Automated cell annotation and classification on histopathology for spatial biomarker discovery by Zhe Li, Seyed Hossein Mirjahanmardi, Rasoul Sali, Feyisope Eweje, Matthew Gopaulchan, Leon Kloker, Xiaoming Zhang, Guoxin Li, Yuming Jiang, Ruijiang Li

“…However, existing efforts are hampered by inefficient and error-prone human annotations. Here, we present an experimental and computational approach for automated cell annotation and classification on H&E-stained images. …”
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Bolt loosening evaluation method based on normalized screw root equivalent stress and loosening life curve by Guangwu Yang, Han Zhao, Long Yang, Wenyang Shao, Shoune Xiao, Tao Zhu, Yuqing Yuan

“…Finally, a bolt-loosening bench test of an antenna bracket under transverse random vibration was performed, and the loosening life of the bolts was evaluated using the S u –N curve. The maximum relative error between the test and theoretically predicted lives was only 6.26%, which verified the accuracy of the bolt-loosening life evaluation method based on the bolt-load equivalence and provided a certain reference for the bolt-loosening life evaluation and anti-loosening design in a random vibration environment.…”
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A Multi-Task Spatiotemporal Graph Neural Network for Transient Stability and State Prediction in Power Systems by Shuaibo Wang, Xinyuan Xiang, Jie Zhang, Zhuohang Liang, Shufang Li, Peilin Zhong, Jie Zeng, Chenguang Wang

“…Experimental results on IEEE standard test systems and real-world power grids demonstrate the framework’s superiority as compared to state-of-the-art AI models, achieving a 48.1% reduction in prediction error, a 6.3% improvement in the classification F1 score, and a 52.1% decrease in inference time, offering a robust solution for modern power system monitoring and safety assessments.…”
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Versatile graceful degradation framework for bio-inspired proprioception with redundant soft sensors by Taku Sugiyama, Kyo Kutsuzawa, Dai Owaki, Elijah Almanzor, Fumiya Iida, Mitsuhiro Hayashibe

“…Notably, the mean proprioception error increases by less than 1.91°(1.36%) when 30% of the sensors are degraded. …”
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Mixed Layer Depth Estimation From Multisource Remote Sensing Data Using Clustering-Machine Learning Method by Zengxin Guan, Kaijun Ren, Senliang Bao, Hengqian Yan, Huizan Wang, Yanlai Zhao, Jianbin Liu

“…The estimated MLD was compared with that of the in-situ data, showing consistency with observed trends and effectively capturing the spatiotemporal characteristics of MLD across seasons and geographic locations. The estimation error (RMSE) was less than 11.2 m. To assess practical applicability, comparative experiments using remote sensing data were performed, highlighting the model's feasibility and utility. …”
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Sensorless Design and Analysis of a Brushed DC Motor Speed Regulation System for Branches Sawing by Shangshang Cheng, Huijun Zeng, Zhen Li, Qingting Jin, Shilei Lv, Jingyuan Zeng, Zhou Yang

“…Experimental results indicate that the system maintains stable speeds across the 2000–6000 RPM range, with a maximum error of 2.32% at 6000 RPM. The improved ripple detection algorithm effectively preserves critical signals while reducing noise. …”
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Single-Shot Wavefront Sensing in Focal Plane Imaging Using Transformer Networks by Hangning Kou, Jingliang Gu, Jiang You, Min Wan, Zixun Ye, Zhengjiao Xiang, Xian Yue

“…Experimental results in both simulated and real-world conditions indicate that our method achieves a 4.5% reduction in normalized wavefront error (NWE) compared to ResNet34, suggesting improved performance over conventional deep learning models. …”
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Ionospheric Correction Based on Ingestion of Global Ionospheric Maps into the NeQuick 2 Model by Xiao Yu, Chengli She, Weimin Zhen, Nava Bruno, Dun Liu, Xinan Yue, Ming Ou, Jisheng Xu

“…The results show good performance of the GIMs-driven-NeQuick model with average 86% of vertical TEC error less than 10 TECU, when the global daily effective ionization indices (Az) versus modified dip latitude (MODIP) are constructed as a second order polynomial. …”
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Development of Mobile Robot-Based Precision 3D Position Measurement System by Pilgong Choi, Jeng-O Kim, Myeongjun Kim, Kyunghan Kim

“…The experimental results demonstrated a positional measurement error within 0.5 mm at an 8 m distance. This novel system reduces the setup time, enhances worker safety, and increases the overall efficiency and capacity of dry dock maintenance operations.…”
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Quality prediction of air-cured cigar tobacco leaf using region-based neural networks combined with visible and near-infrared hyperspectral imaging by Jianxun Yin, Jun Wang, Jian Jiang, Jian Xu, Liang Zhao, Anfu Hu, Qian Xia, Zhihan Zhang, Ming Cai

“…Results showed that the Diversified Region-based Convolutional Neural Network (DR-CNN) achieved the best performance, with a root mean square error of prediction for moisture at 3.109%, chlorophyll at 0.883 mg/g, total nitrogen at 0.153 mg/g, and total sugar at 0.138 mg/g. …”
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Advanced Control Strategy for Induction Motors Using Dual SVM-PWM Inverters and MVT-Based Observer by Omar Allag, Abdellah Kouzou, Meriem Allag, Ahmed Hafaifa, Jose Rodriguez, Mohamed Abdelrahem

“…An advanced observer using sector nonlinearity (SNL) and time-varying parameters from convex theory is developed to manage state observer error dynamics effectively. Stability conditions, defined as linear matrix inequalities (LMIs), are solved using MATLAB R2016b to optimize the observer’s estimator gains. …”
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Determination of cervical vertebral maturation using machine learning in lateral cephalograms by Shahab Kavousinejad, Asghar Ebadifar, Azita Tehranchi, Farzan Zakermashhadi, Kazem Dalaie

“…A ratio-based approach was employed to compute the values of C3 and C4, accompanied by the implementation of an auto_error_reduction (AER) function to enhance the accuracy of landmark selection. …”
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A Lightweight Terrain‐Constraint Model for Wind Spatial Downscaling by Anboyu Guo, Qiyang Liu, Jiuke Wang, Yuanyong Gao, Lixin Wei, Xiaojiang Song, Chi Zhang, Kai Liu, Shuping Ma, Jiu Jiang

“…Compared to traditional interpolation methods and other deep learning models, the mean absolute error is reduced by up to 49%. The terrain‐constraint module, in particular, contributes most significantly to the model's performance, especially in complex terrains, where it enables greater optimization of downscaling results. …”
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Particle Filter Tracking System Based on Digital Zoom and Regional Image Measure by Qisen Zhao, Liquan Dong, Xuhong Chu, Ming Liu, Lingqin Kong, Yuejin Zhao

“…Simulation results demonstrate that the improved target tracking method effectively improves tracking robustness to target motion changes and reduces the tracking center error by 20%, as compared to other state-of-the-art methods. …”
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A 50-m/320-Gb/s DWDM FSO Communication With Afocal Scheme by Wen-Shing Tsai, Hai-Han Lu, Chung-Yi Li, Ting-Chieh Lu, Hung-Hsien Lin, Bo-Rui Chen, Chang-Jen Wu

“…With the aid of a low-noise amplifier and clock/data recovery at the receiving site, good bit-error-rate (BER) performance and clear eye diagram are obtained at a 50-m/320-Gb/s operation. …”
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An Advanced Method for Precise ULA SIMO Radar Calibration Utilizing Synthetic Aperture Radar Imaging Artifacts by Michael Braunwarth, Johanna Geiss, Erik Sippel, Martin Vossiek

“…The proposed method leverages the established theory of accumulating channel imbalances in synthetic aperture radar (SAR) processing, enabling the isolation of error power from the desired signal and noise within the image. …”
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Assessment of High-resolution Local Emissions and Land-use in Air Quality Forecasting at an Urban, Coastal, Desert Environment by Christos Fountoukis, Yasir Mohieldeen, Luis Pomares, Ivan Gladich, Azhar Siddique, Adam Skillern, Mohammed A. Ayoub

“…The use of the local emissions allowed for a significant improvement in the representation of air quality levels in the city. The overall forecast error decreased from –51% to 8% for PM2.5 and from –88% to 20% for NOx while a significant improvement was observed in the diurnal profile of predicted ozone. …”
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Development and cross‐cultural validation of the Japanese version of the Adjustment Disorder‐New Module‐20 by Atsuo Nakagawa, Dai Mitsuda, Yusuke Umegaki, Rahel Bachem, Waka Nogami, Ryotaro Higuchi, Aoi Ito, Hiroki Kocha

“…Results Confirmatory factor analysis supported the theoretical six‐factor model (comparative fit index = 0.923, root‐mean‐square error of approximation = 0.079), with strong correlations between the ADNM‐20 subscales and external measures (e.g., depression PHQ‐9, r = 0.71; anxiety GAD‐7, r = 0.72). …”
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LLM-enhanced disaster geolocalization using implicit geoinformation from multimodal data: A case study of Hurricane Harvey by Wenping Yin, Yong Xue, Ziqi Liu, Hao Li, Martin Werner

“…A multimodal dataset of 1,000 images and 1,000 texts from the Hurricane Harvey Twitter dataset was constructed to evaluate geolocalization accuracy through error distance. The results demonstrated that the proposed method achieves significant improvements over baseline geocoding and toponym retrieval methods, with overall accuracies of 81.45%, 78.40%, 74.60%, 65.20%, and 44.95% within 161, 100, 50, 10, and 1 km, respectively. …”
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UV-Vis spectroscopy coupled with firefly algorithm-enhanced artificial neural networks for the determination of propranolol, rosuvastatin, and valsartan in ternary mixtures by Ahmed Serag, Maram H. Abduljabbar, Yusuf S. Althobaiti, Farooq M. Almutairi, Shaker T. Alsharif, Rami M. Alzhrani, Marwa F. Ahmed, Atiah H. Almalki

“…The firefly algorithm (FA) was evaluated as a variable selection procedure to optimize the developed ANN models resulting in simpler models with improved predictive performance as evident by lower relative root mean square error of prediction (RRMSEP) values compared to the full spectrum ANN models. …”
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