Artificial Intelligence in Numerical Modeling of Silver Nanoparticles Prepared in Montmorillonite Interlayer Space by Parvaneh Shabanzadeh, Norazak Senu, Kamyar Shameli, Maryam Mohaghegh Tabar

“…In this investigation, the accuracy of artificial neural network training algorithm was applied in studying the effects of different parameters on the particles, including the AgNO3 concentration, reaction temperature, UV-visible wavelength, and montmorillonite (MMT) d-spacing on the prediction of size of silver nanoparticles. …”
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Optimization of Traffic Congestion Management in Smart Cities under Bidirectional Long and Short-Term Memory Model by Yujia Zhai, Yan Wan, Xiaoxiao Wang

“…Finally, the data predicted by the BiLSTM algorithm model are compared with the actual data and the data predicted by the long short-term memory (LSTM) algorithm model. …”
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Risk management system and intelligent decision-making for prefabricated building project under deep learning modified teaching-learning-based optimization. by Huazan Liu, Yukang He, Qichao Hu, Jianfei Guo, Lan Luo

“…Then, based on the BP neural network and MTLBO algorithm, we established the MTLBO-BP neural network prediction model and tested its performance. …”
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Development of an interpretable model for foot soft tissue stiffness based on gait plantar pressure analysis by Xiaotian Bai, Xiao Hou, Dazhi Lv, Dazhi Lv, Jialin Wei, Jialin Wei, Yiling Song, Zhengyan Tang, Hongfeng Huo, Hongfeng Huo, Jingmin Liu

“…A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. …”
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The Relationship Between Horizontal Jumping and Sprinting Ability Across Sexes in Young Active Adults by Adam Kleeberger, Dana Agar-Newman, Ming-Chang Tsai, Marc Klimstra

“…Further, athlete mass is a significant factor in the prediction of acceleration ability but not maximum speed, and horizontal jumps were significant factors in the prediction of max speed but not acceleration.…”
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Comparing the effect of pre-anesthesia clonidine and tranexamic acid on intraoperative bleeding volume in rhinoplasty: a machine learning approach by Zahra Asghari Varzaneh, Akram Hemmatipour, Hadi Kazemi-Arpanahi

“…The findings were then compared to determine the most effective medication and the best predictive model. The results revealed that the Linear and Ridge regression algorithms outperformed all other models based on three evaluation metrics: mean absolute error (MAE), mean square error (MSE), and R-squared. …”
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Development and Implementation of a Machine Learning‐Based Flood Forecasting System in Kasese District, Uganda by Edward Miiro, Ismael Kato, Zuhra Nantege, Samuel Ssendi, Khasim Bassajjalaba

“…Two machine learning algorithms, including linear regression and K‐nearest neighbours (KNN) were used to learn from collected hydrological data and make necessary predictions. …”
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Landslide Accumulation Ice-Snow Melting for Thermo-Hydromechanical Coupling and Numerical Simulation by Tongqiang Xiong, Jianlin Li, Lehua Wang, Huafeng Deng, Xiaoliang Xu

“…In this paper, we discussed the phase change coupling algorithm of accumulation bank slope under the action of ice-snow melting. …”
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Adaptive Path Planning for Multi-UAV Systems in Dynamic 3D Environments: A Multi-Objective Framework by Gregorius Airlangga, Ronald Sukwadi, Widodo Widjaja Basuki, Lai Ferry Sugianto, Oskar Ika Adi Nugroho, Yoel Kristian, Radyan Rahmananta

“…This study evaluates and compares the computational performance and practical applicability of advanced path planning algorithms for Unmanned Aerial Vehicles (UAVs) in dynamic and obstacle-rich environments. …”
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Image-Based Malicious Network Traffic Detection Framework: Data-Centric Approach by Doo-Seop Choi, Taeguen Kim, Boojoong Kang, Eul Gyu Im

“…This paper focused on feature engineering instead of AI algorithm selections, presenting an approach that uniquely balances detection accuracy with computational efficiency through strategic dimensionality reduction. …”
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Advancements in Hyperspectral Imaging and Computer-Aided Diagnostic Methods for the Enhanced Detection and Diagnosis of Head and Neck Cancer by I-Chen Wu, Yen-Chun Chen, Riya Karmakar, Arvind Mukundan, Gahiga Gabriel, Chih-Chiang Wang, Hsiang-Chen Wang

“…<b>Results:</b> The meta-analysis findings indicate that LDA surpasses other algorithms, achieving an accuracy of 92%, sensitivity of 91%, and specificity of 93%. …”
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Comparative evaluation of machine learning models versus TIMI score in ST-segment-elevation myocardial infarction patients by Mohit D. Gupta, Dixit Goyal, Shekhar Kunal, Manu Kumar Shetty, M.P. Girish, Vishal Batra, Ankit Bansal, Prashant Mishra, Mansavi Shukla, Vanshika Kohli, Akul Chadha, Arisha Fatima, Subrat Muduli, Anubha Gupta, Jamal Yusuf

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Combined impact of semantic segmentation and quantitative structure modelling of Southern pine trees using terrestrial laser scanning by Jinyi Xia, Timothy A. Martin, Gary F. Peter, Kody M. Brock, Jeff W. Atkins, Matthew A. Gitzendanner, Inacio Bueno, Kim Calders, Ana Paula Dalla Corte, Andrew T. Hudak, Monique Bohora Schlickmann, Michael G. Andreu, Caio Hamamura, Carine Klauberg, Carlos A. Silva

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A novel multi-agent dynamic portfolio optimization learning system based on hierarchical deep reinforcement learning by Ruoyu Sun, Yue Xi, Angelos Stefanidis, Zhengyong Jiang, Jionglong Su

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USE OF ARTIFICIAL INTELLIGENCE TO IDENTIFY AND CORRECT MISCONCEPTIONS ABOUT RADIATION by Oleksandr Tymoshchuk

“…AI tools, including natural language processing models for text analysis and machine learning algorithms for misconceptions classification, were used to provide personalised feedback and targeted corrective information. …”
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Optimal Coverage Path Planning for UAV-Assisted Multiple USVs: Map Modeling and Solutions by Shaohua Pan, Xiaosu Xu, Yi Cao, Liang Zhang

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Genomic Patterns are Associated with Different Sequelae of Patients with Long‐Term COVID‐19 by Nan Zhang, Xizi Luo, Xiangwen Ji, Tian Tian, Runze Wu, Shishun Zhao, Guoqing Wang

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DEVELOPMENT OF METHODOLOGY FOR DESIGNING TESTABLE COMPONENT STRUCTURE OF DISCIPLINARY COMPETENCE by Vladimir I. Freyman

“…The research findings can help promoting learning efficiency increase, a choice of adequate control devices, accuracy of assessment, and also efficient use of personnel, temporal and material resources of higher education institutions. Proposed algorithms, methods and approaches to procedure of control results organization and realization of developed competences and its components can be used as methodical base while designing the computerassisted system for educational process management and quality supervision of graduates’ competences. …”
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Integrative analysis of RNA-Seq data and machine learning approaches to identify Biomarkers for Rhizoctonia solani resistance in sugar beet by Bahman Panahi, Mahdi Hassani, Nahid Hosseinzaeh Gharajeh

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A Novel Method for Describing Texture of Scar Collagen Using Second Harmonic Generation Images by Guannan Chen, Gaoqiang Liu, Xiaoqin Zhu, Mingyu Liu, Encai Zhang, Jichun Li, Kun Zhang, Lihang Lin

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