Validación de la versión española del Cuestionario Breve de Evitación Experiencial (BEAQ) en población clínica

The Brief Experiential Avoidance Questionnaire (BEAQ) has been suggested as the most appropriate instrument for measuring experiential avoidance. However, no Spanish validation has been published. The aim of this study was to validate a Spanish version of the BEAQ in a clinical sample treated at a community mental health unit. Methods: Participants (N = 332) completed the BEAQ as well as other self-report measures of experiential avoidance and psychopathology. Results: Internal consistency was satisfactory (α = .82). No statistically significant gender differences were found in the BEAQ scores. The data also showed high test-retest reliability after four to six weeks, acceptable concurrent validity with another experiential avoidance measure and acceptable convergent validity with the psychopathology measure. The principal component analysis, forcing the one factor solution proposed in the original scale, produced indicators similar to the English version of the BEAQ. Conclusions: These results firmly support the reliability and validity of this Spanish validation, stressing its usefulness as a measure of experiential avoidance in clinical populations.Antecedentes: el Cuestionario Breve de Evitación Experiencial (BEAQ) ha sido propuesto como el instrumento más adecuado para medir la evitación experiencial. Sin embargo, todavía no ha sido publicada ninguna validación en español. Por lo tanto, el objetivo del presente estudio ha sido la validación de una versión española del BEAQ, en una muestra clínica atendida en un Centro de Salud Mental Comunitario. Método: los participantes (N = 332) completaron el BEAQ, así como otras medidas de autoinforme de evitación experiencial y psicopatología. Resultados: la consistencia interna fue satisfactoria (α = .82). No se encontraron diferencias de género estadísticamente significativas en las puntuaciones del BEAQ. Los datos también mostraron una alta fiabilidad test-retest en un intervalo de cuatro a seis semanas, validez concurrente aceptable con otra medida de evitación experiencial y validez convergente aceptable con la medida de psicopatología. El análisis de componentes principales forzando a la solución de un factor, como se propuso en la escala original, obtuvo unos indicadores similares a los obtenidos en dicha versión inglesa. Conclusiones: los resultados confirman la adecuada fiabilidad y validez de la presente versión española del BEAQ, destacando su utilidad como medida de la evitación experiencial en población clínica

Forecasting Recharging Demand to Integrate Electric Vehicle Fleets in Smart Grids

Electric vehicle fleets and smart grids are two growing technologies. These technologies provided new possibilities to reduce pollution and increase energy efficiency. In this sense, electric vehicles are used as mobile loads in the power grid. A distributed charging prioritization methodology is proposed in this paper. The solution is based on the concept of virtual power plants and the usage of evolutionary computation algorithms. Additionally, the comparison of several evolutionary algorithms, genetic algorithm, genetic algorithm with evolution control, particle swarm optimization, and hybrid solution are shown in order to evaluate the proposed architecture. The proposed solution is presented to prevent the overload of the power grid

Monitoring and Fault Location Sensor Network for Underground Distribution Lines

One of the fundamental tasks of electric distribution utilities is guaranteeing a continuous supply of electricity to their customers. The primary distribution network is a critical part of these facilities because a fault in it could affect thousands of customers. However, the complexity of this network has been increased with the irruption of distributed generation, typical in a Smart Grid and which has significantly complicated some of the analyses, making it impossible to apply traditional techniques. This problem is intensified in underground lines where access is limited. As a possible solution, this paper proposes to make a deployment of a distributed sensor network along the power lines. This network proposes taking advantage of its distributed character to support new approaches of these analyses. In this sense, this paper describes the aquiculture of the proposed network (adapted to the power grid) based on nodes that use power line communication and energy harvesting techniques. In this sense, it also describes the implementation of a real prototype that has been used in some experiments to validate this technological adaptation. Additionally, beyond a simple use for monitoring, this paper also proposes the use of this approach to solve two typical distribution system operator problems, such as: fault location and failure forecasting in power cables.Ministerio de Economía y Competitividad, Government of Spain project Sistema Inteligente Inalámbrico para Análisis y Monitorización de Líneas de Tensión Subterráneas en Smart Grids (SIIAM) TEC2013-40767-RMinisterio de Educación, Cultura y Deporte, Government of Spain, for the funding of the scholarship Formación de Profesorado Universitario 2016 (FPU 2016

DC-Voltage-Ratio Control Strategy for Multilevel Cascaded Converters Fed With a Single DC Source

Recently, a multilevel cascaded converter fed with a single DC source has been presented. An analysis of the steady-state working limits of this type of converter is presented in this paper. Limits of the maximum output voltage and the minimum and maximum loading conditions for stable operation of the converter are addressed. In this paper, a way to achieve any DC voltage ratio (inside the stable operation area of the converter) between the H-bridges of the single-DC-source cascaded H-bridge converter is presented. The proposed DC-voltage-ratio control is based on a time-domain modulation strategy that avoids the use of inappropriate states to achieve the DC-voltage-ratio control. The proposed technique is a feedforward-modulation technique which takes into account the actual DC voltage of each H-bridge of the converter, leading to output waveforms with low distortion. In this way, the dc voltage of the floating H-bridge can be controlled while the output voltage has low distortion independently of the desired DC voltage ratio. Experimental results from a two-cell cascaded converter are presented in order to validate the proposed DC-voltage-ratio control strategy and the introduced concepts.Ministerio de Ciencia y Tecnología TEC2006-03863Junta de Andalucía EXC/2005/TIC-117

Increasing the Efficiency of Rule-Based Expert Systems Applied on Heterogeneous Data Sources

Nowadays, the proliferation of heterogeneous data sources provided by different research and innovation projects and initiatives is proliferating more and more and presents huge opportunities. These developments create an increase in the number of different data sources, which could be involved in the process of decisionmaking for a specific purpose, but this huge heterogeneity makes this task difficult. Traditionally, the expert systems try to integrate all information into a main database, but, sometimes, this information is not easily available, or its integration with other databases is very problematic. In this case, it is essential to establish procedures that make a metadata distributed integration for them. This process provides a “mapping” of available information, but it is only at logic level. Thus, on a physical level, the data is still distributed into several resources. In this sense, this chapter proposes a distributed rule engine extension (DREE) based on edge computing that makes an integration of metadata provided by different heterogeneous data sources, applying then a mathematical decomposition over the antecedent of rules. The use of the proposed rule engine increases the efficiency and the capability of rule-based expert systems, providing the possibility of applying these rules over distributed and heterogeneous data sources, increasing the size of data sets that could be involved in the decision-making process

Heterogeneous data source integration for smart grid ecosystems based on metadata mining

The arrival of new technologies related to smart grids and the resulting ecosystem of applications andmanagement systems pose many new problems. The databases of the traditional grid and the variousinitiatives related to new technologies have given rise to many different management systems with several formats and different architectures. A heterogeneous data source integration system is necessary toupdate these systems for the new smart grid reality. Additionally, it is necessary to take advantage of theinformation smart grids provide. In this paper, the authors propose a heterogeneous data source integration based on IEC standards and metadata mining. Additionally, an automatic data mining framework isapplied to model the integrated information.Ministerio de Economía y Competitividad TEC2013-40767-

Analítica de aprendizaje en MOOC mediante métricas dinámicas en tiempo real

Este artículo presenta el diseño y funcionamiento de una experiencia de analítica mediante una plataforma que ofrece métricas dinámicas en tiempo real denominada ?MOOC Dashboard?. La experiencia se ha desarrollado por la Universidad de Southampton y la Universidad Autónoma de Madrid y se ha aplicado al análisis del funcionamiento en los cursos MOOC de la plataforma FutureLearn. El avance de la enseñanza en entornos masivos requiere, entre otras iniciativas, del conocimiento del desempeño del estudiante con respecto al diseño más o menos interactivo que ofrecen estos cursos. La visualización de métricas de aprendizaje y de la huella del estudiante en los cursos permite dinamizar y mejorar los entornos de cursos los MOOC. A través de un enfoque descriptivo-exploratorio se analiza el curso MOOC: ?Digital Marketing: Challenges and Insights? ofrecido por la plataforma FutureLearn? y se presentan los resultados de la aplicación de métricas analíticas dinámicas en tiempo real al desempeño académico de los estudiantes

Adaptive Vectorial Filter for Grid Synchronization of Power Converters Under Unbalanced and/or Distorted Grid Conditions

This paper presents a new synchronization scheme for detecting multiple positive-/negative-sequence frequency harmonics in three-phase systems for grid-connected power converters. The proposed technique is called MAVF-FLL because it is based on the use of multiple adaptive vectorial filters (AVFs) working together inside a harmonic decoupling network, resting on a frequency-locked loop (FLL) which makes the system frequency adaptive. The method uses the vectorial properties of the three-phase input signal in the αβ reference frame in order to obtain the different harmonic components. The MAVF-FLL is fully designed and analyzed, addressing the tuning procedure in order to obtain the desired and predefined performance. The proposed algorithm is evaluated by both simulation and experimental results, demonstrating its ability to perform as required for detecting different harmonic components under a highly unbalanced and distorted input grid voltage