Evaluation and Application of Machine Learning Techniques for Quality Improvement in Metal Product Manufacturing by Katarzyna Antosz, Lucia Knapčíková, Jozef Husár

“…A variety of classification algorithms, including neural networks (NNs), bagged trees (BT), and support vector machines (SVMs), were employed to efficiently analyse and predict defects. …”
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An effective selection of retrieval schemes for data fusion by Batri Krishnan

“…This paper explores an effective selection algorithm, which is derived from the filter concept, by treating low-score returning schemes as noises. …”
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Optimization of Micro-Texture Parameters for Machine Tool Guide Rail Combination Based on Response Surface Methodology and Research on Its Anti-Friction and Lubrication Performance by Youzheng Cui, Bingyang Yan, Minli Zheng, Haijing Mu, Chengxin Liu, Dongyang Wang, Xinmiao Li, Qingwei Li, Hui Jiang, Fengjuan Wang, Qingming Hu

“…This texture can still significantly improve drag reduction and wear resistance in a low-oil state.…”
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Characterization of the Collagen Extraction Manufacturing Process Using Markov Chains and Artificial Neural Networks by Rosa Trasvina-Osorio, Sergio Alonso-Romero, Juan de Anda-Suarez, Valentin Calzada-Ledesma, Javier Yanez-Mendiola, Luis Fernando Villanueva-Jimenez, Erick Rojas-Mancera

“…In the second stage, the predictive model MCMC-ANN presented a mean square error (MSE) of 0.00171, and a standard deviation (SD) of 0.00133. …”
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Optimizing energy and load management in island microgrids for enhancing resilience against resource interruptions by Majid Hosseina, Mahmoud Samiei Moghaddam, Amir Hassannia

“…To effectively solve this high-dimensional, nonlinear problem, we employ the Multi-objective Moth Flame Algorithm (MOMFA), an enhanced metaheuristic evolutionary algorithm designed to handle complex trade-offs between cost, reliability, and resilience. …”
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ATRIAL FLUTTER: CONTEMPORARY POSSIBILITIES OF DIAGNOSIS AND TREATMENT by Yu. A. Bunin

“…Author paid attention that ventricular rate reduction in AF is more difficult task than this in atrial fibrillation. …”
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sedInterFoam 1.0: a three-phase numerical model for sediment transport applications with free surfaces by A. Mathieu, Y. Kim, T.-J. Hsu, C. Bonamy, J. Chauchat

“…Using sedInterFoam, four test cases are successfully reproduced to validate the free-surface evolution algorithm's implementation, mass conservation of sediment and fluid phases, and predictive capabilities and to demonstrate its potential in modeling a broader range of coastal applications with sediment transport dominated by surface waves.…”
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Using AI in Optimizing Oral and Dental Diagnoses—A Narrative Review by Amelia Surdu, Dana Gabriela Budala, Ionut Luchian, Liliana Georgeta Foia, Gina Eosefina Botnariu, Monica Mihaela Scutariu

“…AI technologies, such as machine learning, deep learning, and computer vision, are increasingly being integrated into dental practice to analyze clinical images, identify pathological conditions, and predict disease progression. By utilizing AI algorithms, dental professionals can detect issues like caries, periodontal disease and oral cancer at an earlier stage, thus improving patient outcomes.…”
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Diagnosis of Device Exception Based on Causality of Device Indicators by Zhaohui Wang, Yan Wei, Longhua Shang, Shiwei Zhang, Shixiong Bao, Zhengren Li

“…Experimental validation on the extended-TE dataset demonstrates that our CGNN framework outperforms baseline algorithms, achieving faster fault identification and higher prediction accuracy. …”
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Snake-inspired trajectory planning and control for confined pipeline inspection with hyper-redundant manipulators by Junjie Zhu, Mingming Su, Longchuan Li, Yuxuan Xiang, Jianming Wang, Xuan Xiao

“…To address this issue, a pipeline inspection approach that combines nonlinear model predictive control (NMPC) with the snake-inspired crawling algorithm(SCA) is proposed. …”
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Sensitivity Analysis of Unmanned Aerial Vehicle Composite Wing Structural Model Regarding Material Properties and Laminate Configuration by Artur Kierzkowski, Jakub Wróbel, Maciej Milewski, Angelos Filippatos

“…A Multi-Objective Genetic Algorithm (MOGA), well suited for complex engineering problems, was employed alongside Design of Experiments to develop a precise response surface model, achieving predictive errors of 0% for mass and 2.99% for frequency. …”
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Dynamic Characteristics of a Cylindrical Roller Bearing with Cage Cracks by Yang Yang, Xiaoye Qi, Yongjie Wang, Meiling Wang, Baogang Wen, Jingyu Zhai

“…The derived dynamic differential equations of cylindrical roller bearings were solved by means of the modified Newton–Raphson iterative algorithm and the BDF predictive correction algorithm with automatic variable order and step length. …”
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The cost of solving linear differential equations on a quantum computer: fast-forwarding to explicit resource counts by David Jennings, Matteo Lostaglio, Robert B. Lowrie, Sam Pallister, Andrew T. Sornborger

“…There is increasing effort in developing quantum algorithms to efficiently simulate dynamics beyond Hamiltonian simulation, but so far exact resource estimates are not known. …”
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Development of a Digital Model of the Agricultural Tool Working Element by V. I. Myalenko

“…The digital twin is a virtual model of the agricultural tool working element that allows you to calculate and predict its expected behavior during the entire period of operation.…”
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An Intelligent System for Management of Medical Equipment Maintenance by Abbas Izadi, Mohamad Amin Bakhshali, Hadi Ghasemifard, Omid Sarrafzadeh

“…The system utilizes machine learning algorithms and data analytics to predict equipment failures, schedule maintenance tasks, and manage spare parts inventory efficiently. …”
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Optimizing travel time reliability with XAI: A Virginia interstate network case using machine learning and meta-heuristics by Navid Khorshidi, Shahriar Afandizadeh Zargari, Soheil Rezashoar, Hamid Mirzahossein

“…This paper applies machine learning models to predict travel time reliability in transportation networks, using XGBoost, LightGBM, and CatBoost optimized with seven metaheuristic algorithms. …”
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Near-Infrared Spectroscopy Combined With Support Vector Machine Model to Realize Quality Control of Ginkgolide Production by Lei Liu, Jun Wang, Haiyi Bian, Ahmed N. Abdalla

“…The collect extensive NIRS data throughout the ginkgolide production process and develop chemometric models using PLS, SVM, and random forest algorithms. These models are rigorously validated through cross-validation and independent testing to assess their accuracy and precision in predicting chemical content and classifying product stages. …”
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Reference-Free Assessment of Speech Intelligibility Using Bispectrum of an Auditory Neurogram. by Mohammad E Hossain, Wissam A Jassim, Muhammad S A Zilany

“…The proposed metric also had a wide dynamic range, and the predicted scores were well-separated as a function of hearing loss. …”
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Design and analysis of antenna through machine learning for next-generation IoT system by Rachit Jain, R. Ramya, Vandana Vikas Thakare, P. K. Singhal

“…Notably, the CatBoost algorithm demonstrates superior performance, achieving 77.4% accuracy in predicting antenna return loss. …”
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Combining methylated RNF180 and SFRP2 plasma biomarkers for noninvasive diagnosis of gastric cancer by Zhihao Dai, Jin Jiang, Qianping Chen, Minghua Bai, Quanquan Sun, Yanru Feng, Dong Liu, Dong Wang, Tong Zhang, Liang Han, Litheng Ng, Jun Zheng, Hao Zou, Wei Mao, Ji Zhu

“…Area under the curve (AUC), sensitivity, specificity, positive predictive value, and negative predictive value were determined. …”
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