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Retrieval-and-alignment based large-scale indoor point cloud semantic segmentation

Science China(information Sciences) 2024年第4期67卷 164-180页

作者： Zongyi XU Xiaoshui HUANG Bo YUAN Yangfu WANG Qianni ZHANG Weisheng LI Xinbo GAO school of Computer Science and Technology Chongqing University of Posts and Telecommunications Shanghai Artificial intelligence Laboratory school of electronic Engineering and Computer Science Queen Mary University of London

Current methods for point cloud semantic segmentation depend on the extraction of descriptive features. However, unlike images, point clouds are irregular and often lack texture information, making it demanding to extract discriminative features. In addition, noise, outliers, and uneven point distribution are commonly present in point clouds, which further complicates the segmentation task. To address these problems, a novel architecture is proposed for direct and accurate large-scale point cloud segmentation based on point cloud retrieval and alignment. The proposed approach involves using a feature-based point cloud retrieval method for searching for reference point clouds with annotations from a dataset. In the following segmentation stage, an overlap-based point cloud registration method has been developed to align the target and reference point clouds. For accurate and robust alignment, an overlap region estimation module is trained to locate the optimal overlap region between two pieces of point clouds in a coarse-to-fine manner. In the detected overlap region, the global and local features of the points are extracted and combined for featuremetric registration to obtain accurate transformation parameters between the target and reference point clouds. After alignment, the annotated segmentation of the reference is transferred to the target point clouds to obtain accurate segmentation results. Extensive experiments are conducted to show that the developed method outperforms the state-of-the-art approaches in terms of both accuracy and robustness against noise and outliers.

关键词： point cloud semantic segmentation large-scale indoor point clouds point cloud alignment overlap estimation label transfer

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Dual-blockchain based multi-layer grouping federated learning scheme for heterogeneous data in industrial IoT

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Blockchain(Research and Applications) 2024年第3期5卷 11-21页

作者： Xin Wang Haoji Zhang Haoyu Wu Hongnian Yu school of electronic information and Artificial intelligence Shaanxi University of Science&TechnologyXi’an710021China school of Engineering and the Built Environment Edinburgh Napier UniversityEdinburghEH105DTUnited Kingdom

Federated learning(FL)allows data owners to train neural networks together without sharing local data,allowing the industrial Internet of Things(IIoT)to share a variety of ***,traditional FL frameworks suffer from data heterogeneity and outdated *** address these issues,this paper proposes a dualblockchain based multi-layer grouping federated learning(BMFL)*** divides the participant groups based on the training tasks,then realizes the model training by combining synchronous and asynchronous FL through the multi-layer grouping structure,and uses the model blockchain to record the characteristic tags of the global model,allowing group-manners to extract the model based on the feature requirements and solving the problem of data *** addition,to protect the privacy of the model gradient parameters and manage the key,the global model is stored in ciphertext,and the chameleon hash algorithm is used to perform the modification and management of the encrypted key on the key blockchain while keeping the block header hash ***,we evaluate the performance of BMFL on different public datasets and verify the practicality of the scheme with real fault *** experimental results show that the proposed BMFL exhibits more stable and accurate convergence behavior than the classic FL algorithm,and the key revocation overhead time is reasonable.

关键词： Federal learning Multi-level grouping Editable blockchain Data heterogeneity Industrial Internet of Things(IIOT)

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A Fuzzy Trust Management Mechanism with Dynamic Behavior Monitoring for Wireless Sensor Networks

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China Communications 2024年第5期21卷 177-189页

作者： Fu Shiming Zhang Ping Shi Xuehong school of Artificial intelligence Chongqing University of EducationChongqing 400065China school of Communications and information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China

Traditional wireless sensor networks(WSNs)are typically deployed in remote and hostile environments for information *** wireless communication methods adopted by sensor nodes may make the network highly vulnerable to various *** encryption and authentication mechanisms cannot prevent attacks launched by internal malicious *** trust-based security mechanism is usually adopted to solve this problem in ***,the behavioral evidence used for trust estimation presents some uncertainties due to the open wireless medium and the inexpensive sensor ***,how to efficiently collect behavioral evidences are rarely *** address these issues,in this paper,we present a trust management mechanism based on fuzzy logic and a cloud ***,a type-II fuzzy logic system is used to preprocess the behavioral evidences and alleviate ***,the cloud model is introduced to estimate the trust values for sensor ***,a dynamic behavior monitoring protocol is proposed to provide a balance between energy conservation and safety *** results demonstrate that our trust management mechanism can effectively protect the network from internal malicious attacks while enhancing the energy efficiency of behavior monitoring.

关键词： behavior monitoring cloud fuzzy trust wireless sensor networks

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Tuning the ferroelectricity of Hf0.5Zr0.5O2 with alloy electrodes

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Science China(information Sciences) 2024年第8期67卷 321-330页

作者： Keqin LIU Bingjie DANG Zhiyu YANG Teng ZHANG Zhen YANG Jinxuan BAI Zelun PAN Ru HUANG Yuchao YANG Beijing Advanced Innovation Center for Integrated Circuits School of Integrated Circuits Peking University school of electronic and Computer Engineering Peking University Center for Brain Inspired Chips Institute for Artificial Intelligence Peking University Center for Brain Inspired intelligence Chinese Institute for Brain ResearchBeijing

Tuning ferroelectricity of Hf0.5Zr0.5O2is crucial for facilitating its practical applications in various fields, including in-memory and neuromorphic computing. Previous studies have revealed that the electrodes have a significant influence on ferroelectricity, and changing electrode materials can realize different but discrete ferroelectric polarization values. Here, we introduce an alloy-electrode method, in order to achieve gradual and accurate modulation of ferroelectric polarization, especially useful for matching the polarization charges at the interface of ferroelectric insulators and ferroelectric semiconductors. Au and W electrodes are chosen as baselines for realizing weak and strong ferroelectric polarization, where the intermediate states can be achieved by adjusting the ratio of metals in the Au-W alloy. To demonstrate the generality of this approach, the Cu-W alloy electrode is also realized for tuning ferroelectric polarization. The effect of alloy electrodes on device leakage current, endurance, and retention is evaluated. In addition, the temperature stability of ferroelectric capacitors is tested, where limited changes in both remnant polarization and coercive voltages are observed, showing the great potential of the ferroelectric hafnium oxide. Such gradual modulation of ferroelectric polarization could facilitate the application of Hf0.5Zr0.5O2in in-memory and neuromorphic computing.

关键词： ferroelectric hafnium oxide alloy electrode gradual modulation temperature stability

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Adaptive Successive POI Recommendation via Trajectory Sequences Processing and Long Short-Term Preference Learning

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Computers, Materials and Continua 2024年第1期81卷 685-706页

作者： Si, Yali Li, Feng Zhong, Shan Huo, Chenghang Chen, Jing Liu, Jinglian school of Computer Science and Engineering Changshu Institute of Technology Changshu 15500 China Suzhou Industrial intelligence and Big Data Laboratory Suzhou 215000 China school of information Science and Engineering Yanshan University Qinhuangdao 066004 China College of electronic and information Engineering Guangdong Ocean University Zhanjiang 524088 China

Point-of-interest (POI) recommendations in location-based social networks (LBSNs) have developed rapidly by incorporating feature information and deep learning methods. However, most studies have failed to accurately reflect different users' preferences, in particular, the short-term preferences of inactive users. To better learn user preferences, in this study, we propose a long-short-term-preference-based adaptive successive POI recommendation (LSTP-ASR) method by combining trajectory sequence processing, long short-term preference learning, and spatiotemporal context. First, the check-in trajectory sequences are adaptively divided into recent and historical sequences according to a dynamic time window. Subsequently, an adaptive filling strategy is used to expand the recent check-in sequences of users with inactive check-in behavior using those of similar active users. We further propose an adaptive learning model to accurately extract long short-term preferences of users to establish an efficient successive POI recommendation system. A spatiotemporal-context-based recurrent neural network and temporal-context-based long short-termmemory network are used to model the users' recent and historical checkin trajectory sequences, respectively. Extensive experiments on the Foursquare and Gowalla datasets reveal that the proposed method outperforms several other baseline methods in terms of three evaluation metrics. More specifically, LSTP-ASRoutperforms the previously best baselinemethod (RTPM)with a 17.15% and 20.62% average improvement on the Foursquare and Gowalla datasets in terms of the Fβ metric, respectively. © 2024 The Authors.

关键词： Contrastive Learning

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A new centrality measure based on neighbor loop structure for network dismantling

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Digital Communications and Networks 2024年第2期10卷 472-480页

作者： Qingxia Liu Bang Wang Jiming Qi Xianjun Deng school of electronic information and Communications Huazhong University of Science and TechnologyWuhan430074China school of Cyber Science and Engineering Huazhong University of Science and TechnologyWuhan430074China

Nearly all real-world networks are complex networks and usually are in danger of ***,it is crucial to exploit and understand the mechanisms of network attacks and provide better protection for network *** dismantling aims to find the smallest set of nodes such that after their removal the network is broken into connected components of sub-extensive *** overcome the limitations and drawbacks of existing network dismantling methods,this paper focuses on network dismantling problem and proposes a neighbor-loop structure based centrality metric,NL,which achieves a balance between computational efficiency and evaluation *** addition,we design a novel method combining NL-based nodes-removing,greedy tree-breaking and ***,we compare five baseline methods with our algorithm on ten widely used real-world networks and three types of model networks including Erd€os-Renyi random networks,Watts-Strogatz smallworld networks and Barabasi-Albert scale-free networks with different network generation *** results demonstrate that our proposed method outperforms most peer methods by obtaining a minimal set of targeted attack ***,the insights gained from this study may be of assistance to future practical research into real-world networks.

关键词： Complex networks Network dismantling Centrality measure

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High Order Total Variational Denoising Algorithm Based on lOverlapping Combination Sparse

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Instrumentation 2024年 30-40页

作者： Binxin Tang Xianchun Zhou Chengcheng Cui Yang Rui school of electronic and information Engineering Nanjing University of Information Science and Technology school of Artificial intelligence Nanjing University of Information Science and Technology

For addressing impulse noise in images,this paper proposes a denoising algorithm for non-convex impulse noise images based on the l0norm fidelity *** the total variation of the l0norm has a better denoising effect on the pulse noise,it is chosen as the model fidelity term,and the overlapping group sparse term combined with non-convex higher term is used as the regularization term of the model to protect the image edge texture and suppress the staircase *** the same time,the alternating direction method of multipliers,the majorizationminimization method and the mathematical program with equilibrium constraints were used to solve the *** results show that the proposed model can effectively suppress the staircase effect in smooth regions,protect the image edge details,and perform better in terms of the peak signal-to-noise ratio and the structural similarity index measure.

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Precise region semantics-assisted GAN for pose-guided person image generation

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CAAI Transactions on intelligence Technology 2024年第3期9卷 665-678页

作者： Ji Liu Zhenyu Weng Yuesheng Zhu Communication and information Security Lab Shenzhen Graduate SchoolPeking UniversityShenzhenChina school of Electrical and electronic Engineering Nanyang Technological UniversitySingaporeSingapore

Generating a realistic person's image from one source pose conditioned on another different target pose is a promising computer vision *** previous mainstream methods mainly focus on exploring the transformation relationship between the keypoint-based source pose and the target pose,but rarely investigate the region-based human semantic *** current methods that adopt the parsing map neither consider the precise local pose-semantic matching issues nor the correspondence between two different *** this study,a Region Semantics-Assisted Generative Adversarial Network(RSA-GAN)is proposed for the pose-guided person image gen-eration *** particular,a regional pose-guided semantic fusion module is first devel-oped to solve the imprecise match issue between the semantic parsing map from a certain source image and the corresponding keypoints in the source *** well align the style of the human in the source image with the target pose,a pose correspondence guided style injection module is designed to learn the correspondence between the source pose and the target *** addition,one gated depth-wise convolutional cross-attention based style integration module is proposed to distribute the well-aligned coarse style information together with the precisely matched pose-guided semantic information to-wards the target *** experimental results indicate that the proposed RSA-GAN achieves a 23%reduction in LPIPS compared to the method without using the seman-tic maps and a 6.9%reduction in FID for the method with semantic maps,respectively,and also shows higher realistic qualitative results.

关键词： deep learning image processing

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Arbitrary topological charge vortex beams from carbon dots random lasers

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Rare Metals 2024年第8期43卷 3844-3853页

作者： Xiang-Dong Wang Xiao-Bo Mi Jiu-Ru He Feng-Ying Ma Jun-Qiao Wang Li Song Yong-Qiang Zhang Si-Yu Lu Yong-Sheng Hu school of Physics and Microelectronics Zhengzhou UniversityZhengzhou 450001China State Key Laboratory of Reliability and intelligence of Electrical Equipment and Tianjin Key Laboratory of electronic Materials and Devices School of Electronics and Information EngineeringHebei University of TechnologyTianjin 300401China Green Catalysis Center College of ChemistryZhengzhou UniversityZhengzhou450001China

Vortex beams have attracted great attention due to their promising applications in the fields of high-capacity optical communication,optical micromanipulation,and quantum information ***,we demonstrate vortex beams with flexible control of the topological charge and modes in a carbon dots random laser for the first *** beams with different types,including the Laguerre-Gaussian(LG),Bessel-Gaussian(BG),LG-superposition,and polarized vortex beams with topological charges up to 50,have been successfully ***,vortex beams can be well realized in carbon dots random lasers with different emission wavelengths covering from 465 to 612 *** work would not only enrich the types of vortex laser,especially for solution-processable lasers,but also provide a new route to realizing multicolor and wavelength-tunable vortex lasers.

关键词： Carbon dots Random lasers Vortex beam Topological charge Spatial light modulator

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Fairness in machine learning: definition, testing,debugging, and application

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Science China(information Sciences) 2024年第9期67卷 41-61页

作者： Xuanqi GAO Chao SHEN Weipeng JIANG Chenhao LIN Qian LI Qian WANG Qi LI Xiaohong GUAN Faculty of electronic and information Engineering Xi'an Jiaotong University school of Cyber Science and Engineering Wuhan University Institute for Network Sciences and Cyberspace Tsinghua University

In recent years, artificial intelligence technology has been widely used in many fields, such as computer vision, natural language processing and autonomous driving. Machine learning algorithms, as the core technique of AI, have significantly facilitated people's lives. However, underlying fairness issues in machine learning systems can pose risks to individual fairness and social security. Studying fairness definitions, sources of problems, and testing and debugging methods of fairness can help ensure the fairness of machine learning systems and promote the wide application of artificial intelligence technology in various fields. This paper introduces relevant definitions of machine learning fairness and analyzes the sources of fairness problems. Besides, it provides guidance on fairness testing and debugging methods and summarizes popular datasets. This paper also discusses the technical advancements in machine learning fairness and highlights future challenges in this area.

关键词： artificial intelligence security machine learning security machine learning fairness model testing model debugging

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