Incremental algorithm for Decision Rule generation in data stream contexts

Actualmente, la ciencia de datos está ganando mucha atención en diferentes sectores. Concretamente en la industria, muchas aplicaciones pueden ser consideradas. Utilizar técnicas de ciencia de datos en el proceso de toma de decisiones es una de esas aplicaciones que pueden aportar valor a la industria. El incremento de la disponibilidad de los datos y de la aparición de flujos continuos en forma de data streams hace emerger nuevos retos a la hora de trabajar con datos cambiantes. Este trabajo presenta una propuesta innovadora, Incremental Decision Rules Algorithm (IDRA), un algoritmo que, de manera incremental, genera y modifica reglas de decisión para entornos de data stream para incorporar cambios que puedan aparecer a lo largo del tiempo. Este método busca proponer una nueva estructura de reglas que busca mejorar el proceso de toma de decisiones, planteando una base de conocimiento descriptiva y transparente que pueda ser integrada en una herramienta decisional. Esta tesis describe la lógica existente bajo la propuesta de IDRA, en todas sus versiones, y propone una variedad de experimentos para compararlas con un método clásico (CREA) y un método adaptativo (VFDR). Conjuntos de datos reales, juntamente con algunos escenarios simulados con diferentes tipos y ratios de error, se utilizan para comparar estos algoritmos. El estudio prueba que IDRA, específicamente la versión reactiva de IDRA (RIDRA), mejora la precisión de VFDR y CREA en todos los escenarios, tanto reales como simulados, a cambio de un incremento en el tiempo.Nowadays, data science is earning a lot of attention in many different sectors. Specifically in the industry, many applications might be considered. Using data science techniques in the decision-making process is a valuable approach among the mentioned applications. Along with this, the growth of data availability and the appearance of continuous data flows in the form of data stream arise other challenges when dealing with changing data. This work presents a novel proposal of an algorithm, Incremental Decision Rules Algorithm (IDRA), that incrementally generates and modify decision rules for data stream contexts to incorporate the changes that could appear over time. This method aims to propose new rule structures that improve the decision-making process by providing a descriptive and transparent base of knowledge that could be integrated in a decision tool. This work describes the logic underneath IDRA, in all its versions, and proposes a variety of experiments to compare them with a classical method (CREA) and an adaptive method (VFDR). Some real datasets, together with some simulated scenarios with different error types and rates are used to compare these algorithms. The study proved that IDRA, specifically the reactive version of IDRA (RIDRA), improves the accuracies of VFDR and CREA in all the studied scenarios, both real and simulated, in exchange of more time

FGROUP in the social and healthcare market

[EN] As part of its diversification strategy, FGROUP intends to get into the social and health care market, which shows a very high growth potential due to demographic and social causes. To tackle this strategy, IBV proposed to define FGROUP¿s business model in this new market using the tools Business Model Canvas by Osterwalder et al and Business Model Tracker by IBV. These tools were used as a means of analysis of the evolution in firm¿s capabilities and the state of the environment to obtain sustainable competitive advantages. As a consequence of this analysis, a new product in line with the business model was developed to help in its implementation.[ES] FGROUP pretende entrar en el FGROUP en el mercado sociosanitario mercado sociosanitario como parte de su estrategia de diversificación. Este mercado presenta un potencial de crecimiento muy elevado a nivel mundial debido, entre otras, a causas demográficas y socioeconómicas. Para abordar esta estrategia, el Instituto de Biomecánica (IBV) propuso definir un modelo de negocio en este nuevo mercado empleando las herramientas Business Model Canvas de Osterwalder y Business Model Tracker del IBV. Estas herramientas se utilizaron como medios de análisis de la evolución de las capacidades de la empresa y del estado del entorno para obtener ventajas competitivas sostenibles. Como consecuencia de este análisis, se llevó a cabo el desarrollo de un producto coherente con el modelo de negocio diseñado, que ayudará a ponerlo en práctica.Proyecto financiado en el marco de la convocatoria de los II Planes Sectoriales de Competitividad 2009, dentro de la Actuación 2.6: Diseño, 2.6.2 Prestación de servicios de asesoramiento. Proyecto cofinanciado por los ÇFondos FEDER, dentro del Programa Operativo FEDER de la Comunidad Valenciana 2007-2013Giménez Pla, JF.; Aparisi Hermoso, P.; López Vicente, MA.; Sancho Mollá, M.; Navarro Garcia, FJ.; Gamón Sanz, A.; García Muñoz, N.... (2013). FGROUP en el mercado sociosanitario. Revista de biomecánica. 60:25-27. http://hdl.handle.net/10251/38673S25276

Ahora / Ara

La cinquena edició del microrelatari per l’eradicació de la violència contra les dones de l’Institut Universitari d’Estudis Feministes i de Gènere «Purificación Escribano» de la Universitat Jaume I vol ser una declaració d’esperança. Aquest és el moment en el qual les dones (i els homes) hem de fer un pas endavant i eliminar la violència sistèmica contra les dones. Ara és el moment de denunciar el masclisme i els micromasclismes començant a construir una societat més igualitària. Cadascun dels relats del llibre és una denúncia i una declaració que ens encamina cap a un món millor

Incremental Decision Rules Algorithm: A Probabilistic and Dynamic Approach to Decisional Data Stream Problems

Data science is currently one of the most promising fields used to support the decision-making process. Particularly, data streams can give these supportive systems an updated base of knowledge that allows experts to make decisions with updated models. Incremental Decision Rules Algorithm (IDRA) proposes a new incremental decision-rule method based on the classical ID3 approach to generating and updating a rule set. This algorithm is a novel approach designed to fit a Decision Support System (DSS) whose motivation is to give accurate responses in an affordable time for a decision situation. This work includes several experiments that compare IDRA with the classical static but optimized ID3 (CREA) and the adaptive method VFDR. A battery of scenarios with different error types and rates are proposed to compare these three algorithms. IDRA improves the accuracies of VFDR and CREA in most common cases for the simulated data streams used in this work. In particular, the proposed technique has proven to perform better in those scenarios with no error, low noise, or high-impact concept drifts.This work was supported by grant DIN2018-010101 funded by MCIN/AEI/10.13039/501100011033, Teralco Solutions Ltd, and PROMETEO2021/063 funded by the Generalitat Valenciana. Open Access funding provided by Miguel Hernández University of Elche

MEGARA, the R=6000-20000 IFU and MOS of GTC

MEGARA is the new generation IFU and MOS optical spectrograph built for the 10.4m Gran Telescopio CANARIAS (GTC). The project was developed by a consortium led by UCM (Spain) that also includes INAOE (Mexico), IAA-CSIC (Spain) and UPM (Spain). The instrument arrived to GTC on March 28th 2017 and was successfully integrated and commissioned at the telescope from May to August 2017. During the on-sky commissioning we demonstrated that MEGARA is a powerful and robust instrument that provides on-sky intermediate-to-high spectral resolutions RFWHM ~ 6,000, 12,000 and 20,000 at an unprecedented efficiency for these resolving powers in both its IFU and MOS modes. The IFU covers 12.5 x 11.3 arcsec 2 while the MOS mode allows observing up to 92 objects in a region of 3.5 x 3.5 arcmin 2 . In this paper we describe the instrument main subsystems, including the Folded-Cassegrain unit, the fiber link, the spectrograph, the cryostat, the detector and the control subsystems, and its performance numbers obtained during commissioning where the fulfillment of the instrument requirements is demonstrated. © 2018 SPIE

First scientific observations with MEGARA at GTC

On June 25th 2017, the new intermediate-resolution optical IFU and MOS of the 10.4-m GTC had its first light. As part of the tests carried out to verify the performance of the instrument in its two modes (IFU and MOS) and 18 spectral setups (identical number of VPHs with resolutions R=6000-20000 from 0.36 to 1 micron) a number of astronomical objects were observed. These observations show that MEGARA@GTC is called to fill a niche of high-throughput, intermediateresolution IFU and MOS observations of extremely-faint narrow-lined objects. Lyman-α absorbers, star-forming dwarfs or even weak absorptions in stellar spectra in our Galaxy or in the Local Group can now be explored to a new level. Thus, the versatility of MEGARA in terms of observing modes and spectral resolution and coverage will allow GTC to go beyond current observational limits in either depth or precision for all these objects. The results to be presented in this talk clearly demonstrate the potential of MEGARA in this regard