Gait-based Parkinson’s disease diagnosis and severity classification using force sensors and machine learning by Navita, Pooja Mittal, Yogesh Kumar Sharma, Anjani Kumar Rai, Sarita Simaiya, Umesh Kumar Lilhore, Vimal Kumar

“…The crucial evaluation metrics used for evaluating model performance include accuracy, mean absolute error, and root mean square error. The findings indicate that the suggested model significantly surpasses current methodologies. …”
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Frequency regulation of two-area thermal and photovoltaic power system via flood algorithm by Serdar Ekinci, Davut Izci, Cebrail Turkeri, Aseel Smerat, Absalom E. Ezugwu, Laith Abualigah

“…The proposed FLA-based PI controller achieved a reduction in maximum overshoot by 28.3 %, a decrease in settling time by 23.4 %, and an improvement in steady-state error by 15.7 % compared to the next best-performing optimization method. …”
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A peer-support lifestyle intervention for preventing type 2 diabetes in India: A cluster-randomized controlled trial of the Kerala Diabetes Prevention Program. by Kavumpurathu R Thankappan, Thirunavukkarasu Sathish, Robyn J Tapp, Jonathan E Shaw, Mojtaba Lotfaliany, Rory Wolfe, Pilvikki Absetz, Elezebeth Mathews, Zahra Aziz, Emily D Williams, Edwin B Fisher, Paul Z Zimmet, Ajay Mahal, Sajitha Balachandran, Fabrizio D'Esposito, Priyanka Sajeev, Emma Thomas, Brian Oldenburg

“…We did not adjust for multiple comparisons, which may have increased the overall type I error rate.<h4>Conclusions</h4>A low-cost community-based peer-support lifestyle intervention resulted in a nonsignificant reduction in diabetes incidence in this high-risk population at 24 months. …”
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Cyber epidemic spread forecasting based on the entropy-extremal dynamic interpretation of the SIR model by Viacheslav Kovtun, Krzysztof Grochla, Mohammed Al-Maitah, Saad Aldosary, Tetiana Gryshchuk

“…The empirical results are characterized by a significant reduction in the Mean Absolute Percentage Error regarding the etalon data over the prediction interval, which proves the adequacy of the proposed approach.…”
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A Two-Stage Time-Domain Equalization Method for Mitigating Nonlinear Distortion in Single-Carrier THz Communication Systems by Yunchuan Liu, Hongcheng Yang, Ziqi Liu, Minghan Jia, Shang Li, Jiajie Li, Jingsuo He, Zhe Yang, Cunlin Zhang

“…In an experimental setting at a frequency of 230 GHz and a channel distance of 2.1 m, this method demonstrated a substantial reduction in the system’s bit error rate (BER), exhibiting particularly noteworthy performance enhancements in comparison to before equalization. …”
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Optimizing subsurface pipe layout by considering leaching efficiency of major salt ions to improve crop coverage using HYDRUS-2D by Yi Liu, Wang Tan, Wenzhi Zeng, Chang Ao, Donglin Jiang

“…Configurations targeting major ions, such as Mg²⁺ and HCO₃⁻, outperformed traditional designs based on total salt reduction, with coverage improvement exceeding 16 % in low-coverage areas. …”
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Research of factors influencing the accuracy of determining of oil raw materials quality indicators based on the NMR pulse method by O. S. Agafonov, S. M. Prudnikov, T. A. Shakhrai, E. P. Victorova

“…It has been established that the reduction in the influence of the identified factors is achieved by normalizing the volume of the sample of seeds and measuring its temperature. …”
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A comparative study of four deep learning algorithms for predicting tree stem radius measured by dendrometer: A case study by Guilherme Cassales, Serajis Salekin, Nick Lim, Dean Meason, Albert Bifet, Bernhard Pfahringer, Eibe Frank

“…Our best result showed that a reduction of 97 % in collection events increases the MAE by only 6 % with the LSTM model, demonstrating that resource use optimisation can be achieved by slightly reducing the temporal resolution of data collection with marginal error increase. …”
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Validation of the scale compassion fatigue inventory in health professional Spanish-speaking: a cross-sectional study by Antonio Kobayashi-Gutiérrez, Blanca Miriam Torres-Mendoza, Bernardo Moreno-Jiménez, Rodrigo Vargas-Salomón, Jazmin Marquez-Pedroza, Rosa Martha Meda-Lara

“…The CFA showed good fit indices and psychometric values (Cronbach´s alpha = 0.87, Omega = 0.87, Comparative Fit Index = 0.99, Tucker Lewis = 0.99, root mean square error of approximation = 0.045, Standardized Root Mean Square Residual = 0.05). …”
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Improving large-scale snow albedo modeling using a climatology of light-absorbing particle deposition by M. Gaillard, M. Gaillard, V. Vionnet, M. Lafaysse, M. Dumont, P. Ginoux

“…The revised coefficient improved snow albedo simulations at the 10 experimental sites (average reduction in root-mean-square error (RMSE) of 10 %), with the largest improvements found for the sites in the Arctic (RMSE reduced by 25 %). …”
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Optical Versus Electronic Implementation of Probabilistic Graphical Inference and Experimental Device Demonstration Using Nonlinear Photonics by Masoud Babaeian, Patrick Keiffer, Mark A. Neifeld, Ratchaneekorn Thamvichai, Robert A. Norwood, Pierre-A. Blanche, John Wissinger, N. Peyghambarian

“…The probabilistic inference model has been widely used in various areas, such as error-control coding, machine learning, speech recognition, artificial intelligence, and statistics. …”
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Optimization Research on Magnetic Interference Parameter Identification and Compensation for AUV Platforms by Haodong Wen, Guohua Zhou, Kena Wu, Xinkai Hu, Liezheng Tang, Shuai Xia

“…Numerical simulations demonstrate that, under a 5&#x00B0; attitude error, the L-SHADE algorithm achieves mean decoding accuracies of 86.42%, 81.9%, and 86.15% for the three magnetic field components after training with low-noise data. …”
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Bayesian Model Averaging for Satellite Precipitation Data Fusion: From Accuracy Estimation to Runoff Simulation by Shaowei Ning, Yang Cheng, Yuliang Zhou, Jie Wang, Yuliang Zhang, Juliang Jin, Bhesh Raj Thapa

“…This study highlights BMA’s potential for optimizing hydrological model inputs, providing critical insights for sustainable water management and risk reduction in complex basins.…”
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Missing value interpolation algorithm for long-term temperature observation data based on data augmentation multiple interpolation method by Xiaolin Liu, Bo Wang, Shuanglong Jin, Zongpeng Song

“…For this purpose, an algorithm for interpolating missing values in long-term temperature observation data was designed. The noise reduction method based on Graph Attention Network (GAT) is adopted to handle the noise in the data. …”
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Research on Missing Data Estimation Method for UPFC Submodules Based on Bayesian Multiple Imputation and Support Vector Machines by Xiaoming Yu, Jun Wang, Ke Zhang, Zhijun Chen, Ming Tong, Sibo Sun, Jiapeng Shen, Li Zhang, Chuyang Wang

“…Experimental validation focusing on capacitor voltage, current, and temperature parameters of UPFC submodules under a 50% missing data scenario demonstrates that the proposed method achieves an 18.7% average error reduction and approximately 30% computational efficiency improvement compared to single imputation and traditional multiple imputation approaches, significantly outperforming neural network models. …”
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An Improved Wavelet Soft-Threshold Function Integrated with SVMD Dual-Parameter Joint Denoising for Ancient Building Deformation Monitoring by Jiaxing Zhao, Houzeng Han, Yang Deng, Youqiang Dong, Jian Wang, Wenjin Chen

“…The proposed method significantly preserves vibration features during noise reduction of an ancient building in deformation monitoring, which is crucial for damage assessment.…”
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ANN and Multilayer-ELM based prediction of combustion, performance and emission characteristics of a diesel engine fuelled with Diesel-DTBP blends by Hiren Dave, Vinay Vakharia, Hitesh Panchal, Md Irfanul Haque Siddiqui, Dan Dobrotă

“…Moreover, ML models achieved least error metrics for all three key engine performance metrics. …”
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Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition by Yu Ding, Wenjia Ni, Jiaxin Dong, Jie Yang, Shiyao Meng, Siwei Li

“…The fused dataset demonstrates significant improvements over the original MERRA-2 AOD, with an increase in the coefficient of determination (R²) by 0.1065 and a reduction in root mean square error (RMSE) by 0.0369. …”
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Models for sustainable management of livestock waste based on neural network architectures by Anatoliy Tryhuba, Krzysztof Mudryk, Inna Tryhuba, Marian Kotsylovskyi, Dmytro Sorokin, Olena Bezaltychna, Pawel Pysz, Taras Hutsol

“…The optimized MLP model demonstrated high predictive performance, achieving a mean squared error (MSE) of 0.0005 and a mean absolute percentage error (MAPE) of 6.51%, compared to 8.01% for the baseline model. …”
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A Novel Evolutionary Deep Learning Approach for PM_2.5 Prediction Using Remote Sensing and Spatial–Temporal Data: A Case Study of Tehran by Mehrdad Kaveh, Mohammad Saadi Mesgari, Masoud Kaveh

“…Data preparation processes include noise reduction, spatial interpolation, and addressing missing data. …”
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