DV-DETR: Improved UAV Aerial Small Target Detection Algorithm Based on RT-DETR by Xiaolong Wei, Ling Yin, Liangliang Zhang, Fei Wu

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Research on prediction algorithm of effluent quality and development of integrated control system for waste-water treatment by JianWun Lai

“…The present study presented a prediction algorithm and an Integrated Control System (ICS) to address the problems of conventional methods. …”
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CSCP-YOLO: A Lightweight and Efficient Algorithm for Real-Time Steel Surface Defect Detection by Chenglong Wang, Heng Wang, Yimin Jiang, Lei Yu, Xueting Wang

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Magnetic Source Detection Using an Array of Planar Hall Effect Sensors and Machine Learning Algorithms by Miki Vizel, Roger Alimi, Daniel Lahav, Moty Schultz, Asaf Grosz, Lior Klein

“…To address this, we employed the Levenberg–Marquardt Algorithm (LMA) as a deterministic optimization method to estimate the magnetic source’s position and parameters, as well as machine earning (ML) algorithms, which consist of a Fully Connected Neural Network (FCNN). …”
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Synthetic Data-Based Algorithm Selection for Medical Image Classification Under Limited Data Availability by Maxim Zhabinets, Benjamin Tyler, Martin Lukac, Shinobu Nagayama, Ferdinand Molnár, Michitaka Kameyama

“…The Algorithm selection approach improves performance by dynamically choosing the optimal Algorithm for each input instance. …”
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Nonlinear Unsteady Aerodynamics Reduced Order Model of Airfoils Based on Algorithm Fusion and Multifidelity Framework by Yan Shi, Zhiqiang Wan, Zhigang Wu, Chao Yang

“…In the process of modeling, firstly, a multifidelity model with NARX description provides a general intelligent algorithm framework for unsteady aerodynamics. Then, based on the separated flow theory, the correction equation from low-fidelity model to high-fidelity result is constructed, and the cuckoo algorithm based on chaos optimization is used to identify the parameters. …”
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Investigation of bending angle algorithm and path planning for puncture needles in transjugular intrahepatic portosystemic shunt by Qinmei Liao, Bing Li, Xihao Hu, Xiaoyun Huang, Jiacheng Guo, Yuanzhong Zhu, Wenjing He

“…The optimal bending angle of the puncture needle calculated by this algorithm was validated in Mimics software, successfully achieving path planning. …”
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A separation algorithm for satellite-based AIS received signals based on SSA and RobustICA by Jiansen ZHAO, Zhihao TAN, Haiyan DUAN, Xia LIU, Shengzheng WANG

“…The Hankel matrix of the single-channel AIS signal is processed by singular value decomposition and reconstructed by time series respectively, SSA is used to replace whitening pre-processing in traditional independent component analysis (ICA), and the optimal step size of each iteration of the separation matrix is calculated using the kurtosis contrast function to quickly obtain the optimal separation matrix.ResultsThe simulation results show that the signal mean squared error (SMSE) value of S-RICA is stable at about 1.5 when the signal length changes, while the SMSE of fast independent component analysis (FastICA) is very unstable. …”
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Evaluation of TOPSIS Algorithm for Multi-Criteria Handover in LEO Satellite Networks: A Sensitivity Analysis by Pascal Buhinyori Ngango, Marie-Line Lufua Binda, Michel Matalatala Tamasala, Pierre Sedi Nzakuna, Vincenzo Paciello, Angelo Kuti Lusala

“…The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is widely recognized as an effective multi-criteria decision-making algorithm for handover management in terrestrial cellular networks, especially in scenarios involving dynamic and multi-faceted criteria. …”
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A Lightweight Algorithm for Detection and Grading of Olive Ripeness Based on Improved YOLOv11n by Fengwu Zhu, Suyu Wang, Min Liu, Weijie Wang, Weizhi Feng

“…To address these limitations, this study proposes a lightweight algorithm for detection and grading of olive ripeness based on an Improved YOLOv11n framework. …”
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Automatic detection and classification of drill bit damage using deep learning and computer vision algorithms by Xiongwen Yang, Xiao Feng, Chris Cheng, Jiaqing Yu, Qing Zhang, Zilong Gao, Yang Liu, Bo Chen

“…The experimental results demonstrate that the proposed method significantly enhances the accuracy of bit damage detection and classification while also providing substantial improvements in processing speed and computational efficiency, offering a valuable tool for optimizing drilling operations and reducing costs.…”
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Research on Shale Oil Well Productivity Prediction Model Based on CNN-BiGRU Algorithm by Yuan Pan, Xuewei Liu, Fuchun Tian, Liyong Yang, Xiaoting Gou, Yunpeng Jia, Quan Wang, Yingxi Zhang

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Gene Selection Algorithms in a Single-Cell Gene Decision Space Based on Self-Information by Yan Fang, Yonghua Lin, Chuanbo Huang, Zhaowen Li

“…For gene expression data, the proposed self-information metric demonstrates superiority over other measures by accounting for both lower and upper approximations, thereby facilitating the selection of optimal gene subsets. Finally, gene selection algorithms within a single-cell gene decision space are developed based on the proposed self-information metric, and experiments conducted on 10 publicly available single-cell datasets indicate that the classification performance of the proposed algorithms can be enhanced through the selection of genes pertinent to classification. …”
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Improvement of SAM2 Algorithm Based on Kalman Filtering for Long-Term Video Object Segmentation by Jun Yin, Fei Wu, Hao Su, Peng Huang, Yuetong Qixuan

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Investigating the performance of random oversampling and genetic algorithm integration in meteorological drought forecasting with machine learning by Tahsin Baykal, Özlem Terzi, Gülsün Yıldırım, Emine Dilek Taylan

“…Therefore, this study aims to evaluate the effectiveness of machine learning methods for meteorological drought estimation and to integrate Random Oversampling (ROS) and Genetic Algorithm (GA) methods to improve estimation accuracy. …”
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An Analytic Policy Gradient-Based Deep Reinforcement Learning Motion Cueing Algorithm for Driving Simulators by Xiaowei Huang, Xuhua Shi, Peiyao Wang, Hongzan Xu, Xiaojun Tang, Gaoran Zhang

“…Unlike the online optimization employed in MPC, this algorithm as an offline optimization method, providing substantial computational advantages when integrated into the driving simulator. …”
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Evaluating the generalisability of region-naïve machine learning algorithms for the identification of epilepsy in low-resource settings. by Ioana Duta, Symon M Kariuki, Anthony K Ngugi, Angelina Kakooza Mwesige, Honorati Masanja, Daniel M Mwanga, Seth Owusu-Agyei, Ryan Wagner, J Helen Cross, Josemir W Sander, Charles R Newton, Arjune Sen, Gabriel Davis Jones

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Improved adaptive FPGA dark channel prior dehazing algorithm for edge applications in agricultural scenarios by Qunpeng Gao, Baiquan Qian, Fengqi Yu, Liye Chen, Peng Gao, Jiatao Wu, Zonghong Li, Weixing Wang, C.V. Jiaxing Xie

“…The experimental results show that the optimized algorithm maintains superior dehazing quality (outperforming other dehazing algorithms in the field on metrics including PSNR, SSIM, and information entropy).…”
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Evaluation of genomic mating approach based on genetic algorithms for long-term selection in Huaxi cattle by Yuanqing Wang, Bo Zhu, Jing Wang, Lupei Zhang, Lingyang Xu, Yan Chen, Zezhao Wang, Huijiang Gao, Junya Li, Xue Gao

“…Results In this study, we constructed a simulated population based on the real genotypes of Huaxi cattle, where five generations of simulated breeding were carried out using the genomic optimal contribution selection (GOCS), genetic algorithms strategy and three traditional mating strategies. …”
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Comprehensive Comparison and Validation of Forest Disturbance Monitoring Algorithms Based on Landsat Time Series in China by Yunjian Liang, Rong Shang, Jing M. Chen, Xudong Lin, Peng Li, Ziyi Yang, Lingyun Fan, Shengwei Xu, Yingzheng Lin, Yao Chen

“…When considering different forest disturbance types, COLD achieved the highest accuracies for Fire, Harvest, and Other disturbances, while CCDC was most accurate for Forestation. These findings highlight the necessity of region-specific calibration and parameter optimization tailored to specific disturbance types to improve forest disturbance monitoring accuracy, and also provide a solid foundation for future studies on algorithm modifications and ensembles.…”
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