Comparative effect of different types of artificial teeth and the effect of different surface treatments on the shear bond strength to CAD/CAM denture base by Hajar M. Saleh, Ammar Kh. Al-Noori

“…Purpose: This study aims to evaluate the shear bond strength (SBS) of three types of artificial teeth—acrylic, composite, and computer-aided design and computer-aided manufacturing (CAD/CAM) milled denture teeth—and the effects of three surface treatments: bur roughening, air abrasion (AB), and dichloromethane (DCM). …”
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Vision-Based Gesture-Driven Drone Control in a Metaverse-Inspired 3D Simulation Environment by Yaseen, Oh-Jin Kwon, Jaeho Kim, Jinhee Lee, Faiz Ullah

“…We used transfer learning-based computer vision techniques to detect dynamic hand gestures in real-time. …”
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Novel validity indices for dynamic clustering and an Improved Dynamic Fuzzy C-Means by Ramiro Saltos, Ignacio Carvajal, Fernando Crespo, Richard Weber

“…However, unlike static clustering, where a plethora of validation indices exist to assess the solution’s quality, evaluating the effectiveness of dynamic clustering algorithms remains a challenge. …”
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Investigation of digital and conventional methods for verifying the fitness of CAD/CAM crowns on abutments with different shapes by Michi Abe, Kazuhiro Kon, Shota Fukazawa, Hisatomo Kondo

“…Abstract Purpose To evaluate the marginal and internal compatibility of computer-aided design and computer-aided manufacturing crowns produced via a digital workflow using an intraoral scanner, and to compare this digital-detection technique with the conventional fit test using silicone rubber (silicone-compatibility technique) on various abutments. …”
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Comparison of dynamic mode decomposition with other data-driven models for lung cancer incidence rate prediction by L. Raymond Guo, Jifu Tan, M. Courtney Hughes

“…Machine learning offers powerful tools but can be computationally expensive and require specialized knowledge. …”
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AI-Driven Optimization of Breakwater Design: Predicting Wave Reflection and Structural Dimensions by Mohammed Loukili, Soufiane El Moumni, Kamila Kotrasova

“…Five ML algorithms—Random Forest, Support Vector Regression, Artificial Neural Network, Decision Tree, and Gaussian Process—were applied and evaluated. Results demonstrated that Random Forest and Decision Tree balanced accuracy with computational efficiency, while the Gaussian Process closely matched analytical results but demanded higher computational resources. …”
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Automated Design Method Based on Boosting Algorithms for Improving the Radiation Performance of Microstrip Antenna Arrays by Sina Hasibi Taheri, Ali Lalbakhsh, Amirhassan Zareanborji, Slawomir Koziel

“…The proposed approach replaces computationally expensive full-wave simulations with an ML-driven framework trained on a large dataset of wide-angle impedance matching (WAIM) and microstrip antenna structures. …”
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Kriging-Based Variable Screening Method for Aircraft Optimization Problems with Expensive Functions by Yadong Wang, Xinyao Duan, Jiang Wang, Jin Guo, Minglei Han

“…The computational complexity of airfoil optimization for aircraft wing designs typically involves high-dimensional parameter spaces defined by geometric variables, where each Computational Fluid Dynamics (CFD) simulation cycle may require significant processing resources. …”
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Semantic Topic Modeling of Aviation Safety Reports: A Comparative Analysis Using BERTopic and PLSA by Aziida Nanyonga, Keith Joiner, Ugur Turhan, Graham Wild

“…We assess model performance using both quantitative metrics (topic coherence scores) and qualitative evaluations of topic relevance. The findings show that while pLSA provides a solid probabilistic framework, BERTopic leveraging transformer-based embeddings and HDBSCAN clustering produces more nuanced, context-aware topic groupings, albeit with increased computational demands and tuning complexity. …”
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A numerical study on the optimal placement of two air purifiers for simultaneous operation in a school classroom by Chengxi Yao, Seungjae Lee, Taesung Kim

“…The air purification performance was evaluated by monitoring changes in the concentrations of major pollutants in the classroom, including PM2.5 and CO2, and the airflow distribution and average air age index were applied to evaluate the airflow circulation. …”
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Large Language Models and the Elliott Wave Principle: A Multi-Agent Deep Learning Approach to Big Data Analysis in Financial Markets by Michał Wawer, Jarosław A. Chudziak, Ewa Niewiadomska-Szynkiewicz

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BMWP: the first Bengali math word problems dataset for operation prediction and solving by Sanchita Mondal, Debnarayan Khatua, Sourav Mandal, Dilip K. Prasad, Arif Ahmed Sekh

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Mixture-of-experts graph transformers for interpretable particle collision detection by Donatella Genovese, Alessandro Sgroi, Alessio Devoto, Samuel Valentine, Lennox Wood, Cristiano Sebastiani, Simone Scardapane, Monica D’Onofrio, Stefano Giagu

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A Simulation Framework for Prototyping Intelligent Vehicle-to-Infrastructure Applications: A Case Study on RSU-Based Intersection Movement Assist for Connected Autonomous Vehicles by Chun-Ting Wu, Shao-Hua Wang, Chia-Heng Tu

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A MapReduce-Based Parallel Frequent Pattern Growth Algorithm for Spatiotemporal Association Analysis of Mobile Trajectory Big Data by Dawen Xia, Xiaonan Lu, Huaqing Li, Wendong Wang, Yantao Li, Zili Zhang

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Leverage Sampling Methods and Deep Neural Networks for Fuzzer CAN Bus Message Detection by Thi-Thu-Huong Le, Yeonjeong Hwang, Junyoung Son, Howon Kim

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Advancing EEG-based biometric identification through multi-modal data fusion and deep learning techniques by Touseef Ur Rehman, Madallah Alruwaili, Muhammad Hameed Siddiqi, Yousef Alhwaiti, Sajid Anwar, Zahid Halim, Maaz Alam

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A Data-Driven Approach for Generating Synthetic Load Profiles with GANs by Tsvetelina Kaneva, Irena Valova, Katerina Gabrovska-Evstatieva, Boris Evstatiev

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PhishingGNN: Phishing Email Detection Using Graph Attention Networks and Transformer-Based Feature Extraction by Mejdl Safran, Abdulbaset Musleh

“…By transforming email bodies into relational graphs, PhishingGNN leverages Graph Neural Networks (GNNs) to analyze textual interactions while retaining computational efficiency. Evaluated on an expanded CEAS_08 dataset (39,154 samples: 17,312 non-phishing and 21,842 phishing emails), PhishingGNN achieves state-of-the-art performance: 0.9939 accuracy, balanced precision, recall, and F1-scores of 0.99, and an AUC of 1.00. …”
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Skin‐Compatible Carbopol Electrospun Fiber Membranes with pH‐Dependent Rheological Properties for Biomedical Applications by Daewoo Han, Robert Horvath, Burcu Uner, Giovanni M. Pauletti, Andrew J. Steckl

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