SCL-YOLOv11: A Lightweight Object Detection Network for Low-Illumination Environments by Shulong Zhuo, Hao Bai, Lifeng Jiang, Xiaojian Zhou, Xu Duan, Yiqun Ma, Zihan Zhou

“…Experimental results on the ExDark dataset demonstrate that the proposed algorithm achieves 67.6% mAP@0.5 and 42.4% mAP@0.5:0.95, while reducing parameter count by 38.5% and computational cost by 25.4%. …”
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Projecting Forest Fire Probability in South Korea Under Climate Change, Population, and Forest Management Scenarios Using AI & Process-Based Hybrid Model (FLAM-Net) by Hyun-Woo Jo, Myoungsoo Won, Florian Kraxner, Seong Woo Jeon, Yowhan Son, Andrey Krasovskiy, Woo-Kyun Lee

“…Enhancements included improving backpropagation for optimization and introducing algorithms for national-specific fire ignition dynamics. …”
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Enhanced Rapid Autofocus Back-Projection for PBSAR Based on the GEO Satellite by Te Zhao, Jun Wang, Zuhan Cheng, Ziqian Huang, Jiaqi Song

“…Conventional autofocusing algorithms operate under the assumption that measurement errors primarily perturb phase components while exerting negligible influence on signal envelopes. …”
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Deep Q-Learning-Based Resource Management in IRS-Assisted VLC Systems by Ahmed Al Hammadi, Lina Bariah, Sami Muhaidat, Mahmoud Al-Qutayri, Paschalis C. Sofotasios, Merouane Debbah

“…Moreover, the synergy between the MPF and the DQL algorithms is investigated. To this end, we demonstrate that the MPF algorithm maximizes the fairness amongst the users while the DQL algorithm maximizes the overall SE and improves the robustness against the noise. …”
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Nitrous oxide prediction through machine learning and field-based experimentation: A novel strategy for data-driven insights by Muhammad Hassan, Khabat Khosravi, Travis J. Esau, Gurjit S. Randhawa, Aitazaz A. Farooque, Seyyed Ebrahim Hashemi Garmdareh, Yulin Hu, Nauman Yaqoob, Asad T. Jappa

“…Feature selection and optimization of input scenarios were achieved using a combination of particle swarm optimization (PSO) and manual methods. …”
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Application of Quantum Key Distribution to Enhance Data Security in Agrotechnical Monitoring Systems Using UAVs by Makhabbat Bakyt, Luigi La Spada, Nida Zeeshan, Khuralay Moldamurat, Sabyrzhan Atanov

“…The QKD framework is optimized for real-time operations through adaptive key generation and energy-efficient hardware, alongside Lempel–Ziv–Welch (LZW) compression to improve the bandwidth efficiency. …”
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A Constant False Alarm Rate Detection Method for Sonar Imagery Targets Based on Segmented Ordered Weighting by Wankai Na, Haisen Li, Jian Wang, Jiani Wen, Tianyao Xing, Yuxia Hou

“…This hierarchical framework can significantly improve computational efficiency while reducing the FAR, thus enabling the practical implementation of advanced, computationally intensive CFAR detection methods in real-time target detection in sonar imagery. …”
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Parts-per-quadrillion level gas molecule detection: CO-LITES sensing by Haiyue Sun, Shunda Qiao, Ying He, Xiaorong Sun, Yufei Ma

“…The artificial fish swarm algorithm auto-designed multi-pass cell (MPC) with double helix pattern, and the polymer modified round-head quartz tuning fork (QTF) with low-resonant frequency (f 0) were adopted to improve the gas absorption and QTF’s detection ability. …”
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Development of an interpretable machine learning model based on CT radiomics for the prediction of post acute pancreatitis diabetes mellitus by Xiyao Wan, Yuan Wang, Ziyi Liu, Ziyan Liu, Shuting Zhong, Xiaohua Huang

“…The radiomics model was developed based on the optimal features retained after dimensionality reduction, utilizing the extreme gradient boosting (XGBoost) algorithm. …”
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Evaluation of the quality of depression-related information on Chinese websites and video platforms: a cross-sectional comparative analysis by YueDong Chen, Jia Yin, YuKe Ding, ChangYu Wang, JiaXin Zhu, Lu Niu

“…In addition, the platform needs to prioritize optimizing the algorithm of recommendations and present real high-quality health information to the audience.…”
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Utilization of Neural Network in the Diagnosis of Pes Planus and Pes Cavus with a Smartphone Camera by Samir Ghandour MD, Anton Lebedev BS, Wei Shao Tung BS, Konstantin Semianov BS, Artem Semyanov MS, Daniel Guss MD, MBA, Gregory R. Waryasz MD, John Y. Kwon MD, Christopher W. DiGiovanni MD, Soheil Ashkani-Esfahani MD, Lorena Bejarano-Pineda MD

“…Category: Midfoot/Forefoot Introduction/Purpose: Pes Planus (flatfoot) and Pes Cavus (high arch) are common foot deformities requiring clinical assessment and radiographic imaging for diagnosis and subsequent management. While effective, traditional diagnostic methods pose limitations such as cost, radiation exposure, and accessibility, particularly in underserved areas. …”
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YOLO-RDM: Innovative Detection Methods for Eggplants and Stems in Complex Natural Environment by Qin Liu, Zhibin Zhou, Lu Xiong, Meilian Lu, Jingwen Ouyang

“…Finally, the loss function is substituted with the MPDIoU loss, optimizing the bounding box regression algorithm and enhancing convergence speed and regression accuracy. …”
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Proposal of Low-Speed Sensorless Control of IPMSM Using a Two-Interval Six-Segment High-Frequency Injection Method with DC-Link Current Sensing by Daniel Konvicny, Pavol Makys, Alex Franko

“…The dual-period structure, termed the two-interval six-segment high-frequency injection, allows for more precise current measurement during the signal injection period while maintaining optimal motor control during the field-oriented control period. …”
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ASHM-YOLOv9: A Detection Model for Strawberry in Greenhouses at Multiple Stages by Yan Mo, Shaowei Bai, Wei Chen

“…We enhanced the YOLOv9 model by introducing the Alterable Kernel Convolution (AKConv) to improve the recognition efficiency while ensuring precision. …”
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Graph Neural Network Aided Detection for the Multi-User Multi-Dimensional Index Modulated Uplink by Xinyu Feng, Mohammed El-Hajjar, Chao Xu, Lajos Hanzo

“…To further reduce the detection complexity and improve the detection performance, we propose a pair of Graph Neural Network (GNN) based detectors, which rely on the orthogonal AMP (OAMP) and on the EP algorithm, which we refer to as the GNN-AMP and GEPNet detectors, respectively. …”
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Application of collaborative innovation between the logical brain and the associative brain in oil and gas gathering and transportation systems by Jing GONG, Siheng SHEN, Daqian LIU, Qi KANG, Shangfei SONG, Haihao WU, Bohui SHI

“…Traditional simplified analytical methods struggle to cope with dynamic uncertainties, while existing data-driven algorithms are confronted with the dual challenges of lacking interpretability and insufficient robustness. …”
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Revolutionizing Supply Chain Management With AI: A Path to Efficiency and Sustainability by Kassem Danach, Ali El Dirani, Hassan Rkein

“…Through an in-depth analysis of various AI techniques—such as machine learning, predictive analytics, and optimization algorithms—this study offers novel insights into their applicability in solving complex supply chain problems like demand forecasting, inventory management, and logistics optimization. …”
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Privacy-preserving method for face recognition based on homomorphic encryption. by Zhigang Song, Gong Wang, Wenqin Yang, Yunliang Li, Yinsheng Yu, Zeli Wang, Xianghan Zheng, Yang Yang

“…By grouping similar faces into clusters through clustering analysis, the efficiency of searching encrypted feature values is significantly improved. Performance analysis indicates that the HE_FaceNet framework successfully protects facial data privacy while maintaining high recognition accuracy, and the optimization scheme demonstrates high accuracy and significant computational efficiency across facial datasets of varying sizes.…”
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ADAM-DETR: an intelligent rice disease detection method based on adaptive multi-scale feature fusion by Hanyu Song, Xinyue Huang, Ziqiang Wang, Jianwei Hu, Huasheng Zhang, Hui Yang

“…The algorithm requires only 42.8G FLOPs with 14.3M parameters, achieving an optimal balance between accuracy and efficiency, providing an effective technical solution for disease monitoring in smart agriculture.…”
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An RTM-Driven Machine Learning Approach for Estimating High-Resolution FAPAR From LANDSAT 5/7/8/9 Surface Reflectance by Guodong Zhang, Gaofei Yin, Yi Zhang, Jiangchuan Hu, Zongyan Li, Changjing Wang, Dujuan Ma, Jiangliu Xie

“…This study synergized the strengths of RTM and machine learning algorithm while overcoming the limitations of RTM parameterization and generalization, providing an efficient and robust Landsat FAPAR estimation approach. …”
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