Emerging role of generative AI in renewable energy forecasting and system optimization by Erdiwansyah, Rizalman Mamat, Syafrizal, Mohd Fairusham Ghazali, Firdaus Basrawi, S.M. Rosdi

“…Results indicate that GAN-based models reduce root mean square error (RMSE) by 15–20 % in solar irradiance forecasting and significantly enhance spatial-temporal wind simulations. …”
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Multitask Change-Aware Network and Semisupervised Enhanced Multistep Training for Semantic Change Detection by Yifei Si, Jie Jiang

“…FAM integrates low-level spatial details and high-level semantics from multilevel features, which helps to capture small-sized changes. …”
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Using Multi-Scenario Analyses to Determine the Driving Factors of Land Use in Inland River Basins in Arid Northwest China by Yang You, Pingan Jiang, Yakun Wang, Wen’e Wang, Dianyu Chen, Xiaotao Hu

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“Sunshade World”: A fully coupled GCM evaluation of the climatic impacts of geoengineering by D. J. Lunt, A. Ridgwell, P. J. Valdes, A. Seale

“…We investigate the magnitude and nature of this climate change for the first time within a fully coupled General Circulation Model. We find significant cooling of the tropics, warming of high latitudes and related sea ice reduction, a reduction in intensity of the hydrological cycle, reduced ENSO variability, and an increase in Atlantic overturning. …”
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A New Climate vulnerability Index Sistan and Baluchistan province by esmaeail ahmadi, zahra hejazizadeh, bohlol alijani, Mohammad saligheh, Hassan danaie fard

“…Area with very high vulnerability label expanded from 57.5% to 100%, which reflects the spatial expansion of vulnerability over SB. The overall result is that vulnerability reduction needs for accurate and continuous measurement, on the increase adaptation capacity and mitigate climate sensitivity.…”
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Multi-dimensional water quality indicators forecasting from IoT sensors: A tensor decomposition and multi-head self-attention mechanism. by Li Bo, Lv Junrui, Luo Xuegang

“…Accurate prediction of multi-dimensional water quality indicators is critical for sustainable water resource management, yet existing methods often fail to address the high-dimensional, nonlinear, and spatially correlated nature of data from heterogeneous IoT sensors. …”
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CABAD: A video dataset for benchmarking child aggression recognition by Shehzad Ali, Md Tanvir Islam, Ik Hyun Lee, Mohammad Hijji, Khan Muhammad

“…Leveraging CABAD, we propose CABA_Net, a multi-stage deep-learning framework integrating MobileViT for spatial feature extraction, Temporal Convolutional Networks (TCN) for sequential modeling, and an Attention LSTM for refined temporal attention on behavioral patterns. …”
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Evaluation of the Monitoring Capabilities of Remote Sensing Satellites for Maritime Moving Targets by Weiming Li, Zhiqiang Du, Li Wang, Tiancheng Zhou

“…Firstly, a target motion prediction model for calculating the transfer probability and a satellite observation information calculation model for obtaining observation strips and time windows are established. …”
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A new approach to estimate neighborhood socioeconomic status using supermarket transactions and GNNs by Eduardo Cruz, Monica Villavicencio, Carmen Vaca, Lisette Espín-Noboa, Nervo Verdezoto

“…Using customer consumption data, we created a basket graph and fed it into a graph neural network to predict neighborhood socioeconomic status. The model was trained with spectral and spatial convolutional filters using cross-validation to select the best approach for the prediction. …”
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Comparative Analysis of Non-Negative Matrix Factorization in Fire Susceptibility Mapping: A Case Study of Semi-Mediterranean and Semi-Arid Regions by Iraj Rahimi, Lia Duarte, Wafa Barkhoda, Ana Cláudia Teodoro

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Remote sensing-based detection of brown spot needle blight: a comprehensive review, and future directions by Swati Singh, Lana L. Narine, Janna R. Willoughby, Lori G. Eckhardt

“…However, studies on other needle diseases demonstrated the effectiveness of multisource RS techniques for symptom detection, spatial mapping, and severity assessment. Advancements in machine learning (ML) and deep learning (DL) have further improved RS capabilities for automated disease classification and predictive modeling in forest health monitoring. …”
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Numerical simulation of UGS facilities rebuilt from oil reservoirs based on the coupling of seepage and temperature fields by HE Haiyan, LIU Xianshan, GENG Shaoyang, SUN Junchang, SUN Yanchun, JIA Qian

“…The model is solved discretely using the Finite Volume Method（FVM）, with a Two-Point Flux Approximation（TPFA） scheme for spatial discretization and a backward （implicit） Euler scheme for temporal discretization. …”
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Optimizing Group Activity Recognition With Actor Relation Graphs and GCN-LSTM Architectures by M. R. Tejonidhi, C. V. Aravinda, S. V. Aruna Kumar, C. K. Madhu, A. M. Vinod

“…By integrating the ARG with a hybrid model that combines Graph Convolutional Network (GCN), Long Short-Term Memory (LSTM), and Attention mechanisms, our approach significantly enhances the extraction of spatial and relational features compared to conventional techniques. …”
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Determination of Bioactive Components in Chrysanthemum Tea (Gongju) Using Hyperspectral Imaging Technique and Chemometrics by Yunpeng Wei, Huiqiang Hu, Minghua Yuan, Huaxing Xu, Xiaobo Mao, Yuping Zhao, Luqi Huang

“…Experimental results indicated that the proposed VSPSO achieved a superior accuracy, with R² scores of 0.9280 and 0.8882 for TF and TCA prediction. Furthermore, after the involvement of spatial image information, the fused spectral–spatial features achieved the optimal model accuracy on LightGBM. …”
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Spatiotemporal dynamics and driving factors of human resources for health in traditional Chinese medicine in China by Jiarui Zhang, Sheng Zhou, Yujie Feng, Huaijin Liu, Chengcheng Li

“…This study employs a multiscale geographically weighted regression (MGWR) model to explore the spatial and temporal dynamics of HRH in TCM across 31 Chinese provinces from 2008 to 2021. …”
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Identifying Potential Urban Greenways by Considering Green Space Exposure Levels and Maximizing Recreational Flows: A Case Study in Beijing’s Built-Up Areas by Tao Liu, Le Yu, Xin Chen, Yunmiao Chen, Xiaomeng Li, Xinyi Liu, Yue Cao, Fan Zhang, Chenggang Zhang, Peng Gong

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Tracking daily NO_<i>x</i> emissions from an urban agglomeration based on TROPOMI NO₂ and a local ensemble transform Kalman filter by Y. Kong, Y. Kong, B. Zheng, B. Zheng, Y. Liu

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City guide as a multi-sensory mobile phone application by Konopska Beata, Kamiński Mateusz

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DMP-PUNet: A novel network for two-dimensional InSAR phase unwrapping under severe noise and complex fringes conditions by Yu Chen, Shuai Wang, Yandong Gao, Yanjian Sun, Jinqi Zhao, Kun Tan, Peijun Du

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A Dual-Enhanced Hierarchical Alignment Framework for Multimodal Named Entity Recognition by Jian Wang, Yanan Zhou, Qi He, Wenbo Zhang

“…To address these issues, this paper proposes a dual-enhanced hierarchical alignment (DEHA) framework that achieves dual semantic and spatial enhancement via global–local cooperative alignment optimization. …”
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