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71st Annual Reliability and Maintainability Symposium, RAMS 2025

作者： Grimstad, Joachim Morozov, Andrey Institute of Industrial Automation and Software Engineering University of Stuttgart Pfaffenwaldring 47 Stuttgart70550 Germany

ISBN: (纸本)9798350367744

To our knowledge, this paper offers two novel contributions in this field. First, it addresses the need for runtime dynamic risk assessment in autonomous systems by proposing a framework that enables continuous risk evaluation in complex and dynamic environments at runtime. This framework uses dynamic and inductive graph neural network methods that update and predict during runtime to reflect changes in the environment and can process large amounts of data efficiently. Secondly, it integrates traditional quantitative risk models, to introduce some degree of explainability of the graph neural network by converting the graph into traditional models such as fault trees. The second contribution is the partial proof-of-concept of the proposed concept by training a graph attention network to predict top event probabilities of simple fault trees represented as graphs. The implementation tries simple off-the-shelf algorithms but conducts some initial experimentation with loss functions, dropout layers, and distribution shifted datasets to evaluate the generalization capability of the models. Initial results show promise, demonstrating the potential of using GATs to predict top event probabilities in fault tree analysis. Future research should focus on optimizing dropout probabilities, expanding datasets, and exploring hyperparameter optimization. Additionally, investigating the necessary node features and subdividing graphs for better model handling are key areas for further exploration. Additionally, other methods such as GraphSAGE might be more suitable, and a comparison should be made. This work paves the way for integrating advanced machine learning techniques with traditional risk assessment methodologies, contributing to the development of safer, more reliable, and partially explainable autonomous systems. © 2025 IEEE.

关键词： Graph neural networks

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Hyperspectral Image Classification Method Based on Global Space-Spectral Attention Mechanism

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Journal of Shanghai Jiaotong University (Science) 2025年 1-11页

作者： Qin, Rui Wu, Benze Liu, Xinfu Wu, Yirui College of Computer Science and Software Engineering Hohai University Nanjing211100 China Nangjing Research Institute of Electronic Engineering Nanjing210007 China College of Artificial Intelligence and Automation Hohai University Jiangsu Changzhou213200 China

In hyperspectral remote sensing imagery, pixel interactions within defined spatial extents result in the mixing of adjacent pixels. Additionally, the high similarity of adjacent spectra leads to information redundancy, which hinders the extraction of global spatial and spectral correlations. In order to solve the problems of mixed adjacent pixels and redundant adjacent spectra, this work offers a hyperspectral image classification approach that uses a global space-spectral attention mechanism. First, the proposed method’s global spatial attention module uses multi-scale dilated convolution to produce a bigger receptive field to be capable of capturing global spatial correlation and obtain unmixed pixel information. Then, the global spectral attention module designs a spectral domain partition algorithm, using the combination of regional density as well as information entropy as the threshold to divide spectrum into dispersed subsets and eliminate redundant information. The global context information for entire spectral band is fully exploited, and correlation of the global spectral information is extracted. Finally, the two modules combine to provide a global correlation of space and spectrum. Experiments demonstrate that the suggested method obtains overall accuracies of 97.28%, 94.73%, and 95.76% on the three WHU-Hi hyperspectral datasets, surpassing comparison methods. © Shanghai Jiao Tong University 2024.

关键词： Pixels

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YGC-SLAM:A visual SLAM based on improved YOLOv5 and geometric constraints for dynamic indoor environments

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虚拟现实与智能硬件(中英文) 2025年第1期7卷 62-82页

作者： Juncheng ZHANG Fuyang KE Qinqin TANG Wenming YU Ming ZHANG Department of Automation University of Information Science&TechnologyNanjing 210044China Department of Software University of Information Science&TechnologyNanjing 210044China Wuxi Research Institute of Nanjing University of Information Engineering Wuxi 214101China Department of Rail Transport University of WuxiWuxi 214101China

Background As visual simultaneous localization and mapping(SLAM)is primarily based on the assumption of a static scene,the presence of dynamic objects in the frame causes problems such as a deterioration of system robustness and inaccurate position *** this study,we propose a YGC-SLAM for indoor dynamic environments based on the ORB-SLAM2 framework combined with semantic and geometric constraints to improve the positioning accuracy and robustness of the *** First,the recognition accuracy of YOLOv5 was improved by introducing the convolution block attention model and the improved EIOU loss function,whereby the prediction frame converges quickly for better *** improved YOLOv5 was then added to the tracking thread for dynamic target detection to eliminate dynamic ***,multi-view geometric constraints were used for re-judging to further eliminate dynamic points while enabling more useful feature points to be retained and preventing the semantic approach from over-eliminating feature points,causing a failure of map *** K-means clustering algorithm was used to accelerate this process and quickly calculate and determine the motion state of each cluster of pixel ***,a strategy for drawing keyframes with de-redundancy was implemented to construct a clear 3D dense static point-cloud *** Through testing on TUM dataset and a real environment,the experimental results show that our algorithm reduces the absolute trajectory error by 98.22%and the relative trajectory error by 97.98%compared with the original ORBSLAM2,which is more accurate and has better real-time performance than similar algorithms,such as DynaSLAM and *** The YGC-SLAM proposed in this study can effectively eliminate the adverse effects of dynamic objects,and the system can better complete positioning and map building tasks in complex environments.

关键词： Visual SLAM Dynamic SLAM Target detection Geometric constraints

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Autonomous sortie scheduling for carrier aircraft fleet under towing mode

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Defence Technology(防务技术) 2025年第1期43卷 1-12页

作者： Zhilong Deng Xuanbo Liu Yuqi Dou Xichao Su Haixu Li Lei Wang Xinwei Wang Department of Engineering Mechanics State Key Laboratory of Structural AnalysisOptimization and CAE Software for Industrial EquipmentDalian University of TechnologyDalian116024China School of Mathematical Sciences Dalian University of TechnologyDalian 116024China Naval Aviation University Yantai 264001China China State Shipbuilding Corporation Systems Engineering Research Institute Beijing 100094China Department of Automation School of Information Science and TechnologyTsinghua UniversityBeijing 100084China

Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft *** primary difficulty exactly lies in the spatiotemporal coordination,i.e.,allocation of limited supporting resources and collision-avoidance between heterogeneous dispatch *** this paper,the problem is investigated in the perspective of hybrid flow-shop scheduling problem by synthesizing the precedence,space and resource ***,eight processing procedures are abstracted,where tractors,preparing spots,catapults,and launching are virtualized as *** analyzing the constraints in sortie scheduling,a mixed-integer planning model is *** particular,the constraint on preparing spot occupancy is improved to further enhance the sortie *** basic trajectory library for each dispatch entity is generated and a delayed strategy is integrated to address the collision-avoidance *** efficiently solve the formulated HFSP,which is essentially a combinatorial problem with tightly coupled constraints,a chaos-initialized genetic algorithm is *** solution framework is validated by the simulation environment referring to the Fort-class carrier,exhibiting higher sortie efficiency when compared to existing *** animation of the simulation results is available at ***/video/BV14t421A7Tt/.The study presents a promising supporting technique for autonomous flight deck operation in the foreseeable future,and can be easily extended to other supporting scenarios,e.g.,ammunition delivery and aircraft maintenance.

关键词： Carrier aircraft Autonomous sortie scheduling Resource allocation Collision-avoidance Hybrid flow-shop scheduling problem

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Recursive Broadcasting Approach 33

Recursive Broadcasting Approach

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33rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2025

作者： Harutyunyan, Hovhannes A. Hovhannisyan, Narek Concordia University Department of Computer Science and Software Engineering MontrealQCH3G 1M8 Canada Institute for Informatics and Automation Problems NAS RA Yerevan0014 Armenia

ISBN: (纸本)9798331524937

Broadcasting is one of the fundamental information dissemination primitives in interconnection networks, where a message is passed from one node (called originator) to all other nodes in the network. Following the increasing interest in interconnection networks, extensive research was dedicated to broadcasting. Two main research goals of this area are finding inexpensive network structures that maintain efficient broadcasting and finding the broadcast time for well-known and widely used network topologies. In the scope of this study, we will mainly focus on determining the broadcast time and nearoptimal broadcasting schemes in networks. Determination of the broadcast time of any node in an arbitrary network is known to be NP-hard. Polynomial time solutions are known only for a few network topologies. There also exist various heuristic and approximation algorithms for different network topologies. In this study, we consider the broadcast time problem on graphs that comprise some recursive structures. We initiate a novel direction to designing broadcasting algorithms on recursively defined graphs. We provide a theoretical foundation for future broadcasting studies, as well as discuss several practical applications of the approach we introduce. © 2025 IEEE.

关键词： Interconnection networks (circuit switching)

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Haptic-Aided Navigation Vehicle: Enhancing Obstacle Detection in Blind Spots and Transparent Object Scenarios

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Journal of Shanghai Jiaotong University (Science) 2025年 1-9页

作者： Li, Mingwang Li, Xinde Zhang, Zhentong Zhang, Zeyu Zhao, Haoming School of Software Southeast University Suzhou Jiangsu215000 China School of Automation Southeast University Nanjing210018 China School of Cyber Science and Engineering Southeast University Nanjing211102 China Key Laboratory of Measurement and Control of Complex Systems of Engineering of Ministry of Education Nanjing214135 China Nanjing Center for Applied Mathematics Nanjing211135 China Southeast University Shenzhen Research Institute Shenzhen Guangdong518063 China

As autonomous mobile robots are increasingly deployed in complex environments, traditional vision sensors and LiDAR encounter considerable limitations, particularly in detecting obstacles in blind spots or transparent objects. To address the issue of blind spots, we design a specialized haptic sensing structure and develop the haptic-aided navigation vehicle (HANV). This system integrates haptic sensors and LiDAR to deliver comprehensive perception, significantly enhancing close-range obstacle detection in areas that are typically beyond the range of conventional sensors. To tackle the challenge of transparent obstacles, which are often undetected by both vision and LiDAR sensors, we employ a fusion of haptic sensors and LiDAR. The haptic system provides physical contact feedback, ensuring reliable detection of transparent obstacles such as glass, while LiDAR offers long-range sensing capabilities. This combination enables HANV to navigate effectively in environments with transparent obstacles, overcoming the limitations of traditional sensing systems. Experiment results indicate that the proposed haptic and LiDAR integration substantially improves obstacle detection in both blind spots and environments with transparent obstacles. HANV achieves high success rates, minimal collisions, and efficient obstacle avoidance, particularly excelling in complex, confined spaces where conventional systems prove inadequate. These findings emphasize the efficacy of our approach in enhancing navigation performance in dynamic and challenging environments. (Figure presented.) © Shanghai Jiao Tong University 2025.

关键词： Mobile robots

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Recursive Broadcasting Approach

Recursive Broadcasting Approach

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Euromicro Conference on Parallel, Distributed and Network-Based Processing

作者： Hovhannes A. Harutyunyan Narek Hovhannisyan Department of Computer Science and Software Engineering Concordia University Montreal QC Canada NAS RA Institute for Informatics and Automation Problems Yerevan Armenia

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

关键词： Multicast algorithms Network topology Multiprocessor interconnection Heuristic algorithms Broadcasting Approximation algorithms Polynomials Topology

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Development and Optimization of a WebGL-Based Mechanical Model Simulation Platform 4th

Development and Optimization of a WebGL-Based Mechanical Mod...

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4th International Conference on Mechanical Design and Simulation, MDS 2024

作者： Wang, Xintong Tian, Hao Fang, Jingzhe Zhang, Hualiang Zhang, Tao Software College Shenyang University of Technology Liaoning Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School of Electrical Engineering Shenyang University of Technology Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9789819778867

The need for mechanical model simulation platforms is growing as a result of the ongoing advancements in digital technology and the mechanical manufacturing sector. The application scope and efficacy of simulation platforms are severely limited by the issue of sluggish rendering performance, which frequently arises when obtaining high-quality rendering. When drawing high demand mechanical models, a lot of processing power is frequently needed, which makes real-time rendering speed unsatisfactory for practical purposes. In order to achieve real-time rendering and simulation of 3D robots, this experiment built and implemented a WebGL-based 3D simulation platform. Additionally, the simulation platform can be optimized by increasing frame rate and rendering speed without sacrificing rendering effect by building a mixed bounding box. © The Author(s) 2025.

关键词： Digital elevation model

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Privacy Protection in Palmprint Recognition via Pruning Frequency Channels 18th

Privacy Protection in Palmprint Recognition via Pruning Fr...

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18th Chinese Conference on Biometric Recognition, CCBR 2024

作者： Shi, Siyu Shao, Huikai Zhong, Dexing School of Automation Science and Engineering Xi’an Jiaotong University Shaanxi Xi’an710049 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Xi’an Yizhanghui Technology Co. Shannxi Xi’an712000 China Pazhou Laboratory Guangzhou510335 China Research Institute of Xi’an Jiaotong University Zhejiang311215 China

ISBN: (纸本)9789819610679

Palmprint recognition is an emerging biometric technology with many advantages. However, there is some sensitive personal information in palmprint images. Once accessed by unauthorized malicious third parties, it may lead to privacy breaches. Current palmprint recognition methods focus on recognition accuracy but ignore the privacy protection issue. In this paper, we propose a novel privacy-protecting palmprint recognition method, named Pruning Frequency Channels (PFC). Based on the difference in image perception between the human eye and the model, we eliminate the privacy information in palmprint images by pruning the low-frequency components that can be perceived by humans. Subsequently, we propose a pruning strategy for determining the pruned channels based on the energy of the frequency channels. We explore the impact of the energy ratio threshold on PFC performance and find an energy ratio threshold that is universal to different datasets. Adequate experiments conducted on multiple databases show that our PFC method can perform better than other methods and effectively hide personal privacy information with almost no damage to recognition accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Frequency learning Palmprint recognition Privacy protection

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Temporal Feature Impact Explanation via Dynamic Sliding Window Sampling

Temporal Feature Impact Explanation via Dynamic Sliding Wind...

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Consumer Electronics and Computer engineering (ICCECE), 2021 IEEE International Conference on

作者： Yan Zhou Xiaodong Li Kedong Zhu Feng Li Huibiao Yang Yong Ren College of Computer Science and Software Engineering Hohai University Nanjing China Power Automation Department China Electric Power Research Institute Nanjing China Ningxia Electric Power Research Institute Yinchuan China

ISBN: (数字)9798331533113

ISBN: (纸本)9798331533120

Model interpretation methods are essential for understanding the predictions of machine learning models. How-ever, when applied to dynamic multivariate time series data, existing approaches encounter significant challenges, primarily due to the temporal correlations within the same feature at different time points. Ignoring temporal dependencies of time series data during interpretation usually leads to inadequate explanation results. To address these challenges, we propose a novel algorithm called Dynamic Sliding Window Sampling (DSWS) for explaining time series models. This algorithm dynam-ically generates importance scores for the same feature across various time steps by iteratively removing feature sets from specific time periods. Leveraging a sliding time window with an adaptable length, DSWS effectively captures the temporal dependencies of dynamic features and delineates their influence boundaries. Experiments on both synthetic and real world data sets validate DSWS’ applicability for time series data with dynamic temporal dependencies. Furthermore, it outperforms state-of-the-art methods in computational efficiency.

关键词： Adaptation models Correlation Heuristic algorithms Computational modeling Time series analysis Machine learning Predictive models Computational efficiency Consumer electronics

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