Evaluation of statistical methods applied in theses and dissertations in an Open, Distance and e-Learning University. by Legesse Kassa Debusho, Mahlageng Retang Mashabela, Phuti Naphtaly Sebatjane, Sthembile Sithole, Busisiwe Tabo, Eeva-Maria Rapoo

“…The appropriate application of research methods and statistical analyses used in the studies directly affects the quality of scientific studies. …”
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Risk-based evaluation of machine learning-based classification methods used for medical devices by Martin Haimerl, Christoph Reich

“…Abstract Background In the future, more medical devices will be based on machine learning (ML) methods. In general, the consideration of risks is a crucial aspect for evaluating medical devices. …”
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Physical Layer Spoof Detection and Authentication for IoT Devices Using Deep Learning Methods by Da Huang, Akram Al-Hourani

“…In this work, we propose an authentication method based on radio frequency fingerprinting (RFF) using deep learning. …”
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Research on optimal selection of runoff prediction models based on coupled machine learning methods by Xing Wei, Mengen Chen, Yulin Zhou, Jianhua Zou, Libo Ran, Ruibo Shi

“…Compared to the single LSTM model, the Nash-Sutcliffe Efficiency (NSE) and Pearson’s correlation coefficient (R) of the VMD-LSTM model were improved by 15.06% and 6.82%, respectively; (3) Among the machine learning prediction models coupled with various methods, the VMD-SSA-LSTM model achieved the highest accuracy. …”
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Identification of fungal diseases in strawberry by analysis of hyperspectral images using machine learning methods by A. F. Cheshkova

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Comparative Assessment of Several Effective Machine Learning Classification Methods for Maternal Health Risk by Md Nurul Raihen, Sultana Akter

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A Review of Intrusion Detection for Railway Perimeter Using Deep Learning-Based Methods by Jin Wang, Hongyang Zhai, Yang Yang, Niuqi Xu, Hao Li, Di Fu

“…This article reviews the background and importance of detecting railway perimeter intrusion, summarizes the limitations of traditional detection methods, and emphasizes the potential of improving detection accuracy and efficiency in image recognition with deep learning models. …”
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Identification of critical biomarkers and immune infiltration in preeclampsia through bioinformatics and machine learning methods by Weiwen Li, Lijun Zhong, Kewen Zhao, Jincheng Xie, Shaodong Deng, Yunyong Fang

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Prediction of alkali-silica reaction expansion of concrete using explainable machine learning methods by Yasitha Alahakoon, Hirushan Sajindra, Ashen Krishantha, Janaka Alawatugoda, Imesh U. Ekanayake, Upaka Rathnayake

“…Abstract Traditionally, ASR expansion is determined using experimental and finite element method (FEM) based numerical modelling. However, these methods are time-consuming and computationally costly, which makes ASR prediction challenging. …”
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An Effective Approach for Human Activity Classification Using Feature Fusion and Machine Learning Methods by Muhammad Junaid Ibrahim, Jaweria Kainat, Hussain AlSalman, Syed Sajid Ullah, Suheer Al-Hadhrami, Saddam Hussain

“…Recent advances in image processing and machine learning methods have greatly enhanced the ability of object classification from images and videos in different applications. …”
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Multiclass Classification of Solar Flares in Imbalanced Data Using Ensemble Learning and Sampling Methods by Haodi Jiang, Ryoma Matsuura, Jason T. L. Wang

“…We propose a new method that uses a combination of random undersampling and the synthetic minority oversampling technique (SMOTE) to combat the imbalanced data problem. …”
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Prediction of Anoxic Tonic Seizures due to Asthma in Children Using Machine Learning Methods by Kiomars Motarjem, Meisam Moghimbeygi

Subjects: “…the objective of this study is to investigate the factors influencing asthma attacks in children under six years old using machine learning (ml) methods. there are many statistical methods for data classification that can be used to classify medical…”
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Identifying Catastrophic Outlier Photometric Redshift Estimates in the COSMOS Field with Machine Learning Methods by Mitchell T. Dennis, Esther M. Hu, Lennox L. Cowie

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A tutorial review of policy iteration methods in reinforcement learning for nonlinear optimal control by Yujia Wang, Xinji Zhu, Zhe Wu

“…This tutorial review provides a comprehensive exploration of RL techniques, with a particular focus on policy iteration methods for the development of optimal controllers. …”
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Towards automatic US-MR fetal brain image registration with learning-based methods by Qi Zeng, Weide Liu, Bo Li, Ryne Didier, P. Ellen Grant, Davood Karimi

“…The results show that our method outperforms conventional optimization-based methods and recent learning-based techniques for rigid image registration. …”
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Comparative Evaluation of Traditional Methods and Deep Learning for Brain Glioma Imaging. Review Paper by Kiranmayee Janardhan, Vinay Martin D’Sa Prabhu, T. Christy Bobby

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How can arts-based methods support narrative inquiry into adult learning in the arts? by Samantha Jane Broadhead, Sharon Hooper

“…The aims of the project are twofold: firstly, to evaluate the combination of narrative inquiry and digital film-making hosted on YouTube as a method of investigating adult learning and secondly, through an analysis of the Learning Returns content, to discover what themes the participants considered important to communicate to an imagined, virtual audience. …”
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From Backtracking To Deep Learning: A Survey On Methods For Solving Constraint Satisfaction Problems by Fatima AIT HATRIT, Kamal AMROUN

“…To address this, extensive research has been conducted, leading to the development of effective techniques and algorithms for different types of CSPs, ranging from exhaustive search methods, which explore the entire search space, to modern techniques that use deep learning to learn how to solve CSPs. …”
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A Comparative Study of Various Transfer Learning Models on Skin Cancer Confirmation Methods by Mehmet Ali Altuncu, Kaplan Kaplan, Melih Kuncan

“…The dataset includes four different confirmation methods: confocal, consensus, follow-up, and histopathology. …”
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UAV-Multispectral Based Maize Lodging Stress Assessment with Machine and Deep Learning Methods by Minghu Zhao, Dashuai Wang, Qing Yan, Zhuolin Li, Xiaoguang Liu

“…However, existing studies primarily use machine learning (ML) methods to qualitatively analyze maize lodging (lodging and non-lodging) or estimate the maize lodging percentage, while there is less research using deep learning (DL) to quantitatively estimate maize lodging parameters (type, severity, and direction). …”
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