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Recent advances in heterogeneous catalysis of solar-driven carbon dioxide conversion

Journal of Environmental sciences 2024年第6期140卷 165-182页

作者： Jun Xu Farzaneh Arabpour Roghabadi Ying Luo Vahid Ahmadi Qian Wang Zheng Wang Hong He State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China College of Chemistry and Chemical Engineering Henan Polytechnic UniversityJiaozuoHenan 454000China Department of Process Engineering Faculty of Chemical EngineeringTarbiat Modares UniversityTehranIran Optoelectronics and Nanophotonics Research Group Faculty of Electrical and Computer EngineeringTarbiat Modares UniversityTehranIran Graduate School of Engineering Nagoya UniversityFuro-choChikusa-kuNagoya 464-8603Japan

Solar-driven carbon dioxide(CO_(2))conversion including photocatalytic(PC),photoelectrochemical(PEC),photovoltaic plus electrochemical(PV/EC)systems,offers a renewable and scalable way to produce fuels and high-value chemicals for environment and energy *** review summarizes the basic fundament and the recent advances in the field of solar-driven CO_(2)*** the visible-light absorption is an important strategy to improve solar energy conversion *** separation and migration of photogenerated charges carriers to surface sites and the surface catalytic processes also determine the photocatalytic *** engineering including co-catalyst loading,defect engineering,morphology control,surface modification,surface phase junction,and Z-scheme photocatalytic system construction,have become fundamental strategies to obtain high-efficiency *** to photocatalysis,these strategies have been applied to improve the conversion efficiency and Faradaic efficiency of typical PEC *** PV/EC systems,the electrode surface structure and morphology,electrolyte effects,and mass transport conditions affect the activity and selectivity of electrochemical CO_(2)***,the challenges and prospects are addressed for the development of solar-driven CO_(2)conversion system with high energy conversion efficiency,high product selectivity and stability.

关键词： Solar-driven CO_(2)reduction Photocatalytic system Photoelectrochemical system Photovoltaic plus electrochemical system Surface/interface engineering

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Belief Propagation List Decoding for Polar Codes:Performance Analysis and Software Implementation on GPU

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China Communications 2023年第9期20卷 115-126页

作者： Zhanxian Liu Wei Li Lei Sun Wei Li Jianquan Wang Haijun Zhang School of Computer&Communication Engineering University of Science and Technology BeijingBeijing 100083China Satellite Frequency and Orbit Resource Agency State Radio Monitoring CenterBeijing 100041China School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services Institute of Artificial IntelligenceUniversity of Science and Technology BeijingBeijing 100083China

Belief propagation(BP)decoding outputs soft information and can be naturally used in iterative *** list(BPL)decoding provides comparable error-correction performance to the successive cancellation list(SCL)*** this paper,we firstly introduce an enhanced code construction scheme for BPL decoding to improve its errorcorrection ***,a GPU-based BPL decoder with adoption of the new code construction is ***,the proposed BPL decoder is tested on NVIDIA RTX3070 and *** results show that the presented BPL decoder with early termination criterion achieves above 1 Gbps throughput on RTX3070 for the code(1024,512)with 32 lists under good channel conditions.

关键词： polar code belief propagation SIMT list decoding GPU

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A Rapid Finger Vein Recognition Approach Based on UNet++ 1

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39th CCF National Conference on computer Applications, CCF NCCA 2024

作者： Liu, Peng Jia, Yujiao Cao, Xiaofan Wang, Changjie Fan, Shanshan Institute of Energy and Electrical Engineering Changchun University of Science and Technology Changchun China School of Control and Computer Engineering North China Electric Power University Beijing China Yangzhong Intelligent Electric Research Center North China Electric Power University Beijing China

ISBN: (数字)9789819796748

ISBN: (纸本)9789819796731

With the advancement of biometric technologies, finger vein recognition has garnered widespread attention within the academic community. This paper proposes a method based on the UNet++ model, wherein parameter adjustments are made to the UNet++ architecture to ensure precise pixelwise segmentation of finger vein images. Following the parameter optimization, model compression is applied through structural reparameterization to further increase the recognition speed of the trained model. The approach achieves recognition accuracies of 93.1% on two publicly available finger vein datasets, and it features a feature extraction time of 0.0131 s for a single finger vein image. The recognition time for a single fingerprint vein image is 0.0294 s. The results indicate that the use of the UNet++ model as a framework for finger vein feature extraction and subsequent model compression render it suitable for finger vein recognition tasks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Image segmentation

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research on the autonomous system of the quadruped robot with a manipulator to realize leader-following,object recognition,navigation and operation

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IET Cyber-Systems and Robotics 2022年第4期4卷 376-388页

作者： Jiamin Guo Hui Chai Yibin Li Qin Zhang Zhiying Wang Jialin Zhang Qifan Zhang Haoning Zhao School of Control Science and Engineering Shandong UniversityJinanChina Engineering Research Center of Intelligent Unmanned System Ministry of EducationShandong UniversityJinanChina School of Electrical Engineering University of JinanJinanChina

A systematic solution is developed to improve the autonomous capability of the quadruped robot with a manipulator,such as navigation,recognition and *** developed system adopts novel software,hardware system and system architecture,including a specially designed environment awareness system(EAS).Based on the camera and LiDAR on the EAS,the recognition of multiple common targets,such as the leader,door,window and bag,is *** terms of navigation,a location method is built,that combines the laser odometer and global positioning system.A mapping and path planning module is designed by the Robot-centric Elevation Mapping algorithm and the rapidly exploring rand tree *** operation,a real-time target grasp detection system is proposed based on the You Only Look Once v5 algorithm to improve the success rate of *** whole system is integrated based on the task relevance scheduling strategy to reduce the computational *** tightly integrated system and the subsystems are evaluated by conducting simulations and physical experiments in robot recognition,navigation and *** experiments show that the proposed framework can better achieve the autonomous navigation and operation of the quadruped robot with a ***,the proposed framework is still effective when facing dynamic *** addition,the system can be easily extended to other forms of mobile robot.

关键词： environment awareness system leader-following navigation quadruped robot

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control Flow Divergence Optimization by Exploiting Tensor Cores 24

Control Flow Divergence Optimization by Exploiting Tensor Co...

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61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Pang, Weiguang Jiang, Xu Liu, Songran Qiao, Lei Fu, Kexue Gao, Longxiang Yi, Wang University of Electronic Science and Technology of China China Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China School of Computer Science and Engineering Northeastern University China Beijing Institute of Control Engineering Beijing China Uppsala University Sweden

ISBN: (纸本)9798400706011

Kernels are scheduled on Graphics Processing Units (GPUs) in the granularity of GPU warp, which is a bunch of threads that must be scheduled together. When executing kernels with conditional branches, the threads within a warp may execute different branches sequentially, resulting in a considerable utilization loss and unpredictable execution time. This problem is known as the control flow divergence. In this work, we propose a novel method to predict threads' execution path before the launch of the kernel by deploying a branch prediction network on the GPU's tensor cores, which can efficiently parallel run with the kernels on CUDA cores, so that the divergence problem can be eased in a large extent with the lowest overhead. Combined with a well-designed thread data reorganization algorithm, this solution can better mitigate GPUs' control flow divergence problem. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Tensors

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Biological Influence of Low-Frequency Electromagnetic Field Exposition Based on Selected Cell Death Markers 15

Biological Influence of Low-Frequency Electromagnetic Field ...

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15th International Conference Elektro, ELEKTRO 2024

作者： Cichorowski, Robert Kocikowska, Olga Bajtos, Marek Radil, Roman Janousek, Ladislav De Carrillo, Daria Gendosz Student, Sebastian Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Gliwice Poland Faculty of Automatic Control Electronics and Computer Science Department of Engineering and Systems Biology Gliwice Poland Silesian University of Medicine Faculty of Medical Sciences Department of Physiology Katowice Poland Faculty of Electrical Engineering and Informational Technology Department of Electromagnetic and Biomedical Engineering Žilina Slovakia Silesian University of Medicine Faculty of Medical Sciences in Zabrze Department of Histology Zabrze Poland Silesian University of Technology Biotechnology Center Gliwice Poland

ISBN: (纸本)9798350372359

This work presents the results of the examination of the HeLa cell line exposure on the ELF-EMF (extremely low-frequency electromagnetic field). In particular, the relationship between ELF-EMF exposition time and cell death. The examination of cell death hallmarks were examined by estimation levels of selected proteins - FACL4 (a protein that is a part of the ferroptosis pathway) and CK18 (Cytokeratin related to necrosis and apoptosis pathways) in the proposed model of workers exposed to ELF-EMF week. © 2024 IEEE.

关键词： Electromagnetic fields

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A Dual-Core Dual-Mode Class-F VCO With Wide Frequency Tuning Range Using Wide Inductance-Switching-Range Inductor

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IEEE Microwave and Wireless Technology Letters 2025年第4期35卷 460-463页

作者： Hou, Yaru Li, Runlong Chi, Pei-Ling Yang, Tao University of electronic Science and Technology of China Chengdu610036 China Sichuan Province Engineering Research Center for Broadband Microwave Circuit High Density Integration Chengdu610036 China University of Electronic Science and Technology of China School of Electronic Science and Engineering Sichuan Chengdu610054 China National Yang Ming Chiao Tung University Department of Electrical and Computer Engineering Hsinchu300 Taiwan

A novel dual-core dual-mode class-F voltage-controlled oscillator (VCO) with wide frequency tuning range (TR) is proposed in this letter. It consists of two coupled parallel "8"-shaped inductor and two crossed-coupled VCO cores. To increase the TR of the proposed VCO without adding additional footprint size, a single-turn common-mode inductor is embedded inside the "8"-shaped inductor. By controlling the mode switches, the inductor can work in different modes with large inductance difference, realizing large VCO TR consequently. Then, the two coupled inductors were engineered to form the fundamental and third harmonic resonances, respectively, thereby producing a pseudo-square wave output waveform and realizing class-F operation. With the proposed configuration, the phase noise (PN) of the proposed VCO can be significantly reduced without increasing VCO core size. To demonstrate the proposed idea, a VCO prototype is fabricated in a 65-nm CMOS process with a core size of 1.235×0.8mm. It achieves a wide frequency TR from 2.84 to 7.04 GHz. The measured PN at 1-MHz offset is from -123.9 to -113.1 dBc/Hz, demonstrating an FOMT of 196.0-201.3 dBc/Hz. © 2023 IEEE.

关键词： Variable frequency oscillators

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Human action recognition in immersive virtual reality based on multi-scale spatio-temporal attention network

Human action recognition in immersive virtual reality based ...

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作者： Xiao, Zhiyong Chen, Yukun Zhou, Xinlei He, Mingwei Liu, Li Yu, Feng Jiang, Minghua School of Computer Science and Artificial Intelligence Wuhan Textile University Wuhan China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Engineering Research Center of Hubei Province for Clothing Information Wuhan China

Wearable human action recognition (HAR) has practical applications in daily life. However, traditional HAR methods solely focus on identifying user movements, lacking interactivity and user engagement. This paper proposes a novel immersive HAR method called MovPosVR. Virtual reality (VR) technology is employed to create realistic scenes and enhance the user experience. To improve the accuracy of user action recognition in immersive HAR, a multi-scale spatio-temporal attention network (MSSTANet) is proposed. The network combines the convolutional residual squeeze and excitation (CRSE) module with the multi-branch convolution and long short-term memory (MCLSTM) module to extract spatio-temporal features and automatically select relevant features from action signals. Additionally, a multi-head attention with shared linear mechanism (MHASLM) module is designed to facilitate information interaction, further enhancing feature extraction and improving accuracy. The MSSTANet network achieves superior performance, with accuracy rates of 99.33% and 98.83% on the publicly available WISDM and PAMPA2 datasets, respectively, surpassing state-of-the-art networks. Our method showcases the potential to display user actions and position information in a virtual world, enriching user experiences and interactions across diverse application scenarios. © 2024 John Wiley & Sons Ltd.

关键词： human activity recognition multi-scale feature spatio-temporal feature virtual reality

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A High Resolution Convolutional Neural Network with Squeeze and Excitation Module for automatic Modulation Classification

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China Communications 2024年第10期21卷 132-147页

作者： Duan Ruifeng Zhao Yuanlin Zhang Haiyan Li Xinze Cheng Peng Li Yonghui School of Information Science and Technology Bejing Forestry UniversityBeijing 100083China Engineering Research Center for Forestry-Oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing 100083China Department of Computer Science and Information Technology La Trobe UniversityMelbourneVIC 3086Australia School of Electrical and Information Engineering the University of SydneySydneyNSW 2006Australia

automatic modulation classification(AMC) technology is one of the cutting-edge technologies in cognitive radio communications. AMC based on deep learning has recently attracted much attention due to its superior performances in classification accuracy and robustness. In this paper, we propose a novel, high resolution and multi-scale feature fusion convolutional neural network model with a squeeze-excitation block, referred to as HRSENet,to classify different kinds of modulation *** proposed model establishes a parallel computing mechanism of multi-resolution feature maps through the multi-layer convolution operation, which effectively reduces the information loss caused by downsampling convolution. Moreover, through dense skipconnecting at the same resolution and up-sampling or down-sampling connection at different resolutions, the low resolution representation of the deep feature maps and the high resolution representation of the shallow feature maps are simultaneously extracted and fully integrated, which is benificial to mine signal multilevel features. Finally, the feature squeeze and excitation module embedded in the decoder is used to adjust the response weights between channels, further improving classification accuracy of proposed *** proposed HRSENet significantly outperforms existing methods in terms of classification accuracy on the public dataset “Over the Air” in signal-to-noise(SNR) ranging from-2dB to 20dB. The classification accuracy in the proposed model achieves 85.36% and97.30% at 4dB and 10dB, respectively, with the improvement by 9.71% and 5.82% compared to ***, the model also has a moderate computation complexity compared with several state-of-the-art methods.

关键词： automatic modulation classification deep learning feature squeeze-and-excitation high-resolution multi-scale

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HDCGD-CBAM:Satellite Interference Recognition Algorithm Based on Improved CLDNN and CBAM

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China Communications 2024年第12期21卷 257-274页

作者： Duan Ruifeng Chen Ziyu Meng Wei Wang Xu Yang Guoting Cheng Peng Li Yonghui School of Information Science and Technology Beijing Forestry UniversityBeijing 100083China Engineering Research Center for Forestry-Oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing 100083China Jining Economic and Social Development Research Center Jining 272000China School of Electrical and Information Engineering the University of SydneySydneyNSW 2006Australia Department of Computer Science and Information Technology La Trobe UniversityMelbourneVIC 3086Australia

Satellite communication systems are facing serious electromagnetic interference,and interference signal recognition is a crucial foundation for targeted *** this paper,we propose a novel interference recognition algorithm called HDCGD-CBAM,which adopts the time-frequency images(TFIs)of signals to effectively extract the temporal and spectral *** the proposed method,we improve the Convolutional Long Short-Term Memory Deep Neural Network(CLDNN)in two ***,the simpler Gate Recurrent Unit(GRU)is used instead of the Long Short-Term Memory(LSTM),reducing model parameters while maintaining the recognition ***,we replace convolutional layers with hybrid dilated convolution(HDC)to expand the receptive field of feature maps,which captures the correlation of time-frequency data on a larger spatial ***,Convolutional Block Attention Module(CBAM)is introduced before and after the HDC layers to strengthen the extraction of critical features and improve the recognition *** experiment results show that the HDCGD-CBAM model significantly outper-forms existing methods in terms of recognition accuracy and *** Jamming-to-Signal Ratio(JSR)varies from-30dB to 10dB,it achieves an average accuracy of 78.7%and outperforms the CLDNN by 7.29%while reducing the Floating Point Operations(FLOPs)by 79.8%to ***,the proposed model has fewer parameters with 301k compared to several state-of-the-art methods.

关键词： attention mechanism CLDNN HDC interference recognition satellite communication

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