Can Stereoscopic Density Replace Planar Density for Forest Aboveground Biomass Estimation? A Case Study Using Airborne LiDAR and Landsat Data in Daxing’anling, China by Xuan Mu, Dan Zhao, Zhaoju Zheng, Cong Xu, Jinchen Wu, Ping Zhao, Xiaomin Li, Yong Pang, Yujin Zhao, Tianyu An, Yuan Zeng, Bingfang Wu

“…The optimal RF-based stereo model of H_AM (R² = 0.65, rRMSE = 26.05%) significantly improved AGB estimation compared to the planar model (R² = 0.59, rRMSE = 30.41%). …”
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Spatial-Temporal Semantic Feature Interaction Network for Semantic Change Detection in Remote Sensing Images by Yuhang Zhang, Wuxia Zhang, Songtao Ding, Siyuan Wu, Xiaoqiang Lu

“…The TML-FI is designed to mine the spatial-temporal information by extracting long-range dependencies and spatial information from multilevel features to improve spatial perception. Moreover, Mixed Spatial Reasoning Convolution block (MixSrc) is presented to enrich the spatial information by extracting the multiscale features, thus improving the model's capability to interpret complex scenes. …”
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Fault Prediction of Hydropower Station Based on CNN-LSTM-GAN with Biased Data by Bei Liu, Xiao Wang, Zhaoxin Zhang, Zhenjie Zhao, Xiaoming Wang, Ting Liu

“…Meanwhile, a multi-scale feature extraction network with time–frequency information is designed to improve the accuracy of fault detection. Finally, a dynamic multi-task training algorithm is proposed to ensure the convergence and training efficiency of the deep models. …”
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An Advanced Hybrid Forecasting System for Wind Speed Point Forecasting and Interval Forecasting by Haipeng Zhang, Hua Luo

“…Therefore, in this paper, we developed a prediction system integrating an advanced data preprocessing strategy, a novel optimization model, and multiple prediction algorithms. This combined forecasting system can overcome the inherent disadvantages of the traditional forecasting methods and further improve the prediction performance. …”
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Gated recurrent deep learning approaches to revolutionizing English language learning for personalized instruction and effective instruction by Bo Sun

“…The study investigates the revolutionary possibilities of Gated Recurrent Neural Networks (GRNN) to improve ELL-tailored training. The GRNN-ELL model dynamically adapts to the learner’s progress using powerful sequence modelling and language processing algorithms. …”
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Clinical and molecular implications of cGAS/STING signaling in checkpoint inhibitor immunotherapy by Hao Chen, Yang Zhong, Yang Zhong, Rongjie Feng, Xingyu Zhu, Kang Xu, Mingjie Kuang, Wei Chong

“…Logistic and Cox regression models were utilized to investigate the association between STING signaling and checkpoint inhibitor therapeutic response. …”
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SSCD-YOLO: Semi-Supervised Cross-Domain YOLOv8 for Pedestrian Detection in Low-Light Conditions by Fangliang Cao, Kai Yan, Hongliang Chen, Zhen Wang, Yunliang Du, Zekang Zheng, Kefan Li, Baozhu Qi, Mingjia Wang

“…To mitigate the domain differences between infrared and visible light images and address the challenges of data annotation and poor pedestrian detection performance in low-light environments, we propose a semi-supervised cross-domain YOLOv8 pedestrian detection model SSCD-YOLO for low-light environments. First, a CDF-CycleGAN cross-domain image fusion method is designed, which improves the input of CycleGAN using a diffusion model, integrates the self-attention mechanism into the residual network of the CycleGAN generator to design the SA-Block, replaces the linear layer in the CycleGAN discriminator with an autoencoder, and improves the training method of CycleGAN. …”
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Rice Leaf Disease Classification—A Comparative Approach Using Convolutional Neural Network (CNN), Cascading Autoencoder with Attention Residual U-Net (CAAR-U-Net), and MobileNet-V2... by Monoronjon Dutta, Md Rashedul Islam Sujan, Mayen Uddin Mojumdar, Narayan Ranjan Chakraborty, Ahmed Al Marouf, Jon G. Rokne, Reda Alhajj

“…The initial algorithmic phase involved image pre-processing of the crop images, using a bilateral filter to improve image quality. …”
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Unified Dynamic Dictionary and Projection Optimization With Full-Rank Representation for Hyperspectral Anomaly Detection by Hongran Li, Chao Wei, Yizhou Yang, Zhaoman Zhong, Ming Xu, Dongqing Yuan

“…Traditional reconstruction based methods model the background using a predefined static background dictionary and low-rank representation coefficients. …”
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A Novel Approach for Maize Straw Type Recognition Based on UAV Imagery Integrating Height, Shape, and Spectral Information by Xin Liu, Huili Gong, Lin Guo, Xiaohe Gu, Jingping Zhou

“…This method utilized unmanned aerial vehicle (UAV) multispectral imagery, integrated the Stacking Enhanced Straw Index (SESI) introduced in this study, and combined height, shape, and spectral characteristics to improve recognition accuracy. Using the original five-band multispectral imagery, a new nine-band image of the study area was constructed by integrating the calculated SESI, Canopy Height Model (CHM), Product Near-Infrared Straw Index (PNISI), and Normalized Difference Vegetation Index (NDVI) through band combination. …”
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Optimization of Energy Management Strategy for Series Hybrid Electric Vehicle Equipped with Dual-Mode Combustion Engine Under NVH Constraints by Shupeng Zhang, Hongnan Wang, Chengkai Yang, Zeping Ouyang, Xiaoxin Wen

“…Optimal solutions for EMSs in the literature usually focus on improving fuel efficiency by operating the engine within a high efficiency range, without considering the drivability, which is affected by noise–vibration–harshness (NVH) constraints at low vehicle speeds. …”
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Optimization of PID Controllers Using Groupers and Moray Eels Optimization with Dual-Stream Multi-Dependency Graph Neural Networks for Enhanced Dynamic Performance by Vaishali H. Kamble, Manisha Dale, R. B. Dhumale, Aziz Nanthaamornphong

“…This study presents a novel control strategy that integrates the Groupers and Moray Eels Optimization (GMEO) algorithm with a Dual-Stream Multi-Dependency Graph Neural Network (DMGNN) to optimize PID controller parameters. …”
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Key Technologies in Intelligent O&M System Construction for Urban Rail Transit Communication by WANG Xianlei

“…An equipment health index algorithm model and a big data architecture are proposed, and a tracking and evaluation platform encompassing ′cloud-data-intelligence′ is built. …”
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Brain activity patterns reflecting security perceptions of female cyclists in virtual reality experiments by Mohammad Arbabpour Bidgoli, Arian Behmanesh, Navid Khademi, Phromphat Thansirichaisree, Zuduo Zheng, Sara Saberi Moghadam Tehrani, Sajjad Mazloum, Sirisilp Kongsilp

“…Abstract Active transportation, such as cycling, improves mobility and general health. However, statistics reveal that in low- and middle-income countries, male and female cycling participation rates differ significantly. …”
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Dung beetle optimizer based on mean fitness distance balance and multi-strategy fusion for solving practical engineering problems by Wanru Tang, Haoze Qin, Shuang Kang

“…Abstract As a swarm intelligence algorithm, Dung beetle optimizer (DBO) was inspired by the behavior pattern of dung beetles for survival. …”
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Intelligent reflective surfaces in 5G and beyond: optimizing uplink satellite connectivity for IoT by Callistus Odinaka Obidiozor, Adeeb Sait, Tawfik Al-Hadhrami, Eman H. Alkhammash, Faisal Saeed

“…A reinforcement learning algorithm was employed to optimise IRS phase shifts and beamforming to maximise communication performance. …”
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InvMOE: MOEs Based Invariant Representation Learning for Fault Detection in Converter Stations by Hao Sun, Shaosen Li, Hao Li, Jianxiang Huang, Zhuqiao Qiao, Jialei Wang, Xincui Tian

“…Experimental results on real-world datasets demonstrate that InvMOE achieves superior generalization performance and significantly improves detection accuracy for tasks with limited samples, such as valve cooling water leakage. …”
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EMG-Controlled Soft Robotic Bicep Enhancement by Jiayue Zhang, Daniel Vanderbilt, Ethan Fitz, Janet Dong

“…The McKibben-inspired pneumatic muscle was chosen as the soft actuator for the prototype. A hybrid control algorithm, incorporating PID and model-based control methods, was developed. …”
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WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches by Shehla Gul, Sobia Arshad, Sanay Muhammad Umar Saeed, Adeel Akram, Muhammad Awais Azam

“…Experimental results show that our proposed framework outperforms state-of-the-art approaches, vastly improving DL model detection accuracy by 98% using CNN.…”
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Fuzzy deep learning architecture for cucumber plant disease detection and classification by Anas Bilal, Junaid Ali Khan, Abdulkareem Alzahrani, Khalid Almohammadi, Maha Alamri, Xiaowen Liu

“…Feature vector optimization is performed using a chaotic particle swarm algorithm, enhancing the model’s overall accuracy, reliability, and ease of implementation. …”
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