Detección y diagnóstico de fallas en motores mediante el análisis de vibraciones aplicando técnicas de inteligencia artificial. by Jair Elías Araujo Vargas, Dilan Yesid Franklin Coronel, Victor Manuel Arias Ruiz

“…Thus, artificial intelligence algorithms demonstrated high accuracy in fault detection and resolution, identifying various types of problems in a timely manner; the models contributed significantly to the overall analysis, offering a more reliable approach to predictive industrial maintenance, paving the way for future improvements and the adoption of new, more robust and adaptable algorithms.…”
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A Transformer-Based Approach for Efficient Geometric Feature Extraction from Vector Shape Data by Longfei Cui, Xinyu Niu, Haizhong Qian, Xiao Wang, Junkui Xu

“…Traditional methods rely on different machine learning algorithms tailored to specific types of line and polygon elements, limiting their general applicability. …”
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Smart Grid Security: Proactive Prediction of Advanced Persistent Threats by Motahareh Dehghan, Erfan Khosravain

“…Experimental results show that the ProAPT model significantly outperforms traditional machine learning algorithms like Random Forest, Support Vector Machines, and Logistic Regression, achieving 93.8% accuracy, 93.12% precision, 95.2% recall, and 94.15% F1-Score. …”
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PyNoetic: A modular python framework for no-code development of EEG brain-computer interfaces. by Gursimran Singh, Aviral Chharia, Rahul Upadhyay, Vinay Kumar, Luca Longo

“…For advanced users, it facilitates the seamless integration of custom functionalities and novel algorithms with minimal coding, ensuring adaptability at each design stage. …”
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A hybrid extraction model for semantic knowledge discovery of water conservancy big data by Yanna Feng, Feng Zhang, Yongheng Zhang, Jiangang Dong, PengJu Wang

“…A novel, transferable web information extraction model based on deep learning (WIEM-DL) is proposed, leveraging knowledge graphs, machine learning, and ontology-based methods. This model is designed to adapt to varying website structures, enabling effective cross-website information extraction. …”
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A novel ensemble model for fall detection: leveraging CNN and BiLSTM with channel and temporal attention by Sarita Sahni, Sweta Jain, Sri Khetwat Saritha

“…Despite the proliferation of machine learning and deep learning algorithms for fall detection, their efficacy remains hampered by resilience, robustness, and adaptability challenges across varied input scenarios. …”
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Design of an efficient dynamic context‐based privacy policy deployment model via dual bioinspired Q learning optimisations by Namrata Jiten Patel, Ashish Jadhav

“…The approach employs Firefly Optimiser (FFO) and Ant Lion Optimiser (ALO) algorithms to dynamically adjust privacy parameters and handle large datasets efficiently. …”
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TraitBertGCN: Personality Trait Prediction Using BertGCN with Data Fusion Technique by Muhammad Waqas, Fengli Zhang, Asif Ali Laghari, Ahmad Almadhor, Filip Petrinec, Asif Iqbal, Mian Muhammad Yasir Khalil

“…Abstract Personality prediction via different techniques is an established and trending topic in psychology. The advancement of machine learning algorithms in multiple fields also attracted the attention of Automatic Personality Prediction (APP). …”
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Comparative Analysis of Control Strategies for Microgrid Energy Management with a Focus on Reinforcement Learning by Parisa Mohammadi, Razieh Darshi, Saeed Shamaghdari, Pierluigi Siano

“…In contrast, reinforcement learning, a branch of machine learning, excels by continuously learning and optimizing through real-time interactions This approach offers greater flexibility and adaptability in complex and dynamic environments. …”
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Current Situation and Prospect of Fluid Identification in Non-Resistivity Logging by YUAN Lixin, WU Hongliang, FENG zhou, TIAN Han, WANG Kewen, LIU Peng

“…Meanwhile, trying to extract fast neutron cross-sections for fluid identification based on nuclear logging tools such as Litho Scanner. Combining machine learning algorithms for extracting fluid information and distinguishing properties from spectra. …”
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Non-Contact Dimensional Quality Inspection System of Prefabricated Components Using 3D Matrix Camera by Wanqing Lyu, Xiwang Chen, Wenlong Han, Kun Ni, Rui Jing, Lin Tong, Junzheng Pan, Qian Wang

“…This study thus developed a non-contact image measurement system using an innovative three-dimensional (3D) matrix camera, which automatically performed dimensional quality inspection, utilizing technologies such as a parallel optical axis four-camera matrix imaging and machine learning algorithms. Compared to traditional techniques, this system exhibited enhanced adaptability to the manufacturing process of prefabricated components, along with desirable accuracy and efficiency. …”
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Towards a smart debt collection system: a Design Science Research approach by Michał Przybyłek, Adam Przybyłek, Konrad Wojciechowski, Illia Shkroba

“…The application of AI algorithms in this context has the potential to revolutionize the industry and enhance overall debt collection practices. …”
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Intelligent Fault Diagnosis Across Varying Working Conditions Using Triplex Transfer LSTM for Enhanced Generalization by Misbah Iqbal, Carman K. M. Lee, Kin Lok Keung, Zhonghao Zhao

“…Fault diagnosis plays a pivotal role in ensuring the reliability and efficiency of industrial machinery. While various machine/deep learning algorithms have been employed extensively for diagnosing faults in bearings and gears, the scarcity of data and the limited availability of labels have become a major bottleneck in developing data-driven diagnosis approaches, restricting the accuracy of deep networks. …”
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Spatial Evaluation of <i>Salurnis marginella</i> Occurrence According to Climate Change Using Multiple Species Distribution Models by Jae-Woo Song, Jaho Seo, Wang-Hee Lee

“…<i>marginella</i> by developing multiple species distribution modeling (SDM) algorithms. Specifically, we developed the CLIMEX model and three machine learning-based models (MaxEnt, random forest, and multi-layer perceptron), integrated them to conservatively assess pest occurrence under current and future climates, and overlaid the host distribution with climatically suitable areas of <i>S. marginella</i> to identify high-risk areas vulnerable to the spread and invasion of the pest. …”
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Multimodal dataset for sensor fusion in fall detection by Carla Taramasco, Miguel Pineiro, Pablo Ormeño-Arriagada, Diego Robles, David Araya

“…Adaptable solutions are essential to cater to the diverse conditions under which falls occur. …”
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Optimization Path and Design of Intelligent Logistics Management System Based on ROS Robot by Ruijie Wu

“…Therefore, this paper aimed to design an intelligent logistics management system based on ROS robot and proposed to use the A-star algorithm to calculate the shortest path of the robot so as to achieve the optimal path. …”
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Transfer Learning-Empowered Physical Layer Security in Aerial Reconfigurable Intelligent Surfaces-Based Mobile Networks by Yosefine Triwidyastuti, Tri Nhu Do, Ridho Hendra Yoga Perdana, Kyusung Shim, Beongku An

“…To address these challenges, we develop robust algorithms for optimizing the phase-shift configurations of RIS. …”
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Transfer and deep learning models for daily reference evapotranspiration estimation and forecasting in Spain from local to national scale by Yu Ye, Aurora González-Vidal, Miguel A. Zamora-Izquierdo, Antonio F. Skarmeta

“…This study compares standard ML and Deep Learning (DL) algorithms for estimating and forecasting daily ET0 at different spatial scales in Spain. …”
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ANALYSIS OF GENERAL PLOW BODY TRACTIVE RESISTANCE by A. Yu. Izmaylov, A. A. Artyushin, N. E. Evtyushenkov, G. S. Bisenov, V. F. Rozhin, D. N. Kynev

“…The authors offered algorithm for modeling of technologies of a crop transportation from combine harvesters according to transfer schemes, with use of a loading crane based on the tractor-trailer and replaceable bodies. …”
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Assisting human annotation of marine images with foundation models by Eric C. Orenstein, Eric C. Orenstein, Benjamin Woodward, Lonny Lundsten, Kevin Barnard, Brian Schlining, Kakani Katjia

“…Marine scientists have been leveraging supervised machine learning algorithms to analyze image and video data for nearly two decades. …”
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