A Novel Nonlinear Adaptive Control Method for Longitudinal Speed Control for Four-Independent-Wheel Autonomous Vehicles by Jinhua Zhang, Zhenghao Chen, Jinshi Yu

“…Based on the design of the upper controller, an innovative optimized longitudinal force distribution strategy and the construction of a tire reverse longitudinal slip model are proposed, followed by the design of a fuzzy PID controller as the lower slip ratio controller to achieve precise whole-vehicle longitudinal speed tracking and improve overall control performance. …”
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Masks-to-Skeleton: Multi-View Mask-Based Tree Skeleton Extraction with 3D Gaussian Splatting by Xinpeng Liu, Kanyu Xu, Risa Shinoda, Hiroaki Santo, Fumio Okura

“…Furthermore, we use a minimum spanning tree (MST) algorithm during the optimization loop to regularize the graph to a tree structure. …”
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Energy-based segmentation methods for images with non-Gaussian noise by Jiatao Zhong, Shiyin Du, Canruo Shen, Yiting Chen, Min Gao, Medha Naidu, Xiaoping Shi, Yuejiao Fu

“…We apply the Kullback–Leibler (KL) divergence to demonstrate the feasibility of our method for non-Gaussian noisy images. Notably, the algorithm automatically determines whether the model is solvable using a Gaussian approach and, if not, effortlessly switches to a non-Gaussian alternative. …”
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Infrared Small Target Detection Based on Compound Eye Structural Feature Weighting and Regularized Tensor by Linhan Li, Xiaoyu Wang, Shijing Hao, Yang Yu, Sili Gao, Juan Yue

“…Experimental results demonstrate that the proposed model can rapidly and accurately detect small infrared targets in bio-inspired compound eye image sequences, outperforming other comparative algorithms.…”
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Real-Time Human Group Detection and Clustering in Crowded Environments Using Enhanced Multi-Object Tracking by Hyunmin Lee, Donggoo Kang, Hasil Park, Sangwoo Park, Dasol Jeong, Joonki Paik

“…To address these limitations, we propose a novel algorithm that integrates an optimized YOLOv8 model with DeepSORT tracking, enhancing both detection accuracy and real time performance. …”
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Advances in the application of nomograms for patients with gastric cancer associated with peritoneal metastasis by Shiyang Jin, Zeshen Wang, Qiancheng Wang, Zhenglong Li, Xirui Liu, Kuan Wang

“…For instance, Ji et al. constructed a nomogram integrating PCI, preoperative tumor markers, and peritoneal metastasis duration, achieving an area under the ROC curve (AUC) of 0.985 for overall survival prediction. Imaging-based models leverage CT radiomics and deep learning algorithms to detect occult PM, with Huang et al.’s deep learning model attaining an AUC of 0.900. …”
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Spatiotemporal tensor analysis for effective information mining of hydraulic structures considering environmental excitation and vibration response by Hui Li, Zhang Han, Tengfei Bao, Xiaohan Duan, Guang Yang, Xianyu Xiong, Yibo Ouyang, Jiankang Lou

“…The time-weighted modified dynamic time warping theory and curvature smoothing algorithm were combined to construct the optimal filter model with a balancing factor to extract the effective information from vibration response. …”
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Research on intelligent energy management strategies for connected range-extended electric vehicles based on multi-source information by Xuewen Zhai, Hanwu Liu, Wencai Sun, Zihang Su

“…The Euclidean distance between consecutive traffic scenario matrices is used as a basis for similarity to optimize speed and predict future vehicle speeds. Moreover, a multi-objective intelligent EMS based on deep reinforcement learning (DRL) is employed, utilizing the Deep Deterministic Policy Gradient (DDPG) algorithm to comprehensively consider vehicle dynamics, energy consumption economy, and the degradation of batteries. …”
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Reconstruction for Scanning LiDAR with Array GM-APD on Mobile Platform by Di Liu, Jianfeng Sun, Wei Lu, Sining Li, Xin Zhou

“…This method avoids the need for field-of-view registration, improves data utilization, and reduces the complexity of the algorithm while eliminating the effect of LiDAR motion. …”
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Online variational Gaussian process for time series data by Weidong Wang, Mian Muhammad Yasir Khalil, Leta Yobsan Bayisa

“…Unlike traditional methods that rely on a fixed number of inducing points, OLVGP adaptively adjusts the number of inducing points as new data arrives and optimizes them from the model, ensuring that the model remains computationally efficient while maintaining high predictive accuracy. …”
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Research on ionospheric parameters prediction based on deep learning by Yuntian FENG, Xia WU, Xiong XU, Rongqing ZHANG

“…For ionospheric parameter prediction, the short-term and daily mean value prediction of ionospheric parameters was established by long short-term memory (LSTM) predictive neural network modeling.Two methods of point-by-point prediction and sequence prediction were utilized.Furthermore, in order to predict the hourly and daily changes of ionospheric parameters, the proposed scheme was optimized by multidimensional prediction and empirical mode decomposition (EMD) algorithm.Finally, the feasibility of the proposed optimization algorithm in improving the prediction accuracy of ionospheric parameters is verified.…”
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Random Natural Gradient by Ioannis Kolotouros, Petros Wallden

“…Hybrid quantum-classical algorithms appear to be the most promising approach for near-term quantum applications. …”
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Radiomic Features of Mesorectal Fat as Indicators of Response in Rectal Cancer Patients Undergoing Neoadjuvant Therapy by Francesca Treballi, Ginevra Danti, Sofia Boccioli, Sebastiano Paolucci, Simone Busoni, Linda Calistri, Vittorio Miele

“…Key clinical and imaging parameters, such as age, TNM stage, CRM involvement, and EMVI presence, were recorded. A radiomic model was developed using the LASSO algorithm for feature selection and regularization from 107 extracted radiomic features. …”
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Estimating the Risk of Lower Extremity Complications in Adults Newly Diagnosed With Diabetic Polyneuropathy: Retrospective Cohort Study by Alyce S Adams, Catherine Lee, Gabriel Escobar, Elizabeth A Bayliss, Brian Callaghan, Michael Horberg, Julie A Schmittdiel, Connie Trinacty, Lisa K Gilliam, Eileen Kim, Nima S Hejazi, Lin Ma, Romain Neugebauer

“…While data-driven diabetic polyneuropathy algorithms exist, high-performing, clinically useful tools to assess risk are needed to improve clinical care. …”
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Maximizing the biochemical resolving power of fluorescence microscopy. by Alessandro Esposito, Marina Popleteeva, Ashok R Venkitaraman

“…We describe optimized imaging protocols, provide optimization algorithms and describe precision and resolving power in biochemical imaging thanks to the analysis of the general properties of Fisher information in fluorescence detection. …”
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The ensemble transform Schmidt–Kalman filter: A novel method to compensate for observation uncertainty due to unresolved scales by Zackary Bell, Sarah L. Dance, Joanne A. Waller

“…Observation error due to unresolved scales occurs when there is a difference in scales observed and modeled. To obtain an optimal estimate through data assimilation, the error due to unresolved scales must be accounted for in the algorithm. …”
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Intelligent Charging Navigation for Electric Vehicles Based on Real-time Electricity Price by Rui WU, Liangsong ZHOU, Zhandong YAO

“…Regarding this kind of problem, an electric vehicle intelligent charging navigation strategy based on real-time electricity price is proposed, where the PSO-GA algorithm is used to solve the optimal scheme. The motivation is to guide the EV charging toward an orderly way by virtue of the real-time electricity price mechanism. …”
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A 3D reconstruction platform for complex plants using OB-NeRF by Sixiao Wu, Changhao Hu, Boyuan Tian, Yuan Huang, Shuo Yang, Shanjun Li, Shengyong Xu

“…Furthermore, the precision of the reconstruction was enhanced by optimizing camera poses. An exposure adjustment phase was integrated to improve the algorithm's robustness in uneven lighting conditions. …”
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Externally bonded reinforcement side extended (EBRSE) technique to postpone debonding of FRP laminates in strengthened concrete elements by Mehdi Aghabagloo, Laura Carreras, Cristina Barris, Alba Codina, Marta Baena

“…Additionally, a numerical approach was applied, combining the finite difference method with a metaheuristic optimization algorithm, to derive the bond-slip law governing the constitutive behavior of both systems. …”
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Non‐local low‐rank constraint‐based self‐consistent PMRI reconstruction using eigenvector maps by Jizhong Duan, Ting Pan, Yu Liu, Junfeng Wang

“…Recently, the L1 norm and total variation were combined with the ESPIRiT model to improve the reconstruction quality of magnetic resonance (MR) images. …”
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