ONE TYPICAL EXTREMUM IN ELECTRICAL PROBLEMS by V. I. Goroshko, T. E. Shukovskaya

“…The aim of this work is to attract attention of teachers, scientific personnel, engineers and students to one peculiarity of extremum seeking in different electrical problems. This feature lies in the fact that in many parts of electrical engineering extremum seeking comes to analysis one and the same mathematical structure (T-structure), but differences lie only in many symbols (designation).In one problems this structure appear in finale, the most simple form, but in others – T-structure is “veiled”, and as a rule  we need  elementary algebraic transformation to detect it.Taking into account high frequency of this structure appearing in electrical problems, in the first part of article the authors  carried out the investigation of extremum characteristics of T-structure and show the results in easy algorithms. …”
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Roadside Perception System Based on LiDAR and Millimeter-wave Radar Fusion in Mining Area by JIANG Liangyu

“…The algorithm was tested in Shenyan Xiwan mining area and the result demonstrated that the motion feature of objects at intersection was detected effectively.…”
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Artificial intelligence enhanced electrochemical immunoassay for staphylococcal enterotoxin B by Yuliang Zhao, Tingting Sun, Huawei Zhang, Chao Lian, Zhongpeng Zhao, Yongqiang Jiang, Huiqi Duan, Yuhao Ren, Xuyang Sun, Zhikun Zhan, Mingyue Qu, Shaolong Chen

“…Lastly, a multivariate linear regression algorithm is employed to effectively train and fit the extracted feature data. …”
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Radiation hematologic toxicity prediction in rectal cancer: a comparative radiomics-based study on CT image and dose map by Yingpeng Liu, Liping Guo, Yi Wang, Qingtao Xu, Jingfeng Zhang, Xianyun Meng

“…Then, the radiomic features of the clinical target volume (CTV) in the radiotherapy were extracted, and the least absolute shrinkage and selection operator (LASSO) algorithm was used for feature dimension deduction; three classifiers, that is, support vector machine (SVM) (rbf kernel), random forest, and CatBoost, were used to construct the HT classification model in rectal cancer patients. …”
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Research on Visual SLAM Navigation Techniques for Dynamic Environments by Tongjun Wang, Peijun Zhao

“…Aiming at the inconsistency between the direction of dynamic objects and static background optical flow, this method adopts a high-real-time dynamic region mask detection algorithm to eliminate the feature points in the dynamic region mask, remove the camera motion optical flow according to the original feature information, and then cluster the optical flow amplitude of dynamic objects so as to realize the dynamic region mask detection and eliminate the dynamic signpost points combined with the polar geometric constraints. …”
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Robust Extrinsic Calibration for LiDAR-Camera Systems via Depth and Height Complementary Supervision Network by Chen Yaqing, Wang Huaming

“…Additionally, we introduce an Attention-based Fusion Module (AFM) for efficient feature fusion. Furthermore, we incorporate time compensation and iterative calibration techniques to further enhance the robustness of the algorithm in handling initial alignment errors. …”
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Development and validation of a carotid plaque risk prediction model for coal miners by Yi-Chun Li, Yi-Chun Li, Yi-Chun Li, Tie-Ru Zhang, Tie-Ru Zhang, Tie-Ru Zhang, Fan Zhang, Fan Zhang, Fan Zhang, Chao-Qun Cui, Chao-Qun Cui, Chao-Qun Cui, Yu-Tong Yang, Yu-Tong Yang, Yu-Tong Yang, Jian-Guang Hao, Jian-Ru Wang, Jiao Wu, Hai-Wang Gao, Ying-Bo Liu, Ming-Zhong Luo, Li-Jian Lei, Li-Jian Lei, Li-Jian Lei

“…Finally, a nomogram was plotted to increase its interpretability.ResultsThe XGBoost algorithm demonstrated superior performance in feature screening, identifying the top five features as follows: age, systolic blood pressure, low-density lipoprotein cholesterol, white blood cell count, and body mass index (BMI). …”
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Adaptive respiratory muscle trainer based on hybrid nanogenerator sensor and artificial intelligence by Ziao Xue, Puchuan Tan, Jiangtao Xue, Yuan Xi, Minghao Liu, Yang Zou, Qiang Zheng, Zhou Li, Yuxiang Wu

“…With the help of the principal component analysis algorithm, features related to the fatigue state of muscles were extracted from the collected signals, and the accuracy rate can reach 94.4%. …”
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Identifying common disease trajectories of Alzheimer’s disease with electronic health recordsResearch in context by Mingzhou Fu, Sriram Sankararaman, Bogdan Pasaniuc, Keith Vossel, Timothy S. Chang

“…Causal inferences were explored using the Greedy Equivalence Search algorithm. Validation in the UCHDW included association tests and comparison to control groups. …”
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Inter-annual changes and growth trends mapping of mangrove using Landsat time series imagery by Xiaohui Huang, Yingchun Fu, Hu Ding, Guoan Tang, Peifeng Ma, Liangyun Liu, Yufei Xue, Shuting Wu, Ye Chen

“…To facilitate long-term mapping of mangroves, the Continuous Change Detection and Classification (CCDC) algorithm was utilized on the Google Earth Engine platform (GEE). …”
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Aerial image segmentation of embankment dams based on multispectral remote sensing: a case study in the Belo Monte Hydroelectric Complex, Pará, Brazil by Carlos André de Mattos Teixeira, Thabatta Moreira Alves de Araujo, Evelin Cardoso, Marcos Antonio Costantin Filho, João Weyl Costa, Carlos Renato Lisboa Frances

“…A comprehensive feature engineering and ranking approach is presented to select the most descriptive features that represent the four dataset classes. …”
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WebShield 5.0: Harnessing AI and NLP to combat web threats in Industry 5.0 by Priyanka Verma, Donna O’Shea, Thomas Newe, Ankit Vidyarthi, Deepak Gupta, Jabir Ali, Hamad Aldawsari, John G. Breslin

“…By combining multimodal data and utilizing the Mayfly optimization algorithm for feature selection, IM carries out a thorough analysis for efficient web-based attack detection. …”
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GGSYOLOv5: Flame recognition method in complex scenes based on deep learning. by Fucai Sun, Liping Du, Yantao Dai

“…Moreover, the algorithm is deployed in the Jetson Nano embedded development board to build the flame detection system.…”
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Physical Activity Recognition Utilizing the Built-In Kinematic Sensors of a Smartphone by Yi He, Ye Li

“…We used a combined algorithm of Fisher's discriminant ratio criterion and J 3 criterion for feature selection. …”
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A machine learning based radiomics approach for predicting No. 14v station lymph node metastasis in gastric cancer by Tingting Ma, Tingting Ma, Tingting Ma, Tingting Ma, Tingting Ma, Mengran Zhao, Mengran Zhao, Mengran Zhao, Mengran Zhao, Mengran Zhao, Xiangli Li, Xiangchao Song, Xiangchao Song, Xiangchao Song, Xiangchao Song, Lingwei Wang, Lingwei Wang, Lingwei Wang, Lingwei Wang, Zhaoxiang Ye, Zhaoxiang Ye, Zhaoxiang Ye, Zhaoxiang Ye

“…A total of 1,316 radiomics feature were extracted from portal venous phase images of CECT. …”
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Radiomic study on preoperative multi‐modal magnetic resonance images identifies IDH‐mutant TERT promoter‐mutant gliomas by Haoyu Wang, Shuxin Zhang, Xiang Xing, Qiang Yue, Wentao Feng, Siliang Chen, Jun Zhang, Dan Xie, Ni Chen, Yanhui Liu

“…Conclusions An accurate diagnostic model was constructed for detecting IDHmut pTERTmut gliomas using multimodal radiomic features. …”
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Identification and Validation of Aging Related Genes Signature in Chronic Obstructive Pulmonary Disease by Tian-Tian Li, Hong-Yan Bai, Jing-Hong Zhang, Xiu-He Kang, Yi-Qing Qu

“…The weighted gene co-expression network analysis (WGCNA) constructes co-expression modules and detect COPD-related modules. The least absolute shrinkage and selection operator (LASSO) and the support vector machine recursive feature elimination (SVM-RFE) algorithms were chosen to identify the hub genes and the diagnostic ability. …”
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Research on power data security full-link monitoring technology based on alternative evolutionary graph neural architecture search and multimodal data fusion by Zhenwan Zou, Bin Wang, Tao Chen, Jia Chen

“…By using Particle Swarm Optimization-Genetic Algorithm (PSO-GA) for optimal architecture search and combining the dynamic adaptability of Deep Q-Network (DQN) algorithm, this method can automatically identify the most suitable GNN architecture for power data monitoring, thereby improving the adaptive detection and defense efficiency of the system. …”
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Deep Learning-Based Fault Diagnosis via Multisensor-Aware Data for Incipient Inter-Turn Short Circuits (ITSC) in Wind Turbine Generators by Qinglong Wang, Shihao Cui, Entuo Li, Jianhua Du, Na Li, Jie Sun

“…Our approach is rigorously evaluated using metrics such as confusion matrices, accuracy, recall, average precision (AP), mean average precision (mAP), hypothesis testing, and feature visualization. The experimental results demonstrate that deep learning models outperform machine learning algorithms in terms of precision and stability, achieving an mAP of 99.25% in fault identification, with three-phase current signals emerging as the most reliable indicator of generator faults compared to vibration and electromagnetic data. …”
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An improved hybrid approach involving deep learning for urban greening tree species classification with Pléiades Neo 4 imagery—A case study from Nanjing, Eastern China by Min Sun, Stephane G.P. Debulois, Zhengnan Zhang, Xiaolei Cui, Zhili Chen, Mingshi Li

“…We compared deep learning (DL)-based shadow detection methods with classical index methods in urban green spaces to identify shaded vegetation areas, with the optimal method being selected for subsequent use. …”
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