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12th International Conference on Computer Engineering and Networks, CENet 2022

作者： Yang, Guorui Feng, Tao Huo, Yonghua Tang, Shidang Qu, Zhenying The 54th Research Institute of CETC Hebei Shijiazhuang China National Key Laboratory of Science and Technology on Information System Security Institute of System Engineering Chinese Academy of Military Science Beijing China New China Life Insurance Co. LTD. Hebei Branch Hebei Shijiazhuang China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9789811969003

With the development of computer technology, people have higher and higher requirements for network link quality, which brings new challenges to network management and analysis. By applying link prediction to computer network scenarios, link existence information in the network can be predicted, which facilitates network management and analysis. At present, graph autoencoder is one of the most important models for link prediction. However, the existing model does not take node centrality into account and may have the problem of over-fitting. Therefore, for the scenario of network link state prediction, we design a network link prediction model based on node centrality and noise injection in this paper. In this model, noise is injected before training, and then the decoder is improved based on the variational graph autoencoder model. Node importance index and the weights of the trained nodes are used to add coefficients to the decoder. Finally, the model is proved to be effective in link connectivity prediction. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Network management

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In-process density measurement for model-based process optimization of functionally graded foam microcellular structures in material extrusion additive manufacturing

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Additive Manufacturing 2025年 106卷

作者： Zhao, Donghua Zhou, Zhaowei Ruan, Kaicheng Xu, Xuguang Zhang, Guoquan Chen, Ziwen Wang, Kui Xiong, Yi School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen518055 China Key Laboratory of Traffic Safety on Track of Ministry of Education School of Traffic and Transportation Engineering Central South University Changsha410075 China

Additive manufacturing with in-process foaming enables the creation of complex, porous structures with graded density and porosity. However, the current process planning method, based on volume conservation principles, fails to accurately capture the nonlinear process-density relationship, thereby limiting the precision of density control. Herein, this study proposes a model-based process optimization approach that utilizes a non-contact in-process density measurement method, enabling optimization of both density and track width. First, this approach accelerates data collection and constructs a reliable process-density and process-width regression model, facilitating rapid process optimization of functionally graded foam. Then, the model captures the nonlinear effects of temperature and printing speed on thermally expandable microspheres, where high temperatures and low speeds promote foaming, and vice versa. Finally, foam samples with gradient densities, produced using optimized parameters, validate the regression model's accuracy and feasibility for customizing intralayer and interlayer density, investigating continuous density gradients, and pressure distribution-driven insoles. Generally, the results highlight the critical role of temperature and printing speed in determining foam density and microstructure, significantly advancing high-quality, controlled-density foam production via material extrusion additive manufacturing. Moreover, the study presents a framework for in-situ, in-process density measurement, aiding the rapid development of process parameter windows for density-variable novel materials based on mass conservation. © 2025 Elsevier B.V.

关键词： Process control

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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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Characterization of High-Performance Nanostructured Wick for Heat Pipes

SSRN

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SSRN 2023年

作者： Sun, Qishi Han, Ruiyu Guo, Kailun Wang, Chenglong Zhang, Jing He, Xiaoqiang Qiu, Suizheng Su, Guanghui Tian, Wenxi Department of Nuclear Science and Technology State Key Lab. of Multiphase Flow in Power Engineering Shaanxi Key Lab. of Advanced Nuclear Energy and Technology Xi’an Jiaotong University Xi’an710049 China Key Lab. of Nuclear Reactor System Design Technology China Nuclear Power Research and Design Institute Chengdu610213 China

To investigate the best performance wick forms to support the design and fabrication of high-performance heat pipes, in this paper, two kinds of nanostructured wick were prepared by the oxidation-reduction method. The effect of surface nanostructure on the wick performance was investigated by comparing the surface characteristics, capillary properties, permeability, and evaporation properties. The result shows that the nanostructured wick presented excellent super hydrophilic properties. A liquid-lift visualization experimental method for measuring the capillary performance factor M was proposed, and it was verified to be correct by the separation effect of the capillary pumping experiment under a vacuum environment. With the increasing oxidized degree, the densification of nanoparticles on the wick surface increased the capillary performance factor M from 8.68 μm to 13.81 μm, with a maximum enhancement of 59.1%. The effective capillary radius decreased from 4.70×10-5 m to 4.01×10-5 m, with a maximum reduction of 14.9%. The permeability increased from 4.33×10-10 m2 to 5.83×10-10 m2, with a maximum enhancement of 34.7%. The increase in porosity made the effective capillary radius dominate the competition for permeability, and the capillary performance factor decreased by 17.1%. The thermal resistance of the wick decreased with the enhancement of the capillary performance factor, which fell from 2.03×10-3 m2·K/W to 1.26×10-3 m2·K/W. The current study provides a reference for the future design and preparation of high-performance heat pipe wicks. © 2023, The Authors. All rights reserved.

关键词： Heat resistance

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Natural antibacterial membranes prepared using Schisandra chinensis extracts and polyvinyl alcohol in an environment-friendly manner

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Chemosphere 2024年 346卷 140524页

作者： Jia, Wenting Jiang, Shanxue Wang, Fang Li, Jing Wang, Zeru Yao, Zhiliang School of Ecology and Environment Beijing Technology and Business University Beijing100048 China State Environmental Protection Key Laboratory of Food Chain Pollution Control Beijing Technology and Business University Beijing100048 China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen518055 China

Foodborne pathogens can cause food spoilage and lead to food safety issues. In recent years, food packaging has received a lot of attention. Traditional packaging membranes are non-biodegradable and remain in the environment for a long time. In this study, natural antimicrobial substances were extracted from Schisandra chinensis by a green extraction process using distilled water as the solvent, and the effects of different treatment on the antimicrobial activity of the extract were compared. At the same time, four types of Schisandra chinensis antimicrobial membranes were prepared using polyvinyl alcohol (PVA) as the substrate. The whole extraction and membrane preparation process did not involve organic solvents, making the process green and environment friendly. Material characterization included inverted biological microscopy, scanning electron microscopy (SEM), atomic force microscopy (AFM), Fourier transform infrared spectroscopy (FTIR), tensile strength test, pore size measurement, water uptake test, etc. Among them, no extract particles were observed with the naked eye on the surfaces of MⅡ and MⅣ. MⅡ has a uniformly transparent, nearly colorless morphology and is the most tensile. MⅣ surface is flat and smooth, the microstructure is dense and uniform. At the same time, the four types of membranes were tested against common pathogenic bacteria for 12 h, and the OD600 trend revealed the excellent antimicrobial activity of the membranes against S. aureus, MRSA, E. coli, and L. monocytogenes. The membranes could also be reused at least once. This study provides a new idea for preparing natural plant-based antimicrobial membranes. © 2023 Elsevier Ltd

关键词： Food safety

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Study on flow modes of open natural circulation with low height difference under low power conditions

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International Journal of Advanced Nuclear reactor design and technology 2020年 2卷 10-14页

作者： Yi, Li Jianchuang, Sun Hang, Peng Cheng, Xiang Quan, Biao Cao, Xiaxin Jian, Zhou Ming, Ding Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610041 China Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University Harbin150001 China

Open natural circulation systems are widely applied in the field of energy and chemical industries. Under some special conditions, open natural circulation systems with low height difference need to be applied, but research on this type of systems is not sufficient. In this paper, the flow modes of sucha natural circulation system were experimentally studied at low power level by adopting steam heating. In addition, the flow modes and physical phenomena of the natural circulation system were analyzed in detail under different heating power conditions. It is found that there are four flow modes at different power levels in the natural circulation system due to the influence of non-condensable gas and subcooled boiling. The inlet and outlet temperatures of heating section are analyzed in different flow modes. The result shows that the outlet temperature of heating section can be used as a judgment criterion for different flow modes. © 2019

关键词： Chemical industry

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Knowledge Graph for Identifying Geological Disasters by Integrating Computer Vision with Ontology

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Journal of Earth science 2023年第5期34卷 1418-1432页

作者： Qinjun Qiu Zhong Xie Die Zhang Kai Ma Liufeng Tao Yongjian Tan Zhipeng Zhang Baode Jiang School of Computer Science China University of GeosciencesWuhan 430078China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of GeosciencesWuhan 430074China National Engineering Research Center of Geographic Information System Wuhan 430074China School of Resource and Environmental Sciences Wuhan UniversityWuhan 430074China College of Computer and Information Technology China Three Gorges UniversityYichang 443002China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang 443002China

The occurrence of geological disasters can have a large impact on urban safety. Protecting people’s safety is the most important concern when disasters occur. Safety improvement requires a large amount of comprehensive and representative risk analysis and a large collection of information related to geological hazards, including unstructured knowledge and experience. To address the relevant information and support safety risk analysis, a geological hazard knowledge graph is developed automatically based on computer vision and domain-geoscience ontology to identify geological hazards from input images while obeying safety rules and regulations, even when affected by changes. In the implementation of the knowledge graph, we design an ontology schema of geological disasters based on a top-down approach, and by organizing knowledge as a logical semantic expression, it can be shared using ontology technologies and therefore enable semantic interoperability. Computer vision approaches are then used to automatically detect a set of entities and attributes, using the data from input images, and object types and their attributes are identified so that they can be stored in Neo4j for reasoning and searching. Finally, a reasoning model for geological hazard identification was developed using the Neo4j database to create nodes, relationships, and their properties for modeling, and geological hazards in the images can be automatically identified by searching the Neo4j database. An application on geological hazard is presented. The results show the effectiveness of the proposed approach in terms of identifying possible potential hazards in geological hazards and assisting in formulating targeted preventive measures.

关键词： geological hazard computer vision knowledge graph city safety ontology

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Robot map construction based on topology and hierarchical fusion in unknown environment 2

Robot map construction based on topology and hierarchical fu...

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2nd International Conference on the Frontiers of Intelligent Control, Measurement, and Signal systems, FICMSS 2025

作者： Li, Zirun Zhu, Chunjia Tao, Hao Zhang, Qingfang Pu, Chenyu Xiao, Jinsheng School of Electronic Information Wuhan University Wuhan430072 China China Ship Development and Design Center Hubei Wuhan430064 China National Key Laboratory of Information System and Technology Beijing Institute of Control and Electronic Technology Beijing100038 China

Map construction has always been crucial in exploring enclosed unknown environments. Traditional mapping methods have problems such as low accuracy or long time consumption. Due to the indoor and enclosed nature of unknown environments, inspection robots often encounter challenges in mapping and path planning. To address similar issues, we proposed an optimized indoor mapping solution based on topology technology and hierarchical fusion, and conducted experiments using robots in a library simulation scenario in an unknown environment. Figure 1 shows the map that we have obtained by layering and *** utilizing topology techniques and hierarchical fusion mapping methods, we have effectively simplified the mapping process, reducing computational complexity and cost while obtaining spatial information and this method allows for the consideration of the geometric characteristics of robots when planning safe and accurate passable paths. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Topology

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Dual-Target Point Cloud Registration for Partially Visible Data Using Local and Global Features

SSRN

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SSRN 2024年

作者： Rao, Zhifeng Chen, Yuang Cao, Ming Lin, Zhiyun School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen518055 China Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and Technology Shenzhen518055 China University of Groningen Netherlands Peng Cheng Laboratory Shenzhen518055 China

Point cloud registration is a challenging task when only partially visible data is available. Recently, many learning-based methods have been proposed for this problem and have achieved satisfactory performance. However, they use only one source point cloud and fail to pay attention to the key factor of registration: alignment of attitudes. Based on this phenomenon, we propose a dualtarget point cloud registration model: An end-to-end model, which uses multiple source point clouds and for each source point cloud, a new created target point cloud is added to pay more attention to the alignment of attitudes. Our model is divided into two components: coarse and fine registrations. First, an initialization module is introduced for coarse registration, in which multiple source point clouds are used and for each source point cloud, a new target point cloud specifically for aligning the attitudes is added. Second, we design a two-step Attention-based Representative Overlapping-Point Selection module to select representative overlapping points for fine registration, which uses both global and local features of the point clouds. In the first step, overlapping scores are predicted using global features. In the second step, a feature-matching matrix is obtained based on local features. Representative overlapping points are selected based on the overlapping scores and the feature-matching matrix. Using these points, a weighted SVD algorithm is used to estimate the transformation of fine registration. Extensive experiments on ModelNet40, 7Scenes and ICL-NUIM show that our method achieves the state-of-the-art compared to other learning-based methods. © 2024, The Authors. All rights reserved.

关键词： Matrix algebra

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Joint Beamforming and Offloading design for Integrated Sensing, Communication and Computation system

arXiv

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arXiv 2024年

作者： Liu, Peng Fei, Zesong Wang, Xinyi Zhou, Yiqing Zhang, Yan Liu, Fan The School of Information and Electronics Beijing Institute of Technology Beijing100081 China The State Key Laboratory of Processors The Beijing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China The School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen518055 China

Mobile edge computing (MEC) is powerful to alleviate the heavy computing tasks in integrated sensing and communication (ISAC) systems. In this paper, we investigate joint beamforming and offloading design in a three-tier integrated sensing, communication and computation (ISCC) framework comprising one cloud server, multiple mobile edge servers, and multiple terminals. While executing sensing tasks, the user terminals can optionally offload sensing data to either MEC server or cloud servers. To minimize the execution latency, we jointly optimize the transmit beamforming matrices and offloading decision variables under the constraint of sensing performance. An alternating optimization algorithm based on multidimensional fractional programming is proposed to tackle the non-convex problem. Simulation results demonstrates the superiority of the proposed mechanism in terms of convergence and task execution latency reduction, compared with the state-of-the-art two-tier ISCC framework. Copyright © 2024, The Authors. All rights reserved.

关键词： Beamforming

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