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Titlebook: Web and Wireless Geographical Information Systems; 20th International S Mir Abolfazl Mostafavi,Géraldine Del Mondo Conference proceedings 2

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樓主: 拼圖游戲
31#
發(fā)表于 2025-3-26 21:22:34 | 只看該作者
Lasith Niroshan,James D. Carswellof the Transvaal, fundamentally altered its attitude towards both the Republic and the territories around it. As Baron Oswald von Richthofen, the Under Secretary of State for Foreign Affairs, succinctly put it: ‘We are letting England have South Africa.’. This statement, an explicit declaration of G
32#
發(fā)表于 2025-3-27 04:47:53 | 只看該作者
33#
發(fā)表于 2025-3-27 07:59:09 | 只看該作者
34#
發(fā)表于 2025-3-27 12:42:03 | 只看該作者
Towards Integration of Spatial Context in Building Energy Demand Assessment Supported by CityGML Enes to represent and manage the required spatiotemporal information for BEMs and feed a knowledgebase that can be used in WSN deployment optimization algorithms. Finally, the paper presents and discusses a case study to highlight the advantages and limitations of the proposed approach.
35#
發(fā)表于 2025-3-27 15:47:08 | 只看該作者
36#
發(fā)表于 2025-3-27 18:11:12 | 只看該作者
37#
發(fā)表于 2025-3-28 02:00:53 | 只看該作者
38#
發(fā)表于 2025-3-28 02:04:50 | 只看該作者
Mobility Data Analytics with?KNOT: The KNime mObility Toolkittform with a collection of new components specifically designed to support processing steps typical of mobility data, including map-matching, trajectory partitioning, and road network coverage analysis. To show the effectiveness of these components, we report also on how we applied them to perform a
39#
發(fā)表于 2025-3-28 07:02:13 | 只看該作者
Bus Journey Time Prediction with?Machine Learning: An Empirical Experience in?Two Citiesons is strongly related to the standard deviation of the whole journey times. It emerges that some bus routes show consistency in the prediction error across methods, and for these routes it makes sense to use methods that are fast and computationally efficient, as there is no benefit to applying mo
40#
發(fā)表于 2025-3-28 13:31:05 | 只看該作者
Geosensor Network Optimisation to?Support Decisions at?Multiple Scalesmation loss within spatially nested decision scales. The methods described in this paper fill an important gap as they are i) suggest appropriate sample and geosensor network designs to support cross-scale monitoring, ii) inform on how current network or geosensor coverage could be enhanced by filli
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