Analysis of Science Education Students' Self-Efficacy in Developing Learning Products Through the Project-Based Learning Model by Gunawan Gunawan, Lovy Herayanti, Fuad Tamami

“…This study aims to analyze the self-efficacy levels of Master's students in Science Education in developing learning products (presentations, videos, and a book chapter) implemented through the PjBL model. …”
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An In-depth Investigation of OBIA Classification with High-Resolution Imagery: Unravelling the Explanations Behind Deep Learning and Machine Learning by E. O. Yilmaz, T. Kavzoglu

“…By addressing the limitations of traditional pixel-based methods, OBIA is employed for the classification of segments based on their attributes. The present study evaluates the use of OBIA-based classification in conjunction with deep learning and machine learning classifiers. …”
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Deep Learning Scheduling on a Field-Programmable Gate Array Cluster Using Configurable Deep Learning Accelerators by Tianyang Fang, Alejandro Perez-Vicente, Hans Johnson, Jafar Saniie

“…This paper presents the development and evaluation of a distributed system employing low-latency embedded field-programmable gate arrays (FPGAs) to optimize scheduling for deep learning (DL) workloads and to configure multiple deep learning accelerator (DLA) architectures. …”
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Evaluating Machine Learning and Deep Learning models for predicting Wind Turbine power output from environmental factors. by Montaser Abdelsattar, Mohamed A Ismeil, Karim Menoufi, Ahmed AbdelMoety, Ahmed Emad-Eldeen

“…This study presents a comprehensive comparative analysis of Machine Learning (ML) and Deep Learning (DL) models for predicting Wind Turbine (WT) power output based on environmental variables such as temperature, humidity, wind speed, and wind direction. …”
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Sources of stress in online learning scale: development and validation of an instrument to evaluate students’ stressors associated with the online learning by Ioana-Roxana Topală, Daniela-Veronica Necșoi, Ana-Maria Cazan, Ana-Maria Cazan, Maria-Magdalena Stan

“…Furthermore, SSOLS’s factors would allow educators to predict students’ learning engagement due to the valid predictive association.MethodsThe present research aimed to develop and test an instrument assessing the sources of stress in the context of academic online learning and to articulate its psychometric properties. …”
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The Effect of the Realistic Mathematics Education (RME) Learning Model on the Second-Grade Elementary Students’ Mathematics Learning Outcomes by Sarimauli Simamora, Juliana, Heka Maya Sari Sembiring, Dyan Wulan Sari HS, Darinda Sofia Tanjung, Meikardo Samuel Prayuda

“… The present study discusses the effect of the realistic mathematics education learning model on the mathematics learning outcomes of grade II students of State Elementary School 173472 Sijarango, Pakkat District, Humbang Hasundutan in the academic year 2023/2024. …”
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Deep learning to evaluate seismic-induced soil liquefaction and modified transfer learning between various data sources by Hongwei Guo, Chao Zhang, Hongyuan Fang, Timon Rabczuk, Xiaoying Zhuang

“…In this work, a deep learning model is built and investigated on the soil liquefaction prediction and a modified transfer learning scheme between different data sources is presented. …”
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Comparative Analysis of Machine Learning and Deep Learning Models for Classification and Prediction of Liver Disease in Patients with Hepatitis C by Shalem Preetham Gandu, M. Roshni Thanka, E. Bijolin Edwin, Ebenezer Veemaraj, S. Stewart Kirubakaran

“…This study used the Electronic Health Records dataset from the UCI Machine Learning Repository, which included 615 individuals, of which 540 were healthy, and 75 had hepatitis C. …”
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Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods by Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El-Hafeez, Kareem Ahmed

“…This work compares and reports the classification, machine learning, and deep learning algorithms that predict cardiovascular illnesses. …”
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The Universal Learning Platform (ULP): A Hybrid IoT-Based Learning Environment for Automatic Device and Circuit Characterization by Alexandru Mihai Antonescu, Florin-Silviu Dumitru, Marius Enachescu

“…This paper presents the design, both hardware and software, and hands-on assessment of an IoT Based Learning Environment, constructed around the Universal Learning Platform (ULP), with on-site and remote learning capabilities. …”
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Prediction of Hypertension in the Pediatric Population Using Machine Learning and Transfer Learning: A Multicentric Analysis of the SAYCARE Study by Keisyanne Araujo-Moura, Letícia Souza, Tiago Almeida de Oliveira, Mateus Silva Rocha, Augusto César Ferreira De Moraes, Alexandre Chiavegatto Filho

“…ObjectiveTo develop a machine learning (ML) model utilizing transfer learning (TL) techniques to predict hypertension in children and adolescents across South America.MethodsData from two cohorts (children and adolescents) in seven South American cities were analyzed. …”
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Multiclass leukemia cell classification using hybrid deep learning and machine learning with CNN-based feature extraction by Sazzli Kasim, Sorayya Malek, JunJie Tang, Xue Ning Kiew, Song Cheen, Bryan Liew, Norashikin Saidon, Raja Ezman, Raja Shariff

“…This study presents a novel hybrid methodology that combines pre-trained CNN architectures, including VGG16, InceptionV3, and ResNet50, with advanced classification models such as Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and the deep learning-based Multi-Layer Perceptron (MLP). …”
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Examining the psychosocial model of sense of presence in the learning management system of e-learning center’s Shahid Beheshti university by soraya khazaei, abbas mohammadi, Mahboobeh Arefi, Esmail Jafari

“…Aims: The present study is aimed of providing a model of the sense of presence in the learning management system of e-learning center’s Shahid Beheshti University. …”
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UKRAINIAN HISTORICAL THOUGHT AT THE PRESENT STAGE (ABOUT A. PALIA'S BOOK «A SHORT COURSE IN THE HISTORY OF UKRAINE») by Dubrovskii A.M.

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Increasing the Accessibility of Causal Domain Knowledge via Causal Information Extraction Methods: A Case Study in the Semiconductor Manufacturing Industry by Houssam Razouk, Leonie Benischke, Daniel Gärber, Roman Kern

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LINGUISTIC AND CULTURAL STUDIES IN CLASSES OF GERMAN by Olena Beresten

“…Linguistic and cultural studies are an integral part of learning a foreign language. Language cannot be studied without learning culture, history, geography, traditions, people’s preferences in food, clothing and their behaviour. …”
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Machine learning via DARTS-Optimized MobileViT models for pancreatic Cancer diagnosis with graph-based deep learning by Yusuf Alaca

“…Abstract The diagnosis of pancreatic cancer presents a significant challenge due to the asymptomatic nature of the disease and the fact that it is frequently detected at an advanced stage. …”
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Implementing Case-Method in Maritime-Related Learning: A Qualitative Descriptive Study in Physics Learning on The Topic of Hydrostatics Pressure by Sarkity Dios, Liana Metta, Fitriani Rita, Sundari Putri Dwi

“…Data were analyzed descriptively and presented based on the stages of case- method learning. …”
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Implementing Student Teams Achievement Divisions (STAD) learning model in grade 9 Biology and its impact on learning achievement by Sherab Chophel, Pema Tshewang, Phuntsho Wangdi, Ugyen Wangdi, Sherab Jamtsho

“…The group was tasked with STAD learning activities such as drawing and writing activities, quizzes, presentations, group discussions, tests, questions, and answers. …”
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Towards Deep Learning in Online Courses: A Case Study in Cross-Pollinating Universal Design for Learning and Dialogic Teaching by Qiongli Zhu, Sarfaroz Niyozov

“… This article presents a case study of an online course that cross-pollinated Universal Design for Learning (UDL) and dialogic teaching to facilitate deep learning. …”
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