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27th International Conference on Optical Fiber Sensors, OFS 2022

作者： Kim, Gyeong Hun Chung, Youngjoo Kima, Chang-Seok Engineering Research Center for Color-Modulated Extra-Sensory Perception Technology Pusan National University Busan Korea Republic of Gwangju Institute of Science and Technology School of Electrical Engineering and Computer Science Gwangju Korea Republic of Department of Cogno-Mechatronics Engineering Pusan National University Busan Korea Republic of

ISBN: (纸本)9781957171142

This paper reports the real-time linear-in-distance sampling for a resonance frequency mapping system based on an identical weak fiber Bragg grating (FBG) array. Based on a function of an external clock for the sampling timing of uniform distance spacing, 100 identical weak FBGs could be interrogatedexamined with a high linearity of 0.9996 (R2). © 2022 The Author(s).

关键词： Fiber Bragg gratings

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Polychromatic full-polarization control in mid-infrared light

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Light(Science & Applications) 2023年第5期12卷 894-904页

作者： Jin Chen Feilong Yu Xingsi Liu Yanjun Bao Rongsheng Chen Zengyue Zhao Jiuxu Wang Xiuxia Wang Wen Liu Yuzhi Shi Cheng-Wei Qiu Xiaoshuang Chen Wei Lu Guanhai Li State Key Laboratory of Infrared Physics Shanghai Institute of Technical PhysicsChinese Academy of Sciences500 Yu Tian RoadShanghai 200083China Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesNo.1 SubLane XiangshanHangzhou 310024China Shanghai Research Center for Quantum Sciences 99 Xiupu RoadShanghai 201315China University of Chinese Academy of Science No.19 Yuquan RoadBeijing 100049China Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117583Singapore Institute of Nanophotonics Jinan UniversityGuangzhou 511443China Center for Micro-and Nanoscale Research and Fabrication University of Science and Technology of ChinaHefei 230026China Institute of Precision Optical Engineering School of Physics Science and EngineeringTongji UniversityShanghai 200092China National University of Singapore Suzhou Research Institute No.377 Linquan StreetSuzhouJiangsu 215123China

Objects with different shapes,materials and temperatures can emit distinct polarizations and spectral information in mid-infrared band,which provides a unique signature in the transparent window for object ***,the crosstalk among various polarization and wavelength channels prevents from accurate mid-infrared detections at high signal-to-noise ***,we report full-polarization metasurfaces to break the inherent eigen-polarization constraint over the wavelengths in *** recipe enables to select arbitrary orthogonal polarization basis at individual wavelength independently,therefore alleviating the crosstalk and efficiency degradation.A six-channel all-silicon metasurface is specifically presented to project focused mid-infrared light to distinct positions at three wavelengths,each with a pair of arbitrarily chosen orthogonal *** isolation ratio of 117 between neighboring polarization channels is experimentally recorded,exhibiting detection sensitivity one order of magnitude higher than existing infrared ***,the high aspect ratio~30 of our meta-structures manufactured by deep silicon etching technology at temperature−150℃ guarantees the large and precise phase dispersion control over a broadband from 3 to 4.5μ*** believe our results would benefit the noise-immune mid-infrared detections in remote sensing and space-to-ground communications.

关键词： polarization light noise

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Integration of the grey relational analysis with machine learning for sucrose anaerobic hydrogen production prediction

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International Journal of Hydrogen Energy 2024年 68卷 388-397页

作者： Wang, Xianze Wang, Yifan Tseng, Yu-Yao Gao, Yidi Li, Keqing Wang, Ming-Hung Wu, Jinghui Lay, Chyi-How Huo, Mingxin Engineering Research Center of Low-Carbon Treatment and Green Development of Polluted Water in Northeast China Ministry of Education School of Environment Northeast Normal University Changchun130117 China Science and Technology Innovation Center for Municipal Wastewater Treatment and Water Quality Protection Northeast Normal University Changchun130117 China Key Laboratory of Songliao Aquatic Environment Ministry of Education Jilin Jianzhu University Changchun130118 China Master's Program of Green Energy Science and Technology Feng Chia University Taichung40724 Taiwan Department of Computer Science and Information Engineering National Chung Cheng University Chiayi County Taiwan

Anaerobic fermentation for hydrogen production is influenced by various environmental factors that can limit microbial activity. However, machine learning (ML) shows significant potential in explaining the complexity of biological processes. This study focuses on the application of ML in predicting hydrogen production rates (HPR) during anaerobic fermentation of biomass energy. Grey relation analysis was employed to investigate the correlation between operational parameters and HPR. Five ML algorithms, namely decision tree (DT), random forest (RF), extreme gradient boosting (XGBoost), and K-nearest neighbor (KNN), were utilized in conjunction with operating conditions and digestate characteristics as features, with HPR as the target variable. The evaluation of the models was conducted using mean squared error (MSE) and R squared (R2). Notably, butyrate, oxidation-reduction potential (ORP), and volatile suspended solids (VSS) were identified as key factors influencing hydrogen production during sucrose anaerobic fermentation. Among the ML algorithms tested, XGBoost achieved the highest accuracy, with an R2 value of 0.91 and an MSE of 0.0052. © 2024 Hydrogen Energy Publications LLC

关键词： Machine learning

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列车-轨道-地基土耦合系统三维随机振动的多GPU并行计算方法

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Journal of Central South University 2023年第5期30卷 1722-1736页

作者：朱志辉杨啸李昊徐海坤邹有 National Engineering Research Center of High-speed Railway Construction Technology Central South UniversityChangsha 410075China School of Civil Engineering Central South UniversityChangsha 410075China School of Computer Science and Engineering Central South UniversityChangsha 410083China Information and Network Center Central South UniversityChangsha 410083China

针对列车-轨道-地基土耦合系统随机计算效率低的问题,本文提出了基于多GPU的列车-轨道-地基土随机振动方程的高效并行计算方法。基于OpenMP-CUDA混编技术将虚拟激励法不同频点下的多个线性方程组求解任务分配给多个GPU并行执行;在每块GP... 详细信息

针对列车-轨道-地基土耦合系统随机计算效率低的问题,本文提出了基于多GPU的列车-轨道-地基土随机振动方程的高效并行计算方法。基于OpenMP-CUDA混编技术将虚拟激励法不同频点下的多个线性方程组求解任务分配给多个GPU并行执行;在每块GPU上,采用基于CUDA的预处理共轭梯度法(PCG)并行求解对称正定的等效静力平衡方程。针对耦合系统等效刚度矩阵的稀疏特性,采用行压缩(CSR)格式存储大型稀疏矩阵以节省内存空间。最终通过MATLAB-CUDA混合平台开发并行计算程序,解决了随机振动分析中多个线性方程组串行求解效率低的难题。数值算例表明,基于四GPU节点的多GPU并行算法和单GPU加速PCG算法的计算效率是串行多点同步算法(MPSA)计算效率的22.59倍和3.75倍。

关键词：随机振动并行计算多GPU 三维有限元法列车-轨道-地基土耦合模型

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Predicting Satisfied User and Machine Ratio for Compressed Images: A Unified Approach

arXiv

引用

arXiv 2024年

作者： Zhang, Qi Wang, Shanshe Zhang, Xinfeng Ma, Siwei Pan, Jingshan Gao, Wen National Research Engineering Center of Visual Technology School of Computer Science Peking University Beijing China University of Chinese Academy of Sciences Beijing China National Supercomputer Center in Jinan Jinan China

Nowadays, high-quality images are pursued by both humans for better viewing experience and by machines for more accurate visual analysis. However, images are usually compressed before being consumed, decreasing their quality. It is meaningful to predict the perceptual quality of compressed images for both humans and machines, which guides the optimization for compression. In this paper, we propose a unified approach to address this. Specifically, we create a deep learning-based model to predict Satisfied User Ratio (SUR) and Satisfied Machine Ratio (SMR) of compressed images simultaneously. We first pre-train a feature extractor network on a large-scale SMR-annotated dataset with human perception-related quality labels generated by diverse image quality models, which simulates the acquisition of SUR labels. Then, we propose an MLP-Mixer-based network to predict SUR and SMR by leveraging and fusing the extracted multi-layer features. We introduce a Difference Feature Residual Learning (DFRL) module to learn more discriminative difference features. We further use a Multi-Head Attention Aggregation and Pooling (MHAAP) layer to aggregate difference features and reduce their redundancy. Experimental results indicate that the proposed model significantly outperforms state-of-the-art SUR and SMR prediction methods. Moreover, our joint learning scheme of human and machine perceptual quality prediction tasks is effective at improving the performance of both. © 2024, CC BY.

关键词： Image quality

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Planning Data Poisoning Attacks on Heterogeneous Recommender Systems in a Multiplayer Setting

Planning Data Poisoning Attacks on Heterogeneous Recommender...

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39th IEEE International Conference on Data engineering, ICDE 2023

作者： Yeh, Chin-Yuan Chen, Hsi-Wen Yang, De-Nian Lee, Wang-Chien Yu, Philip S. Chen, Ming-Syan National Taiwan University Graduate Institute of Communication Engineering Taiwan National Taiwan University Department of Electrical Engineering Taiwan Academia Sinica Institute of Information Science Taiwan Academia Sinica Research Center for Information Technology Innovation Taiwan The Pennsylvania State University Department of Computer Science and Engineering United States University of Illinois Chicago Department of Computer Science United States

ISBN: (纸本)9798350322279

Data poisoning attacks against recommender systems (RecSys) often assume a single seller as the adversary. However, in reality, there are usually multiple sellers attempting to promote their items through RecSys manipulation. To obtain the best data poisoning plan, it is important for an attacker to anticipate and withstand the actions of his opponents. This work studies the problem of Multiplayer Comprehensive Attack (MCA) from the perspective of the attacker, considering the subsequent attacks by his opponents. In MCA, we target the Heterogeneous RecSys, where user-item interaction records, user social network, and item correlation graph are used for recommendations. To tackle MCA, we present the Multilevel Stackelberg Optimization over Progressive Differentiable Surrogate (MSOPDS). The Multilevel Stackelberg Optimization (MSO) method is used to form the optimum strategies by solving the Stackelberg game equilibrium between the attacker and his opponents, while the Progressive Differentiable Surrogate (PDS) addresses technical challenges in deriving gradients for candidate poisoning actions. Experiments on Heterogeneous RecSys trained with public datasets show that MSOPDS outperforms all examined prior works by up to 10.6% in average predicted ratings and up to 11.4% in HitRate@3 for an item targeted by an attacker facing one opponent. Source code provided in https://***/jimmy-academia/MSOPDS. © 2023 IEEE.

关键词： Recommender systems

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Compressed Domain Prior-Guided Video Super-Resolution for Cloud Gaming Content

arXiv

引用

arXiv 2025年

作者： Wang, Qizhe Yin, Qian Huang, Zhimeng Jiang, Weijia Su, Yi Ma, Siwei Zhang, Jiaqi National Engineering Research Center of Visual Technology School of Computer Science Peking University China Migu Interactive Entertainment Co. Ltd. China

Cloud gaming is an advanced form of Internet service that necessitates local terminals to decode within limited resources and time latency. Super-Resolution (SR) techniques are often employed on these terminals as an efficient way to reduce the required bit-rate bandwidth for cloud gaming. However, insufficient attention has been paid to SR of compressed game video content. Most SR networks amplify block artifacts and ringing effects in decoded frames while ignoring edge details of game content, leading to unsatisfactory reconstruction results. In this paper, we propose a novel lightweight network called Coding Prior-Guided Super-Resolution (CPGSR) to address the SR challenges in compressed game video content. First, we design a Compressed Domain Guided Block (CDGB) to extract features of different depths from coding priors, which are subsequently integrated with features from the U-net backbone. Then, a series of re-parameterization blocks are utilized for reconstruction. Ultimately, inspired by the quantization in video coding, we propose a partitioned focal frequency loss to effectively guide the model’s focus on preserving high-frequency information. Extensive experiments demonstrate the advancement of our approach. Copyright © 2025, The Authors. All rights reserved.

关键词： Network coding

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NM-LUD: A NLOS Mitigation Method with Low-cost UWB Devices for Indoor Positioning 8

NM-LUD: A NLOS Mitigation Method with Low-cost UWB Devices f...

引用

8th International Conference on computer and Communication Systems, ICCCS 2023

作者： Wu, Tong Li, Han Gao, Bo Xiong, Ke Fan, Pingyi Ben Letaief, Khaled Eng. Res. Center of Network Management Technology for High Speed Railway of Ministry of Education School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China Beijing Jiaotong University Collaborative Innovation Center of Railway Traffic Safety Beijing100044 China Beijing Jiaotong University National Engineering Research Center of Advanced Network Technologies Beijing100044 China Tsinghua University Department of Electronic Engineering Beijing100084 China Hong Kong University of Science and Technology Department of Electrical and Computer Engineering Hong Kong Hong Kong

ISBN: (纸本)9781665456128

Ultra-wideband (UWB) is a popular technology for indoor positioning. However, non-line-of-sight (NLOS) propagation caused by human occlusion dramatically affects the accuracy of UWB-based indoor positioning. Most of the existing works focused on mitigating NLOS errors in the scenarios with building structure occlusion, but the NLOS mitigation under human occlusion has not been well addressed. To this end, this paper aims to mitigate the NLOS impact of human occlusion, and then proposes a method of NLOS mitigation to reduce NLOS ranging errors under human occlusion with low-cost UWB devices (i.e., NM-LUD). It takes a set of signal features extracted from low-cost devices as input, calculates their weights and mitigates the ranging error based on the features' weights. Experiment results on the two data sets collected by LinkTrack S and UML1 UWB devices show that the method reduces ranging error from 0.9009 m to 0.1435 m (about by 84.07%) and from 0.7466 m to 0.0792 m (about by 89.39%) respectively, which greatly mitigates the influence of NLOS caused by human occlusion. © 2023 IEEE.

关键词： Costs

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A Novel Blockchain-Integrated Distributed Data Storage Model with Built-in Load Balancing 16

A Novel Blockchain-Integrated Distributed Data Storage Model...

引用

16th IEEE International Conference on Application of Information and Communication Technologies, AICT 2022

作者： Hammoud, Obadah Tarkhanov, Ivan A. National University of Science and Technology Department of Engineering Cybernetics Moscow Russia State Academic University for Humanities Federal Research Center 'Computer Science and Control' of Russian Academy of Sciences Russia

ISBN: (纸本)9781665451628

Most companies relay on centralized servers, which are considered as a fast and easy to deploy solution for file sharing, but they have many downsides, like security and trust issues, which can be solved using DLT (blockchain) solutions. However, DLT-based solutions have many challenges, such as nodes orchestration, adjusting reliability and double-spending, as well as load balancing. This research proposes a DLT (Distributed Ledger technology) based model for files storage for companies using p2p networks, which takes into account both data reliability and storage space efficiency. More efficient data storage is achieved through the use of the Erasure coding technique. For load balancing, a set of algorithms that can be implemented in the form of a smart contract were proposed. The described model can become the basis of the IT infrastructure for trusted exchange of documents, technical and scientific information, games distributions, mobile applications, updates of scientific, regulatory and technical databases in b2b and b2c format © 2022 IEEE.

关键词： Blockchain

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Multi-Agent Path Finding Using Imitation-Reinforcement Learning with Transformer

Multi-Agent Path Finding Using Imitation-Reinforcement Learn...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Chen, Lin Wang, Yaonan Miao, Zhiqiang Mo, Yang Feng, Mingtao Zhou, Zhen School of Electrical and Information Engineering Hunan University Changsha410082 China National Engineering Research Center for Robot Visual Perception and Control Technology Changsha410082 China School of Computer Science and Technology Xidian University Xian710126 China

ISBN: (纸本)9781665481090

Multi-Agent Path Finding is a problem of finding the optimal set of paths for multiple agents from the starting position to the goal without conflict, which is essential to large-scale robotic systems. Imitation and reinforcement learning are applied to solve the MAPF problem and have achieved certain results, which provides a feasible solution for the path planning problem of large-scale robot systems. The current method improves the performance of distributed strategy-guided agent planning paths in complex environments by introducing the communication between graph neural networks and agents but dramatically reduces the system's robustness. This paper develops a novel imitation reinforcement learning framework by introducing Transformer, which enables algorithms to perform well in complex environments without relying on communication between agents. Compared with its counterparts, experiments show that the policy trained by our method guides the agent to drive from the initial position to the goal without collision and achieve better performance. © 2022 IEEE.

关键词： Reinforcement learning

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