Capítulos (Lenguajes y Sistemas Informáticos)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/11393

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Matrix Representation of Virus Machines
(Springer Nature, 2024) Ramírez de Arellano Marrero, Antonio; Cabarle, Francis George C.; Orellana Martín, David; Pérez Jiménez, Mario de Jesús; Adorna, Henry N.; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial
Virus machines are unconventional and bio-inspired models of computation based on the transmission of viruses among hosts. Virus machines are known to be computationally complete (they are algorithms), able to solve computationally hard problems. In this work we present a novel matrix representation for virus machines. Discrete structures such as vectors and matrices are useful in many technical domains, both in theory and practice. The hosts, number of viruses, and the instructions to control virus transmission are represented as vectors and matrices. In this way the computations of virus machines can be described by linear algebra operations. We also use our matrix representation to show invariants, helpful in formal verifications, of such machines.
WebSnapse Reloaded: The Next-Generation Spiking Neural P System Visual Simulator using Client-Server Architecture
(Atlantis Press, 2024) Gulapa, Mutya; Luzada, Jarred Sueño; Cabarle, Francis George C.; Adorna, Henry N.; Buño, Kelvin C.; Ko, Daryll; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Spiking Neural P Systems (SN P Systems) replicate the brain’s information spiking mechanism through synapses. These systems are known for trading memory for time, making them useful in different areas both inside and outside computer science. While web-based simulators likeWebSnapse offer the potential for centralized GUIs to simulate SN P system variants, their architecture, codebase, and technologies limit their capabilities. This paper presents WebSnapse Reloaded, a recreated version designed for centralization, optimization, and improved user and developer experiences. With a client-server architecture, it enhances storage usage, scalability, and future development possibilities. The modular codebase simplifies extension and maintenance. Optimizations include algorithm refinement through matrix representation and enhanced user experience. WebSnapse Reloaded reduces task steps, improves software implementation, passes correctness benchmarks, and resolves previous issues. Future recommendations include integrating WebGL or alternative graphing libraries, and developing APIs for other SN P variants to streamline simulator extension.
WebSnapse v3: Optimization of the Web-based Simulator of Spiking Neural P System using Matrix Representation, WebAssembly and Other Tools
(Atlantis Press, 2024) Gallos, Louie; Sotto, Jose Lorenzo; Cabarle, Francis George C.; Adorna, Henry N.; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Spiking Neural P systems (SN P system) are a kind of distributed and parallel computational model under membrane computing inspired by how neurons typically communicate with each other through the sending of spikes between synapses. To further study SN P systems, various dedicated simulators have been developed. WebSnapse, a web-based simulator of SN P systems, has been used to serve as visual aid for creating, modifying, and simulating SN P systems. This was upgraded on WebSnapse v2.0 by improving existing functionalities and adding support for more variants of SN P system. However, WebSnapse suffered performance and stability issues, especially when simulating larger SN P systems. This research aims to optimize the performance and stability of WebSnapse using a new way of computing the next state of the system while achieving feature parity with WebSnapse v2.0 and adding LaTeX support for rule input and visualization.
Application of the Weighted Nearest Neighbor Method to Power System Forecasting Problems
(Wiley, 2017-06-19) Gómez Expósito, Antonio; Troncoso, Alicia; Riquelme Santos, Jesús Manuel; Gómez-Quiles, Catalina; Martínez Ramos, José Luis; Riquelme Santos, José Cristóbal; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; Universidad de Sevilla. Departamento de Ingeniería Eléctrica
A time-series database consists of sequences of values or events obtained over repeated measurements of time. Normally, the values are measured at equal time intervals. Time-series databases are popular in many applications, such as stock market analysis, economic and sales forecasting, process and quality control, and observation of natural phenomena (temperature, earthquake, pollution) or medical treatments. The main goal of time series analysis is not only to forecast (i.e., to predict the future values), but also to find correlation relationships within time series; find similar or regular patterns; trends, and outliers. These last goals can be considered as time series modeling (i.e., to gain insight into the mechanisms or underlying causes that generate time series).
Toward Explaining Competitive Success in League of Legends: A Machine Learning Analysis
(Springer Nature, 2024) Galán Sales, Francisco Javier; Linares Barrera, María Lourdes; Reina Jiménez, Pablo; Rodríguez López, Ana; Jiménez Navarro, Manuel Jesús; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Machine learning techniques have recently transformed the way we analyze competitive games. However, accurately detecting the impact of different insights on match outcomes remains a challenge. This study focuses on League of Legends, a popular multiplayer online battle arena game known for its strategic depth and teamwork requirements. We aim to understand how various actions and strategies influence match results, using a dataset from professional tournaments. Factors like “building damage”, “total gold”, and “assists” are analyzed as predictors. We employ tree-based and linear models to predict outcomes, supplemented by SHapley Additive exPlanations for explaining both local and global model outcomes. Our article offers a generalizable match analysis approach, compares explainable methods, and delves into key determinants of victory. The results, showcasing a remarkable 98.8% accuracy with the top-performing model, provide strong support for our conclusions, underlining their reliability.
Cloud development and deployment
(Springer, 2023) Parejo Maestre, José Antonio; Sánchez Jerez, Ana Belén; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
This chapter describes the challenges related to the software deployment and configuration activities, which could be addressed through AI techniques. Additionally, we illustrate the application of such techniques with two specific problems: the QoS-aware binding of web services, and the selection of the optimal configuration in highly-configurable systems. The AI techniques applied to solve such problems are GRASP with Path Relinking and Multi-Objective Evolutionary Algorithms, respectively. These techniques will be applied to deployment scenarios based on empirically obtained data from real-world web services and highly-configurable software systems. These examples are implemented in Java and C, respectively, providing the source code, build scripts and data sets for the sake of reproducibility.
Experiencias en la aplicación de un Ciclo de Mejora en el Aula en la asignatura Proyectos en Informática Clínica
(Editorial Universidad de Sevilla, 2022) González Enríquez, José; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
En este capítulo se describe la puesta en práctica de los conocimientos adquiridos en los Cursos Generales de Docencia Universitaria de la Universidad de Sevilla. Concretamente, el ciclo de mejora en el aula (CIMA) desarrollado se ha llevado a cabo en la asignatura Proyectos en Informática Clínica, optativa del cuarto curso del Grado en Ingeniería de la Salud, impartido en la Escuela Técnica Superior de Ingeniería Informática de esta universidad. Además de definir de forma clara el modelo metodológico a seguir, así como el mapa de contenidos, se desarrolló un cuestionario cuyos resultados fueron usados para analizar la escalera de aprendizaje de los alumnos. Los resultados, demuestran que la aplicación de CIMA mejora significativamente los conocimientos adquiridos por los alumnos, pasando de concentrar a la mayoría de los alumnos en los escalones más bajos, a los más altos.
Human–computer interaction analysis for RPA support
(De Gruyter, 2021) Jiménez Ramírez, Andrés; Reijers, Hajo A.; González Enríquez, José; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
In the last decade, industry has wholeheartedly embraced RPA. A large number of RPA projects have been conducted, which all involve the mimicking of human behavior by software. Although vendor-specific frameworks exist to support all aspects of RPA solutions – from the analysis of the system until the enactment and control of the developed robots – most of them base their solution on workflow diagrams (e. g., BluePrism or UIPath). This chapter explores the benefits of a conceptual RPA framework that is based on log information related to the exact human–computer interaction. While the observation of employees’ computers (i. e., clicks and keystrokes) may lead to the desired data, it is by no means trivial to convert such events into a meaningful log. Our approach shows how to create a so-called user interface (UI) log based on image similarity techniques. This UI log can then be used to provide support for all stages of the RPA lifecycle. Specifically, we will describe a use case in which the UI log is used (1) to support the analysis of the underlying process and (2) to generate a test platform which checks whether or not the developed robots behave in accordance with the analyzed process. We will also discuss how other stages of the RPA lifecycle can leverage the existence of such a UI log, which leads to the identification of new research lines.
Enseñanza de los algoritmos de programación exhaustivos desde un modelo docente constructivista
(Editorial Universidad de Sevilla, 2022) Jiménez Ramírez, Andrés; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Dentro del Grado de ingeniería informática – ingeniería de computadores se ha desarrollado un ciclo de mejora de 8 horas donde se enseña la programación con algoritmos exhaustivos dentro de la asignatura Análisis y Diseño de Datos y Algoritmos. Este ciclo de mejora contempla un proceso metodológico donde las actividades de ideación y debate toman especial relevancia. El artículo contiene el mapa de contenidos y los cuestionarios inicial y final que sirven para comprobar si se ha producido aprendizaje en los alumnos. Tanto las sensaciones del profesor como los resultados de las escaleras de aprendizaje fueron positivos, aunque se identificaron punto de mejora para futuros ciclos de mejora.
Ciclo de Mejora en el Aula (CIMA) en la asignatura de Análisis y Diseño de Datos y Algoritmos. Algoritmos de resolución de problemas sobre grafos virtuales
(Editorial Universidad de Sevilla, 2022) Jiménez Ramírez, Andrés; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Dentro del Grado de ingeniería informática – ingeniería de computadores se ha desarrollado un Ciclo de mejora en el Aula (CIMA) de 12 horas de duración donde los alumnos aprenden a resolver problemas usando grafos virtuales. En este CIMA se ha seguido un proceso metodológico que potencia la realización de actividades de ideación por los alumnos para poder resolver estos problemas. El profesor comienza describiendo el contexto y el problema, haciéndolos cercanos a los alumnos para que éstos puedan debatir sobre su solución, a la vez que el profesor aporta ideas que contrastan con las de los alumnos y les ayuda a reflexionar. Este artículo contiene el mapa de contenidos utilizado por el profesor, así como los cuestionarios que permiten conocer el aprendizaje de los alumnos. Aunque las sensaciones del profesor fueron positivas en su desarrollo, la evaluación del aprendizaje de los alumnos no se pudo realizar por la ausencia de alumnos en la última sesión.
Intelligent Document Processing in End-to-End RPA Contexts: A Systematic Literature Review
(Springer Nature, 2023-03) Martínez Rojas, Antonio; López Carnicer, José Manuel; González Enríquez, José; Jiménez Ramírez, Andrés; Sánchez-Oliva, J. M.; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; Ministerio de Ciencia, Innovación y Universidades (MICIU). España
Automating organizational processes typically involves document processing techniques for a large document set. For that purpose, the Intelligent Document Processing (IDP) paradigm has been studied for decades. With the fast emergence of Robotic Process Automation (RPA) in the process automation landscape, the industrial solution of IDP with RPA integration has risen significantly in the last few years. However, there is no up-to-date overview of the available knowledge in this area. Therefore, this chapter studies the current scientific knowledge about IDP and its integration into RPA through a systematic literature review that analyzed 77 primary studies. In addition, an industry review was performed, analyzing and characterizing 37 industrial tools. Although the results confirm the growth in the research interest in IDP in different dimensions, they also identify a lack of proposals that integrate IDP and RPA paradigms in confrontation with the industrial solutions that have increasingly led to its integration.
Revealing the Importance of Setting Parameters in Declarative Discovery Algorithms: An Evolutionary-Based Methodology
(Springer, 2023) Pradras Fernández, Vanessa; Varela Vaca, Ángel Jesús; Gómez López, María Teresa
Through constraints, declarative process models represent the permitted behaviour associated with a business process, by limiting the potential correct traces. These models can be discovered by analysing an event log. However, various declarative business models can be extracted from a single event log, depending on the desirable level of metrics, such as fitness and generalisation. Existing discovery algorithms enable the type of discovered declarative process model to be customised through a set of configuration parameters. Depending on the values of these parameters, the discovered process can be of high or low quality. Unfortunately, the high number of combinatorial parameters and the high time consumption of process discovery make it impractical to conduct an exhaustive analysis of the configuration parameters to determine the most suitable declarative process model discovered. As a solution, we propose a methodology supported by an implemented framework that uses evolutionary algorithms to reduce computational complexity and to select the highest quality declarative business processes. An experiment is included to show the feasibility of our proposal.
Multi-Objective Lagged Feature Selection Based on Dependence Coefficient for Time-Series Forecasting
(Springer, 2024) Linares Barrera, María Lourdes; Jiménez Navarro, Manuel Jesús; Riquelme Santos, José Cristóbal; Martínez Ballesteros, María del Mar; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; MICIU/AEI/10.13039/501100011033
In the fast-evolving field of machine learning, the process of feature selection is essential for reducing model complexity and enhancing interpretability. Within this context, filter methods have gained recognition for their effectiveness in assessing features through statistical metrics. A recently introduced metric, the Conditional Dependence Coefficient, aims to assess the dependence between subsets of features and a target variable, enhancing our understanding of feature relevance. This paper presents a novel feature selection approach that integrates this statistical metric with a multi-objective evolutionary algorithm. This strategy leverages the flexibility of evolutionary algorithms to efficiently explore the feature space and employs an intuitive metric for identifying pertinent features. Unlike many filter-based approaches, our method does not require thresholds or percentiles related to the number of selected features and evaluates the collective merit of feature subsets instead of the significance of individual features. To address the forecasting challenge of identifying the appropriate time lags and features, we performed experiments on eight distinct datasets containing multivariate time-series data. Comparing our method against a baseline with no feature selection, our results show solid performance in efficacy and a notable reduction in model complexity.
Ciberseguridad cognitiva aplicada al phishing
(Universidad de Vigo, 2023-06) Mariano Velo, José; Varela Vaca, Ángel Jesús; Martínez Gasca, Rafael; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; Proyecto COPERNICA; Proyecto METAMORFOSIS; Proyecto AETHER-US
Los Sistemas cognitivos son sistemas informáticos que emplean las teorías, métodos y herramientas de diversas disciplinas de computación para modelar tareas o procesos cognitivos emulando a la cognición humana. Una de las aplicaciones de éstos sistemas es en el campo de la Ciberseguridad es la detección de técnicas de phishing. Se reciben diariamente miles o millones de correos electrónicos, que son procesados por los distintos filtros de seguridad para catalogarlos en diferentes clases, correos legítimos, con malware, o phishing. A pesar de todas las medidas que se toman, siempre hay un porcentaje de correos electrónicos maliciosos que por diversos motivos pasan dichos filtros. Por ello vamos a definir una propuesta para mejorar la detección de dichos ataques, basada en una aproximación cognitiva. La propuesta se centra en definir el proceso, las potenciales técnicas y métricas usando motores para toma de decisiones ampliada basada en modelos de decisión.
Automatizando RGPD 2016/679 mediante Procesos de Negocio: El caso del Artículo 32
(Fundación Tecnalia Research and Innovation, 2022) Varela Vaca, Ángel Jesús; Martínez Gasca, Rafael; Gómez López, María Teresa; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; ETHERUS; COPERNICA; METAMORFOSIS
El correcto cumplimiento del Reglamento General de Protección de Datos (RGPD) es complejo, debido a la subjetividad en la interpretación de la norma dada y su dificultad en la implantación por parte de las organizaciones. El correcto cumplimiento requerirá una adaptación profunda de los procesos y tareas internas de las organizaciones, pero una incorrecta implantación podría derivar en problemas de seguridad y sanciones para estas. Nuestra propuesta, se centra en la utilización de las tecnologías y metodologías relacionadas con los Procesos de Negocio para digitalizar y automatizar los procesos y tareas que puedan dar soporte a los distintos artículos del RGPD, facilitando la implantación y automatización de estos procesos, a la vez que se crean las evidencias necesarias para demostrar el buen cumplimiento de la norma. Dada la amplitud del RGPD, en este artículo entramos a detallar una prueba de concepto relacionada con el proceso derivado del Art. 32 sobre la Seguridad del tratamiento, proponiendo el proceso concreto que le da soporte. Index Terms—Automatización, Digitalización, RGPD, Protección de datos personales, Proceso de Negocio
Assuring the quality and security of medical robotics process automation
(Taylor & Francis Group, 2022) Escalona Cuaresma, María José; Navarro Pando, José; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
In recent years, the application of new technologies to the healthcare environment is a common practice. However, the COVID-19 pandemic has shown us that this application is a critical necessity for society. The application of disruptive techniques such as Artificial Intelligence or Machine Learning in the healthcare environment is something necessary but not sufficient. It is necessary to take another qualitative leap. This paper presents a reflection on the use of emerging technologies, such as blockchain or the robotization of software processes to further improve healthcare processes.
A Practical Experience Applying Security Audit Techniques in An Industrial Healthcare System
(Springer Nature, 2022) Gómez, Julián; Olivero González, Miguel Ángel; García García, Julián Alberto; Escalona Cuaresma, María José; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; Spanish the Ministry of Science, Economy and University; Andalusian RegionalMinistry of Economy and Knowledge
Healthcare institutions are an ever-innovative field, where modernization is advancing by leaps and bounds. This modernization, called “digitization”, brings with it some concerns that need to be taken into account. The aim of this work is to present away to combine the advantages of cybersecurity and artificial intelligence to protect what is of most concern: electronic medical records and the privacy of patient data. Health-related data in healthcare systems are subject to strict regulations, such as the EU’s General Data Protection Regulation (GDPR), non-compliance with which imposes huge penalties and fines. Healthcare cybersecurity plays an important role in protecting this sensitive data, which is highly valuable to criminals. The methodology used to perform a security assessment process has been orchestrated with frameworks that make the audit process as comprehensive and organized as possible. The results of this study include a security audit on an industrial scenario currently in production. An exploitation and vulnerability analysis has been performed, and more that 450 vulnerabilities has been found. This chapter outlines a systematic approach using artificial intelligence to enable the system security team to facilitate the process of conducting a security audit taking into account the sensitivity of their systems.
SLA4OAI-Analyzer: Automated Validation of RESTful API Pricing Plans
(Springer Nature, 2023) Fresno Aranda, Rafael; Fernández Montes, Pablo; Ruiz Cortés, Antonio; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Nowadays, public web APIs are considered as business assets by many organizations. They provide data and functionality which other developers can integrate within their own services. These APIs are commercialized through pricings, which include a series of plans. Each plan contains features and limitations, coupled with a price. Developers who wish to use the API need to choose which plan better suits their needs. The formal description of pricings is not standardized, which hinders the ability to automate their analysis. The SLA4OAI specification aims to provide an extension for OpenAPI that allows pricings to be described. This specification paves the way for an ecosystem of tools that leverage the information of a pricing. In this paper, we present SLA4OAI-Analyzer, a public API that automatically checks an SLA4OAI specification file for conflicts at different levels. We also provide an online Jupyter notebook to validate the API using different examples.
Coordinación de casos prácticos en asignaturas del área de conocimiento "Gestión de la Información" según modelo curricular de informática de la ACM/IEEE 2013
(Educación Editora, 2018) García Nieto, José M.; Navas Delgado, Ismael; Roldán García, María del Mar; Nebro Urbaneja, Antonio Jesús; Gómez López, María Teresa; Bernárdez Jiménez, Beatriz; Aldana Montes, José F.; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Este artículo presenta el estado de desarrollo y resultados preliminares del proyecto de innovación docente de la Universidad de Málaga (PIE15-183): Coordinación de casos prácticos en asignaturas del área de conociMiento "Gestión de Información" según modelo curricular de informática de la ACM/IEEE 2013
Product optimization in stepwise design
(Springer Nature, 2021) Batory, Don; Oh, Jeho; Heradio, Rubén; Benavides Cuevas, David Felipe; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Stepwise design of programs is a divide-and-conquer strategy to control complexity in program modularization and theorems. It has been studied extensively in the last 30 years and has worked well, although it is not yet commonplace. This paper explores a new area of research, finding efficient products in colossal product spaces, that builds upon past work.

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