Blind Direction-of-Arrival Estimation with Uniform Circular Array in Presence of Mutual Coupling by Song Liu, Lisheng Yang, Shizhong Yang, Qingping Jiang, Haowei Wu

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Contribution of Greening and High-Albedo Coatings to Improvements in the Thermal Environment in Complex Urban Areas by Bonggeun Song, Kyunghun Park

“…The RMSE deviation of the predicted and actual field temperature values was 3–6°C; however, the explanatory power was as high as 60%. …”
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MAD-RAPPEL: Mobility Aware Data Replacement And Prefetching Policy Enrooted LBS by Ajay K. Gupta, Udai Shanker

“…The cache replacement and invalidation module uses the next location prediction algorithm by the application of the mobility Markov model on mobile user’s trajectories. …”
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Integration of multimodal imaging data with machine learning for improved diagnosis and prognosis in neuroimaging by Saurabh Bhattacharya, Sashikanta Prusty, Sanjay P. Pande, Monali Gulhane, Santosh H. Lavate, Nitin Rakesh, Saravanan Veerasamy

“…This work introduces a novel hybrid deep learning method combining CNN, GRU, and a Dynamic Cross-Modality Attention Module to help more efficiently blend spatial and temporal brain data. Through working around issues with current multimodal fusion techniques, our approach increases the accuracy and readability of diagnoses.MethodsUtilizing CNNs and models of temporal dynamics from fMRI connection measures utilizing GRUs, the proposed approach extracts spatial characteristics from sMRI. …”
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Landscape Pattern Changes and Ecological Vulnerability Assessment in Mountainous Regions: A Multi-Scale Analysis of Heishui County, Southwest China by Weiqi Gu, Hong Fu, Wen Jin

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Quantitative inversion of integrated hyperspectral and optical remote sensing images to monitor dust distribution in open pit mines by Simin Feng, Jin Zhang

“…The ZY1-02E satellite demonstrates high feasibility and accuracy in AOD inversion, and the results obtained effectively illustrate the spatial distribution of dust pollution. This highlights the potential for aerosol remote sensing inversion using hyperspectral satellite data, providing effective means for regional dust monitoring, and a scientific basis for subsequent development of dust reduction measures.…”
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Classification and spectrum optimization method of grease based on infrared spectrum by Xin Feng, Yanqiu Xia, Peiyuan Xie, Xiaohe Li

“…The results show that this machine learning method can effectively eliminate the interference fringes in the IR spectrum, and complete the feature selection and dimensionality reduction of the high-dimensional spectral data. The 63 kinds of greases exhibit spatial clustering under certain IR spectrum recognition spectral bands, which are linked to characteristic peaks of lubricating greases and improve the recognition accuracy of these greases. …”
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Residual attention based multi-label learning for apple leaf disease identification by Changjian Zhou, Zhenyuan Zhao, Wenzhuo Chen, Yuquan Feng, Jia Song, Wensheng Xiang

“…Built upon an attention based multi-label learning framework, the channel and spatial attention mechanisms are investigated and embedded in residual network for multi-label disease prediction, which takes advantage of channel-wise and spatial-wise attention weights. …”
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An Improved Wavelet Soft-Threshold Function Integrated with SVMD Dual-Parameter Joint Denoising for Ancient Building Deformation Monitoring by Jiaxing Zhao, Houzeng Han, Yang Deng, Youqiang Dong, Jian Wang, Wenjin Chen

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How does high temperature weather affect tourists' nature landscape perception and emotions? A machine learning analysis of Wuyishan City, China. by Cuicui Ye, Zhengyan Chen, Zheng Ding

“…The results indicate: (1) Emotion prediction and spatial analysis reveal a significant increase in the proportion of negative emotions under high-temperature conditions, reaching 30.1%, with negative emotion hotspots concentrated in the downtown area, whereas, under non-high temperature conditions, negative emotions accounted for 14.1%, with a more uniform spatial distribution. (2) Under non-high temperature conditions, the four most influential factors on tourists' emotions were Color complexity (0.73), Visual entropy (0.71), Greenness (0.68), and Aquatic rate (0.6). …”
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A novel framework for multi-layer soil moisture estimation with high spatio-temporal resolution based on data fusion and automated machine learning by Shenglin Li, Yang Han, Caixia Li, Jinglei Wang

“…Initially, we generated seamless 30 m resolution metrics, including the normalized difference vegetation index (NDVI), land surface temperature (LST), and surface albedo, by employing the modified neighborhood similar pixel interpolator (MNSPI) in conjunction with the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM). …”
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Infrastructure Lifecycle Corrosion Management Using AI Analytics and Digital Twins by Bilal Ayyub, Karl Stambaugh

“…The non-parametric analysis of corrosion data is demonstrated to provide insights into spatial and temporal variations, helping in predictive modeling and decision-making. …”
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Multi-modal action recognition via advanced image fusion techniques for cyber-physical systems by Zaiyong Shou, Daoyu Zhu

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Symbiotic relationship and attribution analysis of digitalization in agriculture, rural, and finance: evidence from China by Xiaojuan Yang, Kai Liu, Weiwei Li, Weiwei Li

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Revisiting the distribution and total amount of nitrogen fixation across the Kuroshio by Takuya Sato, Takuhei Shiozaki, Shota Takino, Kiyotaka Hidaka, Tamaha Yamaguchi, Daiki Ito, Daisuke Ambe, Sayaka Sogawa, Takashi Setou, Yugo Shimizu, Taketoshi Kodama, Kazutaka Takahashi

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Mapping the Cerrado–Amazon Transition Using PlanetScope–Sentinel Data Fusion and a U-Net Deep Learning Framework by Chuanze Li, Angela Harris, Beatriz Schwantes Marimon, Ben Hur Marimon Junior, Matthew Dennis, Polyanna da Conceição Bispo

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Digital twin-enabled post-disaster damage and recovery monitoring with deep learning: leveraging transfer learning, attention mechanisms, and explainable AI by Umut Lagap, Saman Ghaffarian

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Review of flow instability in gas-turbine compression system by Jingyi Zeng, Feng Liu

“…Future directions are proposed, emphasizing the development of unified theoretical models, accelerated numerical methods, and full-annulus experiments to enhance stall prediction and active control strategies.…”
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Seamless global daily soil moisture mapping using deep learning based spatiotemporal fusion by Menghui Jiang, Tian Qiu, Ting Wang, Chao Zeng, Boxuan Zhang, Huanfeng Shen

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Efficient remote sensing image classification using the novel STConvNeXt convolutional network by Bo Liu, Chenmei Zhan, Cheng Guo, Xiaobo Liu, Shufen Ruan

“…Ablation studies further confirm the effectiveness of each module design, particularly demonstrating that the model maintains excellent classification accuracy despite a substantial reduction in parameters.…”
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