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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Li Ping Qian Mingqing Li Xinyu Dong Yuan Wu Xiaoniu Yang College of Information Engineering Zhejiang University of Technology Hangzhou Zhejiang China Department of Computer and Information Science University of Macau Macao SAR China State Key Laboratory of Internet of Things for Smart City University of Macau Macao SAR China Science and Technology on Communication Information Security Control Laboratory Jiaxing China Institute of Cyberspace Security Zhejiang University of Technology Hangzhou China

ISBN: (纸本)9781665435413

Edge computing has been envisioned as a promising approach to enable the computation-intensive yet latencysensitive marine mobile services in the fifth generation and beyond wireless networks. In this paper, we investigate the edge computing in Marine Internet of Things (M-IoT) via the assistance of unmanned surface vehicles (USVs) subject to the eavesdropping attack. In particular, we consider a scenario in which USVs are exploited to provide cooperative jamming for the communication security at the physical layer when the high altitude platform (HAP) is performing task offloading transmission. We jointly optimize the workload offloaded by HAP, the HAP's transmission power as well as each USV's interfering signal power with the objective of minimizing the total energy consumption for completing the total workloads under the latency constraint. The bisection search method is first adopted to obtain the optimal solutions to the offloaded workload and each USV's interfering signal power. Further, by exploiting the monotonicity, the polyblock outer approximation based algorithm (POA-Algorithm) is designed to obtain the HAP's optimal transmission power. Finally, numerical results validate the optimality and effectiveness of our proposed algorithm by comparing it with the results of LINGO and different jamming schemes.

关键词： Energy consumption Wireless networks Search methods Physical layer Approximation algorithms Security Jamming

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A Novel Optimization Algorithm for Thermal Design of MCMs

A Novel Optimization Algorithm for Thermal Design of MCMs

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Chinese control and Decision Conference, CCDC

作者： Jie Yang Ning Ye Hongyuan Shen DongDong Ye Wei Zheng Jia Di College of Information Science and Engineering Northeastern University Shenyang China Beijing Institute of Control Engineering Beijing China Computer Science and Computer Engineering Department University of Arkansas U.S.A.

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

The layout optimization of components becomes a key role on thermal analysis and design of the multi-chip module (MCM). In this paper a novel modified thermal force-directed placement algorithm (MTFPA) is proposed, with the consideration of the components' size effect and improved the efficiency of TFPA. The simulation results show that, while maintaining optimal components placement, the modified algorithm can effectively overcome the components' overlapping and out-of-boundary problems occurred in the original TFPA, and reduce computation time significantly.

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An End-to-End Network for Single Image Dedusting

An End-to-End Network for Single Image Dedusting

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International Conference on Information science and control engineering (ICISCE)

作者： Jiayan Huang Zhaochai Yu Zuoyong Li Xiangpan Zheng Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China College of Mathematics and Computer Science Fuzhou University Fuzhou China

Dust storm not only reduces visibility of natural scene, but also affects capture capability of outdoor monitoring equipment. Image dedusting aims to remove dust storm in images and make image scenes clearer. However, most of existing image enhancement-based methods have focused on defogging and deraining, and have paid little attentions to image dedusting. Therefore, research of image dedusting is necessary. In this paper, we presented an end-to-end network for single image dedusting. First, the proposed method uses an encoder module to encode a dusty image into image feature maps. Second, it uses the latest smoothed dilated residual convolution module to alleviate gridding artifacts caused by a widely-used dilated convolution. Third, it adopts an attention-based module to fuse image features at different levels and extract more contextual image information. Finally, it utilizes a decoder module, which decodes the feature maps, to obtain a residue, and adds it to the input dusty image to obtain the final image dedusting result. Experiments demonstrate the effectiveness of the proposed method in image dedusting.

关键词： Information science control engineering Convolution Storms Fuses Feature extraction Decoding

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Unsupervised Generation of Tradable Topic Indices Through Textual Analysis

SSRN

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SSRN 2024年

作者： Lee, Marcel Spark, Alan Shanghai China Department of Economics Mathematics and Statistics Birkbeck College University of London Malet Street Bloomsbury LondonWC1E 7HX United Kingdom Department of Computer Science and Technology Tsinghua University Haidian District Beijing100084 China Department of Computing and Control Engineering University of Chemistry and Technology Technicka 5 Prague 6166 28 Czech Republic McKinsey & Company. Digital and Analytics Budapester Str. 46 Berlin10787 Germany

Stocks returns are moved by many risk factors. Thematic stock indices try to represent these factors, but are limited by the fact that risk factors are not directly observable. This paper shows a method to uncover hidden risk factors through text analysis. It applies the dynamic variant of the Latent Dirichlet Allocation (LDA) model to annual and quarterly reports to find a topic distribution for each stock. This is then interpreted as the risk factor partition and transformed into a standard normal basis which corresponds to pure risk factors. The weights indicate the proportions necessary to combine the equities into tradable topic indices. The need for human intervention is minimized by determining the optimal parameters automatically. © 2024, The Authors. All rights reserved.

关键词： Machine learning

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Toward parallel intelligence: an interdisciplinary solution for complex systems

arXiv

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arXiv 2023年

作者： Zhao, Yong Zhu, Zhengqiu Chen, Bin Qiu, Sihang Huang, Jincai Lu, Xin Yang, Weiyi Ai, Chuan Huang, Kuihua He, Cheng Jin, Yucheng Liu, Zhong Wang, Fei-Yue College of Systems Engineering National University of Defense Technology Changsha410073 China Hunan Institute of Advanced Technology Changsha410073 China Shanghai Institute of Infectious Disease and Biosecurity Shanghai200032 China Neuherberg Germany Department of Computer Science Hong Kong Baptist University 999077 Hong Kong State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

The growing complexity of real-world systems necessitates interdisciplinary solutions to confront myriad challenges in modeling, analysis, management, and control. To meet these demands, the parallel systems method rooted in Artificial systems, Computational experiments, and Parallel execution (ACP) approach has been developed. The method cultivates a cycle, termed parallel intelligence, which iteratively creates data, acquires knowledge, and refines the actual system. Over the past two decades, the parallel systems method has continuously woven advanced knowledge and technologies from various disciplines, offering versatile interdisciplinary solutions for complex systems across diverse fields. This review explores the origins and fundamental concepts of the parallel systems method, showcasing its accomplishments as a diverse array of parallel technologies and applications, while also prognosticating potential challenges. We posit that this method will considerably augment sustainable development while enhancing interdisciplinary communication and cooperation. © 2023, CC BY-NC-ND.

关键词： Iterative methods

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Multi-View Landmark-Assisted UAV Swarm 6-DoF Pose Estimation Using Resonant Beam and VIO

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IEEE Internet of Things Journal 2025年

作者： Du, Siyuan Xu, Mengyuan Li, Yixuan Fang, Wen Liu, Qingwen Yi, Peng Hong, Yiguang Tongji University School of Computer Science and Technology Shanghai201804 China Tongji University College of Electronic and Information Engineering Shanghai201804 China Chinese Academy of Sciences Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing100190 China

As an essential aerial platform in Internet of Things (IoT) applications, UAV swarms require high-precision attitude estimation in GPS-limited and dynamic environments, which supports higher-level IoT functions such as smart logistics, disaster response, and environmental monitoring. However, most odometry-based pose estimation methods in dynamic scenarios without GPS encounter issues with cumulative errors over time. In this paper, we propose a method to reduce these cumulative errors by constraining the absolute positioning of Visual-Inertial Odometry (VIO) using relative poses obtained from multi-view landmark and Resonant-Beam (RBeam) sensors between UAVs. For synchronous moments, we estimate the 6 Degree-of-Freedom (DoF) relative pose using the Angle of Arrival and Time of Flight data from the RBeam, combined with nonlinear optimization. For asynchronous moments, a two-stage visual estimation method is introduced, combining multi-camera epipolar geometry for rotation recovery and depth reconstruction optimization for translation recovery, enabling the estimation of asynchronous relative poses. Finally, we design a global objective function based on a sliding window and factor graph, integrating RBeam, multi-view landmark, and VIO for absolute 6-DoF pose optimization of the UAV swarm. Simulation results demonstrate that optimizing with the addition of RBeam synchronous relative poses improves overall positioning accuracy by 32.94% compared to pure VIO. Incorporating both RBeam synchronous and visual asynchronous relative poses further enhances overall positioning accuracy by 37.65%. Additionally, the UAV’s attitude benefits from the rotational constraints provided by the RBeam, achieving over 30% improvement in the pitch and yaw directions. © 2014 IEEE.

关键词： Global positioning system

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EMO: Edge Model Overlays to Scale Model Size in Federated Learning

arXiv

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arXiv 2025年

作者： Wu, Di He, Weibo Feng, Wanglei Wen, Zhenyu Qian, Bin Varghese, Blesson School of Computer Science University of St Andrews United Kingdom Institute of Cyberspace Security College of Information Engineering Zhejiang University of Technology China University of Science and Technology of China China State Key Laboratory of Industrial Control Technology Zhejiang University China

Federated Learning (FL) trains machine learning models on edge devices with distributed data. However, the computational and memory limitations of these devices restrict the training of large models using FL. Split Federated Learning (SFL) addresses this challenge by distributing the model across the device and server, but it introduces a tightly coupled data flow, leading to computational bottlenecks and high communication costs. We propose EMO as a solution to enable the training of large models in FL while mitigating the challenges of SFL. EMO introduces Edge Model Overlay(s) between the device and server, enabling the creation of a larger ensemble model without modifying the FL workflow. The key innovation in EMO is Augmented Federated Learning (AFL), which builds an ensemble model by connecting the original (smaller) FL model with model(s) trained in the overlay(s) to facilitate horizontal or vertical scaling. This is accomplished through three key modules: a hierarchical activation replay cache to decouple AFL from FL, a convergence-aware communication controller to optimize communication overhead, and an ensemble inference module. Evaluations on a real-world prototype show that EMO improves accuracy by up to 17.77% compared to FL, and reduces communication costs by up to 7.17× and decreases training time by up to 6.9× compared to SFL. © 2025, CC BY.

关键词： Federated learning

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SVD based scale transform invariant observable degree for LTI system

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science China(Information sciences) 2021年第3期64卷 246-248页

作者： Quanbo GE Peng ZHUO Hongli HE Zhentao HU Zhansheng DUAN Junzhi YU Shenzhen Institute of Guangdong Ocean University School of Automation Hangzhou Dianzi University Test Institute Chinese Flight Test Establishment College of Computer and Information Engineering Henan University The Center for Information Engineering Science Research Xi'an Jiaotong University State Key Laboratory of Complex System Management and Control Institute of AutomationChinese Academy of Sciences

Dear editor,The basic concept of observability is used to express the possibility to recover the state from measurements in modern control theory [1–3]. It is a qualitative parameter,which cannot reflect the observable degree(OD) ability [4,5].Therefore, the OD is presented to quantitatively obtain the function. The quantitative parameter is effective for indicating the exact degree of estimation ability.

关键词： observability matrix observable degree singular value decomposition scale transform invariance linear system linear relation

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Resistance potential of soil bacterial communities along a biodiversity gradient in forest ecosystems

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mLife 2022年第4期1卷 399-411页

作者： Jialiang Kuang Dongmei Deng Shun Han Colin T.Bates Daliang Ning Wensheng Shu Jizhong Zhou The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters Ministry of EducationSchool of Environment and EnergySouth China University of TechnologyGuangzhouChina Institute for Environmental Genomics and Department of Microbiology and Plant BiologyUniversity of OklahomaNormanOklahomaUSA State Key Laboratory of Biocontrol Guangdong Key Laboratory of Plant Resources and Conservation of Guangdong Higher Education InstitutesCollege of Ecology and EvolutionSun Yat-sen UniversityGuangzhouChina Guangxi Key Laboratory of Green Processing of Sugar Resources College of Biological and Chemical EngineeringGuangxi University of Science and TechnologyLiuzhouChina School of Life Sciences South China Normal UniversityGuangzhouChina School of Civil Engineering and Environmental Sciences University of OklahomaNormanOklahomaUSA School of Computer Sciences University of OklahomaNormanOklahomaUSA.8Earth and Environmental SciencesLawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA.

Higher biodiversity is often assumed to be a more desirable scenario for maintaining the functioning of ecosystems,but whether species-richer communities are also more disturbance-tolerant remains *** this study,we investigated the bacterial communities based on 472 soil samples from 28 forests across China with associated edaphic and climatic *** developed two indexes(i.e.,community mean tolerance breadth[CMTB]and community mean response asynchrony[CMRA])to explore the relationship between diversity and community resistance ***,we examined this resistance potential along the climatic and latitudinal *** revealed that CMTB was significantly and negatively related to species richness,resulting from the changes in balance between relative abundances of putative specialists and *** comparison,we found a unimodal relationship between CMRA and richness,suggesting that higher biodiversity might not always lead to higher community ***,our results showed differential local patterns along *** particular,local patterns in the northern region mainly followed general relationships rather than those for the southern forests,which may be attributed to the differences in annual means and annual variations of climate *** findings highlight that the community resistance potential depends on the composition of diverse species with differential environmental tolerance and *** study provides a new,testable evaluation by considering tolerance breadth and response asynchrony at the community level,which will be helpful in assessing the influence of disturbance under rapid shifts in biodiversity and species composition as a result of global environmental change.

关键词： ecological resistance forest soil bacterial community latitudinal gradient specialist–generalist balance species richness

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An Incremental Boolean Algorithm for Computing Minimal Hitting Sets

An Incremental Boolean Algorithm for Computing Minimal Hitti...

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International Congress on Image and Signal Processing, BioMedical engineering and Informatics (CISP-BMEI)

作者： Sen Huang Xiangfu Zhao Xiangrong Tong College of Mathematics and Computer Science Zhejiang Normal University Jinhua China School of Computer and Control Engineering Yantai University Yantai China

ISBN: (数字)9780738105451

ISBN: (纸本)9781665422994

Deriving all minimal hitting sets (MHSs) for a family of conflict sets is a classical problem in model-based diagnosis. An incremental Boolean algorithm for computing MHSs was proposed. According to the traditional Boolean algorithm, after selecting the element, we decomposed the whole family of conflict sets into left and right branches (parts), and incidentally, the left one was a subset of the right one. Therefore, after we got the solution of the left branch, we could directly obtain the solution of the right branch in an incremental way. Experimental results showed that our incremental approach was more efficient than the traditional Boolean algorithm and some other related algorithms, in many cases.

关键词： Signal processing algorithms Computational modeling Minimization Conferences Signal processing Optimization Merging

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