CausMatch: Causal Matching Learning With Counterfactual Preference Framework for Cross-Modal Retrieval by Chen Chen, Dan Wang

Subjects: “…Multimodal learning…”
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Conv‐ELSTM: An ensemble deep learning approach for predicting short‐term wind power by Guibin Wang, Xinlong Huang, Yiqun Li, Hong Wang, Xian Zhang, Jing Qiu

“…This article introduces a hybrid data‐driven framework that employs an ensemble deep learning model to provide highly precise short‐term wind power predictions. …”
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Predicting the delisted companies of Tehran Stock Exchange using machine learning based algorithms by Aminollah Zarghami, Meysam Doaei, Abtin Boostani

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Machine learning techniques for estimating high–temperature mechanical behavior of high strength steels by C. Yazici, F.J. Domínguez-Gutiérrez

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Dynamic Interferometry for Freeform Surface Measurement Based on Machine Learning-Configured Deformable Mirror by Xu Chang, Yao Hu, Jintao Wang, Xiang Liu, Qun Hao

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Language-mixing in Content and Language Integrated Learning: benefit or burden? An auditory recall perspective by Thomas Caira, Mathieu Declerck, Esli Struys

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Integrating Handcrafted Features with Machine Learning for Hate Speech Detection in Albanian Social Media by Fetahi Endrit, Hamiti Mentor, Susuri Arsim, Zenuni Xhemal, Ajdari Jaumin

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Machine Learning and Intelligent Diagnostics in Dental and Orofacial Pain Management: A Systematic Review by Taseef Hasan Farook, Nafij Bin Jamayet, Johari Yap Abdullah, Mohammad Khursheed Alam

“…GRADE approach revealed serious risks of bias and inconsistencies with most studies containing more positive cases than their true prevalence in order to facilitate machine learning. Patient-perceived symptoms and clinical history were generally found to be less reliable than radiographs or histology for training accurate machine learning models. …”
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COVID-19 World Vaccine Adverse Reactions Based on Machine Learning Clustering Algorithm by Lozan M. Abdulrahman, Adnan Mohsin Abdulazeez, Dathar A. Hasan

Subjects: “…COVID-19 Vaccine Reactions, Machine Learning, Clustering Algorithm, VARSE, Weka…”
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Mitigating bias in AI mortality predictions for minority populations: a transfer learning approach by Tianshu Gu, Wensen Pan, Jing Yu, Guang Ji, Xia Meng, Yongjun Wang, Minghui Li

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The implementation of EFL online learning: how do the non-English department students perceive it? by M. Ali Ghufron

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Unsupervised machine and deep learning methods for structural damage detection: A comparative study by Zilong Wang, Young‐Jin Cha

Subjects: “…deep learning…”
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3D Interactions between Virtual Worlds and Real Life in an E-Learning Community by Ulrike Lucke, Raphael Zender

“…The primary advantages of this interconnection are a spatial extension of face-to-face and online learning scenarios and a closer relationship between virtual learners and the real world.…”
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Robust analysis of photovoltaic plants: A framework based on prediction uncertainties by machine learning by Seyyed Shahabaddin Hosseini Dehshiri, Bahar Firoozabadi

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Design of a Novel NNs Learning Tracking Controller for Robotic Manipulator with Joints Flexibility by Pengxiao Jia

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Lunar Calendar Usage to Improve Forecasting Accuracy Rainfall via Machine Learning Methods by Gumgum Darmawan, Gatot Riwi Setyanto, Defi Yusti Faidah, Budhi Handoko

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Password strength verification based on machine learning algorithms and LSTM recurrent neural networks by V. V. Belikov, I. A. Prokuronov

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A Machine Learning Approach to Adapt Local Land Use Planning to Climate Change by Julia Forster, Stefan Bindreiter, Birthe Uhlhorn, Verena Radinger-Peer, Alexandra Jiricka-Pürrer

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Selection of Machine Learning Models for Oil Price Forecasting: Based on the Dual Attributes of Oil by Lei Yan, Yuting Zhu, Haiyan Wang

“…Since the commodity and financial attributes of crude oil will have a long-term or short-term impact on crude oil prices, we propose a de-dimension machine learning model approach to forecast the international crude oil prices. …”
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A Machine Learning Algorithm to Predict Medical Device Recall by the Food and Drug Administration by Victor Barbosa Slivinskis, Isabela Agi Maluli, Joshua Seth Broder

“…Our objective was to evaluate the sensitivity, specificity, and accuracy of a machine learning (ML) algorithm using publicly available data to predict medical device recalls by the FDA. …”
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