Tracking Control of Wave-Adaptive Modular Unmanned Surface Vehicle Using Time-Delay Zeroing Neural Network by Pengfei Guo, Wenyue Zhang, Zheng Li, Zheng Zheng

“…In this paper, we begin by developing two high-order backward finite difference formulas (BFDFs) with a second-order truncation error. These formulas are used to approximate the second and third derivatives of smooth functions. …”
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On the Design of Near-Optimal Generalized Block-Based Spatial Modulation With Low Detection Complexity by Yen-Ming Chen, Wei-Lun Lin, Heng Lee, Tsung-Lin Chen

“…Secondly, a codebook-assisted tree-search detector (CATSD) is introduced, offering a 98% reduction in complexity compared to ML detection while maintaining near-ML error performance. Finally, an alternative codebook search method is presented, accompanied by a complexity analysis that reveals a favorable trade-off between performance and computational cost.…”
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Accurate and Efficient End‐Effector Tracking for Quadrupedal Mobile Manipulators through Coordinated Motion and Decoupled Control by Kun Xu, Qikai Li, Yuhang Zhao, Jiawei Chen, Xilun Ding

“…Finally, a series of experiments demonstrate that the proposed method can successfully perform a variety of trajectory‐tracking tasks, reducing the root mean squared error by 82.7% compared to independent control in the stance mode, and cutting additional computational overhead by 53.4% compared to the unified control.…”
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Fiber-Optic Vector Magnetic Field Sensor Based on Mode Interference and Magnetic Fluid in a Two-Channel Tapered Structure by He Tian, Yuxiao Song, Yanzeng Li, Hanyang Li

“…The experimental results are well consistent with the numerical simulation results and show that the sensitivity of this sensor reaches up to 244 pm/mT, with the direction error being merely ±1.4°. Therefore, the proposed sensor exhibits a unique sensitivity for the measurement of magnetic field intensity and direction in 3D space, which makes it best suitable for applications in transportation, medicine, and smart device.…”
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An Improved Soft Actor–Critic Task Offloading and Edge Computing Resource Allocation Algorithm for Image Segmentation Tasks in the Internet of Vehicles by Wei Zou, Haitao Yu, Boran Yang, Aohui Ren, Wei Liu

“…The results demonstrate that the proposed PER-iSAC significantly reduces task allocation error rates and optimizes task completion times. …”
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Comparative study of interpretable and black-box machine learning for modeling mechanical and tribological properties of 3D-printed PLA/date pits composites by Ahmed Asker, Ahmed Fouly, Mohamed G. B. Atia, Hany S. Abdo, Omar Salah

“…SLSSR constructs models using no more than five basis functions and achieves a mean absolute error of less than 2%, ensuring both accuracy and model transparency. …”
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A novel sequential approach through structural enhancements for designing a new serrated helical heat exchanger by Mohamed A. Hamied, Mina Atta, Pedro García-Regodeseves, Juan Carlos Ríos-Fernández

“…All the numerical models are investigated using k-epsilon turbulence model for cold shell flow rate 2–6 kg/min which is commonly used in different industrial applications. The performance of the numerical model for the heat exchanger was validated by comparison with experimental data and previously published experimental and numerical studies, demonstrating a maximum error of approximately 2 %. …”
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Robust event-triggered control algorithm for ship dynamic positioning considering dynamic characteristics of actuators by Bo LI, Guoqing ZHANG, Xianku ZHANG, Hongguang LÜ

“…In addition, the adaptive parameters are updated online and designed to compensate for the gain uncertainty of the actuators, which reduces the computational load and ensures that the ship can perform dynamic positioning tasks stably.ResultsThe Lyapunov stability theory is used to prove that all error variables in the closed-loop control system satisfy semi-global uniformly ultimately bounded (SGUUB) stability, and the effectiveness of the proposed algorithm is verified through comparison with a simulation.ConclusionsThe results of this study can provide useful references for promoting the development of intelligent ship equipment.…”
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0.91 V reference, 3.3 ppm/°C Sub-BGR with second-order compensation and improved PSRR by Chokkakula Ganesh, Satheesh Kumar S, A. Shanthi, Sk Shoukath Vali

“…The second-order compensation method is implemented for design through an optimized error amplifier and a resistor network with a significantly better temperature coefficient performance. …”
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Least-Squares-Based Deep Learning for Sentinel-2 Derived Bathymetry: A Case Study on Anegada’s Southern Coast by Y. Liu, A. Amiri-Simkooei, R. Lindenbergh, M. Snellen

“…LBSDL depth estimation achieved a root-mean-square error (RMSE) of 2.74 m, representing around 10% of the maximum observed depth, with the best performance in the 2–15 m depth range. …”
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A Hybrid Deep Learning Approach for Improved Detection and Prediction of Brain Stroke by Gayatri Thakre, Rohini Raut, Chetan Puri, Prateek Verma

“…Traditional diagnostic procedures, such as manually interpreting clinical images, are time consuming and error prone. This research investigates the use of hybrid deep learning models, such as recurrent neural networks (RNNs), long short-term memory (LSTM), and convolutional neural networks (CNNs), to improve stroke prediction accuracy. …”
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Moisture Evaluation of Oil-Immersed Insulation in Bushings Based on Frequency Domain Spectroscopy and Grey Relational Analysis by Xianhao Fan, Sheng Li, Tengyue Sun, Yiyi Zhang, Jiefeng Liu

“…The results showed that the average relative (absolute error) is less than 14.6% (0.17%). …”
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Artificial Intelligence-Based Transmission Frequency Prediction in Cable Systems Using Electromagnetic Field Data by Abbas Seif, Hamid Radmanesh, Amir Ahmarinejad, Ahmad Ali Ashrafian

“…To enhance precision, a hybrid neural network—combining transformer, LSTM, and a physics-informed layer grounded in Maxwell’s equations—is proposed, reducing the error to 0.2 MHz (749.8 MHz prediction). The AI approach demonstrates superior computational efficiency while maintaining high accuracy. …”
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Determining Non-Dimensional Group of Parameters Governing the Prediction of Penetration Depth and Holding Capacity of Drag Embedment Anchors Using Linear Regression by Mojtaba Olyasani, Hamed Azimi, Hodjat Shiri

“…To evaluate model performance and identify the most accurate LR models to predict DEA behavior, comprehensive sensitivity, error, and uncertainty analyses were performed. Additionally, LR analysis revealed the most influential input parameters impacting penetration depth and holding capacity. …”
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Quantitative evaluation of increased overpressure from tectonic compression stress and its significance—A case study from the Dabei Gas Field in Kuqa Depression by Gang Wang, Chang-Yu Fan, Zhen-Liang Wang, Hai-Jun Yang, Qing-Kuan Wu

“…This clarifies the stress–strain–pressure coupling process, and provides a quantitative evaluation model with high applicability and accuracy. Applied to the Dabei Gas Field, the results show: (a) IOTCS ranges from 80 to 220 MPa with a 6% relative error compared to aqueous inclusions pressures, indicating high accuracy; (b) IOTCS limits shear fracture development, leading to high fracture density in low fluid pressure zones; and (c) IOTCS increases the driving force for hydrocarbon migration by 1.8 to 2.1 times compared to non-IOTCS conditions.…”
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Model-agnostic meta-learning-based region-adaptive parameter adjustment scheme for influenza forecasting by Jaeuk Moon, Yoona Noh, Sungwoo Park, Eenjun Hwang

“…We experimentally show that MARAPAS outperforms other MAML-based methods, in terms of root mean square error and Pearson correlation coefficient. Particularly, this scheme improves the forecasting performance by up to 34 % compared with that of the state-of-the-art schemes. …”
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Determination of sugar in tangerines by fluorescence with an Improved partial least squares (PLS) algorithm by Lei Liu, Chunzhong Li, Haiyi Bian, Ahmed N Abdalla, Hua Yao, Wen Li

“…The result approved validation dataset’s R -square and root-mean-square error were 0.9777 and 0.002992, respectively. These findings open the door to broader applications in the citrus industry and beyond, with the potential for automating the analysis process and improving overall quality control.…”
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Extremely High-Efficiency Coupling Method for Hollow-Core Photonic Crystal Fiber by Danyun Fan, Zhiqiang Jin, Guanghui Wang, Fei Xu, Yanqing Lu, Dora Juan Juan Hu, Lei Wei, Ping Shum, Xuping Zhang

“…In addition, our proposed method is coaxiality error free, angle deviation free, and insertion length insensitive. …”
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BLE phase-based ranging: accuracy and capability under strong Wi-Fi interference by Igor Kravets, Nazarii Kotliar, Oleksandr Karpin, Andriy Luchechko

“…We show the random distance error increasing more than 3 times for both Inverse Fourier Transform and Multiple Signal Classification algorithms at short distances. …”
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Artificial Intelligence in IVF Laboratories: Elevating Outcomes Through Precision and Efficiency by Yaling Hew, Duygu Kutuk, Tuba Duzcu, Yagmur Ergun, Murat Basar

“…This comprehensive review examines the effects of AI on IVF laboratories, focusing on its role in automating processes such as embryo and sperm selection, optimizing clinical outcomes, and reducing human error. AI’s data analysis and pattern recognition capabilities offer valuable predictive insights, enhancing personalized treatment plans and increasing success rates in fertility treatments. …”
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