Determinants of learning outcomes with online teaching based on students' perception by Petrov Viktorija, Drašković Zoran, Ćelić Đorđe, Rus Matej

“…Background: Research on the topic of determining success of online learning is on the rise. Defining the key success factors, i.e. determinants of online learning success, is extremely important, especially at present as all higher education institutions have been forced to try their hand at teaching with the help of technology. …”
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Defect intelligent recognition of membrane product based on deep learning by Maonian Wu, Ling Li, Wei Peng, Tao Wu, Jinwei Yu, Bo Zheng, Shaojun Zhu

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INSTITUTIONAL POLICIES ON ARTIFICIAL INTELLIGENCE IN UNIVERSITY LEARNING, TEACHING AND RESEARCH by Oleksandr V. Spivakovsky, Serhii A. Omelchuk, Vitaliy V. Kobets, Nataliia V. Valko, Daria S. Malchykova

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Collaborative Uses of GenAI Tools in Project-Based Learning by Maria Perifanou, Anastasios A. Economides

“…Artificial intelligence (AI) is forcing a dramatic transformation of the methods by which we acquire knowledge and engage in collaborative learning. Although there are several studies on how AI can support collaborative learning, there are no published studies examining how students can actually collaborate among themselves while interacting with AI tools. …”
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Transfer Learning-Based Anomaly Detection System for Autonomous Vehicle by Md. Humayun Kabir, Mohammad Nadib Hasan, Ahmad, Hassan Jaki

“…Nevertheless, the issue of CAV cyber security has become a prevalent concern, representing a significant challenge in deploying CAVs. This study presents an intelligent cyber threat detection system (ICTDS) for CAV that utilizes transfer learning to detect cyberattacks on physical components of autonomous vehicles through their network infrastructure. …”
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Semisupervised Learning for Detecting Inverse Compton Emission in Galaxy Clusters by Sheng-Chieh Lin, Yuanyuan Su, Fabio Gastaldello, Nathan Jacobs

“…Traditional spectral fitting often suffers from the degeneracy between the two-temperature thermal (2T) spectrum and the one-temperature plus IC power-law (1T+IC) spectrum. We present a semisupervised deep-learning approach to search for IC emission in galaxy clusters. …”
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Enhancing Air Quality Forecasting Using Machine Learning Techniques by Zeinab Shahbazi, Zahra Shahbazi, Slawomir Nowaczyk

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Hybrid Deep Learning Approach for Automated Sleep Cycle Analysis by Sebastián Urbina Fredes, Ali Dehghan Firoozabadi, Pablo Adasme, David Zabala-Blanco, Pablo Palacios Játiva, Cesar A. Azurdia-Meza

“…This study presents a hybrid neural network architecture composed of convolutional neural network (CNN) layers, bidirectional long short-term memory (BiLSTM) layers, and attention mechanism layers in order to process large volumes of EEG data in PSG files. …”
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Topological Data Analysis and Graph-Based Learning for Multimodal Recommendation by Khalil Bachiri, Ali Yahyaouy, Maria Malek, Nicoleta Rogovschi

“…However, current multimodal methods face challenges such as modality heterogeneity, data sparsity, and feature redundancy, which can result in less effective performance when dealing with complex, high-dimensional datasets. In this study, we present a new framework that combines Topological Data Analysis (TDA) with graph-based learning to improve multimodal recommendations (TDA-MMRec). …”
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Multi-contrast machine learning improves schistosomiasis diagnostic performance. by María Díaz de León Derby, Charles B Delahunt, Ethan Spencer, Jean T Coulibaly, Kigbafori D Silué, Isaac I Bogoch, Anne-Laure Le Ny, Daniel A Fletcher

“…Conventional microscopy is a practical tool for diagnosis and screening of Schistosoma haematobium, but identification of eggs requires a skilled microscopist. Here we present a machine learning (ML)-based strategy for automated detection of S. haematobium that combines two imaging contrasts, brightfield (BF) and darkfield (DF), to improve diagnostic performance. …”
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Deep Reinforcement Learning for Optimal Replenishment in Stochastic Assembly Systems by Lativa Sid Ahmed Abdellahi, Zeinebou Zoubeir, Yahya Mohamed, Ahmedou Haouba, Sidi Hmetty

“…This study presents a reinforcement learning–based approach to optimize replenishment policies in the presence of uncertainty, with the objective of minimizing total costs, including inventory holding, shortage, and ordering costs. …”
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Harnessing Meta-Reinforcement Learning for Enhanced Tracking in Geofencing Systems by Alireza Famili, Shihua Sun, Tolga Atalay, Angelos Stavrou

“…Moreover, the meta-training approach enables the learned policy to quickly adapt to diverse new environments. …”
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Re-Evaluating Deep Learning Attacks and Defenses in Cybersecurity Systems by Meaad Ahmed, Qutaiba Alasad, Jiann-Shiun Yuan, Mohammed Alawad

“…The experiment was conducted by leveraging a deep learning model as a classifier with the three aforementioned datasets. …”
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Image Processing for Tooth Type Classification using Deep Learning by Mahmut Emin Çelik, Mehmet Zahid Genç, Ertuğrul Furkan Savaştaer, Fikret Ulus, Berrin Çelik

“…Methods: The state-of-the-art 6 deep learning classification models -Xception, GoogleNet, ResNet18, ShuffleNet, MobileNetV2, ResNext50- was implemented with transfer learning for model efficiency. …”
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Generative AI-Based Tutoring for Enhancing Learning Engagement and Achievement by Tian Belawati, Dimas Prasetyo

“… This paper presents the findings of a pilot study on the use of generative AI (GAI) in tutorial sessions within a large-scale distance education institution in Indonesia. …”
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Liquid Biopsy Based Bladder Cancer Diagnostic by Machine Learning by Ērika Bitiņa-Barlote, Dmitrijs Bļizņuks, Sanda Siliņa, Mihails Šatcs, Egils Vjaters, Vilnis Lietuvietis, Miki Nakazawa-Miklaševiča, Juris Plonis, Edvīns Miklaševičs, Zanda Daneberga, Jānis Gardovskis

“…The reliability of conventional testing methods does not reach desirable accuracy and sensitivity, and it has an invasive nature. The present study examines the application of machine learning to improve bladder cancer diagnostics by integrating miRNA expression levels, demographic routine laboratory test results, and clinical data. …”
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Assessing serial recall as a measure of artificial grammar learning by Holly E. Jenkins, Ysanne de Graaf, Faye Smith, Nick Riches, Benjamin Wilson, Benjamin Wilson

“…After exposure to “grammatical” sequences of visual symbols generated by the artificial grammar, the participants were presented with novel testing sequences. After a brief pause, participants were asked to recall the sequence by clicking on the visual symbols on the screen in order.ResultsIn both experiments, we found no evidence of artificial grammar learning in the Visual Serial Recall task. …”
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Embedded Hardware-Efficient FPGA Architecture for SVM Learning and Inference by B. B. Shabarinath, Muralidhar Pullakandam

“…By buffering kernel values, it minimizes redundant computations, leading to improved memory efficiency and faster SVM training on FPGA architectures. In addition, we present a embedded hardware-efficient FPGA architecture for the integrated SVM learning based on Parallel SMO with SVM inference. …”
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DEFENDIFY: defense amplified with transfer learning for obfuscated malware framework by Rodrigo Castillo Camargo, Juan Murcia Nieto, Nicolás Rojas, Daniel Díaz-López, Santiago Alférez, Angel Luis Perales Gómez, Pantaleone Nespoli, Félix Gómez Mármol, Umit Karabiyik

“…However, these techniques lack in detecting more advanced malware that employs obfuscation techniques. In this paper, we present DEFENDIFY, a novel framework, empowered by Computer Vision, Deep Learning, and Transfer Learning techniques, that is able to detect completely obfuscated malware with high performance in terms of accuracy and computational consumption. …”
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A Local Dwarf Galaxy Search Using Machine Learning by Huanian Zhang, Guangping Ye, Rongyu Wu, Dennis Zaritsky

“…We present a machine learning search for local, low-mass galaxies ( z  < 0.02 and 10 ^6 M _⊙  <  M _*  < 10 ^9 M _⊙ ) using combined photometric data from the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys (hereafter, Legacy Survey) and the Wide-field Infrared Survey Explorer survey. …”
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