Graph-based reinforcement learning for software-defined networking traffic engineering by Jingwen Lu, Chaowei Tang, Wenyu Ma, Wenjuan Xing

“…Recent machine learning approaches show promise but still face fundamental limitations in handling complex network constraints and maintaining performance across different network scales. …”
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Performance evaluation of brain state discrimination using near-infrared spectroscopy for brain-computer interface: an exploratory case study by Akira Masuo, Takuto Sakuma, Shohei Kato

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Building Information Modeling and AI Algorithms for Optimizing Energy Performance in Hot Climates: A Comparative Study of Riyadh and Dubai by Mohammad H. Mehraban, Aljawharah A. Alnaser, Samad M. E. Sepasgozar

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Application of Artificial Intelligence to Support Design and Analysis of Steel Structures by Sina Sarfarazi, Ida Mascolo, Mariano Modano, Federico Guarracino

“…Inverse Machine Learning (IML) is a major focus since it helps engineers to minimize reliance on iterative trial-and-error by allowing them to identify ideal material properties and geometric configurations depending on predefined performance targets. …”
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Leveraging LIME for Trustworthy Apple Quality Assessment by İsmail Kırbaş, Ahmet Çifci

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AI-driven wastewater management through comparative analysis of feature selection techniques and predictive models by Faruk Dikmen, Ahmet Demir, Bestami Özkaya, Muhammad Owais Raza, Jawad Rasheed, Tunc Asuroglu, Shtwai Alsubai

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Sentiment analysis for deepfake X posts using novel transfer learning based word embedding and hybrid LGR approach by Madiha Khalid, Muhammad Faheem Mushtaq, Urooj Akram, Mejdl Safran, Sultan Alfarhood, Imran Ashraf

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Artificial Intelligence in the Sustainable Design and Manufacturing of Products in Civil Engineering in the Context of Industry 4.0 by Tomáš Mandičák, Annamária Behúnová, Peter Mésároš

“…The research uses primary and secondary data on the use of AI and its potential and impacts in the field of performance and efficiency in design, production, and use in civil engineering. …”
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Comparison of Various Feature Extractors and Classifiers in Wood Defect Detection by Kenan Kiliç, Kazım Kiliç, İbrahim Alper Doğru, Uğur Özcan

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An Interpretable XGBoost Framework for Predicting Oxide Glass Density by Pawel Stoch

“…Using a dataset of 76,593 oxide glasses from the SciGlass database, three machine learning (ML) models (ElasticNet, XGBoost, MLP) were trained and evaluated. …”
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Network-Based Hierarchical Feature Augmentation for Predicting Road Classes in OpenStreetMap by Müslüm Hacar, Diego Altafini, Valerio Cutini

“…Addressing this challenge, our research introduces a novel hierarchical feature augmentation approach to developing machine learning classifiers by the features retrieved from various levels of road network connectivity. …”
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An Efficient Methodology for the Categorization of Software Requirements Using Natural Language Processing and Similarity Analysis by Rahat Izhar, Kenneth Cosh, Lachana Ramingwon, Sakgasit Ramingwong, Shahid N. Bhatti

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CAMP-GNN: A Constraint-Aware Message-Passing Model for Optimal Resource Allocation in Software Projects by Muhammad Asif, Fahd M. Aldosari, Donia Y. Badawood, Abdu Salam

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Stand for Experimental Evaluation of Effects of Hydrogen Use in Internal Combustion Engines by Levente B., Lelea D., Birsan N.

“…Many have learned that HHO injection into the IC engine improves the gas mileage and reduces emissions, some reporting fuel savings of up to 40%, while others even claim to have reached the performance of operating their engines on HHO entirely produced onboard of the running vehicle. …”
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Thermal management and biocompatibility in dry machining: An experimental study of ZrO2-based cutting tool for bone machining by Phanindra Addepalli, Worapong Sawangsri, Saiful Anwar Che Ghani

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Electrical Storm Optimization (ESO) Algorithm: Theoretical Foundations, Analysis, and Application to Engineering Problems by Manuel Soto Calvo, Han Soo Lee

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Using modern clustering techniques for parametric fault diagnostics of turbofan engines by I. J. Buraimah

“…These technological upgrades have made engines very complex and expensive machines which need constant monitoring during their working phase. …”
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Spin-chain based quantum thermal machines by Edoardo Maria Centamori, Michele Campisi, Vittorio Giovannetti

“…We study the performance of quantum thermal machines in which the working fluid of the model is represented by a many-body quantum system that is periodically connected with external baths via local couplings. …”
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Explainable machine learning algorithms to identify predictors of intention to use family planning among women of reproductive-age in Ethiopia: Evidence from the Performance Monito... by Agmasie Damtew Walle, Shimels Derso Kebede, Jibril Bashir Adem, Tewodros Desalegn Nebi, Daniel Niguse Mamo, Sudi Jemal Wado, Ermias Bekele Enyew

“…Performance metrics evaluated these classifiers. Data preparation techniques, such as feature engineering, handling missing values and addressing imbalanced categories, were applied. …”
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Influence of Cutting Parameters and MQL on Surface Finish and Work Hardening of Inconel 617 by Rachel Lai, Andres Hurtado Carreon, Jose M. DePaiva, Stephen C. Veldhuis

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