Prediciendo el crimen en ciudades intermedias: un modelo de “machine learning” en Bucaramanga, Colombia by Juan David Gelvez Ferreira, María-Paula Nieto-Rodríguez, Carlos-Andrés Rocha-Ruiz

“…The results show that the best crime prediction outcomes were obtained when using the models with spatial relationships of graphs by weeks. …”
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Dual Graph for Traffic Forecasting by Long Wei, Zhengxu Yu, Zhongming Jin, Liang Xie, Jianqiang Huang, Deng Cai, Xiaofei He, Xian-Sheng Hua

“…It is challenging due to the complex spatial-temporal correlation on road networks. Most existing research works use sequential Graph Neural Networks (GNN) to model traffic inference. …”
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Possible Systematic Rotation in the Mature Stellar Population of a z = 9.1 Galaxy by Tsuyoshi Tokuoka, Akio K. Inoue, Takuya Hashimoto, Richard S. Ellis, Nicolas Laporte, Yuma Sugahara, Hiroshi Matsuo, Yoichi Tamura, Yoshinobu Fudamoto, Kana Moriwaki, Guido Roberts-Borsani, Ikkoh Shimizu, Satoshi Yamanaka, Naoki Yoshida, Erik Zackrisson, Wei Zheng

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Tree species classification using intensity patterns from individual tree point clouds by Andreas Tockner, Ralf Kraßnitzer, Christoph Gollob, Sarah Witzmann, Tim Ritter, Arne Nothdurft

“…However, recent studies assessing tree species labels on single tree point clouds have been insufficiently accurate in complex forest ecosystems; moreover, explainability of machine-learning methods used in published studies has been insufficient. Whether the predictions of black-box models suffer from over-fitting or whether they are based on characteristic species traits often remains unclear. …”
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Monitoring sub-arctic wetland vegetation using nested scales of spectrometry to inform multiple endmember spectral unmixing of Sentinel-2A imagery by Heidi Cunnick, Joan M Ramage, Dawn Magness, Stephen C Peters

“…We develop a bottom–up reference library for unmixing based on nested scales of data beginning with the highest resolution of a ground collected handheld spectral measurements, progressing to 1 m ^2 resolution using fused hyperspectral-LiDAR data, and then subsequently map predictively at the spatial resolution of the 10 m ^2 multi-spectral imagery of the European Space Agency’s Sentinel-2A. …”
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Trends of Desertification Change and Its Driving Factors in Aksu Region by Zheng Jiaxiang, Sun Guili, Su Xiangling, Ran Yajun, Zheng Xu

“…The mode and intensity of action showed enhancement and non-linear enhancement, respectively. ③ The prediction results from the CA-Markov model showed that if the driving factors did not change, the degree of desertification in the Aksu region would continue to reverse during 2019—2024, and the overall change for the area would be from extremely severe desertification to severe desertification. …”
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Retrospective evaluation of Facial nerve monitoring to prevent nerve damage during robotic drilling in the largest series of patients undergoing the HEARO-procedure. by Jaouad Abari, Marco Matulic, Pablo Galeazzi, Masoud Zoka Assadi, Paul Van de Heyning, Vedat Topsakal

“…Linear regression was used to determine if the minimum stimulation thresholds (FNM) could significantly predict the intra-operative distance (CBCT) between the drilled trajectory and the facial nerve. …”
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Sensitivity assessment and simulation of ecosystem services in response to land use change in arid regions: Empirical evidence from Xinjiang, China by Xiaoyun Li, Chunsheng Wu

“…An improved framework for assessing and simulating ecosystem services combining a modified equivalent factor method, a future land use simulation (FLUS) model, and a cross-sensitivity analysis is proposed. …”
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Transitional Housing and the Family Capacity Building Planner: An Urban Graduation Approach for Improving the Mental Health and Well-Being of Poor Households in Hong Kong by Siu-Ming Chan, Heng Xu, Yuen-Ki Tang, Kim Kwok, Ka-Man Leung

“…Together, these interventions address the multidimensional challenges of urban poverty while fostering sustainable improvements in residents’ capacity to achieve housing security and economic stability. (4) Conclusions: The integration of transitional housing with capacity-building services demonstrates the effectiveness of the Urban Graduation Approach in addressing urban poverty. This model highlights the importance of viewing housing not merely as a physical shelter but as a comprehensive infrastructure for well-being that combines spatial improvements with targeted social support. …”
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Bridging Sensor Gaps via Attention-Gated Tuning for Hyperspectral Image Classification by Xizhe Xue, Haokui Zhang, Haizhao Jing, Lijie Tao, Zongwen Bai, Ying Li

“…Instead of inserting additional parameters inside the basic model, we train a lightweight auxiliary branch that takes intermediate features as input from the basic model and makes predictions. …”
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Shafranov-shift destabilization of ballooning-type micro-instabilities by X. Jian, V. Chan, Z. Qiu, S. Ding, C. Holland, E. Bass, A. Garofalo, X. Liu

“…The reduced transport model TGLF can capture the physics reasonably well.…”
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Multiscale Two-Stream Fusion Network for Benggang Classification in Multi-Source Images by Xuli Rao, Chen Feng, Jinshi Lin, Zhide Chen, Xiang Ji, Yanhe Huang, Renguang Chen

“…Experimental comparisons of different data inputs and network models revealed that the proposed method outperformed current state-of-the-art approaches in extracting spatial features and textures of Benggangs. …”
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AI-augmented pathology: the experience of transfer learning and intra-domain data diversity in breast cancer metastasis detection by Manuel Cossio, Nina Wiedemann, Esther Sanfeliu Torres, Esther Barnadas Sole, Laura Igual

“…To enhance interpretability, we developed a visualization tool that employs color-coded probability maps to highlight tumor regions alongside their prediction confidence. Our experiments demonstrated that integrating an external dataset (Camelyon16) during training significantly improved model performance, surpassing the benefits of data augmentation alone. …”
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Temporal generalization in evergreen leaf type classification using tailored Sentinel-2 composites by Peter Hofinger, Jan Dempewolf, Simon Ecke, Hans-Joachim Klemmt

“…Existing mapping approaches frequently suffer from spatial resolution limitations and temporal constraints. …”
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Interpretable longitudinal glaucoma visual field estimation deep learning system from fundus images and clinical narratives by Xiaoling Huang, Xiangyin Kong, Yan Yan, Zhiyuan Gao, Zihan Li, Chun Zhang, Kai Jin, Juan Ye

“…The pointwise mean absolute error across five models ranged from 3.098 to 4.131 dB. Heatmaps demonstrated the spatial relationship between fundus damage and vision loss. …”
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Explainable AI Meets Synthetic Data: A Deep Learning Framework for Detecting Network Intrusion in NextG Network Infrastructure by Md Junayed Hossain, Khorshed Alam, Md Fahad Monir, Md Mozammal Hoque, Tarem Ahmed

“…Furthermore, we integrate Local Interpretable Model-Agnostic Explanations (LIME) to make model predictions transparent, increasing trust and usability for practical deployment. …”
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Planning for the future, algae bloom dynamics in water management and ecosystem restoration efforts by Paul Julian, William W. Walker, Donatto Surratt, Stephen E. Davis

“…The second model was a hierarchical model that used hydrodynamic and biogeochemical variables to predict chlorophyll-a concentrations across the lake. …”
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Study on the influence of complex fault geometry on earthquake risk assessment based on physical simulation: a case study of the Zhujiangkou Fault in the Guangdong–Hong Kong–Macao... by Houyun Yu, Yilong Li, Xiuwei Ye, Wenqiang Wang, Chunjing Wang, Zhenguo Zhang, Wei Zhang, Xiaofei Chen

“…Dynamic rupture simulations offer a physics-based approach to model earthquake processes and assess seismic hazards. …”
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The Intentional and Unintentional Human Food Subsidy Landscape for a Large Carnivore by Matthew M. Smith, David M. MacFarland, Jennifer L. Price Tack, Jonathan N. Pauli

“…We then predicted a human subsidy landscape that explored the spatial variation between intentional and unintentional sources and modeled the relationship between human food subsidies and conflict. …”
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Mapping Soil Organic Matter in Black Soil Cropland Areas Using Remote Sensing and Environmental Covariates by Yu Zhang, Chong Luo, Wenqi Zhang, Zexin Wu, Deqiang Zang

“…Combining three types of environmental covariates such as drainage, climate and topography, the study area was categorized into dry field and paddy field. Then, the SOM prediction model was constructed using random forest regression method and the accuracy of different strategies was evaluated by 10-fold cross-validation. …”
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