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Target Detection-Oriented RGCN Inference Enhancement Method

computers, Materials & Continua 2025年第4期83卷 1219-1237页

作者： Lijuan Zhang Xiaoyu Wang Songtao Zhang Yutong Jiang Dongming Li Weichen Sun School of Internet of Things Engineering Wuxi UniversityWuxi214105China College of Computer Science and Engineering Changchun University of TechnologyChangchun130012China Computer Science and Technology at Guohao Academy Tongji UniversityShanghai200092China China North Vehicle Research Institute Beijing100072China

In this paper,a reasoning enhancement method based on RGCN(Relational Graph Convolutional Network)is proposed to improve the detection capability of UAV(Unmanned Aerial Vehicle)on fast-moving military targets in urban battlefield *** combining military images with the publicly available VisDrone2019 dataset,a new dataset called VisMilitary was built and multiple YOLO(You Only Look Once)models were tested on *** to the low confidence problem caused by fuzzy targets,the performance of traditional YOLO models on real battlefield images decreases ***,we propose an improved RGCN inference model,which improves the performance of the model in complex environments by optimizing the data processing and graph network *** results show that the proposed method achieves an improvement of 0.4%to 1.7%on mAP@0.50,which proves the effectiveness of the model in military target *** research of this paper provides a new technical path for UAV target detection in urban battlefield,and provides important enlightenment for the application of deep learning in military field.

关键词： RGCN target detection urban battlefield YOLO visual reasoning

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Scheduling a Single-Arm Multi-Cluster Tool With a Condition-Based Cleaning Operation

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IEEE/CAA Journal of Automatica Sinica 2023年第10期10卷 1965-1983页

作者： Qinghua Zhu Hongpeng Li Cong Wang Yan Hou School of Computer Science and Technology Guangdong University of TechnologyGuangzhou 510006China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102-1982 USA

As wafer circuit widths shrink less than 10 nm,stringent quality control is imposed on the wafer fabrication processes. Therefore, wafer residency time constraints and chamber cleaning operations are widely required in chemical vapor deposition, coating processes, etc. They increase scheduling complexity in cluster tools. In this paper, we focus on scheduling single-arm multi-cluster tools with chamber cleaning operations subject to wafer residency time constraints. When a chamber is being cleaned, it can be viewed as processing a virtual wafer. In this way, chamber cleaning operations can be performed while wafer residency time constraints for real wafers are not violated. Based on such a method, we present the necessary and sufficient conditions to analytically check whether a single-arm multi-cluster tool can be scheduled with a chamber cleaning operation and wafer residency time constraints. An algorithm is proposed to adjust the cycle time for a cleaning operation that lasts a long cleaning ***, algorithms for a feasible schedule are also *** an algorithm is presented for operating a multi-cluster tool back to a steady state after the cleaning. Illustrative examples are given to show the application and effectiveness of the proposed method.

关键词： Chamber cleaning multi-cluster tools scheduling semiconductor manufacturing

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Atomic Manganese Manipulating Polysulfide Speciation Pathway for Room-Temperature Na-S Batteries

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CCS Chemistry 2024年第9期6卷 2289-2304页

作者： Hong Zhang Mingli Wang Xiang-Long Huang Songtao Lu Ke Lu Xiaohong Wu School of Chemistry and Chemical Engineering Harbin Institute of TechnologyHarbinHeilongjiang 150001 Institutes of Physical Science and Information Technology Anhui UniversityHefeiAnhui 230601 Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengdu 610054

Sluggish polysulfide redox kinetics,especially the high energy barrier of rate-determining short-chain polysulfide conversion and the high activation barrier of Na_(2)S decomposition during sulfur recovery,compromise the full potential of rechargeable Na-S *** we construct the hierarchical sandwich-structured carbon matrix with atomically dispersed Mn-N4 Lewis acidic sites,taking advantage of their bidirectional electrocatalytic behavior toward interface-mediated reversible sulfur *** and theoretical results reveal that the spatial confinement and catalytic effects facilitated via strong Lewis acid-base electron interactions synergistically manipulate the low kinetically direct Na_(2)S_(4) to Na_(2)S conversion,and the formation of Mn-S bond minimizes the energy barrier of Na_(2)S electrochemical activation during battery recharging,thereby rendering a reversible and tunable polysulfide speciation ***,the degradation of the Na-S cell is due to the depletion of metal anode rather than the loss of active sulfur species and/or aggregation of inactive dead *** expected,the S@Mn/NC cathode delivers outstanding rate capability and ultrahigh cycling ***,a proof-of-concept pouch cell was also demonstrated capable of delivering an energy density up to 840 Wh kgcathode−*** tunable sulfur redox electrochemistry invoked by the bidirectional monodispersed Mn catalytic hot spots facilitates the efficient polysulfide speciation for practical Na-S cells.

关键词： single-atom manganese catalysts polysulfide manipulation reaction kinetics bidirectional catalysts sodium-sulfur batteries

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Predicting superconducting temperatures with new hierarchical neural network AI model

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Frontiers of physics 2025年第1期20卷 165-172页

作者： Shaomeng Xu Pu Chen Mingyang Qin Kui Jin X.-D.Xiang School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China Department of Materials Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Beijing National Laboratory for Condensed Matter Physics Institute of PhysicsChinese Academy of SciencesBeijing 100190China

Superconducting critical temperature is the most attractive material property due to its impact on the applications of electricity transmission,railway transportation,strong magnetic fields for nuclear fusion and medical imaging,quantum computing,*** ability to predict its value is a constant pursuit for condensed matter *** developed a new hierarchical neural network(HNN)AI algorithm to resolve the contradiction between the large number of descriptors and the small number of datasets always faced by neural network AI approaches to materials *** this new HNN-based AI model,a much-increased number of 909 universal descriptors for inorganic compounds,and a dramatically cleaned database for conventional superconductors,we achieved high prediction accuracy with a test R^(2)score of 95.6%.The newly developed HNN model accurately predicted T_(c)of 45 new high-entropy alloy superconductors with a mean absolute percent error below 6%compared to the experimental *** demonstrated a significant potential for predicting other properties of inorganic materials.

关键词： conventional superconducting critical temperature hierarchical neural network universal descriptors artificial intelligence

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Leveraging Network Slicing in SDNs for Handling Application Failures

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2024年第4期51卷 409-421页

作者： Lokesh, Bommareddy Rajagopalan, Narendran School of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravati522237 India Department of Computer Science and Engineering National Institute of Technology Puducherry Karaikal609609 India

Unlike traditional networks, Software-defined networks (SDNs) provide an overall view and centralized control of all the devices in the network. SDNs enable the network administrator to implement the network policy by programming applications on top of the SDN controller using generic APIs. One or more controller instances can be deployed to administer the data flow by maintaining unified control of the entire network. The controller is expected to respond quickly to queries from forwarding devices. Presuming quick responses from the controller while enforcing a complex security mechanism is unreasonable. In this paper, the authors propose a unique, adaptive, lightweight, yet efficient technique called ISOLATOR to mitigate the effect of insider attacks and malfunctioning of distributed applications in an SDN-enabled cloud. The proposed security application upon detecting any suspicious activity by a virtual machine, isolates it by removing the interface to its respective shared network and reconnects it through a restricted network operating in a highly selective mode. By subjecting the data traffic to deep packet inspection, the restricted network searches for a match with a known worm pattern. The application is programmed for the OpenDayLight controller and the results show a significant improvement in identifying malicious activities with minimal latency and computational cost. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Controllers

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Solar-driven photothermal catalytic CO_(2) conversion:a review

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Rare Metals 2024年第7期43卷 2913-2939页

作者： Bachirou Guene Lougou Bo-Xi Geng Ru-Ming Pan Wei Wang Tian-Tian Yan Fang-Hua Li Hao Zhang Oraléou SanguéDjandja Yong Shuai Meisam Tabatabaei Daniel Sabi Takou School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China MIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage Harbin Institute of TechnologyHarbin 150001China State Key Laboratory of Urban Water Resource and Environment Harbin Institute of TechnologyHarbin 150090China School of Electrical Engineering and Automation Harbin Institute of TechnologyHarbin 150001China Guangdong Provincial Key Laboratory of Distributed Energy Systems Engineering Research Center of None-Food Biomass Efficient Pyrolysis and Utilization Technology of Guangdong Higher Education InstitutesDongguan University of TechnologyDongguan 523808China Higher Institution Centre of Excellence(HICoE) Institute of Tropical Aquaculture and Fisheries(AKUATROP)Universiti Malaysia Terengganu21030 Kuala NerusMalaysia Department of Biomaterials Saveetha Dental CollegeSaveetha Institute of Medical and Technical SciencesChennai600077India école Polytechnique d'Abomey-Calavi University of Abomey-Calavi2009CotonouBenin

It is highly desirable to seek green and sustainable technologies,such as employing photo thermal effects to drive energy catalysis processes to address the high energy demand and associated environmental impacts induced by the current *** photothermocatalysis process is an emerging research area with great potential in efficiently converting solar energy through various catalytic ***,achieving simultaneously high conversion efficiency,cyclability,and durability is still a daunting ***,tremendous work is still needed to enhance solar photo thermal catalytic conversion and promote its large-scale *** review developed the principles of coupling solar photon and thermal fields underlying the photothermal effect,exploration of efficient nanocatalysts,development of optofluidic reactor model,and photo thermal synergistic-driven CO_(2) reduction *** ultimate goal was to provide an effective approach that can effectively convert solar energy into photocarriers/hot-electrons and heat,and importantly,can couple them to regulate catalysis reaction pathways toward the production of value-added fuel and chemical energy.

关键词： Photochemistry Photothermal CO_(2)catalytic conversion Nanomaterial Solar fuels and chemicals

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Exploring diversity and time-aware recommendations: an LSTM-DNN model with novel bidirectional dynamic time warping algorithm

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Soft Computing 2025年第4期29卷 2003-2013页

作者： Li, Te Chen, Liqiong Sun, Huaiying Hou, Mengxia Lei, Yunjie Zhi, Kaiwen School of Computer and Engineering East China University of Science and Technology Meilong road Shanghai200237 China School of Computer Science and Information Engineering Shanghai Institute of Technology Haiquan road Shanghai201400 China School of Chemistry and Environmental Engineering Shanghai Institute of Technology Haiquan road Shanghai201400 China

With the advent of the Web 3.0 era, the amount and types of data in the network have sharply increased, and the application scenarios of recommendation algorithms are continuously expanding. Location recommendation has gradually become one of the popular application scenarios in recommendation algorithms. Traditional recommendation algorithms not only ignore the temporal attribute of data when recommending information to users, but also blindly pursue the recommendation accuracy, which will cause certain "information cocoon room" problems. Therefore, this article treats user historical data as a time series and proposes an LSTM-DNN model based on the novel bidirectional Dynamic Time Warping (DTW) algorithm. Firstly, in response to the issue of different users consuming different amounts of information, this article proposes a novel bidirectional DTW algorithm to calculate the similarity between different users. Secondly, this article supplements the user dataset from three perspectives: "utilization" and "exploration" of information, and spatiotemporal attributes of data, which alleviates the problem of data sparsity and cold start in the dataset to a certain extent. Moreover, it effectively enhances the diversity of recommendation results. Finally, this paper constructs an Long Short-Term Memory-Deep Neural Networks (LSTM-DNN) to dynamically obtain user interests and preferences, and proposes a new metric Cumulative Self-System Diversity (CSSD) to measure the diversity of algorithm recommendation results. Experiments have shown that the model effectively enhances the diversity of recommendation results while ensuring recommendation accuracy. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Time series

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Analysis of Software Trustworthiness Based on FAHP-CRITIC Method

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Journal of Shanghai Jiaotong university(science) 2024年第3期29卷 588-600页

作者：高晓彤马艳芳周伟 School of Computer Science and Technology Huaibei Normal UniversityHuaibei 235000AnhuiChina School of Computer Science and Information Engineering Changzhou Institute of TechnologyChangzhou 213000JiangsuChina

Software trustworthiness includes many *** weight allocation of trustworthy at-tributes plays a key role in the software trustworthiness *** practical application,attribute weight usually comes from experts'evaluation to attributes and hidden information derived from ***,when the weight of attributes is researched,it is necessary to consider weight from subjective and objective ***,a novel weight allocation method is proposed by combining the fuzzy analytical hierarchy process(FAHP)method and the criteria importance though intercrieria correlation(CRITIC)***,based on the weight allocation method,the trustworthiness measurement models of component-based software are estab-lished according to the seven combination structures of ***,the model reasonability is verified via proving some metric ***,a case is carried *** to the comparison with other models,the result shows that the model has the advantage of utilizing hidden information fully and analyzing the com-bination of components *** is an important guide for measuring the trustworthiness measurement of component-based software.

关键词： trustworthiness weight component-based software measurement

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Wide field of view large aperture meta-doublet eyepiece

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Light(science & Applications) 2025年第1期14卷 167-176页

作者： Anna Wirth-Singh Johannes E.Fröch Fan Yang Louis Martin Hanyu Zheng Hualiang Zhang Quentin T.Tanguy Zhihao Zhou Luocheng Huang Demis DJohn Biljana Stamenic Juejun Hu Tian Gu Arka Majumdar Department of Physics University of WashingtonSeattleWAUSA Department of Electrical and Computer Engineering University of WashingtonSeattleWAUSA Department of Materials Science and Engineering Massachusetts Institute of TechnologyCambridgeMAUSA Department of Electrical and Computer Engineering University of MassachusettsLowellMAUSA Department of Electrical and Computer Engineering University of CaliforniaSanta BarbaraCAUSA

Wide field of view and light weight optics are critical for advanced eyewear,with applications in augmented/virtual reality and night *** refractive lenses are often stacked to correct aberrations at a wide field of view,leading to limited performance and increased size and *** particular,simultaneously achieving a wide field of view and large aperture for light collection is desirable but challenging to realize in a compact ***,we demonstrate a wide field of view(greater than 60°)meta-optic doublet eyepiece with an entrance aperture of 2.1 *** the design wavelength of 633 nm,the meta-optic doublet achieves comparable performance to a refractive lens-based eyepiece *** meta-doublet eyepiece illustrates the potential for meta-optics to play an important role in the development of high-quality monochrome near-eye displays and night vision systems.

关键词： optics refractive illustrate

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BaMBNet:A Blur-Aware Multi-Branch Network for Dual-Pixel Defocus Deblurring

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 878-892页

作者： Pengwei Liang Junjun Jiang Xianming Liu Jiayi Ma School of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001China Electronic Information School Wuhan UniversityWuhan 430072China IEEE

Reducing the defocus blur that arises from the finite aperture size and short exposure time is an essential problem in computational *** is very challenging because the blur kernel is spatially varying and difficult to estimate by traditional *** to its great breakthrough in low-level tasks,convolutional neural networks(CNNs)have been introdu-ced to the defocus deblurring problem and achieved significant ***,previous methods apply the same learned kernel for different regions of the defocus blurred images,thus it is difficult to handle nonuniform blurred *** this end,this study designs a novel blur-aware multi-branch network(Ba-MBNet),in which different regions are treated *** particular,we estimate the blur amounts of different regions by the internal geometric constraint of the dual-pixel(DP)data,which measures the defocus disparity between the left and right *** on the assumption that different image regions with different blur amounts have different deblurring difficulties,we leverage different networks with different capacities to treat different image ***,we introduce a meta-learning defocus mask generation algorithm to assign each pixel to a proper *** this way,we can expect to maintain the information of the clear regions well while recovering the missing details of the blurred *** quantitative and qualitative experiments demonstrate that our BaMBNet outperforms the state-of-the-art(SOTA)*** the dual-pixel defocus deblurring(DPD)-blur dataset,the proposed BaMBNet achieves 1.20 dB gain over the previous SOTA method in term of peak signal-to-noise ratio(PSNR)and reduces learnable parameters by 85%.The details of the code and dataset are available at https://***/junjun-jiang/BaMBNet.

关键词： Blur kernel convolutional neural networks(CNNs) defocus deblurring dual-pixel(DP)data meta-learning

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