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19th International Conference on Advanced data Mining and Applications, ADMA 2023

作者： Tan, Lei Hu, Miao Zhou, Yipeng Wu, Di School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou510006 China School of Computing Faculty of Science and Engineering Macquarie University SydneyNSW2109 Australia

ISBN: (纸本)9783031466632

Federated Learning (FL) is a promising decentralized machine learning framework that enables a massive number of clients (e.g., smartphones) to collaboratively train a global model over the Internet without sacrificing their privacy. Though FL’s efficacy in non-convex problems is proven, its convergence amidst biased client participation lacks theoretical study. In this paper, we analyze the convergence of FedAvg on non-convex problems, which is the most renowned FL algorithm. We assume even data distribution but non-IID among clients, and elucidate the convergence rate of FedAvg in situations characterized by biased client participation. Our analysis reveals that biased client participation can significantly reduce the precision of the FL model. We validate this through trace-driven experiments, demonstrating that unbiased client participation results in 11% to 50% higher test accuracy compared to extremely biased client participation. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Artificial intelligence

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Signage Detection Based on Adaptive SIFT 1

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11th International Conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2023

作者： Wang, Jiaji Chen, Shuwen Shao, Jiaqi Qu, Hui Wang, Ziyi School of Physics and Information Engineering Jiangsu Second Normal University Nanjing211200 China Jiangsu Province Engineering Research Center of Basic Education Big Data Application Nanjing211200 China State Key Laboratory of Millimeter Waves Southeast University Nanjing210096 China

ISBN: (数字)9789819967063

ISBN: (纸本)9789819967056

In navigation and wayfinding applications, signage is crucial for finding destinations. This paper proposes a new method for detecting signage, with the aim of helping blind individuals navigate unfamiliar indoor environments. To enhance the accuracy of signage detection and eliminate interference, the proposed method initially obtains the attended areas through a saliency map. The signage is then identified in these attended areas using SIFT algorithm-based adaptive threshold. This innovative approach is capable of detecting and recognizing multiple signs. Finally, audio facilitates the detection and recognition of results transferred to the users. Our experimental results, based on indoor signage datasets we collected, demonstrate the efficiency of our proposed method. On average, it takes 0.104 s to process the data. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computer programming

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A knowledge Graph Completion Model with Path-Specific Learning

A Knowledge Graph Completion Model with Path-Specific Learni...

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Medical Artificial Intelligence (MedAI), IEEE International Conference on

作者： Xiulin Zheng Zan Zhang Rui Li Xindong Wu Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education of China) and also with the School of Computer Science and Information Engineering Hefei University of Technology Hefei Anhui China Inspur Academy of Science and Technology Shandong China

ISBN: (数字)9798350377613

ISBN: (纸本)9798350377620

knowledge graphs (KGs) play an increasingly im-portant role in many knowledge-aware tasks. However, existing KGs are struggle with incompleteness, which motivates knowledge graph completion (KGC), that is, predicting the lost links between entities based on observed triples. Reasoning over relation paths in incomplete KGs is popular. Nonetheless, some significant issues are still remained to be addressed, such as path noise and ambiguity of inferred relation. To address these problems, we propose a novel path augmented _Reasoning model with avoidance of Path noise and Disambiguation of inferred relation in this paper, referred to as RPD. In this model, we calculate the sum of resource allocation for each relation path to measure its reliability to avoid the inference of path noise. To address the ambiguity of an inferred relation, we introduce position embedding to denote the relation position along the path when learning path representation. Extensive experiments conducted on benchmark datasets demonstrate the effectiveness of our proposal RPD model in the handling of KGC tasks compared to SOTAs.

关键词： Heavily-tailed distribution Noise knowledge graphs Benchmark testing Transformers Cognition Reliability Resource management Proposals Noise measurement

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Understanding the spatio-temporal dynamics of ecosystem services under multiple future scenarios to assess the progress of Sustainable Development Goals implementation

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Journal of Geographical Sciences 2025年第4期35卷 745-762页

作者： ZHANG Ze JIANG Weiguo LING Ziyan PENG Kaifeng WU Zhifeng LI Zhuo State Key Laboratory of Remote Sensing and Digital Earth Science Faculty of Geographical SciencesBeijing Normal UniversityBeijing 100875China School of Information and Control Engineering Qingdao University of TechnologyQingdao 266520ShandongChina College of Geographic and Environmental Sciences Tianjin Normal UniversityTianjin 300387China School of Geography and Remote Sensing Guangzhou UniversityGuangzhou 510006China National Marine Data and Information Service Tianjin 300171China

Ecosystem services in urban agglomerations are the environmental conditions under which human survival and development are *** assessment of ecosystem services and complex interactions can contribute positively to the achievement of the Sustainable Development Goals(SDGs)for urban ***,studies on the future contribution of multi-scenario ecosystem services to the SDGS are *** pronovel integrated modeling framework that integrates the CLUES,InVEST,SOM,and GWR approaches to address the complex relationship between ecosystem services over a long“past-present-future”time *** construct a novel ecosystem service bundle-based approach for measuring urban agglomerations progress towards achieving ecologically relevant sustainable development goals at multiple *** the future scenario,the water yield(WY),habitat quality(HQ),and soil conservation(SC)show similar spatial patterns,with comparable spatial grids,while carbon stock(CS)remains predominantly unchanged and the ecological protection scenario(EPS)improves more *** high-synergy regions are mainly distributed in bundle 4,and most of the trade-off regions appear in bundles 1 and *** the last 30 years,all but the water-related SDGs are declining in bundle 1 of the two urban agglomerations,which are 15%higher in the Guangxi Beibu Gulf(GBG)than in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA).From 2020 to 2035,the three scenarios demonstrate that the optimization of the SDGs progresses most effectively under the future ecological protection scenario(EPS).In particular,bundles 3 and 4 are significantly *** critical new knowledge can be used in sustainable ecosystem management and decision-making in urban agglomerations.

关键词： Sustainable Development Goals(SDGs) ecosystem service bundle trade-offs and synergies InVEST model self-organizing mapping(SOM)algorithm urban agglomeration in south china

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Angiosperm Genus Classification by RBF-SVM 1

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11th International Conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2023

作者： Chen, Shuwen Wang, Jiaji Ni, Yiyang Shao, Jiaqi Qu, Hui Wang, Ziyi School of Physics and Information Engineering Jiangsu Second Normal University Nanjing211200 China Jiangsu Province Engineering Research Center of Basic Education Big Data Application Nanjing211200 China State Key Laboratory of Millimeter Waves Southeast University Nanjing210096 China

ISBN: (数字)9789819967063

ISBN: (纸本)9789819967056

Angiosperm genus classification performance has plateaued in the last few years. This paper proposed a novel method based on gray-level co-occurrence matrix and radial basis function kernel support vector machine for angiosperm genus classification. We collected a 300-image dataset, 100 are Hibiscus, 100 are Orchis, and the rest 100 are Prunus by digital camera. The results showed that our method achieved an accuracy of 84.73 ± 0.41%. In all, this method is promising in angiosperm genus classification. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Support vector machines

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MANN-TYPE INERTIAL SUBGRADIENT EXTRAGRADIENT METHODS FOR BILEVEL EQUILIBRIUM PROBLEMS

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2022年第4期84卷 19-32页

作者： Ceng, Lu-Chuan Zhu, Li-Jun Yao, Zhangsong Department of Mathematics Shanghai Normal University Shanghai200234 China The Key Laboratory of Intelligent Information and Big Data Processing of NingXia North Minzu University Yinchuan750021 China School of Information Engineering Nanjing Xiaozhuang University Nanjing211171 China

In this paper, we introduce and analyze two Mann-type implicit inertial sub-gradient extragradient algorithms for solving the monotone bilevel equilibrium problem with a general system of variational inclusions and a common fixed-point problem of a finite family of strict pseudocontraction mappings and an asymptotically nonexpansive mapping constraints. Some strong convergence theorems for the proposed algorithms are established under the suitable assumptions. © 2022, Politechnica university of Bucharest. All rights reserved.

关键词： Variational techniques

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Quantum-Inspired Distributed Memetic Algorithm

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Complex System Modeling and Simulation 2022年第4期2卷 334-353页

作者： Guanghui Zhang Wenjing Ma keyi Xing Lining Xing Kesheng Wang the School of Information Science and Technology and the Hebei Key Laboratory of Agricultural Big Data Hebei Agricultural UniversityBaoding 071001China the School of Information Science and Technology Hebei Agricultural UniversityBaoding 071001China. the State Key Laboratory for Manufacturing System Engineering and the Systems Engineering Institute Xi’an Jiaotong UniversityXi’an 710049China the School of Electronic Xidian UniversityXi’an 710071China the Department of Production and Quality Engineering Norwegian University of Science and TechnologyTrondheim 7491Norway

This paper proposed a novel distributed memetic evolutionary model,where four modules distributed exploration,intensified exploitation,knowledge transfer,and evolutionary restart are coevolved to maximize their strengths and achieve superior global *** exploration evolves three independent populations by heterogenous *** exploitation evolves an external elite archive in parallel with exploration to balance global and local *** transfer is based on a point-ring communication topology to share successful experiences among distinct search *** restart adopts an adaptive perturbation strategy to control search diversity *** computation is a newly emerging technique,which has powerful computing power and parallelized ***,this paper further fuses quantum mechanisms into the proposed evolutionary model to build a new evolutionary algorithm,referred to as quantum-inspired distributed memetic algorithm(QDMA).In QDMA,individuals are represented by the quantum characteristics and evolved by the quantum-inspired evolutionary optimizers in the quantum *** QDMA integrates the superiorities of distributed,memetic,and quantum *** experiments are carried out to evaluate the superior performance of *** results demonstrate the effectiveness of special designs and show that QDMA has greater superiority compared to the compared state-of-the-art algorithms based on Wilcoxon’s rank-sum *** superiority is attributed not only to good cooperative coevolution of distributed memetic evolutionary model,but also to superior designs of each special component.

关键词： distributed evolutionary algorithm memetic algorithm quantum-inspired evolutionary algorithm quantum distributed memetic algorithm

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Solid state recycling of used aluminum alloy beverage cans by thermomechanical consolidation

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Heat Treatment and Surface engineering 2022年第1期4卷 90-98页

作者： Wang, Ziyi Yu, Yuanping Jin, Yu Li, Zhuolun Sun, Song Xu, Haoran Wu, Chengxun Zhang, Deliang School of Material Science and Engineering Northeastern University Shenyang China Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University) Ministry of Education Shenyang China

Solid-state recycling of used aluminum alloy beverage cans was accomplished by thermomechanical consolidation of the sheet fragments produced by shredding the cans. Different samples were obtained using two thermomechanical consolidation routes, one involving direct hot extrusion of a sheet fragment compact and the other involving upset hot-forging of a sheet fragment compact followed by hot extrusion of the forged ingot. The microstructures and mechanical properties of the samples were investigated. It was found that the samples contained less pores and exhibited better mechanical properties with a higher extrusion temperature and involving upset forging than with only hot extrusion, the highest tensile strength is 209.5 MPa and the largest elongation to fracture is 29.1%. The surface layers of the samples exhibited a clearly higher strength and tensile ductility than the interior. They also showed significantly different fracture behaviors, with the former being like fully ductile fracture and the latter involving delamination of the sheet fragments, suggesting that the bonding between the fragments is significantly stronger in the surface layer, possibly due to a higher amount of plastic deformation in it. Overall, the best quality solid state recycled material has tensile properties comparable with those of wrought aluminum alloy with the same composition. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： mechanical properties microstructure solid state recycling thermomechanical consolidation of sheet fragments Used aluminum beverage cans

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Vector Bending Sensor Based on 3D Printed Seven Core Fiber 22

Vector Bending Sensor Based on 3D Printed Seven Core Fiber

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22nd International Conference on Optical Communications and Networks, ICOCN 2024

作者： Cao, Yang Luo, Yanhua Chen, Wei Wen, Jianxiang Dong, Yanhua Wang, Tingyun Song, Zhiqiang Zhang, Xiaolei Ni, Jiasheng Wang, Jiaying Peng, Gang-Ding Chu, Yushi Zhang, Jianzhong Shanghai Institute for Advanced Communication and Data Science Shanghai University Institute of Optical Fiber Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai200444 China Shanghai Institute for Advanced Communication and Data Science Shanghai University Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai200444 China Laser Institute Qilu University of Technology Shandong Academy of Sciences Shandong Key Laboratory of Optical Fiber Sensing Technologies Jinan250014 China School of Electrical Engineering and Telecommunications University of New South Wales Photonics and Optical Communications Group SydneyNSW2052 Australia College of Physics and Optoelectronic Engineering Harbin Engineering University Key Laboratory of In-fiber Integrated Optics Ministry of Education Harbin150001 China

ISBN: (纸本)9798350367652

A novel vector bending sensor is proposed based on 3D printed seven core fiber (SCF). There are two sensing elements in the proposed sensor. One is the fiber Bragg grating (FBG) inscribed in the 3D printed SCF, and the other is the Mach-Zehnder interferometer (MZI) with the structure of single-mode fiber (SMF)-SCF-SMF. Two sensing elements exhibit significantly different responses to bending. In the curvature range of 1.115 to M-1, the curvature sensitivity of the MZI element is 22.622 nm/M-1, while that of the FBG element is 0.044 nm/M-1 in the same direction. Especially, due to the asymmetrical structure of 3D printed SCF, the proposed bending sensor clearly displays directional dependence. Given to the flexible design and manufacture of 3D printed fiber in structure and material, this study demonstrates that 3D printing fiber technology brings more opportunities for the development of advanced fiber sensors in future Internet of Things. © 2024 IEEE.

关键词： Mach-Zehnder interferometers

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TSKE: A Dual-Branch Model for knowledge Graph Embedding with Joint Textual and Structural Information 11th

TSKE: A Dual-Branch Model for Knowledge Graph Embedding wit...

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11th International Joint Conference on Rough Sets, IJCRS 2025

作者： Deng, Weibin Xiong, Yuanyuan Jiang, Ziqun Yu, Hong Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications Chongqing China Smart Posts Engineering Technology Research Center Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Cyberspace Big Data Intelligent Security Ministry of Education Chongqing China

ISBN: (纸本)9783031927430

knowledge graphs (KGs) serve as critical structured representations of the real world, modeling entities and their complex relational patterns. While traditional knowledge graph embedding (KGE) methods excel at capturing structural regularities through geometric or tensor operations, they have limitations in effectively integrating structural and textual information. To address this limitation, we propose TSKE, a novel dual-branch architecture that effectively integrates both textual and structural information. The text branch employs language models to encode textual descriptions, generating context-aware semantic representations. Simultaneously, the structure branch introduces a multi-scale dilated attention mechanism that captures local neighborhood patterns and global graph dependencies through hierarchical receptive fields. The efficient channel attention further enhances feature selectivity by adaptively filtering noise and emphasizing feature relevance. TSKE incorporates an adaptive fusion module that dynamically adjusts the contribution weights of textual and structural features. Experimental results demonstrate TSKE’s superior performance in KGE. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Dilated attention knowledge graph embedding Link prediction

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