jul
2024

Descripción:

Smart farming technologies have the potential to revolutionize agriculture by enhancing resource efficiency, productivity, and sustainability. However, small-scale farmers in Latin America face challenges in adopting these technologies due to limited resources and technological constraints. In response, we have developed an affordable smart farming solution that empowers small-scale farmers with a comprehensive system that strategically integrates sensors into monitoring stations allowing control over specific actuators. This solution enables precise and resource-efficient production, by using monitoring stations deployed in crop fields, accessible visualization dashboards for farmers to review collected crop data, and a context-sensitive alert module.

Tipo de publicación: Journal Article

Publicado en: Communications of the ACM

A cost-efficient smart solution for small-scale farmers: a multidisciplinary approach.

Mar
2020

Descripción:

In the near years, the world population will have to deal with a big problem: to pro- duce the food required to satisfy its increasing demand. It is imperative to support farmers to find a solution. In this regard, the information and communication technologies (ICT) sector can help by creating technology which supports agriculture processes to increase the crop production and to reduce the resources consumption. In this paper, we present a cost-efficient solution for small scale farmers. Our platform helps the farmers in the decision-making process by using data recollected from crops and by controlling fertigation. Using it, farmers can be more efficient and waste fewer re- sources.

Tipo de publicación: Conference Proceedings

Research on Optimization Techniques Applied to Precision Agricultural Processes Supported by Technology in Latin America: Opportunities and a Route to Follow

Oct
2020

Descripción:

The agricultural sector is facing significant challenges. Producing more food while consuming fewer resources like water, fertilizers, and arable land is probably the most important. Today more than ever, farmers need specialized technological tools to achieve this goal. It is possible to improve agricultural processes by practicing technology-supported precision agriculture. However, more technology development to optimize crop yield is needed worldwide. In this research, we conducted a systematic literature review in which we studied different articles that propose optimization for agricultural processes. We identified some proposals made from multiple researchers at distinct latitudes, focused on optimizing the irrigation and management of pests and diseases. Nevertheless, there are only a few studies that focus on optimizing the crop yield. They do that by controlling the different factors that can affect it. We also found out that only a few studies have been conducted in the Latin American region. Thus, these findings show areas in which there is still a lot of opportunities to contribute to the agro sector in Latin American countries.

Tipo de publicación: Conference Paper

Publicado en: 2020 XLVI Latin American Computing Conference (CLEI)

Use of Hough Transform and Homography for the Creation of Image Corpora for Smart Agriculture

Dic
2023

Descripción:

In the context of smart agriculture, developing deep learning models demands large and high- quality datasets for training. However, the current lack of such datasets for specific crops poses a significant challenge to the progress of this field. This research proposes an automated method to facilitate the creation of training datasets through automated image capture and pre-processing. The method’s efficacy is demonstrated through two study cases conducted in a Cannabis Sativa cultivation setting. By leveraging automated processes, the proposed approach enables to create large-volume and high-quality datasets, significantly reducing human effort. The results indicate that the proposed method not only simplifies dataset creation but also allows researchers to concentrate on other critical tasks, such as refining image labeling and advancing artificial intelligence model creation. This work contributes towards efficient and accurate deep learning applications in smart agriculture.

Tipo de publicación: Journal Article

Publicado en: Int. J. Cybern. Inform.

Application of Artificial Intelligence for Programming Learning in Higher Education Students

Sep
2023

Descripción:

This systematic review depicts potential uses, tools, and strategies to enhance programming learning in university students pursuing technology-related fields like systems engineering or computer science. The review explores the technical aspects, including types of tools, programs, and Artificial Intelligence (AI) specifications proposed for technology-based university programs. A total of 113 records from 2018 to 2023 were analyzed from IEEE Xplore database, with 41 records meeting the inclusion criteria based on language, document completeness, and the use of AI in higher education, A study published in Dialnet on the experience of a Costa Rican distance learning university is also included. The study highlights that AI support in higher education is utilized in academic performance prediction systems, evaluation and personalization of the learning process, and data analytics. The conclusions emphasize the importance of ethically and responsibly integrating technological tools for AI in education, as well as reevaluating the role of educators and pedagogical mediation strategies.

Tipo de publicación: Conference Paper

Publicado en: JoCICI 2023: IV Jornadas Costarricenses de Investigación en Computación e Informática (JoCICI)

Derechos reservados © 2025 Universidad de Costa RIca