Reinforcement Learning-Based Real-Time Contrasts Control Chart Using an Adaptive Window Size by Kyuchang Chang, Seung Hwan Park

“…By automatically learning an optimal policy, the RL-RTC method eliminates the need for manual parameter tuning and enhances adaptability in dynamic process environments. …”
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A deep learning-based algorithm for the detection of personal protective equipment. by Bo Tong, Guan Li, Xiangli Bu, Yang Wang, Xingchen Yu

“…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”
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Radiative properties of a nonsingular black hole: Hawking radiation and gray-body factor by Asier Alonso-Bardaji, David Brizuela, Marc Schneider

“…This parameter is related to certain corrections expected in the context of loop quantum gravity to the classical general-relativistic dynamics. …”
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An evolutionary game of emergency rescuer dispatch considering different rescue capabilities by SUN Wenjun, ZHU Changfeng, LI Hui

“…To address the issue of imbalance between the supply and demand of rescue personnel at the early stage of emergencies, we construct an evolutionary game model for dispatching emergency rescue personnel. …”
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New design of an intelligent electromagnetic torque controller based on neural network and fractional calculus: Variable-speed wind energy systems application by Yattou El Fadili, Ismail Boumhidi

“…The main contribution of this present work is to tackle this undesirable issue that can damage the system, destroy the components, and lead the system to instability. …”
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A Phase-Cum-Time Variant Fuzzy Time Series Model for Forecasting Non-Stationary Time Series and Its Application to the Stock Market by A. J. Saleena, C. Jessy John, G. Rubell Marion Lincy

“…The concept of the model rebuilding process is applied to handle changes over each phase and the modified parameter adaptation technique is used for the time variations within each phase. …”
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Evaluation of Pore-Type Carbonate Reservoir Connectivity Based on Electrical Imaging by SUN Jianmeng, CHENG Yaodong, HE Juan, LIU Zhang, CHEN Peiyuan

“…Therefore, the evaluation of the connectivity of pore-type carbonate reservoirs is the key issue in the evaluation of carbonate reservoirs. …”
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A Semi-Analytical Model for Pressure Transient Analysis of Multiple Fractured Horizontal Wells in Irregular Heterogeneous Reservoirs by Cheng Chang, Xuefeng Yang, Weiyang Xie, Dan Dai, Yizhao Chen, Xiaojing Ji, Yanzhong Liang, Bailu Teng

“…These irregular geometries, which are commonly encountered in field applications but often oversimplified in conventional models, can substantially influence fluid flow dynamics and transient pressure behavior. To solve this critical issue, this paper presents a semi-analytical model for studying the transient pressure behavior of irregular heterogeneous reservoirs, focusing on the dynamic interactions between hydraulic fractures and the surrounding matrix. …”
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Local Auxiliary Spatial–Spectral Decoupling Transformer Network for Cross-Scene Hyperspectral Image Classification by Qiusheng Chen, Zhuoqun Fang, Zhaokui Li, Qian Du, Shizhuo Deng, Tong Jia, Dongyue Chen

“…In order to compress the model’s parameter search space, a local auxiliary global feature extraction strategy is devised. …”
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TLINet: A defects detection method for insulators of overhead transmission lines using partially transformer block. by Xun Li, Yuzhen Zhao, Yang Zhao, Zhun Guo, Yongming Zhang, Xiangke Jiao, Baoxi Yuan

“…First, a Multi-Branch Partially Transformer Block (MBPTB) is designed to enhance the backbone's capability in capturing global features. Next, a Dynamic Downsampling Module (DyDown) is introduced to mitigate the issue of small-scale defect information blurring. …”
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Event-Triggered Adaptive Neural Network Backstepping Sliding Fault-Tolerant Control of Spacecraft Formation Flying With Input Saturation by Guogang Wang, Wankai Yuan, Xin Wang

“…Firstly, sliding mode control combined with backstepping control is used to address saturation issues. Then, neural networks, minimal parameter learning, and adaptive control are integrated to handle dynamic uncertainties and actuator failures. …”
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PINNing cerebral blood flow: analysis of perfusion MRI in infants using physics-informed neural networks by Christoforos Galazis, Christoforos Galazis, Ching-En Chiu, Ching-En Chiu, Tomoki Arichi, Anil A. Bharath, Anil A. Bharath, Marta Varela, Marta Varela

“…However, cerebral blood flow (CBF) estimation in infants using ASL remains challenging due to the complex interplay of network physiology, involving dynamic interactions between cardiac output and cerebral perfusion, as well as issues with parameter uncertainty and data noise. …”
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STar-DETR: A Lightweight Real-Time Detection Transformer for Space Targets in Optical Sensor Systems by Yao Xiao, Yang Guo, Qinghao Pang, Xu Yang, Zhengxu Zhao, Xianlong Yin

“…First, the improved MobileNetv4 (IMNv4) backbone network is developed to significantly reduce the model’s parameters and computational complexity. Second, group shuffle convolution (GSConv) is incorporated into the efficient hybrid encoder, which reduces convolution parameters while facilitating information exchange between channels. …”
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KFESO-based composite anti-disturbance control for distributed cooperative path following of unmanned surface vehicles by Haoyu CHEN, Haixiang XU, Xiao WEI, Jian WANG, Wei CHEN

“…Furthermore, a kinetic anti-disturbance controller is designed using the backstepping method and the dynamic surface control technique. The Lyapunov stability theory is employed to prove that all error signals in the control system are uniformly ultimately bounded. …”
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Channel attention pyramid network for remote physiological measurement by Jing Zhang, Haixin Sun, Yuhao Hu, Guanghao Zhu, Fang Liu, Boyun Yan, Jiahao Pu, Xiaohui Du, Juanxiu Liu, Lin Liu, Ruqian Hao, Xingguo Wang, Yong Liu

“…Abstract Remote photoplethysmography (rPPG) is an emerging contactless physiological parameter detection method utilizing cameras, showing great promise as a forefront technology for remote health assessment. …”
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An Integrated Mechanical Fault Diagnosis Framework Using Improved GOOSE-VMD, RobustICA, and CYCBD by Jingzong Yang, Xuefeng Li

“…First, to mitigate modal aliasing issues caused by empirical parameter dependency in VMD, we fuse a refraction-guided reverse learning mechanism with a dynamic mutation strategy to develop the IGOOSE. …”
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Exploring the Drive Motor of Electric Vehicles: Structure, Temperature Rises, and Operational Control of Permanent Magnet Motors by Zhongxian Chen, Jiayin Liu

“…The analysis reveals that the structural design is crucial for both the static and dynamic performance of permanent magnet motors. Additionally, it is imperative to identify an optimal trade-off among various performance parameters in these motors. …”
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Non-Fragile Estimation for Nonlinear Delayed Complex Networks with Random Couplings Using Binary Encoding Schemes by Nan Hou, Weijian Li, Yanhua Song, Mengdi Chang, Xianye Bu

“…This paper aims to conduct a non-fragile state estimation such that, in the presence of some variations/perturbations in the gain parameter of the estimator, the estimation error dynamics will reach exponential ultimate boundedness in mean square and the ultimate bound will be minimized. …”
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Rock Mechanical Properties and Breakdown Pressure of High-Temperature and High-Pressure Reservoirs in the Southern Margin of Junggar Basin by Mingwei Kong, Zhaopeng Zhang, Chunyan Zhao, Huasheng Chen, Xinfang Ma, Yushi Zou

“…Secondly, empirical formulas related to the transformation of dynamic and static mechanical parameters in the regional strata were proposed. …”
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Global Fixed-Time Fault-Tolerant Control for Tracked Vehicles with Hierarchical Unknown Input Observers by Xihao Yan, Dongjie Wang, Aixiang Ma, Weixiong Zheng, Sihai Zhao

“…First, a kinematic and dynamic model of the TMV is established considering side slip and track slip, and its linear parameter-varying (LPV) model is constructed through parameter-dependent linearization. …”
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