Mining recurring concepts in a dynamic feature space

Most data stream classification techniques assume that the underlying feature space is static. However, in real-world applications the set of features and their relevance to the target concept may change over time. In addition, when the underlying concepts reappear, reusing previously learnt models can enhance the learning process in terms of accuracy and processing time at the expense of manageable memory consumption. In this paper, we propose mining recurring concepts in a dynamic feature space (MReC-DFS), a data stream classification system to address the challenges of learning recurring concepts in a dynamic feature space while simultaneously reducing the memory cost associated with storing past models. MReC-DFS is able to detect and adapt to concept changes using the performance of the learning process and contextual information. To handle recurring concepts, stored models are combined in a dynamically weighted ensemble. Incremental feature selection is performed to reduce the combined feature space. This contribution allows MReC-DFS to store only the features most relevant to the learnt concepts, which in turn increases the memory efficiency of the technique. In addition, an incremental feature selection method is proposed that dynamically determines the threshold between relevant and irrelevant features. Experimental results demonstrating the high accuracy of MReC-DFS compared with state-of-the-art techniques on a variety of real datasets are presented. The results also show the superior memory efficiency of MReC-DFS.

Detecting Good Practices and Pitfalls when Publishing Vocabularies on the Web

The uptake of Linked Data (LD) has promoted the proliferation of datasets and their associated ontologies bringing their semantic to the data being published. These ontologies should be evaluated at different stages, both during their development and their publication. As important as correctly modelling the intended part of the world to be captured in an ontology, is publishing, sharing and facilitating the (re)use of the obtained model. In this paper, 11 evaluation characteristics, with respect to publish, share and facilitate the reuse, are proposed. In particular, 6 good practices and 5 pitfalls are presented, together with their associated detection methods. In addition, a grid-based rating system is generated. Both contributions, the set of evaluation characteristics and the grid system, could be useful for ontologists in order to reuse existing LD vocabularies or to check the one being built.

Clasificación de imágenes dermatoscópicas

Este proyecto presenta un software para el análisis de imágenes dermatoscópicas correspondiente a lesiones melanocíticas, con el fin de clasificarlas entre lesiones benignas y melanoma. El sistema realiza una segmentación automática de la lesión y la procesa en varas etapas, extrayendo características de relevancia diagnóstica: asimetría, colores, irregularidad del borde, y la presencia de estructuras como redes pigmentadas atípicas o velo azul-blanquecino. Proporciona además una herramienta para el etiquetado manual de estructuras adicionales. La clasificación automática de las lesiones se realiza en base a los métodos de diagnóstico más comúnmente utilizados: las reglas ABCD, Menzies, 7-point checklist, CASH y CHAOS & CLUES. El sistema de clasificación se evalúa sobre una base de datos de imágenes dermatoscópicas, y se realiza una comparativa de los resultados obtenidos por cada método de diagnóstico. ABSTRACT. This project presents a software for the analysis of dermoscopic images of melanocytic lesions, and their classification into benign lesions and melanoma. The system performs automatic segmentation of the lesion and goes through several stages of extraction of certain characteristics relevant to the diagnosis, such as asymmetry, border irregularity, or presence of structures like atypical pigmented network or blue-whitish veil. Automatic classification of the lesions is accomplished by means of the most commonly used diagnostic methods, such as ABCD and Menzies's rules, the 7-point checklist, CASH, and CHAOS & CLUES. The classification system is evaluated by using a dermoscopic image database, and a comparison of the results yielded by the different diagnostic methods is performed.

Sistema de adquisición de datos para una aplicación de detección del ruido de reversa en tiempo real

Entre todas las fuentes de ruido, la activación de la propulsión en reversa de un avión después de aterrizar es conocida por las autoridades del aeropuerto como una causa importante de impacto acústico, molestias y quejas en las proximidades vecinas de los aeropuertos. Por ello, muchos de los aeropuertos de todo el mundo han establecido restricciones en el uso de la reversa, especialmente en las horas de la noche. Una forma de reducir el impacto acústico en las actividades aeroportuarias es implementar herramientas eficaces para la detección de ruido en reversa en los aeropuertos. Para este proyecto de fin de carrera, aplicando la metodología TREND (Thrust Reverser Noise Detection), se pretende desarrollar un sistema software capaz de determinar que una aeronave que aterrice en la pista active el frenado en reversa en tiempo real. Para el diseño de la aplicación se plantea un modelo software, que se compone de dos módulos:  El módulo de adquisición de señales acústicas, simula un sistema de captación por señales de audio. Éste módulo obtiene muestra de señales estéreo de ficheros de audio de formato “.WAV” o del sistema de captación, para acondicionar las muestras de audio y enviarlas al siguiente módulo. El sistema de captación (array de micrófonos), se encuentra situado en una localización cercana a la pista de aterrizaje.  El módulo de procesado busca los eventos de detección aplicando la metodología TREND con las muestras acústicas que recibe del módulo de adquisición. La metodología TREND describe la búsqueda de dos eventos sonoros llamados evento 1 (EV1) y evento 2 (EV2); el primero de ellos, es el evento que se activa cuando una aeronave aterriza discriminando otros eventos sonoros como despegues de aviones y otros sonidos de fondo, mientras que el segundo, se producirá después del evento 1, sólo cuando la aeronave utilice la reversa para frenar. Para determinar la detección del evento 1, es necesario discriminar las señales ajenas al aterrizaje aplicando un filtrado en la señal capturada, después, se aplicará un detector de umbral del nivel de presión sonora y por último, se determina la procedencia de la fuente de sonido con respecto al sistema de captación. En el caso de la detección del evento 2, está basada en la implementación de umbrales en la evolución temporal del nivel de potencia acústica aplicando el modelo de propagación inversa, con ayuda del cálculo de la estimación de la distancia en cada instante de tiempo mientras el avión recorre la pista de aterrizaje. Con cada aterrizaje detectado se realiza una grabación que se archiva en una carpeta específica y todos los datos adquiridos, son registrados por la aplicación software en un fichero de texto. ABSTRACT. Among all noise sources, the activation of reverse thrust to slow the aircraft after landing is considered as an important cause of noise pollution by the airport authorities, as well as complaints and annoyance in the airport´s nearby locations. Therefore, many airports around the globe have restricted the use of reverse thrust, especially during the evening hours. One way to reduce noise impact on airport activities is the implementation of effective tools that deal with reverse noise detection. This Final Project aims to the development of a software system capable of detecting if an aircraft landing on the runway activates reverse thrust on real time, using the TREND (Thrust Reverser Noise Detection) methodology. To design this application, a two modules model is proposed: • The acoustic signals obtainment module, which simulates an audio waves based catchment system. This module obtains stereo signal samples from “.WAV” audio files or the catchment system in order to prepare these audio samples and send them to the next module. The catchment system (a microphone array) is located on a place near the landing runway. • The processing module, which looks for detection events among the acoustic samples received from the other module, using the TREND methodology. The TREND methodology describes the search of two sounds events named event 1 (EV1) and event 2 (EV2). The first is the event activated by a landing plane, discriminating other sound events such as background noises or taking off planes; the second one will occur after event one only when the aircraft uses reverse to slow down. To determine event 1 detection, signals outside the landing must be discriminated using a filter on the catched signal. A pressure level´s threshold detector will be used on the signal afterwards. Finally, the origin of the sound source is determined regarding the catchment system. The detection of event 2 is based on threshold implementations in the temporal evolution of the acoustic power´s level by using the inverse propagation model and calculating the distance estimation at each time step while the plane goes on the landing runway. A recording is made every time a landing is detected, which is stored in a folder. All acquired data are registered by the software application on a text file.

Selected papers from OECD-NEA PSBT benchmark

Historically, the prediction of safety margins has been based on system level thermal-hydraulic calculations employing suitable empirical formulations for assembly specific geometries and fuel-element grid spacers. These works have assessed response, margins, and consequences for the system based on one-dimensional two-fluid or drift-flux type thermalhydraulics formulations with fuel-vendor specific hydraulic losses and heat transfer characteristics for various fuel assemblies, including the so-called hot channel. Analysis of the hot channel gives important information on flow rates, fuel element centerline temperature, fuel sheath temperature, and margin to the departure from nucleate boiling. Given the reliance of the above approaches on empirical formulations obtained from complex and often difficult experiments, there is significant interest in obtaining reliable and accurate results from computation tools which employ more fundamental empirical relationships which can be obtained from subsets of the domain or from other scaled experiments.

Asymptotic optimality of RESTART estimators in highly dependable systems

Abstract We consider a wide class of models that includes the highly reliable Markovian systems (HRMS) often used to represent the evolution of multi-component systems in reliability settings. Repair times and component lifetimes are random variables that follow a general distribution, and the repair service adopts a priority repair rule based on system failure risk. Since crude simulation has proved to be inefficient for highly-dependable systems, the RESTART method is used for the estimation of steady-state unavailability and other reliability measures. In this method, a number of simulation retrials are performed when the process enters regions of the state space where the chance of occurrence of a rare event (e.g., a system failure) is higher. The main difficulty involved in applying this method is finding a suitable function, called the importance function, to define the regions. In this paper we introduce an importance function which, for unbalanced systems, represents a great improvement over the importance function used in previous papers. We also demonstrate the asymptotic optimality of RESTART estimators in these models. Several examples are presented to show the effectiveness of the new approach, and probabilities up to the order of 10-42 are accurately estimated with little computational effort.

Viticultura y Cambio Climático en España: Vulnerabilidad en las distintas regiones y estrategias de adaptación frente al desarrollo de nuevas políticas

El presente trabajo realiza un análisis de la vulnerabilidad de la viticultura en España ante el Cambio Climático que contribuya a la mejora de la capacidad de respuesta del sector vitivinícola a la hora de afrontar los retos de la globalización. Para ello se analiza el impacto que puede tener el Cambio Climático en primer lugar sobre determinados riesgos ocasionados por eventos climáticos adversos relacionados con extremos climáticos y en segundo lugar, sobre los principales índices agro-climáticos definidos en el Sistema de Clasificación Climática Multicriterio Geoviticultura (MCGG), que permiten clasificar las zonas desde un punto de vista de su potencial climático. Para el estudio de las condiciones climáticas se han utilizado los escenarios de Cambio Climático regionalizados del proyecto ESCENA, desarrollados dentro del Plan Nacional de Adaptación al Cambio Climático (PNACC) con el fin de promover iniciativas de anticipación y respuesta al Cambio Climático hasta el año 2050. Como parte clave del estudio de la vulnerabilidad, en segundo lugar se miden las necesidades de adaptación para 56 Denominaciones de Origen Protegidas, definidas por los impactos y de acuerdo con un análisis de sensibilidad desarrollado en este trabajo. De este análisis se desprende que los esfuerzos de adaptación se deberían centrar en el mantenimiento de la calidad sobre todo para mejorar las condiciones en la época de maduración en los viñedos de la mitad norte, mientras que en las zonas de la mitad sur y del arco mediterráneo, además deberían buscar mantener la productividad en la viticultura. Los esfuerzos deberían ser más intensos en esta zona sur y también estarían sujetos a más limitaciones, ya que por ejemplo el riego, que podría llegar a ser casi obligatorio para mantener el cultivo, se enfrentaría a un contexto de mayor competencia y escasez de recursos hídricos. La capacidad de afrontar estas necesidades de adaptación determinará la vulnerabilidad del viñedo en cada zona en el futuro. Esta capacidad está definida por las propias necesidades y una serie de condicionantes sociales y de limitaciones legales, como las impuestas por las propias Denominaciones de Origen, o medioambientales, como la limitación del uso de agua. El desarrollo de estrategias que aseguren una utilización sostenible de los recursos hídricos, así como el apoyo de las Administraciones dentro de la nueva Política Agraria Común (PAC) pueden mejorar esta capacidad de adaptación y con ello disminuir la vulnerabilidad. ABSTRACT This paper analyzes the vulnerability of viticulture in Spain on Climate Change in order to improve the adaptive capacity of the wine sector to meet the diverse challenges of globalization. The risks to quality and quantity are explored by considering bioclimatic indices with specific emphasis on the Protected Designation of Origin areas that produce the premium winegrapes. The Indices selected represents risks caused by adverse climatic events related to climate extremes, and requirements of varieties and vintage quality in the case of those used in the Multicriteria Climatic Classification System. (MCCS). To study the climatic conditions, an ensemble of Regional Climate Models (RCMs) of ESCENA project, developed in the framework of the Spanish Plan for Regional Climate Change Scenarios (PNACC-2012) have been used As a key part of the study of vulnerability risks and opportunities are linked to adaptation needs across the Spanish territory. Adaptation efforts are calculated as proportional to the magnitude of change and according to a sensitivity analysis for 56 protected designations of origin. This analysis shows that adaptation efforts should focus on improving conditions in the ripening period to maintain quality in the vineyards of the northern half of Iberian Peninsula, while in areas of the southern half and in the Mediterranean basin, also should seek to maintain productivity of viticulture. Therefore, efforts should be more intense in the Southern and Eastern part, and may also be subject to other limitations, such as irrigation, which could become almost mandatory to keep growing, would face a context of increased competition and lack of resources water. The ability to meet these needs will determine the vulnerability of the vineyard in each region in the future. This capability is defined also by a number of social factors and legal limitations such as environmental regulations, limited water resources or those imposed by their own Designation of Origin. The development of strategies to ensure sustainable use of water resources and the support schemes in the new Common Agricultural Policy (CAP) can improve the resilience and thus reduce vulnerability.