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Titlebook: Residues and Duality; Lecture Notes of a S Robin Hartshorne Book 1966 Springer-Verlag Berlin Heidelberg 1966 Algebraische Geometrie.Grothen

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Robin Hartshorne hotspots with holes. The proposed algorithm features refinements that improve the performance of a naïve approach. Case studies on real crime datasets confirm the superiority of NHHG over previous approaches. Experimental results on real data show that the proposed approach yields substantial compu
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Robin Hartshorneel abstractions of continuous ST phenomena that are known to the DSE, and therefore, can be supported through queries and processing optimization. The proposed field data types are formalized in a data model language independent way using second order signatures. We formalize both the set of support
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Robin Hartshorneby Regier (2007), claims a particular focus of human cognition to ending relations of events, other research suggests that simplicity principles guide categorization and, additionally, that static information is easier to process than dynamic information. Our experiments show a clear picture: Size m
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Robin Hartshorne spatially distributed settings. Storage and retrieval of this information is provided through a Web Feature Service, which eases integration of collaboration data into existing applications. We further introduce a visualization technique that integrates annotations as complex structured data into t
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in the field, establish a framework to organize the literature and to link three different subject areas (participation and community development, GIS and other related technologies, and planning processes). Th978-3-642-26214-2978-3-540-75401-5Series ISSN 1867-2434 Series E-ISSN 1867-2442
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Robin Hartshornehotspots with doughnut shaped spatial footprint, where the concentration of activities is unusually high (e.g. statistically significant). MNHH is important for societal applications such as criminology, where it may focus the efforts of officials to identify a crime source. MNHH is challenging beca
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Robin Hartshorneards are known to exhibit biophysical variations (e.g., land cover and housing characteristics) and social variations (e.g., demographic and economic adaptations to heat mitigation). Geodemographic model-based classification permits a more extensive set of input variables, with richer attributions;
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