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Fractal autoencoder with redundancy regularization for unsupervised feature selection

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Science China(Information Sciences) 2025年

作者： Meiting SUN Fangyu LI Honggui HAN School of Information Science and Technology Beijing University of Technology Beijing Key Laboratory of Computational intelligence and Intelligent System Engineering Research center of Digital Community Ministry of Education Beijing Institute of Artificial intelligence(Beijing)

Feature selection is a crucial step in data preprocessing because feature selection reduces the dimensionality of data by eliminating irrelevant and redundant features. Since manual labeling is expensive, unsupervised feature selection has received increasing attention in recent years. However, existing unsupervised feature selection methods tend to prioritize selecting highly correlated features over exploring feature diversity. Thus, a regularized fractal autoencoder (RFAE) method is proposed to select informative features in an unsupervised way. Specifically, the fractal autoencoder network extends autoencoders to construct a correspondence neural network and a selection neural network. The correspondence neural network exploits interfeature correlations and the selection neural network selects the informative features. A redundancy regularization strategy consists of a redundancy elimination regularization term based on the dependency between features and a sparse regularization term based on the group lasso. The redundancy regularization strategy eliminates feature subset redundancy and enhances network generalization ability. Extensive experimental results on six publicly available datasets show that the proposed RFAE outperforms the compared methods regarding clustering accuracy and classification accuracy. Moreover, the proposed RFAE achieves acceptable computation efficiency.

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Learning from group supervision: the impact of supervision deficiency on multi-label learning

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Science China(Information Sciences) 2021年第3期64卷 5-17页

作者： Miao XU Lan-Zhe GUO School of Information Technology and Electrical Engineering The University of Queensland riken center for advanced intelligence project National Key Laboratory for Novel Software Technology Nanjing University

Multi-label learning studies the problem where one instance is associated with multiple *** supervised multi-label learning has attracted considerable research attention because of the annotation difficulty. Majority of the studies on weakly supervised multi-label learning assume that one group of weak annotations is available for each instance; however, none of these studies considers multiple groups of weak annotations that can be easily acquired through crowdsourcing. Recent studies on crowdsourced multilabel learning observed that the current query strategies do not agree well with human habits and that data cannot be collected as expected. Therefore, this study aims to design a new query strategy in accordance with human behavior patterns to obtain multiple groups of weak annotations. Further, a learning algorithm is proposed based on neural networks for such type of data. In addition, this study qualitatively and empirically analyzes factors in the proposed query strategy that may impact further learning and provides insights to obtain better query strategy with respect to future crowdsourcing in case of multi-label data.

关键词： multi-label learning weakly supervised leaning weakly supervised multi-label learning query strategy group supervision

LiDAR-Visual SLAM with Integrated Semantic and Texture Information for Enhanced Ecological Monitoring Vehicle Localization

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Computers, Materials & Continua 2025年第1期82卷 1401-1416页

作者： Yiqing Lu Liutao Zhao Qiankun Zhao Foreign Environmental Cooperation center Ministry of Ecology and Environment of PRCBeijing100035China Beijing Computing center Co. Ltd.Beijing Academy of Science and TechnologyBeijing100083China Beijing Guyu Interactive Artificial intelligence Application Co. Ltd.Beijing100024China

Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental *** vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant *** address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data ***,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less ***,visual texture information complements LiDAR-Visual localization by providing additional contextual *** incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of *** approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.

关键词： LiDAR-Visual simultaneous localization and mapping integrated semantic texture information

Chiller faults detection and diagnosis with sensor network and adaptive 1D CNN

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Digital Communications and Networks 2022年第4期8卷 531-539页

作者： Ke Yan Xiaokang Zhou Department of the Built Environment National University of Singapore4 Architecture Drive117566Singapore Faculty of Data Science Shiga UniversityHikone5228522Japan riken center for advanced intelligence project RIKENTokyo1030027Japan

Computer-empowered detection of possible faults for Heating,Ventilation and Air-Conditioning(HVAC)subsystems,e.g.,chillers,is one of the most important applications in Artificial intelligence(AI)integrated Internet of Things(IoT).The cyber-physical system greatly enhances the safety and security of the working facilities,reducing time,saving energy and protecting humans’*** the current trends of smart building design and energy management optimization,Automated Fault Detection and Diagnosis(AFDD)of chillers integrated with IoT is highly *** studies show that standard machine learning techniques,such as Principal Component Analysis(PCA),Support Vector Machine(SVM)and tree-structure-based algorithms,are useful in capturing various chiller faults with high accuracy *** the fast development of deep learning technology,Convolutional Neural Networks(CNNs)have been widely and successfully applied to various ***,for chiller AFDD,few existing works are adopting CNN and its extensions in the feature extraction and classification *** this study,we propose to perform chiller FDD using a CNN-based *** proposed approach has two distinct advantages over existing machine learning-based chiller AFDD ***,the CNN-based approach does not require the feature selection/extraction *** CNN is reputable with its feature extraction capability,the feature extraction and classification processes are merged,leading to a more neat AFDD framework compared to traditional ***,the classification accuracy is significantly improved compared to traditional methods using the CNN-based approach.

关键词： Chiller Fault detection and diagnosis Deep learning neural network Long short term memory Recurrent neural network Gated recurrent unit

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Low tensor-train rank with total variation for magnetic resonance imaging reconstruction

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Science China(Technological Sciences) 2021年第9期64卷 1854-1862页

作者： CHEN QiPeng CAO JianTing Graduate School of Engineering Saitama Institute of TechnologySaitama 369-0293Japan Tensor Learning Unit RIKEN Center for Advanced Intelligence Project(AIP)Tokyo 351-0198Japan

The model by imposing the low-rank minimization has been proved to be effective for magnetic resonance imaging(MRI) completion. Recent studies have also shown that imposing tensor train(TT) and total variation(TV) constraint on tensor completion can produce impressive performance, and the lower TT-rank minimization constraint can be represented as the guarantee for global constraint, while the total variation as the guarantee for regional constraint. In our solution, a new approach is utilized to solve TT-TV model. In contrast with imposing the alternating linear scheme, nuclear norm regularization on TT-ranks is introduced in our method as it is an effective surrogate for rank optimization and our solution does not need to initialize and update tensor cores. By applying the alternating direction method of multipliers(ADMM), the optimization model is disassembled into some sub-problems, singular value thresholding can be used as the solution to the first sub-problem and soft thresholding can be used as the solution to the second sub-problem. The new optimization algorithm ensures the effectiveness of data recovery. In addition, a new method is introduced to reshape the MRI data to a higher-dimensional tensor, so as to enhance the performance of data completion. Furthermore, the method is compared with some other methods including tensor reconstruction methods and a matrix reconstruction method. It is concluded that the proposed method has a better recovery accuracy than others in MRI data according to the experiment results.

关键词： tensor constraint minimization

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Visual localization for asteroid touchdown operation based on local image features

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Astrodynamics 2020年第2期4卷 149-161页

作者： Yoshiyuki Anzai Takehisa Yairi Naoya Takeishi Yuichi Tsuda Naoko Ogawa The University of Tokyo Tokyo113-8654Japan riken center for advanced intelligence project Tokyo103-0027Japan Japan Aerospace Exploration Agency Sagamihara252-5210Japan

In an asteroid sample-return mission,accurate position estimation of the spacecraft relative to the asteroid is essential for landing at the target *** the missions of Hayabusa and Hayabusa2,the main part of the visual position estimation procedure was performed by human operators on the Earth based on a sequence of asteroid images acquired and sent by the *** this approach is still adopted in critical space missions,there is an increasing demand for automated visual position estimation,so that the time and cost of human intervention may be *** this paper,we propose a method for estimating the relative position of the spacecraft and asteroid during the descent phase for touchdown from an image sequence using state-of-the-art techniques of image processing,feature extraction,and structure from *** apply this method to real Ryugu images that were taken by Hayabusa2 from altitudes of 20 km-500 *** is demonstrated that the method has practical relevance for altitudes within the range of 5-1 *** result indicates that our method could improve the efficiency of the ground operation in the global mapping and navigation during the touchdown sequence,whereas full automation and autonomous on-board estimation are beyond the scope of this ***,we discuss the challenges of developing a completely automatic position estimation framework.

关键词： visual navigation structure from motion asteroid touchdown Hayabusa2

A survey on blockchain-based integrity auditing for cloud data

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Digital Communications and Networks 2022年第5期8卷 591-603页

作者： Haoxiang Han Shufan Fei Zheng Yan Xiaokang Zhou The State Key Lab of ISN School of Cyber EngineeringXidian University266 Xinglong Section of Xifeng RoadXi'anShaanxi710126China The Faculty of Data Science Shiga UniversityHikone522-8522Japan The riken center for advanced intelligence project RIKENTokyo103-0027Japan

With the rapid advancement of cloud computing,cloud storage services have developed *** issue that has attracted particular attention in such remote storage services is that cloud storage servers are not enough to reliably save and maintain data,which greatly affects users’confidence in purchasing and consuming cloud storage *** data integrity auditing techniques for cloud data storage are centralized,which faces huge security risks due to single-point-of-failure and vulnerabilities of central auditing *** technology offers a new approach to this *** researchers have endeavored to employ the blockchain for data integrity *** on the search of relevant papers,we found that existing literature lacks a thorough survey of blockchain-based integrity auditing for cloud *** this paper,we make an in-depth survey on cloud data integrity auditing based on ***,we cover essential basic knowledge of integrity auditing for cloud data and blockchain ***,we propose a series of requirements for evaluating existing Blockchain-based Data Integrity Auditing(BDIA)***,we provide a comprehensive review of existing BDIA schemes and evaluate them based on our proposed ***,according to our completed review and analysis,we explore some open issues and suggest research directions worthy of further efforts in the future.

关键词： Blockchain Cloud storage Integrity auditing Decentralization

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A Multi-Objective Particle Swarm Optimization Algorithm Based on Decomposition and Multi-Selection Strategy

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Computers, Materials & Continua 2025年第1期82卷 997-1026页

作者： Li Ma Cai Dai Xingsi Xue Cheng Peng School of Computer Science Shaanxi Normal UniversityXi’an710119China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of TechnologyFuzhou350118China Information Construction and Management center and Institute of Artificial intelligence and Educational New Productivity Ningxia Normal UniversityGuyuan756099China

The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization *** the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search ***,two update strategies based on decomposition are used to update the evolving population and external archive,***,a multiselection strategy is *** first strategy is for the subspace without a non-dominated *** the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global *** second strategy is for the subspace with a non-dominated *** the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local *** third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated *** the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to ***,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search ***,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test *** results show that the proposed algorithm has better performance.

关键词： Multi-objective optimization multi-objective particle swarm optimization decomposition multi-selection strategy

Characterization of ultraviolet communication in a mixed aerosol environment

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Optoelectronics Letters 2025年第2期21卷 77-84页

作者： ZHAO Taifei SUN Yuxin WANG Wuxin ZHANG Haijun PAN Feixiang WU Hao Artificial intelligence Key Laboratory of Sichuan Province Sichuan University of Science & Engineering Faculty of Automation and Information Engineering Xi'an University of Technology

Wireless ultraviolet (UV) has strong scattering characteristics and can communicate through non-direct *** UV signals are transmitted in the atmosphere,they are affected by the absorption and scattering effects of atmospheric particles and atmospheric turbulence,resulting in attenuation of UV signal energy and reduced reliability of the communication *** paper focuses on the channel model of UV non-direct-view single scattering communication,and simulates and analyzes the communication characteristics of UV light in atmospheric turbulence and mixed aerosol environment under horizontal,vertical and oblique range communication *** results show that at equal relative humidity,the wireless UV non-directive scattering communication performance for vertical communication scenarios is more affected by the mixed aerosol environment and the communication performance is worse.

关键词： Atmospheric turbulence