Guiding Field Measurement of Pine Tree Crowns: A Geometric Shape Comparison Using Drone Imagery by A. Hosingholizade, Y. Erfanifard, S. K. Alavipanah, V. García Millan, S. Pirasteh, S. Pirasteh

“…Three analyses were performed to assess the results: correlation analysis (R²), relative root mean square error (RRMSE), and shape analysis, which included overestimation (OverID) and underestimation (UnderID) indices. …”
Get full text

FISNET: A Learnable Fusion-Based Iris Segmentation Network Improving Robustness Across NIR and VIS Modalities by Geetanjali Sharma, Gaurav Jaswal, Aditya Nigam, Raghavendra Ramachandra

“…Iris is one of the most distinctive biometric traits used for reliable identity verification in applications such as border control, secure access systems, and national ID programs. …”
Get full text

Rapid, Precise, and Clinically Relevant Quantification of Urinary Albumin and Creatinine Using a NanoDrop UV/Vis Spectrophotometer by Keith E. Dias, Karly C. Sourris, Jay C. Jha, Karin Jandeleit-Dahm, Bayden R. Wood

“…Partial Least Squares Regression (PLS-R) analysis for BSA yielded a Root Mean Square Error of Calibration (RMSEC) and Cross-Validation (RMSECV) values of 66.93 and 73.92 mg/L, respectively. …”
Get full text

Regularized Kaczmarz Solvers for Robust Inverse Laplace Transforms by Marta González-Lázaro, Eduardo Viciana, Víctor Valdivieso, Ignacio Fernández, Francisco Manuel Arrabal-Campos

“…Inverse Laplace transforms (ILTs) are fundamental to a wide range of scientific and engineering applications—from diffusion NMR spectroscopy to medical imaging—yet their numerical inversion remains severely ill-posed, particularly in the presence of noise or sparse data. …”
Get full text

A big data analysis algorithm for massive sensor medical images by Sarah A. Alzakari, Nuha Alruwais, Shaymaa Sorour, Shouki A. Ebad, Asma Abbas Hassan Elnour, Ahmed Sayed

“…Data arrival rate, resource consumption, propagation delay, transaction epoch, true positive rate, false alarm rate, and root mean square error (RMSE) are some metrics used to evaluate the proposed task.…”
Get full text

Lightweight and hybrid transformer-based solution for quick and reliable deepfake detection by Geeta Rani, Atharv Kothekar, Shawn George Philip, Vijaypal Singh Dhaka, Ester Zumpano, Ester Zumpano, Eugenio Vocaturo, Eugenio Vocaturo

“…Its encoder captures the contextual information from the input patches, and Gaussian Error Linear Unit resolves the vanishing gradient problem.ResultsThe Linformer component reduces the size of the attention matrix. …”
Get full text

Design of an Iterative Method for Malware Detection Using Autoencoders and Hybrid Machine Learning Models by Rijvan Beg, R. K. Pateriya, Deepak Singh Tomar

“…First, in order to reduce the dimensionality of raw malware activity data by 50%, while at the same timestamp preserving critical information, as evidenced by minimal reconstruction error, we apply an autoencoder-based feature learning technique. …”
Get full text

Optimizing photocatalytic dye degradation: A machine learning and metaheuristic approach for predicting methylene blue in contaminated water by Yunus Ahmed, Keya Rani Dutta, Sharmin Nahar Chowdhury Nepu, Meherunnesa Prima, Hamad AlMohamadi, Parul Akhtar

“…It reached a very high R² of 0.9998 on the training set and 0.9915 on the test set, coupled with low error metrics, showcasing its strong generalization capability. …”
Get full text

A Refined Model for Ablation Through Cavitation Bubbles with Ultrashort Pulse Lasers by Shwetabh Verma, Samuel Arba Mosquera

“…Taking a photodisruption model coefficient commonly used in the literature, the root mean square error between the two interaction models was minimized using the generalized reduced gradient fitting method to calculate the optimum scaling factors for the plasma model. …”
Get full text

Machine learning-based retrieval of total column water vapor over land using GMI-sensed passive microwave measurements by Jiafei Xu, Zhizhao Liu

“…The newly retrieved TCWV estimates over land have a correlation coefficient of 0.76 and 0.83, a root-mean-square error (RMSE) of 5.82 mm and 6.02 mm, a relative RMSE of 34.91% and 34.36%, and a mean bias of 0.02 mm and −0.42 mm compared to reference TCWV from GNSS and radiosonde, respectively. …”
Get full text

Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…Results demonstrate that the CNN-LSTM-BMO achieves superior performance with the lowest Root Mean Square Error (RMSE) of 0.5523 and highest R² value of 0.9435, showing statistically significant improvements over other optimization methods as confirmed by paired t-tests (P < 0.05). …”
Get full text

Hydrogeomorphological dynamics and erosion of the soft coasts in tropical Africa, the case study of the Wouri estuary, Cameroon by Philippes Mbevo Fendoung, Aurélia Hubert-Ferrari

“…The Digital Shoreline Analysis System (DSAS) within ArcGIS 10.7.1 quantified shoreline retreat rates using the End Point Rate (EPR) method while meticulously calculating sources of error and uncertainty. Analysis of Landsat imagery revealed that over 75% of the Wouri estuary’s shoreline is eroding, with average retreat rates ranging from − 3 m/year to − 11 m/year between 1975 and 2020. …”
Get full text

From Simulation to Field Validation: A Digital Twin-Driven Sim2real Transfer Approach for Strawberry Fruit Detection and Sizing by Omeed Mirbod, Daeun Choi, John K. Schueller

“…Two separate trials with field images resulted in F1-scores of 0.92 and 0.81 for detection and a sizing error of 1.4 mm (R² = 0.92) when comparing image-derived diameters against caliper measurements. …”
Get full text

Multi-scale machine learning model predicts muscle and functional disease progression by Silvia S. Blemker, Lara Riem, Olivia DuCharme, Megan Pinette, Kathryn Eve Costanzo, Emma Weatherley, Jeff Statland, Stephen J. Tapscott, Leo H. Wang, Dennis W. W. Shaw, Xing Song, Doris Leung, Seth D. Friedman

“…After training, the models predicted fat fraction change with a root mean square error (RMSE) of 2.16% and lean volume change with a RMSE of 8.1 ml in a holdout testing dataset. …”
Get full text

Investigating the impact of meteorological parameters on daily soil temperature changes using machine learning models by Farrokh Asadzadeh, Somayeh Emami, Ahmed Elbeltagi, Muhammed Ernur Akiner, Vahid Rezaverdinejad, Farshid Taran, Ali Salem

“…Additionally, the ANN model exhibited the lowest error rates across all depths, highlighting its superior capability for estimating daily ST in agricultural soils. …”
Get full text

Radar-equivalent snowpack: reducing the number of snow layers while retaining their microwave properties and bulk snow mass by J. Meloche, N. R. Leroux, B. Montpetit, V. Vionnet, C. Derksen

“…Grouping and averaging snow stratigraphy into three layers effectively reproduced the total snowpack backscatter of multilayered snowpacks, with an overall root mean squared error of <span class="inline-formula">0.5</span> dB and <span class="inline-formula"><i>R</i>²=0.98</span>. …”
Get full text

Comparative evaluation of chitosan-based multifunctional wound dressings: a multistage randomised controlled experimental trial by D. I. Ushmarov, S. E. Gumenyuk, A. S. Gumenyuk, T. V. Gayvoronskaya, S. Ya. Karablina, А. V. Pomortsev, A. S. Sotnichenko, K. I. Melkonyan, T. Е. Grigoriev

“…Variation statistics was used for the data analysis, including the mean (M) and standard mean error (± m) estimation. The level of statistical significance was p &lt; 0.05.Results. …”
Get full text

A Cost-Effective Saliva-Based Human Epigenetic Clock Using 10 CpG Sites Identified with the Illumina EPIC 850k Array by Christopher Collins, James Brown, Henry C. Chung

“…<b>Results</b>: The 10-CpG clock’s predictions were highly correlated with chronological age (r = 0.80, R2 = 0.64), with a mean absolute error of ~5.5 years. Its performance, while slightly less precise than Horvath’s or Hannum’s multi-CpG clocks, is notable given the minimal marker set. …”
Get full text

Enhancing County-Level GDP Estimation Accuracy With Downscaled NPP-VIIRS Nighttime Light Data by Weihua Lin, Weixing Xu, Zhaocong Wu, Jiaheng Cao

“…Additionally, the downscaled NTL data improve the accuracy of GDP estimates by reducing the relative error between estimated and statistical GDP compared to NPP-VIIRS NTL data. …”
Get full text

Detail-preserving denoising of CT and MRI images via adaptive clustering and non-local means algorithm by Mohit Sharma, Ayush Dogra, Bhawna Goyal, Anita Gupta, Manob Jyoti Saikia

“…Residual noise in the low-rank matrix is then further suppressed through a coefficient-wise linear minimum mean square error LMMSE estimator in the PCA transform domain. …”
Get full text