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8th International Conference on Communication, Image and Signal Processing, CCISP 2023

作者： He, Rui Xiao, Yunzhe Yang, Shaowu College of Computer Science and Technology National University of Defense Technology Quantum Information & State Key Laboratory of High Performance Computing Changsha China

ISBN: (纸本)9798350305838

Place recognition is a crucial component in the realm of simultaneous localization and mapping (SLAM) and autonomous driving. It can also enhance the performance of loop closure detection and global localization. LiDAR-based place recognition usually relies on global feature descriptors to accurately express the similarity between LiDAR scans. However, it is time-consuming to extract and generate the global feature descriptors from the original LiDAR data. As a result, treating LiDAR-based point clouds place recognition as a 2D image problem using range projection is becoming an increasingly common and successful strategy. Vision Transformer (ViT) is a Transformer model based on self-attention mechanism for image classification. Through self-attention mechanism, ViT out-performs CNN at modeling the global information of images. We investigate that whether ViT can be transferred to LiDAR-based place recognition tasks. Firstly, we introduce a new convolutional stem to replace the original linear embedding layer in ViT. Secondly, we establish synergy by integrating low-level fine-grained features from new convolution layer with high-level coarse-grained features from ViT by skip connections. Thirdly, we aggregate these features to construct the global feature descriptor via the NetVLAD technique. The results of experiments on KITTI confirm that our method can operate online and achieve superior performance on par with existing approaches. © 2023 IEEE.

关键词： Convolution

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A Unity-Gain Buffer Assisted Noise-Shaping SAR ADC Based on Error-Feedback Structure

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Chinese Journal of Electronics 2022年第4期31卷 658-664页

作者： YI Pinyun ZHU Zhangming XU Nuo FANG Liang HAO Yue State Key Laboratory of High Performance Computing College of ComputerNational University of Defense Technology School of Microelectronics Xidian University College of Computer National University of Defense Technology State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology School of MicroelectronicsXidian University

The passive noise-shaping successive approximation register(NS-SAR) analog-to-digital converter(ADC) demonstrates high performance in resolution improvement, power reduction, and process scaling, while its charge-sharing loss and limited bandwidth weaken the noise-shaping effect. This paper presents a first-order NSSAR ADC based on error-feedback(EF) structure to realize high-efficiency noise shaping. It employs a lossless EF path by using a set of ping-pong switching capacitors with passive signal-residue summation technique. The proposed first-order EF NS-SAR prototype can be promoted to multi-order structure with the minor modification. Verified by simulation in 65-nm CMOS process, the proposed 9-bit NS-SAR ADC consumes 183.66 μW when operating at 20 MS/s with the supply voltage of 1.2 V. At the oversampling ratio of 16, it achieves a peak signal-tonoise-and-distortion ratio of 81 d B, yielding Schreier figure of merit of 176.32 d B.

关键词： Noise-shaping SAR ADC Error feedback Unity-gain buffer Lossless integration Ping-pong manner Full-resolution switching

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Self-distillation Enhanced Vertical Wavelet Spatial Attention for Person Re-identification 1

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30th International Conference on MultiMedia Modeling, MMM 2024

作者： Zhang, Yuxuan Tan, Huibin Lan, Long Teng, Xiao Ren, Jing Zhang, Yongjun Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China Beijing100071 China

ISBN: (数字)9783031533082

ISBN: (纸本)9783031533075

Person re-identification is a challenging problem in computer vision, aiming to accurately match and recognize the same individual across different viewpoints and cameras. Due to significant variations in appearance under different scenes, person re-identification requires highly discriminative features. Wavelet features contain richer phase and amplitude information as well as rotational invariance, demonstrating good performance in various visual tasks. However, through our observations and validations, we have found that the vertical component within wavelet features exhibits stronger adaptability and discriminability in person re-identification. It better captures the body contour and detailed information of pedestrians, which is particularly helpful in distinguishing differences among individuals. Based on this observation, we propose a vertical wavelet spatial attention only with the vertical component in the high frequency specifically designed for feature extraction and matching in person re-identification. To enhance spatial semantic consistency and facilitate the transfer of knowledge between different layers of wavelet attention in the neural network, we introduce a self-distillation enhancement method to constrain shallow and deep spatial attention. Experimental results on Market-1501 and DukeMTMC-reID datasets validate the effectiveness of our model. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Distillation

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ISpliter:an intelligent and automatic surface mesh generator using neural networks and splitting lines

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Advances in Aerodynamics 2023年第1期5卷 362-386页

作者： Zengsheng Liu Shizhao Chen Xiang Gao Xiang Zhang Chunye Gong Chuanfu Xu Jie Liu State Key Laboratory of High Performance Computing National University of Defense TechnologyChangsha 410073China College of Computer National University of Defense TechnologyChangsha 410073China Laboratory of Digitizing Software for Frontier Equipment National University of Defense TechnologyChangsha 410073China

In this paper,we present a novel surface mesh generation approach that splits B-rep geometry models into isotropic triangular meshes based on neural networks and splitting *** the first stage,a recursive method is designed to generate plentiful data to train the neural network model *** the second stage,the implemented mesh generator,ISpliter,maps each surface patch into the parameter plane,and then the trained neural network model is applied to select the optimal splitting line to divide the patch into subdomains continuously until they are all *** the third stage,ISpliter remaps the 2D mesh back to the physical space and further optimizes *** typical cases are evaluated to compare the mesh quality generated by ISpliter and two baselines,Gmsh and *** results show that ISpliter can generate isotropic triangular meshes with high average quality,and the generated meshes are comparable to those generated by the other two software under the same configuration.

关键词： Surface mesh generation Artificial neural network Splitting line Triangular element Feature extraction

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A large scale parallel fluid-structure interaction computing platform for simulating structural responses to a detonation shock

A large scale parallel fluid-structure interaction computing...

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作者： Zhang, Sen Guo, Xiao-Wei Li, Chao Liu, Yi Fan, Sijiang Zhao, Ran Yang, Canqun Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha China

Due to the intrinsic nature of multi-physics, it is prohibitively complex to design and implement a simulation software platform for study of structural responses to a detonation shock. In this article, a partitioned fluid-structure interaction computing platform is designed for parallel simulating structural responses to a detonation shock. The detonation and wave propagation are modeled in an open-source multi-component solver based on OpenFOAM and blastFoam, and the structural responses are simulated through the finite element library ***. To capture the interaction dynamics between the fluid and the structure, both solvers are adapted to preCICE. For improving the parallel performance of the computing platform, the inter-solver data is exchanged by peer-to-peer communications and the intermediate server in conventional multi-physics software is eliminated. Furthermore, the coupled solver with detonation support has been deployed on a computing cluster after considering the distributed data storage and load-balancing between solvers. The 3D numerical result of structural responses to a detonation shock is presented and analyzed. On 256 processor cores, the speedup ratio of the simulations for a detonation shock reach 178.0 with 5.1 million of mesh cells and the parallel efficiency achieve 69.5%. The results demonstrate good potential of massively parallel simulations. Overall, a general-purpose fluid-structure interaction software platform with detonation support is proposed by integrating open source codes. And this work has important practical significance for engineering application in fields of construction blasting, mining, and so forth. © 2021 John Wiley & Sons, Ltd.

关键词： Detonation

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OL-CBBA: An Online Task Allocation Algorithm under Weak Communication Conditions 29

OL-CBBA: An Online Task Allocation Algorithm under Weak Comm...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Li, Jun Huang, Wanrong Wu, Honglin Cai, Zhongxuan Zhang, Yongjun National University of Defense Technology Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology Changsha China

ISBN: (纸本)9798350330717

Multiple unmanned aerial vehicles (UAVs) and multiple tasks allocation problem is difficult to solve. Existing task allocation algorithms assume that the UAVs' position is static, and cannot assign tasks with the changing UAVs' position simultaneously during task execution. Those algorithms reduce the efficiency of task allocation. In this paper, we propose an online consensus-based bundle algorithm (OL-CBBA) under weak communication for dynamic task allocation. We consider the situation that the location information of UAVs will constantly change during the dynamic execution of tasks. The algorithm first improves the static CBBA to an online algorithm by updating the task marginal score in task path. Moreover, we specify a flag for the convergence of individual tasks, allowing UAVs to start executing tasks earlier. Extensive comparative experiments prove the highly consistent efficiency of OL-CBBA under weak communication conditions. Specifically, the proposed OL-CBBA attains up to 22% improvement compared with CBBA. © 2023 IEEE.

关键词： Auction Algorithm Decentralized System Dynamic Task Allocation Weak Communication

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Towards Radar Emitter Recognition in Changing Environments with Domain Generalization 2

Towards Radar Emitter Recognition in Changing Environments w...

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2nd International Conference on Signal Processing, Computer Networks and Communications, SPCNC 2023

作者： Wu, Honglin Li, Xueqiong Lan, Long Xu, Liyang Tang, Yuhua Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha China

ISBN: (纸本)9798400716430

Analyzing radar signals from complex Electronic Warfare (EW) environment is a non-trivial task. However, in the real world, the changing EW environment results in inconsistent signal distribution, such as the pulse repetition interval (PRI) mismatch between different detected scenes. In this paper, we propose a novel domain generalization framework to improve the adaptability of signal recognition in changing environments. Specifically, we first design several noise generators to simulate varied scenes. Different from conventional augmentation methods, our introduced generators carefully enhance the diversity of the detected signals and meanwhile maintain the semantic features of the signals. Moreover, we propose a signal scene domain classifier that works in the manner of adversarial learning. The proposed classifier guarantees the signal predictor to generalize to different scenes. Extensive comparative experiments prove the proposed method's superiority. © 2023 ACM.

关键词： Electronic warfare

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Protocol-Aware Process Placement for MPI Programs

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Chinese Journal of Electronics 2025年第4期23卷 701-705页

作者： Xinhai Xu Yufei Lin Xuejun Yang State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China

Current parallel programs are often composed of lots of processes that communicate through message passing. The mapping of the program processes onto the underlying processor. By analyzing the MPI library, we find that the communication protocols have great influence upon the communication characteristics. The profiling information used by the existing process placement methods does not include the communication protocols. We propose and implement a method called Protocol-aware process placement (PaPP) to incorporate the influences of communication protocols into the mapping problem. We demonstrate the validations of PaPP by the experiments using NPB3.3-MPI benchmarks. The experimental results show that compared to basic process placement, the average execution time when using PaPP scheme is reduced by 9.5%.

关键词： Protocols Costs Message passing Benchmark testing Parallel processing Parallel machines Libraries Data mining

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Multi-Restricted Point Cloud Adversarial Attack based on Sensitivity Maps 5

Multi-Restricted Point Cloud Adversarial Attack based on Sen...

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5th International Seminar on Artificial Intelligence, Networking and Information technology, AINIT 2024

作者： Chen, Geng Li, Teng National University of Defense Technology State Key Laboratory of High-Performance Computing Changsha410000 China The College of Advanced Interdisciplinary Studies National University of Defense Technology Changsha410000 China

ISBN: (纸本)9798350385557

The point cloud classification networks have been widely applied in 3D Reconstruction and Remote Sensing. The backbone of these networks is often implemented based on Deep Neural Networks (DNNs). Currently, a series of studies confirm that DNNs are vulnerable and susceptible to interference from adversarial samples. The existing strategies for attack and defense are primarily focused on the image domain. Due to the unordered and unstructured nature of point clouds, there has been limited research on attack algorithms for point clouds. Current black-box transferable attack algorithms face a challenge in balancing adversary and imperceptibility. They often lead to either a low Attack Success Rate (ASR) or the emergence of significant outlier points, which can be removed by Statistical Outlier Removal (SOR) methods easily. Inspired by principles from attack algorithm in image domain, this article introduces a novel approach. After extensive evaluation on several mainstream recognition models (such as PointNet++ and DGCNN), we have demonstrated that our black-box transferable attack method achieves state-of-the-art performance. To the best of our knowledge, we are the first to propose a point cloud black box transferable attack algorithm based on improved MI-FGSM. © 2024 IEEE.

关键词： Deep neural networks

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Degenerate polarization entangled photon source based on a single Ti-diffusion lithium niobate waveguide in a polarization Sagnac interferometer

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Chinese Physics B 2023年第8期32卷 69-73页

作者：孙宇孙昌伟周唯杨然端家晨龚彦晓徐平祝世宁 National Laboratory of Solid State Microstructures and School of Physics Nanjing UniversityNanjing 210093China NanZhi Institude of Advanced Optoelectronic Integration Nanjing 210018China Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China

Combining a Ti-diffusion periodically poled lithium niobate(PPLN)waveguide with a Sagnac interferometer,two opposite directions type-II spontaneous parametric down conversions(SPDC)occur coherently and yield a high brightness,high stability polarization entanglement *** source produces degenerate photon pairs at 1540.4 nm with a brightness of B=(1.36±0.03)×10^(6) pairs/(s·nm·m W).We perform quantum state tomography to reconstruct the density matrix of the output state and obtain a fidelity of F=0.983±*** high brightness and phase stability of our waveguide source enable a wide range of quantum information experiments operating at a low pump power as well as hold the advantage in mass production which can promote the practical applications of quantum technologies.

关键词： polarization entanglement source Sagnac interferometer quantum information lithium niobate waveguide

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