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SPDC-YOLO: An Efficient Small Target Detection Network Based on Improved YOLOv8 for Drone Aerial Image
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PPFL-DCS: Privacy-Preserving Federated Learning Using Neural Transformer and Leveraging Dynamic Client Selection to Accommodate Data Diversity
Published 2025-01-01“…Coping strategies for such challenges frequently involve transferring data to a central location, which raises concerns about latency, efficiency, and privacy. To address these issues, Federated Learning (FL) was developed as a solution to mitigate both the privacy concerns of organizations and the complexities of networked systems. …”
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Improving machine learning detection of Alzheimer disease using enhanced manta ray gene selection of Alzheimer gene expression datasets
Published 2025-08-01“…The early diagnosis of AD is a challenging task due to complex pathophysiology caused by the presence and accumulation of neurofibrillary tangles and amyloid plaques. …”
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An Efficient Network-Based QoE Assessment Framework for Multimedia Networks Using a Machine Learning Approach
Published 2025-01-01“…QoE, a key metric for multimedia services, reflects user satisfaction with service quality. However, measuring QoE is challenging due to its subjective nature and the complexities associated with real-time feedback.This paper presents an open-source framework for assessing QoE in multimedia networks using only key network parameters. …”
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751
Coverage, Throughput, and Energy Efficiency Enhancement in Beamspace Massive MIMO System Using Rate-Splitting and Orthogonal Precoding
Published 2024-01-01“…Following that, we offer an alternating method to solve the approximate optimization issue and select an optimal solution. Furthermore, we deduce an analytic expression for the downlink cell coverage percentage and evaluate the effectiveness of the suggested method in terms of total throughput, energy efficiency, and cell coverage percentage. …”
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752
A Multi-stage Scenario Tree Generation Method for Wind-Solar Load Based on Complex Feature Extraction and Sinkhorn Distance
Published 2024-12-01“…Finally, a simulation example showed that the proposed method had high calculation efficiency, and the generated multi-stage scenario tree for wind-solar load can reflect the uncertainty of wind-solar output and load growth.…”
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An RTM-Driven Machine Learning Approach for Estimating High-Resolution FAPAR From LANDSAT 5/7/8/9 Surface Reflectance
Published 2025-01-01“…This study developed a practical approach integrating radiative transfer (RT) modeling and machine learning to estimate 30-m FAPAR from Landsat surface reflectance. A coupled land–atmosphere RT model (RTM) and shuffled complex evolution optimization algorithm were first implemented at globally distributed VIIRS pixels for realistic simulation of land surface reflectance corresponding Landsat spectral bands and FAPAR under various conditions. …”
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Integrate computation intelligence with Bayes theorem into complex construction installation: a heuristic two-stage resource scheduling optimisation approach
Published 2023-12-01“…The cost control challenge in construction and installation projects has always been a critical concern for construction entities. The complexity of task collaboration among various equipment and nodes during the installation process leads to extended construction duration, resulting in increased construction costs. …”
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Etiopathogenetic rationale usage of treatment-and-prophylactic complex in patients suffering from chronic herpetic infection, who need dental implantation
Published 2018-02-01“…The dynamics of oral liquid biochemical parameters of people with persistent chronic herpes infection during dental implantation indicates proper efficiency of the treatment and prophylactic complex. …”
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An interpretable and adaptable data-driven model for performance prediction in thermal plants
Published 2025-04-01“…Data-driven models are a useful aid for monitoring and control of thermal power plants, but they require an effective feature selection to allow for an accurate, computationally efficient, and interpretable model. …”
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Low-cost video-based air quality estimation system using structured deep learning with selective state space modeling
Published 2025-05-01“…This study proposes Air Quality Prediction-Mamba (AQP-Mamba), a video-based deep learning model that integrates a structured Selective State Space Model (SSM) with a selective scan mechanism and a hybrid predictor (HP) to estimate air quality. …”
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