Vibration Signal-Based Fault Diagnosis of Rotary Machinery Through Convolutional Neural Network and Transfer Learning Method by Chirag Mongia, Shankar Sehgal

“…However, traditional fault detection methods often struggle in dynamic environments due to their dependence on specific training conditions. …”
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The effect of exercises according to the differentiated education method in developing agility and learning the collar skill of students in rhythmic gymnastics by منــال مـحمـد احــمد أ.د مواهب حميد الجبوري

“…Dimensional tests and the statistical bag (spss) were used to extract the Results and through it she concluded through her research to increase the effectiveness of the differentiated teaching method in female students' teaching than the rest of the teaching methods because of its positive impact on learning the performance of ring skill in rhythmic gymnastics. …”
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A Machine Learning-Based Ransomware Detection Method for Attackers’ Neutralization Techniques Using Format-Preserving Encryption by Jaehyuk Lee, Jinwook Kim, Hanjo Jeong, Kyungroul Lee

“…In this article, we present a machine learning-based method for detecting ransomware-infected files encrypted using FPE techniques. …”
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Deep learning algorithm for the automatic assessment of axial vertebral rotation in patients with scoliosis using the Nash–Moe method by Jeoung Kun Kim, Ming Xing Wang, Donghwi Park, Min Cheol Chang

“…The Nash–Moe classification method has been extensively used for AVR assessment; however, its subjective nature can lead to measurement variability. …”
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Mixed-meta Method Concerning the Effect of Blended Learning Practices on Students’ Academic Achievement in Higher Education Settings by Abdullah Bingölbali, Aydın Aslan, Veli Batdi, Emrah Cinkara

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Studying the performance of pavement defects at different road slopes using the vibration-based method and deep machine learning by Amir Shtayat

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RSNC-YOLO: A Deep-Learning-Based Method for Automatic Fine-Grained Tuna Recognition in Complex Environments by Wenjie Xu, Hui Fang, Shengchi Yu, Shenglong Yang, Haodong Yang, Yujia Xie, Yang Dai

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Enhancing landslide susceptibility modelling through a novel non-landslide sampling method and ensemble learning technique by Chao Zhou, Yue Wang, Ying Cao, Ramesh P. Singh, Bayes Ahmed, Mahdi Motagh, Yang Wang, Ling Chen, Guangchao Tan, Shanshan Li

“…The study aims to extract high-quality non-landslide samples and improve the accuracy of landslide susceptibility modelling (LSM) outcomes by applying a coupled method of ensemble learning and Machine Learning (ML). …”
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A reinforcement learning based real-time energy management method for mobile microgrid considering photovoltaic uncertainty by Huasong Fang, Huayue Zhang, Shuli Wen, Zhong Li, Zhilin Zeng, Miao Zhu, Pengfeng Lin

“…To address this issue, this paper proposes a real-time energy management optimization method based on reinforcement learning, specifically tailored to handle PV uncertainty and dynamic load variations during navigation. …”
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Enhancing Qur'anic Literacy Among The Community of Sioban Village Mentawai Islands Through The Service Learning Method by Muhammad Nurul Alim, Jefri Adiminoto, Tio Gunawan, Laode Muhammad Raudhatul Jannah, Muh. Faujan, Ashari Erlangga, Randy Putra Lopolisa, Ahmad Sholihin

“…The methods employed included intensive training sessions, experience-based repetition, and the active involvement of local leaders and families. …”
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Mapping the invasive Spartina alterniflora in sub-meter level with improved phenological spectral features and deep learning method by Bingfeng Zhou, Meng Xu, Jinyan Tian, Yue Huang, Jie Song, Lin Zhu, Xiumin Zhu, Xinyuan Qu, Liyan Zhang, Xiaojuan Li, Huili Gong

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High-precision large-aperture single-frame interferometric surface profile measurement method based on deep learning by Liang Tang, Mingzhi Han, Shuai Yang, Ye Sun, Lirong Qiu, Weiqian Zhao

“…Therefore, this study proposes a high-precision large-aperture single-frame interferometric surface profile measurement (LA-SFISPM) method based on deep learning and explores its capability to realize dynamic measurements with high accuracy. …”
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A novel deep learning model based on YOLOv5 optimal method for coal gangue image recognition by Tongkai Gu, Haiyan Zhao, Yasheng Chang, Sitong Yan, Feihan Cao, Wei Liu

“…Abstract Coal gangue recognition presents significant challenges in the mining industry due to its inefficient and costly traditional treatment methods. The advent of deep learning techniques has introduced novel solutions for automating and online coal gangue processing. …”
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Combining the SHAP Method and Machine Learning Algorithm for Desert Type Extraction and Change Analysis on the Qinghai–Tibetan Plateau by Ruijie Lu, Shulin Liu, Hanchen Duan, Wenping Kang, Ying Zhi

“…Then, on the basis of the best classification model, the Shapely Additive Explanations (SHAP) method is used to clarify the contribution of each classification feature to the identification of desert types during the machine learning classification process, both globally and locally. …”
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A Quality Control Method based on Combination Deep Learning for Measurement Data of Complex Mountain Wind Farm by Runjin YAO, Shuaibing CHENG, Qianqian ZHAO, Wenlong LI, Dong QIAN

“…Mountainous winds exhibit strong intermittent， fluctuating， and non-stationary characteristics due to the influence of terrain， resulting in poor observation quality， which makes conventional quality control methods unable to effectively improve their observation quality.To address this issue， a quality control method （VCG） based on variational mode decomposition， convolutional neural networks， and deep learning of gated cyclic units is constructed， and a particle swarm optimization strategy and wind power reconstruction model are introduced to comprehensively improve the quality of observation data.To verify the effectiveness of this method， 10 minute wind speed and direction data of target wind turbines in six complex mountainous wind farms in Jiangxi Ganzhou， Sichuan Guangyuan， Anhui Wuhu， Hubei Huangshi， Henan Pingdingshan， and Guangxi Hezhou in 2016 was quality controlled by VCG and compared with single machine learning method， spatial regression method （SRT）， and inverse distance weighting method （IDW）.The results indicate that VCG method is suitable for quality control of observed wind data in mountainous wind farms， and has a higher error detection rate for suspicious data compared to conventional methods； The controlled data can better restore the observed background field and have a lower error rate when applied to the power generation evaluation business of wind farms； And it has the characteristics of strong terrain adaptability.…”
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A Fast Identification Method for Seismic Responses of Bridge Structures by Integrating Digital Signal Features and Deep Learning by Zhaoxu Lv, Youliang Ding, Junxiao Guo

“…A method of bridge structure seismic response identification combining signal processing technology and deep learning technology is proposed. …”
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A Combined Deep Learning Method with Attention-Based LSTM Model for Short-Term Traffic Speed Forecasting by Pan Wu, Zilin Huang, Yuzhuang Pian, Lunhui Xu, Jinlong Li, Kaixun Chen

“…Recent studies have shown that deep learning methods, especially long short-term memory (LSTM) models, have good results in short-term traffic flow prediction. …”
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Improving the Skill of Subseasonal to Seasonal (S2S) Wind Speed Forecasts Over India Using Statistical and Machine Learning Methods by Aheli Das, Dondeti Pranay Reddy, Somnath Baidya Roy

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A new method and information system based on artificial intelligence for black flight identification by Arwin Datumaya Wahyudi Sumari, Rosa Andrie Asmara, Ika Noer Syamsiana

“…The contributions of this research are: • a new method of black flight identification that combines air speed data and altitude with Radar Cross Section (RCS) data using machine learning, • a new information system that combines the display of the Plan Position Indicator (PPI) of military radar and ADS-B to accelerate decision-making on black flight, • a new approach to national air defense procedures.…”
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HiViT-IDS: An Efficient Network Intrusion Detection Method Based on Vision Transformer by Hai Zhou, Haojie Zou, Wei Li, Di Li, Yinchun Kuang

“…While these methods substantially improve detection accuracy, they also lead to increased time and resource consumption during training. …”
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