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Deep learning-based user experience evaluation in distance learning
Published 2023“…More than 160,000 tweets, addressing conditions related to the major change in the education system, were gathered from Twitter social network and deep learning-based sentiment analysis models and topic models based on latent dirichlet allocation (LDA) algorithm were developed and analyzed. …”
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Design and implementation of a deep learning-empowered m-Health application
Published 2023“…Later, the web service classifies using the pre-trained model built based on a deep learning algorithm. The final phase displays the confidence rates on the mobile application. …”
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A kernelization algorithm for d-Hitting Set
Published 2010“…For 3-Hitting Set, an arbitrary instance is reduced into an equivalent one that contains at most 5k2+k elements. This kernelization is an improvement over previously known methods that guarantee cubic-order kernels. …”
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Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model
Published 2024“…The proposed approach of DDN is trained with proper data sequences used for communication and the training phase is conducted with the norms of numerous channel variants. …”
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Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment
Published 2022Subjects: -
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Deep Reinforcement Learning for Internet of Drones Networks: Issues and Research Directions
Published 2023“…Due to the highly dynamic nature of IoD networks, conventional methods are expected to encounter inadequacies that can be resolved using emerging deep reinforcement learning (DRL) techniques. In this paper, we discuss the application of DRL for addressing various issues in IoD networks. …”
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Holistic Design: Optimizing Mechatronic Systems Using Multi Objective Optimization
Published 2015Get full text
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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
Published 2022“…Network integration is common in cyber-physical systems (CPS) to allow for remote access, surveillance, and analysis. …”
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Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review
Published 2023Subjects: -
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Optimal multiobjective design of robust power system stabilizers using genetic algorithms
Published 2003“…Optimal multiobjective design of robust multimachine power system stabilizers (PSSs) using genetic algorithms is presented in this paper. …”
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The Use of Microwave Tomography in Bone Healing Monitoring
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EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach
Published 2019“…To reduce the feature dimensionality, spatial, and temporal based, bag of deep features (BoDF) model is proposed. A series of vocabularies consisting of 10 cluster centers of each class is calculated using the k-means cluster algorithm. …”
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Deep Reinforcement Learning for Resource Constrained HLS Scheduling
Published 2022“…In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. The actions and rewards for the proposed algorithm are selected carefully to guide the agent to its objective. …”
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Deep and transfer learning for building occupancy detection: A review and comparative analysis
Published 2022“…The article’s primary emphasis is on reviewing deep learning (DL), and transfer learning (TL) approaches for occupancy detection. …”
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Cyberbullying Detection in Arabic Text using Deep Learning
Published 2023“…Data-driven approaches, such as machine learning (ML), particularly deep learning (DL), have shown promising results. …”
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Power-constrained system-on-a-chip test scheduling using a genetic algorithm
Published 2006“…This paper presents an efficient approach for the test scheduling problem of core-based systems based on a genetic algorithm. The method minimizes the overall test application time of a system-on-a-chip through efficient and compact test schedules. …”
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Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
Published 2021“…On the other hand, keystroke dynamics-based systems achieve very high accuracy but have low anti-spoofing capability. …”