Maestría en Ciencias de la Información y las Comunicaciones
URI permanente para esta colecciónhttp://hdl.handle.net/11349/18
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Ítem Desarrollo de un prototipo de modelo catastral 3d a partir de herramientas de geoprocesamiento para la visualización de los aspectos legales y físicos en una propiedad horizontal en el municipio de Soacha, Cundinamarca(UNIVERSIDAD DISTRITAL FRANCISCO JOSE DE CALDAS) Cumbe Loaiza, Laura Camila; Castillo Mendez , Luis EduardoThis work aims to record the development of the construction of a 3D cadastre model prototype supported by geoprocessing tools that complement geographic information systems (GIS) focused on horizontal property in the municipality of Soacha, in order to create different scenes or views of a co-property and thus have the opportunity to contribute to the development and various applications of cadastre information, representing the real estate right, demarcating the legal and physical aspects of the property.Ítem Diseño de un prototipo en el motor de base de datos para la validación de reglas topológicas y cumplimiento del modelo de aplicación de levantamiento catastral LADM-COL v. 2.0.(Universidad Distrital Francisco José de Caldas) Lopez Calle , Maria Isabel; Ortíz Davila , Álvaro Enrique; Ortíz Davila, Álvaro Enrique [0000-0001-8830-1657]This research arises with the objective of designing a prototype that validates topological rules and ensures compliance with the cadastral survey application model LADM-COL V2.0 in the context of multipurpose cadastre and current regulations. Validation functions are integrated into the database engine, allowing the reporting of the state of cadastral information, generating diagnostics of the data, and facilitating controlled data management. The project considers the perspective of cadastral managers, who receive information from IGAC in R1 and R2 formats, as well as the cadastral geographic database. It is developed using PostgreSQL, an open-source tool, and as a result, topological validation functionality for cadastral databases will be obtained. Additionally, it will include a module for migrating IGAC cadastral information to the survey application model, with results illustrated through a practical case study.Ítem Modelo para la evaluación de la calidad intrínseca y dinámica de los datos abiertos sector salud en Bogotá D.C. basado en machine learning(Universidad Distrital Francisco José de Caldas) Varon Capera , Álvaro; Gaona García , Paulo Alonso; Gaona García, Paulo Alonso [0000-0002-8758-1412]; Varpn Capera, Álvaro [0009-0005-4134-7304The purpose of this master's thesis document, under the in-depth modality, is to conduct a review of the quality status of these historical data, specifically through open data repositories in the health sector within the context of the city of Bogotá, in order to assess their quality. To this end, the quality of open data is evaluated based on criteria related to consistency, accuracy, redundancy, update frequency, among others. Evaluating the quality of open data displayed in repositories would facilitate the reuse of the dataset to carry out studies focused on the prevention of epidemiological events, impacts on the provision of health services, and declines in overall health for a population.Ítem Metodología para la elección de modelos de LLMS en aplicaciones de predicción metereológicas a través de algoritmos de ML sobre entornos de computación en la Nube y capturas de datos a través de IoT(Universidad Distrital Francisco José de Caldas) Bello González, Iván Darío; Gaona García, Elvis Eduardo; Gaona García,Elvis Eduardo [0000-0001-5431-8776]Meteorological prediction is one of the critical factors addressed from various approaches and is fundamental for a wide range of sectors, such as agriculture, renewable energy, disaster management, and urban planning. Recent advances in Large Language Models (LLMs), Internet of Things (IoT), and cloud computing have opened new opportunities to improve the accuracy and efficiency of predictions in these sectors. However, there are several challenges related to the constant variability of environmental conditions and the reliability of data obtained from sensors. This research proposes the development of a comprehensive methodology to evaluate the impact of integrating LLMs with IoT infrastructures and cloud computing, with the aim of determining precision and improving the accuracy of meteorological predictions. The methodology comprises five iterative phases: Identification, Development, Testing and Monitoring, Evaluation, and Analysis. This approach allows for the continuous evaluation of LLMs and the adaptation of the system based on the obtained results, addressing the changing needs of the IoT environment. The study focuses on designing specific metrics to evaluate the performance of LLMs compared to traditional models, deployed within a scalable cloud platform that facilitates the integration of data generated by IoT devices. The methodology incorporates the use of a ReAct (Reasoning and Acting) agent, which improves the system's precision and accuracy by detecting anomalies in the data and adjusting responses accordingly. This agent also demonstrated the ability to identify when the model's performance was insufficient, recommending the use of more reliable data sources as an alternative to ensure the quality of predictions. In the case study, it was evident that some models exhibited low performance, with metrics such as R² close to zero, indicating an inability to capture underlying patterns in the data. However, the inclusion of the ReAct agent mitigated these problems by making critical decisions to maintain the quality of predictions. The results demonstrated the system's ability to adjust and improve as new data is collected, making the process adaptive and more robust. It is expected that the results of this research will significantly contribute to the advancement of meteorological prediction, with direct benefits for critical sectors and various stakeholders. The developed methodology lays the foundation for future research and applications in this field, facilitating more accurate and reliable meteorological predictions. The combination of LLMs with IoT and reactive agents not only enhances predictive capability but also the system's adaptability in changing environments, which is essential for modern meteorological applications.Ítem Diseño de un metamodelo de software para el desarrollo de aplicaciones inmersivas(Universidad Distrital Francisco José de Caldas) Sánchez Cruz, Andrés Felipe; Gelvez García, Nancy Yaneth; Gelvez García,Nancy Yaneth [0000-0003-3334-6959]Users are the main purpose of software development as the process turns around their needs. The goal is always to satisfy them in the best possible way, but often aspects that add value to the software and improve the user experience are over-looked, commonly in immersive scenarios. This is evidenced by the fact that in many cases virtual environments are not suitable, which has underlying issues of usability and interactivity. This document presents a study focus on the design on metamodel based on usability and interactivity features in immersive applications such as virtual, augmented, or mixed reality, as this type of visualization is partic-ularly sensitive to factors that can harm the user experience due to its nature. The sections of the document include the methodology proposal, research on existing pro-jects that use the mentioned features, the design of a metamodel, and the devel-opment of a prototype based on it. Finally, the prototype will be evaluated through a specifically designed test to validate the work done.Ítem Metamodelo software para simulación remota interactiva en ambiente Web(Universidad Distrital Francisco José de Caldas) Piñeros Ramírez, Jeisson Rodrigo; Barón Velandia, Julio; Vanegas Ayala, Sebastián Camilo; Piñeros Ramírez, Jeisson Rodrigo [0009-0006-6809-3292]; Barón Velandia, Julio [0000-0002-9491-5564]; Vanegas Ayala, Sebastián Camilo [0000-0002-8610-9765]Simulation plays a crucial role in supporting the understanding of real-world phenomena; interactive simulation with progressive event visualization is even more valuable for this purpose. However, certain types of systems require significant computational resources, in terms of both memory and processing. A possible solution to this problem is to conduct simulations in a Web environment, allowing the client to perform progressive visualization of the results obtained from the server-side logic processing. Current simulation solutions present challenges for client devices, including low user interactivity on the client device and high consumption of both bandwidth and computational resources for processing simulation logic. This often makes such solutions limit interactivity or become costly in terms of processing, memory, and network usage. How can computational and network requirements on the client be reduced while maintaining high levels of interactivity and progressive visualization in simulation software? The objective of this proposal is to design a software metamodel for interactive remote simulation with progressive visualization in a Web environment by applying a methodological technique based on iterative and incremental models, which allows for obtaining results in both conceptual and development terms.Ítem Pronóstico de la esperanza de vida para la población de Colombia utilizando machine learning(Universidad Distrital Francisco José de Caldas) Peralta Hernández, Angie Estefanía; Salcedo Parra , Octavio José; Salcedo Parra, Octavio José [0000-0002-0767-8522]Introduction: This study evaluated life expectancy in Colombia, analyzing sociodemographic, macroeconomic, and health determinants using machine learning algorithms to identify significant patterns in the data. Objective: To forecast life expectancy in Colombia using machine learning models based on socioeconomic and demographic factors. Materials and Methods: A dynamic life expectancy model was developed using machine learning algorithms, integrating variables related to demography, economy, and health, thus overcoming the limitations of traditional mortality tables. Results: The Gradient Boosting Machines model demonstrated the highest accuracy, providing reliable projections at both the national and gender levels. The results offer a comprehensive overview of the evolution of life expectancy in Colombia and its main determinants. Conclusion: Life expectancy in Colombia is influenced by demographic, economic, educational, and health factors. It is essential to implement public policies aimed at reducing structural inequalities and ensuring essential services, particularly in rural and vulnerable communities.Ítem Predicción de esperanza de vida considerando el covid-19, bajo algoritmos de machine learning basados en datos epidemiológicos y patológicos.Rodríguez López, Jorge Leonardo; Salcedo Parra , Octavio José; Salcedo Parra, Octavio José [0000-0002-0767-8522]This study analyzed the prediction of people's life expectancy from their medical records, considering determinants such as COVID-19 using machine learning algorithms. A methodology based on machine learning models was developed, using pathological and epidemiological information, with the aim of identifying significant patterns in the data. In addition, publicly available data collected during the COVID-19 outbreak were used to estimate life expectancy, thus providing a predictive tool for the analysis of the impact of the pandemic on longevity.Ítem Análisis geográfico para la clarificación del territorio. caso: Resguardo Indígena Llanos del Yari Yaguara 2.(Universidad Distrital Francisco José de Caldas) Guerrero Varona , Luis Miguel; Coronado Sánchez, Paulo CésarThe National Land Agency plays a fundamental role in the legalization of territory for ethnic communities in the country by generating geographic information about indigenous reserves. However, this information lacks thorough verification and updates within the Geographic Information Systems (GIS) model, which has a significant impact on the nation’s rural development. This is especially relevant given that land tenure by ethnic communities represents a substantial portion of rural property and is crucial for the execution of infrastructure and environmental projects. In this context, information about certain indigenous reserves has been manipulated by various entities and professionals, leading to spatial representations that do not align with the actual territory. This study focuses on the indigenous reserve of the Pijao, Tucano, and Piratapuyo communities in the Llanos del Yarí Yaguara II, established by Resolution No. 10 of February 22, 1995. Through spatial analysis, discrepancies were found between the polygon published by the National Land Agency (ANT) and the field reality, particularly concerning natural boundaries. These differences have resulted in errors, such as the overlap with the Chibiriquete National Natural Park, which was expanded through Resolution 1256 of July 10, 2018, by the Ministry of Environment and Sustainable Development (MADS), with the territory of the indigenous reserve. This project proposes a method for evaluating and correcting the quality of geographic information related to the country’s protected areas, demonstrating its practical application through a case study in the indigenous reserve of the Pijao, Tucano, and Piratapuyo communities in the Llanos del Yarí Yaguara II. The aim is to provide tools that reduce errors in the creation of resolutions and official acts related to the country’s protected areas.Ítem Diseño de metodología para validar la integridad de la información de las transacciones de los contratos inteligentes empleando cifrado homomórfico(Universidad Distrital Francisco José de Caldas) Romero Pinto, Jawy Andrés; Gaona García, Elvis; Gaona García, Elvis [0000-0001-5431-8776]; García Barreto, Germán Alberto (Catalogador)Blockchains, such as Ethereum, offer transparency and security through the immutability of their data. However, this transparency can be a problem for applications that require privacy. Smart contracts on these platforms do not have a native mechanism to protect sensitive information. This work presents a fully decentralized confidentiality mechanism compatible with Ethereum and other smart contract platforms. The approach is account-based, similar to Ethereum, for efficiency and ease of use. A smart contract is implemented with an additional layer of encryption to protect the privacy of the information.Ítem Metodología para el análisis de vulnerabilidades aplicado a sistemas de navegación y telemetría presentes en RPA’s(Universidad Distrital Francisco José de Caldas) Rengifo Güiza , Wilmar Neiser; Gaona García , Elvis Eduardo; Gaona García , Elvis Eduardo [0000-0001-5431-8776]This study addresses the issue of vulnerabilities in the navigation and telemetry systems of remotely piloted aircraft (RPA) in Colombia. A review of the RPA database maintained by the UAEAC reveals that 65% of the RPAs registered in Colombia have been affected by a specific vulnerability in their GPS systems [1], in addition to other vulnerabilities in telemetry systems. To address this issue, the objective of this study is to propose an approach for a vulnerability assessment methodology for RPAs, focusing on navigation and telemetry systems. The methodology proposed in this study is based on the concept of aviation safety as a capability rather than a property. This approach, proposed by Janusz Zalewski [2], allows for a more comprehensive measurement and structuring of safety in aircraft systems. The development of the vulnerability assessment methodology is structured to address all airworthiness characteristics and follow multiple stages. The result of the methodology proposed in this study is a hybrid risk assessment approach designed to analyze vulnerabilities in the airworthiness and telemetry systems of RPAs. By raising awareness of the lack of protocols and systems for analyzing RPA vulnerabilities, this study aims to contribute to the development of improved procedures in industrial, scientific, and commercial fields.Ítem Predicción de la incidencia epidemiológica del dengue en Colombia utilizando una Red Neuronal Recurrente a partir de información captada por sensores remotosSilva Avila, Daniel Fernando; Medina Daza, Ruben Javier; Medina Daza, Ruben Javier [0000-0002-9851-9761]Dengue is an endemic viral disease (confined to tropical and subtropical areas) transmitted by the Aedes aegypti mosquito and is a global health concern due to its rapid spread and the increasing severity of outbreaks. This study exploits the power of machine learning algorithms to build a robust regression model from a recurrent neural network, incorporating historical data on dengue in Colombia and environmental variables derived from remotely sensed measurements. This is intended to improve the accuracy of forecasts of dengue cases, as well as to complement the state of the art for this type of epidemiological models. A total of 4 models were created using data from different historically affected departments of Colombia (Antioquia, Norte de Santander, Santander and Valle del Cauca). The models presented an RMSE of 12, 46, 20 and 15 units and an r2 of 0.89, 0.97, 0.97 and 0.88 respectively. Comparing the RMSE with the most representative central range of the data (between the 25th and 75th percentiles), it was found that, for the best performing model, the predictions are between 11% and 30% away from the real values, which is relatively small in the context of the data. This is a promising result as accurate predictions are crucial for public health planning and response allowing targeted interventions in high-risk areas, which can reduce the spread of disease and prevent outbreaks, saving lives and reducing the burden on health systems.Ítem Modelo de optimización para la calidad de servicio (quality of service, qos) en redes wi-fi (802.11ax) aplicando programación multiobjetivoNarváez Jaramillo, Luis AlfredoWifi wireless networks (802.11 ax) are increasingly used by users due to the growing evolution of applications, generating problems in the network such as shared bandwidth, delays, packet losses, among others. For this reason there is a need to guarantee or improve QoS through management systems. In this work, a characterization of the parameters that affect the QoS in a Wi-Fi network (802.11 ax) and the use of multi-objective linear programming as a network improvement management method is carried out, for this an IoT project was developed with the Qubsax company, which is focused on IoT, security systems, closed television among others. Here the technology with the 802.11ac protocol is migrated to 802.11ax, the differences are shown and an optimization model is carried out to improve network coverage, minimizing costs and improving the use of access points, optimizing the network by 33,33 %.Ítem Modelo de evaluación crediticio basado en principios de un ecosistema digital bancario mediante estrategias de business intelligence y mecanismos de reputación en el sector de industria textil de las pymes colombianas(Universidad Distrital Francisco José de Caldas) Rodríguez Rodríguez, William Steven; Gaona García, Paulo Alonso; Gaona García, Paulo Alonso [0000-0002-8758-1412]The high degree of competitiveness of the current market and its constant changes requires quick, accurate, and correct decisions for success within global and regional trade. Added to this is the current global situation caused by the COVID-19 virus pandemic, which has had an impact on all markets and financial sectors. For South America, a 5.2% drop in the economy is expected. Some countries in this subregion were greatly affected by the drop in activity in China, which is an important market for its exports of goods (ECLAC, 2020). SMEs are a group of companies within a specific classification. In the Colombian economy, the main characteristic that defines the classification depends on the number of employees available to the organization. The classification is defined as micro, small, and medium-sized companies. These companies represent the fundamental sector of the economy; 99.6% of companies in Colombia are micro, small, and medium-sized companies. World governments, specifically the Colombian government, have opened aid programs for the SME sector, supporting decisions in banking financial entities. The fiscal packages announced in the region are the first response to the socioeconomic impact of the pandemic. For their part, the central banks of the region have announced “unconventional measures” to expand liquidity, including the purchase of public and private assets. (ECLAC, 2020). Current conditions pose a scenario where banking organizations will have to adapt and employ new alternatives to meet the high flow of potential clients, taking into account the implementation and understanding of new technologies and digital ecosystems. Considering the previous scenario, there is an interest in the financial and academic fields to propose new methodologies for defining access to credit services. Evaluating traditional risk analysis models reveals an opportunity to implement a complementary model that allows determining, based on public opinion and ratings collected and published on digital platforms, whether an organization has a favorable profile to consider the disbursement of financial aid. This analysis is carried out by collecting and classifying data from social digital platforms, such as Facebook and Twitter, implementing methodologies based on sentiment analysis where a result is obtained in the form of classification between a positive or negative profile depending on the interpretation of the base text, with this result a model based on Business Intelligence is defined focused on decision-making for the identification of services and products within a digital banking ecosystem. Finally, this model is validated with respect to traditional risk analysis models to obtain the percentage difference between confirmed and denied products for SMEs.Ítem Modelo semántico de la contratación en las empresas del estado en el marco de la gestión de contenido empresarialErira Trujillo, William Alberto; Coronado Sánchez, Paulo CésarThe high volume of structured and unstructured information managed by state entities in relation to contractual and procurement processes makes it necessary to have more agile and effective consultation methods.This document presents the project for developing a semantic model that has the capacity to express information through its meaning, relationships and rules in a formal manner so that an application can interpret it, make inferences and obtain precise information that results in benefits in terms of time, quality and guarantee of transparency for entities, citizens and users who work with contractual information in public corporations.Ítem Apoyo técnico y administrativo en el marco de convenio y contrato de cooperación interadministrativo para realizar un ejercicio de ciencia de datos con un problema de la Unidad Nacional de Protección (UNP)(Universidad Distrital Francisco José de Caldas) Colmenares Gámez, Sergio Enrique; Escobar Díaz, AndrésThis report outlines the development of a proposal carried out in collaboration with the XUE research group to conduct a process of analysis and knowledge extraction applied to a specific problem of the National Protection Unit (UNP). The initiative follows a data science methodology with a special focus on utilizing the MATLAB® software tool. The project involves the design, proposal, and execution of a data analytics methodology that comprehensively addresses each stage of the process: understanding the domain model associated with the problem, data collection and integration, preparation, analysis (mining), and evaluation of the most suitable methods to extract relevant information. This approach enables the synthesis of MATLAB®’s resources and capabilities in the field of data science. Additionally, the work aims to promote digital transformation within the UNP by providing guidance on the teaching and application of data science concepts. The developed methodology and obtained results serve as tools to facilitate technological adoption and data-driven decision-making.Ítem Identificación de patrones de deserción y riesgo académico en carreras de la Facultad de Ingeniería de la Universidad Distrital a través de técnicas Machine Learning(Universidad Distrital Francisco José de Caldas) Salamanca Vásquez, Esteban; Contreras Bravo, Leonardo Emiro; Contreras Bravo, Leonardo Emiro [0000-0003-4625-8835]This paper focuses on the development of a predictive model to identify the risk of students at the Universidad Distrital of being placed on academic probation or dropping out of their studies. Dropout and academic risk represent crucial problems for the institution, affecting both the academic trajectory of students and the ability of the university to fulfill its educational mission. Dropout refers to when a student abandons his or her studies before completing them, while academic probation is assigned to students with poor performance, such as failing multiple subjects or repeating a course for the third time. This work's main objective is to identify patterns and factors associated with dropout and academic risk through an exploratory data analysis, based on significant variables extracted from the literature. These include socioeconomic level, academic performance, distance of residence to the university, ICFES exam results, type of school, and the grade history of each student. The research uses exploratory data analysis techniques in combination with machine learning methods, moving from the preparation and selection of variables to the application of transformations, in order to develop an accurate classification model for the prediction of dropouts. Through this methodology, it is expected to identify relevant patterns and relationships that reflect the impact of the selected variables on academic results. The proposed predictive model focuses on the use of machine learning algorithms that allow predicting the academic risk of each student individually. This will provide the university with a tool that enables the implementation of personalized interventions and supports, with the aim of improving retention rates and academic success. In conclusion, this degree work represents a significant advance towards the creation of effective student retention strategies, with a data-driven approach that allows a better understanding of the factors that affect dropout and academic risk, which contributes to the improvement of academic performance at the Universidad Distrital.Ítem Mecanismo de clasificación de paisajes de optimización basado en muestreo multiescala y aprendizaje automático(Universidad Distrital Francisco José de Caldas) Rodríguez Hernández, Angie Patricia; Melgarejo Rey, Miguel AlbertoThis work presents an approach to classify the modality in optimization landscapes, combining multiscale sampling with machine learning techniques. A set of optimization functions was selected and labeled according to the modality definition proposed by Kanemitsu et al. To minimize sample bias, a multiscale sampling algorithm was developed, based on the behavior of a random walk guided by a power law, complemented with fine-scale exploitation mechanisms, to both explore and exploit the optimization landscapes. The obtained samples are represented as an image, which is used as input to a convolutional neural network responsible for classifying the landscape modality. Experimental results show that the proposed approach achieves competitive performance in classifying previously unseen landscapes. Furthermore, the results suggest that the multiscale strategy provides more reliable information compared to random sampling, which is the standard technique in optimization landscape analysis. It is important to highlight that this work leads to the assertion that the problem of understanding optimization problems could be viewed as a pattern recognition problem.Ítem Análisis espacial de la fragmentación urbana basado en la destinación económica predominante por manzana en Bogotá D.C.(Universidad Distrital Francisco José de Caldas) Moreno Gama, Juan Manuel; Castillo Méndez, Luis Eduardo; Castillo Méndez, Luis Eduardo [0000-0002-2211-7336]Urban fragmentation is defined as the process of discontinuity of the functional structure of the territory, that is, the rupture of the city as a pre-existing unit. There are previous studies of a qualitative nature that address this urban process at a theoretical and sociological level; however, an index of fragmentation has not yet been characterized and quantified from a spatial analysis in a Colombian city, specifically its capital. This research seeks to fill this knowledge gap through the identification, characterization, quantification and specialization of this phenomenon that will support subsequent guidelines, actions and public policies for the control and monitoring of the problems resulting from fragmentation.Ítem Estimación de la severidad de incendios, usando imágenes satelitales Landsat para el Parque Nacional Natural El Tuparro entre los años 2013 a 2023.Borda Casas, Oscar Fernando; Medina Daza, Rubén Javier; Medina Daza, Rubén Javier [0000-0002-9851-9761]This study aimed to assess the severity of forest fires and analyze their impact on vegetation and surface temperature in El Tuparro National Natural Park, Colombia, during the period 2013-2023. Landsat satellite images were used to generate five spectral indices (NDVI, NBR, NBR2, SAVI, and NDWI), identifying the characteristics of the land cover in the study area. A total of 17 mosaics were generated. Using this information and the best of three supervised machine learning algorithms (Random Forest, SVM, and KNN), each mosaic was classified with the most suitable algorithm to quantify the land cover types. Severity indices (dNBR) were also calculated, and time series were analyzed in GEE for eight affected polygons, evaluating vegetation recovery. Anomalies in each time series were identified using the Isolation Forest algorithm. Finally, surface temperature data obtained from GEE (MODIS-Terra) were analyzed to identify trends and anomalies. The results show that high accuracy was achieved in estimating areas affected by fires. Additionally, a significant impact on biomass and vegetation health was observed in each polygon. However, covers such as grasslands exhibited rapid and effective recovery after the fires. Regarding surface temperature, no significant upward trend was detected during the study period.