Three-Dimensional Path Following Control for Underactuated AUV Based on Ocean Current Observer by Long He, Ya Zhang, Shizhong Li, Bo Li, Zeihui Yuan

“…Accounting for uncertainties like variable ocean currents, this research establishes the AUV’s kinematics and dynamics models and formulates the tracking error within the Frenet–Serret coordinate system. …”
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Distributed Cooperative Disturbance-Rejection Control of Hybrid Alternating Current/Direct Current Distribution Grids with Multiple Inverters by QUAN Shaoli, YU Haozheng, MA Jie, WANG Weiyu, GUO Yong, CHEN Chun

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Critical velocity criterion of explosive charges initiated by fragment impact considering impact angle and charge radius by Hao Cui, Junan Wu, Yuxin Xu, Pu Song, Rui Guo

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Optimization and Modelling of Fracture Height in SECC Cylindrical Cup Deep Drawing Processes by Quy-Huy Trieu, The Thanh Luyen, Duc-Toan Nguyen

“…These findings represent a substantial advancement in deep drawing processes technology, particularly in reducing error rates during the production of cylindrical cups.…”
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Comparison Principle Based Synchronization Analysis of Fractional-Order Chaotic Neural Networks with Multi-Order and Its Circuit Implementation by Rongbo Zhang, Kun Qiu, Chuang Liu, Hongli Ma, Zhaobi Chu

“…In this paper, we explore three aspects of the research challenges, i.e., theoretical limitations of uncertain IFO systems, the fragility of the synchronization controller, and the lack of circuit implementation. …”
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GIS isolation switch contact temperature wireless monitoring by Liu Haoli, Li Jiaqi, Zhang Jiuye, Zhao Yubo, Zhang Jinhua, Wang Liang

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Development of Low-Cost Single-Chip Automotive 4D Millimeter-Wave Radar by Yongjun Cai, Jie Bai, Hui-Liang Shen, Libo Huang, Bing Rao, Haiyang Wang

“…The maximum measurement error is approximately ±0.2° for azimuth angles within the range of ±30° and around ±0.4° for elevation angles within the range of ±13°. …”
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A global dataset of average specific yield for soils by Meizhao Lv, Meixia Lv, Yuanyuan Zha, Lei Wang, Zong-Liang Yang

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Forecasting of virtual power plant generating and energy arbitrage economics in the electricity market using machine learning approach by Tirunagaru V. Sarathkumar, Arup Kumar Goswami, Baseem Khan, Kamel A. Shoush, Sherif S. M. Ghoneim, Ramy N. R. Ghaly

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A vitamin intervention study on the tumour and immune cells via TIV dynamical system-revisited by Khushbu Agrawal, Sunil Kumar, Badr Saad T. Alkahtani, Sara Salem Alzaid

“…Boundedness and non-negativity, residual error and convergence analysis of solutions have been determined using the iterative approach and BWCM. …”
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Deep neural architectures for Kashmiri-English machine translation by Syed Matla Ul Qumar, Muzaffar Azim, S. M. K. Quadri, Mohannad Alkanan, Mohammad Shuaib Mir, Yonis Gulzar

“…We further provide a structured linguistic error analysis and validate the significance of performance differences through bootstrap resampling. …”
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Enhancing Intermittent Spare Part Demand Forecasting: A Novel Ensemble Approach with Focal Loss and SMOTE by Saskia Puspa Kenaka, Andi Cakravastia, Anas Ma’ruf, Rully Tri Cahyono

“…The approach was empirically validated by comparing the model’s Mean Squared Error (MSE) performance and Area Under the Curve (AUC). …”
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Time-Modulated Array-Based Rotating Electric-Field Vector Method for Extracting Angle Information by Geon U Kim, Sang-Hwa Yi, Jeong Phill Kim

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Experimental and Numerical Study of Shape Memory Alloys for Vibration Amplitude Reduction in Mechanical Structures by Hyginus Chidiebere Onyekachi Unegbu, Danjuma Saleh Yawas, Bashar Dan-asabe, Abdulmumin Akoredeley Alabi

“…A finite element model was developed to simulate the behavior of the system, showing strong correlation with experimental data, with a root mean square error (RMSE) of less than 4%. The validated model was further used to predict SMA performance under conditions not tested experimentally, confirming its reliability for broader applications. …”
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Radial Basis Neural Network Construction and Training for Telegraph-Code Structure Reception by D. A. Chistoprudov, V. A. Kozlov, M. R. Bibarsov, D. A. Potyagov, N. Ya. Karasik

“…On the basis of these results the code distance is determined, which ensures the minimum recognition error probability. The results obtained in the developed neural network classifier are compared with those obtained in correlation receivers operating in the signal time and frequency domains. …”
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Immunological biomarkers associated with survival in a cohort of Argentinian patients with common variable immunodeficiency by Adrian Kahn, MD, PhD, Gabriela Luque, BSc, Eduardo Cuestas, MD, PhD, Ana Basquiera, MD, PhD, Brenda Ricchi, BSc, Klaus Schmitz-Abe, PhD, Louis-Marie Charbonnier, MD, Mehdi Benamar, PhD, Ruben Dario Motrich, PhD, Talal A. Chatila, MD, PhD, Virginia E. Rivero, PhD

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A new high-resolution hydrodynamic model for the coastal Beaufort Sea in the Arctic Ocean: model construction and evaluation by J. Blake Clark, J. Blake Clark, Wesley Moses, Ahmed El-Habashi, Maria Tzortziou, Kyle J. Turner, Hisatomo Waga, Hisatomo Waga, Steven Ackelson, Jonathan Sherman, Jonathan Sherman

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Case Report: Hydroa vacciniforme-like lymphoproliferative disorder, an EBV-associated disease, successfully treated with hematopoietic stem cell transplantation by Eduardo Liquidano-Perez, Eduardo Liquidano-Perez, Gibert Maza-Ramos, Marco Yamazaki-Nakashimada, Rodolfo Rodríguez-Jurado, Alfonso G. Ramírez Ristori, Juan Carlos Bustamante-Ogando, Mario Ernesto Cruz-Munoz, Arturo Gutierrez-Guerrero, Marimar Saez-de-Ocariz, Sara Espinosa-Padilla, Nideshda Ramirez-Uribe, Selma C. Scheffler-Mendoza

“…Further research in this area is crucial to understand the immunological basis of HVLD. …”
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Leaf carbon nitrogen and phosphorus concentrations in dominant trees across China’s forests from 2005 to 2020 by Chenxi Li, Honglin He, Xiaoli Ren, Qian Xu, Shiyu Dong, Zining Lin, Luxiang Lin, Zexin Fan, Yongbiao Lin, Juxiu Liu, Qingkui Wang, Anzhi Wang, Ruiying Chang, Zongqiang Xie, Lingli Liu, Fusun Shi

“…The dataset underwent rigorous quality control, including unit harmonization, error checking, and outlier detection, and is provided in accessible CSV format. …”
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Comparing the Efficiency of Sediment Rating Curve and ANN Models in Estimating River Bed-load by Jamal Mosaffaie, Amin Saleh pourjam, Mahmudreza Tabatabaei

“…This means that observed and estimated values ​​of the ANN model are closer together than SRC model, so estimations of ANN model are more accurate. The Root Mean Square Error index (RMSE) for ANN model is also smaller than the SRC model in all stations, so that the sum of five stations RMSE for ANN and SRC models were 2505.7 and 5195.3 respectively. …”
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