Optimal Design of Spur Gears With Increased Contact Ratio by Ustynenko Oleksandr, Cherelev Stanislav, Ondruška Juraj, Protasov Roman, Yepifanov Vitalii, Bondarenko Oleksiy, Andrienko Sergij

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Autoregressive Neural Network for Cloud Concentration Forecast from Hemispheric Sky Images by Cristian Crisosto

“…The results are quantified in terms of the root mean square error (RMSE) and the mean absolute error (MAE). The new algorithm reduced both the RMSE and the MAE of the prediction by approximately 30% compared to the reference persistence model under diverse cloud conditions. …”
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Design of English Intelligent Simulated Paper Marking System by Lina Yang, Wei Liu

“…The results show that the English essay scoring fitting algorithm proposed in this paper can well improve the prediction accuracy of some data and solve the problem of skewed data where the scores show a normal distribution. …”
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Analysis of Energy Consumption in a Federated Learning-Based Zero-Touch Network by Urooj Yousuf Khan, Musharaf Ali Talpur, Umme Laila, Samar Raza Talpur

“… The current world revolves around data. Internet predicts that there are currently 2.8 million devices connected to the Internet. …”
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CatBoost Optimization Using Recursive Feature Elimination by Agus Hadianto, Wiranto Herry Utomo

“…CatBoost is a powerful machine learning algorithm capable of classification and regression application. …”
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Rapid Penetration Path Planning Method for Stealth UAV in Complex Environment with BB Threats by Zhe Zhang, Jian Wu, Jiyang Dai, Cheng He

“…Besides, the multistep search strategy, the prediction technique, and path planning algorithm are developed for stealth UAV to deal with BB threats and achieve the penetration path replanning in complex scenarios. …”
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ADAPTIVE QUASICONTINUUM SIMULATION OF ELASTIC-BRITTLE DISORDERED LATTICES by Karel Mikeš, Milan Jirásek

“…In this work, the QC method is combined with an adaptive algorithm, to obtain correct predictions of crack trajectories in failure simulations. …”
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Navigating the Digital Maze: A Review of AI Bias, Social Media, and Mental Health in Generation Z by Jane Pei-Chen Chang, Szu-Wei Cheng, Steve Ming-Jang Chang, Kuan-Pin Su

“…It also advocates for evidence-based strategies to mitigate the harms associated with algorithmic bias, urging collaboration among AI developers, mental health experts, policymakers and educators at personal, community (school), and national and international levels to cultivate a safer, more supportive digital ecosystem for future generations.…”
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UNVEILING FAKE NEWS DETECTION MODELS AND THEIR INTEGRATION INTO WEB SYSTEMS: AN EXTENSIVE INVESTIGATION by Vimal Gaur, Naman Veerwal, Ujjwal Chaudhary, Sparsh Kadian

“…Powered by Multinomial Naive Bayes and Passive Aggressive Classifier algorithms, Fake News Detection System ensures accurate classification. …”
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Anomaly Detection in IoMT Environment Based on Machine Learning: An Overview by Peyman Vafadoost Sabzevar, Hamidreza Rokhsati, Alireza Chamansara, Ahmad Hajipour

“…The purpose of anomaly detection is to develop methods that can detect attackers' attacks and prevent them from happening again. Algorithms and methods based on statistics play an important role in predicting and diagnosing anomalies. …”
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Immune microenvironment and prognostic genes of triple-negative breast cancer in the context of transcriptome and single-cell sequencing by Xiangqin Huang, Wei Chen, Zhiwu Lin, Hui Zhang, Ruijuan Wang, Cailing Lin

“…Finally, an analysis of the immune microenvironment and drug predictions provided fresh insights for the treatment of TNBC.…”
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Automatic Acne Detection Model Based on Improved YOLOv7 by Delong Zhang, Chunyang Jin, Zhidong Zhang, Xiyuan Cao, Chenyang Xue

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Anemia Classification System Using Machine Learning by Jorge Gómez Gómez, Camilo Parra Urueta, Daniel Salas Álvarez, Velssy Hernández Riaño, Gustavo Ramirez-Gonzalez

“…In this study, a system was developed to predict anemia using blood count data and supervised learning algorithms. …”
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Pioneering machine learning techniques to estimate thermal conductivity of carbon-based phase change materials: A comprehensive modeling framework by Raouf Hassan, Alireza Baghban

“…A dataset of 482 samples, incorporating various nanoparticle types, concentrations, PCM types, and operating temperatures, was curated and refined using the Monte Carlo Outlier Detection algorithm. Extensive machine learning algorithms were explored; however, CatBoost, XGBoost, ANN, Random Forest, and Gradient Boosting emerged as the most accurate models. …”
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Intelligent hydraulic fracturing under industry 4.0—a survey and future directions by Jing Jia, Qinghu Fan, Jianglu Jing, Kehui Lei, Lichang Wang

“…It identifies four technical challenges: integrating heterogeneous data, developing intelligent decision-making algorithms, adaptive surface equipment adjustments, and multi-machine collaborative control. …”
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Adaptive Filter Updating for Energy-Efficient Top- Queries in Wireless Sensor Networks Using Gaussian Process Regression by Jiping Zheng, Baoli Song, Yongge Wang, Haixiang Wang

“…The mechanism can reduce transmissions of redundant data by utilizing filters. However, existing algorithms based on filters consume a vast amount of energy due to filter updating. …”
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Application of Artificial Neural Networks for Developing Temperature-Dependent Fragility Curves for Vulnerability Assessment of I-Girder Bridges by Saeed Sabori Ghomi, Saman Shiravand, Mohammad Mahdi Zare Zardeyni, Najib Rabiee

“…Accordingly, column reduction factors were computed via Eurocode provisions. …”
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High-Performance Identification and Control of MIMO (Multiple Input—Multiple Output) Experimental Module with Fractional-Order Approach Application by Alexandre Marques de Almeida, Alisson Luan Daga, Rafael Palma Setti Penteado Lanzarini, Ervin Kaminski Lenzi, Marcelo Kaminski Lenzi

“…The results demonstrate the superior performance and robustness of the FOPI-PSO fractional control, which achieves up to 79.6% reduction in ITAE and 72.1% reduction in ITSE criteria. …”
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Systemic lupus erythematosus: alertness in the practice of a dermatologist by M. M. Tlish, Zh. Yu. Naatyzh, T. G. Kuznetsova, E. A. Chernenko

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Climatic suitability and potential distribution of earleaf acacia and its candidate biological control agent Trichilogaster sp by Sara S. MacDonald, Emily J. Le Falchier, Lindsay P. Campbell, Ryan Zonneveld, Carey R. Minteer

“…Both models exhibit high predictive accuracy, with AUC values above 0.9. This study emphasizes the need for continued monitoring and management of ELA and evaluates areas in Florida predicted to have suitable climatic conditions for Trichilogaster sp. nov. …”
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