Modeling of train flow handling through a limiting single-track section of the route at the organization of high-speed operation using the existing infrastructure by S. V. Karasev, A. D. Kalidova

“…The article examines the problem of studying the process of handling the opposing train flows through a single track section of the route by modeling for the conditions of organizing high-speed operation while minimizing capital investments in infrastructure. …”
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Adaptive Multi-Robot Exploration for Unknown Environments Using Edge-Weighted Path Planning by Farhad Baghyari, Tyler Parsons, Jaho Seo, Byeongjin Kim, Mingeuk Kim, Hanmin Lee

“…Experimental results demonstrate that the algorithm achieves improved exploration efficiency and adaptability compared to a real-time scheduling method while maintaining computational feasibility. …”
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Comparing MEG and EEG measurement set-ups for a brain-computer interface based on selective auditory attention. by Dovilė Kurmanavičiūtė, Hanna Kataja, Lauri Parkkonen

“…Auditory attention modulates auditory evoked responses to target vs. non-target sounds in electro- and magnetoencephalographic (EEG/MEG) recordings. Employing whole-scalp MEG recordings and offline classification algorithms has been shown to enable high accuracy in tracking the target of auditory attention. …”
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Channel-Hopping Using Reinforcement Learning for Rendezvous in Asymmetric Cognitive Radio Networks by Dongsup Jin, Minho Jang, Ji-Woong Jang, Gyuyeol Kong

“…This paper addresses the rendezvous problem in asymmetric cognitive radio networks (CRNs) by proposing a novel reinforcement learning (RL)-based channel-hopping algorithm. Traditional methods like the jump-stay (JS) algorithm, while effective, often struggle with high time-to-rendezvous (TTR) in asymmetric scenarios where secondary users (SUs) have varying channel availability. …”
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Dense Matching with Low Computational Complexity for Disparity Estimation in the Radargrammetric Approach of SAR Intensity Images by Hamid Jannati, Mohammad Javad Valadan Zoej, Ebrahim Ghaderpour, Paolo Mazzanti

“…Notably, unlike traditional local and global models, the computational complexity of the proposed approach remains stable as the input size or kernel dimensions increase while memory consumption stays low. Compared to a pyramid-based local normalized cross-correlation (NCC) algorithm and adaptive semi-global matching (SGM) models, the proposed method maintains good accuracy comparable to adaptive SGM while reducing processing time by up to 50% relative to pyramid SGM and achieving a 35-fold speedup over the local NCC algorithm with an optimal kernel size. …”
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Basketball teaching methods based on 3D-Convolutional neural network by Chao Huang, Xian Wu

“…The optimized algorithm is then used for video skilled movement detection processing to obtain cropped frame images. …”
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Research on pedestrian detection technology for mining unmanned vehicles by ZHOU Libing, YU Zhengqian, WEI Jianjian, JIANG Xueli, YE Baisong, ZHAO Yexin, YANG Siliang

“…YOLOv3 and a coal mine key position personnel unsafe behavior recognition method based on improved YOLOv7 and ByteTrack experienced missed detections and false positives based on enhanced images, while the proposed pedestrian detection algorithm effectively mitigated these issues.…”
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Improved Cylinder-Based Tree Trunk Detection in LiDAR Point Clouds for Forestry Applications by Shaobo Ma, Yongkang Chen, Zhefan Li, Junlin Chen, Xiaolan Zhong

“…While cylinder fitting algorithms provide a three-dimensional (3D) solution for trunk detection, their performance in complex forest environments remains limited due to sensitivity to parameters like distance thresholds. …”
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What Strategy Central Nervous System Uses to Perform a Movement Balanced? Biomechatronical Simulation of Human Lifting by Ali Leylavi Shoushtari

“…To solve the kinematic redundancy in previous studies it is hypothesize that CNS functions as an optimizer, such of that are the task-based algorithms which search to find optimal solution for each specific task. …”
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Robust design of bicycle infrastructure networks by Christoph Steinacker, Mads Paulsen, Malte Schröder, Jeppe Rich

“…Interestingly, while the more complex optimization models yield better overall welfare results, the improvements over simpler methods are small. …”
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Electric Bus Charging Schedules Relying on Real Data-Driven Targets Based on Hierarchical Deep Reinforcement Learning by Jiaju Qi, Lei Lei, Thorsteinn Jonsson, Lajos Hanzo

“…As a result, the high-level agent learns an effective policy for prescribing the charging targets for every charging period, while the low-level agent learns an optimal policy for setting the charging power of every time step within a single charging period, with the aim of minimizing the charging costs while meeting the charging target. …”
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Personal air cleaning by a user-tracking robot equipped with a nanofiber air cleaner in a large work space by Chengzhong Deng, Zhuolun Niu, Chun Chen

“…Experiments were conducted to measure the clean air delivery rate (CADR) of the nanofiber air cleaner, evaluate the accuracy of the user-tracking algorithm, and determine the optimal deflector setup and user-to-robot distance. …”
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ZZ-YOLOv11: A Lightweight Vehicle Detection Model Based on Improved YOLOv11 by Zhe Zhang, Zhongyang Zhang, Gang Li, Chenxi Xia

“…Experimental data on the optimized KITTI and BDD100K datasets show that the detection accuracy of the ZZ-YOLO algorithm is 70.9%, the mAP (mean Average Precision) @0.5 is 58%, the model-parameter quantity is 14.1GFLOPs compared to the original algorithm, the detection accuracy is increased by 5.7%, and the average precision is increased by 2.3%. …”
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Perceiving Fifth Facade Colors in China’s Coastal Cities from a Remote Sensing Perspective: A New Understanding of Urban Image by Yue Liu, Richen Ye, Wenlong Jing, Xiaoling Yin, Jia Sun, Qiquan Yang, Zhiwei Hou, Hongda Hu, Sijing Shu, Ji Yang

“…Through developing an innovative natural color optimization algorithm, the oversaturation and color bias of Sentinel-2 imageries were addressed. …”
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Hybrid precoding method for mmWave massive MIMO systems based on LFM by Haoyi CHEN, Yifan DING, Ying CHENG

“…Analog-digital hybrid precoding is a key technology for millimeter wave massive MIMO systems that reduce hardware costs while balancing system performance.However,the traditional hybrid precoding scheme often needed to find a suitable codebook for precoding,and some codebooks were not easy to obtain or had deviations in actual situations.An analog-digital hybrid precoding method based on latent factor model (LFM) in machine learning without codebook was proposed for this problem.The LFM decomposition and stochastic gradient descent method were used to approximate the designed precoding matrix to the optimal full digital precoding matrix for good performance.The simulation results show that compared with the hybrid precoding design method based on orthogonal matching pursuit (OMP) algorithm,this method not only does not need a codebook,but also has better performance than the hybrid precoding algorithm based on OMP algorithm,which is closer to optimal full digital precoding method.…”
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Obstacle Avoidance of Surface Agent Formation Based on Streamline Traction at Fixed-Time by Yiping Liu, Yameng Niu, Jianqiang Zhang, Weihao Tao

“…The optimal guiding angular velocity signal is obtained through quadratic programming, ensuring that the SA steers towards the designated position while avoiding obstacles. …”
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Multi-Armed Bandit Approaches for Location Planning with Dynamic Relief Supplies Allocation Under Disaster Uncertainty by Jun Liang, Zongjia Zhang, Yanpeng Zhi

“…We introduce a multi-armed bandit algorithm, named the Geometric Greedy algorithm, to optimize transfer station planning while accounting for subsequent dynamic relief supply distribution and allocation in a stochastic environment. …”
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Stability Study of Distributed Drive Vehicles Based on Estimation of Road Adhesion Coefficient and Multi-Parameter Control by Peng Ji, Fengrui Han, Yifan Zhao

“…First, a seven-degree-of-freedom (7-DOF) vehicle dynamics model is established and optimized with a layered control strategy. The upper-level control module calculates the desired yaw rate and sideslip angle using the two-degree-of-freedom (2-DOF) vehicle model and estimates the road adhesion coefficient by using the singular-value optimized cubature Kalman filtering (CKF) algorithm; the middle-level utilizes the second-order sliding mode controller (SOSMC) as a direct yaw moment controller in order to track the desired yaw rate and sideslip angle while also employing a joint distribution algorithm to control the torque distribution based on vehicle stability parameters, thereby enhancing system robustness; and the lower-level controller performs optimal torque allocation based on the optimal tire loading rate as the objective. …”
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Faster quantum subroutine for matrix chain multiplication via Chebyshev approximation by Xinying Li, Pei-Lin Zheng, Chengkang Pan, Fei Wang, Chunfeng Cui, Xian Lu

“…The algorithm can be applied to any complex matrix. Furthermore, we discuss integrating our QMM algorithm as a subroutine in other matrix operations and propose strategies to optimize QMM for matrices with large condition numbers with numerical simulation.…”
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GYS-RT-DETR: A Lightweight Citrus Disease Detection Model Based on Integrated Adaptive Pruning and Dynamic Knowledge Distillation by Linlin Yang, Zhonghao Huang, Yi Huangfu, Rui Liu, Xuerui Wang, Zhiwei Pan, Jie Shi

“…Secondly, the model adopts two model optimization strategies: (1) The Group_taylor local pruning algorithm is used to reduce memory occupation and the number of computing parameters of the model. (2) The feature-logic knowledge distillation framework is proposed and adopted to solve the problem of information loss caused by the structural difference between teachers and students, and to ensure a good detection performance, while realizing the lightweight character of the model. …”
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