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Asymmetric Sandwiched Nanofibrillated Cellulose Composites Prepared by One-Pot Vacuum Filtration for Ultrahigh Electromagnetic Interference Shielding

SSRN

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SSRN 2023年

作者： Qi, Wenjing Zeng, Lingjun Xue, Bai Wu, Changmei Mai, Xiaoping Xie, Lan Zheng, Qiang Department of Polymer Materials and Engineering College of Materials and Metallurgy Guizhou University Guiyang550025 China State Key Laboratory of Public Big Data Guizhou University Guiyang550025 China National Engineering Research Center for Compounding and Modification of Polymer Materials National and Local Joint Engineering Research Center for Functional Polymer Membrane Materials and Membrane Processes Guiyang550014 China Department of Polymer Science and Engineering Zhejiang University Hangzhou310027 China

High-efficiency electromagnetic interference (EMI) shielding composite films (EMI shielding effectiveness (SE) value > 100 dB) with a small thickness are imminently desired for eliminating the serious electromagnetic wave pollution. Herein, a series of asymmetric sandwiched silver-coated four-needle zinc oxide whisker/nanofibrillated cellulose/Ti3C2Tx (F-ZnO&Ag/NFC/Ti3C2Tx) composite films consisting of the loose F-ZnO&Ag sedimentary layer and compact upper Ti3C2Tx layer were successful fabricated by a facile one-pot vacuum filtration method in combination with gravity-induced delamination. Arising from the favorable electrical conductivity and unique asymmetric sandwich structure, electromagnetic waves can be trapped and dissipated in the F-ZnO&Ag skeletons and strongly multiply reflected between top Ti3C2Tx layer and bottom F-ZnO&Ag layers. Thereby, F-ZnO&Ag/NFC/Ti3C2Tx-30.4 exhibits the ultrahigh averaged EMI SET of 103.9 dB (the maximal value of 123.8 dB) at a low thickness of merely 209 μm, which is far superior to that of almost all the reported NFC composites at the similar thickness to date. In the real EMI shielding application test, F-ZnO&Ag/NFC/Ti3C2Tx composite films are confirmed to effectively block the transmission of controlled signal and switch off the toy car system. Such simple and high-efficiency asymmetric sandwich structure design makes a great progress towards preparing and adjusting thin EMI shielding composite films. © 2023, The Authors. All rights reserved.

关键词： Zinc oxide

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An Eagle-Leg-Inspired Manipulator Composed of a Grasping Mechanism Based on the Motion Law of the Eagle-Claw and an Ankle Joint Mechanism

SSRN

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SSRN 2023年

作者： Zhao, Ruiyuan Li, Xiaotong Chen, Jian Wu, Pengxi College of Engineering China Agricultural University Beijing100083 China Key Laboratory of Smart Agricultural Technology in Tropical South China Ministry of Agriculture and Rural Affairs Guangzhou510642 China Key Laboratory of Spatial‐temporal Big Data Analysis and Application of Natural Resources in Megacities MNR Shanghai200063 China Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural Resources Shenzhen518000 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China

In order to make the multi-rotor UAV more efficient to complete the contact operations such as picking, obstacle cleaning, grasping and inspired by the skeleton structure and motion law of the eagle's leg, this paper proposes a prototype design of a large load, wide range of movement, multiple DOF and collapsible manipulator. It is suitable for medium and larger size multi-rotor UAV. The main structure of the manipulator consists of a planetary reducer and a coupled parallel linkage mechanism. The reducer makes the manipulator more powerful, while the coupled parallel linkage mechanism can increase the movable range of the grasping mechanism. Based on the movement law of eagle’s claw, the grasping mechanism of the manipulator is designed. It can effectively increase the contact area between the target. In order to increase the DOF of the grasping mechanism, an ankle mechanism using a pair of double helical telescopic mechanisms to constrain the DOF of the universal joint is designed. It connects the grasping mechanism and the main structure of the manipulator. This paper shows the development process of the manipulator. The kinematic modeling and control of the manipulator are carried out. The ability of the manipulator system is tested, And the flight test experiment of the UAV carrying the manipulator is also executed. © 2023, The Authors. All rights reserved.

关键词： Manipulators

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A New Type Wireless data Center of Comb Topology 6th

A New Type Wireless Data Center of Comb Topology

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6th International Conference on data Science, ICDS 2019

作者： Zhang, Qingfang Han, Zhijie Du, Xiaoyu School of Computer and Information Engineering Henan University KaifengHenan475004 China Institute of Data and Knowledge Engineering Henan University KaifengHenan475004 China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Network NanjingJiangsu210003 China

ISBN: (纸本)9789811528095

In recent years, group communication has become more and more popular. In the current data center network, multicast plays an extremely important role in group communication. Traditional data center network is designed based on wires. Researchers have proposed Dcell, Bcube and other data center topologies successively. However, in the traditional data center network, the wired topology structure has the disadvantages of high overhead, complex deployment, high maintenance cost, slow heat dissipation and so on. Moreover, the existing wireless data center Flyways structure and Graphite structure have the problems of low connectivity and poor scalability. So this paper proposes and designs a new data center network topology Comb structure (Comb model is a multi-layer cellular structure model, which is a multi-layer structure composed of single-layer honeycomb-like structure interlaced with each other). The structure can effectively improve the connectivity of the data center, shorten the routing path, reduce the probability of node failure in the network, and ensure the smooth network. © Springer Nature Singapore Pte Ltd 2020.

关键词： Topology

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An Offline Assistance Tool for Visually Impaired People Based on Image Captioning

An Offline Assistance Tool for Visually Impaired People Base...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Guo, Yu Chen, Yue Xie, Yuanyan Ban, Xiaojuan Obaidat, Mohammad S. University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China University of Science and Technology Beijing Shunde Innovation School Foshan China School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China Institute of Artificial Intelligence University of Science and Technology Beijing Beijing China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing China King Abdullah Ii School of Information Technology University of Jordan Amman Jordan Amity University UP Noida India

ISBN: (纸本)9781665468190

Eye defects of visually impaired people bring great inconvenience to daily lives. With the rapid development of computers and artificial intelligence, some assistance tools and wearable devices have provided convenience to a certain extent, but they still possess many shortcomings, such as high prices, limited functionality, poor real-time performance, the inability to be used offline and so on. This paper designs an offline assistance tool specifically for visually impaired people that can help them perceive their surrounding environments by taking photos and reading the descriptions output by an image captioning model. Considering that the photos taken by visually impaired people may be incomplete, an improved image stitching method based on a genetic algorithm is proposed to obtain high-quality stitched images as the inputs of the image captioning model. An improved model pruning algorithm is also designed to compress and accelerate the image captioning model to meet the offline and real-time deployment requirements of portable devices. Experimental results and a practical tool show that the developed system based on an image captioning model and pruning can quickly and accurately describe environments, thus assisting visually impaired people anytime and anywhere. © 2022 IEEE.

关键词： Genetic algorithms

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Federated Unlearning with Gradient Descent and Conflict Mitigation 39

Federated Unlearning with Gradient Descent and Conflict Miti...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Pan, Zibin Wang, Zhichao Li, Chi Zheng, Kaiyan Wang, Boqi Tang, Xiaoying Zhao, Junhua The School of Science and Engineering The Chinese Univ of Hong Kong Shenzhen China The Shenzhen Institute of Artificial Intelligence and Robotics for Society China The Guangdong Provincial Key Laboratory of Future Networks of Intelligence China Department of Mathematics Department of Statistics University of Michigan United States Shenzhen Research Institute of Big Data China

ISBN: (纸本)157735897X

Federated Learning (FL) has received much attention in recent years. However, although clients are not required to share their data in FL, the global model itself can implicitly remember clients’ local data. Therefore, it’s necessary to effectively remove the target client’s data from the FL global model to ease the risk of privacy leakage and implement "the right to be forgotten". Federated Unlearning (FU) has been considered a promising way to remove data without full retraining. But the model utility easily suffers significant reduction during unlearning due to the gradient conflicts. Furthermore, when conducting the post-training to recover the model utility, the model is prone to move back and revert what has already been unlearned. To address these issues, we propose Federated Unlearning with Orthogonal Steepest Descent (FedOSD). We first design an unlearning Cross-Entropy loss to overcome the convergence issue of the gradient ascent. A steepest descent direction for unlearning is then calculated in the condition of being non-conflicting with other clients’ gradients and closest to the target client’s gradient. This benefits to efficiently unlearn and mitigate the model utility reduction. After unlearning, we recover the model utility by maintaining the achievement of unlearning. Finally, extensive experiments in several FL scenarios verify that FedOSD outperforms the SOTA FU algorithms in terms of unlearning and model utility. Copyright © 2025, Association for the Advancement of Artificia Intelligence (***). All rights reserved.

关键词： Federated learning

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Robust Beamforming Design for Near-Field DMA-NOMA mmWave Communications With Imperfect Position Information

arXiv

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arXiv 2024年

作者： Xiu, Yue Zhao, Yang Yang, Songjie Zhang, Yufeng Niyato, Dusit Du, Hongyang Wei, Ning The National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China Chengdu611731 China Nanyang Technological University Singapore The Department of Electronic Engineering Tsinghua University Beijing100084 China The College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore

For millimeter-wave (mmWave) non-orthogonal multiple access (NOMA) communication systems, we propose an innovative near-field (NF) transmission framework based on dynamic metasurface antenna (DMA) technology. In this framework, a base station (BS) utilizes the DMA hybrid beamforming technology combined with the NOMA principle to maximize communication efficiency between near-field users (NUs) and far-field users (FUs). In conventional communication systems, obtaining channel state information (CSI) requires substantial pilot signals, significantly reducing system communication efficiency. We propose a beamforming design scheme based on position information to address with this challenge. This scheme does not depend on pilot signals but indirectly obtains CSI by analyzing the geometric relationship between user position information and channel models. However, in practical applications, the accuracy of position information is challenging to guarantee and may contain errors. We propose a robust beamforming design strategy based on the worst-case scenario to tackle this issue. Facing with the multivariable coupled non-convex problems, we employ a dual-loop iterative joint optimization algorithm to update beamforming using block coordinate descent (BCD) and derive the optimal power allocation (PA) expression. We analyze its convergence and complexity to verify the proposed algorithm’s performance and robustness thoroughly. We validate the theoretical derivation of the CSI error bound through simulation experiments. Numerical results show that our proposed scheme performs better than traditional beamforming schemes. Additionally, the transmission framework exhibits strong robustness to NU and FU position errors, laying a solid foundation for the practical application of mmWave NOMA communication systems. The NF transmission framework for mmWave NOMA communication systems based on DMA technology proposed in this work shows significant advantages in improving communication

关键词： Beamforming

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Full Bayesian Significance Testing for Neural Networks

arXiv

引用

arXiv 2024年

作者： Liu, Zehua Li, Zimeng Wang, Jingyuan He, Yue School of Computer Science and Engineering Beihang University Beijing China School of Economics and Management Beihang University Beijing China Key Laboratory of Data Intelligence and Management Beihang University Ministry of Industry and Information Technology Beijing China Department of Computer Science and Technology Tsinghua University Beijing China

Significance testing aims to determine whether a proposition about the population distribution is the truth or not given observations. However, traditional significance testing often needs to derive the distribution of the testing statistic, failing to deal with complex nonlinear relationships. In this paper, we propose to conduct Full Bayesian Significance Testing for neural networks, called nFBST, to overcome the limitation in relationship characterization of traditional approaches. A Bayesian neural network is utilized to fit the nonlinear and multi-dimensional relationships with small errors and avoid hard theoretical derivation by computing the evidence value. Besides, nFBST can test not only global significance but also local and instance-wise significance, which previous testing methods don’t focus on. Moreover, nFBST is a general framework that can be extended based on the measures selected, such as Grad-nFBST, LRP-nFBST, DeepLIFT-nFBST, LIME-nFBST. A range of experiments on both simulated and real data are conducted to show the advantages of our method. Copyright © 2024, The Authors. All rights reserved.

关键词： Lime

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Fuel source shift or cost reduction:Context-dependent adaptation strategies in closely related Neodon fuscus and Lasiopodomys brandtii against hypoxia

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Zoological Research 2022年第4期43卷 497-513页

作者： Xiu-Juan Li Cong-Cong Qiao Bo-Jian Chen Meng-Yang Li Peng Chen Mao-Lin Huang Chun-Xiao Chen Yan Liu Han Cheng Meng-Wan Jiang Lu-Ye Shi Zhen-Long Wang School of Life Sciences Zhengzhou UniversityZhengzhouHenan 450001China College of Environmental Science and Engineering Tongji UniversityShanghai 200092China Jiaxing-Tongji Environmental Research Institute JiaxingZhejiang 314051China State Key Laboratory of Genetic Resources and Evolution Kunming Institute of ZoologyChinese Academy of SciencesKunmingYunnan 650223China Kunming College of Life Science University of Chinese Academy of SciencesKunmingYunnan 650223China School of Artificial Intelligence and Big Data Henan University of TechnologyZhengzhouHenan 450001China

Oxygen is essential for most life *** oxygen supply can disrupt homeostasis and compromise survival,and hypoxia-induced cardiovascular failure is fatal in many animals,including ***,certain species have adapted and evolved to cope with hypoxic environments and are therefore good models for studying the regulatory mechanisms underlying responses to ***,we explored the physiological and molecular responses of the cardiovascular system in two closely related hypoxiaadapted species with different life histories,namely,Qinghai voles(Neodon fuscus)and Brandt’s voles(Lasiopodomys brandtii),under hypoxic(10%O_(2) for 48 h)and normoxic(20.9%O_(2) for 48 h)*** mice(Mus musculus)were used for *** voles live in plateau areas under hypoxic conditions,whereas Brandt’s voles only experience periodic *** and hematological analyses indicated a strong tolerance to hypoxia in both species,but significant cardiac tissue damage and increased blood circulation resistance in mice exposed to *** transcriptome analysis revealed enhanced oxygen transport efficiency as a coping mechanism against hypoxia in both *** and ***,but with some ***,*** showed upregulated expression of genes related to accelerated cardiac contraction and angiogenesis,whereas *** showed significant up-regulation of erythropoiesis-related *** upregulation of hemoglobin synthesis-related genes was observed in both *** addition,differences in cardiometabolic strategies against hypoxia were observed in the ***,*** relied on adenosine triphosphate(ATP)generation via fatty acid oxidation,whereas *** shifted energy production to glucose oxidation under hypoxic conditions and *** employed a conservative strategy involving down-regulation of fatty acid and glucose oxidation and a bradycardia *** conclusion,the cardiovascular sys

关键词： Heart Hypoxia Lasiopodomys brandtii Neodon fuscus RNA sequencing

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Few-shot Class-Incremental Semantic Segmentation via Pseudo-Labeling and knowledge Distillation

arXiv

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arXiv 2023年

作者： Jiang, Chengjia Wang, Tao Li, Sien Wang, Jinyang Wang, Shirui Antoniou, Antonios Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions Wuyi University Wuyishan China College of Computer and Data Science Fuzhou University Fuzhou China Department of Computer Science and Engineering European University Cyprus Nicosia Cyprus

We address the problem of learning new classes for semantic segmentation models from few examples, which is challenging because of the following two reasons. Firstly, it is difficult to learn from limited novel data to capture the underlying class distribution. Secondly, it is challenging to retain knowledge for existing classes and to avoid catastrophic forgetting. For learning from limited data, we propose a pseudo-labeling strategy to augment the few-shot training annotations in order to learn novel classes more effectively. Given only one or a few images labeled with the novel classes and a much larger set of unlabeled images, we transfer the knowledge from labeled images to unlabeled images with a coarse-to-fine pseudo-labeling approach in two steps. Specifically, we first match each labeled image to its nearest neighbors in the unlabeled image set at the scene level, in order to obtain images with a similar scene layout. This is followed by obtaining pseudo-labels within this neighborhood by applying classifiers learned on the few-shot annotations. In addition, we use knowledge distillation on both labeled and unlabeled data to retain knowledge on existing classes. We integrate the above steps into a single convolutional neural network with a unified learning objective. Extensive experiments on the Cityscapes and KITTI datasets validate the efficacy of the proposed approach in the self-driving domain. Code is available from https://***/ChasonJiang/FSCILSS. Copyright © 2023, The Authors. All rights reserved.

关键词： Distillation

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StreamMOS: Streaming Moving Object Segmentation with Multi-View Perception and Dual-Span Memory

arXiv

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arXiv 2024年

作者： Li, Zhiheng Cui, Yubo Zhong, Jiexi Fang, Zheng Faculty of Robot Science and Engineering Northeastern University Shenyang110819 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education Northeastern University Shenyang110819 China

Moving object segmentation based on LiDAR is a crucial and challenging task for autonomous driving and mobile robotics. Most approaches explore spatio-temporal information from LiDAR sequences to predict moving objects in the current frame. However, they often focus on transferring temporal cues in a single inference and regard every prediction as independent of others. This may lead to inconsistent segmentation results for the same object across different frames. To solve this issue, we propose a streaming network with a memory mechanism, called StreamMOS, to build the association of features and predictions among multiple inferences. Specifically, we utilize a short-term memory to convey historical features, which can be regarded as spatial priors of moving objects and are used to enhance current inference by temporal fusion. Meanwhile, we build a long-term memory to store previous predictions and exploit them to refine current forecasts at the voxel and instance levels through voting. Besides, we apply multi-view encoder with cascaded projection and asymmetric convolution to extract motion feature of objects in different representations. Extensive experiments validate that our algorithm gets competitive performance on SemanticKITTI and Sipailou Campus datasets. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep learning

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