Investigating the Analysis of Power Saving Mode in IEEE 802.11 for Wi-Fi Communication by Isam Aameer Ibrahim, Haider TH Salim, Hasan F. Khazaal

“…In this research shows that the optimal BI and LI produce optimal OSS time ratio scheme also achieved optimal average and variance of packet delay. …”
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Study on Novel Surface Defect Detection Methods for Aeroengine Turbine Blades Based on the LFD-YOLO Framework by Wei Deng, Guixiong Liu, Jun Meng

“…The proposed approach employs the LDconv model to adjust the size and shape of convolutional kernels dynamically, integrates the deformable attention mechanism (DAT) to capture minute defect features effectively, and uses Focaler-CIoU to optimize the bounding box loss function of the detection network. …”
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An Improved U-Net-Based Framework for Estimating River Surface Flow Velocity by 周继威, 安国成, 王根一

“…This study aimed to address these limitations by developing a robust framework that integrates improved data labeling strategies, optimized training methods, and a novel neural network architecture to achieve high-precision velocity estimation. …”
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Preparation and Characterization of Grape Seed Oil-Whey Protein Isolate High Internal Phase emulsion by GUO Bing-bing, CHEN Si-xian, XIAO Yu-jia, WANG Qiao-yi, LI Zi-lin, WEI Ya-ran, CHEN Yan, AI You-wei

“…These findings collectively indicate that moderate elevation of whey protein isolate concentration and controlled intensification of homogenization energy can synergistically improve emulsion stability and gel network strength. These conclusions provide references for the high-value utilization of functional oils. …”
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Static Voltage Stability Evaluation and Correction Strategy Based on Stage Solving Strategy and SIFT by Yan Wen, Xiaoming Liu, Yongzhi Zhou, Huiwen Zhang, Donglei Sun

“…In addition, in time phase 1 of the IEEE30 node system, the average value of load margin for each scenario in the first phase was 18.62 MW, which was below the load margin threshold. …”
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FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging by Abhilasha Dave, Cong Wang, James Russell, Ryan Herbst, Jana Thayer

“…We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). …”
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Retrieval of bulk hygroscopicity from PurpleAir PM_2.5 sensor measurements by J. Psotka, E. Tracey, R. J. Sica

“…These values are consistent with the accepted ranges of bulk hygroscopicity for atmospheric particulate matter (0.1 to 0.9) determined in previous studies using calibrated air quality measurement instruments, which suggests that our method allows a new aerosol product to be determined from a large sensor network.</p>…”
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Research on Lightweight Dynamic Security Protocol for Intelligent In-Vehicle CAN Bus by Yuanhao Wang, Yinan Xu, Zhiquan Liu, Suya Liu, Yujing Wu

“…With the integration of an increasing number of outward-facing components in intelligent and connected vehicles, the open controller area network (CAN) bus environment faces increasingly severe security threats. …”
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Personnel localization method for low-visibility environments based on improved YOLOv3 by LU Xiaoya, LI Haifang

“…Next, Darknet53 in YOLOv3 was replaced with the lighter Darknet-19, and CIoU was introduced as the loss function to optimize personnel target identification in the enhanced video. …”
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A GNSS-IR Soil Moisture Inversion Method Considering Multi-Factor Influences Under Different Vegetation Covers by Yadong Yao, Jixuan Yan, Guang Li, Weiwei Ma, Xiangdong Yao, Miao Song, Qiang Li, Jie Li

“…A multi-factor SMC inversion dataset was constructed, and three machine learning models were selected to develop the SMC prediction model: Support Vector Regression (SVR), suitable for small and medium-sized regression tasks; Convolutional Neural Networks (CNN), with robust feature extraction capabilities; and NRBO-XGBoost, which supports automatic optimization. …”
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Morphological Estimation of Primary Branch Inclination Angles in Jujube Trees Based on Improved PointNet++ by Linyuan Shang, Fenfen Yan, Tianxin Teng, Junzhang Pan, Lei Zhou, Chao Xia, Chenlin Li, Mingdeng Shi, Chunjing Si, Rong Niu

“…The experimental results show that compared to PointNet++, the improved network achieved increases of 1.3, 1.47, and 3.33% in accuracy (Acc), class average accuracy (CAA), and mean intersection over union (mIoU), respectively. …”
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Real-Time Detection and Instance Segmentation Models for the Growth Stages of <i>Pleurotus pulmonarius</i> for Environmental Control in Mushroom Houses by Can Wang, Xinhui Wu, Zhaoquan Wang, Han Shao, Dapeng Ye, Xiangzeng Kong

“…Model evaluations reveal that GSP-RTMDet-S achieves an optimal balance between accuracy and speed, with a bounding box mean average precision (bbox mAP) and a segmentation mAP (segm mAP) of 96.40% and 93.70% on the test set, marking improvements of 2.20% and 1.70% over the baseline. …”
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Modelling and Optimisation of Hysteresis and Sensitivity of Multicomponent Flexible Sensing Materials by Kai Chen, Qiang Gao, Yijin Ouyang, Jianyong Lei, Shuge Li, Songxiying He, Guotian He

“…Finally, the optimal solution of the prediction model is obtained using the multi-objective RIME (MORIME) algorithm. …”
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Preliminary Study on Cooperative Route Planning Reinforcement Learning with a Focus on Avoiding Intersection Congestion by Shintaro Katagiri, Tomio Miwa, Kosuke Nishijima

“…To investigate the feasibility of avoiding intersection conflicts through network-level route allocation, we propose a cooperative route allocation model using reinforcement learning than can model the relationship between the complex traffic environment and optimal route solutions. …”
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A Province-Wide Home Dialysis Program Review: Challenges, Strengths, and Future Strategies by Megan Borkum, Micheli Bevilacqua, Alexandra Romann, Krishna Poinen, Sushila Saunders, Linda Turnbull, R. Suneet Singh, Adeera Levin, Michael A. Copland

“…Despite maintaining a home dialysis prevalence of approximately 30%, consistently above the national average, a review was conducted to examine intake and attrition rates and optimize these outcomes within a learning health system context. …”
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The COVID-19 Model with Partially Recovered Carriers by T. S. Faniran, E. A. Bakare, A. O. Falade

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Research on Soybean Seedling Stage Recognition Based on Swin Transformer by Kai Ma, Jinkai Qiu, Ye Kang, Liqiang Qi, Wei Zhang, Song Wang, Xiuying Xu

“…In the performance degradation test of the motion blur level model, the maximum degradation accuracy, overall degradation index, and average degradation index of the optimized Swin-T model were 87.77%, 6.54%, and 2.18%, respectively. …”
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A Lightweight and Adaptive Image Inference Strategy for Earth Observation on LEO Satellites by Bo Wang, Yuhang Fang, Dongyan Huang, Zelin Lu, Jiaqi Lv

“…It also proposes a lightweight and adaptive image inference strategy utilizing the Markov Decision Process (MDP) and Deep Q Network (DQN), which dynamically optimizes model selection to balance accuracy and energy efficiency under varying conditions. …”
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Wide-Range Variable Cycle Engine Control Based on Deep Reinforcement Learning by Yaoyao Ding, Fengming Wang, Yuanwei Mu, Hongfei Sun

“…To solve this problem, this paper adopts a deep reinforcement learning method based on a deep deterministic policy gradient algorithm, and it applies an action space pruning technique to optimize the controller, which significantly improves the convergence speed of network training. …”
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Unifying Non-Markovian Characterization with an Efficient and Self-Consistent Framework by G. A. L. White, P. Jurcevic, C. D. Hill, K. Modi

“…Finally, we conclude our analysis with applications thereof to the efficacy of control techniques to counteract these effects—including noise-aware circuit compilation and optimized dynamical decoupling. We find significant improvements are possible in the diamond norm and average gate fidelity of arbitrary SU(4) operations, as well as related decoupling improvements in contrast to off-the-shelf schemes.…”
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