University students’ emotions about learning subjects through English as a medium of instruction by M. Carmen Galván Malagón, M. Isabel Morera-Bañas

“…Learning academic subjects in English can evoke a range of emotions among university students. …”
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Predicting the Adsorption Efficiency Using Machine Learning Framework on a Carbon-Activated Nanomaterial by Kalapala Prasad, V. Ravi Kumar, R. Suresh Kumar, A. S. Rajesh, Anjani Kumar Rai, Essam A. Al-Ammar, Saikh Mohammad Wabaidur, Amjad Iqbal, Dawit Kefyalew

“…Utilizing various algorithms, many studies assessed the single and binary adsorption of paracetamol on activated carbon. The present study implements that the effectiveness of PCM adsorption on a carbon-activated nanomaterial was predicted using an artificial neural network, a machine learning technology. …”
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Establishing predictive machine learning models for drug responses in patient derived cell culture by Abbi Abdel-Rehim, Oghenejokpeme Orhobor, Gareth Griffiths, Larisa Soldatova, Ross D. King

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A Comprehensive Investigation on Allegations of Irregularities in the Employment of the Learned Profession in the Age of Suleyman the Magnificent by Mehmet İpşirli

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Advancements in Parkinson’s Disease Diagnosis: A Comprehensive Survey on Biomarker Integration and Machine Learning by Ruchira Pratihar, Ravi Sankar

“…This review provides a detailed review of ongoing biomarker research, technological advancements for objective assessment, and enhanced healthcare infrastructure. It presents a comprehensive evaluation of the use of diverse biomarkers for diagnosing Parkinson’s disease (PD) across various datasets, utilizing machine learning models. …”
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Learned helplessness as a factor of impoverishment of the Don Cossacks at the turn of the XIX-XX centuries by A. Y. Peretyatko, K. T. Abdullaeva

“…Attempts to apply the developments of modern psychology to study the history of the Cossacks have not been made up to the present time. Meanwhile, back in 1890 a major researcher of the Don Cossacks N.A. …”
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Region-Wise Recognition and Classification of Arabic Dialects and Vocabulary: A Deep Learning Approach by Fawaz S. Al–Anzi, Bibin Shalini Sundaram Thankaleela

“…This article presents a unique approach to Arabic dialect identification using a pre-trained speech classification model. …”
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Deep learning approaches for estimating maximum wall deflection in excavations with inconsistent clay stratigraphy by Vinh V. Le, HongGiang Nguyen, Nguyen Huu Ngu

“…This paper presents a deep learning architecture combined with exploratory data analysis to estimate maximum wall deflection in deep excavations. …”
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Deep learning deciphers the related role of master regulators and G-quadruplexes in tissue specification by Artem Bashkatov, Andrey Andreasyan, Dmitry Konovalov, Alan Herbert, Maria Poptsova

“…Here, we explore the role of G-flipons in tissue specification. We present a deep learning-based framework for the genome-wide G-flipon predictions across 14 human tissue types. …”
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Structure-Based Deep Learning Framework for Modeling Human–Gut Bacterial Protein Interactions by Despoina P. Kiouri, Georgios C. Batsis, Christos T. Chasapis

“…<b>Methods:</b> This study presents a deep learning-based framework for predicting PPIs between human and gut bacterial proteins using structural data. …”
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Hyperspectral In-Situ Monitoring for Deep Learning-Based Anomaly Classification in Metal Additive Manufacturing by Charles Snyers, Julien Ertveldt, Kyriakos Efthymiadis, Jan Helsen

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Deep reinforcement learning-based routing framework for bidirectional communication in UAV-UGV networks by Prabhakar Saxena, Gayatri M. Phade

“…To overcome these challenges, this paper presents a design, implementation, and optimization of adaptive routing protocol engineered for specific requirements of coordinated network consisting of UAV and UGV. …”
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Synthetic Training Datasets for Architectural Conservation: A Deep Learning Approach for Decay Detection by Giacomo Patrucco, Francesco Setragno, Antonia Spanò

“…The primary objective is to assess the effectiveness of synthetic images for deep learning training, comparing their performance with models trained on traditional datasets. …”
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Optimizing Q-Learning for Automated Cavity Filter Tuning: Leveraging PCA and Neural Networks by Aghanim Amina, Otman Oulhaj, Oukaira Aziz, Lasri Rafik

“…This paper presents a reinforcement learning-based approach to automate the tuning of a 6thorder combline bandpass filter, operating at 941 MHz, using a Q-learning algorithm. …”
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Improving Trust via XAI and Pre-Processing for Machine Learning of Complex Biomedical Datasets by Brandon Hines, Douglas Talbert, Steven Anton

“…Previous work saw the generation of simulated TKRs with varying levels of damage, and structural health monitoring (SHM) techniques were used to collect measure-ments on the samples with the hope of identifying a method to detect the presence of damage. Machine learning was then introduced as a technique to classify the varying levels of damage present in the dataset. …”
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Validation of a machine learning model for indirect screening of suicidal ideation in the general population by Polona Rus Prelog, Teodora Matić, Peter Pregelj, Aleksander Sadikov

“…The presented model for indirect suicidality screening has proven its validity in different circumstances and timeframes, emphasizing its potential as a tool for suicide prevention and intervention in the general population.…”
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Non-digital game-based learning: a powerful tool to teach theories of architecture by Alia Sameh Okasha

“…This paper adopts a qualitative description approach to present empirical techniques of non-digital game-based learning (NDGBL) injected in a theories of architecture course for optimizing students’ deep learning. …”
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Teaching and Learning Vocabulary: What English Language Learners Perceive to Be Effective and Ineffective Strategies by Seyyed Hatam Tamimi Sa’d, Fereshte Rajabi

“…The objective of the present study was three-fold: 1) exploring Iranian English language learners’ Vocabulary Learning Strategies (VLSs), 2) examining language learners’ perceptions of vocabulary learning, and 3) exploring Iranian English language teachers’ Vocabulary Teaching Strategies (VTSs). …”
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A Machine Learning Approach for the Clustering and Classification of Geothermal Reservoirs in the Ying-Qiong Basin by Yujing Duan, Yuan Liang, Qingyun Ji, Zhong Wang

“…The Yingqiong Basin was analysed to develop a machine learning framework to predict the potential of marine geothermal reservoirs (CPPOGR). …”
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Reinforcement Learning-Driven Digital Twin for Zero-Delay Communication in Smart Greenhouse Robotics by Cristian Bua, Luca Borgianni, Davide Adami, Stefano Giordano

“…This study presents a networked cyber-physical architecture that integrates a Reinforcement Learning-based Digital Twin (DT) to enable zero-delay interaction between physical and digital components in smart agriculture. …”
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