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OLMNE+FT: Multiplex network embedding based on overlapping links

Physica A: Statistical Mechanics and its Applications 2022年 596卷

作者： Liang, Bo Wang, Lin Wang, Xiaofan Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and Automation Shanghai University Shanghai China

Network embedding or graph representation learning has recently attracted more researchers’ attention and achieved state-of-the-art performance in many areas and tasks. Nevertheless, most of these methods are targeted for monolayer networks and ignore the multiplexity property of nodes which refers to the multifaceted relationships between two elements. Multiplexity provides multiple types of auxiliary information to refine the characteristics of nodes and can be modeled as a multiplex network. In this study, we propose a multiplex network embedding algorithm to learn a unique embedding for each node in each layer or each relation type. A biased path-dependency random walk strategy is adopted to generate node sequences for integrating different types of relations between nodes, which pays more attention to overlapping links and makes neighbor nodes in the sampling sequence more similar to each other. Then the skip-gram model is used to learn an overall embedding over node sequences. To strengthen the expressive power of the embedding in a specific layer, a fine tuning strategy with low time cost is employed to make the embedding comprise information of nodes at this particular layer and preserve their distinctive properties, and the unique embedding is achieved ultimately. To verify the effectiveness of our algorithms, we validate the performance of our algorithm and other baseline methods in the link prediction task. The results demonstrate that the learned embedding can capture the interlayer relationships and preserve the specific characteristics of nodes, and our algorithms can stably obtain better or comparable performance compared with other methods. © 2022 Elsevier B.V.

关键词： Network embeddings

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Room Impulse Response Reshaping-Based Blind Source Separation for an Underdetermined Reverberant Environment

SSRN

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SSRN 2024年

作者： Xie, Yuan Zou, Tao Yang, Junjie Sun, Weijun Xie, Shengli School of Mechanical and Electrical Engineering Guangzhou University Guangdong-Hong Kong-Macao Key Laboratory of Multi-scale Information Fusion and Collaborative Optimization Control of Complex Manufacturing Process Guangzhou510006 China School of Automation Guangdong University of Technology Joint International Research Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education of the P.R.C. Guangzhou510006 China School of Automation Guangdong University of Technology Guangdong Key Laboratory of IoT Information Processing Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China School of Automation Guangdong University of Technology Key Laboratory of Intelligent Detection and the IoT in Manufacturing Ministry of Education 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Guangzhou510006 China

Blind source separation under an underdetermined reverberation environment is a very challenging issue. The classical method is based on the expectation maximization algorithm. However, it is limited to high reverberation environments, resulting in bad or even invalid separation performance. To eliminate this restriction, a room impulse response reshaping-based expectation maximization method is designed to solve the problem of blind signal separation in an underdetermined reverberant environment. Firstly, a room impulse response reshaping technology is designed to eliminate the influence of audible echo on the reverberant environment, improving the quality of the received signals. Then, a new mathematical model of time-frequency mixing signals is established to reduce the approximation error of model transformation caused by high reverberation. Furthermore, an improved expectation maximization method is proposed for real-time update learning rules of model parameters, and then the sources are separated using the estimators provided by the improved expectation maximization method. Experimental results based on source separation of speech and music mixtures demonstrate that the proposed algorithm achieves better separation performance while maintaining much better robustness than popular expectation maximization methods. © 2024, The Authors. All rights reserved.

关键词： Reverberation

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A Hybrid Wind Power Prediction Model Based on Seasonal Feature Decomposition and Enhanced Feature Extraction

SSRN

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SSRN 2024年

作者： Li, Weipeng Chong, Yuting Guo, Xin Liu, Jun School of Automation and Information Engineering Xi’an University of Technology No. 5 Jinhua South Road Shaanxi Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing No. 5 Jinhua South Road Shaanxi Xi’an710048 China

Efficient and accurate wind power prediction is crucial for enhancing the reliability and safety of power system operation and management. The integration of advanced data-driven forecasting methods with precise and efficient data feature decomposition and extraction techniques is necessary to improve the accuracy of wind power generation prediction, due to the inherent randomness and nonlinearity of physical states impacting wind power output, as well as the abundance of redundant information in their original measurement data. This paper proposes a novel hybrid wind power prediction model based on seasonal feature decomposition of wind energy data and enhanced feature extraction. Its effectiveness and superiority are demonstrated through comprehensive multi-model comparisons. © 2024, The Authors. All rights reserved.

关键词： Wind power

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Depth-aware Fusion Method based on Image and 4D Radar Spectrum for 3D Object Detection

arXiv

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arXiv 2025年

作者： Sun, Yue Qian, Yeqiang Wang, Chunxiang Yang, Ming The Global Institute of Future Technology Shanghai Jiao Tong University Shanghai200240 China The Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

Safety and reliability are crucial for the public acceptance of autonomous driving. To ensure accurate and reliable environmental perception, intelligent vehicles must exhibit accuracy and robustness in various environments. Millimeter-wave radar, known for its high penetration capability, can operate effectively in adverse weather conditions such as rain, snow, and fog. Traditional 3D millimeter-wave radars can only provide range, Doppler, and azimuth information for objects. Although the recent emergence of 4D millimeter-wave radars has added elevation resolution, the radar point clouds remain sparse due to Constant False Alarm Rate (CFAR) operations. In contrast, cameras offer rich semantic details but are sensitive to lighting and weather conditions. Hence, this paper leverages these two highly complementary and cost-effective sensors, 4D millimeter-wave radar and camera. By integrating 4D radar spectra with depth-aware camera images and employing attention mechanisms, we fuse texture-rich images with depth-rich radar data in the Bird’s Eye View (BEV) perspective, enhancing 3D object detection. Additionally, we propose using GAN-based networks to generate depth images from radar spectra in the absence of depth sensors, further improving detection accuracy. Copyright © 2025, The Authors. All rights reserved.

关键词： Radar imaging

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A Direct Anti-high Repetition Jamming Design Method via The Minimum Interval Period Optimization

A Direct Anti-high Repetition Jamming Design Method via The ...

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Chinese control and Decision Conference, CCDC

作者： Jingjing Qiang Hui Liu Xiongjun Wu Yingbo Li Peipei Cao The Eighth Academy of China Aerospace Science and Technology Corporation The 802 Institute of Shanghai Academy of Space Flight Technology Shanghai China Department of Automation Ministry of Education of China Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Shanghai China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

Semi-active laser detection is used extensively on many kinds of high-precision guidance weapon systems in the varied military fields. Although it is of high detection accuracy, this kind of detection mechanism, on the other hand, suffers from various laser interference modes which are added in view of the semi-active laser detection principle, covering from angle deception interference, synchronous forwarding interference, and high repetition frequency interference, etc. As a consequence, the overall performance is reduced accordingly. Among these types of deception interference, the high repetition frequency interference is the most effective one. In this work, to overcome this specific type of interference, a minimum interval period method (MIPM) is proposed to remove high repetition frequency interference and improve the detection accuracy of the laser semi-active guidance system. Numerical experiments validate that, this method is able to achieve good performance testing on the Semi-active laser detection under high repetition frequency interference via the False Alarm Probability (FAP for short) and Missed Alarm Probability (MAP).

关键词： Laser theory Accuracy Weapons Interference Resists Logic gates Laser modes

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Real-Time Maritime Obstacle Detection Based on YOLOv5 for Autonomous Berthing 16th

Real-Time Maritime Obstacle Detection Based on YOLOv5 for Au...

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16th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2021

作者： Chen, Guotong Qi, Jiangtao Dai, Zeyu Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China China Ship Scientific Research Center No. 222 Shanshui East Road Binhu District Wuxi214082 China

ISBN: (纸本)9789811912528

The shipping industry is developing towards intelligence, in which autonomous berthing and docking systems play an important role. Real-time maritime obstacle detection is essential for autonomous berthing, which can protect ships from collisions. In the field of real-time objection detection, YOLOv5s is one of the most effective networks. To solve the real-time maritime obstacle detection for autonomous berthing, we propose an improved network, named YOLOv5s-CBAM, which employs the convolutional block attention module to boost the representation power of YOLOv5s. In addition, we propose another network, named YOLOv5-SE, in which a squeeze-and-excitation block is introduced to recalibrate the channel-wise features adaptively. The experimental results demonstrate that YOLOv5s-CBAM outperforms YOLOv5s in the detection of large obstacles. Both YOLOv5s-CBAM and YOLOv5s-SE achieve state-of-the-art performance in various metrics compared with previous related work for maritime obstacle detection. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Ships

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A Sensitive Nanothermometer Based on DNA Triplex Structure 1

引用

17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Chen, Zhekun Hu, Yingxin Xie, Chun Chen, Kuiting Pan, Linqiang Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China College of Information Science and Technology Shijiazhuang Tiedao University Shijiazhuang050043 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

DNA has been used to construct a variety of nanoscale thermometers due to its unique thermodynamic properties. It has proven to be one of the most promising, yet challenging aspects of DNA-based thermometers, to obtain significant signal changes when the temperature changes slightly. Here, we propose a strategy to construct nanoscale thermometers with sensitive temperature responses based on DNA triplex. The thermometers consist of a CT-rich DNA strand and stabilizing strands, whose conformations vary with temperature. By adjusting the sequence design or introducing mismatch bases in stabilizing strands, the temperature response interval of the thermometer can be reduced to 7 ∘C, which lead to higher sensitivity compared to the interval of 12–15 ∘C for conventional designs. The temperature responses of the thermometer are characterized by fluorescence experiments. The fluorescence kinetics experiments demonstrate the good repeatability. The design of the nanothermometer will be helpful for constructing advanced nanosystem with sensitive temperature responses as well as long service times. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Thermometers

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Tuning Geometric Conformations of Curved DNA Structures by controlling Positions of Nicks 1

引用

17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Xie, Chun Hu, Yingxin Chen, Kuiting Chen, Zhekun Pan, Linqiang Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China College of Information Science and Technology Shijiazhuang Tiedao University Shijiazhuang050043 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

DNA origami is one of the powerful techniques that utilize DNA as building blocks to synthesize nanostructures. Traditionally, through introducing different numbers of insertions and deletions of base pairs in DNA helices, the in-plane bending angle of curved DNA structures could be roughly tuned. Here, we explored a strategy that used the position patterns of nicks in staple strands to tune the geometric conformation of curved DNA origami structures, including in-plane bending, out-of-plane bending, and twisting angles. When the structure adopted different patterns of nicks positions, great difference appeared in the geometric properties. Further, by combining subunits of different nicks position patterns, the bending and twisting of the combined structure was effectively tuned. The strategy increases the design accuracy of curved DNA origami structures and expands the toolbox for designing DNA structures. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Molecular dynamics

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GPC-LIO-SAM:Lidar inertial odometry and mapping method for mobile robot with ground plane constraint

GPC-LIO-SAM:Lidar inertial odometry and mapping method for m...

引用

第43届中国控制会议

作者： Chong Cao Gang Peng Dingxin He Yihao Cao Yue Xu Zhang Deng School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education Engineering Research Center of Autonomous Intelligent Unmanned Systems Ministry of Education Wuhan Lisai Technology Co. Ltd.

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Due to the limitation of the vertical angle resolution of the lidar sensor,the observation information in the vertical direction is reduced,resulting in the elevation cumulative drift phenomenon of many lidar SLAM algorithms in large-scale environment,which reduces the accuracy of pose estimation and the quality of *** order to solve this problem,based on LIO-SAM,this paper proposes a lidar SLAM algorithm with ground plane *** method can effectively extract the ground point cloud and obtain the plane normal vector,and construct the constraint relationship with the prior plane normal *** optimal state estimation is solved by nonlinear optimization method,which effectively reduces the elevation drift caused by the long-term operation of the system in large-scale *** paper compares the improved algorithm with A-LOAM,LeGO-LOAM and original LIO-SAM algorithms in challenging datasets such as KITTI,M2 DGR and *** results show that this method effectively improves the accuracy of pose estimation and the quality of mapping,and limit the elevation drift of mobile robot in ground operation,which has high application value.

关键词： Ground plane constraint elevation drift LIDAR simultaneous localization and mapping(SLAM)

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PG-SLAM: Photo-realistic and Geometry-aware RGB-D SLAM in Dynamic Environments

arXiv

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arXiv 2024年

作者： Li, Haoang Meng, Xiangqi Zuo, Xingxing Liu, Zhe Wang, Hesheng Cremers, Daniel Guangzhou China School of Computation Information and Technology Technical University of Munich Munich Germany MoE Key Lab of Artificial Intelligence Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai Jiao Tong University Shanghai China

Simultaneous localization and mapping (SLAM) has achieved impressive performance in static environments. However, SLAM in dynamic environments remains an open question. Many methods directly filter out dynamic objects, resulting in incomplete scene reconstruction and limited accuracy of camera localization. The other works express dynamic objects by point clouds, sparse joints, or coarse meshes, which fails to provide a photo-realistic representation. To overcome the above limitations, we propose a photo-realistic and geometry-aware RGB-D SLAM method by extending Gaussian splatting. Our method is composed of three main modules to 1) map the dynamic foreground including non-rigid humans and rigid items, 2) reconstruct the static background, and 3) localize the camera. To map the foreground, we focus on modeling the deformations and/or motions. We consider the shape priors of humans and exploit geometric and appearance constraints of humans and items. For background mapping, we design an optimization strategy between neighboring local maps by integrating appearance constraint into geometric alignment. As to camera localization, we leverage both static background and dynamic foreground to increase the observations for noise compensation. We explore the geometric and appearance constraints by associating 3D Gaussians with 2D optical flows and pixel patches. Experiments on various real-world datasets demonstrate that our method outperforms state-of-the-art approaches in terms of camera localization and scene representation. Source codes will be publicly available upon paper acceptance. Copyright © 2024, The Authors. All rights reserved.

关键词： Geometry

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