Construction of a Surface Roughness and Burr Size Prediction Model Through the Ensemble Learning Regression Method by Ali Khosrozadeh, Seyed Ali Niknam, Fatemeh Hajizadeh

“…The model was trained using cutting parameters as inputs and evaluated with performance metrics such as mean absolute error (<i>MAE</i>), mean squared error (<i>MSE</i>), and the coefficient of determination (<i>R</i>²). …”
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Enhanced trajectory reconstruction from sparse and noisy GPS data: A progressive chunked transformer approach by Yonghui Liu, Qian Li, Inhi Kim

“…Trajectory reconstruction from sparse and noisy GPS data is critical for applications such as urban mobility analysis, transportation planning, and navigation systems. …”
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Modeling and Monitoring of the Tool Temperature During Continuous and Interrupted Turning with Cutting Fluid by Hui Liu, Markus Meurer, Thomas Bergs

“…However, the relative error remained consistent across different cutting conditions, with less error observed in interrupted cutting compared to continuous cutting. …”
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Elastic net with Bayesian Density Estimation model for feature selection for photovoltaic energy prediction by Venkatachalam Mohanasundaram, Balamurugan Rangaswamy

“…This research investigation optimizes Feature Selection (FS) and prediction results for PV energy prediction by applying Bayesian Density Estimation (BDE) with Elastic Net (ELNET) regression analysis. …”
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Design and evaluation of children’s education interactive learning system based on human computer interaction technology by Mengru Li, Yang Lv, Yongming Pu, Min Wu

“…User satisfaction reaches 94%, and the error rate is 0.2%. These results demonstrate that the developed learning system significantly impacts children’s learning effectiveness and optimizing user experience.…”
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Real-Time Recognition of Loading Cycles’ Process Based on Electric Mining Shovel Monitoring by Bonan Wang, Yun Duan, Wei Xu

“…Moreover, the dynamic time warping (DTW) algorithm was used to detect and classify the preliminary recognition results by optimizing its distance threshold parameters, reducing the error rate of the model. …”
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Fatigue Life Prediction of the Pin Coupling with Elastic Sleeves Based on Transient Dynamics and the ARIMA Model by Hu Yuming, Xiong Xin, Guo Kai

“…The research results can provide guidance for the anti-fatigue optimization design of pin couplings with elastic sleeves.…”
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The Assessment of Participatory Scenario Planning in Future-Study of the Environment in District 1, Tehran City by Aiub Maroofi, Jila Sajadi, Mohammadtaghi Razavian

“…Therefore, these two propulsive forces were selected as the main axis of scenario analysis and four scenarios were developed in a cooperative way for the future. …”
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Interpretable prediction model for hand-foot-and-mouth disease incidence based on improved LSTM and XGBoost by Xiao LI, Shuyu HE, Yan PENG, Rongxin YANG, Lu TAO, Tingqi LOU, Wenqi HE

“…By simulating the selection, crossover, and mutation mechanisms in biological evolution, the GA efficiently searches for optimal solutions in the parameter space, thereby optimizing the performance of XGBoost. …”
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Water Level Variation Monitoring in East Lake, Wuhan Based on Satellite Altimetry by LIU Huo-sheng, WANG Hai-hong, YU Qian-hui, LU Liang, QIN Peng-cheng, LIU Yi-bing

“…[Results] (1) Statistical analysis of pulse peakiness and waveform width from the lake surface altimetry echoes revealed that approximately 50% of East Lake’s waveforms exhibited specular reflections with distinct sharp peaks, while about 30% displayed complex shapes containing two or more peaks. (2) The results of accuracy validation using the on-site measured data of water levels showed that the 50% threshold retracking method achieved optimal performance, with a root mean square error (RMSE) of 0.108 m and a correlation coefficient of 0.87. (3) Based on the 50% threshold retracking method, and using Jason-3 data, the water level time series of East Lake from September 2017 to February 2022 was established. …”
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Development and psychometric evaluation of the artificial intelligence attitude scale for nurses by Tuğba Öztürk Yıldırım, Mesut Karaman

“…The item pool was developed through a comprehensive literature review. Data analysis included descriptive statistics, item analysis, and exploratory and confirmatory factor analyses, as well as assessments of convergent and divergent validity, correlation analysis, internal consistency reliability, and test-retest reliability. …”
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Authentication of Nigella sativa Seed Oil in Binary and Ternary Mixtures with Corn Oil and Soybean Oil Using FTIR Spectroscopy Coupled with Partial Least Square by Abdul Rohman, Rizka Ariani

“…Fourier transform infrared spectroscopy (FTIR) combined with multivariate calibration of partial least square (PLS) was developed and optimized for the analysis of Nigella seed oil (NSO) in binary and ternary mixtures with corn oil (CO) and soybean oil (SO). …”
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Robust Event-Triggered Energy-to-Peak Filtering for Polytopic Uncertain Systems over Lossy Network with Quantized Measurements by Jidong Wang, Kezhen Han

“…In what follows, a two-stage LMI-based alternative optimization approach is proposed to separately design the filter, which reduces the conservatism of the traditional linearization method of filter analysis conditions. …”
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Development of methods to improve spindle rotation accuracy while maintaining the precision of spindle unit components by Juraev Musurmon, Safarova Dildora, Urinov Nasillo, Akhmedova Khalima, Abdullayev Shokhjakhon

“…Additionally, the use of adaptive deep learning models for error prediction and correction, along with sophisticated measurement techniques like interference fringe analysis and thermal imaging, provided valuable insights into potential spindle misalignments and operational inefficiencies. …”
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Root zone soil moisture mapping at very high spatial resolution using radar-derived surface soil moisture product by Nadia Ouaadi, Abdelghani Chehbouni, Emna Ayari, Bouchra Ait Hssaine, Jamal ElFarkh, Michel Le Page, Salah Er-Raki, Aaron Boone

“…The results show that the approach performs reasonably well using Sentinel-1 SSM product with correlation coefficient (R) between 0.3 and 0.82, root-mean-square error (RMSE) between 0.05 and 0.12 m3/m3 and a bias in the range −0.1–0.07 m3/m3, at 15–20 cm depth. …”
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More is not always better: delta-downscaling climate model outputs from 30 to 5&thinsp;min resolution has minimal impact on coherence with Late Quaternary proxies by L. Timbrell, L. Timbrell, J. Blinkhorn, J. Blinkhorn, M. Colucci, M. Colucci, M. Leonardi, M. Leonardi, M. Chevalier, A. V. Pozzi, M. Grove, E. Scerri, E. Scerri, E. Scerri, A. Manica

“…However, our results imply that using the delta method to downscale to a very fine resolution has a minimal net effect on the coherence of model output with pollen records in most cases. Optimal spatial resolution is therefore likely to be highly dependent on specific research contexts and questions, with careful consideration required regarding the trade-off between highlighting local-scale variations and increasing potential error via unreliable interpolation.…”
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Development of an Efficient and Generalized MTSCAM Model to Predict Liquid Chromatography Retention Times of Organic Compounds by Mengdie Fan, Chenhui Sang, Hua Li, Yue Wei, Bin Zhang, Yang Xing, Jing Zhang, Jie Yin, Wei An, Bing Shao

“…Finally, by training the optimal quantitative structure–retention relationship (QSRR) models for each category of compounds and selecting the best-fitting model for prediction via discriminant analysis during the prediction period, a novel and universal high-throughput retention time prediction model was established. …”
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How to solve small sample size problems in time-series soil organic carbon mapping: New insights from the Third Law of Geography by Jingzhe Wang, Zipeng Zhang, Yankun Wang, Cheng-Zhi Qin, Xiangyue Chen, Yinghui Zhang, Zhongwen Hu

“…Accuracy evaluation and uncertainty analysis consistently demonstrated that models incorporating similarity-based input samples outperformed those relying solely on limited local samples. …”
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A Prediction Model of Stable Warfarin Doses in Patients After Mechanical Heart Valve Replacement Based on a Machine Learning Algorithm by Bowen Guo, Cong Chen, Junhang Jia, Jubing Zheng, Yue Song, Taoshuai Liu, Kui Zhang, Yang Li, Ran Dong

“…The performance of these algorithms was evaluated and compared using R-squared (R2), mean absolute error (MAE), and ideal prediction percentage to identify the optimal algorithm for predicting the stable warfarin dose and verify its clinical significance. …”
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Prompt Framework for Extracting Scale-Related Knowledge Entities from Chinese Medical Literature: Development and Evaluation Study by Jie Hao, Zhenli Chen, Qinglong Peng, Liang Zhao, Wanqing Zhao, Shan Cong, Junlian Li, Jiao Li, Qing Qian, Haixia Sun

“…Ablation studies highlighted the importance of demonstration retrieval and self-verification in improving model reliability. Error analysis revealed four main types of mistakes: identification errors, type errors, boundary errors, and missing entities, indicating areas for further improvement. …”
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