Using data differently and using different data

The lack of adequate measures is often an impediment to robust policy evaluation. We discuss three approaches to measurement and data usage that have the potential to improve the way we conduct impact evaluations. First, the creation of new measures, when no adequate ones are available. Second, the use of multiple measures when a single one is not appropriate. And third, the use of machine learning algorithms to evaluate and understand programme impacts. We motivate the relevance of each of the categories by providing examples where they have proved useful in the past. We discuss the challenges and risks involved in each strategy and conclude with an outline of promising directions for future work

Toward Automated Feature Extraction for Deep Learning Classification of Electrocardiogram Signals

Many recent studies have focused on the automatic classification of electrocardiogram (ECG) signals using deep learning (DL) methods. Most rely on existing complex DL methods, such as transfer learning or providing the models with carefully designed extracted features based on domain knowledge. A common assumption is that the deeper and more complex the DL model is, the better it learns. In this study, we propose two different DL models for automatic feature extraction from ECG signals for classification tasks: A CNN-LSTM hybrid model and an attention/transformer-based model with wavelet transform for the dimensional embedding. Both of the models extract the features from time series at the initial layers of the neural networks and can obtain performance at least equal to, if not greater than, many contemporary deep neural networks. To validate our hypothesis, we used three publicly available data-sets to evaluate the proposed models. Our model achieved a benchmark accuracy of 99.92% for fall detection and 99.93% for the PTB database for myocardial infarction versus normal heartbeat classification

Inertización y valorización de polvos de lijado de barnices procedentes de residuos de la industria de la madera

The present article describes the findings of the first stageof the analysis of xiloarcilla, a material made of clayand a wood industry by-product, namely the wood andpolyurethane varnish powder pump-suctioned off woodcomponents during sanding and polishing. This powderwas added to the clay in proportions of from 1% to 5%by weight. The prime materials as well as the xiloarcillacompound were characterized, in the latter case primarilyto determine its physical-mechanical properties andchemical and environmental feasibility as a constructionmaterial.En este articulo se presentan los resultados obtenidos,en una primera etapa, del estudio del material que denominaremoscomo xiloarcilla, compuesto por arcilla y porun subproducto de las industrias de la madera, que eneste caso son los polvos del lijado y del barnizado y excedentesde estos productos utilizados en el acabado demuchos componentes de madera (PLB), estos polvos seadicionaron a la arcilla en cantidades entre el 1% y el5% del peso total del compuesto. Se realizo un estudiode caracterizacion de los materiales aislados y posteriormentedel compuesto xiloarcilla, con enfasis en el comportamientofisico-mecanico y su respuesta quimica ymedioambiental, como material de construccion

Good and bad practices in pv plants

The PVCROPS project (PhotoVolta ic Cost r€duction, Reliability, Operational performance, Prediction and Simulation), cofinanced by European Commission in the frame of Seventh Framework Programme, has compiled in the “Good and bad practices: Manual to improve the quality and reduce the cost of PV systems” a collection of good and bad practices in actual PV plants . All the situations it collects represent the state-of-the-art of existing PV installations all around Europe. They show how the different parts of an installation can be implem ented properly or not. The aim of this manual is to represent a reference text which can help any PV actor (installers, electricians, maintenance operators, owners, etc.) not only to check and improve an already existing installation but will also, and mainly, avoid the previously known bad practices for the construction of a new PV installation. Thus, solving a priori the known errors, new PV installations will be more reliable, efficient and cost-effective and can recover the initial investment in a shorter time. The manual is going to be free available in the PVCROPS website in several languages

Fall Detection from Electrocardiogram (ECG) Signals and Classification by Deep Transfer Learning

Fall is a prominent issue due to its severe consequences both physically and mentally. Fall detection and prevention is a critical area of research because it can help elderly people to depend less on caregivers and allow them to live and move more independently. Using electrocardiograms (ECG) signals independently for fall detection and activity classification is a novel approach used in this paper. An algorithm has been proposed which uses pre-trained convolutional neural networks AlexNet and GoogLeNet as a classifier between the fall and no fall scenarios using electrocardiogram signals. The ECGs for both falling and no falling cases were obtained as part of the study using eight volunteers. The signals are pre-processed using an elliptical filter for signal noises such as baseline wander and power-line interface. As feature extractors, frequency-time representations (scalograms) were obtained by applying a continuous wavelet transform on the filtered ECG signals. These scalograms were used as inputs to the neural network and a significant validation accuracy of 98.08% was achieved in the first model. The trained model is able to distinguish ECGs with a fall activity from an ECG with a no fall activity with an accuracy of 98.02%. For the verification of the robustness of the proposed algorithm, our experimental dataset was augmented by adding two different publicly available datasets to it. The second model can classify fall, daily activities and no activities with an accuracy of 98.44%. These models were developed by transfer learning from the domain of real images to the medical images. In comparison to traditional deep learning approaches, the transfer learning not only avoids "reinventing the wheel," but also presents a lightweight solution to otherwise computationally heavy problems.This research was funded by the research support program of Fb2, Frankfurt University of Applied Sciences. The research of D.G.-U. has been supported in part by the Spanish MICINN under grants PGC2018-096504-B-C33 and RTI2018-100754-B-I00, the European Union under the 2014-2020 ERDF Operational Programme and the Department of Economy, Knowledge, Business and University of the Regional Government of Andalusia (project FEDER-UCA18-108393). The research of I.M.-B. has been supported in part by the European Commission (ERDF), the Spanish Ministry of Science, Innovation and Universities [RTI2018-093608-BC33]

Análisis y propuesta de mejoras para la eficiencia energética del edificio principal del Instituto c.c. Eduardo Torroja-CSIC

As part of the 80th anniversary of IETcc-CSIC, a proposal for the rehabilitation of the 1953 building is made. The analysis of the main building’s energy performance concludes that it is not energy efficient. Energy efficiency improvement measures based on European directives are proposed, It is recommended to incorporate them step by step, starting with passive measures to reduce energy needs. Afterwards active measures, such as improving the performance of facilities, are proposed, so that the least possible amount of final energy is used to meet the comfort standards. To complete the operation, the use of renewable energy sources is proposed to reduce the consumption of non-renewable primary energy. Energy and building rehabilitation improvement measures in the IETcc-CSIC should be demonstrators for other public buildings with heritage values.En el marco del 80 aniversario del IETcc-CSIC se elabora una propuesta para la rehabilitación del edificio construido en 1953. Partiendo del análisis del comportamiento energético del edificio principal, se concluye que este no es eficiente energéticamente. Se proponen mejoras para la eficiencia energética del edificio tomando en cuenta las directivas europeas. Se recomienda incorporar las mejoras de forma escalonada, comenzando por las medidas pasivas para reducir sus necesidades energéticas. A continuación se proponen medidas activas, como la mejora del rendimiento de las instalaciones, de manera que se emplee la menor cantidad posible de energía final para satisfacer el confort de los usuarios. Para completar la intervención se propone el uso de fuentes de generación de energías renovables en la parcela con el objetivo de reducir el consumo de energía primaria no renovable. Las acciones para la rehabilitación energética e integral del edificio del IETcc-CSIC, deben ser demostradoras para otros edificios públicos con valores patrimoniales

El dispositivo habitable

This paper explains the main concepts supporting the project "Habitar el Dispositivo" which was awarded a prize in the International Competition "25 Bioclimatical Houses" promoted by the "Instituto Tecnológico de Energías Renovables of Tenerife " and organized by the "Colegio de Arquitectos de Canarias" and sponsored by the "International Union of Architects". As opposed to bioclimatical houses which are the result of adding bioclimatical devices to an architectural project, the integration of bioclimatical and architectural concepts in a livable device is proposed. A digital model of the project was built to analyze sunlight and shadow behavior and computer simulations permitted to determine thermal performance. Average thermal satisfaction was 89.75 % during typical summer and winter 24 hour periods.Se presentan los conceptos fundamentales que respaldan la propuesta "Habitar el Dispositivo", premiada en el Concurso Internacional "25 Viviendas Bioclimáticas" promovido por el "Instituto Tecnológico de Energías Renovables del Cabildo de Tenerife", organizado por el "Colegio de Arquitectos de Canarias" y homologado por la "Unión Internacional de Arquitectos". Al contrario de la solución de añadir dispositivos a un proyecto de arquitectura, la propuesta integra conceptos bioclimáticos y arquitectónicos en un dispositivo habitable. Un modelo digital de la edificación permitió estudiar su volumetría y soleamiento en diferentes períodos del año, mientras que su comportamiento térmico se analizó con un programa de simulación en régimen dinámico. El promedio de personas satisfechas en días típicos de verano e invierno fue del 89,75 %

Energy needs and vulnerability estimation at an urban scale for residential neighbourhoods heating in Madrid (Spain)

Urban areas renovation may lead to problematic situations associated with financing of the works in absence of a detailed analysis of the distribution of resources. An analysis of the needs and the obstacles in achieving buildings refurbishment to improve their energy efficiency must be observed. Buildings requiring energy refurbishment will be those with poor construction quality, not adapted to the new energy efficiency requirements. People with insufficient resources to deal with such actions will inhabit many of them. This paper proposes a model for energy needs assessment at an urban scale with the objective set on the refurbishment of residential buildings neighbourhoods, addressing comfort needs. In this sense, aspects of building energy vulnerability are explored as a prerequisite to the analysis of energy poverty in our cities and neighbourhoods. A methodology to characterize heating needs of urban areas is developed by using statistical data from the Spanish Census of Housing and Population. The superimposition of resulting demand values with demographic data allows introducing socioeconomic criteria in order to locate urban energy efficiency and fuel vulnerability. This information is useful in order to address specific public refurbishment strategies based on the reality of socioeconomic aspects of the neighbourhoods and the state of preservation of buildings

Cerramientos bioclimáticos para climas cálidos húmedos: la cuarta vivienda

In intertropical latitudes such as Venezuela with hot humid climates, building envelopes must reduce influence of solar radiation, and in these, roofs and windows must receive special attention. Venezuela is also the country with the highest energy consumption per capita in Iberoamérica, much of which is generated by air conditioning systems in residential buildings, and Maracaibo and the surrounding lake basin have some of the highest temperature and humidity values in Venezuela, which increase energy consumption even more. A bioclimatical house for this climate is proposed. This building incorporates principles from traditional indigenous, colonial and oil company houses in the Maracaibo lake basin to generate a new prototype, called the Fourth House.En climas cálidos húmedos como es el caso de grandes regiones de Venezuela, las envolventes deben reducir la influencia de la radiación solar y, por lo tanto, deben recibir atención especial. Venezuela es también el país con más alto consumo energético per capita en Iberoamérica, generado en su mayor parte por el uso de sistemas de aire acondicionado en las edificaciones residenciales. En Maracaibo y en los alrededores del Lago de Maracaibo se registran los valores más altos de temperatura y humedad en Venezuela, lo que incrementa, aún más, el consumo energético de las viviendas de estas regiones. La minimización del impacto de la radiación solar para lograr la reducción del consumo energético con un mayor bienestar térmico ha sido precisamente uno de los objetivos perseguidos con el desarrollo de una nueva vivienda bioclimática para la región del lago de Maracaibo. Esta incorpora principios de las tres viviendas bioclimáticas previas existentes en esa región: el palafito o vivienda tradicional indígena, la vivienda colonial republicana y la vivienda petrolera. Es por ello que esta vivienda ha sido llamada la Cuarta Vivienda