Civic and social science learning in the Czech Republic: Current state, challenges and prospects by Denisa Labischová, Tomáš Hubálek

“…Approach: The research design is based on the use of descriptive method and on the analysis of documents – laws, ministerial decrees, curriculum, educational programmes, a list of textbooks endorsed by the Ministry of Education, Youth and Sports, educational portals and specialist journals. …”
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DEVELOPMENT OF ARTIFICIAL INTELLIGENCE IN THE SPHERE OF EDUCATION: EDUCOLOGICAL ASPECTS by Olga Melnychenko

“…The author emphasizes that this methodology integrates knowledge about education and the educational sphere as a whole, and is an interdisciplinary direction of scientific development based on numerous methods borrowed from natural sciences, cybernetics, mathematical sciences, etc. …”

An explainable Machine Learning model for Large-Scale Travelling Ionospheric Disturbances forecasting by Ventriglia Vincenzo, Guerra Marco, Cesaroni Claudio, Spogli Luca, Altadill David, Segarra Antoni, Galkin Ivan, Barta Veronika, Verhulst Tobias G.W., de Paula Víctor, Navas-Portella Víctor, Berényi Kitti A., Belehaki Anna

“…The model is based on CatBoost, a gradient boosting framework. …”
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A Synergy Between Machine Learning and Formal Concept Analysis for Crowd Detection by Anas M. Al-Oraiqat, Oleksandr Drieiev, Sattam Almatarneh, Mohammadnoor Injadat, Karim A. Al-Oraiqat, Hanna Drieieva, Yassin M. Y. Hasan

“…Aiming to solve these issues, we take advantage of the prediction capabilities of machine learning models and the analysis and clustering strengths of Formal Concept Analysis (FCA) chosen for its strong mathematical foundation and superior clustering capabilities compared to traditional methods, as highlighted in recent works such as K-means or hierarchical clustering. …”
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Artificial intelligence in suicide prevention: Utilizing deep learning approach for early detection by Vikas Gaur, Gaurav Maggu, Khushboo Bairwa, Suprakash Chaudhury, Sana Dhamija, Tahoora Ali

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Data-driven design of electrolyte additives supporting high-performance 5 V LiNi0.5Mn1.5O4 positive electrodes by Bingning Wang, Hieu A. Doan, Seoung-Bum Son, Daniel P. Abraham, Stephen E. Trask, Andrew Jansen, Kang Xu, Chen Liao

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Advanced predictive machine and deep learning models for round-ended CFST column by Feng Shen, Ishan Jha, Haytham F. Isleem, Walaa J.K. Almoghayer, Mohammad Khishe, Mohamed Kamel Elshaarawy

“…Using an extensive dataset of 200 CFST stub column tests, this research evaluates three machine learning (ML) models – LightGBM, XGBoost, and CatBoost – and three deep learning (DL) models – Deep Neural Network (DNN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM). …”
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Optimal control of manipulator with joint clearance compensation via generalized policy learning by Wenting Liu, Qingliang Zeng, Zhiwen Wang, Jun Zhao, Lin Kong

“…Simulation results demonstrate the effectiveness of the proposed learning algorithm and control method for manipulator clearance compensation. …”
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Design, Implementation, and Evaluation of the Flipped Classroom Teaching Method in Cartilage Histology Course by Azra allahveisi, Mohamad Jafar rezaie, Mahsa Mahmoudi, nasrin abdi

“…Background and Objective: With technological advancements and the rapid growth of innovative educational approaches, methods such as the flipped classroom and problem-based learning have replaced traditional methods like lectures. …”
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Hierarchical Reinforcement Learning for Quadrupedal Robots: Efficient Object Manipulation in Constrained Environments by David Azimi, Reza Hoseinnezhad

“…A novel reward function is central to the method, incorporating sensor-based obstacle observations to optimize the decision-making. …”
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Machine learning in lymphocyte and immune biomarker analysis for childhood thyroid diseases in China by Ruizhe Yang, Wei Li, Qing Niu, WenTao Yang, Wei Gu, Xu Wang

“…It also intends to develop and evaluate a machine learning model to predict if patients have thyroid disorders based on their clinical characteristics, ultimately providing insights to enhance the clinical guidelines for the pathogenesis of childhood thyroid disorders. …”
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Evaluating performance and generalizability of Learning from Demonstration for the harvesting of apples & pears by Robert van de Ven, Ard T. Nieuwenhuizen, Eldert J. van Henten, Gert Kootstra

“…Automating agricultural tasks is challenging because of the large amount of variation in the environment and variation in tasks. Learning from Demonstration (LfD) is a promising method that allows robots to adjust to new environments and tasks easily through an easy training procedure performed by the end-user. …”
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Federated Collaborative Learning with Sparse Gradients for Heterogeneous Data on Resource-Constrained Devices by Mengmeng Li, Xin He, Jinhua Chen

“…Finally, the sparse gradient quantization method is combined with an adaptive weighting strategy, and a collaborative federated learning algorithm is designed for heterogeneous data distribution. …”
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A Deep Learning Approach to Assist in Pottery Reconstruction from Its Sherds by Matheus Ferreira Coelho Pinho, Guilherme Lucio Abelha Mota, Gilson Alexandre Ostwald Pedro da Costa

“…In this work, we investigate a deep learning-based approach to make that process more efficient, accurate, and fast. …”
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A Q-Learning Crested Porcupine Optimizer for Adaptive UAV Path Planning by Jiandong Liu, Yuejun He, Bing Shen, Jing Wang, Penggang Wang, Guoqing Zhang, Xiang Zhuang, Ran Chen, Wei Luo

“…A B-spline-based trajectory smoothing method is also incorporated to improve the feasibility and smoothness of the planned paths. …”
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The analysis of motion recognition model for badminton player movements using machine learning by Xuanmin Zhu, Lizhi Liu, Jingshuo Huang, Genyan Chen, Xi Ling, Yanshuo Chen

“…Abstract This study aims to comprehensively analyze and classify the badminton players’ swing actions by combining the theoretical frameworks of quantum mechanics and machine learning. A badminton stroke recognition method based on Quantum Convolutional Neural Network (QCNN) is proposed. …”
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A novel approach integrating multispectral imaging and machine learning to identify seed maturity and vigor in smooth bromegrass by Chengming Ou, Zhicheng Jia, Shiqiang Zhao, Shoujiang Sun, Ming Sun, Jingyu Liu, Manli Li, Shangang Jia, Peisheng Mao

“…A stacking ensemble learning approach was employed to identify the seed maturity based on multispectral imaging and autofluorescence imaging. …”
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Risky business: medical students’ feedback-seeking behaviours: a mixed methods study by Muirne Spooner, Ciarán Reinhardt, Fiona Boland, Samuel McConkey, Teresa Pawlikowska

“…Three hundred and twenty-five of a total of 514 completed questionnaires and 57 interviews were analysed. Learning goal orientation (LGO), instrumental leadership and supportive leadership related positively to perceived feedback benefits (0.23, 0.2, and 0.31, respectively, p < 0.05). …”
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Factors influencing utilization of school health nurse program among secondary students of Lalitpur, Nepal: a mixed-method study by Saraswati Sharma, Anita Mahotra, Tulsi Ram Thapa, Pushpa Thapa, Shital Bhandary, Suraj Bhushal, Sudarshan Paudel

“…Finally, the study did the triangulation to cross-validate the findings from both quantitative and qualitative studies. Methods A concurrent triangulation mixed-method study was conducted in six public schools randomly selected from each of six local levels of Lalitpur district implementing the ‘’One school one nurse’’ program. …”
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USING 5E INSTRUCTIONAL MODEL WITH ICT SUPPORT IN TEACHING LOWER SECONDARY STUDENTS ON THE TOPIC OF LIGHT REFLECTION by Frank Angelo Pacala

“…The study used a mixed-method design involving 24 students participating in a 5E-based intervention. …”
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