Examinando por Autor "Osaba, Eneko"

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    Diseño e implementación de una meta-heurística multi-poblacional de optimización combinatoria enfocada a la resolución de problemas de asignación de rutas a vehículos
    (Universidad de Deusto, 2015-11-16) Osaba, Eneko; Díaz Martín, José Fernando; Facultad de Ingeniería; Ingeniería Informática y Telecomunicación
    El transporte es un factor crucial para la sociedad actual, tanto para la ciudadanía como para el sector empresarial. Existe una gran variedad de sistemas de transporte, cada uno con sus ventajas e inconvenientes. Del mismo modo, diversas áreas de conocimiento están capacitadas para hacer frente a la planificación eficiente del transporte, ya sea de carácter empresarial, o urbano. En este trabajo se centrará la atención en una de esas áreas: la inteligencia artificial y los problemas de optimización. La gran mayoría de los problemas surgidos en el área del transporte y la logística tienen características comunes, lo que hace que puedan modelizarse como problemas de optimización y que puedan ser vistos como casos particulares de otros problemas genéricos. Estos problemas se encuadran en el ámbito de la optimización combinatoria. Gran parte de los problemas de este tipo cuentan con una complejidad excepcional, haciendo necesaria la utilización de técnicas para su tratamiento. Existen diferentes métodos de esta índole, aunque este trabajo se centrará en las meta-heurísticas. Puede encontrarse un vasto número de meta-heurísticas en la literatura actual, cada una con sus propias características. Debido a la alta complejidad de los problemas a tratar, no hay una técnica definitiva que consiga resolver de forma óptima todos los problemas de optimización. Este hecho hace que el campo tanto de la optimización combinatoria, como el de los problemas de asignación de rutas de transporte, sea un tema de investigación candente. Con todo esto, el presente trabajo de tesis doctoral centrará su esfuerzo en la creación de una nueva meta-heurística que ayude a la resolución de problemas de asignación de rutas a vehículos. La técnica presentada ofrece un valor añadido frente a los métodos existentes, ya sea en relación al rendimiento, o a la aportación de originalidades conceptuales. Con la intención de validar el modelo, se han comparado los resultados de la meta-heurística propuesta con los obtenidos por otros cuatro algoritmos de filosofía similar. Para esta experimentación se han utilizado cuatro famosos problemas de asignación de rutas a vehículos, y dos problemas clásicos de la optimización combinatoria. En la comparativa se ha realizado un completo análisis estadístico sobre la calidad de las soluciones obtenidas y la convergencia temporal de cada técnica, utilizando para ello pruebas estadísticas parámetricas, como el test normal z, y pruebas no paramétricas, como el test de Friedman. Gracias a estos tests se ha podido afirmar de forma rigurosa que la técnica propuesta es competitiva en cuanto a rendimiento se refiere, y original conceptualmente hablando.
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    Ítem
    Genetic optimised serial hierarchical fuzzy classifier for breast cancer diagnosis
    (Inderscience Publishers, 2020) Zhang, Xiao; Onieva Caracuel, Enrique; Perallos Ruiz, Asier; Osaba, Eneko
    Accurate early-stage medical diagnosis of breast cancer can improve the survival rates and fuzzy rule-base system (FRBS) has been a promising classification system to detect breast cancer. However, the existing classification systems involves large number of input variables for training and produces a large number of fuzzy rules, which lead to high complexity and barely acceptable accuracy. In this paper, we present a genetic optimised serial hierarchical FRBS, which incorporates lateral tuning of membership functions and optimisation of the rule base. The serial hierarchical structure of FRBS allows selecting and ranking the input variables, which reduces the system complexity and distinguish the importance of attributes in datasets. We conduct an experimental study on Original Wisconsin Breast Cancer Database and Wisconsin Breast Cancer Diagnostic Database from UCI Machine Learning Repository, and show that the proposed system can classify breast cancer accurately and efficiently.
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    IEM: a unified lifecycle orchestrator for multilingual IaC deployments
    (Association for Computing Machinery, Inc, 2023-04-15) Díaz de Arcaya Serrano, Josu; Osaba, Eneko ; Benguria, Gorka; Etxaniz Errazkin, Iñaki; López Lobo, Jesús ; Alonso, Juncal; Torre Bastida, Ana Isabel ; Almeida, Aitor
    Over the last few years, DevOps methodologies have promoted a more streamlined operationalization of software components in production environments. Infrastructure as Code (IaC) technologies play a key role in the lifecycle management of applications, as they promote the delivery of the infrastructural elements alongside the application components. This way, IaC technologies aspire to minimize the problems associated with the environment by providing a repeatable and traceable process. However, there are a large variety of IaC frameworks, each of them focusing on a different phase of the operationalization lifecycle, hence the necessity to master numerous technologies. In this research, we present the IaC Execution Manager (IEM), a tool devoted to providing a unified framework for the operationalization of software components that encompasses the various stages and technologies involved in the application lifecycle. We analyze an industrial use case to improve the current approach and conclude the IEM is a suitable tool for solving the problem as it promotes automation, while reducing the learning curve associated with the required IaC technologies.
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    A smartphone-based system for outdoor data gathering using a wireless beacon network and GPS data: from cyber spaces to senseable spaces
    (MDPI AG, 2018-05-15) Osaba, Eneko; Pierdicca, Roberto; Malinverni, Eva Savina; Khromova, Anna ; Álvarez Franco, Fernando Javier ; Bahillo, Alfonso
    Information and Communication Technologies (ICTs) and mobile devices are deeply influencing all facets of life, directly affecting the way people experience space and time. ICTs are also tools for supporting urban development, and they have also been adopted as equipment for furnishing public spaces. Hence, ICTs have created a new paradigm of hybrid space that can be defined as Senseable Spaces. Even if there are relevant cases where the adoption of ICT has made the use of public open spaces more “smart”, the interrelation and the recognition of added value need to be further developed. This is one of the motivations for the research presented in this paper. The main goal of the work reported here is the deployment of a system composed of three different connected elements (a real-world infrastructure, a data gathering system, and a data processing and analysis platform) for analysis of human behavior in the open space of Cardeto Park, in Ancona, Italy. For this purpose, and because of the complexity of this task, several actions have been carried out: the deployment of a complete real-world infrastructure in Cardeto Park, the implementation of an ad-hoc smartphone application for the gathering of participants’ data, and the development of a data pre-processing and analysis system for dealing with all the gathered data. A detailed description of these three aspects and the way in which they are connected to create a unique system is the main focus of this paper.
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    Using ICTs for the improvement of public open spaces: the opportunity offered by cyberParks digital tools
    (Springer Verlag, 2019) Osaba, Eneko ; Pierdicca, Roberto; Duarte, Tiago; Bahillo, Alfonso; Mateus, Diogo
    In the last decade, the potential of mobile devices for augmenting outdoor experience opened up new solutions, whose value is twofold. On one hand, users can experience new forms of interaction with space. On the other, stakeholders can have access to the so-called User Generated Data, that is different types of information related to public spaces that could be used to improve their conception of space. In line with this, several digital tools have been developed and tested within the framework of CyberParks COST Action TU-1306 with the intention of exploring how information and communication technologies (ICTs) can contribute to the improvement of Public Open Spaces (POS). In this way, this chapter aims to study the relationship between ICTs and POS, focused on the opportunities offered by three different digital tools: the WAY-CyberParks, the EthnoAlly, and the CyberCardeto. The main advantages of using these digital tools are: (1) the real-time data gathering, (2) maintaining an updated database, (3) collecting traces of different activities and users’ groups “at the same time and space”, and (4) recording their opinion and preferences, via text, video, sound or pictures. Furthermore, the chapter attempts to analyse distinct types of results produced by their use, based on different study cases where the digital tool has been tested. The data obtained in these places serve to demonstrate the features and type of data gathered. With these case studies, the chapter attempts to highlight the main potential of each platform as related to different stakeholders and users.