GAT-Enhanced YOLOv8_L with Dilated Encoder for Multi-Scale Space Object Detection by Haifeng Zhang, Han Ai, Donglin Xue, Zeyu He, Haoran Zhu, Delian Liu, Jianzhong Cao, Chao Mei

“…According to the characteristics of space missions, an annotated dataset containing 8000 satellite and space station images is constructed, covering a variety of lighting, attitude and scale scenes, and providing benchmark support for model training and verification. Experimental results on the space object dataset reveal that the enhanced algorithm achieves a mean average precision (mAP) of 97.2%, representing a 2.1% improvement over the original YOLOv8_L. …”
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Research Progress and Prospect of Green Infrastructure with Public Health Promotion Function by Tongyu LI, Junyi LIXU, Binxia XUE, Yan (USA) SONG

“…Such a framework could significantly enhance urban planning and policy-making by optimizing GI interventions to provide the most significant public health benefits. …”
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Conformal Segmentation in Industrial Surface Defect Detection with Statistical Guarantees by Cheng Shen, Yuewei Liu

“…The former evaluates the distribution that discriminates defects from all samples based on probability. The detection model is improved by retraining with calibration data that is assumed to be independent and identically distributed (i.i.d) with the test data. …”
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Impacts of inter-train distances on aerodynamic drag reduction in heavy-haul train groups by LYU Jun, XIANG Tao, SONG Zongying, GAO Guangjun

“…This paper analyzes the impacts of inter-train distances in this operational mode on the aerodynamic characteristics of trailing trains, using computational fluid dynamics (CFD) methods, based on the SST <italic>k</italic>-<italic>ω</italic> turbulence model. Initial algorithm validation was performed, and the results were compared with data from wind tunnel experiments conducted in a large low-speed wind tunnel at the China aerodynamics research and development center. …”
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LGR-Net: A Lightweight Defect Detection Network Aimed at Elevator Guide Rail Pressure Plates by Ruizhen Gao, Meng Chen, Yue Pan, Jiaxin Zhang, Haipeng Zhang, Ziyue Zhao

“…To overcome these limitations, this paper proposes a lightweight defect detection network (LGR-Net) for guide rail pressure plates based on the YOLOv8n algorithm. To solve the problem of excessive model parameters in the original algorithm, we enhance the baseline model’s backbone network by incorporating the lightweight MobileNetV3 and optimize the neck network using the Ghost convolution module (GhostConv). …”
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Digital Land Suitability Assessment for Irrigated Cultivation of Some Agricultural Crops Using Machine Learning Approaches (Case Study: Qazvin-Abyek) by F. Jannati, F. Sarmadian

“…The utilization of modern mapping techniques such as digital soil mapping and machine learning algorithms can significantly improve the accuracy of land suitability assessment and crop performance prediction. …”
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The Next Frontier in Brain Monitoring: A Comprehensive Look at In-Ear EEG Electrodes and Their Applications by Alexandra Stefania Mihai (Ungureanu), Oana Geman, Roxana Toderean, Lucas Miron, Sara SharghiLavan

“…Recent studies have demonstrated that in-ear EEG can record signals qualitatively comparable to scalp EEG, with an optimized signal-to-noise ratio and improved electrode stability. …”
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A state-of-the-art review of soft computing-based monitoring and control in the machining of hard alloys by Lokesh Kumar, Ashish Goyal, Vimal Kumar Pathak, Abhijit Bhowmik

“…These innovations are supported by suitable modeling and metaheuristic techniques, including adaptive neuro-fuzzy inference systems (ANFIS), simulated annealing, teaching-learning-based optimization (TLBO), the finite element method (FEM), and the non-dominated sorting genetic algorithm II (NSGA-II). …”
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Drilling Condition Identification Method for Imbalanced Datasets by Yibing Yu, Huilin Yang, Fengjia Peng, Xi Wang

“…To address the challenges posed by class imbalance and temporal dependency in drilling condition data and enhance the accuracy of condition identification, this study proposes an integrated method combining feature engineering, data resampling, and deep learning model optimization. Firstly, a feature selection strategy based on weighted symmetrical uncertainty is employed, assigning higher weights to critical features that distinguish minority classes, thereby enhancing class contrast and improving the classification capability of the model. …”
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Object Detection using YOLOv8 : A Systematic Review by Nugraha Asthra Megantara, Ema Utami

“…This study evaluates the performance of YOLOv8 based on precision, recall, F1-score, and mean average precision (mAP) metrics, and compares its advantages and limitations with previous YOLO versions and other object detection algorithms. Improvements in the YOLOv8 architecture, including attention mechanisms, improved feature extraction, and hyperparameter optimization, enable significant improvements in accuracy and computational efficiency, especially for small objects and low-light conditions. …”
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Enhanced YOLO11 for lightweight and accurate drone-based maritime search and rescue object detection. by Beigeng Zhao, Jiawen Zhao, Rui Song, Lizhi Yu, Xia Zhang, Jiren Liu

“…In the lightweight complexity range, the proposed model achieves a relative accuracy improvement of 20.85% to 43.70% compared to these state-of-the-art methods. …”
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The artificial intelligence revolution in gastric cancer management: clinical applications by Runze Li, Jingfan Li, Yuman Wang, Xiaoyu Liu, Weichao Xu, Runxue Sun, Binqing Xue, Xinqian Zhang, Yikun Ai, Yanru Du, Jianming Jiang

“…Although most of the current AI-based models have not been widely used in clinical practice, with the continuous deepening and expansion of precision medicine, we have reason to believe that a new era of AI-driven gastric cancer care is approaching. …”
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Research on the blockchain-based trusted ownership confirmation and value transfer system and its light weight of industrial data assets by WANG Dongchu, FU Yusun, YU Ya

“…The consensus protocol algorithm of the blockchain system was optimized based on the trustworthiness of nodes, reducing the probability of malicious attacks on nodes while improving the efficiency of system transaction consensus, achieving security and lightweight parallelism of the entire system. …”
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Method of Diagnostics of Operation Modes of Individual Heat Supply Units, Allowing to Detect Pre-Emergency Situations at an Early Stage by Dvortsevoy A.I., Borush O.V., Khoreva V.A., Yakovina I.N.

“…This was confirmed by the "Elbow Method", which determined the optimal number, which made it possible to significantly improve the forecasting of emergency modes. …”
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AHA: Design and Evaluation of Compute-Intensive Hardware Accelerators for AMD-Xilinx Zynq SoCs Using HLS IP Flow by David Berrazueta-Mena, Byron Navas

“…We outline criteria for selecting algorithms to improve speed and resource efficiency in HLS design. …”
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Detecting Botrytis Cinerea Control Efficacy via Deep Learning by Wenlong Yi, Xunsheng Zhang, Shiming Dai, Sergey Kuzmin, Igor Gerasimov, Xiangping Cheng

“…The method integrates colony growth environment data and images as network inputs, achieving real-time prediction of colony area through an improved RepVGG network. The innovations include (1) combining channel attention mechanism, multi-head self-attention mechanism, and multi-scale feature extractor to improve prediction accuracy and (2) introducing the Shapley value algorithm to achieve a precise quantitative analysis of environmental variables’ contribution to colony growth. …”
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Abnormal Vibration Analysis of Low-floor Tram by Shuo LYU, Huanyun DAI, Qunsheng WANG

“…By establishing a vehicle dynamics model, the influence of the wheel on the different eccentricity is analyzed, and the vertical ride comfort is greatly improved by optimizing parameters of inter-vehicle longitudinal damper and secondary vertical damper. …”
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Maximum power point tracking control for mechanical rectification wave energy converter by Jianan Xu, Yanpeng Zhao, Yong Zhan, Yansong Yang

“…In order to improve the power generation efficiency, the maximum power point tracking control algorithm is designed based on the admittance differentiation method. …”
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Research on multi-attribute controller for virtual data domain based on software definition network by Jianmin Wang, Bo Zhang, Tongrang Fan, Zijian Fu, Wenbin Zhao

“…Simulation results show that compared with the shortest path mapping and greedy resource mapping algorithms, the virtual domain established by the network resource overhead–allocation algorithm can improve the resource utilization rate by 10% and reduce the intra-domain communication delay by 30%. …”
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Unsignalized intersection vehicle platoon formation scheduling method based on mixed traffic by Junfeng Jiang, Yikang Rui, Bin Ran

“…In deciding the passing order, we propose the Mixed Platoon Scheduling Model (MPSM) to improve the traffic safety and efficiency of unsignalized intersections in mixed traffic environments and to obtain the optimal vehicle passing order without collisions. …”
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