Psychometric properties and Turkish adaptation of the artificial intelligence attitude scale (AIAS-4): evidence for construct validity by Seydi Ahmet Satici, Sinan Okur, Fatma Betül Yilmaz, Simone Grassini

“…In Study I (N = 370), the four-item Artificial Intelligence Attitude Scale-4 (AIAS-4) has a one-dimensional structure as a result of confirmatory factor analysis and the fit index values ​​are at an acceptable level [Comparative Fit Index (CFI) = 0.991; Goodness of Fit Index (GFI) = 0.989; Normed Fit Index (NFI) = 0.988; Tucker-Lewis Index (TLI) = 0.973; Standardized Root Mean Square Residual (SRMR) = 0.018]. …”
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NSA-CHG: An Intelligent Prediction Framework for Real-Time TBM Parameter Optimization in Complex Geological Conditions by Youliang Chen, Wencan Guan, Rafig Azzam, Siyu Chen

“…Comparative analysis revealed a 32.7% reduction in root mean square error (<i>p</i> < 0.01) and 4.8-fold inference speed acceleration relative to conventional methods, establishing a novel data–physics fusion paradigm for TBM control with substantial implications for intelligent tunnelling in complex geological formations.…”
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Modelling the future of cleaner energy: Explainable artificial intelligence model for green hydrogen production rate estimation by Okorie Ekwe Agwu, Saad Alatefi, Ahmad Alkouh

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اللسانيات العصبية بين التقاطع المعرفي والتداخل المصطلحي -من فوضى المنطلق إلى إشكاليّة التداخل المصطلحي... by Aicha Ouggad

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Distress-Based Pavement Condition Assessment Using Artificial Intelligence: A Case Study of Egyptian Roads by Mostafa M. Radwan, Sundus A. Faris, Ahmed Y. Barakat, Ahmad Mousa

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Synergistic Artificial Intelligence framework for robust multivariate medium-term wind power prediction with uncertainty envelopes by Bo Wu, Xiuli Wang, Bangyan Wang, Yaohong Xie, Shixiong Qi, Wenduo Sun, Qihang Huang, Xiang Ma

“…This paper proposes an innovative framework for medium-term wind power forecasting, employing a robust, multi-module Artificial Intelligence approach to improve prediction accuracy and reliability over extended horizons. …”
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Artificial Intelligence Control Methodologies for Shape Memory Alloy Actuators: A Systematic Review and Performance Analysis by Stefano Rodinò, Giuseppe Rota, Matteo Chiodo, Antonio Corigliano, Carmine Maletta

“…This systematic review evaluates artificial intelligence (AI)-based control methodologies to address these limitations, analyzing their efficacy in enhancing precision, adaptability, and reliability for SMA and Magnetic SMA (MSMA) systems. …”
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Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

“…Businesses need a dynamic tool to support their digital innovation management efforts. Artificial intelligence Artificial intelligence is sometimes called machine intelligence, refers to the intelligence shown by machines in various situations, which is in contrast to the natural intelligence in humans; in other words, artificial intelligence refers to systems that can react similar to human intelligent behavior, including understanding complex situations, simulating human thinking processes and reasoning methods and successfully responding to them, learning and having the ability to acquire knowledge and reason to solve problems (Teece et al., 1997). …”
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Critical and creative pedagogies for artificial intelligence and data literacy: an epistemic data justice approach for academic practice by Javiera Atenas, Leo Havemann, Chrissi Nerantzi

“…This paper offers guidance on employing open and creative methods for co-designing critical data and artificial intelligence (AI) literacy spaces and learning activities, rooted in the principles of Data Justice. …”
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Intelligent assessment of damage and prediction of seismic damage spectrum under the effect of Near-Fault earthquakes in Iran by R. Fazli, M. Shamekhi Amiri, H. Pahlavan

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Anomaly Detection and Root Cause Analysis for Energy Consumption of Medium and Heavy Plate: A Novel Method Based on Bayesian Neural Network with Adam Variational Inference by Qiang Guo, Fenghe Li, Hengwen Liu, Jin Guo

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Enhancing predictive analytics in mandibular third molar extraction using artificial intelligence: A CBCT-Based study by Faezeh Khorshidi, Rasool Esmaeilyfard, Maryam Paknahad

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Explainable artificial intelligence-machine learning models to estimate overall scores in tertiary preparatory general science course by Sujan Ghimire, Shahab Abdulla, Lionel P. Joseph, Salvin Prasad, Angela Murphy, Aruna Devi, Prabal Datta Barua, Ravinesh C. Deo, Rajendra Acharya, Zaher Mundher Yaseen

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A Hybrid Forecasting System Based on Comprehensive Feature Selection and Intelligent Optimization for Stock Price Index Forecasting by Xuecheng He, Jujie Wang

“…This paper proposes a hybrid forecasting system based on comprehensive feature selection and intelligent optimization for stock price index forecasting. …”
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Improved Quantum Artificial Bee Colony Algorithm-Optimized Artificial Intelligence Models for Suspended Sediment Load Predicting by Peng Wei, Wang Yu

“…The BDQABC is utilized to optimize artificial intelligence (AI) models, specifically BDQABC-SVR and BDQABC-ANN. …”
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Performance Predictions of Solar-Assisted Heat Pumps: Methodological Approach and Comparison Between Various Artificial Intelligence Methods by Minghui Ma, Oguzhan Pektezel, Vincenzo Ballerini, Paolo Valdiserri, Eugenia Rossi di Schio

“…By comparing the predictive accuracy and modeling time of the three models built, the results demonstrate that the random forest model achieves the best prediction performance, with a mean absolute error (MAE) of 2.42% and a root mean squared error (RMSE) of 4.01% on the train set. …”
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Intelligent 5G-Aided UAV Positioning in High-Density Environments Using Neural Networks for NLOS Mitigation by Morad Mousa, Saba Al-Rubaye

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Development of an interpretable QSPR model to predict the octanol-water partition coefficient based on three artificial intelligence algorithms by Ao Yang, Shirui Sun, Lu Qi, Zong Yang Kong, Jaka Sunarso, Weifeng Shen

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Optimization of ATIG Weld Based on a Swarm Intelligence Approach: Application to the Design of Welding in Selected Manufacturing Processes by Kamel Touileb, Sahbi Boubaker

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Development of an Intelligent Method for Target Tracking in Radar Systems at the Initial Stage of Operation Under Intentional Jamming Conditions by Serhii Semenov, Olga Wasiuta, Alla Jammine, Justyna Golec, Magdalena Krupska-Klimczak, Yevhen Tarasenko, Vitalii Voronets, Vitalii Breslavets, Serhii Lvov, Artem Moskalenko

“…Simulation experiments confirmed the effectiveness of the method: the root mean square error (RMSE) of coordinate estimation was reduced by 25%; the probability of tracking loss decreased by half (from 0.2 to 0.1); and the accuracy of loss prediction exceeded 85%. …”
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