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The literature is flooded with scientific information on most durability properties except water absorption coefficient of masonry units like sandcrete blocks. Also, while waste papers disposal is a systemic problem due to ineffectiveness of waste management system in developing countries, the price of cement is on the increase. This situation, ultimately, causes a bane in achievement of low-cost housing development considering the fact that sandcrete blocks are predominantly used as walling elements for such undertakings. In this study, solid core sandcrete blocks were produced with waste paper ash (WPA) utilized as partial replacement of cement at 5 % and 10 % volumetric levels. Chemically, the WPA was found to show similarity with cement in terms of SiO2, Al2O3, and CaO contents. Density and water absorption coefficient of the block samples were determined. While density ranged from 1682 to 1872 kg/m3, water absorption coefficient varied from 27.04 to 23.49 kg/m2h0.5. Statistically, no significant difference was revealed at p < 0.05 between experimentally-measured water absorption coefficients and those obtained using the model developed for prediction based on density of the samples. Thus, utilization of WPA as described herein could help to reduce the cost of procuring cement and in turn, enhance low-cost building construction. Also, with the developed model (showing dependence of water absorption coefficient on density), durability of sandcrete blocks exposed to moisture –prone environment could be easily predicted. [ABSTRACT FROM AUTHOR]

Buildings are significant components of digital cities, and their precise extraction is essential for the three-dimensional modeling of cities. However, it is difficult to accurately extract building features effectively in complex scenes, especially where trees and buildings are tightly adhered. This paper proposes a highly accurate building point cloud extraction method based solely on the geometric information of points in two stages. The coarsely extracted building point cloud in the first stage is iteratively refined with the help of mask polygons and the region growing algorithm in the second stage. To enhance accuracy, this paper combines the Alpha Shape algorithm with the neighborhood expansion method to generate mask polygons, which help fill in missing boundary points caused by the region growing algorithm. In addition, this paper performs mask extraction on the original points rather than non-ground points to solve the problem of incorrect identification of facade points near the ground using the cloth simulation filtering algorithm. The proposed method has shown excellent extraction accuracy on the Urban-LiDAR and Vaihingen datasets. Specifically, the proposed method outperforms the PointNet network by 20.73% in precision for roof extraction of the Vaihingen dataset and achieves comparable performance with the state-of-the-art HDL-JME-GGO network. Additionally, the proposed method demonstrated high accuracy in extracting building points, even in scenes where buildings were closely adjacent to trees. [ABSTRACT FROM AUTHOR]

Data driven deep learning methods have become the mainstream method of building extraction from remote sensing images. In this paper, deep learning algorithm is used to classify and extract buildings from remote sensing images of rural areas around the Great Wall in the suburbs of Beijing captured by unmanned aerial vehicles. Aiming at the shortcomings of the current mainstream instance segmentation algorithm Mask R-CNN in feature fusion and poor prediction of instance mask boundaries, this paper proposes a boundary optimization algorithm for building instance segmentation based on discrete wavelet transform. Firstly, the discrete wavelet transform is introduced into the segmentation task branch of Mask R-CNN algorithm to extract the low-frequency and high-frequency information of the real mask, in which the high-frequency information includes the boundary information. Secondly, the pixel by pixel prediction of the mask turns into the learning of the low-frequency and high-frequency information of the real mask. The learning of the high-frequency information helps the segmentation network to learn the boundary features better. Finally, using the reversibility of discrete wavelet transform, the low-frequency and high-frequency information of the learned mask is inversely transformed to reconstruct the final mask. The improved algorithm is evaluated on the dataset COCO, and applied to the automatic extraction of buildings. The DWT Mask R-CNN algorithm model achieved 70.2% segmentation accuracy and 71.4% detection accuracy, which were improved by 1% and 0.7% respectively compared with the Mask R-CNN and Cascade Mask R-CNN models. The experimental results show that the instance segmentation edge optimization algorithm combined with wavelet transform has achieved better results on the segmentation boundary, improved the poor effect of mask edge detection and achieved higher detection accuracy, and can accurately extract village buildings. [ABSTRACT FROM AUTHOR]

The concept of sustainability introduced in 1987 has characterised the world of research in the AEC (Architecture, Engineering, and Construction) sector, directing it to try to tackle the problems inherent to the impacts of climate change on buildings. In addition, the advent of COVID-19, disrupting the world and people's habits, has obviously also strongly affected the academic world. Indeed, this paper aims to analyse the changes and differences between the pre- and post-pandemic periods through a two-stage hybrid literature review. First, through a systematic literature review, 90 articles were selected, filtered through different keywords (sustainability, climate, architecture, and buildings). Once the reasoned selection of papers had been made, it was possible to proceed to the second phase, which involved a thematic analysis according to the three classic macro themes of sustainability (Environment, Social, and Economic) and the inclusion of a fourth macro theme (Management and Development), which made it possible to reintroduce a holistic view of the problem. The results of this literature review revealed the presence of a growing interest in the topic analysed and a more homogenous distribution across all continents, with no distinction between developed and developing countries. Economic sustainability interests emerge post-COVID-19 through the deepening of the themes of clean energy and direct control of consumption. At the level of Environmental sustainability, on the other hand, COVID-19 replaced the house at the centre of people's lives. In addition, the Management and Development macro theme highlighted the need for an integrated view of the problem and the unexpected return of researchers preferring new constructions, which, despite alternative green approaches and renovations, can guarantee better performance. [ABSTRACT FROM AUTHOR]

As stated in the Venice Commission Report, the rule of law embraces several aspects, such as legality, legal certainty, prevention of abuse (misuse of powers), equality before the law and non-discrimination, and access to justice. Stability and consistency of law and legitimate expectations as a part of legal certainty are key factors in every democratic country. However, even for countries where democratic standards are highly developed, achievement of all aspects of the rule of law can be a challenge. Areas such as spatial planning and building are very dynamic in their core. However, this should not be an obstacle for stable and long-term regulation. Western democracies are characterized by the long-lasting acts and other regulation in building and spatial planning. Croatia, however, has constant changes in the basic regulation covering mentioned areas. For example, in issuing a building permit, the procedure can be so long lasting that all the relevant regulation may change in the meantime. This affects the investor, the owner of the property and possibly infringes their constitutional rights. Since the issuing of a building permit is in the area of administrative law, the aim of this paper is to analyse which constitutional rights may be affected during frequent changes of basic regulation. The other aim is to research and analyse whether national bodies and courts protect constitutional guarantees in administrative proceedings, and if not, what are the reasons for such practice. This paper is divided into five sections: background and regulatory framework, the rule of law in spatial planning and building, right to a fair trial, protection of property in administrative matters, and conclusion. Methodology used in this paper is normative, comparative, teleological and deductive. The research includes relevant regulation and available domestic and case law of the European Court on Human Rights. Paper is based on domestic and international documentation issued by relevant bodies, such as European Commission Reports, Venice Commission Report, etc. Teleological method is used for interpretation of the regulation and deductive method for the conclusion. Teleological method is used also for recommendations regarding a better application of the principle of the rule of law. [ABSTRACT FROM AUTHOR]