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981
DP-YOLO: A Lightweight Real-Time Detection Algorithm for Rail Fastener Defects
Published 2025-03-01“…To enable accurate and efficient real-time detection of rail fastener defects under resource-constrained environments, we propose DP-YOLO, an advanced lightweight algorithm based on YOLOv5s with four key optimizations. …”
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982
Improving classifier decision boundaries and interpretability using nearest neighbors
Published 2025-07-01“…Unlike prior methods, our approach achieves improvements without introducing trade-offs or necessitating architectural adaptations, while providing actionable insights and theoretical analysis to support its efficacy.…”
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983
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984
Mobile-YOLO: A Lightweight Object Detection Algorithm for Four Categories of Aquatic Organisms
Published 2025-07-01Get full text
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985
An Active RIS-Aided DFRC System for Improved Multi-User Communications
Published 2025-01-01“…We develop a optimization algorithm that leverages weighted minimum mean square error (WMMSE) and fractional programming techniques to maximize the weighted sum rate (WSR) for communication users while ensuring robust radar detection performance. …”
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986
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987
Dynamic Node Management for Energy Optimization in Cognitive Radio Systems
Published 2024-01-01“…The optimal number of cooperative nodes is determined through a greedy algorithm, formulated as a constrained optimization problem. …”
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988
Design of performance evaluation method for higher education reform based on adaptive fuzzy algorithm
Published 2025-08-01Get full text
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989
Machine Learning Techniques for Heart Disease Prediction Using a Multi-Algorithm Approach
Published 2024-11-01“…This analysis explores the efficiency of machine learning systems for heart disease identification through a multi-algorithm approach. The main objective is to identify the best performing algorithm for accurate disease prediction, improving clinical decision making. …”
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990
DLE-YOLO: An efficient object detection algorithm with dual-branch lightweight excitation network
Published 2025-03-01“…Thirdly, the localization loss utilizes SIoU loss to further optimize the accuracy of the bounding box. Our method achieves a mAP value of 46.0% on the MS-COCO dataset, which is a 2% mAP improvement compared to the baseline YOLOv5-m, while bringing a 19.3% reduction in parameter count and a 12.9% decrease in GFLOPs. …”
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991
Evaluation of Traditional and Data-Driven Algorithms for Energy Disaggregation Under Sampling and Filtering Conditions
Published 2025-06-01“…Non-intrusive load monitoring (NILM) enables the disaggregation of appliance-level energy consumption from aggregate electrical signals, offering a scalable solution for improving efficiency. This study compared the performance of traditional NILM algorithms (Mean, CO, Hart85, FHMM) and deep neural network-based approaches (DAE, RNN, Seq2Point, Seq2Seq, WindowGRU) under various experimental conditions. …”
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992
USD-YOLO: An Enhanced YOLO Algorithm for Small Object Detection in Unmanned Systems Perception
Published 2025-03-01“…Second, we introduced the Spatial and Channel Reconstruction Convolution module to reduce redundancy in spatial and channel features while extracting key features of small objects. Additionally, we designed a novel C2f-Global Attention Mechanism module to expand the receptive field and capture more contextual information, optimizing the detection head’s ability to handle small and low-resolution objects. …”
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993
Mode selection and resource optimization for UAV-assisted cellular networks
Published 2024-03-01“…The resource allocation and optimization scheme was studied in a coexistence scenario of unmanned aerial vehicle (UAV) and cellular communication network.To improve spectrum efficiency of the system, UAV users could reuse the cellular spectrum resources to access the network through full duplex or half duplex device-to-device technique.Additionally, a joint access control, mode selection, power control and resource allocation optimization problem was formulated to maximize the overall throughput of the network while ensuring quality of service requirements for both UAV users and ground cellular users.Specifically, the phase 1 method in the convex optimization was adopted for access control and feasibility check, and then the convex and concave procedure (CCCP) iterative algorithm was used to solve the power control problem for feasible UAV user pairs.By using this local optimum value, the original optimization problem can be simplified into a weighted maximization problem.Finally, the Kuhn-Munkres (KM) algorithm was used to match the optimal channel resources and obtain the global optimal throughput value of the system.Numerical results show that the proposed scheme can significantly improve the performance of system.…”
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994
Multiobjective Optimization for Topology and Coverage Control in Wireless Sensor Networks
Published 2015-02-01“…Simulation results demonstrate that the proposed algorithm can improve the network lifetime and coverage while maintaining the network connectivity.…”
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995
Thermomechanical Coupling Analysis and Optimization of Metallic Thermal Protection System
Published 2019-01-01“…The metallic thermal protection system (MPTS) is a key technology for reducing the cost of reusable launch vehicles, offering the combination of increased durability and competitive weights when compared with other systems. A two-stage optimization strategy is proposed in this paper to improve thermal and mechanical performance of MTPS while minimizing its weight. …”
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996
Network slicing resource allocation strategy based on joint optimization
Published 2023-05-01“…To improve network resource utilization that was decreased by different applications with different requirements in 5G networks, a network slicing resource allocation strategy based on joint optimization was proposed, which was utilized to maximize both network resource utilization and network revenue by comprehensively considering in tra-slice and inter-slice resource schedule.Firstly, the user’s average satisfaction function was defined in the inter-slicing resource allocation problem.Furthermore, in terms of the number of users, slicing schedule delay and priority, a proportional fair resource allocation algorithm based on quality of service (QoS) was proposed, which was employed to achieve the best tradeoff between fairness and the users’ requirements among slices.Secondly, after two functions (service degradation and resource migration) were introduced in the inter-slice resource schedule problem, two price models were established for internal access users and external access users respectively, where congestion and non-congestion conditions were analyzed.According to the proposed price models, a Stackelberg game between the base station and users was constructed, and a global search algorithm with low complexity was leveraged to obtain the best response of the game, where the best tradeoff between the base station revenue and user utility was obtained.Simulation results show that the proposed strategy can effectively improve resource utilization and network revenue while reducing network congestion.Therefore, it can better realize fairness in resource allocation.…”
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997
Priority-Aware Spectrum Management for QoS Optimization in Vehicular IoT
Published 2025-05-01“…This dynamic spectrum access scheme integrates interweave, underlay, and coexistence modes to optimize spectrum utilization, energy efficiency, and throughput while minimizing blocking and interruption probabilities. …”
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998
Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms
Published 2025-12-01“…Specifically, the RF algorithm achieved an accuracy of 0.9690, while the SVM algorithm attained an accuracy of 0.9587 in State 1, making them the most effective models in this setting. …”
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999
Wood Panel Defect Detection Based on Improved YOLOv8n
Published 2025-02-01“…However, the accuracy and convergence speed of existing defect detection techniques still require improvement. In this paper, an improved algorithm based on YOLOv8n was designed for accurate detection of wood panel defects. …”
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1000
Quality of Experience Optimization for AR Service in an MEC Federation System
Published 2025-01-01“…To address this shortcoming, we studied AR subtask offloading and resource allocation in a multi-hop, multi-access edge computing federation. Our approach improves the quality of experience (QoE) by optimizing video quality and reducing delay while ensuring fairness, which is modeled as the ratio between provided and required quality. …”
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