Triple-E Principle: Leveraging Occam’s Razor for Dance Energy Expenditure Estimation by Kuan Tao, Kun Meng, Bingcan Gao, Junchao Yang, Junqiang Qiu

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Machine learning analysis of the impact of entrepreneurial mindset dimensions on entrepreneurial intentions of students in EU member countries and an EU candidate country: comparat... by Mirza Pasic, Bojan Jovanovski, Faris Ferizbegovic, Mugdim Pasic

“…Findings provide valuable insights into how these factors vary across different educational, economic, and social contexts with guidance for enhancing education to better support students’ entrepreneurial aspirations.MethodsMachine learning Random Forest was used to analyze the impact of entrepreneurial mindset dimensions, resources, and demographic and academic characteristics on students’ entrepreneurial intentions of students from EU member countries and Bosnia and Herzegovina. …”
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Multi-Trait Phenotypic Analysis and Biomass Estimation of Lettuce Cultivars Based on SFM-MVS by Tiezhu Li, Yixue Zhang, Lian Hu, Yiqiu Zhao, Zongyao Cai, Tingting Yu, Xiaodong Zhang

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Prediction and mapping of leaf water content in Populus alba var. pyramidalis using hyperspectral imagery by Zhao-Kui Li, Hong-Li Li, Xue-Wei Gong, Heng-Fang Wang, Guang-You Hao

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Ensemble learning based sustainable approach to rebuilding metal structures prediction by Tetiana Vlasenko, Taras Hutsol, Vitaliy Vlasovets, Szymon Glowacki, Tomasz Nurek, Iryna Horetska, Savelii Kukharets, Yuriy Firman, Olexandra Bilovod

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Enhancing project-based learning in engineering education: a hybrid DT-CDIO-RA framework for sustainable product design by P. Hariharasakthisudhan, K. Logesh, K. Sathickbasha, Sathish Kannan

“…This methodology provided a robust PBL model, aligning experiential learning with real-world constraints. …”
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Machine learning based radiomics approach for outcome prediction of meningioma – a systematic review [version 1; peer review: 2 approved] by Saikiran Pendem, Divya B, Girish R Menon, Saroh S, Shailesh Nayak S, Prakashini K, Priyanka -

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Winter Oilseed Rape LAI Inversion via Multi-Source UAV Fusion: A Three-Dimensional Texture and Machine Learning Approach by Zijun Tang, Junsheng Lu, Ahmed Elsayed Abdelghany, Penghai Su, Ming Jin, Siqi Li, Tao Sun, Youzhen Xiang, Zhijun Li, Fucang Zhang

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Predicting Student Performance and Enhancing Learning Outcomes: A Data-Driven Approach Using Educational Data Mining Techniques by Athanasios Angeioplastis, John Aliprantis, Markos Konstantakis, Alkiviadis Tsimpiris

“…This study investigates the use of educational data mining (EDM) techniques to predict student performance and enhance learning outcomes in higher education. …”
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Decoding vital variables in predicting different phases of suicide among young adults with childhood sexual abuse: a machine learning approach by Wenbang Niu, Yi Feng, Jiaqi Li, Shicun Xu, Zhihao Ma, Yuanyuan Wang

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3D-BCLAM: A Lightweight Neurodynamic Model for Assessing Student Learning Effectiveness by Wei Zhuang, Yunhong Zhang, Yuan Wang, Kaiyang He

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Machine learning based on pangenome-wide association studies reveals the impact of host source on the zoonotic potential of closely related bacterial pathogens by Cheng Han, Shiying Lu, Pan Hu, Jiang Chang, Deying Zou, Feng Li, Yansong Li, Qiang Lu, Honglin Ren

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Machine learning-based prediction of knee pain risk using lipid metabolism biomarkers: a prospective cohort study from CHARLS by Biao Guo, Yuan Li, Yuan Li, Weihang Peng, Yabin Liu, Fei He, Zhe Zhai

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Predicting pregnancy loss and its determinants among reproductive-aged women using supervised machine learning algorithms in Sub-Saharan Africa by Tirualem Zeleke Yehuala, Sara Beyene Mengesha, Nebebe Demis Baykemagn

“…Additionally, higher levels of education are often correlated with increased awareness of family planning methods and better access to healthcare, which can reduce the likelihood of unintended pregnancy loss.ConclusionThe Random Forest machine learning model demonstrates greater predictive power in estimating pregnancy loss risk factors. …”
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Advancing Real-Time Remote Learning: A Novel Paradigm for Cognitive Enhancement Using EEG and Eye-Tracking Analytics by Nuraini Jamil, Abdelkader Nasreddine Belkacem

“…This study explores the convergence of biometric analytics and machine learning in online education, where the level of student participation directly impacts academic achievement. …”
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Investigation of aromatic compounds and olfactory profiles in cocoa pulp fermentation using yeast-based starters: A Volatilomics and machine learning approach by Haode Chang, Chunhe Gu, Quanmiao Zhang, Wenjing Zhang, Liru Ma, Fei Liu, Zhen Feng

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PREDICTING THE LEARNING PATH TO LEARNER’S OPTIMUM COMPREHENSION by Ifeanyi Isaiah Achi, Chukwuemeka Odi Agwu, Christopher Chizoba Nnamene, Sylvester C. Aniobi, Ifebude Barnabas C., Kelechi Christian Oketa, Godson Kenechukwu Ezeh, John Otozi Ugah

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MoHiPr-TB: A Monthly Gridded Multi-Source Merged Precipitation Dataset for the Tarim Basin Based on Machine Learning by Ping Chen, Junqiang Yao, Jing Chen, Mengying Yao, Liyun Ma, Weiyi Mao, Bo Sun

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Integrating VGG Re-trained Feature Extraction with Machine Learning for Knee Osteoarthritis Severity Levels Detection Using X-ray Images by Simeon Yuda Prasetyo, Ghinaa Zain Nabiilah

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Machine learning based compact MIMO antenna array for 38 GHz millimeter wave application with robust isolation and high efficiency performance by Md. Ashraful Haque, Md. Sharif Ahammed, Soeung Socheatra, Redwan A. Ananta, Md. Jamal Hossain Nirob, Narinderjit Singh Sawaran Singh, Noorlindawaty Md. Jizat, Saeed Alsowail, Samir Salem Al-Bawri

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