检索结果-内蒙古大学图书馆

SSRN 2025年

作者： Li, Jingyuan Du, Chengfei Wang, Yulei Du, Di Liang, Jinlong Shao, Nengqi Feng, Fanzhe Xu, Wenhao Xu, Yongqing Cui, Yi Center for Joint Surgery Intelligent Manufacturing and Rehabilitation Engineering Center The First Affiliated Hospital of Army Medical University Chongqing400038 China Chongqing Municipal Science and Technology Bureau Key Laboratory of Precision Medicine in Joint Surgery Chongqing400038 China Chongqing Municipal Education Commission Key Laboratory of Joint Biology Chongqing400038 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of mechanical engineering Tianjin University of Technology Tianjin300384 China Department of Orthopaedic Surgery 920th Hospital of Joint Logistics Support Force Kunming650032 China Department of Orthopaedic Surgery 920th Hospital of Joint Logistics Support Force No. 212 of Da-Guan Road Xishan District Kunming650032 China

ObjectiveThis study aimed to verify the biomechanical efficacy of a novel internal fixation system for repairing lumbar spondylolysis (LS). Additionally, the changes in the mechanical performance of the novel internal fixation device during compression were *** healthy 25-year-old male volunteer was recruited for lumbar spine CT data acquisition to construct and validate a nonlinear finite element model of the L4-S1 spinal segment (A). Based on this, models were established for L5 spondylolysis (B), traditional internal fixation (C), and the pressurization process of the novel LS repair device fixation (D→E→F). For these six models, we constrained the lower surface of the S1 vertebral body while applying an axial compression force of 500 N and a moment load of 7.5 N·m on the upper surface of the L4 vertebral body to simulate six motions of the lumbar spine. The performance of each finite element model was evaluated by comparing the range of motion (ROM), maximum displacement, and maximum pressure experienced by the lumbar spine under different motion *** with Model C, Models D, E, and F exhibited a reduced ROM and maximum displacement (1%-38.5%, 12.8%-63.6%, and 32.8%-80.2%) compared with Model C during six different motions. Notably, compared with Model C, the novel internal fixation models consistently demonstrated a decreasing trend in the maximum stress on the intervertebral discs (IVD) and an increasing trend in the maximum stress on the articular cartilage and maximum stress and displacement of the bone graft. Moreover, the novel internal fixation model displayed larger ranges of evenly distributed stresses on the isthmus and reduced maximum stress on the internal fixation device across all six motions, with improved stiffness effects during the pressurization process of the novel internal fixation system (D→E→F).ConclusionsAccording to several mechanical comparisons, the novel internal fixation system had better biomechan

关键词： Axial compression

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design of MEMS Step Impedance Microstrip Filter in Ku Band

Design of MEMS Step Impedance Microstrip Filter in Ku Band

引用

IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Tianyu Bai Guohui Yang Kuang Zhang Yingsong Li Tao Jiang School of Electronics and Information Engineering Harbin Institute of Technology Harbin China Anhui Province Key Laboratory of Target Recognition and Feature Extraction LuAn China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology Harbin Engineering University Harbin China

According to the miniaturization characteristics of step impedance resonators, a step impedance bandpass filter with a center frequency of 16.55 GHz and a bandwidth of 500MHz is designed. The effects of parameter changes such as substrate resistivity and the shape of metal via etching on the performance of the filter are studied. Finally, the filter is fabricated and its performance is tested under MEMS technology.

关键词： Band-pass filters Micromechanical devices Microstrip filters Shape Resonator filters Metals Conductivity

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CLIMS++: Cross Language Image Matching with Automatic Context Discovery for Weakly Supervised Semantic Segmentation

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International Journal of Computer Vision 2025年 1-20页

作者： Xie, Jinheng Deng, Songhe Hou, Xianxu Luo, Zhaochuan Shen, Linlin Huang, Yawen Zheng, Yefeng Shou, Mike Zheng Computer Vision Institute School of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Computer Science Wenzhou-Kean University Wenzhou325060 China Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China Show Lab National University of Singapore Singapore639798 Singapore School of AI and Advanced Computing Xi’an Jiaotong-Liverpool University Suzhou215400 China Jarvis Research Center Tencent YouTu Lab Shenzhen518703 China

While promising results have been achieved in weakly-supervised semantic segmentation (WSSS), limited supervision from image-level tags inevitably induces discriminative reliance and spurious relations between target classes and background regions. Thus, Class Activation Map (CAM) usually tends to activate discriminative object regions and falsely includes lots of class-related backgrounds. Without pixel-level supervisions, it could be very difficult to enlarge the foreground activation and suppress those false activation of background regions. In this paper, we propose a novel framework of Cross Language Image Matching with Automatic Context Discovery (CLIMS++), based on the recently introduced Contrastive Language-Image Pre-training (CLIP) model, for WSSS. The core idea of our framework is to introduce natural language supervision to activate more complete object regions and suppress class-related background regions in CAM. In particular, we design object, background region, and text label matching losses to guide the model to excite more reasonable object regions of each category. In addition, we propose to automatically find spurious relations between foreground categories and backgrounds, through which a background suppression loss is designed to suppress the activation of class-related backgrounds. The above designs enable the proposed CLIMS++ to generate a more complete and compact activation map for the target objects. Extensive experiments on PASCAL VOC 2012 and MS COCO 2014 datasets show that our CLIMS++ significantly outperforms the previous state-of-the-art methods. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Semantic Segmentation

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Joint Optimization of Integrated Mixed Maintenance and Distributed Two-Stage Hybrid Flow-Shop Production for Multi-Site Maintenance Requirements

SSRN

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SSRN 2022年

作者： Wang, Zhen Deng, Qianwang Zhang, Like Li, Haiqiu Li, Fengyuan State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China Henan Provincial Key Laboratory of Intelligent Manufacturing of Mechanical Equipment Zhengzhou University of Light Industry Zhengzhou450002 China China Railway Tunnel Group Co. Ltd Guangzhou511400 China

Similar to the synergy of machines and workers in the production process, a perfect operation and maintenance (O&M) service can be implemented only when spare parts and service workers are available at the same time. Considering the production of spare parts and the limited number of workers, an integrated optimization problem of dual scheduling of comprehensive production and maintenance is proposed in this paper. Specifically, in view of the characteristics that distributed hybrid flow-shops are often encountered in the industrial environment and one maintenance activity can be completed by one worker or two workers jointly, we integrate a mixed maintenance service with single and two workers into distributed two-stage hybrid flow-shop production based on multi-site maintenance requirements. By reasonably arranging production and maintenance, a comprehensive production and maintenance scheduling scheme for minimizing the total weighted earliness/tardiness penalty and the number of orders lost is provided. To the end, this paper establishes a mixed integer programming model with dual objectives and proposes an improved NSGA-II (INSGA-II) to solve the above problem. In INSGA-II, an initialization rule, an initialization optimization strategy and three local search operators are designed according to the relevant characteristics of the problem. To give full play to the best performance of the algorithm, the key parameters are set by a full factor experiment. Extensive experiments are carried out, whose results verify that INSGA-II has good advantages in solving the problem studied. © 2022, The Authors. All rights reserved.

关键词： Scheduling

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Federated Graph Learning via Constructing and Sharing Feature Spaces for Cross-Domain IoT

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IEEE Internet of Things Journal 2025年

作者： Chen, Jiale Zhuo, Shengda He, Jinchun Qiu, Wangjie Zhang, Qinnan Xiong, Zehui Zheng, Zhiming Tang, Yin Chen, Min Wang, Changdong Huang, Shuqiang Jinan University College of Cyber Security Guangzhou China Beihang University Institute of Artificial Intelligence Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beijing100191 China Zhongguancun Laboratory Beijing China Singapore University of Technology and Design Information Systems Technology and Design 487372 Singapore Jinan University School of Management Guangzhou China South China University of Technology School of Computer Science and Engineering Guangzhou China Sun Yat-sen University School of Computer Guangzhou China Jinan University College of Cyber Security of Jinan University China Guangdong Key Laboratory of Data Security and Privacy Preserving Guangzhou China

The Internet of Things (IoT) collects large volumes of diverse data, with graph data as a critical component, and extensively utilizes Federated Graph Learning (FGL) to process this data while preserving data security. However, the graph data collected by different IoT institutions are relatively independent due to various factors (e.g., data collection methods, geographical locations), and data access is restricted to local environments due to privacy constraints, IoT institutions typically possess heterogeneous feature spaces. Aggregating under these conditions could potentially contaminate local graph representations. Unfortunately, most existing FGL methods tend to overlook this issue. To address this challenge, we propose Federated Graph Learning via Constructing and Sharing Features (FedCSF), a novel FGL framework designed to build a globally consistent feature space and share it among IoT institutions. To construct and extract the feature space, we employ an uniform feature initialization across IoT institutions and design an encoder to extract both global and local feature relationships, thereby facilitating effective collaboration across data from different IoT institutions. Furthermore, we introduce an independent adaptive aggregation strategy to eliminate the integration of harmful knowledge, ensuring that the contributions from each IoT institution are effectively integrated into the global model. We theoretically analyze the convergence of FedCSF. To validate the effectiveness of FedCSF, we conducted extensive experiments under various settings (i.e., cross-datasets, and cross-domains), demonstrating its significant advantages of FedCSF in terms of performance, convergence speed, and practical adaptability © 2014 IEEE.

关键词： Federated learning

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DNN Task Assignment in UAV Networks: A Generative AI Enhanced Multi-Agent Reinforcement Learning Approach

arXiv

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arXiv 2024年

作者： Tang, Xin Chen, Qian Weng, Wenjie Liao, Binhan Wang, Jiacheng Cao, Xianbin Li, Xiaohuan Guangxi University Key Laboratory of Intelligent Networking and Scenario System School of Information and Communication Guilin University of Electronic Technology Guilin541004 China The College of Computing and Data Science Nanyang Technological University 639798 Singapore School of Architecture and Transportation Engineering Guilin University of Electronic Technology Guilin541004 China National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology Guangxi Nanning530001 China College of Computing and Data Science Nanyang Technological University 639798 Singapore School of Electronic and Information Engineering The Key Laboratory of Advanced Technology of Near Space Information System Ministry of Industry and Information Technology of China Beihang University Beijing100191 China

Unmanned Aerial Vehicles (UAVs) possess high mobility and flexible deployment capabilities, prompting the development of UAVs for various application scenarios within the Internet of Things (IoT). The unique capabilities of UAVs give rise to increasingly critical and complex tasks in uncertain and potentially harsh environments. The substantial amount of data generated from these applications necessitates processing and analysis through deep neural networks (DNNs). However, UAVs encounter challenges due to their limited computing resources when managing DNN models. This paper presents a joint approach that combines multiple-agent reinforcement learning (MARL) and generative diffusion models (GDM) for assigning DNN tasks to a UAV swarm, aimed at reducing latency from task capture to result output. To address these challenges, we first consider the task size of the target area to be inspected and the shortest flying path as optimization constraints, employing a greedy algorithm to resolve the subproblem with a focus on minimizing the UAV’s flying path and the overall system cost. In the second stage, we introduce a novel DNN task assignment algorithm, termed GDM-MADDPG, which utilizes the reverse denoising process of GDM to replace the actor network in multi-agent deep deterministic policy gradient (MADDPG). This approach generates specific DNN task assignment actions based on agents’ observations in a dynamic environment. Simulation results indicate that our algorithm performs favorably compared to benchmarks in terms of path planning, Age of Information (AoI), energy consumption, and task load balancing. Copyright © 2024, The Authors. All rights reserved.

关键词： Motion planning

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Stacking, Strain-Engineering Induced Altermagnetism, Multipiezo Effect, and Topological State in Two-Dimensional Materials

arXiv

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arXiv 2025年

作者： Xun, Wei Liu, Xin Zhang, Youdong Wu, Yin-Zhong Li, Ping Jiangsu Engineering Research Center for Design and Application of Intelligent Detection Equipment School of Electronic Engineering Jiangsu Vocational College of Electronics and Information Huaian223003 China School of Physical Science and Technology Suzhou University of Science and Technology Suzhou215009 China State Key Laboratory for Mechanical Behavior of Materials Center for Spintronics and Quantum System School of Materials Science and Engineering Xi’an Jiaotong University Shaanxi Xi’an710049 China State Key Laboratory for Surface Physics Department of Physics Fudan University Shanghai200433 China State Key Laboratory of Silicon and Advanced Semiconductor Materials Zhejiang University Hangzhou310027 China

Altermagnetism, as a newly identified form of unconventional antiferromagnetism, enables the removal of spin degeneracy in the absence of net magnetization that provides a platform for the low power consumption and ultra-fast device applications. However, the rare attention has been paid to the relationship between stacking, strain and altermagnet, multipiezo effect and topological state. Here, we propose a mechanism to realize the altermagnet, multipiezo effect, and topological state in two-dimensional materials by the stacking and strain engineering. Based on the analysis of symmetry, we find that the spin splitting feature related to the Ut, PTt, MzUt, or MzPTt symmetries in altermagnet multilayers. In addition, we find that the stacking engineering can effectively realize the transform from antiferromagnetism to altermagnetism and semiconductor to metal for the Jauns bilayer V2SeTeO. More interestingly, the strain not only induces an intriguing multipiezo effect, encompassing the piezovalley, piezomagnetism and piezoelectric, but also achieves the abundant topological phase. Our findings offer a generalized direction for manipulating the spin splitting, valley polarization, and topological states, promoting practical application of valleytronic and spintronic devices based on two-dimensional altermagnets. © 2025, CC BY.

关键词： Antiferromagnetism

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TICNet: Three-Branch Real-Time Semantic Segmentation Network with Intensive Compensation of Railway Track Scenes

TICNet: Three-Branch Real-Time Semantic Segmentation Network...

引用

Machine Learning and Computer Application (ICMLCA), International Conference on

作者： Yiwen Bai Lu Yang Lei Zhang Yajing Song School of Transportation Science and Engineering Beihang University Beijing China Tianjin Key Laboratory for Advanced Mechanical System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology) Tianjin China Traffic Control Technology Co. Ltd Beijing China

ISBN: (数字)9798331530334

ISBN: (纸本)9798331530341

With the rapid development of railway traffic system, real-time semantic segmentation plays a crucial role in railway track scene monitoring. However, most of the existing methods use lightweight convolution to reduce the computational complexity, which results in reduced accuracy. To solve this problem, this paper proposes a real-time semantic segmentation network called TICNet, which is specifically used for accurate segmentation of railway track scenes. TICNet uses a novel three-branch structure designed for efficient feature extraction and accurate segmentation. Results on the RailSem19 dataset show that TICNet has a segmentation accuracy of 62.36% mIoU with an inference speed of 81.2 FPS, which is significantly better than many existing methods.

关键词： Accuracy Convolution Semantic segmentation Semantics Focusing Machine learning Feature extraction Real-time systems Computational complexity Monitoring

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design, Fabrication, and Characterization of Soft Robotic Claw Inspired by Parrot Feet for Grasping

SSRN

引用

SSRN 2024年

作者： Hao, Tianze Feng, Jingjing Ma, Yue Liu, Songtao Wang, Jutao Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology School of Mechanical Engineering Tianjin300384 China Automation Equipment Company Limited Tianjin301701 China Tianjin University of Technology China

Soft pneumatic actuators (SPAs) have demonstrated the ability to generate contraction, expansion, and bending strokes in three-dimensional space during pressurization. Gripper composed of SPAs are expected to serve as end effectors to improve the adaptability and lightweight of mobile robots in complex environments. In this study, a soft robotic claw inspired by the zygodactyl structure of parrot feet is developed featuring pneu-net actuators with oblique air chambers. These chambers enable bending and twisting movements, ensuring effective contact with the cylindrical landing objects. Integration of a thin steel sheet as the strain limiting layer not only improves static stability, but also augments the output force by approximately 57%, significantly ameliorating the claw’s gripping strength. Comparative gripping tests on diverse everyday items, indicate that while soft claw with vertical chambers adeptly handle centrosymmetric objects, whose with oblique chambers excel at at securing objects with large diameters, making them particularly suitable for perching applications on unmanned aerial vehicles. Moreover, enhancing the actuators with a uniformly soft surface texture, approximately 1.8 mm in height, notably increases friction force, thereby improving grip and stability. Comprehensive static stability assessments on birch logs confirmed its effective gripping and perching capabilities. The proposed soft claw has certain application prospects in situations that require flexible operation and complex grasping tasks due to its lightweight, flexibility, and strong adaptability. © 2024, The Authors. All rights reserved.

关键词： Pneumatic actuators

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CADEC: A Combinatorial Auction for Dynamic Distributed DNN Inference Scheduling in Edge-Cloud Networks

引用

IEEE Transactions on Mobile computing 2025年

作者： Xu, Xiaolong Hu, Yuhao Cui, Guangming Qi, Lianyong Dou, Wanchun Nanjing University of Information Science and Technology School of Software Nanjing210044 China Nanjing University of Information Science and 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 College of Computer science and technology Qingdao China Georgia State University Department of Computer Science United States

Deep Neural Network (DNN) Inference, as a key enabler of intelligent applications, is often computation-intensive and latency-sensitive. Combining the advantages of cloud computing (abundant computing resources) and edge computing (fast transmission), edge-cloud collaborative DNN inference is a powerful solution to these problems. However, in edge-cloud networks with heterogeneous resources, how to obtain reasonable decisions on server selection, model partition and resource allocation for efficient distributed DNN inference is a hard challenge. Furthermore, it is non-trivial to design suitable resource prices to maximize the social welfare. These challenges even escalate in dynamic edge-cloud networks where decisions should be generated as soon as each user arrives without future information. Therefore, we design a combinatorial auction for dynamic distributed DNN inference scheduling, named CADEC. CADEC first constructs a bid set for each user based on convex optimization theory for optimal solution searching. Next, prices of resources in the edge-cloud network are adjusted according to changes in supply-demand relationship, and whether to admit the request of each user is decided. Finally, the dynamic distributed inference scheduling decisions are generated through the primal-dual algorithm to maximize the social welfare. Theoretical analysis shows the good competitive ratio and polynomial time complexity of CADEC. Results of simulation experiments present that CADEC improves social welfare by up to 46% compared with state-of-the-art distributed DNN inference schemes. © 2002-2012 IEEE.

关键词： Convex optimization

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