Observer-Based Deep Reinforcement Learning for Robust Missile Guidance and Control by Wenwen Wang, Zhihua Chen

“…This study lays the foundation for further research on integrating intelligent control algorithms with advanced learning techniques, as it presents a novel and promising missile guidance control strategy based on integrating ESO and deep reinforcement learning.…”
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Markov-CVAELabeller: A Deep Learning Approach for the Labelling of Fault Data by Christian Velasco-Gallego, Nieves Cubo-Mateo

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Cognitive Radio Transceivers: RF, Spectrum Sensing, and Learning Algorithms Review by Lise Safatly, Mario Bkassiny, Mohammed Al-Husseini, Ali El-Hajj

“…Thus, it relies on a complete adaptive behavior composed of: reconfigurable radio frequency (RF) parts, enhanced spectrum sensing algorithms, and sophisticated machine learning techniques. In this paper, we present a review of the recent advances in CR transceivers hardware design and algorithms. …”
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Shattering Stereotypes: VR's effects on learning and skill development for people with impairments by Yusra, Ananthanagu U., Shekar R.

“…The integration of AI-driven adaptive knowledge models with VR presents an innovative result for personalized education. …”
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Performance Evaluation of Machine Learning Algorithms for Detecting Gas Leakage System by Kondireddy Muni Sankar, Dr. B. Booba

“…Thus present research work focuses on evaluating intelligent models' efficacy in identifying minor leaks in gas pipelines with fundamental operational parameters. …”
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Fault Detection in MV Switchgears Through Unsupervised Learning of Temperature Conditions by Grazia Iadarola, Alessandro Mingotti, Virginia Negri, Susanna Spinsante

“…This paper presents a distributed measurement system intended to effectively monitor the health status of switchgears under varying temperature conditions. …”
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Primary Cardiac Lymphoma: Lessons Learned from a Long Survivor by Baljit Singh, Randy Ip, Ahmed Ibrahim Al-Rajjal, Zyad Kafri, Ayad Al-Katib, Tarik Hadid

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Learning and teaching through inquiry with geospatial technologies: A systematic review by Vendula Mašterová

“…This systematic review presents recommendations and pitfalls for learning and teaching through inquiry with GST, but also recommendations for future research. …”
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Assessing the effectiveness of transfer learning strategies in BLSTM networks for speech denoising by Marvin Coto-Jiménez, Astryd González-Salazar, Michelle Gutiérrez-Muñoz

“…In this work, a comparative study on different transfer learning strategies for reducing training time and increase the effectiveness of this kind of network is presented. …”
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Uncovering business and spatial dimensions of industrial districts, clusters and learning regions by José Luis Hervás Oliver

“…Fiorenza Belussi, entitled Uncovering business and spatial dimensions of industrial districts, clusters and learning regions, presenting the topic and commenting on the different contributions published in the Special Issue.  …”
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A Systematic Review on Reinforcement Learning for Industrial Combinatorial Optimization Problems by Miguel S. E. Martins, João M. C. Sousa, Susana Vieira

“…This paper presents a systematic review on reinforcement learning approaches for combinatorial optimization problems based on real-world industrial applications. …”
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Application of Machine Learning for Radiowave Propagation Modeling Below 6 GHz by Mohammud Z. Bocus, Afzal Lodhi

“…This paper presents the application of supervised learning and use of fully connected neural network (FCNN) for the development of a path specific propagation model for frequencies below 6 GHz. …”
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Instructors’ Perceptions of the Use of Learning Analytics for Data-Driven Decision Making by Arnon Hershkovitz, G. Alex Ambrose, Tal Soffer

“…In recent years, much effort has been put into developing dedicated dashboards for instructors, in which data about students’ activity are presented. However, in many cases, such endeavors take a top-down approach and do not involve instructors in the design process. …”
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Federated learning with enhanced cryptographic security for vehicular cyber-physical systems by Himanshi Babbar, Shalli Rani, Mohammad Shabaz

“…This paper presents a novel federated learning design intended to improve data security in VCPS in order to overcome these issues. …”
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Foundational models and federated learning: survey, taxonomy, challenges and practical insights by Cosmin-Andrei Hatfaludi, Alex Serban

“…The methods were used to construct the taxonomy and enabled their comparison based on complexity, efficiency, and scalability. We present these results as a self-contained overview that not only summarizes the state of the field but also provides insights into the practical aspects of adopting, evolving, and integrating foundational models with federated learning.…”
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Performance evaluation of deep learning algorithms for channel estimation in OFDM-IM by Omer Adiguzel, Ibrahim Develi

“…This paper presents a detailed performance evaluation on the use of various deep neural networks for channel estimation in orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems. …”
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Cloud-Based Intrusion Detection Approach Using Machine Learning Techniques by Hanaa Attou, Azidine Guezzaz, Said Benkirane, Mourade Azrour, Yousef Farhaoui

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Poisonous Plant Prediction Using Explainable Deep Inherent Learning Model by Ahmed S. Maklad, Ashraf Alyanbaawi, Mohammed Farsi, Hani M. Ibrahim, Mahmoud Elmezain

“…The increasing global discovery of plant species presents both opportunities and challenges, particularly in distinguishing between beneficial and poisonous varieties. …”
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Severe Sepsis with Multiorgan Failure due to Melioidosis: A Lesson to Learn by Dinuka S Warapitiya, Shyama Subasinghe, Rukshanie Frances de Silva, Dadallage Lalitha Piyarisi, Kushlani Jayatilleke

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Deep Learning in Written Arabic Linguistic Studies: A Comprehensive Survey by Manar Almanea

“…This article presents a comprehensive survey on recent applications of deep learning (DL) algorithms to written Arabic. …”
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