Optimized design of a permanent magnet brushless DC motor for solar water-pumping applications by Aryadip Sen, Bhim Singh, Kumar Mahtani, Arash Moradzadeh, S.M. Muyeen

“…The proposed design minimizes the volume of the PM, achieving a 20 % reduction in material usage and lowering the overall cost of the motor without compromising performance. …”
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Design and Application of an Energy Management System Based on Artificial Intelligence Technology by Hongye Lin, Xuanying Bai, Chun Li, Shenghan Xu, Haibin Xu, Zne-Jung Lee, Yun Lin, Qunshan Zhou, Jingxun Cai

“…Among the various types of regression algorithms, the mean-square error (<i>MSE</i>) of decision tree regression is 0.36, the <i>MSE</i> of support vector regression (SVR) is 0.09, the <i>MSE</i> of K-nearest neighbor (KNN) regression is 0.57, and the <i>MSE</i> of extreme gradient boosting (XGBoost) regression is 0.32. …”
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Adaptive Management of Multi-Scenario Projects in Cybersecurity: Models and Algorithms for Decision-Making by Vadim Tynchenko, Alexander Lomazov, Vadim Lomazov, Dmitry Evsyukov, Vladimir Nelyub, Aleksei Borodulin, Andrei Gantimurov, Ivan Malashin

“…In computational experiments, the use of fuzzy procedures resulted in an over 25% reduction in errors compared to traditional methods, particularly in adjusting project scenarios from pessimistic to baseline projections. …”
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Multi-decadal spatiotemporal dynamics of alpine plant functional types (PFTs) inferred from Landsat-derived fractional cover across the Yarlung Zangbo river basin, China by Qichi Yang, Lihui Wang, Xiaoqi Li, Xue Yan, Jinliang Huang, Yun Du, Feng Ling

“…The estimated cover fractions for tree cover, shrub cover and herbaceous cover had mean absolute errors of 10.36%, 14.06% and 13.38%, respectively. …”
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Smart Agile Prioritization and Clustering: An AI-Driven Approach for Requirements Prioritization by Aya M. Radwan, Manal A. Abdel-Fattah, Wael Mohamed

“…Various machine learning algorithms are tested, with KNN and Random Forest demonstrating the highest accuracy and lowest Mean Squared Error (MSE), outperforming traditional prioritization techniques. …”
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Accelerating Disease Model Parameter Extraction: An LLM-Based Ranking Approach to Select Initial Studies for Literature Review Automation by Masood Sujau, Masako Wada, Emilie Vallée, Natalie Hillis, Teo Sušnjak

“…Despite the abundance of scientific publications, the manual extraction of these data via systematic literature reviews remains a significant bottleneck, requiring extensive time and resources, and is susceptible to human error. This study examines the application of a large language model (LLM) as an assessor for screening prioritisation in climate-sensitive zoonotic disease research. …”
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Dynamic Modeling and Parameter Optimization of Potato Harvester Under Multi-Source Excitation by Jianguo Meng, Zhipeng Li, Zheng Li, Yanzhou Li, Wenxia Xie

“…The comparison between actual and simulated signals shows that the RMS error of acceleration is only 2.42%, indicating that introducing two degrees of freedom in pitch and roll directions to the potato harvester can accurately describe its vibration characteristics. …”
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Cosmology with Topological Deep Learning by Jun-Young Lee, Francisco Villaescusa-Navarro

“…When applied to the Quijote suite, our TNNs achieve a significant reduction in the mean squared error. Compared to our GNNs, which lack higher-order message-passing, ClusterTNNs show improvements of up to 22% in Ω _m and 34% in σ _8 jointly, while the best FullTNN achieves an improvement of up to 60% in σ _8 . …”
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UAV-based inspection of wind turbine blade surface defects detection technology by TAN Xingguo, ZHANG Gaoming

“…The feature information of defect is separated and extracted through image foreground segmentation and threshold processing, and the connected domain is framed to realize the detection of blade surface. The accuracy and error rate of defect images is calculated and tested by introducing performance evaluation index MIoU. …”
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Prediction of pressure drop in heavy oil water ring based on modified two fluid model by Jiqiang Fu, Mingjun Du, Jiaqiang Jing, Huichao Liu, Jie Sun, Weicong Chen, Yongjiu Chen

“…The comprehensive Reynolds number expression of eccentric water ring can effectively reflect the influence of eccentric effect on shear stress of water wall and the calculation error is less than 20% by predicting the pressure drop of the generalized eccentric water ring with different density differences.…”
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Speech Intelligibility Prediction Using Binaural Processing for Hearing Loss by Xiajie Zhou, Candy Olivia Mawalim, Masashi Unoki

“…Experimental results show that, compared to the baseline system of the second Clarity Prediction Challenge (CPC2) dataset, the proposed method achieves an 8.3% reduction in root mean squared error (RMSE). Notably, the proposed method reduces RMSE by 12.8% when predicting inconsistent hearing loss compared to listeners with consistent hearing levels, confirming the potential of combining hearing loss modeling with binaural processing.…”
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Spot Image Segmentation of Lifting Container Vibration Based on Improved Threshold Method and Mathematical Morphology by Tian-Bing Ma, Qiang Wu, Fei Du, Wei-Kang Hu, Yong-Jing Ding

“…Results show that the improved algorithm in our study has the best threshold segmentation effect, the error classification can be close to 0.0003, and the minimum deviation of the obtained vibration displacement is close to 0.1 pixels, which can realize the accurate extraction of the vibration signal of the vertical shaft tank. …”
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Improving Localization in Wireless Sensor Networks for the Internet of Things Using Data Replication-Based Deep Neural Networks by Jehan Esheh, Sofiene Affes

“…By combining the modified datasets with the original training data, we significantly increase the dataset size, which leads to a substantial reduction in normalized root mean square error (NRMSE). …”
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An improved small object detection CTB-YOLO model for early detection of tip-burn and powdery mildew symptoms in coriander (Coriandrum sativum) for indoor environment using an edge... by Parwit Chutichaimaytar, Zhang Zongqi, Kriengkri Kaewtrakulpong, Tofael Ahamed

“…Early and accurate detection of these symptoms is critical for maintaining yield and quality, yet traditional visual inspection methods are subjective and prone to error. To address this, we developed an enhanced deep learning model, Coriander Tip-Burn YOLO (CTB-YOLO), specifically tailored for detecting small-object symptoms in coriander leaves, emphasizing the reduction of false-positive detections (FP), which could lead to erroneous alerts and unnecessary interventions. …”
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Multifrequency Subsurface Soil Moisture Retrieval for Forest Flows: A Case Study in Te Hiku, New Zealand by Yu-Huan Zhao, Delwyn Moller, Dean Meason, Mahta Moghaddam

“…The multifrequency inversion results revealed that the root mean squared error between the retrieved and measured soil moisture profiles ranged from 0.019 to 0.048 <inline-formula><tex-math notation="LaTeX">$\mathbf {m^{3}/m^{3}}$</tex-math></inline-formula>, with an overall RMSE of 0.032 <inline-formula><tex-math notation="LaTeX">$\mathbf {m^{3}/m^{3}}$</tex-math></inline-formula>. …”
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Characteristics Analysis of Joint Acoustic Echo and Noise Suppression in Periodic Drillstring Waveguide by Li Cheng, Chang Jinfeng, Liu Zhao, Fan Shangchun, Ding Tianhuai

“…The results reveal that the proposed scheme can achieve a much lower error bit ratio over a specified acoustic isolation frequency range with a 30–40 dB reduction in the average noise level compared to traditional single-receiver scheme.…”
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Structural Response Evaluation of Krylov Subspace-Based Reduced-Order Model for Real-Time Structural Health Monitoring and Prediction of Container Ships by Kichan Sim, Byoung Wan Kim, Jeong Sam Han, Kangsu Lee

“…Numerical simulations showed that with 20 reduced orders, the structural response had a relative root mean squared error of 0.02% compared with the full-scale model, whereas computation time decreased by over 99%. …”
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An Improved Orthogonal Frequency Division Multiplexing System-Based Image Steganography Technique by Ali Y. Jaber, Ammar Al-Khafaji, Ahmed Mahfodh Mkhelf

“…Several methods can be used to estimate CFO to compensate for that change in OFDM, including measuring the error rate (BER) as an indicator of the effect of ICI. …”
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Ionospheric Time Series Prediction Method Based on Spatio-Temporal Graph Neural Network by Yifei Chen, Yang Liu, Kunlin Yang, Lanhao Li, Chao Xiong, Jinling Wang

“…For the one-week (84 step) prediction test, the STGNN shows a 27.0% lower error compared to the MLPMultivariate model. The model’s self-adaptive spatial learning and multiscale temporal modeling uniquely enable TEC forecasting under diverse geophysical conditions.…”
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3-D Moving Target Localization in Multistatic HFSWR: Efficient Algorithm and Performance Analysis by Xun Zhang, Jun Geng, Yunlong Wang, Yijia Guo

“…In this paper, we develop a two-stage localization algorithm that first derives a weighted least-squares (WLS) coarse estimate and then performs an algebraic error reduction (ER) procedure to enhance accuracy. …”
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