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arXiv 2021年

作者： Xu, Bo Wang, Peng He, Yijia Chen, Yu Chen, Yongnan Zhou, Ming School of Geodesy and Geomatics Wuhan University Wuhan430079 China Faculty of Robot Science and Engineering Northeastern University Shenyang110819 China Kuaishou Technology Beijing100000 China

Leveraging line features to improve the accuracy of the SLAM system has been studied in many works. However, making full use of the characteristics of different line features (parallel, non-parallel) to improve the SLAM system is rarely mentioned. In this paper, we designed a VIO system based on points and straight lines, which divides straight lines into structural straight lines (that is, straight lines parallel to each other) and non-structural straight lines. In addition, in order to optimize the line features effectively, we only used two parameters to minimize the representation of the structural straight line and the non-structural straight line. Furthermore, we designed a straight line matching strategy based on 2D-2D and 2D-3D matching methods to improve the success rate of straight line matching. We conducted ablation experiments on synthetic data and public datasets, as well as compared our algorithm with state-of-the-art algorithms. The experiments verified the combination of different line features can improve the accuracy of the VIO system, and also demonstrated the effectiveness of our system. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

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Distributed Event-Triggered Bandit Convex Optimization With Time-Varying Constraints

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IEEE Transactions on Control of Network Systems 2025年

作者： Zhang, Kunpeng Yi, Xinlei Wen, Guanghui Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Ministry of Education Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai201210 China Southeast University School of Automation Nanjing210096 China University of Groningen Engineering and Technology Institute Groningen Faculty of Science and Engineering GroningenAG 9747 Netherlands KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm10044 Sweden KTH Royal Institute of Technology Digital Futures Stockholm10044 Sweden

This paper considers the distributed bandit convex optimization problem with time-varying inequality constraints over a network of agents, where the goal is to minimize network regret and cumulative constraint violation. Existing distributed online algorithms solving this problem require that each agent broadcasts its decision to its neighbors at each iteration. However, communication resources are often limited. To better utilize communication resources, we propose a distributed event-triggered online primal-dual algorithm with two-point bandit feedback. Under several classes of appropriately chosen decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. These bounds are comparable to the results achieved by distributed event-triggered online algorithms with full-information feedback. Finally, a numerical example is provided to verify the theoretical results. © 2014 IEEE.

关键词： Optimization algorithms

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Correction to: Person search via class activation map transferring

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Multimedia Tools and Applications 2022年第6期82卷 9553-9553页

作者： Li, Ruilong Zhang, Yunzhou Zhu, Shangdong Liu, Shuangwei College of Information Science and Engineering Northeastern University of China Shenyang China Faculty of Robot Science and Engineering Northeastern University of China Shenyang China

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Dense Stereo Matching Optimization Algorithm based on Image Segmentation and ORB Gravitational Field

Dense Stereo Matching Optimization Algorithm based on Image ...

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2019 IEEE International Conference on Unmanned Systems, ICUS 2019

作者： Xu, Chenglong Wu, Chengdong Qu, Daokui Tian, Daji Song, Jilai Wang, Xiaofeng Northeastern University SIASUN Robot Automation Co. Ltd Faculty of Robot Science and Engineering Shenyang China Northeastern University Faculty of Robot Science and Engineering Shenyang China SIASUN Robot Automation Co. Ltd Shenyang China

ISBN: (纸本)9781728137926

This paper reference the data field ideology from Cognitive Physics, presents a novel dense stereo matching method, in which the cost metric of robustness to texture-less and occluded regions. In order to correct the mismatching and constrain error propagation in cost aggregation, Oriented FAST and Rotated BRIEF (ORB) gravitational field is introduced to the traditional matching cost metrics on the basis of previous studies. Strong feature points can be regarded as correct depth estimation points, which can be used as the center to establish gravitational field for effective energy transmission of each pixel. Then the combined matching cost metrics are aggregated exploiting image segmentation structure. Finally, the experiments on the stereo images of datasets and ours prove that the proposed algorithm has better performance in matching accuracy and robustness. © 2019 IEEE.

关键词： Image segmentation

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Exclusive Lasso Assisted Two-Stage Fuzzy-Rough Feature Selection

TechRxiv

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TechRxiv 2023年

作者： Qu, Yanpeng Qiu, Lin Shang, Changjing Shen, Qiang The College of Artificial Intelligence Dalian Maritime University Dalian116026 China The College of Computer Science and Engineering Northeastern University Shenyang110819 China The Department of Computer Science Faculty of Business and Physical Sciences Aberystwyth University Aberystwyth CeredigionSY23 3DB United Kingdom

Fuzzy-rough sets (FRS) encapsulate the related but distinct concepts of vagueness (for fuzzy sets) and indiscernibility (for rough sets), both of which occur as a result of uncertainty in data, information or knowledge. The application of FRS in feature selection (FS) has employed the dependency degree to guide the FS process with much success. Whilst promising, most existing fuzzy-rough feature selection (FRFS) approaches are only conducted at the level of individual features, considering the inclusion/exclusion of individual features with regard to a candidate feature subset. In this case, the insight of meaningful information about certain inherent feature structure, such as the correlation between features or the collaborative contribution to a common decision may be ignored. To address this issue, an exclusive lasso assisted two-stage fuzzy-rough FS (EL-TSFRFS) method is presented in this paper. First, regarding discernibility, all features are divided into distinct groups using k-means clustering and the exclusive lasso regularization is utilised to select the representative features in each cluster, with such selected features sorted in descending order within the cluster. Second, a feature grouping-based FRFS algorithm is implemented to further determine the final discriminating feature subset. Comparative experimental results show that the reduct gained by the proposed approach generally outperforms those attained by alternative implementations of FRFS, in terms of both the size of the selected feature subset and the subsequent classification accuracy using the feature subset. © 2023, CC BY.

关键词： Feature Selection

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Manipulability of the Kondo effect in a T-shaped triple-quantum-dot structure

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Physical Review B 2020年第8期102卷 085418-085418页

作者： Guang-Yu Yi Cui Jiang Lian-Lian Zhang Su-Rui Zhong Hao Chu Wei-Jiang Gong College of Sciences Northeastern University Shenyang 110819 China Basic Department Shenyang Institute of Engineering Shenyang 110136 China Faculty of Robot Science and Engineering Northeastern University Shenyang 110819 China

We theoretically investigate the Kondo effect of a T-shaped triple-quantum-dot structure, by means of the numerical renormalization group method. It is found that the system's entropy and conductance have opportunities to exhibit abundant transition processes for different interdot-coupling manners, with the decrease of temperature. All these results are caused by different Kondo physics mechanisms. Moreover, in the presence of appropriate parameters, the three-stage Kondo effect comes into being. Next when the electron-hole symmetry is broken or the structural parameters are changed, the Kondo resonance can also be observed in the conductance spectrum. However, it shows alternative dependence on the relevant quantities, i.e., the Coulomb interaction and interdot couplings. All these phenomena exhibit interesting Kondo physics in this system. We believe that this work can be helpful for further understanding of the Kondo effect in the triple-quantum-dot structures.

关键词： Kondo effect Quantum transport Renormalization group

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Signal propagation parameters estimation through designed multi layer fibre with higher dominant modes using OptiFibre simulation

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Journal of Optical Communications 2024年第0期45卷 s453-s463页

作者： Zaki Rashed, Ahmed Nabih Ahammad, S.K. Hasane Daher, Malek G. Sorathiya, Vishal Siddique, Abrar Asaduzzaman, Sayed Rehana, Hasin Dutta, Nitul Patel, Shobhit K. Nyangaresi, Vincent Omollo Jibon, Rayhan Habib Ibrahim, Anas Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering Menoufia University Menouf32951 Egypt Department of ECE Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522302 India Physics Department Islamic University of Gaza P.O. Box 108 Gaza Palestine Department of Information and Communication Technology Marwadi University Rajkot India Department of Smart Robot Convergence and Application Engineering Pukyong National University Busan48513 Korea Republic of Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Computer Science and Engineering Rangamati Science and Technology University Rangamati Bangladesh Department of Computer Science and Engineering Daffodil International University Dhaka Bangladesh Computer Science and Engineering Department SRM University Andhra Pradesh Guntur India Electronics and Communication Engineering Department Marwadi University Gujarat Rajkot India Tom Mboya University College P.O. Box 199-40300 Homabay Kenya Electronics and Communication Engineering Discipline Khulna University Khulna9208 Bangladesh

The aim and scope of the paper is to simulate the signal propagation parameters estimation through designed multi-layer fibre with higher dominant modes by using OptiFibre simulation software. The multi-layer fibre profile has a length of 1000 m is designed and clarified with six layers. RI difference profile variations are clarified with radial distance variations. Modal/group index, group delay, dispersion, mode field diameter and total fibre losses are demonstrated with the fibre wavelength variations. All the dominant mode field distribution for multi-layer fibre are simulated and demonstrated. The other modes for designed multi-layer fibre with the theoretical fibre cutoff values for the different modes based the designed multi-layer fibre are analyzed and clarified clearly in details. © 2022 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Parameter estimation

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Multi-level Feature Fusion Facial Expression Recognition Network

Multi-level Feature Fusion Facial Expression Recognition Net...

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第32届中国控制与决策会议

作者： Qian Hu Chengdong Wu Jianning Chi Xiaosheng Yu Huan Wang College of Information Science and Engineering Northeastern University College of Robot Science and Engineering Northeastern University

In order to solve the problems of face features extraction and the long time consuming in network training,we propose a facial expression recognition network based on multi-level feature fusion *** network structure consists of the following three parts:The multi-level feature fusion block;The multi-granularity feature extraction unit;The global feature fusion structure composed of global residual *** evaluated our proposed algorithm on the CK+dataset and FER2013 dataset,and finally achieved 94.07% accuracy and 65.4% accuracy *** results show that our algorithm can effectively improve the accuracy of expression recognition tasks.

关键词： Expression recognition Deep learning Convolutional neural network Multi-level feature fusion Multigranularity feature extraction

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Effect of Introduction of Mxene on Low Energy Plasma Electrolytic Oxidation

SSRN

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SSRN 2024年

作者： Zhang, Zheng Xu, Chenkai Zou, Minmin Vasilić, Rastko Lu, Xiaopeng Gu, Lijiang Zeng, Dongmei Zhang, Ting Chen, Fei Zhang, You College of New Materials and Chemical Engineering Hydrogen Energy Research Centre Beijing Institute of Petrochemical Technology Beijing102617 China University of Belgrade Faculty of Physics Studentski Trg 12–16 Belgrade11000 Serbia Shenyang National Laboratory for Materials Science Northeastern University Shenyang110819 China

This article describes how 2D MXene-containing coatings on magnesium alloy LA91 which are made utilizing the low-energy plasma electrolytic oxidation (LePEO) processing limit substrate corrosion and provide wear resistance. Corrosion resistance, wear resistance and microhardness of the coating are improved while the voltage required for the PEO process is reduced. Addition of MXene to electrolyte increases its conductivity and results in incorporation of MXene into oxide coating. Although the coating thickness is reduced, it has excellent corrosion resistance, wear resistance and high hardness. The PEO coating, enriched with MXene, exhibits impressive performance metrics compared to the Mg-Li alloy substrate. Its corrosion current density is only 3.3% of that of the Mg-Li alloy, while the average friction coefficient is just 39.9% and hardness is 6.6 times higher. Moreover, it demonstrates enduring corrosion resistance during prolonged immersion and neutral salt spraying tests. This enhancement in performance is attributed to MXene's ability to impede corrosive media transmission, while its interlayer shear and self-lubrication properties contribute to improved wear resistance. © 2024, The Authors. All rights reserved.

关键词： Wear resistance

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Diversity amplification and data generation of Chinese Sign Language based on Generative Adversarial Network

Diversity amplification and data generation of Chinese Sign ...

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Fei Wang Zhen Zeng Shizhuo Sun Yanjun Liu Faculty of Robot Science and Engineering Northeastern University Professer Shenyang China School of Computer Science and Engineering Northeastern University Bachelor Shenyang China

ISBN: (数字)9781728190105

ISBN: (纸本)9781728190112

There are many factors affecting the effectiveness and accuracy of Sign Language Recognition (SLR) based on wearable device combing sEMG and IMU signals. Among them, the diversity of sign language signals caused by various factors will greatly affect the effect of SLR in the process of sign language acquisition and the use of SLR system. In the algorithm design stage, such diversity and difference should be taken into account, so that the designed algorithm can be more robust to these factors. Therefore, it is necessary to design some schemes for data amplification and data generation to solve the problem of sign language data diversity. In this paper, a random core extraction method is proposed for fast data amplification according to the characteristics of time migration without deformation. And considering that a lot of manpower and time are often consumed in the actual data acquisition process, the data volume is not sufficient. We proposed a method of sign language data generation based on Generative Adversarial Networks (GAN). This data amplification method can not only solve the problem of temporal diversity of sign language data set, but also effectively prevent model overfitting by increasing the sample numbers of sign language data set. In the experimental part, the effectiveness of the method is proved by comparing and analyzing the corresponding experimental results in the process of data generation and amplification.

关键词： Assistive technology Gesture recognition Generative adversarial networks Data models Gallium nitride Data mining Interference

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