Safeguards-related event detection in surveillance video using semi-supervised learning approach by Se-Hwan Park, Byung-Hee Won, Seong-Kyu Ahn

Subjects: “…Deep learning…”
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Dynamics of Students’ Opinions in the Context of the Transition to Online Learning Based on Social Network Data by A. V. Bogdanova, Yu. K. Aleksandrova, V. V. Orlova, E. Yu. Petrov, V. F. Glazova

Subjects: “…distance learning…”
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Artificial intelligence and machine learning in mobile apps for mental health: A scoping review. by Madison Milne-Ives, Emma Selby, Becky Inkster, Ching Lam, Edward Meinert

“…PubMed was systematically searched for randomised controlled trials and cohort studies published in English since 2014 that evaluate artificial intelligence- or machine learning-enabled mobile apps for mental health support. …”
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Multitask Learning-Based Pipeline-Parallel Computation Offloading Architecture for Deep Face Analysis by Faris S. Alghareb, Balqees Talal Hasan

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A Deep Reinforcement Learning Approach for Ramp Metering Based on Traffic Video Data by Bing Liu, Yu Tang, Yuxiong Ji, Yu Shen, Yuchuan Du

“…In this work, we propose a deep reinforcement learning (DRL) method to explore the potential of traffic video data in improving the efficiency of ramp metering. …”
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Learning transactions representations for information management in banks: Mastering local, global, and external knowledge by Alexandra Bazarova, Maria Kovaleva, Ilya Kuleshov, Evgenia Romanenkova, Alexander Stepikin, Aleksandr Yugay, Dzhambulat Mollaev, Ivan Kireev, Andrey Savchenko, Alexey Zaytsev

Subjects: “…Representation learning…”
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Detection freezing of gait (FOG) in Parkinson's patients using wearable sensors and deep learning by Maryam Talebvand, Amir Lakizadeh, Faranak Fotouhi

Subjects: “…deep learning…”
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Machine Learning for Lung Cancer Subtype Classification: Combining Clinical, Histopathological, and Biophysical Features by Aiga Andrijanova, Lasma Bugovecka, Sergejs Isajevs, Donats Erts, Uldis Malinovskis, Andis Liepins

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Implementasi total quality learning untuk peningkatan berkelanjutan di tingkat sekolah dasar by Ratnawati Susanto

“…Total quality learning (TQL) merupakan konsep fundamental dan memiliki nilai yang menjadi kunci keberhasilan sebuah institusi manajemen layanan pendidikan dan pembelajaran di sekolah. …”
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Enhancing Heart Attack Prediction with Machine Learning: A Study at Jordan University Hospital by Mohammad Alshraideh, Najwan Alshraideh, Abedalrahman Alshraideh, Yara Alkayed, Yasmin Al Trabsheh, Bahaaldeen Alshraideh

“…This study uses the Jordan University Hospital (JUH) Heart Dataset to develop and evaluate machine-learning models for predicting heart disease. The primary objective of this study is to enhance prediction accuracy by utilizing a comprehensive approach that includes data preprocessing, feature selection, and model development. …”
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Preservice Teachers’ Shifting Perspectives of Individuals with Intellectual and Developmental Disabilities in Service-Learning Experiences by Stephanie Devine, Cynthia Massey, Kathryn Haughney, Akintomide Adebile

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Applied machine learning for predicting the properties and carbon and phosphorus fate of pristine and engineered hydrochar by Shiyu Xie, Tao Zhang, Siming You, Santanu Mukherjee, Mingjun Pu, Qing Chen, Yaosheng Wang, Esmat F. Ali, Hamada Abdelrahman, Jörg Rinklebe, Sang Soo Lee, Sabry M. Shaheen

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The Optimal Machine Learning Model for the Precise Prediction of HighPerformance Concrete Strength Property by Yufeng Qian

“…The present study employs a machine learning-based support vector regression (SVR) method to implement compressive strength prediction. …”
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Decision tree-based learning and laboratory data mining: an efficient approach to amebiasis testing by Enas Al-khlifeh, Ahmad S. Tarawneh, Khalid Almohammadi, Malek Alrashidi, Ramadan Hassanat, Ahmad B. Hassanat

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Finding Neural Biomarkers for Motor Learning and Rehabilitation Using an Explainable Graph Neural Network by J. Han, A. Embs, F. Nardi, S. Haar, A. A. Faisal

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Identifying Ocean Submesoscale Activity From Vertical Density Profiles Using Machine Learning by Leyu Yao, John R. Taylor, Dani C. Jones, Scott D. Bachman

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A Novel Active Learning Technique for Fetal Health Classification Based on XGBoost Classifier by Kaushal Bhardwaj, Niyati Goyal, Bhavika Mittal, Vandna Sharma, Shiv Naresh Shivhare

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RISKS REDUCING THROUGH INTELLIGENT HEADLIGHT MANAGEMENT: OPTIMIZING Q-LEARNING FOR ELECTRIC VEHICLES by Pitchaya Jamjuntr, Chanchai Techawatcharapaikul, Pannee Suanpang

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RFMVDA: An Enhanced Deep Learning Approach for Customer Behavior Classification in E-Commerce Environments by Kwanhee Kim, Mingyu Jo, Ilkyeun Ra, Sangoh Park

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The good, the better and the challenging: Insights into predicting high-growth firms using machine learning by Sermet Pekin, Aykut Şengül

“…This study aims to classify high-growth firms using several machine learning algorithms, including K-Nearest Neighbors, Logistic Regression with L1 (Lasso) and L2 (Ridge) Regularization, XGBoost, Gradient Descent, Naive Bayes and Random Forest. …”
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