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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Dai, Tao Lin, Yang Guo, Hang Wang, Jinbao Zhu, Zexuan College of Computer Science and Software Engineering Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen China Shenzhen City Key Laboratory of Embedded System Design Shenzhen China Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen China

ISBN: (纸本)157735897X

Knowledge distillation (KD) has recently gained great success in the field of object detection. By transferring the knowledge of the spatial or channel domain from the teacher model to the student model, it allows for a more compact representation with minimal performance loss. Despite this progress, existing KD methods typically treat knowledge from spatial or channel domains independently, ignoring the exploitation of the mutual relationship between these domains. In this work, we first explore the connection between spatial and channel domains and find there exists a strong correlation between them, i.e. the salient channels tend to contain significant object regions in the spatial domain. Motivated by this observation, we propose DCSF-KD, a novel Dynamic Channel-wise Spatial Feature Knowledge Distillation framework for object detection by fully exploiting both spatial and channel knowledge. Specifically, we introduce channel-wise spatial feature distillation and global channel attention distillation, using information from both domains to improve the accuracy of the student network. Experiments demonstrate that our DCSF-KD outperforms existing detection methods on both homogeneous and heterogeneous teacher-student network pairs. For example, when using the MaskRCNN-Swin detector as the teacher, and based on RetinaNet and FCOS with ResNet-50 on MS COCO, our DCSF-KD can achieve 41.9% and 44.1% mAP, respectively. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Students

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Research and Application of Nuclear reactor Computational Data Framework Based on HDF5 7th

Research and Application of Nuclear Reactor Computational Da...

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7th International Conference on Artificial Intelligence and Security, ICAIS 2021

作者： Lu, Wei Feng, Jintao Yang, Hao Zeng, Hui Pan, Junjie Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China School of Computer Science Chengdu University of Information Technology Chengdu610225 China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China

ISBN: (纸本)9783030786175

Nuclear reactor computing software need to process and maintain complex and massive data sets. In order to meet the requirement of mass data storage and processing in software, the data storage model and I/O method and programming interface of HDF5 (Hierarchical Data Format v5) are deeply studied. According to the data storage and processing requirement of typical nuclear reactor computing data such as assembly or core neutronics computing data and core thermal-hydraulic computing data, RCDF-H5 (reactor Compute Data Framework based on HDF5) is proposed. KYMRES (KYlin-2 Main RESults databank) and COMRES (COre Main RESults databank) are designed and implemented based on RCDF-H5. The performance tests show that RCDF-H5 has a higher I/O efficiency than conventional storage solutions. A new data storage and management solution for nuclear reactor computing software is provided. © 2021, Springer Nature Switzerland AG.

关键词： Digital storage

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Experimental study on the sub-channel void fraction characteristics of bubbly flow in rod bundles

Experimental study on the sub-channel void fraction characte...

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2020 International Conference on Nuclear Engineering, ICONE 2020, collocated with the ASME 2020 Power Conference

作者： Ren, Quan-Yao Pu, Zeng-Ping Zheng, Mei-Yin Su, Min Chen, Ping Pan, Liang-Ming He, Hui He, Qing-Che Science and Technology on Reactor System Design Technology Laboratory Chengdu China Chongqing China

ISBN: (纸本)9780791883785

The gas-liquid two-phase flow behaviors are always associated with its dynamic void fraction, such as flow resistance, heat transfer coefficient, phase distribution, critical heat flux etc. As regard to the commercial PWR and BWR, rod bundles are the typical geometry, which contains many subchannels for coolant flowing. In present study, the sub-channel void fraction was measured in 5×5 rod bundles with the subchannel impedance void meter consisting of 12 strip electrodes. Based on the measured void fraction in different sub-channels, the void fraction dynamics, PDF (probability distribution function) and CDF (cumulative distribution function) curves were analyzed to make clear the effect of superficial gas and liquid velocity, flow development and casing tube. The empirical correlation for PDF of dynamic sub-channel void fraction has been developed, which showed good fitness with PDF and CDF curves and satisfying accuracy of averaged void fraction. © 2020 American Society of Mechanical Engineers (ASME). All rights reserved.

关键词： Void fraction

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An Adaptive Bionic Sensor: Enhancing Ankle Joint Tracking with High Sensitivity and Superior Cushioning Performance

SSRN

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SSRN 2024年

作者： Jin, Jianqiao Zhang, Chen Zhao, Jianyuan Yu, Minghan Lei, Ming Jin, Chun Yin, Rui Zhao, Weiwei Sauvage Laboratory for Smart Materials The School of Integrated Circuit Harbin Institute of Technology Shenzhen518055 China Shenzhen Key Laboratory of Flexible Printed Electronics Technology Harbin Institute of Technology Shenzhen518055 China State Key Laboratory of Advanced Welding & Joining Harbin Institute of Technology Harbin150001 China Human-Computer Interaction Design Lab School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen518055 China

Flexible sensors are renowned for their rapid responsiveness, high flexibility, and outstanding mechanical properties, making them ideal for applications in wearable devices, sports and health monitoring, and human-machine interfaces. To enhance the sensing performance of these flexible sensors, researchers have drawn inspiration from nature, creating various bionic microstructures. However, these structures often manifest in the macroscopic form of thin films, which do little to improve impact resistance and joint protection. In response, this work achieves a highly sensitive and impact-resistant pressure sensor by integrating bionic principles at both micro and macro levels. Specifically, at the micro level, a muscle-like hydrogel system consisting of MXene nanosheets incorporated into the double network of polyvinyl alcohol and sodium alginate matrix is selected. At the macro level, the bionic prototypes of mimosa leaves and durian spikes with good energy absorption structure, together with octopus’ sucker with good adsorption capacity are selected, and the synergistic construction of the three structures is realized through 3D printing methods. The obtained sensor has an appropriate response range, sensitivity and stability. More importantly, the displacement deformation of the hydrogel can be reduced by 91.22%, while its adhesion strength can be increased by 57.5% compared to the unstructured hydrogel. As a proof-of-concept, the proposed bionic flexible sensor can be used to monitor the motion status of the human ankle joint in real-time, thereby assisting users in making real-time judgments on gait health. © 2024, The Authors. All rights reserved.

关键词： Sodium alginate

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PCA-W: An Simulation Algorithm for Waterlogging in Ground Point Cloud Based On Principal Component Analysis

PCA-W: An Simulation Algorithm for Waterlogging in Ground Po...

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Big Data, Information and Computer Network (BDICN), International Conference on

作者： Yucong Duan Yifan Zhang Ziwen Xu Jie Ma National Key Laboratory of Science and Technology on Multi-spectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan Hubei China China Ship Development and Design Center Wuhan Hubei China

ISBN: (数字)9798350363821

ISBN: (纸本)9798350374612

In the context of autonomous driving, ground point clouds play an important role in system decision-making. However, in the case of adverse weather, ground point clouds may suffer from a certain degree of missing data, which will have a negative impact on some downstream tasks of autonomous driving. With the development of autonomous driving algorithms, deep learning has achieved better results in this field. However, due to the lack of point cloud data sets under adverse weather conditions, the network cannot be effectively trained. This paper proposes a simulation algorithm for ground point clouds with water accumulation, which simulates the phenomenon of missing data in the ground point clouds due to road water accumulation in adverse weather. As a data augmentation method, it can expand the data set for downstream tasks. We evaluated the method on the STF dataset and proved its effectiveness.

关键词： Point cloud compression Deep learning Meteorological radar Laser radar Roads Data augmentation Task analysis

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BDGSE: A Symbolic Execution Technique for High MC/DC

BDGSE: A Symbolic Execution Technique for High MC/DC

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IEEE International Conference on Software Quality, Reliability and Security (QRS)

作者： Huangli Cai Zhiyi Zhang Yifan Jian Dan Li Zhiqiu Huang Collage of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu China Ministry Key Laboratory for Safety-Critical Software Development and Verification Nanjing University of Aeronautics and Astronautics Nanjing China

Modified Condition/Decision Coverage (MC/DC) is a test coverage standard with excellent fault detection capability, which is widely used in testing safety-critical software. Symbolic execution generates test cases automatically to achieve high code coverage. However, since symbolic execution uses short-circuit evaluation to evaluate decisions, it fails to guarantee the consistency of other conditions in a decision required by the MC/DC criterion. As a result, it is incapable of generating MC/DC test cases to test safety-critical systems adequately. To solve this problem, we propose Branch Dependence Guided Symbolic Execution (BDGSE), a symbolic execution technique for high MC/DC. The approach utilizes static analysis to compute the branch dependencies, then guides symbolic execution to selectively explore paths and simplify test cases, and finally generates a small number of test cases to achieve high MC/DC coverage. Our experimental results show that BDGSE can generate high-quality test cases. Although BDGSE generates fewer test cases, it can achieve higher MC/DC coverage than SPF and random methods, and the fault detection capability of test cases generated by BDGSE is comparable to that of test cases generated by SPF.

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Deep Learning-Enabled ISAC-OTFS Pre-equalization design for Aerial-Terrestrial Networks

arXiv

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arXiv 2024年

作者： Wang, Weihao Guo, Jing Wang, Siqiang Wang, Xinyi Yuan, Weijie Fei, Zesong the School of Information and Electronics Beijing Institute of Technology Beijing100081 China the School of System Design and Intelligent Manufacturing The Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen518055 China

Orthogonal time frequency space (OTFS) modulation has been viewed as a promising technique for integrated sensing and communication (ISAC) systems and aerial-terrestrial networks, due to its delay-Doppler domain transmission property and strong Doppler-resistance capability. However, it also suffers from high processing complexity at the receiver. In this work, we propose a novel pre-equalization based ISAC-OTFS transmission framework, where the terrestrial base station (BS) executes pre-equalization based on its estimated channel state information (CSI). In particular, the mean square error of OTFS symbol demodulation and Cramér-Rao lower bound of sensing parameter estimation are derived, and their weighted sum is utilized as the metric for optimizing the pre-equalization matrix. To address the formulated problem while taking the time-varying CSI into consideration, a deep learning enabled channel prediction-based pre-equalization framework is proposed, where a parameter-level channel prediction module is utilized to decouple OTFS channel parameters, and a low-dimensional prediction network is leveraged to correct outdated CSI. A CSI processing module is then used to initialize the input of the pre-equalization module. Finally, a residual-structured deep neural network is cascaded to execute pre-equalization. Simulation results show that under the proposed framework, the demodulation complexity at the receiver as well as the pilot overhead for channel estimation, are significantly reduced, while the symbol detection performance approaches those of conventional minimum mean square error equalization and perfect CSI. Copyright © 2024, The Authors. All rights reserved.

关键词： Channel estimation

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A Nonlinear Disturbance Observer Based on Sliding Mode Control for a Lower Limber Exoskeleton Robot 7

A Nonlinear Disturbance Observer Based on Sliding Mode Contr...

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7th Asia-Pacific Conference on Intelligent Robot systems, ACIRS 2022

作者： Luo, Wenbo Liu, Haokun Yang, Xishun Zhang, Sen Ge, Weimin Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control National Demonstration Center for Experimental Mechanical and Electrical Engineering Education School of Mechanical Engineering Tianjin300384 China

ISBN: (数字)9781665485197

ISBN: (纸本)9781665485197

During the process of human-robot cooperative motion, the internal frictions and modeling errors existing in the system may significantly deteriorate the control precision of a lower limb exoskeleton. To compensate the uncertainty during the human-robot cooperative motion, a nonlinear disturbance observer based sliding mode control strategy is designed in this paper. Firstly, the dynamic model of a lower limb exoskeleton is established. Secondly, low-pass filter and nonlinear disturbance observer are designed to observe the uncertain disturbance and modeling errors. Then, a high-order sliding mode controller is designed to ensure the control precision of the human-robot interaction system. Finally, the effectiveness and reliability of the designed control method are verified with the joint simulation between MATLAB and ADAMS. © 2022 IEEE.

关键词： Sliding mode control

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Magnetically controlled topological braiding with Majorana corner states in second-order topological superconductors

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Physical Review B 2024年第11期109卷 115413-115413页

作者： Lizhou Liu Chengming Miao Hanzhao Tang Ying-Tao Zhang Zhenhua Qiao College of Physics Hebei Normal University Shijiazhuang 050024 China Department of Mathematics and Physics Shijiazhuang Tiedao University Shijiazhuang 050043 China International Centre for Quantum Design of Functional Materials University of Scienceand Technology of China Hefei Anhui 230026 China CAS Key Laboratory of Strongly-Coupled Quantum Matter Physics and Department of Physics University of Science and Technology of China Hefei Anhui 230026 China Hefei National Laboratory University of Science and Technology of China Hefei 230088 China

We theoretically investigate the electronic properties of finite-sized (e.g., triangular and diamond-shaped) Kane-Mele-type topological insulator nanoflakes on top of an s-wave superconductor. We find that the second-order topological superconductor can be generated when the magnetism is only applied on the system boundaries, which host two Majorana corner states located at the corners of two neighboring boundaries. By tuning the applied boundary magnetism, we observe that two isolated Majorana corner states can be adiabatically moved along the system boundaries. Furthermore, we show the possibility of performing topological quantum braiding of the Majorana corner states towards the far-reaching implications of quantum information and quantum computation.

关键词： Edge states Kane-Mele model Topological materials Topological superconductors Quantum dots Two-dimensional electron system Lattice models in condensed matter Materials modeling Tight-binding model

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Optimal design for the Torsional Elastic Element Topology of a Rotary Series Elastic Actuator 7

Optimal Design for the Torsional Elastic Element Topology of...

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7th Asia-Pacific Conference on Intelligent Robot systems, ACIRS 2022

作者： Yang, Xishun Luo, Wenbo Liu, Haokun Zhang, Sen Ge, Weimin Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control National Demonstration Center for Experimental Mechanical and Electrical Engineering Education School of Mechanical Engineering Tianjin300384 China

ISBN: (数字)9781665485197

ISBN: (纸本)9781665485197

The series elastic actuator improves the compliance of exoskeleton by introducing a elastic element and ensures its safe interaction ability. Therefore, it is regarded as a new driving mechanism by scholars. Suitable elastic element is conducive to realize the miniaturization and lightweight of SEA, but its topology design is complex and lack of guidance. Based on the finite element simulation environment and three-dimensional parametric CAD environment, this paper analyzes the influence of different size parameters and topology on the pressure of the elastic element, summarizes the characteristics of three topology structures, and puts forward the optimal design method of a torsional elastic element topology. Through the research, we can conclude that the compression effect of elastic beam with specific shape is better than that of curved elastic beam, and the width of elastic beam has a great influence on the torsional elastic element. © 2022 IEEE.

关键词： Finite element method

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