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UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science 2025年第1期87卷 121-138页

作者： Zheng, Qingchun Wu, Moudong Zhu, Peihao Yang, Bin Li, Shubo Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China China

This paper introduces D-Fusion SLAM, an advanced VSLAM system based on ORB-SLAM2. D-Fusion SLAM integrates depth information to enhance feature selection, aiming to improve accuracy and speed in visual SLAM applications. The system mainly comprises two modules: an image grid filtering module based on grayscale information and a feature selection module integrating depth information. These modules effectively eliminate redundant and useless features, ensuring high-quality features for pose estimation. We tested D-Fusion SLAM on the TUM dataset and compared it with ORB-SLAM2. Experimental results demonstrate that D-Fusion SLAM outperforms ORB-SLAM2, significantly enhancing the system's accuracy and robustness. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Feature Selection

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An Improved Compressive Sensing-Based Model for Efficient Analysis of Monostatic Electromagnetic Scattering Problems

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IEEE Microwave and Wireless Technology Letters 2025年第4期35卷 388-391页

作者： Qi, Qi Fan, Yunuo Cao, Xinyuan Liu, Yi Kong, Meng Huang, Zhixiang Wu, Xianliang Hefei Normal University Anhui Province Key Laboratory of Simulation Calculation and Design for Electronic Information System Hefei230601 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei230601 China

To further accelerate the analysis of monostatic electromagnetic (EM) scattering problems of objects, an improved compressive sensing (CS)-based model is proposed. First, an orthogonal subspace spanned by the wide-angle induced currents is identified by means of the wide-angle incident sources. Then, the sparse transform of the induced currents is replaced by the subspace projection. In addition, an optimal number of measurements is determined, only slightly larger than the dimension of the subspace. Finally, the recovery algorithm is simplified to the least-squares method to solve the resulting overdetermined system. Compared with the traditional CS-based model, the proposed model significantly improves the efficiency of the recovery step and optimizes both the requirement for and the way of determining the number of measurements. © 2023 IEEE.

关键词： Least squares approximations

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Disturbance Observer-Based Adaptive Synchronization of Heterogeneous Chaotic Systems With Uncertainties via DNA Strand Displacement

IEEE Transactions on Computational Biology and Bioinformatic...

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IEEE Transactions on Computational Biology and Bioinformatics 2025年第1期22卷 250-260页

作者： Xiaoxiao Liu Hui Lv Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian China

The application of DNA strand displacement (DSD) for synchronizing chaotic systems has made remarkable progress in recent years. However, uncertainty may exist in the systems, and interference is unavoidable during the synchronization process. This article endeavors to tackle the issue of performance degradation in synchronization caused by disturbances and system uncertainties. Primarily, in order to introduce perturbations in chaotic systems using DSD, the corresponding chemical reaction networks (CRNs) is derived from the ordinary differential equations of the perturbation signal in this paper, leading to the establishment of a composite function that combines trigonometric and exponential functions. Furthermore, combining the design of nonlinear observers with adaptive control methods not only simplifies the derivation process but also allows for the construction of observers using fewer DSD reactions. Through the collaborative efforts of the adaptive law and the observer, it enables the estimation of perturbations and system uncertainties, thereby achieving the synchronization of heterogeneous chaotic systems. Finally, the proposed method successfully synchronizes the Lorenz system and Yang system, even in the presence of system uncertainties and disturbances, demonstrating its effectiveness.

关键词： Observers Synchronization Uncertainty Perturbation methods Computational biology Bioinformatics DNA Chaotic communication Costs Estimation error

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Collaborative optimization for multirobot manufacturing system reliability through integration of SysML simulation and maintenance knowledge graph

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Journal of Manufacturing Systems 2025年 80卷 749-775页

作者： Zhou, Jian Zheng, Lianyu Wang, Yiwei School of Mechanical Engineering and Automation Beihang University Beijing100191 China MIIT Key Laboratory of Intelligent Manufacturing Technology for Aeronautics Advanced Equipments Ministry of Industry and Information Technology Beijing100191 China Beijing Key Laboratory of Digital Design and Manufacturing Technology Beijing100191 China

In the rapidly advancing field of industrial automation, the reliability and maintenance of multirobot manufacturing systems are crucial. This paper proposes a collaborative optimization method for the reliability of multirobot system, combining SysML (System Modeling Language) model simulation with an operational and maintenance knowledge graph, aiming to ensure the reliable operation of multirobot manufacturing systems. The SysML model provides a comprehensive framework to represent the system architecture, workflows, and key parameters, identify critical components and potential bottlenecks, and perform detailed reliability analysis. Simultaneously, by embedding intelligent algorithms, the operational and maintenance knowledge graph enables automatic detection of operational anomalies and intelligent generation of maintenance strategies for industrial robots. By integrating the SysML model with the operational and maintenance knowledge graph, a collaborative optimization framework for the reliability of multirobot system is constructed. This framework not only dynamically adjusts key parameters in the simulation model, enhancing the accuracy and real-time performance of system reliability assessments, but also optimizes maintenance strategies based on system simulation indicators to ensure the reliable operation of multirobot system. Case studies validate that the proposed method improves the reliability of multirobot manufacturing systems, demonstrating that the combination of SysML simulation and the operational and maintenance knowledge graph can effectively address the complexity of modern manufacturing systems, offering significant reference value. © 2025 The Society of Manufacturing Engineers

关键词： Knowledge graph

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Edge-Cloud Cooperation-Driven intelligent Sustainability Evaluation Strategy Based on IoT and CPS for Energy-Intensive Manufacturing Industries

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IEEE Internet of Things Journal 2025年第9期12卷 12287-12297页

作者： Ma, Shuaiyin Huang, Yuming Chen, Yanping Xiao, Qinge Xu, Jun Leng, Jiewu Xi’an University of Posts and Telecommunications Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi’an Key Laboratory of Big Data and Intelligent Computing School of Computer Science and Technology Xi’an710121 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Xidian University Advanced Manufacturing Technology Innovation Center Guangzhou Institute of Technology Guangzhou510555 China Guangdong University of Technology Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment Guangzhou510006 China

The advancement of the Industry 5.0 in information technology has led to increased interest in integrating edge-cloud cooperation with Internet of Things (IoT) and cyber-physical system (CPS) designs. This integration effectively reduces service delays and provides real-time analysis feedback to physical spaces, attracting attention from both academia and industry. These advanced technologies enhance production system intelligence, their alignment with circular economy principles for promoting sustainability has been overlooked. To address this gap, this article proposes an intelligent sustainability evaluation strategy driven by edge-cloud cooperation, IoT, and CPS. The proposed approach aims to enhance production sustainability and intelligence through circular economy perspectives. It introduces improved gray relation analysis and deep clustering network techniques to extract meaningful insights from diverse indicators within the evaluation system. By analyzing relationships between different equipment and workshops, it provides an analytical method that enhances production efficiency while reducing energy consumption and resource waste. To further validate the proposed method, an illustrative example using a partner company’s production data demonstrates its accuracy. © 2014 IEEE.

关键词： Circular economy

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A Dual-Capture and Dual-Output 3D DNA Walker System Integrated with Ligases Enables Ultrasensitive Detection of Single-Nucleotide Polymorphisms

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Analytical Chemistry 2025年第17期97卷 9316-9325页

作者： Zhang, Yunshan Tan, Qianglong Yang, Fang Huang, Tuo Yu, Siyu Ye, Jing Zeng, Jianxian Feng, Xianzhong Zhang, Diming Key Laboratory of Soybean Molecular Design Breeding National Key Laboratory of Black Soils Conservation and Utilization Northeast Institute of Geography and Agroecology Chinese Academy of Sciences Changchun130102 China Research Center for Novel Computing Sensing and Intelligent Processing Zhejiang Laboratory Hangzhou311121 China Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Zhejiang Hangzhou310024 China School of Chemistry and Chemical Engineering Hunan University of Science and Technology Hunan Xiangtan411201 China

DNA walkers, as structurally and functionally programmable signal amplification tools, exhibit great potential for application in the field of biosensing. Traditional DNA walkers often rely on enzymes for operation, posing compatibility challenges, while the handful of existing enzyme-free DNA walkers demonstrate limited performance. To address this, we innovatively developed an efficient enzyme-free 3D DNA walker with dual capture and dual output capabilities. Coupled with ligase chain reaction (LCR), this system facilitates highly sensitive and specific detection of single nucleotide polymorphisms (SNPs). Specifically, LCR precisely identifies single-base mutations, effectively transmitting biological information. The 3D DNA walker system is based on entropy-driven circuit cycling reaction technology. In this system, LCR products serve as the driving strands for the DNA walker, independently binding to track strands and walking legs immobilized on gold nanoparticles, forming a unique dual signal capture mechanism. Each track strand carries two signal chains, significantly enhancing signal amplification efficiency. Benefiting from this novel enzyme-free 3D DNA walker strategy, our biosensing system exhibits exceptional sensitivity to mutant targets (MT), detecting MT at concentrations as low as 30.3 aM and distinguishing heterozygous samples with a 0.01% mutation frequency. Furthermore, this system has been successfully applied to genotyping and mutation abundance assessment of genomes from fresh soybean leaves, demonstrating its vast potential for practical applications. In summary, this research pioneers a novel enzyme-free 3D DNA walker with dual capture and dual output capabilities, and develops an ultrasensitive genotyping tool. This provides strong technical support for the advancement of genetic research. © 2025 American Chemical Society.

关键词： Nucleotides

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Effect of Free-End Torsion on the Corrosion and Mechanical Properties for Mg-3Zn-0.2Ca Alloy

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Acta Metallurgica Sinica(English Letters) 2025年第1期38卷 59-70页

作者： Li-Lan Gao Jiang Ma Yan-Song Tan Xiao-Hao Sun Qi-Jun Gao De-Bao Liu Chun-Qiu Zhang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of TechnologyTianjin300384China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of TechnologyTianjin300384China School of Materials Science and Engineering Tianjin University of TechnologyTianjin300384China

Magnesium alloys with excellent degradability and biocompatibility are promising materials for biomedical implants,saving patients the burden of second ***,their mechanical properties and corrosion resistance are significantly below the requirements for implant *** study aims to improve the mechanical and corrosion resistance properties of Mg-3Zn-0.2Ca alloy by pre-torsion treatment,and find out the optimal shear *** rod-shaped Mg-3Zn-0.2Ca alloy specimens were pre-torsion treated at different torsion *** effect of free-end torsion on Mg-3Zn-0.2Ca alloy was characterized through microstructure analysis,mechanical testing,and corrosion ***-torsion treatment can refine grain and induce twins and dislocations in Mg-3Zn-0.2Ca *** surface hardness increases with the increase in torsion *** yield strength and ultimate strength initially increase and then decrease with increasing torsion angle,while ductility decreases with increasing torsion *** with a shear strain of 30%exhibit the highest tensile strength,reaching 284.78±10.62 MPa,with an elongation of 19.37±1.66%.Furthermore,they show a significant improvement in fatigue lives both before and after *** the stress amplitude is 120 MPa,the fatigue lives for specimens without pre-torsion treatment are 54,275 cycles and 4324 cycles before and after pre-corrosion,while they increased significantly to 92,015 cycles and 5050 cycles with the 30%shear strain,***,the 30%shear strain specimens show a significant reduction in corrosion *** conclusion,pre-torsion treatment can effectively modify the microstructure of Mg-3Zn-0.2Ca alloy,enhancing both mechanical properties and corrosion *** optimal shear strain for this improvement is 30%.This study provides a practical method to enhance the mechanical properties and corrosion resistance of Mg-3Zn-0.2Ca alloy,making it more suitable for biomedical implan

关键词： Magnesium alloy Pre-torsion Microstructure Mechanical property Corrosion resistance

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Multi-Scale Time Series Segmentation Network Based on Eddy Current Testing for Detecting Surface Metal Defects

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 528-538页

作者： Xiaorui Li Xiaojuan Ban Haoran Qiao Zhaolin Yuan Hong-Ning Dai Chao Yao Yu Guo Mohammad S.Obaidat George Q.Huang the School of Intelligence Science and Technology University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering the Key Laboratory of Intelligent Bionic Unmanned Systems and the Institute of Materials Intelligent Technology Liaoning Academy of Materials IEEE the Department of Computer Science Hong Kong Baptist University the School of Computer and Communication Engineering Key Laboratory of Advanced Materials and Devices for Post-Moore Chips Ministry of Education University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing the School of Computer and Communication Engineering University of Science and Technology Beijing the King Abdullah Ⅱ School of Information Technology The University of Jordan the Department of Computational Intelligence the School of Computing SRM University the School of Engineering The Amity University The Hong Kong Polytechnic University

In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh environment leads to significant variations in the shape and size of the defects. To address this challenge, we propose the multivariate time series segmentation network(MSSN), which adopts a multiscale convolutional network with multi-stage and depth-separable convolutions for efficient feature extraction through variable-length templates. To tackle the classification difficulty caused by structural signal variance, MSSN employs logarithmic normalization to adjust instance distributions. Furthermore, it integrates classification with smoothing loss functions to accurately identify defect segments amid similar structural and defect signal subsequences. Our algorithm evaluated on both the Mackey-Glass dataset and industrial dataset achieves over 95% localization and demonstrates the capture capability on the synthetic dataset. In a nuclear plant's heat transfer tube dataset, it captures 90% of defect instances with75% middle localization F1 score.

关键词： Eddy current testing nondestructive testing semantic segmentation time series analysis

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Fairness-Aware Budgeted Edge Server Placement for Connected Autonomous Vehicles

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IEEE Transactions on Mobile computing 2025年第6期24卷 4762-4776页

作者： Wu, Jintao Xu, Xiaolong Cui, Guangming Zhang, Yiwen Qi, Lianyong Dou, Wanchun Cai, Zhipeng Nanjing University of Information Science & Technology Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services School of Software Nanjing210044 China Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun130012 China Nanjing University of Information Science & Technology Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services School of Software China Nanjing University State Key Laboratory for Novel Software Technology China Anhui University School of Computer Science and Technology Anhui230031 China College of Computer Science and Technology Qingdao266580 China Nanjing University State Key Laboratory for Novel Software Technology Nanjing210023 China Georgia State University Department of Computer Science United States

Mobile edge computing (MEC) considerably enhances the capabilities and performance of connected autonomous vehicles (CAVs) by deploying edge servers (ESs) on roadside units (RSUs) near CAVs, thereby ensuring low-latency services. Given the constrained and costly nature of ES resources (computing, storage, and bandwidth), equitable ES utilization is critical for CAV operations. However, fairness considerations are often overlooked in current budgeted edge server placement (ESP) strategies, potentially worsening resource imbalances and compromising user experience. This paper investigates the fairness-aware budgeted edge server placement (FESP) problem within RSUs, proving its NP-hardness. To address FESP, we first propose FESP-O, an integer programming-based optimal approach for small-scale problems, followed by FESP-APX, an approximation approach for large-scale scenarios that provides near-optimal solutions. We analyze the time complexity and approximation ratio of our proposed algorithms and validate their efficacy through experiments on real-world datasets. Extensive experimental results demonstrate significant performance improvements over baseline and state-of-the-art methods, indicating practical suitability and efficiency. © 2002-2012 IEEE.

关键词： Integer linear programming

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Advancements in graphene-based composites: A review of the emerging applications in healthcare

Smart Materials in Medicine

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Smart Materials in Medicine 2025年第1期6卷 120-138页

作者： Batool, Farwa Muhammad, Saz Muazzam, Rabia Waqas, Muhammad Ullah, Zia Roy, Shubham Zhang, Yinghe Wang, Ke Guo, Bing Department of Chemistry Lahore Garrison University DHA Phase VI Lahore Pakistan School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen518055 China School of Science Shenzhen Key Laboratory of Flexible Printed Electronics Technology Shenzhen Key Laboratory of Advanced Functional Carbon Materials Research and Comprehensive Application Harbin Institute of Technology Shenzhen518055 China Government Queen Mary Graduate College Lahore Pakistan

Graphene and related materials are emerging revolutionary materials due to fascinating stimuli-responsive physiochemical properties having widespread applications in developing advanced nano-systems for detection, diagnostics, and therapeutics in biomedical fields. Various materials like metal nanoparticles, polymers, dyes, drugs, and proteins could be combined yielding graphene-based composite materials (GBCMs) to synergistically fulfill different biomedical requirements. The 2D conjugated structure, easy surface functionalization via covalent or van der Waal interactions, and combination with different components for versatile functionalities altogether contribute to the development of GBCM for healthcare applications. This review specifically focuses on GBCMs and discusses specific material properties relevant to their material applications in healthcare. Furthermore, the synthesis, toxicity, and biocompatibility of these GBCMs, and their interactions with biological materials are thoroughly discussed. Importantly, the recent cutting-edge applications in the field of healthcare, including its role in the development of antibacterial, anti-viral, and photothermal therapies, wound healing, drug delivery, neurodegenerative disease therapy, and biosensing based on GBCMs are well-updated. Additionally, the applications of GBCMs in point-of-care devices, wearable electronics, and tissue engineering are well summarized. We hope this review opens up more possibilities to design more innovative healthcare materials derived from graphene. © 2025 The Authors

关键词： Biocompatibility

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