Insulator Partial Discharge Localization Based on Improved Wavelet Packet Threshold Denoising and <inline-formula><math display="inline"><semantics><mrow><msub><mrow><mi mathvarian... by Hongxin Ji, Zijian Tang, Chao Zheng, Xinghua Liu, Liqing Liu

“…With the sensor array designed in this paper, the relative localization error is 3.46%, and the absolute error is within 6 cm, which meets the requirements of engineering applications.…”
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Improved Sliding Mode Active Disturbance Rejection Control for Single-inductance Dual-output Buck Converter by HUANG Jinfeng, ZHOU Jie

“…Additionally, the steady-state error bounds of CRESO and the convergence time of the enhanced TSMC are derived.Results and DiscussionsA simulation and experimental platform for the SIDO Buck converter is established. …”
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Ultra-Wideband Analog Radio-over-Fiber Communication System Employing Pulse-Position Modulation by Sandis Migla, Kristaps Rubuls, Nikolajs Tihomorskis, Toms Salgals, Oskars Ozolins, Vjaceslavs Bobrovs, Sandis Spolitis, Arturs Aboltins

“…To enhance the reliability of transmitted reference PPM (TR-PPM) signals, the transmission system integrates Gray coding and Consultative Committee for Space Data Systems (CCSDS)-standard-compliant Reed-Solomon (RS) error correcting code (ECC). System performance was evaluated by transmitting pseudorandom binary sequences (PRBSs) and measuring the bit error ratio (BER) across a 5-m wireless link between two 20 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="normal">d</mi><mi mathvariant="normal">B</mi><mi mathvariant="normal">i</mi></mrow></semantics></math></inline-formula> gain horn (Ka-band) antennas, with and without a 20 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="normal">k</mi><mi mathvariant="normal">m</mi></mrow></semantics></math></inline-formula> single-mode optical fiber (SMF) link in transmitter side and ECC at the receiver side. …”
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Three-dimensional omnidirectional characterization methods of rock anisotropic wave velocity and acoustic emission location optimization by Shengjun MIAO, Wenxuan YU, Mingchun LIANG, Pengjin YANG, Conghao LI, Zejing LIU

“…The location error for siltstone is greater than that for marble due to three primary reasons. …”
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A Novel Triboelectric–Electromagnetic Hybrid Generator with a Multi-Layered Structure for Wind Energy Harvesting and Wind Vector Monitoring by Jiaqing Niu, Ribin Hu, Ming Li, Luying Zhang, Bei Xu, Yaqi Zhang, Yi Luo, Jiang Ding, Qingshan Duan

“…High-efficiency wind energy collection and precise wind vector monitoring are crucial for sustainable energy applications, smart agriculture, and environmental management. …”
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Streptococcus agalactiae colonization and screening approach in high-risk pregnant women in southern Brazil by Jeane Zanini da Rocha, Jéssica Feltraco, Vanessa Radin, Carla Vitola Gonçalves, Pedro Eduardo Almeida da Silva, Andrea von Groll

“…Grenade culture was considered an easy and low-cost method, while GeneXpert presented higher cost and error rate of 10%. However, 23.3% of the pregnant women were diagnosed exclusively by GeneXpert and the results were obtained in two hours. …”
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Explainable, Flexible, Frequency Response Function-Based Parametric Surrogate for Guided Wave-Based Evaluation in Multiple Defect Scenarios by Paul Sieber, Rohan Soman, Wieslaw Ostachowicz, Eleni Chatzi, Konstantinos Agathos

“…Lamb waves offer a series of desirable features for Structural Health Monitoring (SHM) applications, such as the ability to detect small defects, allowing to detect damage at early stages of its evolution. …”
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A Methodology for Turbine-Level Possible Power Prediction and Uncertainty Estimations Using Farm-Wide Autoregressive Information on High-Frequency Data by Francisco Javier Jara Ávila, Timothy Verstraeten, Pieter Jan Daems, Ann Nowé, Jan Helsen

“…These results demonstrate that the methodology enables interpretable, data-efficient, and uncertainty-aware turbine-level power predictions, suitable for advanced wind farm monitoring and control applications, enabling a more sensitive underperformance detection.…”
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AFHNet: Attention-Free Hybrid Network for Salient Object Detection in Underwater Images by Qian Tang, Zhen Wang, Xuqi Wang, Shan-Wen Zhang

“…Comprehensive experiments conducted on an underwater optical image dataset, comparing AFHNet with 36 state-of-the-art methods, demonstrate its superior performance, achieving a mean absolute error (MAE) of 1.94%. These results highlight the potential of AFHNet to advance underwater vision applications and establish a new benchmark for salient object detection in challenging environments. …”
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Reliable, efficient, and scalable photonic inverse design empowered by physics-inspired deep learning by Shao Guocheng, Zhou Tiankuang, Yan Tao, Guo Yanchen, Zhao Yun, Huang Ruqi, Fang Lu

“…EMNN increases the design speed by 17,000 times than that of the analytical model and reduces the modeling error by two orders of magnitude compared to the numerical model. …”
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Generalized cross-entropy for learning from crowds based on correlated chained Gaussian processes by J. Gil-González, G. Daza-Santacoloma, D. Cárdenas-Peña, A. Orozco-Gutiérrez, A. Álvarez-Meza

“…Machine learning applications heavily depend on labeled data provided by domain experts to train accurate models. …”
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Evaluation of Measurement Uncertainty for the Wave Buoy Calibration Device Using a Vertical Lifting Method by Yafei Huang, Donglei Zhao, Chenhao Gao, Tian Yan, Lijun He

“…The proposed device provides a robust solution for validating wave buoy performance, offering significant practical value for oceanographic studies and coastal engineering applications.…”
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Cuff-less blood pressure monitoring via PPG signals using a hybrid CNN-BiLSTM deep learning model with attention mechanism by Hanieh Mohammadi, Bahram Tarvirdizadeh, Khalil Alipour, Mohammad Ghamari

“…Through meticulous preprocessing steps, the model achieved an impressive mean absolute error (MAE) of 1.88 for systolic blood pressure (SBP) and 1.34 for diastolic blood pressure (DBP) across 5-fold cross-validation. …”
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A New Capillary and Adsorption‒Force Model Predicting Hydraulic Conductivity of Soil During Freeze‒thaw Processes by Shufeng Qiao, Rui Ma, Yunquan Wang, Ziyong Sun, Helen Kristine French, Yanxin Wang

“…By comparison with other existing models, the results demonstrated that the new model is applicable to various types of soils and that the predicted hydraulic conductivity is in the highest agreement with the observed data, while reducing the root mean square error by 38.9% compared to the van Genuchten–Mualem model. …”
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Enhanced transport in non-newtonian nano-level fluid flow over a rotating disk under radiation and soret–dufour effects: A numerical insight by Abbas Khan, Hashim, Bandari Shankar, Suriya Uma Devi, Waseem Sikandar, Kamel Guedri, Bandar M. Fadhl, Wasim Jamshed, Moaz Al-Lehaibi

“…The accuracy of the numerical results is validated through residual error analysis and comparison with benchmark studies. …”
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Medium and short-term load forecasting based on NPMA-LSSVM algorithm in the case of unbalance and minority sample data by YANG Qiuyu, KUANG Shusen, ZHENG Xiaogang, YE Guoqi, ZHANG Zhongxin

“…Using the 9th Electrician Cup Modeling Contest data set and the power consumption data set of 1443 enterprises in Yangzhong City in 2015 as the verification data, the results show that the load data processed by K-means-SyMProD-PCA input into the NPMA-LSSVM model can reduce the forecasting error effectively, it can better solve the problem of short and medium-term power load forecasting in the case of unbalanced minority class samples, which has certain applicability.…”
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Predicting medication wastage using machine learning based on patient beliefs by Firdaus Aziz, Sorayya Malek, Shubathira Sooriamoorthy, Ilham Asyilah Mahamood, Chong Wei Wen, Sharifah M. Syed Ahmad, Putri Nur Fatin Amir Rudin, Adliah Mhd Ali

“…The insights are broadly applicable to other countries with similar healthcare resource challenges.…”
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Estimation of Peak Junction Hotspot Temperature in Three-Level TNPC-IGBT Modules for Traction Inverters Through Chip-Level Modeling and Experimental Validation by Ahmed H. Okilly, Peter Nkwocha Harmony, Cheolgyu Kim, Do-Wan Kim, Jeihoon Baek

“…The outcomes show a relative estimation error of less than 1% when compared to experimental data and approximately 1.15% for the analytical model. …”
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UV Hyperspectral Imaging and Chemometrics for Honeydew Detection: Enhancing Cotton Fiber Quality by Mohammad Al Ktash, Mona Knoblich, Frank Wackenhut, Marc Brecht

“…In conclusion, the integration of hyperspectral imaging with multivariate analysis represents a robust, non-destructive, and rapid approach for real-time detection of honeydew contamination in cotton, offering significant potential for industrial applications.…”
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ReAcc_MF: Multimodal Fusion Model with Resource-Accuracy Co-Optimization for Screening Blasting-Induced Pulmonary Nodules in Occupational Health by Junhao Jia, Qian Jia, Jianmin Zhang, Meilin Zheng, Junze Fu, Jinshan Sun, Zhongyuan Lai, Dan Gui

“…Ablation studies, feature weight maps, and normalized mutual information heatmaps confirm the robustness and interpretability of the model, while uncertainty quantification metrics such as the Brier score and Expected Calibration Error (ECE) better validate the model’s clinical applicability and prediction stability. …”
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