369 research outputs found

    The rate sensitivity and plastic deformation of nanocrystalline tantalum films at nanoscale

    Get PDF
    Nanoindentation creep and loading rate change tests were employed to examine the rate sensitivity (m) and hardness of nanocrystalline tetragonal Ta films. Experimental results suggested that the m increased with the decrease of feature scale, such as grain size and indent depth. The magnitude of m is much less than the corresponding grain boundary (GB) sliding deformation with m of 0.5. Hardness softening behavior was observed for smaller grain size, which supports the GB sliding mechanism. The rate-controlling deformation was interpreted by the GB-mediated processes involving atomic diffusion and the generation of dislocation at GB

    What makes an explosion happen?

    Full text link
    The presence of the nonbonding XH tension constrains and the presence of the anti or super hydrogen bond fosters the explosion in aqueous alkali and molten alkali halides; the combination of the coupled hydrogen bond and the repulsive anti or super hydrogen bond not only stabilzes the structure but also stores energy of the energetic molecular assemblies by shortening all covalent bonds.Comment: 4 figure, 3500 work

    Deep Metric Multi-View Hashing for Multimedia Retrieval

    Full text link
    Learning the hash representation of multi-view heterogeneous data is an important task in multimedia retrieval. However, existing methods fail to effectively fuse the multi-view features and utilize the metric information provided by the dissimilar samples, leading to limited retrieval precision. Current methods utilize weighted sum or concatenation to fuse the multi-view features. We argue that these fusion methods cannot capture the interaction among different views. Furthermore, these methods ignored the information provided by the dissimilar samples. We propose a novel deep metric multi-view hashing (DMMVH) method to address the mentioned problems. Extensive empirical evidence is presented to show that gate-based fusion is better than typical methods. We introduce deep metric learning to the multi-view hashing problems, which can utilize metric information of dissimilar samples. On the MIR-Flickr25K, MS COCO, and NUS-WIDE, our method outperforms the current state-of-the-art methods by a large margin (up to 15.28 mean Average Precision (mAP) improvement).Comment: Accepted by IEEE ICME 202

    Structures and Anomalies of Water

    Full text link
    Introduction of the principles of the asymmetrical, short-range O:H-O coupled oscillater pair and the basic rule for water ice, which reconciles the structure and anomalies of water ice.Comment: 20 pages. In Chines

    TwinTex: Geometry-aware Texture Generation for Abstracted 3D Architectural Models

    Full text link
    Coarse architectural models are often generated at scales ranging from individual buildings to scenes for downstream applications such as Digital Twin City, Metaverse, LODs, etc. Such piece-wise planar models can be abstracted as twins from 3D dense reconstructions. However, these models typically lack realistic texture relative to the real building or scene, making them unsuitable for vivid display or direct reference. In this paper, we present TwinTex, the first automatic texture mapping framework to generate a photo-realistic texture for a piece-wise planar proxy. Our method addresses most challenges occurring in such twin texture generation. Specifically, for each primitive plane, we first select a small set of photos with greedy heuristics considering photometric quality, perspective quality and facade texture completeness. Then, different levels of line features (LoLs) are extracted from the set of selected photos to generate guidance for later steps. With LoLs, we employ optimization algorithms to align texture with geometry from local to global. Finally, we fine-tune a diffusion model with a multi-mask initialization component and a new dataset to inpaint the missing region. Experimental results on many buildings, indoor scenes and man-made objects of varying complexity demonstrate the generalization ability of our algorithm. Our approach surpasses state-of-the-art texture mapping methods in terms of high-fidelity quality and reaches a human-expert production level with much less effort. Project page: https://vcc.tech/research/2023/TwinTex.Comment: Accepted to SIGGRAPH ASIA 202
    • …
    corecore