Post-­‐occupancy monitoring of two flats in Madrid: development and assessment of a mixed methods methodology

Recent research has shown large differences between the expected and the actual energy consumption in buildings. The differences have been attributed partially, to the assumptions made during the design phase of buildings when simulation methods are employed. More accurate occupancy profiles on building operation could help to carry out more precise building performance calculations. This study focuses on the post-occupancy evaluation of two apartments, one renovated and one non renovated, in Madrid within the same building complex. The aim of this paper is to present an application of the mixed-methods methodology (Creswell, 2007) to assess thermal comfort and occupancy practices used in the case studies, and to discuss the shortcomings and opportunities associated with it. The mixed-methods methodology offers strategies for integrating qualitative and quantitative methods to investigate complex phenomena. This approach is expected to contribute to the growing knowledge of occupants’ behaviour and building performance by explaining the differences observed between energy consumption and thermal comfort in relation to people’s saving and comfort practices and the related experiences, preferences and values.

A combined measure for quantifying and qualifying the topology preservation of growing self-organizing maps

The Self-OrganizingMap (SOM) is a neural network model that performs an ordered projection of a high dimensional input space in a low-dimensional topological structure. The process in which such mapping is formed is defined by the SOM algorithm, which is a competitive, unsupervised and nonparametric method, since it does not make any assumption about the input data distribution. The feature maps provided by this algorithm have been successfully applied for vector quantization, clustering and high dimensional data visualization processes. However, the initialization of the network topology and the selection of the SOM training parameters are two difficult tasks caused by the unknown distribution of the input signals. A misconfiguration of these parameters can generate a feature map of low-quality, so it is necessary to have some measure of the degree of adaptation of the SOM network to the input data model. The topologypreservation is the most common concept used to implement this measure. Several qualitative and quantitative methods have been proposed for measuring the degree of SOM topologypreservation, particularly using Kohonen's model. In this work, two methods for measuring the topologypreservation of the Growing Cell Structures (GCSs) model are proposed: the topographic function and the topology preserving map

De los proyectos al programa en el ámbito público: nuevo modelo de evaluación del empleo en la Comunidad de Madrid.

Regarding different programmes belonging to the public sphere, it is essential to have proper tools able to quickly provide accurate data related to impacts generated by its projects. This aspect, along with the actual use of this data is essential for proper planning. This communication presents the system designed for project-based evaluation of the employment programs in the Community of Madrid. This system aims to provide fast and reliable information by relying on a combination of qualitative and quantitative methods from existing information and structures. Another contribution of the designed system is the implementation of the Empowerment Evaluation as a tool to encourage the incorporation of evaluation results to the planning processes in a systematic way.

Multispectral microscopy and quantitative texture

CAMEVA SYSTEM Automated optical identification of ore minerals in polished samples using multispectral digital images Support for basic ore microscopy / ore identification Geometallurgy: Automated system for quantitative mineralogy applications, more efficient than manual methods and less expensive than SEM systems