Improving the Accuracy of Air Temperature Monitoring for Automated Tasks in Agriculture Using Affordable Meteorological Equipment by Ságová Zuzana, Kuznetsov Pavel, Evstigneev Vladyslav, Krenický Tibor, Voronin Dmitriy, Kotelnikov Dmitriy, Yakimovich Boris

“…The developed correction model, incorporating radiation shield geometry and heat transfer dynamics, reduced measurement deviations to 0.5–0.6 °C. The comparative analysis of data collected at Sevastopol meteorological station (June–August 2023) revealed a superior performance of the mathematical correction method (RMSE 0.17 °C, KGE 0.993) compared to the aspirated shield solution. …”
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High-accuracy prediction of vessels’ estimated time of arrival in seaports: A hybrid machine learning approach by Sunny Md. Saber, Kya Zaw Thowai, Muhammad Asifur Rahman, Md. Mehedi Hassan, A.B.M. Mainul Bari, Asif Raihan

“…Utilizing Automatic Identification System (AIS) data from vessels in the Baltic Sea, our model significantly improves ETA predictions, achieving a mean absolute percentage error (MAPE) of 0.25 %. …”
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Modeling and mapping spatial distribution of baseline soil organic carbon stock, a case of West Hararghe, Oromia Regional State, Eastern Ethiopia by Martha Kidemu Negassa, Mitiku Haile, Gudina Legesse Feyisa, Lemma Wogi, Feyera Merga

“…A random forest model was fitted to the data. The accuracy of the prediction was tested using the 10-fold cross-validation method. …”
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A System Dynamics Approach to Corn Production in indonesia: Causal Loop Diagram by Asriani Asriani, Dhian Herdhiansyah

“…Model verification was conducted using the Mean Absolute Percentage Error (MAPE) method, and simulations were performed with Powersim software to project future outcomes. …”
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Developing a near-infrared spectroscopy calibration algorithm for soil organic carbon content in South Africa by Willie Herman Cloete, Gerhard du Preez, George Munnik Van Zijl

“…The impact of methodological parameters, such as sample state, sampling design, processing and machine learning models, on the root mean square error (RMSE) of the validation statistics was also assessed. …”
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Unveiling the drivers of climate change: the impact of economic indicators, renewable energy consumption and human development through a panel ardl approach by Abhinav Pal, Zamurd Ali, Shagufta Tariq Khan, Chandan Kumar Tiwari, Mohd. Abass Bhat

“…The methodology consists of unit root tests to assess staionarity followed by cointegration and error correction analysis. Findings show GDP and renewable energy use significantly impact short-run emissions while industrialization and HDI have minimal impact. …”
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A Simulation of the Densification Process of NdFeB Bulks by a Modified Drucker–Prager Cap Model by Tao Song, Wenbin Jin, Fang Cheng, Bo Sun, Wenbin Qiu, Nan Liu, Hongliang Ge, Rui Wang, Huayun Mao

“…These results indicate that the developed simulation framework effectively identifies crack-prone areas, enabling data-driven optimization to reduce experimental trial-and-error costs in engineering applications.…”
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Age estimation from morphometric features of maxillary central incisors using CBCT images by Sara Hilmi Kazzaz, Tavga Mustafa Faris, Miwan Salahalddin Abdulrahman, Mohammed Taha Ahmed Baban, Ranjdar Mahmood Talabani, Kazhan Omer Abdalrahman

“…Multiple regression analysis was performed to predict age, and a p-value of ≤ 0.05 was considered statistically significant. …”
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SegPhase: development of arrival time picking models for Japan’s seismic network using the hierarchical vision transformer by Shinya Katoh, Yoshihisa Iio, Hiromichi Nagao, Hiroshi Katao, Masayo Sawada, Kazuhide Tomisaka

“…We present SegPhase, a novel seismic arrival time picking model designed to efficiently process large-scale seismic data recorded by dense seismic networks in Japan. …”
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Unsupervised Selection of Color Factor Weight and Segmentation Scale Parameter for Successful Segmentation of Urban Land Use/Land Cover by G. B. Ikokou, K. M. Malale

“…Image segmentation is a crucial step in object-based image analysis of urban remote sensing data. Its primary goal is to divide a digital image into meaningful objects that are internally homogeneous and clearly distinguishable from neighboring segments. …”
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A Continuous Correlated Beta Process Model for Genetic Ancestry in Admixed Populations. by Zachariah Gompert

“…Analyses of simulated data sets show that the method is generally accurate such that ancestry frequency estimates exhibited low root-mean-square error and were highly correlated with the true values, particularly when large (±10 or ±20) SNP windows were used. …”
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Measurement of level of PTSD with the International Trauma Questionnaire (ITQ): bias and precision when using full ordinal or dichotomized items by Tine Nielsen, Ask Elklit, Sabrina Brødsgaard Nielsen, Mikkel Auning-Hansen, Svend Kreiner, Maria Louison Vang

“…Another strand of research on the measurement properties of the ITQ has used dichotomized items and focused on discovering the model that best described the data found no evidence of DIF.Aim: To investigate the consequences of using dichotomized ITQ PTSD items for detecting DIF, other departures from the Rasch model as well as implications for measurement precision.Methods: We used Rasch and graphical log-linear Rasch models for the analysis, as these models have previously been employed in the only psychometric study using the original polytomous ITQ PTSD items.Results: The use of dichotomized PTSD items lead to detection of less DIF than previous research with the polytomous items, and it accentuated local dependence between items and DIF relative to gender. …”
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Collaborative Optimization on Both Weight and Fatigue Life of Fifth Wheel Based on Hybrid Random Forest with Improved BP Algorithm by Huan Xue, Chang Guo, Xiaojian Peng, Saiqing Xu, Kaixian Li, Jianwen Li

“…Compared to the traditional BP approach, this model improved the mean absolute percentage error (MAPE) by 47.62%. Quadratic optimization was conducted based on the optimal design option set, using data analysis to determine the range of values of each variable under specific constraints and to verify the stress-strain and fatigue life for very small values in the range.…”
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Evaluating organic carbon in living and dead trees using GLCM features and explainable machine learning: insights from Italian national forest by Mehdi Fasihi, Alex Falcon, Giorgio Alberti, Luca Cadez, Francesca Giannetti, Antonio Tomao, Giuseppe Serra

“…Finally, we assess model uncertainty using jackknife resampling and error bar analysis. The results indicate that CatBoost and Random Forest models deliver the highest performance for OC estimation. …”
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Development of an analog topology for a multi-layer neuronal network by Luã da Porciuncula Estrela, Marlon Soares Sigales, Elmer A. Gamboa Peñaloza, Marcelo Lemos Rossi, Mateus Beck Fonseca

“…The neural network model based on the XNOR logic function was simulated using a simulation program with integrated circuit emphasis (SPICE), demonstrating its learning capability as the error decreased for each epoch of training. The proposed methodology offers significant advantages for neuromorphic computing, especially in the domain of Internet of Things (IoT), where near-sensor data analysis and edge computation are essential.…”
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An Advanced Generative AI-Based Anomaly Detection in IEC61850-Based Communication Messages in Smart Grids by Aydin Zaboli, Yong-Hwa Kim, Junho Hong

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Meteorological Drivers and Agricultural Drought Diagnosis Based on Surface Information and Precipitation from Satellite Observations in Nusa Tenggara Islands, Indonesia by Gede Dedy Krisnawan, Yi-Ling Chang, Fuan Tsai, Kuo-Hsin Tseng, Tang-Huang Lin

“…We collected surface information data from Moderate-Resolution Imaging Spectroradiometer (MODIS). …”
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Optimizing Lightweight Recurrent Networks for Solar Forecasting in TinyML: Modified Metaheuristics and Legal Implications by Gradimirka Popovic , Zaklina Spalevic , Luka Jovanovic , Miodrag Zivkovic , Lazar Stosic , Nebojsa Bacanin 

“…Simulations, along with a rigid comparative analysis with other contemporary metaheuristics, are also conducted on a real-world dataset, with the best models achieving a mean squared error (MSE) of just 0.000935 volts and 0.007011 volts on the two datasets, suggesting viability for real-world usage. …”
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Is Blood Transfusion in Anesthesia Based on International Standard? by Parisa Akbarpour, Parisa Moradimajd, Azam Saei, jamile Abolghasemi

“… Background: Blood transfusion is a critical procedure where any error in the transmission chain can jeopardize patient safety. …”
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Predictors of Static Postural Loading in Primary-School-Aged Children: Comparing Elastic Net and Multiple Regression Methods by Mohammad Ali Mohseni Bandpei, Reza Osqueizadeh, Hamidreza Goudarzi, Nahid Rahmani, Abbas Ebadi

“…We conducted a permutation importance analysis to obtain and compare predictor rankings for each model. …”
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