Research on DV-Hop location algorithm based on range correction and improved gray wolf optimizer by Xiaoqiang ZHAO, Shuai WU, Chuanyi GAO, Ning LI, Bodong LI, Xiaoyong YANG

“…Node location is an important problem in wireless sensor network.Although the location algorithm based on distance measurement has small positioning error, it has many limitations when applied to outdoor environments.Therefore, based on the original distance vector-hop (DV-Hop) algorithm, received signal strength indication (RSSI) technology and the minimum mean square error (MMSE) criterion to modify the algorithm’s ranging process were introduced, and the improved gray wolf optimizer was used to optimize the process of determining the coordinates of unknown nodes.Simulation results show that, compared with the original DV-Hop algorithm and IPDV-Hop algorithm, the average location error rate of the IGDV-Hop algorithm under the initial parameters was reduced by 28% and 17% respectively, and the location effect was significantly improved.…”
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Combining semiparametric and machine learning approaches for short-term prediction of satellite clock bias by Lihong Jin, Wanzhuo Zhao, Xiong Pan, Qingsong Ai, Mao Cai, Xiaoli Ruan

“…Moreover, this model combines semiparametric techniques with optimized self-attention neural networks and is applied to predict SCB for BDS-3. Its performance is compared with other models, including quadratic polynomial (QP), spectral analysis (SA), and long short-term memory (LSTM) networks. …”
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Harmonic Measurement Algorithm of Power System Integrating Wavelet Transform and Deep Learning by Hanshu Jiang, Yutian Li, Zhu Liu, Guanghao Wu, Zeyang Liu

“… INTRODUCTION: The problem of low accuracy in harmonic measurement is a significant challenge in power systems. …”
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A privacy-preserving federated learning framework by Yang Dongning, Xie Xiaorui, Ji Zhikun, Ji Weiwei

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Traffic noise research in tambov city by A. A. Guskov, N. A. Stepanov, S. A. Anokhin

“…Introduction. The problem of traffic noise on the road network of cities is considered. …”
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Automatic recognition and representation of text in the form of audio stream by L. V. Serebryanaya, I. E. Lasy

“…The problem of automatic speech generation from a text file is considered. …”
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Research on Lightweight Small Object Detection Algorithm Based on Context Representation by Li Qiang, Cui Jianghui

“…This framework model consists of three parts: a backbone network, a multi-scale feature representation network, and a detection head. …”
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An Edge Recognition Method for Insulator State Based on Multi-dimension Feature Fusion by Dongmei HUANG, Yueqi WANG, Anduo HU, Jinzhong SUN, Shuai SHI, Yuan SUN, Lingfeng FANG

“…Traditional insulator state recognition methods have such problems as poor real-time performance and insufficient feature extraction ability. …”
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GRE²-MDCL: Graph Representation Embedding Enhanced via Multidimensional Contrastive Learning by Quanjun Li, Weixuan Li, Xiya Zheng, Junhua Zhou, Wenming Zhong, Xuhang Chen, Chao Long

“…However, most graph neural network models require extensive labelled data, limiting their practical applicability. …”
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Near-Infrared Hyperspectral Target Tracking Based on Background Information and Spectral Position Prediction by Li Wu, Mengyuan Wang, Weixiang Zhong, Kunpeng Huang, Wenhao Jiang, Jia Li, Dong Zhao

“…In order to address the problems of in-plane rotation and fast motion during near-infrared (NIR) video target tracking, this study explores the application of capsule networks in NIR video and proposes a capsule network method based on background information and spectral position prediction. …”
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Practical exploration of English translation activity courses in universities under the background of artificial intelligence by Jiexia Dai

“…This paper used the neural network machine translation model in artificial intelligence to solve the practical problems in implementing of college English translation activities. …”
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GAPO: A Graph Attention-Based Reinforcement Learning Algorithm for Congestion-Aware Task Offloading in Multi-Hop Vehicular Edge Computing by Hongwei Zhao, Xuyan Li, Chengrui Li, Lu Yao

“…Efficient task offloading for delay-sensitive applications, such as autonomous driving, presents a significant challenge in multi-hop Vehicular Edge Computing (VEC) networks, primarily due to high vehicle mobility, dynamic network topologies, and complex end-to-end congestion problems. …”
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Cellular-free RAN slicing resource allocation algorithm based on multi-timescale collaboration by XIA Weiwei, WANG Boye, XIA Yaxing, MIAO Weiwei, WANG Dayang, JING Dongsheng, YAN Feng, SHEN Lianfeng

“…Firstly, the large time-scale slice-oriented resource allocation problem was formulated as a mean square error-minimization-based resource demand prediction model with average user latency constraints, and the accurate allocation of slice resources was achieved by a long and short-term memory time-series prediction network. …”
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ViTMa: A Novel Hybrid Vision Transformer and Mamba for Kinship Recognition in Indonesian Facial Micro-Expressions by Ike Fibriani, Eko Mulyanto Yuniarno, Ronny Mardiyanto, Mauridhi Hery Purnomo

“…The Siamese architecture processes two input images, extracts features fused with feature fusion, and passes them to a classification network. Experiments on the FIW-Local Indonesia dataset demonstrate the effectiveness of this method, with the best model using B16 quadratic features and multiplicative fusion achieving an average accuracy of 85.18% across all kinship categories, outperforming previous approaches. …”
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LEO computing satellite constellation design for heterogeneous QoS requirements by PENG Yuming, SUN Yijing, DI Boya

“…By establishing a satellite-to-terrestrial connection model, the average computational resources and backhaul capacity available to ground users were analyzed and a multi-objective optimization problem for designing ultra-dense LEO constellations was modelled, aiming to minimize the total number of satellites while meeting the heterogeneous quality of service (QoS) requirements for user task offloading. …”
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Time Division Switching Scheme and Performance Analysis of Low Orbit Quantum Satellite Communication by Guang Yang, Min Nie, Fan Jiang

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Channel model-based multiple layers satellite-ground integrated data allocation strategy by SONG Yujie, CAO Yue, CHEN Nuo, SUN Zhili

“…To address the problem of inefficient satellite-ground link handover, unbalanced data allocation, and high probability of data transmission interruptions in space-air-ground integrated networks, a channel model-based multiple layers satellite-ground integrated data allocation strategy (CMDAS) was proposed for the satellite-ground integrated data transmission scenario with a multi-layer architecture. …”
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Channel model-based multiple layers satellite-ground integrated data allocation strategy by SONG Yujie, CAO Yue, CHEN Nuo, SUN Zhili

“…To address the problem of inefficient satellite-ground link handover, unbalanced data allocation, and high probability of data transmission interruptions in space-air-ground integrated networks, a channel model-based multiple layers satellite-ground integrated data allocation strategy (CMDAS) was proposed for the satellite-ground integrated data transmission scenario with a multi-layer architecture. …”
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Chinese Word Sense Disambiguation Based on Word translation and Part of speech by ZHANG Chunxiang, ZHAO Lingyun, GAO Xueyao

“…For vocabulary ambiguity problem in Chinese, CNN (Convolution Neural Network) is adopted to determine true meaning of ambiguous vocabulary where word, part of speech and translation around its left and right adjacent words are used. …”
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Deep Memory Fusion Model for Long Video Question Answering by SUN Guanglu, WU Meng, QIU Jing, LIANG Lili

“…To solve this problem, a deep memory fusion model is proposed based on the memory network.This model uses the memory component of the memory network to effectively retain the fusion features of video clips and subtitles. …”
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