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Rawad Massoud Alan.L Shihadeh Mohamed Roumié Myriam Youness Jocelyne Gerard Nada Saliba Rita Zaarour Maher Abboud Wehbeh Farah Najat Aoun Saliba 《Atmospheric Research》2011,101(4):893-901
The results of the first large scale chemical characterization of PM10 and PM2.5 at three different sites in the urban city of Beirut, Lebanon, are presented. Between May 2009 and April 2010 a total of 304 PM10 and PM2.5 samples were collected by sampling every sixth day at three different sites in Beirut. Observed mass concentrations varied between 19.7 and 521.2 μg m? 3 for PM10 and between 8.4 and 72.2 μg m? 3 for PM2.5, respectively. Inorganic concentrations accounted for 29.7–35.6 μg m? 3 and 46.0–53.5 μg m? 3 of the total mass of PM10 and PM2.5, respectively. Intra-city temporal and spatial variations were assessed based on the study of three factors: correlation coefficients (R) for PM and chemical components, coefficient of divergence (CODs), and source apportionment using positive matrix factorization (PMF). Based on R and COD of PM concentrations, the three sites appear homogeneous. However, when individual elements were compared, heterogeneity among sites was found. This latter was attributed to the variability in the percent contribution of biogenic and local anthropogenic source factors such as traffic related sources and dust resuspension. Other factors included the proximity to the Mediterranean sea, the population density and the topographical structure of the city. Hence, despite its small size (20.8 km2), one PM monitoring site does not reflect an accurate PM level in Beirut. 相似文献
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Choice between series and parallel connections of hysteretic system and viscous damper for seismic protection of structures 
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下载免费PDF全文 Supplemental viscous damping devices are generally envisioned to be connected in parallel to the inelastic parent structure or hysteretic damping devices. This gives rise to higher base shear, and often greater ductility demand of the hysteretic system. The series connection of the viscous and hysteretic system (the inelastic structure or a damper) is an alternative approach. In this paper, comparisons between the series and parallel connections of the hysteretic system and viscous dampers are done through response spectra analyses of single degree of freedom structures. Ductility demand of the hysteretic system and the total base shear are chosen as the response quantities. For the series model, a semi‐implicit solution scheme for classical Maxwell model is modified to include the inelasticity of the time‐independent hysteretic spring. It is observed that the series connection of the 2 dampers gives lower base shear than does the parallel connection. For long‐period and low‐damping structures, the ductility demand of the hysteretic system in series connection is higher than that in parallel connection. Increasing the viscous damping in series connection reduces the ductility demand substantially, lower than that obtained in parallel connection. Practical methods for implementing the series and parallel connections, in line with roof isolation, are also suggested. 相似文献
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Accurate reconstruction of roofs with dormers is challenging. Without careful separation of the dormer points from the points on the roof surface, the estimation of the roof areas is distorted. The characteristic distortion of the density distribution in comparison to the expected normal distribution is the starting point of our method. We propose a hierarchical method which improves roof reconstruction from LiDAR point clouds in a model‐based manner, separating dormer points from roof points using classification methods. The key idea is to exploit probability density functions to reveal roof properties and to skilfully design the features for a supervised learning method using support vector machines. The approach is tested based on real data as well as simulated point clouds. 相似文献
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Identification and Modelling of Translational and Axial Symmetries and their Hierarchical Structures in Building Footprints by Formal Grammars 下载免费PDF全文
下载免费PDF全文 Buildings and other man‐made objects, for many reasons such as economical or aesthetic, are often characterized by their symmetry. The latter predominates in the design of building footprints and building parts such as façades. Thus the identification and modeling of this valuable information facilitates the reconstruction of these buildings and their parts. This article presents a novel approach for the automatic identification and modelling of symmetries and their hierarchical structures in building footprints, providing an important prior for façade and roof reconstruction. The uncertainty of symmetries is explicitly addressed using supervised machine learning methods, in particular Support Vector Machines (SVMs). Unlike classical statistical methods, for SVMs assumptions on the a priori distribution of the data are not required. Both axial and translational symmetries are detected. The quality of the identified major and minor symmetry axes is assessed by a least squares based adjustment. Context‐free formal grammar rules are used to model the hierarchical and repetitive structure of the underlying footprints. We present an algorithm which derives grammar rules based on the previously acquired symmetry information and using lexical analysis describing regular patterns and palindrome‐like structures. This offers insights into the latent structures of building footprints and therefore describes the associated façade in a relational and compact way. 相似文献
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AbstractIn this paper we consider the problem of modelling the stage–discharge relationship by curve fitting using the least squares method. Our basic idea is to present new models which are more flexible and have the ability to model phenomena with increasing or unchanging carrying capacity. The new models present a generalization of some sigmoid smooth models commonly used in practice. They are characterized by a curvilinear asymptote and may have several inflection points. The use of these models on six real datasets collected from the US Geological Survey’s website proves their performance and their ability to model hydrological phenomena.
Editor D. Koutsoyiannis; Associate editor S. Yue 相似文献
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Weilian Li Jan-Henrik Haunert Julius Knechtel Jun Zhu Qing Zhu Youness Dehbi 《Transactions in GIS》2023,27(6):1766-1793
Detecting and collecting public opinion via social media can provide near real-time information to decision-makers, which plays a vital role in urban disaster management and sustainable development. However, there has been little work focusing on identifying the perception and the sentiment polarity expressed by users during and after disasters, particularly regional flood events. In this article, we comprehensively analyze tweets data related to the “European floods in 2021” over time, topic, and sentiment, forming a complete workflow from data processing, topic modeling, sentiment analysis, and topic and sentiment prediction. The aim is to address the following research questions: (1) What are the public perception and main concerns during and after floods? (2) How does the public sentiment change during and after floods? Results indicate that there is a significant correlation between a flood's trend and the heat of corresponding tweets. The three topics that receive the most public concern are: (1) climate change and global warming; (2) praying for the victims: and (3) disaster situations and information. Negative sentiments are predominant during the floods and will continue for some time. We tested five different classifiers, of which TextCNN-attention turned out to deliver the best predictions in topic and sentiment prediction, and performed well for sparse flood tweets, it can be used to predict the topic and sentiment polarity of a single tweet in real-time during the flood events. Our findings can help disaster agencies to better understand the dynamics of social networks and develop stronger situational awareness towards a disaster, which can contribute to scientifically justified decision-making in urban risk management and also meet the challenges associated with the global sustainable development goal 11 (SDGs) on Sustainable Cities and Communities. 相似文献
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Accurate and robust positioning of vehicles in urban environments is of high importance for autonomous driving or mobile mapping. In mobile mapping systems, a simultaneous mapping of the environment using laser scanning and an accurate positioning using global navigation satellite systems are targeted. This requirement is often not guaranteed in shadowed cities where global navigation satellite system signals are usually disturbed, weak or even unavailable. We propose a novel approach which incorporates prior knowledge (i.e., a 3D city model of the environment) and improves the trajectory. The recorded point cloud is matched with the semantic city model using a point‐to‐plane iterative closest point method. A pre‐classification step enables an informed sampling of appropriate matching points. Random forest is used as classifier to discriminate between facade and remaining points. Local inconsistencies are tackled by a segmentwise partitioning of the point cloud where an interpolation guarantees a seamless transition between the segments. The general applicability of the method implemented is demonstrated on an inner‐city data set recorded with a mobile mapping system. 相似文献
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Youness Dehbi Fabian Hadiji Gerhard Gröger Kristian Kersting Lutz Plümer 《Transactions in GIS》2017,21(1):134-150
The automatic interpretation of 3D point clouds for building reconstruction is a challenging task. The interpretation process requires highly structured models representing semantics. Formal grammars can describe structures as well as the parameters of buildings and their parts. We propose a novel approach for the automatic learning of weighted attributed context‐free grammar rules for 3D building reconstruction, supporting the laborious manual design of rules. We separate structure from parameter learning. Specific Support Vector Machines (SVMs) are used to generate a weighted context‐free grammar and predict structured outputs such as parse trees. The grammar is extended by parameters and constraints, which are learned based on a statistical relational learning method using Markov Logic Networks (MLNs). MLNs enforce the topological and geometric constraints. MLNs address uncertainty explicitly and provide probabilistic inference. They are able to deal with partial observations caused by occlusions. Uncertain projective geometry is used to deal with the uncertainty of the observations. Learning is based on a large building database covering different building styles and façade structures. In particular, a treebank that has been derived from the database is employed for structure learning. 相似文献
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Youness Dehbi Andr Henn Gerhard Grger Viktor Stroh Lutz Plümer 《Transactions in GIS》2021,25(1):112-133
This article proposes a novel method for the 3D reconstruction of LoD2 buildings from LiDAR data. We propose an active sampling strategy which applies a cascade of filters focusing on promising samples at an early stage, thus avoiding the pitfalls of RANSAC‐based approaches. Filters are based on prior knowledge represented by (nonparametric) density distributions. In our approach samples are pairs of surflets—3D points together with normal vectors derived from a plane approximation of their neighborhood. Surflet pairs provide parameters for model candidates such as azimuth, inclination and ridge height, as well as parameters estimating internal precision and consistency. This provides a ranking of roof model candidates and leads to a small number of promising hypotheses. Building footprints are derived in a preprocessing step using machine learning methods, in particular support vector machines. 相似文献
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