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Multilines, complex lines and groups
Published in Bob McFarlane, Beginning AutoCAD 2007, 2007
TasksErase the original text item – complete group (GR2) erased?Undo this effect with the UNDO icon Select the explode icon and select any group object and: At the command line enter GROUP <R> and from the dialogue box: pick GR2 linepick Explodepick OKThe text item can now be erased.
Multilines, complex lines and groups
Published in Bob McFarlane, Beginning AutoCAD 2006, 2006
TasksErase the original text item – complete group (GR2) erased?Undo this effect with the UNDO iconSelect the explode icon and select any group object and: At the command line enter GROUP <R> and from the dialogue box: pick GR2 linepick Explodepick OKThe text item can now be erased.
Data Communications for Distributed Building Automation
Published in Richard Zurawski, Networked Embedded Systems, 2017
Wolfgang Kastner, Georg Neugschwandtner
KNX uses a shared-variable model to express the functionality of individual nodes and combine them into a working system. Although this model uses state-based semantics, communication remains event-driven. Network-visible variables of a node application are referred to as group objects. They can be readable, writable, or both (although the latter is discouraged to better keep track of communication dependencies). Each group of communication objects is assigned a unique group address. This address is used to handle all network traffic pertaining to the shared value in a peer-to-peer manner. Group membership is defined individually for each group object of a node, which can belong to multiple groups.
Constructing condensed memories in functorial time
Published in Journal of Experimental & Theoretical Artificial Intelligence, 2023
(Clausen & Scholze, 2021, Definition 1.2) The pro-étale site of a point is the category of profinite sets-, with finite jointly surjective families of maps as covers. A condensed set is a sheaf of sets on. Similarly, a condensed ring/group/object is a sheaf of rings/groups/objects on.
A graph autoencoder network to measure the geometric similarity of drainage networks in scaling transformation
Published in International Journal of Digital Earth, 2023
Huafei Yu, Tinghua Ai, Min Yang, Weiming Huang, Lars Harrie
The uncertainty in GSM_ST can be divided into three categories: (1) GSM_ST involves subjective judgments that depend on spatial cognition (Gao and Cao 2021). Different individuals may have varying opinions on what constitutes a high level of similarity, resulting in a variance of GSM_ST. (2) GSM_ST has different concerns, such as a comparison at a global scale that may overlook important local details. Different map generalization operators may preserve different aspects of the original map, such as selection focusing on the global structure (Zhang and Guilbert 2017) and simplification focusing on the local detail (Ai et al. 2017), leading to varying targets of GSM_ST. (3) The parameters used for GSM_ST are diverse and complex. GSM_ST is a multidisciplinary problem involving mathematical geometry, cartography, and cognition. Numerous parameters, such as direction, bending, density, and classification, can be used to express geometric and topological features. However, choosing one or several as the typical features for GSM_ST is challenging. The rule-based methods are usually used to address these uncertainties in GSM_ST through a weighted calculation based on the similarity of different relations, such as direction, distance, and topology (Yan, Shen, and Li 2016). The similarity in each relation is the ratio of several representative parameters before and after the scaling transformation (Yan and Li 2015; Yang and Wang 2021). However, the rule-based approach requires adjusting parameters and weights for different objects, leading to poor robustness in addressing the uncertainty of GSM_ST, for example, adjusting parameters such as road density and length for road networks, river ordering and flow direction for river networks, and building area and direction. Likewise, the vector-based method, supported by techniques such as the Fourier transform, is limited by the fixed length of the shape descriptor and cannot be applied to a group object such as road networks or drainage networks (Liu et al. 2022). Therefore, due to its uncertainty, the GSM_ST remains a challenge.