Analysis of Teacher Readiness in Implementing Learning Based on Local Maritime Potential by Siregar Eko Febri Syahputra, Sarkity Dios, Fernando Adam, Pratama Yudi, Intasir M. Pemberdi

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The Effectiveness of Science Learning Research Skills: A Meta-Analysis Study by Ipin Aripin, Topik Hidayat, Nuryani Rustaman, Riandi Riandi

“…The stages of the research method include: determining criteria and literature search techniques, conducting literature analysis, coding, and data analysis. Jeffreys's Amazing Statistics Program (JASP) version 0.14.1 was used as a data analysis tool. …”
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Utilising machine learning classification models for meteorological drought monitoring and analysis by Iqra Mumtaz, Rizwan Niaz, Zamama Sajid, Abdu Qaid Alameri, Zulfiqar Ali, Khaled A. Gepreel

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Multiple Machine Learning as a Powerful Tool for Star Cluster Analysis by Denilso Camargo

“…This work proposes a multiple machine learning method (MMLM) aiming to improve the accuracy and robustness of the analysis of star clusters. …”
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Leveraging deep learning for robust EEG analysis in mental health monitoring by Zixiang Liu, Juan Zhao

“…Despite the potential of these approaches, they often fall short in capturing the intricate spatiotemporal relationships within EEG data, leading to lower classification accuracy and poor adaptability across various populations and mental health scenarios.MethodsTo overcome these limitations, we introduce the EEG Mind-Transformer, an innovative deep learning architecture composed of a Dynamic Temporal Graph Attention Mechanism (DT-GAM), a Hierarchical Graph Representation and Analysis (HGRA) module, and a Spatial-Temporal Fusion Module (STFM). …”
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Sentiment analysis of pilgrims using CNN-LSTM deep learning approach by Aisha Alasmari, Norah Farooqi, Youseef Alotaibi

“…However, the opinions of the pilgrims and their feelings about their experience of Hajj are not well known, and the data on social media (SM) is limited. This paper provides a combination of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) algorithms for sentiment analysis of pilgrims using a novel and specialized dataset, namely Catering-Hajj. …”
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Accelerating Energy Forecasting with Data Dimensionality Reduction in a Residential Environment by Rafael Gonçalves, Diogo Magalhães, Rafael Teixeira, Mário Antunes, Diogo Gomes, Rui L. Aguiar

“…The non-stationary nature of energy data is a serious challenge for energy forecasting methods. …”
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Survival analysis using machine learning in transplantation: a practical introduction by Andrea Garcia-Lopez, Maritza Jiménez-Gómez, Andrea Gomez-Montero, Juan Camilo Gonzalez-Sierra, Santiago Cabas, Fernando Giron-Luque

“…Conclusions This study demonstrates the robustness and potential of the RSF model in kidney transplant analysis, achieving strong validation metrics and highlighting its advantages in managing complex, censored data, while emphasizing the need for further exploration of hybrid models and clinical integration.…”
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Affective Computing for Learning in Education: A Systematic Review and Bibliometric Analysis by Rajamanickam Yuvaraj, Rakshit Mittal, A. Amalin Prince, Jun Song Huang

“…The bibliometric analysis reveals that most publications are affiliated with the USA. …”
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Comparative Analysis of Deep Learning Models for Intrusion Detection in IoT Networks by Abdullah Waqas, Sultan Daud Khan, Zaib Ullah, Mohib Ullah, Habib Ullah

“…This study addresses the problem of detecting intrusions in IoT environments by evaluating the performance of deep learning (DL) models under different data and algorithmic conditions. …”
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Predictive analysis of heart disease using quantum-assisted machine learning by Mehroush Banday, Sherin Zafar, Parul Agarwal, M. Afshar Alam, Siddhartha Sankar Biswas, Imran Hussain, K. M. Abubeker

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Analysis and prediction of infectious diseases based on spatial visualization and machine learning by Yunyun Cheng, Yanping Bai, Jing Yang, Xiuhui Tan, Ting Xu, Rong Cheng

“…Then, autoregressive integrated moving average model (ARIMA), extreme learning machine (ELM), support vector regression (SVR), wavelet neural network (Wavelet), recurrent neural network (RNN) and long short-term memory (LSTM) were used to predict COVID-19 epidemic data in Guangdong Province, China; And the prediction performance of each model was compared through prediction accuracy indicators. …”
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Integrating Sentiment Analysis With Machine Learning for Cyberbullying Detection on Social Media by Maram Fahaad Almufareh, Noor Zaman Jhanjhi, Mamoona Humayun, Ghadah Naif Alwakid, Danish Javed, Saleh Naif Almuayqil

“…These steps ensure high-quality input data for machine learning models which significantly enhances their performance. …”
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Artificial intelligence in data storage systems by V. V. Zhilin, O. A. Safar'yan

“…The use of AI in organizing a data warehouse will speed up the system. Artificial intelligence with built-in machine-learning algorithms will provide responding to a situation that affects the state of the sys-tem. …”
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Analysis of Student Tendencies in the Learning Process: Judging from Cheating Behavior by Rachmat Sholahuddin Febry, Ardha Yani, Dini Marliyani, Yola Armita

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Kinematics Analysis of Grasping Manipulator based on ART-RBF Learning Algorithm by Kai Wang, XiaoJin Wan

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Analysis of The Impact of Gadgets on Student Motivation and Learning: Reviewed After Covid by Nur Fadlilah, Shelli Merlina, Isma Yuliza

“…The research subjects used were in 2 classes, namely VIa and VIb. the number of VIa students is 23 people and VIb 22 students, and the number of students from both classes is 45 people. The data analysis techniques used were questionnaires and interviews. …”
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Performance Analysis of Machine Learning Classifiers for Brain Tumor MR Images by Lubna Farhi, Razia Zia, Zain Anwar Ali

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A Review of Simulations and Machine Learning Approaches for Flow Separation Analysis by Xueru Hao, Xiaodong He, Zhan Zhang, Juan Li

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Machine learning empowered coherent Raman imaging and analysis for biomedical applications by Yihui Zhou, Xiaobin Tang, Delong Zhang, Hyeon Jeong Lee

“…Abstract In situ and in vivo visualization and analysis of functional, endogenous biomolecules in living systems have generated a pivotal impact in our comprehension of biology and medicine. …”
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