Determination of Sequential Well Placements Using a Multi-Modal Convolutional Neural Network Integrated with Evolutionary Optimization by Seoyoon Kwon, Minsoo Ji, Min Kim, Juliana Y. Leung, Baehyun Min

“…The learned M-CNN predicts oil productivity at every candidate well location and selects qualified well placement scenarios. …”
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Local response to global risk: a case study of risk perception and communication on Chinese social media regarding Fukushima’s treated radioactive water discharge by Chenxi Sun, Qingliu Ren, Yuejing Ge

“…Three key findings emerge: (1) Temporal dynamics dominate public engagement, with attention peaking within two weeks post-discharge before gradually declining, while fear persists as the predominant emotion despite diminishing anger responses; (2) Coastal regions demonstrate heightened participation due to geographic proximity and seafood consumption patterns, though risk perception shows no consistent spatial gradient; (3) Socioeconomic factors - particularly education levels and seafood consumption - significantly predict communication intensity, whereas economic indicators like per capita GDP show limited influence. …”
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Deep Time Series Intelligent Framework for Power Data Asset Evaluation by Lihong Ge, Xin Li, Li Wang, Jian Wei, Bo Huang

“…In the evaluation of the complex and rich Solar-Power dataset and Electricity dataset, TSENet achieved significant performance improvements over other state-of-the-art baseline methods.Through the synergistic design of deep convolutional structures and an efficient memory mechanism, it effectively addresses issues such as inadequate modeling of long-term dependencies, insufficient extraction of short-term features, and high prediction volatility, thereby significantly enhancing both the accuracy and robustness of forecasting in power asset evaluation tasks.…”
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Mapping Tropical Forested Wetlands Biomass with LiDAR: A Machine Learning Comparison by Jonathan V. Solórzano, Candelario Peralta-Carreta, J. Alberto Gallardo-Cruz

“…The model’s robustness and uncertainty were evaluated through bootstrapping and spatial prediction across the study area, with higher AGB values concentrated near the main water channels. …”
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Multimodal Fusion Multi-Task Learning Network Based on Federated Averaging for SDB Severity Diagnosis by Songlu Lin, Renzheng Tang, Yuzhe Wang, Zhihong Wang

“…The proposed framework is built upon a hybrid deep neural architecture that integrates convolutional layers (CNN) for spatial representation, bidirectional GRUs for temporal modeling, and multi-head self-attention for long-range dependency learning. …”
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Spatio-temporal dynamics of ecosystem service value functions in response to landscape fragmentation in Boma-Gambella trans-boundary landscape, Southwest Ethiopia and East South Su... by Azemir Berhanu Getahun, Amare Bantider Dagnew, Desalegn Yayeh Ayal

“…Utilizing integrated spatial modeling tools such as ArcGIS 10.7, FRAGSTAT 4.2, and benefit transfer approach, the research analyzes landscape fragmentation and the dynamics of ecosystem service value functions. …”
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Economic Aspects of Cash Access Problems by Arkadiusz Manikowski

“…Further research should include econometric modeling using logit/probit models. Originality/value: The obtained results are the first on the impact of access to cash on financial exclusion in Poland and consistent with the situation in other European countries. …”
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Numerical Simulation of Turbopump Inducer Cavitating Behavior by O. Coutier-Delgosha, P. Morel, R. Fortes-Patella, JL. Reboud

“…In the present study a numerical model of 3D cavitating flows is proposed. It is applied to investigate the behavior of a spatial turbopump inducer in noncavitating and cavitating conditions. …”
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The best angle correction of basketball shooting based on the fusion of time series features and dual CNN by Meicai Xiao

“…Segmenting the shooting video, taking the video frame as the input of the key node extraction network of the shooting action, obtaining the video frame with the sequence information of the bone points, extracting the continuous T-frame video stack from it, and inputting it into the spatial context feature extraction network in the shooting posture prediction model based on dual stream CNN (MobileNet V3 network with multi-channel attention mechanism fusion module), extract the space context features of shooting posture; The superimposed optical flow graph of continuous video frames containing sequence information of bone points is input into the time convolution network (combined with Bi-LSTM network of multi-channel attention mechanism fusion module), extract the skeleton temporal sequence features during the shooting movement, using the spatial context features and skeleton temporal sequence features extracted from the feature fusion module, and realizing the prediction of shooting posture through Softmax according to the fusion results, calculate the shooting release speed under this attitude, solve the shooting release angle, and complete the correction of the best shooting release angle by comparing with the set conditions. …”
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Inversion method of organic matter content of different types of soils in black soil area based on hyperspectral indices by Lin Nan, Liu Yanlong, Liu Qiang, Jiang Ranzhe, Ma Xunhu

“…The results showed that the SOM estimation model, built using these feature spectral indices from hyperspectral satellite imagery, achieved high predictive accuracy, with R² values approaching 0.80 for most soil types. …”
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Information Assisted Dictionary Learning for fMRI Data Analysis by Manuel Morante, Yannis Kopsinis, Sergios Theodoridis, Athanassios Protopapas

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Research on channel estimation based on joint perception and deep enhancement learning in complex communication scenarios by Xin Liu, Shanghong Zhao, Yanxia Liang, Shahid Karim

“…In this article, we address the intelligent, reflective surface (IRS)-assisted channel estimation problem and propose an intelligent channel estimation model based on the fusion of convolutional neural network (CNN) and gated recurrent unit (GRU) row features, utilizing the reinforcement learning Deep Deterministic Policy Gradient (DDPG) strategy for Channel Reconstruction Prediction and Generation Network (CRPG-Net). …”
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Regional Analysis of Gender Inequality in the Kazakh Labor Market in the Context of Sustainable Development by G. N. Nyussupova, G. B. Aidarkhanova, L. B. Kenespayeva, G. B. Aubakirova

“…In this study, the authors tried to model spatial indicators of gender inequality in the labor market of the Republic of Kazakhstan. …”
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Study of Morphology of Sorption Substances by A. V. Bondarev, E. T. Zhilyakova, N. B. Demina, V. Y. Novikov

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Offline System for 2D Indoor Navigation Utilizing Advanced Data Structures by Jorge Luis Veloz, Leo Sebastián Intriago, Jean Carlos Palma, Andrea Katherine Alcívar-Cedeño, Álvaro Antón-Sacho, Pablo Fernández-Arias, Edwan Anderson Ariza, Diego Vergara

“…The system leverages advanced spatial modeling techniques to optimize pathfinding and resource efficiency. …”
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Lip-Reading Classification of Turkish Digits Using Ensemble Learning Architecture Based on 3DCNN by Ali Erbey, Necaattin Barışçı

“…While LSTM models are effective in processing temporal data, 3DCNN-based models, which can process both spatial and temporal information, achieved higher accuracy in this study. …”
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Integrating hydrological impacts for cost-effective dryland ecological restoration by Fengyu Fu, Shuai Wang, Xutong Wu, Shiyin Chen, Zimin Tan, ChongChong Ye, José M. Grünzweig

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Generation of 1 km high resolution Standardized precipitation evapotranspiration Index for drought monitoring over China using Google Earth Engine by Yile He, Youping Xie, Junchen Liu, Zengyun Hu, Jun Liu, Yuhua Cheng, Lei Zhang, Zhihui Wang, Man Li

“…After preprocessing such as gridding and sample balancing, a random forest regression model was constructed to achieve high spatial resolution prediction of SPEI. …”
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Assessing Public Transit Network Efficiency and Accessibility in Johor Bahru and Penang, Malaysia: A Data-Driven Approach by Mahbub Hassan, Hridoy Deb Mahin, Ferdoushi Ahmed, Md. Maruf Hassan, Atikur Rahaman, Masuk Abdullah

“…The analysis employs graph-theoretic centrality metrics, kernel density estimation, the Jaccard Similarity Index, and raster-based cost surface modeling to assess transit performance across structural, spatial, and temporal dimensions. …”
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Burned Area Segmentation in Optical Remote Sensing Images Driven by U-Shaped Multistage Masked Autoencoder by Yuxiang Fu, Wei Fang, Victor S. Sheng

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