BCLH2Pro: A novel computational tools approach for hydrogen production prediction via machine learning in biomass chemical looping processes by Thanadol Tuntiwongwat, Sippawit Thammawiset, Thongchai Rohitatisha Srinophakun, Chawalit Ngamcharussrivichai, Somboon Sukpancharoen

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Hybrid Feature Selection and Classifying Stages through Electrocardiogram (ECG) Signal for Heart Disease Prediction by Babu Kumar, Radhakrishnan Soundararajan, Kanimozhi Natesan, Roobini Maridhas Santhi

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A Three-Dimensional Phenotype Extraction Method Based on Point Cloud Segmentation for All-Period Cotton Multiple Organs by Pengyu Chu, Bo Han, Qiang Guo, Yiping Wan, Jingjing Zhang

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Investigation of the application of an automated monitoring system for detecting transmission cable deterioration in Nigeria: A case study of transmission cable lines between Offa... by C.S. Omoniabipi, R. Agbadede, K.C. Emmanuel, O.J. Adewuni, I. Allison

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Practical Approach to Studying Evolutionary Methods for Setting Weight Coefficients of Artificial Neural Networks by D. O. Petrov

“…Options for using the developed software in teaching students the basics of artificial intelligence technologies and evolutionary methods of multicriteria optimization are proposed.…”
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Comparative performance of twelve machine learning models in predicting COVID-19 mortality risk in children: a population-based retrospective cohort study in Brazil by Adriano Lages dos Santos, Maria Christina L. Oliveira, Enrico A. Colosimo, Robert H. Mak, Clara C. Pinhati, Stella C. Gallante, Hercílio Martelli-Júnior, Ana Cristina Simões e Silva, Eduardo A. Oliveira

“…The Logistic Regression (LR) algorithm achieved the highest performance, with an accuracy of 92.5% and an AUC of 80.1%, on the optimized dataset. …”
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Deep learning radiomics nomogram predicts lymph node metastasis in laryngeal squamous cell carcinoma by Yun Liang, Yun Liang, Min He, Wenqing Chen, Wenqing Chen, Lizhen Li, Lizhen Li, Yumeng Dong, Yumeng Dong, Gang Liang, Hui Huangfu, Zengyu Jiang, Zengyu Jiang, Sheng He, Sheng He, Sheng He

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Securing fruit trees future: AI-driven early warning and predictive systems for abiotic stress in changing climate by Muhammad Ahtasham Mushtaq, Muhammad Ateeq, Muhammad Ikram, Shariq Mahmood Alam, Muhammad Mohsin Kaleem, Muhammad Atiq Ashraf, Muhammad Asim, Khalid F. Almutairi, Mahmoud F. Seleiman, Fareeha Shireen

“…Advancement in technology, distinctly artificial intelligence (AI), and machine learning have revolutionized precision farming in agriculture. …”
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A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…Impaction, a tooth alignment issue, is diagnosed using radiographic measurements like panoramic radiographs and CBCT. Artificial Intelligence (AI) is improving the accuracy of predicting dental impaction. …”
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Deep Reinforcement Learning for RIS-Assisted Multi-UAV MU-MISO Communication Networks: Sum-Rate and Energy Efficiency Maximization by Alif Rahmatullah Umar, Hasan Albinsaid, Chia-Po Wei, Chih-Peng Li

“…However, recent studies that integrate reconfigurable intelligent surfaces (RIS) with UAVs tend to focus on limited aspects, such as single-UAV deployments or partial optimization of system parameters, thereby neglecting a comprehensive system-level design. …”
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Deep reinforcement learning Lane-Change Decision-Making for autonomous vehicles based on motion primitives library in hierarchical action space by Guizhe Jin, Zhuoren Li, Bo Leng, Minhua Shao

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Application of business analysis tools in company management by A. Yu. Orlova, A. A. Sorokin, D. G. Lovyannikov

“…We have developed an algorithm for the implementation of a business intelligence system and for this purpose built models in the EPC AS-IS and TO-BE notation. …”
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Design and assessment of AI-based learning tools in higher education: a systematic review by Jihao Luo, Chenxu Zheng, Jiamin Yin, Hock Hai Teo

“…Abstract Artificial intelligence (AI)-based learning tools are increasingly integrated in higher education, offering benefits such as personalized learning experiences, real-time feedback, and increased flexibility. …”
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Deep neural networks excel in COVID-19 disease severity prediction—a meta-regression analysis by Márton Rakovics, Fanni Adél Meznerics, Péter Fehérvári, Tamás Kói, Dezső Csupor, András Bánvölgyi, Gabriella Anna Rapszky, Marie Anne Engh, Péter Hegyi, Andrea Harnos

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Energy Efficiency Maximization in RISs-Assisted UAVs-Based Edge Computing Network Using Deep Reinforcement Learning by Chuanwen Luo, Jian Zhang, Jianxiong Guo, Yi Hong, Zhibo Chen, Shuyang Gu

“…Therefore, we propose the Deep Deterministic Policy Gradients based UAV Trajectory and RIS Phase shift optimization algorithm (UTRP-DDPG) to solve this complex optimization challenge. …”
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Improving the functionality of wireless sensor networks through the use of reinforcement learning and metaheuristic based energy efficient system by Shiwei Zhang, Xinghan Liu

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Secure beamforming design for IRS-assisted SWIPT Internet of things system by Zhengyu ZHU, Jinlei XU, Gangcan SUN, Ning WANG, Wanming HAO

“…In order to meet the new requirements of intelligent signal processing deployment and physical layer security for green interconnection of things, a design method of secure beamforming was proposed to solve the problem of the shortage of sustainable energy supply in the information and energy transmission at the same time Internet of things (IoT) system assisted by intelligent reflecting surface (IRS).Considering the constraints of secrecy rate, transmit power and IRS reflection phase shift, the optimization problem was modeled as a non-convex quadratic programming problem with quadratic constraints, aiming at maximizing the acquisition power of energy collector, and jointly optimizing the base station transmit beamforming matrix, jammer covariance matrix and IRS phase shift.The non-convex quadratic problem was transformed into an equivalent convex problem by using the relaxation variable, semidefinite relaxation method, auxiliary variable and sequence parameter convex approximation method, and an alternative iterative optimization algorithm was proposed to obtain the feasible solution of the original problem.Simulation results show that the proposed algorithm can converge quickly and improve performance effectively compared with the benchmark scheme.…”
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Classification-based point cloud denoising and 3D reconstruction of roadways by Denghong CHEN, Ning PANG, Wen NIE, Juqiang FENG, Jiliang KAN, Jinjing ZHANG

“…This algorithm delivered adaptive optimization performance, yielding types Ⅰ and Ⅱ errors of 1.54 % and 5.37 %, respectively. …”
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Reinforcement learning-based alpha-list iterated greedy for production scheduling by Kuo-Ching Ying, Pourya Pourhejazy, Shih-Han Cheng

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Multi-agent deep reinforcement learning for RIS-assisted secure UAV communication by Bojia Zhao, Danyang Qin, Yuhong Chen, Jiaqiang Yang, Huapeng Tang, Lin Ma

“…To achieve this, we develop a multi-agent twin delayed deep deterministic policy gradient algorithm with energy penalty (MATD3-EP), where multiple agents dynamically solve subproblems and share rewards to achieve global optimization. …”
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