检索结果-内蒙古大学图书馆

Air-Ground Collaborative Mobile Edge Computing:Architecture,Challenges,and Opportunities

China Communications 2024年第5期21卷 1-16页

作者： Qin Zhen He Shoushuai Wang Hai Qu Yuben Dai Haipeng Xiong Fei Wei Zhenhua Li Hailong College of Communications Engineering Army Engineering University of PLANanjing 210000China Department of Information and Communication Noncommissioned Officer Academy of PAPHangzhou 310000China Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information TechnologyNanjing 211106China College of Electronic and Information Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210023China CMC Political and Law Commission Beijing100120China Xi’an Research Institute of High Technology Xi’an 710025China

By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-growing computational demands,it is impossible for a single MEC paradigm to effectively support high-quality intelligent services at end user equipments(UEs).To address this issue,we propose an air-ground collaborative MEC(AGCMEC)architecture in this *** proposed AGCMEC integrates all potentially available MEC servers within air and ground in the envisioned 6G,by a variety of collaborative ways to provide computation services at their best for ***,we introduce the AGC-MEC architecture and elaborate three typical use ***,we discuss four main challenges in the AGC-MEC as well as their potential ***,we conduct a case study of collaborative service placement for AGC-MEC to validate the effectiveness of the proposed collaborative service placement ***,we highlight several potential research directions of the AGC-MEC.

关键词： air-ground architecture collaborative mobile edge computing

来源：评论

学校读者我要写书评

暂无评论

Unified Modeling Method of Heterogeneous Resources for Multi-platform Avionics system Based on AADL 3

Unified Modeling Method of Heterogeneous Resources for Multi...

引用

3rd International Conference on Computer, Control and Robotics, ICCCR 2023

作者： Huang, Hui Liu, Chang Yang, Xunli An, Dong Guo, Yingxian Zhu, Wenjing China Aeronautical Radio Electronics Research Institute Key Laboratory of Avionics System Integration Shanghai China School of Reliability and Systems Engineering Beihang University Beijing China School of Software Beihang University Beijing China

ISBN: (纸本)9781665492126

Currently, single-platform avionics system modeling often uses service-oriented modeling methods to describe service-oriented architecture (SOA). However, for the multi-platform avionics system, the traditional modeling method can not represent the heterogeneous resources uniformly;and the description method of the relationship between services and resources is lacking. To solve these problems, this paper proposes a modeling method based on architecture analysis and design language (AADL). The heterogeneous resource pool model is constructed by unified description of heterogeneous resources internally and externally. In addition, a service-oriented approach is used to match function servitization with resources. This method is used to model a multi-platform avionics system. The example shows that this method can abstract heterogeneous resources in the same way, support multiple types of resources, and describe the relationship between services and resources in the task scenario. © 2023 IEEE.

关键词： Information services

来源：评论

学校读者我要写书评

暂无评论

DarkSAM: Fooling Segment Anything Model to Segment Nothing 38

DarkSAM: Fooling Segment Anything Model to Segment Nothing

引用

38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Zhou, Ziqi Song, Yufei Li, Minghui Hu, Shengshan Wang, Xianlong Zhang, Leo Yu Yao, Dezhong Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Computer Science and Technology Huazhong University of Science and Technology China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia

Segment Anything Model (SAM) has recently gained much attention for its outstanding generalization to unseen data and tasks. Despite its promising prospect, the vulnerabilities of SAM, especially to universal adversarial perturbation (UAP) have not been thoroughly investigated yet. In this paper, we propose DarkSAM, the first prompt-free universal attack framework against SAM, including a semantic decoupling-based spatial attack and a texture distortion-based frequency attack. We first divide the output of SAM into foreground and background. Then, we design a shadow target strategy to obtain the semantic blueprint of the image as the attack target. DarkSAM is dedicated to fooling SAM by extracting and destroying crucial object features from images in both spatial and frequency domains. In the spatial domain, we disrupt the semantics of both the foreground and background in the image to confuse SAM. In the frequency domain, we further enhance the attack effectiveness by distorting the high-frequency components (i.e., texture information) of the image. Consequently, with a single UAP, DarkSAM renders SAM incapable of segmenting objects across diverse images with varying prompts. Experimental results on four datasets for SAM and its two variant models demonstrate the powerful attack capability and transferability of DarkSAM. Our codes are available at: https://***/CGCL-codes/DarkSAM. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Video2Reward: Generating Reward Function from Videos for Legged Robot Behavior Learning 27

Video2Reward: Generating Reward Function from Videos for Leg...

引用

27th European Conference on Artificial Intelligence, ECAI 2024

作者： Zeng, Runhao Zhou, Dingjie Liang, Qiwei Liu, Junlin Li, Hui Huang, Changxin Li, Jianqiang Hu, Xiping Sun, Fuchun Artificial Intelligence Research Institute Shenzhen MSU-BIT University China College of Mechatronics and Control Engineering Shenzhen University China College of Computer Science and Software Engineering Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Department of Computer Science and Technology Tsinghua University China

ISBN: (纸本)9781643685489

Learning behavior in legged robots presents a significant challenge due to its inherent instability and complex constraints. Recent research has proposed the use of a large language model (LLM) to generate reward functions in reinforcement learning, thereby replacing the need for manually designed rewards by experts. However, this approach, which relies on textual descriptions to define learning objectives, fails to achieve controllable and precise behavior learning with clear directionality. In this paper, we introduce a new video2reward method, which directly generates reward functions from videos depicting the behaviors to be mimicked and learned. Specifically, we first process videos containing the target behaviors, converting the motion information of individuals in the videos into keypoint trajectories represented as coordinates through a video2text transforming module. These trajectories are then fed into an LLM to generate the reward function, which in turn is used to train the policy. To enhance the quality of the reward function, we develop a video-assisted iterative reward refinement scheme that visually assesses the learned behaviors and provides textual feedback to the LLM. This feedback guides the LLM to continually refine the reward function, ultimately facilitating more efficient behavior learning. Experimental results on tasks involving bipedal and quadrupedal robot motion control demonstrate that our method surpasses the performance of state-of-the-art LLM-based reward generation methods by over 37.6% in terms of human normalized score. More importantly, by switching video inputs, we find our method can rapidly learn diverse motion behaviors such as walking and running. © 2024 The Authors.

关键词： Robots

来源：评论

学校读者我要写书评

暂无评论

Forming Circle Formations of Multi-agent systems Under Actuator Faults 5th

Forming Circle Formations of Multi-agent Systems Under Actu...

引用

5th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2021

作者： Liu, Jiajun Ru, Xinfeng Xia, Weiguo Wang, Chen China National Aeronautical Radio Electronic Research Institute and National Key Laboratory of Science and Technology on Avionics System Integration Shanghai China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology Dalian China National Engineering Research Center of Software Engineering and the State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China

ISBN: (纸本)9789811939976

A distributed fault-tolerant formation control law is designed in this paper for multi-agent systems under external disturbances and actuator faults including time-varying loss of effectiveness faults. The initial position of each agent is already on a circle and the control purpose is to form a desired formation on this circle. Based on this local information, a distributed adaptive formation control law is designed by employing the congelation of variables method to deal with time-varying actuator faults. Finally, a simulation example is given to verify the effectiveness of the adaptive fault-tolerant control design method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Node Coupling for Inferring Networks from Short Time Series 5th

Node Coupling for Inferring Networks from Short Time Series

引用

5th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2021

作者： Li, Hang Wang, Li Xia, Chengyi Tianjin University of Technology Tianjin300382 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China Engineering Research Center of Learning-Based Intelligent System Ministry of Education Beijing China

ISBN: (纸本)9789811939976

Commonly abstracted as a set of units, the complex systems in the real world are interconnected with each other using the specific dynamical methods. However, in practice, there is nothing else but the performances of the system known, nor are the network structure and the dynamical rules observed. In order to solve this problem, a research has been conducted on network reconstruction, so as to recover the potential network structure and network dynamics from the observed time series. In this paper, a new method is proposed, namely, slope difference similarity (SDS), which is a way of thinking in reverse. Based on the trend of change in nodes, the coupling degree between nodes is judged and the network is reconstructed. By comparing the SDS and Kendall rank correlation method with experiments, the experimental results are obtained in this paper to demonstrate the effectiveness of SDS network reconstruction. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

Approximately Invertible Neural Network for Learned Image Compression

引用

IEEE Transactions on Image Processing 2025年 34卷 3041-3055页

作者： Gao, Yanbo Li, Shuai Fu, Meng Lv, Chong Yang, Zhiyuan Cai, Xun Yuan, Hui Ye, Mao Shandong University School of Software Jinan250100 China Shandong University-WeiHai Research Institute of Industrial Technology Shandong University Weihai264209 China Shandong University School of Control Science and Engineering Jinan250100 China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan250100 China University of Electronic Science and Technology of China Sichuan Chengdu611731 China

Learned image compression has attracted considerable interests in recent years. An analysis transform and a synthesis transform, which can be regarded as coupled transforms, are used to encode an image to latent feature and decode the feature after quantization to reconstruct the image. Inspired by the success of invertible neural networks in generative modeling, invertible modules can be used to construct the coupled analysis and synthesis transforms. Considering the noise introduced in the feature quantization invalidates the invertible process, this paper proposes an Approximately Invertible Neural Network (A-INN) framework for learned image compression. It formulates the rate-distortion optimization in lossy image compression when using INN with quantization, which differentiates from using INN for generative modelling. Generally speaking, A-INN can be used as the theoretical foundation for any INN based lossy compression method. Based on this formulation, A-INN with a progressive denoising module (PDM) is developed to effectively reduce the quantization noise in the decoding. Moreover, a Cascaded Feature Recovery Module (CFRM) is designed to learn high-dimensional feature recovery from low-dimensional ones to further reduce the noise in feature channel compression. In addition, a Frequency-enhanced Decomposition and Synthesis Module (FDSM) is developed by explicitly enhancing the high-frequency components in an image to address the loss of high-frequency information inherent in neural network based image compression, thereby enhancing the reconstructed image quality. Extensive experiments demonstrate that the proposed A-INN framework achieves better or comparable compression efficiency than the conventional image compression approach and state-of-the-art learned image compression methods. © 1992-2012 IEEE.

关键词： Image coding

来源：评论

学校读者我要写书评

暂无评论

Design and analysis of GPS satellite-based augmentation system based on low earth orbit constellations 3

Design and analysis of GPS satellite-based augmentation syst...

引用

2024 3rd International Conference on Aerospace and Control engineering, ICoACE 2024

作者： Yang, Jianlei Jin, Zhengzhen Zheng, Shuaiyong Huang, Shiyong Ma, Guoyu Ji, Shiran Key Laboratory of Satellite Navigation System and Equipment Technology Shijiazhuang050081 China The 54 Research Institute China Electronics Technology Group Shijiazhuang050081 China School of Integrated Circuit Science and Engineering Tianjin University of Technology Tianjin300384 China College of Software Tianjin Normal University Tianjin300387 China

Addressing the need for improved GPS accuracy, especially for low-dynamic users, this study introduces a GPS augmentation system employing Low Earth Orbit (LEO) satellites. We detail the principles of satellite navigation and augmentation and simulate the GPS-LEO constellation to analyse its performance in terms of satellite visibility and Position Dilution of Precision (PDOP). The results demonstrate substantial augmentation in navigation accuracy with the integrated system, as verified by UAV flight experiments. The integration of LEO satellites is anticipated to advance global navigation capabilities, with implications for intelligent transportation, logistics, and precision agriculture. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Global positioning system

来源：评论

学校读者我要写书评

暂无评论

A software Defect Location Method based on Static Analysis Results 9

A Software Defect Location Method based on Static Analysis R...

引用

9th International Conference on Dependable systems and Their Applications, DSA 2022

作者： Shi, Haoxiang Liu, Wu Liu, Jingyu Ai, Jun Yang, Chunhui School of Reliability and System Engineering Beihang University Beijing China Fifth Electronic Research Institute of Miit Ministry of Industry and Information Technology Key Laboratory of Industrial Software Engineering Application Technology Guangzhou China

ISBN: (数字)9781665488778

ISBN: (纸本)9781665488778

Code-graph based software defect prediction methods have become a research focus in SDP field. Among them, Code Property Graph is used as a form of data representation for code defects due to its ability to characterize the structural features and dependencies of defect codes. However, since the coarse granularity of Code Property Graph, redundant information which is not related to defects often attached to the characterization of software defects. Thus, it is a problem to be solved in how to locate software defects at a finer granularity in Code Property Graph. Static analysis is a technique for identifying software defects using set defect rules, and there are many proven static analysis tools in the industry. In this paper, we propose a method for locating specific types of defects in the Code Property Graph based on the result of static analysis tool. Experiments show that the location method based on static analysis results can effectively predict the location of specific defect types in real software program. © 2022 IEEE.

关键词： Static analysis

来源：评论

学校读者我要写书评

暂无评论

A Quantitative Measurement Method of Code Quality Evaluation Indicators based on Data Mining 9

A Quantitative Measurement Method of Code Quality Evaluation...

引用

9th International Conference on Dependable systems and Their Applications, DSA 2022

作者： Shao, Yikang Liu, Wu Ai, Jun Yang, Chunhui School of Reliability and System Engineering Beihang University Beijing China Fifth Electronic Research Institute of Miit Key Laboratory of Industrial Software Engineering Application Technology Ministry of Industry and Information Technology Guangzhou China

ISBN: (数字)9781665488778

ISBN: (纸本)9781665488778

software Code Quality Measurement is a systematic subject with a long history and rich theory. Since the 1960s, a large number of academic research on software code quality measurement methods have been generated. Many scholars have proposed software code quality measurement indicators and measurement methods, and given the measurement trend of evaluation indicators, and proposed a model to measure software quality. However, there are still some blanks in the quantitative evaluation of software code quality evaluation index. The software code quality measurement system is not complete enough to cover all aspects of software code quality from multiple perspectives. In addition, most studies have measured software code quality based on code inspection or code review, which has some limitations. This paper puts forward a software code quality evaluation system based on software network. On this basis, this paper proposes a quantitative measurement method of code quality evaluation indicators based on data mining. It provides a new idea for software quality evaluation or code quality evaluation. © 2022 IEEE.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：