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Definability of Relations by Semigroups of Isotone Transformations

Journal of Applied and Industrial Mathematics 2024年第1期18卷 60-69页

作者： Klyushin, A.A. Kozhukhov, I.B. Manilov, D. Yu. Reshetnikov, A.V. Cadence Design Systems CorkT23 KW81 Ireland National Research University of Electronic Technology Moscow124498 Russia Lomonosov Moscow State University Moscow119991 Russia ELVEES Research and Development Center Moscow Zelenograd1244660 Russia

Abstract: In 1961, L.M. Gluskin proved that a given set with an arbitrary nontrivial quasiorder is determined up to isomorphism or anti-isomorphism by the semigroup of all isotone transformations of, i.e., the transformations of preserving. Subsequently, L.M. Popova proved a similar statement for the semigroup of all partial isotone transformations of;here the relation does not have to be a quasiorder but can be an arbitrary nontrivial reflexiveor antireflexive binary relation on the set. In the present paper, under the same constraints on the relation, we prove that the semigroup of all isotone binary relations (set-valued mappings) of determines up to an isomorphism or anti-isomorphism as well. In addition, for each ofthe conditions,, and, we enumerate all-ary relations satisfying the given condition. © Pleiades Publishing, Ltd. 2024.

关键词： Set theory

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Intelligent recognition and information extraction of radar complex jamming based on time-frequency features

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Journal of Systems Engineering and electronics 2024年第5期35卷 1148-1166页

作者： PENG Ruihui WU Xingrui WANG Guohong SUN Dianxing YANG Zhong LI Hongwen College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China Qingdao Innovation and Development Center Harbin Engineering UniversityQingdao 266000China Information Fusion Research Institute Naval Aeronautical UniversityYantai 264001China National Key Laboratory of Science and Technology on Vessel Integrated Power System Naval University of EngineeringWuhan 430033China

In modern war,radar countermeasure is becoming increasingly fierce,and the enemy jamming time and pattern are changing more *** is challenging for the radar to efficiently identify jamming and obtain precise parameter information,particularly in low signal-to-noise ratio(SNR)*** this paper,an approach to intelligent recognition and complex jamming parameter estimate based on joint time-frequency distribution features is proposed to address this challenging ***,a joint algorithm based on YOLOv5 convolutional neural networks(CNNs)is proposed,which is used to achieve the jamming signal classification and preliminary parameter ***,an accurate jamming key parameters estimation algorithm is constructed by comprehensively utilizing chi-square statistical test,feature region search,position regression,spectrum interpolation,etc.,which realizes the accurate estimation of jamming carrier frequency,relative delay,Doppler frequency shift,and other ***,the approach has improved performance for complex jamming recognition and parameter estimation under low SNR,and the recognition rate can reach 98%under−15 dB SNR,according to simulation and real data verification results.

关键词： complex jamming recognition time frequency feature convolutional neural network(CNN) parameter estimation

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A self-driving solution for resource-constrained autonomous vehicles in parked areas

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High-Confidence Computing 2024年第1期4卷 32-42页

作者： Jin Qian Liang Zhang Qiwei Huang Xinyi Liu Xiaoshuang Xing Xuehan Li College of Information Engineering Taizhou UniversityTaizhou 225300China Engineering Research Center of Integration and Application of Digital Learning Technology Ministry of EducationBeijing 100039China School of Computer Science and Engineering Changshu Institute of TechnologyChangshu 215500China The School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China

Autonomous vehicles in industrial parks can provide intelligent,efficient,and environmentally friendly transportation services,making them crucial tools for solving internal transportation *** the characteristics of industrial park scenarios and limited resources,designing and implementing autonomous driving solutions for autonomous vehicles in these areas has become a research *** paper proposes an efficient autonomous driving solution based on path planning,target recognition,and driving decision-making as its core *** designs for path planning,lane positioning,driving decision-making,and anti-collision algorithms are *** analysis and experimental validation of the proposed solution demonstrate its effectiveness in meeting the autonomous driving needs within resource-constrained environments in industrial *** solution provides important references for enhancing the performance of autonomous vehicles in these areas.

关键词： Autonomous vehicles Path planning Target recognition Driving decision-making Self-driving

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Structure and luminescence study of Gd3+ sensitized Sr2YF7: Eu3+: A novel red luminescent phosphor for high-performance white light diodes and fingerprints

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Ceramics International 2025年第14期51卷 19267-19281页

作者： Yan, Miao Pei, Xiaoqing Liu, Yifan Fan, Lin Jiang, Tao Mi, Zibo Liu, Lina Li, Chun Lin, Hai Li, Shasha Yang, Weiling Zeng, Fanming Su, Zhongmin School of Materials Science and Engineering Changchun University of Science and Technology Changchun130022 China Engineering Research Center of Optoelectronic Functional Materials Ministry of Education Changchun130022 China Jilin University Changchun130012 China Jilin Technology College of Electronic Information Jilin 132021 China

Due to the lack of effective strategies to simultaneously address the two challenging issues of poor luminous efficiency and low thermal stability, the development and large-scale application of solid-state lighting technology are unable to overcome bottlenecks. Therefore, Eu3+ red phosphors were synthesized using the hydrothermal method, with the introduction of Gd3+ to replace Y3+ in the host lattice resulting in a significant improvement in luminescence performance. The luminous intensity of Sr2YF7: 0.1Eu3+, 0.06Gd3+ phosphor at 591 nm increased by 5.50 times. This enhancement can be attributed to the improved local crystal field environment of the doped phosphor. The quantum efficiency of Sr2YF7: 0.1Eu3+ and Sr2YF7: 0.1Eu3+, 0.06Gd3+ phosphors reached 57.88 % and 84.32 % respectively, with the increase in electron traps with a quantum confinement structure after the replacement of Y3+ by Gd3+ contributing to this improvement. Both Eu3+ doped and Eu3+/Gd3+ co-doped phosphors demonstrated thermal stability as high as 90.58 % and 94.59 %, showcasing excellent performance in this aspect. The calculation of the Debye temperature ΘD further supported the exceptional thermal stability of the phosphor. Furthermore, the synthesized phosphor exhibited excellent moisture resistance. The study explored the application of these phosphors in WLEDs and fingerprint detection, showing promising performance. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： Gadolinium compounds

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Improving ECAPA-TDNN Performance with Coordinate Attention

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Journal of Shanghai Jiaotong University (Science) 2024年 1-7页

作者： Liu, Shuanghong Song, Zhida He, Liang School of Computer Science and Technology Xinjiang University Urumqi830017 China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi830017 China Department of Electronic Engineering and Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China

The current mainstream networks, such as squeeze and excitation residual neural network (SE-ResNet) and emphasized channel attention, propagation and aggregation based time delay neural network (ECAPA-TDNN), enhance the capability of speaker embedding extractors to extract more discriminative speaker embeddings by incorporating squeeze and excitation (SE) attention within the convolutional blocks. However, the SE attention focuses solely on encoding inter-channel information, overlooking the importance of spatial positional information and time-frequency information, which are crucial for the model’s performance. In this paper, we first experimentally compare the effectiveness of several mainstream attention mechanisms in the computer vision domain for the ECAPA-TDNN model. Next, we focus on the substantial improvements that coordinate attention (CA) brings to the ECAPA-TDNN model. The introduction of CA can help the model embed time-frequency information into the channel representation. Even without using AS-Norm, our proposed model achieves relative reductions of about 5.3% equal error rate (EER) and 5.5% minimum detection cost function (minDCF) on both the Voxceleb-O and Voxceleb-H test sets compared to the ECAPA-TDNN baseline model. In addition, the EER is relatively reduced by 9.46% on the CN-Celeb1 test set. This result strongly demonstrates that the CA module can effectively improve the generalization ability of the ECAPA-TDNN model. © Shanghai Jiao Tong University 2024.

关键词： Neural network models

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Feature Weighting and Fusion for Few-shot Object Detection in Remote Sensing Images 4

Feature Weighting and Fusion for Few-shot Object Detection i...

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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Deng, Lianyin Song, Yunkai Xie, Honggang Ye, Yunyao Yuan, Zi Xiao, Jinsheng China Academy of Space Technology Research Center Beijing100080 China Wuhan University School of Electronic Information Wuhan430072 China Hubei University of Technology School of Electrical and Electronic Engineering Wuhan430068 China

ISBN: (纸本)9798350349252

Few-shot object detection (FSOD) trains detectors to recognize new objects using very limited data, making it a challenging task in scenarios with scarce labeled examples. In this paper, a small-sample remote sensing target detection method with feature weighting and fusion is proposed by using the meta-learning method. Firstly, the bottleneck structural feature learning module C3 is embedded in the meta-feature extraction network to increase the network depth and receptive field. Secondly, the path aggregation network is used for meta-feature fusion, which effectively improves the perception ability of the network for multi-scale remote sensing targets. Finally, the lightweight convolutional neural network is used to learn the prototype vector to weight the meta-features. The existing knowledge of the model is used to quickly fine-tune the model to adapt to the detection of new types of targets while lightening the model. The experimental results show that the average detection accuracy of the new class of objects reaches 68% and 33% under the 10-shot on the NWPU VHR-10 and DIOR datasets. The visualization results show that the proposed method has a better effect on the detection of small-sample remote sensing targets. © 2024 IEEE.

关键词： Convolutional neural networks

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Study on Grid Control Methods Based on Three-Phase Current Source Type 5-Level Converters 50

Study on Grid Control Methods Based on Three-Phase Current S...

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50th Annual Conference of the IEEE Industrial electronics Society, IECON 2024

作者： Bao, Jianyu Yan, Cheng Gu, Nannan Yang, Liu School of Electronic and Information Engineering Ningbo University of Technology Ningbo China Research and Development Department Ningbo Deye Inverter Technology Co. Ltd Ningbo China Research Institute of Interdisciplinary Intelligent Science Ningbo University of Technology Ningbo China

ISBN: (纸本)9781665464543

Against the backdrop of global energy transition and climate change, enhancing the grid integration efficiency and quality of renewable energy sources is pivotal for achieving sustainable development goals. This paper introduces a three-phase current source type 5-level grid-connected inverter and its control method, designed to offer a system with adjustable power factor for high-quality stable grid operation. This system is particularly suitable for grid integration of renewable energy generation, effectively suppressing the resonance of the CL filter and reducing harmonic distortion in grid current. Detailed simulations of the system demonstrate that the design maintains exceptional performance under various conditions, particularly showing outstanding adaptability and stability in response to grid voltage fluctuations and load changes. © 2024 IEEE.

关键词： Current source inverter Grid-connected inverter Multilevel control Power electronics simulation Renewable energy grid integration Resonance suppression

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Performance Reliability of Reinforcement Learning Algorithms in Obstacle Avoidance Game with Differing Reward Formulations

Performance Reliability of Reinforcement Learning Algorithms...

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2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023

作者： Hansen, Brandon Dozier, Haley Information Technology Laboratory U.S. Army Engineer Research and Development Center VicksburgMS United States

ISBN: (纸本)9798350327595

When formulating environments for complex appli-cation areas, using analogies to games is beneficial as they provide convenient models to test algorithm performance in ways that are transferable to realistic environments. We propose a Frogger like grid based environment containing a simple action space, dynamic obstacles, and discrete game loop for testing Proximal Policy Optimization 2 and Deep Q-Network with comparisons to a heuristic and random agent. The environment contains four dif-ferent reward function implementations, along with two different environment variations to explore adaptability. Seeing how these different parameters effect not just the average performance of the algorithm, but also the reliability of the performance is of concern as reliability determines the expectations of any single performance of an reinforcement learning agent. Experiments in these environments demonstrate common be-haviors of reinforcement learning algorithms showing possible strengths and weakness of the approaches when applied to more complex decision-making scenarios. We explore these behaviors through evaluation techniques meant to measure the agents accumulation of reward in the game. Cross comparing these evaluation techniques elucidates the causation behind agent performance. © 2023 IEEE.

关键词： artificial intelligence Learning machine learning reinforcement learning

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Uncovering the Deep Filter Bubble: Narrow Exposure in Short-Video Recommendation 24

Uncovering the Deep Filter Bubble: Narrow Exposure in Short-...

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33rd ACM Web Conference, WWW 2024

作者： Sukiennik, Nicholas Gao, Chen Li, Nian Department of Electronic Engineering Tsinghua University Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China Shenzhen International Graduate School Tsinghua University Shenzhen China

ISBN: (纸本)9798400701719

Filter bubbles have been studied extensively within the context of online content platforms due to their potential to cause undesirable outcomes such as user dissatisfaction or polarization. With the rise of short-video platforms, the filter bubble has been given extra attention because these platforms rely on an unprecedented use of the recommender system to provide relevant content. In our work, we investigate the deep filter bubble, which refers to the user being exposed to narrow content within their broad interests. We accomplish this using one-year interaction data from a top short-video platform in China, which includes hierarchical data with three levels of categories for each video. We formalize our definition of a "deep"filter bubble within this context, and then explore various correlations within the data: first understanding the evolution of the deep filter bubble over time, and later revealing some of the factors that give rise to this phenomenon, such as specific categories, user demographics, and feedback type. We observe that while the overall proportion of users in a filter bubble remains largely constant over time, the depth composition of their filter bubble changes. In addition, we find that some demographic groups that have a higher likelihood of seeing narrower content and implicit feedback signals can lead to less bubble formation. Finally, we propose some ways in which recommender systems can be designed to reduce the risk of a user getting caught in a bubble. © 2024 Owner/Author.

关键词： Recommender systems

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Deep-learning based on-chip rapid spectral imaging with high spatial resolution

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Chip 2023年第2期2卷 26-33页

作者： Jiawei Yang Kaiyu Cui Yidong Huang Wei Zhang Xue Feng Fang Liu Department of Electronic Engineering Tsinghua UniversityBeijing 100084China Beijing National Research Center for Information Science and Technology(BNRist) Tsinghua UniversityBeijing 100084China Bejing Academy of Quantum Information Science Beijing 100084China

Spectral imaging extends the concept of traditional color cameras to capture images across multiple spectral channels and has broad ap-plication *** spectral cameras based on scanning methods suffer from the drawbacks of low acquisition speed and large ***-chip computational spectral imaging based on metasur-face filters provides a promising scheme for portable applications,but endures long computation time due to point-by-point iterative spec-tral reconstruction and mosaic effect in the reconstructed spectral *** this study,on-chip rapid spectral imaging was demonstrated,which eliminated the mosaic effect in the spectral image by deep-learning-based spectral data cube *** experimental results show that 4 orders of magnitude faster than the iterative spec-tral reconstruction were achieved,and the fidelity of the spectral re-construction for the standard color plate was over 99%for a standard color *** particular,video-rate spectral imaging was demon-strated for moving objects and outdoor driving scenes with good per-formance for recognizing metamerism,where the concolorous sky and white cars can be distinguished via their spectra,showing great po-tential for autonomous driving and other practical applications in the field of intelligent perception.

关键词： Spectral imaging Deep learning Metasurface

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