Study on Lightweight Bridge Crack Detection Algorithm Based on YOLO11 by Xuwei Dong, Jiashuo Yuan, Jinpeng Dai

“…This algorithm uses an efficient multiscale conv all (EMSCA) module to enhance channel and spatial attention, thereby strengthening its ability to extract crack features. …”
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Evaluation System of Blind Spot Warning Algorithm Based on Vehicle to Everything by Yanzhao Yang, Jian Wang, Xinyu Yang, Tingyu Zhang, Xinyu Guo

“…Utilizing simulation software named Virtual Test Drive, this research constructs detailed collision scenarios and performs exhaustive Hardware-in-the-Loop testing. …”
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Ensembles of spectral-spatial convolutional neural network models for classifying soil types in hyperspectral images by N.A. Firsov, V.V. Podlipnov, N.A. Ivliev, D.D. Ryskova, A.V. Pirogov, A.A. Muzyka, A.R. Makarov, V.E. Lobanov, V.I. Platonov, A.N. Babichev, V.A. Monastyrskiy, V.I. Olgarenko, D.P. Nikolaev, R.V. Skidanov, A.V. Nikonorov, N.L. Kazanskiy, V.A. Soyfer

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How spatial resolution mediates canopy spectral diversity as a proxy for marsh plant diversity by Yi Fu, Yunlong Yao, Lei Wang, Huaihu Yi, Yuanqi Shan

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Ensemble Learning for Spatial Modeling of Icing Fields from Multi-Source Remote Sensing Data by Shaohui Zhou, Zhiqiu Gao, Bo Gong, Hourong Zhang, Haipeng Zhang, Jinqiang He, Xingya Xi

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Examination Database and Online Paper Forming Algorithm for Mobile Personalized Learning Test by Wanwu Li, Lin Liu, Hui Zhang, Jinhong Li, Zhi Wang

“…This study aims to analyze and solves key technologies including constraint check paper forming algorithms. This study using fuzzy query methods and spatial queries design a single exam table structure and exam papers for the exam database. …”
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An Approach for Multi-Source Land Use and Land Cover Data Fusion Considering Spatial Correlations by Jing Yang, Yiheng Jiang, Qirui Song, Zheng Wang, Yang Hu, Kaiqiang Li, Yizhong Sun

“…As one of the foundational datasets in geographical information science, land use and land cover (LULC) data plays a crucial role in the study of human–environment interaction mechanisms, urban sustainable development, and other related issues. Although existing research has explored land use type recognition from remote sensing imagery, interpretation algorithms, and other perspectives, significant spatial discrepancies exist between these data products. …”
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Investigating Spatial Effects through Machine Learning and Leveraging Explainable AI for Child Malnutrition in Pakistan by Xiaoyi Zhang, Muhammad Usman, Ateeq ur Rehman Irshad, Mudassar Rashid, Amira Khattak

“…A multi-model approach was employed to address the research questions, which included Ordinary Least Squares Regression (OLS), various Spatial Models, Machine Learning Algorithms and Explainable Artificial Intelligence methods. …”
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On the results of testing some algorithms for calculating coagulation processes in dispersed systems by I. S. Afanasyev, B. A. Ashabokov

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Differentiation of the use of remote traffic research methods by A. А. Testeshev, V. D. Timohovets, T. G. Babich

“…The authors developed an algorithm for selecting a rational method of remote sensing of traffic for different spatial urban structures at micro-, mesoand macro-levels and considered it on the example of 14 urban Russian and foreign agglomerations. …”
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Spatial Downscaling of GRACE Groundwater Storage Based on DTW Distance Clustering and an Analysis of Its Driving Factors by Huazhu Xue, Hao Wang, Guotao Dong, Zhi Li

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An optimized spatial target trajectory prediction model for multi-sensor data fusion in air traffic management by Jian Dong, Yuan Xu, Rigeng Wu, Chengwang Xiao

“…With the evolution of air traffic safety management, the traditional single-sensor approach no longer meets the demands for spatial target surveillance. Consequently, there is increasing research interest in multi-sensor data fusion. …”
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A feature fusion network with spatial-temporal-enhanced strategy for the motor imagery of force intensity variation by Ankai Ying, Ankai Ying, Ankai Ying, Jinwang Lv, Jinwang Lv, Jinwang Lv, Junchen Huang, Junchen Huang, Junchen Huang, Tian Wang, Peixin Si, Peixin Si, Jiyu Zhang, Guokun Zuo, Guokun Zuo, Guokun Zuo, Guokun Zuo, Jialin Xu, Jialin Xu, Jialin Xu, Jialin Xu

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Prediction of the spatial distribution of vine weevil under climate change using multiple variable selection methods by Ga-Young Kim, Wang-Hee Lee

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Spatially Resolved River Monitoring by UAV-Borne 4D-Imaging Radar: Experiments and Preliminary Validation by Giordano Cicioni, Federico Alimenti, Timo Grebner, Julian Kanz, Ron Riekenbrauck, Christian Waldschmidt

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A new machine learning approach based on spatial fuzzy data correlation for recognizing sports activities by Xu Pengru, Zhou Junhui, Kausar Nasreen, Lin Chunlei, Lu Qianqian, Ghaderpour Ebrahim, Pamucar Dragan, Zadeh Ardashir M.

“…Therefore, the data analysis requires additional effort to reduce the overall problems in sports rehabilitation. The existing research difficulties are overcome by applying the proposed spatial data correlation with a support vector machine (SDC-SVM). …”
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Global air quality index prediction using integrated spatial observation data and geographics machine learning by Tania Septi Anggraini, Hitoshi Irie, Anjar Dimara Sakti, Ketut Wikantika

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Spatial transcriptomics and scRNA-seq: decoding tumor complexity and constructing prognostic models in colorectal cancer by Wei Song, Yatao Wang, Min Zhou, Fengqin Guo, Yanliang Liu

“…Methods scRNA-seq alongside spatial transcriptomics was employed to analyze the heterogeneity of tumor cells in CRC, the spatial distribution of tumor cells, and their interactions with the microenvironment. …”
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Predicting the Spatial Distribution of Geological Hazards in Southern Sichuan, China, Using Machine Learning and ArcGIS by Ruizhi Zhang, Dayong Zhang, Bo Shu, Yang Chen

“…Several machine learning models were evaluated, including random forest, XGBoost, and CatBoost, with model optimization performed using the Sparrow Search Algorithm (SSA) to enhance prediction accuracy. This study produced high-resolution susceptibility maps identifying high-risk zones, revealing a distinct spatial pattern characterized by a concentration of hazards in mountainous areas such as Pingshan County, Junlian County, and Gong County, while plains exhibited a relatively lower risk. …”
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IMPORT SUBSTITUTION OF GEODETIC HARDWARE AND SOFTWARE COMPLEXES AS A GUARANTEE OF SECURITY, RELIABILITY AND AVAILABILITY OF SPATIAL DATA by Aleksandr V. Boikov, Andrei G. Zimin, Viktor V. Yurov, Evgenii I. Starovoitov, Vitally A. Telets

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