Prediction of knee joint pain in Tai Chi practitioners: a cross-sectional machine learning approach by Yang Chen, Xiaojie Su, Fei Yao, Yushan Liu, Hua Xing, Yubin Ju, Zhiran Kang, Wuquan Sun, Lijun Yao, Li Gong

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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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A Two-Step Projected Iterative Algorithm for Tropospheric Water Vapor Tomography by Shangyi Liu, Kefei Zhang, Suqin Wu, Wenyuan Zhang, Longjiang Li, Moufeng Wan, Jiaqi Shi, Minghao Zhang, Andong Hu

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Improving Mountainous DSM Accuracy Through an Innovative Opposite-Side Radargrammetry Algorithm by Jian Wang, Huiming Chai, Xiaoshuai Li, Xiaolei Lv

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Spatial and Temporal Interplay Between Oceanic Circulation and Biological Production in Shaping Carbon Export Off the California Coast by M. Messié, C. L. Huffard, M. R. Stukel, H. A. Ruhl

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Algorytm — tożsamość — dylemat społeczny. Zjawisko algorytmizacji w serwisach wideo na żądanie by Dominik Kania

“…The possible influence of algorithms on human’s identity in streaming platforms’ universe is a main topic of this essay. …”
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A One-Stage HMDV Algorithm Applied in Multitarget Detection in SAR Images by Lei Pang, Weihe Huang, Fengli Zhang, Yinhong Song

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Motor imagery EEG signal classification using novel deep learning algorithm by Sathish Mathiyazhagan, M. S. Geetha Devasena

“…Abstract Electroencephalography (EEG) signal classification plays a critical role in various biomedical and cognitive research applications, including neurological disorder detection and cognitive state monitoring. …”
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Research on Cooperative Localization Method in Dynamic Networks by ZHANG Zhihua, SUN Bin, LI Bingchen, ZHOU Zhongfu, SHEN Feng

“…These circumstances can result in a decrease in the accuracy of cooperative localization algorithms or even cause them to malfunction. In order to address the above problems, this paper carries out the research on cooperative localization method, and proposes the filtering method of adaptive adjustment of observation error covariance matrix and the fusion of the federated filtering method, which enables the cooperative localization system to work normally in the case of the change of anchor nodes and ordinary nodes among mobile nodes, the disappearance or emergence of ranging values between nodes, and the random access and exit of nodes, etc. …”
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Variable Selection Algorithm for Explaining Anomalies in Real-World Regenerative Thermal Oxidizers by Min-Ji Seo, Myung-Ho Kim

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Research on neuromorphic vision sensor and its applications by Yongsheng SANG, Renhao LI, Yaoqian LI, Qiangwei WANG, Yao MAO

“…Neuromorphic vision sensor is a biologically inspired artificial neural system that mimics algorithmic behavior of biological vision systems,which has numerous advantages over standard vision sensors,such as high temporal resolution,low latency,low power,high dynamic range,etc.At first,a brief introduction to neuromorphic engineering,neuromorphic chips,and vision sensors was given.Then the main computing methods for neuromorphic vision were reviewed,including probability and statistics,spiking neural network and deep neural network.Finally,several kinds of applications based on neuromorphic vision sensors were given,such as simultaneous localization and mapping (SLAM),image reconstruction (IR),etc.A review of hardware,computing methods and applications for neuromorphic vision sensors was given,which provided a comprehensive reference for researchers.…”
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