RETRACTED: Temporal-Difference Graph-Based Optimization for High-Quality Reconstruction of MODIS NDVI Data by Shengtai Ji, Shuxin Han, Jiaxin Hu, Yuguang Li, Jing-Cheng Han

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Node-Based Graph Convolutional Network With SLIC Method for Breast Cancer Ultrasound Images Classification by Kien Trang, Fung Fung Ting, Bao Quoc Vuong, Chee-Ming Ting

“…This research presents a novel node-based Graph Convolutional Network (GCN) approach for the classification of breast cancer from ultrasound images. …”
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Generalized Shortest Path Problem: An Innovative Approach for Non-Additive Problems in Conditional Weighted Graphs by Adrien Durand, Timothé Watteau, Georges Ghazi, Ruxandra Mihaela Botez

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Gods, graves and graphs – social and semantic network analysis based on Ancient Egyptian and Indian corpora by Frederik Elwert, Simone Gerhards, Sven Sellmer

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TempODEGraphNet: predicting user churn using dynamic social graphs and neural ODEs. by Minseop Lee, Jiyoung Woo

“…Experimental results reveal that the proposed model achieves a higher F1 score compared with conventional algorithms and static graph models. Dynamic graphs more accurately reflect changes in user behavior compared with static graphs, particularly in domains with active interactions such as massively multiplayer online role-playing games. …”
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MSASGCN :  Multi-Head Self-Attention Spatiotemporal Graph Convolutional Network for Traffic Flow Forecasting by Yang Cao, Detian Liu, Qizheng Yin, Fei Xue, Hengliang Tang

“…Experiments on two real datasets verify the stability of our proposed model, obtaining a better prediction performance than the baseline algorithms. The correlation metrics get significantly reduced compared with traditional time series prediction methods and deep learning methods without using graph neural networks, according to MAE and RMSE results. …”
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Dynamic load balancing in cloud computing using predictive graph networks and adaptive neural scheduling by K. Rajammal, M. Chinnadurai

“…To overcome these issues, a novel approach is presented in this research work utilizing Spiking Neural Networks (SNNs) for adaptive decision-making and Temporal Graph Neural Networks (TGNNs) for dynamic resource state modeling. …”
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Optimizing coverage in wireless sensor networks using deep reinforcement learning with graph neural networks by G. Pushpa, R. Anand Babu, S. Subashree, S. Senthilkumar

“…To address these limitations, this research introduces a novel hybrid model that integrates Deep Reinforcement Learning (DRL) with Graph Neural Networks (GNN). …”
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ARGContextProfiler: extracting and scoring the genomic contexts of antibiotic resistance genes using assembly graphs by Nazifa Ahmed Moumi, Shafayat Ahmed, Connor Brown, Amy Pruden, Liqing Zhang

“…Several tools, databases, and algorithms are now available to facilitate the identification of ARGs in metagenomic sequencing data; however, direct annotation of short-read data provides limited contextual information. …”
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A deep learning framework for predicting disease-gene associations with functional modules and graph augmentation by Xianghu Jia, Weiwen Luo, Jiaqi Li, Jieqi Xing, Hongjie Sun, Shunyao Wu, Xiaoquan Su

“…Results Addressing these limitations, here we introduce a deep learning framework called ModulePred for predicting disease-gene associations. ModulePred performs graph augmentation on the protein interaction network using L3 link prediction algorithms. …”
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Natural gas logistics management using multi-criteria optimisation methods by Sergey N. Lanin

“…The main objective of the article is to develop and justify a combined approach for optimising these processes, including the use of graph theory and multi-criteria genetic algorithms to minimise the transportation costs and to maximise the revenue. …”
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The Air Transportation System as a Subsystem of Modern Communication Space: Analysis Based on Transfer Entropy Graphs by Sagit Valeev, Natalya Kondratyeva

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Construction and Application of Feature Recommendation Model for Remote Sensing Interpretation of Rock Strata Based on Knowledge Graph by Liufeng Tao, Qirui Wu, Miao Tian, Zhong Xie, Jianguo Chen, Yueyu Wu, Qinjun Qiu

“…These include limited use of cross-modal data (e.g., geochemical tables, outcrop images) and a reliance on static knowledge representations. Future research will introduce dynamic graph updating mechanisms and multi-modal fusion architectures to improve adaptability across diverse geological lithological and structural environments.…”
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Graph-based two-level indicator system construction method for smart city information security risk assessment by Li Yang, Kai Zou, Yuxuan Zou

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TTG-Text: A Graph-Based Text Representation Framework Enhanced by Typical Testors for Improved Classification by Carlos Sánchez-Antonio, José E. Valdez-Rodríguez, Hiram Calvo

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WEST GCN-LSTM: Weighted stacked spatio-temporal graph neural networks for regional traffic forecasting by Theodoros Theodoropoulos, Angelos-Christos Maroudis, Uwe Zdun, Antonios Makris, Konstantinos Tserpes

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Wetland Scene Segmentation of Remote Sensing Images Based on Lie Group Feature and Graph Cut Model by Canyu Chen, Guobin Zhu, Xiliang Chen

“…Given the increasingly severe destruction of wetlands in recent years, research and monitoring for wetland protection are urgently needed. …”
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User-cooperative dynamic resource allocation for backscatter-aided wireless-powered MEC network by Huaiwen He, Chenghao Zhou, Feng Huang, Hong Shen, Yihong Yang, Shangsong Liang, Xinyuan Jin

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An Algorithm to Automatically Generate the Combinatorial Orbit Counting Equations. by Ine Melckenbeeck, Pieter Audenaert, Tom Michoel, Didier Colle, Mario Pickavet

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FastClothGNN: Optimizing message passing in Graph Neural Networks for accelerating real-time cloth simulation by Yang Zhang, Kailuo Yu, Xinyu Zhang

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