SDFA-Net: Synergistic Dynamic Fusion Architecture With Deformable Attention for UAV Small Target Detection by Yunsong Qi, Hengwei Cao

“…Through cross-domain validation of the ALU and HIT-UAV datasets, the ablation experiments and comparative analysis fully validated the effectiveness of the algorithmic improvement, and its detection accuracy and robustness were significantly improved over the baseline model. …”
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From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications by Evgenia Gkintoni, Anthimos Aroutzidis, Hera Antonopoulou, Constantinos Halkiopoulos

“…Despite these advances, challenges remain more significant in real-time EEG processing, where a trade-off between accuracy and computational efficiency limits practical implementation. High computational cost is prohibitive to the use of deep learning models in real-world applications, therefore indicating a need for the development and application of optimization techniques. …”
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Cloud-edge Collaborative Data Processing Method for Intelligent Operation and Maintenance of Power Grid Production Equipment by LI Yadan, CHEN Xiaofeng, HUANG Xiaoming, ZHANG Sunxuan

“…Finally, an optimization algorithm for cloud-edge collaborative data processing based on processing delay and backlog aware matching is proposed. …”
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End-of-Line Quality Control Based on Mel-Frequency Spectrogram Analysis and Deep Learning by Jernej Mlinarič, Boštjan Pregelj, Gregor Dolanc

“…The neural network was trained on a highly imbalanced dataset, using oversampling and Bayesian hyperparameter optimization. The final classification algorithm achieved classification metrics with high accuracy (99%). …”
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An online tool based on the Internet of Things and intelligent blockchain technology for data privacy and security in rural and agricultural development by Krishnaprasath Vellimalaipattinam Thiruvenkatasamy, Hayder M. A. Ghanimi, Sudhakar Sengan, Meshal Ghalib Alharbi

“…Central to this model is the proposed Quantum Neural Network + Bayesian Optimization (QNN + BO), a practiced algorithm that, when combined with methods like the Elliptic Curve Cryptography (ECC) and Coyote Optimization Algorithm (COA), guarantees secure data flow, processing, and storage. …”
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Microservice selection approach for mobile users in edge computing environment by ZHAO Shuxu, JIANG Kaijun, WANG Xiaolong

“…Furthermore, a microservice selection algorithm was proposed based on the cloud-edge speedup model and a dynamic cloud-edge migration strategy to handle cross-domain migration under user mobility. …”
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Short-Term Wind Power Prediction Based on MVMD-AVOA-CNN-LSTM-AM by Xiqing Zang, Zehua Wang, Shixu Zhang, Mingsong Bai

“…For this reason, this paper proposes a combined prediction model based on the Pearson correlation coefficient method, multivariate variational mode decomposition (MVMD), African vultures optimization algorithm (AVOA) for leader–follower patterns, convolutional neural network (CNN), long short-term memory (LSTM), and attention mechanism (AM). …”
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Video Recognition of Government Community Management Cases Based on Partial Differential Equation Method by Yumeng Sun

“…Based on this, this paper improves the traditional partial differential equation algorithm of image recognition, selects the GAC model based on image segmentation in the main function, and innovatively optimizes the stop function of its equation function, so as to improve the effect of community case image segmentation. …”
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A performance enhanced distributed computing framework for clustering by local direction centrality upon Apache Spark by Zhipeng Gui, Zichen Huang, Huan Chen, Dehua Peng, Yuhang Liu, Guangyao Fang, Qianxi Lan, Anqi Zhao, Huayi Wu

“…To improve its computational efficiency and scalability, we proposed a performance enhanced distributed framework of CDC, named D-CDC, by workflow-level algorithm optimization and distributed computational acceleration. …”
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Research and application of Gaussian coupled control bistable stochastic resonance system with independent parameter regulation by Tiantian Hou, Shangbin Jiao, Yi Wang, Nianlong Song, Jianghua Li, Wenchuan Cui

“…This optimization approach leverages the algorithm’s ability to enhance population diversity and improve convergence accuracy, thereby optimizing the system’s performance. …”
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Control Strategy for PHEB Based on Actual Driving Cycle with Driving Style Characteristic by Jianping Gao, Zhenhai Xu, Xiaojie Gao

“…Based on the 6 driving cycles, the key parameters of rule-based control strategy are optimized and established by a combinatorial optimization algorithm in Isight. …”
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Phase diagram from nonlinear interaction between superconducting order and density: toward data-based holographic superconductor by Sejin Kim, Kyung Kiu Kim, Yunseok Seo

“…We introduce positional embedding layers to improve the learning process in our algorithm, and the Adam optimization is used to predict the critical temperature data via holographic calculation with appropriate accuracy. …”
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RIM-Net: A Real-Imaginary-Magnitude Network for NLOS/LOS Identification in UWB Indoor Positioning Systems by Jiacheng Ni, Fang Li, Shuai Cao, Linsong Li

“…Experimental results demonstrate that RIM-Net achieves an average accuracy of 92.36% on benchmark datasets while maintaining generalization capabilities above 85% in unseen environments. Furthermore, the optimization of the TOA algorithm validated the effectiveness of RIM-Net in localization, achieving an average performance improvement of 9.66%. …”
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Deep Q-Networks for Minimizing Total Tardiness on a Single Machine by Kuan Wei Huang, Bertrand M. T. Lin

“…The framework incorporates seven distinct reward-shaping strategies, among which the Minimum Estimated Future Tardiness strategy notably enhances the DQN model’s performance. Specifically, it achieves an average improvement of 14.33% over Earliest Due Date (EDD), 11.90% over Shortest Processing Time (SPT), 17.65% over Least Slack First (LSF), and 8.86% over Apparent Tardiness Cost (ATC). …”
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Research and application of deep learning object detection methods for forest fire smoke recognition by Luhao He, Yongzhang Zhou, Lei Liu, Yuqing Zhang, Jianhua Ma

“…This study investigates the application effectiveness of deep learning-based object detection technology in forest fire smoke recognition by using the YOLOv11x algorithm to develop an efficient fire detection model. …”
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Estimating Soil Cd Contamination in Wheat Farmland Using Hyperspectral Data and Interpretable Stacking Ensemble Learning by Liang Zhong, Meng Ding, Shengjie Yang, Xindan Xu, Jianlong Li, Zhengguo Sun

“…Ultimately, the SHAP method was used to shed light on the model’s decision-making process. The results show that (1) FOD can further highlight the spectral features, thereby strengthening the correlation between soil Cd content and wavelength; (2) the CARS algorithm extracted 3.4–6.8% of the feature wavelengths from the full spectrum, and most of them were the wavelengths with high correlation with soil Cd; (3) the optimal estimation precision was achieved using the FOD1.5-SNV spectral pre-processing combined with the Stacking model (<i>R</i>² = 0.77, RMSE = 0.05 mg/kg, RPD = 2.07), and the model effectively quantitatively estimated soil Cd contamination; and (4) SHAP further revealed the contribution of each base model and characteristic wavelengths in the Stacking modeling process. …”
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Research Status and Development Trends of Deep Reinforcement Learning in the Intelligent Transformation of Agricultural Machinery by Jiamuyang Zhao, Shuxiang Fan, Baohua Zhang, Aichen Wang, Liyuan Zhang, Qingzhen Zhu

“…This paper proposes research directions from three key dimensions-“algorithm capability enhancement, deployment architecture optimization, and generalization ability improvement”-offering theoretical references and practical pathways for the continuous evolution of intelligent agricultural equipment.…”
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Core-periphery structure for district metered area partitioning in urban water distribution systems by Rair Solis Jacome, Thomaz Anchieta, Bruno M. Brentan, Manuel Herrera, Xitlali Delgado Galvan, Jose Antonio Arciniega Nevarez, Jesus Mora Rodriguez

“…The proposed core-periphery-informed DMA design integrates hydraulic and topological analyses to identify central and peripheral network areas, applies a community structure detection algorithm conditioned by these areas, and uses an optimisation model to determine the optimal placement of boundary devices, enhancing network resilience and reducing costs. …”
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Reliability Prediction for Computer Numerical Control Machine Servo Systems Based on an IPSO-Based RBF Neural Network by Zheng Jiang, GuangJian Wang, ZuGuang Huang, Ye He, RuiJuan Xue

“…A novel reliability prediction model based on radial basis function (RBF) neural network optimized by improved particle swarm optimization (IPSO) was proposed. …”
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Maximum Energy Absorbed from the Persian Gulf Waves Considering Uncertainty in Power Take off Parameters by Mohammad Jalali, Reihaneh Kardehi Moghaddam, Naser Pariz

“…Compared to particle swarm optimization and conventional black hole algorithm, the results of the proposed method indicate enhancements in reference velocity tracking and absorbed power. …”
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