Reconstruction of Electrochemical Impedance Spectroscopy from Time-Domain Pulses of a 3.7 kWh Lithium-Ion Battery Module by Manuel Kasper, Manuel Moertelmaier, Hartmut Popp, Ferry Kienberger, Nawfal Al-Zubaidi R-Smith

“…The experimental EIS data were corrected by a multistep calibration workflow in a frequency range from 50 mHz to 1 kHz, achieving error corrections of up to 80% at 1 kHz. The reconstructed impedances from the pulse test data are in good agreement with the EIS experiments in a broad frequency range, delivering relevant electrochemical information including the ohmic resistance and dynamic time constants of a battery module and its corresponding submodules. …”
Get full text

Vibration Analysis and Optimization of Iron-Core Reactors Based on Fe-Based Soft Magnetic Composite Materials by Yangyang Ma, Wenle Song, Jie Gao, Yang Liu, Yilei Shang, Weimei Zhao, Fuyao Yang

“…The characteristic parameters of the improved model are identified using the particle swarm optimization–simulated annealing (PSO-SA) algorithm, with the identified root mean square error not exceeding 3.5, verifying the model’s accuracy. …”
Get full text

Effects of aerobic training on brachial artery flow-mediated dilation in healthy adults: a meta-analysis of inter-individual response differences in randomized controlled trials by Armin H. Paravlic, Kristina Drole

“…The standard deviation of change scores in the intervention and control groups suggests that most of the variation in the observed change from pre-to-post intervention is due to other factors (e.g., measurement error, biological variability etc.) unrelated to the intervention itself. …”
Get full text

Variable Structure Depth Controller for Energy Savings in an Underwater Device: Proof of Stability by João Bravo Pinto, João Falcão Carneiro, Fernando Gomes de Almeida, Nuno A. Cruz

“…Specifically, the stability proof is based on a novel analysis of the system’s trajectory in the net buoyancy force-versus-depth error plane. The findings were applied to a depth-controlled sensor platform previously developed by the authors, using a well-established system model and considering physical constraints. …”
Get full text

Analysis of reservoir rock permeability changes due to solid precipitation during waterflooding using artificial neural network by Azizollah Khormali, Soroush Ahmadi, Aleksandr Nikolaevich Aleksandrov

“…These effects were associated with a reduction in solubility, collisions of the particles, and large numbers of ions in the porous media. …”
Get full text

Simulation of urban flooding using 3D computational fluid dynamics with turbulence model by Muhammad Waqar Saleem, Muhammad Rashid, Sajjad Haider, Mohiq Khalid, Amro Elfeki

“…An alarming increase in the frequency of extreme rainfall events necessitates advanced flood risk reduction methods. This study uses ANSYS Fluent to simulate the 'Model urban city' flow experiment, comparing aligned and staggered urban layouts. …”
Get full text

Applying the FAIR Principles to Open Educational Resources: A Semantic Similarity Approach to Improve Resource Discovery by Farzaneh Sadeghi, Auriol Degbelo, Carsten Kessler, Reza Zolnouri

“…Notably, even with limited training data, fine-tuning the Sentence-BERT model significantly improved performance, resulting in a 16% reduction in mean squared error compared to the base model. …”
Get full text

Temperature Compensation Method for Tunnel Magnetoresistance Micro-Magnetic Sensors Through Reference Magnetic Field by Tao Kuai, Qingfa Du, Jiafei Hu, Shilong Shi, Peisen Li, Dixiang Chen, Mengchun Pan

“…Additionally, the repeatability of sensitivity temperature characteristic curves was enhanced, with a reduction in root mean square error from 0.84 to 0.21. …”
Get full text

Temperature rise of high-speed bearing in gearbox of 5 MW wind turbine based on Bayesian-LightGBM and improved PSO-SVM troubleshooting by Minan Tang, Zhanglong Tao, Jiandong Qiu, Jinping Li, Mingyu Wang, Hongjie Wang, Chuntao Rao

“…Firstly, the initial dimensionality reduction of SCADA data is performed by sparse random projection matrix, which reduces the redundant data. …”
Get full text

Flocking-Inspired Solar Tracking System with Adaptive Performance in Varied Environmental Conditions by Khadidja Dahli, Adrian Ilinca, Abdellah Benallal, Nawal Cheggaga, Tayeb Allaoui

“…The tracking accuracy improved by 84%, with the mean tracking error reduced in the range of 0.78° to 1.09°. The system also captured 17.4% more solar irradiance, showcasing its superior efficiency. …”
Get full text

Learning on Bandwidth Constrained Multi-Source Data With MIMO-Inspired DPP MAP Inference by Xiwen Chen, Huayu Li, Rahul Amin, Abolfazl Razi

“…Extensive experiments verify the superiority of our scalable method over the most commonly used data selection methods, including GreeDi, Greedymax, random selection, and stratified sampling by a substantial gain of at least 12% reduction in Relative Diversity Error (RDE). This enhanced diversity translates to a substantial improvement in the performance of various downstream learning tasks, including multi-level classification (2%-4% gain in accuracy), object detection (2% gain in mAP), and multiple-instance learning (1.3% gain in AUC).…”
Get full text

An enhanced deep learning approach for speaker diarization using TitaNet, MarbelNet and time delay network by Muzamil Ahmed, Riad Alharbey, Ali Daud, Hikmat Ullah Khan, Javeria Nawal, Ghazia Arshad

“…It integrates noise reduction, adaptive beamforming, and neural diarization to enhance diarization performance in complex acoustic environments. …”
Get full text

Combination of machine learning and Raman spectroscopy for prediction of drug release in targeted drug delivery formulations by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

“…Notably, KRR exhibited exceptional performance, achieving an R² of 0.997 on the training set and 0.992 on the test set, with a mean squared error (MSE) of 0.0004. In comparison, K-ELM and QR achieved lower R² values of 0.923 and 0.817 on the test set, respectively. …”
Get full text

Combinatorial Data‐Driven Innovation of Ecofriendly Transparent Solar Heat Control Coating for Green Buildings by Weibin Zhang, Man Kwan Law, Muhammad Bilal Asif, Jinglei Yang

“…However, many studies have focused only on TSHC coatings composed of single functional nanoparticles, and the development of these coatings traditionally relied on trial‐and‐error methods. Herein, we propose a real experimental data‐driven tandem neural networks (NNs) model, comprising spectrum NNs and inverse design NNs, for the combinatorial innovation, development, and optimization of TSHC coatings. …”
Get full text

Impact of Cloud Microphysics Initialization Using Satellite and Radar Data on CMA-MESO Forecasts by Lijuan Zhu, Yuan Jiang, Jiandong Gong, Dan Wang

“…Furthermore, the root mean square error (RMSE) of the 2 m temperature forecasts decreased across all 1–72 h lead times, with a 4.2% reduction during the 1–9 h period, while the geopotential height RMSE reductions reached 5.8%, 3.3%, and 2.0% at 24, 48, and 72 h, respectively. …”
Get full text

Development and Validation of a Methodology for Predicting Fuel Consumption and Emissions Generated by Light Vehicles Based on Clustering of Instantaneous and Cumulative Vehicle Po... by Paúl Alejandro Montúfar Paz, Julio Cesar Cuisano

“…Using data collected from 10 vehicles over 2000 h and covering altitudes from 0 to 4000 m above sea level in Ecuador, the method not only improved the accuracy of consumption predictions, reducing the margin of error by up to 10% at high altitudes, but also provided a detailed understanding of how altitude affects both consumption and emissions. …”
Get full text

Seismic Attribute Extraction and Application Based on the Gabor Wavelet Transform by Ran Xiong, Xuri Huang, Liang Guo, Xuan Zou, Haonan Tian

“…The results show that when the seismic Gabor attributes are used, the accuracy and root mean square error (RMSE) of the stratigraphic identification with the SVM, RF and XGBoost models are significantly better than those of the seismic amplitude and spectrum data only.…”
Get full text

A Pedaling Torque Observation Approach for Sensorless Electric Bicycles by Riccardo Mandriota, Niklas Konig, Emanuele Grasso, Matthias Nienhaus

“…Also, an online low-computational effort road slope estimation method based on Kalman filtering, that accounts for cornering effect errors, is proposed. The considered approaches, that utilize wheel speed, inertial, and motor current measurements, are tested in an outdoor setting with variable slopes and curves. …”
Get full text

Optimization Design and Experimental Analysis of Resistance-Reducing Anti-Fracture Rotary Blade Based on DEM Techniques by Xiaochuan Zhao, Zhikai Ma, Jianguo Zhao, Jianchang Li, Jiale Zhao, Binhao Dai, Meilin An, Jiaping Wang, Jianjun Hao

“…The comparison between field trial results and simulation data showed an error rate (<5%), confirming the simulation test’s feasibility. …”
Get full text

Time-series characterization of various honey types under different storage conditions based on total polyphenol content and fluorescence properties by Takumi Murai, Teruki Tobari, Sota Kudo, Yoshito Saito

“…Partial least squares regression (PLSR) models constructed using EEM data demonstrated robust TPC prediction capability with R²cv of 0.92, root mean square error cross validation (RMSECV) of 40.66 μg gallic acid equivalent/g and residual prediction deviation (RPD) of 3.61. …”
Get full text