Maximum scour depth estimation around side-by-side piers due to spacing effects for sustainable hydraulic infrastructure design by Buddhadev Nandi, Subhasish Das

“…A lot of research has been done on single bridge piers using experimental, numerical or database-driven models. …”
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Multi-task genomic prediction using gated residual variable selection neural networks by Yuhua Fan, Patrik Waldmann

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Domain Adversarial Convolutional Neural Network Improves the Accuracy and Generalizability of Wearable Sleep Assessment Technology by Adonay S. Nunes, Matthew R. Patterson, Dawid Gerstel, Sheraz Khan, Christine C. Guo, Ali Neishabouri

“…Compared to commonly used sleep algorithms, this model resulted in the smallest error in wake after sleep onset (MAE of 48.7, Cole–Kripke of 86.2, Sadeh of 108.2, z-angle of 57.5) and sleep efficiency (MAE of 11.8, Cole–Kripke of 18.4, Sadeh of 23.3, z-angle of 9.3) outcomes. …”
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Development of High Throughput Rapid Turbidimetric Assay for Potency Determination of Gramicidin by Mostafa Essam Eissa, Engy Refaat Rashed, Dalia Essam Eissa

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Synthetic Data Generation for Machine Learning-Based Hazard Prediction in Area-Based Speed Control Systems by Mariusz Rychlicki, Zbigniew Kasprzyk

“…Based on these data, several simulation scenarios were run and compared to real-world observations using average speed, the percentage of speed limit violations, root mean square error (RMSE), and percentage compliance. A new metric, the Combined Speed Accuracy Score (CSAS), has been introduced to assess the consistency of simulation results with real-world data. …”
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Next-generation diabetes diagnosis and personalized diet-activity management: A hybrid ensemble paradigm. by Muhammad Sajid, Kaleem Razzaq Malik, Ali Haider Khan, Sajid Iqbal, Abdullah A Alaulamie, Qazi Mudassar Ilyas

“…Leveraging efficient learning and inference techniques, the study achieves a meager error rate of less than 30% using an extensive dataset comprising over 100 million user-rated foods. …”
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An Ensemble Learning Approach for Drought Analysis and Forecasting in Central Bangladesh by Md. Alomgir Hossain, Momotaz Begum, Md. Nasim Akhtar, Md. Alamin Talukder, Nomanur Rahman, Mahfuzur Rahman

“…The random forest (RF) model demonstrated high performance in predicting SPI and SPEI, achieving an accuracy of 93.8%–94.0%, precision of 90.9%–92.7%, recall of 89.5%–92.0%, and F1-scores of 90.3%–92.0%. Its error metrics included MAE (0.055–0.068), MSE (0.0032–0.0052), RMSE (0.056–0.072), and R2 (0.914–0.965) across an 80% training and 20% testing split. …”
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Near-infrared hyperspectral imaging and robust statistics for in vivo non-melanoma skin cancer and actinic keratosis characterisation. by Lloyd A Courtenay, Innes Barbero-García, Saray Martínez-Lastras, Susana Del Pozo, Miriam Corral de la Calle, Alonso Garrido, Diego Guerrero-Sevilla, David Hernandez-Lopez, Diego González-Aguilera

“…The analysis revealed that the spectral regions between 900.66-1085.38 nm, 1109.06-1208.53 nm, 1236.95-1322.21 nm, and 1383.79-1454.83 nm showed the highest differences in this regard, with <1% probability of these observations being a Type I statistical error. Our findings demonstrate that hyperspectral imagery in the near-infrared spectrum is a valuable tool for analyzing, diagnosing, and evaluating non-melanoma skin lesions, contributing significantly to skin cancer research.…”
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Linearized MILP Model With Improved Soft Actor-Critic Algorithm for Dynamic and Efficient Active Distribution Network Planning by Jinlin Liao, Guilian Wu, Jia Lin

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Predicting CO2 adsorption in KOH-activated biochar using advanced machine learning techniques by Raouf Hassan, Alireza Baghban

“…Their superior performance is evidenced by high R2 values of 0.9235 (SVR) and 0.9327 (CatBoost), coupled with low mean squared error values of 0.2207 (SVR) and 0.1942 (CatBoost). …”
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Soft Robot Workspace Estimation via Finite Element Analysis and Machine Learning by Getachew Ambaye, Enkhsaikhan Boldsaikhan, Krishna Krishnan

“…The trained neural network demonstrates promising estimation accuracy with an R-squared value of 0.99 and a root mean square error of 0.783. The workspaces of asymmetric double-chamber and single-chamber soft robots were compared, revealing that the double-chamber robot offers approximately 185 times more reachable workspace than the single-chamber soft robot.…”
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Advanced localization techniques for autonomous road vehicles: Integrating ultrasonic and beacon-based systems by D. N. Nithilam, B. Paulchamy

“…The Ultrasonic Indoor Positioning System achieves position accuracies of 3–4 cm for static targets and 4–7 cm for moving targets, with a minimal error rate. In comparison, the single beacon approach achieves localization within approximately 30 cm of the true position, with a range measurement accuracy of 1–4 cm and a settling time of around 50 s. …”
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Performance assessment of sustainable evacuated tube heat pipe solar collector driven seawater desalination system by Manish Sonkar, B. Kiran Naik

“…This study proposes a solar-powered humidification and dehumidification freshwater extraction system, analyzing its efficiency through heat transfer modeling. Despite extensive research on thermal desalination using various renewable energy sources, limited attention has been given to solar energy applications, particularly for humidification-dehumidification-based freshwater extraction and seawater recovery. …”
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Statistical Downscaling of General Circulation Models (GCMs); History, Principles, and Methods by Dina Yazdany, Azar Zarrin, Abbasali Dadashi-Roudbari

“…Examining the results showed that the CMhyd software has a significant error in both extracting the direct model output and the bias correction method. …”
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Predicting CO₂ Emissions with Advanced Deep Learning Models and a Hybrid Greylag Goose Optimization Algorithm by Amel Ali Alhussan, Marwa Metwally, S. K. Towfek

“…The empirical results show that the GGBERO-optimized BIGRU model produced a Mean Squared Error (MSE) of 1.0 × 10⁻⁵, the best tested approach. …”
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DATA COMPRESSION USING WAVELET TRANSFORM IN BIOTELEMETRY SYSTEMS by O.E. Bezborodova, A.Yu. Bodin, O.N. Bodin, M.N. Kramm, D.V. Martynov

“…For a biotelemetric system as a radio engineering and information-measuring system, the main indicators are measurement error and reliability of data transmission. Materials and methods. …”

Analisis Perbandingan Kinerja Sensor Jarak HC-SR04 dan GP2Y0A21YK Dengan Menggunakan Thingspeak dan Wireshark by Iman Hedi Santoso, Arif Indra Irawan

“…Until now, Internet of Things (IoT) is a very interesting topic to research. This is due to the wide role that IoT can play in human life. …”
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Optimizing solar PV systems using fuzzy logic for Climate-Resilient Healthcare infrastructure in Kyrgyzstan by Nivine Guler, Zied Ben Hazem, Ali Gunes

“…Also, the proposed scheme showed 3% prediction error when checked with the PVWatts calculator. Moreover, the proposed system avoids large computational complexity and miniaturization, which makes it more realistic in practice. …”
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Detection Method for Bolts with Mission Pins on Transmission Lines Based on DBSCAN-FPN by Zhenbing ZHAO, Shuai ZHANG, Wei JIANG, Peng WU

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Prediction of super-large diameter shield attitude based on LSTM-Transformer by Linfabao Dai, Wenming Chen, Mingqing Xiao, Wenhao Sun, Zhengzheng Wang

“…The model predicts four key shield attitude parameters and is validated using field data from the Jiangyin-Jingjiang Yangtze river tunnel project, with comparative analysis against existing models. The research results show that: (1) The LSTM-Transformer attitude prediction model achieves an R2 value of 0.881 and a mean absolute error (MAE) value of 2.24 mm, outperforming existing models in prediction accuracy; (2) Feature importance analysis reveals the key parameters that should be prioritized during shield attitude adjustment, providing a theoretical basis for dynamic attitude control; (3) The model effectively provides early warnings for shield attitude deviation risks, significantly enhancing construction safety and efficiency. …”
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