Educationnal Sciences Using The E-learning Methods by A. Khireddine, K. Benmahammed

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Accelerating Syntax Learning with Powtoon-Assisted Mnemonics by Muhammad Kafahulloh, Mohamad Zaka Al Farisi, Ali Abd al-Rubb Radman Taha

“…The learning steps in this research include planning material, creating Powtoon content, making presentations and delivery, providing interactive exercises, repetition and memorization, evaluating learning, reflecting, and closing. …”
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Organisational Learning in Startup Development and International Growth by Jurgita Sekliuckiene, Rimgaile Vaitkiene, Vestina Vainauskiene

“… Objective: This article explores the conceptual link between the development stages of a startup and organisational learning with the aim to conceptualise the practices of organisational learning levels emerging in specific life cycle stages of a global startup. …”
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Augmentation of Semantic Processes for Deep Learning Applications by Maximilian Hoffmann, Lukas Malburg, Ralph Bergmann

“…The popularity of Deep Learning (DL) methods used in business process management research and practice is constantly increasing. …”
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Discriminative graph regularized representation learning for recognition. by Jinshan Qi, Rui Xu

“…To uncover compact low-dimensional feature representations with strong generalization and discrimination capabilities for recognition tasks, in this paper, we present a novel discriminative graph regularized representation learning (DGRL) model that is able to elegantly incorporate both global and local geometric structures as well as the label structure of data into a joint framework. …”
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Deep Learning Applications in Medical Image Processing by Ayşe Gül Eker, Nevcihan Duru

“…Thanks to the developing mathematical models and hardware devices, deep learning has taken a wide place in this field. In this study, the application of deep learning methods in the field of medical image processing has been examined. …”
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Targeted molecular generation with latent reinforcement learning by Ragy Haddad, Eleni E. Litsa, Zhen Liu, Xin Yu, Daniel Burkhardt, Govinda Bhisetti

“…Abstract Computational methods for generating molecules with specific physiochemical properties or biological activity can greatly assist drug discovery efforts. Deep learning generative models constitute a significant step towards that direction. …”
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Models of Blended Learning: Organizational and Didactic Typology by V. I. Blinov, E. Yu. Esenina, I. S. Sergeev

“…The article shows the connection of the proposed  typology of organizational and didactic models of blended learning with other typologies and individual models presented in foreign and domestic  publications.…”
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Deep Learning System for E-Waste Management by Godfrey Perfectson Oise, Susan Konyeha

“…The deep learning system for e-waste management presented in this proposal is a transformative solution designed to address the escalating challenges of garbage collection and management in urban environments. …”
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Trimodal machine learning based biometrics system by Maciej Szymkowski, Khalid Saeed

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Quantum Kernel Machine Learning With Continuous Variables by Laura J. Henderson, Rishi Goel, Sally Shrapnel

“…The popular qubit framework has dominated recent work on quantum kernel machine learning, with results characterising expressivity, learnability and generalisation. …”
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Primer on machine learning applications in brain immunology by Niklas Binder, Ashkan Khavaran, Roman Sankowski

“…We explore how machine learning, particularly deep learning methods like autoencoders and graph neural networks, is addressing these challenges by enhancing dimensionality reduction, data integration, and feature extraction. …”
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Distributionally Robust Policy and Lyapunov-Certificate Learning by Kehan Long, Jorge Cortes, Nikolay Atanasov

“…This article presents novel methods for synthesizing distributionally robust stabilizing neural controllers and certificates for control systems under model uncertainty. …”
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The problem with two-event sequence learning by pigeons by Thomas R. Zentall, Daniel N. Peng

“…Abstract Bonobos appear to show little evidence of learning to make one response (R1) to an AB sequence and a different response (R2) to sequences BB, AA, and BA (Lind et al. …”
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Structure-preserving learning for multi-symplectic PDEs by Süleyman Yıldız, Pawan Goyal, Peter Benner

“…Abstract This paper presents an energy-preserving machine learning method for inferring reduced-order models (ROMs) by exploiting the multi-symplectic form of partial differential equations (PDEs). …”
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Coordinate Representations for Interference Reduction in Motor Learning. by Sang-Hoon Yeo, Daniel M Wolpert, David W Franklin

“…When opposing force fields are presented alternately or randomly across trials for identical reaching movements, subjects learn neither force field, a behavior termed 'interference'. …”
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Prediction of Corona-Virus Using Deep Learning by Laith Al-Ali

“…The data set is divided into 75% of the training data and 25% of the test data after applying deep learning algorithms. Python libraries such as pandas, NumPy, and matplotlib are also used in addition to sklearn and Keras. …”
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Learning Electromagnetic Metamaterial Physics With ChatGPT by Darui Lu, Yang Deng, Jordan M. Malof, Willie J. Padilla

“…Results are compared to conventional machine learning approaches including feed-forward neural networks, random forest, linear regression, and K-nearest neighbor (KNN). …”
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Machine learning opportunities to predict obstetric haemorrhages by Yu. S. Boldina, A. A. Ivshin

“…One of the particular AI variants is presented by machine learning (ML), which develops accurate predictive models using computer analysis. …”
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Improving students’ arguments through collaborative learning by Dona Kumala Shinta, F. Filia

“…Attempts to improve students’ written arguments through collaborative learning have been conducted in numerous studies. However, there are few studies on improving students’ spoken arguments through collaborative learning, especially in Bahasa Indonesia.  …”
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