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Transformers in Distribution System01:27

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Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
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Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
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StrucADT: Generating Structure-Controlled 3D Point Clouds With Adjacency Diffusion Transformer.

Zhenyu Shu, Jiajun Shen, Zhongui Chen

    IEEE Transactions on Visualization and Computer Graphics
    |August 19, 2025
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    Summary
    This summary is machine-generated.

    This study introduces a novel method for controllable 3D point cloud generation using shape structures. The proposed model, StrucADT, enables users to specify part relationships for generating customized 3D shapes.

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    Area of Science:

    • Computer Vision
    • 3D Shape Generation
    • Machine Learning

    Background:

    • Existing 3D generative models produce diverse shapes but lack user control.
    • Controllable 3D point cloud generation is crucial for practical applications.

    Purpose of the Study:

    • To develop a novel method for controllable 3D point cloud generation.
    • To enable generation of 3D point clouds based on user-defined structural requirements.

    Main Methods:

    • Introduced StructureGraph representation based on part adjacency.
    • Developed StrucADT, a structure-controllable point cloud generation model.
    • Utilized StructureGraphNet, cCNF Prior, and Diffusion Transformer modules.

    Main Results:

    • Generated high-quality and diverse 3D point cloud shapes.
    • Achieved state-of-the-art performance in controllable point cloud generation.
    • Demonstrated successful generation of point clouds based on specified structures.

    Conclusions:

    • The proposed method effectively addresses the lack of control in 3D point cloud generation.
    • StrucADT enables precise control over 3D shape generation through structural specifications.
    • This work advances the field of controllable 3D shape synthesis.