Research on the Characteristic Identification and Multidimensional Dynamic Evolution of Urban–Rural Fringe in Harbin, China by Jing Ning, Haozhi Ma, Yu Sun, Ning Wang, Mengqiu Wang

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Real-Time Fault Diagnosis of Mooring Chain Jack Hydraulic System Based on Multi-Scale Feature Fusion Under Diverse Operating Conditions by Yujia Liu, Wenhua Li, Haoran Ye, Shanying Lin, Lei Hong

“…Under complex and dynamic marine operating conditions, different severity faults in the CJ hydraulic system display distinct time-scale characteristics. Hence, this paper proposes a real-time fault diagnosis method of the CJ hydraulic system based on multi-scale feature fusion. …”
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Critical energy distribution and fracture characteristics of heterogeneous rock under splitting condition by Hongguang JI, Zhen FU, Yuezheng ZHANG, Chunrui ZHANG, Dongsheng CHEN

“…Through quantitative calculation, the study obtained the spatial variability characteristics of the deformation of granite. …”
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A multi-time scale charging load forecasting method for electric private cars based on an improved gravity model considering stochastic charging behavior by Xiaohong Dong, Ruize Wang, Xiaodan Yu

“…Therefore, a multi-time scale charging load forecasting method for EPCs based on an improved gravity model that considers stochastic charging behavior is proposed. …”
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R-SABMNet: A YOLOv8-Based Model for Oriented SAR Ship Detection with Spatial Adaptive Aggregation by Xiaoting Li, Wei Duan, Xikai Fu, Xiaolei Lv

“…However, ships in SAR images exhibit various characteristics including complex land scattering interference, variable scales, and dense spatial arrangements. …”
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OCTOPUS: Across-social network user identification via multi-category spatio-temporal trajectories by Yating Qu, Ling Xing, Kaikai Deng, Honghai Wu, Yue Ling, Deshun Jia

“…However, the integration of multi-category user data is constrained by the data sparsity, fragmentation, and asymmetry characteristics, resulting in a limitation to the accuracy of user identification. …”
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Multi-omics Analysis of Histone-related Genes in Osteosarcoma: A Multidimensional Integrated Study Revealing Drug Sensitivity and Immune Microenvironment Characteristics by Yang Yang MD, Xinqiao Tang MD, Zhong Liu MD

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Study on Multi-Scenario Rain-Flood Disturbance Simulation and Resilient Blue-Green Space Optimization in the Pearl River Delta by Wei Dai, Yang Tan

“…Firstly, based on an analysis of the current status quo of blue-green space in the Pearl River Delta and the identification of potential areas at risk from rain and floods, this paper elucidates that resilient blue-green space in the Pearl River Delta should be guided by a systematic, bottom-line, and forward-looking orientation while considering spatial characteristics such as multi-scale network connectivity, redundancy and diversity/multi-functionality. …”
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Simulating Land Use and Evaluating Spatial Patterns in Wuhan Under Multiple Climate Scenarios: An Integrated SD-PLUS-FD Modeling Approach by Hao Yuan, Xinyu Li, Meichen Ding, Guoqiang Shen, Mengyuan Xu

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Predicting characteristics of bursty bulk flows in Earth’s plasma sheet using machine learning techniques by Xuedong Feng, Jian Yang, Jacob Bortnik, Chih-Ping Wang, Jiang Liu, Jiang Liu

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Data Flow Forecasting for Smart Grid Based on Multi-Verse Expansion Evolution Physical–Social Fusion Network by Kun Wang, Bentao Hu, Jiahao Zhang, Ruqi Zhang, Hongshuo Zhang, Sunxuan Zhang, Xiaomei Chen

“…To tackle the challenges of low forecasting accuracy and high error rates caused by the long sequences, nonlinearity, and multi-scale and non-stationary characteristics of financial flow data, a forecasting model based on multi-verse expansion evolution (MVE²) and spatial–temporal fusion network (STFN) is proposed. …”
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A novel YOLOv11-Driven deep learning algorithm for UAV multispectral oil spill detection in Inland lakes by Yu Zhang, Jian Xing, Weida Chen, Haitao Wang, Bingyu Shi, Yang Song, Xiaoou Huang, Zihan Jiang

“…Our model integrates the self-developed ADHF module—which fuses multi-scale features using an adaptive diffusion-based hierarchical feature aggregation strategy—with the SimAM attention module to enhance key feature extraction. …”
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Research on Spatiotemporal Evolution Characteristics and Driving Mechanisms of Agricultural Drought in the Yellow River Basin by JU Yongsheng, WEI Yong, HU Anlong, LI Huiyong, GUO Aijun

“…Therefore, this paper took the Yellow River Basin in arid regions, semi-arid regions, and the transitional zone between humid and semi-humid regions as an example and used trend test, run length theory, and standard soil index (SSI) methods to reveal the spatiotemporal distribution characteristics and evolution laws of multi-scale agricultural drought. 17 extreme climate indexes and analysis of variance (ANOVA) methods were used to quantitatively reveal the impact of droughts. …”
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Fault Diagnosis Method for Main Pump Motor Shielding Sleeve Based on Attention Mechanism and Multi-Source Data Fusion by Nengqing Liu, Xuewei Xiang, Hui Li, Zhi Chen, Peng Jiang

“…This method takes the measurable data (torque, rotational speed, voltage, and current) of the main pump motor operation as input signals. First, a multi-scale convolutional neural network based on the attention mechanism (AM-MSCNN) is established to extract rich multi-scale features of the data, and the spatial and channel attention mechanisms are used to fuse the multi-scale features. …”
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Spatio-Temporal Characteristics and Driving Forces of Landscape Ecological Risks in Highly Urbanized Areas: A Case Study of Suzhou City by Lingyue LU, Dawei SHAO, Dianming WU

“…The formation mechanism, spatio-temporal heterogeneous driving effect and scale response law of LER in highly urbanized areas still need to be systematically explored.MethodsUtilizing multi-source data spanning the period from 1995 to 2020, including Landsat TM/ETM imagery, digital elevation model (DEM) and NASA datasets, this research focuses on exploring the characteristics of spatio-temporal variability of LER and corresponding drivers in Suzhou at the optimal scale, utilizing the LER evaluation model and the geographically and temporally weighted regression (GTWR) framework.Results1) The landscape pattern of Suzhou City is scale-dependent, with significant variations in the landscape pattern index for each land type at the optimal scale. …”
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PatchOut: A novel patch-free approach based on a transformer-CNN hybrid framework for fine-grained land-cover classification on large-scale airborne hyperspectral images by Renjie Ji, Kun Tan, Xue Wang, Shuwei Tang, Jin Sun, Chao Niu, Chen Pan

“…For the encoder module, we introduce a computationally efficient reduced Transformer module integrated with convolutional neural network (CNN), to leverage their complementary strengths for long-range and local feature extraction, respectively. A multi-scale spatial-spectral feature fusion (MSSSFF) module is also proposed to amalgamate the characteristics of different levels from the encoder, which enhances the overall feature representation. …”
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Unsupervised Multimodal UAV Image Registration via Style Transfer and Cascade Network by Xiaoye Bi, Rongkai Qie, Chengyang Tao, Zhaoxiang Zhang, Yuelei Xu

“…The architecture integrates a cross-modal style transfer network (CSTNet) that transforms visible images into pseudo-infrared representations to unify modality characteristics, and a multi-scale cascaded registration network (MCRNet) that performs progressive spatial alignment across multiple resolution scales using diffeomorphic deformation modeling to ensure smooth and invertible transformations. …”
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Spatiotemporal Analysis of Drought and Its Driving Factors in the Yellow River Basin Based on a Standardized Precipitation Evapotranspiration Index by Chong Wei, Danning Su, Dongbao Zhao, Yixuan Li, Junwei He, Zhiguo Wang, Lianhai Cao, Huicong Jia

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Enhancing Large-Area DEM modeling of GF-7 stereo imagery: Integrating ICESat-2 data with Multi-characteristic constraint filtering and terrain matching correction by Kai Chen, Wen Dai, Fayuan Li, Sijin Li, Chun Wang

“…To tackle this issue, this paper proposes a method aimed at enhancing the accuracy of the BA process. Initially, the multi-characteristic constraint is used to filter the ICESat-2 ATL08 product to obtain control points and check points. …”
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YOLO-SUMAS: Improved Printed Circuit Board Defect Detection and Identification Research Based on YOLOv8 by Ying Tang, Runhao Liu, Sheng Wang

“…Aiming at the demand for defect detection accuracy and efficiency under the trend of high-density and integration in printed circuit board (PCB) manufacturing, this paper proposes an improved YOLOv8n model (YOLO-SUMAS), which enhances detection performance through multi-module collaborative optimization. The model introduces the SCSA attention mechanism, which improves the feature expression capability through spatial and channel synergistic attention; adopts the Unified-IoU loss function, combined with the dynamic bounding box scaling and bi-directional weight allocation strategy, to optimize the accuracy of high-quality target localization; integrates the MobileNetV4 lightweight architecture and its MobileMQA attention module, which reduces the computational complexity and improves the inference speed; and combines ASF-SDI Neck structure with weighted bi-directional feature pyramid and multi-level semantic detail fusion to strengthen small target detection capability. …”
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