Research on Path Optimization of Vehicle-Drone Joint Distribution considering Customer Priority by Xiaoye Zhou, Yuhao Feng

“…Compared with the three algorithms and error analysis, the effectiveness of the model and the two-stage algorithm was verified. …”
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Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning by Wenjun XU, Silei WU, Fengyu WANG, Lan LIN, Guojun LI, Zhi ZHANG

“…In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.…”
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Towards a Standard Benchmarking Framework for Domain Adaptation in Intelligent Fault Diagnosis by Mohammed M. Farag

“…We demonstrate the framework’s capabilities and application mechanisms using a CNN classifier and an adversarial DA algorithm. Benchmarking results reveal significant accuracy drops from 99% to 36% and 45% with variances of 15% and 20% for the CWRU and PU datasets, respectively, under controlled domain shift conditions. …”
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Scaffolding decision spaces in decision support systems: Using plagiarism screening software in editorial offices by Felicitas Hesselmann

“…The implications of this shift are discussed, emphasizing the need for advancing our understanding of power dynamics inherent in algorithm–human interactions within automated decision-making systems.…”
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Predicting future morphological changes of lesions from radiotracer uptake in 18F-FDG-PET images. by Ulas Bagci, Jianhua Yao, Kirsten Miller-Jaster, Xinjian Chen, Daniel J Mollura

“…Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75 ± 1.75%. …”
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CSDK: A Chi-square distribution-Kernel method for image de-noising under the Internet of things big data environment by Lin Teng, Hang Li

“…It also shows a consistent accuracy, edge preservation, and detailed retention improvement compared to the classic de-noising algorithms.…”
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StratLearn-z: Improved photo-$z$ estimation from spectroscopic data subject to selection effects by Chiara Moretti, Maximilian Autenrieth, Riccardo Serra, Roberto Trotta, David A. van Dyk, Andrei Mesinger

“…We benchmark our results against the GPz algorithm, quantifying the performance of the two algorithms with a set of metrics. …”
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Optimization of light exposure and sleep schedule for circadian rhythm entrainment. by Jiawei Yin, A Agung Julius, John T Wen

“…We solve the time-optimal entrainment problem for the two-process model for both scenarios using an extension of the gradient descent algorithm to non-smooth systems. To illustrate the efficacy of our time-optimal entrainment strategies, we consider two common use cases: transmeridian travelers and shift workers. …”
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Research on axial compensation precision puncture control method of prostate puncture robot by Li Bing, Zhu Junwu, Yuan Lipeng

“…Then, an improved adaptive particle swarm optimization (PSO) algorithm based on Levy Flight is proposed to identify parameters of this control model for puncture prostate in this article. …”
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Analysis of the Calculation of a Plasma Sheath Using the Parallel SO-DGTD Method by Qian Yang, Bing Wei, Linqian Li, Debiao Ge

“…To demonstrate our algorithm, a plasma sheath model of the high-speed blunt cone was established based on the results of the multiphysics software, and our algorithm was used to extract the radar cross-section (RCS) versus different incident angles of the model.…”
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SART-Type Image Reconstruction from Overlapped Projections by Hengyong Yu, Changguo Ji, Ge Wang

“…Inspired by the single-source simultaneous algebraic reconstruction technique (SART), we hereby develop a multisource SART-type reconstruction algorithm regularized by a sparsity-oriented constraint in the soft-threshold filtering framework to reconstruct images from overlapped projections. …”
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RL based transmission power control for energy harvesting sensor by LIU Nanjun, JIA Riheng, XU Wentao, LI Minglu

“…Decisions were made solely based on these limited observations. The soft actor-critic (SAC) algorithm was used to control transmission power, with an appropriate reward function and action clipping method. …”
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Probabilistic phase labeling and lattice refinement for autonomous materials research by Ming-Chiang Chang, Sebastian Ament, Maximilian Amsler, Duncan R. Sutherland, Lan Zhou, John M. Gregoire, Carla P. Gomes, R. Bruce van Dover, Michael O. Thompson

“…The algorithm estimates probabilities for phase combinations without requiring additional phase space information or training. …”
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Simultaneous vehicular location and velocity detection towards 6G integrated communication and sensing by Bingpeng ZHOU, Shanshan MA

“…Joint vehicle location and velocity estimation algorithm was proposed for 6G millimeter wave integrated communication and sensing (ICAS), which was challenging due to random channel fading and multipath interference.A novel receiver state sensing (RSS) algorithm was proposed to simultaneously estimate vehicle (receiver) location and velocity, in conjunction with reflection channel estimation.Moreover, a novel multi-carrier Doppler calibration scheme was developed to reduce the disturbance of Doppler effect on RSS performance via frequency shift compensation.The impact of system parameters, e.g., signal bandwidth, the number of transceiver antenna and sub-carriers, on RSS performance was evaluated as well.It was verified by simulations that the proposed RSS algorithm outperformed state-of-the-art baseline methods due to the employed problem-specific system design.In addition, it was shown by simulations that the achieved RSS error was reduced with the increasing of sub-carrier frequency, the number of transceiver antennas and sub-carriers, and it was increased with the increasing distance between base station and vehicle receiver.Particularly, the vehicle location estimation accuracy was increasing with system bandwidth, but it was invariant with central carrier frequency, since only baseband features of received signal were employed for vehicle localization.In contrast, the vehicle velocity detection accuracy was increasing with central carrier frequency, yet it was insensitive to system bandwidth, given the fixed number of sub-carriers.…”
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Advancing Dynamic Emergency Route Optimization with a Composite Network Deep Reinforcement Learning Model by Jin Zhang, Hao Xu, Ding Liu, Qi Yu

“…This method utilizes the actor–critic framework, combined with attention mechanisms, pointer networks, and long short-term memory neural networks, to determine effective disaster relief path, and it compares the obtained scheduling scheme with the results obtained from the DRL algorithm based on the single-network model and ant colony optimization (ACO) algorithm. …”
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Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning by Wenjun XU, Silei WU, Fengyu WANG, Lan LIN, Guojun LI, Zhi ZHANG

“…In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.…”
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Bearing Fault Prediction Based on Mixed Domain Features and GWO-SVM by Xuan Zhou, Ruiyang Xia, Zhaodong Zhang, Sasa Duan, Mao Cheng, Chengjiang Zhou, Min Mao

“…First, the wavelet soft threshold is used to remove the noise of the original signal and then the empirical Fourier decomposition (EFD) is used in the decomposition and reconstruct signals. …”
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Enhanced Landslide Visualization and Trace Identification Using LiDAR-Derived DEM by Jie Lv, Chengzhuo Lu, Minjun Ye, Yuting Long, Wenbing Li, Minglong Yang

“…Finally, a threshold is determined through a fractal model, and the Mean-Shift algorithm is utilized for clustering and denoising to extract landslide traces. …”
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Variability-Aware Machine Learning Model Selection: Feature Modeling, Instantiation, and Experimental Case Study by Cristina Tavares, Nathalia Nascimento, Paulo Alencar, Donald Cowan

“…Specifically, this shift is impacting ML model selection, which is one of the key phases in this process. …”
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A Three-Stage-Concatenated Non-Linear MMSE Interference Rejection Combining Aided MIMO-OFDM Receiver and its EXIT-Chart Analysis by Jue Chen, Siyao Lu, Tsang-Yi Wang, Jwo-Yuh Wu, Chih-Peng Li, Soon Xin Ng, Robert G. Maunder, Lajos Hanzo

“…It also generates the soft information, enabling turbo equalization, wherein iterative detector and decoder iteratively exchange their soft information. …”
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