Intelligent Inversion of Mechanical Parameters of Surrounding Rock of Underground Water-Sealed Storage Cavern During Construction by CAO Yang-bing, CHEN Ke-xin, HUANG Yue, LI Yao, ZHANG Sui, HUANG Zhen-ping

“…Finally, an intelligent inversion model for the mechanical parameters of the surrounding rock is constructed using samples obtained from numerical simulations and an evolutionary neural network model. Comprehensively estimating the initial value ranges of the mechanical parameters of the surrounding rock for different classes of rock mass basic quality can avoid large deviations in inversion results caused by the wide optimization range of intelligent algorithms. …”
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EFCNet for small object detection in remote sensing images by Yutong Wang, Zhensong Li, Shiliang Zhu, Xiaotan Wei

“…The model employs a novel backbone network, ODCSP-Darknet53, to enhance feature extraction efficiency, and incorporates the small object enhancement bi-directional feature pyramid network (STEBIFPN) structure in the neck region of the network for optimized scaling of small object information. …”
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Cost-Effective, Time-Efficient Passenger Rail System for the Eastern United States by James Mathias, Dal Hyung Kim

“…The results of the program predicted a passenger starting at the farthest point of the system boards the train at 16:02 on average and arrives at a different point of the system at 07:57 on average the following day, assuming the train travels an average speed of 70 mph. …”
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Data-Driven Decision-Making for Flexible Natural Gas Allocation Under Uncertainties: An Agent-Based Modelling Approach by Noor Yusuf, Ahmed AlNouss, Roberto Baldacci, Tareq Al-Ansari

“…The results reveal that cases prioritising natural gas monetisation for export outperform those meeting power requirements in average annual profitability. In case 4, considering a full network with power, the average annual profitability in the economic scenario reduces by approximately 47% compared to case 3, representing the optimal network configuration with $5.22 billion in average annual profitability. …”
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Hierarchical Feature Fusion and Enhanced Attention Mechanism for Robust GAN-Generated Image Detection by Weinan Zhang, Sanshuai Cui, Qi Zhang, Biwei Chen, Hui Zeng, Qi Zhong

“…In recent years, with the rapid advancement of deep learning technologies such as generative adversarial networks (GANs), deepfake technology has become increasingly sophisticated. …”
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Tomato yellow leaf curl virus detection based on cross-domain shared attention and enhanced BiFPN by Henghui Mo, Linjing Wei

“…The network’s neck incorporates an enhanced Bidirectional Feature Pyramid Network (BiFPN), integrating feature maps of various scales to boost early symptom detection capabilities. …”
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A Blockchain-Based Architecture of Web3.0: A Comprehensive Decentralized Model With Relay Nodes, Unique IDs and P2P by Hyunjoo Yang, Sejin Park

“…When faced with malicious requests, the system significantly reduces verification latency to an average of 0.0106 ms, ensuring rapid rejection and preserving network stability, while legitimate requests are processed efficiently with an average latency of 0.4125 ms.Experiments comparing latency-based and random-based relay selection methods across various network configurations (public-public, public-private, private-private) demonstrate that latency-based selection optimizes connection setup times in low-latency environments, while random-based selection provides robust performance in complex network scenarios. …”
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FCB-YOLOv8s-Seg: A Malignant Weed Instance Segmentation Model for Targeted Spraying in Soybean Fields by Zishang Yang, Lele Wang, Chenxu Li, He Li

“…The FCB-YOLOv8s-Seg model incorporates a lightweight backbone network to accelerate computations and reduce model size, with optimized Squeeze-and-Excitation Networks (SENet) and Bidirectional Feature Pyramid Network (BiFPN) modules integrated into the neck network to enhance weed recognition accuracy. …”
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An Improved YOLOv7-Tiny-Based Algorithm for Wafer Surface Defect Detection by Mengyun Li, Xueying Wang, Hongtao Zhang, Xiaofeng Hu

“…First, a coordinate attention (CA) module is incorporated into the feature extraction network to enhance the network’s ability to learn features at defect locations. …”
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Flaw-YOLOv5s: A Lightweight Potato Surface Defect Detection Algorithm Based on Multi-Scale Feature Fusion by Haitao Wu, Ranhui Zhu, Hengren Wang, Xiangyou Wang, Jie Huang, Shuwei Liu

“…Then, the SPPF in the backbone network is replaced by SPPELAN, which combines SPP with ELAN to enable the model to perform multi-scale pooling and feature extraction, optimizing detection capacity for small targets in potatoes. …”
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DeployFusion: A Deployable Monocular 3D Object Detection with Multi-Sensor Information Fusion in BEV for Edge Devices by Fei Huang, Shengshu Liu, Guangqian Zhang, Bingsen Hao, Yangkai Xiang, Kun Yuan

“…The feature fusion module constructs a two-stage fusion network to optimize the fusion and alignment of multi-sensor features. …”
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Improved double DQN with deep reinforcement learning for UAV indoor autonomous obstacle avoidance by Ruiqi Yu, Qingdang Li, Jiewei Ji, Tingting Wu, Jian Mao, Shun Liu, Zhen Sun

“…The algorithm enhances the perception and learning capabilities by optimizing the network model and employs a dynamic exploration strategy that encourages exploration in the early stage and reduces it later to accelerate convergence and improve efficiency. …”
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Design and Implementation of a Deep Learning Model and Stochastic Model for the Forecasting of the Monthly Lake Water Level by Waleed Ahmed Hassen Al-Nuaami, Lamiaa Abdul-jabbar Dawod, B. M. Golam Kibria, Shahryar Ghorbani

“…In this study, an artificial neural network (ANN), a deep learning (DL) neural network model, and an autoregressive integrated moving average (ARIMA) model were employed for the water level forecasting of the St. …”
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Autonomous Obstacle Avoidance with Improved Deep Reinforcement Learning Based on Dynamic Huber Loss by Xiaoming Xu, Xian Li, Na Chen, Dongjie Zhao, Chunmei Chen

“…Specifically, in static environments, the Dynamic Huber-loss-based DRL framework achieves a 98.85% success rate with an optimized average path length of 10.73; in dynamic environments, it attains a 74.20% success rate with an average path length of 37.04; adding wind disturbances in a dynamic environment, it attains a 70.95% success rate with an average path length of 40.40, highlighting its enhanced performance and adaptability.…”
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Proactive Edge Caching With Popularity Prediction and Content Replication by Ilhan Demirci, Omer Korcak

“…The increasing demand for low-latency content delivery in 5G networks highlights the need for intelligent edge caching solutions. …”
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Enhanced extracellular matrix remodeling due to embedded spheroid fluidization by Tao Zhang, Shabeeb Ameen, Sounok Ghosh, Kyungeun Kim, Mrinal Pandey, Brian C H Cheung, Minh Thanh, Alison E Patteson, Mingming Wu, J M Schwarz

“…We are therefore able to quantify the regime of optimal spheroid-fiber network mechanical reciprocity. …”
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Predictive Analysis of Maritime Congestion Using Dynamic Big Data and Multiscale Feature Analysis by Yalin Wu

“…Gated recurrent unit (GRU) neural network and autoregressive moving average (ARMA) models are utilized to predict trend and noise components, respectively. …”
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A method of identification and localization of tea buds based on lightweight improved YOLOV5 by Yuanhong Wang, Yuanhong Wang, Jinzhu Lu, Jinzhu Lu, Qi Wang, Qi Wang, Zongmei Gao

“…The Fuding white tea bud image dataset was established by collecting Fuding white tea images; then the lightweight network ShuffleNetV2 was used to replace the YOLOV5 backbone network; the up-sampling algorithm of YOLOV5 was optimized by using CARAFE modular structure, which increases the sensory field of the network while maintaining the lightweight; then BiFPN was used to achieve more efficient multi-scale feature fusion; and the introduction of the parameter-free attention SimAm to enhance the feature extraction ability of the model while not adding extra computation. …”
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Ocean Internal Wave Detection in SAR Images Based on Improved YOLOv7 by Limei Cai, Guozhen Zha, Mingsen Lin, Xiao Wang, Honghua Zhang

“…The experimental results show that the F1, (mean average precision) mAP50, and mAP50:95 of the improved YOLOv7 network model are 91.3%, 94.3%, and 59.1%, respectively, which are 5.3%, 2.7%, and 2.8% higher compared to the baseline model.…”
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LBT-YOLO: A Lightweight Road Targeting Algorithm Based on Task Aligned Dynamic Detection Heads by Pei Tang, Zhenyu Ding, Minnan Jiang, Weikai Xu, Mao Lv

“…Secondly, a new neck network structure BCFPN (Bidirectional Collocated Feature Pyramid Network) is designed based on the weighted bidirectional feature pyramid network, which enhances the feature fusion and the interaction of contextual information, and improves the detection accuracy of the model. …”
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