The process of abandonment of the corrals at the district of Famorca: an etnoarchaeological analysis of its effect on the material whole.

Els diferents graus d’abandonament que ofereixen els corrals al terme de Famorca (Alacant) donen peu a un estudi etnoarqueològic dels conjunts materials que s’hi troben. La intenció de l’estudi és veure els efectes del postabandonament sobre el conjunt material bàsic d’aquestes estructures ramaderes tradicionals.Los diferentes grados de abandono en que se encuentran los corrales en el término municipal de Famorca (Alacant) sirven de base para un estudio etnoarqueológico de los conjuntos materiales que presentan. Con este estudio se pretende analizar los efectos del post-abandonamiento sobre el conjunto material “base” de estas estructuras tradicionalesThe present essay analyzes the effect of post-abandonment processes on the material assemblage of corrals in the Famorca distric (Alacant). The study aims at assessing the effects of the post-abandonment on the original material assemblage of these traditonal sites

Sensor selection based on principal component analysis for fault detection in wind turbines

Growing interest for improving the reliability of safety-critical structures, such as wind turbines, has led to the advancement of structural health monitoring (SHM). Existing techniques for fault detection can be broadly classified into two major categories: model-based methods and signal processing-based methods. This work focuses in the signal-processing-based fault detection by using principal component analysis (PCA) as a way to condense and extract information from the collected signals. In particular, the goal of this work is to select a reduced number of sensors to be used. From a practical point of view, a reduced number of sensors installed in the structure leads to a reduced cost of installation and maintenance. Besides, from a computational point of view, less sensors implies lower computing time, thus the detection time is shortened. The overall strategy is to firstly create a PCA model measuring a healthy wind turbine. Secondly, with the model, and for each fault scenario and each possible subset of sensors, it measures the Euclidean distance between the arithmetic mean of the projections into the PCA model that come from the healthy wind turbine and the mean of the projections that come from the faulty one. Finally, it finds the subset of sensors that separate the most the data coming from the healthy wind turbine and the data coming from the faulty one. Numerical simulations using a sophisticated wind turbine model (a modern 5MW turbine implemented in the FAST software) show the performance of the proposed method under actuators (pitch and torque) and sensors (pitch angle measurement) faults of different type: fixed value, gain factor, offset and changed dynamics.Postprint (published version

Learning to count with deep object features

Learning to count is a learning strategy that has been recently proposed in the literature for dealing with problems where estimating the number of object instances in a scene is the final objective. In this framework, the task of learning to detect and localize individual object instances is seen as a harder task that can be evaded by casting the problem as that of computing a regression value from hand-crafted image features. In this paper we explore the features that are learned when training a counting convolutional neural network in order to understand their underlying representation. To this end we define a counting problem for MNIST data and show that the internal representation of the network is able to classify digits in spite of the fact that no direct supervision was provided for them during training. We also present preliminary results about a deep network that is able to count the number of pedestrians in a scene.Comment: This paper has been accepted at Deep Vision Workshop at CVPR 201

Wind turbine condition monitoring strategy through multiway PCA and multivariate inference

This article states a condition monitoring strategy for wind turbines using a statistical data-driven modeling approach by means of supervisory control and data acquisition (SCADA) data. Initially, a baseline data-based model is obtained from the healthy wind turbine by means of multiway principal component analysis (MPCA). Then, when the wind turbine is monitorized, new data is acquired and projected into the baseline MPCA model space. The acquired SCADA data are treated as a random process given the random nature of the turbulent wind. The objective is to decide if the multivariate distribution that is obtained from the wind turbine to be analyzed (healthy or not) is related to the baseline one. To achieve this goal, a test for the equality of population means is performed. Finally, the results of the test can determine that the hypothesis is rejected (and the wind turbine is faulty) or that there is no evidence to suggest that the two means are different, so the wind turbine can be considered as healthy. The methodology is evaluated on a wind turbine fault detection benchmark that uses a 5 MW high-fidelity wind turbine model and a set of eight realistic fault scenarios. It is noteworthy that the results, for the presented methodology, show that for a wide range of significance, a in [1%, 13%], the percentage of correct decisions is kept at 100%; thus it is a promising tool for real-time wind turbine condition monitoring.Peer ReviewedPostprint (published version

Valencian museums of ethnology

El artículo repasa el panorama de los museos de etnología valencianos desde diferentes perspectivas. En una primera parte del trabajo, se aportan algunos datos de tipo histórico sobre los considerados “primeros” museos de etnografía, y se propone un análisis de su distribución geográfica, así como de las principales temáticas reflejadas en estas instituciones. La situación de la museografía etnográfica valenciana se describe en la segunda mitad del artículo, planteando un panorama diverso en el que conviven planteamientos clásicos con apuestas innovadoras.This paper aims to review the panorama of the ethnographic museums in the Valencian region (Mediterranean Spain). In the first part of the work, some historic data on the creation of ethnographic museums in the area is shown. Along with these, the geographic distribution as well as thematic definition of this type of museums is analyzed. Finally, the second part of the paper is devoted to describe the museographic present of these institutions in the Valencian country area

Damage diagnosis for offshore fixed wind turbines

This paper proposes a damage diagnosis strategy to detect and classify different type of damages in a laboratory offshore-fixed wind turbine model. The proposed method combines an accelerometer sensor network attached to the structure with a conceived algorithm based on principal component analysis (PCA) with quadratic discriminant analysis (QDA). The paradigm of structural health monitoring can be undertaken as a pattern recognition problem (comparison between the data collected from the healthy structure and the current structure to diagnose given a known excitation). However, in this work, as the strategy is designed for wind turbines, only the output data from the sensors is used but the excitation is assumed unknown (as in reality is provided by the wind). The proposed methodology is tested in an experimental laboratory tower modeling an offshore-fixed jacked-type wind turbine. The obtained results show the reliability of the proposed approach.Peer ReviewedPostprint (published version

Demystify production to return cinema to the people : The Mining Film Workshop (Bolivia, 1983)

Peer reviewedPublisher PD

Warmi : the first Peruvian women-led film collective

Warmi Cine y Video, the first group of Peruvian women filmmakers, was founded in Lima in 1989. They released their last work in 1998. The 1990s were an agitated period in Peru. The totalitarian drift of the state, under a de facto dictatorship headed by Alberto Fujimori, created an asphyxiating atmosphere. Political agendas focused on the bloody internal armed conflict (1980-2000). In that troubled context —without ignoring it but determined to highlight what did not make the headlines— this collective, led by María Barea, managed to make a series of films that constituted a new kind of discourse in Peru due to their ability to mettre-en-scène the lives of unacknowledged lower class women.Peer reviewe