Learning Analytics for Bridging the Skills Gap: A Data-Driven Study of Undergraduate Aspirations and Skills Awareness for Career Preparedness by Joel Weijia Lai, Lei Zhang, Chun Chau Sze, Fun Siong Lim

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Applying genetic algorithm to extreme learning machine in prediction of tumbler index with principal component analysis for iron ore sintering by Senhui Wang

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Investigation of groundwater quality indices and health risk assessment of water resources of Jiroft city, Iran, by machine learning algorithms by Sobhan Maleky, Maryam Faraji, Majid Hashemi, Akbar Esfandyari

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Prediction of football injuries using GPS-based data in Iranian professional football players: a machine learning approach by Reza Saberisani, Amir Hossein Barati, Mostafa Zarei, Paulo Santos, Armin Gorouhi, Luca Paolo Ardigò, Hadi Nobari

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Assessing Glioblastoma Treatment Response Using Machine Learning Approach Based on Magnetic Resonance Images Radiomics: An Exploratory Study by Amirreza Sadeghinasab, Jafar Fatahiasl, Marziyeh Tahmasbi, Sasan Razmjoo, Mohammad Yousefipour

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Unveiling farmers’ perceptions: a citizen science and machine learning approach to exploring drivers in the adequacy and fairness of water systems by Vasilios Plakandaras, Fahad Khan Khadim, Vassiliki Kazana, Emmanouil Anagnostou, Amvrossios C Bagtzoglou

Subjects: “…machine learning…”
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Channel Mixer Layer: Multimodal Fusion Toward Machine Reasoning for Spatiotemporal Predictive Learning of Ionospheric Total Electron Content by Peng Liu, Tatsuhiro Yokoyama, Takuya Sori, Mamoru Yamamoto

Subjects: “…spatiotemporal predictive learning…”
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Automated Detection of Macular Diseases by Optical Coherence Tomography and Artificial Intelligence Machine Learning of Optical Coherence Tomography Images by Soichiro Kuwayama, Yuji Ayatsuka, Daisuke Yanagisono, Takaki Uta, Hideaki Usui, Aki Kato, Noriaki Takase, Yuichiro Ogura, Tsutomu Yasukawa

“…The purpose of this study is to test deep learning with image augmentation for automated detection of chorioretinal diseases. …”
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Enhancing trauma triage in low-resource settings using machine learning: a performance comparison with the Kampala Trauma Score by Mike Nsubuga, Timothy Mwanje Kintu, Helen Please, Kelsey Stewart, Sergio M. Navarro

Subjects: “…Machine learning…”
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Bearing Response Prediction in Hydrothermal Aged Carbon Fiber Reinforced Epoxy Composite Joints Using Machine Learning Techniques by Mohit Kumar, Govind Vashishtha, Babita Dhiman, Sumika Chauhan

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Enhancing precision in multiple sclerosis lesion segmentation: A U-net based machine learning approach with data augmentation by Oezdemir Cetin, Berkay Canel, Gamze Dogali, Unal Sakoglu

“…This study proposes a robust machine learning algorithm designed to identify MS lesions using both single-modal and multi-modal MRI data. …”
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Forecasting O3 and NO2 concentrations with spatiotemporally continuous coverage in southeastern China using a Machine learning approach by Zeyue Li, Jianzhao Bi, Yang Liu, Xuefei Hu

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UAV-assisted federated learning with hybrid LoRa P2P/LoRaWAN for sustainable biosphere by Mehran Behjati, Haider A. H. Alobaidy, Rosdiadee Nordin, Nor Fadzilah Abdullah

Subjects: “…federated learning…”
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Qualitative study on nurse preceptors’ preparedness, roles and familiarity with the basic principles of teaching and learning in a district hospital in Ghana by Dorothy Serwaa Boakye, Vida Maame Kissiwaa Amoah, Edward Appiah Boateng, John Antwi, Joyce Yeboah, Jennifer Owusu

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Crop yield prediction through machine learning: A path towards sustainable agriculture and climate resilience in Saudi Arabia by Mohammad M. Islam, Majed Alharthi, Rotana S. Alkadi, Rafiqul Islam, Abdul Kadar Muhammad Masum

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Development of the algorithm for classifying industries according to the type of intra-factory cooperation of main and auxiliary processes using machine learning by T. V. Malysheva

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Energy Use and Demand Prediction Using Time-Series Deep Learning Forecasting Techniques: Application for a University Campus by Bivin Pradeep, Parag Kulkarni, Farman Ullah, Abderrahmane Lakas

“…., analysis of energy consumption and demand forecasting using deep learning-based time series techniques such as Long short-term memory (LSTM), Bi-directional Long short-term memory (BiLSTM), Gated recurrent unit (GRU), and Bidirectional Gated recurrent units (BiGRU). …”
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Enhancing laboratory education through collaborative online international learning: A case study between USA and UK students by Matthew Allan Jones, Pika Miklavc, MaryAnne Stewart

Subjects: “…International Learning1…”
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WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches by Shehla Gul, Sobia Arshad, Sanay Muhammad Umar Saeed, Adeel Akram, Muhammad Awais Azam

Subjects: “…deep learning (DL)…”
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A Data-Driven Fault Prediction Method for Nuclear Power Systems Based on End-to-End Deep Learning Framework by Lu Chao, Chunbing Wang, Shuai Chen, Qizhi Duan, Hongyun Xie

“…At the same time, due to the rapid development of deep learning technology, it has become a meaningful development direction to predict the fault state of nuclear power plants within the framework of supervised deep learning. …”
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