Environmental Protection And Public Procurement

European Union law has decisively influenced the development and recent evolution of national legislation on environment and on public procurement. One of the most important objetives of European Directives on public procurement have been to introduce environmental protection. But the principles of objectivity, transparency, publicity and non discrimination must be respect in all cases. These principles constitute at present the foundation of all public rules on procurement and are characterized by their transversality as they cover and are manifest in all stages of the contract, preparation and performance

Technical Administrative Legal And Environmental Protection

Environmental law uses various techniques or tools to achieve its aims and objectives and for the protection of individual rights and interests involved. Administrative techniques can be systematized in terms of their content, distinguishing between preventive intervention techniques, development tools, techniques of repression, environmental planning, trading instruments and complementary economic measures

Fracture test of a Gothic ribbed vault

A Gothic ribbed vault has been built at the School of Architecture of Madrid in order to investigate the construction complexities of this kind of vaults. The ribbed vault is described in the manuscript of Alonso de Vandelvira, and its shape was reconstructed making using the drawings this architect from the 16th century. The fracture test was carried on by loading the central keystone of the vault until its collapse took place. The experiment was filmed and by doing so, it was possible to observe the failure mechanism of the vault. At the same time, it was interesting to compare this collapse experience with the results obtained using two different me-thods. First, a stability calculation was carried out through graphic statics, and secondly a calcu-lation was performed using the rigid-block analysis method. The focus of this paper is to show and analyze the results of both studies

Predicting High-Value Customers in a Portuguese Wine Company

Wine companies operate in a very competitive environment in which they must provide better-customised services and products to survive and gain advantage. The high customer turnover rate is a problem for these companies. This work aims to provide wine companies with new knowledge about customers that help to retain the existing ones. The study applies a collected dataset from a transaction database in a medium-sized ortuguese wine company to determinate: (1) customer lifetime value; (2) cluster customer value as output (customer loyalty). The measurement of the customer lifetime value (CLV) was analysed using the Pareto/NBD model and gamma-gamma model. Clustering techniques are employed to segment customers according to Recency, Frequency, and Monetary (RFM) values. Study findings show that exists three clusters with different interest to the marketing strategies, identifying the high-value customers, to target using marketing to increase their lifetime value effectively. The implications for the marketing strategy decisions is that using techniques based on the RFM model can make the most from data of customers and transactions databases and thus create sustainable advantages.info:eu-repo/semantics/publishedVersio

Multilabel Prototype Generation for Data Reduction in k-Nearest Neighbour classification

Prototype Generation (PG) methods are typically considered for improving the efficiency of the $k$-Nearest Neighbour ($k$NN) classifier when tackling high-size corpora. Such approaches aim at generating a reduced version of the corpus without decreasing the classification performance when compared to the initial set. Despite their large application in multiclass scenarios, very few works have addressed the proposal of PG methods for the multilabel space. In this regard, this work presents the novel adaptation of four multiclass PG strategies to the multilabel case. These proposals are evaluated with three multilabel $k$NN-based classifiers, 12 corpora comprising a varied range of domains and corpus sizes, and different noise scenarios artificially induced in the data. The results obtained show that the proposed adaptations are capable of significantly improving -- both in terms of efficiency and classification performance -- the only reference multilabel PG work in the literature as well as the case in which no PG method is applied, also presenting a statistically superior robustness in noisy scenarios. Moreover, these novel PG strategies allow prioritising either the efficiency or efficacy criteria through its configuration depending on the target scenario, hence covering a wide area in the solution space not previously filled by other works

Multilabel Prototype Generation for data reduction in K-Nearest Neighbour classification

Prototype Generation (PG) methods are typically considered for improving the efficiency of the k-Nearest Neighbour (kNN) classifier when tackling high-size corpora. Such approaches aim at generating a reduced version of the corpus without decreasing the classification performance when compared to the initial set. Despite their large application in multiclass scenarios, very few works have addressed the proposal of PG methods for the multilabel space. In this regard, this work presents the novel adaptation of four multiclass PG strategies to the multilabel case. These proposals are evaluated with three multilabel kNN-based classifiers, 12 corpora comprising a varied range of domains and corpus sizes, and different noise scenarios artificially induced in the data. The results obtained show that the proposed adaptations are capable of significantly improving—both in terms of efficiency and classification performance—the only reference multilabel PG work in the literature as well as the case in which no PG method is applied, also presenting statistically superior robustness in noisy scenarios. Moreover, these novel PG strategies allow prioritising either the efficiency or efficacy criteria through its configuration depending on the target scenario, hence covering a wide area in the solution space not previously filled by other works.This research was partially funded by the Spanish Ministerio de Ciencia e Innovación through the MultiScore (PID2020-118447RA-I00) and DOREMI (TED2021-132103A-I00) projects. The first author is supported by grant APOSTD/2020/256 from “Programa I+D+i de la Generalitat Valenciana”

Book review: Ralph R. Frerichs: Deadly river - Cholera and cover-up in post-earthquake

As most of PV systems, CPV systems are also affected by mismatching losses, particularly due to misalignment of optics and receivers. As a result, module level power electronics can help to increase their energy yield by making every CPV module deliver it maximum power at the output. Among the different alternatives, solutions based on DC power optimizers exhibit higher conversion efficiencies and lower costs than microinverters. However, while microinverters ensure optimal operation independently from the operating conditions, system design with DC power optimizers must be carefully examined to avoid potential underperformance. This paper describes not only the customized design and validation of a high-efficiency and economical DC power optimizer for HCPV systems, but also a comprehensive analysis of the whole system design to optimize its production under expected working conditions.Main design specifications (electrical parameters of module and number of modules per tracker), as well as supporting information for mismatching losses estimation, have been provided by ASSE within CPVMatch project. This work has received funding from the European Union’s Horizon 2020 research and innovation programme within the project CPVMatch under grant agreement No 640873

Stochastic Technical Losses Analysis of Smart Grids under Uncertain Demand

This paper has been presented at: 53rd International Universities Power Engineering ConferenceTechnical losses of smart grids can be computed using the customer's smart meter measurements (active and reactive energy) and the energy measurement registered by the Low Voltage (LV) supervisor deployed at secondary substations. However, in some LV networks, some customers do not provide information regarding the energy consumed and produced in real time. This fact complicates the calculation of technical losses because this information is necessary for estimating the load demand for this subset of customers. In this paper, a stochastic approach is proposed for the estimation of technical losses in smart grids under uncertain load demands (e.g., non-telemetered customers and uncertain smart meters readings). Load demand estimation of non-metered customers was performed by means of a top-down approach. Intra-hour load demand profiles of customers were synthetically generated by applying a Markov process. The data and network used in this process corresponded to the roll-out deployed by the Spanish Research and Development (R&D) demonstration project OSIRIS.This work has been partly funded by the Spanish Ministry of Economy and Competitiveness through the National Program for Research Aimed at the Challenges of Society under the project OSIRIS (RTC-2014-1556-3)