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A Cloud Computing User Experience Focused Load Balancing Method Based on?Modified CMA-ES Algorithmegy) algorithm, called WS-ESS-CMA-ES algorithm, to allocate computing resources and solve the above problem. The process of using the proposed algorithm to solve the problem of cloud computing resource allocation in real scenarios is simulated, and compared with some other algorithms. The experiment

spinal-stenosis

Energy-Efficient Task Offloading in?UAV-Enabled MEC via?Multi-agent Reinforcement Learningding strategies and transmission power. Furthermore, a UAV-enabled MEC with Non-Orthogonal Multiple Access architecture is introduced, incorporating task computation and transmission queue models. In addition, a differential reward function that considers both system-level rewards and individual rew

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: A Privacy-Preserving Federated Recommendation Framework via?Knowledge Graph Enhancementt local interaction items and obscure gradients, we employ pseudo-labeling and . (LDP). Extensive experiments conducted on three real-world datasets demonstrate the competitive performance of our approach compared to centralized algorithms while ensuring privacy preservation. Moreover, . achieves an

liaison

Efficient and?Reliable Federated Recommendation System in?Temporal Scenariosg the learning of nonlinear relationships among diverse latent factors. This approach not only addresses the privacy concerns by preserving the confidentiality of user data but also enables the modeling of temporal dynamics to enhance the accuracy and relevance of recommendations over time.

Neuralgia

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NLP-Based Test Co-evolution Prediction for IoT Application Maintenanceodel was built by learning the correlations among these features to determine the possibility of test co-evolution. We evaluated the effectiveness of our NLP-based approach on 15 widely used Python projects in the IoT domain. The evaluation result shows that the prediction accuracy of our model achi

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畸形

Genetic-A* Algorithm-Based Routing for?Continuous-Flow Microfluidic Biochip in?Intelligent Digital Hmate solution in the solution space. Experimental results show that this method can reduce routing length and minimize routing crossings, thereby improving the parallel transmission speed of reagents on CFMB. This approach provides a feasible solution for large-scale automated routing of CFMB in the

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A Cloud-Based Sign Language Translation System via CNN with Smart Glassesenters to test the sign language translation system ten times for each person, and the final average accuracy rate was 72%. Through such an interpreting system, it brings a convenient and efficient communication experience to the hearing-impaired person and people who need to communicate with the he