Descubrimiento automático de mappings en un caso de uso real con altas exigencias de certeza

Los sistemas de integración de información resuelven las diferencias entre las fuentes, en la mayoría de los casos, mediante la creación de mappings, puentes semánticos entre los elementos de las fuentes. Hasta ahora se han propuesto comparadores para generar un conjunto de mappings para cada par de elementos de las fuentes a integrar, y se han realizado estudios experimentales con ellos. El valor añadido del presente trabajo frente a los trabajos experimentales anteriores es que se ha llevado a cabo en un caso real embebido en una aplicación real (en el dominio geográfico) con altas exigencias de certeza

OEGMerge: a case-based model for merging ontologies

No long ago ontology merging was a necessary activity, however, the current methods used in ontology merging present neither detailed cases nor an accurate formalization. For validating these methods, it is convenient to have a case list as complete as possible. In this paper we present the OEGMerge model, developed from the OEG (Ontological Engineering Group at UPM) experience, which describes precisely the merging casuistic and the actions to carry out in each case. In this first approach, the model covers only the taxonomy of concepts, attributes and relations

Estudio y formalización del proceso de mezcla de ontologías

Desde hace tiempo la mezcla de ontolog?as es una actividad necesaria, sin embargo, los actuales m?todos de mezcla de ontolog?as no tienen una casu?stica detallada ni una formalizaci?n precisa. Para la validaci?n de estos m?todos, es conveniente disponer de una casu?stica lo m?s completa posible. Por ello, en este art?culo se presenta el modelo OEGMerge, desarrollado a partir de la experiencia del Grupo de Ingenier?a Ontol?gica (OEG) de la UPM, en el que se describe detallada y formalmente la casu?stica de mezcla y las acciones a realizar en cada caso. En esta primera aproximaci?n s?lo se abarca taxonom?a de conceptos, atributos y relaciones

Algoritmo de agregación de mappings basado en reglas de selección

Los sistemas de integración de información resuelven las diferencias entre las fuentes, en la mayoría de los casos, mediante la creación de mappings, puentes semánticos entre los elementos de las fuentes. Hasta ahora se han propuesto técnicas para generar un conjunto de mappings para cada par de elementos de las fuentes a integrar, sin embargo, hasta la publicación del presente trabajo, no se disponía de un algoritmo de agregación público y general para distintos tipos de fuentes que permitiera sintetizar este conjunto de mappings en uno solo. El enfoque aquí presentado está basado en reglas y ha sido aplicado en la integración de catálogos de mobiliario y en la integración de recursos en el dominio geoespacia

OEGMerge: un modelo de mezcla de ontologías basado en casuísticas

Desde hace tiempo la mezcla de ontologías es una actividad necesaria, sin embargo, los actuales métodos de mezcla de ontologías no tienen una casuística detallada ni una formalización precisa. Para la validación de estos métodos, es conveniente disponer de una casuística lo más completa posible. Por ello, en este artículo se presenta el modelo OEGMerge, desarrollado a partir de la experiencia del Grupo de Ingeniería Ontológica (OEG) de la UPM, en el que se describe detallada y formalmente la casuística de mezcla y las acciones a realizar en cada caso. En esta primera aproximación sólo se abarca taxonomía de conceptos, atributos y relacione

Sub-arcsecond Morphology of Planetary Nebulae

Planetary nebulae (PNe) can be roughly categorized into several broad morphological classes. The high quality images of PNe acquired in recent years, however, have revealed a wealth of fine structures that preclude simplistic models for their formation. Here we present narrow-band, sub-arcsecond images of a sample of relatively large PNe that illustrate the complexity and variety of small-scale structures. This is especially true for bipolar PNe, for which the images reveal multi-polar ejections and, in some cases, suggest turbulent gas motions. Our images also reveal the presence or signs of jet-like outflows in several objects in which this kind of component has not been previously reported.Comment: 7 pages, 7 figures, Accepted for publication in PAS

Smart Water Management towards Future Water Sustainable Networks

[EN] Water management towards smart cities is an issue increasingly appreciated under financial and environmental sustainability focus in any water sector. The main objective of this research is to disclose the technological breakthroughs associated with water and energy use. A methodology is proposed and applied in a case study to analyze the benefits to develop smart water grids, showing the advantages offered by the development of control measures. The case study showed the positive results, particularly savings of 57 GWh and 100 Mm3 in a period of twelve years when different measures from the common ones were developed for the monitoring and control of water losses in smart water management. These savings contributed to reducing the CO2 emissions to 47,385 t CO2-eq. Finally, in order to evaluate the financial effort and savings obtained in this reference systems (RS) network, the investment required in the monitoring and water losses control in a correlation model case (CMC) was estimated, and, as a consequence, the losses level presented a significant reduction towards sustainable values in the next nine years. Since the pressure control is one of the main issues for the reduction of leakage, an estimation of energy production for Portugal is also presentedRamos, HM.; Mcnabola, A.; López Jiménez, PA.; Pérez-Sánchez, M. (2020). Smart Water Management towards Future Water Sustainable Networks. Water. 12(1):1-13. https://doi.org/10.3390/w12010058S113121Sachidananda, M., Webb, D., & Rahimifard, S. (2016). A Concept of Water Usage Efficiency to Support Water Reduction in Manufacturing Industry. Sustainability, 8(12), 1222. doi:10.3390/su8121222Boyle, T., Giurco, D., Mukheibir, P., Liu, A., Moy, C., White, S., & Stewart, R. (2013). Intelligent Metering for Urban Water: A Review. Water, 5(3), 1052-1081. doi:10.3390/w5031052Ritzema, H., Kirkpatrick, H., Stibinger, J., Heinhuis, H., Belting, H., Schrijver, R., & Diemont, H. (2016). Water Management Supporting the Delivery of Ecosystem Services for Grassland, Heath and Moorland. Sustainability, 8(5), 440. doi:10.3390/su8050440Pérez-Sánchez, M., Sánchez-Romero, F. J., & López-Jiménez, P. A. (2017). Nexo agua-energía: optimización energética en sistemas de distribución. Aplicación ‘Postrasvase Júcar-Vinalopó’ (España). Tecnología y ciencias del agua, 08(4), 19-36. doi:10.24850/j-tyca-2017-04-02Howell, S., Rezgui, Y., & Beach, T. (2017). Integrating building and urban semantics to empower smart water solutions. Automation in Construction, 81, 434-448. doi:10.1016/j.autcon.2017.02.004Mounce, S. R., Pedraza, C., Jackson, T., Linford, P., & Boxall, J. B. (2015). Cloud Based Machine Learning Approaches for Leakage Assessment and Management in Smart Water Networks. Procedia Engineering, 119, 43-52. doi:10.1016/j.proeng.2015.08.851Lombardi, P., Giordano, S., Farouh, H., & Yousef, W. (2012). Modelling the smart city performance. Innovation: The European Journal of Social Science Research, 25(2), 137-149. doi:10.1080/13511610.2012.660325Smart Cities: Strategic Sustainable Development for an Urban World. Sweden: School of Engineering, Blekinge Institute of Technology https://www.diva-portal.org/smash/get/diva2:832150/FULLTEXT01.pdfSmart Cities: Ranking of European Medium-Sized. Vienna, Austria: Centre of Regional Science (SRF), Vienna University of Technology http://www.smart-cities.eu/download/smart_cities_final_report.pdfHellström, D., Jeppsson, U., & Kärrman, E. (2000). A framework for systems analysis of sustainable urban water management. Environmental Impact Assessment Review, 20(3), 311-321. doi:10.1016/s0195-9255(00)00043-3Smart Water Grid. USA: Department of Civil and Environmental Engineering, Colorado State University http://www.engr.colostate.edu/~pierre/ce_old/Projects/Rising%20Stars%20Website/Martyusheva,Olga_PlanB_TechnicalReport.pdfSmart Metering Introduction. Obtained on 12 August 2015, from Alliance for Water Efficiency http://www.allianceforwaterefficiency.org/smart-meter-introduction.aspxNtuli, N., & Abu-Mahfouz, A. (2016). A Simple Security Architecture for Smart Water Management System. Procedia Computer Science, 83, 1164-1169. doi:10.1016/j.procs.2016.04.239Britton, T. C., Stewart, R. A., & O’Halloran, K. R. (2013). Smart metering: enabler for rapid and effective post meter leakage identification and water loss management. Journal of Cleaner Production, 54, 166-176. doi:10.1016/j.jclepro.2013.05.018Sharvelle, S., Dozier, A., Arabi, M., & Reichel, B. (2017). A geospatially-enabled web tool for urban water demand forecasting and assessment of alternative urban water management strategies. Environmental Modelling & Software, 97, 213-228. doi:10.1016/j.envsoft.2017.08.009Distribution System Water Quality Monitoring: Sensor Technology Evaluation Methodology and Results.A Guide for Sensor Manufacturers and Water Utilities. Ohio: EPA–Environmental Protection Agency https://www.epa.gov/sites/production/files/2015-06/documents/distribution_system_water_quality_monitoring_sensor_technology_evaluation_methodology_results.pdfSCADA: Supervisory Control and Data Acquision. USA: ISA–The Instrumentation, Systemas and Automation Society https://www.fer.unizg.hr/_download/repository/SCADA-Supervisory_And_Data_Acquisition.pdfCan we make water systems smarter? Opflow http://innovyze.com/news/showcases/SmartWaterNetworks.pdfGurung, T. R., Stewart, R. A., Beal, C. D., & Sharma, A. K. (2015). Smart meter enabled water end-use demand data: platform for the enhanced infrastructure planning of contemporary urban water supply networks. Journal of Cleaner Production, 87, 642-654. doi:10.1016/j.jclepro.2014.09.054Romano, M., & Kapelan, Z. (2014). Adaptive water demand forecasting for near real-time management of smart water distribution systems. Environmental Modelling & Software, 60, 265-276. doi:10.1016/j.envsoft.2014.06.016Samora, I., Franca, M. J., Schleiss, A. J., & Ramos, H. M. (2016). Simulated Annealing in Optimization of Energy Production in a Water Supply Network. Water Resources Management, 30(4), 1533-1547. doi:10.1007/s11269-016-1238-5Sanchis, R., Díaz-Madroñero, M., López-Jiménez, P. A., & Pérez-Sánchez, M. (2019). Solution Approaches for the Management of the Water Resources in Irrigation Water Systems with Fuzzy Costs. Water, 11(12), 2432. doi:10.3390/w11122432Alonso Campos, J. C., Jiménez-Bello, M. A., & Martínez Alzamora, F. (2020). Real-time energy optimization of irrigation scheduling by parallel multi-objective genetic algorithms. Agricultural Water Management, 227, 105857. doi:10.1016/j.agwat.2019.105857Controlo Ativo de Perdas de Água. Lisboa: EPAL–Empresa Portuguesa das Águas Livres http://www.epal.pt/EPAL/docs/default-source/epal/publica%C3%A7%C3%B5es-t%C3%A9cnicas/controlo-ativo-de-perdas-de-%C3%A1gua.pdf?sfvrsn=30Ndirangu, N., Ng’ang’a, J., Chege, A., de Blois, R.-J., & Mels, A. (2013). Local solutions in Non-Revenue Water management through North–South Water Operator Partnerships: the case of Nakuru. Water Policy, 15(S2), 137-164. doi:10.2166/wp.2013.117Romero, L., Pérez-Sánchez, M., & Amparo López-Jiménez, P. (2017). Improvement of sustainability indicators when traditional water management changes: a case study in Alicante (Spain). AIMS Environmental Science, 4(3), 502-522. doi:10.3934/environsci.2017.3.50

Strength distribution of solar magnetic fields in photospheric quiet Sun regions

The magnetic topology of the solar photosphere in its quietest regions is hidden by the difficulties to disentangle magnetic flux through the resolution element from the field strength of unresolved structures. The observation of spectral lines with strong coupling with hyperfine structure, like the observed MnI line at 553.7 nm, allows such differentiation. The main aim is to analyse the distribution of field strengths in the network and intranetwork of the solar photosphere through inversion of the MnI line at 553.7 nm. An inversion code for the magnetic field using the Principal Component Analysis (PCA) has been developed. Statistical tests are run on the code to validate it. The code has to draw information from the small-amplitude spectral feature oppearing in the core of the Stokes V profile of the observed line for field strengths below a certain threshold, coinciding with lower limit of the Paschen-Back effect in the fine structure of the involved atomic levels. The inversion of the observed profiles, using the circular polarization (V) and the intensity (I), shows the presence of magnetic fields strengths in a range from 0 to 2 kG, with predominant weak strength values. Mixed regions with mean strength field values of 1130 and 435 Gauss are found associated with the network and intranetwork respectively. The MnI line at 553 nm probes the field strength distribution in the quiet sun and shows the predominance of weak, hectoGauss fields in the intranetwork, and strong, kiloGauss fields in the network. It also shows that both network and intranetwork are to be understood at our present spatial resolutions as field distributions of which we hint the mean properties.Comment: 10 pages, 6 figure

Galaxy and mass assembly (GAMA): The environmental impact on SFR and metallicity in galaxy groups

We present a study of the relationships and environmental dependencies between stellar mass, star formation rate, and gas metallicity for more than 700 galaxies in groups up to redshift 0.35 from the Galaxy And Mass Assembly (GAMA) survey. To identify the main drivers, our sample was analysed as a function of group-centric distance, projected galaxy number density, and stellar mass. By using control samples of more than 16 000 star-forming field galaxies and volume-limited samples, we find that the highest enhancement in SFR (0.3 dex) occurs in galaxies with the lowest local density. In contrast to previous work, our data show small enhancements of ∼0.1 dex in SFR for galaxies at the highest local densities or group-centric distances. Our data indicates quenching in SFR only for massive galaxies, suggesting that stellar mass might be the main driver of quenching processes for star forming galaxies. We can discard a morphological driven quenching, since the Sérsic index distribution for group and control galaxies are similar. The gas metallicity does not vary drastically. It increases ∼0.08 dex for galaxies at the highest local densities, and decreases for galaxies at the highest group-centric distances, in agreement with previous work. Altogether, the local density, rather than group-centric distance, shows the stronger impact in enhancing both, the SFR and gas metallicity. We applied the same methodology to galaxies from the IllustrisTNG simulations, and although we were able to reproduce the general observational trends, the differences between group and control samples only partially agree with the observations

Galaxy and mass assembly (GAMA): The environmental impact on SFR and metallicity in galaxy groups

We present a study of the relationships and environmental dependencies between stellar mass, star formation rate, and gas metallicity for more than 700 galaxies in groups up to redshift 0.35 from the Galaxy And Mass Assembly (GAMA) survey. To identify the main drivers, our sample was analysed as a function of group-centric distance, projected galaxy number density, and stellar mass. By using control samples of more than 16 000 star-forming field galaxies and volume-limited samples, we find that the highest enhancement in SFR (0.3 dex) occurs in galaxies with the lowest local density. In contrast to previous work, our data show small enhancements of ∼0.1 dex in SFR for galaxies at the highest local densities or group-centric distances. Our data indicates quenching in SFR only for massive galaxies, suggesting that stellar mass might be the main driver of quenching processes for star forming galaxies. We can discard a morphological driven quenching, since the Sérsic index distribution for group and control galaxies are similar. The gas metallicity does not vary drastically. It increases ∼0.08 dex for galaxies at the highest local densities, and decreases for galaxies at the highest group-centric distances, in agreement with previous work. Altogether, the local density, rather than group-centric distance, shows the stronger impact in enhancing both, the SFR and gas metallicity. We applied the same methodology to galaxies from the IllustrisTNG simulations, and although we were able to reproduce the general observational trends, the differences between group and control samples only partially agree with the observations