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NGDcrm:a numeric graph dependency-based conflict resolution method for knowledge graph

high technology Letters 2021年第2期27卷 153-162页

作者： Ma Jiangtao Wang Yanjun Chen Xueting Qiao Yaqiong College of Computer and Communication Engineering Zhengzhou Universily of Lighl IndustryZhengzhou 450002P.R.China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450002P.R.China School of Computer&Communication Engineering University of Science and Technology BeijingBeijing 100083P.R.China School of Information Engineering North China University of W ater Resources and Electric PowerZhengzhou 450046P.R.China

Knowledge graph(KG)conflict resolution is to solve knowledge conflicts problem in the construction of *** at the problem of KG conflict resolution,a KG conflict resolution algorithm NGDcrm is proposed,which is a numeric graph dependency-based conflict resolution *** utilizes the dependency graph to perform arithmetic calculation and predicate comparison of numerical entity knowledge in the *** first uses a parallel segmentation method to segment the KG;then,it extracts the features of the KG according to KG embedding;finally,it uses numerical graph dependencies to detect and correct the wrong facts in the KG based on the extracted *** experimental results on real data show that NGDcrm is better than the state-of-the-art knowledge conflict resolution *** them,the AUC value of NGDcrm on the DBpedia dataset is 15.4%higher than the state-of-the-art method.

关键词： dependency graph knowledge conflict resolution knowledge graph(KG) numeric graph dependency(NGD)

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Experimental review on Majorana zero-modes in hybrid nanowires

arXiv

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arXiv 2020年

作者： Fu, Ji-Bang Li, Bin Zhang, Xin-Fang Yu, Guang-Zheng Huang, Guang-Yao Deng, Ming-Tang Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology NUDT Changsha410073 China

As the condensed matter analog of Majorana fermion, the Majorana zero-mode is well known as a building block of fault-tolerant topological quantum computing. This review focuses on the recent progress of Majorana experiments, especially experiments about semiconductor-superconductor hybrid devices. We first sketch Majorana zero-mode formation from a bottom-up view, which is more suitable for beginners and experimentalists. Then, we survey the status of zero-energy state signatures reported recently, from zero-energy conductance peaks, the oscillations, the quantization, and the interactions with extra degrees of freedom. We also give prospects of future experiments for advancing one-dimensional semiconductor nanowire-superconductor hybrid materials and devices. Copyright © 2020, The Authors. All rights reserved.

关键词： Hybrid materials

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high-Frequency Stereo Matching Network

High-Frequency Stereo Matching Network

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Haoliang Zhao Huizhou Zhou Yongjun Zhang Jie Chen Yitong Yang Yong Zhao Text Computing & Cognitive Intelligence Engineering Research Center of National Education Ministry State Key Laboratory of Public Big Data College of Computer Science and Technology Institute of Artificial Intelligence Guizhou University Guiyang Guizhou China Ghost-Valley AI Technology Shenzhen Guangdong China School of Physics and Optoelectronic Engineering Guangdong University of Technology Guangzhou China The Key Laboratory of Integrated Microsystems Shenzhen Graduate School Peking University China

In the field of binocular stereo matching, remarkable progress has been made by iterative methods like RAFT-Stereo and CREStereo. However, most of these methods lose information during the iterative process, making it difficult to generate more detailed difference maps that take full advantage of high-frequency information. We propose the Decouple module to alleviate the problem of data coupling and allow features containing subtle details to transfer across the iterations which proves to alleviate the problem significantly in the ablations. To further capture high-frequency details, we propose a Normalization Refinement module that unifies the disparities as a proportion of the disparities over the width of the image, which address the problem of module failure in cross-domain scenarios. Further, with the above improvements, the ResNet-like feature extractor that has not been changed for years becomes a bottleneck. Towards this end, we proposed a multi-scale and multi-stage feature extractor that introduces the channel-wise self-attention mechanism which greatly addresses this bottleneck. Our method (DLNR) ranks 1st on the Middlebury leaderboard, significantly outperforming the next best method by 13.04%. Our method also achieves SOTA performance on the KITTI-2015 benchmark for D1-fg. Code and demos are available at: https://***/David-Zhao-1997/high-frequency-Stereo-Matching-Network.

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Machine Learning for Actionable Warning Identification: A Comprehensive Survey

arXiv

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arXiv 2023年

作者： Ge, Xiuting Fang, Chunrong Li, Xuanye Sun, Weisong Wu, Daoyuan Zhai, Juan Lin, Shangwei Zhao, Zhihong Liu, Yang Chen, Zhenyu State Key Laboratory for Novel Software Technology Nanjing University No.22 Hankou Road Jiangsu Nanjing210093 China College of Computing and Data Science Nanyang Technological University Nanyang Avenue 50 Singapore The Hong Kong University of Science and Technology Clear Water Bay Hong Kong Manning College of Information & Computer Sciences University of Massachusetts 140 Governors Drive Miami Amherst United States

Actionable Warning Identification (AWI) plays a crucial role in improving the usability of static code analyzers. With recent advances in Machine Learning (ML), various approaches have been proposed to incorporate ML techniques into AWI. These ML-based AWI approaches, benefiting from ML’s strong ability to learn subtle and previously unseen patterns from historical data, have demonstrated superior performance. However, a comprehensive overview of these approaches is missing, which could hinder researchers and practitioners from understanding the current process and discovering potential for future improvement in the ML-based AWI community. In this paper, we systematically review the state-of-the-art ML-based AWI approaches. First, we employ a meticulous survey methodology and gather 51 primary studies from 2000/01/01 to 2023/09/01. Then, we outline a typical ML-based AWI workflow, including warning dataset preparation, preprocessing, AWI model construction, and evaluation stages. In such a workflow, we categorize ML-based AWI approaches based on the warning output format. Besides, we analyze the key techniques used in each stage, along with their strengths, weaknesses, and distribution. Finally, we provide practical research directions for future ML-based AWI approaches, focusing on aspects like data improvement (e.g., enhancing the warning labeling strategy) and model exploration (e.g., exploring large language models for AWI). Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Resilience of Quantum key Distribution Source Against Laser-Damage Attack by a Variety of Lasers

Resilience of Quantum Key Distribution Source Against Laser-...

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Conference on Lasers and Electro-Optics Europe (CLEO EUROPE)

作者： Daria Ruzhitskaya Irina Zhluktova Anastasiya Ponosova Daniil Trefilov Poompong Chaiwongkhot Anqi Huang Vladimir Kamynin Vadim Makarov Russian Quantum Center Skolkovo Moscow Russia NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow Russia Prokhorov General Physics Institute of Russian Academy of Sciences Moscow Russia MIREA - Russian Technological University Moscow Russia Vigo Quantum Communication Center University of Vigo Vigo Spain Department of Physics Faculty of Science Mahidol University Bangkok Thailand State Key Laboratory of High Performance Computing Institute for Quantum Information College of Computer Science and Technology National University of Defense Technology Changsha China Shanghai Branch National Laboratory for Physical Sciences at Microscale CAS Center for Excellence in Quantum Information University of Science and Technology of China Shanghai People's Republic of China

ISBN: (纸本)9798350345995

Quantum key distribution (QKD) systems provide quantum-safe key exchange. Therefore, complete security analysis of implementations of QKD protocols is in the focus of interest of a worldwide information-security community. For today, a number of QKD loopholes are closed by countermeasures, which are also considered in emerging QKD security evaluation and certification [1]–[3]. However, new threats to practical QKD implementations are still found, such as the laser-damage attack, which is a powerful hacking strategy. In investigations, CW laser radiation is most often used, but in contrast to it, the interaction of pulsed laser radiation with optical materials may lead to a wide range of effects, like nonlinear effects, dielectric breakdown, etc.

关键词： Fiber optic components high power lasers Nonlinear effects Optical materials Quantum key distribution Quantum key distribution networks

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Ultra-Fast Mini License Plate Recognition System Based-on Vision Processing Unit 20

Ultra-Fast Mini License Plate Recognition System Based-on Vi...

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Proceedings of the 2020 2nd International Conference on Big-data Service and Intelligent Computation

作者： Junhui Wang Shuangyin Ren Jiezhong He Xiaolan Ji Diqing Huang College of Computer National University of Defense Technology and State Key Laboratory of Mathematical Engineering and Advanced Computing China National Key Laboratory of Science and Technology on Information System Security Institute of Systems Engineering Academy of Military Science College of Computer National University of Defense Technology

ISBN: (纸本)9781450388399

As more embedded environments need license plate recognition systems, how to recognize car plates with high speed/accuracy and low energy has become an important and challenging problem. In this paper, we propose a ultra-Fast miNi (FaNi) license plate recognition (LPR) system. The FaNi system are divided into one training sub-system and one inference sub-system. The former are used to get some offline features; then, the latter is deployed online to recognize license numbers with nearly real-time speed. The inference system is comprised of the vision processing unit (VPU) and the display unit. These two parts are both implemented with hardware logic. Experiments show that the FaNi system can obtain high accuracy and high speed with low resource cost.

关键词： VPU Plate Recognition System FPGA

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Dadm: Enhancing Eeg Artifact Removal by Fusing Artifact Representation into the Time-Frequency Domain

SSRN

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SSRN 2024年

作者： Li, Haoran Feng, Fan Kang, Jiarong Zhang, Jin Gong, Xiaoli Lu, Tingjuan Sun, Zhe Solé-Casals, Jordi College of Computer Science Nankai University Tianjin China Department of Biomedical Engineering School of Medicine Tsinghua University Beijing China Tianjin Key Laboratory of Brain Science and Intelligent Rehabilitation Nankai University Tianjin China State Key Laboratory of High-end Server and Storage Technology China 903rd Hospital of PLA China Faculty of Medicine Faculty of Health Data Science Juntendo University Japan Data and Signal Processing Group University of Vic Central University of Catalonia Catalonia Vic08500 Spain

The electroencephalogram (EEG) provides essential data for analyzing brain activities. However, artifacts such as electrooculography (EOG) and electromyography (EMG) often interleave with the EEG signals, significantly affecting the quality of EEG signal analysis. The heterogeneous distribution of these artifacts in the time-frequency domain makes it challenging to remove multiple artifacts using a unified model. In this paper, we propose an Artifact-Aware EEG Denoising Model, referred to as DADM, to effectively remove various types of artifacts in a unified manner. We first obtain an artifact representation that indicates the type of artifact from a pre-trained artifact classification model. This artifact representation is then used as prior knowledge, which is fused into the denoising model in the frequency-time domain. This enables the model to become aware of the artifact type and precisely remove artifacts based on their type. Due to the heterogeneous distributions of artifacts in the frequency domain, we introduce a frequency enhancement module that can identify specific types of artifacts based on their representation and remove them using a hard attention mechanism. Additionally, we design a time-domain compensation module to enhance the denoising capability of DADM by compensating for potential losses of global information. Comprehensive experiments demonstrate that DADM significantly outperforms the Novel CNN in denoising EEG signals, showing a notable 7.77% improvement in correlation coefficient (CC) metrics. © 2024, The Authors. All rights reserved.

关键词： Electroencephalography

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Structure-Preserving Operator Learning: Modeling the Collision Operator of Kinetic Equations

arXiv

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arXiv 2024年

作者： Lee, Jae Yong Schotthöfer, Steffen Xiao, Tianbai Krumscheid, Sebastian Frank, Martin Center for Artificial Intelligence and Natural Sciences Korea Institute for Advanced Study Seoul Korea Republic of Oak Ridge National Laboratory Computer Science and Mathematics Division Oak RidgeTN United States State Key Laboratory of High Temperature Gas Dynamics Centre for Interdisciplinary Research in Fluids Institute of Mechanics Chinese Academy of Sciences Beijing China School of Engineering Science University of Chinese Academy of Sciences Beijing China Karlsruhe Institute of Technology Scientific Computing Center Karlsruhe76131 Germany

This work explores the application of deep operator learning principles to a problem in statistical physics. Specifically, we consider the linear kinetic equation, consisting of a differential advection operator and an integral collision operator, which is a powerful yet expensive mathematical model for interacting particle systems with ample applications, e.g., in radiation transport. We investigate the capabilities of the Deep Operator network (DeepONet) approach to modelling the high dimensional collision operator of the linear kinetic equation. This integral operator has crucial analytical structures that a surrogate model, e.g., a DeepONet, needs to preserve to enable meaningful physical simulation. We propose several DeepONet modifications to encapsulate essential structural properties of this integral operator in a DeepONet model. To be precise, we adapt the architecture of the trunk-net so the DeepONet has the same collision invariants as the theoretical kinetic collision operator, thus preserving conserved quantities, e.g., mass, of the modeled many-particle system. Further, we propose an entropy-inspired data-sampling method tailored to train the modified DeepONet surrogates without requiring an excessive expensive simulation-based data generation. © 2024, CC BY-NC-SA.

关键词： Kinetic energy

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Anomalous strain effect on the thermal conductivity of low-buckled two-dimensional silicene

引用

National science Review 2021年第9期8卷 23-31页

作者： Bin Ding Xiaoyan Li Wuxing Zhou Gang Zhang Huajian Gao Institute of High Performance Computing A*STAR Centre for Advanced Mechanics and Materials Applied Mechanics Laboratory Department of Engineering Mechanics Tsinghua University School of Materials Science and Engineering & Hunan Provincial Key Laboratory of Advanced Materials for New Energy Storage and Conversion Hunan University of Science and Technology School of Mechanical and Aerospace Engineering College of Engineering Nanyang Technological University

The thermal conductivity of two-dimensional materials, such as graphene, typically decreases when tensile strain is applied, which softens their phonon modes. Here, we report an anomalous strain effect on the thermal conductivity of monolayer silicene, a representative low-buckled two-dimensional (LB-2D)material. Reax FF-based molecular dynamics simulations are performed to show that biaxially stretched monolayer silicene exhibits a remarkable increase in thermal conductivity, by as much as 10 times the freestanding value, with increasing applied strain in the range of [0, 0.1], which is attributed to increased contributions from long-wavelength phonons. A further increase in strain in the range of [0.11, 0.18] results in a plateau of the thermal conductivity in an oscillatory manner, governed by a unique dynamic bonding behavior under extreme loading. This anomalous effect reveals new physical insights into the thermal properties of LB-2D materials and may provide some guidelines for designing heat management and energy conversion devices based on such materials.

关键词： low-buckled two-dimensional materials strain effect thermal conductivity bonding dynamics

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A lightweight collective communication based parallel algorithm for the greedy point selection in RBF mesh deformation 21

A lightweight collective communication based parallel algori...

引用

21st IEEE International Conference on high performance computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data science and Systems, HPCC/SmartCity/DSS 2019

作者： Zhao, Ran Li, Chao Guo, Xiaowei Fan, Sijiang Wang, Yi Liu, Yi Yang, Canqun State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781728120584

The greedy algorithm is one of the most efficient point selection method utilized by radial basis function (RBF) based mesh deformation in computational fluid dynamic (CFD). To improve the computational efficiency of the greedy process, several parallelization methods are developed in the past few years for the data reduction. However, these methods produce additional time cost because of the communication redundancy which can restrict the parallel scale. This paper proposes a new parallel strategy for the greedy selection in which a lightweight collective communication is adopted to replace the point-to-point communication. In addition, this strategy emphasizes that all the parallel processes operate under the same computational complexity as much as possible to reinforce the load balancing. Specifically, a three-dimension undulating fish model is utilized to validate the lightweight collective communication strategy. And finally, the proposed one gets up to 20% time performance improvement on average compared with two classic parallel methods. © 2019 IEEE.

关键词： Data reduction

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