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Community-Level Practice Checklists for Health Protection During Cold Spells in China

China CDC weekly 2024年第5期6卷 83-87页

作者： Jing Shang Mengzhen Zhao Zhao Liu Xiya Zhang Shiguang Miao Ishaq D.Sulaymon Wenjia Cai Institute of Urban Meteorology CMABeijingChina School of Management and Economics Beijing Institute of TechnologyBeijingChina School of Airport Economics and Management Beijing Institute of Economics and ManagementBeijingChina Department of Earth System Science Tsinghua UniversityBeijingChina Sand and Dust Storm Warning Regional Center National Center for MeteorologyJeddahSaudi Arabia Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science and TechnologyNanjing CityJiangsu ProvinceChina

Communities play a crucial role in protecting the health of vulnerable populations such as the elderly,low-income groups,and high-risk individuals during cold ***,current strategies for responding to cold spells primarily consist of programmatic policies that lack practicality,specificity,and detailed implementation guidelines for community ***,this study aims to identify and analyze the challenges faced by communities in responding to cold spells,review international experiences,and develop a set of practical checklists for community-level health *** checklists will assist community workers and volunteers in effectively preparing for,responding to,and recovering from cold spells.

关键词： preparing income primarily

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TRNet: Two-Tier Recursion Network for Co-Salient Object Detection

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IEEE Transactions on Circuits and systems for Video technology 2025年第6期35卷 5844-5857页

作者： Cong, Runmin Yang, Ning Liu, Hongyu Zhang, Dingwen Huang, Qingming Kwong, Sam Zhang, Wei Shandong University School of Control Science and Engineering Jinan250061 China Ministry of Education Key Laboratory of Machine Intelligence and System Control Jinan250061 China Beijing Jiaotong University Institute of Information Science Beijing100044 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China Northwestern Polytechnical University Brain and Artificial Intelligence Laboratory School of Automation Xi'an710129 China University of Chinese Academy of Sciences School of Computer Science and Technology Beijing101408 China Lingnan University Hong Kong

Co-salient object detection (CoSOD) is to find the salient and recurring objects from a series of relevant images, where modeling inter-image relationships plays a crucial role. Different from the commonly used direct learning structure that inputs all the intra-image features into some well-designed modules to represent the inter-image relationship, we resort to adopting a recursive structure for inter-image modeling, and propose a two-tier recursion network (TRNet) to achieve CoSOD in this paper. The two-tier recursive structure of the proposed TRNet is embodied in two stages of inter-image extraction and distribution. On the one hand, considering the task adaptability and inter-image correlation, we design an inter-image exploration with recursive reinforcement module to learn the local and global inter-image correspondences, guaranteeing the validity and discriminativeness of the information in the step-by-step propagation. On the other hand, we design a dynamic recursion distribution module to fully exploit the role of inter-image correspondences in a recursive structure, adaptively assigning common attributes to each individual image through an improved semi-dynamic convolution. Experimental results on five prevailing CoSOD benchmarks demonstrate that our TRNet outperforms other competitors in terms of various evaluation metrics. The code and results of our method are available at https://***/rmcong/TRNetTCSVT2025. © 1991-2012 IEEE.

关键词： HTTP

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A Phase-Dependent and EMG-Driven Variable Stiffness Control Strategy for Upper Limb Rehabilitation Robot

A Phase-Dependent and EMG-Driven Variable Stiffness Control ...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Li, Pengcheng Guo, Shuxiang Li, Chunying Southern University of Technology and Science Department of Electronic and Electrical Engineering Shenzhen China Aerospace Center Hospital School of Life Science Key Laboratory of Convergence Medical Engineering System and Healthcare Technology Ministry of Industry and Information Technology Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665481090

Bilateral training is a widely adopted approach in upper limb rehabilitation due to its effectiveness and ease of implementation. Variable stiffness actuators enhance this approach by facilitating compliant human-machine interaction, ensuring both comfort and safety. However, optimizing stiffness levels for individual subjects to maximize training effectiveness remains a significant challenge. The difficulty of different task phases varies across subjects, necessitating customized robotic assistance. This paper proposes an adaptive stiffness modulation strategy that leverages the cyclic nature of rehabilitation tasks. An adaptive frequency oscillator is employed for real-time phase detection, while a tuning rule, based on motion tracking error and muscular activation, dynamically adjusts stiffness levels. Experimental validation with two participants demonstrated that the proposed strategy effectively promotes affected arm motion and tailors assistance to the user's specific needs. © 2024 IEEE.

关键词： Human robot interaction

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Multi-secret Sharing Scheme for Zero Trust Environment 14

Multi-secret Sharing Scheme for Zero Trust Environment

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14th IEEE International Conference on Software engineering and Service science, ICSESS 2023

作者： Zhou, Qin Yang, Rumiao Zhou, Hao Cai, Lei Yongyou Network Technology Co. Ltd Beijing China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China North China Institute of Computing Technology The 4th System Department Beijing China

ISBN: (纸本)9798350336269

The zero-trust concept of 'never trust, always verify' injected new vitality into the development of network security. However, the related research on zero trust is still preliminary, and the research on secure data transmission is relatively less. How to achieve secure data transmission in zero trust environment is a problem to be solved. Aiming the data transmission scenario of private data secret sharing among agents, this paper proposed a secure data transmission scheme based on multi-secret sharing to solve the problems of identity comparison confirmation of participants and adjust the access structure according to the security value of trust evaluation in existing secret sharing schemes. The proposed scheme adopts the secret sharing design without the trusted third party, which avoids the security risk of trusted third party disclosure in the traditional secret sharing scheme. Secondly, in the system parameter setting phase, the identity of participants and zero-trust identity database are compared to combine the characteristics of zero-trust 'identity authentication', to improve the security of secret sharing. Finally, during secret distribution, zero-trust trust evaluation security values are used to adjust the access structure based on zero-trust 'trust evaluation' to ensure secure data transmission. © 2023 IEEE.

关键词： Data communication systems

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Assessing a BERT-based model for analyzing subjectivity and classifying academic articles

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Multimedia Tools and Applications 2024年第42期83卷 90511-90532页

作者： Mehmood, Atif Shahid, Farah Khan, Rizwan Ahmed, Shahzad Ibrahim, Mostafa M. Zheng, Zhonglong School of Computer Science and Technology Zhejiang Normal University Jinhua321002 China Zhejiang Institute of Photoelectronics & Zhejiang Institute for Advanced Light Source Zhejiang Normal University Zhejiang Jinhua321004 China Faculty of Information Technology Beijing University of Technology Beijing100024 China Department of Electrical Engineering Faculty of Engineering Minia University Minia61519 Egypt

The metaverse concept extends beyond virtual worlds and can be applied to collaborative analysis environments. Data analysts worldwide may read academic article extracts in real-time in a shared digital workplace to mine and analyze data using the metaverse. Furthermore, a semantic metaverse in natural language processing might also involve creating a digital environment with linguistic and semantic connections. Many dedicated researchers navigating the complexities of natural language processing in the metaverse era have spent considerable time searching for relevant papers. However, online reviews and evaluations of articles are helpful for their assistance and may save the researcher time. In this work, human specialists manually produced a dataset from four conferences and evaluated subjectively using rule-based techniques. Subsequently, we aim to evaluate the effectiveness of pre-trained word embeddings and pre-trained BERT models seamlessly integrated with convolutional neural networks. This endeavor focuses on the subjective analysis and classification of contributions and previous work sentences extracted from academic literature. For comparison, various deep learning architectures were systematically employed, including long short-term memory-GloVe and bi-directional long short-term memory-GloVe, alongside classical machine learning methods. Our findings show that the proposed BERT model achieved state-of-the-art performance in classification and subjective analysis tasks with an accuracy of 91.50% and F1 score of 91.00%. Finally, we plan to utilize sentence similarity to identify contributions within abstracts, thus outlining potential avenues for future research. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Natural language processing systems

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A Study Of Dynamic Thresholds Power Detection Spectrum Sensing Techniques In CRN 9

A Study Of Dynamic Thresholds Power Detection Spectrum Sensi...

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9th International Conference on Advanced Computing and Communication systems, ICACCS 2023

作者： Keerthika, J. AnandaKumar, H. Priya, V. Yuvalatha, S. Gayathri, N. Sri Eshwar College of Engineering Department of Computer Science and Engineering Coimbatore India Dr NGP Institute of Technology Department of Artificial Intelligence and Data Science Coimbatore India Bannari Amman Institute of Technology Department of Computer Science and Business System Sathyamangalam India

ISBN: (纸本)9798350397376

A Cognitive radio is the mobile communication technologies which help to utilize the efficient need of radio spectrum origin. The performance of CRN is significantly impacted by the spectrum sensing function. The problem of bandwidth has risen as a more specific one with breakthroughs in remote communications. By forgiving unlicensed users to usage the available spectrum in primary networks is the solution to the CR technology. An innovative method for enhancing the electromagnetic spectrum's use efficiency, cognitive radio is a encouraging technology. Spectrum sensing has high spectral resolution capabilities and aids in the detection of the spectrum holes. The various methodologies are used to enhance the spectrum sensing essence. These techniques are distinguished by a sensing threshold, which is crucial to the performance of the sensing. The most important element in selecting the best threshold to optimize spectrum sensing performance is the dynamic threshold in the proposed system's spectrum detection algorithm. The energy earned from the licensed user over a precise time of observation, then the dynamic threshold is commutated between two levels. The estimation of the noise ambiguity factor forms the basis for threshold evaluations. These criteria are used to hike the likelihood of detection and contraction the possibility of false alarms. © 2023 IEEE.

关键词： Cognitive radio

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Real-Time Myanmar Hand Gestures Recognition Using Deep Learning Models 8th

Real-Time Myanmar Hand Gestures Recognition Using Deep Learn...

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8th International Conference on Intelligent Technologies, ICIT 2023

作者： Kyaw, Nwe Ni Mitra, Pabitra Sinha, G.R. Department of Computer Science and Engineering Indian Institute of Technology Kharagpur West Bengal721302 India Indian Knowledge System Lab International Institute of Information Technology Bangalore Karnataka Bengaluru560100 India

ISBN: (纸本)9789819738588

The proposed system for recognizing Myanmar sign language between individuals who are deaf. The aim of this study is to develop deep learning models for the purpose of accurately identifying dynamic hand gesture images depicting 14 classes of Myanmar words and numbers. The present system utilizes a new dataset comprising 7834 images for 14 classes obtained through Webcam. The objective of this study is to enhance the robustness of the new model. Next, we proceed to evaluate the proposed model by comparing them to those of existing convolutional neural network models. These models are generally recognized as effective deep-learning approaches for recognition tasks. The proposed model exhibits a performance level of 96% for both validation and testing accuracies. Furthermore, the experimental finding demonstrates that the model, convolutional layers, achieved an accuracy of 100% in recognizing Myanmar Sign Language (MSL). © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Acoustic propagation uncertainty in internal wave environments using an ocean-acoustic joint model

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Chinese Physics B 2023年第3期32卷 308-319页

作者：高飞徐芳华李整林秦继兴章沁雅 Department of Earth System Science Ministry of Education Key Laboratory of Earth System ModelingInstitute for Global Change StudiesTsinghua UniversityBeijing 100084China Naval Research Institute Tianjin 300061China School of Ocean Engineering and technology Sun Yat-Sen UniversityZhuhai 519000China State Key Laboratory of Acoustics Institute of AcousticsChinese Academy of SciencesBeijing 100190China

An ocean-acoustic joint model is developed for research of acoustic propagation uncertainty in internal wave *** internal waves are numerically produced by tidal forcing over a continental slope using an ocean *** parameters(i.e.,internal wave,source depth,and water depth)contribute to the dynamic waveguide environments,and result in stochastic sound *** sensitivity of the transmission loss(TL)to environment parameters,statistical characteristics of the TL variation,and the associated physical mechanisms are investigated by the Sobol sensitivity analysis method,the Monte Carlo sampling,and the coupled normal mode theory,*** results show that the TL is most sensitive to the source depth in the near field,resulted from the initial amplitudes of higher-order modes;while in middle and far fields,the internal waves are responsible for more than 80%of the total acoustic propagation *** addition,the standard deviation of the TL in the near field and the shallow layer is smaller than those in the middle and far fields and the deep layer.

关键词： acoustic propagation uncertainty ocean-acoustic joint model internal wave sensitivity analysis

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Equalizer Zero-Determinant Strategy in Discounted Repeated Stackelberg Asymmetric Game

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Journal of systems science & Complexity 2024年第1期37卷 184-203页

作者： CHENG Zhaoyang CHEN Guanpu HONG Yiguang Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology10044 StockholmSweden. Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 210201China

This paper focuses on the performance of equalizer zero-determinant(ZD)strategies in discounted repeated Stackelberg asymmetric *** the leader-follower adversarial scenario,the strong Stackelberg equilibrium(SSE)deriving from the opponents’best response(BR),is technically the optimal strategy for the ***,computing an SSE strategy may be difficult since it needs to solve a mixed-integer program and has exponential complexity in the number of *** this end,the authors propose an equalizer ZD strategy,which can unilaterally restrict the opponent’s expected *** authors first study the existence of an equalizer ZD strategy with one-to-one situations,and analyze an upper bound of its performance with the baseline SSE *** the authors turn to multi-player models,where there exists one player adopting an equalizer ZD *** authors give bounds of the weighted sum of opponents’s utilities,and compare it with the SSE ***,the authors give simulations on unmanned aerial vehicles(UAVs)and the moving target defense(MTD)to verify the effectiveness of the proposed approach.

关键词： Discounted repeated Stackelberg asymmetric game equalizer zero-determinant strategy strong Stackelberg equilibrium strategy

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Brillouin Frequency Shift Extraction for BOTDA Based on Gramian Angular Fields 4

Brillouin Frequency Shift Extraction for BOTDA Based on Gram...

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4th International Computational Imaging Conference, CITA 2024

作者： Zhu, Borong Zhang, Zhihao Qian, Yuhao Ma, Xiaole Wang, Liang Yu, Kuanglu Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China Institute of Information Science School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China National Engineering Laboratory for Next Generation Internet Access System School of Optics and Electronic Information Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781510688834

To accurately extract Brillouin frequency shift of BOTDA with large sweeping step sizes, a novel structure of GAFCNN is proposed, combining time series coding with convolutional neural networks. The experimental data validation results demonstrate that the GAFCNN is capable of obtaining more accurate results under large sweep steps and low signal-to-noise ratios (SNRs) than other current methods. © 2025 SPIE.

关键词： Convolutional neural networks

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