Ultra-short-term Multi-region Power Load Forecasting Based on Spearman-GCN-GRU Model by Junying WU, Xin LU, Hong LIU, Bin ZHANG, Shouliang CHAI, Yunchun LIU, Jianan WANG

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SASTGCN: Semantic-Augmented Spatio-temporal graph convolutional network for subway flow prediction by Shiyuan Jin, Changfeng Jing, Sheng Yao, Yushan Zhang, Pu Zhao, Jinlong Zhang

“…The SASTGCN model was validated with the card swiping data in Shanghai, the prediction ability and error analysis results demonstrated the performance outperform nine baseline methods, and the accuracy was improved by approximately 21%. …”
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Analysis and Modeling of Particle Velocities in Premixed Abrasive Water Jets by Weiqin Zuo, Cheng Huang, Yanwei Liu, Hongkai Han, Fuchang Hao, Fajun Zhao, Fei Huang

“…The standard deviation of the experimental results is 3.81-4.22 m/s, while the average error is less than 4%.…”
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Synthesis of a global daily average gapless land surface temperature dataset from 2003 to 2018 by Xin Pan, Xu Ding, Kevin Tansey, Rufat Guluzade, Penghua Hu, Zi Yang, Suyi Liu, Jie Yuan, Zhanchuan Wang, Ziyu Lv, Wenyi Duan, Yingbao Yang

“…Abstract Land Surface Temperature (LST) plays a crucial role in research in the fields of energy balance, hydrology, meteorology, geography, and ecology, serving as a significant input indicator of widespread interest. …”
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SLAM Algorithm for Mobile Robots Based on Improved LVI-SAM in Complex Environments by Wenfeng Wang, Haiyuan Li, Haiming Yu, Qiuju Xie, Jie Dong, Xiaofei Sun, Honggui Liu, Congcong Sun, Bin Li, Fang Zheng

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Parameter estimation of submarine power cables in offshore applications using machine learning-based methods by Felipe P. de Albuquerque, Rafael Nascimento, Gabriel de Castro Biage, Rooney R.A. Coelho, Ronaldo F. Ribeiro Pereira, Eduardo C. Marques da Costa, Mario L. Pereira Filho, Cassio G. Lopes, José R. Cardoso

“…The maximum observed estimation error was approximately 1%, underscoring the robustness, efficiency, and practical viability of the proposed framework for the electrical characterization of submarine transmission systems.…”
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Model Parametrization-Based Genetic Algorithms Using Velocity Signal and Steady State of the Dynamic Response of a Motor by Mayra Cruz-Fernández, J. T. López-Maldonado, Omar Rodriguez-Abreo, Alondra Anahí Ortiz Verdín, J. Iván Amezcua Tinajero, Idalberto Macías-Socarrás, Juvenal Rodríguez-Reséndiz

“…The function reconstruction is performed with a Root Mean Square Error (RMSE) of less than 1% for both the speed and current signals. …”
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U-SeqNet: learning spatiotemporal mapping relationships for multimodal multitemporal cloud removal by Qian Zhang, Xiangnan Liu, Tao Peng, Xiao Yang, Mengzhen Tang, Xinyu Zou, Meiling Liu, Ling Wu, Tingwei Zhang

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Rainfall estimation in the West African Sahel: comparison and cross-validation of top-down vs. bottom-up precipitation products in Burkina Faso by Roland Yonaba, Axel Belemtougri, Tazen Fowé, Lawani Adjadi Mounirou, Elias Nkiaka, Moctar Dembélé, Akpoti Komlavi, Serigne M’backé Coly, Mahamadou Koïta, Harouna Karambiri

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Energy storage efficiency modeling of high-entropy dielectric capacitors using extreme learning machine and swarm-based hybrid support vector regression computational methods by Yas Al-Hadeethi, Taoreed O. Owolabi, Mouftahou B. Latif, Bahaaudin M. Raffah, Ahmad H. Milyani, Saheed A. Tijani

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Visual analysis of LLM-based entity resolution from scientific papers by Siyu Wu, Yi Yang, Weize Wu, Ruiming Li, Yuyang Zhang, Ge Wang, Huobin Tan, Zipeng Liu, Lei Shi

“…We propose human-in-the-loop refinement over the entity resolution process using visual analytics techniques, which allows domain experts to interactively integrate insights into LLM intelligence, including error analysis and interpretation of the retrieval-augmented generation (RAG) algorithm. …”
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Neural Network-based CF4 and SF6/CF4 Detection in High Altitude and Extreme Cold Regions by Rukuo MA, Jie DONG, Yatian WANG, Guoxin YI, Xianghao DING, Le MA

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An intelligent bridge multi-dimension deflection IoT monitoring system based on laser datum and imaging by Dan Zhao, Huifeng Wang, Hao Du, Haoyi Cheng, Lu Peng, Yaru Liang, He Huang, Yunmeng Li

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Flood Classification and Improved Loss Function by Combining Deep Learning Models to Improve Water Level Prediction in a Small Mountain Watershed by Rukai Wang, Ximin Yuan, Fuchang Tian, Minghui Liu, Xiujie Wang, Xiaobin Li, Minrui Wu

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The Spatial Dimming Scheme for the MU-MIMO-OFDM VLC System by Zhen Feng, Caili Guo, Zabih Ghassemlooy, Yang Yang

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Investigating the Effect of Grooves on the Hydraulic Parameters of a Sharp-crested Trapezoidal Side Weir by R. Daneshfaraz, E. Aminvash, R. Omidvar, V. Süme, H. O. Marangoz, E. Yılmaz

“…The validation with experimental data by comparison showed that the relative error in the range of 0.4-2.6%. It was found from the results that the discharge coefficient increases in the no-grooved model and decreases in the grooved model. …”
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Application of the Correlation Measurement Method for Reconstructing of the Velocity Profile with Spatial and Temporal Discretization in Studies of the Hydrodynamics of Turbulent F... by S. M. Dmitriev, A. E. Khrobostov, D. N. Solncev, A. A. Barinov, A. A. Chesnokov, I. A. Konovalov, M. A. Makarov, T. K. Zyryanova

“…The correlation method for measuring of the coolant fl rate is used in the operation of nuclear power plants and is widespread in research practice including study of turbulent fl    hydrodynamics. …”
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Combining machine learning with UAV derived multispectral aerial images for wheat yield prediction, in southern Brazil by Henrique dos Santos Felipetto, Erivelto Mercante, Octavio Viana, Adão Robson Elias, Giovani Benin, Lucas Scolari, Arthur Armadori, Diandra Ganascini Donato

“…This research aims to evaluate the performance of machine learning algorithms and multispectral aerial images in estimating wheat grain yield, contributing to the eradication of hunger and food security. …”
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The effect of conservation agriculture technologies adoption on food production and security in Northern Malawi: evidence from Mzimba district by George N. Chidimbah Munthali, George N. Chidimbah Munthali, He Puming, Lazarus Obed Livingstone Banda, Peter Stephen Donald Ngulube, Gama Rivas Daru, Thokozani Mzumara, Moses M. N. Chitete, Zondiwe Mabilabo Jere

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Efficient Hardware Implementation of a Multi-Layer Gradient-Free Online-Trainable Spiking Neural Network on FPGA by Ali Mehrabi, Yeshwanth Bethi, Andre van Schaik, Andrew Wabnitz, Saeed Afshar

“…By using simple local adaptive selection thresholds, a Winner-Take-All (WTA) constraint on each layer, and a modified weight update rule that is more amenable to hardware, the trainer module allocates neuronal resources optimally at each layer without having to pass high-precision error measurements across layers. All elements in the system, including the training module, interact using event-based binary spikes. …”
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