Spatial Gap-Filling of Himawari-8 Hourly AOD Products Using Machine Learning with Model-Based AOD and Meteorological Data: A Focus on the Korean Peninsula by Youjeong Youn, Seoyeon Kim, Seung Hee Kim, Yangwon Lee

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Improving electric vehicle charging forecasting: A hybrid deep learning approach for probabilistic predictions by Ali Jamali Jahromi, Mohammad Reza Masoudi, Mohammad Mohammadi, Shahabodin Afrasiabi

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Tensor-Based Predictor–Corrector Algorithm for Power Generation and Transmission Reliability Assessment with Sequential Monte Carlo Simulation by Erika Pequeno dos Santos, Beatriz Silveira Buss, Mauro Augusto da Rosa, Diego Issicaba

“…The approach allows for searching for sequences of operation points which can be assigned as success states within the sequential Monte Carlo simulation. …”
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A Fault Identification Method for Electric Submersible Pumps Based on DAE-SVM by Peihao Yang, Jiarui Chen, Hairong Zhang, Sheng Li

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An Innovative Real-Time Recursive Framework for Techno-Economical Self-Healing in Large Power Microgrids Against Cyber–Physical Attacks Using Large Change Sensitivity Analysis by Mehdi Zareian Jahromi, Elnaz Yaghoubi, Elaheh Yaghoubi, Mohammad Reza Maghami, Harold R. Chamorro

“…Additionally, this framework optimizes operational points, including resource generation and network reconfiguration, by simultaneously considering technical, economic, and reliability parameters—a comprehensive integration often overlooked in recent studies. …”
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An Efficient Path Planning Algorithm Based on Delaunay Triangular NavMesh for Off-Road Vehicle Navigation by Ting Tian, Huijing Wu, Haitao Wei, Fang Wu, Jiandong Shang

“…This mesh leverages Delaunay triangulation’s empty circle and maximum-minimum angle properties, which accurately represent irregular obstacles without compromising computational efficiency. Finally, an improved A* path planning algorithm is developed to find the optimal off-road mobility path from a start point to an end point, and identify a path triangle chain with which to calculate the shortest path. …”
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Applying MLP-Mixer and gMLP to Human Activity Recognition by Takeru Miyoshi, Makoto Koshino, Hidetaka Nambo

“…Convolutional neural networks (CNNs), initially proposed for computer vision tasks, are examples of models applied to sensor data. …”
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Bistatic Scattering due to Hydrometeors on Cochannel Intersystem Communication Links over a Subtropical Path by P. A. Owolawi, T. Wallingo

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Modern Trends in the Mathematical Simulation of Pressure-Driven Membrane Processes by Huliienko S. V., Korniienko Y. M., Gatilov K. O.

“…Besides the conventional approaches, which include the irreversible thermodynamics, diffusion and pore flow (and models which consider the membrane surface charge for nanofiltration process), the application of the methods the computational fluid dynamics, artificial neural networks, optimization, and economic analysis have been considered. …”
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Performance prediction of sintered NdFeB magnet using multi-head attention regression models by Qichao Liang, Qiang Ma, Hao Wu, Rongshun Lai, Yangyang Zhang, Ping Liu, Tao Qi

“…To enhance interpretability of neural network, we collected 1,200 high-quality experimental data points and developed a multi-head attention regression model by integrating an attention mechanism into the neural network. …”
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Text-Enhanced Graph Attention Hashing for Cross-Modal Retrieval by Qiang Zou, Shuli Cheng, Anyu Du, Jiayi Chen

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A Contrastive Learning Framework for Vehicle Spatio-Temporal Trajectory Similarity in Intelligent Transportation Systems by Qiang Tong, Zhi-Chao Xie, Wei Ni, Ning Li, Shoulu Hou

“…The rapid development of vehicular networks has facilitated the extensive acquisition of vehicle trajectory data, which serve as a crucial cornerstone for a variety of intelligent transportation system (ITS) applications, such as traffic flow management and urban mobility optimization. …”
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Enhanced Neural Architecture for Real-Time Deep Learning Wavefront Sensing by Jianyi Li, Qingfeng Liu, Liying Tan, Jing Ma, Nanxing Chen

“…We introduce a novel multi-objective neural architecture search (MNAS) method designed to attain Pareto optimality in terms of error and floating-point operations (FLOPs) for the WFSNet. …”
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The triple-helix model as foundation of innovative entrepreneurial ecosystems by Klaus Bruno Schebesch, Horațiu Florin Șoim, Radu Lucian Blaga

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Epileptic Seizure Detection in EEG Signals Using Machine Learning and Deep Learning Techniques by Hepseeba Kode, Khaled Elleithy, Laiali Almazaydeh

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Real-Time Sea State Estimation for Wave Energy Converter Control via Machine Learning by Tanvir Alam Shifat, Ryan Coe, Gioegio Bacelli, Ted Brekken

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YOLOv8n-SMMP: A Lightweight YOLO Forest Fire Detection Model by Nianzu Zhou, Demin Gao, Zhengli Zhu

“…Key innovations include the following: introducing the SlimNeck solution to streamline the neck network by replacing conventional convolutions with Group Shuffling Convolution (GSConv) and substituting the Cross-convolution with 2 filters (C2f) module with the lightweight VoV-based Group Shuffling Cross-Stage Partial Network (VoV-GSCSP) feature extraction module; integrating the Multi-dimensional Collaborative Attention (MCA) mechanism between the neck and head networks to enhance focus on fire-related regions; adopting the Minimum Point Distance Intersection over Union (MPDIoU) loss function to optimize bounding box regression during training; and implementing selective channel pruning tailored to the modified network architecture. …”
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A hybrid centralized-decentralized traffic control framework for unmanned aerial vehicles in urban low-altitude airspace by Xiangdong Chen, Shen Li, Meng Li

“…Numerical experiments validate the proposed framework, highlighting its effectiveness in improving traffic efficiency and network throughput. Key insights are provided regarding the role of network structure, the placement of take-off and landing points, and control parameters in optimizing UAM operations.…”
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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

“…Meantime, deformable convolution is used to expand the receptive field and reduce computational complexity. The feature fusion module constructs a two-stage fusion network to optimize the fusion and alignment of multi-sensor features. …”
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Finding a suitable chest x-ray image size for the process of Machine learning to build a model for predicting Pneumonia by Kriengsak Yothapakdee, Yosawaj Pugtao, Sarawoot Charoenkhun, Tanunchai Boonnuk, Kreangsak Tamee

“…These findings assist in optimizing chest X-ray image sizes for pneumonia prediction models by weighing diagnostic accuracy against computational resources.…”
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