Deep learning approach to the estimation of the ratio of reproductive modes in a partially clonal population by T. A. Nikolaeva, A. A. Poroshina, D. Yu. Sherbakov

“…When the training dataset’s dimensionality aligns with the actual data, the model converges to the minimum error much faster, highlighting the significance of dataset design in predictive performance. …”
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Deep Neural Network-Based Temperature Mapping Technique for Heat Sink on Electronic Devices Using Local Thermocouple Sensors by Jaehee Shin, Hyun Ahn, Gwang-Hyeon Mun, Jeongmin Lee, Pouria Zaghari, Young-Min Park, Jinhyoung Park, Jong Eun Ryu, Dong-Won Jang

“…This study introduces an artificial neural network using two thermocouples for cost-effective temperature distribution prediction. Experimental data from heated systems on chip with attached heat sinks were used for training and validation, integrating thermocouple measurements and infrared camera data. …”
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Ensemble Machine Learning, Deep Learning, and Time Series Forecasting: Improving Prediction Accuracy for Hourly Concentrations of Ambient Air Pollutants by Valentino Petrić, Hussain Hussain, Kristina Časni, Milana Vuckovic, Andreas Schopper, Željka Ujević Andrijić, Simonas Kecorius, Leizel Madueno, Roman Kern, Mario Lovrić

“…The utilisation of surface atmospheric ERA5-Land datasets within the models as model features showed high feature post hoc importance in the best (hybrid) models per pollutant and site. Furthermore, error analysis was performed to understand better the conditions under which these models might fail. …”
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Ultra-high-resolution modeling of ground-level ozone for long-term exposure risk assessment driven by GTR-transformer by Jiahuan Chen, Heng Dong, Zili Zhang, Sicong He

“…The model exhibits outstanding performance in multi-dimensional validation, achieving a coefficient of determination of up to 0.94 and a root mean square error as low as 7.59 μg/m3. Employing SHapley Additive exPlanations (SHAP) analysis, we identify key drivers of ozone, including 2 m dewpoint temperature and surface solar radiation downwards (SHAP: 4.88 and 3.83, respectively), substantiating the photochemical regulation mechanism. …”
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Inertial sensor-based heel strike and energy expenditure prediction using a hybrid machine learning approach by Kethohalli R Vidyarani, Viswanath Talasila, Raafay Umar, Venkatesan Prem, Ravi Prasad K Jagannath, Gurusiddappa R Prashanth

“…Objective Gait analysis plays a critical role in healthcare, biomechanics, and sports science, particularly for estimating energy expenditure (EE). …”
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Financial Policies and Corporate Income Tax Administration in Nigeria by Cordelia Onyinyechi Omodero, Joy Limaro Yado

“…Additionally, statistical data on interest and exchange rates are gathered from the World Bank. …”
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Steady-State Model Enabled Dynamic PEMFC Performance Degradation Prediction via Recurrent Neural Network by Qiang Liu, Weihong Zang, Wentao Zhang, Yang Zhang, Yuqi Tong, Yanbiao Feng

“…The processed dataset, comprising model-calculated reference outputs under dynamic conditions synchronized with filtered operational parameters, served as inputs for a recurrent neural network (RNN). Comparative analysis of multiple RNN variants revealed that the hybrid methodology achieved superior prediction fidelity, demonstrating a root mean square error of 0.6228%. …”
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Moving toward the digitalization of neuropsychological tests: An exploratory study on usability and operator perception by Maria Grazia Maggio, Fabio Mauro Giambò, Martina Barbera, Paolo De Pasquale, Francesca Bruno, Andrea Calderone, Angelo Quartarone, Amelia Rizzo, Rocco Salvatore Calabrò

“…Key qualitative feedback indicated that participants appreciated the speed, efficiency, and reduced error rates of digital tools, with many noting improvements in data organization and reporting. …”
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Towards estimating the proportion of dead and missing vines at the field level by Baptiste OGER, Cécile Laurent, Philippe Vismara, Bruno Tisseyre

“…The second part of the study focused on characterising the estimation error values that can result from these estimations. …”
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Network Pharmacology-Driven Sustainability: AI and Multi-Omics Synergy for Drug Discovery in Traditional Chinese Medicine by Lifang Yang, Hanye Wang, Zhiyao Zhu, Ye Yang, Yin Xiong, Xiuming Cui, Yuan Liu

“…The conventional trial-and-error approaches for bioactive compound screening from herbs raise sustainability concerns, including excessive resource consumption and suboptimal temporal efficiency. …”
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Predictive nomogram of high-risk patients with active tuberculosis in latent tuberculosis infection by Kui Li, Siyi Liu, Yingli He, Renyu Ran

“…Methodology: Patients with confirmed ATB were enrolled alongside LTBI individuals as a reference, with relevant clinical data gathered. LASSO regression cross-validation reduced data dimensionality. …”
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An interpretable XAI deep EEG model for schizophrenia diagnosis using feature selection and attention mechanisms by Ahmad Almadhor, Stephen Ojo, Thomas I. Nathaniel, Shtwai Alsubai, Abdullah Alharthi, Abdullah Al Hejaili, Gabriel Avelino Sampedro

“…Conventional Schizophrenia diagnosis techniques are time- consuming and prone to error. The study proposes a novel automated technique for diagnosing Schizophrenia based on electroencephalogram (EEG) sensor data, aiming to enhance interpretability and prediction performance.MethodsThis research utilizes Deep Learning (DL) models, including the Deep Neural Network (DNN), Bi-Directional Long Short-Term Memory-Gated Recurrent Unit (BiLSTM- GRU), and BiLSTM with Attention, for the detection of Schizophrenia based on EEG data. …”
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Assessing the impact of future altimeter constellations in the Met Office global ocean forecasting system by R. R. King, M. J. Martin, L. Gaultier, J. Waters, C. Ubelmann, C. Donlon

“…However, we still achieve promising impacts from the assimilation of wide-swath altimetry, and work is ongoing to develop improved methods to account for spatially correlated observation errors within our data assimilation scheme.</p>…”
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Effectiveness of Integrated Traffic Management of Military Police and Traffic Police in Reducing Drive Speed n Arterial Roads: An Experimental Study by Teguh Patriot

“…Data analysis was conducted using N Gain Score and normal distribution statistical tests with a 5% error rate. …”
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Prediction of Future Land Use and Land Cover Change Impact on Peak Flood: In Case of Babur Watershed, Tekeze Basin, Ethiopia by Kahsu Hubot, Haddush Goitom, Gebremeskel Aregay, Teame Yisfa

“…The performance of the HEC‐HMS model was evaluated through sensitivity analysis, calibration, and validation. Both the calibration (1992–1998) and validation (1999–2001) results showed a good match between measured and simulated flow data with the coefficient of determination (R2) of 0.72, percent of bias (PBIAS) of 1.60%, root mean square error (RMSE) of 0.5, and Nash–Sutcliffe efficiency (NSE) of 0.774 for the calibration, and R2 of 0.86, PBIAS of −9.54%, RMSE of 0.4, and NSE of 0.842 for the validation period. …”
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Optimizing Precipitation Forecasting and Agricultural Water Resource Allocation Using the Gaussian-Stacked-LSTM Model by Maofa Wang, Bingcheng Yan, Yibo Zhang, Lu Zhang, Pengcheng Wang, Jingjing Huang, Weifeng Shan, Haijun Liu, Chengcheng Wang, Yimin Wen

“…Our study investigates the use of machine learning models for daily precipitation prediction using data from 56 meteorological stations in Jilin Province, China. …”
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Hyperspectral Remote Sensing Estimation of Rice Canopy LAI and LCC by UAV Coupled RTM and Machine Learning by Zhongyu Jin, Hongze Liu, Huini Cao, Shilong Li, Fenghua Yu, Tongyu Xu

“…The results indicate that the RPIOSL-UBM model’s hyperspectra closely match measured data in the 500–650 nm and 750–1000 nm ranges, reducing the root mean square error (RMSE) by 0.0359 compared to the PROSAIL model. …”
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Sensor lag adjustments on a mobile meteorological cart in tropical environments: a case study from an Urban Park in Singapore by Moshe Mandelmilch, Sin Kang Yik, Beatrice H Ho, Graces N Y Ching, Peter J Crank, Winston T L Chow

“…Overall, results suggest that mobile climate measurements via SMaRTy along a designated route, when corrected for lag, yield accurate data that can be applied toward urban climate analysis.…”
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Enhancing quality inspection efficiency and reliability of unscreened recycled coarse aggregates (RCA) streams using innovative mobile sensor-based technology by Cheng Chang, Francesco Di Maio, Rajeev Bheemireddy, Perry Posthoorn, Abraham T. Gebremariam, Peter Rem

“…Using advanced 3D scanning and laser-induced breakdown spectroscopy (LIBS), the system ensures reliable real-time analysis of particle size distribution (PSD) (Root Mean Square Error: <5.5%) and contaminant detection (Accuracy: 0.94). …”
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Determination of the dynamic characteristics of a gear pump by the load variation method using special bench systems by V. I. Sanchugov, P. D. Rekadze

“…Methods of spectral analysis of pulsating pressure were applied in the work. …”
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