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Multivariate Time Series Anomaly Detection Based on Spatial-Temporal Network and Transformer in Industrial Internet of Things

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Computers, Materials & Continua 2024年第8期80卷 2815-2837页

作者： Mengmeng Zhao Haipeng Peng Lixiang Li Yeqing Ren Information Security Center State Key Laboratory ofNetworking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China National Engineering Laboratory for Disaster Backup and Recovery Beijing University of Posts and TelecommunicationsBeijing100876China Department of Information Science and Engineering Zaozhuang UniversityZaozhuang277160China

In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working *** the systems are attacked,timely identification of outliers in time series is critical to ensure *** many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these *** to the superior capability of Transformer in learning time series *** paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved ***,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are ***,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each *** scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each *** interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory *** introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph *** on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.

关键词： Multivariate time series anomaly detection spatial-temporal network Transformer

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Integrated Clustering and Routing Design and Triangle Path Optimization for UAV-Assisted Wireless Sensor Networks

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China Communications 2024年第4期21卷 178-192页

作者： Shao Liwei Qian Liping Wu Mengru Wu Yuan College of Information Engineering Zhejiang University of TechnologyHangzhou 310014China State Key Laboratory of Internet of Things for Smart City University of MacaoMacaoChina Department of Computer and Information Science University of MacaoMacaoChina

With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower ***,a large amount of data generated from monitoring and long-distance transmission places a heavy burden on sensor nodes with the limited battery *** this,we investigate an unmanned aerial vehicles assisted mobile wireless sensor network(UAV-assisted WSN)to prolong the network lifetime in this ***,we use UAVs to assist the WSN in collecting *** the current UAV-assisted WSN,the clustering and routing schemes are determined ***,such a separate consideration might not maximize the lifetime of the whole WSN due to the mutual coupling of clustering and *** efficiently prolong the lifetime of the WSN,we propose an integrated clustering and routing scheme that jointly optimizes the clustering and routing *** the whole network space,it is intractable to efficiently obtain the optimal integrated clustering and routing ***,we propose the Monte-Las search strategy based on Monte Carlo and Las Vegas ideas,which can generate the chain matrix to guide the algorithm to find the solution *** point-to-point collection leads to long collection paths,so a triangle optimization strategy is then proposed that finds a compromise path to shorten the collection path based on the geometric distribution and energy of sensor *** avoid the coverage hole caused by the death of sensor nodes,the deployment of mobile sensor nodes and the preventive mechanism design are *** emergency data transmission mechanism is further proposed to reduce the latency of collecting the latency-sensitive data due to the absence of *** with the existing schemes,the proposed scheme can prolong the lifetime of the UAVassisted WSN at least by 360%,and shorten the collection path of UAVs by 56.24%.

关键词： Monte-Las search strategy triangle path optimization unmanned aerial vehicles wireless sensor networks

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Multi-scale feature fusion for facial expression recognition

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Neural Computing and Applications 2025年第17期37卷 11399-11420页

作者： Guo, Jiatao Peng, Junjie Huang, Yansong Chen, Gan Cai, Zesu Tan, Shuhua School of Computer Engineering and Science Shanghai University Shanghai China Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai China School of Computer Science and Technology Harbin Institute of Technology Harbin China National Engineering Laboratory for Logistics Information Technology YTO Express Co. Ltd. Shanghai China

As an important computer vision task that can be used in many areas, facial expression recognition (FER) has been widely studied which much progress has been obtained especially when deep learning (DL) approaches have been introduced in FER. However, existing methods are restricted to extracting localized information or utilizing attention mechanism to focus on the region most relevant to the emotion, possibly resulting in errors in facial expression interpretation. Moreover, the inconsistency of image sizes in the wild FER datasets further increases the difficulty of the FER task. To address these issues, we propose a multi-scale feature fusion (MSFF) for FER. Specifically, our method first extracts features from facial images using multi-scale feature extraction to obtain rich multi-dimensional information. Meanwhile, extensive feature extraction at different scales is achieved by expanding the receptive field of the model, which provides the basis for more detailed analysis of facial expressions. Eventually, features at different scales are fused to enhance their synergistic effect. Subsequently, the adaptive extraction of comprehensive and valuable information from the fused features is performed, optimizing the performance of expression recognition. Extensive experimental results demonstrate that the proposed method outperforms the state-of-the-art methods on in-the-wild datasets. It is promising for FER in realistic and complex scenarios. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Feature extraction

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Large-scale synoptic and weather drivers for the co-occurrence of fine particulate matter and ozone extremes over China

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science China Earth sciences 2025年第5期68卷 1448-1457页

作者： Wei WANG Yiting ZHOU Mengmeng LI Yuting LU Xinyi JIANG Tijian WANG Bingliang ZHUANG Shu LI Chenchao ZHAN Xiaoyun SUN Xin HUANG School of Atmospheric Sciences Nanjing University Nanjing-Helsinki Institute in Atmospheric and Earth System Sciences Nanjing University Frontiers Science Center for Critical Earth Material Cycling School of Atmospheric Physics Nanjing University of Information Science and Technology Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing Anhui Institute of Meteorological Sciences

The co-occurrence of extreme weather events and air pollution events, such as elevated fine particulate matter(PM2.5)and ozone（O3）, poses a significant threat to human health, a concern that is anticipated to be exacerbated under climate *** a 9-year dataset of surface air pollutant observations and reanalysis data, this study investigated the large-scale synoptic and weather drivers behind the co-occurrence of PM2.5and O3extremes in China. These co-occurrences are mostly observed during the warm season（March to October） and are particularly prevalent(25.8 days yr-1) in cleaner regions situated in South China. Such co-occurrences are usually associated with elevated air temperatures（～27.7°C）, lower wind speeds(～1.4 ms-1) and atmospheric humidity（～51.9%）. Notably, a substantial proportion of these co-occurrences（up to 76.4%） coincide with extreme weather linked to stagnant weather and extreme heat conditions. By employing an objective clustering approach, we identified the typical synoptic systems conducive to the widespread co-occurrence of PM2.5and O3extremes, including the Western Pacific Subtropical High, Northeast Blocking High, Mongolian High, and typhoons. These findings underscore a robust correlation between the co-occurrence of PM2.5and O3extremes and the annual variations in extreme weather and prevailing weather patterns, suggesting an increased likelihood of concurrent air pollution and extreme weather episodes under a warming climate across China.

关键词： Co-occurrence pollution Ozone PM2.5 Extreme weather T-PCA

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Probing the role of Fe and Sr co-doped BaZrO3 for enhanced cathode performance in protonic ceramics fuel cells

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International Journal of Hydrogen Energy 2025年 139卷 510-518页

作者： Yin, Yanru Xiao, Qi Zhang, Wenying Li, Kai Yan, Dong Li, Jian Jia, Lichao School of Materials Science and Engineering State Key Laboratory of Materials Processing and Die & Mould Technology Huazhong University of Science and Technology Wuhan430074 China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan430074 China School of Materials Science and Engineering Xi'an Shiyou University Xi'an710065 China

Cathode materials greatly govern the performance of protonic ceramics fuel cells (PCFCs), and development of suitable cathodes for PCFCs now becomes important. In this study, the traditional proton conductor BaZrO3 is tailored with Sr and Fe elements, aiming to design proper cathodes for PCFCs. The structural, electronic, and catalytic effects of dual-element doping on BaZrO3-based materials are systemically investigated. Experimental and computational analyses reveal that a 75 % iron doping concentration (BaZr0·25Fe0·75O3) markedly enhances oxygen vacancy concentration, reduces proton migration barriers, and elevates electrical conductivity. Notably, moderate strontium doping (50 %) synergistically improves performance, whereas excessive doping (75 %) induces adverse effects on oxygen vacancy concentration, proton migration, and electrical conductivity. The optimized Ba0·5Sr0·5Zr0·25Fe0·75O3 cathode achieves a peak power density of 945 mW cm-2 at 700 °C. These findings elucidate the interplay between dopant elements, doping concentrations, and material properties related to electrochemical performance, offering actionable strategies for designing high-performance PCFC cathodes. © 2025 Hydrogen Energy Publications LLC

关键词： Proton conductivity

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Isolated Bipolar Modular Multilevel DC-DC Converter with Self-balancing Capability for Interconnection of MVDC and LVDC Grids

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CSEE Journal of Power and Energy systems 2023年第1期9卷 365-379页

作者： Jinmu Lai Xin Yin Yaoqiang Wang Lin Jiang Zia Ullah Xianggen Yin School of Electrical and Information EngineeringZhengzhou UniversityZhengzhou 450001China Department of Electrical Engineering and ElectronicsUniversity of LiverpoolLiverpoolUK State Key Laboratory of Advanced Electromagnetic Engineering and TechnologyHuazhong University of Scienceand TechnologyWuhan 430074China

Bipolar medium-voltage DC(MVDC)and lowvoltage DC(LVDC)grids have the advantages of flexible integration of distributed renewable-energy generation and reliable power *** order to achieve voltage conversion,power transfer,and electrical isolation for bipolar MVDC and LVDC grids,a high-power DC-DC converter is ***,this paper proposes an isolated bipolar modular multilevel DCDC converter(BiMMDC)with power self-balancing capability for interconnection of MVDC and LVDC *** proposed BiMMDC consists of two series connected MMCs in the MV stage to configure a bipolar MVDC interface,and interleaved converters combined with a dual-transformer are designed in the LV stage to configure the bipolar LVDC interface and to provide a self-balancing *** circuits of two series-connected MMCs and a dual-transformer with interleaved converters are *** that,operation principles of the proposed BiMMDC are introduced,considering balanced/unbalanced power transfer of bipolar LVDC grid and monopolar shortcircuit or open-circuit faults at MVDC *** control scheme is also presented for the proposed BiMMDC under different operating ***,a Matlab simulation and controller hardware-in-the-loop(CHIL)evaluation results are provided to validate the feasibility and effectiveness of the proposed typology and its operating performance.

关键词： Bipolar DC-DC converter equivalent circuit modular monopolar operation multilevel self-balancing

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Additive Noise Model Structure Learning Based on Spatial Coordinates

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第8期5卷 3858-3871页

作者： Yang, Jing Lu, Ting Zhu, Youjie Hefei University of Technology Intelligent Interconnected Systems Laboratory of Anhui Province Hefei230009 China Hefei University of Technology School of Computer Science and Information Engineering Hefei230009 China

Discovering causal relationships from a large amount of observational data is an important research direction in data mining. To address the challenges of discovering and constructing causal networks on nonlinear and high-dimensional data, this article proposes a new structural learning algorithm called spatial coordinates based (SCB). The SCB algorithm effectively discovers causal networks from large scale nonlinear data. In this article, we make three main contributions. Firstly, based on the Hilbert-Schmidt independence criterion (HSIC), we propose new independence test coefficients: spatial coordinate (SC) coefficient and conditional spatial coordinate (CSC) coefficient. We also prove that the statistical distribution of the CSC coefficient follows a standard normal distribution. Secondly, using the statistical distribution of the CSC coefficient, we redefine the correlation of variables and combine it with local learning to propose the SCB algorithm. Finally, we demonstrate the effectiveness of the algorithm through experiments on data generated from various nonlinear function dependencies. Compared to existing algorithms, the causal network models constructed using the SCB algorithm exhibit significant improvements in accuracy and time performance. The effectiveness of the proposed method is further validated on real power plant data. © 2020 IEEE.

关键词： Additive noise

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Preventing 51% Attack by Using Consecutive Block Limits in Bitcoin

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IEEE Access 2024年 12卷 77852-77869页

作者： Mahmood Babur, Sohail Ur Rehman Khan, Shafiq Yang, Jing Chen, Yen-Lin Soon Ku, Chin Yee Por, Lip Government Murray College Department of Information Technology Sialkot51010 Pakistan Capital University of Science and Technology Department of Computer Science Islamabad44730 Pakistan Universiti Malaya Department of Computer System and Technology Kuala Lumpur50603 Malaysia National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106344 Taiwan Universiti Tunku Abdul Rahman Department of Computer Science Kampar31900 Malaysia

In permissionless blockchain systems, Proof of Work (PoW) is utilized to address the issues of double-spending and transaction starvation. When an attacker acquires more than 50% of the hash power of the entire network, they gain the ability to engage in double-spending activities, posing a significant threat to the PoW consensus algorithm. This research focuses on the consensus algorithm employed in the Bitcoin system, explaining how it operates and the security challenges it faces. The proposed modification to the PoW algorithm imposes a restriction on miners: they are not allowed to accept consecutive blocks from the same miner into the final local blockchain to prevent the 51% attack problem. This modification supports transactions that require six confirmations. In the event an attacker attempts a 51% attack with a private chain that consists of fewer than 6 blocks, it becomes easier to detect a double-spending attack before accepting the attacker's private chain. The modified algorithm introduces a 'Safe Mode Detection Algorithm' that scrutinizes incoming blocks for adjustments at the top of the local blockchain. If inconsistencies are identified, the consensus algorithm proceeds cautiously by comparing the UTXO dictionaries from the attacker's chain with those from the miner's own blockchain. This meticulous comparison aims to detect instances of double-spending. If such instances are detected, the miner rejects the attacker's chain, establishing a double-spend-free environment and thwarting 51% attacks. © 2013 IEEE.

关键词： Blockchain

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Self-assembled Fe_(3)O_(4)nanoparticles on V2C MXene for enhanced supercapacitor and microwave absorption applications

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Journal of Advanced Ceramics 2025年第3期14卷 183-196页

作者： Qixun Xia Ranlu Miao Wen Guo Min Xia Libo Wang Qianku Hu Aiguo Zhou School of Materials Science and Engineering Henan Polytechnic UniversityJiaozuo 454003China Henan Province Expressway Efficient Energy Storage Technology and Application Engineering Research Center Zhengzhou 450121China Department of Macromolecular Science Fudan UniversityShanghai 200438China Henan Radio Requlation Information System Backup Center Zhengzhou 450008China

Rapid advancements in modern electronic devices necessitate the development of materials that can simultaneously provide efficient energy storage and effective microwave ***,a novel composite material was prepared via the self-assembly of Fe_(3)O_(4)nanoparticles on the surface of V2C *** composite exhibited characteristics suitable for supercapacitor and electromagnetic absorption applications,highlighting the synergistic relationship between energy storage and electromagnetic wave absorption *** electrochemical tests revealed that the specific capacity of the V_(2)C MXene/Fe_(3)O_(4)composite(42.67 mAh·g^(−1))considerably improved compared with those of the raw *** prepared V2C MXene/Fe_(3)O_(4)//V_(2)C MXene/Fe_(3)O_(4)symmetric supercapacitor(SSC)demonstrated an energy density of 44.8 Wh·L^(−1),a power density of 959.4 W·L−1,and a capacity retention of 80.14%after 8000 ***,the V2C MXene/Fe_(3)O_(4)composite exhibited an optimal reflection loss(RL)of−42.4 dB in the Ku band,with an effective absorption bandwidth of 1.9 GHz(14.6–16.5 GHz).This composite material has broad application potential in modern electronic devices owing to its high energy storage capacity and effective electromagnetic wave *** dual functionality improves device performance and offers a compact solution for energy storage and effective microwave absorption.

关键词： MXenes Fe_(3)O_(4) two-dimensional(2D)materials supercapacitors microwave absorption

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Potassium ion pre‑intercalated MnO_(2)for aqueous multivalent ion batteries

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Frontiers of Optoelectronics 2023年第4期16卷 81-89页

作者： Zikang Xu Ruiqi Ren Hang Ren Jingyuan Zhang Jinyao Yang Jiawen Qiu Yizhou Zhang Guoyin Zhu Liang Huang Shengyang Dong School of Environmental Science and Engineering School of Chemistry and Materials ScienceNanjing University of Information Science and TechnologyNanjing 210044China Wuhan National Laboratory for Optoelectronics School of Optical and Electronic InformationHuazhong University of Science and TechnologyWuhan 430074China

Manganese dioxide(MnO_(2)),as a cathode material for multivalent ion(such as Mg^(2+)and Al^(3+))storage,is investigated due to its high initial ***,during multivalent ion insertion/extraction,the crystal structure of MnO_(2)partially collapses,leading to fast capacity decay in few charge/discharge ***,through pre-intercalating potassium-ion(K+)intoδ-MnO_(2),we synthesize a potassium ion pre-intercalated MnO_(2),K_(0.21)MnO_(2)·0.31H_(2)O(KMO),as a reliable cathode material for multivalent ion *** as-prepared KMO exhibits a high reversible capacity of 185 mAh/g at 1 A/g,with considerable rate performance and improved cycling stability in 1 mol/L MgSO_(4)*** addition,we observe that aluminum-ion(Al^(3+))can also insert into a KMO *** work provides a valid method for modifcation of manganesebased oxides for aqueous multivalent ion batteries.

关键词： Aqueous batteries Multivalent ion batteries Magnesium ion Aluminum ion MnO_(2)

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