Intelligent Teaching Recommendation Model for Practical Discussion Course of Higher Education Based on Naive Bayes Machine Learning and Improved <i>k</i>-NN Data Mining Algorithm by Xiao Zhou, Ling Guo, Rui Li, Ling Liu, Juan Pan

“…Aiming at the existing problems in practical teaching in higher education, we construct an intelligent teaching recommendation model for a higher education practical discussion course based on naive Bayes machine learning and an improved <i>k</i>-NN data mining algorithm. …”
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Developing a hybrid feature selection method to detect botnet attacks in IoT devices by Alshaeaa H.Y., Ghadhban Z.M., Ministry of Education, Iraq

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Interpretable Ensemble Learning Approach for Predicting Student Adaptability in Online Education Environments by Shakib Sadat Shanto, Akinul Islam Jony

“…Various machine learning (ML) and deep learning (DL) models, including decision tree (DT), random forest (RF), support vector machine (SVM), K-nearest neighbors (KNN), XGBoost, and artificial neural networks (ANNs), are applied for adaptability prediction. …”
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Machine Learning Models for Carbonation Depth Prediction in Reinforced Concrete Structures: A Comparative Study by Rafael Aredes Couto, Igor Augusto Guimarães Campos, Elvys Dias Reis, Daniel Hasan Dalip, Flávia Spitale Jacques Poggiali, Péter Ludvig

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Measuring Raven’s Progressive Matrices Combining Eye-Tracking Technology and Machine Learning (ML) Models by Shumeng Ma, Ning Jia

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Development of Anthro-Fitness Model for Evaluating Firefighter Recruits’ Performance Readiness Using Machine Learning by Mohamed Borhanudin Mohd Yusof, Musa Rabiu Muazu, Nazarudin Mohamad Nizam, Abdul Majeed Anwar P. P., Raj Naresh Bhaskar, Razmaan Mohd Azraai Mohd

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Development of an explainable machine learning model for Alzheimer’s disease prediction using clinical and behavioural features by Rajkumar Govindarajan, K. Thirunadanasikamani, Komal Kumar Napa, S. Sathya, J. Senthil Murugan, K. G. Chandi Priya

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CMIP6 multi-model ensemble projection of reference evapotranspiration using machine learning algorithms by Milad Nouri, Shadman Veysi

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A Machine-Learning Model for the Prediction of Triple-Negative Breast Cancer Based on Multiparameter MRI by Cai Y, Li Y, Wang W, Zhou Y, Wang J, Zhang L, Lu H

“…In the primary cohort, univariate analysis, logistic regression analysis and Boruta algorithm were used to determine the independent predictors for TNBC and non-TNBC. The machine learning classifier XGboost was developed based on the features to predict TNBC. …”
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A Hybrid Machine Learning and Optimization Model to Minimize the Total Cost of BRT Brake Components by Saeed Najafi-Zangeneh, Naser Shams Gharneh, Ali Arjomandi-Nezhad, Erfan Hassannayebi

“…This study aims to implement a hybrid machine learning and optimization model to minimize the total investment and reliability-related costs in a bus rapid transit (BRT) system. …”
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Developing a Fatigue Detection Model for Hospital Nurses Using HRV Measures and Machine Learning by Wynona Salsabila Hafiz, Maya Arlini Puspasari, Dewi Yunia Fitriani, Richard Joseph Hanowski, Danu Hadi Syaifullah, Salsabila Annisa Arista

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Roman urdu hate speech detection using hybrid machine learning models and hyperparameter optimization by Waqar Ashiq, Samra Kanwal, Adnan Rafique, Muhammad Waqas, Tahir Khurshaid, Elizabeth Caro Montero, Alicia Bustamante Alonso, Imran Ashraf

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Explainable machine learning models for identifying mild cognitive impairment in older patients with chronic pain by Xiaoang Zhang, Yuping Liao, Daying Zhang, Weichen Liu, Zhijian Wang, Yaxin Jin, Shushu Chen, Jianmei Wei

“…SVM-RFE and LASSO regression were used for variable selection. We then developed machine learning models and interpreted them by SHAP. …”
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Construction of a prediction model for moderate to severe perimenopausal syndrome based on machine learning algorithms by ZHANG Min, GU Tingting, GUAN Wei, LIU Xiangxiang, SHI Junyao

“…Objective To identify risk factors for perimenopausal syndrome (PMS) among perimenopausal women using machine learning algorithms, and to construct a predictive model for the risk of developing moderate to severe PMS in perimenopausal women. …”
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Assessing safety in horizontal curves using surrogate safety measures and machine learning by Navid Nadimi, Hojjat Fathipour, Abbas Sheykhfard

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Power management in isolated microgrids using machine learning-based robust model predictive control by Chou-Yi Hsu, Amit Ved, Hannah Jessie Rani R, Zayd Ajsan Balsem, Nora Rashid Najem, Abhayveer Singh, P․Sasi Kiran, Ankita Aggarwal, Satish Kumar Samal, Alireza Kamranfar

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Investigating the impact of meteorological parameters on daily soil temperature changes using machine learning models by Farrokh Asadzadeh, Somayeh Emami, Ahmed Elbeltagi, Muhammed Ernur Akiner, Vahid Rezaverdinejad, Farshid Taran, Ali Salem

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How accurately can supervised machine learning model predict a targeted psychiatric disorder? by Haitham Jahrami, Amir H. Pakpour, Waqar Husain, Achraf Ammar, Zahra Saif, Ali Husain Alsalman, Adel Aloffi, Khaled Trabelsi, Seithikurippu R. Pandi-Perumal, Michael V. Vitiello

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Oxidative balance score and menopausal status: insights from epidemiological analysis and machine learning models by Chunlin Dong, Chunlin Dong, Ding Ma, Ding Ma, Ding Ma, Jinjin Yu, Ke Gu, Yaying Lin, Jing Song, Yuan Wang, Yanjun Zhou

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Research on learning achievement classification based on machine learning. by Jianwei Dong, Ruishuang Sun, Zhipeng Yan, Meilun Shi, Xinyu Bi

“…In order to improve the accuracy and robustness of student performance classification, we adopted Gaussian Distribution based Data Augmentation technique (GDO), combined with multiple Deep Learning (DL) and Machine Learning (ML) models. We explored the application of different Machine Learning and Deep Learning models in classifying student grades. …”
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