A Few-shot Learning Method for Intent Analysis of Air Combat Confrontation Behaviors by PAN Ming, ZHENG Jingsong, LI Jinliang, FANG Long, YANG Yang, ZHAO Shijie

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Using Wavelet Analysis and Deep Learning for EMG-Based Hand Movement Signal Classification by Abdullah Erhan Akkaya, Harun Güneş

“…In this study; time series electromyography (EMG) data have been classified according to hand movements using wavelet analysis and deep learning. …”
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The Development of Ethnoscience in Chemistry Learning in Indonesia: A Bibliometric Analysis of Literacy and Cultural Relevance by Vika Puji Cahyani, Dewiyanti Fadly

“…This study uses a bibliometric technique and is quantitative descriptive in nature. he stages include Selection of Topic and Research Objectives, Data Collection, Data Cleaning and Processing, Data Analysis, Data Visualisation, Interpretation and Discussion. …”
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Advances in Application of Federated Machine Learning for Oncology and Cancer Diagnosis by Mohammad Nasajpour, Seyedamin Pouriyeh, Reza M. Parizi, Meng Han, Fatemeh Mosaiyebzadeh, Yixin Xie, Liyuan Liu, Daniel Macêdo Batista

“…In this paper, we conducted a comprehensive literature review aimed at identifying the most advanced federated learning applications in cancer research and clinical oncology analysis. …”
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Decoding cancer prognosis with deep learning: the ASD-cancer framework for tumor microenvironment analysis by Ziyuan Huang, Yunzhan Li, Vanni Bucci, John P. Haran

“…Building on this powerful potential, Zhang et al. proposed a semi-supervised learning framework called Autoencoder-Based Subtypes Detector for Cancer (ASD-cancer) to improve the multi-omics data analysis (H. …”
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Advanced Machine Learning for Preschooler Magnetic Resonance Imaging Analysis in Classification of Anxiety Disorders by Salik Mian, Pranav Kunderu, Shivm Patel

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Open-World Semi-Supervised Learning for fMRI Analysis to Diagnose Psychiatric Disease by Chang Hu, Yihong Dong, Shoubo Peng, Yuehan Wu

“…To improve open-world semi-supervised representation learning and classification in fMRI under low-label settings, we propose a novel open-world semi-supervised learning approach tailored for functional magnetic resonance imaging analysis, termed Open-World Semi-Supervised Learning for fMRI Analysis (OpenfMA). …”
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Plastic to apparel: an analysis of sustainable purchasing intention using a machine learning ensemble by Carmella Andrea L. Cabrera, Ardvin Kester S. Ong, John Francis T. Diaz, Maela Madel L. Cahigas, Ma. Janice J. Gumasing

“…Data preprocessing using feature selection and correlation analysis was conducted to validate the available data, performed data cleaning process, and data aggregation. …”
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Survey of research on encrypted traffic classification based on machine learning by FU Yu, LIU Taotao, WANG Kun, YU Yihan

“…However, the complexity and variability of the current network traffic environment rendered traditional classification methods largely ineffective. Machine learning, particularly deep learning, with its strong feature extraction capabilities, has been widely used in the field of encrypted traffic classification. …”
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Natural Language Processing and Machine Learning for Analysis of Radiology Reports: A Systematic Review by Umay Kulsoom, Frank G. Glavin, Malika Bendechache

“…Integrating AI technologies can improve data analysis, enhance diagnostic accuracy, and streamline clinical workflows, reducing the burden on physicians. …”
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Time Series Analysis of Solar Power Generation Based on Machine Learning for Efficient Monitoring by Umer Farooq, Muhammad Faheem Mushtaq, Zahid Ullah, Muhammad Talha Ejaz, Urooj Akram, Sheraz Aslam

“…The study consists of many analytical phases, including exploratory data analysis, power generation data analysis, and inverter data analysis, which are carried out on two separate power plants. …”
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Comprehensive Review of Privacy, Utility, and Fairness Offered by Synthetic Data by A. Kiran, P. Rubini, S. Saravana Kumar

“…It is increasingly used in both data analysis and building predictive models from the data. …”
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Retracted: Efficiency Analysis of Machine Learning Intelligent Investment Based on K-Means Algorithm by Liang Li, Jia Wang, Xuetao Li

“…With the rapid development of technologies such as big data, intelligent data analysis and cloud computing, the application of Internet financial technology has become more and more extensive, and with the advent of the era of large asset management in the domestic wealth management industry, in order to improve the efficiency of financial services, traditional finance is needed. …”
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Analysis of ability to listen to descriptive text through the implementation of the learning team’s strategy student by Ruth C Paath

“…The data analysis technique is inductive based on the facts obtained in the learning process and then constructed according to its type. …”
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Energy consumption analysis and prediction in exercise training based on accelerometer sensors and deep learning by Zhangjian Guo, Tongling Wang, Shuxun Chi, Li Huang

“…Additionally, by analyzing the relationship between the X, Y, and Z-axis accelerations, overall magnitude, and energy consumption, a multidimensional feature analysis framework is proposed to enhance the model’s comprehensive understanding of motion data. …”
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Exploring the potential and limitations of deep learning and explainable AI for longitudinal life course analysis by Helen Coupland, Neil Scheidwasser, Alexandros Katsiferis, Megan Davies, Seth Flaxman, Naja Hulvej Rod, Swapnil Mishra, Samir Bhatt, H. Juliette T. Unwin

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Deep Learning for Urban Tree Canopy Coverage Analysis: A Comparison and Case Study by Grayson R. Morgan, Danny Zlotnick, Luke North, Cade Smith, Lane Stevenson

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Unleashing the Potential of Blockchain and Machine Learning: Insights and Emerging Trends From Bibliometric Analysis by Nouhaila El Akrami, Mohamed Hanine, Emmanuel Soriano Flores, Daniel Gavilanes Aray, Imran Ashraf

“…Alternatively, ML is a sub-field of artificial intelligence (AI) that empowers systems to enhance their performance by learning from data. The integration of these data-driven paradigms holds the potential to reinforce data privacy and security, improve data analysis accuracy, and automate complex processes. …”
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Is Blended Learning Effective in Developing Critical Thinking Skills? : A Meta-Analysis Study by Aris Martiana, Siti Irene Astuti Dwiningrum, Suranto Aw

“…This is done to estimate aggregates, project forest plots, test heterogeneity, and investigate publication bias. The analysis found that there is accuracy in using a random effect model aggregate with a high heterogeneity effect size and no prob-lems in publication, so following the research objective the blended learning model is effective in developing critical thinking skills in learning so that technology in education has a positive impact Keywords: Blended learning, critical thinking, meta-analysis, effective…”
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FedRSC: A Federated Learning Analysis for Multi-Label Road Surface Classifications by Ioannis V. Vondikakis, Ilias E. Panagiotopoulos, George J. Dimitrakopoulos

“…The presented analysis prioritizes the privacy of road users’ data and leverages the advantages of collective data analysis while building confidence in the system. …”
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