689 research outputs found
Jiahui Zhang, cello, Thursday, May 31, 2012
No full textIn partial fulfillment of the requirements for the degree of
Master of Musi
Bilinear Sparse Target Detection for Asbestos Identification in Hyperspectral PRISMA Data
No full textA Symplectic Numerical Power Flow Framework Based on Wave Finite-Element Method for Assembled Structural Systems
No full textIdentifying the propagation paths of dominant wave modes in complex assembled structure is critical for implementing wave-based vibration and noise control strategies, such as phononic band gaps. This paper presents a symplectic numerical framework to compute the wave-mode power flow in engineering assembled structures based on wave finite element method (WFEM). The power orthogonality among wave modes is explicitly formulated through the symplectic orthogonality (SO) and its adjoint form (SAO), and this formulation is further extended to the Zhong-Williams and lambda(phi) symplectic schemes. The generalized symplectic adjoint orthogonality (GSAO) and phi_SAO are subsequently proposed, providing a physically consistent basis for modal diagonalization and coherent wave propagation within the generalized symplectic eigenspace. These developments enable direct computation of the forced response and power flow entirely within the symplectic space, without reverting to the wave space. Six power-flow formulations are systematically compared and shown to yield consistent results on both beam and cylindrical shell structures. An electric motor housing is used as a case study, in which the proposed approach establishes a wave-mode power flow network. It is noted that the power-flow formulation relies on symplectic orthogonality defined for conservative WFEM systems and therefore cannot be directly applied to non-Hermitian systems
MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization
No full textWe present MultiBodySync, a novel, end-to-end trainable multi-body motion segmentation and rigid registration framework for multiple input 3D point clouds. The two non-trivial challenges posed by this multi-scan multibody setting that we investigate are: (i) guaranteeing correspondence and segmentation consistency across multiple input point clouds capturing different spatial arrangements of bodies or body parts; and (ii) obtaining robust motion-based rigid body segmentation applicable to novel object categories. We propose an approach to address these issues that incorporates spectral synchronization into an iterative deep declarative network, so as to simultaneously recover consistent correspondences as well as motion segmentation. At the same time, by explicitly disentangling the correspondence and motion segmentation estimation modules, we achieve strong generalizability across different object categories. Our extensive evaluations demonstrate that our method is effective on various datasets ranging from rigid parts in articulated objects to individually moving objects in a 3D scene, be it single-view or full point clouds. Code at https: //github.com/huangjh-pub/multibody-sync
Application of biodegradable implants in pediatric orthopedics: shifting from absorbable polymers to biodegradable metals
No full textOver the past two decades, advances in pediatric orthopedics and closed reduction combined with percutaneous internal fixation techniques have led to significant growth in pediatric orthopedics surgery. Implants such as Kirschner-wires, cannulated screws and elastic stabilization intramedullary nails are commonly used in these procedures. However, traditional implants made of metal or inert materials are not absorbable, leading to complications that affect treatment outcomes. To address this issue, absorbable materials with excellent mechanical properties, good biocompatibility, and controlled degradation rates have been developed and applied in clinical practice. These materials include absorbable polymers and biodegradable metals. This article provides a comprehensive summary of these resorbable materials from a clinician's perspective. In addition, an in-depth discussion of the feasibility of their clinical applications and related research in pediatric orthopedics is included. We found that the applications of absorbable implants in pediatric orthopedics are shifting from absorbable polymers to biodegradable metals and emphasize that the functional characteristics of resorbable materials must be coordinated and complementary to the treatment in pediatric orthopedics
Different genes of the same type of architecture: Waterfront dwellings in Amsterdam and Suzhou
No full textIn the 17th century, both Amsterdam and Suzhou were in a period of rapid social and economic development. When faced with similar water environment and social problems such as conflicts between population and limited land resource, the residents of the two places chose completely different ways to build their dwellings. In response to such differences, this study explores the reasons for the differences between the traditional waterfront dwellings in Amsterdam and Suzhou in the 17th century. First of all, the study describes the social conditions at that time and the development processes of waterfront dwellings in the two places to construct a basic historical framework. Then it interprets the specific differences in the respective relationships between the two waterfront dwellings and the water environment, indicating the objective architectural differences. Next, it analyzes the reasons for forming the specific differences from three aspects which are social culture, lifestyle, natural environment and climate, and reveals the influence of these factors on the results of architectural form differentiation. Finally, starting from the reasons for the differences, further thinking about the current architectural practice is carried out, so as to bring some enlightenment to the readers.AR2A011Architecture, Urbanism and Building Science
Slimmable neural networks for edge devices
No full textWhile methods based on deep learning have witnessed major breakthroughs in machine perception and generative modeling, the problem of how to run neural networks within latency budget for edge devices remains unsolved. This thesis presents a new approach to train a single neural network executable at arbitrary widths for instant and adaptive accuracy-efficiency trade-offs at runtime.
First a simple and general method is presented to train a single neural network executable at different widths (number of channels in a layer). The width can be chosen from a predefined widths set to adaptively optimize accuracy-efficiency trade-offs at runtime. Instead of training individual networks with different width configurations, we train a shared network with switchable batch normalization. At runtime, the network can adjust its width on the fly according to on-device benchmarks and resource constraints, rather than downloading and offloading different models. Our trained networks, named slimmable neural networks, achieve ImageNet classification accuracy similar to (and in many cases better than) that of individually trained models of MobileNet v1, MobileNet v2, ShuffleNet and ResNet-50 at different widths. We also demonstrate better performance of slimmable models compared with individual ones across a wide range of applications including COCO bounding-box object detection, instance segmentation and person keypoint detection without tuning hyper-parameters. We visualize and discuss the learned features of slimmable networks.
Further, we propose a systematic approach to train universally slimmable networks (US-Nets), extending slimmable networks to execute at arbitrary width, and generalizing to networks both with and without batch normalization layers. In addition, we propose two improved training techniques for US-Nets, named the sandwich rule and the inplace distillation, to enhance training process and boost testing accuracy. We show improved performance of universally slimmable MobileNet v1 and MobileNet v2 on ImageNet classification task, compared with individually trained ones and 4-switch slimmable network baselines. We also evaluate the proposed US-Nets and improved training techniques on tasks of image super-resolution and deep reinforcement learning. Extensive ablation experiments on these representative tasks demonstrate the effectiveness of our proposed methods. Our discovery opens up the possibility to directly evaluate a FLOPs-Accuracy spectrum of network architectures. Finally, we demonstrate an application to search for channel number configurations based on proposed slimmable networks.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01The student, Jiahui Yu, accepted the attached license on 2019-02-14 at 14:34.The student, Jiahui Yu, submitted this Thesis for approval on 2019-02-14 at 14:42.This Thesis was approved for publication on 2019-02-15 at 11:18.DSpace SAF Submission Ingestion Package generated from Vireo submission #13390 on 2019-08-22 at 16:19:49Made available in DSpace on 2019-08-23T20:44:31Z (GMT). No. of bitstreams: 2
YU-THESIS-2019.pdf: 1268760 bytes, checksum: c091ef8a839188e9d52d208dee832b8a (MD5)
LICENSE.txt: 4206 bytes, checksum: 1b6cf1c051b15c1073c51d0ad5e1abd0 (MD5)
Previous issue date: 2019-02-15Embargo set by: Seth Robbins for item 112252
Lift date: 2021-08-23T20:44:50Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 112252
Lift date: 2021-08-23T20:46:41Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 112252
Lift date: 2021-08-23T20:47:38Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 112252
Lift date: 2021-08-23T20:48:32Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemLimited Restriction Lifted for Item 112252 on 2021-08-24T09:15:34Z
Qin ai de da ren qi shi wo mei you na me huai, wo zhi shi jing bu xia lai
No full textChildren are not small adults. Thes book provides real voices from 10 different children and the illustrator is an 11-year-old- ADHD genius. These touching stories help adults understand and accompany ADHD children more effectively and more friendly
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