Evaluation of aerodynamic coefficients of supercritical airfoil NASA sc(2) 0712: A comparative study of 2D and 3D flow models with experimental validations by Šukunda Teodora, Svorcan Jelena, Ivanov Toni

“…By performing spatial computations of turbulent flow around a supercritical airfoil, it is possible to reduce the relative error of drag coefficients by less than 10%.…”
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Learning to represent causality in recommender systems driven by large language models (LLMs) by Serge Stéphane Aman, Tiemoman Kone, Behou Gerald N’guessan, Kouadio Prosper Kimou

“…We further provide an error analysis and discuss the implications of using causal modeling for scalable, transparent, and GDPR-compliant recommender systems. …”
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Optimal Selection of Intrinsic Mode Functions Applied to Seizure Detection by Luis Daladier Guerrero Otoya, Maximiliano Bueno López, Eduardo Giraldo Suárez, Marta Molinas Cabrera

“…Method: This study addressed a significant gap by proposing a novel approach for the automated selection of the most relevant intrinsic mode functions (IMFs) using empirical mode decomposition and discrimination metrics such as the Minkowski distance, the mean square error, cross-correlation, and the entropy function. …”
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Impact of tourism, globalization, and technological patents on ecological footprint in ASEAN countries: static and dynamic panel regression approaches by Nazhat Nury Aspy, Liton Chandra Voumik, Miguel Angel Esquivias, Lilik Sugiharti, Mihir Kumar Das, Dulal Chandra Pattak

“…Focusing on eight ASEAN nations (Brunei, Cambodia, Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam) for the period between 1990 and 2020, this study employs Driscoll Kraay Standard Error (DKSE) and Quantile Regression methodologies to examine this phenomenon comprehensively. …”
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Estimation of Atmospheric Boundary Layer Turbulence Parameters over the South China Sea Based on Multi-Source Data by Ying Liu, Tao Luo, Kaixuan Yang, Hanjiu Zhang, Liming Zhu, Shiyong Shao, Shengcheng Cui, Xuebing Li, Ningquan Weng

“…Utilizing Monin–Obukhov Similarity Theory (MOST) as the theoretical foundation, the model’s performance is evaluated by comparing its outputs with the observed diurnal cycle of near-surface optical turbulence. Error analysis indicates a root mean square error (RMSE) of less than 1 and a correlation coefficient exceeding 0.6, validating the model’s predictive capability. …”
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Making student voice heard in dialogic feedback: feedback design matters by Jessica To, Dominique Aluquin, Kelvin Heng Kiat Tan

“…To bridge the gap, this collaborative action research explored how feedback could be redesigned to invite student voice in a Singapore secondary school.MethodologyWe collaborated with three Social Studies teachers to transform their error-focused practice into dialogic feedback accentuating student voice. …”
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Extreme heat prediction through deep learning and explainable AI. by Fatima Shafiq, Amna Zafar, Muhammad Usman Ghani Khan, Sajid Iqbal, Abdulmohsen Saud Albesher, Muhammad Nabeel Asghar

“…Our findings demonstrate that the LSTM model outperforms others with a lead time of 1-3 days and minimal error metrics, achieving an accuracy of 96.2%. Through the utilization of SHAP and LIME XAI methods, we elucidate the significance of humidity and maximum temperature in accurately predicting extreme heat events. …”
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Transforming higher education with robotic process automation: enhancing efficiency, innovation, and student-centered learning by Vivek Bhardwaj, Mukesh Kumar

“…Case studies reveal common success factors, including significant time savings, error reduction, and improved satisfaction for both students and staff. …”
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Research on improving the ranging accuracy of ships with stereo vision through Kalman filter optimization. by Zhongbo Peng, Jie Han, Liang Tong, Lumeng Wang, Dan Liu, Shijie Sun

“…Within a distance of 20m from the ship target, the error can be controlled within 3%, showcasing the applicability of the method proposed in this paper in complex inland waterway environments contributes to the enhancement of ships' environmental perception capabilities and navigation safety, holding positive implications for the development of intelligent vessels.…”
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Monetary Policy Transmission Under Global Versus Local Geopolitical Risk: Exploring Time-Varying Granger Causality, Frequency Domain, and Nonlinear Territory in Tunisia by Emna Trabelsi

“…Once clarity emerges, they may adjust their behavior, aligning with the long-run effects observed in the Vector Error Correction Model (VECM). Furthermore, we identify an exacerbating investor sentiment following tightening monetary policy, during global and local geopolitical episodes. …”
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Vergence fusion sustaining oscillations by John L. Semmlow, Tara Alvarez, Chang Yaramothu, Mitchell Scheiman

“…Data have clinical implications in that dysfunction in feedback control may manifest as additional vergence error which may be reflected in the frequency spectrum.…”
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Ctta: a novel chain-of-thought transfer adversarial attacks framework for large language models by Xinxin Yue, Zhiyong Zhang, Junchang Jing, Weiguo Wang

“…This has significant implications for enhancing the security and robustness of LLMs.…”
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Perspectives on water quality analysis emphasizing indexing, modeling, and application of artificial intelligence for comparison and trend forecasting by Rijurekha Dasgupta, Subhasish Das, Gourab Banerjee, Asis Mazumdar

“…Using statistical operations and soft computing techniques have been done by researchers to combat the subjectivity error in indexing. To achieve better results, WQMs are being modified to incorporate the physical processes influencing water quality more robustly. …”
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Multi-objective optimization of gold price forecasting using the pareto alpha-cut technique by Pullooru Bhavana

“…We employed three distinct models: the Autoregressive Distributed Lag (ARDL) model, a stochastic model, and the Autoregressive Integrated Moving Average (ARIMA) model, to capture the underlying dynamics of gold price fluctuations influenced by macroeconomic factors.The methodology incorporates the Pareto optimality approach combined with fuzzy logic to manage trade-offs among multiple performance metrics, specifically Root Mean Squared Error (RMSE), volatility, and R-squared. By applying the alpha-cut technique, we filtered out less optimal models, retaining only those that met a predefined level of acceptability across all criteria.Results indicate that the ARDL model consistently outperformed the others, achieving superior accuracy and fit, while the stochastic model exhibited robust stability. …”
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Determining the optimal threshold of foreign direct investment for sustainable improvement in Ghana’s trade balance by David Aboagye Danquah, Charles Barnor

“…The study employed the autoregressive distributed lag (ARDL) models, error correction models and smooth threshold regression techniques to establish the relationship between FDI and trade balance. …”
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Interrelationships Among Government Participation, Population and Growth of per Capita Income: Inquiry on Top Twenty Income-Holding Countries in the World by Ramesh Chandra Das

“…The empirical results relating to income growth, thus, have sustainability implications.…”
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Parameter Extraction for Photovoltaic Models with Flood-Algorithm-Based Optimization by Yacine Bouali, Basem Alamri

“…Applying metaheuristic algorithms with the Newton–Raphson-based objective function reduced the root-mean-square error (RMSE) more effectively than traditional methods. …”
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Joint estimation of hand-foot-mouth disease model and prediction in korea using the ensemble kalman filter. by Wasim Abbas, Sieun Lee, Sangil Kim

“…<h4>Results</h4>The findings reveal a significant alignment between the model and the observed data, as evidenced by root-mean-square error (RMSE) values below 1000 for inpatients and below 10000 for outpatients starting in June. …”
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Improved Ellipsoidal Intersection Method for 2D Data Fusion by Muhammed Mert Ulupinar, Gokhan Soysal

“…Monte Carlo simulations under various correlation cases demonstrate that Improved Ellipsoidal Intersection method calculates lower root mean square error compared to existing techniques, particularly in high-correlation cases. …”
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Hydrological parameter sensitivity analysis for water evaluation and planning model calibration in the Borkena River Sub-basin by Elias Fiseha Mekonnen, Gebremariam Adane Getu

“…The model performance was evaluated using metrics such as Nash–Sutcliffe Efficiency (NSE), Root Mean Square Error (RMSE), Percentage of Bias (PBIAS), and Coefficient of Determination (R2). …”
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