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Classification of Learner Retention using Machine Learning Approaches by Nur Amalina Diyana Suhaimi , Norshaliza Kamaruddin, Thirumeni T Subramaniam, Nilam Nur Amir Sjarif, Maslin Masrom, Nurazean Maarop

“…The benefit of performing Machine Learning is that it enables the identification of at-risk learners at the earliest opportunity and therefore implement the earliest interventions to retain them. …”
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Linear and stratified sampling-based deep learning models for improving the river streamflow forecasting to mitigate flooding disaster by Afan H.A., Yafouz A., Birima A.H., Ahmed A.N., Kisi O., Chaplot B., El-Shafie A.

An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…The research implements stock prediction analysis as a case study for training the neural network by adopting MGWO algorithm. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit... by Dokala Janandra, Krishna Kishore

“…Hence, many countries are trying to implement renewable/sustainable energy sources to preserve the environment. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels by Mfarej, Sumaya Dhari Awad

“…In the fourth part a deep learning (DL) algorithm of channel estimation for two fad�ing channel models, Tropical and Temperate in the satellite communication system is presented. …”
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A Review Of The Student Academic Planner System by Fathi, A.M.Z., Nurdiana, A.

Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues by Aisyah, Yunus, Norfilza, Mohd Mokhtar, Raja Affendi, Raja Ali, Siti Maryamg, Ahmad Kendon, Hajar Fauzan, Ahmad

“…Here, we also proposed pipelines based on a predictive model using statistical and machine learning algorithms to accurately differentiate colorectal adenocarcinoma and polyp patients from normal individuals. …”
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State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model by Dickson Neoh Tze How, Dr.

“…In the first stage, the model is pre-trained using unlabeled data with unsupervised learning. In the second stage, the model is fine-tuned or re-trained using labeled data with supervised learning. …”