Abstract
A method is presented to determine the appropriate number of photovoltaic panels that should be installed in an end-user photovoltaic installation to guarantee the supply of energy to the load during the hours of solar radiation, according to factors such as the installation area and global solar radiation. Solar radiation is predicted by approximating the daily distribution of global irradiance through a Gaussian function, which is subsequently corrected using a heuristic approach. Meteorological parameters are used as input data such as the daily solar insolation and the maximum global irradiance for each day; this last parameter is obtained through an expert system based on fuzzy logic that was programmed and trained with the data of ambient temperature and relative humidity that were obtained in the processing stage. Output from this expert system is the predicted values of maximum radiation obtained for each day for a selectable time interval. With the predicted solar radiation, the generation of electrical energy from the photovoltaic panels is calculated. The load is randomly modeled from a pattern of the energy demand of the building to be powered by the photovoltaic system. The number of photovoltaic panels needed is found with the information acquired in the previous stages and the information of the energy demand of the load and the installation area. The results are the number of solar panels that would be needed at all hours of the day from which the radiation prediction was made.

Abstract
Building rehabilitation is a reality, and all phases of rehabilitation work need to be efficient and sustainable. Current procedures for assessing construction conditions are time-consuming, laborious and expensive and pose threats to the health and safety of engineers, especially when inspecting locations not easy to access. In an initial step, a survey of the condition of the building is carried out, which subsequently implies the elaboration of a report of existing pathologies, intervention solutions and associated costs. This survey involves an inspection of the site (through photographs and videos). This work aims to detect and locate cracks defects in images of painted facade walls of buildings. A VGG16 pre-trained model was evaluated first on a public database with cracked and not cracked concrete surfaces and then on a private database of images of painted building facades with and without cracks. The predicted activation maps were analysed with Grad-CAM methods to validate the models’ prediction. The proposed model achieved 99% accuracy on the concrete public dataset and 78% on the building's facade private dataset. The limitations and the future works are identified. © 2022, University of Cantabria - Building Technology R&D Group. All rights reserved.

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Purpose This paper aims to explore the changes imposed by the general data protection regulation (GDPR) on software engineering practices. The fundamental objective is to have a perception of the practices and phases that have experienced the greatest changes. Additionally, it aims to identify a set of good practices that can be adopted by software engineering companies. Design/methodology/approach This study uses a qualitative methodology through four case studies involving Portuguese software engineering companies. Two of these companies are small and medium enterprises (SMEs) while the other remaining two are micro-companies. The thematic analysis is adopted to identify patterns in the performed interviews. Findings The findings indicate that significant changes have occurred at all stages of software development. In particular, the initial stages of identifying requirements and modeling processes were the stages that experienced the greatest changes. On the opposite, the technical development phase has not noticeably changed but, nevertheless, it is necessary to look at the importance of training software developers for GDPR rules and practices. Research limitations/implications Two relevant limitations were identified as follows: only four case studies involving micro-companies and SMEs were considered, and only the traditional software development methodology was considered. The use of agile methodologies was not explored in this study and the findings can only be mainly applied to the waterfall model. Originality/value This study offers mainly practical contributions by identifying a set of challenges that are posed to software engineering companies by the implementation of GDPR. Through their knowledge, it is expected to help these companies to better prepare themselves and anticipate the challenges they will necessarily face.

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OBJECTIVES: Existing individual-level human data cover large populations on many dimensions such as lifestyle, demography, laboratory measures, clinical parameters, etc. Recent years have seen large investments in data catalogues to FAIRify data descriptions to capitalise on this great promise, i.e. make catalogue contents more Findable, Accessible, Interoperable and Reusable. However, their valuable diversity also created heterogeneity, which poses challenges to optimally exploit their richness. METHODS: In this opinion review, we analyse catalogues for human subject research ranging from cohort studies to surveillance, administrative and healthcare records. RESULTS: We observe that while these catalogues are heterogeneous, have various scopes, and use different terminologies, still the underlying concepts seem potentially harmonizable. We propose a unified framework to enable catalogue data sharing, with catalogues of multi-center cohorts nested as a special case in catalogues of real-world data sources. Moreover, we list recommendations to create an integrated community of metadata catalogues and an open catalogue ecosystem to sustain these efforts and maximise impact. CONCLUSIONS: We propose to embrace the autonomy of motivated catalogue teams and invest in their collaboration via minimal standardisation efforts such as clear data licensing, persistent identifiers for linking same records between catalogues, minimal metadata 'common data elements' using shared ontologies, symmetric architectures for data sharing (push/pull) with clear provenance tracks to process updates and acknowledge original contributors. And most importantly, we encourage the creation of environments for collaboration and resource sharing between catalogue developers, building on international networks such as OpenAIRE and research data alliance, as well as domain specific ESFRIs such as BBMRI and ELIXIR. IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.