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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Using Machine Learning to Identify Educational Predictors of Career and Job Satisfaction in Adults with Disabilities by Beau LeBlond, Bryan R. Christ, Benjamin Ertman, Olivia Chapman, Rea Pillai, Paul B. Perrin

“…<i>Purpose</i>: This study explored the potential long-term effects of academic-related variables, including academic satisfaction, college degree attainment, unmet academic accommodation needs, and demographic characteristics on the job and career satisfaction of adults with disabilities using modern machine learning techniques. <i>Method</i>: Participants (<i>n</i> = 409) completed an online survey assessing these constructs. …”
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STUDYING AI TECHNOLOGIES  IN EXTRACURRICULAR ACTIVITIES WITH TEENAGERS by Nataliia Valko, Nataliya Kushnir

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Machine learning analysis of factors affecting college students’ academic performance by Jingzhao Lu, Yaju Liu, Shuo Liu, Zhuo Yan, Xiaoyu Zhao, Yi Zhang, Chongran Yang, Haoxin Zhang, Wei Su, Peihong Zhao

“…By employing the chi-square test to identify features closely related to academic performance, this paper discussed the main influencing factors and utilized machine learning models (such as LOG, SVC, RFC, XGBoost) for prediction. …”
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An improved machine-learning model for lightning-ignited wildfire prediction in Texas by Qi Zhang, Cong Gao, Chunming Shi

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['UBI-XGB: IDENTIFICATION OF UBIQUITIN PROTEINS USING MACHINE LEARNING MODEL'] by Sikandar Rahu, Ali Ghulam, Ali Farman, Dhani Bux Talpur, Mir Sajjad Hussain Talpur, Erum Saba, Zulfikar Ahmed Maher, Saima Tunio

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Coronary Heart Disease Risk Prediction Model Based on Machine Learning by YUE Haitao, HE Chanchan, CHENG Yuyou, ZHANG Sencheng, WU You, MA Jing

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A Machine Learning-Based Parameterized Tropical Cyclone Precipitation Model by Yi Lu, Jie Yin, Peiyan Chen, Hui Yu, Sirong Huang

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Construction of disability risk prediction model for the elderly based on machine learning by Jing Chen, Yifei Ren, Jie Ding, Qingqing Hu, Jiajia Xu, Jun Luo, Zhaowen Wu, Ting Chu

“…Abstract The study aimed to develop a predictive model using machine learning algorithms, providing healthcare professionals with a novel tool for assessing disability risk in older adults. …”
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Predictive athlete performance modeling with machine learning and biometric data integration by Qin Jianjun, Haytham F. Isleem, Walaa J. K. Almoghayer, Mohammad Khishe

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Unveiling sustainable tourism themes with machine learning based topic modeling by Payel Das, Santanu Mandal, Prema Nedungadi, Raghu Raman

“…Using the PRISMA framework, we analyzed publications covering the years 2015–2023. A machine learning-based BERTopic model was employed to extract meaningful topics and map publications to the relevant SDGs. …”
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Advanced Hybrid Machine Learning Model for Accurate Detection of Cardiovascular Disease by Navita, Pooja Mittal, Yogesh Kumar Sharma, Umesh Kumar Lilhore, Sarita Simaiya, Kashif Saleem, Ehab Seif Ghith

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Model Klasifikasi Machine Learning untuk Prediksi Ketepatan Penempatan Karir by Hendri Mahmud Nawawi, Agung Baitul Hikmah, Ali Mustopa, Ganda Wijaya

“…That is becoming increasingly popular is the use of Machine Learning  algorithms in the decision-making process. …”
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Integrating Microgrids into Engineering Education: Modeling and Analysis for Voltage Stability in Modern Power Systems by Farheen Bano, Ali Rizwan, Suhail H. Serbaya, Faraz Hasan, Christos-Spyridon Karavas, Georgios Fotis

“…The research used a quantitative methodology to survey 100 engineering students enrolled in a microgrid modeling class to achieve the study’s objectives. The data analysis involved machine learning models such as Random Forest, Gradient Boosting, K-Means, hierarchical clustering, and regression models. …”
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Development and validation of machine learning classifiers for predicting treatment-needed retinopathy of prematurity by Nasser Shoeibi, Majid Abrishami, Seyedeh Maryam Hosseini, Mohammad-Reza Ansari-Astaneh, Razieh Farrahi, Bahareh Gharib, Fatemeh Neghabi, Mojtaba Abrishami, Mehdi Sakhaee, Mehrdad Motamed Shariati

“…Abstract Background This study aims to design and evaluate various supervised machine-learning models for identifying premature infants who require treatment based on demographic data and clinical findings from screening examinations. …”
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Comparing the Effectiveness of Machine Learning and Deep Learning Models in Student Credit Scoring: A Case Study in Vietnam by Nguyen Thi Hong Thuy, Nguyen Thi Vinh Ha, Nguyen Nam Trung, Vu Thi Thanh Binh, Nguyen Thu Hang, Vu The Binh

“…This study aims to evaluate and compare the predictive effectiveness of four supervised learning models—such as Random Forest, Gradient Boosting, Support Vector Machine, and Deep Neural Network (implemented with PyTorch version 2.6.0)—in forecasting student credit eligibility. …”
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Enhancing augmented reality with machine learning for hands-on origami training by Mikołaj Łysakowski, Jakub Gapsa, Chenxu Lyu, Thomas Bohné, Sławomir Konrad Tadeja, Piotr Skrzypczyński, Piotr Skrzypczyński

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Evaluating machine learning models comprehensively for predicting maximum power from photovoltaic systems by Samir A. Hamad, Mohamed A. Ghalib, Amr Munshi, Majid Alotaibi, Mostafa A. Ebied

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MACHINE LEARNING MODELS FOR PERFORMANCE PREDICTION OF YOUNG PLAYERS IN FOOTBALL ACADEMIES – A REVIEW by Armand Florin Bertea, Cezar Honceriu

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On the Investigation of Monthly River Flow Generation Complexity Using the Applicability of Machine Learning Models by Ma Shaofu, Anas Mahmood Al-Juboori, Asmaa Hussein Alwan, Abdel-Salam G. Abdel-Salam

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