Titlebook: Digital Technologies and Applications; Proceedings of ICDTA Saad Motahhir,Badre Bossoufi Conference proceedings 2024 The Editor(s) (if appl

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Optimization of Acoustic Wave Transmission in a One-Dimensional System Using the Parallelepiped-Shap, such as industrial noise control, which offers the possibility of developing more effective attenuation methods. For communication devices, the study helps improve sound quality, facilitating clearer voice communication.

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R. L. Beard,R. A. S. Chandraratna strength in technology progress and financial area. The United Kingdom and China are closely following. To highlight authorship influence, we underscore the fact that a majority of authors contributed with only a single work. Co-citation research gives extra light on author cooperation practices. T

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cators in streamlining the process of searching for resources so they can focus on enhancing the learning journey. The study investigates the context and challenges of OER use, gives an overview of Language Models (LLMs), and describes the MOERID implementation, with a focus on integrating NLP and m

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Non-Isothermal Flows of Viscoelastic Fluids and testing time. In all dataset subsets we worked on in addition to the NSL-KDD dataset, eXtreme Gradient Boosting significantly beat the other algorithms. From all the experimental results, it is concluded that XGBoost is a plausible choice for an intrusion detection system in terms of all the me

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Extrusion Flow between Parallel Plates, such as industrial noise control, which offers the possibility of developing more effective attenuation methods. For communication devices, the study helps improve sound quality, facilitating clearer voice communication.

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Flow Birefringence in Polymer Rheometry’s distinct attributes, functionalities, domains of application, and constraints will enable researchers and professionals to make well-informed decisions when selecting the most suitable tool for their requirements.

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Unfaire Taktiken erkennen und abwehren normal LSTMs or convolutional long short-term memory networks. By contrast, empirically Deep Q-Network (DQN) was more compatible than conventional Q-Learning when applied towards evolving pricing strategies over time leading up greater rewards and consistency amidst market volatilities. Market tren