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8th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2023

作者： Ma, Yuanyuan Zhi, Ruxin Xu, Zhan Ministry of Information Industry Beijing Information Science and Technology University Key Laboratory of Information and Communication Systems Beijing100101 China Ministry of Education Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Beijing100101 China

ISBN: (纸本)9798350317923

This paper centers around the examination of a downlink system comprising of a base station (BS) located at the center of a circular cell. Within this cell, we find cache-equipped users uniformly distributed. Our aim is to explore an innovative approach to enhance spectral efficiency by dividing the users into two groups, effectively utilizing the principles of nonorthogonal multiple access (NOMA) and coded caching. Introducing the NOMA over coded caching scheme, we propose a novel method to elevate the service rate. We derive closedform expressions to accurately quantify the performance of NOMA over coded caching in terms of the service rate. Simulation experiments are conducted to validate the superiority of our proposed algorithm. The results demonstrate the remarkable efficacy of the NOMA over coded caching schemes in significantly improving the service rate, surpassing the conventional coded caching and non-encoding caching schemes. © 2023 IEEE.

关键词： Spectrum efficiency

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Highly efficient ozone elimination by metal doped ultra-fine Cu_(2)O nanoparticles

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Journal of Environmental sciences 2023年第12期134卷 108-116页

作者： Anqi Wang Le Zhang Jian Guan Xiaoze Wang Guojun Ma Guijun Fan Hang Wang Ning Han Yunfa Chen State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Key Laboratory of Science&Technology on Particle Materials Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China School of Metallurgical Engineering Xi’an University of Architecture and TechnologyXi’an 710055China

Nowadays,ozone contamination becomes dominant in air and thus challenges the research and development of cost-effective *** this study,metal doped Cu_(2)O catalysts are synthesized via reduction of Cu^(2+)by ascorbic acid in base solutions containing doping metal *** results show that compared with pure Cu_(2)O,the Mg^(2+)and Fe^(2+)dopants enhance the O_(3)removal efficiency while Ni2+depresses the *** specific,Mg-Cu_(2)O shows high O3removal efficiency of 88.4%in harsh environment of 600,000 mL/(g·hr) space velocity and 1500 ppmV O_(3),which is one of the highest in the *** and electron paramagnetic spectroscopy characterization shows higher concentration of crystal defects induced by the Mg^(2+)dopants,favoring the *** in-situ diffuse reflectance Fourier transform infrared spectroscopy shows the intermediate species in the O_(3)degradation process change from O_(2)^(2-)dominant of pure Cu_(2)O to O_(2)^(-)dominant of Mg-Cu2O,which would contribute to the high *** these results show the promising prospect of the Mg-Cu_(2)O for highly efficiency O_(3)removal.

关键词： Ozone catalyst Cu_(2)O Dopant Ultra-fine nanoparticles

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The Methodology of Mask Detection Employing the YOLOv7 Framework 4

The Methodology of Mask Detection Employing the YOLOv7 Frame...

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4th International Conference on Neural Networks, information and Communication engineering, NNICE 2024

作者： Zhang, Fucheng Tian, Pinfang Wuhan University of Science and Technology School of Computer Science and Technology Wuhan China Hubei Key Laboratory of Intelligent Information Processing and Real-TimeIndustrial Systems Wuhan China

ISBN: (纸本)9798350394375

In the current field of object detection, the YOLOv7 model demonstrates significant advantages in terms of both detection speed and accuracy. However, the model shows deficiencies in focussing on key information, and its loss function's sensitivity to bounding boxes results in suboptimal performance in densely populated environments and small target detection scenarios. To address these issues, this study proposes a mask target detection method based on YOLOv7. By integrating a channel attention mechanism into the YOLOv7 model, this method enhances the model's focus on important information in images, effectively reducing interference from background factors. Additionally, the method incorporates Normalized Wasserstein Distance (NWD) into the loss function to optimize the model's evaluation of small target detection. Experimental verification shows that the improved model maintains its original detection speed while increasing the overall accuracy to 92.1%, a 2.9% improvement over the original YOLOv7 model. It achieves a 3.3% increase in the mAP.5 metric. This indicates that the optimised YOLOv7 model has superior detection capabilities, allowing it to perform mask-wearing detection tasks more rapidly and accurately in natural environments. © 2024 IEEE.

关键词： Object detection

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Underwater images enhancement using contrast limited adaptive parameter settings histogram equalization

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Multimedia Tools and Applications 2024年 1-15页

作者： Chen, Yahui Liang, Yitao College of Information Science and Engineering Henan University of Technology Henan Zhengzhou China Henan Key Laboratory of Grain Photoelectric Detection and Control Henan Zhengzhou China

CLAHE is widely used in underwater image processing because of its excellent performance in contrast enhancement. The selection of the clip point formula is the core problem of the CLAHE methods, and the selection of suitable clipping value has become the focus of some extended methods. In this paper, an automatic CLAHE underwater image enhancement algorithm is proposed. The method determines the clipping value according to the high-order moment dynamic features of each block of the underwater image. By quantifying the dynamic features of each block in the image more precisely, and then adding it to the clipping value formula, the contrast and details of the underwater image can be effectively enhanced. In order to effectively improve the saturation and brightness of underwater images, this paper chooses a more accurate and intuitive HSV model. Experimental results show that our methods enhance the contrast subjectively, while suppressing the amplification of noise very well, and also increase the saturation of underwater images. In objective metrics, our method obtains the best values in underwater quality assessment (UIQM), SSIM, and PSNR. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Underwater imaging

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Residual Tensor Train: A Quantum-Inspired Approach for Learning Multiple Multilinear Correlations

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第5期4卷 1101-1113页

作者： Chen, Yiwei Pan, Yu Dong, Daoyi Zhejiang University Institute of Cyber-Systems and Control College of Control Science and Engineering Hangzhou310027 China Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control College of Control Science and Engineering Hangzhou310027 China University of New South Wales School of Engineering and Information Technology CanberraACT2600 Australia

States of quantum many-body systems are defined in a high-dimensional Hilbert space, where rich and complex interactions among subsystems can be modeled. In machine learning, complex multiple multilinear correlations may also exist within input features. In this article, we present a quantum-inspired multilinear model, named residual tensor train (ResTT), to capture the multiple multilinear correlations of features, from low to high orders, within a single model. ResTT is able to build a robust decision boundary in a high-dimensional space for solving fitting and classification tasks. In particular, we prove that the fully connected layer and the Volterra series can be taken as special cases of ResTT. Furthermore, we derive the rule for weight initialization that stabilizes the training of ResTT based on a mean-field analysis. We prove that such a rule is much more relaxed than that of tensor train (TT), which means that ResTT can easily address the vanishing and exploding gradient problem that exists in the existing TT models. Numerical experiments demonstrate that ResTT outperforms the state-of-the-art tensor network and benchmark deep learning models on MNIST and Fashion-MNIST datasets. Moreover, ResTT achieves better performance than other statistical methods on two practical examples with limited data, which are known to have complex feature interactions. © 2020 IEEE.

关键词： Neural networks

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Convolutional Neural Networks Aided Reinforcement Learning for Accelerated Optimization of Antenna Topology

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Applied Computational Electromagnetics Society Journal 2025年第1期40卷 35-41页

作者： Dou, Jiangling Gong, Hao Wei, Shuaibing Chen, Haokang Chen, Yujie Shen, Tao Song, Jian Yunnan Key Laboratory of Computer Technologies Application Kunming University of Science and Technology Kunming650500 China School of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China College of Mechanical and Electrical Engineering Yunnan Electromechanical Vocational and Technical College Kunming650500 China

A machine learning (ML) framework is proposed to achieve the automatic and rapid optimization of antenna topologies. A convolutional neural network (CNN) is utilized as a surrogate model (SM) and is combined with reinforcement learning (RL) algorithms. Specifically, the RL agent interacts with simulation software to learn. Data accumulated from electromagnetic (EM) simulations are used to train the SM. The CNN-based SM predicts antenna performance based on the topology of the antenna. Subsequently, the SM replaces EM simulations within the RL training environment. The RL agent interacts with the CNN-based SM to search for the optimal topology. This approach significantly reduces dependence on time-consuming EM simulations. To validate the effectiveness of the optimization method, a center-fed microstrip patch antenna is optimized. Simulation results demonstrate that, compared to other optimization methods, impedance bandwidth is improved, while the number of simulation samples and optimization time are significantly reduced. © ACES.

关键词： Convolutional neural networks

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Interaction pathways of implant metal localized corrosion and macrophage inflammatory reactions

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Bioactive Materials 2024年第1期31卷 355-367页

作者： Meng Li Jing Wu Wenbo Geng Pengfei Gao Yulu Yang Xuan Li Kun Xu Qiang Liao Kaiyong Cai Key Laboratory of Biorheological Science and Technology Ministry of EducationCollege of BioengineeringChongqing UniversityChongqing400044PR China Key Laboratory of Low-grade Energy Utilization Technologies and Systems Chongqing UniversityMinistry of EducationSchool of Energy and Power EngineeringChongqing400044PR China

Macrophages play a central role in immunological responses to metallic species associated with the localized corrosion of metallic implants,and mediating in peri-implant ***,the pathways of localized corrosion-macrophage interactions were systematically investigated on 316L stainless steel(SS)implant *** monitoring under macrophage-mediated inflammatory conditions showed a decreased pitting corrosion resistance of 316L SSs in the presence of RAW264.7 cells as the cells would disrupt biomolecule adsorbed layer on the metal *** pitting potentials were furtherly decreased when the RAW264.7 cells were induced to the M1 pro-inflammatory phenotype by the addition of lipopolysaccharide(LPS),and pitting corrosion preferentially initiated at the peripheries of *** overproduction of aggressive ROS under inflammatory conditions would accelerate the localized corrosion of 316L SS around *** pitting corrosion condition,the viability and pro-inflammatory polarization of RAW264.7 cells were region-dependent,lower viability and more remarkable morphology transformation of macrophages in the pitting corrosion region than the pitting-free *** pitting corrosion of 316L SS induced high expression of CD86,TNF-α,IL-6 and high level of intracellular ROS in *** release of metallic species(Fe^(2+),Cr^(3+),Ni^(2+),etc)and uneven distribution of surface overpotential stimulated macrophage inflammatory responses near the corrosion pits.A synergetic effect of localized corrosion and macrophages was revealed,which could furtherly promote localized corrosion of 316L SS and macrophage inflammatory *** results provided direct evidence of corrosion-macrophage interaction in metallic implants and disclosed the pathways of this mutual stimulation effect.

关键词： Metallic implant Macrophage Localized corrosion Inflammatory reaction Material-cell interaction

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Electronic structure regulation of Fe-doped Ni2P nanocrystals towards durable electrocatalytic oxygen evolution

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Rare Metals 2024年第12期43卷 6405-6415页

作者： Ya Liu Xing Cao Jia-Jia Liu Mei-Sheng Han Gao-Wei Zhang Yu-Bin Zhao Huan-Hui Chen Liang Yu Jun-Rong Zeng Zhi-Kai Cheng Liu-Biao Zhong Li-Juan Song Ye-Jun Qiu Shenzhen Engineering Lab of Flexible Transparent Conductive Films School of Materials Science and EngineeringHarbin Institute of TechnologyShenzhen518055China School of Physics Harbin Institute of TechnologyHarbin150001China Department of Mechanical and Energy Engineering Southern University of Science and TechnologyShenzhen518055China School of Science Harbin Institute of TechnologyShenzhen 518055China Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic Systems Harbin Institute of TechnologyShenzhen518055China

The inherent electrocatalytic potential of transition metal phosphides(TMPs)for oxygen evolution is influenced by the reduced efficiency of electron transfer resulting from the interaction between electronegative phosphorus atoms and transition ***,we introduce Fe into Ni_(2)P nanocrystals by thermal injection synthesis method,and anchor them on nickel foam(NF)by facile spraying to prepare self-supporting oxygen evolution reaction(OER)***,the optimized electrode of Ni_(2)P-Fe-2/NF demonstrates low overpotentials of 212 mV with 10 mA·cm^(-2)and a 0.9%decay within300 h test of 50 mA·cm^(-2).Notably,when electrode size was expanded to 600 cm^(2)and applied to a larger electrolyzer,its 9 h decay rate at 6 A current was only 1.69%.Characterization results show that Fe doped NiOOH is generated during OER reaction as actual catalyst,Results from density functional theory(DFT)computations suggest that Fe doping shifts NiOOH d-band center to Fermi level,lowering critical *OOH intermediates formation energy barrier during the OER *** findings inform the large-scale industrial application of TMPs as robust electrocatalysts.

关键词： Electronic structure regulation Fe doping Colloidal nanocrystals Ni2P Oxygen evolution reaction

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An efficient memory data organization strategy for application-characteristic graph processing

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Frontiers of Computer science 2022年第1期16卷 191-193页

作者： Peng FANG Fang WANG Zhan SHI Dan FENG Qianxu YI Xianghao XU Yongxuan ZHANG Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage SystemEngineering Research Center of data storage systems and TechnologyMinistry of Education of ChinaSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan430074China

1 Introduction Graph processing has received significant attention for its ability to cope with large-scale and complex unstructured data in the ***,most of the graph processing applications exhibit an irregular memor... 详细信息

关键词： application processing pattern

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Simultaneous synthesis of heat-integrated water networks by a nonlinear program:Considering the wastewater regeneration reuse

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Chinese Journal of Chemical engineering 2022年第4期35卷 402-411页

作者： Fangyou Yan Wei Li Jinli Zhang School of Chemical Engineering and Material Science Tianjin University of Science and TechnologyTianjin 300457China Key Laboratory for Green Chemical Technology MOE School of Chemical Engineering and TechnologyTianjin UniversityTianjin 300072China Key Laboratory of Systems Bioengineering MOE School of Chemical Engineering and TechnologyTianjin UniversityTianjin 300072China

Heat-integrated water network synthesis(HIWNS)has received considerable attention for the advantages of reducing water and energy *** is effective in water and energy *** integer non-linear programming(MINLP)is usually applied in *** this work,a novel nonlinear programming(NLP)was proposed for HIWNS by considering wastewater reuse and wastewater regeneration *** variables are changed to non-linear equation by the methods for identifying stream roles and denoting the existence of process *** model is tested by examples with single and multiple regeneration unit *** testing results showed that the NLP is an alternative method for HIWNS with wastewater reuse and regeneration reuse.

关键词： None-linear programming Heat-integrated water network synthesis Wastewater regeneration reuse

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