Two-Stage Optimization of Mobile Energy Storage Sizing, Pre-Positioning, and Re-Allocation for Resilient Networked Microgrids with Dynamic Boundaries by Hongtao Lei, Bo Jiang, Yajie Liu, Cheng Zhu, Tao Zhang

“…The proposed framework is modeled mathematically and solved using a customized progressive hedging algorithm. …”
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Fuzzy reliability as a tool to estimate the technological and organizational solutions in construction projects by Irene Ladnykh, Nabi Ibadov

“…The numerical example presented in this article allows us to evaluate the practical significance of the proposed assessment tool on the network model. The conclusion suggests further research and improvement of the proposed framework.…”
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Performance evaluation of enhanced deep learning classifiers for person identification and gender classification by Vasu Krishna Suravarapu, Hemprasad Yashwant Patil

“…As a result, it is perceived that a considerable improvement was observed using the enhanced models.…”
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Urban Road Change Detection using Morphological Processing by Ei Phyu Sin Win

“…Use Google Earth Pro to get the necessary data photos and search for road improvements. After collecting images from different seasons and years, we can find precise answers by combining them with precise algorithms. …”
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Clinical validation of a novel hand dexterity measurement device. by Conor D Hayden, Bruce P Murphy, Deirdre Gilsenan, Bahman Nasseroleslami, Orla Hardiman, Deirdre Murray

“…This device could act as an objective outcome measure in clinical trials and may be useful in improving patient care.…”
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Ecological and Real-Time Route Selection Method for Multiple Vehicles in Urban Road Network by Liping Yan, Yue Tang, Chan Peng, Yu Cai, Wenbo Zhang, Jing Wang

“…Compared with three non-negotiated optimization algorithms based on swarm technology, EMR2SM is verified by experiments that it improves the efficiency and accuracy of the optimal route selection for multiple vehicles and reduces vehicle emissions, which can effectively reduce traffic congestion and environmental pollution.…”
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Attention-mechanism-based tracking method for intelligent Internet of vehicles by Xu Kang, Bin Song, Jie Guo, Xiaojiang Du, Mohsen Guizani

“…It mainly includes the following contents: (1) a fully convolutional neural network fused attention mechanism with the selection of the deep features for convolution; (2) a separation method for template and semantic background region to separate target vehicles from the background in the initial frame adaptively; (3) a two-stage method for model training using our traffic dataset. The experimental results show that the proposed method improves the tracking accuracy without an increase in tracking time. …”
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Enhancing Arabic handwritten word recognition: a CNN-BiLSTM-CTC architecture with attention mechanism and adaptive augmentation by Bounour Imane, Ammour Alae, Khaissidi Ghizlane, Mostafa Mrabti

“…Results demonstrate that incorporating attention significantly enhances the character accuracy rate (CAR) and word accuracy rate (WAR), with further improvements observed when using adaptive augmentation. …”
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A Survey of the Multi-Sensor Fusion Object Detection Task in Autonomous Driving by Hai Wang, Junhao Liu, Haoran Dong, Zheng Shao

“…To further explore the future development trends of multi-sensor fusion object detection, we introduce the mainstream framework Transformer model of the multi-sensor fusion object detection algorithm, and we also provide a comprehensive summary of the feature fusion algorithms used in multi-sensor fusion object detection, specifically focusing on the fusion of camera and LiDAR data. …”
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Optimizing Q-Learning for Automated Cavity Filter Tuning: Leveraging PCA and Neural Networks by Aghanim Amina, Otman Oulhaj, Oukaira Aziz, Lasri Rafik

“…To overcome these limitations, PCA is applied to minimize the dimensionality of the S11 response data, keeping only the most relevant information while improving computational efficiency. A feedforward neural network is employed to predict the PCA-reduced S-parameters, serving as a surrogate model that enables faster decision-making within the Q-learning framework. …”
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Deep Reinforcement Learning-Based Two-Phase Hybrid Optimization for Scheduling Agile Earth Observation Satellites by Guanghui Zhou, Zhicheng Jin, Dongning Liu

“…To balance solution quality and computational efficiency, a deep reinforcement learning (DRL)-based algorithmic framework is proposed. A Markov decision process (MDP) is formulated as the foundational model for the DRL architecture. …”
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Attention-Based LiDAR–Camera Fusion for 3D Object Detection in Autonomous Driving by Zhibo Wang, Xiaoci Huang, Zhihao Hu

“…Experimental validation on the nuScenes dataset demonstrates the model’s robustness in complex scenarios, achieving a mean Average Precision (mAP) of 64.5% and a 12.2% improvement over baseline methods. …”
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Intelligent resource allocation in internet of things using random forest and clustering techniques by Nahideh Derakhshanfard, Lida Hosseinzadeh, Fahimeh Rashid Jafari, Ali Ghaffari

“…Simulation results show that the proposed approach improves prediction accuracy to 94%, reduces energy consumption by 20%, and decreases response time by 10% compared to existing methods. …”
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Research on a Microexpression Recognition Technology Based on Multimodal Fusion by Jie Kang, Xiao Ying Chen, Qi Yuan Liu, Si Han Jin, Cheng Han Yang, Cong Hu

“…In this paper, we propose a microexpression recognition method based on multimodal fusion through a comparative study of traditional microexpression recognition algorithms such as LBP algorithm and CNN and LSTM deep learning algorithms. …”
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Power quality solutions for rail transport using AI-based unified power quality conditioners by D. K. Nishad, A. N. Tiwari, Saifullah Khalid, Sandeep Gupta

“…Abstract This paper proposes an artificial intelligence-based Unified Power Quality Conditioner (AI-UPQC) and a unique Dynamic K-factor PI (DKPI) algorithm for PI-UPQC to address power quality issues in electrified railway systems. …”
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Application of artificial intelligence in the diagnosis and treatment of lacrimal disorders: challenges and opportunities by PENG Xintong, LI Guangyu

“…AI has the ability to provide more precise disease identification and treatment strategies through efficient image analysis, multimodal data fusion, and deep learning algorithms. Additionally, it enables regular monitoring and dynamic adjustment of patients' conditions, improving treatment outcomes. …”
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Energy-Adaptive SGHSMC: A Particle-Efficient Nonlinear Filter for High-Maneuver Target Tracking by Chang Ho Kang, Sun Young Kim

“…The simulation employs a univariate nonstationary growth model, demonstrating improvements of 39% in tracking accuracy over the extended Kalman filter (EKF) and 29% over standard sequential Monte Carlo methods. …”
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An OFDM Signal Enhancement and Demodulation Method Based on Segmented Asymmetric Bistable Stochastic Resonance by Gaohui Liu, Xiaqiang Chu

“…The quantum particle swarm optimization algorithm is employed to fine-tune system parameters. …”
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Synthetic Data-Driven Approaches for Chinese Medical Abstract Sentence Classification: Computational Study by Jiajia Li, Zikai Wang, Longxuan Yu, Hui Liu, Haitao Song

“…Additionally, we seek to develop more accurate text classification algorithms to improve the precision of Chinese medical abstract classification. …”
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Words high-frequency drying processes simulation of wooden tangent towers in a vacuum chamber by A. N. Kachanov, D. A. Korenkov, A. A. Revkov, V. V. Maksimov, O. V. Vorkunov

“…This model is characterized by the possibility of using simple algorithms for analyzing differential equation systems based on the finite differe nce method and requiring less initial data on the drying material properties. …”
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